Seasonal and annual extreme precipitation over the Peruvian Andes have been mapped for the first time. Maps were developed using the most complete, quality‐controlled and homogenous daily precipitation records in Peru from 1973 to 2016. For each observed rain gauge series, we defined parameters as the de‐clustered daily intensity, total precipitation duration, total magnitude and dry‐spell length. Then, we fitted the seasonal and annual series of these variables to a Generalized‐Pareto distribution using a peak‐over‐threshold approach. We estimated the distribution parameters and validated the performance of different thresholds to obtain the best estimation of precipitation probability. We also mapped the distribution parameters obtained for the different meteorological stations using the universal kriging algorithm, accounting for elevation and the distance to the Pacific Ocean as co‐variables. The accuracy of the extreme precipitation maps for a period of 25 and 50 years were validated using a jack‐knife approach. Some of the maps show strong uncertainty given the random spatial distribution of the variables as a consequence of the complex topography and climate of the region. Nevertheless, the maps show a useful general assessment of the spatial distribution of the precipitation hazard probability over the region, providing a good agreement with the estimations obtained in the meteorological stations for some variables and time periods analysed. Extreme precipitation maps over this high‐complex terrain of Peru are of key importance for flood risk assessment, water resources management, crop yield, soil conservation and human settlements.
<p>We develop for the first time maps of annual and seasonal extreme precipitation risk in the Andean region of Peru. For this purpose, we used the complete daily precipitation records existing in Peru and after a careful quality control and homogeneity checking we selected 178 stations distributed across the mountainous chain. In each meteorological station, we obtained series of events of de-clustered daily intensity, total precipitation duration, total magnitude and dry-spell length. Using a peak-over-threshold approach we fitted the annual and seasonal series of these variables to a Generalized-Pareto distribution, obtained the distribution parameters and validated the performance of different thresholds to obtain reliable estimations of the precipitation probability. We found that a 90<sup>th</sup> percentile is in general the most suitable to develop the estimations for the different variables. The parameters obtained in the different meteorological stations were mapped using a universal krigging approach using the elevation and the distance to the ocean as co-variables. Maps of parameters were validated using a jack-knife approach and maximum expected precipitation intensity, magnitude, duration and dry-spell length estimated for a period of 25 and 50 years. The reliability of the spatial methodology was validated comparing observed precipitation and estimated by the spatial modelling in the different stations.</p>
This study assessed changes in the maximum and minimum surface air temperatures across Peru during the period 1964–2014. For this purpose, we employed the most complete records of air temperature series that were also subjected to a rigorous quality control and homogenization protocol. Based on the homogenized series, we created a monthly gridded data set of maximum and minimum air temperatures at a 5 × 5 km grid spacing. The results suggest a general warming trend in surface air temperature across Peru, albeit with clear spatial and seasonal variation. Our results also reveal some differences in the detectable trends between maximum and minimum air temperatures. Maximum air temperature trends mainly increased during the austral summer (DJF), but cold season minimum air temperature trends showed an opposite pattern, with the strongest warming being recorded in the austral winter (JJA). In addition, maximum air temperature trends exhibited a clear elevation-warming dependency, with the strongest warming recorded at highly elevated sites. On the contrary, this dependency is weakened for minimum air temperature trends, as lower magnitudes of change and even a cooling trend were observed at high elevations during most months of the year. For mean air temperature trends, there are no clear spatial and temporal seasonal differences across Peru.