scholarly journals Evaluation of Model-Predicted Top-of-Atmosphere Radiation and Cloud Parameters over Africa with Observations from GERB and SEVIRI

2011 ◽  
Vol 24 (15) ◽  
pp. 4015-4036 ◽  
Author(s):  
Wouter Greuell ◽  
Erik van Meijgaard ◽  
Nicolas Clerbaux ◽  
Jan Fokke Meirink
Keyword(s):  
Satellite Data ◽  
Climate Model ◽  
Longwave Radiation ◽  
Radiation Budget ◽  
Trade Wind ◽  
Water Path ◽  
Cloud Parameters ◽  
Cloud Properties ◽  
Condensed Water ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract This study compared the Regional Atmospheric Climate Model version 2 (RACMO) with satellite data by simultaneously looking at cloud properties and top-of-atmosphere (TOA) fluxes. This study used cloud properties retrieved from Spinning Enhanced Visible and Infrared Imager (SEVIRI) data and TOA shortwave and longwave outgoing radiative fluxes measured by one of the Geostationary Earth Radiation Budget (GERB) sensors. Both SEVIRI and GERB resolve the diurnal cycle extremely well with 96 images per day. To test the physical parameterizations of the model, RACMO was run for a domain-enclosing Africa and part of the surrounding oceans. Simulations for July 2006, forced at the lateral boundaries by ERA-Interim reanalyses, show generally accurate positioning of the various cloud regimes but also some important model–observation differences, which the authors tried to reduce by altering model parameterizations. These differences are as follows: 1) TOA albedo differences in clear-sky regions like the Sahara and southern Africa. These differences were considerably reduced by prescribing the surface albedo from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data. 2) A considerable overestimation of outgoing longwave radiation within the continental ITCZ caused by the fact that modeled cirrus clouds are far too thin. 3) Underestimation by the model of cloud cover, condensed water path and albedo of the stratocumulus fields off the coast of Angola. The authors reduced these underestimations by suppressing the amount of turbulent mixing above the boundary layer, by prescribing droplet radii derived from SEVIRI data, and by assuming in-cloud horizontal homogeneity for the radiation calculations. 4) Overestimation by the model of the albedo of the trade wind cumulus fields over the Atlantic Ocean. This study argues that this overestimation is likely caused by a model overestimation of condensed water path. In general, the analyses demonstrate the power of the simultaneous evaluation of the TOA fluxes and cloud properties.

Evaluation of the Daylight Cycle of Model-Predicted Cloud Amount and Condensed Water Path over Europe with Observations from MSG SEVIRI

2009 ◽  
Vol 22 (7) ◽  
pp. 1749-1766 ◽  
Author(s):  
R. A. Roebeling ◽  
E. van Meijgaard
Keyword(s):  
Diurnal Cycle ◽  
Climate Models ◽  
Climate Model ◽  
Cloud Amount ◽  
Daily Maximum ◽  
Accurate Information ◽  
Water Path ◽  
Cloud Properties ◽  
Condensed Water ◽  
The Mediterranean

Abstract The evaluation of the diurnal cycle of cloud amount (CA) and cloud condensed water path (CWP) as predicted by climate models receives relatively little attention, mostly because of the lack of observational data capturing the diurnal cycle of such quantities. The Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard the geostationary Meteosat-8 satellite is the first instrument able to provide accurate information on diurnal cycles during daylight hours of cloud properties over land and ocean surfaces. This paper evaluates the daylight cycle of CA and CWP as predicted by the Regional Atmospheric Climate Model version 2 (RACMO2), using corresponding SEVIRI retrievals. The study is done for Europe using hourly cloud properties retrievals from SEVIRI during the summer months from May to September 2004. The results of this study show that SEVIRI-retrieved daylight cycles of CA and CWP provide a powerful tool for identifying climate model deficiencies. Over Europe the SEVIRI retrievals of cloud condensed water paths comprise about 80% liquid water and about 20% ice water. The daylight cycles of CA and CWP from SEVIRI show large spatial variations in their mean values and time of daily maximum and daytime-normalized amplitude. In general, RACMO2 overestimates CWP by about 30% and underestimates CA by about 20% as compared to SEVIRI. The largest amplitudes are observed in the Mediterranean and northern Africa. For the greater part of the ocean and coastal areas the time of daily maximum CWP is found during morning, whereas over land this maximum is found after local solar noon. These features are reasonably well captured by RACMO2. In the Mediterranean and continental Europe RACMO2 tends to predict maximum CWP associated with convection to occur about two hours earlier than SEVIRI indicates.

scholarly journals The Climate Monitoring SAF Outgoing Longwave Radiation from AVHRR

2020 ◽  
Vol 12 (6) ◽  
pp. 929 ◽  
Author(s):  
Nicolas Clerbaux ◽  
Tom Akkermans ◽  
Edward Baudrez ◽  
Almudena Velazquez Blazquez ◽  
William Moutier ◽  
...  
Keyword(s):  
Outgoing Longwave Radiation ◽  
Radiant Energy ◽  
Longwave Radiation ◽  
Energy System ◽  
Radiation Budget ◽  
Climate Data ◽  
Night Time ◽  
Cloud Properties ◽  
Climate Monitoring ◽  
Orbital Drift

Data from the Advanced Very High Resolution Radiometer (AVHRR) have been used to create several long-duration data records of geophysical variables describing the atmosphere and land and water surfaces. In the Climate Monitoring Satellite Application Facility (CM SAF) project, AVHRR data are used to derive the Cloud, Albedo, and Radiation (CLARA) climate data records of radiation components (i.a., surface albedo) and cloud properties (i.a., cloud cover). This work describes the methodology implemented for the additional estimation of the Outgoing Longwave Radiation (OLR), an important Earth radiation budget component, that is consistent with the other CLARA variables. A first step is the estimation of the instantaneous OLR from the AVHRR observations. This is done by regressions on a large database of collocated observations between AVHRR Channel 4 (10.8 µm) and 5 (12 µm) and the OLR from the Clouds and Earth’s Radiant Energy System (CERES) instruments. We investigate the applicability of this method to the first generation of AVHRR instrument (AVHRR/1) for which no Channel 5 observation is available. A second step concerns the estimation of daily and monthly OLR from the instantaneous AVHRR overpasses. This step is especially important given the changes in the local time of the observations due to the orbital drift of the NOAA satellites. We investigate the use of OLR in the ERA5 reanalysis to estimate the diurnal variation. The developed approach proves to be valuable to model the diurnal change in OLR due to day/night time warming/cooling over clear land. Finally, the resulting monthly mean AVHRR OLR product is intercompared with the CERES monthly mean product. For a typical configuration with one morning and one afternoon AVHRR observation, the Root Mean Square (RMS) difference with CERES monthly mean OLR is about 2 Wm−2 at 1° × 1° resolution. We quantify the degradation of the OLR product when only one AVHRR instrument is available (as is the case for some periods in the 1980s) and also the improvement when more instruments are available (e.g., using METOP-A, NOAA-15, NOAA-18, and NOAA-19 in 2012). The degradation of the OLR product from AVHRR/1 instruments is also quantified, which is done by “masking” the Channel 5 observations.

scholarly journals Comparison of MODIS and VIIRS cloud properties with ARM ground-based observations over Finland

2016 ◽  
Vol 9 (7) ◽  
pp. 3193-3203 ◽  
Author(s):  
Moa K. Sporre ◽  
Ewan J. O'Connor ◽  
Nina Håkansson ◽  
Anke Thoss ◽  
Erik Swietlicki ◽  
...  
Keyword(s):  
Infrared Imaging ◽  
Microwave Radiometer ◽  
Single Layer ◽  
Radar Data ◽  
Liquid Water Path ◽  
Cloud Parameters ◽  
Cloud Properties ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Biogenic Aerosols ◽  
Cloud Mask

Abstract. Cloud retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments aboard the satellites Terra and Aqua and the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument aboard the Suomi-NPP satellite are evaluated using a combination of ground-based instruments providing vertical profiles of clouds. The ground-based measurements are obtained from the Atmospheric Radiation Measurement (ARM) programme mobile facility, which was deployed in Hyytiälä, Finland, between February and September 2014 for the Biogenic Aerosols – Effects on Clouds and Climate (BAECC) campaign. The satellite cloud parameters cloud top height (CTH) and liquid water path (LWP) are compared with ground-based CTH obtained from a cloud mask created using lidar and radar data and LWP acquired from a multi-channel microwave radiometer. Clouds from all altitudes in the atmosphere are investigated. The clouds are diagnosed as single or multiple layer using the ground-based cloud mask. For single-layer clouds, satellites overestimated CTH by 326 m (14 %) on average. When including multilayer clouds, satellites underestimated CTH by on average 169 m (5.8 %). MODIS collection 6 overestimated LWP by on average 13 g m−2 (11 %). Interestingly, LWP for MODIS collection 5.1 is slightly overestimated by Aqua (4.56 %) but is underestimated by Terra (14.3 %). This underestimation may be attributed to a known issue with a drift in the reflectance bands of the MODIS instrument on Terra. This evaluation indicates that the satellite cloud parameters selected show reasonable agreement with their ground-based counterparts over Finland, with minimal influence from the large solar zenith angle experienced by the satellites in this high-latitude location.

Use of satellite-based sensing in land surface climatology

1994 ◽  
Vol 18 (1) ◽  
pp. 1-15 ◽  
Author(s):  
David Greenland
Keyword(s):  
Satellite Data ◽  
Land Surface ◽  
Climate Models ◽  
Climate Model ◽  
Meteorological Data ◽  
Sensible Heat Flux ◽  
Longwave Radiation ◽  
Climate Modelling ◽  
Area Index ◽  
Surface Climate

Common types of satellite-derived measurements are reviewed with respect to how they are used to provide information on variables important to land surface climatology. The variables considered include solar radiation, surface albedo, surface temperature, outgoing longwave radiation, cloud cover, net radiation, soil moisture, latent and sensible heat flux, surface cover and leaf area index. A selection of land surface climate modelling schemes is identified and considered with a view to their practicality for use with satellite-derived data. Issues arising from the foregoing considerations include the absence from satellite data of some variables required by land surface climate models, the importance of extreme pixel values in model parameterization, the importance of matching spatial resolution in satellite data and climate model, and the need to have concurrent, independently observed, meteorological data in order to make full use of the satellite data.

scholarly journals Geostationary Enhanced Temporal Interpolation for CERES Flux Products

2013 ◽  
Vol 30 (6) ◽  
pp. 1072-1090 ◽  
Author(s):  
David R. Doelling ◽  
Norman G. Loeb ◽  
Dennis F. Keyes ◽  
Michele L. Nordeen ◽  
Daniel Morstad ◽  
...  
Keyword(s):  
Global Climate ◽  
Radiant Energy ◽  
Energy System ◽  
Radiation Budget ◽  
Cloud Properties ◽  
Marine Stratus ◽  
Temporal Interpolation ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Observation Times

Abstract The Clouds and the Earth’s Radiant Energy System (CERES) instruments on board the Terra and Aqua spacecraft continue to provide an unprecedented global climate record of the earth’s top-of-atmosphere (TOA) energy budget since March 2000. A critical step in determining accurate daily averaged flux involves estimating the flux between CERES Terra or Aqua overpass times. CERES employs the CERES-only (CO) and the CERES geostationary (CG) temporal interpolation methods. The CO method assumes that the cloud properties at the time of the CERES observation remain constant and that it only accounts for changes in albedo with solar zenith angle and diurnal land heating, by assuming a shape for unresolved changes in the diurnal cycle. The CG method enhances the CERES data by explicitly accounting for changes in cloud and radiation between CERES observation times using 3-hourly imager data from five geostationary (GEO) satellites. To maintain calibration traceability, GEO radiances are calibrated against Moderate Resolution Imaging Spectroradiometer (MODIS) and the derived GEO fluxes are normalized to the CERES measurements. While the regional (1° latitude × 1° longitude) monthly-mean difference between the CG and CO methods can exceed 25 W m−2 over marine stratus and land convection, these regional biases nearly cancel in the global mean. The regional monthly CG shortwave (SW) and longwave (LW) flux uncertainty is reduced by 20%, whereas the daily uncertainty is reduced by 50% and 20%, respectively, over the CO method, based on comparisons with 15-min Geostationary Earth Radiation Budget (GERB) data.

scholarly journals Analysis of geostationary satellite derived cloud parameters associated with high ice water content environments

2016 ◽  
Author(s):  
Adrianus de Laat ◽  
Eric Defer ◽  
Julien Delanoë ◽  
Fabien Dezitter ◽  
Amanda Gounou ◽  
...  
Keyword(s):  
Water Content ◽  
Cloud Parameters ◽  
Cloud Properties ◽  
Infrared Imager ◽  
Aviation Hazards ◽  
Ice Water Content ◽  
Condensed Water ◽  
Convective Cells ◽  
Cloud Ice ◽  
Ice Water

Abstract. We present a newly developed high ice water content mask (High IWC) based on measurements of the cloud physical properties (CPP) algorithm applied to the geostationary Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI). The mask was developed within the European High Altitude Ice Crystals (HAIC) project for detection of upper atmospheric high IWC, which can be a hazard for aviation. Evaluation of the High IWC mask with satellite measurements of active remote sensors of cloud properties (CLOUDSAT/CALIPSO combined in the DARDAR product) shows that the High IWC mask can be fine-tuned for detection of high IWC values > 1 g/m3 in the DARDAR profiles. The best CPP predictors of High IWC were the condensed water path, cloud optical thickness, cloud phase, and cloud top height. The evaluation of the High IWC mask against DARDAR provided some indications that the MSG-CPP High IWC mask is more sensitive to cloud ice or cloud water in the upper part of the cloud, which is relevant for aviation purposes. Biases in the CPP results were also identified, in particular a solar zenith angle (SZA) dependence that reduces the performance of the High IWC mask for SZAs > 60°. Verification statistics show that for the detection of High IWC a trade-off has to be made between better detection of High IWC scenes and more false detections, i.e. scenes identified by the High IWC mask that do not contain IWC > 1 g/m3. However, the large majority of these detections still contain IWC values between 0.1–1 g/m3. Comparison of the High IEC mask against results from the Rapid Developing Thunderstorm (RDT) algorithm applied to the same geostationary SEVIRI data showed that there are similarities and differences with the High IWC mask: the RDT algorithm is very capable of detection young/new convective cells and areas, whereas the High IWC mask appears to be better capable of detecting more mature and ageing convection as well as cirrus remnants. The lack of detailed understanding what causes aviation hazards related to High IWC hampers further tuning of the High IWC mask. Additional evaluation of the High IWC mask against field campaign data should provide more information on the performance of the MSG-CPP High IWC mask and contribute to a better characterization.

scholarly journals Retrieval of microphysical cloud parameters from EM-FTIR spectra measured in Arctic summer 2017

2020 ◽  
Author(s):  
Philipp Richter ◽  
Mathias Palm ◽  
Christine Weinzierl ◽  
Hannes Griesche ◽  
Penny M. Rowe ◽  
...  
Keyword(s):  
Microwave Radiometer ◽  
High Sensitivity ◽  
Cloud Water ◽  
The Arctic ◽  
Droplet Radius ◽  
Spectral Radiance ◽  
Water Path ◽  
Cloud Parameters ◽  
Infrared Spectral ◽  
Condensed Water

Abstract. Infrared spectral radiances of optically thin clouds show high sensitivity to changes of the microphysical cloud parameters. Therefore, measurements of infrared spectral radiance of clouds in the spectral range from 770.9 cm−1 to 1163.4 cm−1 using a mobile Fourier Transform Infrared spectrometer were performed on the German research vessel Polarstern in the Arctic in summer 2017. A new retrieval for microphysical cloud parameters of optically thin clouds called Total Cloud Water retrieval, designed to retrieve cloud water optical depth τcw, total effective droplet radius rtotal and condensed water path CWP from infrared spectral radiances without the incorporation of spectral radiances in the far-infrared below 600cm−1, has been developed for application on radiances from the measurement campaign. Validation is performed against derived quantities from a combined cloud radar, lidar and microwave radiometer measurement synergy retrieval, called Cloudnet, performed by the Leibnitz Institute for Trospheric Research. Applied to spectral radiances of synthetic testcases, Total Cloud Water retrieval shows a high ability to retrieve τcw with a correlation of |r| = 0.98, as well as to retrieve CWP with |r| = 0.95 and rtotal with |r| = 0.86. Using the dataset from the campaign, a comparison between CWP from Total Cloud Water retrieval and Cloudnet was performed and showed a correlation of |r| = 0.81. In conclusion, the comparison to artificial clouds and the validation using Cloudnet showed that Total Cloud Water retrieval is able to retrieve the condensed water path from clouds for optically thin clouds and makes it a useful complementation for thin clouds to existing microwave-based measurements.

scholarly journals A dataset of microphysical cloud parameters, retrieved from Emission-FTIR spectra measured in Arctic summer 2017

2021 ◽  
Author(s):  
Philipp Richter ◽  
Mathias Palm ◽  
Christine Weinzierl ◽  
Hannes Griesche ◽  
Penny M. Rowe ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Infrared Spectra ◽  
Liquid Water ◽  
Microwave Radiometer ◽  
The Arctic ◽  
Liquid Water Path ◽  
Water Path ◽  
Cloud Parameters ◽  
Cloud Properties ◽  
Infrared Spectral

Abstract. A dataset of microphysical cloud parameters from optically thin clouds, retrieved from infrared spectral radiances measured in summer 2017 in the Arctic, is presented. Measurements were conducted using a mobile Fourier-transform infrared (FTIR) spectrometer which was carried by the RV Polarstern. This dataset contains retrieved optical depths and effective radii of ice and water, from which the liquid water path and ice water path are calculated. These water paths and the effective radii are compared with derived quantities from a combined cloud radar, lidar and microwave radiometer measurement synergy retrieval, called Cloudnet. Comparing the liquid water paths from the infrared retrieval and Cloudnet shows significant correlations with a standard deviation of 8.60 g · m−2. Although liquid water path retrievals from microwave radiometer data come with a uncertainty of at least 20 g · m−2, a significant correlation and a standard deviation of 5.32 g · m−2 between the results of clouds with a liquid water path of at most 20 g · m−2 retrieved from infrared spectra and results from Cloudnet can be seen. Therefore, despite its large uncertainty, the comparison with data retrieved from infrared spectra shows that optically thin clouds of the measurement campaign in summer 2017 can be observed well using microwave radiometers within the Cloudnet framework. Apart from this, the dataset of microphysical cloud properties presented here allows to perform calculations of the cloud radiative effects, when the Cloudnet data from the campaign are not available, which was from the 22nd July 2017 until the 19th August 2017. The dataset is published at Pangaea (Richter et al., 2021).

scholarly journals Examination of POLDER/PARASOL and MODIS/Aqua Cloud Fractions and Properties Representativeness

2011 ◽  
Vol 24 (16) ◽  
pp. 4435-4450 ◽  
Author(s):  
Shan Zeng ◽  
Frédéric Parol ◽  
Jérôme Riedi ◽  
Céline Cornet ◽  
François Thieuleux
Keyword(s):  
Cloud Cover ◽  
Temporal Variations ◽  
Cloud Fraction ◽  
Atmospheric Sciences ◽  
Cloud Parameters ◽  
Cloud Properties ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Level 2

Abstract The Polarization and Anisotropy of Reflectances for Atmospheric Sciences Coupled with Observations from a Lidar (PARASOL) and Aqua are two satellites on sun-synchronous orbits in the A-Train constellation. Aboard these two platforms, the Polarization and Directionality of Earth Reflectances (POLDER) and Moderate Resolution Imaging Spectroradiometer (MODIS) provide quasi simultaneous and coincident observations of cloud properties. The similar orbits but different detecting characteristics of these two sensors call for a comparison between the derived datasets to identify and quantify potential uncertainties in retrieved cloud properties. To focus on the differences due to different sensor spatial resolution and coverage, while minimizing sampling and weighting issues, the authors have recomputed monthly statistics directly from the respective official level-2 products. The authors have developed a joint dataset that contains both POLDER and MODIS level-2 cloud products collocated on a common sinusoidal grid. The authors have then computed and analyzed monthly statistics of cloud fractions corresponding either to the total cloud cover or to the “retrieved” cloud fraction for which cloud optical properties are derived. These simple yet crucial cloud statistics need to be clearly understood to allow further comparison work of the other cloud parameters. From this study, it is demonstrated that on average POLDER and MODIS datasets capture correctly the main characteristics of global cloud cover and provide similar spatial distributions and temporal variations. However, each sensor has its own advantages and weaknesses in discriminating between clear and cloudy skies in particular situations. Also it is shown that significant differences exist between the MODIS total cloud fraction (day mean) and the “retrieved” cloud fraction (combined mean). This study found a global negative difference of about 10% between POLDER and MODIS day-mean cloud fraction. On the contrary, a global positive difference of about 10% exists between POLDER and MODIS combined-mean cloud fraction. These statistical biases show both global and regional distributions that can be driven by sensors characteristics, environmental factors, and also carry potential information on cloud cover structure. These results provide information on the quality of cloud cover derived from POLDER and MODIS and should be taken into account for the use of other cloud products.

scholarly journals Spatial variability of the sea-ice radiation budget and its effect on aggregate-area fluxes

2001 ◽  
Vol 33 ◽  
pp. 248-252 ◽  
Author(s):  
Xuanji Wang ◽  
Jeffrey R. Key
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Climate Model ◽  
Radiative Properties ◽  
Radiation Budget ◽  
Small Scale ◽  
Spatial And Temporal Variability ◽  
Radiative Fluxes ◽  
Cloud Properties ◽  
Longwave Flux

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.

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