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David P. Kratz, Ming-Dah Chou, and Michael M-H. Yan

Abstract

Fast and accurate parameterizations have been developed for the transmission functions of the CO2 9.4- and 10.4-μm bands, as well as the CFC-11, CFC-12, and CFC-22 bands located in the 8-12-μm region. The parameterizations are based on line-by-line calculations of transmission functions for the CO2 bands and on high spectral resolution laboratory measurements of the absorption coefficients for the CFC bands. Also developed are the parameterizations for the H2O transmission functions for the corresponding spectral bands. Compared to the high-resolution calculations, fluxes at the tropopause computed with the parameterizations are accurate to within 10% when overlapping of gas absorptions within a band is taken into account. For individual gas absorption, the accuracy is of order 0%–2%.

The climatic effects of these trace gases have been studied using a zonally averaged multilayer energy balance model, which includes seasonal cycles and a simplified deep ocean. With the trace gas abundances taken to follow the Intergovernmental Panel on Climate Change Low Emissions “B” scenario, the transient response of the surface temperature is simulated for the period 1900–2060. The minor CO2 and CFC bands contribute about 20%–25% of the total warming at the surface, which is comparable to the contribution from the CH4 and N2O bands. Collectively, these minor absorption bands account for 40%–45% of the total surface temperature increases. Thus, the climate warming due to absorption in these bands is comparable to that in the 15-μm CO2 band.

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Ming-Dah Chou, David P. Kratz, and William Ridgway

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Parameterizations for infrared radiation (IR) in clear atmosphere can be made fast and accurate by grouping spectral regions with similar radiative properties, and by separating the low pressure region of the atmosphere from the high pressure region. Various approaches are presented in this study to parameterizing the broadband transmission functions for use in numerical climate models. For water vapor and carbon dioxide (CO2) bands, the transmission functions are parameterized separately for the middle atmosphere (0.01–30 mb) and for the region below. In the middle atmosphere where the dependence of absorption on pressure and temperature is not strong, the diffuse transmission functions are derived from that at a reference pressure and temperature. In the lower stratosphere and the troposphere, the spectra are grouped into band-center regions and band-wing regions. One-parameter scaling is applied to approximate a nonhomogeneous path with an equivalent homogeneous path, and the diffuse transmittances are either fit by analytical functions or interpolated from precomputed tables.

As opposed to the one-parameter scaling, which applies only to a relatively narrow pressure range, the two-parameter scaling (commonly called the Curtis-Godson approximation) is applied to parameterizing the carbon dioxide (CO2) and ozone (O3) transmission functions in both the middle and the lower atmosphere. The diffuse transmission functions are simply interpolated from three small precomputed tables. The accuracies of cooling rates in the 15-μm band computed using the approximation for both the middle and the lower atmospheres are comparable with that using the parameterizations separately for the middle and the lower atmospheres. The radiative effect of nitrous oxide (N2O) and methane (CH4) is also examined. Parameterizations are presented for the N2O and CH4 diffuse transmission functions.

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Patrick Minnis, Louis Nguyen, David R. Doelling, David F. Young, Walter F. Miller, and David P. Kratz

Abstract

To establish a more reliable reference instrument for calibration normalization, this paper examines the differences between the various thermal infrared imager channels on a set of research and operational satellites. Mean brightness temperatures from 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. 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 broadband longwave radiances of the Clouds and the Earth's Radiant Energy System (CERES) scanners on TRMM. No statistically significant trend in the calibration of any of the three (3.7, 10.8, and 12.0 μm) VIRS thermal channels could be detected from the comparisons with CERES data taken during 1998 and 2000 indicating that the VIRS channels can serve as a reliable reference for intercalibrating satellite imagers. However, a small day–night difference in the VIRS thermal channels detected at very low temperatures should be taken into account. In general, most of the channels agreed to within less than ±0.7 K over a temperature range between 200 and 300 K. Some of the smaller differences can be explained by spectral differences in the channel response functions. A few larger differences were found at 200 K for some of the channels suggesting some basic calibration differences for lower temperatures. A nearly 3-K bias in the ATSR-2 11-μm channel relative to VIRS and GOES-8 was found at the cold end of the temperature range. The intercalibrations described here are being continued on a routine basis.

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Patrick Minnis, Louis Nguyen, David R. Doelling, David F. Young, Walter F. Miller, and David P. Kratz

Abstract

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-μm 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 μm) 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 −1% 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.

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David P. Kratz, Shashi K. Gupta, Anne C. Wilber, and Victor E. Sothcott

Abstract

Surface radiative fluxes have been derived with the objective of supplementing top-of-atmosphere (TOA) radiative fluxes being measured under NASA’s Clouds and the Earth’s Radiant Energy System (CERES) project. This has been accomplished by using combinations of CERES TOA measurements, parameterized radiative transfer algorithms, and high-quality meteorological datasets available from reanalysis projects. Current CERES footprint-level products include surface fluxes derived from two shortwave (SW) and three longwave (LW) algorithms designated as SW models A and B and LW models A, B, and C. The SW and LW models A work for clear conditions only; the other models work for both clear and cloudy conditions. The current CERES Edition-4A computed surface fluxes from all models are validated against ground-based flux measurements from high-quality surface networks like the Baseline Surface Radiation Network and NOAA’s Surface Radiation Budget Network (SURFRAD). Validation results as systematic and random errors are provided for all models, separately for five different surface types and combined for all surface types as tables and scatterplots. Validation of surface fluxes is now a part of CERES processing and is used to continually improve the above algorithms. Since both models B work for clear and cloudy conditions alike and meet the accuracy requirement, their results are considered to be the most reliable and most likely to be retained for future work. Both models A have limited use given that they work for clear skies only. Models B will continue to undergo further improvement as more validation results become available.

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Shashi K. Gupta, David P. Kratz, Anne C. Wilber, and L. Cathy Nguyen

Abstract

Parameterized shortwave and longwave algorithms developed at the Langley Research Center have been used to derive surface radiative fluxes in the processing of the Clouds and the Earth's Radiant Energy System (CERES) data obtained from flight aboard the Tropical Rainfall Measuring Mission (TRMM) satellite. Retrieved fluxes were validated on an instantaneous–footprint basis using coincident surface measurements obtained from the Atmospheric Radiation Measurement (ARM) program's Southern Great Plains (SGP) central facility, the ARM/SGP network of extended facilities, and a number of surface sites of the Baseline Surface Radiation Network (BSRN) and the Climate Monitoring and Diagnostics Laboratory (CMDL). Validation was carried out separately for clear-sky and all-sky conditions. For the shortwave, systematic errors varied from −12 to 10 W m−2 for clear skies and from −5 to 35 W m−2 for all-sky conditions. Random errors varied from 20 to 40 W m−2 for clear skies but were much larger (45–85 W m−2) for all-sky conditions. For the longwave, systematic errors were comparatively small for both clear-sky and all-sky conditions (0 to −10 W m−2) and random errors were within about 20 W m−2. In general, comparisons with surface data from the ARM/SGP site (especially the central facility) showed the best agreement. Large systematic errors in shortwave comparisons for some sites were related to flaws in the surface measurements. Larger errors in longwave fluxes for some footprints were found to be related to the errors in cloud mask retrievals, mostly during the nighttime. Smaller longwave errors related to potential errors in the operational analysis products used in satellite retrievals were also found. Still, longwave fluxes obtained with the present algorithm nearly meet the accuracy requirements for climate research.

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David P. Kratz, Shashi K. Gupta, Anne C. Wilber, and Victor E. Sothcott

Abstract

The Clouds and the Earth’s Radiant Energy System (CERES) project uses two shortwave (SW) and two longwave (LW) algorithms to derive surface radiative fluxes on an instantaneous footprint basis from a combination of top-of-atmosphere fluxes, ancillary meteorological data, and retrieved cloud properties. Since the CERES project examines the radiative forcings and feedbacks for Earth’s entire climate system, validation of these models for a wide variety of surface conditions is paramount. The present validation effort focuses upon the ability of these surface-only flux algorithms to produce accurate CERES Edition 2B single scanner footprint data from the Terra and Aqua spacecraft measurements. To facilitate the validation process, high-quality radiometric surface observations have been acquired that were coincident with the CERES-derived surface fluxes. For both SW models, systematic errors range from −20 to −12 W m−2 (from −2.8% to −1.6%) for global clear-sky cases, while for the all-sky SW model, the systematic errors range from 14 to 21 W m−2 (3.2%–4.8%) for global cloudy-sky cases. Larger systematic errors were seen for the individual surface types, and significant random errors where observed, especially for cloudy-sky cases. While the SW models nearly achieved the 20 W m−2 accuracy requirements established for climate research, further improvements are warranted. For the clear-sky LW model, systematic errors were observed to fall within ±5.4 W m−2 (±1.9%) except for the polar case in which systematic errors on the order from −15 to −11 W m−2 (from −13% to −7.2%) occurred. For the all-sky LW model, systematic errors were less than ±9.2 W m−2 (±7.6%) for both the clear-sky and cloudy-sky cases. The random errors were less than 17 W m−2 (6.2%) for clear-sky cases and 28 W m−2 (13%) for cloudy-sky cases, except for the desert cases in which very high surface skin temperatures caused an overestimation in the model-calculated surface fluxes. Overall, however, the LW models met the accuracy requirements for climate research.

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Anne Garnier, Jacques Pelon, Philippe Dubuisson, Michaël Faivre, Olivier Chomette, Nicolas Pascal, and David P. Kratz

Abstract

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 μm is 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.

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Shashi K. Gupta, David P. Kratz, Paul W. Stackhouse Jr., Anne C. Wilber, Taiping Zhang, and Victor E. Sothcott

Abstract

An improvement was developed and tested for surface longwave flux algorithms used in the Clouds and the Earth’s Radiant Energy System processing based on lessons learned during the validation of global results of those algorithms. The algorithms involved showed significant overestimation of downward longwave flux for certain regions, especially dry–arid regions during hot times of the day. The primary cause of this overestimation was identified and the algorithms were modified to (i) detect meteorological conditions that would produce an overestimation, and (ii) apply a correction when the overestimation occurred. The application of this correction largely eliminated the positive bias that was observed in earlier validation studies. Comparisons of validation results before and after the application of correction are presented.

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David P. Kratz, Paul W. Stackhouse Jr., Shashi K. Gupta, Anne C. Wilber, Parnchai Sawaengphokhai, and Greg R. McGarragh

Abstract

The Clouds and the Earth’s Radiant Energy Systems (CERES) project utilizes radiometric measurements taken aboard the Terra and Aqua spacecrafts to derive the world-class data products needed for climate research. Achieving the exceptional fidelity of the CERES data products, however, requires a considerable amount of processing to assure quality and to verify accuracy and precision, which results in the CERES data being released more than 6 months after the satellite observations. For most climate studies such delays are of little consequence; however, there are a significant number of near–real time uses for CERES data products. The Fast Longwave and Shortwave Radiative Flux (FLASHFlux) data product was therefore developed to provide a rapid release version of the CERES results, which could be made available to the research and applications communities within 1 week of the satellite observations by exchanging some accuracy for speed. FLASHFlux has both achieved this 1-week processing objective and demonstrated the ability to provide remarkably good agreement when compared with the CERES data products for both the instantaneous single-scanner footprint (SSF) fluxes and the time- and space-averaged (TISA) fluxes. This paper describes the methods used to expedite the production of the FLASHFlux SSF fluxes by utilizing data from the CERES and Moderate Resolution Imaging Spectroradiometer instruments, as well as other meteorological sources. This paper also reports on the validation of the FLASHFlux SSF results against ground-truth measurements and the intercomparison of FLASHFlux and CERES SSF results. A complementary paper will discuss the production and validation of the FLASHFlux TISA fluxes.

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