A complex aerosol transport event over Europe during the 2017 Storm Ophelia in CAMS forecast systems: analysis and evaluation

In mid-October 2017 Storm Ophelia crossed over western coastal Europe, inducing the combined transport of Saharan dust and Iberian biomass burning aerosols over several European areas. In this study we assess the performance of the Copernicus Atmosphere Monitoring Service (CAMS) forecast systems during this complex aerosol transport event and the potential benefits that data assimilation and regional models could bring. To this end, CAMS global and regional forecast data are analysed and compared against observations from passive (MODIS: Moderate Resolution Imaging Spectroradiometer aboard Terra and Aqua) and active (CALIOP/CALIPSO: Cloud-Aerosol LIdar with Orthogonal Polarization aboard Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) satellite sensors and ground-based measurements (EMEP: European Monitoring and Evaluation Programme). The analysis of the CAMS global forecast indicates that dust and smoke aerosols, discretely located on the warm and cold fronts of Ophelia, respectively, were affecting the aerosol atmospheric composition over Europe during the passage of the Storm. The observed MODIS aerosol optical depth (AOD) values are satisfactorily reproduced by the CAMS global forecast system, with a correlation coefficient of 0.77 and a fractional gross error (FGE) of 0.4. The comparison with a CAMS global control simulation not including data assimilation indicates a significant improvement in the bias due to data assimilation implementation, as the FGE decreases by 32 %. The qualitative evaluation of the IFS (Integrated Forecast System) dominant-aerosol type and location against the CALIPSO observations overall reveals a good agreement. Regarding the footprint on air quality, both CAMS global and regional forecast systems are generally able to reproduce the observed signal of increase in surface particulate matter concentrations. The regional component performs better in terms of bias and temporal variability, with the correlation deteriorating over forecast time. Yet, both products exhibit inconsistencies on the quantitative and temporal representation of the observed surface particulate matter enhancements, stressing the need for further development of the air quality forecast systems for even more accurate and timely support of citizens and policy-makers.

Development of Customized Variable-Resolution CPAS for Meteorological Simulation

<div> <p>    The model performance and run-time are two major concerns in numerical weather prediction. Both are substantially dependent on the grid specification, in particular, the number of grids, resolution and coverage of the refinement regions. In the Model for Prediction Across Scales - Atmosphere (MPAS-A), unstructured Voronoi mesh is used and the infrastructure, particularly the dynamic core, is implemented to support this flexible topology. However, only several standard meshes are available for download while customization is not supported. Moreover, the use of a globally-constant time-step (determined by the smallest grid) poses challenges on high resolution forecast using meshes with large resolution variation due to impractically long-running time. A Customizable Unstructured Mesh Generation (CUMG) and Hierarchical Time-Stepping (HTS) was developed in the ClusterTech Platform for Atmospheric Simulation (CPAS), offering a potential path for high-resolution local/regional forecast in MPAS-A’s framework. The CUMG algorithm enables local mesh refinement in arbitrary shape using user-defined horizontal resolution at any desired locations. Meshes with large resolution variation, for example, ranging from 128 km to 1 km can be generated. The resulting meshes are 100% well-staggered, and zero obtuse Delaunay triangle is guaranteed. The CPAS provides a web-based graphical user interface and no coding is needed for specifying the refinements. In real simulations, grids are integrated in time with heterogenous time-step according to their cell spacings using HTS. It reduces the model run-time tremendously, particularly for meshes with large resolution variation. </p> </div><div> <p>    In this study, a comparison on the mesh quality, efficiency and performance of a CPAS customized 128-to-1 km mesh to the MPAS-A standard 60-to-3 km mesh with and without HTS was performed. Three historical weather conditions over southern China in 2018 were selected to evaluate their performance: (i) passage of a cold front (ii) heavy rainfall and (iii) passage of a tropical cyclone. In general, the CPAS 128-to-1 km mesh was found to have better quality over the MPAS-A 60-to-3 km mesh, namely cell quality, angle-based triangle quality, and triangle quality. Moreover, using HTS, the benchmarked saving of the total run-time for the CPAS 128-to-1 km mesh and MPAS-A 60-to-3 km mesh are 56.8% (2.33x speedup) and 16.5% (1.20x speedup), respectively. Furthermore, the model results were validated through comparison with the National Centers for Environmental Prediction (NCEP) Final (FNL) Operational Global Analysis. The 5-day simulation results of various forecast variables within the area of interest (a lat-long box covering 3 km refinement region of the MPAS-A 60-to-3 km mesh) with and without HTS for both meshes show comparable performance in all cases. The promising model performance along with remarkable speedup indicates the validity and feasibility of high resolution local/regional forecast using customized global variable-resolution meshes in an operational manner. </p> </div>

An Experiment in Weather Prediction for North East and South West Monsoon Over Chennai

There is a growing demand for spot specific forecast. Presently this has to be extracted from the regional forecast based on synoptic models. Synoptic models require input from various observatories of regions or the country and the central analysis centre is required for generating the synoptic charts. But recently the authors have established the potential of local data alone as a continuous time scale for use in effective local forecast using data mining techniques. Following the same association rule mining and classifier approach is tried for the forecast of wet and dog days on North East Monsoon and South West Monsoon months for the Chennai region with Latitude 13°11' N and Longitude 80°11' E, a coastal station over Bay of Bengal in South India and results are presented.

The conditions of formation of Au–Ag epithermal mineralization of the Amguemo-Kanchalan volcanic field (Eastern Chukotka)

The article considers the conditions of formation of Au–Ag epithermal mineralization of the Amguemo-Kanchalan volcanic field (AKVP), located on the Western closure of the East Chukchi flank zone of the Okhotsk-Chukchi volcanic belt (OCHVB). In the AKVP potentially large Au–Ag Valunisty mine and several perspective deposits and ore occurrences (Zhilnoye, Shah, Gornoye, Ognennoye and Osennee) are localized. The results of thermo- and cryometric studies of fluid inclusions in quartz and calcite of epithermal veins showed that the solutions was dominated by chlorides Na and K. Epithermal mineralization was deposited by heterogeneous hydrothermal fluids with low salt concentrations (0.2–3.6 wt. % equiv. NaCl, in medium-temperature conditions – 174–354°C). The fluid pressure reached 30–160 bar, which corresponds to the formation depth of 0.1–0.6 km, under hydrostatic conditions. The obtained results allow us to attribute the studied epithermal mineralization to the low sulfidation class. The magmatic hearth of andesitic magmas and meteoric waters are the most probable sources of ore-forming fluids. The information given in the article is of practical importance for regional forecast-metallogenic constructions, prospecting and evaluation of epithermal Au–Ag deposits.