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1

McFarlane, Sally A., and K. Franklin Evans. "Clouds and Shortwave Fluxes at Nauru. Part II: Shortwave Flux Closure." Journal of the Atmospheric Sciences 61, no. 21 (November 1, 2004): 2602–15. http://dx.doi.org/10.1175/jas3299.1.

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Abstract The datasets currently being collected by the Atmospheric Radiation Measurement (ARM) program on the islands of Nauru and Manus represent the longest time series of ground-based cloud measurements in the tropical western Pacific region. In this series of papers, a shortwave flux closure study is presented using observations collected at the Nauru site between June 1999 and May 2000. The first paper presented frequency of occurrence of nonprecipitating clouds detected by the millimeter-wavelength cloud radar (MMCR) at Nauru and statistics of their retrieved microphysical properties. This paper presents estimates of the cloud radiative effect over the study period and results from a closure study in which retrieved cloud properties are input to a radiative transfer model and the modeled surface fluxes are compared to observations. The average surface shortwave cloud radiative forcing is 48.2 W m−2, which is significantly smaller than the cloud radiative forcing estimates found during the Tropical Ocean Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE) field project. The difference in the estimates during the two periods is due to the variability in cloud amount over Nauru during different phases of the El Niño–Southern Oscillation (ENSO). In the closure study, modeled and observed surface fluxes show large differences at short time scales, due to the temporal and spatial variability of the clouds observed at Nauru. Averaging over 60 min reduces the average root-mean-square difference in total flux to 10% of the observed flux. Modeled total downwelling fluxes are unbiased with respect to the observed fluxes while direct fluxes are underestimated and diffuse fluxes are overestimated. Examination of the differences indicates that cloud amount derived from the ground-based measurements is an overestimate of the radiatively important cloud amount due to the anisotropy of the cloud field at Nauru, interpolation of the radar data, uncertainty in the microwave brightness temperature measurements for thin clouds, and the uncertainty in relating the sixth moment of the droplet size distribution observed by the radar to the more radiatively important moments.
2

Ma, Yingtao, Rachel T. Pinker, Margaret M. Wonsick, Chuan Li, and Laura M. Hinkelman. "Shortwave Radiative Fluxes on Slopes." Journal of Applied Meteorology and Climatology 55, no. 7 (July 2016): 1513–32. http://dx.doi.org/10.1175/jamc-d-15-0178.1.

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AbstractSnow-covered mountain ranges are a major source of water supply for runoff and groundwater recharge. Snowmelt supplies as much as 75% of the surface water in basins of the western United States. Net radiative fluxes make up about 80% of the energy balance over snow-covered surfaces. Because of the large extent of snow cover and the scarcity of ground observations, use of remotely sensed data is an attractive option for estimating radiative fluxes. Most of the available methods have been applied to low-spatial-resolution satellite observations that do not capture the spatial variability of snow cover, clouds, or aerosols, all of which need to be accounted for to achieve accurate estimates of surface radiative fluxes. The objective of this study is to use high-spatial-resolution observations that are available from the Moderate Resolution Imaging Spectroradiometer (MODIS) to derive surface shortwave (0.2–4.0 μm) downward radiative fluxes in complex terrain, with attention on the effect of topography (e.g., shadowing or limited sky view) on the amount of radiation received. The developed method has been applied to several typical melt seasons (January–July during 2003, 2004, 2005, and 2009) over the western part of the United States, and the available information was used to derive metrics on spatial and temporal variability of shortwave fluxes. Issues of scale in both the satellite and ground observations are also addressed to illuminate difficulties in the validation process of satellite-derived quantities. It is planned to apply the findings from this study to test improvements in estimation of snow water equivalent.
3

Rodriguez-Puebla, C., R. T. Pinker, and S. Nigam. "Relationship between downwelling surface shortwave radiative fluxes and sea surface temperature over the tropical Pacific: AMIP II models versus satellite estimates." Annales Geophysicae 26, no. 4 (May 13, 2008): 785–94. http://dx.doi.org/10.5194/angeo-26-785-2008.

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Abstract. Incident shortwave radiation at the Earth's surface is the driving force of the climate system. Understanding the relationship between this forcing and the sea surface temperature, in particular, over the tropical Pacific Ocean is a topic of great interest because of possible climatic implications. The objective of this study is to investigate the relationship between downwelling shortwave radiative fluxes and sea surface temperature by using available data on radiative fluxes. We assess first the shortwave radiation from three General Circulation Models that participated in the second phase of the Atmospheric Model Intercomparison Project (AMIP II) against estimates of such fluxes from satellites. The shortwave radiation estimated from the satellite is based on observations from the International Satellite Cloud Climatology Project D1 data and the University of Maryland Shortwave Radiation Budget model (UMD/SRB). Model and satellite estimates of surface radiative fluxes are found to be in best agreement in the central equatorial Pacific, according to mean climatology and spatial correlations. We apply a Canonical Correlation Analysis to determine the interrelated areas where shortwave fluxes and sea surface temperature are most sensitive to climate forcing. Model simulations and satellite estimates of shortwave fluxes both capture well the interannual signal of El Niño-like variability. The tendency for an increase in shortwave radiation from the UMD/SRB model is not captured by the AMIP II models.
4

Scott, James D., and Michael A. Alexander. "Net Shortwave Fluxes over the Ocean." Journal of Physical Oceanography 29, no. 12 (December 1999): 3167–74. http://dx.doi.org/10.1175/1520-0485(1999)029<3167:nsfoto>2.0.co;2.

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5

Ma, Y., and R. T. Pinker. "Modeling shortwave radiative fluxes from satellites." Journal of Geophysical Research: Atmospheres 117, no. D23 (December 4, 2012): n/a. http://dx.doi.org/10.1029/2012jd018332.

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6

Wilber, Anne C., G. Louis Smith, Shashi K. Gupta, and Paul W. Stackhouse. "Annual Cycles of Surface Shortwave Radiative Fluxes." Journal of Climate 19, no. 4 (February 15, 2006): 535–47. http://dx.doi.org/10.1175/jcli3625.1.

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Abstract The annual cycles of surface shortwave flux are investigated using the 8-yr dataset of the surface radiation budget (SRB) components for the period July 1983–June 1991. These components include the downward, upward, and net shortwave radiant fluxes at the earth's surface. The seasonal cycles are quantified in terms of principal components that describe the temporal variations and empirical orthogonal functions (EOFs) that describe the spatial patterns. The major part of the variation is simply due to the variation of the insolation at the top of the atmosphere, especially for the first term, which describes 92.4% of the variance for the downward shortwave flux. However, for the second term, which describes 4.1% of the variance, the effect of clouds is quite important and the effect of clouds dominates the third term, which describes 2.4% of the variance. To a large degree the second and third terms are due to the response of clouds to the annual cycle of solar forcing. For net shortwave flux at the surface, similar variances are described by each term. The regional values of the EOFs are related to climate classes, thereby defining the range of annual cycles of shortwave radiation for each climate class.
7

Winton, Michael. "Simple Optical Models for Diagnosing Surface–Atmosphere Shortwave Interactions." Journal of Climate 18, no. 18 (September 15, 2005): 3796–805. http://dx.doi.org/10.1175/jcli3502.1.

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Abstract A technique is developed for diagnosing effective surface and atmospheric optical properties from climate model shortwave flux diagnostics. These properties can be used to distinguish the contributions of surface and atmospheric optical property changes to shortwave flux changes at the surface and top of the atmosphere. In addition to the four standard shortwave flux diagnostics (upward, downward, surface, and top of atmosphere), the technique makes use of surface-down and top-up fluxes over a zero-albedo surface obtained from an auxiliary online shortwave calculation. The simple model optical properties, when constructed from the time-mean fluxes, are effective optical properties, useful for predicting the time-mean response to optical property changes. The technique is tested against auxiliary online shortwave calculations at four validation albedos and shown to predict the monthly mean surface absorption with an rms error of less than 2% over the globe. The reasons for the accuracy of the technique are explored. Less accurate techniques that make use of existing shortwave diagnostics are presented and compared.
8

Sai Krishna, S. V. S., P. Manavalan, and P. V. N. Rao. "Estimation of Net Radiation using satellite based data inputs." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-8 (November 28, 2014): 307–13. http://dx.doi.org/10.5194/isprsarchives-xl-8-307-2014.

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Daily net surface radiation fluxes are estimated for Indian land mass at spatial grid intervals of 0.1 degree. Two approaches are employed to obtain daily net radiation for four sample days viz., November 19, 2013, December 16, 2013, January 8, 2014 and March 20, 2014. Both the approaches compute net shortwave and net longwave fluxes, separately and sum them up to obtain net radiation. The first approach computes net shortwave radiation using daily insolation product of Kalpana VHRR and 15 days time composited broadband albedo product of Oceansat OCM2. The net outgoing longwave radiation is computed using Stefan Boltzmann equation corrected for humidity and cloudiness. In the second approach, instantaneous clear-sky net-shortwave radiation is estimated using computed clear-sky incoming shortwave radiation and the gridded MODIS 16-day time composited albedo product. The net longwave radiation is obtained by estimating outgoing and incoming longwave radiation fluxes, independently. In this, MODIS derived surface emissivity and skin temperature parameters are used for estimating outgoing longwave radiation component. In both the approaches, surface air temperature data required for estimation of net longwave radiation fluxes are extracted from India Meteorological Department’s (IMD) Automatic Weather Station (AWS) records. Estimates by the two different approaches are evaluated by comparing daily net radiation fluxes with CERES based estimates corresponding to the sample days, through statistical measures. The estimated all sky daily net radiation using the first approach compared well with CERES SYN1deg daily average net radiation with r<sup>2</sup> values of the order of 0.7 and RMS errors of the order of 8&ndash;16 w/m<sup>2</sup>.
9

Key, Jeffrey R., Yong Liu, and Robert S. Stone. "Development and evaluation of surface shortwave flux parameterizations for use in sea-ice models." Annals of Glaciology 25 (1997): 33–37. http://dx.doi.org/10.3189/s0260305500013756.

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The surface radiation budget of the polar regions strongly influences ice growth and melt. Thermodynamic sea-ice models therefore require accurate yet computationally efficient methods of computing radiative fluxes. In this paper a new parameterization of the downwelling shortwave radiation flux at the Arctic surface is developed and compared to a variety of existing schemes. Parameterized llnxes are compared to in situ measurements using data for one year at Barrow, Alaska. Our results show that the new parameterization can estimate the downwelling shortwave flux with mean and root mean square errors of 1 and 5%, respectively, for clear conditions and 5 and 20% for cloudy conditions. The new parameterization offers a unified approach to estimating downwelling shortwave fluxes under clear and cloudy conditions, and is more accurate than existing schemes.
10

Key, Jeffrey R., Yong Liu, and Robert S. Stone. "Development and evaluation of surface shortwave flux parameterizations for use in sea-ice models." Annals of Glaciology 25 (1997): 33–37. http://dx.doi.org/10.1017/s0260305500013756.

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The surface radiation budget of the polar regions strongly influences ice growth and melt. Thermodynamic sea-ice models therefore require accurate yet computationally efficient methods of computing radiative fluxes. In this paper a new parameterization of the downwelling shortwave radiation flux at the Arctic surface is developed and compared to a variety of existing schemes. Parameterized llnxes are compared to in situ measurements using data for one year at Barrow, Alaska. Our results show that the new parameterization can estimate the downwelling shortwave flux with mean and root mean square errors of 1 and 5%, respectively, for clear conditions and 5 and 20% for cloudy conditions. The new parameterization offers a unified approach to estimating downwelling shortwave fluxes under clear and cloudy conditions, and is more accurate than existing schemes.
11

May, Jackie C., Clark Rowley, and Charlie N. Barron. "NFLUX Satellite-Based Surface Radiative Heat Fluxes. Part II: Gridded Products." Journal of Applied Meteorology and Climatology 56, no. 4 (April 2017): 1043–57. http://dx.doi.org/10.1175/jamc-d-16-0283.1.

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AbstractThe Naval Research Laboratory (NRL) ocean surface flux (NFLUX) system provides near-real-time satellite-based gridded surface heat flux fields over the global ocean within hours of the observed satellite measurements. NFLUX can serve as an alternative to current numerical weather prediction models—in particular, the U. S. Navy Global Environmental Model (NAVGEM)—that provide surface forcing fields to operational ocean models. This study discusses the satellite-based shortwave and longwave global gridded analysis fields, which complete the full suite of NFLUX-provided ocean surface heat fluxes. A companion paper discusses the production of satellite swath-level surface shortwave radiation and longwave radiation estimates. The swath-level shortwave radiation estimates are converted into clearness-index values. Clearness index reduces the dependency on solar zenith angle, which allows for the assimilation of observations over a given time window. An automated quality-control process is applied to the swath-level estimates of clearness index and surface longwave radiation. Then 2D variational analyses of the quality-controlled satellite estimates with background atmospheric model fields form global gridded radiative heat flux fields. The clearness-index analysis fields are converted into shortwave analysis fields to be used in other applications. Three-hourly shortwave and longwave analysis fields are created from 1 May 2013 through 30 April 2014. These fields are validated against observations from research vessels and moored-buoy platforms and compared with NAVGEM. With the exception of the mean bias, the NFLUX fields have smaller errors when compared with those of NAVGEM.
12

Mackie, Anna, Paul I. Palmer, and Helen Brindley. "Characterizing energy budget variability at a Sahelian site: a test of NWP model behaviour." Atmospheric Chemistry and Physics 17, no. 24 (December 21, 2017): 15095–119. http://dx.doi.org/10.5194/acp-17-15095-2017.

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Abstract. We use observations of surface and top-of-the-atmosphere (TOA) broadband radiation fluxes determined from the Atmospheric Radiation Measurement programme mobile facility, the Geostationary Earth Radiation Budget (GERB) and Spinning Enhanced Visible and Infrared Imager (SEVIRI) instruments and a range of meteorological variables at a site in the Sahel to test the ability of the ECMWF Integrated Forecasting System cycle 43r1 to describe energy budget variability. The model has daily average biases of −12 and 18 W m−2 for outgoing longwave and reflected shortwave TOA radiation fluxes, respectively. At the surface, the daily average bias is 12(13) W m−2 for the longwave downwelling (upwelling) radiation flux and −21(−13) W m−2 for the shortwave downwelling (upwelling) radiation flux. Using multivariate linear models of observation–model differences, we attribute radiation flux discrepancies to physical processes, and link surface and TOA fluxes. We find that model biases in surface radiation fluxes are mainly due to a low bias in ice water path (IWP), poor description of surface albedo and model–observation differences in surface temperature. We also attribute observed discrepancies in the radiation fluxes, particularly during the dry season, to the misrepresentation of aerosol fields in the model from use of a climatology instead of a dynamic approach. At the TOA, the low IWP impacts the amount of reflected shortwave radiation while biases in outgoing longwave radiation are additionally coupled to discrepancies in the surface upwelling longwave flux and atmospheric humidity.
13

Wang, Chunxiao, Yaoming Ma, Binbin Wang, Weiqiang Ma, Xuelong Chen, and Cunbo Han. "Analysis of the Radiation Fluxes over Complex Surfaces on the Tibetan Plateau." Water 13, no. 21 (November 3, 2021): 3084. http://dx.doi.org/10.3390/w13213084.

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Analysis of long-term, ground-based observation data on the Tibetan Plateau help to enhance our understanding of land-atmosphere interactions and their influence on weather and climate in this region. In this paper, the daily, monthly, and annual averages of radiative fluxes, surface albedo, surface temperature, and air temperature were calculated for the period of 2006 to 2019 at six research stations on the Tibetan Plateau. The surface energy balance characteristics of these six stations, which include alpine meadow, alpine desert, and alpine steppe, were then compared. The downward shortwave radiation at stations BJ, QOMS, and NAMORS was found to decrease during the study period, due to increasing cloudiness. Meanwhile, the upward shortwave radiation and surface albedo at all stations were found to have decreased overall. Downward longwave radiation, upward longwave radiation, net radiation, surface temperature, and air temperature showed increasing trends on inter-annual time scales at most stations. Downward shortwave radiation was maximum in spring at BJ, QOMS, NADORS, and NAMORS, due to the influence of the summer monsoon. Upward shortwave radiation peaked in October and November due to the greater snow cover. BJ, QOMS, NADORS, and NAMORS showed strong sensible heat fluxes in the spring while MAWORS showed strong sensible heat fluxes in the summer. The monthly and diurnal variations of surface albedo at each station were “U” shaped. The diurnal variability of downward longwave radiation at each station was small, ranging from 220 to 295 W·m−2.The diurnal variation in surface temperature at each station slightly lagged behind changes in downward shortwave radiation, and the air temperature, in turn, slightly lagged behind the surface temperature.
14

Wang, Xuanji, and Jeffrey R. Key. "Spatial variability of the sea-ice radiation budget and its effect on aggregate-area fluxes." Annals of Glaciology 33 (2001): 248–52. http://dx.doi.org/10.3189/172756401781818130.

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AbstractThe spatial and temporal variability of surface, cloud and radiative properties of sea ice are examined using new satellite-derived products. Downwelling short- and longwave fluxes exhibit temporal correlation over about 180 days, but cloud optical depth and cloud fraction show almost no correlation over time. The spatial variance of surface properties is shown to increase much less rapidly than that of cloud properties. The effect of small-scale inhomogeneity in surface and cloud properties on the calculation of radiative fluxes at ice- and climate-model gridscales is also investigated. Annual mean differences between gridcell fluxes computed from average surface and cloud properties and averages of pixel-by-pixel fluxes are 9.46% for the downwelling shortwave flux and −7.04% for the longwave flux. Therefore, using mean surface and cloud properties to compute surface radiative fluxes in a gridcell results in an overestimate of the shortwave flux and an underestimate of the longwave flux. Model sensitivity studies show that such biases may result in substantial errors in modeled ice thickness. Clearly, the sub-gridscale inhomogeneity of surface and atmospheric properties must be considered when estimating aggregate-area fluxes in sea-ice and climate models.
15

Forman, B. A., and S. A. Margulis. "High-resolution satellite-based cloud-coupled estimates of total downwelling surface radiation for hydrologic modelling applications." Hydrology and Earth System Sciences Discussions 6, no. 2 (April 3, 2009): 3041–87. http://dx.doi.org/10.5194/hessd-6-3041-2009.

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Abstract. A relatively simple satellite-based radiation model yielding high-resolution (in space and time) downwelling longwave and shortwave radiative fluxes at the Earth's surface is presented. The primary aim of the approach is to provide a basis for deriving physically consistent forcing fields for distributed hydrologic models using satellite-based remote sensing data. The physically-based downwelling radiation model utilises satellite inputs from both geostationary and polar-orbiting platforms and requires only satellite-based inputs except that of a climatological lookup table derived from a regional climate model. Comparison against ground-based measurements over a 14-month simulation period in the Southern Great Plains of the United States demonstrates the ability to reproduce radiative fluxes at 4 km/h resolution with good accuracy during all-sky conditions. For hourly fluxes, a mean difference of −2 W m−2 with a root mean square difference of 21 W m−2 was found for the longwave fluxes whereas a mean difference of −7 W m−2 with a root mean square difference of 29 W m−2 was found for the shortwave fluxes. Additionally, comparison against advanced downwelling longwave and solar insolation products during all-sky conditions showed comparable uncertainty in the longwave estimates and reduced uncertainty in the shortwave estimates. The relatively simple form of the model enables future usage in ensemble-based applications including data assimilation frameworks in order to explicitly account for input uncertainties while providing the potential for conditioning estimates from other readily available products derived from more sophisticated retrieval algorithms.
16

Forman, B. A., and S. A. Margulis. "High-resolution satellite-based cloud-coupled estimates of total downwelling surface radiation for hydrologic modelling applications." Hydrology and Earth System Sciences 13, no. 7 (July 7, 2009): 969–86. http://dx.doi.org/10.5194/hess-13-969-2009.

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Abstract. A relatively simple satellite-based radiation model yielding high-resolution (in space and time) downwelling longwave and shortwave radiative fluxes at the Earth's surface is presented. The primary aim of the approach is to provide a basis for deriving physically consistent forcing fields for distributed hydrologic models using satellite-based remote sensing data. The physically-based downwelling radiation model utilises satellite inputs from both geostationary and polar-orbiting platforms and requires only satellite-based inputs except that of a climatological lookup table derived from a regional climate model. Comparison against ground-based measurements over a 14-month simulation period in the Southern Great Plains of the United States demonstrates the ability to reproduce radiative fluxes at a spatial resolution of 4 km and a temporal resolution of 1 h with good accuracy during all-sky conditions. For hourly fluxes, a mean difference of −2 W m−2 with a root mean square difference of 21 W m−2 was found for the longwave fluxes whereas a mean difference of −7 W m−2 with a root mean square difference of 29 W m−2 was found for the shortwave fluxes. Additionally, comparison against advanced downwelling longwave and solar insolation products during all-sky conditions showed comparable uncertainty in the longwave estimates and reduced uncertainty in the shortwave estimates. The relatively simple form of the model enables future usage in ensemble-based applications including data assimilation frameworks in order to explicitly account for input uncertainties while providing the potential for conditioning estimates from other readily available products derived from more sophisticated retrieval algorithms.
17

de Boer, G., W. D. Collins, S. Menon, and C. N. Long. "Using surface remote sensors to derive mixed-phase cloud radiative forcing: an example from M-PACE." Atmospheric Chemistry and Physics Discussions 11, no. 4 (April 20, 2011): 12487–518. http://dx.doi.org/10.5194/acpd-11-12487-2011.

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Abstract. A suite of ground-based measurements are used in conjunction with a column version of the Rapid Radiative Transfer Model (RRTMG) to derive the cloud radiative forcing of mixed-phase stratiform clouds observed during the United States Department of Energy (US DOE) Atmospheric Radiation Measurement (ARM) Mixed-Phase Arctic Clouds Experiment (M-PACE) between September and November of 2004. In total, sixteen half hour time periods are reviewed due to their coincidence with radiosonde launches. Cloud liquid (ice) water paths are found to range between 11.0–366.4 (0.5–114.1) gm−2, and cloud physical thicknesses fall between 286–2075 m. Combined with temperature and hydrometeor size estimates, this information is used to calculate surface radiative fluxes using RRTMG, which are demonstrated to generally agree with measured fluxes from surface-based radiometric instrumentation. Errors in longwave flux estimates are found to be largest for thin clouds, while shortwave flux errors are generally largest for thicker clouds. Cloud radiative forcing is calculated for all profiles, and illustrates the dominance of the longwave component during this time of year, with net cloud forcing generally between 50 and 90 Wm−2. Finally, sensitivity of calculated surface fluxes to droplet effective radius, surface albedo and surface temperature are tested, with changes in minimum droplet size between 3.5 and 10 μm altering the surface shortwave flux by up to 50 Wm−2, and changes in surface albedo between 0.5 and 0.95 altering surface shortwave fluxes by up to 85 Wm−2.
18

Barpanda, Pragallva, and Tiffany A. Shaw. "Surface Fluxes Modulate the Seasonality of Zonal-Mean Storm Tracks." Journal of the Atmospheric Sciences 77, no. 2 (November 25, 2019): 753–79. http://dx.doi.org/10.1175/jas-d-19-0139.1.

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Abstract The observed zonal-mean extratropical storm tracks exhibit distinct hemispheric seasonality. Previously, the moist static energy (MSE) framework was used diagnostically to show that shortwave absorption (insolation) dominates seasonality but surface heat fluxes damp seasonality in the Southern Hemisphere (SH) and amplify it in the Northern Hemisphere (NH). Here we establish the causal role of surface fluxes (ocean energy storage) by varying the mixed layer depth d in zonally symmetric 1) slab-ocean aquaplanet simulations with zero ocean energy transport and 2) energy balance model (EBM) simulations. Using a scaling analysis we define a critical mixed layer depth dc and hypothesize 1) large mixed layer depths (d &gt; dc) produce surface heat fluxes that are out of phase with shortwave absorption resulting in small storm track seasonality and 2) small mixed layer depths (d &lt; dc) produce surface heat fluxes that are in phase with shortwave absorption resulting in large storm track seasonality. The aquaplanet simulations confirm the large mixed layer depth hypothesis and yield a useful idealization of the SH storm track. However, the small mixed layer depth hypothesis fails to account for the large contribution of the Ferrel cell and atmospheric storage. The small mixed layer limit does not yield a useful idealization of the NH storm track because the seasonality of the Ferrel cell contribution is opposite to the stationary eddy contribution in the NH. Varying the mixed layer depth in an EBM qualitatively supports the aquaplanet results.
19

Shinohara, Ryuichiro, Yoji Tanaka, Ariyo Kanno, and Kazuo Matsushige. "Relative impacts of increases of solar radiation and air temperature on the temperature of surface water in a shallow, eutrophic lake." Hydrology Research 52, no. 4 (July 14, 2021): 916–26. http://dx.doi.org/10.2166/nh.2021.148.

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Abstract We monitored lake surface water temperatures from 1992 to 2019 in Lake Kasumigaura, a shallow lake in Japan. We hypothesized that increases of shortwave radiation had increased surface water temperatures and heat fluxes more than had the increases of air temperature. We used the heat flux analyses and the sensitivity analyses to test the hypothesis. The fluxes of solar radiation gradually increased during the study period in a manner consistent with the phenomenon of global brightening. The increase was especially apparent in the spring. The rate of increase of surface water temperature was especially significant in May. Air temperature did not significantly increase in May, but it increased significantly in June (0.40 °C decade−1). A sensitivity analysis of the heat fluxes at the lake surface (shortwave radiation, longwave radiation, latent heat flux, and sensible heat flux) revealed that surface water temperature was more sensitive to changes of shortwave radiation than to air temperature during the spring. Although other factors such as inflows of groundwater and river water may also have impacted surface water temperatures, the increase of solar radiation appeared to be the major factor responsible for the increase of surface water temperature during the spring in Lake Kasumigaura.
20

Wild, Martin, and Erich Roeckner. "Radiative Fluxes in the ECHAM5 General Circulation Model." Journal of Climate 19, no. 16 (August 15, 2006): 3792–809. http://dx.doi.org/10.1175/jcli3823.1.

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Abstract Radiative fluxes in the ECHAM5 general circulation model (GCM) are evaluated using both surface and satellite-based observations. The fluxes at the top of the atmosphere (TOA) are generally in good agreement with the satellite data. Larger deviations in simulated cloud forcing are found especially at lower latitudes where the shortwave component within the intertropical convergence zone is overestimated during boreal summer and underestimated in the marine stratocumulus regimes, especially during boreal winter. At the surface the biases in the radiative fluxes are significantly smaller than in earlier versions of the same model and in other GCMs. The shortwave clear-sky fluxes are shown to be in good agreement with newly derived observational estimates. Compared to the preceding model version, ECHAM4, the spurious absorption of solar radiation in the cloudy atmosphere disappears due to the higher resolution in the near-infrared bands of the shortwave radiation code. This reduces the biases with respect to collocated surface and TOA observations. It is illustrated that remaining biases in atmospheric absorption may be related to the crude aerosol climatology, which does not account for high loadings of absorbing aerosol such as from biomass burning, whereas the biases disappear in areas and seasons where aerosol effects are less important. In the longwave, the introduction of the Rapid Radiative Transfer Model (RRTM) radiation code leads to an increase in the longwave downward flux at the surface at high latitudes, thereby reducing biases typically found in GCMs. The considerable skill in the simulation of the fluxes at the earth’s surface underlines the suitability of ECHAM5 as an atmospheric component of an integrated earth system model.
21

Wonsick, Margaret M., Rachel T. Pinker, Wen Meng, and Louis Nguyen. "Evaluation of Surface Shortwave Flux Estimates from GOES: Sensitivity to Sensor Calibration." Journal of Atmospheric and Oceanic Technology 23, no. 7 (July 1, 2006): 927–35. http://dx.doi.org/10.1175/jtech1894.1.

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Abstract Parameters derived from satellite observations depend on the quality of the calibration method applied to the raw satellite radiance measurements. This study investigates the sensitivity of absolute reflectance, derived cloud cover, and estimated surface shortwave (SW) downward fluxes to two different calibration methods for the visible sensor aboard the eighth Geostationary Operational Environmental Satellite (GOES-8). The first method was developed at NOAA's National Environmental Satellite, Data, and Information Service (NESDIS), and the second at the NASA Langley Research Center. Differences in visible reflectance ranged from −0.5% to 3%. The average difference in monthly mean cloud amount was ∼3%, and the average difference in monthly mean shortwave downward flux was 5 W m−2. Differences in bias and rms of the SW fluxes when evaluated against ground station measurements were less than 3 W m−2. Neither calibration method was shown to consistently outperform the other. This evaluation yields an estimate of the errors in fluxes that can be attributed to calibration.
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Chen, Jinxuan, Christoph Gerbig, Julia Marshall, and Kai Uwe Totsche. "Short-term forecasting of regional biospheric CO<sub>2</sub> fluxes in Europe using a light-use-efficiency model (VPRM, MPI-BGC version 1.2)." Geoscientific Model Development 13, no. 9 (September 7, 2020): 4091–106. http://dx.doi.org/10.5194/gmd-13-4091-2020.

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Abstract. Forecasting atmospheric CO2 concentrations on synoptic timescales (∼ days) can benefit the planning of field campaigns by better predicting the location of important gradients. One aspect of this, accurately predicting the day-to-day variation in biospheric fluxes, poses a major challenge. This study aims to investigate the feasibility of using a diagnostic light-use-efficiency model, the Vegetation Photosynthesis Respiration Model (VPRM), to forecast biospheric CO2 fluxes on the timescale of a few days. As input, the VPRM model requires downward shortwave radiation, 2 m temperature, and enhanced vegetation index (EVI) and land surface water index (LSWI), both of which are calculated from MODIS reflectance measurements. Flux forecasts were performed by extrapolating the model input into the future, i.e., using downward shortwave radiation and temperature from a numerical weather prediction (NWP) model, as well as extrapolating the MODIS indices to calculate future biospheric CO2 fluxes with VPRM. A hindcast for biospheric CO2 fluxes in Europe in 2014 has been done and compared to eddy covariance flux measurements to assess the uncertainty from different aspects of the forecasting system. In total the range-normalized mean absolute error (normalized) of the 5 d flux forecast at daily timescales is 7.1 %, while the error for the model itself is 15.9 %. The largest forecast error source comes from the meteorological data, in which error from shortwave radiation contributes slightly more than the error from air temperature. The error contribution from all error sources is similar at each flux observation site and is not significantly dependent on vegetation type.
23

Donohoe, Aaron, and David S. Battisti. "The Seasonal Cycle of Atmospheric Heating and Temperature." Journal of Climate 26, no. 14 (July 12, 2013): 4962–80. http://dx.doi.org/10.1175/jcli-d-12-00713.1.

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Abstract The seasonal cycle of the heating of the atmosphere is divided into a component due to direct solar absorption in the atmosphere and a component due to the flux of energy from the surface to the atmosphere via latent, sensible, and radiative heat fluxes. Both observations and coupled climate models are analyzed. The vast majority of the seasonal heating of the northern extratropics (78% in the observations and 67% in the model average) is due to atmospheric shortwave absorption. In the southern extratropics, the seasonal heating of the atmosphere is entirely due to atmospheric shortwave absorption in both the observations and the models, and the surface heat flux opposes the seasonal heating of the atmosphere. The seasonal cycle of atmospheric temperature is surface amplified in the northern extratropics and nearly barotropic in the Southern Hemisphere; in both cases, the vertical profile of temperature reflects the source of the seasonal heating. In the northern extratropics, the seasonal cycle of atmospheric heating over land differs markedly from that over the ocean. Over the land, the surface energy fluxes complement the driving absorbed shortwave flux; over the ocean, they oppose the absorbed shortwave flux. This gives rise to large seasonal differences in the temperature of the atmosphere over land and ocean. Downgradient temperature advection by the mean westerly winds damps the seasonal cycle of heating of the atmosphere over the land and amplifies it over the ocean. The seasonal cycle in the zonal energy transport is 4.1 PW. Finally, the authors examine the change in the seasonal cycle of atmospheric heating in 11 models from phase 3 of the Coupled Model Intercomparison Project (CMIP3) due to a doubling of atmospheric carbon dioxide from preindustrial concentrations. The seasonal heating of the troposphere is everywhere enhanced by increased shortwave absorption by water vapor; it is reduced where sea ice has been replaced by ocean, which increases the effective heat storage reservoir of the climate system and thereby reduces the seasonal magnitude of energy fluxes between the surface and the atmosphere. As a result, the seasonal amplitude of temperature increases in the upper troposphere (where atmospheric shortwave absorption increases) and decreases at the surface (where the ice melts).
24

Lutsko, Nicholas J., and Ken Takahashi. "What Can the Internal Variability of CMIP5 Models Tell Us about Their Climate Sensitivity?" Journal of Climate 31, no. 13 (July 2018): 5051–69. http://dx.doi.org/10.1175/jcli-d-17-0736.1.

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The relationship between climate models’ internal variability and their response to external forcings is investigated. Frequency-dependent regressions are performed between the outgoing top-of-atmosphere (TOA) energy fluxes and the global-mean surface temperature in the preindustrial control simulations of the CMIP5 archive. Two distinct regimes are found. At subdecadal frequencies the surface temperature and the outgoing shortwave flux are in quadrature, while the outgoing longwave flux is linearly related to temperature and acts as a negative feedback on temperature perturbations. On longer time scales the outgoing shortwave and longwave fluxes are both linearly related to temperature, with the longwave continuing to act as a negative feedback and the shortwave acting as a positive feedback on temperature variability. In addition to the different phase relationships, the two regimes can also be seen in estimates of the coherence and of the frequency-dependent regression coefficients. The frequency-dependent regression coefficients for the total cloudy-sky flux on time scales of 2.5 to 3 years are found to be strongly ( r2 > 0.6) related to the models’ equilibrium climate sensitivities (ECSs), suggesting a potential “emergent constraint” for Earth’s ECS. However, O(100) years of data are required for this relationship to become robust. A simple model for Earth’s surface temperature variability and its relationship to the TOA fluxes is used to provide a physical interpretation of these results.
25

Ruckstuhl, C., and R. Philipona. "TURAC—A New Instrument Package for Radiation Budget Measurements and Cloud Detection." Journal of Atmospheric and Oceanic Technology 22, no. 10 (October 1, 2005): 1473–79. http://dx.doi.org/10.1175/jtech1800.1.

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Abstract Atmospheric radiation flux measurements and the resulting surface radiation budget are important quantities for greenhouse effect and climate change investigations. Accurate net shortwave and longwave fluxes, in conjunction with numerical algorithms, also allow monitoring of the radiative effect of clouds and the nowcasting of the cloud amount. To achieve certain advantages on the accuracy of flux measurements a new instrument is developed that measures downward and upward shortwave and longwave radiation with the same sensors. Two high-quality instruments—a pyranometer for shortwave and a pyrgeometer for longwave measurements—are mounted on a pivotable sensor head, which is rotated up and down in 10-min intervals. To keep the instrument domes free from dew and ice, and to minimize the pyranometer thermal offset, both sensors are ventilated with slightly heated air. Additionally, a ventilated temperature and humidity sensor is integrated in the new instrument. The combination of measurements of radiation fluxes, temperature, and humidity allows for instrument use for autonomous and automatic cloud amount detection. The Temperature, Humidity, Radiation and Clouds (TURAC) sensor has been successfully tested under harsh alpine winter conditions, as well as under moderate lowland conditions. Comparisons to reference instruments showed all radiation fluxes to be within a maximum bias and rms difference of 1.6% or 1.4 W m−2 on daily averages.
26

DeMott, Charlotte A., David A. Randall, and Marat Khairoutdinov. "Implied Ocean Heat Transports in the Standard and Superparameterized Community Atmospheric Models." Journal of Climate 23, no. 7 (April 1, 2010): 1908–28. http://dx.doi.org/10.1175/2009jcli2987.1.

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Abstract Implied ocean heat transport (To) based on net surface energy budgets is computed for two versions of the Community Atmospheric Model (CAM, version 3.0) general circulation model (GCM). The first version is the standard CAM with parameterized convection. The second is the multiscale modeling framework (MMF), in which parameterized convection is replaced with a two-dimensional cloud-resolving model in each GCM grid column. Although global-mean net surface energy totals are similar for both models, differences in the geographic distributions of the component errors lead to distinctly different To for each model, with CAM’s To generally agreeing with observationally based To estimates, and the MMF’s To producing northward transport at all latitudes north of ∼50°S. Analysis of component error sources in the To calculation identifies needed improvements in the MMF. Net surface shortwave radiation and latent heat fluxes over the oceans are the primary causes of To errors in the MMF. Surface shortwave radiation biases in the MMF are associated with liquid and/or ice water content biases in tropical and extratropical convection and a deficit of marine stratocumulus clouds. It is expected that tropical ice water contents in the MMF can be made more realistic via improvements to the cloud microphysics parameterization. MMF marine stratocumulus clouds are overly sensitive to low-level relative humidity and form only with nearly saturated conditions and a shallow boundary layer. Latent heat flux errors in the MMF are amplifications of those found in the CAM and are concentrated in the trade wind regime and the Asian monsoon region and the adjacent western Pacific Ocean. Potential improvements to To are estimated by replacing either simulated net surface shortwave or latent heat fluxes with those from observations and recomputing To. When observed shortwave fluxes are used, both CAM and MMF produce greatly improved To curves for both hemispheres. When To is computed using observed latent heat fluxes, CAM To degrades slightly and MMF To improves, especially in the sign of Southern Hemisphere transport.
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Juszak, Inge, Maitane Iturrate-Garcia, Jean-Philippe Gastellu-Etchegorry, Michael E. Schaepman, Trofim C. Maximov, and Gabriela Schaepman-Strub. "Drivers of shortwave radiation fluxes in Arctic tundra across scales." Remote Sensing of Environment 193 (May 2017): 86–102. http://dx.doi.org/10.1016/j.rse.2017.02.017.

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Pinker, Rachel T., Yingtao Ma, Wen Chen, Istvan Laszlo, Hongqing Liu, Hye-Yun Kim, and Jaime Daniels. "Top-of-the-atmosphere reflected shortwave radiative fluxes from GOES-R." Atmospheric Measurement Techniques 15, no. 17 (September 6, 2022): 5077–94. http://dx.doi.org/10.5194/amt-15-5077-2022.

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Abstract. Under the GOES-R activity, new algorithms are being developed at the National Oceanic and Atmospheric Administration (NOAA)/Center for Satellite Applications and Research (STAR) to derive surface and top-of-the-atmosphere (TOA) shortwave (SW) radiative fluxes from the Advanced Baseline Imager (ABI), the primary instrument on GOES-R. This paper describes a support effort in the development and evaluation of the ABI instrument capabilities to derive such fluxes. Specifically, scene-dependent narrow-to-broadband (NTB) transformations are developed to facilitate the use of observations from ABI at the TOA. Simulations of NTB transformations have been performed with MODTRAN 4.3 using an updated selection of atmospheric profiles and implemented with the final ABI specifications. These are combined with angular distribution models (ADMs), which are a synergy of ADMs from the Clouds and the Earth's Radiant Energy System (CERES) and from simulations. Surface conditions at the scale of the ABI products as needed to compute the TOA radiative fluxes come from the International Geosphere–Biosphere Programme (IGBP). Land classifications at 1/6∘ resolution for 18 surface types are converted to the ABI 2 km grid over the contiguous United States (CONUS) and subsequently re-grouped to 12 IGBP types to match the classification of the CERES ADMs. In the simulations, default information on aerosols and clouds is based on that used in MODTRAN. Comparison of derived fluxes at the TOA is made with those from CERES, and the level of agreement for both clear and cloudy conditions is documented. Possible reasons for differences are discussed. The product is archived and can be downloaded from the NOAA Comprehensive Large Array-data Stewardship System (CLASS).
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Shaw, Tiffany A., Pragallva Barpanda, and Aaron Donohoe. "A Moist Static Energy Framework for Zonal-Mean Storm-Track Intensity." Journal of the Atmospheric Sciences 75, no. 6 (May 30, 2018): 1979–94. http://dx.doi.org/10.1175/jas-d-17-0183.1.

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Abstract A moist static energy (MSE) framework for zonal-mean storm-track intensity, defined as the extremum of zonal-mean transient eddy MSE flux, is derived and applied across a range of time scales. According to the framework, storm-track intensity can be decomposed into contributions from net energy input [sum of shortwave absorption and surface heat fluxes into the atmosphere minus outgoing longwave radiation (OLR) and atmospheric storage] integrated poleward of the storm-track position and MSE flux by the mean meridional circulation or stationary eddies at the storm-track position. The framework predicts storm-track decay in spring and amplification in fall in response to seasonal insolation. When applied diagnostically the framework shows shortwave absorption and land turbulent surface heat fluxes account for the seasonal evolution of Northern Hemisphere (NH) intensity; however, they are partially compensated by OLR (Planck feedback) and stationary eddy MSE flux. The negligible amplitude of Southern Hemisphere (SH) seasonal intensity is consistent with the compensation of shortwave absorption by OLR and oceanic turbulent surface heat fluxes (ocean energy storage). On interannual time scales, El Niño minus La Niña conditions amplify the NH storm track, consistent with decreased subtropical stationary eddy MSE flux. Finally, on centennial time scales, the CO2 indirect effect (sea surface temperature warming) amplifies the NH summertime storm track whereas the direct effect (increased CO2 over land) weakens it, consistent with opposing turbulent surface heat flux responses over land and ocean.
30

Schwartz, Andrew J., Hamish A. McGowan, Alison Theobald, and Nik Callow. "Quantifying the impact of synoptic weather types and patterns on energy fluxes of a marginal snowpack." Cryosphere 14, no. 8 (August 28, 2020): 2755–74. http://dx.doi.org/10.5194/tc-14-2755-2020.

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Abstract. Synoptic weather patterns are investigated for their impact on energy fluxes driving melt of a marginal snowpack in the Snowy Mountains, southeast Australia. K-means clustering applied to ECMWF ERA-Interim data identified common synoptic types and patterns that were then associated with in situ snowpack energy flux measurements. The analysis showed that the largest contribution of energy to the snowpack occurred immediately prior to the passage of cold fronts through increased sensible heat flux as a result of warm air advection (WAA) ahead of the front. Shortwave radiation was found to be the dominant control on positive energy fluxes when individual synoptic weather types were examined. As a result, cloud cover related to each synoptic type was shown to be highly influential on the energy fluxes to the snowpack through its reduction of shortwave radiation and reflection/emission of longwave fluxes. As single-site energy balance measurements of the snowpack were used for this study, caution should be exercised before applying the results to the broader Australian Alps region. However, this research is an important step towards understanding changes in surface energy flux as a result of shifts to the global atmospheric circulation as anthropogenic climate change continues to impact marginal winter snowpacks.
31

Hatzianastassiou, N., C. Matsoukas, A. Fotiadi, K. G. Pavlakis, E. Drakakis, D. Hatzidimitriou, and I. Vardavas. "Global distribution of Earth's surface shortwave radiation budget." Atmospheric Chemistry and Physics 5, no. 10 (November 1, 2005): 2847–67. http://dx.doi.org/10.5194/acp-5-2847-2005.

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Abstract. The monthly mean shortwave (SW) radiation budget at the Earth's surface (SRB) was computed on 2.5-degree longitude-latitude resolution for the 17-year period from 1984 to 2000, using a radiative transfer model accounting for the key physical parameters that determine the surface SRB, and long-term climatological data from the International Satellite Cloud Climatology Project (ISCCP-D2). The model input data were supplemented by data from the National Centers for Environmental Prediction - National Center for Atmospheric Research (NCEP-NCAR) and European Center for Medium Range Weather Forecasts (ECMWF) Global Reanalysis projects, and other global data bases such as TIROS Operational Vertical Sounder (TOVS) and Global Aerosol Data Set (GADS). The model surface radiative fluxes were validated against surface measurements from 22 stations of the Baseline Surface Radiation Network (BSRN) covering the years 1992-2000, and from 700 stations of the Global Energy Balance Archive (GEBA), covering the period 1984-2000. The model is in good agreement with BSRN and GEBA, with a negative bias of 14 and 6.5 Wm-2, respectively. The model is able to reproduce interesting features of the seasonal and geographical variation of the surface SW fluxes at global scale. Based on the 17-year average model results, the global mean SW downward surface radiation (DSR) is equal to 171.6 Wm-2, whereas the net downward (or absorbed) surface SW radiation is equal to 149.4 Wm-2, values that correspond to 50.2 and 43.7% of the incoming SW radiation at the top of the Earth's atmosphere. These values involve a long-term surface albedo equal to 12.9%. Significant increasing trends in DSR and net DSR fluxes were found, equal to 4.1 and 3.7 Wm-2, respectively, over the 1984-2000 period (equivalent to 2.4 and 2.2 Wm-2 per decade), indicating an increasing surface solar radiative heating. This surface SW radiative heating is primarily attributed to clouds, especially low-level, and secondarily to other parameters such as total precipitable water. The surface solar heating occurs mainly in the period starting from the early 1990s, in contrast to decreasing trend in DSR through the late 1980s. The computed global mean DSR and net DSR flux anomalies were found to range within ±8 and ±6 Wm-2, respectively, with signals from El Niño and La Niña events, and the Pinatubo eruption, whereas significant positive anomalies have occurred in the period 1992-2000.
32

Guo, G., and J. A. Coakley. "Satellite Estimates and Shipboard Observations of Downward Radiative Fluxes at the Ocean Surface." Journal of Atmospheric and Oceanic Technology 25, no. 3 (March 1, 2008): 429–41. http://dx.doi.org/10.1175/2007jtecha990.1.

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Abstract Clouds and the Earth’s Radiant Energy System (CERES) uses a suite of instruments on the Terra and Aqua satellites combined with analyzed weather data and information on surface conditions to estimate surface radiative fluxes. CERES estimates for the Terra satellite were compared with measurements of the surface radiative fluxes collected with the research vessels (RVs) Wecoma and Thomas G. Thompson radiometers for cruises off the Oregon coast undertaken during 2000–03. To assess the shipboard measurements, the radiometer observations were analyzed to identify cloud-free conditions characterized by ∼1–2 h of relatively stable radiative fluxes. Fluxes for the cloud-free conditions were compared with those calculated using profiles of temperature and humidity from analyzed meteorological fields for the times and locations of the measurements and broadband radiative transfer models. For summertime conditions along the Oregon coast, and assuming a marine aerosol having 0.55-μm optical depth of 0.05, modeled and observed values of the shortwave flux agreed to within 1%–2%. Similar comparisons for the downward cloud-free longwave flux were within 1%–3%. This agreement also held for the CERES surface radiative flux estimates with CERES cloud-free fields of view for ocean scenes within 50 km of the ship being compared with 30-min averages of the shipboard measurements centered on the times of the Terra overpass. Using the CERES observations to identify cloud-free conditions for the Wecoma revealed that in some cases the shipboard measurements of the shortwave flux varied erratically. Criteria were adopted to avoid such behavior, yielding periods in which the surface radiative fluxes were reasonably stable for a range of cloud-free and cloudy conditions. With the criteria applied, the absolute magnitude of the mean differences between the shipboard measurements and the CERES estimates for the downward shortwave flux were within 2%, with RMS differences less than 6% within each month of CERES–shipboard matchups. The absolute magnitude of the mean differences for the downward longwave flux was less than 2%, with RMS differences less than 5%.
33

May, Jackie C., Clark Rowley, and Charlie N. Barron. "NFLUX Satellite-Based Surface Radiative Heat Fluxes. Part I: Swath-Level Products." Journal of Applied Meteorology and Climatology 56, no. 4 (April 2017): 1025–41. http://dx.doi.org/10.1175/jamc-d-16-0282.1.

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AbstractThe Naval Research Laboratory (NRL) ocean surface flux (NFLUX) system originally provided operational near-real-time satellite-based surface state parameter and turbulent heat flux fields over the global ocean. This study extends the NFLUX system to include the production of swath-level shortwave and longwave radiative heat fluxes at the ocean surface. A companion paper presents the production of the satellite-based global gridded radiative heat flux analysis fields. The swath-level radiative heat fluxes are produced using the Rapid Radiative Transfer Model for Global Circulation Models (RRTMG), with the primary inputs of satellite-derived atmospheric temperature and moisture profiles and cloud information retrieved from the Microwave Integrated Retrieval System (MIRS). This study uses MIRS data provided for six polar-orbiting satellite platforms. Additional inputs to the RRTMG include sea surface temperature, aerosol optical depths, atmospheric gas concentrations, ocean surface albedo, and ocean surface emissivity. Swath-level shortwave flux estimates are converted into clearness index values, which are used in data assimilation because the clearness index values are less dependent on the solar zenith angle. The NFLUX swath-level shortwave flux, longwave flux, and clearness index estimates are produced for 1 May 2013–30 April 2014 and validated against observations from research vessel and moored buoy platforms. Each of the flux parameters compares well among the various satellites.
34

Masunaga, Hirohiko, and Tristan S. L’Ecuyer. "The Southeast Pacific Warm Band and Double ITCZ." Journal of Climate 23, no. 5 (March 1, 2010): 1189–208. http://dx.doi.org/10.1175/2009jcli3124.1.

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Abstract The east Pacific double intertropical convergence zone (ITCZ) in austral fall is investigated with particular focus on the growing processes of its Southern Hemisphere branch. Satellite measurements from the Tropical Rainfall Measuring Mission (TRMM) and Quick Scatterometer (QuikSCAT) are analyzed to derive 8-yr climatology from 2000 to 2007. The earliest sign of the south ITCZ emerges in sea surface temperature (SST) by January, followed by the gradual development of surface convergence and water vapor. The shallow cumulus population starts growing to form the south ITCZ in February, a month earlier than vigorous deep convection is organized into the south ITCZ. The key factors that give rise to the initial SST enhancement or the southeast Pacific warm band are diagnosed by simple experiments. The experiments are designed to calculate SST, making use of an ocean mixed layer “model” forced by surface heat fluxes, all of which are derived from satellite observations. It is found that the shortwave flux absorbed into the ocean mixed layer is the primary driver of the southeast Pacific warm band. The warm band does not develop in boreal fall because the shortwave flux is seasonally so small that it is overwhelmed by other negative fluxes, including the latent heat and longwave fluxes. Clouds offset the net radiative flux by 10–15 W m−2, which is large enough for the warm band to develop in boreal fall if it were not for clouds reflecting shortwave radiation. Interannual variability of the double ITCZ is also discussed in brief.
35

Hatzianastassiou, N., C. Matsoukas, A. Fotiadi, K. G. Pavlakis, E. Drakakis, D. Hatzidimitriou, and I. Vardavas. "Global distribution of Earth’s surface shortwave radiation budget." Atmospheric Chemistry and Physics Discussions 5, no. 4 (July 11, 2005): 4545–97. http://dx.doi.org/10.5194/acpd-5-4545-2005.

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Abstract. The monthly mean shortwave (SW) radiation budget at the Earth's surface (SRB) was computed on 2.5-degree longitude-latitude resolution for the 17-year period from 1984 to 2000, using a radiative transfer model accounting for the key physical parameters that determine the surface SRB, and long-term climatological data from the International Satellite Cloud Climatology Project (ISCCP-D2). The model input data were supplemented by data from the National Centers for Environmental Prediction – National Center for Atmospheric Research (NCEP-NCAR) and European Center for Medium Range Weather Forecasts (ECMWF) Global Reanalysis projects, and other global data bases such as TIROS Operational Vertical Sounder (TOVS) and Global Aerosol Data Set (GADS). The model surface radiative fluxes were validated against surface measurements from 22 stations of the Baseline Surface Radiation Network (BSRN) covering the years 1992–2000, and from 700 stations of the Global Energy Balance Archive (GEBA), covering the period 1984–2000. The model is in very good agreement with BSRN and GEBA, with a negative bias of 14 and 6.5 Wm-2, respectively. The model is able to reproduce interesting features of the seasonal and geographical variation of the surface SW fluxes at global scale, which is not possible with surface measurements. Based on the 17-year average model results, the global mean SW downward surface radiation (DSR) is equal to 171.6 Wm−2, whereas the net downward (or absorbed) surface SW radiation is equal to 149.4 Wm−2, values that correspond to 50.2 and 43.7% of the incoming SW radiation at the top of the Earth's atmosphere. These values involve a long-term surface albedo equal to 12.9%. Significant increasing trends in DSR and net DSR fluxes were found, equal to 4.1 and 3.7 Wm−2, respectively, over the 1984–2000 period (equivalent to 2.4 and 2.2 Wm−2 per decade), indicating an increasing surface solar radiative heating. This surface SW radiative heating is primarily attributed to clouds, especially low-level, and secondarily to other parameters such as total precipitable water. The surface solar heating occurs mainly in the period starting from the early 1990s, in contrast to the commonly reported decreasing trend in DSR through the late 1980s, found also in our study. The computed global mean DSR and net DSR flux anomalies were found to range within ±8 and ±6 Wm−2, respectively, with signals from El Niño and La Niña events, and the Pinatubo eruption, whereas significant positive anomalies have occurred in the period 1992–2000.
36

Tegegne, Eyale Bayable, Yaoming Ma, Xuelong Chen, Weiqiang Ma, Bingbing Wang, Zhangwei Ding, and Zhikun Zhu. "Estimation of the distribution of the total net radiative flux from satellite and automatic weather station data in the Upper Blue Nile basin, Ethiopia." Theoretical and Applied Climatology 143, no. 1-2 (October 28, 2020): 587–602. http://dx.doi.org/10.1007/s00704-020-03397-9.

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AbstractNet radiation is an important factor in studies of land–atmosphere processes, water resource management, and global climate change. This is particularly true for the Upper Blue Nile (UBN) basin, where significant parts of the basin are dry and evapotranspiration (ET) is a major mechanism for water loss. However, net radiation has not yet been appropriately parameterized in the basin. In this study, we estimated the instantaneous distribution of the net radiation flux in the basin using data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard the Terra satellite and Automatic Weather Station (AWS) data. Downward shortwave radiation and air temperature usually vary with topography, so we applied residual kriging spatial interpolation techniques to convert AWS data for point locations into gridded surface data. Simulated net radiation outputs were validated through comparison with independent field measurements. Validation results show that our method successfully reproduced the downward shortwave, upward shortwave, and net radiation fluxes. Using AWS data and residual kriging spatial interpolation techniques makes our results robust and comparable to previous works that used satellite data at a finer spatial resolution than MODIS. The estimated net shortwave, longwave, and total radiation fluxes were in close agreement with ground truth measurements, with mean bias (MB) values of − 14.84, 5.7, and 20.53 W m−2 and root mean square error (RMSE) values 83.43, 32.54, and 78.07 W m−2, respectively. The method presented here has potential applications in research focused on energy balance, ET estimation, and weather prediction for regions with similar physiographic features to those of the Nile basin.
37

Rutan, David A., Seiji Kato, David R. Doelling, Fred G. Rose, Le Trang Nguyen, Thomas E. Caldwell, and Norman G. Loeb. "CERES Synoptic Product: Methodology and Validation of Surface Radiant Flux." Journal of Atmospheric and Oceanic Technology 32, no. 6 (June 2015): 1121–43. http://dx.doi.org/10.1175/jtech-d-14-00165.1.

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AbstractThe Clouds and the Earth’s Radiant Energy System Synoptic (SYN1deg), edition 3, product provides climate-quality global 3-hourly 1° × 1°gridded top of atmosphere, in-atmosphere, and surface radiant fluxes. The in-atmosphere surface fluxes are computed hourly using a radiative transfer code based upon inputs from Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS), 3-hourly geostationary (GEO) data, and meteorological assimilation data from the Goddard Earth Observing System. The GEO visible and infrared imager calibration is tied to MODIS to ensure uniform MODIS-like cloud properties across all satellite cloud datasets. Computed surface radiant fluxes are compared to surface observations at 85 globally distributed land (37) and ocean buoy (48) sites as well as several other publicly available global surface radiant flux data products. Computed monthly mean downward fluxes from SYN1deg have a bias (standard deviation) of 3.0 W m−2 (5.7%) for shortwave and −4.0 W m−2 (2.9%) for longwave compared to surface observations. The standard deviation between surface downward shortwave flux calculations and observations at the 3-hourly time scale is reduced when the diurnal cycle of cloud changes is explicitly accounted for. The improvement is smaller for surface downward longwave flux owing to an additional sensitivity to boundary layer temperature/humidity, which has a weaker diurnal cycle compared to clouds.
38

Kratz, David P., Paul W. Stackhouse, Shashi K. Gupta, Anne C. Wilber, Parnchai Sawaengphokhai, and Greg R. McGarragh. "The Fast Longwave and Shortwave Flux (FLASHFlux) Data Product: Single-Scanner Footprint Fluxes." Journal of Applied Meteorology and Climatology 53, no. 4 (April 2014): 1059–79. http://dx.doi.org/10.1175/jamc-d-13-061.1.

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AbstractThe Clouds and the Earth’s Radiant Energy Systems (CERES) project utilizes radiometric measurements taken aboard the Terra and Aqua spacecrafts to derive the world-class data products needed for climate research. Achieving the exceptional fidelity of the CERES data products, however, requires a considerable amount of processing to assure quality and to verify accuracy and precision, which results in the CERES data being released more than 6 months after the satellite observations. For most climate studies such delays are of little consequence; however, there are a significant number of near–real time uses for CERES data products. The Fast Longwave and Shortwave Radiative Flux (FLASHFlux) data product was therefore developed to provide a rapid release version of the CERES results, which could be made available to the research and applications communities within 1 week of the satellite observations by exchanging some accuracy for speed. FLASHFlux has both achieved this 1-week processing objective and demonstrated the ability to provide remarkably good agreement when compared with the CERES data products for both the instantaneous single-scanner footprint (SSF) fluxes and the time- and space-averaged (TISA) fluxes. This paper describes the methods used to expedite the production of the FLASHFlux SSF fluxes by utilizing data from the CERES and Moderate Resolution Imaging Spectroradiometer instruments, as well as other meteorological sources. This paper also reports on the validation of the FLASHFlux SSF results against ground-truth measurements and the intercomparison of FLASHFlux and CERES SSF results. A complementary paper will discuss the production and validation of the FLASHFlux TISA fluxes.
39

Forman, B. A., and S. A. Margulis. "Impact of Covariance Localization on Ensemble Estimation of Surface Downwelling Longwave and Shortwave Radiation Fluxes." Journal of Hydrometeorology 13, no. 4 (August 1, 2012): 1301–16. http://dx.doi.org/10.1175/jhm-d-11-073.1.

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Abstract Accurate estimates of terrestrial hydrologic states and fluxes are, in large part, dependent on accurate estimates of the spatiotemporal variability and uncertainty of land surface forcings, including downwelling longwave (LW) and shortwave (SW) fluxes. However, such characterization of land surface forcings does not always receive proper attention. This study attempts to better estimate LW and SW fluxes, including their uncertainties, by merging different sources of information while considering horizontal error correlations via implementation of a 2D conditioning procedure within a Bayesian framework. A total of 25 experiments were performed utilizing four different, readily available downwelling radiation products. The localized region of space used to constrain horizontal error correlations was defined using an influence length, , specified a priori. Quantitative comparisons are made against an independent, ground-based observational network. In general, results suggest moderate improvement in cloudy-sky LW fluxes and modest improvement in clear-sky SW fluxes during certain times of the year when using the 2D framework relative to a more traditional 1D framework, but only up to a certain influence length scale. Beyond this length scale the flux estimates were typically degraded because of the introduction of spurious correlations. The influence length scale that yielded the greatest improvement in LW radiative flux estimation during cloudy-sky conditions, in general, increased with increasing cloud cover. These findings have implications for improving downwelling radiative flux estimation and further enhancing existing Land Data Assimilation System (LDAS) frameworks.
40

McFarlane, Sally A., and K. Franklin Evans. "Clouds and Shortwave Fluxes at Nauru. Part I: Retrieved Cloud Properties." Journal of the Atmospheric Sciences 61, no. 6 (March 2004): 733–44. http://dx.doi.org/10.1175/1520-0469(2004)061<0733:casfan>2.0.co;2.

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41

Sinitsyn, A., and S. Gulev. "Application of integral parametrization “SAIL” for climatology incoming shortwave radiation fluxes." IOP Conference Series: Earth and Environmental Science 606 (November 27, 2020): 012059. http://dx.doi.org/10.1088/1755-1315/606/1/012059.

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42

Xu, Kuan-Man. "The Sensitivity of Diagnostic Radiative Properties to Cloud Microphysics among Cloud-Resolving Model Simulations." Journal of the Atmospheric Sciences 62, no. 4 (April 1, 2005): 1241–54. http://dx.doi.org/10.1175/jas3401.1.

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Abstract This study examines the sensitivity of diagnosed radiative fluxes and heating rates to different treatments of cloud microphysics among cloud-resolving models (CRMs). The domain-averaged CRM outputs are used in this calculation. The impacts of the cloud overlap and uniform hydrometeor assumptions are examined using outputs having spatially varying cloud fields from a single CRM. It is found that the cloud overlap assumption impacts the diagnosis more significantly than the uniform hydrometeor assumption for all radiative fluxes. This is also the case for the longwave radiative cooling rate except for a layer above 7 km where it is more significantly impacted by the uniform hydrometeor assumption. The radiative cooling above upper-tropospheric anvils and the warming below these clouds are overestimated by about 0.5 K day−1 using the domain-averaged outputs. These results are used to further quantify intermodel differences in radiative properties due to different treatments of cloud microphysics among 10 CRMs. The magnitudes of the intermodel differences, as measured by the deviations from the consensus of 10 CRMs, are found to be smaller than those due to the cloud overlap assumption and comparable to those due to the uniform hydrometeor assumption for most shortwave radiative fluxes and the net radiative fluxes at the top of the atmosphere (TOA) and at the surface. For all longwave radiative fluxes, they are smaller than those due to cloud overlap and uniform hydrometeor assumptions. The consensus of all diagnosed radiative fluxes except for the surface downward shortwave flux agrees with observations to a degree that is close to the uncertainties of satellite- and ground-based measurements.
43

Protat, A., S. A. Young, S. A. McFarlane, T. L’Ecuyer, G. G. Mace, J. M. Comstock, C. N. Long, E. Berry, and J. Delanoë. "Reconciling Ground-Based and Space-Based Estimates of the Frequency of Occurrence and Radiative Effect of Clouds around Darwin, Australia." Journal of Applied Meteorology and Climatology 53, no. 2 (February 2014): 456–78. http://dx.doi.org/10.1175/jamc-d-13-072.1.

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AbstractThe objective of this paper is to investigate whether estimates of the cloud frequency of occurrence and associated cloud radiative forcing as derived from ground-based and satellite active remote sensing and radiative transfer calculations can be reconciled over a well-instrumented active remote sensing site located in Darwin, Australia, despite the very different viewing geometry and instrument characteristics. It is found that the ground-based radar–lidar combination at Darwin does not detect most of the cirrus clouds above 10 km (because of limited lidar detection capability and signal obscuration by low-level clouds) and that the CloudSat radar–Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) combination underreports the hydrometeor frequency of occurrence below 2-km height because of instrument limitations at these heights. The radiative impact associated with these differences in cloud frequency of occurrence is large on the surface downwelling shortwave fluxes (ground and satellite) and the top-of-atmosphere upwelling shortwave and longwave fluxes (ground). Good agreement is found for other radiative fluxes. Large differences in radiative heating rate as derived from ground and satellite radar–lidar instruments and radiative transfer calculations are also found above 10 km (up to 0.35 K day−1 for the shortwave and 0.8 K day−1 for the longwave). Given that the ground-based and satellite estimates of cloud frequency of occurrence and radiative impact cannot be fully reconciled over Darwin, caution should be exercised when evaluating the representation of clouds and cloud–radiation interactions in large-scale models, and limitations of each set of instrumentation should be considered when interpreting model–observation differences.
44

Nordling, Kalle, Hannele Korhonen, Jouni Räisänen, Antti-Ilari Partanen, Bjørn H. Samset, and Joonas Merikanto. "Understanding the surface temperature response and its uncertainty to CO&lt;sub&gt;2&lt;/sub&gt;, CH&lt;sub&gt;4&lt;/sub&gt;, black carbon, and sulfate." Atmospheric Chemistry and Physics 21, no. 19 (October 8, 2021): 14941–58. http://dx.doi.org/10.5194/acp-21-14941-2021.

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Abstract. Understanding the regional surface temperature responses to different anthropogenic climate forcing agents, such as greenhouse gases and aerosols, is crucial for understanding past and future regional climate changes. In modern climate models, the regional temperature responses vary greatly for all major forcing agents, but the causes of this variability are poorly understood. Here, we analyze how changes in atmospheric and oceanic energy fluxes due to perturbations in different anthropogenic climate forcing agents lead to changes in global and regional surface temperatures. We use climate model data on idealized perturbations in four major anthropogenic climate forcing agents (CO2, CH4, sulfate, and black carbon aerosols) from Precipitation Driver Response Model Intercomparison Project (PDRMIP) climate experiments for six climate models (CanESM2, HadGEM2-ES, NCAR-CESM1-CAM4, NorESM1, MIROC-SPRINTARS, GISS-E2). Particularly, we decompose the regional energy budget contributions to the surface temperature responses due to changes in longwave and shortwave fluxes under clear-sky and cloudy conditions, surface albedo changes, and oceanic and atmospheric energy transport. We also analyze the regional model-to-model temperature response spread due to each of these components. The global surface temperature response stems from changes in longwave emissivity for greenhouse gases (CO2 and CH4) and mainly from changes in shortwave clear-sky fluxes for aerosols (sulfate and black carbon). The global surface temperature response normalized by effective radiative forcing is nearly the same for all forcing agents (0.63, 0.54, 0.57, 0.61 K W−1 m2). While the main physical processes driving global temperature responses vary between forcing agents, for all forcing agents the model-to-model spread in temperature responses is dominated by differences in modeled changes in longwave clear-sky emissivity. Furthermore, in polar regions for all forcing agents the differences in surface albedo change is a key contributor to temperature responses and its spread. For black carbon, the modeled differences in temperature response due to shortwave clear-sky radiation are also important in the Arctic. Regional model-to-model differences due to changes in shortwave and longwave cloud radiative effect strongly modulate each other. For aerosols, clouds play a major role in the model spread of regional surface temperature responses. In regions with strong aerosol forcing, the model-to-model differences arise from shortwave clear-sky responses and are strongly modulated by combined temperature responses to oceanic and atmospheric heat transport in the models.
45

Stanelle, T., B. Vogel, H. Vogel, D. Bäumer, and Ch Kottmeier. "Feedback between dust particles and atmospheric processes over West Africa in March 2006 and June 2007." Atmospheric Chemistry and Physics Discussions 10, no. 3 (March 23, 2010): 7553–99. http://dx.doi.org/10.5194/acpd-10-7553-2010.

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Abstract. We used the comprehensive model system COSMO-ART to quantify the impact of mineral dust on the radiative fluxes, the temperature and the feedback between dust particles and their emissions. We simulated two dust storms over West Africa in March 2006 and in June 2007. Simulations with and without coupling of the actual dust concentration with the radiative fluxes and the thermodynamics were carried out for each case. The model results for the 2006 case were compared with observations of the AMMA campaign. At the surface the shortwave radiative effect of mineral dust can be described by a linear relation between the changes in net surface radiation and the aerosol optical depth. For an aerosol optical depth (AOD) at 450 nm of 1 the average shortwave radiation reduction amounts −130 W m−2 during noon. The longwave radiative effect of mineral dust is nonlinear, with an average increase of +70 W m−2 for an AOD (450 nm) of 1. At the top of the atmosphere the effect of the dust layer with an AOD of 1 on radiative fluxes is not as significant as at the surface. It is slightly positive for the shortwave and approximately 26 W m−2 for the longwave radiation. The height range and the extension of the dust layer determine the effect of dust particles on the 2 m temperature. When the dust layer is attached to the surface and lasts for several days it leads to an increase of the surface temperature even during daytime. In case of an elevated dust layer there is a decrease in 2 m temperature of up to 4 K during noon. It is shown, that the temperature changes caused by mineral dust may result in horizontal temperature gradients which also modify near surface winds. Since surface wind thresholds decide the uptake of dust from the surface, a feedback on total emission fluxes is established. The coupled model provides an increase in the total emission fluxes of dust particles by about 16% during the dust storm in March 2006 and 25% during the dust episode in June 2007.
46

Stanelle, T., B. Vogel, H. Vogel, D. Bäumer, and C. Kottmeier. "Feedback between dust particles and atmospheric processes over West Africa during dust episodes in March 2006 and June 2007." Atmospheric Chemistry and Physics 10, no. 22 (November 17, 2010): 10771–88. http://dx.doi.org/10.5194/acp-10-10771-2010.

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Abstract. We used the comprehensive model system COSMO-ART to quantify the impact of mineral dust on the radiative fluxes, the temperature and the feedback between dust particles and their emissions. We simulated two dust storms over West Africa in March 2006 and in June 2007. Simulations with and without coupling of the actual dust concentration with the radiative fluxes and the thermodynamics were carried out for each case. The model results for the 2006 case were compared with observations of the AMMA campaign. At the surface the shortwave radiative effect of mineral dust can be described by a linear relation between the changes in net surface radiation and the aerosol optical depth (AOD). For an AOD at 450 nm of 1 the average shortwave radiation reduction amounts −140 W m−2 during noon. The longwave radiative effect of mineral dust is nonlinear, with an average increase of +70 W m−2 for an AOD (450 nm) of 1. At the top of the atmosphere the effect of the dust layer with an AOD of 1 on radiative fluxes is not as significant as at the surface. It is slightly positive for the shortwave and approximately 26 W m−2 for the longwave radiation. The height range and the extension of the dust layer determine the effect of dust particles on the 2 m temperature. When the dust layer is attached to the surface and lasts for several days it leads to an increase of the surface temperature even during daytime. In case of an elevated dust layer there is a decrease in 2 m temperature of up to 4 K during noon. It is shown, that the temperature changes caused by mineral dust may result in horizontal temperature gradients which also modify near surface winds. Since surface wind thresholds decide the uptake of dust from the surface, a feedback on total emission fluxes is established. The coupled model provides an increase in the total emission fluxes of dust particles by about 16% during the dust storm in March 2006 and 25% during the dust episode in June 2007.
47

Ferrett, Samantha, Matthew Collins, and Hong-Li Ren. "Diagnosing Relationships between Mean State Biases and El Niño Shortwave Feedback in CMIP5 Models." Journal of Climate 31, no. 4 (February 2018): 1315–35. http://dx.doi.org/10.1175/jcli-d-17-0331.1.

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The rate of damping of tropical Pacific sea surface temperature anomalies (SSTAs) associated with El Niño events by surface shortwave heat fluxes has significant biases in current coupled climate models [phase 5 of the Coupled Model Intercomparison Project (CMIP5)]. Of 33 CMIP5 models, 16 have shortwave feedbacks that are weakly negative in comparison to observations, or even positive, resulting in a tendency of amplification of SSTAs. Two biases in the cloud response to El Niño SSTAs are identified and linked to significant mean state biases in CMIP5 models. First, cool mean SST and reduced precipitation are linked to comparatively less cloud formation in the eastern equatorial Pacific during El Niño events, driven by a weakened atmospheric ascent response. Second, a spurious reduction of cloud driven by anomalous surface relative humidity during El Niño events is present in models with more stable eastern Pacific mean atmospheric conditions and more low cloud in the mean state. Both cloud response biases contribute to a weak negative shortwave feedback or a positive shortwave feedback that amplifies El Niño SSTAs. Differences between shortwave feedback in the coupled models and the corresponding atmosphere-only models (AMIP) are also linked to mean state differences, consistent with the biases found between different coupled models. Shortwave feedback bias can still persist in AMIP, as a result of persisting weak shortwave responses to anomalous cloud and weak cloud responses to atmospheric ascent. This indicates the importance of bias in the atmosphere component to coupled model feedback and mean state biases.
48

Su, Wenying, Patrick Minnis, Lusheng Liang, David P. Duda, Konstantin Khlopenkov, Mandana M. Thieman, Yinan Yu, et al. "Determining the daytime Earth radiative flux from National Institute of Standards and Technology Advanced Radiometer (NISTAR) measurements." Atmospheric Measurement Techniques 13, no. 2 (February 5, 2020): 429–43. http://dx.doi.org/10.5194/amt-13-429-2020.

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Abstract. The National Institute of Standards and Technology Advanced Radiometer (NISTAR) onboard the Deep Space Climate Observatory (DSCOVR) provides continuous full-disk global broadband irradiance measurements over most of the sunlit side of the Earth. The three active cavity radiometers measure the total radiant energy from the sunlit side of the Earth in shortwave (SW; 0.2–4 µm), total (0.4–100 µm), and near-infrared (NIR; 0.7–4 µm) channels. The Level 1 NISTAR dataset provides the filtered radiances (the ratio between irradiance and solid angle). To determine the daytime top-of-atmosphere (TOA) shortwave and longwave radiative fluxes, the NISTAR-measured shortwave radiances must be unfiltered first. An unfiltering algorithm was developed for the NISTAR SW and NIR channels using a spectral radiance database calculated for typical Earth scenes. The resulting unfiltered NISTAR radiances are then converted to full-disk daytime SW and LW flux by accounting for the anisotropic characteristics of the Earth-reflected and emitted radiances. The anisotropy factors are determined using scene identifications determined from multiple low-Earth orbit and geostationary satellites as well as the angular distribution models (ADMs) developed using data collected by the Clouds and the Earth's Radiant Energy System (CERES). Global annual daytime mean SW fluxes from NISTAR are about 6 % greater than those from CERES, and both show strong diurnal variations with daily maximum–minimum differences as great as 20 Wm−2 depending on the conditions of the sunlit portion of the Earth. They are also highly correlated, having correlation coefficients of 0.89, indicating that they both capture the diurnal variation. Global annual daytime mean LW fluxes from NISTAR are 3 % greater than those from CERES, but the correlation between them is only about 0.38.
49

Ebell, Kerstin, Tatiana Nomokonova, Marion Maturilli, and Christoph Ritter. "Radiative Effect of Clouds at Ny-Ålesund, Svalbard, as Inferred from Ground-Based Remote Sensing Observations." Journal of Applied Meteorology and Climatology 59, no. 1 (January 2020): 3–22. http://dx.doi.org/10.1175/jamc-d-19-0080.1.

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AbstractFor the first time, the cloud radiative effect (CRE) has been characterized for the Arctic site Ny-Ålesund, Svalbard, Norway, including more than 2 years of data (June 2016–September 2018). The cloud radiative effect, that is, the difference between the all-sky and equivalent clear-sky net radiative fluxes, has been derived based on a combination of ground-based remote sensing observations of cloud properties and the application of broadband radiative transfer simulations. The simulated fluxes have been evaluated in terms of a radiative closure study. Good agreement with observed surface net shortwave (SW) and longwave (LW) fluxes has been found, with small biases for clear-sky (SW: 3.8 W m−2; LW: −4.9 W m−2) and all-sky (SW: −5.4 W m−2; LW: −0.2 W m−2) situations. For monthly averages, uncertainties in the CRE are estimated to be small (~2 W m−2). At Ny-Ålesund, the monthly net surface CRE is positive from September to April/May and negative in summer. The annual surface warming effect by clouds is 11.1 W m−2. The longwave surface CRE of liquid-containing cloud is mainly driven by liquid water path (LWP) with an asymptote value of 75 W m−2 for large LWP values. The shortwave surface CRE can largely be explained by LWP, solar zenith angle, and surface albedo. Liquid-containing clouds (LWP > 5 g m−2) clearly contribute most to the shortwave surface CRE (70%–98%) and, from late spring to autumn, also to the longwave surface CRE (up to 95%). Only in winter are ice clouds (IWP > 0 g m−2; LWP < 5 g m−2) equally important or even dominating the signal in the longwave surface CRE.
50

Vinukollu, Raghuveer K., Justin Sheffield, Eric F. Wood, Michael G. Bosilovich, and David Mocko. "Multimodel Analysis of Energy and Water Fluxes: Intercomparisons between Operational Analyses, a Land Surface Model, and Remote Sensing." Journal of Hydrometeorology 13, no. 1 (February 1, 2012): 3–26. http://dx.doi.org/10.1175/2011jhm1372.1.

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Abstract Using data from seven global model operational analyses (OA), one land surface model, and various remote sensing retrievals, the energy and water fluxes over global land areas are intercompared for 2003/04. Remote sensing estimates of evapotranspiration (ET) are obtained from three process-based models that use input forcings from multisensor satellites. An ensemble mean (linear average) of the seven operational (mean-OA) models is used primarily to intercompare the fluxes with comparisons performed at both global and basin scales. At the global scale, it is found that all components of the energy budget represented by the ensemble mean of the OA models have a significant bias. Net radiation estimates had a positive bias (global mean) of 234 MJ m−2 yr−1 (7.4 W m−2) as compared to the remote sensing estimates, with the latent and sensible heat fluxes biased by 470 MJ m−2 yr−1 (13.3 W m−2) and −367 MJ m−2 yr−1 (11.7 W m−2), respectively. The bias in the latent heat flux is affected by the bias in the net radiation, which is primarily due to the biases in the incoming shortwave and outgoing longwave radiation and to the nudging process of the operational models. The OA models also suffer from improper partitioning of the surface heat fluxes. Comparison of precipitation (P) analyses from the various OA models, gauge analysis, and remote sensing retrievals showed better agreement than the energy fluxes. Basin-scale comparisons were consistent with the global-scale results, with the results for the Amazon in particular showing disparities between OA and remote sensing estimates of energy fluxes. The biases in the fluxes are attributable to a combination of errors in the forcing from the OA atmospheric models and the flux calculation methods in their land surface schemes. The atmospheric forcing errors are mainly attributable to high shortwave radiation likely due to the underestimation of clouds, but also precipitation errors, especially in water-limited regions.

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