[1] Precipitation downscaling improves the coarse resolution and poor representation of precipitation in global climate models and helps end users to assess the likely hydrological impacts of climate change. This paper integrates perspectives from meteorologists, climatologists, statisticians, and hydrologists to identify generic end user (in particular, impact modeler) needs and to discuss downscaling capabilities and gaps. End users need a reliable representation of precipitation intensities and temporal and spatial variability, as well as physical consistency, independent of region and season. In addition to presenting dynamical downscaling, we review perfect prognosis statistical downscaling, model output statistics, and weather generators, focusing on recent developments to improve the representation of space‐time variability. Furthermore, evaluation techniques to assess downscaling skill are presented. Downscaling adds considerable value to projections from global climate models. Remaining gaps are uncertainties arising from sparse data; representation of extreme summer precipitation, subdaily precipitation, and full precipitation fields on fine scales; capturing changes in small‐scale processes and their feedback on large scales; and errors inherited from the driving global climate model.

Glacier changes are a vivid example of how environmental systems react to a changing climate. Distributed surface mass balance models, which translate the meteorological conditions on glaciers into local melting rates, help to attribute and detect glacier mass and volume responses to changes in the climate drivers. A well-calibrated model is a suitable test bed for sensitivity, detection, and attribution analyses for many scientific applications and often serves as a tool for quantifying the inherent uncertainties. Here, we present the open-source COupled Snowpack and Ice surface energy and mass balance model in PYthon (COSIPY), which provides a flexible and user-friendly framework for modeling distributed snow and glacier mass changes. The model has a modular structure so that the exchange of routines or parameterizations of physical processes is possible with little effort for the user. The framework consists of a computational kernel, which forms the runtime environment and takes care of the initialization, the input–output routines, and the parallelization, as well as the grid and data structures. This structure offers maximum flexibility without having to worry about the internal numerical flow. The adaptive subsurface scheme allows an efficient and fast calculation of the otherwise computationally demanding fundamental equations. The surface energy balance scheme uses established standard parameterizations for radiation as well as for the energy exchange between atmosphere and surface. The schemes are coupled by solving both surface energy balance and subsurface fluxes iteratively such that consistent surface skin temperature is returned at the interface. COSIPY uses a one-dimensional approach limited to the vertical fluxes of energy and matter but neglects any lateral processes. Accordingly, the model can be easily set up in parallel computational environments for calculating both energy balance and climatic surface mass balance of glacier surfaces based on flexible horizontal grids and with varying temporal resolution. The model is made available on a freely accessible site and can be used for non-profit purposes. Scientists are encouraged to actively participate in the extension and improvement of the model code.

We present a new open-source, collaborative “COupled Snowpack and Ice surface energy and MAss balance model” (COSIMA) that is evaluated for Zhadang glacier, Tibetan Plateau. The model is calibrated, run, and validated based on in situ measurements and atmospheric model data from the High Asia Refined analysis (HAR) over the period April 2009 to June 2012. Results for the model runs forced by both in situ measurements and HAR agree well with observations of various atmospheric, glaciological, surface, and subsurface parameters on the glacier. A time-lapse camera system next to the glacier provides a 3-year image time series of the mean transient snow line altitude and the snow cover pattern, which is used for the spatial and temporal validation of the model. The model output corresponds very well to the observed temporal and spatial snow cover variability. The model is then run for a 10-year period of October 2001 to September 2011 forced with HAR data. In general, the radiation components dominate...

The mass balance of mountain glaciers is of interest for several applications (e.g., local hydrology or climate projections), and turbulent fluxes can be an important contributor to glacier surface mass balance during strong melting events. The underlying complex terrain leads to spatial heterogeneity and non‐stationarity of turbulent fluxes. Owing to the contribution of thermally induced flows and gravity waves, exchange mechanisms are fully three‐dimensional, instead of only vertical. Additionally, glaciers have their own distinct microclimate, governed by a down‐glacier katabatic wind, which protects the glacier ice and interacts with the surrounding flows on multiple scales. In this study, we perform large‐eddy simulations with the Weather Research and Forecasting model at a horizontal grid spacing of 48 m to gain insight into the boundary‐layer processes over an Alpine valley glacier, the Hintereisferner. We choose two case studies from the Hintereisferner experiment measurement campaign with different synoptic wind directions (southwest and northwest). Model evaluation with an array of eddy‐covariance stations on the glacier tongue and surroundings reveals that the Weather Research and Forecasting model is able to simulate the general glacier boundary‐layer structure. Under a southwesterly airflow, the down‐glacier wind is supported by the synoptic wind parallel to the glacier axis, a stable boundary layer is present over the ice surface, and local processes govern the turbulence kinetic energy production. Under northwesterly airflow, a cross‐glacier valley flow and a breaking gravity wave lead to strong turbulent mixing and to the subsequent erosion of the glacier boundary layer. Stationarity analysis of the sensible heat flux suggests non‐stationary behaviour for both case study days, whereas non‐stationarity is highest on the northwesterly day during the gravity‐wave event. These results suggest that the synoptic wind direction has, in addition to upstream topography and the atmospheric stability, a strong impact on whether a local glacier boundary layer can form or not, influencing whether a glacier is able to maintain its own microclimate.

Patagonia is thought to be one of the wettest regions on Earth, although available regional precipitation estimates vary considerably. This uncertainty complicates understanding and quantifying the observed environmental changes, such as glacier recession, biodiversity decline in fjord ecosystems and enhanced net primary production. The Patagonian Icefields, for example, are one of the largest contributors to sea-level rise outside the polar regions, and robust hydroclimatic projections are needed to understand and quantify current and future mass changes. The reported projections of precipitation from numerical modelling studies tend to overestimate those from in situ determinations, and the plausibility of these numbers has never been carefully scrutinized, despite the significance of this topic to our understanding of observed environmental changes. Here I use simple physical arguments and a linear model to test the plausibility of the current precipitation estimates and its impact on the Patagonian Icefields. The results show that environmental conditions required to sustain a mean precipitation amount exceeding 6.09±0.64 m yr⁻¹ are untenable according to the regional moisture flux. The revised precipitation values imply a significant reduction in the surface mass balance of the Patagonian Icefields compared to previously reported values. This yields a new perspective on the response of Patagonia's glaciers to climate change and their sea-level contribution and might also help reduce uncertainties in the change of other precipitation-driven environmental phenomena.