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This paper assesses the resolution dependance of clouds and precipitation over Germany by numerical simulations with the COnsortium for Small-scale MOdeling (COSMO) model. Six intensive observation periods of the HOPE (HD(CP)2 Observational Prototype Experiment) measurement campaign conducted in spring 2013 and 1 summer day of the same year are simulated. By means of a series of grid-refinement resolution tests (horizontal grid spacing 2.8, 1 km, 500, and 250 m), the applicability of the COSMO model to represent real weather events in the gray zone, i.e., the scale ranging between the mesoscale limit (no turbulence resolved) and the large-eddy simulation limit (energy-containing turbulence resolved), is tested. To the authors' knowledge, this paper presents the first non-idealized COSMO simulations in the peer-reviewed literature at the 250-500m scale. It is found that the kinetic energy spectra derived from model output show the expected -5/3 slope, as well as a dependency on model resolution, and that the effective resolution lies between 6 and 7 times the nominal resolution. Although the representation of a number of processes is enhanced with resolution (e.g., boundary-layer thermals, low-level convergence zones, gravity waves), their influence on the temporal evolution of precipitation is rather weak. However, rain intensities vary with resolution, leading to differences in the total rain amount of up to +48 %. Furthermore, the location of rain is similar for the springtime cases with moderate and strong synoptic forcing, whereas significant differences are obtained for the summertime case with air mass convection. Domain-averaged liquid water paths and cloud condensate profiles are used to analyze the temporal and spatial variability of the simulated clouds. Finally, probability density functions of convection-related parameters are analyzed to investigate their dependance on model resolution and their impact on cloud formation and subsequent precipitation. [ABSTRACT FROM AUTHOR]

In this paper bioaerosol measurements conducted with the Waveband Integrated Bioaerosol Sensor mark 4 (WIBS-4) are presented. The measurements comprise aerosol chamber characterization experiments and a one-year ambient measurement period at a semi-rural site in South Western Germany. This study aims to investigate the sensitivity of WIBS-4 to biological and non-biological aerosols and detection of biological particles in the ambient aerosol. Several types of biological and non-biological aerosol samples, including fungal spores, bacteria, mineral dust, ammonium sulphate, combustion soot, and fluorescent polystyrene spheres, were analyzed by WIBS-4 in the laboratory. The results confirm the sensitivity of the ultraviolet light-induced fluorescence (UV-LIF) method to biological fluorophores and show the good discrimination capabilities of the two excitation wavelengths/detection wavebands method applied in WIBS-4. However, a weak cross-sensitivity to non-biological fluorescent interferers remains and is discussed in this paper. All the laboratory studies have been undertaken in order to prepare WIBS-4 for ambient aerosol measurements. According to the one-year ambient aerosol study, number concentration of fluorescent biological aerosol particles (FBAP) show strong seasonal and diurnal variability. The highest number concentration of FBAP was measured during the summer term and decreased towards the winter period when colder and drier conditions prevail. Diurnal FBAP concentrations start to increase after sunset and reach maximum values during the late night and early morning hours. On the other hand, the total aerosol number concentration was almost always higher during daytime than during nighttime and a sharp decrease after sunset was observed. There was no correlation observed between the FBAP concentration and the meteorological parameters temperature, precipitation, wind direction and wind speed. However, a clear correlation was identified between the FBAP number concentration and the relative humidity. Humidity-controlled release mechanisms of some fungal spore species are discussed as a possible explanation. [ABSTRACT FROM AUTHOR]

The summer flood of 2013 set a new record for large-scale floods in Germany for at least the last 60 years. In this paper we analyse the key hydro-meteorological factors using extreme value statistics as well as aggregated severity indices. For the long-term classification of the recent flood we draw comparisons to a set of past large-scale flood events in Germany, notably the high-impact summer floods from August 2002 and July 1954. Our analysis shows that the combination of extreme initial wetness at the national scale-caused by a pronounced precipitation anomaly in the month of May 2013-and strong, but not extraordinary event precipitation were the key drivers for this exceptional flood event. This provides additional insights into the importance of catchment wetness for high return period floods on a large scale. The database compiled and the methodological developments provide a consistent framework for the rapid evaluation of future floods. [ABSTRACT FROM AUTHOR]

Multi-wavelength lidar measurements in the melting layer revealing the presence of dark and bright bands have been performed by the University of BASILicata Raman lidar system (BASIL) during a stratiform rain event. Simultaneously radar measurements have been also performed from the same site by the University of Hamburg cloud radar MIRA 36 (35.5 GHz), the University of Hamburg dualpolarization micro rain radar (24.15 GHz) and the University of Manchester UHF wind profiler (1.29 GHz). Measurements from BASIL and the radars are illustrated and discussed in this paper for a specific case study on 23 July 2007 during the Convective and Orographically-induced Precipitation Study (COPS). Simulations of the lidar dark and bright band based on the application of concentric/eccentric sphere Lorentz-Mie codes and a melting layer model are also provided. Lidar and radar measurements and model results are also compared with measurements from a disdrometer on ground and a two-dimensional cloud (2DC) probe onboard the ATR42 SAFIRE. Measurements and model results are found to confirm and support the conceptual microphysical/ scattering model elaborated by Sassen et al. (2005). [ABSTRACT FROM AUTHOR]

This paper describes an innovative project which has just been launched at the "Laboratoire de Météorologie Physique" (LaMP) in Clermont-Ferrand in collaboration with the "Meteorologische Institut" in Hamburg, where a low cost X-band high resolution precipitation radar is combined with supporting measurements and a bin microphysical cloud resolving model in order to develop adapted Z-R relationships for accurate rain rate estimates over a local area such as a small catchment basin, an urban complex or even an agriculture domain. In particular, the use of K-band micro rain radars which can retrieve vertical profiles of drop size distribution and the associated reflectivity will be used to perform direct comparisons with X-band radar volume samples while a network of rain-gauges provides ground truth to which our rain estimates will be compared. Thus, the experimental suite of instrumentation should provide a detailed characterization of the various rain regimes and their associated Z-R relationship. Furthermore, we will make use of the hilly environment of the radar to test the use of novel attenuation methods in order to estimate rainfall rates. A second important aspect of this work is to use the detailed cloud modeling available at LaMP. Simulations of precipitating clouds in highly resolved 3-D dynamics model allow predicting the spectra of rain drops and precipitating ice particles. Radar reflectivity determined from these model studies will be compared with the observations in order to better understand which raindrop size spectrum shape factor should be applied to the radar algorithms as a function of the type of precipitating cloud. Likewise, these comparisons between the modeled and the observed reflectivity will also give us the opportunity to further improve our model microphysics and the parameterizations for meso-scale models. [ABSTRACT FROM AUTHOR]

This paper presents a hydrometeorological reconstruction of the flood triggering meteorological situation and the simulation of discharges of the flood event of December 1882 in the Neckar catchment in Baden-Württemberg (southwest Germany). The course of the 1882 flood event in the Neckar catchment in southwest Germany and the weather conditions which led to this flood were reconstructed by evaluating the information from various historical sources. From these historical data, daily input data sets were derived for run-off modeling. For the determination of the precipitation pattern at the end of December 1882, the sparse historical data were modified by using a similar modern day precipitation pattern with a higher station density. The results of this run-off simulation are compared with contemporary historical data and also with 1-D hydraulic simulations using the HEC-RAS model. [ABSTRACT FROM AUTHOR]

This paper deals with a two-year study of karst soils and eolian dust deposition on the Reiteralpe paleosurface (1600 to 2000 m), Northern Calcareous Alps, Germany. Thirty soil profiles of Cambisols developed on Triassic and Cretaceous limestones are investigated. Dust samples collected periodically on snow cover provide influx rates and a seasonal dust record. Samples of soils, insoluble bedrock residue, and dust are characterized by pedological (e.g. grain size) and mineralogical (e.g. heavy minerals) data. The data indicate that limestone subtypes with varying crack-fillings (ferrous clays) determine the colors and amounts of residue. Both correlate positively with the thickness of reddish Bo-horizons, supporting their autochthonous character. The topsoils, however, show substantial eolian addition (silt, fine sand, mica). In winter, far-traveled red Saharan dust without organic material prevails, carried to the area by strong foehn winds. In early springtime, browner dust (organic rich) is observed which contains periglacial silicate-rich detritus from regional sources such as the Crystalline Austrian Alps. The measured winter dust influx rates are 4.8 cm per 10,000 years (related to 210 winter days). This is more than twice the calculated thickness of Holocene residue accumulation out of limestone weathering (2.3 cm per 10,000 years, related to 210 winter days), which indicates that eolian dust is a major contributor to alpine karst soil development. [ABSTRACT FROM AUTHOR]

The attenuation of a radar signal is a serious problem facing meteorologists and hydrologists. In heavy rain, reflectivity information can be completely lost from large portions of a radar scan. The problem is particularly acute for X-band radars. Current methods of correcting for attenuation face many difficulties, mainly because the actual amount of attenuation at any given time is unknown. In this paper a backward-iterative attenuation-correction algorithm is presented that uses the attenuation measured by a microwave link with its receiver collocated with an X-band weather radar in Essen, Germany. Data are also available from a network of rain gauges located in the vicinity of the link path. This network provides a measure of “ground truth” rainfall against which radar estimates can be compared. The results show that the algorithm can recover much of the reflectivity information that is lost due to attenuation of the radar beam. The method is seen to be particularly effective in convective conditions where heavy rainfall can cause severe attenuation. [ABSTRACT FROM AUTHOR]

The drought of 2018 in central and northern Europe showed once more the large impact that this natural hazard can have on the environment and society. Such droughts are often seen as slowly developing phenomena. However, root zone soil moisture deficits can rapidly develop during periods lacking precipitation and meteorological conditions that favor high evapotranspiration rates. These periods of soil moisture stress can persist for as long as the meteorological drought conditions last, thereby negatively affecting vegetation and crop health. In this study, we aim to characterize past soil moisture stress events over the croplands of southwestern Germany and, furthermore, to relate the characteristics of these past events to different soil and climate properties. We first simulated daily soil moisture over the period 1989–2018 on a 1 km resolution grid, using the physically based hydrological model TRAIN. We then derived various soil moisture stress characteristics, including probability, development time, and persistence, from the simulated time series of all agricultural grid cells (n≈15000). Logistic regression and correlation were then applied to relate the derived characteristics to the plant-available storage capacity of the root zone and to the climatological setting. Finally, sensitivity analyses were carried out to investigate how results changed when using a different parameterization of the root zone, i.e., soil based or fixed, or when assessing soil moisture drought (anomaly) instead of stress. Results reveal that the majority of agricultural grid cells across the study region reached soil moisture stress during prominent drought years. The development time of these soil moisture stress events varied substantially, from as little as 10 d to over 4 months. The persistence of soil moisture stress varied as well and was especially high for the drought of 2018. A strong control on the probability and development time of soil moisture stress was found to be the storage capacity of the root zone, whereas the persistence was not strongly linearly related to any of the considered controls. On the other hand, the sensitivity analyses revealed the increased control of climate on soil moisture stress characteristics when using a fixed instead of a soil-based root zone storage. Thus, the strength of different controls depends on the assumptions made during modeling. Nonetheless, the storage capacity of the root zone, whether it is a characteristic of the soil or a difference between a shallow or deep rooting crop, remains an important control on soil moisture stress characteristics. This is different for SM drought characteristics, which have little or contrasting relation with the storage capacity of the root zone. Overall, the results give insight to the large spatial and temporal variability in soil moisture stress characteristics and suggest the importance of considering differences in root zone soil storage for agricultural drought assessments. [ABSTRACT FROM AUTHOR]

We use sophisticated machine-learning techniques on a network of summer temperature and precipitation time series taken from stations throughout Germany for the years from 1960 to 2018. In particular, we consider (normalized) maximized mutual information as the measure of similarity and expand on recent clustering methods for climate modeling by applying a weighted kernel-based k-means algorithm. We find robust regional clusters that are both time invariant and shared by networks defined separately by precipitation and temperature time series. Finally, we use the resulting clusters to create a nonstationary model of regional summer temperature extremes throughout Germany and are thereby able to quantify the increase in the probability of observing high extreme summer temperature values (> 35 °C) compared with the last 30 years. [ABSTRACT FROM AUTHOR]

Estimates of present and future extreme sub-hourly rainfall are derived from a daily spatial followed by a sub-daily temporal downscaling, the latter of which incorporates a novel, and crucial, temperature sensitivity. Specifically, daily global climate fields are spatially downscaled to local temperature T and precipitation P, which are then disaggregated to a temporal resolution of 10 min using a multiplicative random cascade model. The scheme is calibrated and validated with a group of 21 station records of 10-min resolution in Germany. The cascade model is used in the classical (denoted as MC) and in the new T-sensitive (MC+) version, which respects local Clausius–Clapeyron (CC) effects such as CC scaling. Extreme P is positively biased in both MC versions. Observed T sensitivity is absent in MC but well reproduced by MC+. Long-term positive trends in extreme sub-hourly P are generally more pronounced and more significant in MC+ than in MC. In units of 10-min rainfall, observed centennial trends in annual exceedance counts (EC) of P > 5 mm are +29% and in 3-yr return levels (RL) +27%. For the RCP4.5-simulated future, higher extremes are projected in both versions MC and MC+: per century, EC increases by 30% for MC and by 83% for MC+; the RL rises by 14% for MC and by 33% for MC+. Because the projected daily P trends are negligible, the sub-daily signal is mainly driven by local temperature. [ABSTRACT FROM AUTHOR]

The predictability of deep moist convection depends on many factors, such as the synoptic-scale flow, the geographical region (i.e., the presence of mountains), and land surface–atmosphere as well as aerosol–cloud interactions. This study addresses all these factors by investigating the relative impact of orography, soil moisture, and aerosols on precipitation over Germany in different weather regimes. To this end, we conduct numerical sensitivity studies with the COnsortium for Small-sale MOdelling (COSMO) model at high spatial resolution (500 m grid spacing) for 6 days with weak and strong synoptic forcing. The numerical experiments consist of (i) successive smoothing of topographical features, (ii) systematic changes in the initial soil moisture fields (spatially homogeneous increase/decrease, horizontal uniform soil moisture, different realizations of dry/wet patches), and (iii) different assumptions about the ambient aerosol concentration (spatially homogeneous and heterogeneous fields). Our results show that the impact of these perturbations on precipitation is on average higher for weak than for strong synoptic forcing. Soil moisture and aerosols are each responsible for the maximum precipitation response for three of the cases, while the sensitivity to terrain forcing always shows the smallest spread. For the majority of the analyzed cases, the model produces a positive soil moisture–precipitation feedback when averaged over the entire model domain. Furthermore, the amount of soil moisture affects precipitation more strongly than its spatial distribution. The precipitation response to changes in the CCN concentration is more complex and case dependent. The smoothing of terrain shows weaker impacts on days with strong synoptic forcing because surface fluxes are less important and orographic ascent is still simulated reasonably well, despite missing fine-scale orographic features. We apply an object-based characterization to identify whether and how the perturbations affect the structure, location, timing, and intensity of precipitation. These diagnostics reveal that the structure component, comparing the size and shape of precipitating objects to the reference simulation, is on average highest in the soil moisture and aerosol simulations, often due to changes in the maximum precipitation amounts. This indicates that the dominant mechanisms for convection initiation remain but that precipitation amounts depend on the strength of the trigger mechanisms. Location and amplitude parameters both vary over a much smaller range. Still, the temporal evolution of the amplitude component correlates well with the rain rate. Our results suggest that for quantitative precipitation forecasting, both aerosols and soil moisture are of similar importance and that their inclusion in convective-scale ensemble forecasting containing classical sources of uncertainty should be assessed in the future. [ABSTRACT FROM AUTHOR]

A reconstruction of hydroclimate with an annual resolution covering millennia for a geographically limited region in continental Europe significantly improves our knowledge of past climate dynamics. With the use of an extensive collection of oak ring-width series (Quercus robur and Quercus petraea) from living trees, historic timbers and subfossil alluvial wood deposits from the Main River region in southern Germany, a regional, 2000-year long, seasonally resolved hydroclimate reconstruction for the Main region has been developed. Climate-growth response analysis has been performed with daily climate records from AD 1900 onwards. To test the stability of the developed transfer function, a bootstrapped transfer function stability test (BTFS) as well as a classical calibration/verification approach have been implemented to study climate-growth model performance. Living oak trees from the Main River region show a significant sensitivity to the precipitation sum from 26 February to 6 July (spring to midsummer) during the full (r=0.49 , p<0.01 , N=116) and split (r=0.58 , p<0.01 , N=58) calibration periods. BTFS confirmed the stability of the developed transfer function. The developed precipitation reconstruction reveals high variability on a high- to mid-frequency scale during the past two millennia. Very dry spring to midsummer seasons lasting multiple years appeared in the decades AD 500/510s, 940s, 1170s, 1390s and 1160s. At the end of the AD 330s, a persistent multi-year drought with drastically reduced rainfall (with regard to 1901–2000) could be identified, which was the driest decade over the past 2000 years in this region. In the AD 550s, 1050s, 1310s and 1480s, multi-year periods with high rainfall hit the Main region. In spring to midsummer of AD 338, precipitation was reduced by ∼38 % and in AD 357 it increased by ∼39 %. The presented hydroclimate reconstruction and its comparison to other records reveal interesting insights into the hydroclimate dynamics of the geographically limited area over the Common Era, in addition to revealing noticeable temporal differences. [ABSTRACT FROM AUTHOR]

Regional climate model simulations have routinely been applied to assess changes in precipitation extremes at daily time steps. However, shorter sub-daily extremes have not received as much attention. This is likely because of the limited availability of high temporal resolution data, both for observations and for model outputs. Here, summertime depth duration frequencies of a subset of the EURO-CORDEX 0.11 ∘ ensemble are evaluated with observations for several European countries for durations of 1 to 12 h. Most of the model simulations strongly underestimate 10-year depths for durations up to a few hours but perform better at longer durations. The spatial patterns over Germany are reproduced at least partly at a 12 h duration, but all models fail at shorter durations. Projected changes are assessed by relating relative depth changes to mean temperature changes. A strong relationship with temperature is found across different subregions of Europe, emission scenarios and future time periods. However, the scaling varies considerably between different combinations of global and regional climate models, with a spread in scaling of around 1–10 % K -1 at a 12 h duration and generally higher values at shorter durations. [ABSTRACT FROM AUTHOR]

Changes in extreme precipitation due to climate change often require the application of methods to bias correct simulated atmospheric fields, including extremes. Most existing bias correction techniques (i) only focus on the bias in the mean value or on the extreme values separately, and (ii) exclude zero values from analysis, even though their presence is significant in daily precipitation. We developed a copula-based bias correction scheme that is suitable for zero-inflated daily precipitation data to correct the bias in mean as well as in extreme precipitation at any specific statistical quantile. In considering the whole of Germany as a test bed, the proposed scheme is found to work well across the entire study area, including the German Alpine regions. The joint distribution between observed and regional climate model (RCM)-derived precipitation is developed through copulas. In particular, the joint distribution is modified to make it discrete at zero in order to account for zero values. The benefit of considering zero precipitation values is revealed through the improved performance of bias correction both in the mean and extreme values. Second, the quantile that best captures the bias (whether in the mean or any extreme value) is determined for a specific location and varies spatially and seasonally. This relaxation in selecting the location-specific optimal quantile renders the proposed methodology spatially transferable. By acknowledging possible changes in extreme precipitation due to climate change, the proposed scheme is expected to be suitable for climate change impact assessments for extreme events worldwide. [ABSTRACT FROM AUTHOR]

The cumulative occurrence of heavy precipitation and flood events during recent years in various Central European locations emphasises the urgent need to improve extreme rainfall observations and forecasts. Precipitation gauges based on a weighing system allow the recording of intense short-term precipitation events with a very high temporal resolution (down to 1 min). In this study, observational data that were collected during the period 2000 to 2016 for 126 stations of two corresponding measuring networks in the Central German state of Hesse were investigated for the first time to answer the following questions: (1) Are the recorded high-resolution precipitation data plausible and comparable between both networks? (2) Which atmospheric circulation patterns were specifically prone to produce short-term intense precipitation events? Although the two networks are equipped with the same measuring technology, systematic differences concerning their maximum 1 min precipitation amounts occur, which may be explained by different instrumental software settings. We could minimise those discrepancies by accumulating the existing 1 min data to 15 min. Subsequently, the 15 min daily maximum values and accumulated daily sums were analysed regarding the impact of large-scale atmospheric circulation patterns, based on the well-known "Großwetterlagen" classification. We identified a clear connection between atmospheric circulation and heavy precipitation over Hesse, while indicating some differences between daily (24 h) and sub-daily (15 min) events. High daily precipitation sums often relate to westerlies and central cyclones, while intense short-term events are frequently generated by warm-humid continental air from southern and eastern Europe as well as trough conditions, where the trough's core is found west of the study area. Our results underline the importance of expanding and enhancing high-resolution precipitation observations in Germany as well as other countries. [ABSTRACT FROM AUTHOR]

The application of an ensemble reduction technique to the European branch of the World Climate Research Program Coordinated Regional Downscaling Experiment (EURO-CORDEX)ensemble at resolution ''EUR-11'' (~12.5 km) under the RCP8.5 scenario is presented. The technique is based on monthly mean changes between a reference and two future time periods, calculated for eight regions in Germany, of the parameters near-surface air temperature (tas), precipitation totals (pr), contribution of precipitation from very wet days to precipitation totals (R95pTOT), near-surface specific humidity (huss), and surface down-welling shortwave radiation (rsds). The sensitivity of the reduction procedure with respect to a number of tuning parameters is investigated. When the optimal combination of tuning parameters is applied, the technique allows the reduction from 15 to 7 ensemble members, while the reduced ensemble reproduces about 94% of the spread of the full ensemble. Keeping in mind that climate projection ensembles are expected to grow substantially in the near future, this ensemble reduction technique can be useful to limit the computational efforts necessary for further processing and applications such as impact modeling. [ABSTRACT FROM AUTHOR]

Variations of climate are a major cause of uncertainty in crop yields. This paper analyses the impacts of extreme weather events on wheat yields reported in the German Farm Accountancy Data Network (FADN). The FADN-sample has continuously encompassed about 11,500 farms each year since 1995/96. While the average of farm yields within a county correspond to the official average county yield, farm yields show higher annual fluctuations over time. In order to assess the impacts of extreme weather events on wheat yields, the farm data is spatially joined with data on local natural site conditions on the municipality level. Soil data such as the field capacity is taken from soil maps and altitude above sea level from digital terrain maps. The variables are averaged over the arable land in the municipalities using GIS. Meteorological data observed at weather observation stations of the German Weather Service such as temperature (minimum, average, maximum), precipitation, and potential evaporation are interpolated on a 1x1 km grid and aggregated to municipalities. Various indicators reflecting extreme weather events such as the number of days with extreme frost, freeze-thaw cycles, drought and heat during the vegetation period and enduring rain and wet soil at harvest are derived on the basis of the soil and daily weather data. Multivariate regression analyses are applied for clustered homogenous soil-climate-regions to elicit the impacts of defined extreme climate events on wheat yields. First results reflect the regionally different exposure to extreme weather events in Germany. While farmers in the northern regions suffered rather from enduring rain and soil moisture at harvest, drought caused major problems on sandy soils in the eastern regions. Of course, due to the focus on weather extremes, a substantial part of weather-induced yield fluctuation remains unexplained. Nevertheless, the results provide valuable information regarding risk management for farms. [ABSTRACT FROM AUTHOR]

Climate signal maps can be used to identify regions where robust climate changes can be derived from an ensemble of climate change simulations. Here, robustness is defined as a combination of model agreement and the significance of the individual model projections. Climate signal maps do not show all information available from the model ensemble, but give a condensed view in order to be useful for non-climate scientists who have to assess climate change impact during the course of their work. Three different ensembles of regional climate projections have been analyzed regarding changes of seasonal mean and extreme precipitation (defined as the number of days exceeding the 95th percentile threshold of daily precipitation) for Germany, using climate signal maps. Although the models used and the scenario assumptions differ for the three ensembles (representative concentration pathway (RCP) 4.5 vs. RCP8.5 vs. A1B), some similarities in the projections of future seasonal and extreme precipitation can be seen. For the winter season, both mean and extreme precipitation are projected to increase. The strength, robustness and regional pattern of this increase, however, depends on the ensemble. For summer, a robust decrease of mean precipitation can be detected only for small regions in southwestern Germany and only from two of the three ensembles, whereas none of them projects a robust increase of summer extreme precipitation. [ABSTRACT FROM AUTHOR]

Soil microbial communities play an important role in forest ecosystem functioning, but how climate change will affect the community composition and consequently bacterial functions is poorly understood. We assessed the effects of reduced precipitation with the aim of simulating realistic future drought conditions for one growing season on the bacterial community and its relation to soil properties and forest management. We manipulated precipitation in beech and conifer forest plots managed at different levels of intensity in three different regions across Germany. The precipitation reduction decreased soil water content across the growing season by between 2 to 8% depending on plot and region. T-RFLP analysis and pyrosequencing of the 16S rRNA gene were used to study the total soil bacterial community and its active members after six months of precipitation reduction. The effect of reduced precipitation on the total bacterial community structure was negligible while significant effects could be observed for the active bacteria. However, the effect was secondary to the stronger influence of specific soil characteristics across the three regions and management selection of overstorey tree species and their respective understorey vegetation. The impact of reduced precipitation differed between the studied plots; however, we could not determine the particular parameters being able to modify the response of the active bacterial community among plots. We conclude that the moderate drought induced by the precipitation manipulation treatment started to affect the active but not the total bacterial community, which points to an adequate resistance of the soil microbial system over one growing season. [ABSTRACT FROM AUTHOR]

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This study addresses the problem of combining radar information and gauge measurements. Gauge measurements are the best available source of absolute rainfall intensity albeit their spatial availability is limited. Precipitation information obtained by radar mimics well the spatial patterns but is biased for their absolute values. In this study copula models are used to describe the dependence structure between gauge observations and rainfall derived from radar reflectivity at the corresponding grid cells. After appropriate time series transformation to generate "iid" variates, only the positive pairs (radar > 0, gauge > 0) of the residuals are considered. As not each grid cell can be assigned to one gauge, the integration of point information, i.e. gauge rainfall intensities, is achieved by considering the structure and the strength of dependence between the radar pixels and all the gauges within the radar image. Two different approaches, namely Maximum Theta and Multiple Theta, are presented. They finally allow for generating precipitation fields that mimic the spatial patterns of the radar fields and correct them for biases in their absolute rainfall intensities. The performance of the approach, which can be seen as a bias-correction for radar fields, is demonstrated for the Bavarian Alps. The bias-corrected rainfall fields are compared to a field of interpolated gauge values (ordinary kriging) and are validated with available gauge measurements. The simulated precipitation fields are compared to an operationally corrected radar precipitation field (RADOLAN). The copula-based approach performs similarly well as indicated by different validation measures and successfully corrects for errors in the radar precipitation. [ABSTRACT FROM AUTHOR]

Possible aerosol-cloud-precipitation effects over Germany are investigated using the COSMO model in a convection-permitting configuration close to the operational COSMO-DE. Aerosol effects on clouds and precipitation are modeled by using an advanced two-moment microphysical parameterization taking into account aerosol assumptions for cloud condensation nuclei (CCN) as well as ice nuclei (IN). Simulations of three summer seasons have been performed with various aerosol assumptions, and are analysed regarding surface precipitation, cloud properties, and the indirect aerosol effect on near-surface temperature. We find that the CCN and IN assumptions have a strong effect on cloud properties, like condensate amounts of cloud water, snow and rain as well as on the glaciation of the clouds, but the effects on surface precipitation are -- when averaged over space and time -- small. This robustness can only be understood by the combined action of microphysical and dynamical processes. On one hand, this shows that clouds can be interpreted as a buffered system where significant changes to environmental parameters, like aerosols, have little effect on the resulting surface precipitation. On the other hand, this buffering is not active for the radiative effects of clouds, and the changes in cloud properties due to aerosol perturbations may have a significant effect on radiation and near-surface temperature. [ABSTRACT FROM AUTHOR]

Empirical frequency distributions of multiplicative cascade weights, or breakdown coefficients, at small timescales are analyzed for 5-min precipitation time series from four gauges in Germany. It is shown that histograms of the weights, W, are strongly deformed by the recording precision of rainfall amounts. A randomization procedure is proposed to statistically remove the artifacts due to precision errors in the original series. Evolution of the probability distributions of W from beta-like for large timescales to combined beta-normal distribution with a pronounced peak at W ≈ 0.5 for small timescales is observed. A new 3N-B distribution built from 3 separate normal, N, distributions and one beta, B, distribution is proposed for reproduction of the empirical histograms of W at small timescales. Parameters of the 3N-B distributions are fitted for all gauges and analyzed timescales. Microcanonical cascades models with a generator based on 3N-B distributions are developed and their performance at disaggregating precipitation at 1280-min intervals down to 5-min intervals is evaluated. [ABSTRACT FROM AUTHOR]

A transient shallow-convection scheme is implemented into the general circulation model ECHAM5 and the coupled aerosol model HAM, developed at the Max Planck Institute for Meteorology in Hamburg. The shallow-convection scheme is extended to take the ice phase into account. In addition, a detailed double-moment microphysics approach has been added. In this approach, the freezing processes and precipitation formation are dependent on aerosols. Furthermore, in the scheme, tracers are transported and scavenged consistently as in the rest of the model. Results of a single-column model simulation for the Barbados Oceanography and Meteorology Experiment (BOMEX) campaign are compared with previously published large-eddy simulation (LES) results. Compared to the standard version, the global ECHAM5-HAM simulations with the newly implemented scheme show a decreased frequency of shallow convection in better agreement with LES. Less shallow convection is compensated by more stratus and stratocumulus. Deep and especially midlevel convection are markedly affected by those changes, which in turn influence high-level clouds. Generally, a better agreement with the observations can be obtained. For a better understanding of the scheme''s impact and to test different setting parameters, sensitivity analyses are performed. The mixing properties, cloud-base vertical velocity, and launching layer of the test parcel, respectively, are varied. In this context, results from simulations without shallow convection are also presented. [ABSTRACT FROM AUTHOR]

Simulations of orographic precipitation over the low mountain ranges of southwestern Germany and eastern France with two different physics-based linear precipitation models are presented. Both models are based on 3D airflow dynamics from linear theory and consider advection of condensed water and leeside drying. Sensitivity studies for idealized conditions and a real case study show that the amount and spatial distribution of orographic precipitation is strongly controlled by characteristic time scales for cloud and hydrometeor advection and background precipitation due to large-scale lifting. These parameters are estimated by adjusting the model results on a 2.5-km grid to observed precipitation patterns for a sample of 40 representative orography-dominated stratiform events (24 h) during a calibration period (1971--80). In general, the best results in terms of lowest rmse and bias are obtained for characteristic time scales of 1600 s and background precipitation of 0.4 mm h−−1. Model simulations of a sample of 84 events during an application period (1981--2000) with fixed parameters demonstrate that both models are able to reproduce quantitatively precipitation patterns obtained from observations and reanalyses from a numerical model [[Consortium for Small-scale Modeling (COSMO)]]. Combining model results with observation data shows that heavy precipitations over mountains are restricted to situations with strong atmospheric forcings in terms of synoptic-scale lifting, horizontal wind speed, and moisture content. [ABSTRACT FROM AUTHOR]

Eddy-covariance and Sodar/RASS experimental measurement data of the COPS (Convective and Orographically-induced Precipitation Study) field campaign 2007 are used to investigate the generation of near-ground free convection conditions (FCCs) in the Kinzig valley, Black Forest, Southwest Germany. The measured high-quality turbulent flux data revealed that FCCs are initiated near the ground in situations where moderate to high buoyancy fluxes and a simultaneously occurring drop of the wind speed were present. The minimum in wind speed - observable by the Sodar measurements through the whole vertical extension of the valley atmosphere - is the consequence of a thermally-induced valley wind system, which changes its wind direction from down to up-valley winds in the morning hours. Buoyancy then dominates over shear within the production of turbulence kinetic energy near the ground. These situations are detected by the stability parameter (ratio of the measurement height to the Obukhov length) when the level of free convection, which starts above the Obukhov length, drops below that of the sonic anemometer. An analysis of the scales of turbulent motions during FCCs using wavelet transform shows the occurrence of large-scale turbulence structures. Regarding the entire COPS measurement period, FCCs in the morning hours occur on about 50% of all days. Enhanced surface fluxes of latent and sensible heat are found on these days. [ABSTRACT FROM AUTHOR]

A total of more than 140000 kg of small-magnitude rockfall deposits was measured in eight rockfall collectors of altogether 940 m2 in size between 1999-2003 below a 400-600m high rock face in the Reintal, German Alps. Measurements were conducted with a temporal resolution up to single days to attribute rockfall intensity to observed triggering events. Precipitation was assessed by a rain gauge and high-resolution precipitation radar. Intense rainstorms triggered previously unreported rockfall intensities of up to 300 000 g/(m2h) that we term "secondary rockfall event." In comparison to dry periods without frost (10-2g/(m2h)), rockfall deposition increased by 2-218 times during wet freeze-thaw cycles and by 56-thousand to 40-million times during secondary rockfall events. We obtained three nonlinear logistic growth models that relate rockfall intensity [g/(m2h)] to rainfall intensity [mm/h]. The models account for different rock wall intermediate storage volumes, triggering thresholds and storage depletion. They apply to all rockfall collector positions with correlations from R2=0.89 to 0.99. Thus, the timing of more than 90% of the encountered rockfall is explained by the triggering factor rainfall intensity. A combination of rockfall response models with radar-supported storm cell forecast could be used to anticipate hazardous rockfall events, and help to reduce the exposure of individuals and mobile structures (e.g. cable cars) to the hazard. According to meteorological recordings, the frequency of these intense rockfall events is likely to increase in response to global warming. [ABSTRACT FROM AUTHOR]

This study deals with a lysimetrical-meteorological data series collected on the large-scale lysimeter site "St. Arnold", Germany, from November 1965 to April 2007. The particular relevance of this data rests both upon its perdurability and upon the fact that the site is comprised of a grassland basin, an oak/beech and a pine basin. Apart from analyzing long term trends of the meteorological measurements, the primary objective of this study is to investigate the water balance in grassland and forested basins, in particular comparing the precipitation term to leachate quantities and potential and actual evapotranspiration. The latter are based upon the Penman and the Penman-Monteith approaches, respectively. The main results of this survey are that, on a long-term average, the grassland basin turns more than half (53%) of its annually incoming precipitation into leachate and only 36% into water vapour, while the deciduous forest exhibits a ratio of 37% for leachate and 56% for evapotranspiration, and the evergreen coniferous forest shows the highest evaporation rate (65%) and the lowest leachate rate (26%). Concerning these water balances, considerable differences both between basins and between seasons stand out. While summer periods exhibit high evapotranspiration rates for the forests and moderate ones for the grassland, winter periods are characterised by considerable leachate quantities for grassland and the deciduous forest and moderate ones for the coniferous forest. Following the analysis of the climatic development in St. Arnold, trends towards a milder and more humid regional climate were detected. [ABSTRACT FROM AUTHOR]

For derived flood frequency analysis based on hydrological modelling long continuous precipitation time series with high temporal resolution are needed. Often, the observation network with recording rainfall gauges is poor, especially regarding the limited length of the available rainfalltime series. Stochastic precipitation synthesis is a good alternative either to extend or to regionalise rainfall series to provide adequate input for long-term rainfall-runoff modelling with subsequent estimation of design floods. Here, a new two step procedure for stochastic synthesis of continuous hourly space-time rainfall is proposed and tested for the extension of short observed precipitation time series. First, a single-site alternating renewal model is presented to simulate independent hourly precipitation time series for several locations. The alternating renewal model describes wet spell durations, dry spell durations and wet spell intensities using univariate frequency distributions separately for two seasons. The dependence between wet spell intensity and duration is accounted for by 2-copulas. For disaggregation of the wet spells into hourly intensities a predefined profile is used. In the second step a multi-site resampling procedure is applied on the synthetic point rainfall event series to reproduce the spatial dependence structure of rainfall. Resampling is carried out successively on all synthetic event series using simulated annealing with an objective function considering three bivariate spatial rainfall characteristics. In a case study synthetic precipitation is generated for some locations with short observation records in two mesoscale catchments of the Bode river basin located in northern Germany. The synthetic rainfall data are then applied for derived flood frequency analysis using the hydrological model HECHMS. The results show good performance in reproducing average and extreme rainfall characteristics as well as in reproducing observed flood frequencies. The presented model has the potential to be used for ungauged locations through regionalisation of the model parameters. [ABSTRACT FROM AUTHOR]

The objective in this study is to investigate the influence of the spatial resolution of the rainfall input on the model calibration and application. The analysis is carried out by varying the distribution of the raingauge network. A meso-scale catchment located in southwest Germany has been selected for this study. First, the semi-distributed HBV model is calibrated with the precipitation interpolated from the available observed rainfall of the different raingauge networks. An automatic calibration method based on the combinatorial optimization algorithm simulated annealing is applied. The performance of the hydrological model is analyzed as a function of the raingauge density. Secondly, the calibrated model is validated using interpolated precipitation from the same raingauge density used for the calibration as well as interpolated precipitation based on networks of reduced and increased raingauge density. Lastly, the effect of missing rainfall data is investigated by using a multiple linear regression approach for filling in the missing measurements. The model, calibrated with the complete set of observed data, is then run in the validation period using the above described precipitation field. The simulated hydrographs obtained in the above described three sets of experiments are analyzed through the comparisons of the computed Nash-Sutcliffe coefficient and several goodness-of-fit indexes. The results show that the model using different raingauge networks might need re-calibration of the model parameters, specifically model calibrated on relatively sparse precipitation information might perform well on dense precipitation information while model calibrated on dense precipitation information fails on sparse precipitation information. Also, the model calibrated with the complete set of observed precipitation and run with incomplete observed data associated with the data estimated using multiple linear regressions, at the locations treated as missing measurements, performs well. [ABSTRACT FROM AUTHOR]

Based on the mean daily values of air temperature, air pressure, and precipitation totals at 13 climatological stations within the territory of the Czech Republic in the period 1961–2002, a statistical analysis of “meteorological singularities” (i.e., calendar-dependent deviations from the mean annual variation for selected meteorological elements) was performed. At the 13 stations analysed, a total of 45 meteorological singularities (37 singularities in air temperature, 35 in air pressure, and 30 in precipitation) were found. The singularities detected correlate well with cases traditionally recognised in the Czech Republic as well as with the results of analyses performed for Germany. Despite the considerable variability of singularities in time and space, most of them are found across the entire territory of the Czech Republic and can be observed for the most part in all three elements processed. The majority of the singularities detected may be explained on the basis of circulation mechanisms, by relating them to a significantly higher occurrence of certain groups of synoptic situations characterised by anomalous temperature or precipitation effects. Cases of “competition” between singularities, when different singularities may occur on the same calendar day, were found. [ABSTRACT FROM AUTHOR]

A dynamical downscaling scheme is usually used to provide a short range flood forecasting system with high-resolved precipitation fields. Unfortunately, a single forecast of this scheme has a high uncertainty concerning intensity and location especially during extreme events. Alternatively, statistical downscaling techniques like the analogue method can be used which can supply a probabilistic forecasts. However, the performance of the analogue method is affected by the similarity criterion, which is used to identify similar weather situations. To investigate this issue in this work, three different similarity measures are tested: the euclidean distance (1), the Pearson correlation (2) and a combination of both measures (3). The predictor variables are geopotential height at 1000 and 700 hPa-level and specific humidity fluxes at 700 hPa-level derived from the NCEP/NCAR-reanalysis project. The study is performed for three mesoscale catchments located in the Rhine basin in Germany. It is validated by a jackknife method for a period of 44 years (1958-2001). The ranked probability skill score, the Brier Skill score, the Heidke skill score and the confidence interval of the Cramer association coefficient are calculated to evaluate the system for extreme events. The results show that the combined similarity measure yields the best results in predicting extreme events. However, the confidence interval of the Cramer coefficient indicates that this improvement is only significant compared to the Pearson correlation but not for the euclidean distance. Furthermore, the performance of the presented forecasting system is very low during the summer and new predictors have to be tested to overcome this problem. [ABSTRACT FROM AUTHOR]

Summary ¶Temporal changes in the occurrence of extreme events in time series of observed precipitation are investigated. The analysis is based on a European gridded data set and a German station-based data set of recent monthly totals (1896/1899?1995/1998). Two approaches are used. First, values above certain defined thresholds are counted for the first and second halves of the observation period. In the second step time series components, such as trends, are removed to obtain a deeper insight into the causes of the observed changes. As an example, this technique is applied to the time series of the German station Eppenrod. It arises that most of the events concern extreme wet months whose frequency has significantly increased in winter. Whereas on the European scale the other seasons also show this increase, especially in autumn, in Germany an insignificant decrease in the summer and autumn seasons is found. Moreover it is demonstrated that the increase of extreme wet months is reflected in a systematic increase in the variance and the Weibull probability density function parameters, respectively. [ABSTRACT FROM AUTHOR]

We investigate the relationship between precipitation and runoff data from a small forested catchment in the Harz mountains (Germany). For this purpose, we develop a conceptual model including memory effects to predict the runoff signal using the precipitation data as input. An enhanced variant of the model also includes air temperature as input variable. We show in terms of correlation functions that this model describes the main dynamical properties of the runoff, especially the delay between rain event and runoff response as the annual persistence in the runoff data. [ABSTRACT FROM AUTHOR]

Satellite and reanalysis precipitation products perform poorly over regions with low-density ground observation networks. In order to improve space-dependent parameterization of precipitation estimation models in data-scarce environments, the delineation boundaries of precipitation regimes should be accurately identified. Existing approaches to characterize precipitation regimes by seasonal or other climatological properties do not account for small scale spatial-temporal variability. Precipitation time series can be used to account for this small-scale variability in regime classification. Unfortunately, precipitation products with global coverage perform poorly at small time scales over data scarce regions. A methodology of using satellite-based cloud-top temperature (CTT) time series as a proxy of precipitation time series for precipitation regime classification was developed, and its potential and uncertainty were analyzed. A precipitation regime in this study was defined on the basis of characteristic small-scale temporal distribution and variability of precipitation at a given place. Dynamic time warping was used to calculate the distance between two time series. Criteria to select the optimal temporal scale of time series for clustering and the number of clusters were also developed. The method was validated over Germany and applied to Tanzania, characterized by complex climatology and low density ground observations. This approach was evaluated against precipitation regime classification based on a satellite precipitation product. Results show that CTT outcompetes satellite-based precipitation for classification of precipitation regime classification. The CTT-based classification can be used as precursor to spatially adapted precipitation estimation algorithms where parameters are calibrated by gauge data or other ground-based precipitation observations, and parameterization can be used for satellite-precipitation estimates, precipitation forecasts in numerical or stochastic weather models, etc. [ABSTRACT FROM AUTHOR]

The precipitation diurnal cycle (PDC) varies with the season and location. Its link to large-scale weather circulations has been studied in different regions. However, comparable information is lacking for Central Europe. Two decades of hourly precipitation data were combined with records of objective weather patterns over Germany, focusing on the general atmospheric wind directions (WD). The PDC is characterized by the frequency and the average amount of hourly precipitation. The precipitation frequency generally has two peaks: one in the morning and the other in the afternoon. The morning peak of the precipitation amount is small compared to that of the afternoon peak. Remarkably, WD has a prominent influence on the PDC. Days with southwesterly WD have a high afternoon peak and a lower morning peak, while days with northwesterly WD have a high morning peak and a lower afternoon peak. Furthermore, the seasonal variations of PDC are dominated by the seasonal frequency of WD classes. This study presents a general overview of the PDC in Germany with regard to its variation with seasonality, geographical location, elevation, and WD. [ABSTRACT FROM AUTHOR]