Basic meteorological data are essential for evaluating impacts of spatiotemporal variability in climate forcing on hydrology and agroecosystems. Without these data, it is not possible to estimate important factors, such as the water requirements for agricultural crops, including biofuel crops.
In order to facilitate research that can enable better policy via more accurate information, the CLIMA team developed high-resolution grids (0.25o × 0.25o) of daily precipitation, reference evapotranspiration (ETo), and the five climate variables generally required to estimate evapostranspiration for Brazil (maximum and minimum temperature, solar radiation, relative humidity, and wind speed).
The core data used to generate the gridded data sets are the ground-based weather stations in Brazil that are operated by federal (INMET, ANA) and state (DAEE for São Paulo) agencies. In total, we used a total of 3,625 rain gauges and 735 weather stations.
The results are reported in Xavier et al. (2016) as and the data are freely available for researchers across Brazil, and the world, to use for improved modeling to inform science and policy.
Research and policy implications and suggestions
Before this project there was not a high quality set of weather data, available for all researchers, characterizing the weather data across Brazil. Because of this, researchers, including agronomists, economists, and earth systems scientists (e.g., climate modelers) can better calibrate their models to this historical conditions of Brazil. These data in turn should improve the accuracy of models that inform policy in a more accurate manner.
We suggest that a moderate amount of research funding be allocated to an annual updating of these gridded data sets.
Xavier, A.C., Scanlon, B.R. and King, C.W. (2016). Open-access dataset for daily meteorological variables in Brazil (1980- 2013). CLIMA Policy Brief #2, Centro Clima/COPPE/UFRJ, Rio de Janeiro, 4 p.
Background paper and data
Xavier, Alexandre C., King, Carey W. and Scanlon, Bridget R. Daily gridded meteorological variables in Brazil (1980-2013), International Journal of Climatology, 2016, 36 (6), 2644–2659. Link to paper: http://onlinelibrary.wiley.com/doi/10.1002/joc.4518/full.
Direct link to download data (login required): https://utexas.box.com/Xavier-etal-IJOC-DATA