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- Author or Editor: Norman G. Loeb x
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Abstract
Despite recent improvements in satellite instrument calibration and the algorithms used to determine reflected solar (SW) and emitted thermal (LW) top-of-atmosphere (TOA) radiative fluxes, a sizeable imbalance persists in the average global net radiation at the TOA from satellite observations. This imbalance is problematic in applications that use earth radiation budget (ERB) data for climate model evaluation, estimate the earth’s annual global mean energy budget, and in studies that infer meridional heat transports. This study provides a detailed error analysis of TOA fluxes based on the latest generation of Clouds and the Earth’s Radiant Energy System (CERES) gridded monthly mean data products [the monthly TOA/surface averages geostationary (SRBAVG-GEO)] and uses an objective constrainment algorithm to adjust SW and LW TOA fluxes within their range of uncertainty to remove the inconsistency between average global net TOA flux and heat storage in the earth–atmosphere system. The 5-yr global mean CERES net flux from the standard CERES product is 6.5 W m−2, much larger than the best estimate of 0.85 W m−2 based on observed ocean heat content data and model simulations. The major sources of uncertainty in the CERES estimate are from instrument calibration (4.2 W m−2) and the assumed value for total solar irradiance (1 W m−2). After adjustment, the global mean CERES SW TOA flux is 99.5 W m−2, corresponding to an albedo of 0.293, and the global mean LW TOA flux is 239.6 W m−2. These values differ markedly from previously published adjusted global means based on the ERB Experiment in which the global mean SW TOA flux is 107 W m−2 and the LW TOA flux is 234 W m−2.
Abstract
Despite recent improvements in satellite instrument calibration and the algorithms used to determine reflected solar (SW) and emitted thermal (LW) top-of-atmosphere (TOA) radiative fluxes, a sizeable imbalance persists in the average global net radiation at the TOA from satellite observations. This imbalance is problematic in applications that use earth radiation budget (ERB) data for climate model evaluation, estimate the earth’s annual global mean energy budget, and in studies that infer meridional heat transports. This study provides a detailed error analysis of TOA fluxes based on the latest generation of Clouds and the Earth’s Radiant Energy System (CERES) gridded monthly mean data products [the monthly TOA/surface averages geostationary (SRBAVG-GEO)] and uses an objective constrainment algorithm to adjust SW and LW TOA fluxes within their range of uncertainty to remove the inconsistency between average global net TOA flux and heat storage in the earth–atmosphere system. The 5-yr global mean CERES net flux from the standard CERES product is 6.5 W m−2, much larger than the best estimate of 0.85 W m−2 based on observed ocean heat content data and model simulations. The major sources of uncertainty in the CERES estimate are from instrument calibration (4.2 W m−2) and the assumed value for total solar irradiance (1 W m−2). After adjustment, the global mean CERES SW TOA flux is 99.5 W m−2, corresponding to an albedo of 0.293, and the global mean LW TOA flux is 239.6 W m−2. These values differ markedly from previously published adjusted global means based on the ERB Experiment in which the global mean SW TOA flux is 107 W m−2 and the LW TOA flux is 234 W m−2.
Abstract
Cloud macrophysical changes over the Pacific Ocean from 2007 to 2017 are examined by combining CALIPSO and CloudSat (CALCS) active-sensor measurements, and these are compared with MODIS passive-sensor observations. Both CALCS and MODIS capture well-known features of cloud changes over the Pacific associated with meteorological conditions during El Niño–Southern Oscillation (ENSO) events. For example, midcloud (cloud tops at 3–10 km) and high cloud (cloud tops at 10–18 km) amounts increase with relative humidity (RH) anomalies. However, a better correlation is obtained between CALCS cloud volume and RH anomalies, confirming more accurate CALCS cloud boundaries than MODIS. Both CALCS and MODIS show that low cloud (cloud tops at 0–3 km) amounts increase with EIS and decrease with SST over the eastern Pacific, consistent with earlier studies. It is also further shown that the low cloud amounts do not increase with positive EIS anomalies if SST anomalies are positive. While similar features are found between CALCS and MODIS low cloud anomalies, differences also exist. First, relative to CALCS, MODIS shows stronger anticorrelation between low and mid/high cloud anomalies over the central and western Pacific, which is largely due to the limitation in detecting overlapping clouds from passive MODIS measurements. Second, relative to CALCS, MODIS shows smaller impacts of mid- and high clouds on the low troposphere (<3 km). The differences are due to the underestimation of MODIS cloud layer thicknesses of mid- and high clouds.
Abstract
Cloud macrophysical changes over the Pacific Ocean from 2007 to 2017 are examined by combining CALIPSO and CloudSat (CALCS) active-sensor measurements, and these are compared with MODIS passive-sensor observations. Both CALCS and MODIS capture well-known features of cloud changes over the Pacific associated with meteorological conditions during El Niño–Southern Oscillation (ENSO) events. For example, midcloud (cloud tops at 3–10 km) and high cloud (cloud tops at 10–18 km) amounts increase with relative humidity (RH) anomalies. However, a better correlation is obtained between CALCS cloud volume and RH anomalies, confirming more accurate CALCS cloud boundaries than MODIS. Both CALCS and MODIS show that low cloud (cloud tops at 0–3 km) amounts increase with EIS and decrease with SST over the eastern Pacific, consistent with earlier studies. It is also further shown that the low cloud amounts do not increase with positive EIS anomalies if SST anomalies are positive. While similar features are found between CALCS and MODIS low cloud anomalies, differences also exist. First, relative to CALCS, MODIS shows stronger anticorrelation between low and mid/high cloud anomalies over the central and western Pacific, which is largely due to the limitation in detecting overlapping clouds from passive MODIS measurements. Second, relative to CALCS, MODIS shows smaller impacts of mid- and high clouds on the low troposphere (<3 km). The differences are due to the underestimation of MODIS cloud layer thicknesses of mid- and high clouds.
Abstract
Clouds and the Earth's Radiant Energy System (CERES) investigates the critical role that clouds and aerosols play in modulating the radiative energy flow within the Earth–atmosphere system. CERES builds upon the foundation laid by previous missions, such as the Earth Radiation Budget Experiment, to provide highly accurate top-of-atmosphere (TOA) radiative fluxes together with coincident cloud and aerosol properties inferred from high-resolution imager measurements. This paper describes the method used to construct empirical angular distribution models (ADMs) for estimating shortwave, longwave, and window TOA radiative fluxes from CERES radiance measurements on board the Tropical Rainfall Measuring Mission satellite. To construct the ADMs, multiangle CERES measurements are combined with coincident high-resolution Visible Infrared Scanner measurements and meteorological parameters from the European Centre for Medium-Range Weather Forecasts data assimilation product. The ADMs are stratified by scene types defined by parameters that have a strong influence on the angular dependence of Earth's radiation field at the TOA. Examples of how the new CERES ADMs depend upon the imager-based parameters are provided together with comparisons with existing models.
Abstract
Clouds and the Earth's Radiant Energy System (CERES) investigates the critical role that clouds and aerosols play in modulating the radiative energy flow within the Earth–atmosphere system. CERES builds upon the foundation laid by previous missions, such as the Earth Radiation Budget Experiment, to provide highly accurate top-of-atmosphere (TOA) radiative fluxes together with coincident cloud and aerosol properties inferred from high-resolution imager measurements. This paper describes the method used to construct empirical angular distribution models (ADMs) for estimating shortwave, longwave, and window TOA radiative fluxes from CERES radiance measurements on board the Tropical Rainfall Measuring Mission satellite. To construct the ADMs, multiangle CERES measurements are combined with coincident high-resolution Visible Infrared Scanner measurements and meteorological parameters from the European Centre for Medium-Range Weather Forecasts data assimilation product. The ADMs are stratified by scene types defined by parameters that have a strong influence on the angular dependence of Earth's radiation field at the TOA. Examples of how the new CERES ADMs depend upon the imager-based parameters are provided together with comparisons with existing models.
Clouds and the Earth’s Radiant Energy System (CERES) FluxByCldTyp Edition 4 Data ProductAbstract
The Clouds and the Earth’s Radiant Energy System (CERES) project has provided the climate community 20 years of globally observed top of the atmosphere (TOA) fluxes critical for climate and cloud feedback studies. The CERES Flux By Cloud Type (FBCT) product contains radiative fluxes by cloud type, which can provide more stringent constraints when validating models and also reveal more insight into the interactions between clouds and climate. The FBCT product provides 1° regional daily and monthly shortwave (SW) and longwave (LW) cloud-type fluxes and cloud properties sorted by seven pressure layers and six optical depth bins. Historically, cloud-type fluxes have been computed using radiative transfer models based on observed cloud properties. Instead of relying on radiative transfer models, the FBCT product utilizes Moderate Resolution Imaging Spectroradiometer (MODIS) radiances partitioned by cloud type within a CERES footprint to estimate the cloud-type broadband fluxes. The MODIS multichannel derived broadband fluxes were compared with the CERES observed footprint fluxes and were found to be within 1% and 2.5% for LW and SW, respectively, as well as being mostly free of cloud property dependencies. These biases are mitigated by constraining the cloud-type fluxes within each footprint with the CERES Single Scanner Footprint (SSF) observed flux. The FBCT all-sky and clear-sky monthly averaged fluxes were found to be consistent with the CERES SSF1deg product. Several examples of FBCT data are presented to highlight its utility for scientific applications.
Abstract
The Clouds and the Earth’s Radiant Energy System (CERES) project has provided the climate community 20 years of globally observed top of the atmosphere (TOA) fluxes critical for climate and cloud feedback studies. The CERES Flux By Cloud Type (FBCT) product contains radiative fluxes by cloud type, which can provide more stringent constraints when validating models and also reveal more insight into the interactions between clouds and climate. The FBCT product provides 1° regional daily and monthly shortwave (SW) and longwave (LW) cloud-type fluxes and cloud properties sorted by seven pressure layers and six optical depth bins. Historically, cloud-type fluxes have been computed using radiative transfer models based on observed cloud properties. Instead of relying on radiative transfer models, the FBCT product utilizes Moderate Resolution Imaging Spectroradiometer (MODIS) radiances partitioned by cloud type within a CERES footprint to estimate the cloud-type broadband fluxes. The MODIS multichannel derived broadband fluxes were compared with the CERES observed footprint fluxes and were found to be within 1% and 2.5% for LW and SW, respectively, as well as being mostly free of cloud property dependencies. These biases are mitigated by constraining the cloud-type fluxes within each footprint with the CERES Single Scanner Footprint (SSF) observed flux. The FBCT all-sky and clear-sky monthly averaged fluxes were found to be consistent with the CERES SSF1deg product. Several examples of FBCT data are presented to highlight its utility for scientific applications.
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.
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.
Abstract
Observations from the Clouds and the Earth’s Radiant Energy System (CERES), Moderate Resolution Imaging Spectroradiometer (MODIS), Multiangle Imaging Spectroradiometer (MISR), and Sea-Viewing Wide-Field-of-View Sensor (SeaWiFS) between 2000 and 2005 are analyzed in order to determine if these data are meeting climate accuracy goals recently established by the climate community. The focus is primarily on top-of-atmosphere (TOA) reflected solar radiances and radiative fluxes. Direct comparisons of nadir radiances from CERES, MODIS, and MISR aboard the Terra satellite reveal that the measurements from these instruments exhibit a year-to-year relative stability of better than 1%, with no systematic change with time. By comparison, the climate requirement for the stability of visible radiometer measurements is 1% decade−1. When tropical ocean monthly anomalies in shortwave (SW) TOA radiative fluxes from CERES on Terra are compared with anomalies in Photosynthetically Active Radiation (PAR) from SeaWiFS—an instrument whose radiance stability is better than 0.07% during its first six years in orbit—the two are strongly anticorrelated. After scaling the SeaWiFS anomalies by a constant factor given by the slope of the regression line fit between CERES and SeaWiFS anomalies, the standard deviation in the difference between monthly anomalies from the two records is only 0.2 W m−2, and the difference in their trend lines is only 0.02 ± 0.3 W m−2 decade−1, approximately within the 0.3 W m−2 decade−1 stability requirement for climate accuracy. For both the Tropics and globe, CERES Terra SW TOA fluxes show no trend between March 2000 and June 2005. Significant differences are found between SW TOA flux trends from CERES Terra and CERES Aqua between August 2002 and March 2005. This discrepancy is due to uncertainties in the adjustment factors used to account for degradation of the CERES Aqua optics during hemispheric scan mode operations. Comparisons of SW TOA flux between CERES Terra and the International Satellite Cloud Climatology Project (ISCCP) radiative flux profile dataset (FD) RadFlux product show good agreement in monthly anomalies between January 2002 and December 2004, and poor agreement prior to this period. Commonly used statistical tools applied to the CERES Terra data reveal that in order to detect a statistically significant trend of magnitude 0.3 W m−2 decade−1 in global SW TOA flux, approximately 10 to 15 yr of data are needed. This assumes that CERES Terra instrument calibration remains highly stable, long-term climate variability remains constant, and the Terra spacecraft has enough fuel to last 15 yr.
Abstract
Observations from the Clouds and the Earth’s Radiant Energy System (CERES), Moderate Resolution Imaging Spectroradiometer (MODIS), Multiangle Imaging Spectroradiometer (MISR), and Sea-Viewing Wide-Field-of-View Sensor (SeaWiFS) between 2000 and 2005 are analyzed in order to determine if these data are meeting climate accuracy goals recently established by the climate community. The focus is primarily on top-of-atmosphere (TOA) reflected solar radiances and radiative fluxes. Direct comparisons of nadir radiances from CERES, MODIS, and MISR aboard the Terra satellite reveal that the measurements from these instruments exhibit a year-to-year relative stability of better than 1%, with no systematic change with time. By comparison, the climate requirement for the stability of visible radiometer measurements is 1% decade−1. When tropical ocean monthly anomalies in shortwave (SW) TOA radiative fluxes from CERES on Terra are compared with anomalies in Photosynthetically Active Radiation (PAR) from SeaWiFS—an instrument whose radiance stability is better than 0.07% during its first six years in orbit—the two are strongly anticorrelated. After scaling the SeaWiFS anomalies by a constant factor given by the slope of the regression line fit between CERES and SeaWiFS anomalies, the standard deviation in the difference between monthly anomalies from the two records is only 0.2 W m−2, and the difference in their trend lines is only 0.02 ± 0.3 W m−2 decade−1, approximately within the 0.3 W m−2 decade−1 stability requirement for climate accuracy. For both the Tropics and globe, CERES Terra SW TOA fluxes show no trend between March 2000 and June 2005. Significant differences are found between SW TOA flux trends from CERES Terra and CERES Aqua between August 2002 and March 2005. This discrepancy is due to uncertainties in the adjustment factors used to account for degradation of the CERES Aqua optics during hemispheric scan mode operations. Comparisons of SW TOA flux between CERES Terra and the International Satellite Cloud Climatology Project (ISCCP) radiative flux profile dataset (FD) RadFlux product show good agreement in monthly anomalies between January 2002 and December 2004, and poor agreement prior to this period. Commonly used statistical tools applied to the CERES Terra data reveal that in order to detect a statistically significant trend of magnitude 0.3 W m−2 decade−1 in global SW TOA flux, approximately 10 to 15 yr of data are needed. This assumes that CERES Terra instrument calibration remains highly stable, long-term climate variability remains constant, and the Terra spacecraft has enough fuel to last 15 yr.
Abstract
Longwave (LW) spectral flux and cloud radiative effect (CRE) are important for understanding the earth’s radiation budget and cloud–radiation interaction. Here, the authors extend their previous algorithms to collocated Atmospheric Infrared Sounder (AIRS) and Cloud and the Earth’s Radiant Energy System (CERES) observations over the entire globe and show that the algorithms yield consistently good performances for measurements over both land and ocean. As a result, the authors are able to derive spectral flux and CRE at 10-cm−1 intervals over the entire LW spectrum from all currently available collocated AIRS and CERES observations. Using this multiyear dataset, they delineate the climatology of spectral CRE, including the far IR, over the entire globe as well as in different climate zones. Furthermore, the authors define two quantities, IR-effective cloud-top height (CTHeff) and cloud amount (CAeff), based on the monthly-mean spectral (or band by band) CRE. Comparisons with cloud fields retrieved by the CERES–Moderate Resolution Imaging Spectroradiometer (MODIS) algorithm indicate that, under many circumstances, the CTHeff and CAeff can be related to the physical retrievals of CTH and CA and thus can enhance understandings of model deficiencies in LW radiation budgets and cloud fields. Using simulations from the GFDL global atmosphere model, version 2 (AM2); NASA’s Goddard Earth Observing System, version 5 (GEOS-5); and Environment Canada’s Canadian Centre for Climate Modelling and Analysis (CCCma) Fourth Generation Canadian Atmospheric General Circulation Model (CanAM4) as case studies, the authors further demonstrate the merits of the CTHeff and CAeff concepts in providing insights on global climate model evaluations that cannot be obtained solely from broadband LW flux and CRE comparisons.
Abstract
Longwave (LW) spectral flux and cloud radiative effect (CRE) are important for understanding the earth’s radiation budget and cloud–radiation interaction. Here, the authors extend their previous algorithms to collocated Atmospheric Infrared Sounder (AIRS) and Cloud and the Earth’s Radiant Energy System (CERES) observations over the entire globe and show that the algorithms yield consistently good performances for measurements over both land and ocean. As a result, the authors are able to derive spectral flux and CRE at 10-cm−1 intervals over the entire LW spectrum from all currently available collocated AIRS and CERES observations. Using this multiyear dataset, they delineate the climatology of spectral CRE, including the far IR, over the entire globe as well as in different climate zones. Furthermore, the authors define two quantities, IR-effective cloud-top height (CTHeff) and cloud amount (CAeff), based on the monthly-mean spectral (or band by band) CRE. Comparisons with cloud fields retrieved by the CERES–Moderate Resolution Imaging Spectroradiometer (MODIS) algorithm indicate that, under many circumstances, the CTHeff and CAeff can be related to the physical retrievals of CTH and CA and thus can enhance understandings of model deficiencies in LW radiation budgets and cloud fields. Using simulations from the GFDL global atmosphere model, version 2 (AM2); NASA’s Goddard Earth Observing System, version 5 (GEOS-5); and Environment Canada’s Canadian Centre for Climate Modelling and Analysis (CCCma) Fourth Generation Canadian Atmospheric General Circulation Model (CanAM4) as case studies, the authors further demonstrate the merits of the CTHeff and CAeff concepts in providing insights on global climate model evaluations that cannot be obtained solely from broadband LW flux and CRE comparisons.
Abstract
The emerging picture of frontal scale air–sea interaction derived from high-resolution satellite observations of surface winds and sea surface temperature (SST) provides a unique opportunity to test the fidelity of high-resolution coupled climate simulations. Initial analysis of the output of a suite of Community Climate System Model (CCSM) experiments indicates that characteristics of frontal scale ocean–atmosphere interaction, such as the positive correlation between SST and surface wind stress, are realistically captured only when the ocean component is eddy resolving. The strength of the coupling between SST and surface stress is weaker than observed, however, as has been found previously for numerical weather prediction models and other coupled climate models. The results are similar when the atmospheric component model grid resolution is doubled from 0.5° to 0.25°, an indication that shortcomings in the representation of subgrid scale atmospheric planetary boundary layer processes, rather than resolved scale processes, are responsible for the weakness of the coupling. In the coupled model solutions the response to mesoscale SST features is strongest in the atmospheric boundary layer, but there is a deeper reaching response of the atmospheric circulation apparent in free tropospheric clouds. This simulated response is shown to be consistent with satellite estimates of the relationship between mesoscale SST and all-sky albedo.
Abstract
The emerging picture of frontal scale air–sea interaction derived from high-resolution satellite observations of surface winds and sea surface temperature (SST) provides a unique opportunity to test the fidelity of high-resolution coupled climate simulations. Initial analysis of the output of a suite of Community Climate System Model (CCSM) experiments indicates that characteristics of frontal scale ocean–atmosphere interaction, such as the positive correlation between SST and surface wind stress, are realistically captured only when the ocean component is eddy resolving. The strength of the coupling between SST and surface stress is weaker than observed, however, as has been found previously for numerical weather prediction models and other coupled climate models. The results are similar when the atmospheric component model grid resolution is doubled from 0.5° to 0.25°, an indication that shortcomings in the representation of subgrid scale atmospheric planetary boundary layer processes, rather than resolved scale processes, are responsible for the weakness of the coupling. In the coupled model solutions the response to mesoscale SST features is strongest in the atmospheric boundary layer, but there is a deeper reaching response of the atmospheric circulation apparent in free tropospheric clouds. This simulated response is shown to be consistent with satellite estimates of the relationship between mesoscale SST and all-sky albedo.
Abstract
The cloud radiative effect (CRE) of each longwave (LW) absorption band of a GCM’s radiation code is uniquely valuable for GCM evaluation because 1) comparing band-by-band CRE avoids the compensating biases in the broadband CRE comparison and 2) the fractional contribution of each band to the LW broadband CRE (f CRE) is sensitive to cloud-top height but largely insensitive to cloud fraction, thereby presenting a diagnostic metric to separate the two macroscopic properties of clouds. Recent studies led by the first author have established methods to derive such band-by-band quantities from collocated Atmospheric Infrared Sounder (AIRS) and Clouds and the Earth’s Radiant Energy System (CERES) observations. A study is presented here that compares the observed band-by-band CRE over the tropical oceans with those simulated by three different atmospheric GCMs—the GFDL Atmospheric Model version 2 (GFDL AM2), NASA Goddard Earth Observing System version 5 (GEOS-5), and the fourth-generation AGCM of the Canadian Centre for Climate Modelling and Analysis (CCCma CanAM4)—forced by observed SST. The models agree with observation on the annual-mean LW broadband CRE over the tropical oceans within ±1 W m−2. However, the differences among these three GCMs in some bands can be as large as or even larger than ±1 W m−2. Observed seasonal cycles of f CRE in major bands are shown to be consistent with the seasonal cycle of cloud-top pressure for both the amplitude and the phase. However, while the three simulated seasonal cycles of f CRE agree with observations on the phase, the amplitudes are underestimated. Simulated interannual anomalies from GFDL AM2 and CCCma CanAM4 are in phase with observed anomalies. The spatial distribution of f CRE highlights the discrepancies between models and observation over the low-cloud regions and the compensating biases from different bands.
Abstract
The cloud radiative effect (CRE) of each longwave (LW) absorption band of a GCM’s radiation code is uniquely valuable for GCM evaluation because 1) comparing band-by-band CRE avoids the compensating biases in the broadband CRE comparison and 2) the fractional contribution of each band to the LW broadband CRE (f CRE) is sensitive to cloud-top height but largely insensitive to cloud fraction, thereby presenting a diagnostic metric to separate the two macroscopic properties of clouds. Recent studies led by the first author have established methods to derive such band-by-band quantities from collocated Atmospheric Infrared Sounder (AIRS) and Clouds and the Earth’s Radiant Energy System (CERES) observations. A study is presented here that compares the observed band-by-band CRE over the tropical oceans with those simulated by three different atmospheric GCMs—the GFDL Atmospheric Model version 2 (GFDL AM2), NASA Goddard Earth Observing System version 5 (GEOS-5), and the fourth-generation AGCM of the Canadian Centre for Climate Modelling and Analysis (CCCma CanAM4)—forced by observed SST. The models agree with observation on the annual-mean LW broadband CRE over the tropical oceans within ±1 W m−2. However, the differences among these three GCMs in some bands can be as large as or even larger than ±1 W m−2. Observed seasonal cycles of f CRE in major bands are shown to be consistent with the seasonal cycle of cloud-top pressure for both the amplitude and the phase. However, while the three simulated seasonal cycles of f CRE agree with observations on the phase, the amplitudes are underestimated. Simulated interannual anomalies from GFDL AM2 and CCCma CanAM4 are in phase with observed anomalies. The spatial distribution of f CRE highlights the discrepancies between models and observation over the low-cloud regions and the compensating biases from different bands.
Abstract
The Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) product combines CERES and Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on the Terra and Aqua satellites to create a record of Earth’s Radiation Budget (ERB) and the associated cloud properties. As the Terra and Aqua orbits are no longer maintained at a fixed mean local time, EBAF recently transitioned to the CERES and Visible Infrared Imaging Radiometer Suite (VIIRS) instruments on NOAA-20 to avoid introducing a time-dependent bias in the record. To ensure smooth transitions between the Terra, combined Terra and Aqua (Terra+Aqua), and NOAA-20 portions of the record, regional climatological adjustments derived from the overlap period between missions are applied to anchor the entire record to Terra+Aqua. We estimate the random error in global monthly anomalies following the transitions to be <0.15 Wm−2 for TOA flux and <0.1% for cloud fraction, much smaller than the standard deviation in the corresponding anomalies. As the number of ERB instruments will decrease from four to one in just ten years, there is a high probability that a data gap in the EBAF record will occur, making it challenging to maintain continuity. We estimate that there is a 33% probability of a data gap in 2028 and a 60% probability in 2035. Bridging a data gap using computed TOA fluxes from one satellite product and one atmospheric reanalysis results in errors that are a factor of 4 larger than those obtained when there is overlap between successive missions.
Abstract
The Clouds and the Earth’s Radiant Energy System (CERES) Energy Balanced and Filled (EBAF) product combines CERES and Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on the Terra and Aqua satellites to create a record of Earth’s Radiation Budget (ERB) and the associated cloud properties. As the Terra and Aqua orbits are no longer maintained at a fixed mean local time, EBAF recently transitioned to the CERES and Visible Infrared Imaging Radiometer Suite (VIIRS) instruments on NOAA-20 to avoid introducing a time-dependent bias in the record. To ensure smooth transitions between the Terra, combined Terra and Aqua (Terra+Aqua), and NOAA-20 portions of the record, regional climatological adjustments derived from the overlap period between missions are applied to anchor the entire record to Terra+Aqua. We estimate the random error in global monthly anomalies following the transitions to be <0.15 Wm−2 for TOA flux and <0.1% for cloud fraction, much smaller than the standard deviation in the corresponding anomalies. As the number of ERB instruments will decrease from four to one in just ten years, there is a high probability that a data gap in the EBAF record will occur, making it challenging to maintain continuity. We estimate that there is a 33% probability of a data gap in 2028 and a 60% probability in 2035. Bridging a data gap using computed TOA fluxes from one satellite product and one atmospheric reanalysis results in errors that are a factor of 4 larger than those obtained when there is overlap between successive missions.
