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- Author or Editor: R. G. Ellingson x
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Abstract
Throughout most of the shortwave spectrum, atmospheric gases do not absorb the abundant amount of incoming solar radiation. The shortwave-scattering albedo of clouds is very large. The combination of large amounts of incoming solar radiation, low gaseous absorptivity, and large cloud-scattering albedo enables clouds at one level of the atmosphere to affect the shortwave radiative transfer at all other atmospheric levels. Absorption by atmospheric gases is much stronger in the longwave. This localizes the effects of clouds in the longwave. Since longwave absorption is weakest in the window region (8–12 μm), cloud effects there will have the greatest chance of propagating to other levels of the atmosphere. In partially overcast conditions, individual cloud geometry and optical properties are important factors. Longwave calculations of most GCMs ignore individual cloud geometry. For liquid water clouds, the optical properties of clouds are also ignored.
Previous work in the window region by Takara and Ellingson considered opaque clouds with no absorption or emission by atmospheric gases. Under those conditions, the effect of cloud scattering was comparable to cloud geometry. In this work, the comparison of longwave scattering and geometric effects in the window region is improved by including partially transparent clouds and adding absorption and emission by atmospheric gases. The results show that for optically thick water clouds, it is sufficient to model the geometry; scattering can be neglected. The window region errors are less than 5 W m−2 for fluxes and 0.05 K day−1 for heating rates. The flat-plate approximation worked for ice clouds; the window region flux errors are less than 3 W m−2 with heating rate errors less than 0.05 K day−1.
Abstract
Throughout most of the shortwave spectrum, atmospheric gases do not absorb the abundant amount of incoming solar radiation. The shortwave-scattering albedo of clouds is very large. The combination of large amounts of incoming solar radiation, low gaseous absorptivity, and large cloud-scattering albedo enables clouds at one level of the atmosphere to affect the shortwave radiative transfer at all other atmospheric levels. Absorption by atmospheric gases is much stronger in the longwave. This localizes the effects of clouds in the longwave. Since longwave absorption is weakest in the window region (8–12 μm), cloud effects there will have the greatest chance of propagating to other levels of the atmosphere. In partially overcast conditions, individual cloud geometry and optical properties are important factors. Longwave calculations of most GCMs ignore individual cloud geometry. For liquid water clouds, the optical properties of clouds are also ignored.
Previous work in the window region by Takara and Ellingson considered opaque clouds with no absorption or emission by atmospheric gases. Under those conditions, the effect of cloud scattering was comparable to cloud geometry. In this work, the comparison of longwave scattering and geometric effects in the window region is improved by including partially transparent clouds and adding absorption and emission by atmospheric gases. The results show that for optically thick water clouds, it is sufficient to model the geometry; scattering can be neglected. The window region errors are less than 5 W m−2 for fluxes and 0.05 K day−1 for heating rates. The flat-plate approximation worked for ice clouds; the window region flux errors are less than 3 W m−2 with heating rate errors less than 0.05 K day−1.
Abstract
Comparisons of zonally averaged outgoing longwave fluxes estimated from 10 μm radiance observations on NOAA polar orbiting satellites with flat plate observations on the Nimbus 6 ERB experiment have shown the NOAA estimates to be systematically larger than the ERB data. The NOAA flux estimation technique has been examined with the use of a new radiative transfer model and with several new assumptions concerning the properties of clouds in the field of view of the satellite to determine if there are situations which will lead to such differences. The analysis indicates that the operational estimation technique overestimates fluxes for middle and high cloud conditions. The use of new assumptions concerning the cloud cover and the use of a radiation model different from that used in the initial study will reduce the NOAA-ERB flux differences by approximately 30%.
Abstract
Comparisons of zonally averaged outgoing longwave fluxes estimated from 10 μm radiance observations on NOAA polar orbiting satellites with flat plate observations on the Nimbus 6 ERB experiment have shown the NOAA estimates to be systematically larger than the ERB data. The NOAA flux estimation technique has been examined with the use of a new radiative transfer model and with several new assumptions concerning the properties of clouds in the field of view of the satellite to determine if there are situations which will lead to such differences. The analysis indicates that the operational estimation technique overestimates fluxes for middle and high cloud conditions. The use of new assumptions concerning the cloud cover and the use of a radiation model different from that used in the initial study will reduce the NOAA-ERB flux differences by approximately 30%.
Abstract
General circulation models use the flat black plate approximation to calculate longwave radiative transfer through broken cloud fields. This neglects both cloud geometry and longwave optical properties. It is known that cloud geometry is important in longwave transmission. Since the longwave single scattering albedo is as high as 0.75, it is also necessary to determine the importance of scattering effects. A Monte Carlo simulation was used to compute the upward and downward fluxes for simplified cloud fields with a range of cloud geometries and optical properties. Based on these fluxes, the effective cloud fractions were found. The results show that scattering can have a significant effect on fluxes and effective cloud fractions. The effects are largest for low cloud upward fluxes and high cloud downward fluxes. To attain high percentage accuracy, it is necessary to model both cloud geometry and scattering.
Abstract
General circulation models use the flat black plate approximation to calculate longwave radiative transfer through broken cloud fields. This neglects both cloud geometry and longwave optical properties. It is known that cloud geometry is important in longwave transmission. Since the longwave single scattering albedo is as high as 0.75, it is also necessary to determine the importance of scattering effects. A Monte Carlo simulation was used to compute the upward and downward fluxes for simplified cloud fields with a range of cloud geometries and optical properties. Based on these fluxes, the effective cloud fractions were found. The results show that scattering can have a significant effect on fluxes and effective cloud fractions. The effects are largest for low cloud upward fluxes and high cloud downward fluxes. To attain high percentage accuracy, it is necessary to model both cloud geometry and scattering.
Abstract
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.
Abstract
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.
The U.S. Department of Energy has established an unmanned aerospace vehicle (UAV) measurement program. The purpose of this paper is to describe the evolution of the program since its inception, review the progress of the program, summarize the measurement capabilities developed under the program, illustrate key results from the various UAV campaigns carried out to date, and provide a sense of the future direction of the program. The Atmospheric Radiation Measurement (ARM)–UAV program has demonstrated how measurements from unmanned aircraft platforms operating under the various constraints imposed by different science experiments can contribute to our understanding of cloud and radiative processes. The program was first introduced in 1991 and has evolved in the form of four phases of activity each culminating in one or more flight campaigns. A total of 8 flight campaigns produced over 140 h of science flights using three different UAV platforms. The UAV platforms and their capabilities are described as are the various phases of the program development. Examples of data collected from various campaigns highlight the powerful nature of the observing system developed under the auspices of the ARM–UAV program and confirm the viability of the UAV platform for the kinds of research of interest to ARM and the clouds and radiation community as a whole. The specific examples include applications of the data in the study of radiative transfer through clouds, the evaluation of cloud parameterizations, and the development and evaluation of cloud remote sensing methods. A number of notable and novel achievements of the program are also highlighted.
The U.S. Department of Energy has established an unmanned aerospace vehicle (UAV) measurement program. The purpose of this paper is to describe the evolution of the program since its inception, review the progress of the program, summarize the measurement capabilities developed under the program, illustrate key results from the various UAV campaigns carried out to date, and provide a sense of the future direction of the program. The Atmospheric Radiation Measurement (ARM)–UAV program has demonstrated how measurements from unmanned aircraft platforms operating under the various constraints imposed by different science experiments can contribute to our understanding of cloud and radiative processes. The program was first introduced in 1991 and has evolved in the form of four phases of activity each culminating in one or more flight campaigns. A total of 8 flight campaigns produced over 140 h of science flights using three different UAV platforms. The UAV platforms and their capabilities are described as are the various phases of the program development. Examples of data collected from various campaigns highlight the powerful nature of the observing system developed under the auspices of the ARM–UAV program and confirm the viability of the UAV platform for the kinds of research of interest to ARM and the clouds and radiation community as a whole. The specific examples include applications of the data in the study of radiative transfer through clouds, the evaluation of cloud parameterizations, and the development and evaluation of cloud remote sensing methods. A number of notable and novel achievements of the program are also highlighted.
Abstract
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.
Abstract
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 intercomparison of radiation codes used in retrieving upper-tropospheric humidity (UTH) from observations in the ν2 (6.3 μm) water vapor absorption band was performed. This intercomparison is one part of a coordinated effort within the Global Energy and Water Cycle Experiment Water Vapor Project to assess our ability to monitor the distribution and variations of upper-tropospheric moisture from spaceborne sensors. A total of 23 different codes, ranging from detailed line-by-line (LBL) models, to coarser-resolution narrowband (NB) models, to highly parameterized single-band (SB) models participated in the study. Forward calculations were performed using a carefully selected set of temperature and moisture profiles chosen to be representative of a wide range of atmospheric conditions. The LBL model calculations exhibited the greatest consistency with each other, typically agreeing to within 0.5 K in terms of the equivalent blackbody brightness temperature (Tb ). The majority of NB and SB models agreed to within ±1 K of the LBL models, although a few older models exhibited systematic Tb biases in excess of 2 K. A discussion of the discrepancies between various models, their association with differences in model physics (e.g., continuum absorption), and their implications for UTH retrieval and radiance assimilation is presented.
An intercomparison of radiation codes used in retrieving upper-tropospheric humidity (UTH) from observations in the ν2 (6.3 μm) water vapor absorption band was performed. This intercomparison is one part of a coordinated effort within the Global Energy and Water Cycle Experiment Water Vapor Project to assess our ability to monitor the distribution and variations of upper-tropospheric moisture from spaceborne sensors. A total of 23 different codes, ranging from detailed line-by-line (LBL) models, to coarser-resolution narrowband (NB) models, to highly parameterized single-band (SB) models participated in the study. Forward calculations were performed using a carefully selected set of temperature and moisture profiles chosen to be representative of a wide range of atmospheric conditions. The LBL model calculations exhibited the greatest consistency with each other, typically agreeing to within 0.5 K in terms of the equivalent blackbody brightness temperature (Tb ). The majority of NB and SB models agreed to within ±1 K of the LBL models, although a few older models exhibited systematic Tb biases in excess of 2 K. A discussion of the discrepancies between various models, their association with differences in model physics (e.g., continuum absorption), and their implications for UTH retrieval and radiance assimilation is presented.
