Meteorological Network Research Articles

Rainfall and runoff time-series trend analysis using LSTM recurrent neural network and wavelet neural network with satellite-based meteorological data: case study of Nzoia hydrologic basin

This study compares LSTM neural network and wavelet neural network (WNN) for spatio-temporal prediction of rainfall and runoff time-series trends in scarcely gauged hydrologic basins. Using long-term in situ observed data for 30 years (1980–2009) from ten rain gauge stations and three discharge measurement stations, the rainfall and runoff trends in the Nzoia River basin are predicted through satellite-based meteorological data comprising of: precipitation, mean temperature, relative humidity, wind speed and solar radiation. The prediction modelling was carried out in three sub-basins corresponding to the three discharge stations. LSTM and WNN were implemented with the same deep learning topological structure consisting of 4 hidden layers, each with 30 neurons. In the prediction of the basin runoff with the five meteorological parameters using LSTM and WNN, both models performed well with respective R2 values of 0.8967 and 0.8820. The MAE and RMSE measures for LSTM and WNN predictions ranged between 11–13 m3/s for the mean monthly runoff prediction. With the satellite-based meteorological data, LSTM predicted the mean monthly rainfall within the basin with R2 = 0.8610 as compared to R2 = 0.7825 using WNN. The MAE for mean monthly rainfall trend prediction was between 9 and 11 mm, while the RMSE varied between 15 and 21 mm. The performance of the models improved with increase in the number of input parameters, which corresponded to the size of the sub-basin. In terms of the computational time, both models converged at the lowest RMSE at nearly the same number of epochs, with WNN taking slightly longer to attain the minimum RMSE. The study shows that in hydrologic basins with scarce meteorological and hydrological monitoring networks, the use satellite-based meteorological data in deep learning neural network models are suitable for spatial and temporal analysis of rainfall and runoff trends.

Verification of Regional Deterministic Precipitation Analysis Products Using Snow Data Assimilation for Application in Meteorological Network Assessment in Sparsely Gauged Nordic Basins

AbstractSparse precipitation information can result in uncertainties in hydrological modeling practices. Precipitation observation network augmentation is one way to reduce the uncertainty. Meanwhile, in basins with snowpack-dominated hydrology, in the absence of a high-density precipitation observation network, assimilation of in situ and remotely sensed measurements of snowpack state variables can also provide the possibility to reduce flow estimation uncertainty. Similarly, assimilation of existing precipitation observations into gridded numerical precipitation products can alleviate the adverse effects of missing information in poorly instrumented basins. In Canada, the Regional Deterministic Precipitation Analysis (RDPA) data from the Canadian Precipitation Analysis (CaPA) system have been increasingly applied for flow estimation in sparsely gauged Nordic basins. Moreover, CaPA-RDPA data have also been applied to establish observational priorities for augmenting precipitation observation networks. However, the accuracy of the assimilated data should be validated before being applicable in observation network assessment. The assimilation of snowpack state variables has proven to significantly improve streamflow estimates, and therefore, it can provide the benchmark against which the impact of assimilated precipitation data on streamflow simulation can be compared. Therefore, this study introduces a parsimonious framework for performing a proxy validation of the precipitation-assimilated products through the application of snow assimilation in physically based hydrologic models. This framework is demonstrated to assess the observation networks in three boreal basins in Yukon, Canada. The results indicate that in most basins, the gridded analysis products generally enjoyed the level of accuracy required for accurate flow simulation and therefore were applied in the meteorological network assessment in those cases.

Klimaticheskiye izmeneniya termicheskikh usloviy v tikhookeanskoy subarktike v usloviyakh sovremennogo global'nogo potepleniya

Purpose. The study is aimed at identifying the regional features of the surface air temperature in the coastal zone and over the Pacific Ocean (to the north of 40° N) manifested as a result of global climate changes at the turn of the XX–XXI centuries, and at assessing their trends and possible causal relationships with the processes in the atmosphere and on the ocean surface. Methods and Results. Based on the Global Meteorological Network and NOAA reanalysis data, the regional features of interannual fluctuations of the surface air temperature and their relationship with variations in the fields of pressure, wind and water temperature on the ocean surface, and with climate indices over the past 4 decades were identified. In order to determine the temperature field spatialtemporal structure and to zone the water area according to the features of climate changes, the methods of cluster, correlation analysis and the apparatus of empirical orthogonal functions were used. The results obtained made it possible to characterize the degree of heterogeneity of the studied area response to the ongoing global changes, to identify different domains and to assess quantitatively the warming rate in these water areas. Conclusions. The tendencies of modern warming are manifested in the trends of interannual air temperature variability, on the average, by ~0.20°C/10 years in the subarctic, and indicate significant regional differences (1.5–2 times) in the ongoing changes. In the west of the region, the warming rate is higher than in the east, where the temperature trends are minimal or statistically insignificant. In the warm period of a year, their values are higher than those in the cold period. The alternation phases of the warm and cold periods are consistent with the variation tendencies in the characteristics both of the atmospheric action centers and various climatic parameters. The corresponding correlations are most widely manifested in variations in the empirical orthogonal functions modes of the H500 geopotential field, and the PDO, NP, SOI, PTW, AD and EP/NP indices. Stable anomalies and trends of the ocean surface temperature in the North Atlantic also play an important role in formation of the Та anomalies in the western subarctic.

Spatial and seasonal patterns of rainfall erosivity in the Lake Kivu region: Insights from a meteorological observatory network

In the Lake Kivu region, water erosion is the main driver for soil degradation, but observational data to quantify the extent and to assess the spatial-temporal dynamics of the controlling factors are hardly available. In particular, high spatial and temporal resolution rainfall data are essential as precipitation is the driving force of soil erosion. In this study, we evaluated to what extent high temporal resolution data from the TAHMO network (with poor spatial and long-term coverage) can be combined with low temporal resolution data (with a high spatial density covering long periods of time) to improve rainfall erosivity assessments. To this end, 5 minute rainfall data from TAHMO stations in the Lake Kivu region, representing ca. 37 observation-years, were analyzed. The analysis of the TAHMO data showed that rainfall erosivity was mainly controlled by rainfall amount and elevation and that this relation was different for the dry and wet season. By combining high and low temporal resolution databases and a set of spatial covariates, an environmental regression approach (GAM) was used to assess the spatiotemporal patterns of rainfall erosivity for the whole region. A validation procedure showed relatively good predictions for most months (R2 between 0.50 and 0.80), while the model was less performant for the wettest (April) and two driest months (July and August) (R2 between 0.24 and 0.38). The predicted annual erosivity was highly variable with a range between 2000 and 9000 MJ mm ha−1 h−1 yr−1 and showed a pronounced east–west gradient which is strongly influenced by local topography. This study showed that the combination of high and low temporal resolution rainfall data and spatial prediction models can be used to improve the assessments of monthly and annual rainfall erosivity patterns that are grounded in locally calibrated and validated data.

Present and Future High-Resolution Climate Forcings over Semiarid Catchments: Case of the Tensift (Morocco)

In semiarid areas, the climate is characterized by strong spatiotemporal variability while the meteorological ground network is often very sparse. In this context, the spatial distribution of meteorological variables is thus a real issue for watershed hydrology, agronomy and the study of surface–atmosphere retroaction in these regions. The aim of this study is twofold: (1) to evaluate and to adapt a reanalysis system “Système d’Analyse Fournissant des Renseignements Adaptés à la Nivologie” (SAFRAN) to map the meteorological variables on the Tensift catchment (Morocco) between 2004 and 2014; (2) to project temperature and precipitation for the 2041–2060 horizon at high-resolution based on the Euro-CORDEX database at 12 km resolution (using two Representative Concentration Pathway -RCPs- scenarios and four Regional Climate Models), on the SAFRAN reanalysis and on a network of meteorological stations. SAFRAN was assessed: (1) based on leave-one-out for a station located in the plain and another in the mountains; (2) by comparison to another re-analysis system named the Meteorological Distribution System for High-Resolution Terrestrial Modeling (MicroMet); (3) by comparison to in situ measurements of snowfall at one station and to the daily Snow Cover Area derived from the Moderate-Resolution Imaging Spectroradiometer (MODIS) product at the catchment scale. The evaluation of the SAFRAN reanalysis showed that an irregular grid up to 1 km resolution is better for reproducing meteorological variables than the regular version of SAFRAN at 8 km, especially in mountains. The projection of the SAFRAN forcing is conducted in three steps corresponding to the three subsections below: (1) disaggregation of the Euro-CORDEX climate scenarios using the Q–Q approach based on stations data; (2) computation of the spatialized delta-change between historical and future Euro-CORDEX runs after Q–Q correction; (3) futurization of SAFRAN using the spatialized delta change values. The mountainous area is expected to face a higher increase in air temperature than the plains, reaching +2.5 °C for RCP8.5 and +1.71 °C for RCP4.5 over 2041–2060. This warming will be accompanied by a marked decrease in precipitation (−16% for RCP8.5). These present and future spatialized data sets should be useful for impact studies, in particular those focusing on water resources.

Identifying a Suitable Estimation Method for Evapotranspiration in Wasit Province

Water is one of the important natural resources due to its applicability to a broad range of contexts, the most important of which are economic and agricultural; indeed, the largest amount of water used by humans is consumed for agricultural purposes. Water resource management is thus very important to managing crises. Referential evapotranspiration constitutes a high percentage of the water consumed in agriculture, making the accurate estimation of ETo values important to determining the quantities of water required for irrigation projects. It also contributes to the planning of water investment and improving management based on predictions about the upcoming hydrological situation. The study area for the current work suffers in particular from a lack of climatic data in the Dujaila region. The focus of this study was thus on possibility of using hydrological methods that require less climatic data as compared to the Penman-Monteith equation to estimate evapotranspiration accurately. The reference evapotranspiration was estimated using the Penman-Monteith (PM-FAO-56), Jensen-Haise, Blaney Criddle, Kharrufa and Hargreaves equations, utilising climate data from the Al Kut Meteorological Station and the Agricultural Meteorological Network for the period 2013 and 2018. The other results then were compared with the reference Penman-Monteith equation in terms of the determination coefficient and mean absolute; overall, the Hargreaves equation was found to be most accurate for predicting the value of ETo, with the values of R2 and MAPE being 0.995 and 6.2%, respectively.

Achieving High Reliability in Data Acquisition

An urban environment defines a specific micro-climate which directly affects the quality of life in urbanized areas and often has a negative impact on urban populations. Phenomena like urban heat and surface heat islands are direct products of an urban lifestyle. Urban meteorological networks (UMNs) are a tool that can help to better understand and analyze the current situation and make the right decisions about future urban development. Deployed to monitor and record different objects and their states inside urban areas, UMNs build a long-term meteorological data time series database. The most commonly used systems for achieving this goal include wireless sensor networks (WSNs). This paper presents a combined experience in deploying three different WSN systems. During seven years of research in this field, the authors have recognized the importance of data reliability in data acquisition. More importantly, due to the lack of research addressing the reliability of the data received from WSNs by the core segment of the server (processes used in receiving, validating, parsing, and storing data into a database instance), the received data are used in scientific studies without questioning their reliability. To determine the possibility of shifting information provided by the data measured from sensor networks before it is stored in a desired form of database, this paper proposes a highly reliable socket server model. The model is built with high reliability and performance in mind and it includes three major processes, which use a combination of signals and control messages to pass information about their states. A case study is performed using high-end hardware, running a Linux operating system stressed to its limits. Repetition testing revealed inconsistency in the information provided by the operating system to the application layer, which could lead to the loss of information about short-term and rarely occurring monitored objects. The results lead to the conclusion that there is a clear need for a higher level of data reliability in the process of data acquisition by UMNs. The proposed socket server should fill this gap within the server’s core segment.

Testing Evapotranspiration Estimates Based on MODIS Satellite Data in the Assessment of the Groundwater Recharge of Karst Aquifers in Southern Italy

In many Italian regions, and particularly in southern Italy, karst aquifers are the main sources of drinking water and play a crucial role in the socio-economic development of the territory. Hence, estimating the groundwater recharge of these aquifers is a fundamental task for the proper management of water resources, while also considering the impacts of climate changes. In the southern Apennines, the assessment of hydrological parameters that is needed for the estimation of groundwater recharge is a challenging issue, especially for the spatial and temporal inhomogeneity of networks of rain and air temperature stations, as well as the variable geomorphological features and land use across mountainous karst areas. In such a framework, the integration of terrestrial and remotely sensed data is a promising approach to limit these uncertainties. In this research, estimations of actual evapotranspiration and groundwater recharge using remotely sensed data gathered by the Moderate Resolution Imaging Spectrometer (MODIS) satellite in the period 2000–2014 are shown for karst aquifers of the southern Apennines. To assess the uncertainties affecting conventional methods based on empirical formulas, the values estimated by the MODIS dataset were compared with those calculated by Coutagne, Turc, and Thornthwaite classical empirical formulas, which were based on the recordings of meteorological stations. The annual rainfall time series of 266 rain gauges and 150 air temperature stations, recorded using meteorological networks managed by public agencies in the period 2000–2014, were considered for reconstructing the regional distributed models of actual evapotranspiration (AET) and groundwater recharge. Considering the MODIS AET, the mean annual groundwater recharge for karst aquifers was estimated to be about 448 mm·year−1. In contrast, using the Turc, Coutagne, and Thornthwaite methods, it was estimated as being 494, 533, and 437 mm·year−1, respectively. The obtained results open a new methodological perspective for the assessment of the groundwater recharge of karst aquifers at the regional and mean annual scales, allowing for limiting uncertainties and taking into account a spatial resolution greater than that of the existing meteorological networks. Among the most relevant results obtained via the comparison of classical approaches used for estimating evapotranspiration is the good matching of the actual evapotranspiration estimated using MODIS data with the potential evapotranspiration estimated using the Thornthwaite formula. This result was considered linked to the availability of soil moisture for the evapotranspiration demand due to the relevant precipitation in the area, the general occurrence of soils covering karst aquifers, and the dense vegetation.

帝国日本の気象観測網拡大と梅雨研究 (特集 近現代の気象学における観測とシミュレーション)

帝国日本の気象観測網拡大と梅雨研究 (特集 近現代の気象学における観測とシミュレーション)

Analysis of air temperature dynamics in the "local climate zones" of Novi Sad (Serbia) based on long-term database from an urban meteorological network.

A comprehensive analysis of air temperature (Ta) dynamics in "local climate zones" (LCZs) of Novi Sad (Serbia) was based on measurements from 17 stations during 3years. Hourly changes of Ta, cooling rates (CR), heating rates (HR), and urban heat island (UHI) intensity were assessed on seasonal and annual level and during heat wave (HW) and cold wave (CW) periods. Substantial differences are observed for minimum (Tmin) and mean temperatures (Tmean) between LCZs. Two-phase nocturnal cooling was recognized with the first cooling phase characterized by intensive LCZ dependent cooling starting at 1-3h before sunset and lasting until 3-4h after sunset. The second cooling phase lasts until sunrise and is characterized by less intensive and LCZ nondependent cooling. The most intensive cooling (CRpeak) was observed in first cooling phase of HW and ranged from - 1.6°Ch-1 in street canyon (LCZ 2) to - 3.9°Ch-1 in forest (LCZ A). Furthermore, a new cooling indicator (CRtotal) was introduced. Due to cooling differences, the most intensive UHI of 5.5°C was noticed between LCZs 2 and A at sunset + 1h during HW. Two-phase diurnal heating was also recognized in LCZs with the first heating phase characterized by intensive LCZ dependent heating starting at sunrise and lasting until 4-7h afterwards. The most intensive heating (HRpeak) ranged from 2.0°Ch-1 in street canyon to 3.0°Ch-1 in industrial area (LCZ 8) during HW. The second heating phase lasts until sunset and is characterized by less intensive heating and smaller HR differences between LCZs.

История становления метеорологических наблюдений на востоке России и в ряде восточных странах

Introduction. The article reviews the history of the origin and development of meteorological observations in the East of Russia and some Eastern countries of Eurasia. Goals. The paper seeks not just to describe the sequence of events from the history of the development of meteorology as a science in the East, but rather to find patterns that lead to the chain of research on the nature of the region, identify the main stages or periods thereof, consider and clarify the development of meteorology in the East of Russia and Eastern Eurasia. Materials. The work employs a set of complementary research methods, such as theoretical analysis of geographical and historical literature on the problem under consideration; provides insights into archival materials and published sources; conducts comparative analysis of events from the history of the origin and development of meteorological science on the Eastern borders of our country. Conclusions. The study of archival materials and published sources made it possible to determine trends in the development of meteorological research in the region. The article primarily focuses on the influence of the Beijing Magnetic Meteorological and Main Physical Observatories on the emergence and development of the meteorological network of the East.

Citizen weather stations data for monitoring applications and urban climate research: an example of Moscow megacity

This study considers experience in use of crowdsourced meteorological observations from the world’s biggest network of citizen weather stations (CWSs), Netatmo, for urban climate research and applied monitoring services on the example of Moscow megacity. Crowdsourcing paradigm is an emerging alternative to the development of expensive urban meteorological networks. We have experimentally evaluated the uncertainties of the Netatmo temperature observations and regard them as being acceptable when the stations are shadowed from the sun. In order to filter out the misrepresentative observations, a quality-control algorithm has been developed. Within more than 1500 CWSs in the Moscow region, only about 25% meet this quality control, which is still one order of magnitude higher than the number of official Roshydromet weather stations in the study area. Such amount of data opens new opportunities for spatially-resolving urban climate studies and for applied services. As an example of the latter, we present a prototype of a web-mapping application for a near-real-time temperature monitoring system in Moscow. The application’s backend includes automatic services for downloading of observations from Netatmo and official Roshydromet networks, as well as for database maintaining. The processed data are visualized interactively in a web browser. The application is available on the Internet at http://carto.geogr.msu.ru/mosclim/. It will be further developed to include a real-time thermal comfort assessment based on the contemporary PET and UTCI biometeorological indices, a visualization of the interpolated fields, and other improvements.

Mezhgodovaya izmenchivost' termicheskikh usloviy vo vnetropicheskoy zone yuzhnoy chasti Tikhogo okeana na rubezhe XX–XXI vekov

Purpose. The aim of the study consists in identifying the spatial-temporal features of interannual changes in the surface air temperature Ta, the sea surface temperature (SST) and the upper 1000-meter water layer temperature Tw in the extratropical zone of the South Pacific Ocean over the past four decades, which are manifested as a result of the planetary changes and a shift in the climatic regime at the turn of the XX–XXI centuries. Besides, the revealed features’ trends and their possible cause-and-effect relationships with the processes in the atmosphere and on the ocean surface are planned to be assessed. Methods and Results. Based on the Global Meteorological Network and Reanalysis data (NOAA), regional features and trends of the water and air temperature interannual fluctuations, and their relation to variations in the pressure and wind fields, intensity of the atmosphere action centers (AAC) and climatic indices (CI) over the past 4 decades have been determined. Applied were the methods of the cluster, correlation and regression analysis, as well as the apparatus of empirical orthogonal functions (EOF). The positive trends in changes of the Ta and SST fields are manifested mainly in the northwestern part of the region, where they are statistically significant and reach their maximum 0.4–0.6°C over 10 years in the Tasman Sea region and to the northeast of New Zealand. The water areas with minimal, negative or insignificant values of the air and water temperature trends are located on the southern and eastern peripheries of the water area under study – in the areas of influence of cold currents. Over the entire investigated water area, the trends in the mean annual SST and Ta were ~ 0.04–0.06°C/10 years that are 2–3 times less than those in the subarctic region of the North Pacific Ocean. The features of spatial-temporal variability of the water temperature trends at different horizons differ significantly from the characteristics of the SST trends. The trends’ spatial distribution is already transformed within the upper 200-m layer; and deeper, maximums of this value are observed in the southeastern part of the water area. Conclusions. The results obtained made it possible to characterize the degree of heterogeneity of response of the atmosphere surface layer, SST and vertical distribution of Tw in the extratropical zone of the South Pacific to the ongoing global changes, to identify the isolated areas, to estimate quantitatively the warming rate in these water areas, and to compare these estimates with those of the other regions in the Pacific Ocean. It is shown that the individual phases of alternation of the warm and cold periods in the interannual temperature variation are consistent with the changes of the regional CI and the AAC state; this fact emphasizes the inhomogeneous nature of these processes in space and time.

Overhauling the Activities of Ghana Meteorological Agency through ICT

Faced with the growing risks of weather and climate disasters to economic and social development, the global community needs to act quickly to strengthen National Meteorological and Hydrological Services. This strengthening must be done in a way that transforms the agency, especially in developing Ghana into a robust professional agency capable of delivering the right information to the right people at the right time. Although the cost of modernizing and sustaining the Ghana Meteorological Agency will be huge, the rewards for Ghana and its citizens will be much significant. This analytical work assesses the Ghana Meteorological Agency (GMET) for Hydrometeorology based on the user community needs. The analysis identifies gaps and challenges such as a deterioration of hydro meteorological observation networks and outdated technologies, and a lack of modern equipment and forecasting methods in producing and delivering weather, climate and hydrological information and services, and it lays out a technical technological and strategic framework for policy and decision makers in the Ministry of communication and the government at large. The Road Map postulates three scenarios, which are institutional strengthening and capacity building; modernization of observation, ICT and forecasting infrastructure; and enhancement of service delivery system for modernizing the GMET based on the potential cost and benefits of each while aiming at a greater national, regional and public good. The proposed scenarios target the GMET capacity: (i) to produce, manage, translate and communicate hydro-meteorological information to the user community; (ii) to assist the community in accessing, interpreting and using the information; (iii) to better disseminate and respond to warnings for public safety and economic security; (iv) to inform planning and decision making for cost-effective investments in climate-resilient development; and empowering its human resource; (v) identify red zone regions with these muddles. Strengthening these five pillars can help solidify Ghana’s resilience to natural hazards and climate change and help enhance the economic performance of such weather dependent sectors as agriculture, energy, transport and water resources management. This study recommends that, low-cost, high-priority activities are provided to achieve critical minimal capabilities to provide weather, climate and hydrological services and monetary investments are also needed to facilitate full modernization and bring the Ghana Meteorological Agency to the level of advanced middle income countries’ capabilities for providing data, forecasts and warning services to meet user needs. Keywords: Hydro-meteorological, Overhauling, ICT, Modernization, Sustainability.

Soil electrical resistivity monitoring as a practical tool for evaluating irrigation systems efficiency at the orchard scale: a case study in a vineyard in Central Chile

In many orchards, irrigation scheduling is designed based on data from meteorological networks and considering homogeneous soil properties. Such assumptions may result in inefficient irrigation, which is difficult to constrain without expensive or invasive techniques. Here we have evaluated the ability of the electrical resistivity tomography (ERT) for detecting meter-scale irrigation uniformity and deep percolation during irrigation. The spatiotemporal variability of soil volumetric water content (VWC) in a vineyard located near Santiago (Chile) was inferred using ERT monitoring of two irrigation cycles. The electrical resistivity structure up to 4 m depth was estimated using two-dimensional inversion of ERT data. ERT results were verified by comparing resistivity models with VWC measured with soil moisture sensors, soil properties mapped in a 2 m-depth soil pit, and the spatiotemporal evolution of VWC obtained by solving numerically Richards equation. Largest temporal variations of resistivity were observed within the root depth (1 m) and are consistent with expected relative changes in VWC during irrigation. ERT images exhibit lateral changes in resistivity at these depths, likely indicating non-uniform infiltration of water controlled by observed soil texture variations. Resistivity changes were also observed below the root zone, suggesting that a fraction of the irrigation water percolates downward. These findings can be explained by an excess of irrigation water applied during the monitoring, which was planned considering regional evapotranspiration (ET) data that overestimated the actual ET measured at the vineyard. Altogether, our results suggest that ERT monitoring during irrigation is a cost-effective tool to constrain the performance of irrigation systems.

Understanding the dynamical-microphysical-electrical processes associated with severe thunderstorms over the Beijing metropolitan region

The Dynamical-microphysical-electrical Processes in Severe Thunderstorms and Lightning Hazards (STORM973) project conducted coordinated comprehensive field observations of thunderstorms in the Beijing metropolitan region (BMR) during the warm season from 2014 to 2018. The aim of the project was to understand how dynamical, microphysical and electrical processes interact in severe thunderstorms in the BMR, and how to assimilate lightning data in numerical weather prediction models to improve severe thunderstorm forecasts. The platforms used in the field campaign included the Beijing Lightning Network (BLNET, consisting of 16 stations), 2 X-band dual linear polarimetric Doppler radars, and 4 laser raindrop spectrometers. The collaboration also made use of the China Meteorological Administration’s mesoscale meteorological observation network in the Beijing-Tianjin-Hebei region. Although diverse thunderstorm types were documented, it was found that squall lines and multicell storms were the two major categories of severe thunderstorms with frequent lightning activity and extreme rainfall or unexpected local short-duration heavy rainfall resulting in inundations in the central urban area, influenced by the terrain and environmental conditions. The flash density maximums were found in eastern Changping District, central and eastern Shunyi District, and the central urban area of Beijing, suggesting that the urban heat island effect has a crucial role in the intensification of thunderstorms over Beijing. In addition, the flash rate associated with super thunderstorms can reach hundreds of flashes per minute in the central city regions. The super (5% of the total), strong (35%), and weak (60%) thunderstorms contributed about 37%, 56%, and 7% to the total flashes in the BMR, respectively. Owing to the close connection between lightning activity and the thermodynamic and microphysical characteristics of the thunderstorms, the lightning flash rate can be used as an indicator of severe weather events, such as hail and short-duration heavy rainfall. Lightning data can also be assimilated into numerical weather prediction models to help improve the forecasting of severe convection and precipitation at the cloud-resolved scale, through adjusting or correcting the thermodynamic and microphysical parameters of the model.

Agricultural Drought Monitoring by MODIS Potential Evapotranspiration Remote Sensing Data Application

The current Polish Agricultural Drought Monitoring System (ADMS) adopted Climatic Water Balance (CWB) as the main indicator of crop losses caused by drought conditions. All meteorological data needed for CWB assessment are provided by the ground meteorological stations network. In 2018, the network consisted of 665 stations, among which in only 58 stations full weather parameters were registered. Therefore, only these stations offered a possibility to estimate the exact values of potential evapotranspiration, which is a component of the CWB algorithm. This limitation affects the quality of CWB raster maps, interpolated on the basis of the meteorological stations network for the entire country. However, the interpolation process itself may introduce errors; therefore, the adaptation of satellite data (that are spatially continuous) should be taken into account, even if the lack of data due to cloudiness remains a serious problem. In this paper, we involved the remote sensing data from MODIS instrument and considered the ability to integrate those data with values determined by using ground measurements. The paper presents results of comparisons for the CWB index assessed using ground station data and those obtained from potential evapotranspiration as the product from Moderate Resolution Imaging Spectroradiometer (MODIS) remote sensing instrument. The comparisons of results were performed for specific points (locations of ground stations) and were expressed by differences in means values. Analysis of Pearson’s correlation coefficient (r), Mann–Kendal trend test (Z-index), mean absolute error (MAE) and root mean square error (RMSE) for ten years’ series were evaluated and are presented. In addition, the basic spatial interpretation of results has been proposed. The correlation test revealed the r coefficient in the range from 0.06 to 0.68. The results show good trend agreement in time between two types of CWB with constantly higher values of this index, which is estimated using ground measurement data. In results for 34 (from 43 analyzed) stations the Mann–Kendal test provide the consistent trend, and only nine trends were inconsistent. Analyses revealed that the disagreement between the two considered indices (determined in different ways) increased significantly in the warmer period with a significant break point between R7 and R8 that falls at the end of May for each examined year. The value of MAE varied from 80 mm to 135 mm.

Daily evolution of urban heat islands in a Brazilian tropical continental climate during dry and rainy periods

High temperatures are typically recorded in tropical continental climate regions, with heat intensified by urban heat islands. This research attempts to investigate the intensity and maintenance of heat islands in the lower atmosphere and their spatial distribution during different periods of the day using multicriteria modeling. The present study was conducted in Presidente Prudente city, located west of São Paulo State, Brazil, between south latitudes 22°18′ and 22°06′ and west longitudes 51°47′ and 51°34′; its 2019 population is estimated at 228,743 inhabitants (IBGE, 2019). Air temperature and humidity data were recorded by a meteorological network comprising 26 points distributed throughout the intraurban and surrounding country. Data collection took place during both the dry and rainy seasons' most representative months (August and December 2015, respectively), in evenly spaced periods of the day (0 h, 3 h, 6 h, 9 h, 12 h, 15 h, 18 h, and 21 h). For the integration of primary and secondary data, descriptive statistics of simple and multiple linear regression were adopted. Results show that the heat islands' magnitude and continuity in different periods of the day vary according to surface characteristics (land use, relief, and vegetation) and the city's climatic seasonality. The highest and lowest magnitudes were recorded during the dry rainy season, respectively. It is believed that urban heat islands analysis will enable the subsidizing of territorial management and urban planning, and it will lead to a healthier development of cities, which will enhance societal sustainability.

Improving ANN-based streamflow estimation models for the Upper Indus Basin using satellite-derived snow cover area

The mountainous catchments often witness contrasting regimes and the limited available meteorological network creates uncertainty in both the hydrological data and developed models. To overcome this problem, remotely sensed data could be used in addition to on-ground observations for hydrological forecasting. The fusion of these two types of data gives a better picture and helps to generate adequate hydrological forecasting models. The study aims at the improvement of ANN-based streamflow estimation models by using an integrated data-set containing, the satellite-derived snow cover area (SCA) with on-ground flow observations. For this purpose, SCA of three sub catchments of Upper Indus Basin, namely Gilgit, Astore and Bunji coupled with their respective gauge discharges is used as model inputs. The weekly stream-flow models are developed for inflows at Besham Qila located just upstream of Tarbela dam. The data-set for modeling is prepared through normalizing all variables by scaling between 0 and 1. A mathematical tool, Gamma test is applied to fuse the inputs, and a best input combination is selected on the basis of minimum gamma value. A feed forward neural network trained via two layer Broyden Fletcher Goldfarb Shanno algorithm is used for model development. The models are evaluated on the basis of set of performance indicators, namely, Nash–Sutcliffe Efficiency, Root Mean Square Error, Variance and BIAS. A comparative assessment has also been made using these indicators for models developed, through data-set containing gauge discharges, only and the data-set fused with satellite-derived SCA. In particular, the current study concluded that the efficiency of ANN-based streamflow estimation models developed for mountainous catchments could be improved by integrating the SCA with the gauge discharges.

Weather Radar Network Benefit Model for Nontornadic Thunderstorm Wind Casualty Cost Reduction

AbstractAn econometric geospatial benefit model for nontornadic thunderstorm wind casualty reduction is developed for meteorological radar network planning. Regression analyses on 22 years (1998–2019) of storm event and warning data show, likely for the first time, a clear dependence of nontornadic severe thunderstorm warning performance on radar coverage. Furthermore, nontornadic thunderstorm wind casualty rates are observed to be negatively correlated with better warning performance. In combination, these statistical relationships form the basis of a cost model that can be differenced between radar network configurations to generate geospatial benefit density maps. This model, applied to the current contiguous U.S. weather radar network, yields a benefit estimate of $207 million (M) yr−1 relative to no radar coverage at all. The remaining benefit pool with respect to enhanced radar coverage and scan update rate is about $36M yr−1. Aggregating these nontornadic thunderstorm wind results with estimates from earlier tornado and flash flood cost reduction models yields a total benefit of $1.12 billion yr−1 for the present-day radars and a remaining radar-based benefit pool of $778M yr−1.