Skip to main content
Log in

A survey of studies into errors in large scale space-time averages of rainfall, cloud cover, sea surface processes and the earth's radiation budget as derived from low earth orbit satellite instruments because of their incomplete temporal and spatial coverage

  • Published:
Surveys in Geophysics Aims and scope Submit manuscript

Abstract

This survey considers those studies conducted into estimating errors in satellite derived large scale space-time means (of the order of 250 km by 250 km by a month) for rainfall, cloud cover, sea surface processes and the Earth's radiation budget, resulting from their incomplete coverage of the space-time volume over which the mean is evaluated. Many of these studies have focused on estimating the errors in space-time means post satellite launch and compare mean data derived from such satellites with that from an independent data set. Pre-launch studies tend to involve computer simulations of a satellite overflying and sampling from an existing data set and hence the two approaches give values for sampling errors for specific cases. However, more generic sampling papers exist that allow the exact evaluation of sampling errors for any instrument or combination of instruments if their sampling characteristics and the auto-correlation of the parameter field are known. These generic and simulation techniques have been used together on the same data sets and are found to give very similar values for the sampling error and are presented. Also considered are studies in which data from several satellites, or satellite and ground based measurements are combined to improve estimates in the above means. This improvement being brought about not only by increased spatial and temporal coverage but also by a reduction in retrieval error.

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

Access this article

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

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Adler, R.F., Negri, A.J., and Hakkarinen, I.M.: 1991, ‘Rain estimation from combining geosynchro-nous IR and low orbit microwave data’, Global and Planetary Change 90(1–3), 87–92.

    Google Scholar 

  • Adler, R.F., Negri, A.J., Keehn, P.R., and Hakkarinen, I.M.: 1993, ‘Estimation of monthly rainfall over Japan and surrounding waters from a combination of low orbit microwave and geosynchronous IR data’, J. Appl. Meteorol. 32(2), 335–356.

    Google Scholar 

  • Atlas, D. and Bell, T.L.: 1992, ‘The relation of radar to cloud area-time integrals for rain measurements from space’, Mon. Wea. Rev. 120(9), 1997–2008.

    Google Scholar 

  • Andersen, O.B.: 1994, ‘Ocean tides in the North-Atlantic and adjacent seas from ERS-1 altimetry’, J. Geophys. Res. (Oceans) 99(C11), 22,557–22,573.

    Google Scholar 

  • Andersen, O.B.: 1995, ‘Global tides from ERS-1 and TOPEX/POSEIDON altimetry’, J. Geophys. Res. (Oceans) 100(C12), 25,249–25,259.

    Google Scholar 

  • Augustine, J.A., Woodley, W.L., Scott, R.W., and Changnon, S.A.: 1994, ‘Using geosynchronous satellite imagery to estimate summer-season rainfall over the Great-Lakes’, J. Great Lakes Res. 20(4), 683–700.

    Google Scholar 

  • AVISO: 1992, ‘AVISO user handbook: merged TOPEX/POSEIDONproducts’, AVI-NT–02–101-CN, Edition 2.1.

  • Baker, D.J.: 1990, Planet Earth-the view from space, Harvard University Press, ISBN 0–674–67070–1, 191 pages

  • Barth, N.H.: 1992, ‘Choosing altimeter orbits as a problem in experiment design’, Oceanologica ACTA 15(5), 459–470.

    Google Scholar 

  • Barnier, B., Capella, J., and Obrien, J.J.: 1994, ‘The use of satellite scatterometer winds to drive a primitive equation model of the Indian Ocean-the impact of band-like sampling'.

  • Bell, T.L. and Reid, N.: 1993, ‘Detecting the diurnal cycle of rainfall using satellite observations’, J. Appl. Meteorol. 32(2), 311–322

    Google Scholar 

  • Bell, T.L., Abdullah, A., Martin, R.L., and North, G.R.: 1990, ‘Sampling errors for satellite tropical rainfall-Monte-Carlo study using a space-time stochastic model’,J. Geophys. Res. (Atmospheres) 95(Nd3), 2195–2205.

    Google Scholar 

  • Bell, T.L. and Kundu, P.K.: 1994, (Pre-Publication) 'TRMM follow-on: sampling error and proposed orbits'.

  • Berg, W. and Avery, S.K.: 1995, ‘Evaluation of monthly rainfall estimates derived from the special sensor microwave/imager (SSM/I) over the tropical Pacific’, J. Geophys. Res. (Atmospheres) 100(D1), 1295–1315.

    Google Scholar 

  • Blanc, F. and Letraon, P.Y.: 1992, ‘Note on the use of an altimeter mean sea-surface for mesoscale variability studies’, Oceanologica ACTA 15(5), 471–478.

    Google Scholar 

  • Boutin, J. and Etcheto, J.: 1991, ‘Intrinsic error in the air-sea CO2 exchange coefficient resulting from the use of satellite wind’, Tellus Series B-Chemical and Physical Meteorology 43(2), 236–246.

    Google Scholar 

  • Brooks, D.R. and Minnis, P.: 1984, ‘Simulation of the Earth's monthly average regional radiation balance derived from satellite measurements’, J. Clim. Appl. Meteorol. 23(3), 392–403.

    Google Scholar 

  • Calahan, R.F., Short, D.A., and North, G.R.: 1981, ‘Cloud fluctuation statistics’, Mon. Wea. Rev. 110, 26–43.

    Google Scholar 

  • Chang, A.T.C., Chiu, L.S., and Yang, G.: 1995, ‘Diurnal cycle of oceanic precipitation from SSM/I data’, Mon. Wea. Rev. 123(11), 3371–3380.

    Google Scholar 

  • Chelton, D.B. and Schlax, M.G.: 1991, ‘Estimation of time averages from irregularly spaced obser-vations-with application to coastal zone colour scanner estimates of chlorophyll concentration’, J. Geophys. Res. (Oceans) 96(Nc8), 14,669–14,692.

    Google Scholar 

  • Cosgrove, C.M. and Garstang, M.: 1995, ‘Simulation of rain events from rain-gauge measurements’, Inter. J. Climatol. 15(9), 1021–1029.

    Google Scholar 

  • Cotton, P.D. and Carter, D.J.T.: 1994, ‘Cross calibration of TOPEX, ERS-1 and GEOSAT wave heights’, J. Geophys. Res. (Oceans) 99(C12), 25,025–25,033.

    Google Scholar 

  • Duncan, M.R., Austin, B., Fabry, F., and Austin, G.L.: 1993, ‘The effect of gauge sampling density on the accuracy of streamflow prediction for rural catchments’, J. Hydrol. 142(1–4), 445–476.

    Google Scholar 

  • Fieguth, P.W., Karl, W.C, Willsky, A.S., and Wunsch, C.: 1995, ‘Multiresolution optimal interpolation and statistical-analysis of TOPEX/POSEIDON altimetry, IEEE Transactions on Geoscience and Remote Sensing 33(2), 280–292.

    Google Scholar 

  • Graves, C.E., Valdes, J.B., Shen, S.S.P., and North, G.R.: 1993, ‘Evaluation of sampling errors of precipitation from space-borne and ground sensors’, J. Appl. Meteorol. 32(2), 374–385.

    Google Scholar 

  • Guyanne, T.D. (Ed.): 1990, ‘Report of the 'Atlid' consultancy group’, ESA SP-1121, ISBN 092–9092–056–4.

  • Ha, E. and North, G.R.: 1994, ‘Use of multiple gauges and microwave attenuation of precipitation for satellite verification’, J. Atmos. Oceanic Technol. 11(3), 629–636.

    Google Scholar 

  • Ha, E. and North, G.R.: 1995, ‘Model studies of beam filling error for rainrate retrieval with microwave radiometers’, J. Atmos. Oceanic Technol. 12(2), 268–281.

    Google Scholar 

  • Halpern, D. and Wentz, F.: 1994, ‘On the problem of measuring interannual wind-speed variations using SSM/I data’, Geophys. Res. Letters 21(3), 193–196.

    Google Scholar 

  • Harris, A.R., Brown, S.J., and Mason, I.M.: 1994, ‘The effect of windspeed on sea-surface temperature retrieval from space’, Geophys. Res. Letters 21(16), 1715–1718.

    Google Scholar 

  • Hernadez, R.F., Letraon, P.Y., and Morrow, R.: 1995, ‘Mapping mesoscale variability of the azores cur-rent using TOPEX/POSEIDON and ERS-1 altimetry, together with hydrographic and Lagrangian measurements’, J. Geophys. Res. (Oceans) 100(C12), 24,995–25,006.

    Google Scholar 

  • Hucek, R., Stowe, L., and Joyce, R.: 1996, ‘Evaluating the design of an Earth radiation budget instrument with system simulations. 3. CERES-1 diurnal sampling error’, J. Atmos. Oceanic Technol. 13(2), 383–399.

    Google Scholar 

  • Huffman, G.J., Adler, R.F., Rudolf, B., Schneider, U., and Keehn, P.R.: 1995, ‘Global precipitation estimates based on a technique for combining satellite-based estimates, rain-gauge analysis, and NWP model precipitation information’, J. Clim.8(5), 1284–1295.

    Google Scholar 

  • Illingworth, A.J. and McKendrick, I.J.: 1994, Report of the GEWEX topical workshop on 'Utility and feasibility of a cloud profiling radar’, Published by IGPO.

  • Kedem, B., Chiu, L.S., and North, G.R.: 1990, ‘Estimation of mean rain rate: Application to satellite observations’, J. Geophys. Res. (Atmospheres) 95(Nd2), 1965–1972.

    Google Scholar 

  • Kummerow, C. and Giglio, L.: 1995, ‘A method of combining microwave and infrared rainfall observations’, J. Atmos. Oceanic Technol. 12(1), 33–45.

    Google Scholar 

  • Kuo, K-S., Welch, R.M., Weger, R.C., Engelstad, M.A., and Sengupta, S.K.: 1993, ‘The three-dimensional structure of cumulus clouds over the ocean. 1. Structural analysis’, J. Geophys. Res. 98(D11), 20,685–20,711.

    Google Scholar 

  • Laughlin, C.: 1981, ‘On the effect of temporal sampling on the observation of mean rainfall’, in: D. Atlas and O. Thiele (eds.), Precipitation measurements from space, NASA/Workshop report, Avail. Goddard Space Flight Centre, Greenbelt, Md20771, pp. 61–66.

    Google Scholar 

  • Li, Q.H., Bras, R.L., and Veneziano, D.: 1996, ‘Analysis of Darwin rainfall-implications of sampling strategy’, J. Appl. Meteorol. 35(3), 372–385.

    Google Scholar 

  • Liao, X.H., Rossow, W.B., and Rind, D: 1995, ‘Comparison between Sage-II and ISCCP high-level clouds. 1. Global and zonal mean cloud amounts, J. Geophys. Res. (Atmospheres) 100(D1), 1121–1135.

    Google Scholar 

  • Lim, H.S., Graves, C.E., North, G.R., and Wilheit, T.T.: 1995, ‘Rainfall estimation from ESMR-5 measurements and application to El-Nino’, J. Appl. Meteorol. 34(2), 391–403.

    Google Scholar 

  • Letraon, P.Y. and Hernandez, F.: 1992, ‘Mapping the oceanic mesoscale circulation-validation of satellite altimetry using surface drifters’, J. Atmos. Oceanic Technol.9(5), 687–698.

    Google Scholar 

  • Lovejoy, S.: 1982, ‘Area-perimeter relation for rain and cloudy areas’, Science 216(9), 185–187.

    Google Scholar 

  • Luo, G.: 1995, ‘Simulations exploring the dependence of cloud-cover frequency distributions on cloud size and image pixel resolution’, J. Atmos. Oceanic Technol. 12, 712–720.

    Google Scholar 

  • Luo, G., Lin, X.J., and Coakley, J.A.: 1994, Emissivities and droplet radii for marine stratocumulus’, J. Geophys. Res. (Atmospheres) 99(D2), 3685–3698.

    Google Scholar 

  • Mazzega, P., and Berge, M.: 1994, ‘Ocean Tides in the Asian semi-enclosed seas from TOPEX/POSEIDON’, J. Geophys. Res. (Oceans) 99(C12), 24,867–24,881.

    Google Scholar 

  • McConnell, A. and North, G.R.: 1987, ‘Sampling errors in satellite estimates of tropical rain’, J. Geophys. Res. (Atmospheres) 92(Nc8), 9567–9570.

    Google Scholar 

  • Minnett, P.J.: 1991, ‘Consequences of sea-surface temperature variability on the validation and applications of satellite measurements’, J. Geophys. Res. (Oceans) 96(Nc10), 18,475–18,489.

    Google Scholar 

  • Minnis, P. and Harrison, E.F.: 1978, ‘Diurnal variability of cloud and clear-sky radiative parameters derived from GOES data. Part III: November 1978 radiative parameters’, J. Clim. Appl. Meteorol. 23, 1032–1051.

    Google Scholar 

  • Minnis, P., Young, D.F., and Harrison, E.F.: 1991, ‘Examination of the relationship between outgoing infrared window and total longwave fluxes using satellite data’, J. Clim.4(11), 1114–1133.

    Google Scholar 

  • Morrissey, M.L., Maliekal, J.A., Greene, J.S., and Wang, J.M.: 1995, ‘The uncertainty of simple spatial averages using rain-gauge networks’, Water Resourc. Res. 31(8), 2011–2017.

    Google Scholar 

  • Morrissey, M.L. and Janowiak, J.E.: 1996, ‘Sampling-induced conditional biases in satellite climate-scale rainfall estimates’, J. Appl. Meteorol. 35(4), 541–548.

    Google Scholar 

  • Morrissey, M.L., and Wang, Y.P., 1995, ‘Verifying satellite microwave rainfall estimates over the open-ocean’, J. Appl. Meteorol. 34(4), 794–804.

    Google Scholar 

  • Nakamoto, S., Fang, Z., Matsura, T., Kawano, T., Kashino, Y., Muneyama, K, and Nakanishi, T.: 1994, ‘Spatial sampling requirements for tropical Pacific sea surface variability’, J. Geophys. Res. (Oceans) 99(C9),18,363–18,370.

    Google Scholar 

  • Negri, A.J. and Adler, R.F.: 1993, An intercomparison of 3 satellite infrared rainfall techniques over Japan and surrounding waters’, J. Appl. Meteorol. 32(2), 357–373.

    Google Scholar 

  • Negri, A.J., Adler, R.F., Nelkin, E.J., and Huffman, G.J.: 1994, ‘Regional rainfall climatologies derived from special sensor microwave imager (SSM/I) data’, Bull. Amer. Meteorol. Soc. 75(7), 165–1182.

    Google Scholar 

  • Negri, A.J., Adler, R.F., Maddox, M.A., Howard, K.W., and Keehn, P.R.: 1993, ‘A regional rainfall climatology over Mexico and the southwest United-States derived from passive microwave and geosynchronous infrared data’, J. Clim.6(11), 2144–2161.

    Google Scholar 

  • North, G.R. and Nakamoto, S.: 1989, ‘Formalism for comparing rain estimation design’, J. Atmos. Oceanic Technol.6(6), 985–992.

    Google Scholar 

  • North, G.R., Shen, S.S.P., and Upson, R.B.: 1991, ‘Combining rain gauges with satellite measurements for optimal estimates of area-time averaged rain rate’, Water Resourc. Res. 27(10), 2785–2790.

    Google Scholar 

  • North, G.R., Shen, S.S.P., and Upson, R.B.: 1993, ‘Sampling errors in rainfall estimates by multiple satellites’, J. Appl. Meteorol. 32(2), 399–410.

    Google Scholar 

  • North, G.R., Valdes, J.B., Ha, E., and Shen, S.S.P.: 1994, ‘The ground truth problem for satellite estimates of rain rate’, J. Atmos. Oceanic Technol. 11(4), 1035–1041.

    Google Scholar 

  • Oki, R. and Sumi, A.: 1994, ‘Sampling simulations of TRMM rainfall estimation using radar AMeDAS composites’, J. Appl. Meteorol. 33(12), 1597–1608.

    Google Scholar 

  • Peterslidard, C.D. and Wood, E.F.: 1994, ‘Estimating storm areal average rainfall intensity in-field experiments’, Water Resourc. Res. 30(7), 2119–2131.

    Google Scholar 

  • Pinker, R.T., Frouin, R., and Li, Z.: 1995, ‘A review of satellite methods to derive surface shortwave irradiance’, Remote Sensing Environ. 51(1), 108–124.

    Google Scholar 

  • Pinker, R.T., and Laszlo, I.: 1991, ‘Effects of spatial sampling of satellite data on derived surface solar irradiance’, J. Atmos. Oceanic Technol.8(1), 96–107.

    Google Scholar 

  • Ray, R.: 1993, ‘Global ocean tide models on the eve of TOPEX/POSEIDON’, IEEE Trans. Geos. Remote Sensing, 31, 355–364.

    Google Scholar 

  • Reynolds, R.W. and Smith, T.M.: 1994, ‘Improved global sea-surface temperature analyses using optimum interpolation’, J. Clim.7(6), 929–948.

    Google Scholar 

  • Rieland, M. and Raschke, E.: 1991, ‘Diurnal variability of the Earth radiation budget-Sampling requirements, time integration aspects and error-estimates for the Earth radiation budget experi-ment (ERBE)’, Theoret. Appl. Climatol. 44(1), 9–24.

    Google Scholar 

  • Rossow, W.B.: 1994, Report of the GEWEX topical workshop on 'Utility and feasibility of a cloud profiling radar’, published by IGPO.

  • Rossow, W.B. and Garder, L.C.: 1993a, ‘Cloud detection using satellite measurements of infrared and visible radiances for ISCCP’, J. Clim.6(12), 2341–2369

    Google Scholar 

  • Rossow, W.B. and Garder, L.C.: 1993b, ‘Validation of ISCCP cloud detections’, J. Clim.6(12), 2370–2393.

    Google Scholar 

  • Rossow, W.B., Garder, L.C., Lu, P. J., and Walker, A.: 1991, ‘International Cloud Climatology Project (ISCCP) documentation of cloud data’, World Climate Research Programme for ICSU and WMO.

  • Rossow, W.B. and Schiffer, R.A.: 1991, ‘ISCCP cloud data products’, Bull. Amer. Meteorol. Soc. 72(1), 2–20.

    Google Scholar 

  • Rossow, W.B., Walker, A.W., and Garder, L.C.: 1993, ‘Comparison of ISCCP and other cloud amounts’, J. Clim.6(12), 2394–2418.

    Google Scholar 

  • Salby, M.L.: 1982a, ‘Sampling theory for asynoptic satellite-observations. 1. Space time spectra, resolution and aliasing’, J. Atmos. Sci. 39(11), 2577–2600.

    Google Scholar 

  • Salby, M.L.: 1982b, ‘Sampling theory for asynoptic satellite observations. 2. Fast Fourier synoptic mapping’, J. Atmos. Sci. 39(11), 2601–2614.

    Google Scholar 

  • Salby, M.L. and Callaghan, P.: 1995, (Pre-publication) 'Sampling error in climate properties derived from satellite measurements: relationship to diurnal variability'.

  • ScaRaB on Meteor-3: 1994, ‘CNES Research announcement, Direction des programmes’, Paris, December 16, No. DP/OT/94–235/NT/.

  • Schlax, M.G., and Chelton, D.B.: 1994, ‘Aliased tidal errors in TOPEX/POSEIDON sea-surface height data’, J. Geophys. Res. (Oceans) 99(C12), 24,761–24,775.

    Google Scholar 

  • Schlussel, P., Schanz, L., and Englisch, G.: 1995, ‘Retrieval of latent-heat flux and longwave irradiance at the sea-surface from SSM/I and AVHRR measurements’, Adv. Space Res. 16(10), 107–116.

    Google Scholar 

  • Seze, G. and Rossow, W.B.: 1991, ‘Effects of satellite data resolution on measuring the space-time variations of surfaces and clouds’, Inter. J. Remote Sensing, 12(5), 921–952.

    Google Scholar 

  • Shin, K.S. and North, G.R.: 1988, ‘Sampling error study for rainfall estimate by satellite using a stochastic-model’, J. Appl. Meteorol. 27(11), 1218–1231.

    Google Scholar 

  • Shin, K.S., Riba, P.E., and North, G.R.: 1990, ‘Estimation of area-averaged rainfall over tropical oceans from microwave radiometry-a single channel approach’, J. Appl. Meteorol. 29(10), 1031–1042.

    Google Scholar 

  • Smedstad, O.M. and Fox, D.N.: 1994, ‘Assimilation of altimeter data in a 2-layer primitive equation model of the gulf stream’, J. Phys. Oceanog. 24(2), 305–325.

    Google Scholar 

  • Spencer, R.W.: 1993, ‘Global oceanic precipitation from the MSU during 1979–91 and comparisons to other climatologies’, J. Clim.6(7), 1301–1326

    Google Scholar 

  • Spencer, R.W. and Christy, J.R.: 1993, ‘Precision lower stratospheric temperature monitoring with the MSU-technique, validation, and results 1979–1991’, J. Clim.6(6), 1194–1204.

    Google Scholar 

  • Spencer, R.W. and Christy, J.R.: 1992a, ‘Precision and radiosonde validation of satellite gridpoint temperature anomalies. 1. MSU Channel-2’, J. Clim.5(8), 847–857.

    Google Scholar 

  • Spencer, R.W. and Christy, J.R.: 1992b, ‘Precision and radiosonde validation of satellite gridpoint temperature Anomalies. 2. A tropospheric retrieval and trends during 1979–90’, J. Clim.5(8), 858–866.

    Google Scholar 

  • Steiner, M.: 1996, ‘Uncertainty in estimates of monthly areal rainfall for temporally sparse remote observations’, Water Resourc. Res. 32(2), 373–388.

    Google Scholar 

  • Stowe, L., Ardanuy, P., Hucek, R., Abel, P., and Jacobowitz, H.: 1993, ‘Evaluating the design of an Earth radiation budget instrument with system simulations. 1. Instantaneous estimates’, J. Atmos. Ocean. Technol. 10(6), 809–857

    Google Scholar 

  • Stowe, L., Hucek, R., Ardanuy, P., and Joyce, R.: 1994, ‘Evaluating the design of an Earth radiation budget instrument with system simulations. 2. Minimisation of instantaneous sampling errors for CERES-I’, J. Atmos. Ocean. Technol. 11(5), 1169–1183.

    Google Scholar 

  • Soman, V.V., Valdes, J.B., and North, G.R.: 1995, ‘Satellite sampling and the diurnal cycle statistics of Darwin rainfall data’, J. Appl. Meteorol. 34(11), 2481–2490.

    Google Scholar 

  • Tessier, Y., Lovejoy, S., and Schertzer, D.: 1993, ‘Universal multifractals: theory and observations for rain and clouds’, J. Appl. Meteorol. 32(2), 223–250.

    Google Scholar 

  • Turner, B.J. and Austin, G.L.: 1993, ‘Spatial variability of summer Florida precipitation and its impact on microwave radiometer rainfall measurement systems’, J. Appl. Meteorol. 32(2), 172–181.

    Google Scholar 

  • Valdes, J.B., Ha, E.H., Yoo, C., and North, G.R.: 1994, ‘Stochastic characterisation of space-time precipitation-implications for remote-sensing’, Adv. Water Resourc. 17(1–2), 47–59.

    Google Scholar 

  • Viollier, M., Kandel, R., and Raberanto, P.: 1995, ‘Inversion and space-time averaging algorithms for ScaRaB-comparisons with ERBE’, Annales Geophysicae-Atmos. Hydros. Space Sci. 13(9), 959–968.

    Google Scholar 

  • Wielicki, B.A. and Parker, L.: 1992, ‘On detection of cloud cover from satellite sensors: the effect of sensor spatial resolution’, J. Geophys. Res. (Atmospheres) 97(D12), 12,799–12,823.

    Google Scholar 

  • Weng, F.Z., Ferraro, R.R. and Grody, N.C.: 1994, ‘Global precipitation estimations using defence meteorological satellite program F10 and F11 special sensor microwave imager data’, J. Geophys. Res. (Atmospheres) 99(D7), 14,493–14,502.

    Google Scholar 

  • Wunsch, C.: 1989, ‘Sampling characteristics of satellite orbits’, J. Atmos. Oceanic Technol.6(6), 891–907.

    Google Scholar 

  • Zeng, L.X. and Levy, G.: 1995, ‘Space and time aliasing structure in monthly mean polar-orbiting satellite data’, J. Geophys. Res. (Atmospheres) 100(D3), 5133–5142.

    Google Scholar 

  • Zhang, Y.C., Rossow, W.B., and Lacis, A.A.: 1995, "Calculation of surface and top of atmosphere fluxes from physical quantities based on ISCCP data sets. 1. Method and sensitivity to input data uncertainties’, J. Geophys. Res. (Atmospheres) 100(D1), 1149–1165.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Astin, I. A survey of studies into errors in large scale space-time averages of rainfall, cloud cover, sea surface processes and the earth's radiation budget as derived from low earth orbit satellite instruments because of their incomplete temporal and spatial coverage. Surveys in Geophysics 18, 385–403 (1997). https://doi.org/10.1023/A:1006512715662

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/A:1006512715662

Keywords

Navigation