Bodo Ahrens

Med-CORDEX initiative for Mediterranean climate studies

The Mediterranean is expected to be one of the most prominent and vulnerable climate change “hot spots” of the 21st century, and the physical mechanisms underlying this finding are still not clear. Furthermore complex interactions and feedbacks involving ocean-atmosphere-land-biogeochemical processes play a prominent role in modulating the climate and environment of the Mediterranean region on a range of spatial and temporal scales. Therefore it is critical to provide robust climate change information for use in Vulnerability/Impact/Adaptation assessment studies considering the Mediterranean as a fully coupled environmental system. The Med-CORDEX initiative aims at coordinating the Mediterranean climate modeling community towards the development of fully coupled regional climate simulations, improving all relevant components of the system, from atmosphere and ocean dynamics to land surface, hydrology and biogeochemical processes. The primary goals of Med-CORDEX are to improve understanding of past climate variability and trends, and to provide more accurate and reliable future projections, assessing in a quantitative and robust way the added value of using high resolution and coupled regional climate models. The coordination activities and the scientific outcomes of Med-CORDEX can produce an important framework to foster the development of regional earth system models in several key regions worldwide.

Can Regional Climate Models Represent the Indian Monsoon

AbstractThe ability of four regional climate models (RCMs) to represent the Indian monsoon was verified in a consistent framework for the period 1981–2000 using the 45-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) as lateral boundary forcing data. During the monsoon period, the RCMs are able to capture the spatial distribution of precipitation with a maximum over the central and west coast of India, but with important biases at the regional scale on the east coast of India in Bangladesh and Myanmar. Most models are too warm in the north of India compared to the observations. This has an impact on the simulated mean sea level pressure from the RCMs, being in general too low compared to ERA-40. Those biases perturb the land–sea temperature and pressure contrasts that drive the monsoon dynamics and, as a consequence, lead to an overestimation of wind speed, especially over the sea. The timing of the monsoon onset of the RCMs is in good agreement with the one obtained from...

Downscaled climate change projections with uncertainty assessment over India using a high resolution multi-model approach

This study presents the possible regional climate change over South Asia with a focus over India as simulated by three very high resolution regional climate models (RCMs). One of the most striking results is a robust increase in monsoon precipitation by the end of the 21st century but regional differences in strength. First the ability of RCMs to simulate the monsoon climate is analyzed. For this purpose all three RCMs are forced with ECMWF reanalysis data for the period 1989-2008 at a horizontal resolution of ~25 km. The results are compared against independent observations. In order to simulate future climate the models are driven by lateral boundary conditions from two global climate models (GCMs: ECHAM5-MPIOM and HadCM3) using the SRES A1B scenario, except for one RCM, which only used data from one GCM. The results are presented for the full transient simulation period 1970-2099 and also for several time slices. The analysis concentrates on precipitation and temperature over land. All models show a clear signal of gradually wide-spread warming throughout the 21st century. The ensemble-mean warming over India is 1.5°C at the end of 2050, whereas it is 3.9°C at the end of century with respect to 1970-1999. The pattern of projected precipitation changes shows considerable spatial variability, with an increase in precipitation over the peninsular of India and coastal areas and, either no change or decrease further inland. From the analysis of a larger ensemble of global climate models using the A1B scenario a wide spread warming (~3.2°C) and an overall increase (~8.5%) in mean monsoon precipitation by the end of the 21st century is very likely. The influence of the driving GCM on the projected precipitation change simulated with each RCM is as strong as the variability among the RCMs driven with one.

Precipitation by a regional climate model and bias correction in Europe and South Asia

Because coarse-grid global circulation models do not allow for regional estimates of the water balance or trends of extreme precipitation, downscaling of global simulations is necessary to generate regional precipitation. This paper applies for downscaling the regional climate model CLM as a dynamical downscaling method (DDM) and two statistical downscaling methods (SDMs). Because the SDMs neglect information available to the DDM, and vice versa, a combination of the dynamical and statistical approaches is proposed here. In this combined approach, a simple statistical step is carried out to correct for the regional model biases in the dynamically downscaled simulations. To test the proposed methods, coarse-grid global re-analysis data (ERA40 with ∼ 1.125° grid spacing) is downscaled in two regions with different climatology and orography: one in South Asia and the other in Europe. All of the methods are tested on daily precipitation with 0.5° grid spacing. The SDMs are generally successful: the standardized root mean square error of rain day intensity is reduced from ERA40s 0.16 to 0.10 in a test area to the west of the European Alps. The CLM simulations perform less well (with a corresponding error of 0.14), but represent a promising approach if the user requires flexibility and independence from observational data. The proposed bias correction of the CLM simulations performs very well in European test areas (better than or at least comparable with the SDMs; i.e., with a corresponding error of 0.07), but fails in South Asia. An investigation of the observed and simulated precipitation climate in the test areas shows a strong dependence of the bias correction performance on sampling statistics (i.e., rain day frequency) and on the robustness of bias estimation.

Asynchronous responses of East Asian and Indian summer monsoons to mountain uplift shown by regional climate modelling experiments

It has been demonstrated in climate models that both the Indian and East Asian summer monsoons (ISM and EASM) are strengthened by the uplift of the entire Asian orography or Tibetan Plateau (TP) (i.e. bulk mountain uplift). Such an effect is widely perceived as the major mechanism contributing to the evolution of Asian summer monsoons in the Neogene. However, geological evidence suggests more diachronous growth of the Asian orography (i.e. regional mountain uplift) than bulk mountain uplift. This demands a re-evaluation of the relation between mountain uplift and the Asian monsoon in the geological periods. In this study, sensitivity experiments considering the diachronous growth of different parts of the Asian orography are performed using the regional climate model COSMO-CLM to investigate their effects on the Asian summer monsoons. The results show that, different from the bulk mountain uplift, the regional mountain uplift can lead to an asynchronous development of the ISM and EASM. While the ISM is primarily intensified by the thermal insulation (mechanical blocking) effect of the southern TP (Zagros Mountains), the EASM is mainly enhanced by the surface sensible heating of the central, northern and eastern TP. Such elevated surface heating can induce a low-level cyclonic anomaly around the TP that reduces the ISM by suppressing the lower tropospheric monsoon vorticity, but promotes the EASM by strengthening the warm advection from the south of the TP that sustains the monsoon convection. Our findings provide new insights to the evolution of the Asian summer monsoons and their interaction with the tectonic changes in the Neogene.

On the Weighting of Multimodel Ensembles in Seasonal and Short-Range Weather Forecasting

Abstract The performance of multimodel ensemble forecasting depends on the weights given to the different models of the ensemble in the postprocessing of the direct model forecasts. This paper compares the following different weighting methods with or without taking into account the single-model performance: equal weighting of models (EW), simple skill-based weighting (SW), using a simple model performance indicator, and weighting by Bayesian model averaging (BMA). These methods are tested for both short-range weather and seasonal temperature forecasts. The prototype seasonal multimodel ensemble is the Development of a European Multimodel Ensemble System for Seasonal-to-Interannual Prediction (DEMETER) system, with four different models and nine forecasts per model. The short-range multimodel prototype system is the European Meteorological Services (EUMETNET) Poor-Man’s Ensemble Prediction System (PEPS), with 14 models and one forecast per model. It is shown that despite the different forecast ranges and ...

Soil Moisture–Precipitation Feedback Processes in the Indian Summer Monsoon Season

AbstractSoil moisture can influence precipitation through a feedback loop with land surface evapotranspiration. A series of numerical simulations, including soil moisture sensitivity experiments, have been performed for the Indian summer monsoon season (ISM). The simulations were carried out with the nonhydrostatic regional climate model Consortium for Small-Scale Modeling (COSMO) in climate mode (COSMO-CLM), driven by lateral boundary conditions derived from the ECMWF Interim reanalysis (ERA-Interim). Positive as well as negative feedback processes through local and remote effects are shown to be important. The regional moisture budget studies have exposed that changes in precipitable water and changes in precipitation efficiency vary in importance, in time, and in space in the simulations for India. Overall, the results show that the premonsoonal soil moisture has a significant influence on the monsoonal precipitation, and thus confirmed that modeling of soil moisture is essential for reliable simulatio...

Risk Factors for the Presence of Chikungunya and Dengue Vectors (Aedes aegypti and Aedes albopictus), Their Altitudinal Distribution and Climatic Determinants of Their Abundance in Central Nepal

Background The presence of the recently introduced primary dengue virus vector mosquito Aedes aegypti in Nepal, in association with the likely indigenous secondary vector Aedes albopictus, raises public health concerns. Chikungunya fever cases have also been reported in Nepal, and the virus causing this disease is also transmitted by these mosquito species. Here we report the results of a study on the risk factors for the presence of chikungunya and dengue virus vectors, their elevational ceiling of distribution, and climatic determinants of their abundance in central Nepal. Methodology/Principal Findings We collected immature stages of mosquitoes during six monthly cross-sectional surveys covering six administrative districts along an altitudinal transect in central Nepal that extended from Birgunj (80 m above sea level [asl]) to Dhunche (highest altitude sampled: 2,100 m asl). The dengue vectors Ae. aegypti and Ae. albopictus were commonly found up to 1,350 m asl in Kathmandu valley and were present but rarely found from 1,750 to 2,100 m asl in Dhunche. The lymphatic filariasis vector Culex quinquefasciatus was commonly found throughout the study transect. Physiographic region, month of collection, collection station and container type were significant predictors of the occurrence and co-occurrence of Ae. aegypti and Ae. albopictus. The climatic variables rainfall, temperature, and relative humidity were significant predictors of chikungunya and dengue virus vectors abundance. Conclusions/Significance We conclude that chikungunya and dengue virus vectors have already established their populations up to the High Mountain region of Nepal and that this may be attributed to the environmental and climate change that has been observed over the decades in Nepal. The rapid expansion of the distribution of these important disease vectors in the High Mountain region, previously considered to be non-endemic for dengue and chikungunya fever, calls for urgent actions to protect the health of local people and tourists travelling in the central Himalayas.

Evaluation of Satellite-Based and Reanalysis Precipitation Data in the Tropical Pacific

AbstractGlobal precipitation monitoring is essential for understanding the earth’s water and energy cycle. Therefore, usage of satellite-based precipitation data is necessary where in situ data are rare. In addition, atmospheric-model-based reanalysis data feature global data coverage and offer a full catalog of atmospheric variables including precipitation. In this study, two model-based reanalysis products, the interim reanalysis by the European Centre for Medium-Range Weather Forecasts (ERA-Interim) and NASA’s Modern-Era Retrospective Analysis for Research and Applications (MERRA), as well as two satellite-based datasets obtained by the Global Precipitation Climatology Centre (GPCP) and Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data (HOAPS) are evaluated. The evaluation is based on monthly precipitation in the tropical Pacific Ocean during the time period 1989–2005. Rain-gauge atoll station data provided by the Pacific Rainfall Database (PACRAIN) are used as ground-based reference. ...

Evaluating Satellite-Based Diurnal Cycles of Precipitation in the African Tropics

AbstractPrecipitation plays a major role in the energy and water cycles of the earth. Because of its variable nature, consistent observations of global precipitation are challenging. Satellite-based precipitation datasets present an alternative to in situ–based datasets in areas sparsely covered by ground stations. These datasets are a unique tool for model evaluations, but the value of satellite-based precipitation datasets depends on their application and scale. Numerous validation studies considered monthly or daily time scales, while less attention is given to subdaily scales. In this study subdaily satellite-based rainfall data are analyzed in West Africa, a region with strong diurnal variability. Several satellite-based precipitation datasets are validated, including Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA), TRMM 3G68 products, Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks (PERSIANN), and Climate Prediction C...