Tobias Sauter

Precipitation downscaling under climate change: Recent developments to bridge the gap between dynamical models and the end user

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.

Natural Three-Dimensional Predictor Domains for Statistical Precipitation Downscaling

The paper presents an approach for conditional airmass classification based on local precipitation rate distributions. The method seeks, within the potential region, three-dimensional atmospheric predictor domains with high impact on the local-scale phenomena. These predictor domains are derived by an algorithm consisting of a clustering method, namely, self-organizing maps, and a nonlinear optimization method, simulated annealing. The findings show that the resulting spatial structures can be attributed to well-known atmospheric processes. Since the optimized predictor domains probably contain relevant information for precipitation generation, these grid points may also be potential inputs for nonlinear downscaling methods. Based on this assumption, the potential of these optimized large-scale predictors for downscaling has been investigated by applying an artificial neural network as a nonparametric statistical downscaling model. Compared to preset local predictors, using the optimized predictors improves the accuracy of the downscaled time series, particularly in summer and autumn. However, optimizing predictors by a conditional classification does not guarantee that a predictor increases the explained variance of the downscaling model. To study the contribution of each predictor to the output variance, either individually or by interactions with other parameters, the sources of uncertainty have been estimated by global sensitivity analysis, which provides model-free sensitivity measures. It is shown that predictor interactions play an important part in the modeling process and should be taken into account in the predictor screening.

Evaluation of a Coupled Snow and Energy Balance Model for Zhadang Glacier, Tibetan Plateau, Using Glaciological Measurements and Time-Lapse Photography

Abstract 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 overall energy turnover (65%), followed by the turbulent fluxes (31%). The generally dry atmosphere on the Tibetan Plateau causes sublimation to be responsible for 26% of the total mass loss. A proportion of 11% of the surface and subsurface melt refreezes within the snowpack.

A 17-year Record of Meteorological Observations Across the Gran Campo Nevado Ice Cap in Southern Patagonia, Chile, Related to Synoptic Weather Types and Climate Modes

The network of long-term meteorological observations in Southernmost Patagonia is still sparse but crucial to improve our understanding of climatic variability, in particular in the more elevated and partially glaciated Southernmost Andes. Here we present a unique 17-year meteorological record (2000-2016) of four automatic weather stations across the Gran Campo Nevado Ice Cap (53

Recent atmospheric variability at Kibo Summit, Kilimanjaro, and its relation to climate mode activity

^{\circ}

Snow Cover Change as a Climate Indicator in Brunswick Peninsula, Patagonia

S) in the Southernmost Andes (Chile) and the conventional weather station Jorge Schythe of the Instituto de la Patagonia in Punta Arenas for comparison. We revisit the relationship between in-situ observations and large-scale climate models as well as mesoscale weather patterns. For this purpose, a 37-year record of ERA Interim Reanalysis data has been used to compute a weather type classification based on a hierarchical correlation-based leader algorithm. The orographic perturbation on the predominantly westerly airflow determines the hydroclimatic response across the mountain range, leading to significant west-east gradients of precipitation, air temperature and humidity. Annual precipitation sums heavily drop within only tens of kilometers from \textasciitilde 7500 mm\,a

Glacier Mass Changes of Lake-Terminating Grey and Tyndall Glaciers at the Southern Patagonia Icefield Derived From Geodetic Observations and Energy and Mass Balance Modeling

^{-1}

Statistical downscaling of daily temperatures in the NW Iberian Peninsula from global climate models: validation and future scenarios

to less than 800 mm\,a

Spatio-temporal prediction of snow cover in the Black Forest mountain range using remote sensing and a recurrent neural network

^{-1}

Impact of two conceptual precipitation downscaling schemes on mass-balance modeling of Gran Campo Nevado ice cap, Patagonia

. The occurrence of high precipitation events of up to 620 mm in 5 days and wet spells of up to 61 consecutive days underscore the year-around wet conditions in the Southernmost Andes. Given the strong link between large-scale circulation and orographically controlled precipitation, the synoptic-scale weather conditions largely determine the precipitation and temperature variability on all time scales. Major synoptic weather types with distinct low-pressure cells in the Weddell Sea or Bellingshausen Sea, causing a prevailing southwesterly, northwesterly or westerly airflow, determine the weather conditions in Southernmost Patagonia during 68