Hydrological applications of remote sensing Atmospheric States and Fluxes-Insolation (VIS)

1 Hydrological applications of remote sensing: Atmospheric States and Fluxes-Insolation (VIS) Unique id: hsa053- R T Pinker Department of Meteorology University of Maryland College Park, Maryland 20742 Tel: 301-405-5380 FAX: 314-9482 e-mail: pinker@atmos.umd.edu Keywords: insolation; surface radiative fluxes; shortwave radiation; satellite estimates of surface radiation ABSTRACT Environmental satellites are now considered as promising tools to monitor climate and climate change by providing information on the terrestrial water and energy storage Radiative fluxes are the key forcing functions that determine the exchange of fluxes between the land and the atmosphere at the various temporal and spatial scales For several years now observations from satellites have been used to obtain information on atmospheric and surface radiative fluxes and presently, such information is being derived on a semi-operational basis Reviewed will be the context for the need of such information, methodologies used to obtain it, evaluation of the resulting fluxes, current status of data availability, examples of applications in hydrological studies and climate research, links to international activities, and future prospects INTRODUCTION 1.1 Need for information Information on the spatial and temporal distribution of surface radiative fluxes is required for modeling the hydrologic cycle, for representing interactions and feedbacks between the atmosphere and the terrestrial biosphere (Dickinson, 1986; HendersonSellers, 1993; Prince et al., 1997), and for estimating global oceanic and terrestrial net primary productivity (Goward, 1989; Running et al 1999; Platt, 1986) It is also needed for validating climate models (Garrat et al., 1993; Wild et al., 1995; Wielicki et al., 2002); improving the understanding of transport of heat, moisture, and momentum across the surface-atmosphere interface (Berbery et al., 1999; Baumgartner and Anderson, 1999; Sui et al., 2002); and for improving parameterizations (Chen et al., 1996) Surface shortwave radiative fluxes are of interest due to their dominant role as forcing functions of surface energy budgets (Wood et al., 1997; Wielicki et al., 1995; Mitchell et al., 2003; Rodell et al., 2003) Studies on long-range weather are performed with the aid of numerical weather prediction and general circulation models In order to use model results with confidence, there is a need to evaluate them at scales at which they are implemented Satellite observations are considered to be the only source of global scale information that could be used for model evaluation With the progress made in the use of satellites to probe the atmosphere, the stage was set for focused efforts to advance satellite methods in climate research The Joint Scientific Committee (JSC) of the WCRP endorsed the Global Energy and Water Cycle Experiment (GEWEX) as a core activity (Chahine, 1992) The key GEWEX objectives are: determination of the hydrological cycle and energy fluxes by global measurements of observable atmospheric and surface properties; modeling of the global hydrological cycle; development of capabilities to predict variations of global and hydrological processes and water resources, and their response to environmental change; and foster the development of observational techniques, data assimilation suitable for operational application to long-range weather forecasts, hydrology, and climate predictions Similar objectives play a key role in various national programs For instance, the Interagency Committee on Earth and Environmental Sciences as well as the Intergovernmental Panel on Climate Change have identified clouds and the hydrological cycle to be of highest scientific priority in global change research (Gates et al., 1999; Houghton et al., 2001) Clouds play a major role in determining the net radiative balance, via optical properties and amount Objectives of the NOAA Climate and Global Change Program include “improvement of our ability to observe, understand, predict, an respond to changes in the global environment” Specific national research interests are linked to the GEWEX program in the framework of the continental scale GEWEX experiments such as the GEWEX Continental-scale International Project GCIP/GAPP over the United States, LBA in the Amazon, BALTEX and GAME Methods to derive surface radiative fluxes have been made in the framework of most of these basin scale studies, specifically, over BALTEX by Stuhlman, over LBA by Pereira and Ceballos, over GAME by Takamura et al For example, the specific objectives of the GEWEX Continental-scale International Project (GCIP) and the GEWEX Americas Prediction Project (GAPP) (a continuation of GCIP) (WCRP-67, 1992; NRC, 1998) are: determination of the time/space variability of the hydrologic cycle and the energy budgets over the Mississippi River Basin; development and validation of macro-scale hydrologic models; and, utilization of existing and future satellite observations for achieving these objectives A summary of what was achieved can be found in Roads et al (2003) The interest in surface radiative fluxes for the LBA is to have information needed for evaluating land surface parameterization, and to estimate the surface hydrological and energy budgets over the Amazon Basin, provide otherwise missing surface data that are critical to provide adequate documentation of regional and continental energy and water cycles within the LBA; provide otherwise missing surface data that are critical to enhance the understanding of mesoscale convective and/or land surface processes, provide information to modelers that is critical to demonstrate the use of remotely sensed hydrometeorological variables in connection with models of land surface fluxes One of the major objectives of the LBA program is to improve the understanding of the hydrological cycle in this region, which serves as a major modulator of the hemispheric climate Major land use changes have been taking place in this region This year alone, the largest conflagration since 1925 in the Amazon Rain Forest in the region of Roraima occurred The blaze that has scorched an area of savanna of the size of Maryland and Delaware, spread to the forested area It started about two months ago by settlers who were clearing savanna regions for cropland, and the situation went out of control due ton the dry conditions, caused by the recent El Nino It is anticipated that spaceborne remote sensing capabilities will help to define the basin scale forcing functions, in order to determine how the basin functions as a regional entity Drastic changes have to be accounted for in the models that attempt to estimate the forcing functions by methods of remote sensing This is important because there is not enough confidence in the accuracy of large scale models to project future change, and validation against remotely sensed data is important In particular, due to the lack of pertinent global change data from conventional sources The data to be produced will also enable to improve estimates of Net Primary Productivity in this region, namely, the growth of vegetation and CO exchange 1.2 Feasibility In the last two decades, it has been demonstrated that radiative fluxes could be derived from satellite observations with reasonable accuracy (Pinker et al., 1995; Frouin and Pinker, 1995; Rossow and Zhang, 1995; Whitlock et al., 1995; Ohmura et al., 1998; Gupta et al., 1998) Long-term satellite observations over large spatial scales are now available for implementing inference schemes for deriving radiative fluxes (Schiffer and Rossow, 1995; Rossow and Schiffer, 1999) Methods to derive SW fluxes from satellite observations have been implemented by several groups on different spatial and temporal scales Both METEOSAT, GOES, GMS and polar orbiting satelliteshave been used (Stuhlman et al., 1990; Pinker and Laszlo, 1992; Darnell et al., 1992; Gupta et al., 1992 Chou, 1994; Lee, 1993, Brison et al., 1994; Li et al., 1995; Rossow and Zhang, 1995) Global scale implementation was possible because of the availability of satellite data, which included nformation on the state of the atmosphere (Schiffer and Rossow, 1985) Valuable experience has been gained from the merging of the various global data sets (satellite observations; TOVS retrievals; snow cover) into coherent formats Two SW algorithms, developed at the NASA Langley Research Center (Darnell et al., 1992) and at the University of Maryland (Pinker and Laszlo, 1992) are currently used at NASA Langley Research Center in support of the WCRP/GEWEX activities Attempts to implement retrieval methodologies operationally have been also successful For example, NOAA/NESDIS is supporting GCIP/GAPP activities by developing new operational products from satellite observations [Leese, 1994; 1997] A new product on insolation is a collaborative effort between NOAA/NESDIS, NOAA/National Centers for Environmental Prediction (NCEP), and the University of Maryland Shortwave upwelling and downwelling (0.2-4.0 µm) radiative fluxes at the surface and at the top of the atmosphere, as derived from The inferred shortwave radiative fluxes include total and diffuse quantities (as appropriate), as well as spectral components (e.g., the photosynthetically active radiation (PAR)) The interface between the satellite data and the inference models has been developed at NOAA/NESDIS (Tarpley et al., 1996) NOAA/NCEP provides information on the state of the atmosphere and surface conditions, as available from the analyzed output fields from the Eta model (Rogers et al., 1996) The University of Maryland is involved in model development and modifications (Pinker and Laszlo, 1992a; 1992b; Pinker et al., 2003), sensitivity studies, validation against ground observations, data archiving, and data distribution The Surface Radiation Budget (SRB) model is implemented at NOAA/NESDIS in real time on an hourly basis, for 0.5-degree targets for an area bounded by 66°-126° W longitude and 24°-54° N latitude belts For each target, at appropriate forecast times, selected data from the NCEP regional forecast model are delivered to the satellite data stream, as inputs to the SRB model This approach ensures timely and high quality information input to the satellite inference scheme In turn, the derived radiative fluxes help to diagnose the NCEP forecast model as to its ability to predict correctly radiative fluxes Review of selected inference schemes Methods spanning a wide range of complexity have been developed to derive surface radiative fluxes from satellite observations These have been reviewed in a series of publications by Schmetz (1989; 1991; 1993) The emphasis has been on the critical evaluation of sensitivities to input parameters, as well as physical principles of the methodologies In reviews that followed, the different parts of the spectrum were discussed independently The current status of SW retrievals is summarized in Pinker et al (1995) and Whitlock et al (1995) Methods to derive PAR are described in Frouin and Pinker (1995) A summary of future satellite observations of relevance for SRB research are presented in Wielicki et al (1995) 2.2.1 Physical principles In his discussion of physical principles that allow to derive SRB from satellite observations, Schmetz (1989) has stressed the importance of the close linear coupling between SW (0.2-4.0 mm) reflected radiance at the top of the atmosphere (albedo) and the surface irradiance Cloud extinction (transmittance) and albedo are linearly related since atmospheric constituents not emit radiation at solar wavelength There is a dependence on solar zenith angle; gaseous and aerosol absorption and scattering; surface reflectivity; and clouds 2.2.2 Current status A modified version of the GEWEX SRB algorithm (Pinker and Laszlo, 1992a; Whitlock et al., 1995; Ohmura et al., 1998) (Version 1.1), developed at the University of Maryland is used The algorithm estimates downward and upward fluxes both at the top of the atmosphere (TOA) and at the surface A diagram of the flux retrieval process is presented in Figure The TOA downward flux (Ftd) is calculated from the extraterrestrial solar spectrum by accounting for the variation in sun-earth distance and the position of the sun in the sky relative to the local vertical (solar zenith angle) The downward flux at the surface (Fsd) is obtained by determining what fraction of Ftd reaches the surface as the radiation is transferred through the atmosphere This fraction, which is referred to as the flux transmittance (T), depends on the composition of the atmosphere (e.g., amount of water vapor and ozone, optical thickness of cloud and aerosol), on the length of the path the radiation travels through the atmosphere (determined by the solar zenith angle), and to a lesser degree, on the albedo of the surface Once T is known, the surface downward flux is obtained as Fsd = T Ftd The algorithm estimates T from the satellite derived TOA albedo (as described below) This is possible because for a given atmosphere and surface, the TOA albedo and the flux transmittance are uniquely related to each other Once Fsd is known, the upward flux at the surface (Fsu) is calculated as Fsu = As Fsd, where As is the surface albedo Similarly, the flux reflected to space by the earth-atmosphere system (TOA upward flux, Ftu) is obtained from the product of Ftd and the TOA albedo (At), namely, Ftu = At Ftd T is determined from a comparison of modeled values of the shortwave (0.2-4.0 µm) TOA albedos to the shortwave TOA albedo obtained from the satellite measurement, and the transmittance corresponding to the modeled TOA albedo that matches the satellite-derived value is selected For practical reasons, the pairs of albedos and transmittances are calculated for atmospheres with a non-reflecting lower boundary The surface reflection is added in a separate step The modeled TOA albedos and the corresponding transmittances are calculated at five spectral intervals (0.2-0.4, 0.4-0.5, 0.5-0.6, 0.6-0.7 and 0.7-4.0 µm) for discrete values of the solar zenith angle, amount of water vapor and ozone, aerosol and cloud optical thickness, using the delta-Eddington radiative transfer method described in Joseph et al (1976) Radiative properties of aerosols and clouds are taken from the Standard Radiation Atmospheres (WCP-55, 1983) and from Stephens et al (1984), respectively Absorption by ozone and water vapor are parameterized following Lacis and Hansen (1974) The albedo-transmittance pairs are made available in a lookup table for the algorithm separately for clear and cloudy 10 atmospheres, and the flux transmittances for clear and cloudy skies are determined by matching the satellite-observed clear and cloudy shortwave TOA albedos, respectively For a given solar zenith angle, surface albedo and amount of ozone and water vapor, the matching process involves the adjustment of the aerosol optical depth for clear sky and that of the cloud optical depth for cloudy sky For GCIP/GAPP, the satellite-observed TOA shortwave albedo is obtained from the visible (0.55-0.75 µm) radiance measured by the imager instrument onboard the GOES-8 satellite through spectral and angular transformations (Zhou et al., 1996) (for details see section 3.2) In deriving the fluxes, first the surface albedo is estimated from the “clearest” shortwave TOA albedo observed over a number of days (clear-sky composite albedo), and then corrected for Rayleigh scattering, aerosol extinction, and absorption by ozone and water vapor In this step, the amount of aerosol is specified according to the Standard Radiation Atmospheres (WCP55, 1983) For GCIP/GAPP, the column amount of ozone is taken from the McClatchy atmospheres (Kneizys et al., 1988) as a function of latitude and season, while water vapor is from the NCEP Eta model Next, albedo-transmittance pairs are selected from the lookup table according to the solar zenith angle, water vapor and ozone amount, and are combined with the surface albedo to yield shortwave TOA albedos One set of pairs is for varying values of aerosol optical depth (clear atmosphere), and the other is for varying values of cloud optical depth (cloudy atmosphere) Finally, the shortwave albedos derived from the instantaneous satellite-observed clear-sky and cloudy-sky radiances are matched with the clear and cloudy sets of albedo-transmittance pairs, and clear-sky and cloudy-sky transmittances, and from these, clear-sky and cloud-sky fluxes are obtained The clear-sky and cloudysky fluxes are then weighted according to the 47 Geosciences, Environment and Resources, National Research Council, National Academy Press, Washington DC, 93 pages Ohmura, A., E G Dutton, B Forgan, C Frohlich, H Gilgen, H Hegner, A Heimo, G Konig-Langlo, B McArthur, G Muller, R Philipona, R T Pinker, C H Whitlock, K Dehne, and M Wild, Baseline Surface Radiation Network 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to broadband transformations for GOES 8, Second International Scientific Conference on the Global Energy and Water Cycle, 17-21 June 1996, Washington, D.C., 1996 54 FURTHER READING TABLES AND CAPTIONS Table Characteristics of the GOES-8 satellite (after Menzel and Purdom, 1994) Channel Wavelength (µm) Field of view (km) Sub-point resol (Km) 0.52-0.72 1.0x1.0 0.57x1.0 3.78-4.03 4.0x4.0 2.3x4.0 6.47-7.02 8.0x8.0 2.3x8.0 10.2-11.2 4.0x4.0 2.3x4.0 11.5-12.5 4.0x4.0 2.3x4.0 Table Operational limits on measured short-wave radiation (Wm-2) [After Shi and Long, 2002] Best Typical Worst Diffuse SW 4.0 + 1.4 9.0 + 3.1 12.0+3.8 Direct Norma; 6.3 + 3.3 13.3 + 6.3 12.0 + 3.8 Upwelling SW 11.1 + 2.8 FIGURES AND CAPTIONS Manifest Document Elements Supplied Article title Contributor(s) name(s) Basic affiliation Keywords 55 Abstract Introduction Main text Acknowledgements Related articles 10 Software links textbox 11 References 12 Further reading 13 Tables and captions 14 Figures and captions 15 Schemes and captions 16 List of Files filename the application/version used to create the file type of platform/computer operating system you use whether it is black and white or colour List of Figures File Filename Application/version Platform/OS RESULTS The following notations will be used: stda-shortwave toa downward all-sky stua-shortwave toa upward all-sky stna-shortwave toa net all-sky (down-up) ssda-shortwave surface downward all-sky ssua-shortwave surface upward all-sky Color or black and white 56 ssna-shortwave surface net all-sky (down-up) saaa-shortwave atmosphere absorbed all-sky (stna-ssna) vsda-visible surface downward all-sky In Table we present the global annual averages for eleven years (1983-1994) of all the above parameters Presented are mean values, as well as the spatial standard deviations, minimum and maximum values, and the number of cell used in the computations Table1 Global Annual Average: July 1983-June 1994 Parameter Mean Std Min Max N stda stua stna ssda ssua ssna saaa vsda 302.5 104.7 197.7 163.5 30.9 132.5 65.2 76.5 85.6 17.1 90.9 59.4 25.6 72.3 20.7 28.8 160.4 56.2 59.4 67.2 5.9 22.9 34.0 31.3 415.1 174.9 355.1 291.9 135.7 273.0 117.7 136.6 10368 10368 10368 10368 10368 10368 10368 10368 Table Parameter: stna stna JUL AUG SEP OCT NOV DEC JAN FEB MAR APR MAY Monthly averages for period: July 1983-June 1994 Mean 206.389 196.741 186.315 188.871 199.249 211.676 209.542 199.205 187.925 190.717 198.808 Std 121.167 111.006 111.917 114.7 123.013 129.156 127.949 119.254 116.182 113.468 117.546 Min 0 0 0 0 0 Max 418.591 387.945 370.509 390.454 410.345 426.155 419.809 394.982 381.318 383.318 395.882 N 10060 10186 10368 10368 10228 9934 10042 10244 10368 10256 10096 57 JUN 207.805 123.148 419.78 9936 Tabl e3 Parameter: stda ssda JUL AUG SEP OCT NOV DEC JAN FEB MAR APR MAY JUN Table Monthly averages for period: July 1983-June 1994 Mean 165.07 154.176 146.23 154.122 171.967 186.876 180.507 164.172 149.978 155.455 166.916 172.038 Std 98.327 86.1152 84.9432 84.7851 101.407 117.14 109.52 90.2012 87.6047 86.7445 95.9468 103.679 Min 0 0 0 0 0 0 Max 353.609 324.091 307.036 330.755 343.936 399.227 354.464 321.236 318.445 320.436 335.036 356.95 N 10060 10186 10368 10368 10228 9934 10042 10244 10368 10256 10096 9936 58 Parameter: stda stda JUL AUG SEP OCT NOV DEC JAN FEB MAR APR MAY JUN Mean 309.249 290.698 272.57 285.716 314.61 338.89 329.86 302.684 277.849 286.29 305.372 317.951 Parameter: stda Month JUL AUG SEP OCT NOV DEC JAN FEB MAR APR MAY JUN 1.4 Monthly averages for period: July 1983-June 1994 Std 175.195 143.622 133.144 137.594 171.38 195.957 184.561 148.872 135.788 135.743 164.157 184.266 Min 0 0 0 0 0 0 Max 475.473 440.009 427.827 441.945 479.182 547.6 498.9 460.536 436.464 437.864 460.118 515.26 N 10060 10186 10368 10368 10228 9934 10042 10244 10368 10256 10096 9936 Monthly averages for period:July 1983-June 1994 Mean 69.3656 64.3945 59.0091 61.0818 66.5736 71.2107 69.3879 64.2585 59.3446 61.9929 66.9179 70.5333 Std 41.3817 34.2803 31.0304 30.5605 36.3100 40.6895 38.8285 32.4909 30.3841 30.8713 37.5007 42.3718 Min 0 0 0 0 0 0 Max 132.336 128.545 122.273 122.082 126.200 136.791 136.491 126.155 124.436 124.273 128.200 132.250 N 10060 10186 10368 10368 10228 9934 10042 10244 10368 10256 10096 9936 Content of CD-ROM In addition to this “Background” folder, the CD-ROM contains the following folders: Documentation-html and text files giving information about the data (structure parameters, missing values, etc.) Software-sample Fortran programs for reading the data and sample outputs produced by these programs 59 Data-the daily and monthly binary data files Images-images of monthly mean fluxes surface shortwave downward fluxes; surface PAR downward fluxes; top of the atmosphere net shortwave fluxes; top of the atmosphere shortwave cloud forcing; and atmospheric all-sky shortwave absorption, all in units of Wm-2 Grid structure Each file has information for 10368 (2.5 by 2.5 degree, equal-angle) cells (144 longitudes by 72 latitudes) All cells are present, even when data are missing The cells are written sequentially, proceeding eastward through the latitude zone, then northward to the next latitude zone The center lat/lon coordinates of the first cell are 88.75 S, 1.25 E, and those of the last cell are 88.75 N, 358.75 E The applet on the CD-ROM can be used to extract data The data can also be accessed manually by going to the data subdirectory All the files are in an equal angle format and compressed using gzip The files can be uncompressed using WinZip on Windows, Stuffit under MacOS, or with gunzip on any unix like operating system This applet will run properly either under Netscape 4.05 or higher or the Java(TM) Plugin or In Internet Explorer with the Java(TM) Plugin Installed Due to technical issues related to Java implementation in Microsoft Internet Explorer, the applet will not run in Internet Explorer unless the Java(TM) plugin is installed For your convenience a copy of Netscape and the Java(TM) Plugin for Windows is included on this cdrom In order to allow this applet to write the extracted data from the CD-ROM to local storage, it has been signed by the University of Maryland Certificate Authority This applet will not be run properly unless you accept the University of Maryland as a trusted entity Please go to the University of Maryland Certificate Authority web site and follow the instructions to install the University of Maryland certificate in your browser (this requires you to be connected to the internet) 60 Adler, R F., C Kidd, G Petty, M Morissey, and H M Goodman, 2001: Intercomparison of Global Precipitation Products: the Third Precipitation Intercomparison Project (PIP-3) Bull Amer Meteor Soc., 82(7), 1377-1396 However, given a focus on insolation, I recommend that include a discussion of the AGRMET product produced by the Air Force Weather Agency, which we use in GLDAS Section 4.b.1) in the GLDAS overview paper (in press at BAMS) describes AGRMET I'll send that paper attached to a separate message Jesse can give you some figures   NASA Langley Research Center, where the first version of  the model was implemented with ISCCP C1 data.  We have  delivered version 2.1 to NASA Langley, where work is in  progress to prepare the infrastructure for algorithm  implementation at 1 degree resolution, to be compatible with the CERES data structure.  We participated in the recent EOS 61 Waves and SWAM Workshops, for coordination of satellite  retrieval validation activities ... measurements of observable atmospheric and surface properties; modeling of the global hydrological cycle; development of capabilities to predict variations of global and hydrological processes and water... use of remotely sensed hydrometeorological variables in connection with models of land surface fluxes 5 One of the major objectives of the LBA program is to improve the understanding of the hydrological. .. wind, humidity and pressure to forecast land surface states, and errors in any of these quantities can greatly impact simulations of soil moisture, runoff, snow pack and latent and sensible heat