Storm damage in the Black Forest caused by the winter storm "Lothar" - Part 1: Airborne damage assessment

An airborne survey of the Black Forest as affected by the winter storm "Lothar" in 1999 is performed by means of a color line scanner (CLS) with a CCD sensor, whose data in a visible and a near-infrared channel provide the Normalized Difference Vegetation Index (NDVI) as a measure of the damage in previously intact forest areas. The camera data, height data from a digital evelation model (DEM), land use information, and soil data are georeferenced and processed in a geographic information system (GIS) to derive relationship of the damage pattern to the characteristics of the local orography and soil types. The data cover an area of 4900 km$^2$, 2767 km$^2$ of which were forested. The 363 detected storm damage areas with a minimum detection size of 1.5 ha amount to 0.8% of the total forest area. Visual inspections at certain sites prove that none of the larger damage areas are missed, but areas smaller than 1.5 ha cause the total damage area to be up to twice our result, i.e. ≈1.6% of the forest area. More than 50% of the detected damaged areas are smaller than 5 ha and most of them have a size ranging from 1.5 to 3.5 ha. Forests on slopes with an inclination angle between 10 and 15 degrees show the highest fraction of damaged forest, doubling those on plains and below 5 degrees inclination angle. Forests on northwestern slopes are more affected than those on southwestern and western slopes, which faced the wind during highest wind speed occurrence. In contrast to other studies, this paper shows, that in steep areas, lee slopes are more damaged than the luv slopes. As expected, wet to moist soils represent an unstable location for the trees. But also medium-dry to dry locations that were considered to be relatively stable exhibited a highly damaged forest fraction. This can be attributed to mostly saturated soil from previous rain

Regional scale effects of the aerosol cloud interaction simulated with an online coupled comprehensive chemistry model

We have extended the coupled mesoscale atmosphere and chemistry model COSMO-ART to account for the transformation of aerosol particles into cloud condensation nuclei and to quantify their interaction with warm cloud microphysics on the regional scale. The new model system aims to fill the gap between cloud resolving models and global scale models. It represents the very complex microscale aerosol and cloud physics as detailed as possible, whereas the continental domain size and efficient codes will allow for both studying weather and regional climate. The model system is applied in a first extended case study for Europe for a cloudy five day period in August 2005. <br><br> The model results show that the mean cloud droplet number concentration of clouds is correlated with the structure of the terrain, and we present a terrain slope parameter TS to classify this dependency. We propose to use this relationship to parameterize the probability density function, PDF, of subgrid-scale cloud updraft velocity in the activation parameterizations of climate models. <br><br> The simulations show that the presence of cloud condensation nuclei (CCN) and clouds are closely related spatially. We find high aerosol and CCN number concentrations in the vicinity of clouds at high altitudes. The nucleation of secondary particles is enhanced above the clouds. This is caused by an efficient formation of gaseous aerosol precursors above the cloud due to more available radiation, transport of gases in clean air above the cloud, and humid conditions. Therefore the treatment of complex photochemistry is crucial in atmospheric models to simulate the distribution of CCN. <br><br> The mean cloud droplet number concentration and droplet diameter showed a close link to the change in the aerosol. To quantify the net impact of an aerosol change on the precipitation we calculated the precipitation susceptibility <i>β</i> for the whole model domain over a period of two days with an hourly resolution. The distribution function of <i>β</i> is slightly skewed to positive values and has a mean of 0.23. Clouds with a liquid water path LWP of approximately 0.85 kg m<sup>−2</sup> are on average most susceptible to aerosol changes in our simulations with an absolute value of <i>β</i> of 1. The average <i>β</i> for LWP between 0.5 kg m<sup>−2</sup> and 1 kg m<sup>−2</sup> is approximately 0.4

Winter storm risk of residential structures ? model development and application to the German state of Baden-Württemberg

International audienceThe derivation of probabilities of high wind speeds and the establishment of risk curves for storm damage is of prime importance in natural hazard risk analysis. Risk curves allow the assessment of damage being exceeded at a given level of probability. In this paper, a method for the assessment of winter storm damage risk is described in detail and applied to the German state of Baden-Württemberg. Based on meteorological observations of the years 1971?2000 and on damage information of 4 severe storm events, storm hazard and damage risk of residential buildings is calculated on the level of communities. For this purpose, highly resolved simulations of storm wind fields with the Karlsruher Atmospheric Mesoscale Model (KAMM) are performed and a storm damage model is developed. Risk curves including the quantification of the uncertainties are calculated for every community. Local differences of hazard and risk are presented in state-wide maps. An average annual winter storm damage to residential buildings of minimum 15 million Euro (reference year 2000) for Baden-Württemberg is expected

When Do Subpollen Particles Become Relevant for Ice Nucleation Processes in Clouds?

When exposed to sufficiently humid environments, pollen grains burst and release large quantities of small subpollen particles (SPPs) which carry ice nucleating macromolecules. In this study, for the first time we develop a physically based parameterization describing the bursting process of pollen by applying a turgor pressure parameterization and quantify the impact SPPs have on overall ice nucleation in clouds. SPPs are generated from simulated birch pollen emissions over Europe for a 10-day case study in spring. We found SPP concentrations to surpass pollen grain concentrations by 4–6 orders of magnitude leading to an abundance of biological ice nuclei from SPPs in the range of 10$^3$−10$^4$ m$^{−3}$. However, it is found that these concentrations lead to only small changes in hydrometeor number densities and precipitation. Addressing the question when SPPs become relevant for ice nucleation in clouds, we conducted a sensitivity investigation. We find that amplifying ice nucleation efficiency of biological particles by factors greater 100 increases the ice particle numbers by up to 25% (T ≈ 268 K). Strong reductions show in cloud droplet number concentration and water vapor at these temperatures while water vapor is increasing at 600 m. Overall, we found a net reduction of water in the atmosphere as liquid and particularly water vapor density is reduced, while frozen water mass density increases above 257 K. Findings indicate an alteration of mixed-phase cloud composition and increased precipitation (up to 6.2%) when SPPs are considered as highly efficient biological ice nuclei

The importance of plume rise on the concentrations and atmospheric impacts of biomass burning aerosol

We quantified the effects of the plume rise of biomass burning aerosol and gases for the forest fires that occurred in Saskatchewan, Canada, in July 2010. For this purpose, simulations with different assumptions regarding the plume rise and the vertical distribution of the emissions were conducted. Based on comparisons with observations, applying a one-dimensional plume rise model to predict the injection layer in combination with a parametrization of the vertical distribution of the emissions outperforms approaches in which the plume heights are initially predefined. Approximately 30 % of the fires exceed the height of 2 km with a maximum height of 8.6 km. Using this plume rise model, comparisons with satellite images in the visible spectral range show a very good agreement between the simulated and observed spatial distributions of the biomass burning plume. The simulated aerosol optical depth (AOD) with data of an AERONET station is in good agreement with respect to the absolute values and the timing of the maximum. Comparison of the vertical distribution of the biomass burning aerosol with CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation) retrievals also showed the best agreement when the plume rise model was applied. We found that downwelling surface short-wave radiation below the forest fire plume is reduced by up to 50 % and that the 2 m temperature is decreased by up to 6 K. In addition, we simulated a strong change in atmospheric stability within the biomass burning plume

A new estimator of heat periods for decadal climate predictions - A complex network approach

Regional decadal predictions have emerged in the past few years as a research field with high application potential, especially for extremes like heat and drought periods. However, up to now the prediction skill of decadal hindcasts, as evaluated with standard methods, is moderate and for extreme values even rarely investigated. In this study, we use hindcast data from a regional climate model (CCLM) for eight regions in Europe and quantify the skill of the model alternatively by constructing time-evolving climate networks and use the network correlation threshold (link strength) as a predictor for heat periods. We show that the skill of the network measure to estimate the low-frequency dynamics of heat periods is superior for decadal predictions with respect to the typical approach of using a fixed temperature threshold for estimating the number of heat periods in Europe

Saharan Dust Event Impacts on Cloud Formation and Radiation over Western Europe

We investigated the impact of mineral dust particles on clouds, radiation and atmospheric state during a strong Saharan dust event over Europe in May 2008, applying a comprehensive online-coupled regional model framework that explicitly treats particle-microphysics and chemical composition. Sophisticated parameterizations for aerosol activation and ice nucleation, together with two-moment cloud microphysics are used to calculate the interaction of the different particles with clouds depending on their physical and chemical properties. The impact of dust on cloud droplet number concentration was found to be low, with just a slight increase in cloud droplet number concentration for both uncoated and coated dust. For temperatures lower than the level of homogeneous freezing, no significant impact of dust on the number and mass concentration of ice crystals was found, though the concentration of frozen dust particles reached up to 100 l-1 during the ice nucleation events. Mineral dust particles were found to have the largest impact on clouds in a temperature range between freezing level and the level of homogeneous freezing, where they determined the number concentration of ice crystals due to efficient heterogeneous freezing of the dust particles and modified the glaciation of mixed phase clouds. Our simulations show that during the dust events, ice crystals concentrations were increased twofold in this temperature range (compared to if dust interactions are neglected). This had a significant impact on the cloud optical properties, causing a reduction in the incoming short-wave radiation at the surface up to -75Wm-2. Including the direct interaction of dust with radiation caused an additional reduction in the incoming short-wave radiation by 40 to 80Wm-2, and the incoming long-wave radiation at the surface was increased significantly in the order of +10Wm-2. The strong radiative forcings associated with dust caused a reduction in surface temperature in the order of -0.2 to -0.5K for most parts of France, Germany, and Italy during the dust event. The maximum difference in surface temperature was found in the East of France, the Benelux, and Western Germany with up to -1 K. This magnitude of temperature change was sufficient to explain a systematic bias in numerical weather forecasts during the period of the dust event

Skill and added value of the MiKlip regional decadal prediction system for temperature over Europe

In recent years, several decadal prediction systems have been developed to provide multi-year predictions of the climate for the next 5–10 years. On the global scale, high decadal predictability has been identified for the North Atlantic sector, often extending over Europe. The first full regional hindcast ensemble, derived from dynamical downscaling, was produced within the German MiKlip project (‘decadal predictions’). The ensemble features annual starting dates from 1960 to 2017, with 10 decadal hindcasts per starting year. The global component of the prediction system uses the MPI-ESM-LR and the downscaling is performed with the regional climate model COSMO-CLM (CCLM). The present study focusses on a range of aspects dealing with the skill and added value of regional decadal temperature predictions over Europe. The results substantiate the added value of the regional hindcasts compared to the forcing global model as well as to un-initialized simulations. The results show that the hindcasts are skilful both for annual and seasonal means, and that the scores are comparable for different observational reference data sets. The predictive skill increases from earlier to more recent start-years. A recalibration of the simulation data generally improves the skill further, which can also be transferred to more user-relevant variables and extreme values like daily maximum temperatures and heating degree-days. These results provide evidence of the potential for the regional climate predictions to provide valuable climate information on the decadal time-scale to users