Marcus Breil

Bias reduction in decadal predictions of West African monsoon rainfall using regional climate models

The West African monsoon rainfall is essential for regional food production, and decadal predictions are necessary for policy makers and farmers. However, predictions with global climate models reveal precipitation biases. This study addresses the hypotheses that global prediction biases can be reduced by dynamical downscaling with a multimodel ensemble of three regional climate models (RCMs), a RCM coupled to a global ocean model and a RCM applying more realistic soil initialization and boundary conditions, i.e., aerosols, sea surface temperatures (SSTs), vegetation, and land cover. Numerous RCM predictions have been performed with REMO, COSMO-CLM (CCLM), and Weather Research and Forecasting (WRF) in various versions and for different decades. Global predictions reveal typical positive and negative biases over the Guinea Coast and the Sahel, respectively, related to a southward shifted Intertropical Convergence Zone (ITCZ) and a positive tropical Atlantic SST bias. These rainfall biases are reduced by some regional predictions in the Sahel but aggravated by all RCMs over the Guinea Coast, resulting from the inherited SST bias, increased westerlies and evaporation over the tropical Atlantic and shifted African easterly waves. The coupled regional predictions simulate high-resolution atmosphere-ocean interactions strongly improving the SST bias, the ITCZ shift and the Guinea Coast and Central Sahel precipitation biases. Some added values in rainfall bias are found for more realistic SST and land cover boundary conditions over the Guinea Coast and improved vegetation in the Central Sahel. Thus, the ability of RCMs and improved boundary conditions to reduce rainfall biases for climate impact research depends on the considered West African region.

Quantification of the Uncertainties in Soil and Vegetation Parameterizations for Regional Climate Simulations in Europe

AbstractThe deterministic description of the subgrid-scale land–atmosphere interaction in regional climate model (RCM) simulations is changed by using stochastic soil and vegetation parameterizations. For this, the land–atmosphere interaction parameterized in a land surface model (LSM) is perturbed stochastically by adding a random value to the input parameters using a random number generator. In this way, a stochastic ensemble is created that represents the impact of the uncertainties in these subgrid-scale processes on the resolved scale circulation. In a first step, stochastic stand-alone simulations with the VEG3D LSM are performed to identify sensitive model parameters. Afterward, VEG3D is coupled to the Consortium for Small-Scale Modeling–Climate Limited-Area Modeling (COSMO-CLM) RCM and stochastically perturbed simulations driven by ERA-Interim (2001–10) are performed for the Coordinated Downscaling Experiment–European Domain (EURO-CORDEX) at a horizontal resolution of 0.22°. The simulation results...

High Resolution Climate Modeling with the CCLM Regional Model

Using the CRAY XE-6 at the HLRS high performance computing facilities provides the possibility to study various aspects of the regional climate employing the regional climate model COSMO-CLM. The research activities of the group “Regional Climate and Water Cycle” at the KIT focus on the regional atmospheric water cycle and, especially, on extremes and different goals are pursued in the individual research projects. Different regions and orographies are studied using different resolutions from 50 to 3 km. Furthermore, different time spans are investigated and computational capacities from 2 to 500 node-hours per year (Wall Clock Time) are required. The analyses comprise decadal climate simulations of Germany, Europe and Africa to assess regional decadal climate predictability. Further, climate projections are carried out for Baden-Wurttemberg (Germany) and novel ensemble generating techniques are implemented to better describe the involved uncertainties. High resolution (3 km) experiments are performed for Baden-Wurttemberg to study extremes and the effects of climate change on soil erosion. Moreover, the possibilities of adaption to climate change for Baden-Wurttemberg are analysed, with focus on extremes and combination of extremes (such as dry soil and extreme precipitation).

Einfluss der Boden-Vegetation-Atmosphären Wechselwirkungen auf die dekadische Vorhersagbarkeit des Westafrikanischen Monsuns

Diese Arbeit geht der Frage nach, wie sich die Wechselwirkungen zwischen Boden, Vegetation und Atmosphare auf die Auspragung des Westafrikanischen Monsuns auswirken. Dafur werden Klimasimulationen mit dem Regionalen Klimamodell COSMO-CLM durchgefuhrt, an das zwei unterschiedliche Boden-Vegetationsmodelle gekoppelt werden. Aus den Simulationsergebnissen werden sensitive Prozesse innerhalb dieses Systemkomplexes abgeleitet und deren Einfluss auf die dekadische Variabilitat des Monsuns untersucht.

Sensitivity of European temperature to albedo parameterization in the regional climate model COSMO-CLM linked to extreme land use changes

Previous studies based on observations and models are uncertain about the biophysical impact of af- and deforestation in the northern hemisphere mid-latitude summers, and show either a cooling or warming. The magnitude and direction is still uncertain. In this study, the effect of three different albedo parameterizations in the regional climate model COSMO-CLM (v5.09) is examined performing afforestation experiments at 0.44° horizontal resolution across the EURO-CORDEX domain during 1986-2015. Idealized de- and af-forestation simulations are compared to a simulation with no land cover change. Emphasis is put on the impact of changes in radiation and turbulent fluxes. A clear latitudinal pattern is found, which results partly due to the strong land cover conversion from forest- to grassland in the high latitudes and open land to forest conversion in mid-latitudes. Afforestation warms the climate in winter, and strongest in mid-latitudes. Results are indifferent in summer owing to opposing albedo and evapotranspiration effects of comparable size but different sign. Thus, the net effect is small for summer. Depending on the albedo parameterization in the model, the temperature effect can turn from cooling to warming in mid-latitude summers. The summer warming due to deforestation to grassland is up to 3 °C higher than due to afforestation. The cooling by grass or warming by forest is in magnitude comparable and small in winter. The strength of the described near-surface temperature changes depends on the magnitude of the individual biophysical changes in the specific background climate conditions of the region. Thus, the albedo parameterization need to account for different vegetation types. Furthermore, we found that, depending on the region, the land use change effect is more important than the model uncertainty due to albedo parameterization. This is important information for model development.

High Resolution Climate Modelling with the CCLM Regional Model for Europe and Africa

The High Performance Computing System (HPC) CRAY XE6 operated by HLRS is a powerful tool to study various aspects of the regional climate. Employing the regional climate model (RCM) COSMO-CLM, the research focus of IMK-TRO is on the regional atmospheric water cycle, especially on extremes, and different goals are pursued in individual research projects (MiKlip, KLIMOPASS and KLIWA). The simulation regions comprise Germany, Europe, and Africa with resolutions varying from 50 km to 2.8 km. Furthermore, different time spans are investigated. Decadal simulations are performed to assess decadal regional climate predictability. Projections of the future climate consider periods up to the end of the twenty-first century. To quantify the uncertainty of climate projections and predictions as well as the quality of the models, ensembles are built by different techniques. The Soil-Vegetion-Atmosphere-Transfer model (SVAT) VEG3D is coupled to COSMO-CLM via OASIS3-MCT to investigate the effect of soil and vegetation processes on decadal climate predictions. High resolution (2.8 km) experiments are performed for the State of Baden–Wurttemberg to study the potential added value and extremes. Computational capacities from 100 to 650 node–hours per simulated year (Wall Clock Time) are required for these simulations.