| Introduction |
| Meteorological data essential for water resource planning and research is fairly difficult to obtain for the Indian citizen. At the same time, in the past decade, several international initiatives have put online published global datasets that represent a significant knowledge bank that could be put to good use in India. Entire datasets from 1901 to 2002 for any part of India based on simple on-line dropdown menus is made available for users. Users are encouraged to use this data judiciously. From this dataset, several useful estimates pertaining to the water balance can be made. |
| Data Source |
| The database that is used for this work, is the publicly available Climate Research Unit (CRU) TS2.1 dataset, out of the Tyndall Centre for Climate Change Research, School of Environmental Sciences, University of East Anglia in Norwich, UK. This published dataset consists of interpolated (on a 0.5 degree latitude-longitude grid) global monthly rainfall, temperature, humidity and cloud cover data, from 1901 to 2002 (Mitchell and Jones, 2005). |
| Processing of the CRU dataset: |
| Typically, large spatiotemporal datasets of this sort require the use of Geographic Information Systems (GIS). For the purpose of converting the CRU dataset from its orginal format, the opensource GIS software GRASS (Geographic Resources Analytical Support System) was used on a Ubuntu Linux operating system. The original datasets, available at http://www.cru.uea.ac.uk/~timm/grid/CRU_TS_2_0.html, were converted into GRASS raster formats. GRASS GIS modules along with Linux scripting were used to extract the monthly average rainfall; maximum, minimum and average temperatures; and vapour pressure (humidity), from 1901 to 2002, for the Indian subcontinent. |
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The Evapotranspiration data was derived from the weather data using the procedures of the FAO-56 manual (Allen et. al, 1998), referenced at the bottom of this page.
Please click here for an explanation of the equations used to derive the data. |
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The district-wise meteorological data was obtained by simple linear averaging from the gridded data of the CRU dataset. Where there were data gaps in the CRU grids and the data gap was less than 25% of the district area, we have done a simple approximation to get the data for each district. Where the data gap was more than 25% we have not shown any data for that district. |
| Notes: |
| Local data should be used wherever available. This dataset is most useful for regional applications. Examples of such use include (but is not limited to): |
| Regional, or basin-wide rainfall and weather assessments including water balance modeling; |
| Regional, or basin-wide rainwater harvesting potential; |
| A preliminary estimate of the water balance for smaller areas, when local data is unavailable; |
| A comparison of rainfall and other weather parameters between different regions/basins. |
| We request that any use of the data should acknowledge the India Water Portal, the Tyndall Centre for Climate Change Research, and also include Mitchell et al. publication |
| Acknowledgements: |
| Vishal K. Mehta - Arghyam/Cornell University, Climate Research Unit, UK. |
| We thank Professors Stephen D. DeGloria and M. Todd Walter of Cornell University, for their guidance in accomplishing this work. |
| References and Recommended Reading: |
Mitchell, T.D., Jone, P.D. (2005). "An improved method of constructing a database of monthly climate observations and associated highresolution
grids" International Journal of Climatology 25:693712
Read the paper
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| Allen, R. G., Pereira, L.S., Raes, D., Smith, M. (1998). "Crop evapotranspiration: Guidelines for computing crop water requirements" FAO Irrigation and drainage paper 56, Rome, Italy.
http://www.fao.org/docrep/X0490E/x0490e00.htm
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