Design of operational application system of cruise missile supported by meteorological and marine information

In information war, the concept of “digital battlefield” is put forward, and battlefield meteorological and marine information has become an important part of digital battlefield. Based on the in-depth analysis of the impact of meteorological marine information on cruise missile, this paper puts forward the multi-dimensional demand analysis method of meteorological marine information supporting cruise missile combat application and the architecture design method based on MBSE, and gives the conceptual design framework of combat application system to provide information support for cruise missile combat application.

Assessment of climate services prototypes on seasonal water management for the Mediterranean regions

<p>In the framework of the MEDSCOPE project, Météo-France has initiated the development of new prototypes for seasonal water resource management in the Mediterranean region, addressing different scientific and technical challenges essential for a future operationalization of the services . In order to have a replicable result on the Mediterranean area, we decided first to consider the three large watersheds onof the Rhone river in France, the Ebro river in Spain and the Po river in Italy.</p><p>Our first challenge was to use a new hydrologic model SURFEX-CTRIP, covering the whole Mediterranean area. Another point was to perfect and evaluate a new downscaling tool named ADAMONT permitting to debiase all seasonal forecast input variables needed for hydrology applications and not only (temperature and, precipitation and 5 other surface meteorological parameters). We decided also to assess the new UERRA hydrological analyse available on these three countries. Lthe last challenge was to identify local end users facing with decision making process at seasonal scale for water resources management and develop decision help products adapted to their needs.</p><p>The evaluation of these prototypes, carried out over the period 2019-2020 using the MF Syst 6 and then Syst 7 seasonal forecasting model, has highlighted a significant potential in a future operational application but also difficulties to be overcome.</p><p>The communication will present the main results of this work and discuss the lessons to be learnet from this experience</p><p> </p>

Statistical post-processing of ensemble forecasts at the Belgian met service

<p>Statistical post-processing of ensemble weather forecasts has become an essential step in the forecasting chain as it enables the correction of biases and reliable uncertainty estimates of ensembles (Gneiting, 2014).  One algorithm recently proposed to perform the correction of ensemble weather forecasts is a linear member-by-member (MBM) Model Output Statistics (MOS) system, post-processing each member of the ECMWF ensemble (Van Schaeybroeck & Vannitsem, 2015). This method consists in correcting the mean and variability of the ensemble members in line with the observed climatology. At the same time, it calibrates the ensemble spread such as to match, on average, the mean square error of the ensemble mean. The MBM method calibrates the ensemble forecasts based on the station observations by minimizing the continuous ranked probability score (CRPS).</p><p><span>Using this method, the Royal Meteorological Institute of Belgium has started in 2020 its new postprocessing program by developing an operational application to perform the calibration of the ECMWF ensemble forecasts at the stations points for the minimum and maximum temperature, and for wind gusts. </span>In this report, we will first describe briefly the postprocessing methods being used and the architecture of the application. We will then present the results over the first few months of operation. Finally, we will discuss the future developments of this application and of the program.</p><p><span><br></span></p><p><span> </span> <span> </span></p><p><strong>Gneiting</strong>, <strong>T.</strong>, 2014: Calibration of medium-range weather forecasts. <em>ECMWF Technical Memorandum</em> <strong>No. 719</strong></p><p><span> </span> <span> </span></p><p><strong>Van Schaeybroeck</strong>, <strong>B.</strong> & <strong>Vannitsem</strong>, <strong>S.</strong>, 2015: Ensemble post-processing using member-by-member approaches: theoretical aspects. <em>Quarterly Journal of the Royal Meteorological Society</em>, <strong>141</strong>, 807–818.</p>

A revision of the Combined Drought Indicator (CDI) used in the European Drought Observatory (EDO)

Building on almost 10 years of expertise and operational application of the Combined Drought Indicator (CDI), which is implemented within the European Commission's European Drought Observatory (EDO) for the purposes of early warning and monitoring of agricultural droughts in Europe, this paper proposes a revised version of the index. The CDI conceptualizes drought as a cascade process, where a precipitation shortage (WATCH stage) develops into a soil water deficit (WARNING stage), which in turn leads to stress for vegetation (ALERT stage). The main goal of the revised CDI proposed here is to improve the indicator's performance for those events that are currently not reliably represented, without altering either the modelling conceptual framework or the required input datasets. This is achieved by means of two main modifications: (a) use of the previously occurring CDI value to improve the temporal consistency of the time series and (b) introduction of two temporary classes – namely TEMPORARY RECOVERY for soil moisture and vegetation greenness, respectively – to avoid brief discontinuities in a stage. The efficacy of the modifications is tested by comparing the performances of the revised and currently implemented versions of the indicator for actual drought events in Europe during the last 20 years. The revised CDI reliably reproduces the evolution of major droughts, outperforming the current version of the indicator, especially for long-lasting events, and reducing the overall temporal inconsistencies in stage sequencing of about 70 %. Since the revised CDI does not need supplementary input datasets, it is suitable for operational implementation within the EDO drought monitoring system.

Snow profile alignment and similarity assessment for aggregating, clustering, and evaluating snowpack model output for avalanche forecasting

Snowpack models simulate the evolution of the snow stratigraphy based on meteorological inputs and have the potential to support avalanche risk management operations with complementary information relevant for their avalanche hazard assessment, especially in data-sparse regions or at times of unfavorable weather and hazard conditions. However, the adoption of snowpack models in operational avalanche forecasting has been limited, predominantly due to missing data processing algorithms and uncertainty around model validity. Thus, to enhance the usefulness of snowpack models for the avalanche industry, numerical methods are required that evaluate and summarize snowpack model output in accessible and relevant ways. We present algorithms that compare and assess generic snowpack data from both human observations and models, which consist of multidimensional sequences describing the snow characteristics of grain type, hardness, and age. Our approach exploits Dynamic Time Warping, a well-established method in the data sciences, to match layers between snow profiles and thereby align them. The similarity of the aligned profiles is then evaluated by our independent similarity measure based on characteristics relevant for avalanche hazard assessment. Since our methods provide the necessary quantitative link to data clustering and aggregating methods, we demonstrate how snowpack model output can be grouped and summarized according to similar hazard conditions. By emulating aspects of the human avalanche hazard assessment process, our methods aim to promote the operational application of snowpack models so that avalanche forecasters can begin to build an understanding of how to interpret and trust operational snowpack simulations.

THE CONCEPT OF SOCIETAL SECURITY: THEORY, DISCUSSION, AND CASPIAN PERSPECTIVES

The issue of ensuring security remains one of the most important for the social sciences at the present stage. In recent decades, the concept of societal security, which tracks its origin to Copenhagen School, has been increasingly prominent. The purpose of this article is to systematize the main provisions of the societal approach to security and to identify the possibility of its operational application to the study of the Caspian region. The main provisions of the societal approach include the following factors: the reference object of the research is the so-called "societal community"; the basis for the existence of such a community is a collective, most often cultural, sometimes confessional identity; this problem is always considered in relation to a certain social space, which is transformed under the influence of political, economic, and environmental factors. Traditionally, the societal approach has been applied to the analysis of security problems in the European space: the Baltic States, Spain, there is an experience of its application to African society in some Asian countries. Another interesting area for analysis may be the Caspian region, which after the collapse of the USSR has become a strategically important Euro-Asian geopolitical and economic hub. However, the regional specifics require researcher to implement a creative application of this approach, taking into account both theoretical criticisms and the specifics of the space itself.

SOCIOLOGICAL INFORMATION THEORY IN URBAN AGGLOMERATION MANAGEMENT

The article notes that informatization of the management process is currently one of the most pressing and at the same time one of the most difficult tasks. The aim of the work is to analyze and systematize the main theoretical and methodological provisions on the interdependence of sociological information and the management of urban agglomerations. It is noted that in the modern situation of social development, when due to the large flow of information there is a need for its awareness and operational application for the management of all structures of urban agglomeration, it is important to adhere to the theoretical and methodological pro-visions identified in the work.

Gridded Satellite Sounding Retrievals in Operational Weather Forecasting: Product Description and Emerging Applications

The National Aeronautics and Space Administration (NASA) Short-term Prediction Research and Transition Center (SPoRT) has been part of a collaborative effort within the National Oceanic and Atmospheric Administration (NOAA) Joint Polar Satellite System (JPSS) Proving Ground and Risk Reduction (PGRR) Program to develop gridded satellite sounding retrievals for the operational weather forecasting community. The NOAA Unique Combined Atmospheric Processing System (NUCAPS) retrieves vertical profiles of temperature, water vapor, trace gases, and cloud properties derived from infrared and microwave sounder measurements. A new, optimized method for deriving NUCAPS level 2 horizontally and vertically gridded products is described here. This work represents the development of approaches to better synthesize remote sensing observations that ultimately increase the availability and usability of NUCAPS observations. This approach, known as “Gridded NUCAPS”, was developed to more effectively visualize NUCAPS observations to aid in the quick identification of thermodynamic spatial gradients. Gridded NUCAPS development was based on operations-to-research feedback and is now part of the operational National Weather Service display system. In this paper, we discuss how Gridded NUCAPS was designed, how relevant atmospheric fields are derived, its operational application in pre-convective weather forecasting, and several emerging applications that expand the utility of NUCAPS for monitoring phenomena such as fire weather, the Saharan Air Layer, and stratospheric air intrusions.