Abstract. Climate time series are of major importance for base line studies for climate change impact and adaptation projects. However, for instance, in mountain regions and in developing countries there exist significant gaps in ground based climate records in space and time. Specifically, in the Peruvian Andes spatially and temporally coherent precipitation information is a prerequisite for ongoing climate change adaptation projects in the fields of water resources, disasters and food security. The present work aims at evaluating the ability of Tropical Rainfall Measurement Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) to estimate precipitation rates at daily 0.25 • × 0.25 • scale in the Central Andes and the dependency of the estimate performance on changing spatial and temporal resolution. Comparison of the TMPA product with gauge measurements in the regions of Cuzco, Peru and La Paz, Bolivia were carried out and analysed statistically. Large biases are identified in both investigation areas in the estimation of daily precipitation amounts. The occurrence of strong precipitation events was well assessed, but their intensities were underestimated. TMPA estimates for La Paz show high false alarm ratio.The dependency of the TMPA estimate quality with changing resolution was analysed by comparisons of 1-, 7-, 15-and 30-day sums for Cuzco, Peru. The correlation of TMPA estimates with ground data increases strongly and almost linearly with temporal aggregation. The spatial aggre- In order to profit from the TMPA combination product on a daily basis, a procedure to blend it with daily precipitation gauge measurements is proposed.Different sources of errors and uncertainties introduced by the sensors, sensor-specific algorithm aspects and the TMPA processing scheme are discussed. This study reveals the possibilities and restrictions of the use of TMPA estimates in the Central Andes and should assist other researchers in the choice of the best resolution-accuracy relationship according to requirements of their applications.

Assignificantimpactsofclimatechangeareincreasinglyconsideredunavoidable,adaptationhas become a policypriority. Itis generally agreedthat science is importantfor the adaptation process but specific guidance on how and to what degree science should contribute and be embedded in this process is still limited which is at odds with the high demand for science contributions to climate adaptation by international organizations, national governments and others. Here we presentandanalyzeexperiencesfromthetropicalAndesbasedonarecentscience-policyprocess on the national and supra-national government level. During this process a framework for the science contribution in climate adaptation has been developed; it consists of three stages, including(1) the framing and problemdefinition, (2)the scientific assessmentof climate, impacts, vulnerabilitiesandrisks,and(3)theevaluationofadaptationoptionsandtheirimplementation.A large amount of methods has been analyzed for stage (2), and a number of major climate adaptation projects in the region assessed for (3). Our study underlines the importance of joint problem framing among various scientific and non-scientific actors, definition of socio-environmental systems, time frames, and a more intense interaction of social and physical climate and impact sciences.Scientifically,thescarcityofenvironmental,socialandeconomic data inregions like the Andes continue to represent a limitation to adaptation, and further investments into coordinated socio-environmental monitoring, data availability and sharing are essential.

Climate time series are of major importance for base line studies for climate change impact and adaptation projects. However, in mountain regions and in developing countries there exist significant gaps in ground based climate records in space and time. Specifically, in the Peruvian Andes spatially and temporally coherent precipitation information is a prerequisite for ongoing climate change adaptation projects in the fields of water resources, disasters and food security. The present work aims at evaluating the ability of Tropical Rainfall Measurement Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) to estimate precipitation rates at daily 0.25° × 0.25° scale in the Central Andes and the dependency of the estimate performance on changing spatial and temporal resolution. Comparison of the TMPA product with gauge measurements in the regions of Cuzco, Peru and La Paz, Bolivia were carried out and analysed statistically. Large biases are identified in both investigation areas in the estimation of daily precipitation amounts. The occurrence of strong precipitation events was well assessed, but their intensities were underestimated. TMPA estimates for La Paz show high false alarm ratio. <br><br> The dependency of the TMPA estimate quality with changing resolution was analysed by comparisons of 1-, 7-, 15- and 30-day sums for Cuzco, Peru. The correlation of TMPA estimates with ground data increases strongly and almost linearly with temporal aggregation. The spatial aggregation to 0.5°, 0.75° and 1° grid box averaged precipitation and its comparison to gauge data of the same areas revealed no significant change in correlation coefficients and estimate performance. <br><br> In order to profit from the TMPA combination product on a daily basis, a procedure to blend it with daily precipitation gauge measurements is proposed. <br><br> Different sources of errors and uncertainties introduced by the sensors, sensor-specific algorithm aspects and the TMPA processing scheme are discussed. This study reveals the possibilities and restrictions of the use of TMPA estimates in the Central Andes and should assist other researchers in the choice of the best resolution-accuracy relationship according to requirements of their applications

Abstract. The El Niño and La Niña impacts on the hydrology of Peru were assessed based on discharge data (1968–2006) of 20 river catchments distributed over three drainage regions in Peru: 14 in the Pacific Coast (PC), 3 in the Lake Titicaca (TL) region, and 3 in the Amazonas (AM). To classify the El Niño and La Niña events, we used the Southern Oscillation Index (SOI) based on hydrological years (September to August). Using the SOI values, the events were re-classified as strong El Niño (SEN), moderate El Niño (MEN), normal years (N), moderate La Niña (MLN) and strong La Niña (SLN). On average during the SEN years, sharp increases occurred in the discharges in the north central area of the PC and decreases in the remaining discharge stations that were analyzed, while in the years of MEN events, these changes show different responses than those of the SEN. During the years classified as La Niña, positive changes are mostly observed in the majority of the stations in the rivers located in the center of Peru's Pacific Coast. Another important result of this work is that the Ilave River (south of the Titicaca watershed) shows higher positive (negative) impacts during La Niña (El Niño) years, a fact that is not clearly seen in the rivers of the northern part of the Titicaca watershed (Ramis and Huancane rivers).

Abstract. In the frame of a Swiss-Peruvian climate change adaptation initiative (PACC), operational and historical data series of more than 100 stations of the Peruvian Meteorological and Hydrological Service (SENAMHI) are now accessible in a dedicated data portal. The data portal allows for example the comparison of data series or the interpolation of spatial fields as well as download of data in various data formats. It is thus a valuable tool supporting the process of data homogenisation and generation of a regional baseline climatology for a sound development of adequate climate change adaptation measures. The procedure to homogenize air-temperature and precipitation data series near Cusco city is outlined and followed by an exemplary trend analysis. Local air temperature trends are found to be in line with global mean trends.