Skip to main content

Advertisement

SpringerLink
Log in

Review on estimation methods of the Earth’s surface energy balance components from ground and satellite measurements

  • Published:
Journal of Earth System Science Aims and scope Submit manuscript

Abstract

Accurate estimation of the Earth’s surface energy balance (SEB) components is very much important for characterising the environmental, hydrological and bio-geophysical processes to predict the weather and climate or climate change. This narrative review summarises the basic theories of estimation methods of the solar (shortwave) radiation, thermal (longwave) radiation and evapotranspiration (latent heat flux) from both the ground and satellite measurements, which are inherently complex to measure at large scale. This paper discusses the reviews of prior and recent advances in the estimation methods and models by focusing their advantages, disadvantages and recommendations. Uncertainties associated with satellite estimations and some key directions for further studies are also discussed, including the status of ground-based measurements at regional and global scales and the advent of new satellite technologies for quantifying the SEB components more accurately. This study infers that the further advances in the satellite remote sensing and worldwide ground-based measurement networks will enhance the capabilities for the potential estimation of the SEB parameters as well as monitoring the global water and energy cycles to develop significant environmental studies for the betterment of living on the Earth.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  • Allen R, Tasumi M and Trezza R 2007 Satellite-based energy balance for mapping evapotranspiration with internalized calibration (METRIC)-model; J. Irrig. Drain. Eng.  133 380–394.

    Google Scholar 

  • Allen R, Burnett B, Kramber W H, Kjaersgaard J, Kilic A, Kelly C and Trezza R 2013 Automated calibration of the METRIC-landsat evapotranspiration process; J. Am. Water Resour. Assoc.  49 563–576.

    Google Scholar 

  • Amatya P, Ma Y, Han C, Wang B and Devkota L 2015 Mapping regional distribution of land surface heat fluxes on the southern side of the central Himalayas using TESEBS; Theor. Appl. Climatol.  124 835–846.

    Google Scholar 

  • Anderson M C, Norman J M, Mecikalski J R, Otkin J A and Kustas W P 2007 A climatological study of evapotranspiration and moisture stress across the continental United States based on thermal remote sensing: 1. Model formulation; J. Geophys. Res. Atmos.  112 D10117:1–D10117:17.

  • ASCE–EWRI 2005 The ASCE standardized reference evapotranspiration equation; ASCE–EWRI Standardization of Reference Evapotranspiration Task Committee Report, ASCE Reston, VA.

  • Augustine J, Hodges G, Cornwall C, Michalsky J and Medina C 2005 An update on SURFRAD – The GCOS surface radiation budget network for the continental United States; J. Atmos. Oceanic Technol.  22 1460–1472.

    Google Scholar 

  • Baldocchi D, Falge E, Gu L, Olson R, Hollinger D, Running S, Anthoni A, Bernhofer C, Davis K, Evans R, Fuentes J, Goldstein A, Katul G, Law B, Lee X H, Malhi Y, Meyers T, Munger W, Oechel W, Pilegaard K and Wofsy S 2001 A new tool to study the temporal and spatial variability of ecosystem-scale carbon dioxide, water vapor, and energy flux densities; Bull. Am. Meteor. Soc.  82 2415–2434.

    Google Scholar 

  • Barkstrom B R and Smith G L 1986 The earth radiation budget experiment: Science and implementation; Rev. Geophys.  24 379–390.

    Google Scholar 

  • Baseline surface radiation network (n.d.) http://www.bsrn.awi.de/

  • Bastiaanssen W 1995 Regionalization of surface flux densities and moisture indicators in composite terrain; PhD Thesis, Wageningen Agricultural University, Wageningen, The Netherlands.

  • Bastiaanssen W 2000 SEBAL-based sensible and latent heat fluxes in the irrigated Gediz Basin Turkey; J. Hydrol.  229 87–100.

    Google Scholar 

  • Bastiaanssen W, Menenti M, Feddes R and Holtslag A 1998a A remote sensing surface energy balance algorithm for land (SEBAL): 1. Formulation; J. Hydrol.  212–213 198–212.

    Google Scholar 

  • Bastiaanssen W, Pelgrum H, Wang J, Ma Y, Moreno J, Roerink G and van der Wal T 1998b A remote sensing surface energy balance algorithm for land (SEBAL): 2. Validation; J. Hydrol.  212–213 213–229.

    Google Scholar 

  • Bastiaanssen W, Noordman E, Pelgrum H, Davids G, Thoreson B and Allen R 2005 SEBAL model with remotely sensed data to improve water-resources management under actual field conditions; J. Irrig. Drain. Eng.  131 85–93.

    Google Scholar 

  • Bastiaanssen W, Thoreson B, Clark B and Davids G 2010 Discussion of application of SEBAL model for mapping evapotranspiration and estimating surface energy fluxes in South-Central Nebraska by Ramesh K Singh, Ayse Irmak, Suat Irmak and Derrel L Martin; J. Irrig. Drain. Eng.  136 282–283.

    Google Scholar 

  • Bonan G B 2008 Ecological Climatology: Concepts and Application; 2nd edn, Cambridge University Press, Cambridge, Chapter 1, pp. 1–24.

  • Bowen I S 1926 The ratio of heat losses by conduction and evaporation from any water surface; Phys. Rev.  27 779–787.

    Google Scholar 

  • Carlson T N, Gillies R R and Perry E M 1994 A method to make use of thermal infrared temperature and NDVI measurements to infer surface soil water content and fractional vegetation cover; Remote Sens. Rev.  9 161–173.

    Google Scholar 

  • Carrillo-Rojas G, Silva B, Córdova M, Célleri R and Bendix J 2016 Dynamic mapping of evapotranspiration using an energy balance-based model over an Andean Páramo Catchment of Southern Ecuador; Remote. Sens. (Basel)  8 160.

    Google Scholar 

  • Chen X, Su Z, Ma Y, Yang K and Wang B 2013 Estimation of surface energy fluxes under complex terrain of Mt. Qomolangma over the Tibetan Plateau; Hydrol. Earth Syst. Sci.  7 1607–1618.

    Google Scholar 

  • Choudhury B and Menenti M 1993 Parameterization of land surface evaporation by means of location dependent potential evaporation and surface temperature range; Department for Environment, Food and Rural Affairs (Defra), London, UK, Vol. 212, pp. 561–568.

  • Cros S and Wald L 2003 Survey of the main databases providing solar radiation data at ground level; In: Proceedings of the 23rd EARSeL annual symposium remote sensing in transition (ed.) Goossens R I and Ghent, Belgium, pp. 491–497.

  • Dawson T E, Burgess S S O, Tu K P, Oliveira R S, Santiago L S and Fisher J B 2007 Nighttime transpiration in woody plants from contrasting ecosystems; Tree Physiol.  27 561–575.

    Google Scholar 

  • Diak G R, Mecikalski J R, Anderson M C, Norman J M, Kustas W P, Torn R D and Dewolf R L 2004 Estimating land surface energy budgets from space: Review and current efforts at the university review and current efforts at the University of Wisconsin-Madison and USDA-ARS; Bull. Am. Meteor. Soc.  85(1) 65–76.

    Google Scholar 

  • Dutta D, Mahalakshmi D, Singh M, Goyal P, Paul S, Sharma J and Dadhwal V 2015 Satellite-Based estimation of instantaneous radiative fluxes over continental USA – A case study; J. Indian Soc. Remote Sens.  43(4) 1–9.

    Google Scholar 

  • Ellingson R, Ferraro R and Gruber A 1983 An examination of a technique for estimating the longwave radiation budget from satellite radiance observations; Adv. Space Res.  2 21–23.

    Google Scholar 

  • Fisher J, Tu K and Baldocchi D 2008 Global estimates of the land-atmosphere water flux based on monthly AVHRR and ISLSCP-II data, validated at 16 FLUXNET sites; Remote Sens. Environ.  112 901–919.

    Google Scholar 

  • FLUXNET A Global Network (n.d.) https://fluxnet.ornl.gov/

  • Foken T 2008 The energy balance closure problem: An overview; Ecol. Appl.  18 1351–1367.

    Google Scholar 

  • Gavilán P and Berengena J 2007 Accuracy of the Bowen ratio-energy balance method for measuring latent heat flux in a semiarid advective environment; Irrigation Sci.  25 127–140.

    Google Scholar 

  • Gebler S, Hendricks Franssen H-J, Pütz T, Post H, Schmidt M and Vereecken H 2015 Actual evapotranspiration and precipitation measured by lysimeters: A comparison with eddy covariance and tipping bucket; Hydrol. Earth Syst. Sci.  19 2145–2216.

    Google Scholar 

  • Gilgen H and Ohmura A 1999 The global energy balance archive; Bull. Am. Meteor. Soc.  80 831–850.

    Google Scholar 

  • Global Energy and Water Cycle Exchange (n.d.) http://www.gewex.org/

  • Guide to Meteorological Instruments and Methods of Observation (\(7{{\rm th}}\) edn) 2008 https://www.wmo.int/pages/prog/HrBgcos/documents/gruanmanuals/CIMO/CIMO_Guide-HrB7th_Edition-2008.pdf

  • Ha W, Kolb T, Springer A, Dore S, O’Donnell F, Morales R, Lopez S M and Koch G 2015 Evapotranspiration comparisons between eddy covariance measurements and meteorological and remote-sensing-based models in disturbed ponderosa pine forests; Ecohydrology  8 1335–1350.

    Google Scholar 

  • Harries J E, Russell J E, Hanafin J A, Brindley H, Futyan J, Rufus J, Kellock S, Matthews G, Wrigley R, Last A, Mueller J, Mossavati R, Ashmall J, Sawyer E, Parker D, Caldwell M, Allan R P, Smith A, Bates M J and Coan B 2005 The geostationary earth radiation budget project; Bull. Am. Meteor. Soc.  83 977–992.

    Google Scholar 

  • Hartmann D 1994 Global Physical Climatology; International Geophysics Series Academic Press, London, UK, 56p.

    Google Scholar 

  • Hena M, Ali M and Rahman M 2013 A simple statistical model to estimate incident solar radiation at the surface from NOAA AVHRR satellite data; Int. J. Inf. Technol. Comput. Sci.  02 36–41.

    Google Scholar 

  • Huang G, Ma M, Liang S, Liu S and Li X 2011 A LUT based approach to estimate surface solar irradiance by combining MODIS and MTSAT data; J. Geophys. Res.  116 D22201:1–D22201:14.

    Google Scholar 

  • Jackson R, Idso S and Reginato R P 1981 Canopy temperature as a crop water stress indicator; Water Resour. Res.  17 1133–1138.

    Google Scholar 

  • Jacobowitz H and Tighe R 1984 The earth radiation budget derived from the Nimbus-7 ERB experiment; J. Geophys. Res.  89 4997–5010.

    Google Scholar 

  • Jiao Z, Yan G, Zhao J, Wang T and Chen L 2015 Estimation of surface upward longwave radiation from MODIS and VIIRS clear-sky data in the Tibetan Plateau; Remote Sens. Environ.  162 221–237.

    Google Scholar 

  • Kalma J D, McVicar T R and McCabe M F 2008 Estimating land surface evaporation: A review of methods using remotely sensed surface temperature data; Surv. Geophys.  29 421–469.

    Google Scholar 

  • Kawai Y and Kawamura H 2005 Validation and improvement of satellite derived surface solar radiation over the northwestern Pacific Ocean; J. Oceanogr.  61 79–89.

    Google Scholar 

  • Kiehl J T and Trenberth K E 1997 Earth’s annual global mean energy budge; Bull. Am. Meteor. Soc.  78 197–208.

    Google Scholar 

  • Kim D and Ramanathan V 2008 Solar radiation budget and radiative forcing due to aerosols and clouds; J. Geophys. Res.  113 D02203:1–D02203:34.

  • Krishnamurti T N and Biswas M K 2006 Transitions in the surface energy balance during the life cycle of a monsoon season; J. Earth Syst. Sci.  115(2) 185–201.

    Google Scholar 

  • Kustas W 1990 Estimates of evapotranspiration with a one-layer and 2-layer model of heat-transfer over partial canopy cover; J. Appl. Meteorol.  29 704–715.

    Google Scholar 

  • Kustas W and Norman J 1999 Evaluation of soil and vegetation heat flux predictions using a simple two-source model with radiometric temperatures for partial canopy cover; Agric. Forest. Meteorol.  94 13–29.

    Google Scholar 

  • L’ecuyer T S, Beaudoing H K, Rodell M, Olson W, Lin B, Kato S, Clayson C A, Wood E, Sheffield J, Adler R, Huffman G, Bosilovich M, Gu G, Robertson F, Houser P R, Chambers D, Famiglietti J S, Fetzer E and Liu W T 2015 The observed state of the energy budget in the early twenty-first century; J. Clim.  28 8319–8346.

    Google Scholar 

  • Lee M-I, Kang I-S and Kim J-K 2001 Influence of cloud-radiation interaction on simulating tropical intraseasonal oscillation with an atmospheric general circulation model; J. Geophys. Res.  106 14,219–14,233.

    Google Scholar 

  • Li F, Kustas W, Prueger J, Neale C and Jackson T 2005 Utility of remote sensing based two-source energy balance model under low and high vegetation cover conditions; J. Hydrometeorol.  6 878–891.

    Google Scholar 

  • Li Z, Tang R, Wan Z, Bi Y, Zhou C, Tang B, Yan G and Zhang X 2009 A review of current methodologies for regional evapotranspiration estimation from remotely sensed data; Sensors  9 3801–3853.

    Google Scholar 

  • Liang S, Zheng T, Liu R G, Fang H L, Tsay S C and Running S 2006 Estimation of incident photosynthetically active radiation from moderate resolution imaging spectrometer data; J. Geophys. Res.  111 D15208:1–D15208:13.

  • Liang S, Wang K and Wild X Z 2010 Review on estimation of land surface radiation and energy budgets from ground measurements, remote sensing and model simulations; IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens.  3 225–240.

    Google Scholar 

  • Lichun P, Wanbiao L, Jing Y, Dong C, Yuming L and Lijia C 2015 A review of parameterization methods for downward shortwave and longwave radiation on the surface; Acta Sci. Nat. Univ. Pekin.  51 772–782.

    Google Scholar 

  • Liou Y-A and Kar S 2014 Evapotranspiration estimation with remote sensing and various surface energy balance algorithms – A review; Energies  7 2821–2849.

    Google Scholar 

  • Liu Y, Hiyama T, Yasunari T and Tanaka H 2012 A nonparametric approach to estimating terrestrial evaporation: Validation in eddy covariance sites; Agric. Forest. Meteorol.  157 49–59.

    Google Scholar 

  • Long C and Dutton E G 2002 BSRN Global Network recommended QC tests, V2.0; http://hdl.handle.net/10013/epic.38770.d001

  • Lu N, Liu R, Liu J and Liang S 2010 An algorithm for estimating downward shortwave radiation from GMS 5 visible imagery and its evaluation over China; J. Geophys. Res. Atmos.  115 D18102:1–D18102:15.

  • Lu N, Qin J, Yang K and Sun J 2011 A simple and efficient algorithm to estimate daily global solar radiation from geostationary satellite data; Energy  36 3179–3188.

    Google Scholar 

  • Ma Y and Pinker R T 2012 Modeling shortwave radiative fluxes from satellites; J. Geophys. Res.  117 D23202:1–D23202:19.

    Google Scholar 

  • Ma W, Hafeez M, Ishikawa H and Ma Y 2013 Evaluation of SEBS for estimation of actual evapotranspiration using ASTER satellite data for irrigation areas of Australia; Theor. Appl. Climatol.  112 609–616.

    Google Scholar 

  • Main Geophysical Observatory, World Radiation Data Center, St. Petersburg, Russia, http://wrdc.mgo.rssi.ru

  • Meijninger W 2003 Surface fluxes over natural landscapes using scintillometry; PhD Thesis, Wageningen University, Wageningen, The Netherlands.

  • MODIS https://terra.nasa.gov/about/terra-instruments/modis

  • Mueller R, Matsoukas C, Gratzki A and Hollmann R 2009 The CM–SAF operational scheme for the satellite based retrieval of solar surface irradiance – A LUT based eigenvector hybrid approach; Remote Sens. Environ.  113 1012–1024.

    Google Scholar 

  • Nieveen J and Green A 1998 Measuring sensible heat flux over pasture using the Ct2 profile method; Bound. Layer Meteorol.  91 23–35.

  • Norman J, Kustas W and Humes K 1995 Source approach for estimating soil and vegetation energy fluxes in observations of directional radiometric surface temperature; Agric. Forest. Meteorol.  77 263–293.

    Google Scholar 

  • Nouri H, Beecham S, Kazemi F and Hassanli A 2013 A review of ET measurement techniques for estimating the water requirements of urban landscape vegetation; Urban Water J.  10 247–259.

    Google Scholar 

  • Ohmura A, Dutton E G, Forgan B, Frohlich C, Gilgen, H, Hegner H, Heimo A, Konig-Langlo B, McArthur B, Muller G, Philipona R, Pinker R, Whitlock C H, Dehne K and Wild M 1998 Baseline surface radiation network (BSRN/WCRP): New precision radiometry for climate research; Bull. Am. Meteor. Soc.  79 2115–2136.

    Google Scholar 

  • Pan X, Liu Y and Fan X 2016 Satellite retrieval of surface evapotranspiration with nonparametric approach: Accuracy assessment over a semiarid region; Adv. Meteorol. 2016, ID 1584316:1–ID 1584316:14.

    Google Scholar 

  • Park M-S, Ho C-H, Cho H and Choi Y-S 2015 Retrieval of outgoing longwave radiation from COMS narrowband infrared imagery; Adv. Atmos. Sci.  32 375–388.

    Google Scholar 

  • Paulescu M, Paulescu E, Gravila P and Badescu V 2013 Weather modeling and forecasting of PV systems operation; Springer-Verlag, London, Vol. XVIII, Chapter 2, pp. 20–24.

  • Pauwels V and Samson R 2006 Comparison of different methods to measure and model actual evapotranspiration rates for a wet sloping grassland; Agric. Water Manag.  82 1–24.

    Google Scholar 

  • Pinter P J Jr 1986 Effect of dew on canopy reflectance and temperature; Remote Sens. Environ.  19 187–205.

    Google Scholar 

  • Pyrgeometer (n.d.) https://en.wikipedia.org/wiki/PyrgeoHrBmeterHrB

  • Renzullo L J, Barrett D J, Marks A S, Hill M J, Guerschman J P and Mu Q 2008 Multi-sensor model-data fusion for estimation of hydrologic and energy flux parameters; Remote Sens. Environ.  112 1306–1319.

    Google Scholar 

  • Rigollier C, Lefèvre M and Wald L 2004 The method Heliosat-2 for deriving shortwave solar radiation from satellite images; Sol. Energy  77 159–169.

    Google Scholar 

  • Roderick M L, Farquhar G D, Berry S L and Noble I R 2001 On the direct effect of clouds and atmospheric particles on the productivity and structure of vegetation; Oecologia  129 21–30.

    Google Scholar 

  • Roerink G, Su Z and Menenti M 2000 S-SEBI: A simple remote sensing algorithm to estimate the surface energy balance; Phys. Chem. Earth B  25 147–157.

    Google Scholar 

  • Ryu Y, Baldocchi D D, Kobayashi H, Ingen C V, Li J, Black T A, Beringer J, Gorsel E V, Knohl A, Law B E and Roupsard O 2011 Integration of MODIS land and atmosphere products with a coupled-process model to estimate gross primary productivity and evapotranspiratiom from 1 km to global scale; Global Biogeochem. Cycles  25 GB4017:1–GB4017:24.

  • Samain B, Simons G, Voogt M, Defloor W, Bink N-J and Pauwels V 2012 Consistency between hydrological model, large aperture scintillometer and remote sensing based evapotranspiration estimates for a heterogeneous catchment; Hydrol. Earth Syst. Sci.  16 2095–2107.

    Google Scholar 

  • Sanchez J, Kustas W, Caselles V and Anderson M 2007 Modelling surface energy fluxes over maize using a two-source patch model and radiometric soil and canopy temperature observations; Remote Sens. Environ.  112 1130–1143.

    Google Scholar 

  • Schmetz J 1989 Towards a surface radiation climatology: Retrieval of downward irradiances from satellites; Atmos. Res.  23 287–321.

    Google Scholar 

  • Schmetz J, Pili P, Tjemkes S, Just D, Kerkmann J, Rota S and Ratier A 2002 An introduction to Meteosat Second Generation (MSG); Bull. Am. Meteor. Soc.  83 977–992.

    Google Scholar 

  • Schmithüsen H, Sieger R and König-Langlo G 2012 BSRN toolbox – A tool to create quality checked output files from BSRN datasets and station-to-archive files; Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Bremerhaven.

  • Schumacher C, Houze Jr R and Kraucunas I 2004 The tropical dynamical response to latent heating estimates derived from the TRMM precipitation radar; J. Atmos. Sci.  61 1341–1358.

    Google Scholar 

  • Shang-Ping Xie, Kosaka Y and Okumura Y M 2016 Distinct energy budgets for anthropogenic and natural changes during global warming hiatus; Nat. Geosci.  9 29–33.

    Google Scholar 

  • Shi T, Guan D, Wu J, Wang A, Jin C and Han S 2015 Comparison of methods for estimating evapotranspiration rate of dry forest canopy: Eddy covariance, Bowen ratio energy balance, and Penman-Monteith equation; J. Geophys. Res.: Atmos.  19 2145–2161.

  • Slingo A and Slingo J 1988 The response of general circulation model to cloud longwave radiative forcing. I: Introduction and initial experiments; Quart. J. Roy. Meteorol. Soc.  114 1027–1062.

    Google Scholar 

  • Solar Instruments/Atmospheric Science Instruments, http://www.kippzonen.com/

  • Soumi NPP, https://www.nasa.gov/mission_pages/NPP/main/index.html

  • Stephens G L and L’Ecuyer T 2013 The global energy balance from a surface prospective; Clim. Dyn.  40 3107–3134.

    Google Scholar 

  • Su Z 2002 The surface energy balance system (SEBS) for estimation of turbulent heat fluxes; Hydrol. Earth Syst. Sci.  6 85–99.

    Google Scholar 

  • Su Z, Li X, Zhou Y, Wan L, Wen J and Sintonen K 2003 Estimating areal evaporation from remote sensing; Proc. IEEE Int.  2 1166–1168.

    Google Scholar 

  • Su H, Mccabe M F, Wood E F, Su Z and Prueger J H 2005 Modeling evapotranspiration during SMACEX: Comparing two approaches for local- and regional-scale prediction; J. Hydrometeorol.  6 910–922.

    Google Scholar 

  • Sun H A 2016 Two-source model for estimating evaporative fraction (TMEF) coupling Priestley–Taylor formula and two-stage trapezoid; Remote Sens.  8 248.

    Google Scholar 

  • Sun Z, Liu J, Zeng X and Liang H 2012 Parameterization of instantaneous global horizontal irradiance: Cloudy-sky component; J. Geophys. Res.  117 D14202:1–D14202:10.

    Google Scholar 

  • Surface Radiation (SURFRAD) Network (n.d.) http://www.esrl.noaa.gov/gmd/grad/surfrad/

  • Tang Q, Peterson S, Cuenca R, Hagimoto Y and Lettenmaier D 2009 Satellite-based near-real-time estimation of irrigated crop water consumption; J. Geophys. Res. Atmos.  114 D05114:1–D05114:14.

  • Tang W, Qin J, Yang K, Liu S, Lu N and Niu X 2016 Retrieving high-resolution surface solar radiation with cloud parameters derived by combining MODIS and MTSAT data; J. Geophys. Res. Atmos.  16 2543–2557.

    Google Scholar 

  • The Advanced Space-borne Thermal Emission and Reflection Radiometer, http://asterweb.jpl.nasa.gov/

  • The Clouds and the Earth’s Radiant Energy System, http://ceres.larc.nasa.gov/

  • The Geostationary Operational Environmental Satellite- Advanced Baseline Imager(ABI), http://www.goes-r.gov/spacesegment/abi.html

  • Trenberth K, Fasullo J and Kiehl J 2009 Earth’s global energy budget; Bull. Am. Meteor. Soc.  90 311–323.

    Google Scholar 

  • Vázquez-Navarro M, Mayer B and Mannstein H 2013 A fast method for the retrieval of integrated longwave and shortwave top-of-atmosphere upwelling irradiances from MSG/SEVIRI (RRUMS); AMT  6 2627–2640.

    Google Scholar 

  • Verstraete W, Veroustraete F and Feyen J 2005 Estimating evapotranspiration of European forests from NOAA-imagery at satellite overpass time: Towards an operational processing chain for integrated optical and thermal sensor data products; Remote Sens. Environ.  96 256–276.

    Google Scholar 

  • Wan Z, Zhang K, Xue X, Hong Z, Hong Y and Gourley J 2015 Water balance based actual evapotranspiration reconstruction from ground and satellite observations over the Conterminous United States; Water Resour. Res.  51 6485–6499.

    Google Scholar 

  • Wang J and Bras R 2011 A model of evapotranspiration based on the theory of maximum entropy production; Water Resour. Res.  47 W03521:1–W03521:10.

  • Wang K and Liang S 2008 An improved method for estimating global evapotranspiration based on satellite determination of surface net radiation, vegetation index, temperature, and soil moisture; J. Hydrometeorol.  9 712–727.

    Google Scholar 

  • Wang K and Liang S 2009 Global atmospheric downward longwave radiation over land surface under all-sky conditions from 1973 to 2008; J. Geophys. Res. Atmos.  114 D19101:1–D19101:12.

  • Wang W and Liang S 2010 A method for estimating clear-sky instantaneous land surface longwave radiation from GOES sounder and GOES-R ABI data; IEEE Geosci. Remote Sens. Lett.  7 708–712.

    Google Scholar 

  • Wang H and Pinker R T 2009 Shortwave radiative fluxes from MODIS: Model development and implementation; J. Geophys. Res.  114 D20201:1–D20201:17.

  • Wang K, Wang P, Li Z, Cribb M and Sparrow M 2007 A simple method to estimate actual evapotranspiration from a combination of net radiation, vegetation index, and temperature; J. Geophys. Res. Atmos.  112 D15107:1–D15107:14.

  • Wang P, Sneep M, Veefkind J, Stammes P and Levelt P 2014 Evaluation of broadband surface solar irradiance from the ozone monitoring instrument; Remote Sens. Environ.  149 88–99.

    Google Scholar 

  • Ward H and Evans J G 2015 Infrared and millimetre-wave scintillometry in the suburban environment – Part 2: Large-area sensible and latent heat fluxes; Atmos. Meas. Tech.  8 1407–1424.

    Google Scholar 

  • Wild M, Folini D, Schar C, Loeb N, Dutton E and Langlo G 2009 Earth global energy budget; Bull. Am. Meteor. Soc.  90 311–323.

    Google Scholar 

  • World Climate Research Programme, http://www.wcrp-climate.org

  • Yan G, Wang T, Jiao Z, Mu X, Zhao J and Chen L 2016 Topographic radiation modeling and spatial scaling of clear-sky land surface longwave radiation over rugged terrain; Remote Sens. Environ.  172 15–27.

    Google Scholar 

  • Yang Y, Long D, Guan H, Liang W, Simmons C and Batelaan O 2015 Comparison of three dual-source remote sensing evapotranspiration models during the MUSOEXE-12 campaign: Revisit of model physics; Water Resour. Res.  51 3145–3165.

    Google Scholar 

  • Yeom J and Han K 2010 Improved estimation of surface solar insolation using a neural network and MTSAT-1R data; Comput. Geosci.  36 590–597.

    Google Scholar 

  • Yingying C, Jiancheng S, Yuanyuan Q and Lingmei J 2008 The simulation study on land surface energy budget over China area based on Lis-Noah Land Surface Model; ISPRS, Beijing, Vol. XXXVII.

  • Yu S, Xin X and Liu Q 2013 Estimation of clear-sky longwave downward radiation from HJ-1B thermal data; Sci. China: Earth Sci.  56 829–842.

    Google Scholar 

  • Yu S, Xin X and Zhang H 2014 Algorithms comparison for calculating downward longwave radiation by MODIS data under clear and cloudy skies; In: Proc. SPIE  9242 924210.

  • Zelenka A, Perez R, Seals R and Renne D 1988 Effective accuracy of the satellite-derived hourly irradiance; Theor. Appl. Climatol.  62 199–207.

    Google Scholar 

  • Zhang K, Kimball J S, Mu Q, Jones L A, Goetz S J and Running S W 2009 Satellite based analysis of northern ET trends and associated changes in the regional water balance from 1983 to 2005; J. Hydrol.  379 92–110.

    Google Scholar 

  • Zhang X, Liang S, Zhou G, Wu H and Zhao X 2014 Generating global land surface satellite incident shortwave radiation and photosynthetically active radiation products from multiple satellite data; Remote Sens. Environ.  152 318–332.

    Google Scholar 

  • Zhang K, Kimball J and Running S 2016 A review of remote sensing based actual evapotranspiration estimation; WIREs Water  3 834–853.

    Google Scholar 

  • Zhou Y, Kratz D, Wilber A, Gupta S and Cess R 2007 An improved algorithm for retrieving surface downwelling longwave radiation from satellite measurements; J. Geophys. Res.  112 D15102:1–D15102:13.

Download references

Acknowledgements

This study was financially supported by the National Key Research and Development Program of China (grant nos. 2016YFA0602302 and 2016YFB0502502). We also wish to acknowledge the intellectual and material contributions of CAS-TWAS President’s Fellowship.

Author information

Authors and Affiliations

  1. Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, 100 094, People’s Republic of China

    Md Masudur Rahman & Wanchang Zhang

  2. University of Chinese Academy of Sciences, Beijing, 100 049, People’s Republic of China

    Md Masudur Rahman

Authors
  1. Md Masudur Rahman
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Wanchang Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Wanchang Zhang.

Additional information

Corresponding editor: Amit Kumar Patra

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Rahman, M.M., Zhang, W. Review on estimation methods of the Earth’s surface energy balance components from ground and satellite measurements. J Earth Syst Sci 128, 84 (2019). https://doi.org/10.1007/s12040-019-1098-5

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s12040-019-1098-5

Keywords

Search

Navigation