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Regional precipitation recycling is the measure of the contribution of local evaporation E to local precipitation. This study provides a set of two methods developed in the Weather Research and Forecasting WRF model system for investigating regional precipitation recycling mechanisms: (1) tracking of tagged atmospheric water species originating from evaporation in a source region, ie E-tagging, and (2) three-dimensional budgets of total and tagged atmospheric water species. These methods are used to quantify the effect of return flow and nonwell vertical mixing neglected in the computation of the bulk precipitation recycling ratio. The developed algorithms are applied to a WRF simulation of the West African Monsoon 2003. The simulated region is characterized by vertical wind shear condition, i.e., southwesterlies in the low levels and easterlies in the mid-levels, which favors return flow and nonwell vertical mixing. Regional precipitation recycling is investigated in 100 3 100 and 1000 3 1000 km 2 areas. A prerequisite condition for evaporated water to contribute to the precipitation process in both areas is that it is lifted to the mid-levels where hydrometeors are produced. In the 100 3 100 (1000 3 1000) km 2 area the bulk precipitation recycling ratio is 0.9 (7.3) %. Our budget analysis reveals that return flow and nonwell vertically mixed outflow increase this value by about 10.2 (2.9) and 10.2 (1.6) %, respectively, thus strengthening the well-known scale-dependency of regional precipitation recycling.

[1] In this study, high-resolution climate change data from the regional climate models COSMO-CLM, HIRHAM, RegCM, and REMO were evaluated in the Greater Alpine Region (GAR; 4°W-19°W and 43°N-49°N) and three additional subareas of 1.5°by 1°i n size. Evaluation statistics include mean temperature and precipitation, frequency of days with precipitation over 1 mm and over 15 mm, 90% quantile of the frequency distribution, and maximum number of consecutive dry days. The evaluation for the period indicates that the models reproduce spatial precipitation patterns and the annual cycle. The mean precipitation domain bias varies between 11% and 40% in winter season and between À14.5% and 11% in summer. Larger errors are found for other statistics and in the various regions. No single best model could be identified comparing modeled precipitation characteristics with observational reference. The study shows that there is still high uncertainty in the expected climate change. Furthermore, future temperature and precipitation changes simulated with different SRES scenarios and calculated by different RCMs overlap. The temperature calculations for the period 2071-2100 related to the period 1961-1990 in the GAR area show an increase in the monthly mean 2m temperature of up to 4.8 K in summer. In the GAR area, a precipitation decrease of up to 29% in summer and precipitation increase of approximately 20% in the winter season is simulated. Summer and autumn temperatures are expected to increase more than winter and spring temperatures. Detailed analysis reveals that the different regional climate model runs based on different regional models, different driving global models and different emission scenarios show similar trends, but differ in the magnitude of the expected climate change signal. All models seem to agree on the increased frequency of high-precipitation events in the winter season.Citation: Smiatek, G., H. Kunstmann, R. Knoche, and A. Marx (2009), Precipitation and temperature statistics in high-resolution regional climate models: Evaluation for the European Alps,

[1] In this study we investigated possible feedbacks of predicted future climate change on forest soil NO and N 2 O emissions in Europe. For this we used two climate scenarios, one representing a 10-year period of present-day climate (1991)(1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000) and a 9-year period for future climate conditions (2031)(2032)(2033)(2034)(2035)(2036)(2037)(2038)(2039). The climate scenarios were used to drive the GIS-coupled biogeochemical model Photosynthesis-Evapotranspiration-ModelDenitrification-Decomposition-Model (PnET-N-DNDC), which has currently been tested for its predicting capability for soil N trace gas emissions for various sites across Europe. The model results show a complex, spatially differentiated pattern of changes in future N 2 O and NO emissions from the forest soils across Europe, which were driven by the combined effect of changes in precipitation and temperature. Overall, the model predicted that N 2 O emissions from the European forest soils will on average decrease by 6%. This decrease was mainly due to the shift in N 2 O:N 2 ratio driven by enhanced denitrification. NO emissions were found to increase by 9%. The increases in NO emissions were mainly due to increases in temperature. Only for the regions where soil moisture was predicted to markedly increase or suffer from water stress during the vegetation period, a reduction of NO emissions was simulated. The simulations show the possibility and feasibility for assessing climate change feedbacks on biogenic N trace gas emissions from soils at a regional scale.

[1] In order to investigate possible effects of global climate change on the near-surface concentrations of photochemical compounds in southern Germany, nested regional simulations with a coupled climate-chemistry model were carried out. The simulations with a horizontal resolution of 60 km for Europe and 20 km for central Europe were driven by meteorological boundary conditions provided by a long-term simulation of the global climate model ECHAM4. Two time slices of about 10 years were compared, one representing the 1990s and one representing the 2030s. For the region of southern Germany the simulations show an increase of the mean summer temperature by almost 2°along with a decrease of cloud water and ice and a corresponding increase of the photolysis frequencies and the emissions of biogenic hydrocarbons. Under the model assumption of unchanged anthropogenic emissions this leads to an increase of the mean mixing ratios of most photooxidants. Because of the complex topography and the heterogeneous distribution of precursor emissions all parameters show pronounced regional patterns. The average daily maximum ozone concentrations in southern Germany increase for the considered scenario by nearly 10% in the summer months. Depending on the region, the increase of the mean daily maximum ranges between 2 and 6 ppb. As a consequence, the number of days when the 8-hour mean of the ozone concentration exceeds the threshold value of 120 mg m À3 increases by 5 to 12 days per year.Citation: Forkel, R., and R. Knoche (2006), Regional climate change and its impact on photooxidant concentrations in southern Germany: Simulations with a coupled regional climate-chemistry model,