Abstract

The diurnal cycle of outgoing longwave radiation (OLR) computed by a climate model provides a powerful test of the numerical description of various physical processes. Diurnal cycles of OLR computed by version 3 of the Hadley Centre Atmospheric Model (HadAM3) are compared with those observed by the Earth Radiation Budget Satellite (ERBS) for the boreal summer season (June–August). The ERBS observations cover the domain from 55°S to 55°N. To compare the observed and modeled diurnal cycles, the principal component (PC) analysis method is used over this domain. The analysis is performed separately for the land and ocean regions. For land over this domain, the diurnal cycle computed by the model has a root-mean-square (RMS) of 11.4 W m⁻², as compared with 13.3 W m⁻² for ERBS. PC-1 for ERBS observations and for the model are similar, but the ERBS result has a peak near 1230 LST and decreases very slightly during night, whereas the peak of the model result is an hour later and at night the OLR decreases by 7 W m⁻² between 2000 and 0600 LST. Some of the difference between the ERBS and model results is due to the computation of convection too early in the afternoon by the model. PC-2 describes effects of morning/afternoon cloudiness on OLR, depending on the sign. Over ocean in the ERBS domain, the model RMS of the OLR diurnal cycle is 2.8 W m⁻², as compared with 5.9 W m⁻² for ERBS. Also, for the model, PC-1 accounts for 66% of the variance, while for ERBS, PC-1 accounts for only 16% of the variance. Thus, over ocean, the ERBS results show a greater variety of OLR diurnal cycles than the model does.

Abstract

The present study evaluates the ability of a cloud-resolving model (CRM) to simulate the physical properties of tropical deep convective cloud objects identified from a Clouds and the Earth’s Radiant Energy System (CERES) data product. The emphasis of this study is the comparisons among the small-, medium-, and large-size categories of cloud objects observed during March 1998 and between the large-size categories of cloud objects observed during March 1998 (strong El Niño) and March 2000 (weak La Niña). Results from the CRM simulations are analyzed in a way that is consistent with the CERES retrieval algorithm and they are averaged to match the scale of the CERES satellite footprints. Cloud physical properties are analyzed in terms of their summary histograms for each category.

It is found that there is a general agreement in the overall shapes of all cloud physical properties between the simulated and observed distributions. Each cloud physical property produced by the CRM also exhibits different degrees of disagreement with observations over different ranges of the property. The simulated cloud tops are generally too high and cloud-top temperatures are too low except for the large-size category of March 1998. The probability densities of the simulated top-of-the-atmosphere (TOA) albedos for all four categories are underestimated for high albedos, while those of cloud optical depth are overestimated at its lowest bin. These disagreements are mainly related to uncertainties in the cloud microphysics parameterization and inputs such as cloud ice effective size to the radiation calculation.

Summary histograms of cloud optical depth and TOA albedo from the CRM simulations of the large-size category of cloud objects do not differ significantly between the March 1998 and 2000 periods, consistent with the CERES observations. However, the CRM is unable to reproduce the significant differences in the observed cloud-top height while it overestimates the differences in the observed outgoing longwave radiation and cloud-top temperature between the two periods. Comparisons between the CRM results and the observations for most parameters in March 1998 consistently show that both the simulations and observations have larger differences between the large- and small-size categories than between the large- and medium-size, or between the medium- and small-size categories. However, the simulated cloud properties do not change as much with size as observed. These disagreements are likely related to the spatial averaging of the forcing data and the mismatch in time and space between the numerical weather prediction model from which the forcing data are produced and the CERES observed cloud systems.

Abstract

This study presents an objective classification methodology that uses Earth Observing System (EOS) satellite data to classify distinct “cloud objects” defined by cloud-system types, sizes, geographic locations, and matched large-scale environments. This analysis method identifies a cloud object as a contiguous region of the earth with a single dominant cloud-system type. It determines the shape and size of the cloud object from the satellite data and the cloud-system selection criteria. The statistical properties of the identified cloud objects are analyzed in terms of probability density functions (PDFs) based upon the Clouds and the Earth’s Radiant Energy System (CERES) Single Satellite Footprint (SSF) data.

Four distinct types of oceanic cloud objects—tropical deep convection, boundary layer cumulus, transition stratocumulus, and solid stratus—are initially identified from the CERES data collected from the Tropical Rainfall Measuring Mission (TRMM) satellite for this study. Preliminary results are presented from the analysis of the grand-mean PDFs of these four distinct types of cloud objects associated with the strong 1997/98 El Niño in March 1998 and the very weak 2000 La Niña in March 2000. A majority of the CERES footprint statistical characteristics of observed tropical deep convection are similar between the two periods in spite of the climatological contrast. There are, however, statistically significant differences in some cloud macrophysical properties such as the cloud-top height and cloud-top pressure and moderately significant differences in outgoing longwave radiation (OLR), cloud-top temperature, and ice diameter. The footprint statistical characteristics of the three observed boundary layer cloud-system types are distinctly different from one another in all cloud microphysical, macrophysical, optical properties, and radiative fluxes. The differences between the two periods are not significant for most cloud microphysical and optical properties and the top-of-the-atmosphere albedo, but are statistically significant for some cloud macrophysical properties and OLR. These characteristics of the grand-mean PDFs of cloud microphysical, macrophysical, and optical properties and radiative fluxes can be usefully compared with cloud model simulations.

Furthermore, the proportion of different boundary layer cloud types is changed between the two periods in spite of small differences in their grand-mean statistical properties. An increase of the stratus population and a decrease of the cumulus population are evident in the El Niño period compared to the very weak La Niña period. The number of the largest tropical convective cloud objects is larger during the El Niño period, but the total number of tropical convective cloud objects is approximately the same in the two periods.

Abstract

Four distinct types of cloud objects—tropical deep convection, boundary layer cumulus, stratocumulus, and overcast stratus—were previously identified from CERES Tropical Rainfall Measuring Mission (TRMM) data. Six additional types of cloud objects—cirrus, cirrocumulus, cirrostratus, altocumulus, transitional altocumulus, and solid altocumulus—are identified from CERES Aqua satellite data in this study. The selection criteria for the 10 cloud object types are based on CERES footprint cloud fraction and cloud-top pressure, as well as cloud optical depth for the high-cloud types. The cloud object is a contiguous region of the earth with a single dominant cloud-system type. The data are analyzed according to cloud object types, sizes, regions, and associated environmental conditions. The frequency of occurrence and probability density functions (PDFs) of selected physical properties are produced for the July 2006–June 2010 period. It is found that deep convective and boundary layer types dominate the total population while the six new types other than cirrostratus do not contribute much in the tropics and subtropics. There are pronounced differences in the size spectrum between the types, with the largest ones being of deep convective type and with stratocumulus and overcast types over the ocean basins off west coasts. The summary PDFs of radiative and cloud physical properties differ greatly among the size categories. For boundary layer cloud types, the differences come primarily from the locations of cloud objects: for example, coasts versus open oceans. They can be explained by considerable variations in large-scale environmental conditions with cloud object size, which will be further qualified in future studies.

Abstract

Clouds and the Earth’s Radiant Energy System (CERES) is a NASA spaceborne measurement program for monitoring the radiation environment of the earth–atmosphere system. The first CERES instrument is scheduled to be launched on board the Tropical Rainfall Measuring Mission (TRMM) satellite in late 1997. In addition to gathering traditional cross-track fixed azimuth measurements for calculating monthly mean radiation fields, this single CERES scanner instrument will also be required to collect angular radiance data using a rotating azimuth configuration for developing new angular dependence models (ADMs). Since the TRMM single CERES instrument can only be run in either one of these two configurations at any one time, it will need to be operated in a cyclical pattern between these two scan modes to achieve the intended measurement goals. To minimize the errors in the derived monthly mean radiation field due to missing cross-track scanner measurements during this satellite mission, determination of the optimal scan mode sequence for the TRMM single CERES instrument is carried out. The Earth Radiation Budget Experiment S-4 daily mean cross-track scanner data product for April and July 1985 and January 1986 is used with a simple temporal sampling scheme to produce simulated daily mean cross-track scanner measurements under different TRMM CERES operational scan mode sequences. Error analysis is performed on the monthly mean radiation fields derived from these simulated datasets. It is found that the best monthly mean result occurred when the cross-track scanner is operated on a “2 days on and 1 day off” mode. This scan mode sequence will effectively allow for 2 consecutive days of cross-track scanner data and 1 day of angular radiance measurement for each 3-day period. The root-mean-square errors for the monthly mean all-sky (clear sky) longwave and shortwave radiation field, due to missing cross-track scanner measurements for this particular case, are expected to be less than 2.5 (0.5) and 5.0 (1.5) W m⁻², respectively.

Abstract

Characteristics of tropical deep convective cloud objects observed over the tropical Pacific during January–August 1998 are examined using the Tropical Rainfall Measuring Mission/Clouds and the Earth’s Radiant Energy System Single Scanner Footprint (SSF) data. These characteristics include the frequencies of occurrence and statistical distributions of cloud physical properties. Their variations with cloud object size, sea surface temperature (SST), and satellite precession cycle are analyzed in detail. A cloud object is defined as a contiguous patch of the earth composed of satellite footprints within a single dominant cloud-system type.

It is found that statistical distributions of cloud physical properties are significantly different among three size categories of cloud objects with equivalent diameters of 100–150 (small), 150–300 (medium), and >300 km (large), except for the distributions of ice particle size. The distributions for the larger-size category of cloud objects are more skewed toward high SSTs, high cloud tops, low cloud-top temperature, large ice water path, high cloud optical depth, low outgoing longwave (LW) radiation, and high albedo than the smaller-size category. As SST varied from one satellite precession cycle to another, the changes in macrophysical properties of cloud objects over the entire tropical Pacific were small for the large-size category of cloud objects, relative to those of the small- and medium-size categories. This evidence supports the fixed anvil temperature hypothesis of Hartmann and Larson for the large-size category. Combined with the result that a higher percentage of the large-size category of cloud objects occurs during higher SST subperiods, this implies that macrophysical properties of cloud objects would be less sensitive to further warming of the climate. On the other hand, when cloud objects are classified according to SST ranges, statistical characteristics of cloud microphysical properties, optical depth, and albedo are not sensitive to the SST, but those of cloud macrophysical properties are dependent upon the SST. This result is related to larger differences in large-scale dynamics among the SST ranges than among the satellite precession cycles. Frequency distributions of vertical velocity from the European Centre for Medium-Range Weather Forecasts model that is matched to each cloud object are used to further understand some of the findings in this study.

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

Observationally based atmospheric energy balance is analyzed using Clouds and the Earth’s Radiant Energy System (CERES)-derived TOA and surface irradiance, Global Precipitation Climatology Project (GPCP)-derived precipitation, dry static and kinetic energy tendency and divergence estimated from ERA-Interim, and surface sensible heat flux from SeaFlux. The residual tends to be negative over the tropics and positive over midlatitudes. A negative residual implies that the precipitation rate is too small, divergence is too large, or radiative cooling is too large. The residual of atmospheric energy is spatially and temporally correlated with cloud objects to identify cloud types associated with the residual. Spatially, shallow cumulus, cirrostratus, and deep convective cloud-object occurrence are positively correlated with the absolute value of the residual. The temporal correlation coefficient between the number of deep convective cloud objects and individual energy components, net atmospheric irradiance, precipitation rate, and the sum of dry static and kinetic energy divergence and their tendency over the western Pacific are 0.84, 0.95, and 0.93, respectively. However, when all energy components are added, the atmospheric energy residual over the tropical Pacific is temporally correlated well with the number of shallow cumulus cloud objects over tropical Pacific. Because shallow cumulus alters not enough atmospheric energy compared to the residual, this suggests the following: 1) if retrieval errors associated with deep convective clouds are causing the column-integrated atmospheric energy residual, the errors vary among individual deep convective clouds, and 2) it is possible that the residual is associated with processes in which shallow cumulus clouds affect deep convective clouds and hence atmospheric energy budget over the tropical western Pacific.

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

This paper gives an update on the observed decadal variability of the earth radiation budget (ERB) using the latest altitude-corrected Earth Radiation Budget Experiment (ERBE)/Earth Radiation Budget Satellite (ERBS) Nonscanner Wide Field of View (WFOV) instrument Edition3 dataset. The effects of the altitude correction are to modify the original reported decadal changes in tropical mean (20°N to 20°S) longwave (LW), shortwave (SW), and net radiation between the 1980s and the 1990s from 3.1, −2.4, and −0.7 to 1.6, −3.0, and 1.4 W m⁻², respectively. In addition, a small SW instrument drift over the 15-yr period was discovered during the validation of the WFOV Edition3 dataset. A correction was developed and applied to the Edition3 dataset at the data user level to produce the WFOV Edition3_Rev1 dataset. With this final correction, the ERBS Nonscanner-observed decadal changes in tropical mean LW, SW, and net radiation between the 1980s and the 1990s now stand at 0.7, −2.1, and 1.4 W m⁻², respectively, which are similar to the observed decadal changes in the High-Resolution Infrared Radiometer Sounder (HIRS) Pathfinder OLR and the International Satellite Cloud Climatology Project (ISCCP) version FD record but disagree with the Advanced Very High Resolution Radiometer (AVHRR) Pathfinder ERB record. Furthermore, the observed interannual variability of near-global ERBS WFOV Edition3_Rev1 net radiation is found to be remarkably consistent with the latest ocean heat storage record for the overlapping time period of 1993 to 1999. Both datasets show variations of roughly 1.5 W m⁻² in planetary net heat balance during the 1990s.