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Offshore waters provide resources for human beings, while on the other hand, threaten them because of marine disasters. Ocean stations are part of offshore observation networks, and the quality of their data is of great significance for exploiting and protecting the ocean. We used hourly mean wave height, temperature, and pressure real-time observation data taken in the Xiaomaidao station (in Qingdao, China) from June 1, 2017, to May 31, 2018, to explore the data quality using eight quality control methods, and to discriminate the most effective method for Xiaomaidao station. After using the eight quality control methods, the percentages of the mean wave height, temperature, and pressure data that passed the tests were 89.6%, 88.3%, and 98.6%, respectively. With the marine disaster (wave alarm report) data, the values failed in the test mainly due to the influence of aging observation equipment and missing data transmissions. The mean wave height is often affected by dynamic marine disasters, so the continuity test method is not effective. The correlation test with other related parameters would be more useful for the mean wave height. [ABSTRACT FROM AUTHOR]

Interaction between adverse weather conditions and motor vehicle crashes is an important topic for traffic engineers and hydrometeorologists. With the recent availability of high resolution precipitation products (hourly, 4 × 4 km), it is possible to evaluate crash risk during rainfall events more accurately. Texas, the second largest state in the U.S., with a relatively high population density in its eastern part that receives significant rainfall from tropical events, experiences many hazardous traffic conditions every year. This study investigates temporal and spatial variability of the Relative Accident Risk (RAR) due to rainy conditions across Texas during the year 2015 using a Crash-Based Matched Pairs Analysis (CB-MPA) approach for every 4 × 4 km grid using an hourly time scale. The overall findings show that rainfall increases crash risk across the state by about 57%, while seasonal-based analysis confirms the role of precipitation patterns on crash rates. Although eastern and central counties (wetter and more urbanized) have remarkably higher rates of crash occurrence, the western counties (mainly rural and dry) show higher RAR values. Moreover, higher rainfall intensity can increase RAR up to three-fold while directly having an adverse effect on crash injury type. There is a relatively high correlation between rainfall intensity and RAR values (R 2  = 0.76). The analysis also shows higher RAR values on high-speed interstate highways and tollways compared to urban local streets. RAR values also vary according to the gender and age of drivers. The study findings shed light on future paths toward more detailed applications of high-resolution environmental data in crash risk analysis. [ABSTRACT FROM AUTHOR]

The contemporary trend in the degradation of arable southern chernozems (Haplic Chernozems Pachic) in the steppe zone of south-eastern European Russia under the impact of water erosion has been evaluated based on a field study of changes in the deposition rate of eroded products on the bottoms of the currently stable negative landforms within a small catchment (1.92 km2 in area) with almost completely tilled slopes in the west of Orenburg oblast, in the basin of the Samara River (a left tributary of the Volga River). The dating of deposited sediments and the analysis of their temporal dynamics have been performed using the radioactive isotope 137Cs as a chronomarker. The results of a thorough analysis of catchment topography, grain size distribution data on soils and sediments, hydrometeorological observations, and satellite data have been used. It is found that the mean accumulation rate of chernozem erosion products on the bottom of a small catchment valley was 1.9-2.0 cm/year (16.5-28.4 kg/m2 annually) during the period of 1959-1986 (4.2-4.8 cm/year, or 30.4-83.5 kg/m2 annually in 1959-1963) compared to only 0.52-0.68 cm/year, or 6.6-11.9 kg/m2 annually, during the period of 1986-2016; i.e., the thickness of deposited sediments decreased at least by 3.0-3.6 times, and their mass decreased by 2.0-4.3 times (2.9 times on the average). It is shown that the main reason for the presumed significant decrease in the erosion rate of southern chernozems in the region during the last decades was the reduction in surface water runoff from slopes during the spring snowmelt period, as well as the probable change in the structure of crop rotation toward some increase in the share of perennial grasses, and erosion control measures. [ABSTRACT FROM AUTHOR]

This study presents results from the Weather Research and Forecasting (WRF) model applied for climatological downscaling simulations over highly complex terrain along the Eastern Mediterranean. We sequentially downscale general circulation model results, for a mild and wet year (2003) and a hot and dry year (2010), to three local horizontal resolutions of 9, 3 and 1 km. Simulated near-surface hydrometeorological variables are compared at different time scales against data from an observational network over the study area comprising rain gauges, anemometers, and thermometers. The overall performance of WRF at 1 and 3 km horizontal resolution was satisfactory, with significant improvement over the 9 km downscaling simulation. The total yearly precipitation from WRF's 1 km and 3 km domains exhibited < 10% bias with respect to observational data. The errors in minimum and maximum temperatures were reduced by the downscaling, along with a high-quality delineation of temperature variability and extremes for both the 1 and 3 km resolution runs. Wind speeds, on the other hand, are generally overestimated for all model resolutions, in comparison with observational data, particularly on the coast (up to 50%) compared to inland stations (up to 40%). The findings therefore indicate that a 3 km resolution is sufficient for the downscaling, especially that it would allow more years and scenarios to be investigated compared to the higher 1 km resolution at the same computational effort. In addition, the results provide a quantitative measure of the potential errors for various hydrometeorological variables. [ABSTRACT FROM AUTHOR]

Data collected using the micro rain radar (MRR) situated in Jinan city, eastern China, were used to explore the altitudinal and temporal evolution of rainfall microphysical characteristics, and to analyze the bright band (BB) characteristics and hydrometeor classification. Specifically, a low-intensity and stable stratiform precipitation event that occurred from 0000 to 0550 UTC 15 February 2015 and featured a BB was studied. During this event, the rainfall intensity was less than 2 mm h at a height of 300 m, which was above the radar site level, so the errors caused by the vertical air motion could be ignored. The freezing height from the radiosonde matched well with the top of the BB observed by the MRR. It was also found that the number of 0.5-1 mm diameter drops showed no noticeable variation below the BB. The maximum fall velocity and the maximum gradient fall velocity (GFV) of the raindrops appeared at the bottom of the BB. Meanwhile, a method that uses the GFV and reflectivity to identify the altitude and the thickness of the BB was established, with which the MRR can provide a reliable and real-time estimation of the 0°C isotherm. The droplet fall velocity was used to classify the types of snow crystals above the BB. In the first 20 min of the selected precipitation event, graupel prevailed above the BB; and at an altitude of 2000 m, graupel also dominated in the first 250 min. After 150 min, the existence of graupel and dendritic crystals with water droplets above the BB was inferred. [ABSTRACT FROM AUTHOR]

The present investigation was conducted to analyse the trends in hydrometeorological data to addresses how these trends impacted on the water extent of Wular Lake, Kashmir. Temporal changes in the lake surface area have been analysed, using the Landsat satellite data. The nonparametric Mann–Kendall and Sen’s methods were used to determine trends in hydrometeorological data. In addition, trends in extreme indices of frost days (FD), summer days, days with rainfall > 10 mm (R10), days with rainfall > 20 mm (R20) and dry spell for temperature and precipitation were also analysed. The results suggest an overall decrease in extreme rainfall events, R10 and R20, and annual precipitation pattern with increase in maximum and minimum annual average temperatures. Furthermore, the analysis of extreme temperature events suggests warming trend with increased number of warm days and decreased number of FD. With regard to water extent of the lake, an intense decreasing trend was observed. [ABSTRACT FROM PUBLISHER]

A comprehensive hydrometeorological and glaciological data set is presented, originating from a multitude of recordings at several intensively operated research sites in the Rofental (1891-3772 m a.s.l., Ötztal Alps, Austria). The data sets are spanning a period of 150 years and hence represent a unique, worldwide unprecedented pool of high mountain observations. Their collection has originally been initiated to support the scientific investigation of the glaciers Hintereis-, Kesselwand- and Vernagtferner. Later, additional measurements of meteorological and hydrological variables have been undertaken; data now comprise records of temperature, relative humidity, short- and longwave radiation, wind speed and direction, air pressure, precipitation and water levels. For the glaciers, annual mass balance, glacier front variation and flow velocities as well as photographic images of the glacier status have been recorded. Since 2001, a series of distributed (airborne and terrestrial) laserscans has been processed. Most recently, a permanent terrestrial laser scanner installed on "Im hintern Eis" (3244 m a.s.l.) enables to continuously observe almost the entire area of Hintereisferner. The data and research undertaken at the sites of investigation enable combined research of atmospheric, cryospheric and hydrological processes in complex terrain, and support the development of several state-of-the art hydroclimatological and glacier mass balance models. The institutions taking part in the Rofental research framework have joined to a cooperation consortium and promote their site in several international research initiatives. In the framework of INARCH, all original research data sets are now provided to the scientific community according to the Creative Commons Attribution License by means of the PANGAEA repository (https://doi.org/doi:10.1594/PANGAEA.876120). [ABSTRACT FROM AUTHOR]

Climate change is expected to alter the frequency and intensity of extreme rainfall events, affecting the rainfall intensity-durationfrequency (IDF) curve information used in the design, maintenance, and operation of water infrastructure in Canada. Presented in this study are analyses of precipitation data from 567 Environment Canada hydro-meteorological stations using the web-based IDF_CC tool, which applies a novel equidistance quantile-matching downscaling method to generate future IDF curve information. Results for the year 2100 based on The Second Generation Canadian Earth System Model (CanESM2) and a multimodel ensemble median of 24 global climate models (GCMs) were generated. A natural neighbor spatial interpolation method was used to generate results for ungauged locations. One in 5-year, 2-h and one in 100-year, 24-h precipitation events were explored. Results based on CanESM2 indicated a reduction in extreme precipitation in central regions of Canada under specific analyses and increases in other regions. Relative to the multimodel ensemble median approach, the CanESM2 results suggested more spatial variability in change of IDFs, and the ensemble median generated generally lower values than CanESM2. By using the median value that lowers the importance of extreme outputs, the ensemble median approach obscured uncertainty associated with GCM outputs. While the IDF_CC tool helps fill an important gap related to accessing local climate change information, it is important to consider uncertainty in GCM outputs when making climate change adaptation decisions. [ABSTRACT FROM AUTHOR]

ABSTRACT Interpolating soil moisture at the regional scale (104-107 km2) is challenging because in situ observations tend to be sparse, and hydrometeorological conditions and soil characteristics have significant spatial variability. This study is the first to apply the reduced optimal interpolation ( ROI) method to soil moisture. The ROI method uses both in situ and variable infiltration capacity ( VIC) simulated-soil moisture to generate interpolated soil moisture surfaces in Oklahoma. The ROI method is based on an empirical orthogonal function ( EOF) analysis that identifies the leading spatial modes of soil moisture variation based on the model simulation and then applies these EOFs using the temporal variations in the observed soil moisture. The interpolated soil moisture surfaces generated using ROI are compared with Cokriging, which also uses VIC simulations as a secondary input, and the inverse distance weighting ( IDW) approach. The accuracy of all three interpolation methods are evaluated using soil moisture measurements from 65 stations. The ROI method is significantly more accurate than IDW and it also outperforms Cokriging. We demonstrate that ROI can be used to accurately depict the spatial patterns of soil moisture at the local and regional level. [ABSTRACT FROM AUTHOR]

The article offers information on the weather and climate in Russia in 2015. Topics mentioned include the hydrometeorological observations performed at Roshydromet Observation Network, the averaged air temperature in the country, as well as the precipitation, the weather events recorded such as strong winds and heavy rain, and the damage caused by weather anomalies.

Based on daily precipitation data for 1951–2009 from 18 hydrometeorological stations all over the Crimean peninsula, a 58-year data series of extreme precipitation parameters (precipitation concentration, level of extreme precipitation and number of days with extreme precipitation) were calculated. Linear trends of calculated parameters are estimated in this paper. Manifestations of the Pacific decadal oscillation (PDO) of the extreme precipitation changes were analyzed. The precipitation concentration is found to increase in the Crimean Mountains region in the winter season, but in the summer season the precipitation concentration is characterized by uniform distribution. Linear trends of the winter and summer precipitation concentration during the last 58 years are predominantly negative over Crimea. The maximum values of precipitation level in the winter season are typical for the Crimean Mountains region. In the summer season, values of precipitation change insignificantly. The number of days with extreme precipitation exhibits decreasing trends in the winter season over the territory of Crimea. In the summer season, the number of days with extreme precipitation in south-eastern part of Crimea has increasing trends. The negative PDO phase in the winter season was found to accompany increased precipitation concentration (up to 11%) all over Crimea and by decreased concentration (up to 4%) in the summer season in central, southern, and eastern regions of Crimea. The number of extreme precipitation days in the winter season is up to 30% higher in the negative PDO phase over the whole territory of Crimea, while in the summer it is up to 60% lower in the south-eastern part of peninsula. [ABSTRACT FROM AUTHOR]

This paper presents a study to develop a heat index, for use in hot and humid sub-tropical climate in Hong Kong. The study made use of hospitalization data and heat stress measurement data in Hong Kong from 2007 to 2011. The heat index, which is called Hong Kong Heat Index (HKHI), is calculated from the natural wet bulb temperature, the globe temperature, and the dry bulb temperature together with a set of coefficients applicable to the high humidity condition in the summer of Hong Kong. Analysis of the response of hospitalization rate to variation in HKHI and two other heat indices, namely Wet Bulb Globe Temperature (WBGT) and Net Effective Temperature (NET), revealed that HKHI performed generally better than WBGT and NET in reflecting the heat stress impact on excess hospitalization ratio in Hong Kong. Based on the study results, two reference criteria of HKHI were identified to establish a two-tier approach for the enhancement of the heat stress information service in Hong Kong. [ABSTRACT FROM AUTHOR]

ABSTRACT In hydrometeorological prediction systems, meteorological real-time data and forecast data from numerical weather prediction models are needed as input for hydrological and hydraulic models. This paper evaluates the application of a validated hydrological-hydraulic model chain by using real-time operationally available precipitation-forcing datasets as a benchmark. The analyses should detect the problems occurring once the prediction system will leave the calibration environment and need to be reconfigured for real-time deployment. The precipitation-forcing benchmarks used for 2013 were rain gauge measurements, quantitative radar estimates, quantitative precipitation estimates ( QPE) and a radar-rain gauge merged precipitation product generated by spatio-temporal co-kriging (with external drift). The discharge was simulated in a transnational river basin in southern Switzerland and northern Italy. The best discharge simulation results were obtained when rain gauge data from automatic measurement stations were used as meteorological input for the models, because these were used for the model calibration. The modelled radar QPE greatly underestimated the rainfall volume, and thus the simulated discharge, because the raw radar time series were too short for calibration. Therefore, quantile mapping was applied to post-process the radar QPE. Quantile mapping, as applied in this work with relatively short available radar-only precipitation records, appears to be unsuitable for operational use, but adequate as a post-processing method for past data series. Combining the rain gauge and radar QPE improved simulations significantly compared with the original radar QPE. A lower performance was found in the Italian region because the meteorological stations were not considered there for processing this product. [ABSTRACT FROM AUTHOR]

Pathways to the production of precipitation in two cloud microphysics schemes available in the Weather Research and Forecasting (WRF) Model are investigated in a scenario of tropical cyclone intensification. Comparisons of the results from the WRF Model simulations indicate that the variation in the simulated initial rapid intensification of an idealized tropical cyclone is due to the differences between the two cloud microphysics schemes in their representations of pathways to the formation and growth of precipitating hydrometeors. Diagnoses of the source and sink terms of the hydrometeor budget equations indicate that the major differences in the production of hydrometeors between the schemes are in the spectral definition of individual hydrometeor categories and spectrum-dependent microphysical processes, such as accretion growth and sedimentation. These differences lead to different horizontally averaged vertical profiles of net latent heating rate associated with significantly different horizontally averaged vertical distributions and production rates of hydrometeors in the simulated clouds. Results from this study also highlight the possibility that the advantage of double-moment formulations can be overshadowed by the uncertainties in the spectral definition of individual hydrometeor categories and spectrum-dependent microphysical processes. [ABSTRACT FROM AUTHOR]

Space-based precipitation radar data have been underused in data assimilation studies and operations despite their valuable information on vertically resolved hydrometeor profiles around the globe. The authors developed direct assimilation of reflectivities (Ze) from the Dual-Frequency Precipitation Radar (DPR) on board the Global Precipitation Measurement (GPM) Core Observatory to improve mesoscale predictions. Based on comparisons with Ze observations, this cloud resolving model mostly reproduced Ze but produced overestimations of Ze induced by excessive snow with large diameter particles. With an ensemble-based variational scheme and preprocessing steps to properly treat reflectivity observations including conservative quality control and superobbing procedures, the authors assimilated DPR Ze and/or rain-affected radiances of GPM Microwave Imager (GMI) for the case of Typhoon Halong in July 2014. With the vertically resolving capability of DPR, the authors effectively selected Ze observations most suited to data assimilation, for example, by removing Ze above the melting layer to avoid contamination due to model bias. While the GMI radiance had large impacts on various control variables, the DPR made a fine delicate analysis of the rain mixing ratio and updraft. This difference arose from the observation characteristics (coverage width and spatial resolution), sensitivities represented in the observation operators, and structures of the background error covariance. Because the DPR assimilation corrected excessive increases in rain and clouds due to the radiance assimilation, the combined use of DPR and GMI generated more accurate analysis and forecast than separate use of them with respect to the agreement of observations and tropical cyclone position errors. [ABSTRACT FROM AUTHOR]

Studied is the regional predictability of the low-frequency variability of the atmosphere and of the related patterns of atmospheric circulation for monthly and seasonal time periods in the Northern Hemisphere. Used is the SL-AV global semi-Lagrangian model worked out in the Institute of Numerical Mathematics of Russian Academy of Sciences jointly with the Hydrometcenter of Russia. It is demonstrated using the factor analysis that the model simulates successfully the first principal modes of variability explaining 85-90% of cumulative variance. Teleconnection indices which enable identifying the patterns of zonal flow and blocking, are used as the quantitative characteristics of low-frequency variability. In the framework of diagnostic verification, the useful signal was not revealed in the results of hydrodynamic modeling in the integration intervals of the second, third, and fourth months. The quality of forecasts at the monthly and seasonal time scales vary significantly depending on the region and season. Statistically significant correlations (in the limits of the 5-% significance level) between the actual and prognostic data are obtained for the regions of Northern Eurasia and North America only. No useful information was obtained in the forecasts of large-scale patterns over the oceans. The level of practical instability increases from winter to summer in all cases. The conclusion is made on the advisability of using the obtained results for monthly and seasonal weather forecasting. [ABSTRACT FROM AUTHOR]

The article discusses a study that analyzes the hydrometeorological observations of the Russian Academy of Science regarding the climate change of the Sea of Azov in Ukraine and Russia since the early 21st century. Topics discussed include the dynamics of winter temperature at a varying salinity of 0.5 to 13 percent, use of average daily negative air temperatures to analyze the freezing of ice and calculation of ice thickness using Stefan equation.

Abstract: This paper presents our first experience with the application of the METRo model, which forecasts road surface temperature and road conditions (e.g., wet or dry surface, ice) in the Czech Republic. In our version, the model uses online measurements from road weather stations (RWS) in the Czech Republic and weather forecasts from ALADIN, the operational numerical weather prediction NWP model of the Czech Hydrometeorological Institute. The METRo model was quasi-operationally tested during the winter season (November 2012–February 2013) using data from 25 RWS. We compared three model runs with an emphasis on road surface temperature. The first run used the original model and served as a reference. The second run applied model output statistics (MOS) to ALADIN forecasts of temperature and humidity at 2m above the ground, which are required by METRo. The third run applied METRo in a nowcasting mode by starting the model every hour and using new measurements available from the RWS. The results indicated that MOS improved the accuracy of the temperature and humidity at 2m but had little impact on the forecasted road surface temperature. However, the nowcasting scheme significantly improved the accuracy of the forecasts for the initial 3 to 4h. The evaluation of the METRo results suggests that the radiation flux forecast is crucial for an accurate road surface temperature forecast. [Copyright &y& Elsevier]

The review is compiled on the basis of the results of the operation of the total ozone (TO) monitoring in the CIS and Baltic countries functioning in the operational regime at the Central Aerological Observatory (CAO). The monitoring system uses the data from the national network with M-124 filter ozonometers under the methodological supervision of the Main Geophysical Observatory. The quality of the functioning of the entire system is under operational control based on the observations obtained from the OMI satellite equipment (NASA, the United States). The basic TO observation data are generalized for each month of the first quarter of 2014 and for the quarter as a whole. The results of regular observations of surface ozone content carried out in the Moscow region and in the Crimea are generalized as well. [ABSTRACT FROM AUTHOR]

A coupled atmosphere-ocean model intended for the simulation of coupled circulation at time scales up to a season is developed. The semi-Lagrangian atmospheric general circulation model of the Hydrometeorological Centre of Russia, SLAV, is coupled with the sigma model of ocean general circulation developed at the Institute of Numerical Mathematics, Russian Academy of Sciences (INM RAS), INMOM. Using this coupled model, numerical experiments on ensemble modeling of the atmosphere and ocean circulation for up to 4 months are carried out using real initial data for all seasons of an annual cycle in 1989-2010. Results of these experiments are compared to the results of the SLAV model with the simple evolution of the sea surface temperature. A comparative analysis of seasonally averaged anomalies of atmospheric circulation shows prospects in applying the coupled model for forecasts. It is shown with the example of the El Niño phenomenon of 1997-1998 that the coupled model forecasts the seasonally averaged anomalies for the period of the nonstationary El Niño phase significantly better. [ABSTRACT FROM AUTHOR]

Frequency, intensity, areal extent (AE) and duration of rain spells during summer monsoon exhibit large intra-seasonal and inter-annual variations. Important features of the monsoon period large-scale wet spells over India have been documented. A main monsoon wet spell (MMWS) occurs over the country from 18 June to 16 September, during which, 26.5 % of the area receives rainfall 26.3 mm/day. Detailed characteristics of the MMWS period large-scale extreme rain events (EREs) and spatio-temporal EREs (ST-EREs), each concerning rainfall intensity (RI), AE and rainwater (RW), for 1 to 25 days have been studied using 1° gridded daily rainfall (1951-2007). In EREs, 'same area' (grids) is continuously wet, whereas in ST-EREs, 'any area' on the mean under wet condition for specified durations is considered. For the different extremes, second-degree polynomial gave excellent fit to increase in values from distribution of annual maximum RI and RW series with increase in duration. Fluctuations of RI, AE, RW and date of occurrence (or start) of the EREs and the ST-EREs did not show any significant trend. However, fluctuations of 1° latitude-longitude grid annual and spatial maximum rainfall showed highly significant increasing trend for 1 to 5 days, and unprecedented rains on 26-27 July 2005 over Mumbai could be a realization of this trend. The Asia-India monsoon intensity significantly influences the MMWS RW. [ABSTRACT FROM AUTHOR]

Scatterometer ocean surface winds have been providing very valuable information to researchers and operational weather forecasters for over 10 years. However, the scatterometer wind retrievals are compromised when rain is present. Merely flagging all rain-affected areas removes the most dynamic and interesting areas from the wind analysis. Fortunately, the Advanced Earth Observing Satellite II ( ADEOS-II) mission carried a radiometer [the Advanced Microwave Scanning Radiometer (AMSR)] and a scatterometer, allowing for independent, collocated retrievals of rain. The authors developed an algorithm that uses AMSR observations to estimate the rain inside the scatterometer beam. This is the first in a series of papers that describe their approach to providing rain estimation and correction to scatterometer observations. This paper describes the retrieval algorithm and evaluates it using simulated data. Part II will present its validation when applied to AMSR observations. This passive microwave rain retrieval algorithm addresses the issues of nonuniform beam filling and hydrometeor uncertainty in a novel way by 1) using a large number of soundings to develop the retrieval database, thus accounting for the geographically varying atmospheric parameters; 2) addressing the spatial inhomogeneity of rain by developing multiple retrieval databases with different built-in inhomogeneity and rain intensity, along with a 'rain indicator' to select the most appropriate database for each observed scene; 3) developing a new cloud-versus-rain partitioning that allows the use of a variety of drop size distribution assumptions to account for some of the natural variability diagnosed from the soundings; and 4) retrieving atmospheric and surface parameters just outside the rainy areas, thus providing information about the environment to help decrease the uncertainty of the rain estimates. [ABSTRACT FROM AUTHOR]

The Mediterranean hydrometeorological observatory Cévennes-Vivarais (OHM-CV) coordinates hydrometeorological observations (radars, rain gauges, water level stations) on a regional scale in South-Eastern France. In the framework of OHM-CV, temporary GPS measurements have been carried out for 2 months in autumn 2002, when the heaviest rainfall are expected. These measurements increase the spatial density of the existing permanent GPS network, by adding three more receivers between the Mediterranean coast and the Cévennes-Vivarais range to monitor maritime source of water vapour flow feeding the precipitating systems over the Cévennes-Vivarais region. In addition, a local network of 18 receivers covered an area of 30 by 30 km within the field of view of the meteorological radar. These regional and local networks of permanent and temporary stations are used to monitor the precipitable water vapour (PWV) with high temporal resolution (15 min). Also, the dense local network provided data which have been inversed using tomographic techniques to obtain the 3-D field of tro15 pospheric water vapour content. This study presents methodological tests for retrieving GPS tropospheric observations from dense networks, with the aim of assessing the uncertainties of GPS retrievals. Using the optimal tropospheric GPS retrieval methods, high resolution measurements of PWV on a local scale (a few kilometres) are discussed for rain events. Finally, the results of 3-D fields of water vapour densities from GPS tomography are analysed with respect to precipitation fields derived from a meteorological radar, showing a good correlation between precipitation and water vapour depletion areas. [ABSTRACT FROM AUTHOR]

Coarse-resolution climate and weather forecast models cannot accurately parameterize small-scale, non-linear processes without accounting for subgrid-scale variability. To do so, some models integrate over the subgrid variability analytically. Although analytic integration methods are attractive, they can be used only with physical parameterizations that have a sufficiently simple functional form. Instead, this paper introduces a method to integrate subgrid variability using a type of Monte-Carlo integration. The method generates subcolumns with suitable vertical correlations and feeds them into a microphysics parameterization. The subcolumn methodology is non-intrusive and can be used with a wide variety of physical parameterizations. Our subcolumn generator is multivariate, which is important for physical processes that involve two or more hydrometeor species, such as accretion of cloud droplets by rain drops. In order to reduce sampling noise in the integrations, our subcolumn generator employs two variance reduction methods, namely importance and stratified (Latin hypercube) sampling. For this reason, we name the subcolumn generator the Subgrid Importance Latin Hypercube Sampler (SILHS). This paper tests SILHS in interactive, single-column simulations of a marine stratocumulus case and a shallow cumulus case. The paper then compares simulations that use SILHS with those that use analytic integration. Although the SILHS solutions exhibit considerable noise from time step to time step, the noise is greatly damped in most of the time-averaged profiles. [ABSTRACT FROM AUTHOR]

The article presents a study that was conducted to analyze variations in hydrometeorological parameters. It used the continuous wavelet transform for the analysis of the temperature, precipitation, and drainage series obtained at hydrological posts and meteorological stations in Bashkiria. It revealed that the wavelet analysis reveals the spatial-temporal specifics in oscillations of temperature, precipitation, and drainage in Bashkiria. Several figures are presented that depict the results of analysis in the form of power spectra of the analyzed parameters.

The article discusses the Third International Workshop on Next-Generation Numerical Weather Prediction (NWP) Models held on August 30-September 1, 2010 in Seogulpo, Jeju, South Korea. Information is provided on the topics of the workshop which include cloud-resolving scale modeling, hydrometeorological center modeling, and model dynamics.

Based on the results of multiannual oceanographic research at the Murmansk Marine Biological Institute in the 'Kola Meridian' secular section, the recent tendencies of cyclic climate changes in the Barents Sea are discussed on the basis of the data on ice coverage and coastal meteorological conditions. It has been shown that a return from the extremely warm and warm state to the normal one was observed in the period of winter 2005/06-winter 2010/11. Further, this may be changed both to cooling and warming, which verifies the hypothesis about predominance of cyclic natural variability in the thermal and ice characteristics of the Arctic Region. [ABSTRACT FROM AUTHOR]

Summary: Characterisation of the error structure of radar quantitative precipitation estimation (QPE) is a major issue for applications of radar technology in hydrological modelling. Due to the variety of sources of error in radar QPE and the impact of correction algorithms, the problem can only be addressed practically by comparison of radar QPEs with reference values derived from ground-based measurements. Using the radar and raingauge datasets of the Bollène-2002 experiment, a preliminary investigation of this subject has been carried out within a geostatistical framework in the context of the Cévennes–Vivarais Mediterranean Hydrometeorological Observatory. First, raingauge measurements were critically analysed using variograms to detect erroneous squared differences between pairs of raingauge values. The anisotropic block kriging technique was then used to compute and select the most reliable reference values. The statistical distribution and the spatial and temporal structure of the residuals between radar and reference values was established and analysed. The error variance separation concept was also tested to estimate the variance of the residuals between the radar estimates and the true unknown rainfall. A preliminary version of the radar QPE error model was established for 1-km2 domains and time steps ranging from 1 to 12h using the limited data sample of the Bollène-2002 experiment. The error model is dependent on the time scales considered and needs to be conditioned on the rain rate and rainfall type as well as on the radar range. [ABSTRACT FROM AUTHOR]

The objective of spatial downscaling strategies is to increase the information content of coarse datasets at smaller scales. In the case of quantitative precipitation estimation (QPE) for hydrological applications, the goal is to close the scale gap between the spatial resolution of coarse datasets (e.g., gridded satellite precipitation products at resolution L × L) and the high resolution (l × l; L ≫ l) necessary to capture the spatial features that determine spatial variability of water flows and water stores in the landscape. In essence, the downscaling process consists of weaving subgrid-scale heterogeneity over a desired range of wavelengths in the original field. The defining question is, which properties, statistical and otherwise, of the target field (the known observable at the desired spatial resolution) should be matched, with the caveat that downscaling methods be as a general as possible and therefore ideally without case-specific constraints and/or calibration requirements? Here, the attention is focused on two simple fractal downscaling methods using iterated functions systems (IFS) and fractal Brownian surfaces (FBS) that meet this requirement. The two methods were applied to disaggregate spatially 27 summertime convective storms in the central United States during 2007 at three consecutive times (1800, 2100, and 0000 UTC, thus 81 fields overall) from the Tropical Rainfall Measuring Mission (TRMM) version 6 (V6) 3B42 precipitation product (∼25-km grid spacing) to the same resolution as the NCEP stage IV products (∼4-km grid spacing). Results from bilinear interpolation are used as the control. A fundamental distinction between IFS and FBS is that the latter implies a distribution of downscaled fields and thus an ensemble solution, whereas the former provides a single solution. The downscaling effectiveness is assessed using fractal measures (the spectral exponent β, fractal dimension D, Hurst coefficient H, and roughness amplitude R) and traditional operational scores statistics scores [false alarm rate (FR), probability of detection (PD), threat score (TS), and Heidke skill score (HSS)], as well as bias and the root-mean-square error (RMSE). The results show that both IFS and FBS fractal interpolation perform well with regard to operational skill scores, and they meet the additional requirement of generating structurally consistent fields. Furthermore, confidence intervals can be directly generated from the FBS ensemble. The results were used to diagnose errors relevant for hydrometeorological applications, in particular a spatial displacement with characteristic length of at least 50 km (2500 km2) in the location of peak rainfall intensities for the cases studied. [ABSTRACT FROM AUTHOR]

The influence of aerosols on various hydrometeorological processes was discussed. [ABSTRACT FROM AUTHOR]

Aircraft in situ observations of precipitation during the Rain in Cumulus over the Ocean (RICO) field project are used to study and parameterize the effects of precipitation on cloud probes. Specifically, the effects of precipitation on the Forward Scattering Spectrometer Probe, the King cloud liquid water hot-wire probe, and the particle volume monitor are parameterized as linear functions of the precipitation water content. [ABSTRACT FROM AUTHOR]

The operation of a network of hydrometeorological stations constitutes basic infrastructure for the management of water resources. Despite the increased need for rational water management in Greece, there is not a single network of hydrometeorological stations. Various State Services have established sectional networks of limited coverage, resulting in many disadvantages. This study aims at the optimisation of the existing network, using GIS methods. An optimum network of hydrometeorological stations is designed, which constitutes the base for the optimisation of the present network. The optimum network consists of 1379 hydrometeorological stations and is based on the guidelines of international organisations. The uniform spatial distribution of the stations and criteria concerning the selection of the appropriate site, such as the low terrain slope, easy accessibility and proximity to special interest points, were of special importance for its development. Eventually, only the 20% of the existing stations remain at their locations and are included in the optimised network. The rest of the stations should be redistributed according to the proposed sites of the optimum network. [ABSTRACT FROM AUTHOR]

A space-filling algorithm (SFA) based on 2D spectral estimation techniques was developed to extrapolate the spatial domain of the narrow-swath near-instantaneous rain-rate estimates from Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and TRMM Microwave Imager (TMI) using thermal infrared imagery (Meteosat-5) without making use of calibration or statistical fitting. A comparison against rain gauge observations and the original PR 2A25 and TMI 2A12 estimates in the central Himalayas during the monsoon season (June–September) over a 3-yr period of 1999–2001 was conducted to assess the algorithm’s performance. Evaluation over the continental United States was conducted against the NCEP stage IV combined radar and gauge analysis for selected events. Overall, the extrapolated PR and TMI rainfall fields derived using SFA exhibit skill comparable to the original TRMM estimates. The results indicate that probability of detection and threat scores of the reconstructed products are significantly better than the original PR data at high-elevation stations (>2000 m) on mountain ridges, and specifically for rainfall rates exceeding 2–5 mm h-1 and for afternoon convection. For low-elevation stations located in steep narrow valleys, the performance varies from year to year and deteriorates strongly for light rainfall (false alarm rates significantly increase). A preliminary comparison with other satellite products (e.g., 3B42, a TRMM-adjusted merged infrared-based rainfall product) suggests that integrating this algorithm in currently existing operational multisensor algorithms has the potential to improve significantly spatial resolution, texture, and detection of rainfall, especially in mountainous regions, which present some of the greatest challenges in precipitation retrieval from satellites over land, and for hydrological operations during extreme events. [ABSTRACT FROM AUTHOR]

Data communication via Low-Earth-Orbit (LEO) Satellites between portable hydrometeorological measuring stations is the backbone of our system. This networking allows automated event sampling with short time increments also for E. coli field analysis. All activities of the course of the event-sampling can be observed on an internet platform based on a Linux-Server. Conventionally taken samples compared with the auto-sampling procedure revealed corresponding results and were in agreement with the ISO 9308-1 reference method. E. coli concentrations were individually corrected by event specific inactivation coefficients (0.10-0.14 day-1), compensating losses due to sample storage at spring temperature in the auto sampler. Two large summer events in 2005/2006 at an important alpine karst spring (LKAS2) were monitored including detailed analysis of E. coli dynamics (n = 271) together with comprehensive hydrological characterisations. High-resolution time series demonstrated a sudden increase of E. coli concentrations in spring water (approximately 2 log10 units) with a specific time delay after the beginning of the event. Statistical analysis suggested the spectral absorption coefficient measured at 254 nm (SAC254) as an early warning surrogate for real time monitoring of faecal input. Together with the LEO-satellite based system it is a helpful tool for early-warning systems in the field of drinking water protection. [ABSTRACT FROM AUTHOR]

Two economic models are employed to perform a value assessment of short-range ensemble forecasts of 24-h precipitation probabilities for hydroelectric reservoir operation. Using a static cost–loss model, the value of the probability information is compared to the values of a deterministic control high-resolution forecast and of an ensemble-average forecast for forecast days 1 and 2. It is found that the probabilistic ensemble forecast provides value to a much wider range of hydroelectric operators than either the deterministic high-resolution forecast or the ensemble-average forecast, although for a small subset of operators the value of the three forecasts is the same. Forecasts for day-1 precipitation provide measurably higher value than forecasts for day-2 precipitation because of the loss of skill in the longer-range forecasts. A decision theory model provides a continuous-variable weighting of a user-specific utility function. The utility function weights are supplied by the ensemble prediction system, and the outcome is compared with weights calculated from a deterministic model, from the ensemble average, and from climatology. It is found that the methods employing the full ensemble and the ensemble average outperform the single deterministic model and climatology for the hydroelectric reservoir scenario studied. [ABSTRACT FROM AUTHOR]

High-resolution (3 km) time-lagged (initialized every 3 h) multimodel ensembles were produced in support of the Hydrometeorological Testbed (HMT)-West-2006 campaign in northern California, covering the American River basin (ARB). Multiple mesoscale models were used, including the Weather Research and Forecasting (WRF) model, Regional Atmospheric Modeling System (RAMS), and fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5). Short-range (6 h) quantitative precipitation forecasts (QPFs) and probabilistic QPFs (PQPFs) were compared to the 4-km NCEP stage IV precipitation analyses for archived intensive operation periods (IOPs). The two sets of ensemble runs (operational and rerun forecasts) were examined to evaluate the quality of high-resolution QPFs produced by time-lagged multimodel ensembles and to investigate the impacts of ensemble configurations on forecast skill. Uncertainties in precipitation forecasts were associated with different models, model physics, and initial and boundary conditions. The diabatic initialization by the Local Analysis and Prediction System (LAPS) helped precipitation forecasts, while the selection of microphysics was critical in ensemble design. Probability biases in the ensemble products were addressed by calibrating PQPFs. Using artificial neural network (ANN) and linear regression (LR) methods, the bias correction of PQPFs and a cross-validation procedure were applied to three operational IOPs and four rerun IOPs. Both the ANN and LR methods effectively improved PQPFs, especially for lower thresholds. The LR method outperformed the ANN method in bias correction, in particular for a smaller training data size. More training data (e.g., one-season forecasts) are desirable to test the robustness of both calibration methods. [ABSTRACT FROM AUTHOR]

In late April 2006, NASA launched Cloudsat, an earth-observing satellite that uses a near-nadir-pointing millimeter-wavelength radar to probe the vertical structure of clouds and precipitation. The first step in using Cloudsat measurements is to distinguish clouds and other hydrometeors from radar noise. In this article the operational Cloudsat hydrometeor detection algorithm is described, difficulties due to surface clutter are discussed, and several examples from the early mission are shown. A preliminary comparison of the Cloudsat hydrometeor detection algorithm with lidar-based results from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite is also provided. [ABSTRACT FROM AUTHOR]

The trends of the surface water and energy budget components in the Mississippi River basin from 1948 to 2004 are investigated using a combination of hydrometeorological observations and observation-constrained simulations of the land surface conditions using the latest version of the Community Land Model version 3 (CLM3). The atmospheric forcing data for the CLM3 were constructed by adding the intramonthly variations from the 6-hourly National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalysis to observation-based analyses of monthly precipitation, surface air temperature, and cloud cover. The model-based analysis suggests that, for the surface water budget, the observed increase in basin-averaged precipitation is compensated by increases in both runoff and evapotranspiration. For the surface energy budget, the decrease of net shortwave radiation associated with observed increases in cloudiness is compensated by decreases in both net longwave radiation and sensible heat flux, while the latent heat flux increases in association with wetter soil conditions. Both the simulated surface water and energy budgets support the view that evapotranspiration has increased in the Mississippi River basin from 1948 to 2004. Sensitivity experiments show that the precipitation change dominates the evapotranspiration trend, while the temperature and solar radiation changes have only small effects. Large spatial variations within the Mississippi River basin and the contiguous United States are also found. However, the increased evapotranspiration is ubiquitous despite spatial variations in hydrometeorology. [ABSTRACT FROM AUTHOR]

Time-series of precipitable water vapour (PWV), derived from continuous Global Positioning System (GPS) observations, are analysed for the two South African stations HRAO and SUTH. Since water vapour is a major greenhouse gas, observed changes in atmospheric PWV could be indicative of weather and climate change. Our main contribution is a realistic noise model of the PWV observations which enables one to draw correct conclusions about the significance of the derived PWV increase or decrease for given time spans longer than five years. It is demonstrated that the PWV residuals that are obtained after fitting a trend and yearly signal to the data are, due to the simple model's exclusion of short-term scatter, much larger than the PWV uncertainties provided by the GPS analysis software. Although a better solution for the associated uncertainties is obtained by using the variance of these PWV residuals for the uncertainty rescaling, it is shown that the ARMA(1,1) noise model better represents the associated statistical uncertainties than the simple white noise model. The ARMA (1,1)-derived PWV trend uncertainties are approximately 2 times greater than those for a rescaled white noise model. Finally, it is argued that the variability of the annual signal prevents any trend estimation using time series shorter than about five years. A quantitative measure is presented to determine the minimum period of continuous GPS observational data required to measure PWV trends to a specified accuracy. As result of our study, we conclude that no statistically significant PWV trends are observed at the two GPS stations between 1998 and 2006. [ABSTRACT FROM AUTHOR]

The article explains that the Glory space mission is focused on the accurate monitoring of total solar irradiance and terrestrial aerosols. Glory is a remote sensing observatory launched by the U.S. National Aeronautics and Space Administration (NASA). Earth's climate depends upon the balance between solar radiation and the response of the Earth's surface and atmosphere via reflection and absorption. A graph is presented that details the estimated changes in climate forcings during the period between the year 1880 and the year 2003.

Central Asian drought has had drastic impacts on vast regions over recent years. Longer records and insight into temporal drought patterns could aid greatly in anticipating extreme events and agrarian planning. Mongolia is representative of the central Asian region, and tree-ring resources are used herein to extend the climate record and test for solar influence and/or Pacific Ocean teleconnections. Absolutely dated tree-ring-width chronologies from five sampling sites in west-central Mongolia were used in precipitation models and an individual model was made using the longest of the five tree-ring records (1340–2002). The tree-ring sites are in or near the Selenge River basin, the largest river in Mongolia and a major input into Lake Baikal in Siberia. Regression models resulted in a reconstruction of streamflow that extends from 1637 to 1997 and explains 49% of the flow variation. Spectral analysis indicated significant variation in the frequencies common to Pacific Ocean variations [Pacific decadal oscillation (PDO) and ENSO] and also some quasi-solar and lunar-nodal periodicities similar to previous Mongolian hydrometeorological reconstructions in eastern Mongolia based on tree rings. [ABSTRACT FROM AUTHOR]

The Cévennes–Vivarais Mediterranean Hydrometeorological Observatory (OHM-CV) is a research initiative aimed at improving the understanding and modeling of the Mediterranean intense rain events that frequently result in devastating flash floods in southern France. A primary objective is to bring together the skills of meteorologists and hydrologists, modelers and instrumentalists, researchers and practitioners, to cope with these rather unpredictable events. In line with previously published flash-flood monographs, the present paper aims at documenting the 8–9 September 2002 catastrophic event, which resulted in 24 casualties and an economic damage evaluated at 1.2 billion euros (i.e., about 1 billion U.S. dollars) in the Gard region, France. A description of the synoptic meteorological situation is first given and shows that no particular precursor indicated the imminence of such an extreme event. Then, radar and rain gauge analyses are used to assess the magnitude of the rain event, which was particularly remarkable for its spatial extent with rain amounts greater than 200 mm in 24 h over 5500 km2. The maximum values of 600–700 mm observed locally are among the highest daily records in the region. The preliminary results of the postevent hydrological investigation show that the hydrologic response of the upstream watersheds of the Gard and Vidourle Rivers is consistent with the marked space–time structure of the rain event. It is noteworthy that peak specific discharges were very high over most of the affected areas (5–10 m3 s-1 km-2) and reached locally extraordinary values of more than 20 m3 s-1 km-2. A preliminary analysis indicates contrasting hydrological behaviors that seem to be related to geomorphological factors, notably the influence of karst in part of the region. An overview of the ongoing meteorological and hydrological research projects devoted to this case study within the OHM-CV is finally presented. [ABSTRACT FROM AUTHOR]

Outlines the evaluation process used for prototype operational hydrometeorological workstations of the United States National Weather Service (NWS). Role of evaluation; Evaluation methods; Reduction of risks associated with modernization of the NWS; Use of results from the methods to improve workstation design, implementation and training.

After a decade spent standing at the dock, U.S. marine scientists are getting ready to launch a network of ocean observatories. Drawing on 5 days of talks at a meeting attended by more than 300 scientists and engineers, an independent panel will assemble a detailed plan for a $200 million project. Researchers have long craved an escape from the confines of ship-based expeditions that record mere snapshots of long-term ocean changes. Three years ago, U.S. National Science Foundation endorsed the concept of building a trio of new facilities that would continuously pump marine data directly to researchers over the Internet. One observatory would consist of a set of movable buoys moored deep in the open ocean. Another would expand a nascent network of near-shore sensors.