An important driver of the terrestrial hydrological cycle is atmospheric evaporative demand. Recent studies using measurements of pan evaporation have found evidence that the atmospheric evaporative demand has been declining over the second half of the 20th century. This work analyses long-term time series of pan evaporation obtained from approximately 150 ± 30 weather stations located in Mexico with aridity indexes ranging from 0.3 to 10 for 1961-2010. The results show a consistent decline in annual pan evaporation for 1960-1990 (−3.8 mm year −2 ) and for 1990-2010 (−2.6 mm year −2 ) periods whereas the average change during the complete period corresponds to −3.3 mm year −2 . Statistically significant negative changes using the non-parametric Mann-Kendall test were found in 43% of the stations for the early and 27% for the recent periods, respectively. The temperature, relative humidity, radiative and aerodynamic controls attributed to the observed changes are analysed with the Noah model output from the Global Land Data Assimilation System Version 2 (GLDAS-2). Among the climatological variables extracted from GLDAS-2, it was the annual wind speed and net radiation that gave the highest statistical correlations. This work agrees with previous studies that pan evaporation rates have been in a declining trend during the second half of the 20th century though milder decline rates have been observed over the last 20 years. Finally, we show that the magnitude of change in regions dominated by wind and in those dominated by radiative processes can strongly differ.KEY WORDS

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A spatiotemporal object-based rainfall analysis method is used to evaluate the hydrological response of two systematic satellite error sources for storm estimation in the Capivari catchment, Brazil. This method is called Spatiotemporal Contiguous Object-based Rainfall Analysis (ST-CORA) specifically evaluates the error structure of satellite-based rainfall products using a 3D pattern clustering algorithm. Errors due to location and magnitude in the Near Real-time (NRT) CMORPH product are subtracted by adjusting the shift and the intensity distribution with respect to a storm object obtained from gauge-adjusted weather radar. Synthetic scenarios of each error source are used as forcing for hourly calibrated distributed hydrological 'wflow-sbm' model to evaluate the main sources of systematic errors in the hydrological response. Two types of storm events in the study area are evaluated: short-lived and a long-lived storm. The results indicate that the spatiotemporal characteristics obtained by ST-CORA clearly reflect the main source of errors of the CMORPH storm detection. It is found that location is the main source of error for the short-lived storm event, while volume is the main source in the longlived storm event. The subtraction of both errors leads to an important reduction of the simulated streamflow in the catchment. The method applied can be useful in bias correction schemes for satellite estimations especially for extreme precipitation events.