Improved retrieval of direct and diffuse downwelling surface  shortwave flux in cloudless atmosphere using dynamic estimates of aerosol  content and type: application to the LSA-SAF project

Abstract. Downwelling surface shortwave flux (DSSF) is a key parameter to addressing many climate, meteorological, and solar energy issues. Under clear sky conditions, DSSF is particularly sensitive to the variability both in time and space of the aerosol load and chemical composition. Hitherto, this dependence has not been properly addressed by the Satellite Application Facility on Land Surface Analysis (LSA-SAF), which operationally disseminates instantaneous DSSF products over the continents since 2005 considering constant aerosol conditions. In the present study, an efficient method is proposed for DSSF retrieval that will overcome the limitations of the current LSA-SAF product. This method referred to as SIRAMix (Surface Incident Radiation estimation using Aerosol Mixtures) is based upon an accurate physical parameterization coupled with a radiative transfer-based look up table of aerosol properties. SIRAMix considers a tropospheric layer composed of several major aerosol species that are conveniently mixed to reproduce real aerosol conditions as best as possible. This feature of SIRAMix allows it to provide not only accurate estimates of global DSSF but also the direct and diffuse DSSF components, which are crucial radiative terms in many climatological applications. The implementation of SIRAMix is tested in the present article using atmospheric analyses from the European Center for Medium-Range Weather Forecasts (ECMWF). DSSF estimates provided by SIRAMix are compared against instantaneous DSSF measurements taken at several ground stations belonging to several radiation measurement networks. Results show an average root mean square error (RMSE) of 23.6, 59.1, and 44.9 W m−2 for global, direct, and diffuse DSSF, respectively. These scores decrease the average RMSE obtained for the current LSA-SAF product by 18.6%, which only provides global DSSF for the time being, and, to a lesser extent, for the state of the art in the matter of DSSF retrieval (RMSE decrease of 10.9, 6.5, and 19.1% for global, direct, and diffuse DSSF with regard to the McClear algorithm). The main limitation of the proposed approach is its high sensitivity to the quality of the ECMWF aerosol inputs, which is proved to be sufficiently accurate for reanalyses but not for forecast data. Given the proximity of DSSF retrieval to the modeling of the atmospheric direct effect, SIRAMix is also able to quantify the direct radiative forcing at the surface due to a given atmospheric component (e.g., gases or aerosols).

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Improved retrieval of direct and diffuse downwelling surface shortwave flux in cloudless atmosphere using dynamic estimates of aerosol content and type: application to the LSA-SAF project

Atmospheric Chemistry and Physics Discussions ◽

10.5194/acpd-14-8333-2014 ◽

2014 ◽

Vol 14 (6) ◽

pp. 8333-8392 ◽

Cited By ~ 1

Author(s):

X. Ceamanos ◽

D. Carrer ◽

J.-L. Roujean

Keyword(s):

Land Surface ◽

Radiative Forcing ◽

High Sensitivity ◽

Incident Radiation ◽

Aerosol Layer ◽

Production Chain ◽

Weather Forecasts ◽

Clear Sky ◽

Atmospheric Inputs ◽

Sky Conditions

Abstract. Downwelling surface shortwave flux (DSSF) is a key parameter to address many climate, meteorological, and solar energy issues. Under clear sky conditions, DSSF is particularly sensitive to the variability both in time and space of the aerosol load and chemical composition. Hitherto, this dependence has not been properly addressed by the Satellite Application Facility on Land Surface Analysis (LSA-SAF), which operationally disseminates instantaneous DSSF products over the continents since 2005 considering unchanging aerosol conditions. In the present study, an efficient method is proposed for DSSF retrieval that will overcome the limitations of the current LSA-SAF product. This method referred to as SIRAMix (Surface Incident Radiation estimation using Aerosol Mixtures) is based on an accurate physical parameterization that is coupled with a radiative transfer-based look up table of aerosol properties. SIRAMix considers an aerosol layer constituted of several major aerosol species that are conveniently mixed to match real aerosol conditions. This feature of SIRAMix allows it to provide not only accurate estimates of global DSSF but also the direct and diffuse DSSF components, which are crucial radiative terms in many climatological applications. The implementation of SIRAMix is tested in the present article using atmospheric inputs from the European Center for Medium-Range Weather Forecasts (ECMWF). DSSF estimates provided by SIRAMix are compared against instantaneous DSSF measurements taken at several ground stations belonging to several radiation measurement networks. Results show an average root mean square error (RMSE) of 23.6 W m−2, 59.1 W m−2, and 44.9 W m−2 for global, direct, and diffuse DSSF, respectively. These scores decrease the average RMSE obtained for the current LSA-SAF product by 18.6%, which only provides global DSSF for the time being, and, to a lesser extent, for the state of the art in matter of DSSF retrieval (RMSE decrease of 10.9%, 6.5%, and 19.1% for global, direct, and diffuse DSSF with regard to the McClear algorithm). In addition to the retrieval of DSSF, SIRAMix is able to quantify the radiative forcing at the surface due to a given atmospheric component (e.g., gases or aerosols). The main limitation of the proposed approach is its high sensitivity to the quality of the ECMWF aerosol inputs, which is proved to be sufficiently accurate for reanalyses but not for forecasted data. This outcome will be taken into account in the forthcoming implementation of SIRAMix in the operational production chain of the LSA-SAF project.

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Estimating Surface Soil Heat Flux in Permafrost Regions Using Remote Sensing-Based Models on the Northern Qinghai-Tibetan Plateau under Clear-Sky Conditions

Remote Sensing ◽

10.3390/rs11040416 ◽

2019 ◽

Vol 11 (4) ◽

pp. 416 ◽

Cited By ~ 1

Author(s):

Cheng Yang ◽

Tonghua Wu ◽

Jiemin Wang ◽

Jimin Yao ◽

Ren Li ◽

...

Keyword(s):

Remote Sensing ◽

Land Surface ◽

Surface Soil ◽

Ground Surface ◽

Soil Heat Flux ◽

Parameterization Scheme ◽

Clear Sky ◽

Sky Conditions ◽

Permafrost Regions

The ground surface soil heat flux (G0) quantifies the energy transfer between the atmosphere and the ground through the land surface. However; it is difficult to obtain the spatial distribution of G0 in permafrost regions because of the limitation of in situ observation and complication of ground surface conditions. This study aims at developing an improved G0 parameterization scheme applicable to permafrost regions of the Qinghai-Tibet Plateau under clear-sky conditions. We validated several existing remote sensing-based models to estimate G0 by analyzing in situ measurement data. Based on the validation of previous models on G0; we added the solar time angle to the G0 parameterization scheme; which considered the phase difference problem. The maximum values of RMSE and MAE between “measured G0” and simulated G0 using the improved parameterization scheme and in situ data were calculated to be 6.102 W/m2 and 5.382 W/m2; respectively. When the error of the remotely sensed land surface temperature is less than 1 K and the surface albedo measured is less than 0.02; the accuracy of estimates based on remote sensing data for G0 will be less than 5%. MODIS data (surface reflectance; land surface temperature; and emissivity) were used to calculate G0 in a 10 x 10 km region around Tanggula site; which is located in the continuous permafrost region with long-term records of meteorological and permafrost parameters. The results obtained by the improved scheme and MODIS data were consistent with the observation. This study enhances our understanding of the impacts of climate change on the ground thermal regime of permafrost and the land surface processes between atmosphere and ground surface in cold regions.

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Direct Aerosol Radiative Forcing Uncertainty Based on a Radiative Perturbation Analysis

Journal of Climate ◽

10.1175/2010jcli3543.1 ◽

2010 ◽

Vol 23 (19) ◽

pp. 5288-5293 ◽

Cited By ~ 81

Author(s):

Norman G. Loeb ◽

Wenying Su

Keyword(s):

Radiative Forcing ◽

Single Scattering ◽

Single Scattering Albedo ◽

Aerosol Radiative Forcing ◽

Clear Sky ◽

Radiative Perturbation ◽

Sky Conditions ◽

Global Mean ◽

Aerosol Properties ◽

Aerosol Radiative

Abstract To provide a lower bound for the uncertainty in measurement-based clear- and all-sky direct aerosol radiative forcing (DARF), a radiative perturbation analysis is performed for the ideal case in which the perturbations in global mean aerosol properties are given by published values of systematic uncertainty in Aerosol Robotic Network (AERONET) aerosol measurements. DARF calculations for base-state climatological cloud and aerosol properties over ocean and land are performed, and then repeated after perturbing individual aerosol optical properties (aerosol optical depth, single-scattering albedo, asymmetry parameter, scale height, and anthropogenic fraction) from their base values, keeping all other parameters fixed. The total DARF uncertainty from all aerosol parameters combined is 0.5–1.0 W m−2, a factor of 2–4 greater than the value cited in the Intergovernmental Panel on Climate Change’s (IPCC’s) Fourth Assessment Report. Most of the total DARF uncertainty in this analysis is associated with single-scattering albedo uncertainty. Owing to the greater sensitivity to single-scattering albedo in cloudy columns, DARF uncertainty in all-sky conditions is greater than in clear-sky conditions, even though the global mean clear-sky DARF is more than twice as large as the all-sky DARF.

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Coupling Groundwater, Vegetation, and Atmospheric Processes: A Comparison of Two Integrated Models

Journal of Hydrometeorology ◽

10.1175/jhm-d-16-0159.1 ◽

2017 ◽

Vol 18 (5) ◽

pp. 1489-1511 ◽

Cited By ~ 17

Author(s):

Mauro Sulis ◽

John L. Williams ◽

Prabhakar Shrestha ◽

Malte Diederich ◽

Clemens Simmer ◽

...

Keyword(s):

Land Surface ◽

Convective Precipitation ◽

Atmospheric Processes ◽

Clear Sky ◽

The North ◽

Western Germany ◽

The Difference ◽

Heat And Moisture ◽

Sky Conditions ◽

Diagram Approach

Abstract This study compares two modeling platforms, ParFlow.WRF (PF.WRF) and the Terrestrial Systems Modeling Platform (TerrSysMP), with a common 3D integrated surface–groundwater model to examine the variability in simulated soil–vegetation–atmosphere interactions. Idealized and hindcast simulations over the North Rhine–Westphalia region in western Germany for clear-sky conditions and strong convective precipitation using both modeling platforms are presented. Idealized simulations highlight the strong variability introduced by the difference in land surface parameterizations (e.g., ground evaporation and canopy transpiration) and atmospheric boundary layer (ABL) schemes on the simulated land–atmosphere interactions. Results of the idealized simulations also suggest a different range of sensitivity in the two models of land surface and atmospheric parameterizations to water-table depth fluctuations. For hindcast simulations, both modeling platforms simulate net radiation and cumulative precipitation close to observed station data, while larger differences emerge between spatial patterns of soil moisture and convective rainfall due to the difference in the physical parameterization of the land surface and atmospheric component. This produces a different feedback by the hydrological model in the two platforms in terms of discharge over different catchments in the study area. Finally, an analysis of land surface and ABL heat and moisture budgets using the mixing diagram approach reveals different sensitivities of diurnal atmospheric processes to the groundwater parameterizations in both modeling platforms.

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Satellite-Based Estimation of Temporally Resolved Dust Radiative Forcing in Snow Cover

Journal of Hydrometeorology ◽

10.1175/jhm-d-15-0150.1 ◽

2016 ◽

Vol 17 (7) ◽

pp. 1999-2011 ◽

Cited By ~ 3

Author(s):

Steven D. Miller ◽

Fang Wang ◽

Ann B. Burgess ◽

S. McKenzie Skiles ◽

Matthew Rogers ◽

...

Keyword(s):

Solar Irradiance ◽

Radiative Forcing ◽

Hydrological Cycle ◽

Clear Sky ◽

Operational Management ◽

Moderate Resolution ◽

Resolution Imaging ◽

Moderate Resolution Imaging Spectroradiometer ◽

Sky Conditions

Abstract Runoff from mountain snowpack is an important freshwater supply for many parts of the world. The deposition of aeolian dust on snow decreases snow albedo and increases the absorption of solar irradiance. This absorption accelerates melting, impacting the regional hydrological cycle in terms of timing and magnitude of runoff. The Moderate Resolution Imaging Spectroradiometer (MODIS) Dust Radiative Forcing in Snow (MODDRFS) satellite product allows estimation of the instantaneous (at time of satellite overpass) surface radiative forcing caused by dust. While such snapshots are useful, energy balance modeling requires temporally resolved radiative forcing to represent energy fluxes to the snowpack, as modulated primarily by varying cloud cover. Here, the instantaneous MODDRFS estimate is used as a tie point to calculate temporally resolved surface radiative forcing. Dust radiative forcing scenarios were considered for 1) clear-sky conditions and 2) all-sky conditions using satellite-based cloud observations. Comparisons against in situ stations in the Rocky Mountains show that accounting for the temporally resolved all-sky solar irradiance via satellite retrievals yields a more representative time series of dust radiative effects compared to the clear-sky assumption. The modeled impact of dust on enhanced snowmelt was found to be significant, accounting for nearly 50% of the total melt at the more contaminated station sites. The algorithm is applicable to regional basins worldwide, bearing relevance to both climate process research and the operational management of water resources.

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Temporal heterogeneity in aerosol characteristics and the resulting radiative impacts at a tropical coastal station – Part 2: Direct short wave radiative forcing

Annales Geophysicae ◽

10.5194/angeo-25-2309-2007 ◽

2007 ◽

Vol 25 (11) ◽

pp. 2309-2320 ◽

Cited By ~ 45

Author(s):

S. Suresh Babu ◽

K. Krishna Moorthy ◽

S. K. Satheesh

Keyword(s):

Radiative Forcing ◽

Monsoon Season ◽

Short Wave ◽

Coastal Station ◽

Near Surface ◽

Aerosol Radiative Forcing ◽

Clear Sky ◽

Synoptic Conditions ◽

Post Monsoon Season ◽

Sky Conditions

Abstract. Seasonal distinctiveness in the microphysical and optical properties of columnar and near-surface (in the well mixed region) aerosols, associated with changes in the prevailing synoptic conditions, were delineated based on extensive (spread over 4 years) and collocated measurements at the tropical coastal location, Trivandrum (8.55° N; 76.97° E, 3 m a.m.s.l.), and the results were summarized in Part 1 of this two-part paper. In Part 2, we use these properties to develop empirical seasonal aerosol models, which represent the observed features fairly accurately, separately for winter monsoon season (WMS, December through March), inter-monsoon season (IMS, April and May), summer monsoon season (SMS, June through September) and post monsoon season (PMS, October and November). The models indicate a significant transformation in the aerosol environment from an anthropogenic-dominance in WMS to a natural-dominance in SMS. The modeled aerosol properties are used for estimating the direct, short wave aerosol radiative forcing, under clear-sky conditions. Our estimates show large seasonal changes. Under clear sky conditions, the daily averaged short-wave TOA forcing changes from its highest values during WMS, to the lowest values in SMS; this seasonal change being brought-in mainly by the reduction in the abundance and the mass fraction (to the composite) of black carbon aerosols and of accumulation mode aerosols. The resulting atmospheric forcing varies from the highest, (47 to 53 W m−2) in WMS to the lowest (22 to 26 W m−2) in SMS.

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McClear: a new model estimating downwelling solar radiation at ground level in clear-sky conditions

Atmospheric Measurement Techniques ◽

10.5194/amt-6-2403-2013 ◽

2013 ◽

Vol 6 (9) ◽

pp. 2403-2418 ◽

Cited By ~ 154

Author(s):

M. Lefèvre ◽

A. Oumbe ◽

P. Blanc ◽

B. Espinar ◽

B. Gschwind ◽

...

Keyword(s):

Correlation Coefficient ◽

Weather Prediction ◽

Ground Level ◽

Surface Radiation ◽

Radiative Transfer Model ◽

Transfer Model ◽

Clear Sky ◽

Sky Conditions ◽

Aerosol Properties

Abstract. A new fast clear-sky model called McClear was developed to estimate the downwelling shortwave direct and global irradiances received at ground level under clear skies. It is a fully physical model replacing empirical relations or simpler models used before. It exploits the recent results on aerosol properties, and total column content in water vapour and ozone produced by the MACC project (Monitoring Atmosphere Composition and Climate). It accurately reproduces the irradiance computed by the libRadtran reference radiative transfer model with a computational speed approximately 105 times greater by adopting the abaci, or look-up table, approach combined with interpolation functions. It is therefore suited for geostationary satellite retrievals or numerical weather prediction schemes with many pixels or grid points, respectively. McClear irradiances were compared to 1 min measurements made in clear-sky conditions at several stations within the Baseline Surface Radiation Network in various climates. The bias for global irradiance comprises between −6 and 25 W m−2. The RMSE ranges from 20 W m−2 (3% of the mean observed irradiance) to 36 W m−2 (5%) and the correlation coefficient ranges between 0.95 and 0.99. The bias for the direct irradiance comprises between −48 and +33 W m−2. The root mean square error (RMSE) ranges from 33 W m−2 (5%) to 64 W m−2 (10%). The correlation coefficient ranges between 0.84 and 0.98. This work demonstrates the quality of the McClear model combined with MACC products, and indirectly the quality of the aerosol properties modelled by the MACC reanalysis.

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Response of surface shortwave cloud radiative effect to greenhouse gases and aerosols and its impact on summer maximum temperature

Atmospheric Chemistry and Physics ◽

10.5194/acp-20-8251-2020 ◽

2020 ◽

Vol 20 (13) ◽

pp. 8251-8266 ◽

Cited By ~ 1

Author(s):

Tao Tang ◽

Drew Shindell ◽

Yuqiang Zhang ◽

Apostolos Voulgarakis ◽

Jean-Francois Lamarque ◽

...

Keyword(s):

Radiative Forcing ◽

Eastern China ◽

Global Climate Models ◽

Maximum Temperature ◽

Boreal Summer ◽

Daily Maximum Temperature ◽

Daily Maximum ◽

Sulfate Aerosols ◽

Clear Sky ◽

Sky Conditions

Abstract. Shortwave cloud radiative effects (SWCREs), defined as the difference of the shortwave radiative flux between all-sky and clear-sky conditions at the surface, have been reported to play an important role in influencing the Earth's energy budget and temperature extremes. In this study, we employed a set of global climate models to examine the SWCRE responses to CO2, black carbon (BC) aerosols, and sulfate aerosols in boreal summer over the Northern Hemisphere. We found that CO2 causes positive SWCRE changes over most of the NH, and BC causes similar positive responses over North America, Europe, and eastern China but negative SWCRE over India and tropical Africa. When normalized by effective radiative forcing, the SWCRE from BC is roughly 3–5 times larger than that from CO2. SWCRE change is mainly due to cloud cover changes resulting from changes in relative humidity (RH) and, to a lesser extent, changes in cloud liquid water, circulation, dynamics, and stability. The SWCRE response to sulfate aerosols, however, is negligible compared to that for CO2 and BC because part of the radiation scattered by clouds under all-sky conditions will also be scattered by aerosols under clear-sky conditions. Using a multilinear regression model, it is found that mean daily maximum temperature (Tmax) increases by 0.15 and 0.13 K per watt per square meter (W m−2) increase in local SWCRE under the CO2 and BC experiment, respectively. When domain-averaged, the contribution of SWCRE change to summer mean Tmax changes was 10 %–30 % under CO2 forcing and 30 %–50 % under BC forcing, varying by region, which can have important implications for extreme climatic events and socioeconomic activities.

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Using MODIS land surface temperatures and the Crocus snow model to understand the warm bias of ERA-Interim reanalyses at the surface in Antarctica

The Cryosphere Discussions ◽

10.5194/tcd-8-55-2014 ◽

2014 ◽

Vol 8 (1) ◽

pp. 55-84 ◽

Cited By ~ 3

Author(s):

H. Fréville ◽

E. Brun ◽

G. Picard ◽

N. Tatarinova ◽

L. Arnaud ◽

...

Keyword(s):

Surface Temperature ◽

Land Surface ◽

Data Set ◽

Warm Bias ◽

Clear Sky ◽

Surface Temperatures ◽

Stable Conditions ◽

Land Surface Temperatures ◽

Sky Conditions

Abstract. MODIS land surface temperatures in Antarctica were processed in order to produce a gridded data set at 25 km resolution, spanning the period 2000–2011 at an hourly time-step. The AQUA and TERRA orbits and MODIS swath width, combined with frequent clear-sky conditions, lead to very high availability of quality-controlled observations: on average, hourly data are available 14 h per day at the grid points around the South Pole and more than 9 over a large area of the Antarctic Plateau. Processed MODIS land surface temperatures, referred to hereinafter as MODIS Ts, were compared with in situ hourly measurements of surface temperature collected over the entire year 2009 by 7 stations from the BSRN and AWS networks. In spite of an occasional failure in the detection of clouds, MODIS Ts exhibit a good performance, with a bias ranging from −1.8 to 0.1 °C and errors ranging from 2.2 to 4.8 °C root mean square at the 5 stations located on the plateau. These results show that MODIS Ts can be used as a precise and accurate reference to test other surface temperature data sets. Here, we evaluate the performance of surface temperature in the ERA-Interim reanalysis. During conditions detected as cloud-free by MODIS, ERA-Interim shows a widespread warm bias in Antarctica in every season, ranging from +3 to +6 °C on the plateau. This confirms a recent study which showed that the largest discrepancies in 2 m air temperature between ERA-Interim and the HadCRUT4 data set occur in Antarctica. A comparison with in situ surface temperature shows that this bias is not strictly limited to clear-sky conditions. A detailed comparison with stand-alone simulations by the Crocus snowpack model, forced by ERA-Interim, and with the ERA-Interim/land simulations, shows that the warm bias may be due primarily to an overestimation of the surface turbulent fluxes in very stable conditions. Numerical experiments with Crocus show this is likely due to an overestimation of the surface exchange coefficients under very stable conditions.

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Using MODIS land surface temperatures and the Crocus snow model to understand the warm bias of ERA-Interim reanalyses at the surface in Antarctica

The Cryosphere ◽

10.5194/tc-8-1361-2014 ◽

2014 ◽

Vol 8 (4) ◽

pp. 1361-1373 ◽

Cited By ~ 40

Author(s):

H. Fréville ◽

E. Brun ◽

G. Picard ◽

N. Tatarinova ◽

L. Arnaud ◽

...

Keyword(s):

Surface Temperature ◽

Land Surface ◽

Data Set ◽

Surface Exchange ◽

Warm Bias ◽

Clear Sky ◽

Surface Temperatures ◽

Stable Conditions ◽

Land Surface Temperatures ◽

Sky Conditions

Abstract. Moderate-Resolution Imaging spectroradiometer (MODIS) land surface temperatures in Antarctica were processed in order to produce a gridded data set at 25 km resolution, spanning the period 2000–2011 at an hourly time step. The Aqua and Terra orbits and MODIS swath width, combined with frequent clear-sky conditions, lead to very high availability of quality-controlled observations: on average, hourly data are available 14 h per day at the grid points around the South Pole and more than 9 h over a large area of the Antarctic Plateau. Processed MODIS land surface temperatures, referred to hereinafter as MODIS Ts values, were compared with in situ hourly measurements of surface temperature collected over the entirety of the year 2009 by seven stations from the Baseline Surface Radiation Network (BSRN) and automatic weather stations (AWSs). In spite of an occasional failure in the detection of clouds, MODIS Ts values exhibit a good performance, with a bias ranging from −1.8 to 0.1 °C and errors ranging from 2.2 to 4.8 °C root mean square at the five stations located on the plateau. These results show that MODIS Ts values can be used as a precise and accurate reference to test other surface temperature data sets. Here, we evaluate the performance of surface temperature in the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis known as ERA-Interim reanalysis. During conditions detected as cloud free by MODIS, ERA-Interim shows a widespread warm bias in Antarctica in every season, ranging from +3 to +6 °C on the plateau. This confirms a recent study which showed that the largest discrepancies in 2 m air temperature between ERA-Interim and the global temperature data set HadCRUT4 compiled by the Met Office Hadley Centre and the University of East Anglia's Climatic Research Unit occur in Antarctica. A comparison with in situ surface temperature shows that this bias is not strictly limited to clear-sky conditions. A detailed comparison with stand-alone simulations by the Crocus snowpack model, forced by ERA-Interim, and with the ERA-Interim/land simulations, shows that the warm bias may be due primarily to an overestimation of the surface turbulent fluxes in very stable conditions. Numerical experiments with Crocus show that a small change in the parameterization of the effects of stability on the surface exchange coefficients can significantly impact the snow surface temperature. The ERA-Interim warm bias appears to be likely due to an overestimation of the surface exchange coefficients under very stable conditions.

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