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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]

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]

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]

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]

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]