Skip to main content

Climate analysis with satellite versus weather station data

Climatic Change volume 81, pages 71–83 (2007)Cite this article

Abstract

This paper compares how well satellite versus weather station measurements of climate predict agricultural performance in Brazil, India, and the United States. Although weather stations give accurate measures of ground conditions, they entail sporadic observations that require interpolation where observations are missing. In contrast, satellites have trouble measuring some ground phenomenon such as precipitation but they provide complete spatial coverage of various parameters over a landscape. The satellite temperature measurements slightly outperform the interpolated ground station data but the precipitation ground measurements generally outperform the satellite surface wetness index. In India, the surface wetness index outperforms station precipitation but this may be reflecting irrigation, not climate. The results suggest that satellites provide promising measures of temperature but that ground station data may still be preferred for measuring precipitation in rural settings.

This is a preview of subscription content, access via your institution.

Access options

Buy single article

Instant access to the full article PDF.

USD 39.95

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

References

  • Basist A, Williams Jr C, Grody N, Ross TE, Shen S, Chang A, Ferraro R, Menne MJ (2001) Using the Special Sensor Microwave Imager to monitor surface wetness. J of Hydrometeorology 2:297–308

    Article  Google Scholar 

  • Basist A, Peterson N, Peterson T, Williams C (1998) Using the Special Sensor Microwave Imager to monitor land surface temperature, wetness, and snow cover. J Appl Meteor 37:888–911

    Article  Google Scholar 

  • Gutman GG (1991) Vegetation Indices from AVHRR Data: An Update and Future Prospects. Remote Sens Environ 35:121–136

    Article  Google Scholar 

  • Group on Earth Observation (2003) Draft Framework, http://earthobservations.org

  • Houghton J, Ding Y, Griggs D, Noguer M, van der Linden P, Dai X, Maskell K, Johnson C (eds) (2001) Climate Change 2001: The Scientific Basis. Third Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge

  • Kidwell KB (1997) Global Vegetation Index User's Guide. Department of Commerce, NOAA/NESDIS, National Climate Data Center. Washington D.C., p 52

    Google Scholar 

  • Kogan FN (2001) Operational Space Technology for Global Vegetation Assessment. Bull Amer Meteor Soc 82:1949–1964

    Article  Google Scholar 

  • Kogan FN (1997) Global Drought Watch from Space. Bull Amer Meteor Soc 78:621–636

    Article  Google Scholar 

  • Kogan FN (1990) Remote sensing of weather impacts on vegetation in non-homogeneous areas. Int J Remote Sens 11:1405–1419

    Article  Google Scholar 

  • Kogan FN (1995) Droughts of the Late 1980s in the United States as Derived from NOAA Polar Orbiting Satellite Data. Bull Amer Meteor Soc 76:655–668

    Article  Google Scholar 

  • Lakshmi V, Susskind J (2000) Validation of TOVS Land Surface Parameters Using Ground Observations. J of Geophysical Research 105:2179–2190

    Article  Google Scholar 

  • McCarthy J, Canziani O, Leary N, Dokken D, White K (eds) (2001) Climate Change 2001: Impacts. Adaptation, and Vulnerability. Third Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge

  • Mendelsohn R, Nordhaus W, Shaw D (1994) The Impact of Global Warming on Agriculture: A Ricardian Analysis. American Economic Review 84:753–771

    Google Scholar 

  • Mendelsohn R, Dinar A, Sanghi A (2001) The Effect of Development on the Climate Sensitivity of Agriculture. Environment and Development Economics 6:85–101

    Article  Google Scholar 

  • Mendelsohn R, Dinar A (2003) Climate, Water, and Agriculture. Land Economics 79:328–341

    Article  Google Scholar 

  • Rao CRN, Chen J (1999) Revised post-launch calibration of the visible and near-infrared channels of the Advanced Very High Resolution Radiometer on the NOAA-14 spacecraft. Int J Remote Sens 20:3485–3491

    Article  Google Scholar 

  • Teng W, Wang J, Doraiswamy P (1993) Relationship between satellite microwave radiometric data, antecedent precipitation index, and regional soil moisture. Int J Remote Sens 14:2483–2500

    Article  Google Scholar 

  • Valery M, Champeaux J, Chauvin F, Meriquet C, Lacaze R (2003) A Global database of land surface parameters at 1-km resolution in meteorological and climate models. J of Climate 16:1261–1282

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Yale University, Yale FES, 230 Prospect Street, New Haven, CT, 06511, 203-432-5128, USA

    Robert Mendelsohn

  2. Yale FES, 210 Prospect Street, New Haven, CT, 06511. 718-623-0835, USA

    Pradeep Kurukulasuriya

  3. Commodity Hedgers Inc., 1 Heather Downs, Alexander, NC, 28700, 828-658-1626, USA

    Alan Basist

  4. NOAA, Room 712, WWB, 5200 Auth Road, Camp Springs, MD, 20746, 301-763-8042, USA

    Felix Kogan

  5. National Climatic Data Center, 151 Patten Avenue, Asheville, NC, 28801, 828-271-4711, USA

    Claude Williams

Authors
  1. Robert Mendelsohn
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Pradeep Kurukulasuriya
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Alan Basist
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Felix Kogan
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Claude Williams
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Robert Mendelsohn.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Mendelsohn, R., Kurukulasuriya, P., Basist, A. et al. Climate analysis with satellite versus weather station data. Climatic Change 81, 71–83 (2007). https://doi.org/10.1007/s10584-006-9139-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10584-006-9139-x

Keywords

  • Surface Wetness
  • Weather Station Data
  • Defense Meteorological Satellite Program
  • Springer Climatic Change
  • Satellite Temperature