David P. Kratz

Clouds and the Earth's Radiant Energy System (CERES): algorithm overview

The Clouds and the Earths Radiant Energy System (CERES) is part of NASAs Earth Observing System (EOS), CERES objectives include the following. (1) For climate change analysis, provide a continuation of the Earth Radiation Budget Experiment (ERBE) record of radiative fluxes at the top-of-the-atmosphere (TOA), analyzed using the same techniques as the existing ERBE data. (2) Double the accuracy of estimates of radiative fluxes at TOA and the Earths surface. (3) Provide the first long-term global estimates of the radiative fluxes within the Earths atmosphere. (4) Provide cloud property estimates collocated in space and time that are consistent with the radiative fluxes from surface to TOA. In order to accomplish these goals, CERES uses data from a combination of spaceborne instruments: CERES scanners, which are an improved version of the ERBE broadband radiometers, and collocated cloud spectral imager data on the same spacecraft. The CERES cloud and radiative flux data products should prove extremely useful in advancing the understanding of cloud-radiation interactions, particularly cloud feedback effects on the Earths radiation balance. For this reason, the CERES data should be fundamental to the ability to understand, detect, and predict global climate change. CERES results should also be very useful for studying regional climate changes associated with deforestation, desertification, anthropogenic aerosols, and ENSO events. This overview summarizes the Release 3 version of the planned CERES data products and data analysis algorithms. These algorithms are a prototype for the system that will produce the scientific data required for studying the role of clouds and radiation in the Earths climate system.

Radiative Forcing by Well-Mixed Greenhouse Gases: Estimates from Climate Models in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4)

The radiative effects from increased concentrations of well-mixed greenhouse gases (WMGHGs) represent the most significant and best understood anthropogenic forcing of the climate system. The most comprehensive tools for simulating past and future climates influenced by WMGHGs are fully coupled atmosphere-ocean general circulation models (AOGCMs). Because of the importance of WMGHGs as forcing agents it is essential that AOGCMs compute the radiative forcing by these gases as accurately as possible. We present the results of a radiative transfer model intercomparison between the forcings computed by the radiative parameterizations of AOGCMs and by benchmark line-by-line (LBL) codes. The comparison is focused on forcing by CO2, CH4, N2O, CFC-11, CFC-12, and the increased H2O expected in warmer climates. The models included in the intercomparison include several LBL codes and most of the global models submitted to the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). In general, the LBL models are in excellent agreement with each other. However, in many cases, there are substantial discrepancies among the AOGCMs and between the AOGCMs and LBL codes. In some cases this is because the AOGCMs neglect particular absorbers, in particular the near-infrared effects of CH4 and N2O, while in others it is due to the methods for modeling the radiative processes. The biases in the AOGCM forcings are generally largest at the surface level. We quantify these differences and discuss the implications for interpreting variations in forcing and response across the multimodel ensemble of AOGCM simulations assembled for the IPCC AR4.

Achieving Climate Change Absolute Accuracy in Orbit

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission will provide a calibration laboratory in orbit for the purpose of accurately measuring and attributing climate change. CLARREO measurements establish new climate change benchmarks with high absolute radiometric accuracy and high statistical confidence across a wide range of essential climate variables. CLARREOs inherently high absolute accuracy will be verified and traceable on orbit to Systeme Internationale (SI) units. The benchmarks established by CLARREO will be critical for assessing changes in the Earth system and climate model predictive capabilities for decades into the future as society works to meet the challenge of optimizing strategies for mitigating and adapting to climate change. The CLARREO benchmarks are derived from measurements of the Earths thermal infrared spectrum (5–50 μm), the spectrum of solar radiation reflected by the Earth and its atmosphere (320–2300 nm), and radio occultation refractivity from which...

The correlated k-distribution technique as applied to the AVHRR channels

Abstract Correlated k -distributions have been created to account for the molecular absorption found in the spectral ranges of the five Advanced Very High Resolution Radiometer (AVHRR) satellite channels. The production of the k -distributions was based upon an exponential-sum fitting of transmissions (ESFT) technique which was applied to reference line-by-line absorptance calculations. To account for the overlap of spectral features from different molecular species, the present routines made use of the multiplication transmissivity property which allows for considerable flexibility, especially when altering relative mixing ratios of the various molecular species. To determine the accuracy of the correlated k -distribution technique as compared to the line-by-line procedure, atmospheric flux and heating rate calculations were run for a wide variety of atmospheric conditions. For the atmospheric conditions taken into consideration, the correlated k -distribution technique has yielded results within about 0.5% for both the cases where the satellite spectral response functions were applied and where they were not. The correlated k -distributions principal advantage is that it can be incorporated directly into multiple scattering routines that consider scattering as well as absorption by clouds and aerosol particles.

Remote sensing of cloud properties using MODIS airborne simulator imagery during SUCCESS: 1. Data and models

We investigate methods to infer cloud properties such as cloud optical thickness, thermodynamic phase, cloud particle size, and cloud overlap by comparing cloud and clear-sky radiative transfer computations to measurements provided by the Moderate Resolution Imaging Spectroradiometer (MODIS) airborne simulator (MAS). The MAS scanning spectroradiometer was flown on the NASA ER-2 during the Subsonic Aircraft Contrail and Cloud Effects Special Study (SUCCESS) field campaign during April and May 1996. The MAS bands chosen for this study correspond to wavelengths of 0.65, 1.63, 1.90, 2.15, 3.82, 8.52, 11, and 12 μm. Clear-sky absorption due to water vapor, ozone, and other trace gases is calculated using a set of correlated k-distribution routines developed specifically for these MAS bands. Scattering properties (phase function, single-scattering albedo, and extinction cross section) are derived for water droplet clouds using Mie theory. Scattering properties for ice-phase clouds are incorporated for seven cirrus models: cirrostratus, cirrus uncinus, cold cirrus, warm cirrus, and cirrus at temperatures of T = −20°C, −40°C, and −60°C. The cirrus are composed of four crystal types: hexagonal plates, two-dimensional bullet rosettes, hollow columns, and aggregates. Results from comparison of MAS data from a liquid water cloud with theoretical calculations indicate that estimates of optical thickness and particle size are reasonably consistent with one another no matter which spectral bands are used in the analysis. However, comparison of MAS data from a cirrus cloud with theoretical calculations shows consistency in optical thickness but not with particle size among the various band combinations used in the analysis. The methods described in this paper are used in two companion papers to explore techniques to infer cloud thermodynamic phase and cloud overlap.

Energy transport in the thermosphere during the solar storms of April 2002

The dramatic solar storm events of April 2002 deposited a large amount of energy into the Earths upper atmosphere, substantially altering the thermal structure, the chemical composition, the dynam ...

Rapid Calibration of Operational and Research Meteorological Satellite Imagers. Part I: Evaluation of Research Satellite Visible Channels as References

Operational meteorological satellites generally lack reliable onboard calibration systems for solar-imaging channels. Current methods for calibrating these channels and for normalizing similar channels on contemporaneous satellite imagers typically rely on a poorly calibrated reference source. To establish a more reliable reference instrument for calibration normalization, this paper examines the use of research satellite imagers that maintain their solar-channel calibrations by using onboard diffuser systems that rely on the sun as an absolute reference. The Visible Infrared Scanner (VIRS) on the Tropical Rainfall Measuring Mission(TRMM) satellite and the second Along-Track Scanning Radiometer (ATSR-2) on the second European Remote Sensing Satellite (ERS-2) are correlated with matched data from the eighth Geostationary Operational Environmental Satellite (GOES-8), the fifth Geostationary Meteorological satellite(GMS-5), and with each other to examine trends in the solar channels. VIRS data are also correlated with the Terra satellite’s Moderate Resolution Imaging Spectroradiometer (MODIS) provisional data as a preliminary assessment of their relative calibrations. As an additional check on their long-term stability, the VIRS data are compared to the relevant corresponding broadband shortwave radiances of the Clouds and the Earth’s Radiant Energy System (CERES) scanners on TRMM. No statistically significant trend in the calibration of the VIRS 0.65- and 1.64-mm channels could be detected from the comparisons with CERES data taken during 1998 and 2000. The VIRS-to-GOES-8 correlations revealed an annual degradation rate for the GOES-8 visible (0.67 mm) channel of ;7.5% and an initial drop of 16% in the gain from the prelaunch value. The slopes in the GOES-8 visible-channel gain trend lines derived from VIRS data taken after January 1998 and ATSR-2 data taken between October 1995 and December 1999 differed by only 1%‐2% indicating that both reference instruments are highly stable. The mean difference of 3%‐4.8% between the VIRS‐GOES-8 and ATSR-2‐GOES-8 gains is attributed to spectral differences between ATSR-2 and VIRS and to possible biases in the ATSR-2 channel-2 calibration. A degradation rate of 1.3% per year found for the GMS-5 visible channel was confirmed by comparisons with earlier calibrations. The MODIS and VIRS calibrations agreed to within 21% to 3%. Some of the differences between VIRS and the provisional MODIS radiances can be explained by spectral differences between the two instruments. The MODIS measures greater reflectance than VIRS for bright scenes. Although both VIRS and ATSR-2 provide temporally stable calibrations, it is recommended that, at least until MODIS calibrations are finalized, VIRS should be used as a reference source for normalizing operational meteorological satellite imagers because of its broader visible filter.

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

Abstract A new method for determining unfiltered shortwave (SW), longwave (LW), and window 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 cloud is present. Relative errors in instantaneous unfiltered radiances from this method are generally well below 1% for SW radiances (std dev ≈0.4% or ≈1 W m−2 equivalent flux), less than 0.2% for LW radiances (std dev ≈0.1% or ≈0.3 W m−2 equivalent flux), and less than 0.2% (std dev ≈0.1%) for window channel radiances. When three months (June, July, and August of 1998) of CERES Earth Radiation Budget Experiment (ERBE)-like unfiltered radiances from the Tropical Rainfall Measuring Mission satellite between 20°S and 20°N are compared with archived Earth Radiation Budget Satellite (ERBS) scanner measurements for the sa...

Retrieval of Cloud Properties Using CALIPSO Imaging Infrared Radiometer. Part I: Effective Emissivity and Optical Depth

The paper describes the operational analysis of the Imaging Infrared Radiometer (IIR) data, which have been collected in the framework of the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) mission for the purpose of retrieving high-altitude (above 7 km) cloud effective emissivity and optical depth that can be used in synergy with the vertically resolved Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) collocated observations. After an IIR scene classification is built under the CALIOP track, the analysis is applied to features detected by CALIOP when found alone in the atmospheric column or when CALIOP identifies an opaque layer underneath. The fast-calculation radiative transfer (FASRAD) model fed by ancillary meteorological and surface data is used to compute the different components involved in the effective emissivity retrievals under the CALIOP track. The track analysis is extended to the IIR swath using homogeneity criteria that are based on radiative equivalence. The effective optical depth at 12.05 m mi s shown to be a good proxy for about one-half of the cloud optical depth, allowing direct comparisons with other databases in the visible spectrum. A step-by-step quantitative sensitivity and performance analysis is provided. The method is validated through comparisons of collocated IIR and CALIOP optical depths for elevated single-layered semitransparent cirrus clouds, showing excellent agreement (within 20%) for values ranging from 1 down to 0.05. Uncertainties have been determined from the identified error sources. The optical depth distribution of semitransparent clouds is found to have a nearly exponential shape with a mean value of about 0.5–0.6.

An improved algorithm for retrieving surface downwelling longwave radiation from satellite measurements

Retrieving surface longwave radiation from space has been a difficult task since the surface downwelling longwave radiation (SDLW) are integrations from radiation emitted by the entire atmosphere, while those emitted from the upper atmosphere are absorbed before reaching the surface. It is particularly problematic when thick clouds are present since thick clouds will virtually block all the longwave radiation from above, while satellites observe atmosphere emissions mostly from above the clouds. Zhou and Cess developed an algorithm for retrieving SDLW based upon detailed studies using radiative transfer model calculations and surface radiometric measurements. Their algorithm linked clear sky SDLW with surface upwelling longwave flux and column precipitable water vapor. For cloudy sky cases, they used cloud liquid water path as an additional parameter to account for the effects of clouds. Despite the simplicity of their algorithm, it performed very well for most geographical regions except for those regions where the atmospheric conditions near the surface tend to be extremely cold and dry. Systematic errors were also found for areas that were covered with ice clouds. An improved version of the algorithm was developed that prevents the large errors in the SDLW at low water vapor amounts. The new algorithm also utilizes cloud fraction and cloud liquid and ice water paths measured from the Cloud and the Earths Radiant Energy System (CERES) satellites to separately compute the clear and cloudy portions of the fluxes. The new algorithm has been validated against surface measurements at 29 stations around the globe for the Terra and Aqua satellites. The results show significant improvement over the original version. The revised Zhou-Cess algorithm is also slightly better or comparable to more sophisticated algorithms currently implemented in the CERES processing. It will be incorporated in the CERES project as one of the empirical surface radiation algorithms.