Daily gridded meteorological variables in Brazil (1980–2013)

Abstract

Basic meteorological data are essential for evaluating impacts of spatiotemporal variability in climate forcing on hydrology and agroecosystems. The objective of this work was to develop high-resolution grids (0.25 ∘ × 0.25 ∘ ) of daily precipitation, evapotranspiration, and the five climate variables generally required to estimate evapostranspiration for Brazil. These five variables are maximum and minimum temperature, solar radiation, relative humidity, and wind speed. We tested six different interpolation schemes to create the grids for these variables. The data were obtained from 3625 rain gauge and 735 weather stations for period of 1980-2013. We used a cross-validation approach that compares point observed data to point interpolated estimates to select the best interpolation scheme for each climate variable. We also present the performance of the best interpolation for each climate variable at daily timescales and for river basins. The inverse distance weighting and angular distance weighting methods produced the best results. Performance of all methods was poorer prior to 1995 because of fewer stations and available data. The performance of the interpolation varies for different seasons for almost all variables. Forecasting capability was tested for precipitation only and performed adequately for the system state (wet or dry). Variations in the interpolation schemes across river basins are primarily attributed to differences in gauge or station network density. This freely available gridded meteorological data set significantly advances the availability of climate data in Brazil.

Solar Radiation Models and Gridded Databases to Fill Gaps in Weather Series and to Project Climate Change in Brazil

“…For proper simulations, these models require high-quality and long-term historical daily weather data [2]. However, the major difficulty regarding historical weather data in Brazil is the low density of weather stations, associated with the reduced number of measured variables and the large amount of missing data [3][4][5].…”

“…Among the different approaches used to fill weather data gaps in, the main methods are climatic generators, which generate stochastic sequences of daily data, such as WGEN [6] and SIMMETEO [7] generators; empirical correlations using commonly measured meteorological variables present in the observed data [8][9][10]; and the use of the gridded weather database, based on satellite and/or surface data [2,4,11].…”

“…Given the great importance of historical weather data for assessing the impacts of climate change on human activities, mainly agriculture, in addition to the fact that Brazil has a low weather station density, with a large amount of missing data [3][4][5], the general objective of this study was to evaluate the performance of di erent alternatives to ll in weather data gaps and, based on that, to create climate change scenarios for Brazil. More speci cally, this study aimed (i) to evaluate the performance of temperature-based models for estimating solar radiation and gridded databases, such as AgCFSR, AgMERRA, NASA/POWER, and XAVIER, as procedures to ll in gaps of weather data (maximum and minimum air temperature, solar radiation, rainfall, wind speed, and relative humidity) for the period of 1980-2009; (ii) to generate, from the complete historical weather data, climate change scenarios, over the medium-term (2040-2069) and long-term (2070-2099) periods, based on seven GCMs of CMIP5, under intermediate (RCP4.5) and high (RCP8.5) emission scenarios; and (iii) to identify patterns of climate change in air temperature and rainfall in di erent Brazilian regions to de ne the expected trends in relation to the historical climate.…”

Hydrological system time lag responses to meteorological shifts

“…P obs consists of a gridded product constructed by Xavier, King and Scanlon (2015) using 1127 rain gauges in the Paraná basin. P sat consists of rainfall estimates from the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA), product 3B43 version 7.…”

Seasonal drought prediction for semiarid northeast Brazil: About the added value of a process-based hydrological model

“…A time series of daily precipitation for 380 stations within and in close vicinity around the study area were provided by FUNCEME. Other daily meteorological time series needed by the model (relative humidity, air temperature, and incoming shortwave radiation) were derived from the gridded dataset (0.25°30 × 0.25°resolution) of Xavier et al (2016). …”