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12 - Raingauge and satellite datasets

Published online by Cambridge University Press:  10 October 2009

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Summary

The organisations assembling datasets

Most precipitation data have been collected by national weather services (NWSs) and national hydrological organisations, and by those collecting data for some specific project. But many of these records do not cover long enough periods, few spanning a century without some break or discontinuity. Until concerns about climate change arose recently this was an acceptable state of affairs. Now that we wish to understand and follow the climate changes that have occurred, are occurring and will occur in all climatic variables including precipitation, in the future, it has become necessary to look more closely at all these disparate data and to assemble them into some order covering the entire globe. None of these data were collected for this purpose, but for the simpler and more routine function of weather forecasting on a national scale or for water resources assessment on a local or regional scale. For climatic research, however, it is necessary to assemble all of these unrelated data into one integrated global dataset. Let us first take a look at the organisations involved in attempting this difficult task or in some way contributing to it.

The World Meteorological Organization (WMO)

The WMO is an intergovernmental organisation of 187 member states and territories which originated as the International Meteorological Organization, founded in 1873. Established in 1950, WMO became the specialised agency of the United Nations for weather and climate, operational hydrology and related geophysical sciences.

Type
Chapter
Information
Precipitation
Theory, Measurement and Distribution
, pp. 231 - 245
Publisher: Cambridge University Press
Print publication year: 2006

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References

Dai, A., Fung, I. and Del, Genio A. (1997). Surface observed global land precipitation variations during 1900–88. Journal of Climate, 10, 2943–29622.0.CO;2>CrossRefGoogle Scholar
Dai, A. G., Lamb, P. J., Trenberth, K. E., Hulme, M., Jones, P. D. and Xie, P. P. (2004). The recent Sahel drought is real. International Journal of Climatology, 24, 1323–1331CrossRefGoogle Scholar
Doherty, R. M., Hulme, M. and Jones, C. G. (1999). A gridded reconstruction of land and ocean precipitation for the extended tropics from 1974 to 1994. International Journal of Climatology, 19, 119–1423.0.CO;2-X>CrossRefGoogle Scholar
F⊘rland, E. J. (1994). Trends and Problems in Norwegian Snow Records. In Climate Variations in Europe. Proceedings of Workshop on Climate Variations, Majvik, Finland, pp. 205–215Google Scholar
F⊘rland, E. J. and Hanssen-Bauer, I. (2000). Increased precipitation in the Norwegian arctic: true or false?Climate Change, 46, 485–509CrossRefGoogle Scholar
Groisman, P. Ya. and Legates, D. R. (1995). Documenting and detecting long-term precipitation trends: where we are and what should be done. Climate Change, 32, 601–622CrossRefGoogle Scholar
Huffman, G. J., Adler, R. F., Arkin, P.et al. (1997). The Global Precipitation Climatology Project (global precipitation climatology project) Combined Precipitation Dataset. Bulletin of the American Meteorological Society, 78, 5–202.0.CO;2>CrossRefGoogle Scholar
Huffman, G. J., Adler, R. F., Morrissey, M. M.et al. (2000). Global precipitation at 1 degree daily resolution from multi-satellite observations. Journal of Hydrometeorology, 2, 36–502.0.CO;2>CrossRefGoogle Scholar
Hulme, M. (1994). Validation of large-scale precipitation fields in general circulation models. In Desbois, M. and Desalmand, F. (Eds.) Global Precipitation and Climate Change (ed. M. Desbois and F. Desalmand). Berlin: Springer, pp. 387–406CrossRef
Hulme, M. (1995). Estimating global changes in precipitation. Weather, 50, 34–42CrossRefGoogle Scholar
Intergovernmental Panel on Climate Change (Intergovernmental Panel on Climate Change) (2001). Climate Change 2001: the Scientific Basis Chapter 14, Advancing our Understanding. www.ipcc.ch
Jaeger, L. (1976). Monatskarten des Niederschlags für die ganze Erde. Berichte des Deutschen Wetterdienstes, 139. Offenbach: Deutscher WetterdienstGoogle Scholar
Jones, S. B. (1983). The Estimation of Catchments' Average Point Rainfalls. Institute of Hydrology Report 87. Wallingford: Institute of Hydrology (now Centre for Ecology and Hydrology (formerly Institute of Hydrology (now Centre for Ecology and Hydrology)))Google Scholar
Katz, R. W. and Glantz, M. H. (1986). Anatomy of a rainfall index. Monthly Weather Review, 114, 764–7712.0.CO;2>CrossRefGoogle Scholar
Legates, D. R. and Willmott, C. J. (1990). Mean seasonal and spatial variability in gauge-corrected global precipitation. International Journal of Climatology, 10, 111–128CrossRefGoogle Scholar
New, M., Hulme, M. and Jones, P. D. (2000). Representing twentieth century space-time climate variability. Part II: development of 1901–1996 monthly grids of terrestrial surface climate. Journal of Climate, 13, 2217–22382.0.CO;2>CrossRefGoogle Scholar
New, M., Todd, M., Hulme, M. and Jones, P. (2001). Precipitation measurements and trends in the twentieth century. International Journal of Climatology, 21, 1899–1922CrossRefGoogle Scholar
Perry, M. and Hollis, D. (2005a). The development of a new set of long-term climate averages for the UK. International Journal of Climatology, 25, 1023–1039CrossRefGoogle Scholar
Perry, M and Hollis, D. (2005b). The generation of monthly gridded datasets for a range of climate variables over the UK. International Journal of Climatology, 25, 1041–1054CrossRefGoogle Scholar
Rodda, J. C. (1962). An objective method for the assessment of areal rainfall amounts. Weather, 17, 54–59CrossRefGoogle Scholar
Rudolf, B., Hauschild, H., Rueth, W. and Schneider, U. (1994). Terrestrial precipitation analysis: operational method and required density of point measurements. In Global Precipitation and Climate Change (ed. Desbois, M. and Desalmand, F.). Berlin: Springer, pp. 173–186CrossRefGoogle Scholar
Rudolf, B., Gruber, A., Adler, R., Huffman, G., Janowiak, J. and Xie, P. (1999). global precipitation climatology project analyses based on observations as a basis for NWP and climate model verification. In Proceedings of the world climate research programme 2nd International Reanalysis Conference, Reading, UK. world climate research programme reportGoogle Scholar
Strangeways, I. C. (2003). Measuring the Natural Environment, 2nd edn. Cambridge: Cambridge University PressCrossRefGoogle Scholar
Thiessen, A. H. (1911). Precipitation averages for large areas. Monthly Weather Review, 39, 1082–1084Google Scholar
Todd, M. C., Kidd, C. K., Kniveton, D. R. and Bellerby, T. J. (2001). A combined microwave and infrared technique for estimation of small scale rainfall. Journal of Atmosphere and Ocean Technologies, 18, 742–7552.0.CO;2>CrossRefGoogle Scholar
World Meteorological Organization (1996). Guide to Meteorological Instruments and Methods Of Observation, 6th edn. World Meteorological Organization, No. 8. Geneva: World Meteorological Organization
Xie, P. and Arkin, P. A. (1996a). Analyses of global monthly precipitation using gauge observations, satellite estimates and numerical model predictions. Journal of Climate, 9, 840–8582.0.CO;2>CrossRefGoogle Scholar
Xie, P. and Arkin, P. A. (1996b). An intercomparison of gauge observations and satellite estimates of monthly precipitation. International Journal of Climatology, 34, 1143–1160Google Scholar
Xie, P., Rudolf, B., Schneider, U. and Arkin, P. A. (1996). Gauge-based monthly analysis of global land precipitation from 1971 to 1994. Journal of Geophysical Research – Atmosphere, 101, 19023–19034CrossRefGoogle Scholar
Yang, D. Q., Kane, D., Zhang, Z. P., Legates, D. and Goodison, B. (2005). Bias corrections of long-term (1973–2004) daily precipitation data over the northern regions. Geophysical Research Letters, 32, L19501CrossRefGoogle Scholar

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