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This study hybridizes the background error covariance (BEC) of the hourly atmospheric three-dimensional variational data assimilation (3DVar) in Local Analysis (LA) operated at Japan Meteorological Agency using the flow-dependent BEC derived from the singular vector-based Mesoscale Ensemble Prediction System (MEPS) and the static BEC. The impact of introducing the hybrid BEC into the 3DVar is examined, along with its sensitivities to various factors like the ensemble size that is augmented by using lagged ensemble forecasts, the weight given to the ensemble-based component of BEC, the localization scales, and the use (or not) of the cross-variable correlation. This hybrid 3DVar system can be operated with small additional computational cost because it has no coupling with another ensemble data assimilation system. In sensitivity experiments, this hybrid 3DVar is shown to yield smaller forecast root mean square errors than the pure 3DVar, especially for surface variables. Moreover, the hybrid 3DVar shows a better equitable threat score for strong precipitation. These improvements were greater in the experiments with larger ensemble sizes that were increased by using lagged ensemble forecasts because of the reduced sampling errors in the ensemble-based BEC. These results were sensitive to the weight given to the ensemble-based BEC and the horizontal localization scale, whose optimal values were found to be approximately 0.5 and 100 km, respectively. The longer vertical correlation scale and the cross-variable correlation were also found important to create dynamically-balanced analysis, which is especially true for heavy rain cases. [ABSTRACT FROM AUTHOR]

Geographical indication (GI) represents the specific good quality and reputation of the regional characteristics of agricultural products, which is a positive approach for stabilising the export of agricultural products, realising high quality and high prices for agricultural products and rural revitalisation. Based on the China-EU Geographical Indications Agreement, this paper discusses the differences between China and the European Union (EU) in terms of GI protection from three aspects: the institutional framework, the operational system, and the operational status of GIs. The purpose of the study is to identify the differences between China and the EU in the protection of GIs, China's shortcomings, and gaps, and to propose policy recommendations for China to protect GI products better, exploit the economic impact of GIs and enhance the competitiveness of China's exports. [ABSTRACT FROM AUTHOR]

Combining optical and synthetic aperture radar (SAR) data for crop mapping has become a crucial way to improve classification accuracy, especially in cloudy and rainy areas. However, the acquisition of optical images is significantly unstable due to the influence of cloudy and rainy weather, which seriously restricts the application of this method in practice. To solve this problem, this study proposed an optical-SAR imagery-based rice mapping method which has the advantages of less dependence on optical images, easy operation and high classification accuracy. To account for the trait of sparse availability of optical images, this method only needs one clear sky optical image in the rice growth period and combined it with multi-temporal SAR images to achieve a high accuracy rice mapping result. Meanwhile, this paper also proposed a comprehensively multi-scale segmentation parameter optimization algorithm, which considers the area consistency, shape error and location difference between the segmented object and reference object, and adopts an orthogonal experiment approach. Based on the optical image, the boundaries of the parcel objects can be segmented, which were subsequently used to perform the object-oriented classification. The results show that the overall accuracy of the proposed method in Yangzhou City is 94.64%. Moreover, according to a random pick test, it is encouraging that the proposed method has strong robustness in response to the instability of the acquisition time of SAR images. A relatively high overall accuracy of 90.09% suggested that the proposed method can provide a reliable rice mapping result in cloudy and rainy areas. [ABSTRACT FROM AUTHOR]

The regional data assimilation system at the Japan Meteorological Agency uses a variational data assimilation system based on the non-hydrostatic model ASUCA (named ASUCA-Var). This paper reviews the configurations and current status of ASUCA-Var. To consider the consistency of analysis and prognostic variables, the control variables of ASUCA-Var include soil variables and basic atmospheric variables. The background-errors based on the control variables are calculated every 3 h for land and sea grid points to better reflect the representative error covariance structure, considering daily variations and differences in structure on land and sea. Although the cost function is designed to be a perfect quadratic form, the basic field update method in the optimization process allows the nonlinearity of the observation operator and numerical weather prediction model to be incorporated into the solution of optimization problem in the incremental four-dimensional variational (4D-Var) method. The outer/inner models used in the incremental 4D-Var method are based on ASUCA, with suitable configurations according to each resolution and applied linearization. Observation operators are implemented for various kinds of observations used, with unified interfaces encapsulating external simulators. Variational quality control and variational bias correction are also introduced for advanced observation handling within the variational system. Parallelization is introduced to enhance computational efficiency, including adjoint calculations. To assess the impact of assimilated observations, degrees of freedom for signal are also available. Additionally, as a system for operational use, ASUCA-Var is designed for sustainable development. The meso-scale analysis and local analysis workflows are presented as operational implementations of ASUCA-Var. ASUCA-Var enhances forecasting in a wide range of validation indices. The major future improvements of ASUCA-Var include the introduction of the flow-dependent background-error and extension of the control variable to hydrometeors, which are expected to enhance the prediction accuracy of the operational regional model. [ABSTRACT FROM AUTHOR]

• DHI-GHM provides valuable hydrological information for data scarce areas. • DHI-GHM allows for hourly simulations, as often as new forecasts are available. • Physical based parameter estimation gives informed start for calibration activities. • DHI-GHM produces comparable results in world's main basins to other GHMs. • DHI-GHM is an operational system ideal to support decision-making. An operational global hydrological model (DHI-GHM) has been developed that provides historical, real-time, 10-day and seasonal forecast simulations at the global scale. DHI-GHM is comprised of a distributed gridded rainfall-runoff model with a spatial resolution of 0.1° and an agile kinematic routing model that moves water between model grid cells and sub-catchments and in the river system. Model output includes gridded hydrological variables, such as soil moisture content and different runoff components, and discharge at more than 1 million river points globally. DHI-GHM uses a novel parameterization scheme, where global data products of land surface physical characteristics are used to establish relations with model parameters, and thus DHI-GHM does not rely on local discharge data for model calibration. Multiple forcing datasets were tested, and the combination of ERA5 precipitation and Priestley-Taylor potential evaporation yielded the overall best results with a median KGE of 0.51 and average water balance error of 0.78% based on data from 1667 discharge stations worldwide. The model results and the operational system are particularly relevant for organizations with national, regional, or global scope who need information on large areas at once and for data scarce areas or projects without resources for local scale models. [ABSTRACT FROM AUTHOR]

The paper considers the structure of the operational system of radio equipment, determines the procedures related to the estimation of the quality parameters in the radio flight support operational system, using the ready-to-operate factor and the probability of no failure operation in a finite time interval, and shows the analytical ratios for the probability density function (PDF). [ABSTRACT FROM PUBLISHER]

REDD+ operational system is a security system which is an organic bond of application system and evaluation system. According to the relationships of each elements in REDD+ operational system, such as interaction, mutual restraint, and the characteristics of organic unity, a mathematical method was used to build a hierarchical analysis model to solve the matrix by C++ procedure. Finally our study explored the weights and prioritization of the three above elements in REDD + running system and their priority ordering. Our results indicated an important theoretical and realistic significance in ensuring the balance development of REDD+ operational system and system's evaluation standard. [ABSTRACT FROM AUTHOR]

Abstract: It is shown the development and preliminary results of operational ionosphere dynamics prediction system for the Brazilian Space Weather program. The system is based on the Sheffield University Plasmasphere–Ionosphere Model (SUPIM), a physics-based model computer code describing the distribution of ionization within the Earth mid to equatorial latitude ionosphere and plasmasphere, during geomagnetically quiet periods. The model outputs are given in a 2-dimensional plane aligned with Earth magnetic field lines, with fixed magnetic longitude coordinate. The code was adapted to provide the output in geographical coordinates. It was made referring to the Earth’s magnetic field as an eccentric dipole, using the approximation based on International Geomagnetic Reference Field (IGRF-11). During the system operation, several simulation runs are performed at different longitudes. The original code would not be able to run all simulations serially in reasonable time. So, a parallel version for the code was developed for enhancing the performance. After preliminary tests, it was frequently observed code instability, when negative ion temperatures or concentrations prevented the code from continuing its processing. After a detailed analysis, it was verified that most of these problems occurred due to concentration estimation of simulation points located at high altitudes, typically over 4000km of altitude. In order to force convergence, an artificial exponential decay for ion–neutral collisional frequency was used above mentioned altitudes. This approach shown no significant difference from original code output, but improved substantially the code stability. In order to make operational system even more stable, the initial altitude and initial ion concentration values used on exponential decay equation are changed when convergence is not achieved, within pre-defined values. When all code runs end, the longitude of every point is then compared with its original reference station longitude, and differences are compensated by changing the simulation point time slot, in a temporal adjustment optimization. Then, an approximate neighbor searching technique was developed to obtain the ion concentration values in a regularly spaced grid, using inverse distance weighting (IDW) interpolation. A 3D grid containing ion and electron concentrations is generated for every hour of simulated day. Its spatial resolution is 1° of latitude per 1° of longitude per 10km of altitude. The vertical total electron content (VTEC) is calculated from the grid, and plotted in a geographic map. An important feature that was implemented in the system is the capacity of combining observational data and simulation outputs to obtain more appropriate initial conditions to the ionosphere prediction. Newtonian relaxation method was used for this data assimilation process, where ionosonde data from four different locations in South America was used to improve the system accuracy. The whole process runs every day and predicts the VTEC values for South America region with almost 24h ahead. [Copyright &y& Elsevier]

Abstract: This work implements a Web-based Geographic Information System (Web GIS) for an existing oil spill monitoring and forecasting service, developed in the framework of the MARCOAST project. This is achieved by remotely presenting the results of the oil spill forecasting module via a dedicated Web GIS, which allows authenticated end users to view the simulation results in a geographical context. A number of Web GIS technologies for presentation of dissimilar types of semi-dynamic geographic data are applied and their respective capabilities for publishing and remote presentation of interactive geospatial information, such as oil spill spread animation overlaid on background data (terrain elevation data, satellite imagery, etc.), are described. More specifically, technologies like ESRI® ArcIMS® (Arc Internet Map Server) and Open Source GeoServer with OpenLayers client library are implemented. The capabilities of the system for visualization and mapping are illustrated by specific applications concerning the spreading scenarios of oil spills in two selected areas of the Aegean Sea, Greece. The presented Web GIS offers added value in the form of providing the end user with comprehensive and synthetic, both spatial and temporal, environmental information through a remotely customizable user-friendly graphical interface. In this context, its integration to a marine pollution monitoring and forecasting system could result in an enhanced pollution awareness and emergency management tool. [Copyright &y& Elsevier]

Abstract: This paper describes the generic data assimilation software tool DATools. DATools can be used as standalone or within Delft-FEWS. DATools is completely configurable via XML configuration. DATools is built up of three components: a Filter, a Stochastic Modeler, and a Stochastic Observer. Configuration of all these three parts is explained in detail. At the moment two data assimilation filters are available within DATools: (1) ensemble Kalman Filter and (2) the residual resampling filter. Results of a twin experiment with both filters with DATtools show similar results as a previous study performed with custom implementations. It is also shown that DATools can function inside Delft-FEWS software used for operational flood forecasting. Applying EnKF to a 1D hydrodynamic SOBEK-RE model of the river Rhine within the operational system FEWS-NL Rhine and Meuse improves the forecasts at the Lobith gaugin station and downstream of Lobith. DATools has been coupled with the HBV-96, SOBEK, and REW models and will be coupled to MODFLOW, Delft-3D, and the geotechnical model MSetlle in the near future. Uncertainty analysis with this tool is also possible and calibration will be added later this year. [Copyright &y& Elsevier]

An overview of the current operational wind wave prediction system and of new developments at the Korea Meteorological Administration (KMA) is presented. KMA has operated a numerical ocean wave prediction system since 1992. The first major upgrade was done in 1999 with the adaptation of a third-generation wave model (WAM) for both regional (ReWAM-0.25 deg resolution, covering Northeast Asia) and global (GoWAM-1.25 deg resolution) domains. In 2005, the KMA replaced its NEC SX5 computer with a 1024-CPU Cray X1E system, a Parallel Vector Processor (PVP) machine with 128 node modules. A coastal ocean wave prediction system (CoWAM) has been designed and is currently under test mode. Six CoWAM domains, each of 3 deg longitude by 2 deg latitude in size, with a mesh size of 1 km, are nested inside the regional ocean wave prediction system. The directional wave spectra at the boundaries of the CoWAM are provided from a 1/12° resolution upgraded version of the operational ReWAM. The WAVEWATCH-III code (developed at NOAA) is used for the upgraded ReWAM and new CoWAM system. To ensure the required model performance in the Massively Parallel Processor (MPP) architecture of the new supercomputer, a Message Passing Interface (MPI) has been implemented in the model source code. The sea surface wind and significant wave height are verified routinely on a monthly basis. The global moored buoy data (including the coastal buoys operated by KMA) and remote sensing data from Topex/Poseidon, and Jason (retrieved wave heights) and QuikSCAT (retrieved wind data) are used for verification of the wave prediction system. This validation and a comparison of results from the new ReWAM and CoWAM against buoy data off the coast of Korea are discussed. [ABSTRACT FROM AUTHOR]

The most important characteristic of major forest fire incidents, from a societal perspective, is their potentiality to seriously and irreversibly damage regions of significant natural beauty. In addition, the extent and severity of such incidents may significantly affect the population and the environment of the adjacent areas. Following a forest fire event, effort should be made to limit such effects. Management decisions should be based on rational and quantitative information based on the site specific circumstances and the possible consequences. To produce such information we have developed an operational system for managing large-scale wildland fire incidents. Its architecture involves an integrated framework of GIS and RDBMS technology systems equipped with interactive communication capabilities. The operational system was developed for Windows 98 platforms, for the region of Penteli Mountain Attika. The fire simulation tool of the operational system that was based on a fuzzy/neural system for the estimation of fire spread and a corresponding discrete contour propagation model for estimating fire consequences as a function of influencing factors such as terrain characteristics, vegetation type and density and meteorological conditions was presented in a related work [Appl. Math. Model. 28(2004), this issue]. Several case studies are presented to illustrate the effectiveness of the proposed approach. [Copyright &y& Elsevier]

During explosive eruptions, emergency responders and government agencies need to make fast decisions that should be based on an accurate forecast of tephra dispersal and assessment of the expected impact. Here, we propose a new operational tephra fallout monitoring and forecasting system based on quantitative volcanological observations and modelling. The new system runs at the Istituto Nazionale di Geofisica e Vulcanologia, Osservatorio Etneo (INGV-OE) and is able to provide a reliable hazard assessment to the National Department of Civil Protection (DPC) during explosive eruptions. The new operational system combines data from low-cost calibrated visible cameras and satellite images to estimate the variation of column height with time and model volcanic plume and fallout in near-real-time (NRT). The new system has three main objectives: (i) to determine column height in NRT using multiple sensors (calibrated cameras and satellite images); (ii) to compute isomass and isopleth maps of tephra deposits in NRT; (iii) to help the DPC to best select the eruption scenarios run daily by INGV-OE every three hours. A particular novel feature of the new system is the computation of an isopleth map, which helps to identify the region of sedimentation of large clasts (≥5 cm) that could cause injuries to tourists, hikers, guides, and scientists, as well as damage buildings in the proximity of the summit craters. The proposed system could be easily adapted to other volcano observatories worldwide. [ABSTRACT FROM AUTHOR]