Search Results
Regional projections of temperature and precipitation changes: Robustness and uncertainty aspects
2017, Piniewski, M., Mezghani, A., Szczésniak, M., Kundzewicz, Z.W.
This study presents the analysis of bias-corrected projections of changes in temperature and precipitation in the Vistula and Odra basins, covering approximately 90% of the Polish territory and small parts of neighbouring countries in Central and Eastern Europe. The ensemble of climate projections consists of nine regional climate model simulations from the EURO-CORDEX ensemble for two future periods 2021-2050 and 2071-2100, assuming two representative concentration pathways (RCPs) 4.5 and 8.5. The robustness is measured by the ensemble models' agreement on significant changes.We found a robust increase in the annual mean of daily minimum and maximum temperature, by 1-1.4 °C in the near future and by 1.9-3.8 °C in the far future (areal-means of the ensemble mean values). Higher increases are consistently associated with minimum temperature and the gradient of change goes from SWto NE regions. Seasonal projections of both temperature variables reflect lower robustness and suggest a higher future increase in winter temperatures than in other seasons, notably in the far future under RCP 8.5 (by more than 1 °C). However, changes in annual means of precipitation are uncertain and not robust in any of the analysed cases, even though the climate models agree well on the increase. This increase is intensified with rising global temperatures and varies from 5.5% in the near future under RCP 4.5 to 15.2%in the far future under RCP 8.5. Spatial variability is substantial, although quite variable between individual climate model simulations. Although seasonal means of precipitation are projected to considerably increase in all four combinations of RCPs and projection horizons for winter and spring, the high model spread reduces considerably the robustness, especially for the far future. In contrast, the ensemble members agree well that overall, the summer and autumn (with exception of the far future under RCP 8.5) precipitation will not undergo statistically significant changes.
Evaluation of water balance components in the Elbe river catchment simulated by the regional climate model CCLM
2014, Volkholz, J., Grossman-Clarke, S., Hattermann, F.F., Böhm, U.
For investigations of feedbacks between the hydrological cycle and the climate system, we assess the performance of the regional climate model CCLM in reconstructing the water balance of the Elbe river catchment. To this end long-term mean precipitation, evapotranspiration and runoff are evaluated. Extremes (90th percentile) are also considered in the case of precipitation. The data are provided by a CCLM presentday simulation for Europe that was driven by large-scale global reanalyses. The quality of the model results is analyzed with respect to suitable reference data for the period 1970 to 1999. The principal components of the hydrological cycle and their seasonal variations were captured well. Basin accumulated, averaged daily precipitation, evapotranspiration and runoff differ by no more than 10% from observations. Larger deviations occur mainly in summer, and at specific areas.
Changes of temperature-related agroclimatic indices in Poland
2016, Graczyk, D., Kundzewicz, Z.W.
Reliability of regional climate model simulations of extremes and of long-term climate
2004, Böhm, U., Kücken, M., Hauffe, D., Gerstengarbe, E.-W., Werner, P.C., Flechsig, M., Keuler, K., Block, A., Ahrens, W., Nocke, T.
We present two case studies that demonstrate how a common evaluation methodology can be used to assess the reliability of regional climate model simulations from different fields of research. In Case I, we focused on the agricultural yield loss risk for maize in Northeastern Brazil during a drought linked to an El-Niño event. In Case II, the present-day regional climatic conditions in Europe for a 10-year period are simulated. To comprehensively evaluate the model results for both kinds of investigations, we developed a general methodology. On its basis, we elaborated and implemented modules to assess the quality of model results using both advanced visualization techniques and statistical algorithms. Besides univariate approaches for individual near-surface parameters, we used multivariate statistics to investigate multiple near-surface parameters of interest together. For the latter case, we defined generalized quality measures to quantify the model's accuracy. Furthermore, we elaborated a diagnosis tool applicable for atmospheric variables to assess the model's accuracy in representing the physical processes above the surface under various aspects. By means of this evaluation approach, it could be demonstrated in Case Study I that the accuracy of the applied regional climate model resides at the same level as that we found for another regional model and a global model. Excessive precipitation during the rainy season in coastal regions could be identified as a major contribution leading to this result. In Case Study II, we also identified the accuracy of the investigated mean characteristics for near-surface temperature and precipitation to be comparable to another regional model. In this case, an artificial modulation of the used initial and boundary data during preprocessing could be identified as the major source of error in the simulation. Altogether, the achieved results for the presented investigations indicate the potential of our methodology to be applied as a common test bed to different fields of research in regional climate modeling.
Ensemble simulations for the RCP8.5-Scenario
2015, Gerstengarbe, F.-W., Hoffmann, P., Österle, H., Werner, P.C.
SEMIC: An efficient surface energy and mass balance model applied to the Greenland ice sheet
2017, Krapp, Mario, Robinson, Alexander, Ganopolski, Andrey
We present SEMIC, a Surface Energy and Mass balance model of Intermediate Complexity for snow- and ice-covered surfaces such as the Greenland ice sheet. SEMIC is fast enough for glacial cycle applications, making it a suitable replacement for simpler methods such as the positive degree day (PDD) method often used in ice sheet modelling. Our model explicitly calculates the main processes involved in the surface energy and mass balance, while maintaining a simple interface and requiring minimal data input to drive it. In this novel approach, we parameterise diurnal temperature variations in order to more realistically capture the daily thaw–freeze cycles that characterise the ice sheet mass balance. We show how to derive optimal model parameters for SEMIC specifically to reproduce surface characteristics and day-to-day variations similar to the regional climate model MAR (Modèle Atmosphérique Régional, version 2) and its incorporated multilayer snowpack model SISVAT (Soil Ice Snow Vegetation Atmosphere Transfer). A validation test shows that SEMIC simulates future changes in surface temperature and surface mass balance in good agreement with the more sophisticated multilayer snowpack model SISVAT included in MAR. With this paper, we present a physically based surface model to the ice sheet modelling community that is general enough to be used with in situ observations, climate model, or reanalysis data, and that is at the same time computationally fast enough for long-term integrations, such as glacial cycles or future climate change scenarios.
Climate change impacts on hydrology and water resources
2015, Hattermann, F.F., Huang, S., Koch, H.
The regional aerosol-climate model REMO-HAM
2012, Pietikäinen, J.-P., O'Donnell, D., Teichmann, C., Karstens, U., Pfeifer, S., Kazil, J., Podzun, R., Fiedler, S., Kokkola, H., Birmili, W., O'Dowd, C., Baltensperger, U., Weingartner, E., Gehrig, R., Spindler, G., Kulmala, M., Feichter, J., Jacob, D., Laaksonen, A.
REMO-HAM is a new regional aerosol-climate model. It is based on the REMO regional climate model and includes most of the major aerosol processes. The structure for aerosol is similar to the global aerosol-climate model ECHAM5-HAM, for example the aerosol module HAM is coupled with a two-moment stratiform cloud scheme. On the other hand, REMO-HAM does not include an online coupled aerosol-radiation nor a secondary organic aerosol module. In this work, we evaluate the model and compare the results against ECHAM5-HAM and measurements. Four different measurement sites were chosen for the comparison of total number concentrations, size distributions and gas phase sulfur dioxide concentrations: Hyytiälä in Finland, Melpitz in Germany, Mace Head in Ireland and Jungfraujoch in Switzerland. REMO-HAM is run with two different resolutions: 50 × 50 km2 and 10 × 10 km2. Based on our simulations, REMO-HAM is in reasonable agreement with the measured values. The differences in the total number concentrations between REMO-HAM and ECHAM5-HAM can be mainly explained by the difference in the nucleation mode. Since we did not use activation nor kinetic nucleation for the boundary layer, the total number concentrations are somewhat underestimated. From the meteorological point of view, REMO-HAM represents the precipitation fields and 2 m temperature profile very well compared to measurement. Overall, we show that REMO-HAM is a functional aerosol-climate model, which will be used in further studies.