Andreas Gobiet

21st century climate change in the European Alps—A review☆

Reliable estimates of future climate change in the Alps are relevant for large parts of the European society. At the same time, the complex Alpine region poses considerable challenges to climate models, which translate to uncertainties in the climate projections. Against this background, the present study reviews the state-of-knowledge about 21st century climate change in the Alps based on existing literature and additional analyses. In particular, it explicitly considers the reliability and uncertainty of climate projections. Results show that besides Alpine temperatures, also precipitation, global radiation, relative humidity, and closely related impacts like floods, droughts, snow cover, and natural hazards will be affected by global warming. Under the A1B emission scenario, about 0.25 °C warming per decade until the mid of the 21st century and accelerated 0.36 °C warming per decade in the second half of the century is expected. Warming will probably be associated with changes in the seasonality of precipitation, global radiation, and relative humidity, and more intense precipitation extremes and flooding potential in the colder part of the year. The conditions of currently record breaking warm or hot winter or summer seasons, respectively, may become normal at the end of the 21st century, and there is indication for droughts to become more severe in the future. Snow cover is expected to drastically decrease below 1500-2000 m and natural hazards related to glacier and permafrost retreat are expected to become more frequent. Such changes in climatic parameters and related quantities will have considerable impact on ecosystems and society and will challenge their adaptive capabilities.

Empirical-statistical downscaling and error correction of regional climate models and its impact on the climate change signal

Realizing the error characteristics of regional climate models (RCMs) and the consequent limitations in their direct utilization in climate change impact research, this study analyzes a quantile-based empirical-statistical error correction method (quantile mapping, QM) for RCMs in the context of climate change. In particular the success of QM in mitigating systematic RCM errors, its ability to generate “new extremes” (values outside the calibration range), and its impact on the climate change signal (CCS) are investigated. In a cross-validation framework based on a RCM control simulation over Europe, QM reduces the bias of daily mean, minimum, and maximum temperature, precipitation amount, and derived indices of extremes by about one order of magnitude and strongly improves the shapes of the related frequency distributions. In addition, a simple extrapolation of the error correction function enables QM to reproduce “new extremes” without deterioration and mostly with improvement of the original RCM quality. QM only moderately modifies the CCS of the corrected parameters. The changes are related to trends in the scenarios and magnitude-dependent error characteristics. Additionally, QM has a large impact on CCSs of non-linearly derived indices of extremes, such as threshold indices.

Projections of future water resources and their uncertainty in a glacierized catchment in the Swiss Alps and the subsequent effects on hydropower production during the 21st century

[1] Hydropower accounts for about 20% of the worldwide electrical power production. In mountainous regions this ratio is significantly higher. In this study we present how future projected climatic forcing, as described in regional climate models (RCMs), will affect water resources and subsequently hydropower production in downstream hydropower plants in a glacierized alpine valley (Vispa valley, Switzerland, 778 km 2 ). In order to estimate future runoff generation and hydropower production, we used error-corrected and downscaled climate scenarios from regional climate models (RCMs) as well as glacier retreat projections from a dynamic glacier model and coupled them to a physically based hydrological model. Furthermore, we implemented all relevant hydropower operational rules in the hydrological model to estimate future hydropower production based on the runoff projections. The uncertainty of each modeling component (climate projections, glacier retreat, and hydrological projection) and the resulting propagation of uncertainty to the projected future water availability for energy production were assessed using an analysis of variance. While the uncertainty of the projections is considerable, the consistent trends observed in all projections indicate significant changes to the current situation. The model results indicate that future melt- and rainfall-runoff will increase during spring but decline during summer. The study concludes by outlining the most relevant expected changes for hydropower operations.

The European climate under a 2 °C global warming

A global warming of 2 C relative to pre-industrial climate has been considered as a threshold which society should endeavor to remain below, in order to limit the dangerous effects of anthropogenic climate change. The possible changes in regional climate under this target level of global warming have so far not been investigated in detail. Using an ensemble of 15 regional climate simulations downscaling six transient global climate simulations, we identify the respective time periods corresponding to 2 C global warming, describe the range of projected changes for the European climate for this level of global warming, and investigate the uncertainty across the multi-model ensemble. Robust changes in mean and extreme temperature, precipitation, winds and surface energy budgets are found based on the ensemble of simulations. The results indicate that most of Europe will experience higher warming than the global average. They also reveal strong distributional patterns across Europe, which will be important in subsequent impact assessments and adaptation responses in different countries and regions. For instance, a North‐South (West‐East) warming gradient is found for summer (winter) along with a general increase in heavy precipitation and summer extreme temperatures. Tying the ensemble analysis to time periods with a prescribed global temperature change rather than fixed time periods allows for the identification of more robust regional patterns of temperature changes due to removal of some of the uncertainty related to the global models’ climate sensitivity.

Parameterization-Induced Error Characteristics of MM5 and WRF Operated in Climate Mode over the Alpine Region: An Ensemble-Based Analysis

AbstractThis study investigates the role of physical parameterization in regional climate model simulations. The authors also present a comprehensive assessment of errors arising from use of physical parameterization schemes, and their consequent impact on model performance in a region of complex topography. An error range related to the choice of physical parameterization is provided for 2-m air temperature T2m and precipitation.Two state-of-the-art nonhydrostatic mesoscale regional climate models, the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) and the Weather Research and Forecasting (WRF) model, are used to dynamically downscale the 40-yr ECMWF Re-Analysis (ERA-40) to a spatial resolution of 10 km × 10 km in the European alpine region. Simulated T2m and precipitation are compared with gridded observational datasets. The model performance on regional and subregional scales is evaluated on daily, monthly, seasonal, and annual time scales....

High Resolution Sensitivity Studies with the Regional Climate Model CCLM in the Alpine Region

The presented study investigates the performance of the regional climate model CCLM operated at high resolution (10km grid) over the European Alpine region to find a suitable setup for long term regional climate simulations over mountainous terrain and to quantify various error sources. CCLM is run in 8 different setups, spanning a substantial range of possible settings of the model and is driven by the ECMWFs ERA-40 re-analysis. The results are systematically evaluated focussing on 2 m air temperature and precipitation amount. The annual mean error in the entire Alpine region lies between -0.14 and -0.42 mm/d for precipitation and -0.98 and -1.44K for temperature, depending on the model setup. By objectively defining climate subregions covering the Alpine region we also take advantage of the high model resolution to analyze subregional performance of the CCLM. It is shown that modifications of the domain size and vertical resolution have the greatest impact on the results, while altering the parameterization and numerics does not yield a significantly different outcome.

Precipitation in the EURO-CORDEX 0.11° and 0.44° simulations: high resolution, high benefits ?

In the framework of the EURO-CORDEX initiative an ensemble of European-wide high-resolution regional climate simulations on a 0.11∘(∼12.5km)\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}

Impacts of uncertainties in European gridded precipitation observations on regional climate analysis

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