The Regional Atmospheric Water Budget over Southwestern Germany under Different Synoptic Conditions

Transcription

1 FEBRUARY 2013 S A S S E E T A L. 69 The Regional Atmospheric Water Budget over Southwestern Germany under Different Synoptic Conditions ROMI SASSE, GERD SCHÄDLER, AND CHRISTOPH KOTTMEIER Institute of Meteorology and Climate Research, KIT Karlsruhe, Eggenstein-Leopoldshafen, Germany (Manuscript received 24 August 2011, in final form 14 August 2012) ABSTRACT Thisstudyaddressesthequestionofhowcomplextopographyinalow-mountainregionaffectsthe partitioning and the variability of the atmospheric water budget components (WBCs) as a function of synoptic-scale flow conditions. The WBCs are calculated for regions of different size and location in southwestern Germany and the summer months from 2005 to 2009 using the high-resolution regional climate model COSMO-CLM driven by Global Model (GME) analyses. Comparisons with observations from the Convective and Orographically-induced Precipitation Study (COPS) performed in summer 2007 show that the model is capable of simulating the atmospheric water budget reasonably (absolute mean error between 0.1 and 0.7 kg m 22 day 21 ). To investigate the influence of synoptic weather conditions, the daily WBCs are classified based on the inflow direction of the air masses and the cyclonality at 500 hpa. Using statistical tests, four groups out of the six synoptic conditions have significantly different distributions of the WBCs. This can be explained by differences in the air mass features and the influence of high/low pressure systems. The sensitivity of the modeled WBCs to topography and land cover is investigated by comparing a region in the flat upper Rhine Valley with one in the mountainous Black Forest/Swabian Jura. Compared to the Rhine Valley, increases of evapotranspiration (15% to 116%), precipitation (126% to 157%), and moisture convergence (124% to 193%) are noticeable in the lowmountain region. Local modifications of the synoptic-scale flow, thermally induced winds, and land use cause this intensification of the atmospheric water budget, especially on the windward slopes of the mountains. 1. Introduction The atmospheric water cycle is an important part of the climate system. To understand regional modifications and impacts of global climate change, knowledge about the atmospheric water budget and the contributions of its components is needed. These are the temporal change of the atmospheric water vapor content, horizontal moisture transport, precipitation, and evapotranspiration. Furthermore, quantitative knowledge of the variability of the components and of the influencing factors is required. From long-term changes of the frequency and spatial distributions of the water budget components (WBCs), conclusions can be drawn with regard to the water cycle in a changing climate. Corresponding author address: Romi Sasse, Institute of Meteorology and Climate Research (IMK-TRO), Karlsruhe Institute of Technology (KIT), Hermann-von-Helmholtz-Platz 1, Eggenstein-Leopoldshafen, Germany. romi.sasse@kit.edu Trenberth et al. (2003) stated that evaporation and the atmosphere s moisture-holding capacity rise in a warming climate and, as a result, low-level moisture convergence as well as precipitation intensities increase. Haerter et al. (2010) pointed out that changes in the precipitation intensities cannot simply be derived from temperature changes. Instead, changes in all processes leading to higher atmospheric moisture contents (evapotranspiration and horizontal water vapor transport) owing to global warming have to be taken into account. Depending on the spatial scale of the water budget studies available, that is mostly the global or the continental scale, the water transfer rates are found to vary largely. The WBCs of the global water cycle under present climate conditions already differ among various authors (e.g., Peixoto and Oort 1992; Trenberth et al. 2007). These uncertainties are even larger when going from the global to the regional scale because of the high variability due to orography, soil characteristics, vegetation, and synoptic conditions. Moreover, the quantification DOI: /JHM-D Ó 2013 American Meteorological Society

2 70 J O U R N A L O F H Y D R O M E T E O R O L O G Y VOLUME 14 of the global and the regional atmospheric water budget is aggravated by the lack of reliable data, especially on climatological time scales (e.g., Trenberth et al. 2007; Jin and Zangvil 2010). Reliable information about horizontal moisture transport and evapotranspiration is essential to determine their contribution to precipitation (e.g., Brubaker et al. 1993) and to identify the sources of water vapor leading to extreme precipitation (e.g., Sodemann et al. 2009). In particular, narrow bands, called atmospheric rivers, along which 90% of the moisture transport from the subtropics to the midlatitudes is concentrated (Zhu and Newell 1998), are decisive for the initiation of the most extreme winter floods in midlatitude regions (Lavers et al. 2011). Moreover, heavy precipitation resulting in floods and increased evapotranspiration causing droughts in the absence of precipitation are the focus of hydrological, agricultural, and water and risk management concerns (Trenberth et al. 2003). Adaptation and precaution measures require spatially and temporally integrated information about the WBCs in various regions (e.g., in large river catchments). Former studies investigated areas with sizes of approximately 10 5 km 2 and larger (e.g., Rasmusson 1968; Brubaker et al. 1993; Berbery and Rasmusson 1999; Draper and Mills 2008), which are difficult to downscale to water budgets for small river catchments and regions used for agriculture or forestry. For the realistic determination of the regional atmospheric water budget, high-resolution data are needed. In this context, regional model simulations are a powerful tool to quantify the complete atmospheric water budget at high spatial and temporal resolution. Up to now, the resolution of regional models used for water budget analyses has been in the range of approximately 50 km (Berbery and Rasmusson 1999) to 14 km (Sodemann et al. 2009). Feldmann et al. (2008) and Früh et al. (2010) studied the spatial distribution and the annual cycles of precipitation and its extremes using regional climate simulations with a resolution of 10 and 18 km, respectively. Using southwestern Germany a region characterized by complex topography and land use as an example, precipitation simulation is improved by an increased model resolution. However, to reflect small-scale processes like convection and valley winds, resolution still is too coarse. Based on the validation of the regional climate model [the Consortium for Small-Scale Modeling model in climate mode (COSMO-CLM)], Meissner et al. (2009) recommend its application at a horizontal resolution of less than 10 km to achieve a more realistic representation of the nearsurface temperature, precipitation amounts, and local as well as regional precipitation patterns. Model validation is necessary to verify whether the representation of the atmospheric WBCs is realistic. In general, measurement networks only offer low station densities so that the WBCs are not routinely known from observations. In contrast to this, field campaigns like the Convective and Orographically-induced Precipitation Study (COPS) operate with a higher number of stations for periods from a few months to one year [COPS Long Observation Period (LOP)] and, in particular, during intensive observation periods (IOPs) of a few days. COPS took place in southwestern Germany and eastern France from 1 June to 31 August 2007 (Kottmeier et al. 2008; Wulfmeyer et al. 2011). The main objective of this campaign was the investigation of processes causing convective precipitation over complex terrain and the improvement of quantitative precipitation forecasts (QPF). The database provided by COPS is thus useful for the validation of the modeled atmospheric water budget. The purpose of the present study is (i) to determine the WBCs for regions in southwestern Germany using high-resolution regional COSMO-CLM simulations and COPS observations and (ii) to improve the understanding of the variability of the atmospheric water budget. The following scientific questions are addressed: (i) Do the atmospheric water budgets under various synoptic conditions differ from each other in a statistically significant manner? (ii) Does the atmospheric water budget intensify (i.e., are there larger values of the WBCs) in lowmountain regions? The novelty of this model-based sensitivity study consists in combining the analysis of the partitioning of the atmospheric water budget with studies on its variability under different synoptic-scale flow conditions over complex terrain. 2. Model setup and observations a. Model configuration The model simulations are performed with the regional climate model COSMO-CLM. COSMO is the regional nonhydrostatic operational weather forecast model of the German Weather Service (DWD; Doms and Schättler 2002; Doms et al. 2005); COSMO-CLM refers to the COSMO simulations in the climate mode (Rockel et al. 2008). To produce the regional simulations, dynamical downscaling is applied. The highresolution data thus obtained are based on physically consistent processes and include climate system feedbacks (Fowler et al. 2007).

3 FEBRUARY 2013 S A S S E E T A L. 71 TABLE 1. Model setup used in the present study. Model version COSMO_4.8_clm7 Global model GME Horizontal resolution km Number of horizontal grid points Number of vertical layers 40 Time integration scheme Leapfrog Time step 40 s Parameterization of the grid-scale precipitation Two-category ice scheme (also cloud-ice scheme; Doms et al. 2005) Convection parameterization Tiedtke scheme (Tiedtke 1989) FIG. 1. Topography of the simulation area. The gray rectangle marks the COPS region. Global analysis data from the Global Model (GME; 40-km horizontal resolution, 40 vertical layers) of the DWD, which are available every three hours, are used as initial and boundary conditions for the regional model simulations. The lower boundary conditions are the turbulent surface fluxes which are parameterized based on a stability and roughness-length dependent flux formulation (Doms et al. 2005). This scheme in turn requires the surface temperature and surface specific humidity from the multilayer soil vegetation model TERRA-ML, which is coupled to COSMO-CLM and describes the various thermal and hydrological soil processes. The model domain covers large parts of Germany and the Alpine region (Fig. 1) and has a horizontal grid resolution of (approximately 7 km) with 40 vertical layers in terrain-following coordinates. The model level k 5 40 is about 10 m above the surface (k 5 39 at 34.4 m, k 5 38 at 68.8 m, etc.). The model setup (Table 1) is based on the suggestion by Meissner et al. (2009) in order to yield the best configuration for high-resolution COSMO-CLM simulations in southwestern Germany. For long-term statistical analyses of the variability of the atmospheric water budget, the model runs are conducted for the summer months (June, July, and August) of the years Since the COSMO-CLM simulations are performed for summer only, a spinup time of two weeks is used for every simulation (Knote et al. 2010). b. Observations made during the COPS field campaign To validate the modeled WBCs for southwestern Germany, observations of high spatial and temporal resolution from the COPS field campaign (Kottmeier et al. 2008; Wulfmeyer et al. 2011) are used. The following observations are of special interest (Table 2): TABLE 2. Observed meteorological variable, number of stations, and temporal resolution during COPS. The abbreviations used are as follows: global positioning system (GPS); global telecommunication system (GTS); Helmholtz Centre Potsdam, German Research Centre for Geosciences (GFZ); Satellite Positioning Service of the German State Survey (SAPOS); Institut National des Sciences de l Univers/Centre National de la Recherche Scientifique (INSU/CRNS); Ecole et Observatoire des Sciences de la Terre (EOST); Réseau GPS Permanent (RGP); Institut National de la Recherche Agronomique (INRA); Karlsruhe Institute of Technology (KIT); German Weather Service (DWD); Landesanstalt für Umwelt, Messungen und Naturschutz Baden-Württemberg (LUBW); and Ludwig-Maximilians-Universität (LMU). Observed variable Integrated water vapor content Latent heat flux Precipitation Derived quantity Temporal water vapor change Evapotranspiration Precipitation Measurement technique Ground-based GPS stations Eddy-covariance method Surface stations and GTS observations Number of stations in CV A Temporal resolution 15 min 1 min, 10 min 1 h, 24 h Data provider GFZ, SAPOS, INSU/CRNS, EOST, RGP, and INRA KIT, University of Bayreuth, and Météo France DWD, LUBW, KIT, University of Bayreuth, University of Innsbruck, LMU Munich, University of Vienna, and University of Leeds

4 72 J O U R N A L O F H Y D R O M E T E O R O L O G Y VOLUME 14 FIG. 2. Scheme of the atmospheric water transport. View of the Rhine Valley from northwest. Horizontal moisture transport into/ out of the CV (Q y ), evapotranspiration (E y ), and precipitation (P). (i) integrated water vapor content derived from groundbased measurements using the global positioning system (GPS) (Dick et al. 2001; Bender et al. 2008), (ii) precipitation surface measurements, and (iii) the observation of evapotranspiration using latent heat flux measurements at energy balance stations (Eigenmann et al. 2011). The latent heat flux data have been obtained by means of the eddy-covariance method. For the horizontal moisture transport, observations are not available and, thus, the validation of the modeled WBCs for summer 2007 is limited to the temporal water vapor change, precipitation, and evapotranspiration. Since only half of the energy balance stations provide continuous data series for June 2007, the comparison of the observed and modeled evapotranspiration time series is confined to the period from 1 July to 31 August Methods a. Calculation of the atmospheric water budget components The WBCs are determined for a control volume (CV) comprising the different regions of interest. The convergence of the moisture flux 2$ Q y (shortly called moisture convergence or convergence), evapotranspiration E y, and precipitation P are the main processes changing the water vapor content W y in a CV (Fig. 2). The temporal moisture change is described by the water vapor budget equation (Peixoto and Oort 1992): W y t 52$ Q y 1 E y 1 P. (1) Positive values of the WBCs indicate an increase of water vapor in the CV, whereas negative values denote a decrease. Precipitation leads to a loss of atmospheric FIG. 3. CVs chosen for different analyses (section 3b) in southwestern Germany. moisture and, therefore, its values have a negative sign. Calculating the volume-averaged WBCs reduces spatial displacement errors and allows for an appropriate characterization of the regional water budget. The WBCs are determined from both model simulations and observations as daily rates in units of kg m 22 day 21 in order to study the impact of synoptic conditions, which have a representative time scale of one to several days (Kraus 2004), on the atmospheric water budget. Before integrating the observations at the earth s surface over the CV, the local station data are spatially interpolated onto a regular grid using the geostatistical method of kriging (Krige 1951). Within this method, the value at a location x 0 is estimated by taking all observations at the stations x i (1 # i # n where n is the total number of stations) into account. The distances between x 0 and x i are considered as well. The interpolation of the precipitation data is practicable because of the high-density observation network (Fig. 3). Although the GPS network is less extended, the atmospheric moisture field is assumed to be more homogeneous in comparison to precipitation and, thus, the interpolation of the observed water vapor change is feasible from the available station data. However, kriging is not performed on the evapotranspiration observations since the number of energy balance stations is too low to obtain accurate interpolation results. Furthermore, the model output is available on a longitude latitude grid and no interpolation has to be applied.

5 FEBRUARY 2013 S A S S E E T A L. 73 TABLE 3. Regional characteristics of the CVs A, B, and C. The land use statistics are taken from the ECOCLIMAP dataset (Masson et al. 2003). The WBCs are modeled mean values for the summer period Regional characteristics A B C Mean elevation (m) Standard deviation of elevation (m) Total forest cover (%) Deciduous forest cover (%) Evergreen forest cover (%) Mixed forest cover (%) Arable land and pasture cover (%) Others (e.g., urban land) (%) $ Q y (kg m 22 day 21 ) E y (kg m 22 day 21 ) P (kg m 22 day 21 ) je y /Pj ( ) FIG. 4. Daily water vapor change rates from 1 Jun to 31 Aug 2007 for CV A. Solid gray lines 5 observations; black dashed lines 5 simulations. b. Investigation areas The chosen CVs A, B, and C are shown in Fig. 3. The modeled water vapor change and precipitation are validated for CV A (approximately 10 4 km 2 ), to take advantage of as many GPS and precipitation stations as possible. Because of the low number of energy balance stations, the observed and modeled evapotranspiration rates are compared at the stations only. Furthermore, CV A is used to study the influence of synoptic conditions on the water budget. Synoptic-scale systems, such as high and low pressure systems, have minimum cross sections of approximately 200 km (Kraus 2004). To identify the effect of single high or low pressure systems, the horizontal extent of the CV should not exceed approximately 200 km. This prerequisite is met by CV A. The impact of the topography and land cover is investigated by comparing two CVs with different terrain structures: CV B (approximately 10 3 km 2 ) in the upper Rhine Valley is characterized by flat terrain with heights lower than 300 m above sea level. CV C (approximately 10 3 km 2 ) is located in the low-mountain region of the Black Forest and Swabian Jura and, thus, represents orographically structured terrain over 600 m. All CVs extend over 10 km in the vertical direction. Their regional characteristics are listed in Table 3. a. Model validation Over the summer period, the temporal variation of the modeled daily WBCs is rather synchronous to the observations (Figs. 4 6), but W y / t and P are generally overestimated (Figs. 4 and 5) whereas E y is often underestimated by COSMO-CLM (Fig. 6). For W y / t, the agreement between the observations and simulations is very good as indicated by the Pearson correlation coefficient of 0.9. Its value is reduced to 0.73 for P and is about 0.65 in case of E y. Furthermore, the absolute mean deviations amount to 0.1 kg m 22 day 21 for W y / t, 0.5 kg m 22 day 21 for P, and 0.7 kg m 22 day 21 for E y. However, the daily deviations, in particular for precipitation, can be much larger (e.g., on 21 June 2007 with the precipitation simulations exceeding the observations by 19.9 kg m 22 day 21 ). The total precipitation amount in summer 2007 is 329 kg m 22 in the simulations and 282 kg m 22 in the observations (i.e., the 4. Results Before investigating how the atmospheric water budget responds to different synoptic conditions, topography, and land cover in COSMO-CLM, the modeled WBCs are validated against the COPS observations to assess the accuracy of the model results. FIG. 5. As in Fig. 4, but for daily precipitation rates.

6 74 J O U R N A L O F H Y D R O M E T E O R O L O G Y VOLUME 14 FIG. 6. Station mean of daily evapotranspiration rates from 1 Jul to 31 Aug Formatting is as in Fig. 4. modeled precipitation exceeds the observations by 17%). In COSMO-CLM, the overestimated precipitation intensities are often connected to an underestimation of the evapotranspiration [e.g., on 9 July and 16 August 2007 (Figs. 5 and 6)], since low-level moisture gradients and temperatures may be too low. Moreover, the modeled evapotranspiration rates are higher than the observations after rainfall (e.g., from 13 to 16 July and 4 to 6 August 2007), indicating that the interactions between the WBCs are simulated correctly. To detect local differences between the modeled and observed WBCs, the simulations and observations of W y / t and E y are compared against each other at COPS stations (Fig. 7a). Because of the high station density within the precipitation observation network, the modeled and observed precipitation distributions are compared using the gridded datasets (Fig. 7b). Few GPS stations (circles in Fig. 7a) in the southwestern part of CV A including the eastern Vosges, the Rhine Valley, and the western Black Forest show an overestimation of the modeled water vapor change. In comparison to the other GPS stations in CV A, maximum errors occur here. This coincides with the region where the precipitation overestimation by COSMO-CLM is a maximum in comparison to the observations (Fig. 7b). Furthermore, major underestimation of the modeled evapotranspiration can be found here (triangles in Fig. 7a). However, most of the GPS stations in CV A indicate an underestimation of the water vapor change by COSMO-CLM (Fig. 7a), which is likely to be linked to the large areas of underestimated modeled precipitation (Fig. 7b). This in turn may be related to increased low-level moisture gradients and temperatures, followed by an overestimation of the modeled evapotranspiration as detected at two energy balance stations in the Black Forest (Fig. 7a). The differences between modeled and observed precipitation reflect the occasional problems associated with QPF in general, which motivated the COPS experiment (Kottmeier et al. 2008; Barthlott et al. 2010). In particular, the numerical simulation of convection and precipitation (i.e., location and timing) over complex terrain is challenging for state-of-the-art weather forecast and climate models, especially in summer, because of the small spatial scale and the fast temporal evolution of the associated processes. The uncertainties are mainly related to poor representation of boundary layer FIG. 7. Difference between simulations (Sim) and observation (Obs) of (a) the water vapor change and evapotranspiration at COPS stations (circle 5 GPS station; triangle 5 energy balance station), and (b) gridded precipitation in CV A for the summer months (JJA) Color scales in (a) and (b) represent mean deviation; numbers in (a) are standard deviation at GPS (red) and energy balance stations (green); gray contour lines and numbers in (b) are standard deviation.

7 FEBRUARY 2013 S A S S E E T A L. 75 TABLE 4. Relative number of days related to the weather classes and their subclasses (weather types) considered in this study. The separation is based on the objective weather type classification (Bissolli and Dittmann 2001). Weather class SW NW SE NE XXA XXZ Total number of days Anticyclonic flow at 950 hpa, anticyclonic flow at 500 hpa, dry air 10% 26% 5% 49% 29% Anticyclonic flow at 950 hpa, anticyclonic flow at 500 hpa, moist air 30% 20% 9% 5% 37% Anticyclonic flow at 950 hpa, cyclonic flow at 500 hpa, dry air 13% 42% 0% 19% 23% Anticyclonic flow at 950 hpa, cyclonic flow at 500 hpa, moist air 16% 10% 9% 14% 35% Cyclonic flow at 950 hpa, anticyclonic flow at 500 hpa, dry air 1% 0% 5% 0% 8% Cyclonic flow at 950 hpa, anticyclonic flow at 500 hpa, moist air 16% 0% 43% 5% 26% Cyclonic flow at 950 hpa, cyclonic flow at 500 hpa, dry air 3% 2% 0% 0% 23% Cyclonic flow at 950 hpa, cyclonic flow at 500 hpa, moist air 11% 0% 29% 8% 19% features such as small-scale inhomogenities in the relevant meteorological fields as well as the strength and lifting capabilities in convergence lines. However, mesoscale convergence lines and frontal zones are reproduced by the model, implying that regional moisture transports and precipitation are simulated properly under different synoptic-scale flow conditions. The deviations between modeled and observed evapotranspiration are in the range of known uncertainties (Jaeger et al. 2009) and are likely to be related to differences in the solar radiation and cloud cover as well as to different surface characteristics such as vegetation cover, land use, and local exposition. For instance, the energy balance stations at (48.58N, 7.58E) and (48.48N, 88E) are located in highly evapotranspirating maize fields (Eigenmann et al. 2011). This crop type is not considered specifically in COSMO-CLM and, thus, modeled evapotranspiration rates may be underestimated (Fig. 7a). The landscape heterogeneity is also assumed to be the main reason for uncertainties in the turbulent flux measurements (Eigenmann et al. 2011), which again lead to deviations between observed and modeled evapotranspiration. Although the local model performance may vary within the CVs, the WBCs respond to changes among each other and, thus, the interaction between the WBCs along with their temporal variation is reflected by the model. In addition, the model results are physically consistent, implying a very good closure of the atmospheric water budget (residuum below 0.5%). The modeled WBCs are thus used in the following sections in order to study the dependence of the atmospheric water budget on synoptic-scale flow conditions as well as topography and land cover. b. Atmospheric water budget under different synoptic-scale flow conditions Changes in the atmospheric water budget under global warming are, among other factors, likely to be associated with changes in the frequency and manifestation of synoptic-scale flow conditions and, thus, an improved understanding of how synoptic regimes control the WBCs is crucial. For this purpose, similar synoptic conditions are grouped together by means of the objective weather type classification (Bissolli and Dittmann 2001). 1) CLASSIFICATION OF THE SYNOPTIC CONDITIONS The objective weather type classification distinguishes 40 weather types based on the prevailing synoptic-scale flow direction, the humidity of air masses, and the cyclonality at 950 and 500 hpa. Since 1 July 1979, the weather types have been assigned to each calendar day on the basis of the operational numerical weather analysis and forecast system of the DWD for Germany and neighboring regions (Bissolli and Dittmann 2001). In the present study, the weather types are combined into six weather classes (Table 4) of similar type to increase the sample size of each class. It will be shown that distinctly different WBCs result for the classes that are defined in terms of the mean wind direction (SW, NW, SE, and NE). Additionally, days on which the inflow direction cannot be attributed clearly are distinguished based on the 500-hPa cyclonality. Hence, mid upper tropospheric high-pressure conditions with stagnant air masses (XXA) can be differentiated from mid upper tropospheric low-pressure conditions (XXZ). 2) SYNOPTIC MECHANISMS CONTROLLING THE WATER BUDGET COMPONENTS Each weather class shows characteristics concerning the air mass humidity and the occurrence of low and high pressure systems at 950 and 500 hpa (Table 4) that have the potential to influence the atmospheric water budget considerably. To investigate whether its partitioning differs between the weather classes, the synoptic mechanisms controlling the WBCs are discussed based on the probability and cumulative distributions of 2$ Q y, E y,andp for CV A (Fig. 8).

8 76 J O U R N A L O F H Y D R O M E T E O R O L O G Y VOLUME 14 FIG. 8. (left) Probability distributions (PDF) and (right) cumulative distributions (CDF) of (a),(b) the convergence of the moisture flux, (c),(d) evapotranspiration, and (e),(f) precipitation for each weather class related to CV A and the summer months (JJA) from 2005 to 2009.

9 FEBRUARY 2013 S A S S E E T A L. 77 The 500-hPa cyclonality indicates whether troughs or ridges are present in the mid upper troposphere, which are of major importance for the large-scale cloud distribution, stratification, and mean vertical motion of air masses (Kottmeier et al. 2008). In relation to the position of near-surface pressure systems and the air mass characteristics (temperature and humidity), the WBCs respond to the following synoptic processes: (i) XXZ, SE, and SW flow conditions are mainly related to warm and moist air masses and, moreover, low pressure systems at the surface are most likely to occur along with 500-hPa troughs (Table 4). The associated positive vorticity advection generates convergent moisture fluxes (Kottmeier et al. 2008), with probabilities in the range of 45% 60% (Fig. 8b). The consequent lifting-induced condensation of water vapor leads to high precipitation probabilities between 70% and 80% (Fig. 8f). The maximum precipitation probability is present under XXZ conditions and is related to the most frequent occurrence of near-surface low pressure systems in comparison to the classes SE and SW (Table 4). However, because of the high frequency of convergence rates between 15 and 20 kg m 22 day 21 in the class SE (Fig. 8a), the probability of absolute precipitation intensities exceeding 12 kg m 22 day 21 is higher particularly in comparison to XXZ conditions (Fig. 8e). This may be even more pronounced since moist air masses are more likely under SE conditions than under XXZ conditions (Table 4). Furthermore, the near-surface moisture convergence causes the low-level moisture gradient to decrease under XXZ, SE, and SW conditions, which is followed by declined evapotranspiration intensities. Low evapotranspiration rates (,2 kgm 22 day 21 ) are encountered most likely with a probability of 60% in the class XXZ (Fig. 8d), which is again associated with the frequent occurrence of low pressure systems at 950 hpa (Table 4). Evapotranspiration rates below 1 kg m 22 day 21 are most frequent for SE conditions (10% probability; Fig. 8d) since the probability of high convergence rates between 15 and 20 kg m 22 day 21 reaches a maximum under this synoptic regime (Fig. 8a). (ii) NE, XXA, and NW conditions are generally related to the inflow of cold and dry air masses and the occurrence of near-surface high pressure systems in connection with ridges at 500 hpa (Table 4). Because of the associated negative vorticity advection, these synoptic regimes cause air masses to subside and moisture fluxes to diverge (Kottmeier et al. 2008) with probabilities up to 70% (Fig. 8b). These mechanisms are followed by clear sky conditions and, thus, decreasing precipitation potential (40% 50% probability; Fig. 8f). However, the precipitation probabilities under NW conditions are even lower than under NE and XXA conditions. This is linked to the more frequent occurrence of nearsurface high pressure systems (Table 4) in comparison to the classes NE and XXA. Along with the predominance of dry air masses (Table 4), absolute precipitation rates below 1 kg m 22 day 21 are most likely under NW conditions (Fig. 8e). Furthermore, the prevailing divergent moisture flux under NE, XXA, and NW conditions leads to an enhanced lowlevel moisture gradient and, thus, to increased evapotranspiration. Evapotranspiration intensities lower than 1 kg m 22 day 21 occur with a probability of approximately 2% only (Fig. 8d). In general, the progression of the 500-hPa troughs and ridges leads to the day-to-day variability in the synoptic conditions (Kottmeier et al. 2008) and, thus, in the atmospheric water budget. This variability is largest for SW conditions since the subclasses appear at similar frequencies in contrast to the other weather classes (Table 4). Consequently, occurrence and intensity of convergence and divergence may differ from those of the other classes and, thus, the WBCs in particular 2$ Q y (Fig. 8a) show a large variability in the probability distributions. These results suggest that the atmospheric water budgets differ between the weather classes when taking into account the probability distributions of 2$ Q y, E y, and P, respectively. The water budget under XXZ, SE, and SW conditions is likely to be distinguishable from that under NE, XXA, and NW conditions. Moreover, the probability distributions of the WBCs indicate differences between the classes XXZ, SE, and SW, respectively. The water budget under NW conditions may also differ considerably from that under NE and XXA conditions, whereas for the classes NE and XXA, the distributions of the WBCs do not show any evident differences. 3) ATMOSPHERIC WATER BUDGET FOR DIFFERENT WEATHER CLASSES The differences between the probability distributions of the WBCs seen from Fig. 8 are tested for statistical significance. For consistency reasons, the same tests are used for all WBCs namely, the Wilcoxon signed-rank test and the Kolmogorov Smirnov test (Wilks 2006). Both tests do not need any assumption about the theoretical distribution of the WBCs. Their underlying null hypothesis states that two datasets have the same

10 78 J O U R N A L O F H Y D R O M E T E O R O L O G Y VOLUME 14 mass characteristics (temperature and humidity) and the impact of high and low pressure systems. c. Impact of topography and land cover on the atmospheric water budget Besides synoptic-scale flow conditions, surface inhomogenities related to topography and land cover are of decisive importance for the atmospheric water budget. Hence, the question of how terrain affects the modeled WBCs for the various weather classes is discussed in the following. FIG. 9. Grouping of the typical atmospheric WBCs with respect to the six weather classes. The results are based on the Wilcoxon signed-rank test and the Kolmogorov Smirnov test as well as probability distributions (Fig. 8). distribution function. The objective of the tests is to confirm or to reject this null hypothesis at the 95% significance level. The hypothesis test applied to differences among the precipitation distributions of the weather classes (Fig. 9a) separates the classes with high precipitation contributions (SE, XXZ, and SW) from those with low precipitation intensities (NE, XXA, and NW). Regarding the evapotranspiration distributions (Fig. 9b), only weather class XXZ differs from the classes SE and SW in a statistically significant manner. The check of the differences among the distributions of 2$ Q y reveals deviations between the classes XXA and NW (Fig. 9c). Between the distributions of the classes NE and NW as well as of NE and XXA, no differences can be seen from the test results. Since the mean value of the convergence distribution is negative for NW conditions (Fig. 8a), the class NW can be separated from NE and XXA, while the classes NE and XXA cannot be distinguished. When considering all WBCs, the atmospheric water budgets can therefore be divided into four groups (Fig. 9): (i) XXZ conditions with high precipitation and low evapotranspiration, (ii) SE and SW conditions with high precipitation and higher evapotranspiration than under XXZ conditions, (iii) NE and XXA conditions with low precipitation, and (iv) NW conditions with low precipitation and a dominance of divergence compared to convergence. Although not all weather classes can be distinguished based on the probability distributions of the WBCs, it is evident that the synoptic conditions affect the atmospheric water budget considerably because of the air 1) SPATIAL DISTRIBUTION OF THE WATER BUDGET COMPONENTS IN SOUTHWESTERN GERMANY Regional factors, such as the topography and land cover, apparently influence the spatial distribution of the WBCs (Fig. 10). On the average, convergent moisture fluxes (Fig. 10a) prevail in the western Black Forest, the northwestern Swabian Jura, and in the eastern Vosges. Moreover, the western Black Forest is characterized by large areas with maximum intensities of precipitation and evapotranspiration, which are larger than those of the Swabian Jura and the Rhine Valley (Figs. 10b and 10c). However, the moisture convergence pattern (Fig. 10a) is much more heterogeneous than the precipitation field (Fig. 10b). Although the occurrence of low-level moisture convergence (not shown here) favors rainfall (section 4b), the initiation of convection and precipitation is also controlled by other factors such as orography, surface heating, spatial inhomogeneities of land use, and soil water content, as well as atmospheric stratification and stability (Kottmeier et al. 2008). Moisture divergence dominates over the mountain ridges as well as on the eastern and southeastern slopes of the mountains (Fig. 10a). In the Rhine Valley, divergence predominates together with minimum precipitation and evapotranspiration (Figs. 10b and 10c). The absolute precipitation and evapotranspiration rates are in general higher over most parts of the lowmountain region compared to the Rhine Valley. The increase of evapotranspiration in the northwestern Black Forest is also supported by the available COPS observations (Fig. 10c). In addition, the orographic enhancement of precipitation is confirmed by the observational data collected during COPS (Fig. 7b). Since the intensities of precipitation, evapotranspiration, and convergence are larger in the Black Forest and the Swabian Jura than in the Rhine Valley, we conclude that the atmospheric water budget is intensified in the low-mountain region. However, W y / t differs only slightly between regions C and D, since the other WBCs may cancel each other. This means that the water

11 FEBRUARY 2013 S A S S E E T A L. 79 FIG. 10. Spatial distribution of the mean (a) convergence of moisture flux, (b) precipitation, and (c) evapotranspiration for the summer months (JJA) from 2005 to The rectangles mark the positions of CV B (blue) and CV C (red). Triangles in (c) represent mean observed evapotranspiration for summer transfer rates due to moisture convergence, precipitation, and evapotranspiration are different between the two CVs but their sums, reflected in W y / t [Eq. (1)], are about the same. 2) OROGRAPHIC INTENSIFICATION OF THE WATER BUDGET COMPONENTS OF THE LOW-MOUNTAIN REGION COMPARED TO THE FLAT REGION The mean WBCs are determined for the CVs B (flat terrain) and C (orographically structured terrain; Fig. 3, Table 3) in order to investigate the hypothesized intensification over mountainous terrain for the six weather classes (section 4b). Figure 11 illustrates the mean relative change of the WBCs between the CVs C and B. Positive values indicate increases of evapotranspiration, absolute precipitation, and convergent moisture fluxes in the low-mountain region compared to the Rhine Valley and vice versa. The relative differences of evapotranspiration (Fig. 11a) and precipitation (Fig. 11b) are determined directly via their contributions in units of kg m 22 day 21. However, for the calculation of the relative differences of convergence (Fig. 11c), the normalized convergence 2$ Q y /E y is used. Since the convergence in kg m 22 day 21 shows positive and negative values (Fig. 8a), its mean may be close to zero and does not represent this FIG. 11. Means of the relative difference of (a) evapotranspiration, (b) precipitation, and (c) normalized convergence [section 4c(2)] between CV C and CV B for the summer months (JJA) from 2005 to Positive values indicate increases of evapotranspiration, absolute precipitation, and convergent moisture fluxes in region C compared to region B and vice versa.

12 80 J O U R N A L O F H Y D R O M E T E O R O L O G Y VOLUME 14 variability. Evapotranspiration is suitable for the normalization because of its positive values and its low variability in comparison to the other WBCs (Figs. 8 and 10). The first condition (i.e., positive values) implies that the sign of the ratio 2$ Q y /E y does not change and the information about whether convergence or divergence occurs is still captured. The second condition (i.e., low variability) means that the evapotranspiration rarely approaches zero, in contrast to, for example, precipitation. For all weather classes, evapotranspiration is 15% to 116% larger in the low-mountain region [i.e., increase between 0.1 and 0.4 kg m 22 day 21 ; Fig. 11a] and, except for SW conditions, the precipitation difference is in the range of 126% to 157% (i.e., between 0.4 and 3.6 kg m 22 day 21 ; Fig. 11b). In contrast to this, SW conditions show a decrease of the absolute precipitation intensities by 210% in CV C, which corresponds to 0.3 kg m 22 day 21. The relative increase of evapotranspiration is generally lower than that of precipitation. Runoff, soil water storage, and, in general, the damping effect of the soil and vegetation reduce the amount of evaporated water in comparison to precipitation. As a consequence, evapotranspiration is less variable. Except for the classes SW and NW, the normalized convergence increases between 124% and 193% in CV C. A relative change of nearly 100% implies that moisture convergence increases almost as much as evapotranspiration. Under SW conditions, convergence dominates in CV B, whereas divergence prevails in CV C. The relative increase of the divergent moisture fluxes is 1226% on the average. For the class NW, divergence predominates in CVs B and C, but its normalized contribution is 164% larger in the region of the Black Forest and Swabian Jura. Consequently, the comparison of the CVs B and C reveals an enhancement of all WBCs and, therefore, the intensification of the atmospheric water budget in the low-mountain region except under SW and NW conditions. 3) REASONS OF OROGRAPHIC INTENSIFICATION To understand the larger WBCs in the mountainous region compared to the Rhine Valley, several reasons have to be considered: (i) The synoptic-scale moisture transport toward the mountains is followed by moisture convergence and orographic uplift, which may cause water vapor to precipitate on the windward mountain slopes. In general, the absolute precipitation intensity is highest before the maximum elevation is reached. Behind the mountains crests, the intensities are reduced, but orographically induced precipitation still may occur (Kunz 2003). Since southwest is the main inflow direction during the investigation period (Table 4), convergence and, thus, precipitation with maximum intensities predominate on the western slope of the Black Forest (Figs. 10a and 10b). As a consequence, the intensification of the water budget can be associated with sloping terrain. (ii) Besides the synoptic-scale flow, thermally induced small-scale wind systems are present over orographically structured terrain because of enhanced insolation and heating on the mountain slopes. Convergence occurs and may cause convection as well as cloud formation over the mountain ridges under weak synoptic-scale forcing (Raymond and Wilkening 1980; Barthlott et al. 2006; Kottmeier et al. 2008). Weak synoptic-scale forcing was related to one-third of the IOPs during COPS, but two-thirds of the IOPs were associated with convection under midtropospheric forcing (Kottmeier et al. 2008; Barthlott et al. 2010; Corsmeier et al. 2011). Consequently, both synoptic-scale flow and local wind systems are important to the development of moisture convergence and precipitation. With respect to this study, weak synoptic-scale forcing is more relevant under XXA and XXZ conditions, whereas both synoptic-scale flow and thermally induced wind systems play an important role in the classes SW, NW, SE, and NE. (iii) Relevant factors causing the enhancement of evapotranspiration in the low-mountain region compared to the Rhine Valley (Figs. 10c and 11a) are stronger heating of the mountain slopes and higher wind velocities due to the dynamically and thermally induced wind systems. In addition, vegetation and land use are of major importance for evapotranspiration (Lawrence et al. 2007). In comparison to the Rhine Valley, the percentage of forest cover is higher by 33% in the low-mountain region, in particular due to 37% more evergreen forest (Table 3), which contributes considerably to the enhancement of evapotranspiration. The mean annual transpiration rates of deciduous and evergreen forests exceed those of arable land and pasture (Brechtel and Hammes 1985) which are the dominating land uses in the Rhine Valley (Table 3). For the orographic enhancement of convergence and precipitation, the processes related to the interaction between synoptic-scale inflow and orography are of major importance. Hence, the associated intensification of the atmospheric water budget occurs particularly at

13 FEBRUARY 2013 S A S S E E T A L. 81 FIG. 12. Spatial distribution of the mean precipitation for the weather classes (a) SW and (b) NW in the summer months (JJA) from 2005 to The rectangles mark the positions of CV B (blue) and CV C (red). the windward slopes of the mountains. This is also evident under SW and NW conditions, although the comparison between the CVs C and D indicates decreasing convergence and precipitation in the low-mountain region (Figs. 11b and 11c). While SW flow conditions cause maximum precipitation intensities to occur on the windward western slope of the Black Forest (Fig. 12a), minimum precipitation and divergence prevail on the lee side (Kunz 2003), where CV C is located. For the weather class NW, accordingly, the absence of enhanced convergent moisture flux in CV C, although precipitation increases (Figs. 11b and 11c), can be explained by its position on the lee side. First, the mean relative precipitation increase by 126% in CV C, as seen from the model results, is small compared to the other weather classes (Fig. 11b). Second, absolute precipitation intensities are clearly reduced under NW conditions (Fig. 12b) in comparison to Fig. 10b. The lowest absolute precipitation rates can be found in the Rhine Valley, while maximum precipitation occurs on the windward western side of the Black Forest. Thus, in the eastern Black Forest and southwestern Swabian Jura (lee side), divergence and low absolute precipitation rates (,1.5 kg/(m 2 d)) dominate. However, a part of the windward slope of the Black Forest, where absolute precipitation intensities up to 4 kg/(m 2 d) occur, is covered by CV C and causes precipitation to increase in comparison to CV B (Fig. 11b). The intensification of evapotranspiration, however, does not necessarily depend on the increase of convergence and precipitation (Fig. 11a). Factors like a higher forest cover, stronger insolation, and the consequent heating of the slopes as well as the increased wind velocities in the low-mountain region are likely to be more important to evapotranspiration. However, an intensified water transport via convergence and precipitation as evident under SE, NE, XXA, and XXZ conditions (Figs. 11b and 11c) increases the water amount available on the land surface. The water can thus be transferred back into the atmosphere via evapotranspiration as long as the water-holding capacity of the soil is adequate. 5. Summary and conclusions In this study, we used the regional climate model COSMO-CLM to quantify the atmospheric water budget for regions of different size and location in southwestern Germany and investigated how the partitioning and the variability of the WBCs depends on synopticscale flow conditions, topography, and land cover. For this purpose, high-resolution simulations were

14 82 J O U R N A L O F H Y D R O M E T E O R O L O G Y VOLUME 14 performed for the summer months [June August (JJA)] from 2005 to 2009 and, thus, the daily contributions of water vapor change, moisture convergence, precipitation, and evapotranspiration were calculated for CVs with areas of about 10 3 to 10 4 km 2. The WBCs observed at GPS stations (Dick et al. 2001; Bender et al. 2008), precipitation gauges, and energy balance stations during the COPS field campaign in summer 2007 were used to verify the suitability of COSMO-CLM results for regional water budget studies. Model validation shows good agreements between the modeled and observed WBCs (absolute mean error between 0.1 and 0.7 kg m 22 day 21 ). Particularly, the temporal variation of moisture change, precipitation, and evapotranspiration is represented well in the model. However, water vapor change rates and precipitation intensities are overestimated in COSMO-CLM. In connection with precipitation events, modeled evapotranspiration is mainly underestimated, whereas evapotranspiration rates are higher than observed intensities during the dry days following rainfall. In view of the low number of stations and the uncertainties in the observational datasets, in particular for evapotranspiration, the application of the observations for comprehensive model validation and water budget studies is difficult. In comparison, the COSMO-CLM simulations provide consistent and high-resolution data for the detailed analysis of the regional water budget. Moreover, the interaction among the WBCs is reproduced and the model is capable of simulating their variability under different synoptic conditions over complex terrain in a satisfactory way. We therefore conclude that relative changes of the WBCs between different CVs can be assessed from the model results. Synoptic-scale flow conditions have a considerable impact on the atmospheric water budget, as was shown for the CV comprising the upper Rhine Valley and the northern Black Forest. Based on the inflow directions, and the 500-hPa cyclonality in case of nondefined inflows (Bissolli and Dittmann 2001), the daily WBCs are grouped into six weather classes. Comparison of the probability distributions of the WBCs indicates significant differences among the six weather classes. Using the Wilcoxon signed-rank test as well as the Kolmogorov Smirnov test (Wilks 2006) and in consideration of all WBCs, four significantly different groups can be distinguished: (i) low-pressure conditions with nondefined inflow direction (XXZ), (ii) conditions with southwesterly (SW) and southeasterly (SE) inflow, (iii) conditions with northeasterly inflow (NE) and high-pressure conditions with weak winds (XXA), and (iv) conditions with northwesterly inflow (NW). These synoptic-scale flow conditions control (i) the air mass temperature and humidity as well as (ii) the lifting and subsidence of the air masses due to the occurrence of low- and highpressure conditions at the surface and in the mid upper troposphere and, thus, affect the partitioning of the atmospheric water budget. The comparison of the modeled WBCs between the upper Rhine Valley and the low-mountain region of the Black Forest and the Swabian Jura shows that atmospheric water transport is intensified in the lowmountain region. This intensification exists under different synoptic conditions and is most pronounced on the windward slopes of the mountains. However, the intensity of the increase of the WBCs over complex terrain is influenced by the synoptic regime and the interaction between synoptic-scale flow and orography. For the CV in the southeastern Black Forest and the southwestern Swabian Jura, evapotranspiration is enhanced by 15 to116% compared to the CV in the upper Rhine Valley. This corresponds to an increase between 0.1 and 0.4 kg m 22 day 21. Precipitation enhancement is in the range of 126 to 157% (except under SW conditions) [i.e., between 0.4 and 3.6 kg m 22 day 21 ] and normalized convergence is about 124% to 193% higher (except under SW and NW conditions). A nearly 100% increase indicates that convergence intensifies almost to the same extent as evapotranspiration. Under SW and NW conditions, the increase of convergence and partly precipitation is not evident for the chosen CV because of its location on the lee side. The intensification of the atmospheric water budget over complex terrain is caused by (i) the synoptic-scale flow and the forced lifting of air masses at mountains; (ii) thermally induced wind systems initiating convection, cloud formation, and precipitation; and (iii) forest cover. The importance of (ii) increases under weak synoptic-scale forcing. In addition, the enhancement of evapotranspiration, regardless of synoptic conditions, highlights the importance of land use for the water budget in the low-mountain region. All factors (i), (ii), and (iii) are affected by orography-related features like the exposition of mountain slopes, soil features, local climatological characteristics (altitudinal vegetation zone), and land use. We have thus shown that the atmospheric water budget intensifies in low-mountain regions under presence of synoptic-scale and thermal forcing unless forest cover is the predominant land use. Depending on the size of the CV located in mountainous terrain and the position of the orographic structures with respect to the main flow direction, the relative changes of the WBCs may differ from the ones given here. The methods and results presented in this study provide a basis for further model-based analyses of the water budget. The findings documented in this article