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Numerous satellite-based precipitation datasets have been successively made available. Their precipitation estimates rely on clouds properties derived from microwave and thermal sensors in a so-named 'top-down' approach. Recently, a 'bottom-up' approach to infer precipitation from soil moisture (SM) estimates has resulted in the release of two new precipitation datasets (P-datasets). One uses satellite-based SM estimates from the European Spatial Agency (ESA) Climate Change Initiative (CCI) (SM2RAIN-CCI) while the other uses satellitebased SM from European Organization for the Exploitation of Meteorological Satellites (EUMETSAT) Advanced SCATterometer (ASCAT) (SM2RAIN-ASCAT). This study assesses SM2RAIN-ASCAT and-CCI reliability over two arid regions: Bolivian and Peruvian Altiplano and Pakistan (South Asia) using (a) direct comparisons with rain gauges and (b) testing the sensitivity of streamflow modelling to the P-datasets. Selecting two different regions and different indicators helps to assess whether the P-dataset reliability varies depending on the assessment method and location. For comparison purposes, the most reliable P-datasets from the literature are also considered (IMERG-E v.6, IMERG-L v.6, IMERG-F v.6, CHIRPS v.2 and MSWEP v.2.2). Compared to rain gauge observations and based on the modified Kling-Gupta Efficiency (KGE) values, the SM2RAIN-ASCAT and-CCI are more accurate in the Altiplano than in Pakistan. This difference is explained by a more favourable physical context for satellite-based SM estimates in the Altiplano. Over the Altiplano and despite an overall positive bias, SM2RAIN-ASCAT describes rain gauges temporal dynamics as well as IMERG-F v.6, CHIRPS v.2 and MSWEP v.2.2 and provides streamflow simulations very close to those obtained when using IMERG-F v.6, CHIRPS v.2 and MSWEP v.2.2 as forcing data.

Amazonian deforestation has accelerated during the last decade, threatening an ecosystem where almost one third of the regional rainfall is transpired by the local rainforest. Due to the precipitation recycling, the southwestern Amazon, including the Amazon-Andes transition region, is particularly sensitive to forest loss. This study evaluates the impacts of Amazonian deforestation in the hydro-climatic connectivity between the Amazon and the eastern tropical Andes during the austral summer (December-January-February) in terms of hydrological and energetic balances. Using 10-year high-resolution simulations (2001–2011) with the Weather Research and Forecasting Model, we analyze control and deforestation scenario simulations. Regionally, deforestation leads to a reduction in the surface net radiation, evaporation, moisture convergence and precipitation (~ 20%) over the entire Amazon basin. In addition, during this season, deforestation increases the atmospheric subsidence over the southern Amazon and weakens the regional Hadley cell. Atmospheric stability increases over the western Amazon and the tropical Andes inhibiting convection in these areas. Consequently, major deforestation impacts are observed over the hydro-climate of the Amazon-Andes transition region. At local scale, nighttime precipitation decreases in Bolivian valleys (~ 20–30%) due to a strong reduction in the humidity transport from the Amazon plains toward Andes linked to the South American low-level jet. Over these valleys, a weakening of the daytime upslope winds is caused by local deforestation, which reduces the turbulent fluxes at lowlands. These alterations in rainfall and atmospheric circulation could impact the rich Andean ecosystems and its tropical glaciers.

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