Impact of Surface Roughness and Soil Texture on Mineral Dust Emission Fluxes Modeling

Dust production models (DPM) used to estimate vertical fluxes of mineral dust aerosols over arid regions need accurate data on soil and surface properties. The Laboratoire Inter-Universitaire des Systemes Atmospheriques (LISA) data set was developed for Northern Africa, the Middle East, and East Asia. This regional data set was built through dedicated field campaigns and include, among others, the aerodynamic roughness length, the smooth roughness length of the erodible fraction of the surface, and the dry (undisturbed) soil size distribution. Recently, satellite-derived roughness length and high-resolution soil texture data sets at the global scale have emerged and provide the opportunity for the use of advanced schemes in global models. This paper analyzes the behavior of the ERS satellite-derived global roughness length and the State Soil Geographic data base-Food and Agriculture Organization of the United Nations (STATSGO-FAO) soil texture data set (based on wet techniques) using an advanced DPM in comparison to the LISA data set over Northern Africa and the Middle East. We explore the sensitivity of the drag partition scheme (a critical component of the DPM) and of the dust vertical fluxes (intensity and spatial patterns) to the roughness length and soil texture data sets. We also compare the use of the drag partition scheme to a widely used preferential source approach in global models. Idealized experiments with prescribed wind speeds show that the ERS and STATSGO-FAO data sets provide realistic spatial patterns of dust emission and friction velocity thresholds in the region. Finally, we evaluate a dust transport model for the period of March to July 2011 with observed aerosol optical depths from Aerosol Robotic Network sites. Results show that ERS and STATSGO-FAO provide realistic simulations in the region

Review article: A European perspective on wind and storm damage – from the meteorological background to index-based approaches to assess impacts

Wind and windstorms cause severe damage to natural and human-made environments. Thus, wind-related risk assessment is vital for the preparation and mitigation of calamities. However, the cascade of events leading to damage depends on many factors that are environment-specific and the available methods to address wind-related damage often require sophisticated analysis and specialization. Fortunately, simple indices and thresholds are as effective as complex mechanistic models for many applications. Nonetheless, the multitude of indices and thresholds available requires a careful selection process according to the target sector. Here, we first provide a basic background on wind and storm formation and characteristics, followed by a comprehensive collection of both indices and thresholds that can be used to predict the occurrence and magnitude of wind and storm damage. We focused on five key sectors: forests, urban areas, transport, agriculture and wind-based energy production. For each sector we described indices and thresholds relating to physical properties such as topography and land cover but also to economic aspects (e.g. disruptions in transportation or energy production). In the face of increased climatic variability, the promotion of more effective analysis of wind and storm damage could reduce the impact on society and the environment

The NMMB/BSC-CTM: a multiscale online chemical weather prediction system

Abstract: The model NMMB/BSC-CTM is a new fully on-line chemical weather prediction system under development at the Earth Sciences Department of the Barcelona Supercomputing Center in collaboration with several research institutions. The basis of the development is the NCEP new global/regional Nonhydrostatic Multiscale Model on the B grid (NMMB). Its unified nonhydrostatic dynamical core allows regional and global simulations and forecasts. A mineral dust module has been coupled within the NMMB. The new system, NMMB/BSCDUST, simulates the atmospheric life cycle of the eroded desert dust. The main characteristics are its on-line coupling of the dust scheme with the meteorological driver, the wide range of applications from meso to global scales, and the dust shortwave and longwave radiative feedbacks on meteorology. In order to complement such development, the BSC works also in the implementation of a fully on-line gas-phase chemical mechanism. Chemical species are advected and mixed at the corresponding time steps of the meteorological tracers using the same numerical scheme of the NMMB. Advection is Eulerian, positive definite and monotone. The final objective of the work is to develop a fully chemical weather prediction system, namely NMMB/BSC-CTM, able to resolve gas-aerosol-meteorology interactions from global to local scales. Future efforts will be oriented to incorporate a multi-component aerosol module within the system with the aim to solve the life-cycle of relevant aerosols at global scale (dust, sea salt, sulfate, black carbon and organic carbon). In the present contribution we describe the status of development of the system and first evaluation results of the gas-phase chemistry.Postprint (published version

Review article: A European perspective on wind and storm damage – from the meteorological background to index-based approaches to assess impacts

Wind and windstorms cause severe damage to natural and human-made environments. Thus, wind-related risk assessment is vital for the preparation and mitigation of calamities. However, the cascade of events leading to damage depends on many factors that are environment-specific and the available methods to address wind-related damage often require sophisticated analysis and specialization. Fortunately, simple indices and thresholds are as effective as complex mechanistic models for many applications. Nonetheless, the multitude of indices and thresholds available requires a careful selection process according to the target sector. Here, we first provide a basic background on wind and storm formation and characteristics, followed by a comprehensive collection of both indices and thresholds that can be used to predict the occurrence and magnitude of wind and storm damage. We focused on five key sectors: forests, urban areas, transport, agriculture and wind-based energy production. For each sector we described indices and thresholds relating to physical properties such as topography and land cover but also to economic aspects (e.g. disruptions in transportation or energy production). In the face of increased climatic variability, the promotion of more effective analysis of wind and storm damage could reduce the impact on society and the environment

weather@home 2: validation of an improved global–regional climate modelling system

Extreme weather events can have large impacts on society and, in many regions, are expected to change in frequency and intensity with climate change. Owing to the relatively short observational record, climate models are useful tools as they allow for generation of a larger sample of extreme events, to attribute recent events to anthropogenic climate change, and to project changes in such events into the future. The modelling system known as weather@home, consisting of a global climate model (GCM) with a nested regional climate model (RCM) and driven by sea surface temperatures, allows one to generate a very large ensemble with the help of volunteer distributed computing. This is a key tool to understanding many aspects of extreme events. Here, a new version of the weather@home system (weather@home 2) with a higher-resolution RCM over Europe is documented and a broad validation of the climate is performed. The new model includes a more recent land-surface scheme in both GCM and RCM, where subgrid-scale land-surface heterogeneity is newly represented using tiles, and an increase in RCM resolution from 50 to 25 km. The GCM performs similarly to the previous version, with some improvements in the representation of mean climate. The European RCM temperature biases are overall reduced, in particular the warm bias over eastern Europe, but large biases remain. Precipitation is improved over the Alps in summer, with mixed changes in other regions and seasons. The model is shown to represent the main classes of regional extreme events reasonably well and shows a good sensitivity to its drivers. In particular, given the improvements in this version of the weather@home system, it is likely that more reliable statements can be made with regards to impact statements, especially at more localized scales

Compound events in Germany in 2018: drivers and case studies

The European continent is regularly affected by a wide range of extreme events and natural hazards including heatwaves, extreme precipitation, droughts, cold spells, windstorms, and storm surges. Many of these events do not occur as single extreme events, but rather show a multivariate character, the so-called compound events. Within the scope of the interdisciplinary project climXtreme (https://climxtreme.net/), we investigate the interplay of extreme weather events, their characteristics and changes, intensity, frequency and uncertainties in the past, present and future and associated impacts on various socio-economic sectors in Germany and Central Europe. This contribution presents several case studies with special emphasis on the calendar year of 2018, which is of particular interest given the exceptional sequence of different compound events across large parts of Europe, with devastating impacts on human lives, ecosystems and infrastructure. We provide new evidence on drivers of spatially and temporally compound events (heat and drought; heavy precipitation in combination with extreme winds) with adverse impacts on ecosystems and society using large-scale atmospheric patterns. We shed light on the interannual influence of droughts on surface water and the impact of water scarcity and heatwaves on agriculture and forests. We assessed projected changes in compound events at different current and future global surface temperature levels, demonstrating the importance of better quantifying the likelihood of future extreme events for adaptation planning. Finally, we addressed research needs and future pathways, emphasising the need to define composite events primarily in terms of their impacts prior to their statistical characterisation