While the Amazon rainforest area has a known effect on precipitation and global water vapour circulation, it is still poorly understood. This is in part due to the lack and inconsistency in atmospheric observations in the area. This dataset holds the high resolution (0.5 x 0.5 deg; 8 vertical levels) monthly means of 5 atmospheric variables (air temperature, pressure, water vapour pressure, vertical velocity and horizontal wind speed) over the Amazon Basin for the period 1972 to 2009. This data is public and in particular, version 1.0 is citable (DOI: 10.5285/2dfce039-cd71-43b3-bed4-98978e78f1bb).

This dataset holds the high resolution (0.5 x 0.5 deg; 8 vertical levels) monthly means of 5 atmospheric variables (air temperature, pressure, water vapour pressure, vertical velocity and horizontal wind speed) over the Amazon Basin for the period 1972 to 2009 (version 1.0). This data is public and citable (DOI: 10.5285/2dfce039-cd71-43b3-bed4-98978e78f1bb). It was constructed using the predictive capabilities of Time-Delayed Neural Networks (TDNN) method. Thirty years of monthly averages of current climate data (1971-2000) of the NCEP/NCAR reanalysis dataset were used to train the TDNNs, which were then validated on the next 10 years (2001-2010). Once validated, the downscaling model was fed with the higher resolution CRU TS3.1 data and SRTM-1km elevation data (thereby obtaining the higher resolution dataset).