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Journal articles on the topic 'Run-Time bias-Correction'

Author: Grafiati

Published: 7 July 2024

Last updated: 31 July 2025

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1

Okui, Ryo. "Asymptotically Unbiased Estimation of Autocovariances and Autocorrelations with Panel Data in the Presence of Individual and Time Effects." Journal of Time Series Econometrics 6, no. 2 (2014): 129–81. http://dx.doi.org/10.1515/jtse-2013-0017.

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AbstractThis article proposes asymptotically unbiased estimators of autocovariances and autocorrelations for panel data with both individual and time effects. We show that the conventional autocovariance estimators suffer from the bias caused by the elimination of individual and time effects. The bias related to individual effects is proportional to the long-run variance, and it related to time effects is proportional to the value of the estimated autocovariance. For the conventional autocorrelation estimators, the elimination of time effects does not cause a bias while the elimination of indi

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2

Yan, Changxiang, and Jiang Zhu. "A Simple Bias Correction Scheme in Ocean Data Assimilation." Journal of Marine Science and Engineering 11, no. 1 (2023): 205. http://dx.doi.org/10.3390/jmse11010205.

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The mode bias is present and time-dependent due to imperfect configurations. Data assimilation is the process by which observations are used to correct the model forecast, and is affected by the bias. How to reduce the bias is an important issue. This paper investigates the roles of a simple bias correction scheme in ocean data assimilation. In this scheme, the misfits between modeled and monthly temperature and salinity with interannual variability from the Met Office Hadley Centre subsurface temperature and salinity data set (EN4.2.2) are used for the innovations in assimilation via the Ense

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von Auer, Ludwig, and Alena Shumskikh. "Substitution Bias in the Measurement of Import and Export Price Indices: Causes and Correction." Journal of Official Statistics 38, no. 1 (2022): 107–26. http://dx.doi.org/10.2478/jos-2022-0006.

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Abstract The import and export price indices of an economy are usually compiled by some Laspeyres type index. It is well known that such an index formula is prone to substitution bias. Therefore, also the terms of trade (ratio of export and import price index) are likely to be distorted. The underlying substitution bias accumulates over time. The present article introduces a simple and transparent retroactive correction approach that addresses the source of the substitution bias and produces meaningful long-run time series of import and export price levels and, therefore, of the terms of trade

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Osuch, M., R. J. Romanowicz, D. Lawrence, and W. K. Wong. "Assessment of the influence of bias correction on meteorological drought projections for Poland." Hydrology and Earth System Sciences Discussions 12, no. 10 (2015): 10331–77. http://dx.doi.org/10.5194/hessd-12-10331-2015.

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Abstract. Possible future climate change effects on drought severity in Poland are estimated for six ENSEMBLE climate projections using the Standard Precipitation Index (SPI). The time series of precipitation represent six different RCM/GCM run under the A1B SRES scenario for the period 1971–2099. Monthly precipitation values were used to estimate the Standard Precipitation Index (SPI) for multiple time scales (1, 3, 6, 12 and 24 months) for a spatial resolution of 25 km × 25 km for the whole country. Trends in SPI were analysed using a Mann–Kendall test with Sen's slope estimator for each 25

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Rogers, Bruce, David Giles, Nick Draper, Laurent Mourot, and Thomas Gronwald. "Influence of Artefact Correction and Recording Device Type on the Practical Application of a Non-Linear Heart Rate Variability Biomarker for Aerobic Threshold Determination." Sensors 21, no. 3 (2021): 821. http://dx.doi.org/10.3390/s21030821.

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Recent study points to the value of a non-linear heart rate variability (HRV) biomarker using detrended fluctuation analysis (DFA a1) for aerobic threshold determination (HRVT). Significance of recording artefact, correction methods and device bias on DFA a1 during exercise and HRVT is unclear. Gas exchange and HRV data were obtained from 17 participants during an incremental treadmill run using both ECG and Polar H7 as recording devices. First, artefacts were randomly placed in the ECG time series to equal 1, 3 and 6% missed beats with correction by Kubios software’s automatic and medium thre

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Rocha, Fabiana. "Correlação poupança-investimento: o que é possível dizer sobre o modelo de correção de erros a partir dos dados brasileiros." Economia Aplicada 7, no. 1 (2003): 5–21. https://doi.org/10.11606/1413-8050/ea220071.

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The purpose of this paper is to determine if the error correction model is superior to the other time series tests (cointegration between saving and investment and stationarity of the current account) which focused the long run relationship in evaluating the degree of capital mobility, as suggested by Jansen (1996). Besides it seeks to determine which kind of bias results from the estimates of the short run correlation, with variables in levels or first differences. Using Brazilian data for the period 1960-1996 as example all the tests point in the same direction, that is, capital mobility. Th

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Phan Van, Tan, Hiep Van Nguyen, Long Trinh Tuan, et al. "Seasonal Prediction of Surface Air Temperature across Vietnam Using the Regional Climate Model Version 4.2 (RegCM4.2)." Advances in Meteorology 2014 (2014): 1–13. http://dx.doi.org/10.1155/2014/245104.

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To investigate the ability of dynamical seasonal climate predictions for Vietnam, the RegCM4.2 is employed to perform seasonal prediction of 2 m mean (T2m), maximum (Tx), and minimum (Tn) air temperature for the period from January 2012 to November 2013 by downscaling the NCEP Climate Forecast System (CFS) data. For model bias correction, the model and observed climatology is constructed using the CFS reanalysis and observed temperatures over Vietnam for the period 1980–2010, respectively. The RegCM4.2 forecast is run four times per month from the current month up to the next six months. A mod

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Krinner, Gerhard, Julien Beaumet, Vincent Favier, Michel Déqué, and Claire Brutel-Vuilmet. "Empirical Run-Time Bias Correction for Antarctic Regional Climate Projections With a Stretched-Grid AGCM." Journal of Advances in Modeling Earth Systems 11, no. 1 (2019): 64–82. http://dx.doi.org/10.1029/2018ms001438.

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Gupta, Abhimanyu, and Myung Hwan Seo. "Robust Inference on Infinite and Growing Dimensional Time‐Series Regression." Econometrica 91, no. 4 (2023): 1333–61. http://dx.doi.org/10.3982/ecta17918.

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We develop a class of tests for time‐series models such as multiple regression with growing dimension, infinite‐order autoregression, and nonparametric sieve regression. Examples include the Chow test and general linear restriction tests of growing rank p. Employing such increasing p asymptotics, we introduce a new scale correction to conventional test statistics, which accounts for a high‐order long‐run variance (HLV), which emerges as p grows with sample size. We also propose a bias correction via a null‐imposed bootstrap to alleviate finite‐sample bias without sacrificing power unduly. A si

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Wei, Linyong, Shanhu Jiang, Liliang Ren, et al. "Bias correction of GPM IMERG Early Run daily precipitation product using near real-time CPC global measurements." Atmospheric Research 279 (December 2022): 106403. http://dx.doi.org/10.1016/j.atmosres.2022.106403.

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Ma, Qiumei, Lihua Xiong, Jun Xia, Bin Xiong, Han Yang, and Chong-Yu Xu. "A Censored Shifted Mixture Distribution Mapping Method to Correct the Bias of Daily IMERG Satellite Precipitation Estimates." Remote Sensing 11, no. 11 (2019): 1345. http://dx.doi.org/10.3390/rs11111345.

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Satellite precipitation estimates (SPE) provide useful input for hydrological modeling. However, hydrological modeling is frequently hindered by large bias and errors in SPE, inducing the necessity for bias corrections. Traditional distribution mapping bias correction of daily precipitation commonly uses Bernoulli and gamma distributions to separately model the probability and intensities of precipitation and is insufficient towards extremes. This study developed an improved distribution mapping bias correction method, which established a censored shifted mixture distribution (CSMD) as a trans

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12

Sperna Weiland, F. C., L. P. H. van Beek, J. C. J. Kwadijk, and M. F. P. Bierkens. "The ability of a GCM-forced hydrological model to reproduce global discharge variability." Hydrology and Earth System Sciences Discussions 7, no. 1 (2010): 687–724. http://dx.doi.org/10.5194/hessd-7-687-2010.

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Abstract. Data from General Circulation Models (GCMs) are often used in studies investigating hydrological impacts of climate change. However GCM data are known to have large biases, especially for precipitation. In this study the usefulness of GCM data for hydrological studies was tested by applying bias-corrected daily climate data of the 20CM3 control experiment from an ensemble of twelve GCMs as input to the global hydrological model PCR-GLOBWB. Results are compared with discharges calculated from a model run based on a reference meteorological dataset constructed from the CRU TS2.1 data a

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Keppenne, C. L., M. M. Rienecker, N. P. Kurkowski, and D. A. Adamec. "Ensemble Kalman filter assimilation of temperature and altimeter data with bias correction and application to seasonal prediction." Nonlinear Processes in Geophysics 12, no. 4 (2005): 491–503. http://dx.doi.org/10.5194/npg-12-491-2005.

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Abstract. To compensate for a poorly known geoid, satellite altimeter data is usually analyzed in terms of anomalies from the time mean record. When such anomalies are assimilated into an ocean model, the bias between the climatologies of the model and data is problematic. An ensemble Kalman filter (EnKF) is modified to account for the presence of a forecast-model bias and applied to the assimilation of TOPEX/Poseidon (T/P) altimeter data. The online bias correction (OBC) algorithm uses the same ensemble of model state vectors to estimate biased-error and unbiased-error covariance matrices. Co

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Beaumet, Julien, Michel Déqué, Gerhard Krinner, Cécile Agosta, Antoinette Alias, and Vincent Favier. "Significant additional Antarctic warming in atmospheric bias-corrected ARPEGE projections with respect to control run." Cryosphere 15, no. 8 (2021): 3615–35. http://dx.doi.org/10.5194/tc-15-3615-2021.

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Abstract. In this study, we use run-time bias correction to correct for the Action de Recherche Petite Echelle Grande Echelle (ARPEGE) atmospheric model systematic errors on large-scale atmospheric circulation. The bias-correction terms are built using the climatological mean of the adjustment terms on tendency errors in an ARPEGE simulation relaxed towards ERA-Interim reanalyses. The bias reduction with respect to the Atmospheric Model Intercomparison Project (AMIP)-style uncorrected control run for the general atmospheric circulation in the Southern Hemisphere is significant for mean state a

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15

Tornago, Marta. "Operating a PbWO₄ EM calorimeter in a harsh radiation environment." EPJ Web of Conferences 320 (2025): 00003. https://doi.org/10.1051/epjconf/202532000003.

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The CMS Electromagnetic Calorimeter (ECAL) is the largest homogeneous calorimeter operating in a high energy physics experiment. During the course of the LHC Run 1, Run 2, and Run 3, ECAL has made essential contributions to the CMS physics program by precisely measuring the energy, position, and time of arrival of photons and electrons, and of hadronic jets. Among the masterpieces of physics results achieved with its excellent energy resolution is the observation of the Higgs boson in its two photon decay in 2012, and the precise measurement of its properties. Operating a lead-tungstate scinti

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Michel, Adrien, Johannes Aschauer, Tobias Jonas, Stefanie Gubler, Sven Kotlarski, and Christoph Marty. "SnowQM 1.0: a fast R package for bias-correcting spatial fields of snow water equivalent using quantile mapping." Geoscientific Model Development 17, no. 24 (2024): 8969–88. https://doi.org/10.5194/gmd-17-8969-2024.

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Abstract. Snow plays a crucial role in regional climate systems worldwide. It is a key variable in the context of climate change because of its direct feedback to the climate system, while at the same time being very sensitive to climate change. Long-term spatial data on snow cover and snow water equivalent are scarce, due to the lack of satellite data or forcing data to run land surface models back in time. This study presents an R package, SnowQM, designed to correct for the bias in long-term spatial snow water equivalent data compared to a shorter-term and more accurate dataset, using the m

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17

Balmaseda, Magdalena A., Arthur Vidard, and David L. T. Anderson. "The ECMWF Ocean Analysis System: ORA-S3." Monthly Weather Review 136, no. 8 (2008): 3018–34. http://dx.doi.org/10.1175/2008mwr2433.1.

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Abstract A new operational ocean analysis/reanalysis system (ORA-S3) has been implemented at ECMWF. The reanalysis, started from 1 January 1959, is continuously maintained up to 11 days behind real time and is used to initialize seasonal forecasts as well as to provide a historical representation of the ocean for climate studies. It has several innovative features, including an online bias-correction algorithm, the assimilation of salinity data on temperature surfaces, and the assimilation of altimeter-derived sea level anomalies and global sea level trends. It is designed to reduce spurious c

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Leeuwenburgh, Olwijn. "Validation of an EnKF System for OGCM Initialization Assimilating Temperature, Salinity, and Surface Height Measurements." Monthly Weather Review 135, no. 1 (2007): 125–39. http://dx.doi.org/10.1175/mwr3272.1.

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Abstract Results are presented from a decade-long assimilation run with a 64-member OGCM ensemble in a global configuration. The assimilation system can be used to produce ocean initial conditions for seasonal forecasts. The ensemble is constructed with the Max Planck Institute Ocean Model, where each member is forced by differently perturbed 40-yr European Centre for Medium-Range Weather Forecasts Re-Analysis atmospheric fields over sequential 10-day intervals. Along-track altimetric data from the European Remote Sensing and the Ocean Topography Experiment (TOPEX)/Poseidon satellites, as well

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Saravanan, P., A. R. Prethivirajan, A. S. Sivaprasanna, K. Udhayakumar, and C. Sivapragasam. "Performance Evaluation of an ANN based Bias Correction algorithm in Monthly and Daily Precipitation Time Series of La Farge Station, USA." Disaster Advances 16, no. 4 (2023): 27–33. http://dx.doi.org/10.25303/1604da027033.

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Understanding the change of future precipitation over long run is highly necessary in climate change impact studies. Mostly, simulated future precipitation series are found to be biased more with the historically observed precipitation series which need to be corrected before use for any impact studies. Many conventional and data-driven methods are available to correct this bias. In this study, to bias correct the monthly and daily precipitation series, Artificial Neural Network based method is applied and compared with the conventional methods. The normalized root mean squared errors obtained

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20

Martinaitis, Steven M., Heather M. Grams, Carrie Langston, Jian Zhang, and Kenneth Howard. "A Real-Time Evaporation Correction Scheme for Radar-Derived Mosaicked Precipitation Estimations." Journal of Hydrometeorology 19, no. 1 (2018): 87–111. http://dx.doi.org/10.1175/jhm-d-17-0093.1.

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Abstract Precipitation values estimated by radar are assumed to be the amount of precipitation that occurred at the surface, yet this notion is inaccurate. Numerous atmospheric and microphysical processes can alter the precipitation rate between the radar beam elevation and the surface. One such process is evaporation. This study determines the applicability of integrating an evaporation correction scheme for real-time radar-derived mosaicked precipitation rates to reduce quantitative precipitation estimate (QPE) overestimation and to reduce the coverage of false surface precipitation. An evap

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Aryastana, Putu, Cokorda Agung Yujana, Kadek Windy Candrayana, and Krisna Himawan Subiyanto. "Analisis statistik kinerja dan koreksi kesalahan data curah hujan berbasis satelit di Provinsi Bali." Majalah Geografi Indonesia 39, no. 1 (2025): 61. https://doi.org/10.22146/mgi.99971.

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Abstrak.Data curah hujan yang akurat, reliabel, dan mendekati waktu nyata adalah faktor penting dalam analisis peramalan dan mitigasi bencara alam hidro klimatologi (banjir, tanah longsor, topan, dan curah hujan ekstrim), pemodelan hidrologi, prakiraan cuaca, perencanaan pertanian, manajemen ekologi, dan manajemen sumber daya air. Observasi curah hujan stasiun menghadapi kendala di Provinsi Bali, terutama pengukuran jarang ditemui di daerah terpencil dan pegunungan. Oleh karena itu, perlu mencari sumber data hujan yang dapat diandalkan seperti produk hujan berbasis satelit, yang menyediakan da

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22

Kumar, Dipankar, and Satoshi Takewaka. "Automatic Shoreline Position and Intertidal Foreshore Slope Detection from X-Band Radar Images using Modified Temporal Waterline Method with Corrected Wave Run-up." Journal of Marine Science and Engineering 7, no. 2 (2019): 45. http://dx.doi.org/10.3390/jmse7020045.

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Automatic and accurate shoreline position and intertidal foreshore slope detection are challenging and significantly important for coastal dynamics. In the present study, a time series shoreline position and intertidal foreshore slope have been automatically detected using modified Temporal Waterline Method (mTWM) from time-averaged X-band radar images captured throughout the course of two-week tidal cycle variation over an area spanning 5.6 km on the Hasaki coast between 12 April 2005 and 31 December 2008. The methodology is based on the correlation map between the pixel intensity variation o

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Tsaurai, Kunofiwa. "Personal remittances, banking sector development and economic growth in Israel: A trivariate causality test." Corporate Ownership and Control 13, no. 1 (2015): 1014–27. http://dx.doi.org/10.22495/cocv13i1c9p5.

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The current study investigates the causal relationship between personal remittances and economic growth using Israel time series data from 1975 to 2011. In a bid to contain the omission-of-variable bias not addressed in many past studies on this topic, this study included banking sector development as a third variable in the relationship between personal remittances and economic growth to create a tri-variate causality framework. Personal remittances as a ratio of GDP, domestic credit to private sector by banks as a ratio of GDP and GDP per capita were used as proxies for personal remittances,

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van der A, R. J., M. A. F. Allaart, and H. J. Eskes. "Multi sensor reanalysis of total ozone." Atmospheric Chemistry and Physics Discussions 10, no. 4 (2010): 11401–48. http://dx.doi.org/10.5194/acpd-10-11401-2010.

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Abstract. A single coherent total ozone dataset, called the Multi Sensor Reanalysis (MSR), has been created from all available ozone column data measured by polar orbiting satellites in the near-ultraviolet Huggins band in the last thirty years. Fourteen total ozone satellite retrieval datasets from the instruments TOMS (on the satellites Nimbus-7 and Earth Probe), SBUV (Nimbus-7, NOAA-9, NOAA-11 and NOAA-16), GOME (ERS-2), SCIAMACHY (Envisat), OMI (EOS-Aura), and GOME-2 (Metop-A) have been used in the MSR. As first step a bias correction scheme is applied to all satellite observations, based

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van der A, R. J., M. A. F. Allaart, and H. J. Eskes. "Multi sensor reanalysis of total ozone." Atmospheric Chemistry and Physics 10, no. 22 (2010): 11277–94. http://dx.doi.org/10.5194/acp-10-11277-2010.

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Abstract. A single coherent total ozone dataset, called the Multi Sensor Reanalysis (MSR), has been created from all available ozone column data measured by polar orbiting satellites in the near-ultraviolet Huggins band in the last thirty years. Fourteen total ozone satellite retrieval datasets from the instruments TOMS (on the satellites Nimbus-7 and Earth Probe), SBUV (Nimbus-7, NOAA-9, NOAA-11 and NOAA-16), GOME (ERS-2), SCIAMACHY (Envisat), OMI (EOS-Aura), and GOME-2 (Metop-A) have been used in the MSR. As first step a bias correction scheme is applied to all satellite observations, based

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Aryastana, Putu, Cokorda Agung Yujana, and Kadek Windy Candrayana. "A comparative analysis of rainfall data from IMERG early run and ground-based rain gauges on Bali Island." IOP Conference Series: Earth and Environmental Science 1416, no. 1 (2024): 012035. https://doi.org/10.1088/1755-1315/1416/1/012035.

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Abstract Ground-based precipitation measurements encounter challenges in various parts of Bali due to the limited number of gauge stations. Therefore, it is essential to identify dependable alternatives like satellite-derived precipitation data, which offer continuous precipitation time series with high spatial resolution. This study assessed the effectiveness of near real-time global satellite precipitation products, specifically the Integrated Multi-satellite Retrievals for Global Precipitation Measurement-Early Run (IMERG-E) compared to gauge data from 43 stations across Bali Province. To e

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Yakubu, Ibrahim Nandom, Aziza Hashi Abokor, and Iklim Gedik Balay. "Re-examining the impact of financial intermediation on economic growth: evidence from Turkey." Journal of Economics and Development 23, no. 2 (2021): 116–27. http://dx.doi.org/10.1108/jed-09-2020-0139.

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PurposeThis study seeks to investigate the impact of financial intermediation on economic growth in Turkey using annual data spanning 1970–2017.Design/methodology/approachBased on the results of the augmented Dickey–Fuller and Phillips–Perron unit root tests for stationarity, the authors employ the Autoregressive Distributed Lag (ARDL) bounds testing to cointegration to establish the long-run impact of financial intermediation alongside other control factors on economic growth. The study also examines the short-run relationship between financial intermediation and economic growth by estimating

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Storto, Andrea, and Simona Masina. "C-GLORSv5: an improved multipurpose global ocean eddy-permitting physical reanalysis." Earth System Science Data 8, no. 2 (2016): 679–96. http://dx.doi.org/10.5194/essd-8-679-2016.

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Abstract. Global ocean reanalyses combine in situ and satellite ocean observations with a general circulation ocean model to estimate the time-evolving state of the ocean, and they represent a valuable tool for a variety of applications, ranging from climate monitoring and process studies to downstream applications, initialization of long-range forecasts and regional studies. The purpose of this paper is to document the recent upgrade of C-GLORS (version 5), the latest ocean reanalysis produced at the Centro Euro-Mediterraneo per i Cambiamenti Climatici (CMCC) that covers the meteorological sa

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Ishaq, Maryam, Ghulam Ghouse, and Muhammad Ishaq Bhatti. "Another Prospective on Real Exchange Rate and the Traded Goods Prices: Revisiting Balassa–Samuelson Hypothesis." Sustainability 14, no. 13 (2022): 7529. http://dx.doi.org/10.3390/su14137529.

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This paper proposes a new variant and reinvestigates the validity of the Balassa–Samuelson (BS) hypothesis for nine East and South Asian countries under new specifications. The BS hypothesis is often criticized for one of its fundamental, but oversimplified assumptions related to Purchasing Power Parity (PPP) holding which can be confirmed for cronss-country tradables’ prices, implying nontraded-sector prices are solely responsible for inducing trend deviations in real exchange rate. The assumption, when empirically tested, does not always hold valid, revealing a price difference in tradables

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Emad, Anas, and Lukas Siebicke. "True eddy accumulation – Part 2: Theory and experiment of the short-time eddy accumulation method." Atmospheric Measurement Techniques 16, no. 1 (2023): 41–55. http://dx.doi.org/10.5194/amt-16-41-2023.

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Abstract. A new variant of the eddy accumulation method for measuring atmospheric exchange is derived, and a prototype sampler is evaluated. The new method, termed short-time eddy accumulation (STEA), overcomes the requirement of fixed accumulation intervals in the true eddy accumulation method (TEA) and enables the sampling system to run in a continuous flow-through mode. STEA enables adaptive time-varying accumulation intervals, which improves the system's dynamic range and brings many advantages to flux measurement and calculation. The STEA method was successfully implemented and deployed t

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Tobin, Kenneth J., and Marvin E. Bennett. "Impact of model complexity and precipitation data products on modeled streamflow." Journal of Hydroinformatics 16, no. 3 (2013): 588–99. http://dx.doi.org/10.2166/hydro.2013.056.

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With the proliferation of remote sensing platforms as well as numerous ground products based on weather radar estimation, there are now multiple options for precipitation data beyond traditional rain gauges for which most hydrologic models were originally designed. This study evaluates four precipitation products as input for generating streamflow simulations using two hydrologic models that significantly vary in complexity. The four precipitation products include two ground products from the National Weather Service: the Multi-sensor Precipitation Estimator (MPE) and rain gauge data. The two

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Bianco, Laura, Irina V. Djalalova, James M. Wilczak, et al. "Impact of model improvements on 80 m wind speeds during the second Wind Forecast Improvement Project (WFIP2)." Geoscientific Model Development 12, no. 11 (2019): 4803–21. http://dx.doi.org/10.5194/gmd-12-4803-2019.

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Abstract. During the second Wind Forecast Improvement Project (WFIP2; October 2015–March 2017, held in the Columbia River Gorge and Basin area of eastern Washington and Oregon states), several improvements to the parameterizations used in the High Resolution Rapid Refresh (HRRR – 3 km horizontal grid spacing) and the High Resolution Rapid Refresh Nest (HRRRNEST – 750 m horizontal grid spacing) numerical weather prediction (NWP) models were tested during four 6-week reforecast periods (one for each season). For these tests the models were run in control (CNT) and experimental (EXP) configuratio

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Lee, Seunghee, Ganghan Kim, Myong-In Lee, Yonghan Choi, Chang-Keun Song, and Hyeon-Kook Kim. "Seasonal Dependence of Aerosol Data Assimilation and Forecasting Using Satellite and Ground-Based Observations." Remote Sensing 14, no. 9 (2022): 2123. http://dx.doi.org/10.3390/rs14092123.

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This study examines the performance of a data assimilation and forecasting system that simultaneously assimilates satellite aerosol optical depth (AOD) and ground-based PM10 and PM2.5 observations into the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem). The data assimilation case for the surface PM10 and PM2.5 concentrations exhibits a higher consistency with the observed data by showing more correlation coefficients than the no-assimilation case. The data assimilation also shows beneficial impacts on the PM10 and PM2.5 forecasts for South Korea for up to 24 h from th

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Barron, Charlie N., A. Birol Kara, Harley E. Hurlburt, C. Rowley, and Lucy F. Smedstad. "Sea Surface Height Predictions from the Global Navy Coastal Ocean Model during 1998–2001*." Journal of Atmospheric and Oceanic Technology 21, no. 12 (2004): 1876–93. http://dx.doi.org/10.1175/jtech-1680.1.

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Abstract A ⅛° global version of the Navy Coastal Ocean Model (NCOM), operational at the Naval Oceanographic Office (NAVOCEANO), is used for prediction of sea surface height (SSH) on daily and monthly time scales during 1998–2001. Model simulations that use 3-hourly wind and thermal forcing obtained from the Navy Operational Global Atmospheric Prediction System (NOGAPS) are performed with/without data assimilation to examine indirect/direct effects of atmospheric forcing in predicting SSH. Model–data evaluations are performed using the extensive database of daily averaged SSH values from tide g

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Mooring, Todd A., Isaac M. Held, and R. John Wilson. "Effects of the Mean Flow on Martian Transient Eddy Activity: Studies with an Idealized General Circulation Model." Journal of the Atmospheric Sciences 76, no. 8 (2019): 2375–97. http://dx.doi.org/10.1175/jas-d-18-0247.1.

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Abstract The extent to which the eddy statistics of the Martian atmosphere can be inferred from the mean state and highly simplified assumptions about diabatic and frictional processes is investigated using an idealized general circulation model (GCM) with Newtonian relaxation thermal forcing. An iterative technique, adapted from previous terrestrial studies, is used to generate radiative equilibrium temperatures such that the three-dimensional time-mean temperature fields of the idealized model match means computed from the Mars Analysis Correction Data Assimilation (MACDA). Focusing on a per

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Sureshbabu, Mohana Devi, and Veeramani Bagyaveereswaran. "Advanced Battery Management for Lithium-Ion EVs: Integrating Extended Kalman Filter and Modified Multi-Layer Perceptron for Enhanced State Monitoring." World Electric Vehicle Journal 16, no. 4 (2025): 234. https://doi.org/10.3390/wevj16040234.

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An efficient Battery Management System (BMS) specifically for Electric Vehicles is crucial for improving battery run time performance. A primary function of an effective BMS is accurately determining the State of Charge (SOC) and State of Health (SOH) of lithium-ion batteries in Electric Vehicles (EVs). However, many existing studies have concentrated on examining sensor malfunctions in batteries to avert problems such as overcharging and overheating and are lacking in terms of effective handling of non-linear behaviors. To overcome these limitations, the proposed work introduces a hybrid appr

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Marçal, Emerson Fernandes, and Eli Hadad Junior. "Is It Possible to Beat the Random Walk Model in Exchange Rate Forecasting? More Evidence for Brazilian Case." Brazilian Review of Finance 14, no. 1 (2016): 65. http://dx.doi.org/10.12660/rbfin.v14n1.2016.59329.

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Abstract The seminal study of Meese et al. (1983) on exchange rate forecastability had a great impact on the international finance literature. The authors showed that exchange rate forecasts based on structural models are worse than a naive random walk. This result is known as the Meese--Rogoff (MR) puzzle. Although the validity of this result has been checked for many currencies, studies for the Brazilian currency are not common. In 1999, Brazil adopted the dirty floating exchange rate regime. Rossi (2013) ran an extensive study on the MR puzzle but did not analyse Brazilian data. Our goal is

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Batté, Lauriane, and Michel Déqué. "Randomly correcting model errors in the ARPEGE-Climate v6.1 component of CNRM-CM: applications for seasonal forecasts." Geoscientific Model Development 9, no. 6 (2016): 2055–76. http://dx.doi.org/10.5194/gmd-9-2055-2016.

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Abstract. Stochastic methods are increasingly used in global coupled model climate forecasting systems to account for model uncertainties. In this paper, we describe in more detail the stochastic dynamics technique introduced by Batté and Déqué (2012) in the ARPEGE-Climate atmospheric model. We present new results with an updated version of CNRM-CM using ARPEGE-Climate v6.1, and show that the technique can be used both as a means of analyzing model error statistics and accounting for model inadequacies in a seasonal forecasting framework.The perturbations are designed as corrections of model d

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Cheevaprasert, Sirikanya, Rajeshwar Mehrotra, Sansarith Thianpopirug, and Nutchanart Sriwongsitanon. "An Evaluation of Statistical Downscaling Techniques for Simulating Daily Rainfall Occurrences in the Upper Ping River Basin." Hydrology 7, no. 3 (2020): 63. http://dx.doi.org/10.3390/hydrology7030063.

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This study presents an exhaustive evaluation of the performance of three statistical downscaling techniques for generating daily rainfall occurrences at 22 rainfall stations in the upper Ping river basin (UPRB), Thailand. The three downscaling techniques considered are the modified Markov model (MMM), a stochastic model, and two variants of regression models, statistical models, one with single relationship for all days of the year (RegressionYrly) and the other with individual relationships for each of the 366 days (Regression366). A stepwise regression is applied to identify the significant

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Eldering, Annmarie, Thomas E. Taylor, Christopher W. O'Dell, and Ryan Pavlick. "The OCO-3 mission: measurement objectives and expected performance based on 1 year of simulated data." Atmospheric Measurement Techniques 12, no. 4 (2019): 2341–70. http://dx.doi.org/10.5194/amt-12-2341-2019.

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Abstract. The Orbiting Carbon Observatory-3 (OCO-3) is NASA's next instrument dedicated to extending the record of the dry-air mole fraction of column carbon dioxide (XCO2) and solar-induced fluorescence (SIF) measurements from space. The current schedule calls for a launch from the Kennedy Space Center no earlier than April 2019 via a Space-X Falcon 9 and Dragon capsule. The instrument will be installed as an external payload on the Japanese Experimental Module Exposed Facility (JEM-EF) of the International Space Station (ISS) with a nominal mission lifetime of 3 years. The precessing orbit o

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Fouotsa Manfouo, Noé Carème, Linke Potgieter, Andrew Watson, and Johanna H. Nel. "A Comparison of the Statistical Downscaling and Long-Short-Term-Memory Artificial Neural Network Models for Long-Term Temperature and Precipitations Forecasting." Atmosphere 14, no. 4 (2023): 708. http://dx.doi.org/10.3390/atmos14040708.

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General circulation models (GCMs) run at regional resolution or at a continental scale. Therefore, these results cannot be used directly for local temperatures and precipitation prediction. Downscaling techniques are required to calibrate GCMs. Statistical downscaling models (SDSM) are the most widely used for bias correction of GCMs. However, few studies have compared SDSM with multi-layer perceptron artificial neural networks and in most of these studies, results indicate that SDSM outperform other approaches. This paper investigates an alternative architecture of neural networks, namely the

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Kinnard, Christophe, Olivier Larouche, Michael N. Demuth, and Brian Menounos. "Modelling glacier mass balance and climate sensitivity in the context of sparse observations: application to Saskatchewan Glacier, western Canada." Cryosphere 16, no. 8 (2022): 3071–99. http://dx.doi.org/10.5194/tc-16-3071-2022.

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Abstract. Glacier mass balance models are needed at sites with scarce long-term observations to reconstruct past glacier mass balance and assess its sensitivity to future climate change. In this study, North American Regional Reanalysis (NARR) data were used to force a physically based, distributed glacier mass balance model of Saskatchewan Glacier for the historical period 1979–2016 and assess its sensitivity to climate change. A 2-year record (2014–2016) from an on-glacier automatic weather station (AWS) and historical precipitation records from nearby permanent weather stations were used to

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Brocca, Luca, Paolo Filippucci, Sebastian Hahn, et al. "SM2RAIN–ASCAT (2007–2018): global daily satellite rainfall data from ASCAT soil moisture observations." Earth System Science Data 11, no. 4 (2019): 1583–601. http://dx.doi.org/10.5194/essd-11-1583-2019.

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Abstract. Long-term gridded precipitation products are crucial for several applications in hydrology, agriculture and climate sciences. Currently available precipitation products suffer from space and time inconsistency due to the non-uniform density of ground networks and the difficulties in merging multiple satellite sensors. The recent “bottom-up” approach that exploits satellite soil moisture observations for estimating rainfall through the SM2RAIN (Soil Moisture to Rain) algorithm is suited to build a consistent rainfall data record as a single polar orbiting satellite sensor is used. Her

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Landgraf, Steven, and Abdur Chowdhury. "Factoring emerging markets into the relationship between global liquidity and commodities." Journal of Economic Studies 42, no. 4 (2015): 622–40. http://dx.doi.org/10.1108/jes-11-2013-0171.

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Purpose – What caused the mid-2000s world commodity price “bubble” and the recent commodity price growth? Some have suggested that rapid global industrial growth over the past decade is the key driver of price growth. Others have argued that high commodity prices are a result of excessively loose monetary policy. The purpose of this paper is to extend the current research in this area by incorporating emerging economies, the BRIC (Brazil, Russia, India, and China) nations specifically, into global measures. Design/methodology/approach – The paper uses a vector error correction (VEC) model and

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Qin, Jieye, Christopher J. Green, and Kavita Sirichand. "Spot–Futures Price Adjustments in the Nikkei 225: Linear or Smooth Transition? Financial Centre Leadership or Home Bias?" Journal of Risk and Financial Management 16, no. 2 (2023): 117. http://dx.doi.org/10.3390/jrfm16020117.

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This paper studies price discovery in Nikkei 225 markets through the nonlinear smooth transition price adjustments between spot and future prices and across all three futures markets. We test for smooth transition nonlinearity and employ an exponential smooth transition error correction model (ESTECM) with exponential generalised autoregressive conditional heteroscedasticity (EGARCH), allowing for the effects of transaction costs, heterogeneity, and asymmetry in Nikkei price adjustments. We show that the ESTECM-EGARCH is the appropriate model as it offers new insights into Nikkei price dynamic

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Balhane, Saloua, Frédérique Cheruy, Fatima Driouech, et al. "Towards an advanced representation of precipitation over Morocco in a global climate model with resolution enhancement and empirical run‐time bias corrections." International Journal of Climatology, February 26, 2024. http://dx.doi.org/10.1002/joc.8405.

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AbstractMorocco, as a Mediterranean and North African country, is acknowledged as a climate change hotspot, where increased drought and related water resource shortages present a real challenge for human and natural systems. However, its geographic position and regional characteristics make the simulation of the distribution and variability of precipitation particularly challenging in the region. In this study, we propose an approach where the Laboratoire de Météorologie Dynamique Zoom (LMDZ) GCM is run with a stretched grid configuration developed with enhanced resolution (35 km) over the reg

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Tiwari, Amar Deep, Parthasarathi Mukhopadhyay, and Vimal Mishra. "Influence of bias correction of meteorological and streamflow forecast on hydrological prediction in India." Journal of Hydrometeorology, January 25, 2021. http://dx.doi.org/10.1175/jhm-d-20-0235.1.

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AbstractThe efforts to develop a hydrologic model-based operational streamflow forecast in India are limited. We evaluate the role of bias correction of meteorological forecast and streamflow post-processing on hydrological prediction skill in India. We use the Variable Infiltration Capacity (VIC) model to simulate runoff and root zone soil moisture in the Narmada basin (drainage area: 97,410 km2), which was used as a testbed to examine the forecast skill along with the observed streamflow. We evaluated meteorological and hydrological forecasts during the monsoon (June-September) season for 20

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Krinner, Gerhard, Viatcheslav Kharin, Romain Roehrig, John Scinocca, and Francis Codron. "Historically-based run-time bias corrections substantially improve model projections of 100 years of future climate change." Communications Earth & Environment 1, no. 1 (2020). http://dx.doi.org/10.1038/s43247-020-00035-0.

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Abstract Climate models and/or their output are usually bias-corrected for climate impact studies. The underlying assumption of these corrections is that climate biases are essentially stationary between historical and future climate states. Under very strong climate change, the validity of this assumption is uncertain, so the practical benefit of bias corrections remains an open question. Here, this issue is addressed in the context of bias correcting the climate models themselves. Employing the ARPEGE, LMDZ and CanAM4 atmospheric models, we undertook experiments in which one centre’s atmosph

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Goldberg, Andrew, Isabella Rosario, Jonathan Power, Guillermo Horga, and Kenneth Wengler. "Strategies for motion- and respiration-robust estimation of fMRI intrinsic neural timescales." Imaging Neuroscience, 2024. http://dx.doi.org/10.1162/imag_a_00326.

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Abstract Intrinsic neural timescales (INT) reflect the time window of neural integration within a brain region and can be measured via resting-state fMRI (rs-fMRI). Despite the potential relevance of INT to cognition, brain organization, and neuropsychiatric illness, the influences of physiological artifacts on rs-fMRI INT have not been systematically considered. Two artifacts, head motion and respiration, pose serious issues in rs-fMRI studies. Here, we described their impact on INT estimation and tested the ability of two denoising strategies for mitigating these artifacts, high-motion frame

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Wade, Madeline, Aaron Daniel Viets, Theresa Chmiel, Madeline Stover та Leslie Wade. "Improving LIGO calibration accuracy by using time-dependent ﬁlters to compensate for temporal variations". Classical and Quantum Gravity, 15 грудня 2022. http://dx.doi.org/10.1088/1361-6382/acabf6.

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Abstract The response of the Advanced LIGO interferometers is known to vary with time [1]. Accurate calibration of the interferometers must therefore track and compensate for temporal variations in calibration model parameters. These variations were tracked during the first three Advanced LIGO observing runs, and compensation for some of them has been implemented in the calibration procedure. During the second observing run, multiplicative corrections to the interferometer response were applied while producing calibrated strain data both in real time and in high latency. In a high-latency cali

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