Interactive coupling of regional atmosphere with biosphere in the new generation regional climate system model REMO-iMOVE

The main objective of this study is the coupling of the regional climate model REMO with a new land surface scheme including dynamic vegetation phenology, and the evaluation of the new model version called REMO with interactive MOsaic-based VEgetation: REMO-iMOVE. First, we focus on the documentation of the technical aspects of the new model constituents and the coupling mechanism. The representation of vegetation in iMOVE is based on plant functional types (PFTs). Their geographical distribution is prescribed to the model which can be derived from different land surface data sets. Here, the PFT distribution is derived from the GLOBCOVER 2000 data set which is available on 1 km × 1 km horizontal resolution. Plant physiological processes like photosynthesis, respiration and transpiration are incorporated into the model. The vegetation modules are fully coupled to atmosphere and soil. In this way, plant physiological activity is directly driven by atmospheric and soil conditions at the model time step (two minutes to some seconds). In turn, the vegetation processes and properties influence the exchange of substances, energy and momentum between land and atmosphere. With the new coupled regional model system, dynamic feedbacks between vegetation, soil and atmosphere are represented at regional to local scale. In the evaluation part, we compare simulation results of REMO-iMOVE and of the reference version REMO2009 to multiple observation data sets of temperature, precipitation, latent heat flux, leaf area index and net primary production, in order to investigate the sensitivity of the regional model to the new land surface scheme and to evaluate the performance of both model versions. Simulations for the regional model domain Europe on a horizontal resolution of 0.44° had been carried out for the time period 1995–2005, forced with ECMWF ERA-Interim reanalyses data as lateral boundary conditions. REMO-iMOVE is able to simulate the European climate with the same quality as the parent model REMO2009. Differences in near-surface climate parameters can be restricted to some regions and are mainly related to the new representation of vegetation phenology. The seasonal and interannual variations in growth and senescence of vegetation are captured by the model. The net primary productivity lies in the range of observed values for most European regions. This study reveals the need for implementing vertical soil water dynamics in order to differentiate the access of plants to water due to different rooting depths. This gets especially important if the model will be used in dynamic vegetation studies

Regional climate model simulations as input for hydrological applications: evaluation of uncertainties

International audienceThe ERA15 Reanalysis (1979-1993) has been dynamically downscaled over Central Europe using 4 different regional climate models. The regional simulations were analysed with respect to 2m temperature and total precipitation, the main input parameters for hydrological applications. Model results were validated against three reference data sets (ERA15, CRU, DWD) and uncertainty ranges were derived. For mean annual 2 m temperature over Germany, the simulation bias lies between -1.1°C and +0.9°C depending on the combination of model and reference data set. The bias of mean annual precipitation varies between -31 and +108 mm/year. Differences between RCM results are of the same magnitude as differences between the reference data sets

Case study for the assessment of the biogeophysical effects of a potential afforestation in Europe

BACKGROUND: A regional-scale sensitivity study has been carried out to investigate the climatic effects of forest cover change in Europe. Applying REMO (regional climate model of the Max Planck Institute for Meteorology), the projected temperature and precipitation tendencies have been analysed for summer, based on the results of the A2 IPCC-SRES emission scenario simulation. For the end of the 21st century it has been studied, whether the assumed forest cover increase could reduce the effects of the greenhouse gas concentration change. RESULTS: Based on the simulation results, biogeophysical effects of the hypothetic potential afforestation may lead to cooler and moister conditions during summer in most parts of the temperate zone. The largest relative effects of forest cover increase can be expected in northern Germany, Poland and Ukraine, which is 15-20% of the climate change signal for temperature and more than 50% for precipitation. In northern Germany and France, potential afforestation may enhance the effects of emission change, resulting in more severe heavy precipitation events. The probability of dry days and warm temperature extremes would decrease. CONCLUSIONS: Large contiguous forest blocks can have distinctive biogeophysical effect on the climate on regional and local scale. In certain regions of the temperate zone, climate change signal due to greenhouse gas emission can be reduced by afforestation due to the dominant evaporative cooling effect during summer. Results of this case study with a hypothetical land cover change can contribute to the assessment of the role of forests in adapting to climate change. Thus they can build an important basis of the future forest policy

The role of forests in mitigating climate change - A case study for Europe

A regional-scale case study has been carried out to assess the possible climatic benefits of forest cover increase in Europe. For the end of the 21st century (2071-2090) it has been investigated, whether the projected climate change could be reduced assuming potential afforestation of the continent. The magnitude of the biogeophysical effects of enhanced forest cover on temperature and precipitation means and extremes have been analyzed relative to the magnitude of the climate change signal applying the regional climate model REMO. The simulation results indicate that in the largest part of the temperate zone potential afforestation may reduce the projected climate change through cooler and moister conditions, thus could contribute to the mitigation of the projected climate change for the entire summer period. The largest relative effect of forest cover increase can be expected in northern Germany, Poland and Ukraine. Here, the projected precipitation decrease could be fully compensated, the temperature increase could be relieved by up to 0.5 degrees C, and the probability of extremely warm and dry days could be reduced. Results can help to identify the areas, where forest cover increase could be the most effective from climatic point of view. Thus they can build an important basis of the future adaptation strategies and forest policy

Assessing the transferability of the regional climate model REMO to different COordinated Regional Climate Downscaling EXperiment (CORDEX) Regions

The transferability of the regional climate model REMO with a standard setup over different regions of the world has been evaluated. The study is based on the idea that the modeling parameters and parameterizations in a regional climate model should be robust to adequately simulate the major climatic characteristic of different regions around the globe. If a model is not able to do that, there might be a chance of an “overtuning” to the “home-region”, which means that the model physics are tuned in a way that it might cover some more fundamental errors, e.g., in the dynamics. All simulations carried out in this study contribute to the joint effort by the international regional downscaling community called COordinated Regional climate Downscaling EXperiment (CORDEX). REMO has been integrated over six CORDEX domains forced with the so-called perfect boundary conditions obtained from the global reanalysis dataset ERA-Interim for the period 1989 to 2008. These six domains include Africa, Europe, North America, South America, West Asia and the Mediterranean region. Each of the six simulations was conducted with the identical model setup which allows investigating the transferability of a single model to regions with substantially different climate characteristics. For the consistent evaluation over the different domains, a new evaluation framework is presented by combining the Köppen-Trewartha climate classification with temperature-precipitation relationship plots and a probability density function (PDF) skill score method. The evaluation of the spatial and temporal characteristics of simulated precipitation and temperature, in comparison to observational datasets, shows that REMO is able to simulate the mean annual climatic features over all the domains quite reasonably, but still some biases remain. The regions over the Amazon and near the coast of major upwelling regions have a significant warm bias. Wet and dry biases appear over the mountainous regions and East Africa, respectively. The temperature over South America and precipitation over the tundra and highland climate of West Asia are misrepresented. The probable causes leading to these biases are discussed and ideas for improvements are suggested. The annual cycle of precipitation and temperature of major catchments in each domain are also well represented by REMO. The model has performed well in simulating the inter- and intra-seasonal characteristics of different climate types in different regions. Moreover, the model has a high ability in representing the general characteristics of different climate types as measured by the probability density function (PDF) skill score method. Although REMO seems to perform best over its home domain in Europe (domain of development and testing), the model has simulated quite well the climate characteristics of other regions with the same set of parameterization options. Therefore, these results lead us to the conclusion that REMO is well suited for long-term climate change simulations to examine projected future changes in all these regions