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ISSUES IN THE INTEGRATION OF RESEARCH AND OPERATIONAL SATELLITE SYSTEMS FOR CLIMATE RESEARCH: I. SCIENCE AND DESIGN 9 Earth Radiation Budget INTRODUCTION The Earth radiation budget (ERB) is a combination of the broadband fluxes of solar radiation reflected by Earth and the fluxes of longwave radiation absorbed and emitted by Earth and its atmosphere. The net radiation N at the top of the atmosphere (TOA) may be defined in terms of three quantities (Hartmann, 1994): N = S(1 − α) − I where S is the solar insolation, α is the planetary albedo, and I is the outgoing longwave radiation emitted by Earth to space. The goal of ERB measurement programs is to provide observations of the space and time distributions of both α and I and usually S as well (Wielicki et al., 1995). The radiation budget is a critical component of the energy budget of Earth's climate system and is thus fundamental to the study of climate. The variation of the radiation budget with latitude is the principal force driving the transport of heat from low to high latitudes via the circulations of the atmosphere and oceans. Changes in the radiation budget induced by increasing concentrations of greenhouse gases and aerosols and changes in the solar insolation at the top of the atmosphere define the radiative forcings of climate. Modulations of the radiation budget associated with changing surface and atmospheric conditions, including clouds, give rise to significant climate feedbacks that are considered to be one of the most uncertain aspects in our understanding of climate and climatic change (IPCC, 1995). ERB measurements seek to contribute to two key scientific goals: (1) the determination of how long- and shortwave fluxes are distributed in space and how they vary in time and (2) the development of a quantitative understanding of the links between the radiation budget and the properties of the atmosphere and surface that define that budget. The committee's assessment of the current ERB observation systems and National Polar-orbiting Operational Environmental Satellite System (NPOESS) plans for future long-term measurements is presented in Box 9.1.
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ISSUES IN THE INTEGRATION OF RESEARCH AND OPERATIONAL SATELLITE SYSTEMS FOR CLIMATE RESEARCH: I. SCIENCE AND DESIGN Box 9.1 Findings Present satellite Earth radiation budget (ERB) measurement programs have provided valuable observations that have advanced our understanding of the two science issues described in the introduction to this chapter, and further advances in this understanding are expected in the Earth Observing System (EOS) and post-EOS eras. However, understanding of the radiation budget of the planet is still largely confined to top-of-the-atmosphere (TOA) fluxes; we have not made significant progress in achieving the science goals stated above. Although TOA information is important for a number of reasons, it is unable to give direct insight into processes that influence the radiation budget of the atmosphere and surface. The Clouds and the Earth's Radiant Energy System (CERES) developed for EOS (Wielicki et al., 1996) can meet the TOA requirements defined in the NOAA IORD-1 climate requirements document (IPO NPOESS, 1996). Surface flux requirements, however, cannot be met with these measurements alone and require significant ancillary information. The requirements for some of this additional information (such as cloud base) cannot be met entirely with planned National Polar-orbiting Operational Environmental Satellite System (NPOESS) observations, although the issue of how much cloud base information is contained in the NPOESS observing system is a topic of ongoing research. Future ERB instruments should not be simply a copy of CERES but should have enhanced capabilities that CERES does not provide. The next advance in ERB measurements must come in the direction of providing a better and more direct way of determining the radiation budget at the surface, within the atmosphere, and at the top of the atmosphere. The challenge is to determine the most appropriate enhancement to achieve this goal (one example is an enhanced spectral flux measurement capability). There is an ongoing debate on the climatic value of continuous ERB measurements. Closure on this debate is needed, and the extent to which the data expected from EOS will advance progress toward the stated goals of an ERB measurement program will have to be assessed. Therefore current planning activities should not preclude the incorporation of CERES-like or ideally enhanced ERB observations as part of the NPOESS climate-observing strategy. This should include the NPOESS Preparatory Project Pathfinder mission being planned to bridge the gap between the end of the first EOS missions in 2006 and the start of NPOESS in 2009. The next steps in ERB observations might include: A calibrated spectral imager to fly alongside a CERES-like instrument. Imager data are required for scene identification and to define the appropriate angular model used to retrieve flux information. These data must be calibrated and contain more capable cloud channels beyond those channels used for ocean color. Current AVHRR-like channels are not sufficient for this purpose, but the channels of MODIS and those planned for VIIRS would provide an adequate means for scene identification. Sampling requires measurements from multiple satellites. A minimum of two orbits is required to sample the diurnal cycle, but three are preferable. A measurement strategy that provides a more direct way of determining the radiation budget at the surface and within the atmosphere. The challenge is to determine the most appropriate observing strategy to achieve this goal (such as more spectral flux measurement capability). Correlative measurements of the principal atmospheric constituents governing the distribution and variability of the fluxes measured at the TOA. This ideally should include information on cloud water and ice path as well as aerosol optical depth.
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ISSUES IN THE INTEGRATION OF RESEARCH AND OPERATIONAL SATELLITE SYSTEMS FOR CLIMATE RESEARCH: I. SCIENCE AND DESIGN RADIATION BUDGET IN THE SATELLITE ERA Two ERB activities have contributed significantly to observations of the radiation budget: the Earth Radiation Budget Experiment (ERBE) (Barkstrom et al., 1989) and the Clouds and the Earth's Radiant Energy System (CERES) (Wielicki et al., 1996). Progress in measurements of the ERB from space can be summarized in terms of three observing eras: before 1984, 1984 to 1997, and after 1997. The Pre-ERBE Era (Before 1984) Before ERBE, the radiation budget was determined using a variety of data sets collected from different experimental satellite programs, notably from the Nimbus series of experimental satellites (House, 1985). These early contributions significantly improved our understanding of ERB. For example, the earliest satellite observations led to a downward revision of Earth's albedo, from the pre-satellite-era value of 50 percent to near the current value of 30 to 31 percent (Vonder Haar and Suomi, 1971). Most of the observations before 1984 came from flat-plate sensors that collected radiation over a broad region of Earth (at an approximate resolution of 10 degrees latitude/longitude). Estimates of the effects of clouds on the radiation budget were attempted using these data, but the results were hampered by the coarse resolution of the measurements. Errors attached to these early flux data are difficult to quantify, and the best estimates are approximately 10 Wm−2 (Ellis et al., 1978). The ERBE Era (1984 to 1997) ERBE flew both wide-field-of-view, flat-plate radiometers and the narrow-field-of-view scanning radiometer (Barkstrom et al., 1989). Attention has focused on analyses of measurements from the scanner, which provided data for approximately 6 years before failing in 1990. The improved spatial resolution of flux data achieved with this scanner is perhaps the most important advance offered by ERBE, because it led to better estimates of the difference between cloudy and clear-sky fluxes and thus a better estimate of the effect of clouds on the ERB (Harrison et al., 1990). The usefulness of this information for testing global climate models is now well documented. Monthly mean ERBE flux errors are estimated at 5 to 10 Wm−2. The CERES Era (post-1997) The first of the CERES experiments was launched in 1997 on the Tropical Rainfall Measuring Mission (TRMM) satellite (Wielicki et al., 1996). The measurement approach of CERES is ostensibly the same as that of ERBE, with advances in the improved angular sampling and cloud classification that reduce the monthly mean flux error to 1 or 2 Wm−2. The TRMM CERES instrument has not been operational since August 1998, owing to a technical problem that should not affect the performance of the CERES instruments on Earth Observing System (EOS) AM and EOS PM. OBSERVING STRATEGY There are two approaches to the satellite measurement of radiative fluxes at the TOA. One approach uses uncalibrated operational satellite data; the second approach, which is more direct, uses calibrated, spectrally integrated data such as that provided by ERBE and CERES to determine these fluxes. This more direct approach relies on measurements of broadband (i.e., spectrally integrated) radiances to obtain fluxes and requires angular correction factors (described below). The less direct approach was developed largely out of necessity and was designed to provide information when none was available from other sources (Minnis et al., 1991). The data from the less direct approach are used to fill gaps in time series of radiation budget data and to improve on the less-than-ideal sampling characteristics of existing data. The indirect approach employs the narrow (spectral) band radiance measurements available from scanning operational sensors to determine fluxes. These data are usually uncalibrated and the method of conversion
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ISSUES IN THE INTEGRATION OF RESEARCH AND OPERATIONAL SATELLITE SYSTEMS FOR CLIMATE RESEARCH: I. SCIENCE AND DESIGN requires two corrections: one angular correction to convert radiances to fluxes and a second broadband correction to convert spectral information to broadband information. Estimates of solar fluxes using this method are highly uncertain; their value is dubious and their quality debatable. By contrast, the estimation of longwave fluxes from spectral radiance data from the High-resolution Infrared Sounder (HIRS) has been shown to be more reliable (Ellingson et al., 1994). It should be noted that the instrument capabilities and measurement strategies differ substantially between shortwave and longwave ERB observations. For example, Highly calibrated spectra measurements are much easier to obtain for longwave radiation. So far, only the broadband shortwave ERB measurements have demonstrated sufficient calibration accuracy and stability. Averages of TOA fluxes and surface fluxes, at climate time and space scales, are expected to be closely related for shortwave fluxes (approximately linear) but only weakly related for longwave fluxes. Time sampling and angular sampling are more difficult for shortwave than for longwave ERB, as is clear from the error analysis in Table 9.1. These differences suggest that different strategies may be needed for shortwave and longwave flux measurements to improve on the CERES capability. TABLE 9.1 Error Analysis of ERB Measurements of Flux, Shortwave vs. Longwave Monthly Average Regional 5-yr Trend S0 = 348 Wm−2 S0 = 348 Wm−2 Monthly Zonal Average Equator-Pole Radiation Difference (Wm−2) Monthly Average Regional, 1 Standard Deviation S0 = 348 Wm−2 Instantaneous Pixel, 1 Standard Deviation S0 = 1,000 Wm−2 ERBEa CERESb ERBE CERES ERBE CERES ERBE CERES Shortwave radiation Calibration 2.0 1.0 0.2 0.1 2.1 1.0 6.0 3.0 Angle sampling 0.0 0.0 12.0 4.0 3.3 1.1 37.5 12.5 Time sampling 0.0 0.0 2.9 1.4 3.9 1.9 0.0 0.0 Space sampling 0.3 0.3 0.0 0.0 0.3 0.3 0.0 0.0 Total error 2.0 1.1 12.3 4.3 5.5 2.5 38.0 12.9 Longwave radiation Calibration 2.4 1.2 2.6 1.3 2.4 1.2 2.4 1.2 Angle sampling 0.0 0.0 2.0 0.7 1.6 0.5 12.5 4.2 Time sampling 0.0 0.0 0.6 0.6 1.3 1.3 0.0 0.0 Space sampling 0.2 0.2 0.0 0.0 0.2 0.2 0.0 0.0 Total error 2.4 1.2 3.3 1.6 3.2 1.9 12.7 4.3 Net radiation Calibration 3.1 1.6 2.6 1.3 3.2 1.6 6.5 3.2 Angle sampling 0.0 0.0 12.2 4.1 3.7 1.2 39.5 13.2 Time sampling 0.0 0.0 2.9 1.6 4.1 2.3 0.0 0.0 Space sampling 0.4 0.4 0.0 0.0 0.4 0.4 0.0 0.0 Total 3.1 1.6 12.8 4.5 6.4 3.1 40.1 13.6 Science requirementc 2 to 5 <1 10 1 to 3 10 2 to 5 None 10 NOTE: S0 is the global, annual mean solar insolation at the top of the atmosphere. aERBE: Crosstrack scanner only, two satellites, 2.5° latitude/longitude regions. bCERES: Crosstrack and rotating azimuth scanners, MODIS, three satellites, 1.25° regions. cAs specified by CERES.
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ISSUES IN THE INTEGRATION OF RESEARCH AND OPERATIONAL SATELLITE SYSTEMS FOR CLIMATE RESEARCH: I. SCIENCE AND DESIGN Flux Retrievals TOA fluxes are retrieved from radiance data using precomputed angular models that convert the measured radiances L to hemispheric fluxes F according to F = πLR−1 where R is the Angular Directional Model (ADM), which accounts for the anisotropy of the radiation field. The best way of obtaining broadband fluxes F is to provide calibrated broadband measurements of L. While it is important to maintain a high level of accuracy in the calibration of L, the largest sources of error in retrieved fluxes relate to the uncertainty in the angular models (see Table 9.1). This uncertainty arises partly from the lack of full angular sampling and partly from the complexity of the dependence of R on the properties of the scene, in particular the dependence on cloud properties (such as optical properties and cloud volume). ERBE uses 12 observationally derived ADM types based loosely on cloud volume (Wielicki and Green, 1989). One of the reasons CERES is able to reduce the error associated with the retrieval of flux is the better resolution of the ADMs obtained from a broader angular sample and the better cloud property information from related measurements. The additional information about the scene is derived using data from another sensor, such as the Visible and Infrared Imaging System (VIIRS) on TRMM or the Moderate-resolution Imaging Spectroradiometer (MODIS) on AM and PM. In principle, classifying the ADMs in terms of a larger class of properties provides a way of defining the appropriate ADM more accurately. The number of ADM categories proposed by CERES is more than an order of magnitude larger than the 12 categories used for ERBE. The CERES team estimates that the better-resolved ADMs, derived from the better sampling and classification of CERES, will reduce the ADMs' contribution to error by a factor of approximately 3 (see Table 9.1). Sampling Characteristics The second important component of the TOA flux observing system, and one common to many climate measurement problems, is the nature of the sampling of the measurements. Undersampling of fluxes in space and time is responsible for much of the error budget of fluxes (see Table 9.1). These errors arise from the limitations associated with the asynoptic nature of the sampling of polar-orbiting satellites, which observe different locales at different instants in time. This is a problem for any observing system on polar-orbiting satellites, because space and time behaviors are mixed. Asynoptic sampling biases on time mean properties are a particular problem for those properties that undergo marked diurnal variation, typical of many climate processes, particularly those related to hydrological processes (clouds and precipitation and the resulting radiative fluxes). Although the systematic error associated with undersampling the diurnal cycle is most serious for polar-orbiting measurements, in which diurnal variability is indistinguishable from the time-mean, it surfaces even in processing measurements. It occurs because the diurnal cycle is not perfectly repeatable, it is spatially coherent and therefore difficult to remove, and it is sampled too slowly to be truly resolved in such observations. As a result, time-mean behavior is analyzed by undersampled diurnal variability (as is low-frequency behavior in general), making errors in the two closely related (Salby and Callaghan, 1996). Three distinct approaches have been proposed to address this problem: The most obvious is to use a combination of observations from multiple satellites that provide adequate sampling of the diurnal cycle. In the CERES era, this will include a combination of measurements from the AM and PM satellites as well as from the precessing TRMM satellite. Simulations of the sampling errors in TOA fluxes that are due to undersampling by a single satellite and by combinations of all three satellites demonstrate how these errors can be systematically reduced by adding temporal sampling provided by measurements from two and three satellites. The second approach is to use geostationary data to provide the characteristic diurnal variability of spectral radiances (obtained from geostationary imagers) and apply this variability to a model of the diurnal cycle to correct
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ISSUES IN THE INTEGRATION OF RESEARCH AND OPERATIONAL SATELLITE SYSTEMS FOR CLIMATE RESEARCH: I. SCIENCE AND DESIGN sampling biases in the broadband fluxes (Brooks and Minnis, 1984). A variation of this strategy has been adopted in analyzing CERES data collected under the TRMM. In this case, narrowband, 3-hourly geostationary data are used to provide the magnitude of the diurnal cycle, while a single broadband sensor on a low Earth orbit provides the broadband reference field. The diurnal correction is treated as a second-order correction, and so it is less critically dependent on the calibration of the geostationary data or the broadband/narrowband relationship. The accuracy of this approach will be demonstrated by comparing all three CERES measurements (TRMM, EOS-AM, EOS-PM) to results for any one satellite plus geostationary data. The third approach is to fly a radiation budget instrument on the geostationary satellite, thereby providing proper sampling of the space-time variations of the radiation budget and eliminating the diurnal sample error. The first Geostationary Earth Radiation Budget (GERB) instrument is to be launched as part of the payload of the MeteoSat Second Generation (MSG) in 2001. It will provide an opportunity to assess the nature of sampling errors, at least over the region observed by the MSG 1 field of view, and to test the sampling error corrections developed for the other data sets. There are a number of complications associated with geostationary observations of the ERB. First, the observations are not global. Second, unlike low-Earth-orbiting satellites, the geostationary satellite view limits the climate observations for any given region of Earth to a single viewing zenith angle. This limitation causes an even larger dependence on angular model corrections and will increase the angular sampling errors shown in Table 9.1. As a result, angular sampling errors will be aliased into spatial patterns of the radiation field. The magnitude of these errors has yet to be quantified, but it can be determined once sufficient overlapping CERES and GERB data have been compared. Key Elements of the ERB Observing System The key elements of an ERB observing system are the following: Broadband or narrowband radiometers (preferably scanning) providing calibrated radiance data; A capability for coincident scene identification, including an ability to determine cloud properties, which requires a calibrated imaging radiometer; A data reprocessing strategy applying ADMs determined from accumulated observations. For instance, CERES flux estimates will come from reprocessing data after the CERES ADM statistics are categorized and accumulated. It is not known whether these ADMs constructed from CERES are sufficient for application to other (future) data. Preliminary CERES data sets using ERBE ADMs will be provided for initial releases of data. The factors that contribute to the error budget of the ERB observing system, as suggested in Table 9.1, vary according to the space-time averaging adopted in the data. For example, at instantaneous time scales, angular sampling errors dominate the radiation budget measurements. For daily regional average estimates, time sampling dominates. For monthly regional means, there is a rough balance between time sampling, angle sampling, and calibration uncertainty. For interannual zonal or regional means, calibration uncertainty dominates. The ability to monitor regional and zonal climate change therefore depends most critically on calibration stability for overlapping measurements and on absolute accuracy for nonoverlapping measurements. CALIBRATION AND VALIDATION STRATEGIES Maintenance of a precise and accurate calibration is an important part of the ERB measurement strategy. The goal of CERES is 0.5 percent for longwave fluxes and 1 percent for shortwave fluxes. A key to achieving these calibration goals is the combination of prelaunch calibration and in-orbit calibrations performed approximately every 2 weeks. The prelaunch calibration is performed at a special calibration facility that provides a fundamental traceability of the data to reference standards. In-orbit calibration uses a combination of blackbody sources, deep-space views, and views of the Sun through a diffusing mirror, although there are significant errors associated with the last.
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ISSUES IN THE INTEGRATION OF RESEARCH AND OPERATIONAL SATELLITE SYSTEMS FOR CLIMATE RESEARCH: I. SCIENCE AND DESIGN The current CERES absolute accuracies stated above translate to an absolute accuracy of between 1 and 3 Wm−2 in net flux, similar to the magnitude of greenhouse-gas-related climate forcings. The calibration stability of the CERES instrument on TRMM, however, is better than 0.25 Wm−2 for shortwave and longwave. This stability offers the first demonstrated ability to achieve direct measurements of climate change anomalies with a precision significantly higher than that projected for currently known climate forcings. OPPORTUNITIES The GERB sensor on MSG 1 is expected to be launched in 2001 and continued on both MSG 2 and MSG 3. Unfortunately, current U.S. satellite plans do not include TOA flux measurements beyond EOS. It would be possible, however, to add a radiation budget instrument to the NPOESS Preparatory Project (NPP) Pathfinder mission being planned to bridge the gap between the end of the first EOS missions in 2006 and the start of NPOESS in 2009. Ideally for ERB climate monitoring, the NPP mission would fly with a broadband radiation measurement and calibrated cloud imager, in a 1:30 p.m. Sun-synchronous orbit to overlap EOS PM and the NPOESS 1:30 p.m. orbit. In this case, all three missions (EOS PM, NPP, and NPOESS) would provide the necessary broadband radiation and cloud imager data to continue the climate time series. There is a concern that radiation budget measurements on NPOESS may have a lower priority when it comes to funding than weather measurements. In this case, the ERBE experience might be repeated: funding cuts or cost overruns could eliminate the radiation budget measurement from the NPOESS platform. In the committee's view, NOAA and NASA should develop a strategy to avoid this: NASA flies the prototypes, but NOAA cannot afford to continue the climate time series. From NOAA's perspective, this is a matter of priorities: weather is a higher priority than climate. A solution to this might be for NASA to fund the climate-oriented broadband radiometer, while NOAA provides the spacecraft, calibrated imager, and launch that are required to support the higher-priority weather mission. LIMITATIONS AND THE EVOLUTION STRATEGY The emphasis of existing radiation budget measurements has largely shifted toward reducing the error characteristics of the measurements. As noted above, this involves three phases of activity: Maintaining high calibration accuracy, Improving the accuracy of the ADMs by improving the angular sampling and scene classification, and Improving the time and space sampling. Current ERB satellite measuring programs provide useful information about the TOA fluxes, but this information has its limitations, two of which follow: Progress toward confirming our estimates of radiative forcing of climate requires careful monitoring of the radiation budget. These forcings are small, and except for episodic events like volcanic eruptions (Minnis et al., 1993), the radiative forcings associated with these relatively short periods of observation have been too small to be detectable by present TOA broadband-flux observing systems. Current CERES has a precision that can detect radiative forcing. It is perhaps unrealistic to expect significant improvements in the accuracy of ERB measurements beyond those claimed by CERES. Climate responses such as temperature and humidity profiles, however, have a more discernible and easily detectable spectral signature in the thermal infrared (Goody et al., 1995). Achieving highly calibrated, high-spectral-resolution data, however, may require reduced spatial sampling, such as a nadir-only view and a field-of-view size of roughly 100 km. For use in climate monitoring, further quantification is needed to study the trade-off between the increased signal gained with spectral resolution and the increased noise caused by limited spatial sampling. It may be necessary to combine highly calibrated instruments.
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ISSUES IN THE INTEGRATION OF RESEARCH AND OPERATIONAL SATELLITE SYSTEMS FOR CLIMATE RESEARCH: I. SCIENCE AND DESIGN Developing a quantitative understanding of the links between the radiation budget and the properties of the atmosphere that define these fluxes continues to be an important motivation for research on and measurement of the radiation budget (Wielicki et al., 1995). Progress on this topic continues to be elusive, however, owing in part to the limitations of existing TOA information. The nature of these limitations is exemplified in studies of the effects of clouds on TOA fluxes. It is well documented that the net effect of clouds on TOA fluxes is a balance between changes in solar fluxes associated with the larger albedo of clouds and changes in longwave emission to space associated with changes in cloud top altitude. These changes produce reciprocal effects that approximately balance at the top of the atmosphere but not within the atmosphere or at the surface. With NASA's recent selection of the CloudSat and PICASSO-CENA ESSP missions for launch, key measurements will begin to address this major limitation. The next step in ERB measurements requires a more capable radiation budget observing system than currently exists. This new system should provide observations that will (1) establish a more direct link between the observed fluxes and the parameters that affect these fluxes and (2) provide an improved ability to measure the flux distributions within the atmosphere and at the surface. This will only be partially met by the coincident measurements of relevant properties such as cloud information and ERB fluxes expected in the EOS era. REFERENCES Barkstrom, B., E.F. Harrison, G.L. Smith, R.N. Green, J. Kibler, R. Cess, and the ERBE Science Team. 1989. Earth Radiation Budget Experiment (ERBE) archival and April 1985 results. Bull. Am. Meteorol. Soc. 70: 1254-1262. Brooks, David R., and Patrick Minnis. 1984. Simulation of the Earth's monthly average regional radiation balance derived from satellite measurements. Journal of Climate and Applied Meteorology 23(3): 392-403. Ellingson, R., H-T. Lee, D. Yanuk, and A. Gruber. 1994. Validation of a technique for estimating outgoing long-wave radiation from HIRS radiance observations. J. Atmos. Ocean. Technol. 11: 357-365. Ellis, J.S., T.H. Vonder Haar, S. Levitusand, and A.H. Oort. 1978. The annual variation of the global heat balance of Earth. J. Geophys. Res. 84: 1958-1962. Goody, R.M., R. Haskins, W. Abdou, and L. Chen. 1995. Detection of climate forcing using emission spectra. Issledovaniye Zemli is Kosmosa (Earth Research from Space) 5: 22-23. Harrison, E.F., P. Minnis, B. Barkstrom, V. Ramanathan, R.E.D. Cess, and G.G. Gibsoin. 1990. Seasonal variation of cloud radiative forcing derived from the ERBE . J. Geophys. Res. 95: 18667-18703. Hartmann, D. 1994. Global Physical Climatology. San Diego: Academic Press, 408 pp. House, F.B. 1985. Observing the earth radiation budget from satellites: past, present and a look to the future. Adv. Space Res. 5: 89-98. Integrated Program Office (IPO), National Polar-orbiting Operational Environmental Satellite System (NPOESS). 1996. Integrated Operational Requirements Document (IORD) I. Joint Agency Requirements Group Administrators. 61 pp. + figures. International Panel on Climate Change (IPCC). 1995. The Science of Climate Change, Houghton et al. (eds.), Cambridge, U.K.: Cambridge University Press, 572 pp. Minnis, P., D.F. Young, and E.F. Harrison. 1991. Examination of the relationship between outgoing infrared window and total longwave fluxes using satellite data. J. Climate 4: 1114-1133. Minnis, P., E.F. Harrison, L.L. Stowe, G.G. Gibson, F.M. Denn, D.R. Doelling, and W.L. Smith, Jr. 1993. Radiative climate forcing by Mt. Pinatubo eruption. Science 259: 1411-1415. Salby, M.L., and P. Callaghan. 1996. Sampling error in climate properties derived from satellite measurements: relationship to diurnal variability. J. Climate 10: 18-36. Vonder Haar, T.H., and V. Suomi. 1971. Measurements of the earth's radiation budget from satellites during a 5-year period: I: Extended time and space means. J. Atmos. Sci. 28: 305-314. Wielicki, B., and R.N. Green. 1989. Cloud identification for ERBE radiative flux retrieval. J. Appl. Meteorol. 28: 1133-1146. Wielicki, B., B. Barkstrom, E.F. Harrison, R.B. Lee, G.L. Smith, and J. Cooper. 1996. Clouds and the earth's radiant energy system (CERES): an earth observing system experiment . Bull. Am. Meteorol. Soc. 77: 853-867. Wielicki, B., R.D. Cess, M.D. King, D.A. Randall, and E.F. Harrison. 1995. Mission to planet earth: role of clouds and radiation in climate. Bull. Am. Meteorol. Soc. 76: 2125-2153.
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