Radiant Energy System Instrument Research Articles

Earth's albedo variations 1998–2014 as measured from ground‐based earthshine observations

AbstractThe Earth's albedo is a fundamental climate parameter for understanding the radiation budget of the atmosphere. It has been traditionally measured not only from space platforms but also from the ground for 16 years from Big Bear Solar Observatory by observing the Moon. The photometric ratio of the dark (earthshine) to the bright (moonshine) sides of the Moon is used to determine nightly anomalies in the terrestrial albedo, with the aim of quantifying sustained monthly, annual, and/or decadal changes. We find two modest decadal scale cycles in the albedo, but with no significant net change over the 16 years of accumulated data. Within the evolution of the two cycles, we find periods of sustained annual increases, followed by comparable sustained decreases in albedo. The evolution of the earthshine albedo is in remarkable agreement with that from the Clouds and the Earth's Radiant Energy System instruments, although each method measures different slices of the Earth's Bond albedo.

Radiative characteristics of fog over the Indo-Gangetic Plains during northern winter

The Indo-Gangetic plains (IGP), spread across northern parts of India, Pakistan and Bangladesh is a hot-spot for fog formation during northern winter. The unavailability of long-term fog data over the IGP from any space based platform incites the utilization of monthly International Satellite Cloud Climatology Project (ISCCP-D2) cloud data for studying fog at this region. Fog is primarily represented as low level stratus and stratocumulus clouds in ISCCP cloud data. Top of atmosphere cloud radiative forcing measured by Clouds and the Earth’s Radiant Energy System instruments onboard Aqua/Terra satellites indicates a net radiative cooling by fog over the IGP region. Also, the analysis of gridded surface temperature data from India meteorological department suggests that negative temperature anomalies prevail over the regions of radiative cooling exerted by fog. These negative anomalies in surface temperature may cause further dipping of the temperature over the IGP during fog years. This study suggests that foggy winter will be colder than non-foggy winter over the IGP.

An examination of the nature of global MODIS cloud regimes

We introduce global cloud regimes (previously also referred to as weather states) derived from cloud retrievals that use measurements by the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument aboard the Aqua and Terra satellites. The regimes are obtained by applying clustering analysis on joint histograms of retrieved cloud top pressure and cloud optical thickness. By employing a compositing approach on data sets from satellites and other sources, we examine regime structural and thermodynamical characteristics. We establish that the MODIS cloud regimes tend to form in distinct dynamical and thermodynamical environments and have diverse profiles of cloud fraction and water content. When compositing radiative fluxes from the Clouds and the Earth's Radiant Energy System instrument and surface precipitation from the Global Precipitation Climatology Project, we find that regimes with a radiative warming effect on the atmosphere also produce the largest implied latent heat. Taken as a whole, the results of the study corroborate the usefulness of the cloud regime concept, reaffirm the fundamental nature of the regimes as appropriate building blocks for cloud system classification, clarify their association with standard cloud types, and underscore their distinct radiative and hydrological signatures.

Can Top-of-Atmosphere Radiation Measurements Constrain Climate Predictions? Part I: Tuning

Perturbed physics configurations of version 3 of the Hadley Centre Atmosphere Model (HadAM3) driven with observed sea surface temperatures (SST) and sea ice were tuned to outgoing radiation observations using a Gauss–Newton line search optimization algorithm to adjust the model parameters. Four key parameters that previous research found affected climate sensitivity were adjusted to several different target values including two sets of observations. The observations used were the global average reflected shortwave radiation (RSR) and outgoing longwave radiation (OLR) from the Clouds and the Earth's Radiant Energy System instruments combined with observations of ocean heat content. Using the same method, configurations were also generated that were consistent with the earlier Earth Radiation Budget Experiment results. Many, though not all, tuning experiments were successful, with about 2500 configurations being generated and the changes in simulated outgoing radiation largely due to changes in clouds. Clear-sky radiation changes were small, largely due to a cancellation between changes in upper-tropospheric relative humidity and temperature. Changes in other climate variables are strongly related to changes in OLR and RSR particularly on large scales. There appears to be some equifinality with different parameter configurations producing OLR and RSR values close to observed values. These models have small differences in their climatology with the one group being similar to the standard configuration and the other group drier in the tropics and warmer everywhere.

Performance and Long-Term Stability of the Prelaunch Radiometric Calibration Facility for the Clouds and the Earth's Radiant Energy System Instruments

The Radiometric Calibration Facility (RCF) at Northrop Grumman Aerospace Systems was used between 1995 and 2008 to establish the prelaunch calibration of the first six Clouds and the Earth's Radiant Energy System (CERES) instruments, with the seventh CERES instrument scheduled to be tested in the RCF in 2012. This paper reviews the performance of the RCF radiometric standards, which are the narrow-field blackbody (NFBB) and the short-wave reference source, as well as the RCF transfer active-cavity radiometer, in the context of the CERES prelaunch calibration process. A detailed investigation of the long-term stability of these standards over the 1999-2008 time span of CERES FM5 testing is reported, showing that the RCF calibrations in the long and short waves have remained stable relative to the NFBB absolute reference at levels of 0.06% and 0.5%, respectively, over the eight-year span.

Space observations of cold-cloud phase change

This study examines the vertically resolved cloud measurements from the cloud-aerosol lidar with orthogonal polarization instrument on Aqua satellite from June 2006 through May 2007 to estimate the extent to which the mixed cloud-phase composition can vary according to the ambient temperature, an important concern for the uncertainty in calculating cloud radiative effects. At -20 degrees C, the global average fraction of supercooled clouds in the total cloud population is found to be about 50% in the data period. Between -10 and -40 degrees C, the fraction is smaller at lower temperatures. However, there are appreciable regional and temporal deviations from the global mean (> +/- 20%) at the isotherm. In the analysis with coincident dust aerosol data from the same instrument, it appears that the variation in the supercooled cloud fraction is negatively correlated with the frequencies of dust aerosols at the -20 degrees C isotherm. This result suggests a possibility that dust particles lifted to the cold cloud layer effectively glaciate supercooled clouds. Observations of radiative flux from the clouds and earth's radiant energy system instrument aboard Terra satellite, as well as radiative transfer model simulations, show that the 20% variation in the supercooled cloud fraction is quantitatively important in cloud radiative effects, especially in shortwave, which are 10-20 W m(-2) for regions of mixed-phase clouds affected by dust. In particular, our results demonstrate that dust, by glaciating supercooled water, can decrease albedo, thus compensating for the increase in albedo due to the dust aerosols themselves. This has important implications for the determination of climate sensitivity.

Validation of Clouds and Earth Radiant Energy System instruments aboard the Terra and Aqua satellites

A comparison of unfiltered radiances measured by Clouds and Earth Radiant Energy System (CERES) instruments (FM1 and FM4) operating on two different platforms, Terra and Aqua satellites, is presented. Data for the comparison were collected at orbital crossings in July and August 2002 and June 2003. Using a special scanning mode, viewing geometries of the instruments were matched to provide a large data set for comparing all three channels. In addition, the data collected over Greenland were used for a more stringent test of the consistency of the shortwave radiances. Statistics are computed for different scene types, and a confidence test is applied to compiled averages to show the consistency of 1% between measurements taken from the two different platforms. Results of the unfiltered radiance comparison are based on Edition2 of the FM1 and FM4 ES8 (Earth Radiation Budget Experiment–like) data product.

Angular Distribution Models for Top-of-Atmosphere Radiative Flux Estimation from the Clouds and the Earth’s Radiant Energy System Instrument on the Tropical Rainfall Measuring Mission Satellite. Part I: Methodology

Top-of-atmosphere (TOA) radiative fluxes from the Clouds and the Earth s Radiant Energy System (CERES) are estimated from empirical angular distribution models (ADMs) that convert instantaneous radiance measurements to TOA fluxes. This paper evaluates the accuracy of CERES TOA fluxes obtained from a new set of ADMs developed for the CERES instrument onboard the Tropical Rainfall Measuring Mission (TRMM). The uncertainty in regional monthly mean reflected shortwave (SW) and emitted longwave (LW) TOA fluxes is less than 0.5 W/sq m, based on comparisons with TOA fluxes evaluated by direct integration of the measured radiances. When stratified by viewing geometry, TOA fluxes from different angles are consistent to within 2% in the SW and 0.7% (or 2 W/sq m) in the LW. In contrast, TOA fluxes based on ADMs from the Earth Radiation Budget Experiment (ERBE) applied to the same CERES radiance measurements show a 10% relative increase with viewing zenith angle in the SW and a 3.5% (9 W/sq m) decrease with viewing zenith angle in the LW. Based on multiangle CERES radiance measurements, 18 regional instantaneous TOA flux errors from the new CERES ADMs are estimated to be 10 W/sq m in the SW and, 3.5 W/sq m in the LW. The errors show little or no dependence on cloud phase, cloud optical depth, and cloud infrared emissivity. An analysis of cloud radiative forcing (CRF) sensitivity to differences between ERBE and CERES TRMM ADMs, scene identification, and directional models of albedo as a function of solar zenith angle shows that ADM and clear-sky scene identification differences can lead to an 8 W/sq m root-mean-square (rms) difference in 18 daily mean SW CRF and a 4 W/sq m rms difference in LW CRF. In contrast, monthly mean SW and LW CRF differences reach 3 W/sq m. CRF is found to be relatively insensitive to differences between the ERBE and CERES TRMM directional models.

A method for assessing the quality of model‐based estimates of ground temperature and atmospheric moisture using satellite data

A method is developed for validating model‐based estimates of atmospheric moisture and ground temperature using satellite data. The approach relates errors in estimates of clear‐sky longwave fluxes at the top of the Earth‐atmosphere system to errors in geophysical parameters. The fluxes include clear‐sky outgoing longwave radiation (CLR) and radiative flux in the window region between 8 and 12 μm (RadWn). The approach capitalizes on the availability of satellite estimates of CLR and RadWn and other auxiliary satellite data, and multiple global four‐dimensional data assimilation (4‐DDA) products. The basic methodology employs off‐line forward radiative transfer calculations to generate synthetic clear‐sky longwave fluxes from two different 4‐DDA data sets. Simple linear regression is used to relate the clear‐sky longwave flux discrepancies to discrepancies in ground temperature (δTg) and broad‐layer integrated atmospheric precipitable water (δpw). The slopes of the regression lines define sensitivity parameters which can be exploited to help interpret mismatches between satellite observations and model‐based estimates of clear‐sky longwave fluxes. For illustration we analyze the discrepancies in the clear‐sky longwave fluxes between an early implementation of the Goddard Earth Observing System Data Assimilation System (GEOS2) and a recent operational version of the European Centre for Medium‐Range Weather Forecasts data assimilation system. The analysis of the synthetic clear‐sky flux data shows that simple linear regression employing δTg and broad layer δpw provides a good approximation to the full radiative transfer calculations, typically explaining more than 90% of the 6 hourly variance in the flux differences. These simple regression relations can be inverted to “retrieve” the errors in the geophysical parameters. Uncertainties (normalized by standard deviation) in the monthly mean retrieved parameters range from 7% for δTg to ∼20% for the lower tropospheric moisture between 500 hPa and surface. The regression relationships developed from the synthetic flux data, together with CLR and RadWn observed with the Clouds and Earth Radiant Energy System instrument, are used to assess the quality of the GEOS2 Tg and pw. Results showed that the GEOS2 Tg is too cold over land, and pw in upper layers is too high over the tropical oceans and too low in the lower atmosphere.

Improving Global Analysis and Short–Range Forecast Using Rainfall and Moisture Observations Derived from TRMM and SSM/I Passive Microwave Sensors

As a follow-on to the Tropical Rainfall Measuring Mission (TRMM), the National Aeronautics and Space Administration in the United States, the National Space Development Agency of Japan, and the European Space Agency are considering a satellite mission to measure the global rainfall. The plan envisions an improved TRMM-like satellite and a constellation of eight satellites carrying passive microwave radiometers to provide global rainfall measurements at 3-h intervals. The success of this concept relies on the merits of rainfall estimates derived from passive microwave radiometers. This article offers a proof-of-concept demonstration of the benefits of using rainfall and total precipitable water (TPW) information derived from such instruments in global data assimilation with observations from the TRMM Microwave Imager (TMI) and two Special Sensor Microwave/Imager (SSM/I) instruments. Global analyses that optimally combine observations from diverse sources with physical models of atmospheric and land processes can provide a comprehensive description of the climate systems. Currently, such data analyses contain significant errors in primary hydrological fields such as precipitation and evaporation, especially in the Tropics. It is shown that assimilating the 6-h-averaged TMI and SSM/I surface rain rate and TPW retrievals improves not only the hydrological cycle but also key climate parameters such as clouds, radiation, and the upper-tropospheric moisture in the analysis produced by the Goddard Earth Observing System Data Assimilation System, as verified against radiation measurements by the Clouds and the Earth's Radiant Energy System instrument and brightness temperature observations by the Television Infrared Observational Satellite Operational Vertical Sounder instruments. Typically, rainfall assimilation improves clouds and radiation in areas of active convection, as well as the latent heating and large-scale motions in the Tropics, while TPW assimilation leads to reduced moisture biases and improved radiative fluxes in clear-sky regions. Ensemble forecasts initialized with analyses that incorporate TMI and SSM/I rainfall and TPW data also yield better short-range predictions of geopotential heights, winds, and precipitation in the Tropics. These results were obtained using a variational procedure based on a 6-h time integration of a column model of moist physics with prescribed dynamical and other physical tendencies. The procedure estimates moisture tendency corrections at observation locations by minimizing the least square differences between the observed TPW and rain rates and those generated by the column model over a 6-h analysis window. These tendency corrections are then applied during the assimilation cycle to compensate for errors arising from both initial conditions and deficiencies in model physics. Our results point to the importance of addressing deficiencies in model physics in assimilating data types such as precipitation, for which the forward model based on convective parameterizations may have significant systematic errors. This study offers a compelling illustration of the potential of using rainfall and TPW information derived from passive microwave instruments to significantly improve the quality of four-dimensional global datasets for climate analysis and weather forecasting applications.

Determination of Unfiltered Radiances from the Clouds and the Earth’s Radiant Energy System Instrument

A new method for determining unfiltered shortwave (SW), longwave (LW) and window (W) radiances from filtered radiances measured by the Clouds and the Earth's Radiant Energy System (CERES) satellite instrument is presented. The method uses theoretically derived regression coefficients between filtered and unfiltered radiances that are a function of viewing geometry, geotype and whether or not cloud is present. Relative errors in insta.ntaneous unfiltered radiances from this method are generally well below 1% for SW radiances (approx. 0.4% 1(sigma) or approx.l W/sq m equivalent flux), < 0.2% for LW radiances (approx. 0.1% 1(sigma) or approx.0.3 W/sq m equivalent flux) and < 0.2% (approx. 0.1% 1(sigma) for window channel radiances.

Comparison of Model Fluxes with Surface and Top-of-the-Atmosphere Observations

Abstract The global observation network of the atmospheric broadband radiation reached an unprecedent extent in 1998 with the simultaneous availability of longwave and shortwave measurements of the Clouds and the Earth’s Radiant Energy System instrument on board the Tropical Rainfall Measuring Mission spacecraft, and of a number of surface stations as part of the Atmospheric Radiation Measurement, Baseline Surface Radiation Network, and Surface Radiation network programs. In this paper, these observations are used to assess the quality of the longwave and shortwave components of both the top-of-the-atmosphere and the surface radiation budget computed by the ECMWF operational forecast system. The main features of the boundary radiation are well captured by the system. Clouds appear to be the main modulator of the uncertainty of the top-of-the-atmosphere radiation and of the shortwave surface radiation. This is explained by both model cloud deficiencies and inadequate cloud representation in the radiative t...

Evaluating the Design of an Earth Radiation Budget Instrument with System Simulations. Part III: CERES-I Diurnal Sampling Error

Accuracy estimates for the broadband CERES-I (Clouds and Earth's Radiant Energy System Instrument) measurements of daily average radiant exitance are presented. This is a continuation of the authors’ earlier CERES sampling studies published as Part I and II. Daily averaging errors result from not sampling the entire 24-h period with a system of polar satellites. Instantaneous errors, the subject of the previous studies, are also included. Separate estimates for daily average emitted longwave (LW) and reflected shortwave (SW) radiant fluxes are given. The earth SW and LW reference radiation fields are derived from 3-h Geosynchronous Operational Environmental Satellite data, time interpolated between image times, and partitioned into upwelling radiances using scene-dependent angular dependence models (ADMs). Perturbations in these ADMs are introduced to cause instantaneous angular sampling errors (also referred to as ADM errors). These ADM errors, along with spatial sampling errors, are propagated through the time integration process for a more realistic estimate of the daily average error. Three satellite observing configurations are considered. They represent individually, and in combination, a proposed European Polar Orbiting Platform and National Aeronautics and Space Administration Earth Observing System-A sun-synchronous polar-orbiting satellite system. The Earth Radiation Budget Experiment single and multiple satellite time and space averaging algorithms are used for the satellite retrieval. One-satellite spatial root-mean-square (rms) daily averaged SW flux errors of 11–17 W m−2 are obtained for 2.5° latitude-longitude regions over the area studied (15°S–45°N, 50°–120°W). The two-satellite system has errors that are some 40%–60% less, having values between 5 and 9 W m−2. Only the two-satellite system can meet the 10 W m−2 user accuracy requirement for regional daily averaged SW fluxes. Longwave flux errors of 5–6 W m−2 and 3–4 W m−2, respectively, are found for the one- and two-satellite configurations. The largest component of CERES 2.5° daily averaged target area error is due to sparse temporal sampling. The ADM error propagated into the daily average becomes more important as the temporal sampling error is reduced with the two-satellite system. For this system, the ADM error component (of the daily averaged error) for SW radiation reaches a magnitude that can be as large as 8 W m−2 at high solar zenith angles (SZA), where scene anisotropy is usually greatest. Over the study domain, up to 15% of the total rms error is due to ADM errors. Moreover, CERES 2.5° zonal mean daily averaged errors exhibit a latitudinal dependence of some 7 W m−2 for a 60° change in latitude in the presence of 30% systematic errors in the ADMs. This is largely attributable to the SZA dependence of instantaneous ADM error. Without ADM errors, zonal mean daily averaged target area biases range up to 3–4 W m−2 with an irregular latitudinal variation.

Evaluating the Design of an Earth Radiation Budget Instrument with System Simulations. Part II: Minimization of Instantaneous Sampling Errors for CERES-I

Much of the new record of broadband earth radiation budget satellite measurements to be obtained during the late 1990s and early twenty-first century will come from the dual-radiometer Clouds and Earth's Radiant Energy System Instrument (CERES-I) flown aboard sun-synchronous polar orbiters. Simulation studies conducted in this work for an early afternoon satellite orbit indicate that spatial root-mean-square (rms) sampling errors of instantaneous CERES-I shortwave flux estimates will range from about 8.5 to 14.0 W/m on a 2.5 deg latitude and longitude grid resolution. Rms errors in longwave flux estimates are only about 20% as large and range from 1.5 to 3.5 W/sq m. These results are based on an optimal cross-track scanner design that includes 50% footprint overlap to eliminate gaps in the top-of-the-atmosphere coverage, and a 'smallest' footprint size to increase the ratio in the number of observations lying within to the number of observations lying on grid area boundaries. Total instantaneous measurement error also depends on the variability of anisotropic reflectance and emission patterns and on retrieval methods used to generate target area fluxes. Three retrieval procedures from both CERES-I scanners (cross-track and rotating azimuth plane) are used. (1) The baseline Earth Radiaton Budget Experiment (ERBE) procedure, which assumes that errors due to the use of mean angular dependence models (ADMs) in the radiance-to-flux inversion process nearly cancel when averaged over grid areas. (2) To estimate N, instantaneous ADMs are estimated from the multiangular, collocated observations of the two scanners. These observed models replace the mean models in computation of satellite flux estimates. (3) The scene flux approach, conducts separate target-area retrievals for each ERBE scene category and combines their results using area weighting by scene type. The ERBE retrieval performs best when the simulated radiance field departs from the ERBE mean models by less than 10%. For larger perturbations, both the scene flux and collocation methods produce less error than the ERBE retrieval. The scene flux technique is preferable, however, because it involves fewer restrictive assumptions.

Evaluating the Design of an Earth Radiation Budget Instrument with System Simulations. Part I: Instantaneous Estimates

A set of system simulations has been performed to evaluate candidate scanner designs for an Earth Radiation Budget Instrument (ERBI) for the Earth Observing System (EOS) of the late 1990s. Five different instruments are considered: 1) the Active Cavity Array (ACA), 2) the Clouds and Earth's Radiant Energy System-Instrument (CERES-1), 3) the Conically Scanning Radiometer (CSR), (4) the Earth Radiation Budget Experiment Cross-Track Scanner (ERBE), and 5) the Nimbus-7 Biaxial Scanner (N7). Errors in instantaneous, top-of-the-atmosphere (TOA) satellite flux estimates are assumed to arise from two measurement problems: the sampling of space over a given geographic domain, and sampling in angle about a given spatial location. In the limit where angular sampling errors vanish [due to the application of correct angular dependence models (ADMs) during inversion], the accuracy of each scanner design is determined by the instrument's ability to map the TOA radiance field in a uniform manner. In this regard, the instruments containing a cross-track scanning component (CERES-1 and ERBE) do best. As errors in ADMs are encountered, cross-track instruments incur angular sampling errors more rapidly than biaxial instruments (N7, ACA, and CSR) and eventually overtake the biaxial designs in their total error amounts. A latitude bias (north-south error gradient) in the ADM error of cross-track instruments also exists. This would be objectionable when ADM errors are systematic over large areas of the globe. For instantaneous errors, however, cross-track scanners outperform biaxial or conical scanners for 2.5° latitude × 2.5° longitude target areas. providing that the ADM error is less than or equal to 30%. A key issue is the amount of systematic ADM error (departures from the mean models) that is present at the 2.5° resolution of the ERBE target areas. If this error is less than 30%, then the CERES-I, ERBE, and CSR, in order of increasing error, provide the most accurate instantaneous flux estimates, within 2–3 W m−2 of each other in reflected shortwave flux. The magnitude of this error is near the 10 W m−2 accuracy requirement of the user community. Longwave flux errors have been found to have the same space and time characteristics as errors in shortwave radiation, but only about 25% as large.