An international Intercomparison of 3D Radiation Codes (I3RC) underscores the vast progress of recent years, but also highlights the challenges ahead for routine implementation in remote sensing and global climate modeling applications. Modeling atmospheric and oceanic processes is one of the most important methods of the earth sciences for understanding the interactions of the various components of the surface-atmosphere system and predicting future weather and climate states. Great leaps in the availability of computing power at continuously decreasing costs have led to widespread popularity of computer models for research and operational applications. As part of routine scientific work, output from models built for AFFILIATIONS: CAHALAN-NASA

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Research funded by the U.S. Department of Energy's Atmospheric Radiation Measurement (ARM) program has led to significant improvements in longwave radiative transfer modeling over the last decade. These improvements, which have generally come in small incremental changes, were made primarily in the water vapor self- and foreign-broadened continuum and the water vapor absorption line parameters. These changes, when taken as a whole, result in up to a 6 W m−2 improvement in the modeled clear-sky downwelling longwave radiative flux at the surface and significantly better agreement with spectral observations. This paper provides an overview of the history of ARM with regard to clear-sky longwave radiative transfer, and analyzes remaining related uncertainties in the ARM state-of-the-art Line-by-Line Radiative Transfer Model (LBLRTM). A quality measurement experiment (QME) for the downwelling infrared radiance at the ARM Southern Great Plains site has been ongoing since 1994. This experiment has three objectives: 1) to validate and improve the absorption models and spectral line parameters used in line-by-line radiative transfer models, 2) to assess the ability to define the atmospheric state, and 3) to assess the quality of the radiance observations that serve as ground truth for the model. Analysis of data from 1994 to 1997 made significant contributions to optimizing the QME, but is limited by small but significant uncertainties and deficiencies in the atmospheric state and radiance observations. This paper concentrates on the analysis of QME data from 1998 to 2001, wherein the data have been carefully selected to address the uncertainties in the 1994–97 dataset. Analysis of this newer dataset suggests that the representation of self-broadened water vapor continuum absorption is 3%–8% too strong in the 750–1000 cm−1 region. The dataset also provides information on the accuracy of the self- and foreign-broadened continuum absorption in the 1100–1300 cm−1 region. After accounting for these changes, remaining differences in modeled and observed downwelling clear-sky fluxes are less than 1.5 W m−2 over a wide range of atmospheric states.

An international program of intercomparison of radiation codes used in climate models has been initiated because of the central role of radiative processes in many proposed climate change mechanisms. During the past 6 years, results of calculations from such radiation codes have been compared with each other, with results from the most detailed radiation models (line‐by‐line models) and with observations from within the atmosphere. Line‐by‐line model results tend to agree with each other to within 1%; however, the intercomparison shows a spread of 10–20% in the calculations of radiation budget components by the less detailed climate model codes. The spread among the results is even larger (30–40%) for the sensitivities of the codes to changes in radiatively important variables, such as carbon dioxide and water vapor. The analysis of the model calculations shows that the outliers to many of the clear‐sky calculations appear to be related to those models that have not tested the techniques used to perform the integration over altitude. When those outliers are removed, the agreement between narrow band models and the line‐by‐line models is about ±2% for fluxes at the atmospheric boundaries, about ±5% for the flux divergence for the troposphere, and to about ±5% for the change of the net flux at the tropopause as CO2 doubles. However, this good agreement does not extend to the majority of the models currently used in climate models. The lack of highly accurate flux observations from within the atmosphere has made it necessary to rely on line‐by‐line model results for evaluating model accuracy. As the intercomparison project has proceeded, the number of models agreeing more closely with the line‐by‐line results has increased as the understanding of the various parameterizations has improved and as coding errors have been discovered. The most recent results indicate that several climate model techniques are in the marginal range of (relative) accuracy for longwave flux calculations for many climate programs. However, not all such models will give such accuracy. It is recommended that a code not be accepted to provide such accuracy until it has made comparisons to the line‐by‐line results of this study. The data necessary to make such comparisons are included herein. However, uncertainties in the physics of line wings and in the proper treatment of the water vapor continuum make it impossible for the line‐by‐line models to provide an absolute reference for evaluating less‐detailed model calculations. A dedicated field measurement program is recommended for the purpose of obtaining accurate spectral radiance rather than integrated fluxes as a basis for evaluating model performance.

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The Advanced Very High Resolution Radiometer (AVHRR) outgoing longwave radiation (OLR) product, which NOAA has been operationally generating since 1979, is a very long data record that has been used in many applications, yet past studies have shown its limitations and several algorithm-related deficiencies. Ellingson et al. have developed the multispectral algorithm that largely improved the accuracy of the narrowband-estimated OLR as well as eliminated the problems in AVHRR. NOAA has been generating High Resolution Infrared Radiation Sounder (HIRS) OLR operationally since September 1998. In recognition of the need for a continuous and long OLR data record that would be consistent with the earth radiation budget broadband measurements in the National Polar-orbiting Operational Environmental Satellite System (NPOESS) era, and to provide a climate data record for global change studies, a vigorous reprocessing of the HIRS radiance for OLR derivation is necessary.This paper describes the development of the new HIRS OLR climate dataset. The HIRS level 1b data from the entire Television and Infrared Observation Satellite N-series (TIROS-N) satellites have been assembled. A new radiance calibration procedure was applied to obtain more accurate and consistent HIRS radiance measurements. The regression coefficients of the HIRS OLR algorithm for all satellites were rederived from calculations using an improved radiative transfer model. Intersatellite calibrations were performed to remove possible discontinuity in the HIRS OLR product from different satellites. A set of global monthly diurnal models was constructed consistent with the HIRS OLR retrievals to reduce the temporal sampling errors and to alleviate an orbital-drift-induced artificial trend. These steps significantly improved the accuracy, continuity, and uniformity of the HIRS monthly mean OLR time series. As a result, the HIRS OLR shows a comparable stability as in the Earth Radiation Budget Satellite (ERBS) nonscanner OLR measurements.HIRS OLR has superb agreement with the broadband observations from Earth Radiation Budget Experiment (ERBE) and Clouds and the Earth's Radiant Energy System (CERES) in the ENSO-monitoring regions. It shows compatible ENSO-monitoring capability with the AVHRR OLR. Globally, HIRS OLR agrees with CERES with an accuracy to within 2 W m Ϫ2 and a precision of about 4 W m Ϫ2. The correlation coefficient between HIRS and CERES global monthly mean is 0.997. Regionally, HIRS OLR agrees with CERES to within 3 W m Ϫ2 with precisions better than 3 W m Ϫ2 in most places. HIRS OLR could be used for constructing climatology for applications that plan to use NPOESS ERBS and previously used AVHRR OLR observations. The HIRS monthly mean OLR data have high accuracy and precision with respect to the broadband observations of ERBE and CERES. It can be used as an independent validation data source. The uniformity and continuity of HIRS OLR time series suggest that it could be used as a reliable transfer reference for the discontinuous broadband...

The recognition of the central role of radiative processes in many proposed climate change mechanisms and the perception of possibly significant uncertainties in the estimates of these fundamental processes led the Joint Scientific Committee of the World Climate Research Programme and the International Radiation Commission of the International Association of Meteorology and Atmospheric Physics to initiate the International Intercomparison of Radiation Codes in Climate Models (ICRCCM). The results from model calculations with specified clear‐and‐cloudy conditions show that many radiation algorithms may have unidentifiable but large errors that may significantly affect the conclusions of the studies in which they are used. This is true for climate modeling but may also be the case for other applications such as the estimation of radiation fluxes at the surface from satellite observations. As the study has progressed over a 4‐year period, there has been a narrowing of results as errors were found in some codes and as the understanding of many modeling problems increased. Many of the results, particularly for clear‐sky conditions, indicate that we are close to the range of (relative) accuracy for calculating flux quantities necessary for many climate programs. However, not all models will give such accuracy. It is recommended that the ICRCCM test cases be used to test radiation algorithms prior to their application to climate‐related problems. The participants feel that the rather large discrepancies revealed during ICRCCM cannot be decisively resolved by further calculation. Therefore the group recommends the organization of a program to simultaneously measure spectral radiance at high spectral resolution along with the atmospheric data necessary to calculate radiances.

Recent climate modeling results point to the Arctic as a region that is particularly sensitive to global climate change. The Arctic warming predicted by the models to result from the expected doubling of atmospheric carbon dioxide is two to three times the predicted mean global warming, and considerably greater than the warming predicted for the Antarctic. The North Slope of Alaska-Adjacent Arctic Ocean (NSA-AAO) Cloud and Radiation Testbed (CART) site of the Atmospheric Radiation Measurement (ARM) Program is designed to collect data on temperature-ice-albedo and water vapor-cloud-radiation feedbacks, which are believed to be important to the predicted enhanced warming in the Arctic. The most important scientific issues of Arctic, as well as global, significance to be addressed at the NSA-AAO CART site are discussed, and a brief overview of the current approach toward, and status of, site development is provided. ARM radiometric and remote sensing instrumentation is already deployed and taking data in the perennial Arctic ice pack as part of the SHEBA (Surface Heat Budget of the Arctic Ocean) experiment. In parallel with ARM's participation in SHEBA, the NSA-AAO facility near Barrow was formally dedicated on 1 July 1997 and began routine data collection early in 1998. This schedule permits the U.S. Department of Energy's ARM Program, NASA's Arctic Cloud program, and the SHEBA program (funded primarily by the National Science Foundation and the Office of Naval Research) to be mutually supportive. In addition, location of the NSA-AAO Barrow facility on National Oceanic and Atmospheric Administration land immediately adjacent to its Climate Monitoring and Diagnostic Laboratory Barrow Observatory includes NOAA in this major interagency Arctic collaboration.