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In this study we investigate the scaling of precipitation extremes with temperature in the Mediterranean region by assessing against observations the present day and future regional climate simulations performed in the frame of the HyMeX and MED-CORDEX programs. Over the 1979–2008 period, despite differences in quantitative precipitation simulation across the various models, the change in precipitation extremes with respect to temperature is robust and consistent. The spatial variability of the temperature–precipitation extremes relationship displays a hook shape across the Mediterranean, with negative slope at high temperatures and a slope following Clausius–Clapeyron (CC)-scaling at low temperatures. The temperature at which the slope of the temperature–precipitation extreme relation sharply changes (or temperature break), ranges from about 20 °C in the western Mediterranean to <10 °C in Greece. In addition, this slope is always negative in the arid regions of the Mediterranean. The scaling of the simulated precipitation extremes is insensitive to ocean–atmosphere coupling, while it depends very weakly on the resolution at high temperatures for short precipitation accumulation times. In future climate scenario simulations covering the 2070–2100 period, the temperature break shifts to higher temperatures by a value which is on average the mean regional temperature change due to global warming. The slope of the simulated future temperature–precipitation extremes relationship is close to CC-scaling at temperatures below the temperature break, while at high temperatures, the negative slope is close, but somewhat flatter or steeper, than in the current climate depending on the model. Overall, models predict more intense precipitation extremes in the future. Adjusting the temperature–precipitation extremes relationship in the present climate using the CC law and the temperature shift in the future allows the recovery of the temperature–precipitation extremes relationship in the future climate. This implies negligible regional changes of relative humidity in the future despite the large warming and drying over the Mediterranean. This suggests that the Mediterranean Sea is the primary source of moisture which counteracts the drying and warming impacts on relative humidity in parts of the Mediterranean region.
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.
Spatial interpolation of rain gauge data is important in forcing of hydrological simulations or evaluation of weather predictions, for example. The spatial density of available data sites is often changing with time. This paper investigates the application of statistical distance, like one minus common variance of time series, between data sites instead of geographical distance in interpolation. Here, as a typical representative of interpolation methods the inverse distance weighting interpolation is applied and the test data is daily precipitation observed in Austria. Choosing statistical distance instead of geographical distance in interpolation of an actually available coarse observation network yields more robust interpolation results at sites of a denser network with actually lacking observations. The performance enhancement is in or close to mountainous terrain. This has the potential to parsimoniously densify the currently available observation network. Additionally, the success further motivates search for conceptual rain-orography interaction models as components of spatial rain interpolation algorithms in mountainous terrain.
Influence of sea surface roughness length parameterization on Mistral and Tramontane simulations
(2016)
The Mistral and Tramontane are mesoscale winds in southern France and above the Western Mediterranean Sea. They are phenomena well suited for studying channeling effects as well as atmosphere–land/ocean processes. This sensitivity study deals with the influence of the sea surface roughness length parameterizations on simulated Mistral and Tramontane wind speed and wind direction. Several simulations with the regional climate model COSMO-CLM were performed for the year 2005 with varying values for the Charnock parameter α. Above the western Mediterranean area, the simulated wind speed and wind direction pattern on Mistral days changes depending on the parameterization used. Higher values of α lead to lower simulated wind speeds. In areas, where the simulated wind speed does not change much, a counterclockwise rotation of the simulated wind direction is observed.
Evaluation of radiation components in a global freshwater model with station-based observations
(2016)
In many hydrological models, the amount of evapotranspired water is calculated using the potential evapotranspiration (PET) approach. The main driver of several PET approaches is net radiation, whose downward components are usually obtained from meteorological input data, whereas the upward components are calculated by the model itself. Thus, uncertainties can be large due to both the input data and model assumptions. In this study, we compare the radiation components of the WaterGAP Global Hydrology Model, driven by two meteorological input datasets and two radiation setups from ERA-Interim reanalysis. We assess the performance with respect to monthly observations provided by the Baseline Surface Radiation Network (BSRN) and the Global Energy Balance Archive (GEBA). The assessment is done for the global land area and specifically for energy/water limited regions. The results indicate that there is no optimal radiation input throughout the model variants, but standard meteorological input datasets perform better than those directly obtained by ERA-Interim reanalysis for the key variable net radiation. The low number of observations for some radiation components, as well as the scale mismatch between station observations and 0.5° × 0.5° grid cell size, limits the assessment.
Projections from coarse-grid global circulation models are not suitable for regional estimates of water balance or trends of extreme precipitation and temperature, especially not in complex terrain. Thus, downscaling of global to regionally resolved projections is necessary to provide input to integrated water resources management approaches for river basins like the Upper Danube River Basin (UDRB) and the Upper Brahmaputra River Basin (UBRB).
This paper discusses the application of the regional climate model COSMO-CLM as a dynamical downscaling tool. To provide accurate data the COSMO-CLM model output was post-processed by statistical means. This downscaling chain performs well in the baseline period 1971 to 2000. However, COSMO-CLM performs better in the UDRB than in the UBRB because of a longer application experience and a less complex climate in Europe.
Different climate change scenarios were downscaled for the time period 1960–2100. The projections show an increase of temperature in both basins and for all seasons. The values are generally higher in the UBRB with the highest values occurring in the region of the Tibetan Plateau. Annual precipitation shows no substantial change. However, seasonal amounts show clear trends, for instance an increasing amount of spring precipitation in the UDRB. Again, the largest trends for different precipitation statistics are projected in the region of the Tibetan Plateau. Here, the projections show up to 50% longer dry periods in the months June to September with a simultaneous increase of about 10% for the maximum amount of precipitation on five consecutive days. For the Assam region in India, the projections also show an increase of 25% in the number of consecutive dry days during the monsoon season leading to prolonged monsoon breaks.
Recently, new soil data maps were developed, which include vertical soil properties like soil type. Implementing those into a multilayer Soil-Vegetation-Atmosphere-Transfer (SVAT) scheme, discontinuities in the water content occur at the interface between dissimilar soils. Therefore, care must be taken in solving the Richards equation for calculating vertical soil water fluxes. We solve a modified form of the mixed (soil water and soil matric potential based) Richards equation by subtracting the equilibrium state of soil matrix potential ψE from the hydraulic potential ψh. The sensitivity of the modified equation is tested under idealized conditions. The paper will show that the modified equation can handle with discontinuities in soil water content at the interface of layered soils.
Towards the goal to understand the role of land-surface processes over the Indian sub-continent, a series of soil-moisture sensitivity simulations have been performed using a non-hydrostatic regional climate model COSMO-CLM. The experiments were driven by the lateral boundary conditions provided by the ERA-Interim (ECMWF) reanalysis. The simulation results show that the pre-monsoonal soil moisture has a significant influence on the monsoonal precipitation. Both, positive and negative soil-moisture precipitation (S-P) feedback processes are of importance. The negative S-P feedback process is especially influential in the western and the northern parts of India.
Mistral and tramontane wind speed and wind direction patterns in regional climate simulations
(2016)
The Mistral and Tramontane are important wind phenomena that occur over southern France and the northwestern Mediterranean Sea. Both winds travel through constricting valleys before flowing out towards the Mediterranean Sea. The Mistral and Tramontane are thus interesting phenomena, and represent an opportunity to study channeling effects, as well as the interactions between the atmosphere and land/ocean surfaces. This study investigates Mistral and Tramontane simulations using five regional climate models with grid spacing of about 50 km and smaller. All simulations are driven by ERA-Interim reanalysis data. Spatial patterns of surface wind, as well as wind development and error propagation along the wind tracks from inland France to offshore during Mistral and Tramontane events, are presented and discussed. To disentangle the results from large-scale error sources in Mistral and Tramontane simulations, only days with well simulated large-scale sea level pressure field patterns are evaluated. Comparisons with the observations show that the large-scale pressure patterns are well simulated by the considered models, but the orographic modifications to the wind systems are not well simulated by the coarse-grid simulations (with a grid spacing of about 50 km), and are reproduced slightly better by the higher resolution simulations. On days with Mistral and/or Tramontane events, most simulations underestimate (by 13 % on average) the wind speed over the Mediterranean Sea. This effect is strongest at the lateral borders of the main flow—the flow width is underestimated. All simulations of this study show a clockwise wind direction bias over the sea during Mistral and Tramontane events. Simulations with smaller grid spacing show smaller biases than their coarse-grid counterparts.
Spatial interpolation of rain gauge data is important in forcing of hydrological simulations or evaluation of weather predictions, for example. This paper investigates the application of statistical distance, like one minus common variance of observation time series, between data sites instead of geographical distance in interpolation. Here, as a typical representative of interpolation methods the inverse distance weighting interpolation is applied and the test data is daily precipitation observed in Austria. Choosing statistical distance instead of geographical distance in interpolation of available coarse network observations to sites of a denser network, which is not reporting for the interpolation date, yields more robust interpolation results. The most distinct performance enhancement is in or close to mountainous terrain. Therefore, application of statistical distance in the inverse distance weighting interpolation or in similar methods can parsimoniously densify the currently available observation network. Additionally, the success further motivates search for conceptual rain-orography interaction models as components of spatial rain interpolation algorithms in mountainous terrain.