Forecast Verification of the Current Icing Potential (CIP) to Predict Lightning Hazards at U.S. Spaceports

Government spaceports employ extensive lightning detection networks that may not be available at commercial spaceports. Therefore, the Federal Aviation Administration identified the need for diagnosing the threat of triggered lightning without in-situ measurements. Anecdotal observations of the Aviation Weather Center’s Current Icing Potential (CIP) diagnostic model indicated a potentially high correlation between lightning activity and icing potential. A forecast verification study and supporting representative case studies were conducted to quantify the CIP’s ability to diagnose existing lightning hazards. The study showed that high positive statistical correlations between the CIP and lightning activity do exist, but so do negative correlations. During the forecast verification study, the CIP’s ability to diagnose lightning hazards was found to be ineffective due to extensive over-prediction, and, perhaps more importantly, a failure to capture both lightning initiation and cessation. Case study analysis confirmed the CIP’s inability to capture lightning initiation and cessation

Multi-Criteria Decision Analysis as a tool to extract fishing footprints and estimate fishing pressure: application to small scale coastal fisheries and implications for management in the context of the Maritime Spatial Planning Directive

In the context of the Maritime Spatial Planning Directive and with the intention of contributing to the implementation of a future maritime spatial plan, it was decided to analyze data from the small scale coastal fisheries sector of Greece and estimate the actual extent of its activities, which is largely unknown to date. To this end we identified the most influential components affecting coastal fishing: fishing capacity, bathymetry, distance from coast, Sea Surface Chlorophyll (Chl-a) concentration, legislation, marine traffic activity, trawlers and purse seiners fishing effort and no-take zones. By means of Multi-Criteria Decision Analysis (MCDA) conducted through a stepwise procedure, the potential fishing footprint with the corresponding fishing intensity was derived. The method provides an innovative and cost-effective way to assess the impact of the, notoriously hard to assess, coastal fleet. It was further considered how the inclusion of all relevant anthropogenic activities (besides fishing) could provide the background needed to plan future marine activities in the framework of Marine Spatial Planning (MSP) and form the basis for a more realistic management approach

GDIS, a global dataset of geocoded disaster locations

This article presents a new open source extension to the Emergency Events Database (EM-DAT) that allows researchers, for the first time, to explore and make use of subnational, geocoded data on major disasters triggered by natural hazards. The Geocoded Disasters (GDIS) dataset provides spatial geometry in the form of GIS polygons and centroid latitude and longitude coordinates for each administrative entity listed as a disaster location in the EM-DAT database. In total, GDIS contains spatial information on 39,953 locations for 9,924 unique disasters occurring worldwide between 1960 and 2018. The dataset facilitates connecting the EM-DAT database to other geographic data sources on the subnational level to enable rigorous empirical analyses of disaster determinants and impacts

Using global datasets to estimate flood exposure at the city scale: an evaluation in Addis Ababa

Copyright \ua9 2024 Carr, Trigg, Haile, Bernhofen, Alemu, Bekele and Walsh.Introduction: Cities located in lower income countries are global flood risk hotspots. Assessment and management of these risks forms a key part of global climate adaptation efforts. City scale flood risk assessments necessitate flood hazard information, which is challenging to obtain in these localities because of data quality/scarcity issues, and the complex multi-source nature of urban flood dynamics. A growing array of global datasets provide an attractive means of closing these data gaps, but their suitability for this context remains relatively unknown. Methods: Here, we test the use of relevant global terrain, rainfall, and flood hazard data products in a flood hazard and exposure assessment framework covering Addis Ababa, Ethiopia. To conduct the tests, we first developed a city scale rain-on-grid hydrodynamic flood model based on local data and used the model results to identify buildings exposed to flooding. We then observed how the results of this flood exposure assessment changed when each of the global datasets are used in turn to drive the hydrodynamic model in place of its local counterpart. Results and discussion: Results are evaluated in terms of both the total number of exposed buildings, and the spatial distribution of exposure across Addis Ababa. Our results show that of the datasets tested, the FABDEM global terrain and the PXR global rainfall data products provide the most promise for use at the city scale in lower income countries

A High-Resolution Regional Climate Model Physics Ensemble for Northern Sub-Saharan Africa

While climate information from General Circulation Models (GCMs) are usually too coarse for climate impact modelers or decision makers from various disciplines (e.g., hydrology, agriculture), Regional Climate Models (RCMs) provide feasible solutions for downscaling GCM output to finer spatiotemporal scales. However, it is well known that the model performance depends largely on the choice of the physical parameterization schemes, but optimal configurations may vary e.g., from region to region. Besides land-surface processes, the most crucial processes to be parameterized in RCMs include radiation (RA), cumulus convection (CU), cloud microphysics (MP), and planetary boundary layer (PBL), partly with complex interactions. Before conducting long-term climate simulations, it is therefore indispensable to identify a suitable combination of physics parameterization schemes for these processes. Using the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis product ERA-Interim as lateral boundary conditions, we derived an ensemble of 16 physics parameterization runs for a larger domain in Northern sub-Saharan Africa (NSSA), northwards of the equator, using two different CU-, MP-, PBL-, and RA schemes, respectively, using the Weather Research and Forecasting (WRF) model for the period 2006–2010 in a horizontal resolution of approximately 9 km. Based on different evaluation strategies including traditional (Taylor diagram, probability densities) and more innovative validation metrics (ensemble structure-amplitude-location (eSAL) analysis, Copula functions) and by means of different observation data for precipitation (P) and temperature (T), the impact of different physics combinations on the representation skill of P and T has been analyzed and discussed in the context of subsequent impact modeling. With the specific experimental setup, we found that the selection of the CU scheme has resulted in the highest impact with respect to the representation of P and T, followed by the RA parameterization scheme. Both, PBL and MP schemes showed much less impact. We conclude that a multi-facet evaluation can finally lead to better choices about good physics scheme combinations

Remote Sensing of Hydro-Meteorology

Flood/drought, risk management, and policy: decision-making under uncertainty. Hydrometeorological extremes and their impact on human–environment systems. Regional and nonstationary frequency analysis of extreme events. Detection and prediction of hydrometeorological extremes with observational and model-based approaches. Vulnerability and impact assessment for adaptation to climate change

Globally invariant metabolism but density-diversity mismatch in springtails.

Soil life supports the functioning and biodiversity of terrestrial ecosystems. Springtails (Collembola) are among the most abundant soil arthropods regulating soil fertility and flow of energy through above- and belowground food webs. However, the global distribution of springtail diversity and density, and how these relate to energy fluxes remains unknown. Here, using a global dataset representing 2470 sites, we estimate the total soil springtail biomass at 27.5 megatons carbon, which is threefold higher than wild terrestrial vertebrates, and record peak densities up to 2 million individuals per square meter in the tundra. Despite a 20-fold biomass difference between the tundra and the tropics, springtail energy use (community metabolism) remains similar across the latitudinal gradient, owing to the changes in temperature with latitude. Neither springtail density nor community metabolism is predicted by local species richness, which is high in the tropics, but comparably high in some temperate forests and even tundra. Changes in springtail activity may emerge from latitudinal gradients in temperature, predation and resource limitation in soil communities. Contrasting relationships of biomass, diversity and activity of springtail communities with temperature suggest that climate warming will alter fundamental soil biodiversity metrics in different directions, potentially restructuring terrestrial food webs and affecting soil functioning

Tools and metrics to characterize extreme climate events and evaluate climatic datasets over the Upper Colorado River Basin for societal applications

This study supports the Denver Water management goals by providing tools and metrics that are relevant for operational activities. The study focuses mainly on drought events, but with a slight mention of pluvial conditions over upper Colorado River basin (UCRB), the region that supplies water to Denver community. The study uses observed monthly minimum and maximum temperatures and monthly precipitation datasets (Climatic Research Unit; CRU and Precipitation-Elevation Regression on Independent Slopes Model; PRISM) and modeling outputs from 34 members of the Community Earth System Model Large Ensemble (CESM-LE) to monitor and characterize droughts over the region. With these datasets, we compute two multi-scalar moisture indices: standardized precipitation evapotranspiration index (SPEI) and standardized precipitation index (SPI) on a 36-month scale. We evaluate the capability of the CESM-LE to reproduce drought over the region using the more recently developed spatial verification tool, the Method for Object-based Diagnostic Evaluation (MODE) technique. In addition, the study examines the large-scale atmospheric circulation features associated with drought and pluvial conditions using reanalysis output. The results reveal the usefulness of these datasets, the drought indicators, and the spatial verification technique as important analytical tools to monitor and characterize extreme hydroclimatic conditions over UCRB