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1

Beeks, Graydon, Frank J. Cipolla, and Donald Hunsberger. "The Wind Ensemble and Its Repertoire: Essays on the Fortieth Anniversary of the Eastman Wind Ensemble." Notes 53, no. 1 (September 1996): 84. http://dx.doi.org/10.2307/900313.

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2

Kreitner, Kenneth, Frank J. Cipolla, and Donald Hunsberger. "The Wind Ensemble and Its Repertoire: Essays on the Fortieth Anniversary of the Eastman Wind Ensemble." American Music 14, no. 2 (1996): 228. http://dx.doi.org/10.2307/3052358.

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3

Chamberlin, Reed. "Hi-Fi, Middle Brow? Frederick Fennell, Mercury Records, and the Eastman Wind Ensemble From 1952 to 1962." SAGE Open 10, no. 4 (October 2020): 215824402095492. http://dx.doi.org/10.1177/2158244020954926.

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Frederick Fennell, founder of the internationally acclaimed Eastman Wind Ensemble (EWE), is considered by many to be the catalyst for the modern wind-band movement, often credited with revolutionizing thought and practice within the discipline. While this perception remains valid, evidence suggests that Fennell was much less serious (or “high-brow”) than many believe. Derived from original research in the Fennell Archive at the Eastman School of Music, this article seeks to highlight tensions between Fennell’s desire to record serious wind-band music and the demands of Mercury Records (EWE record label, 1952–1964) to record populist repertoire. Fennell’s archival material suggests that his philosophy was directly influenced by Mercury’s bottom line with the objective of selling records to the masses. Surprisingly, this synthesized a dynamic approach to programming for Fennell and the EWE—one that remains a tradition to this day. The influence of recorded media’s populist objective fused an approach for Fennell that is much more “middle-brow” than many may have believed.
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4

Lin, Jonathan, Kerry Emanuel, and Jonathan L. Vigh. "Forecasts of Hurricanes Using Large-Ensemble Outputs." Weather and Forecasting 35, no. 5 (October 1, 2020): 1713–31. http://dx.doi.org/10.1175/waf-d-19-0255.1.

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AbstractThis paper describes the development of a model framework for Forecasts of Hurricanes Using Large-Ensemble Outputs (FHLO). FHLO quantifies the forecast uncertainty of a tropical cyclone (TC) by generating probabilistic forecasts of track, intensity, and wind speed that incorporate the state-dependent uncertainty in the large-scale field. The main goal is to provide useful probabilistic forecasts of wind at fixed points in space, but these require large ensembles [O(1000)] to flesh out the tails of the distributions. FHLO accomplishes this by using a computationally inexpensive framework, which consists of three components: 1) a track model that generates synthetic tracks from the TC tracks of an ensemble numerical weather prediction (NWP) model, 2) an intensity model that predicts the intensity along each synthetic track, and 3) a TC wind field model that estimates the time-varying two-dimensional surface wind field. The intensity and wind field of a TC evolve as though the TC were embedded in a time-evolving environmental field, which is derived from the forecast fields of ensemble NWP models. Each component of the framework is evaluated using 1000-member ensembles and four years (2015–18) of TC forecasts in the Atlantic and eastern Pacific basins. We show that the synthetic track algorithm generates tracks that are statistically similar to those of the underlying global ensemble models. We show that FHLO produces competitive intensity forecasts, especially when considering probabilistic verification statistics. We also demonstrate the reliability and accuracy of the probabilistic wind forecasts. Limitations of the model framework are also discussed.
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5

Sekiyama, Tsuyoshi Thomas, Mizuo Kajino, and Masaru Kunii. "Ensemble Dispersion Simulation of a Point-Source Radioactive Aerosol Using Perturbed Meteorological Fields over Eastern Japan." Atmosphere 12, no. 6 (May 22, 2021): 662. http://dx.doi.org/10.3390/atmos12060662.

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We conducted single-model initial-perturbed ensemble simulations to quantify uncertainty in aerosol dispersion modeling, focusing on a point-source radioactive aerosol emitted from the Fukushima Daiichi Nuclear Power Plant (FDNPP) in March 2011. The ensembles of the meteorological variables were prepared using a data assimilation system that consisted of a non-hydrostatic weather-forecast model with a 3-km horizontal resolution and a four-dimensional local ensemble transform Kalman filter (4D-LETKF) with 20 ensemble members. The emission of radioactive aerosol was not perturbed. The weather and aerosol simulations were validated with in-situ measurements at Hitachi and Tokai, respectively, approximately 100 km south of the FDNPP. The ensemble simulations provided probabilistic information and multiple case scenarios for the radioactive aerosol plumes. Some of the ensemble members successfully reproduced the arrival time and intensity of the radioactive aerosol plumes, even when the deterministic simulation failed to reproduce them. We found that a small ensemble spread of wind speed produced large uncertainties in aerosol concentrations.
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6

Parodi, Antonio, Martina Lagasio, Maurizio Maugeri, Barbara Turato, and William Gallus. "Observational and Modelling Study of a Major Downburst Event in Liguria: The 14 October 2016 Case." Atmosphere 10, no. 12 (December 6, 2019): 788. http://dx.doi.org/10.3390/atmos10120788.

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Downbursts are very disruptive weather events that can produce large amounts of damage. The most studied downbursts are those occurring in the United States and continental Europe, but they can happen globally. This work is an observational and modelling analysis of a major downburst event that occurred on 14 October 2016 over eastern Liguria (Italy). This downburst affected an area 30 km long and 10 km wide, producing observed wind gusts of 40 m/s with major impacts to railways, trees, and houses, with more than 2.5 million euros of damage. First, the general environment influencing this downburst is identified and analyzed, then the event is reproduced with a small multi-physics high-resolution ensemble using the Weather Research and Forecasting (WRF)–advanced research WRF (ARW) model, with 1 km horizontal grid spacing. The event was poorly predicted beforehand, and the difficulty in forecasting this event is confirmed by the fact that so few ensemble members suggested the occurrence of damaging winds over eastern Liguria. However, one of the eight members performed well and its output helped to reveal the primary mechanisms for the downburst, suggesting that high-resolution ensembles using mixed physics may be a useful tool for improving the prediction of similar extreme events in the Mediterranean region in the future.
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7

Clark, Adam J., William A. Gallus, Ming Xue, and Fanyou Kong. "Convection-Allowing and Convection-Parameterizing Ensemble Forecasts of a Mesoscale Convective Vortex and Associated Severe Weather Environment." Weather and Forecasting 25, no. 4 (August 1, 2010): 1052–81. http://dx.doi.org/10.1175/2010waf2222390.1.

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Abstract An analysis of a regional severe weather outbreak that was related to a mesoscale convective vortex (MCV) is performed. The MCV-spawning mesoscale convection system (MCS) formed in northwest Kansas along the southern periphery of a large cutoff 500-hPa low centered over western South Dakota. As the MCS propagated into eastern Kansas during the early morning of 1 June 2007, an MCV that became evident from multiple data sources [e.g., Weather Surveillance Radar-1988 Doppler (WSR-88D) network, visible satellite imagery, wind-profiler data, Rapid Update Cycle 1-hourly analyses] tracked through northwest Missouri and central Iowa and manifested itself as a well-defined midlevel short-wave trough. Downstream of the MCV in southeast Iowa and northwest Illinois, southwesterly 500-hPa winds increased to around 25 m s−1 over an area with southeasterly surface winds and 500–1500 J kg−1 of surface-based convective available potential energy (CAPE), creating a favorable environment for severe weather. In the favorable region, multiple tornadoes occurred, including one rated as a category 3 storm on the enhanced Fujita scale (EF3) that caused considerable damage. In the analysis, emphasis is placed on the role of the MCV in leading to a favorable environment for severe weather. In addition, convection-allowing forecasts of the MCV and associated environmental conditions from the 10-member Storm-Scale Ensemble Forecast (SSEF) system produced for the 2007 NOAA Hazardous Weather Testbed Spring Experiment are compared to those from a similarly configured, but coarser, 30-member convection-parameterizing ensemble. It was found that forecasts of the MCV track and associated environmental conditions (e.g., midlevel winds, low-level wind shear, and instability) were much better in the convection-allowing ensemble. Errors in the MCV track from convection-parameterizing members likely resulted from westward displacement errors in the incipient MCS. Furthermore, poor depiction of MCV structure and maintenance in convection-parameterizing members, which was diagnosed through a vorticity budget analysis, likely led to the relatively poor forecasts of the associated environmental conditions. The results appear to be very encouraging for convection-allowing ensembles, especially when environmental conditions lead to a high degree of predictability for MCSs, which appeared to be the case for this particular event.
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8

Misios, Stergios, Ioannis Logothetis, Mads F. Knudsen, Christoffer Karoff, Vassilis Amiridis, and Kleareti Tourpali. "Decline in Etesian winds after large volcanic eruptions in the last millennium." Weather and Climate Dynamics 3, no. 3 (July 29, 2022): 811–23. http://dx.doi.org/10.5194/wcd-3-811-2022.

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Abstract. The northerly Etesian winds are a stable summertime circulation system in the eastern Mediterranean, emerging from a steep pressure gradient between the central Europe and Balkans high-pressure and the Anatolian low-pressure systems. Etesian winds are influenced by the variability in the Indian summer monsoon (ISM), but their sensitivity to external forcing on interannual and longer timescales is not well understood. Here, for the first time, we investigate the sensitivity of Etesian winds to large volcanic eruptions in a set of model simulations over the last millennium and reanalysis of the 20th century. We provide model evidence for significant volcanic signatures, manifested as a robust reduction in the wind speed and the total number of days with Etesian winds in July and August. These are robust responses to all strong eruptions in the last millennium, and in the extreme case of Samalas, the ensemble-mean response suggests a post-eruption summer without Etesians. The significant decline in the number of days with Etesian winds is attributed to the weakening of the ISM in the post-eruption summers, which is associated with a reduced large-scale subsidence and weakened surface pressure gradients in the eastern Mediterranean. Our analysis identifies a stronger sensitivity of Etesian winds to the Northern Hemisphere volcanic forcing, particularly for volcanoes before the 20th century, while for the latest large eruption of Pinatubo modelled and observed responses are insignificant. These findings could improve seasonal predictions of the wind circulation in the eastern Mediterranean in the summers after large volcanic eruptions.
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9

Zhang, Fuqing, Meng Zhang, and Jonathan Poterjoy. "E3DVar: Coupling an Ensemble Kalman Filter with Three-Dimensional Variational Data Assimilation in a Limited-Area Weather Prediction Model and Comparison to E4DVar." Monthly Weather Review 141, no. 3 (March 1, 2013): 900–917. http://dx.doi.org/10.1175/mwr-d-12-00075.1.

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Abstract This study examines the performance of a hybrid ensemble-variational data assimilation system (E3DVar) that couples an ensemble Kalman filter (EnKF) with the three-dimensional variational data assimilation (3DVar) system for the Weather Research and Forecasting (WRF) Model. The performance of E3DVar and the component EnKF and 3DVar systems are compared over the eastern United States for June 2003. Conventional sounding and surface observations as well as data from wind profilers, aircraft and ships, and cloud-tracked winds from satellites, are assimilated every 6 h during the experiments, and forecasts are verified using standard sounding observations. Forecasts with 12- to 72-h lead times are found to have noticeably smaller root-mean-square errors when initialized with the E3DVar system, as opposed to the EnKF, especially for the 12-h wind and moisture fields. The E3DVar system demonstrates similar performance as an EnKF, while using less than half the number of ensemble members, and is less sensitive to the use of a multiphysics ensemble to account for model errors. The E3DVar system is also compared with a similar hybrid method that replaces the 3DVar component with the WRF four-dimensional variational data assimilation (4DVar) method (denoted E4DVar). The E4DVar method demonstrated considerable improvements over E3DVar for nearly all model levels and variables at the shorter forecast lead times (12–48 h), but the forecast accuracies of all three ensemble-based methods (EnKF, E3DVar, and E4DVar) converge to similar results at longer lead times (60–72 h). Nevertheless, all methods that used ensemble information produced considerably better forecasts than the two methods that relied solely on static background error covariance (i.e., 3DVar and 4DVar).
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10

Godinez, Humberto C., Jon M. Reisner, Alexandre O. Fierro, Stephen R. Guimond, and Jim Kao. "Determining Key Model Parameters of Rapidly Intensifying Hurricane Guillermo (1997) Using the Ensemble Kalman Filter." Journal of the Atmospheric Sciences 69, no. 11 (November 1, 2012): 3147–71. http://dx.doi.org/10.1175/jas-d-12-022.1.

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Abstract In this work the authors determine key model parameters for rapidly intensifying Hurricane Guillermo (1997) using the ensemble Kalman filter (EnKF). The approach is to utilize the EnKF as a tool only to estimate the parameter values of the model for a particular dataset. The assimilation is performed using dual-Doppler radar observations obtained during the period of rapid intensification of Hurricane Guillermo. A unique aspect of Guillermo was that during the period of radar observations strong convective bursts, attributable to wind shear, formed primarily within the eastern semicircle of the eyewall. To reproduce this observed structure within a hurricane model, background wind shear of some magnitude must be specified and turbulence and surface parameters appropriately specified so that the impact of the shear on the simulated hurricane vortex can be realized. To identify the complex nonlinear interactions induced by changes in these parameters, an ensemble of model simulations have been conducted in which individual members were formulated by sampling the parameters within a certain range via a Latin hypercube approach. The ensemble and the data, derived latent heat and horizontal winds from the dual-Doppler radar observations, are utilized in the EnKF to obtain varying estimates of the model parameters. The parameters are estimated at each time instance, and a final parameter value is obtained by computing the average over time. Individual simulations were conducted using the estimates, with the simulation using latent heat parameter estimates producing the lowest overall model forecast error.
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11

Alessandrini, Stefano, Luca Delle Monache, Christopher M. Rozoff, and William E. Lewis. "Probabilistic Prediction of Tropical Cyclone Intensity with an Analog Ensemble." Monthly Weather Review 146, no. 6 (June 2018): 1723–44. http://dx.doi.org/10.1175/mwr-d-17-0314.1.

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An analog ensemble (AnEn) technique is applied to the prediction of tropical cyclone (TC) intensity (i.e., maximum 1-min averaged 10-m wind speed). The AnEn is an inexpensive, naturally calibrated ensemble prediction of TC intensity derived from a training dataset of deterministic Hurricane Weather Research and Forecasting (HWRF; 2015 version) Model forecasts. In this implementation of the AnEn, a set of analog forecasts is generated by searching an HWRF archive for forecasts sharing key features with the current HWRF forecast. The forecast training period spans 2011–15. The similarity of a current forecast with past forecasts is estimated using predictors derived from the HWRF reforecasts that capture thermodynamic and kinematic properties of a TC’s environment and its inner core. Additionally, the value of adding a multimodel intensity consensus forecast as an AnEn predictor is examined. Once analogs are identified, the verifying intensity observations corresponding to each analog HWRF forecast are used to produce the AnEn intensity prediction. In this work, the AnEn is developed for both the eastern Pacific and Atlantic Ocean basins. The AnEn’s performance with respect to mean absolute error (MAE) is compared with the raw HWRF output, the official National Hurricane Center (NHC) forecast, and other top-performing NHC models. Also, probabilistic intensity forecasts are compared with a quantile mapping model based on the HWRF’s intensity forecast. In terms of MAE, the AnEn outperforms HWRF in the eastern Pacific at all lead times examined and up to 24-h lead time in the Atlantic. Also, unlike traditional dynamical ensembles, the AnEn produces an excellent spread–skill relationship.
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12

Tim, Nele, Eduardo Zorita, Birgit Hünicke, Xing Yi, and Kay-Christian Emeis. "The importance of external climate forcing for the variability and trends of coastal upwelling in past and future climate." Ocean Science 12, no. 3 (June 23, 2016): 807–23. http://dx.doi.org/10.5194/os-12-807-2016.

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Abstract. The eastern boundary upwelling systems, located in the subtropics at the eastern boundary of the Atlantic and Pacific oceans and mainly driven by the trade winds, are the major coastal upwelling regions. Previous studies have suggested that the intensity of upwelling in these areas in the past centuries may have been influenced by the external radiative forcing, for instance by changes in solar irradiance, and it will also be influenced in the future by the increasing atmospheric greenhouse gases. Here, we analyse the impact of the external climate forcing on these upwelling systems in ensembles of simulations of two Earth system models. The ensembles contain three simulations for each period covering the past millennium (900–1849) and the 20th century (1850–2005). One of these Earth system models additionally includes the near future (2006–2100). Using a set of simulations, differing only in their initial conditions, enables us to test whether the observed variability and trends are driven by the external radiative forcing. Our analysis shows that the variability of the simulated upwelling is largely not affected by the external forcing and that, generally, there are no significant trends in the periods covering the past and future. Only in future simulations with the strongest increase of greenhouse gas concentrations the upwelling trends are significant and appear in all members of the ensemble.
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13

Torn, Ryan D., and Gregory J. Hakim. "Performance Characteristics of a Pseudo-Operational Ensemble Kalman Filter." Monthly Weather Review 136, no. 10 (October 2008): 3947–63. http://dx.doi.org/10.1175/2008mwr2443.1.

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The 2-yr performance of a pseudo-operational (real time) limited-area ensemble Kalman filter (EnKF) based on the Weather Research and Forecasting Model is described. This system assimilates conventional observations from surface stations, rawinsondes, the Aircraft Communications Addressing and Reporting System (ACARS), and cloud motion vectors every 6 h on a domain that includes the eastern North Pacific Ocean and western North America. Ensemble forecasts from this system and deterministic output from operational numerical weather prediction models during this same period are verified against rawinsonde and surface observation data. Relative to operational forecasts, the forecast from the ensemble-mean analysis has slightly larger errors in wind and temperature but smaller errors in moisture, even though satellite radiances are not assimilated by the EnKF. Time-averaged correlations indicate that assimilating ACARS and cloud wind data with flow-dependent error statistics provides corrections to the moisture field in the absence of direct observations of that field. Comparison with a control experiment in which a deterministic forecast is cycled without observation assimilation indicates that the skill in the EnKF’s forecasts results from assimilating observations and not from lateral boundary conditions or the model formulation. Furthermore, the ensemble variance is generally in good agreement with the ensemble-mean error and the spread increases monotonically with forecast hour.
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14

Zheng, Xiao-Tong, Shang-Ping Xie, Yan Du, Lin Liu, Gang Huang, and Qinyu Liu. "Indian Ocean Dipole Response to Global Warming in the CMIP5 Multimodel Ensemble*." Journal of Climate 26, no. 16 (August 6, 2013): 6067–80. http://dx.doi.org/10.1175/jcli-d-12-00638.1.

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Abstract The response of the Indian Ocean dipole (IOD) mode to global warming is investigated based on simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5). In response to increased greenhouse gases, an IOD-like warming pattern appears in the equatorial Indian Ocean, with reduced (enhanced) warming in the east (west), an easterly wind trend, and thermocline shoaling in the east. Despite a shoaling thermocline and strengthened thermocline feedback in the eastern equatorial Indian Ocean, the interannual variance of the IOD mode remains largely unchanged in sea surface temperature (SST) as atmospheric feedback and zonal wind variance weaken under global warming. The negative skewness in eastern Indian Ocean SST is reduced as a result of the shoaling thermocline. The change in interannual IOD variance exhibits some variability among models, and this intermodel variability is correlated with the change in thermocline feedback. The results herein illustrate that mean state changes modulate interannual modes, and suggest that recent changes in the IOD mode are likely due to natural variations.
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15

Kumar, Rajesh, Gil Lemos, Alvaro Semedo, and Faisal Alsaaq. "Parameterization-Driven Uncertainties in Single-Forcing, Single-Model Wave Climate Projections from a CMIP6-Derived Dynamic Ensemble." Climate 10, no. 4 (March 24, 2022): 51. http://dx.doi.org/10.3390/cli10040051.

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This study is focused on the impact of different parameterizations in the state-of-the art wave model WAVEWATCH3 (WW3) in describing the present climate and future wave climate projections. We have used a Coupled Model Intercomparison Project Phase 6 (CMIP6)-derived single-wind forcing (from EC-EARTH) to produce a dynamic wind-wave climate ensemble for its historic (1995–2014) and future (2081–2100) periods. We discuss the uncertainty due to the wave model (intra-model uncertainty) in simulating the present and future wave climate. The historical wave climate runs were compared against the ERA5 reanalysis and found to be in good agreement for the significant wave height. This gives a good degree of confidence to investigate the intra-model uncertainty in WW3 using the available physics packages such as ST2, ST3, ST4, and ST6. In general, for the historic period, ST3 and ST4 physics packages perform better in the tropics whereas ST6 performs better in the extratropics, based on M-Score performance assessment. The study also reveals that the extratropical South Indian Ocean and tropical eastern South Pacific areas exhibit a larger amount of uncertainty, mainly induced by the ST2 physics package. The results of this study shed new light on the impacts associated with the use of multiple physics parameterizations in wave climate ensembles, an issue that has not received the necessary attention in scientific literature.
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16

Jeong, Dae Il, Alex J. Cannon, and Robert J. Morris. "Projected changes to wind loads coinciding with rainfall for building design in Canada based on an ensemble of Canadian regional climate model simulations." Climatic Change 162, no. 2 (May 21, 2020): 821–35. http://dx.doi.org/10.1007/s10584-020-02745-y.

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Abstract Strong wind coinciding with rainfall is an important weather phenomenon in many science and engineering fields. This study investigates changes in hourly extreme driving rain wind pressure (DRWP)—a climatic variable used in building design in Canada—for future periods of specified global mean temperature change using an ensemble of a Canadian regional climate model (CanRCM4) driven by the Canadian Earth system model (CanESM2) under the Representative Concentration Pathway 8.5 scenario. Evaluation of the model shows that the CanRCM4 ensemble reproduces hourly extreme wind speeds and rainfall (> 1.8 mm/h) occurrence frequency and the associated design (5-year return level) DRWP across Canada well when compared with 130 meteorological stations. Significant increases in future design DRWP are projected over western, eastern, and northern Canada, with the areal extent and relative magnitude of the increases scaling approximately linearly with the amount of global warming. Increases in future rainfall occurrence frequency are driven by the combined effect of increases in precipitation amount and changes in precipitation type from solid to liquid due to increases in air temperature; these are identified as the main factors leading to increases in future design DRWP. Future risk ratios of the design DRWP are highly dependent on those of the rainfall occurrence, which shows large increases over the three regions, while they are partly affected by the increases in future extreme wind speeds over western and northeastern Canada. Increases in DRWP can be an emerging risk for existing buildings, particularly in western, eastern, and northern Canada, and a consideration for managing and designing buildings across Canada.
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de Szoeke, Simon P., and Shang-Ping Xie. "The Tropical Eastern Pacific Seasonal Cycle: Assessment of Errors and Mechanisms in IPCC AR4 Coupled Ocean–Atmosphere General Circulation Models*." Journal of Climate 21, no. 11 (June 1, 2008): 2573–90. http://dx.doi.org/10.1175/2007jcli1975.1.

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Abstract Warmer SST and more rain in the Northern Hemisphere are observed year-round in the tropical eastern Pacific with southerly wind crossing the equator toward the atmospheric heating. The southerlies are minimal during boreal spring, when two precipitation maxima straddle the equator. Fourteen atmosphere–ocean coupled GCMs from the Coupled Model Intercomparison Project (CMIP3) and one coupled regional model are evaluated against observations with simple metrics that diagnose the seasonal cycle and meridional migration of warm SST and rain. Intermodel correlations of the metrics elucidate common coupled physics. These models variously simulate the climatology of SST and ITCZ rain. In 8 out of 15 models the ITCZ alternates symmetrically between the hemispheres with the seasons. This seasonally alternating ITCZ error generates two wind speed maxima per year—one northerly and one southerly—resulting in spurious cooling in March and a cool SST error of the equatorial ocean. Most models have too much rain in the Southern Hemisphere so that SST and rain are too symmetric about the equator in the annual mean. Weak meridional wind on the equator near the South American coast (2°S–2°N, 80°–90°W) explains the warm SST error there. Northeasterly wind jets blow over the Central American isthmus in winter and cool the SST in the eastern Pacific warm pool. In some models the strength of these winds contributes to the early demise of their northern ITCZ relative to observations. The February–April northerly wind bias on the equator is correlated to the antecedent December–February Central American Pacific wind speed at −0.88. The representation of southern-tropical stratus clouds affects the underlying SST through solar radiation, but its effect on the meridional atmospheric circulation is difficult to discern from the multimodel ensemble, indicating that errors other than the simulation of stratus clouds are also important for accurate simulation of the meridional asymmetry. This study identifies several features to be improved in atmospheric and coupled GCMs, including the northeasterly cross–Central American wind in winter and meridional wind on the equator. Improved simulation of the seasonal cycle of meridional wind could alleviate biases in equatorial SST and improve simulation of ENSO and its teleconnections.
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Kramer, W., and H. A. Dijkstra. "Optimal localized observations for advancing beyond the ENSO predictability barrier." Nonlinear Processes in Geophysics 20, no. 2 (April 2, 2013): 221–30. http://dx.doi.org/10.5194/npg-20-221-2013.

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Abstract. The existing 20-member ensemble of 50 yr ECHAM5/MPI-OM simulations provides a reasonably realistic Monte Carlo sample of the El Niño–Southern Oscillation (ENSO). Localized observations of sea surface temperature (SST), zonal wind speed and thermocline depth are assimilated in the ensemble using sequential importance sampling to adjust the weight of ensemble members. We determine optimal observation locations, for which assimilation yields the minimal ensemble spread. Efficient observation locations for SST lie in the ENSO pattern, with the optimum located in the eastern and western Pacific for minimizing uncertainty in the NINO3 and NINO4 index, respectively. After the assimilation of the observations, we investigate how the weighted ensemble performs as a nine-month probabilistic forecast of the ENSO. Here, we focus on the spring predictability barrier with observation in the January–March (March–May) period and assess the remaining predictive power in June (August) for NINO3 (NINO4). For the ECHAM5/MPI-OM ensemble, this yields that SST observations around 110° W and 140° W provide the best predictive skill for the NINO3 and NINO4 index, respectively. Forecasts can be improved by additionally measuring the thermocline depth at 150° W.
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Karspeck, Alicia R., and Jeffrey L. Anderson. "Experimental Implementation of an Ensemble Adjustment Filter for an Intermediate ENSO Model." Journal of Climate 20, no. 18 (September 15, 2007): 4638–58. http://dx.doi.org/10.1175/jcli4245.1.

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Abstract The assimilation of sea surface temperature (SST) anomalies into a coupled ocean–atmosphere model of the tropical Pacific is investigated using an ensemble adjustment Kalman filter (EAKF). The intermediate coupled model used here is the operational version of the Zebiak–Cane model, called LDEO5. The assimilation is applied as a means of estimating the true state of the system in the presence of incomplete observations of the state. In the first part of this study assimilation is performed under the “perfect model” assumption, where SST observations are synthetically derived from a trajectory of the model. The focus is on how and why changes in the filter parameters (ensemble size, covariance localization, and covariance inflation) affect the quality of the analysis. It is shown that isotropic covariance localization does not benefit the analysis even when a small number of ensemble members are used. These results suggest that destruction of the “balance” between variables caused by localization is more detrimental than spurious correlation due to small ensemble size. In the second part of this study the EAKF is used to assimilate an independent dataset of SST observations. The EAKF/Zebiak–Cane assimilation system is able to correctly estimate the phase and intensity of ENSO, as measured by the average SST anomaly in the eastern equatorial Pacific. A comparison of the analysis herein to independent wind stress and thermocline depth datasets suggests that even with the assimilation of only SST observations it is possible to reproduce over 70% of the interannual variability of thermocline depth in the eastern equatorial Pacific and off the coast of the Philippine Islands. The interannual variability of zonal wind stress in the central and western equatorial Pacific is also well correlated with independent observations (R > 0.75).
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Bett, P. E., H. E. Thornton, and R. T. Clark. "European wind variability over 140 yr." Advances in Science and Research 10, no. 1 (April 3, 2013): 51–58. http://dx.doi.org/10.5194/asr-10-51-2013.

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Abstract. We present initial results of a study on the variability of wind speeds across Europe over the past 140 yr, making use of the recent Twentieth Century Reanalysis data set, which includes uncertainty estimates from an ensemble method of reanalysis. Maps of the means and standard deviations of daily wind speeds, and the Weibull-distribution parameters, show the expected features, such as the strong, highly-variable wind in the north-east Atlantic. We do not find any clear, strong long-term trends in wind speeds across Europe, and the variability between decades is large. We examine how different years and decades are related in the long-term context, by looking at the ranking of annual mean wind speeds. Picking a region covering eastern England as an example, our analyses show that the wind speeds there over the past ~ 20 yr are within the range expected from natural variability, but do not span the full range of variability of the 140-yr data set. The calendar-year 2010 is however found to have the lowest mean wind speed on record for this region.
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Elsberry, Russell L., Hsiao-Chung Tsai, Corie Capalbo, Wei-Chia Chin, and Timothy P. Marchok. "Opportunity for Tropical Cyclone Lifecycle Predictions from Pre-Formation to Ending Stage: Eastern North Pacific 2021 Season." Atmosphere 13, no. 7 (June 22, 2022): 1008. http://dx.doi.org/10.3390/atmos13071008.

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Building on previous studies of western North Pacific formation and intensity predictions along the ECMWF ensemble medium-range track forecasts, the first objective of this transition to the eastern North Pacific was to provide earlier forecasts of the Time-to-Formation (T2F) and Time-to-Hurricane (T2H) than are available from the National Hurricane Center Advisories. For the first six hurricanes of the 2021 season, the first detections in the ECMWF ensemble were 8 days to 12 days in advance of the T2F times and 9 days to 13 days in advance of the T2H times. The major advance in this study has been to document that the ECMWF ensemble is also capable of predicting Ending-T2H and Ending-T2F timings and positions along those 15-day ECMWF ensemble track forecasts. This study for the first time documents the opportunity for high wind warnings during the entire lifecycle of the 2021 season hurricanes even days in advance of formation. Validations of the pre-hurricane and Ending-hurricane tracks and timings are provided for the lifecycles of seven hurricanes and the “Almost-Hurricane Guillermo”. Because the technique has been accepted for operational testing at the Joint Typhoon Warning Center, a companion article has been submitted that will describe the flowchart methodology for evaluating the twice-daily ECMWF ensemble forecasts to select the most likely pre-hurricane circulation as early as possible while non-selecting the likely false alarm circulations.
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22

Niznik, Matthew J., and Benjamin R. Lintner. "Circulation, Moisture, and Precipitation Relationships along the South Pacific Convergence Zone in Reanalyses and CMIP5 Models." Journal of Climate 26, no. 24 (December 2, 2013): 10174–92. http://dx.doi.org/10.1175/jcli-d-13-00263.1.

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Abstract One theorized control on the position of the South Pacific convergence zone (SPCZ) is the amount of low-level inflow from the relatively dry southeastern Pacific basin. Building on an analysis of observed SPCZ region synoptic-scale variability by Lintner and Neelin, composite analysis is performed here on two reanalysis products as well as output from 17 models in phase 5 of the Coupled Model Intercomparison Project (CMIP5). Using low-level zonal wind as a compositing index, it is shown that the CMIP5 ensemble mean, as well as many of the individual models, captures patterns of wind, specific humidity, and precipitation anomalies resembling those obtained for reanalysis fields between weak- and strong-inflow phases. Lead–lag analysis of both the reanalyses and models is used to develop a conceptual model for the formation of each composite phase. This analysis indicates that an equatorward-displaced Southern Hemisphere storm track and an eastward-displaced equatorial eastern Pacific westerly (wind) duct are features of the weak-inflow phase although, as indicated by additional composite analyses based on these features, each appears to account weakly for the details of the low-level inflow composite anomalies. Despite the presence of well-known biases in the CMIP5 simulations of the SPCZ region climate, the models appear to have some fidelity in simulating synoptic-scale relationships between low-level winds, moisture, and precipitation, consistent with observations and simple theoretical understanding of interactions of dry air inflow with deep convection.
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23

Fox-Rabinovitz, Michael S., Ernesto Hugo Berbery, Lawrence L. Takacs, and Ravi C. Govindaraju. "A Multiyear Ensemble Simulation of the U.S. Climate with a Stretched-Grid GCM." Monthly Weather Review 133, no. 9 (September 1, 2005): 2505–25. http://dx.doi.org/10.1175/mwr2956.1.

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Abstract Multiyear (1987–97) limited ensemble integrations using a stretched-grid GCM, previously developed and experimented with by the authors, are employed for U.S. regional climate simulations. The ensemble members (six in total) are produced at two different regional resolutions: three members with 60-km and the other three members with 10-km regional resolution. The use of these two finer and coarser regional resolution ensemble members allows one to examine the impact of resolution on the overall quality of the simulated regional fields. For the multiyear ensemble simulations, an efficient regional downscaling to realistic mesoscales has been obtained. The ensemble means of the midtroposphere prognostic variables (height and meridional wind) show an overall good resemblance to the global reanalysis, especially for summer. Low-level features like the warm season Great Plains low-level jet are well represented in the simulations. During winter the 100-km simulations develop a southward wind east of the Rockies that is present neither in the reanalyses nor in the 60-km simulations. The analysis of the annual mean precipitation and its variance reveals that the ensemble simulations reproduce many of the observed features of a high-resolution rain gauge dataset analyzed on a 0.5° × 0.5° grid. Signal-to-noise ratios are larger than 1.5 s over a major part of the United States, especially over the Midwest and also over the mountainous regions like the Rockies and the Appalachians, suggesting that the orographic forcing is contributing to a larger signal. The ratios are smaller toward the eastern and western U.S. coastlines. This result could be attributed, at least in part, to limits in the representation of the land–sea contrasts. For comparison purposes, an additional simulation has been performed using a global uniform 2° × 2.5° grid with the same number of global grid points as those of the above stretched grids. The stretched-grid GCM ensemble means show, overall, a better regional depiction of features than those of the uniform-grid GCM. The results of the study show that even using limited ensemble integrations with a state-of-the-art stretched-grid GCM is beneficial for reducing the uncertainty of the multiyear regional climate simulation, especially when using finer 60-km regional resolution.
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24

Angevine, W. M., J. Brioude, S. McKeen, and J. S. Holloway. "Uncertainty in Lagrangian pollutant transport simulations due to meteorological uncertainty from a mesoscale WRF ensemble." Geoscientific Model Development 7, no. 6 (December 2, 2014): 2817–29. http://dx.doi.org/10.5194/gmd-7-2817-2014.

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Abstract. Lagrangian particle dispersion models require meteorological fields as input. Uncertainty in the driving meteorology is one of the major uncertainties in the results. The propagation of uncertainty through the system is not simple, and it has not been thoroughly explored. Here, we take an ensemble approach. Six different configurations of the Weather Research and Forecast (WRF) model drive otherwise identical simulations with FLEXPART-WRF for 49 days over eastern North America. The ensemble spreads of wind speed, mixing height, and tracer concentration are presented. Uncertainty of tracer concentrations due solely to meteorological uncertainty is 30–40%. Spatial and temporal averaging reduces the uncertainty marginally. Tracer age uncertainty due solely to meteorological uncertainty is 15–20%. These are lower bounds on the uncertainty, because a number of processes are not accounted for in the analysis.
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25

Angevine, W. M., J. Brioude, S. McKeen, and J. S. Holloway. "Uncertainty in Lagrangian pollutant transport simulations due to meteorological uncertainty at mesoscale." Geoscientific Model Development Discussions 7, no. 4 (July 23, 2014): 4603–43. http://dx.doi.org/10.5194/gmdd-7-4603-2014.

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Abstract. Lagrangian particle dispersion models require meteorological fields as input. Uncertainty in the driving meteorology is one of the major uncertainties in the results. The propagation of uncertainty through the system is not simple, and has not been thoroughly explored. Here, we take an ensemble approach. Six different configurations of the Weather Research and Forecast (WRF) model drive otherwise identical simulations with FLEXPART for 49 days over eastern North America. The ensemble spreads of wind speed, mixing height, and tracer concentration are presented. Uncertainty of tracer concentrations due solely to meteorological uncertainty is 30–40%. Spatial and temporal averaging reduces the uncertainty marginally. Tracer age uncertainty due solely to meteorological uncertainty is 15–20%. These are lower bounds on the uncertainty, because a number of processes are not accounted for in the analysis.
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26

Zhu, Jieshun, Arun Kumar, Hui Wang, and Bohua Huang. "Sea Surface Temperature Predictions in NCEP CFSv2 Using a Simple Ocean Initialization Scheme." Monthly Weather Review 143, no. 8 (August 1, 2015): 3176–91. http://dx.doi.org/10.1175/mwr-d-14-00297.1.

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Abstract In contrast to operational climate predictions based on sophisticated ocean data assimilation schemes at the National Centers for Environmental Predictions (NCEP), this study applied a simple ocean initialization scheme to the NCEP latest seasonal prediction model, the Climate Forecast System, version 2 (CFSv2). In the scheme, sea surface temperature (SST) was the only observed information applied to derive ocean initial states. The physical basis for the method is that, through air–sea coupling, SST is capable of reproducing some observed features of ocean evolutions by forcing the atmospheric winds. SST predictions based on the scheme are compared against hindcasts from the National (lately North American) Multimodel Ensemble (NMME) project. It was found that due to substantial biases in the tropical eastern Pacific in the ocean initial conditions produced by SST assimilation, ENSO SST predictions were not as good as those with sophisticated initialization schemes (e.g., hindcasts in the NMME project). However, in other basins, SST predictions based on a simple ocean initialization procedure were not worse (sometimes even better) than those with sophisticated initialization schemes. These comparisons indicate that it was helpful that subsurface ocean information be assimilated to improve the tropical Pacific SST predictions, while SST-based ocean assimilation was an effective way to enhance SST prediction capability in other ocean basins. By examining multimodel ensembles with the simple scheme-based hindcasts either included or excluded in NMME, it is also suggested that including the hindcast would generally benefit multimodel ensemble forecasts. In addition, possible ways to further improve ENSO SST predictions with the simple initialization scheme are also discussed.
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27

Lakku, Naresh K. G., and Manasa R. Behera. "Skill and Intercomparison of Global Climate Models in Simulating Wind Speed, and Future Changes in Wind Speed over South Asian Domain." Atmosphere 13, no. 6 (May 25, 2022): 864. http://dx.doi.org/10.3390/atmos13060864.

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Investigating the role of complex dynamical components of a global climate model (GCM) in improving near-surface wind speed (WS) simulation is vital for the climate community in building reliable future WS projections. The relative skill of GCMs in representing WS at diverse climate variable scales (daily, monthly, seasonal, and annual) over land and ocean areas of the South Asian domain is not clear yet. With this in mind, this paper evaluated the skill of 28 Coupled Model Intercomparison Project phase five GCMs in reproducing the WS using a devised relative score approach. It is recommended to use the mean ensemble of MPI-ESM-MR, CSIRO-Mk3.6.0, and GFDL-ESM2G GCMs for understanding future changes in wind–wave climate and offshore wind energy potential. The inter-comparison of GCMs shows that the GCM with high or low atmospheric resolution does not necessarily exhibit the best or worst performance, respectively, whereas the dynamic components in the model configuration play the major role, especially the atmosphere component relative to other dynamical components. The strengthening of annual and seasonal mean WS is observed over coastal plains of the United Republic of Tanzania, Oman, eastern Thailand, eastern Gulf of Thailand and Sumatra, and weakening over the central northern equatorial region of the Indian Ocean in the 21st century for RCP4.5 and RCP8.5 emission scenarios.
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28

DeMaria, Mark, John A. Knaff, Michael J. Brennan, Daniel Brown, Richard D. Knabb, Robert T. DeMaria, Andrea Schumacher, et al. "Improvements to the Operational Tropical Cyclone Wind Speed Probability Model." Weather and Forecasting 28, no. 3 (June 1, 2013): 586–602. http://dx.doi.org/10.1175/waf-d-12-00116.1.

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Abstract The National Hurricane Center Hurricane Probability Program, which estimated the probability of a tropical cyclone passing within a specific distance of a selected set of coastal stations, was replaced by the more general Tropical Cyclone Surface Wind Speed Probabilities in 2006. A Monte Carlo (MC) method is used to estimate the probabilities of 34-, 50-, and 64-kt (1 kt = 0.51 m s−1) winds at multiple time periods through 120 h. Versions of the MC model are available for the Atlantic, the combined eastern and central North Pacific, and the western North Pacific. This paper presents a verification of the operational runs of the MC model for the period 2008–11 and describes model improvements since 2007. The most significant change occurred in 2010 with the inclusion of a method to take into account the uncertainty of the track forecasts on a case-by-case basis, which is estimated from the spread of a dynamical model ensemble and other parameters. The previous version represented the track uncertainty from the error distributions from the previous 5 yr of forecasts from the operational centers, with no case-to-case variability. Results show the MC model provides robust estimates of the wind speed probabilities using a number of standard verification metrics, and that the inclusion of the case-by-case measure of track uncertainty improved the probability estimates. Beginning in 2008, an older operational wind speed probability table product was modified to include information from the MC model. This development and a verification of the new version of the table are described.
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29

Hsin, Yi-Chia. "Trends of the Pathways and Intensities of Surface Equatorial Current System in the North Pacific Ocean." Journal of Climate 29, no. 18 (August 31, 2016): 6693–710. http://dx.doi.org/10.1175/jcli-d-15-0850.1.

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Abstract An ensemble of ocean reanalysis products is utilized to quantify the long-term tendencies of pathways and along-pathway transports of the three surface equatorial currents (North Equatorial Current, North Equatorial Countercurrent, and northern branch of the South Equatorial Current) in the North Pacific Ocean during the period of the 1900s–2000s. This study uses 12 ocean reanalysis products in the ensemble for the period after the 1960s, while only 2 Simple Ocean Data Assimilation (SODA) products are taken into consideration for the period prior to 1960s. The analyses indicate that the three currents in the western (eastern) Pacific Ocean have more southern (northern) mean central positions and tend to move southward (northward) over the past 100 years. All three currents have weakening tendencies, with the exception of the North Equatorial Current having intensified in the western Pacific Ocean. The Sverdrup dynamics, which directly relates the wind-driven circulation in the interior ocean to wind stress curl and Earth rotation, can be applied to simply address the long-term changes of intensities and pathways of the three surface currents in the tropical North Pacific Ocean.
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30

Lewis, William E., Timothy L. Olander, Christopher S. Velden, Christopher Rozoff, and Stefano Alessandrini. "Analog Ensemble Methods for Improving Satellite-Based Intensity Estimates of Tropical Cyclones." Atmosphere 12, no. 7 (June 28, 2021): 830. http://dx.doi.org/10.3390/atmos12070830.

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Accurate, reliable estimates of tropical cyclone (TC) intensity are a crucial element in the warning and forecast process worldwide, and for the better part of 50 years, estimates made from geostationary satellite observations have been indispensable to forecasters for this purpose. One such method, the Advanced Dvorak Technique (ADT), was used to develop analog ensemble (AnEn) techniques that provide more precise estimates of TC intensity with instant access to information on the reliability of the estimate. The resulting methods, ADT-AnEn and ADT-based Error Analog Ensemble (ADTE-AnEn), were trained and tested using seventeen years of historical ADT intensity estimates using k-fold cross-validation with 10 folds. Using only two predictors, ADT-estimated current intensity (maximum wind speed) and TC center latitude, both AnEn techniques produced significant reductions in mean absolute error and bias for all TC intensity classes in the North Atlantic and for most intensity classes in the Eastern Pacific. The ADTE-AnEn performed better for extreme intensities in both basins (significantly so in the Eastern Pacific) and will be incorporated in the University of Wisconsin’s Cooperative Institute for Meteorological Satellite Studies (UW-CIMSS) workflow for further testing during operations in 2021.
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31

Zovko-Rajak, Dragana, Kevin J. Tory, Robert J. B. Fawcett, Jeffrey D. Kepert, and Lawrence J. Rikus. "High-resolution ensemble prediction of the Australian East Coast Low of April 2015." Journal of Southern Hemisphere Earth Systems Science 68, no. 1 (2018): 165. http://dx.doi.org/10.1071/es18009.

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An analysis of the East Coast Low (ECL) that affected the eastern coast of Australia between 20 and 23 April 2015 is presented, to get a better understanding of the dynamics of the storm as well as its predictability. For this, an ensemble consisting of 24 high-resolution simulations conducted using the ACCESS model is used. The simulated ensemble-mean forecast rainfall is in good agreement with the observed rainfall and identifies Dungog as the area of highest risk of extreme rainfall. A subset of ensemble members shows very little rain in the Dungog area; instead the high rainfall is located further south or east, indicating that a larger part of the coast was at some risk of significant rain. Ensemble member comparisons show that the strongest surface winds and highest rainfall occur to the south of the main surface low, while the strengthening of an upper-troposphere north-westerly jet and the associated cut-off low occur west of the surface low. However, small synoptic-scale differences between members produce large differences in the location and strength of near-surface extreme winds and highest rainfall, which develop in response to the same dynamic processes in each member. The analysis also showed that the thermal advection rainfall diagnostic is applicable to high-resolution data and could be used for analysing ECL development.
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32

Zamboni, Laura, Carlos R. Mechoso, and Fred Kucharski. "Relationships between Upper-Level Circulation over South America and Rainfall over Southeastern South America: A Physical Base for Seasonal Predictions." Journal of Climate 23, no. 12 (June 15, 2010): 3300–3315. http://dx.doi.org/10.1175/2009jcli3129.1.

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Abstract The existence of a significant simultaneous correlation between bimonthly mean precipitation anomalies over southeastern South America (SESA) and either the first or the second (depending on season) leading mode of interannual variability of upper-level wind over South America (SA) is demonstrated during all seasons except winter. The pattern associated with these modes of variability is similar during all seasons and consists of a continental-scale vortex centered over the eastern coast of subtropical SA. The vortex has a quasi-barotropic structure during all seasons, and its variability modifies moisture transport from the South American low-level jet and the western tropical Atlantic to SESA thus creating precipitation anomalies in this region. During spring (October–November) and summer (January–February) the circulation creates a second center of precipitation anomalies over the South Atlantic convergence zone that are of opposite sign to those over SESA, while during fall (April–May) precipitation anomalies are primarily confined to SESA. On the basis of the correlation between upper-level winds and precipitation, an empirical method to produce long-range forecasts of bimonthly mean precipitation over SESA is developed. Method tests in hindcast mode for the period 1959–2001 show a potential for reliable predictions during the southern spring, summer, and fall. The method is further tested in an experimental mode by using Development of a European Multimodel Ensemble System for Seasonal-to-Interannual Prediction (DEMETER) wind hindcasts. Forecasts obtained in this way are skillful during spring only, with highest skill during El Niño–Southern Oscillation years. During summer and fall, the DEMETER forecasts of wind anomalies limit the method’s ability to make reliable real predictions.
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33

Ivantsyk, Timur V., and Alexey M. Salimov. "The Eastern wing of the Musin-Pushkin estate in Moscow based on historical, architectural and field studies." Vestnik MGSU, no. 10 (October 2022): 1307–23. http://dx.doi.org/10.22227/1997-0935.2022.10.1307-1323.

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Introduction. The paper concentrates on a cultural heritage object that is involved in forming the architectural look of the Musin-Pushkin Estate at the intersection of Dobroslobodskaya and Spartakovskaya Streets in Moscow (now the group of buildings of the Moscow State University of Civil Engineering) — the eastern wing of the ensemble, that forms the eastern corner of the estate. This building hasn’t a status of cultural heritage object and has undergone numerous renovations and reorganisations by present time, and we can see the signs of it in the interiors and on the facades of the monument. The main aim of this work — to retrace the wing’s forming during the history by consideration its volume it the context of the surrounding buildings, to uncover the initial look of the monument, and to define its construction periodization, and, as a consequence, — to propose graphical reconstruction of this structure, which will consider not only the earliest period of the structure’s being, but the stage of the enrichment by new, however no less interesting architectural forms. Materials and methods. The study of the monument was based on the method of comprehensive source study, which includes the search and analysis of sources and literature, field studies, including probing, pit sampling and measuring work, as well as chemical development study of building and finishing materials. Using the comparative method, this object was studied among stylistically and typologically similar buildings. Results. As a result of the studies, an amount of the signs show on the availability of the historical core, which has formed the volume of the wing. The construction periodization of the monument was identified, its existing volumes were dated, the initial elements of the building were revealed and studied, and later strata were identified, which allowed to identify a look of the structure in different periods of it’s being and developing a graphic reconstruction of the eastern wing at the initial period. Conclusions. The proposed reconstruction of the monument has resulted from the comprehensive studies allowing to reconstruct the initial look of the building with taking into account its losted volumes. As a result, it will enrich one of the most fascinating manor ensembles in Moscow providing its completion.
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34

Lengaigne, Matthieu, Jean-Philippe Boulanger, Christophe Menkes, and Hilary Spencer. "Influence of the Seasonal Cycle on the Termination of El Niño Events in a Coupled General Circulation Model." Journal of Climate 19, no. 9 (May 1, 2006): 1850–68. http://dx.doi.org/10.1175/jcli3706.1.

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Abstract In this study, the mechanisms leading to the El Niño peak and demise are explored through a coupled general circulation model ensemble approach evaluated against observations. The results here suggest that the timing of the peak and demise for intense El Niño events is highly predictable as the evolution of the coupled system is strongly driven by a southward shift of the intense equatorial Pacific westerly anomalies during boreal winter. In fact, this systematic late-year shift drives an intense eastern Pacific thermocline shallowing, constraining a rapid El Niño demise in the following months. This wind shift results from a southward displacement in winter of the central Pacific warmest SSTs in response to the seasonal evolution of solar insolation. In contrast, the intensity of this seasonal feedback mechanism and its impact on the coupled system are significantly weaker in moderate El Niño events, resulting in a less pronounced thermocline shallowing. This shallowing transfers the coupled system into an unstable state in spring but is not sufficient to systematically constrain the equatorial Pacific evolution toward a rapid El Niño termination. However, for some moderate events, the occurrence of intense easterly wind anomalies in the eastern Pacific during that period initiate a rapid surge of cold SSTs leading to La Niña conditions. In other cases, weaker trade winds combined with a slightly deeper thermocline allow the coupled system to maintain a broad warm phase evolving through the entire spring and summer and a delayed El Niño demise, an evolution that is similar to the prolonged 1986/87 El Niño event. La Niña events also show a similar tendency to peak in boreal winter, with characteristics and mechanisms mainly symmetric to those described for moderate El Niño cases.
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35

Torn, Ryan D., Jeffrey S. Whitaker, Philip Pegion, Thomas M. Hamill, and Gregory J. Hakim. "Diagnosis of the Source of GFS Medium-Range Track Errors in Hurricane Sandy (2012)." Monthly Weather Review 143, no. 1 (January 1, 2015): 132–52. http://dx.doi.org/10.1175/mwr-d-14-00086.1.

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Abstract Medium-range forecasts of Hurricane Sandy’s track were characterized by widely diverging solutions, with some suggesting that Sandy would make landfall over the mid-Atlantic region of the United States, while others forecast the storm to move due east to the north of Bermuda. Here, dynamical processes responsible for the eastward-tracking forecasts are diagnosed using an 80-member ensemble of experimental Global Forecast System (GFS) forecasts initialized five days prior to landfall. Comparing the ensemble members with tracks to the east against those with tracks to the west indicates that the eastern members were characterized by a lower-amplitude upper-tropospheric anticyclone on the poleward side of Sandy during the first 24 h of the forecast, which in turn was associated with a westerly perturbation steering wind. The amplification of this ridge in each set of members was modulated by differences in the advection of potential vorticity (PV) by the irrotational wind associated with Sandy’s secondary circulation and isentropic lift along a warm front that formed on the poleward side of Sandy. The amplitude of the irrotational wind in this region was proportional to the 0-h water vapor mixing ratio, and to a lesser extent the 0-h upper-tropospheric horizontal divergence. These two quantities modulated the vertical profile of grid-scale condensation within the model and subsequent upper-tropospheric divergence. The results from this study suggest that additional observations within regions of large-scale precipitation outside the tropical cyclone (TC) core could benefit TC track forecasts, particularly when the TC is located near an upper-tropospheric PV gradient.
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36

Hegyi, Bradley M., Yi Deng, Robert X. Black, and Renjun Zhou. "Initial Transient Response of the Winter Polar Stratospheric Vortex to Idealized Equatorial Pacific Sea Surface Temperature Anomalies in the NCAR WACCM." Journal of Climate 27, no. 7 (March 26, 2014): 2699–713. http://dx.doi.org/10.1175/jcli-d-13-00289.1.

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Abstract Perpetual winter simulations using the NCAR Whole Atmosphere Community Climate Model (WACCM) are conducted to document the differences of the initial transient response of the boreal winter Northern Hemisphere stratospheric polar vortex to central (CPW) and eastern Pacific warming (EPW) events. Idealized patches of positive sea surface temperature (SST) anomalies are superimposed onto a climatological SST field to mimic canonical CPW and EPW forcings. A 20-member ensemble was created by varying initial atmospheric conditions for both CPW and EPW cases. In the ensemble average, the vortex weakens under both CPW and EPW forcing, indicated by a negative zonal mean zonal wind tendency. This tendency is mainly tied to changes in the eddy-driven mean meridional circulation (MMC). A negative anomaly in the eddy momentum flux convergence also plays a secondary role in the weakening. The vortex response, however, differs dramatically among individual ensemble members. A few ensemble members exhibit initial vortex strengthening although weaker in magnitude and shorter in duration than the initial weakening in the ensemble average. The initial state and the subsequent internal variation of the extratropical atmosphere is at least as important as the type of SST forcing in determining the transient response of the stratospheric polar vortex. Interactions between the internal variability of the vortex and SST-driven wave anomalies ultimately determine the nature of the initial transient response of the vortex to EPW and CPW forcing. This sensitivity to the initial atmospheric state has implications for understanding medium-range forecasts of the extratropical atmospheric response to emerging tropical SST anomalies, particularly over high-latitude regions.
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37

Wang, Chunzai, Sang-ki Lee, and David B. Enfield. "Impact of the Atlantic Warm Pool on the Summer Climate of the Western Hemisphere." Journal of Climate 20, no. 20 (October 15, 2007): 5021–40. http://dx.doi.org/10.1175/jcli4304.1.

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Abstract The Atlantic warm pool (AWP) is a large body of warm water that comprises the Gulf of Mexico, the Caribbean Sea, and the western tropical North Atlantic. Located to its northeastern side is the North Atlantic subtropical high (NASH), which produces the tropical easterly trade winds. The easterly trade winds carry moisture from the tropical North Atlantic into the Caribbean Sea, where the flow intensifies, forming the Caribbean low-level jet (CLLJ). The CLLJ then splits into two branches: one turning northward and connecting with the Great Plains low-level jet (GPLLJ), and the other continuing westward across Central America into the eastern North Pacific. The easterly CLLJ and its westward moisture transport are maximized in the summer and winter, whereas they are minimized in the fall and spring. This semiannual feature results from the semiannual variation of sea level pressure in the Caribbean region owing to the westward extension and eastward retreat of the NASH. The NCAR Community Atmospheric Model and observational data are used to investigate the impact of the climatological annual mean AWP on the summer climate of the Western Hemisphere. Two groups of the model ensemble runs with and without the AWP are performed and compared. The model results show that the effect of the AWP is to weaken the summertime NASH, especially at its southwestern edge. The AWP also strengthens the summertime continental low over the North American monsoon region. In response to these pressure changes, the CLLJ and its moisture transport are weakened, but its semiannual feature does not disappear. The weakening of the easterly CLLJ increases (decreases) moisture convergence to its upstream (downstream) and thus enhances (suppresses) rainfall in the Caribbean Sea (in the far eastern Pacific west of Central America). Model runs show that the AWP’s effect is to always weaken the southerly GPLLJ. However, the AWP strengthens the GPLLJ’s northward moisture transport in the summer because the AWP-induced increase of specific humidity overcomes the weakening of southerly wind, and vice versa in the fall. Finally, the AWP reduces the tropospheric vertical wind shear in the main development region that favors hurricane formation and development during August–October.
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Bellafiore, D., E. Bucchignani, S. Gualdi, S. Carniel, V. Djurdjeviæ, and G. Umgiesser. "Evaluating meteorological climate model inputs to improve coastal hydrodynamic studies." Advances in Science and Research 6, no. 1 (August 22, 2011): 227–31. http://dx.doi.org/10.5194/asr-6-227-2011.

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Abstract. This work compares meteorological results from different regional climate model (RCM) implementations in the Mediterranean area, with a focus on the northern Adriatic Sea. The need to use these datasets as atmospheric forcings (wind and atmospheric pressure fields) for coastal hydrodynamic models to assess future changes in the coastal hydrodynamics, is the basis of the presented analysis. It would allow the assessment of uncertainties due to atmospheric forcings in providing coastal current, surge and wave climate changes from future implementations of hydrodynamic models. Two regional climate models, with different spatial resolutions, downscaled from two different global climate models (whose atmospheric components are, respectively, ECHAM4 and ECHAM5), were considered. In particular, the RCM delivered wind and atmospheric pressure fields were compared with measurements at four stations along the Italian Adriatic coast. The analyses were conducted using a past control period, 1960–1990, and the A1B IPCC future scenario (2070–2100). The chosen scenario corresponds to a world of very rapid economic and demographic growth that peaks in mid-century, with a rapid introduction of new efficient technologies, which balance fossil and non-fossil resources (IPCC, 2007). Consideration is given to the accuracy of each model at reproducing the basic statistics and the trends. The role of models' spatial resolution in reproducing global and local scale meteorological processes is also discussed. The Adriatic Sea climate is affected by the orography that produces a strengthening of north-eastern katabatic winds like bora. Therefore, spatial model resolution, both for orography and for a better resolution of coastline (Cavaleri et al., 2010), is one of the important factors in providing more realistic wind forcings for future hydrodynamic models implementations. However, also the characteristics in RCM setup and parameterization can explain differences between the datasets. The analysis from an ensemble of model implementation would provide more robust indications on climatic wind and atmospheric pressure variations. The scenario-control comparison shows a general increase in the mean atmospheric pressure values while a decrease in mean wind speed and in extreme wind events is seen, particularly for the datasets with higher spatial resolution.
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39

Siongco, Angela Cheska, Hsi-Yen Ma, Stephen A. Klein, Shaocheng Xie, Alicia R. Karspeck, Kevin Raeder, and Jeffrey L. Anderson. "A Hindcast Approach to Diagnosing the Equatorial Pacific Cold Tongue SST Bias in CESM1." Journal of Climate 33, no. 4 (February 15, 2020): 1437–53. http://dx.doi.org/10.1175/jcli-d-19-0513.1.

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AbstractAn ensemble seasonal hindcast approach is used to investigate the development of the equatorial Pacific Ocean cold sea surface temperature (SST) bias and its characteristic annual cycle in the Community Earth System Model, version 1 (CESM1). In observations, eastern equatorial Pacific SSTs exhibit a warm phase during boreal spring and a cold phase during late boreal summer–autumn. The CESM1 climatology shows a cold bias during both warm and cold phases. In our hindcasts, the cold bias during the cold phase develops in less than 6 months, whereas the cold bias during the warm phase takes longer to emerge. The fast-developing cold-phase cold bias is associated with too-strong vertical advection and easterly wind stress over the eastern equatorial region. The antecedent boreal summer easterly wind anomalies also appear in atmosphere-only simulations, indicating that the errors are intrinsic to the atmosphere component. For the slower-developing warm-phase cold bias, we find that the too-cold SSTs over the equatorial region are associated with a slowly evolving upward displacement of subsurface ocean zonal currents and isotherms that can be traced to the ocean component.
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40

Terada, Mio, Shoshiro Minobe, and Curtis Deutsch. "Mechanisms of Future Changes in Equatorial Upwelling: CMIP5 Intermodel Analysis." Journal of Climate 33, no. 2 (January 15, 2020): 497–510. http://dx.doi.org/10.1175/jcli-d-19-0128.1.

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AbstractThe future change in equatorial upwelling between 1971–2000 and 2071–2100 is investigated using data from 24 coupled climate models. The multimodel ensemble (MME) mean exhibits substantial equatorial upwelling decrease in the eastern Pacific and weaker decrease in the western Atlantic Ocean. The MME mean of upwelling change and intermodel variation of that are decomposed into distinct isopycnal and diapycnal components. In the Pacific, the diapycnal upwelling decreases near the surface, associated with a weakened Ekman pumping. The isopycnal upwelling decreases at depths of 75–200 m around the core of the Equatorial Undercurrent (EUC) due to flattening of the density layer in which it flows. Both the weakened Ekman pumping and the EUC flattening are induced by the locally weakened trade wind over the eastern Pacific basin. In the equatorial Atlantic, both the change in MME mean and the intermodel variation of upwellings are significantly related to the weakened trade wind and enhanced stratification, although these drivers are not independent. The results for the Pacific Ocean imply that future reduction in upwelling may have impacts at different depths by different mechanisms. In particular, the rapid warming of sea surface temperature in the eastern Pacific basin may be mainly caused by the near-surface diapycnal upwelling reduction rather than isopycnal upwelling reduction associated EUC flattening, which is important at deeper levels.
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41

Wang, Ding, Boyang Liu, Pang-Ning Tan, and Lifeng Luo. "OMuLeT: Online Multi-Lead Time Location Prediction for Hurricane Trajectory Forecasting." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 01 (April 3, 2020): 963–70. http://dx.doi.org/10.1609/aaai.v34i01.5444.

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Hurricanes are powerful tropical cyclones with sustained wind speeds ranging from at least 74 mph (for category 1 storms) to more than 157 mph (for category 5 storms). Accurate prediction of the storm tracks is essential for hurricane preparedness and mitigation of storm impacts. In this paper, we cast the hurricane trajectory forecasting task as an online multi-lead time location prediction problem and present a framework called OMuLeT to improve path prediction by combining the 6-hourly and 12-hourly forecasts generated from an ensemble of dynamical (physical) hurricane models. OMuLeT employs an online learning with restart strategy to incrementally update the weights of the ensemble model combination as new observation data become available. It can also handle the varying dynamical models available for predicting the trajectories of different hurricanes. Experimental results using the Atlantic and Eastern Pacific hurricane data showed that OMuLeT significantly outperforms various baseline methods, including the official forecasts produced by the U.S. National Hurricane Center (NHC), by more than 10% in terms of its 48-hour lead time forecasts.
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42

Wang, Xuguang, Dale M. Barker, Chris Snyder, and Thomas M. Hamill. "A Hybrid ETKF–3DVAR Data Assimilation Scheme for the WRF Model. Part II: Real Observation Experiments." Monthly Weather Review 136, no. 12 (December 1, 2008): 5132–47. http://dx.doi.org/10.1175/2008mwr2445.1.

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Abstract The hybrid ensemble transform Kalman filter–three-dimensional variational data assimilation (ETKF–3DVAR) system developed for the Weather Research and Forecasting (WRF) Model was further tested with real observations, as a follow-up for the observation system simulation experiment (OSSE) conducted in Part I. A domain encompassing North America was considered. Because of limited computational resources and the large number of experiments conducted, the forecasts and analyses employed relatively coarse grid spacing (200 km) to emphasize synoptic scales. As a first effort to explore the new system with real observations, relatively sparse observation datasets consisting of radiosonde wind and temperature during 4 weeks of January 2003 were assimilated. The 12-h forecasts produced by the hybrid analysis produced less root-mean-square error than the 3DVAR. The hybrid improved the forecast more in the western part of the domain than the eastern part. It also produced larger improvements in the upper troposphere. The overall magnitude of the ETKF ensemble spread agreed with the overall magnitude of the background forecast error. For individual variables and layers, the consistency between the spread and the error was less than the OSSE in Part I. Given the coarse resolution and relatively sparse observation network adopted in this study, caution is warranted when extrapolating these results to operational applications. A case study was also performed to further understand a large forecast improvement of the hybrid during the 4-week period. The flow-dependent adjustments produced by the hybrid extended a large distance into the eastern Pacific data-void region. The much improved analysis and forecast by the hybrid in the data void subsequently improved forecasts downstream in the region of verification. Although no moisture observations were assimilated, the hybrid updated the moisture fields flow dependently through cross-variable covariances defined by the ensemble, which improved the forecasts of cyclone development.
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43

Jury, Mark R. "Marine climate change over the eastern Agulhas Bank of South Africa." Ocean Science 16, no. 6 (December 17, 2020): 1529–44. http://dx.doi.org/10.5194/os-16-1529-2020.

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Abstract. The rate of change in the marine environment over the eastern Agulhas Bank along the south coast of South Africa (32–37∘ S, 20–30∘ E) is studied using reanalysis observations for 1900–2015 and coupled ensemble model projections for 1980–2100. Outcomes are influenced by resolution and time span: ∼ 1∘ datasets covering the whole period capture large-scale changes, while ∼ 0.5∘ datasets in the satellite era better distinguish the cross-shelf gradients. Although sea surface temperatures offshore are warming rapidly (0.05 ∘C yr−1 since 1980), a trend toward easterly winds and a locally stronger Agulhas Current have intensified nearshore upwelling (−0.03 ∘C yr−1). The subtropical ridge is gradually moving poleward, leading to a drier climate.
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44

Hill, Aaron J., Gregory R. Herman, and Russ S. Schumacher. "Forecasting Severe Weather with Random Forests." Monthly Weather Review 148, no. 5 (April 28, 2020): 2135–61. http://dx.doi.org/10.1175/mwr-d-19-0344.1.

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Abstract Using nine years of historical forecasts spanning April 2003–April 2012 from NOAA’s Second Generation Global Ensemble Forecast System Reforecast (GEFS/R) ensemble, random forest (RF) models are trained to make probabilistic predictions of severe weather across the contiguous United States (CONUS) at Days 1–3, with separate models for tornado, hail, and severe wind prediction at Day 1 in an analogous fashion to the Storm Prediction Center’s (SPC’s) convective outlooks. Separate models are also trained for the western, central, and eastern CONUS. Input predictors include fields associated with severe weather prediction, including CAPE, CIN, wind shear, and numerous other variables. Predictor inputs incorporate the simulated spatiotemporal evolution of these atmospheric fields throughout the forecast period in the vicinity of the forecast point. These trained RF models are applied to unseen inputs from April 2012 to December 2016, and their forecasts are evaluated alongside the equivalent SPC outlooks. The RFs objectively make statistical deductions about the relationships between various simulated atmospheric fields and observations of different severe weather phenomena that accord with the community’s physical understandings about severe weather forecasting. Using these quantified flow-dependent relationships, the RF outlooks are found to produce calibrated probabilistic forecasts that slightly underperform SPC outlooks at Day 1, but significantly outperform their outlooks at Days 2 and 3. In all cases, a blend of the SPC and RF outlooks significantly outperforms the SPC outlooks alone, suggesting that use of RFs can improve operational severe weather forecasting throughout the Day 1–3 period.
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45

Madaus, Luke E., and Clifford F. Mass. "Evaluating Smartphone Pressure Observations for Mesoscale Analyses and Forecasts." Weather and Forecasting 32, no. 2 (March 3, 2017): 511–31. http://dx.doi.org/10.1175/waf-d-16-0135.1.

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Abstract Smartphone pressure observations have the potential to greatly increase surface observation density on convection-resolving scales. Currently available smartphone pressure observations are tested through assimilation in a mesoscale ensemble for a 3-day, convectively active period in the eastern United States. Both raw pressure (altimeter) observations and 1-h pressure (altimeter) tendency observations are considered. The available observation density closely follows population density, but observations are also available in rural areas. The smartphone observations are found to contain significant noise, which can limit their effectiveness. The assimilated smartphone observations contribute to small improvements in 1-h forecasts of surface pressure and 10-m wind, but produce larger errors in 2-m temperature forecasts. Short-term (0–4 h) precipitation forecasts are improved when smartphone pressure and pressure tendency observations are assimilated as compared with an ensemble that assimilates no observations. However, these improvements are limited to broad, mesoscale features with minimal skill provided at convective scales using the current smartphone observation density. A specific mesoscale convective system (MCS) is examined in detail, and smartphone pressure observations captured the expected dynamic structures associated with this feature. Possibilities for further development of smartphone observations are discussed.
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46

Zhou, Xiaqiong, Yuejian Zhu, Dingchen Hou, Yan Luo, Jiayi Peng, and Richard Wobus. "Performance of the New NCEP Global Ensemble Forecast System in a Parallel Experiment." Weather and Forecasting 32, no. 5 (October 1, 2017): 1989–2004. http://dx.doi.org/10.1175/waf-d-17-0023.1.

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Abstract A new version of the Global Ensemble Forecast System (GEFS, v11) is tested and compared with the operational version (v10) in a 2-yr parallel run. The breeding-based scheme with ensemble transformation and rescaling (ETR) used in the operational GEFS is replaced by the ensemble Kalman filter (EnKF) to generate initial ensemble perturbations. The global medium-range forecast model and the Global Forecast System (GFS) analysis used as the initial conditions are upgraded to the GFS 2015 implementation version. The horizontal resolution of GEFS increases from Eulerian T254 (~52 km) for the first 8 days of the forecast and T190 (~70 km) for the second 8 days to semi-Lagrangian T574 (~34 km) and T382 (~52 km), respectively. The sigma pressure hybrid vertical layers increase from 42 to 64 levels. The verification of geopotential height, temperature, and wind fields at selected levels shows that the new GEFS significantly outperforms the operational GEFS up to days 8–10 except for an increased warm bias over land in the extratropics. It is also found that the parallel system has better reliability in the short-range probability forecasts of precipitation during warm seasons, but no clear improvement in cold seasons. There is a significant degradation of TC track forecasts at days 6–7 during the 2012–14 TC seasons over the Atlantic and eastern Pacific. This degradation is most likely a sampling issue from a low number of TCs during these three TC seasons. The results for an extended verification period (2011–14) and the recent two hurricane seasons (2015 and 2016) are generally positive. The new GEFS became operational at NCEP on 2 December 2015.
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47

Tim, N., E. Zorita, B. Hünicke, X. Yi, and K. C. Emeis. "Imprint of external climate forcing on coastal upwelling in past and future climate." Ocean Science Discussions 12, no. 6 (November 23, 2015): 2899–930. http://dx.doi.org/10.5194/osd-12-2899-2015.

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Abstract. The Eastern Boundary Upwelling Systems are the major coastal upwelling regions. The trade winds are driving these upwelling regimes located in the subtropics at the eastern boundary of the Atlantic and Pacific Ocean. Here we analyse the impact of the external climate forcing, e.g. the greenhouse gas concentration, solar activity and volcano eruptions, on these upwelling systems in simulations of ensembles of two Earth System Models. The ensembles contain three simulations for each time period which cover the past millennium (900–1850), the 20th century (1850–2005) and the near future (2006–2100). Using a set of simulations, differing only in their initial conditions, enables us to detect whether the variability is driven internally or externally. Our analysis shows that the variability of the simulated upwelling is to the most driven internally and that there are no significant trends except for the scenario with the most dramatic increase of greenhouse gas concentrations.
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48

Wolfram, Phillip J., Todd D. Ringler, Mathew E. Maltrud, Douglas W. Jacobsen, and Mark R. Petersen. "Diagnosing Isopycnal Diffusivity in an Eddying, Idealized Midlatitude Ocean Basin via Lagrangian, in Situ, Global, High-Performance Particle Tracking (LIGHT)." Journal of Physical Oceanography 45, no. 8 (August 2015): 2114–33. http://dx.doi.org/10.1175/jpo-d-14-0260.1.

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AbstractIsopycnal diffusivity due to stirring by mesoscale eddies in an idealized, wind-forced, eddying, midlatitude ocean basin is computed using Lagrangian, in Situ, Global, High-Performance Particle Tracking (LIGHT). Simulation is performed via LIGHT within the Model for Prediction across Scales Ocean (MPAS-O). Simulations are performed at 4-, 8-, 16-, and 32-km resolution, where the first Rossby radius of deformation (RRD) is approximately 30 km. Scalar and tensor diffusivities are estimated at each resolution based on 30 ensemble members using particle cluster statistics. Each ensemble member is composed of 303 665 particles distributed across five potential density surfaces. Diffusivity dependence upon model resolution, velocity spatial scale, and buoyancy surface is quantified and compared with mixing length theory. The spatial structure of diffusivity ranges over approximately two orders of magnitude with values of O(105) m2 s−1 in the region of western boundary current separation to O(103) m2 s−1 in the eastern region of the basin. Dominant mixing occurs at scales twice the size of the first RRD. Model resolution at scales finer than the RRD is necessary to obtain sufficient model fidelity at scales between one and four RRD to accurately represent mixing. Mixing length scaling with eddy kinetic energy and the Lagrangian time scale yield mixing efficiencies that typically range between 0.4 and 0.8. A reduced mixing length in the eastern region of the domain relative to the west suggests there are different mixing regimes outside the baroclinic jet region.
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49

Chen, Shangfeng, and Bin Yu. "Projection of winter NPO-following winter ENSO connection in a warming climate: uncertainty due to internal climate variability." Climatic Change 162, no. 2 (July 8, 2020): 723–40. http://dx.doi.org/10.1007/s10584-020-02778-3.

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Abstract Previous observational and modeling studies indicate that the wintertime North Pacific Oscillation (NPO) could significantly impact the following winter El Niño-Southern Oscillation (ENSO) variability via the seasonal footprinting mechanism (SFM). This study explores climate projections of this winter NPO-ENSO relation in a warming climate based on a 50-member large ensemble of climate simulations conducted with the second-generation Canadian Earth System Model (CanESM2). The ensemble mean of the 50 members can well reproduce the observed winter NPO pattern, the NPO-ENSO relationship, and the SFM process over the historical period 1950–2003. These 50 members are then employed to examine climate projections of the NPO-ENSO connection over the anthropogenic forced period 2020–2073. Results indicate that there exists a large spread of projected NPO-ENSO connections across these 50 ensemble members due to internal climate variability. Internal climate variability brings uncertainties in the projection of the winter NPO-ENSO connection originally seen in projected changes of the subtropical center of the winter NPO. The spread of projections of winter NPO-associated atmospheric anomalies over the subtropical North Pacific further results in various responses in the projections of winter and spring precipitation anomalies over the tropical North Pacific, as well as spring zonal wind anomalies over the tropical western Pacific, which eventually lead to uncertainties in the projection of the sea surface temperature anomalies in the tropical central-eastern Pacific from the following summer to winter.
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Dethloff, Klaus, Wieslaw Maslowski, Stefan Hendricks, Younjoo J. Lee, Helge F. Goessling, Thomas Krumpen, Christian Haas, et al. "Arctic sea ice anomalies during the MOSAiC winter 2019/20." Cryosphere 16, no. 3 (March 14, 2022): 981–1005. http://dx.doi.org/10.5194/tc-16-981-2022.

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Abstract. During the winter of 2019/2020, as the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) project started its work, the Arctic Oscillation (AO) experienced some of its largest shifts, ranging from a highly negative index in November 2019 to an extremely positive index during January–February–March (JFM) 2020. The permanent positive AO phase for the 3 months of JFM 2020 was accompanied by a prevailing positive phase of the Arctic Dipole (AD) pattern. Here we analyze the sea ice thickness (SIT) distribution based on CryoSat-2/SMOS satellite-derived data augmented with results from the hindcast simulation by the fully coupled Regional Arctic System Model (RASM) from November 2019 through March 2020. A notable result of the positive AO phase during JFM 2020 was large SIT anomalies of up to 1.3 m that emerged in the Barents Sea (BS), along the northeastern Canadian coast and in parts of the central Arctic Ocean. These anomalies appear to be driven by nonlinear interactions between thermodynamic and dynamic processes. In particular, in the Barents and Kara seas (BKS), they are a result of enhanced ice growth connected with low-temperature anomalies and the consequence of intensified atmospherically driven sea ice transport and deformations (i.e., ice divergence and shear) in this area. The Davies Strait, the east coast of Greenland and the BS regions are characterized by convergence and divergence changes connected with thinner sea ice at the ice borders along with an enhanced impact of atmospheric wind forcing. Low-pressure anomalies that developed over the eastern Arctic during JFM 2020 increased northerly winds from the cold Arctic Ocean to the BS and accelerated the southward drift of the MOSAiC ice floe. The satellite-derived and simulated sea ice velocity anomalies, which compared well during JFM 2020, indicate a strong acceleration of the Transpolar Drift relative to the mean for the past decade, with intensified speeds of up to 6 km d−1. As a consequence, sea ice transport and deformations driven by atmospheric surface wind forcing accounted for the bulk of the SIT anomalies, especially in January 2020 and February 2020. RASM intra-annual ensemble forecast simulations with 30 ensemble members forced with different atmospheric boundary conditions from 1 November 2019 through 30 April 2020 show a pronounced internal variability in the sea ice volume, driven by thermodynamic ice-growth and ice-melt processes and the impact of dynamic surface winds on sea ice formation and deformation. A comparison of the respective SIT distributions and turbulent heat fluxes during the positive AO phase in JFM 2020 and the negative AO phase in JFM 2010 corroborates the conclusion that winter sea ice conditions in the Arctic Ocean can be significantly altered by AO variability.
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