Hydrochemical response of spring and mine waters in the Upper Harz Mountains (Germany) after dry periods and heavy rain events

2021 ◽  
Author(s):  
Elke Bozau ◽  
Georg Bauer ◽  
Tobias Licha ◽  
Sonja Lojen
Keyword(s):  
Heavy Rain ◽  
Harz Mountains ◽  
Mine Waters ◽  
Rain Events

scholarly journals Comparison of Radar-Based Hail Detection Using Single- and Dual-Polarization

2019 ◽  
Vol 11 (12) ◽  
pp. 1436 ◽  
Author(s):  
Skripniková ◽  
Řezáčová
Keyword(s):  
Comparative Analysis ◽  
Heavy Rain ◽  
Radar Data ◽  
Severe Weather ◽  
Detection Methods ◽  
Polarimetric Radar ◽  
Dual Polarization ◽  
Rain Events ◽  
Single Polarization ◽  
Strong Agreement

The comparative analysis of radar-based hail detection methods presented here, uses C-band polarimetric radar data from Czech territory for 5 stormy days in May and June 2016. The 27 hail events were selected from hail reports of the European Severe Weather Database (ESWD) along with 21 heavy rain events. The hail detection results compared in this study were obtained using a criterion, which is based on single-polarization radar data and a technique, which uses dual-polarization radar data. Both techniques successfully detected large hail events in a similar way and showed a strong agreement. The hail detection, as applied to heavy rain events, indicated a weak enhancement of the number of false detected hail pixels via the dual-polarization hydrometeor classification. We also examined the performance of hail size detection from radar data using both single- and dual-polarization methods. Both the methods recognized events with large hail but could not select the reported events with maximum hail size (diameter above 4 cm).

scholarly journals Spatial structures and directionalities in Monsoonal precipitation over South Asia

2010 ◽  
Vol 17 (5) ◽  
pp. 371-381 ◽  
Author(s):  
N. Malik ◽  
N. Marwan ◽  
J. Kurths
Keyword(s):  
Indian Subcontinent ◽  
Monsoon Season ◽  
Daily Rainfall ◽  
Heavy Rain ◽  
Data Sets ◽  
Spatial Structures ◽  
Break Phase ◽  
Rainfall Events ◽  
Monsoonal Precipitation ◽  
Rain Events

Abstract. Precipitation during the monsoon season over the Indian subcontinent occurs in form of enormously complex spatiotemporal patterns due to the underlying dynamics of atmospheric circulation and varying topography. Employing methods from nonlinear time series analysis, we study spatial structures of the rainfall field during the summer monsoon and identify principle regions where the dynamics of monsoonal rainfall is more coherent or homogenous. Moreover, we estimate the time delay patterns of rain events. Here we present an analysis of two separate high resolution gridded data sets of daily rainfall covering the Indian subcontinent. Using the method of event synchronization (ES), we estimate regions where heavy rain events during monsoon happen in some lag synchronised form. Further using the delay behaviour of rainfall events, we estimate the directionalities related to the progress of such type of rainfall events. The Active (break) phase of a monsoon is characterised by an increase(decrease) of rainfall over certain regions of the Indian subcontinent. We show that our method is able to identify regions of such coherent rainfall activity.

scholarly journals Effect of natural rainfall on the migration characteristics of runoff and sediment on purple soil sloping cropland during different planting stages

2021 ◽  
Author(s):  
Yi Wang ◽  
Jiupai Ni ◽  
Chengsheng Ni ◽  
Sheng Wang ◽  
Deti Xie
Keyword(s):  
Sediment Yield ◽  
Soil Loss ◽  
Heavy Rain ◽  
Sediment Concentration ◽  
Purple Soil ◽  
Torrential Rain ◽  
Sediment Yields ◽  
Natural Rainfall ◽  
Sediment Loss ◽  
Rain Events

Abstract Due to the difficulty in monitoring subsurface runoff and sediment migration, their loss loads are still not clear and need further study. This study monitored water and soil loss occurring within experimental field plots for two calendar years under natural rainfall events. The sediment loss load was quantified by considering the corresponding water flow flux and its sediment concentration. The results showed that 60.04% of the runoff and 2.83% of the sediment were lost underground. The annual underground sediment loss reached up to 54.6 kg*ha−1*yr−1. A total of 69.68% of the runoff yield and 67.25% of the sediment yield were produced during the corn planting stage (CPS: March–July). Heavy rain and torrential rain events produced 94.45%, 65.46% of the annual runoff and 94.45%, 76.21% of the sediment yields during the corn-planting stage and summer fallow period (SFP: August–September). The rain frequency, rainfall, and rainfall duration of each planting stage significantly affected the resulting runoff and sediment yield. Measures aimed at the prevention and control of water-soil loss from purple soil sloping land should heavily focus on torrential rain and heavy rain events during the CPS and SFP. This paper aims to provide a practical reference for quantifying the water and soil loss from purple soil sloping cropland.

scholarly journals Export of <sup>134</sup>Cs and <sup>137</sup>Cs in the Fukushima river systems at heavy rains by Typhoon Roke in September 2011

2013 ◽  
Vol 10 (2) ◽  
pp. 2767-2790 ◽  
Author(s):  
S. Nagao ◽  
M. Kanamori ◽  
S. Ochiai ◽  
S. Tomihara ◽  
K. Fukushi ◽  
...  
Keyword(s):  
Nuclear Power ◽  
Heavy Rain ◽  
Rain Event ◽  
Normal Flow ◽  
Flow Conditions ◽  
Pulse Input ◽  
Heavy Rain Event ◽  
Coastal Marine ◽  
Rain Events ◽  
Heavy Rains

Abstract. Effects of a heavy rain event on radiocesium export were studied at stations on the Natsui River and the Same River in Fukushima Prefecture, Japan after Typhoon Roke during 21–22 September 2011, six months after the Fukushima Daiichi Nuclear Power Plant accident. Radioactivity of 134Cs and 137Cs in river waters was 0.011–0.098 Bq L−1 at normal flow conditions during July–September in 2011, but it increased to 0.85 Bq L−1 in high flow conditions by heavy rains occurring with the typhoon. The particulate fractions of 134Cs and 137Cs were 21–56% in the normal flow condition, but were close to 100% after the typhoon. These results indicate that the pulse input of radiocesium associated with suspended particles from land to coastal ocean occurred by the heavy rain event. Export flux of 134Cs and 137Cs by the heavy rain accounts for 30–50% of annual radiocesium flux in 2011. Results show that rain events are one factor controlling the transport and dispersion of radiocesium in river watersheds and coastal marine environments.

scholarly journals Improvement in WRF model prediction for heavy rain events over North Sumatra region using satellite data assimilation

2021 ◽  
Vol 893 (1) ◽  
pp. 012040
Author(s):  
Immanuel Jhonson Arizona Saragih ◽  
Huda Abshor Mukhsinin ◽  
Kerista Tarigan ◽  
Marzuki Sinambela ◽  
Marhaposan Situmorang ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Initial Data ◽  
Satellite Data ◽  
Wrf Model ◽  
Heavy Rain ◽  
Convective System ◽  
Large Area ◽  
Weather Forecasts ◽  
Rain Events ◽  
North Sumatra

Abstract Located adjacent to the Indian Ocean and the Malacca Strait as a source of water vapour, and traversed by the Barisan Mountains which raise the air orographically causing high diurnal convective activity over the North Sumatra region. The convective system that was formed can cause heavy rainfall over a large area. Weather Research and Forecasting (WRF) was a numerical weather model used to make objective weather forecasts. To improve the weather forecasts accuracy, especially for predict heavy rain events, needed to improve the output of the WRF model by the assimilation technique to correct the initial data. This research was conducted to compare the output of the WRF model with- and without assimilation on 17 June 2020 and 14 September 2020. Assimilation was carried out using the 3D-Var technique and warm starts mode on three assimilation schemes, i.e. DA-AMSU which used AMSU-A satellite data, DA-MHS which used MHS satellite data, and DA-BOTH which used both AMSU-A and MHS satellite data. Model output verification was carried out using the observational data (AWS, AAWS, and ARG) and GPM-IMERG data. The results showed that the satellite data assimilation corrects the WRF model initial data, so as increasing the accuracy of rainfall predictions. The DA-BOTH scheme provided the best improvement with a final weighted performance score of 0.64.

scholarly journals Reply to “Comments on ‘Incorporating the Effects of Moisture into a Dynamical Parameter: Moist Vorticity and Moist Divergence’”

2016 ◽  
Vol 31 (4) ◽  
pp. 1397-1405
Author(s):  
Weihong Qian ◽  
Ning Jiang ◽  
Jun Du
Keyword(s):  
Large Scale ◽  
Value Added ◽  
Heavy Rain ◽  
Heavy Precipitation ◽  
Small Scale ◽  
Precipitation Efficiency ◽  
Long Duration ◽  
Advection Term ◽  
Rain Events ◽  
Mathematical Derivation

Abstract Mathematical derivation, meteorological justification, and comparison to model direct precipitation forecasts are the three main concerns recently raised by Schultz and Spengler about moist divergence (MD) and moist vorticity (MV), which were introduced in earlier work by Qian et al. That previous work demonstrated that MD (MV) can in principle be derived mathematically with a value-added empirical modification. MD (MV) has a solid meteorological basis. It combines ascent motion and high moisture: the two elements necessary for rainfall. However, precipitation efficiency is not considered in MD (MV). Given the omission of an advection term in the mathematical derivation and the lack of precipitation efficiency, MD (MV) might be suitable mainly for heavy rain events with large areal coverage and long duration caused by large-scale quasi-stationary weather systems, but not for local intense heavy rain events caused by small-scale convection. In addition, MD (MV) is not capable of describing precipitation intensity. MD (MV) worked reasonably well in predicting heavy rain locations from short to medium ranges as compared with the ECMWF model precipitation forecasts. MD (MV) was generally worse than (though sometimes similar to) the model heavy rain forecast at shorter ranges (about a week) but became comparable or even better at longer ranges (around 10 days). It should be reiterated that MD (MV) is not intended to be a primary tool for predicting heavy rain areas, especially in the short range, but is a useful parameter for calibrating model heavy precipitation forecasts, as stated in the original paper.

Impact of a severe rain event on C- and N-DBP precursor removal using IEX

2018 ◽  
Vol 18 (6) ◽  
pp. 2092-2099
Author(s):  
K. Doederer ◽  
Z. Ilieva ◽  
J. Keller
Keyword(s):  
Ion Exchange ◽  
Heavy Rain ◽  
Health Concern ◽  
Rain Event ◽  
Heavy Rain Event ◽  
Removal Capacity ◽  
C And N ◽  
Pre Treatment ◽  
Rain Events ◽  
Magnetic Ion

Abstract During disinfection, dissolved organic matter (DOM) is the major precursor to form disinfection by-products (DBPs), which may be of potential human health concern. Previous research focused on waters of continental climates and less on subtropical environments. However, water sources in subtropical climates are regularly impacted by major rain events during the summer months. This study evaluated the C- and N-DBP precursor removal capacity of two conventional ion exchange (IEX) resins and one magnetic ion exchange (MIEX) resin with a raw water at normal conditions and impacted by a heavy rain event. The rain event introduced 3 mg C/L total organic carbon (TOC) comprised mainly of low to medium molecular weight organics. All three resins were able to remove TOC and DBP precursors (&gt;66%) but being less efficient in reducing turbidity (3–48%) and colour (9–24%). The resin with the smallest bead size was affected the most by the increased medium MW DOM loading resulting in DOM and C-DBP precursor removal performance losses of 10% and 22%. When applied as a pre-treatment for coagulation, MIEX was more efficient in DBP precursor control than coagulation in addressing the additional organic and DBP precursor loading after a heavy rain event.

Development of a lightning model and implementation into a meteorological model developed in Japan~ Validation through the comparison with the ground base measurement

2021 ◽  
Author(s):  
Yousuke Sato ◽  
Syugo Hayashi ◽  
Akihiro Hashimoto
Keyword(s):  
Vertical Structure ◽  
Heavy Rain ◽  
Japan Meteorological Agency ◽  
Network System ◽  
Meteorological Model ◽  
Lightning Detection ◽  
Base Measurement ◽  
The Difference ◽  
Rain Events ◽  
The Vertical Distribution

&lt;p&gt;A lightning model was developed (Sato et al. 2019, 2021) and implemented into a community meteorological model in Japan (SCALE: Nishizawa et al. 2015, Sato et al. 2015). The lightning model coupled with SCALE was validated through the comparison with the ground base lightning measurement (LIghtning DEtection Network system: LIDEN) operated by Japan Meteorological Agency. For the validation, we conducted downscale simulations targeting on two heavy rain events, which occurred on July, 2017 and July, 2018. The heavy rainfall in both events were triggered by Baiu front system on July in Japan and cumulative precipitation exceeded 800 mm/48 hours, but lightning frequency in the 2017 case was much higher than that of the 2018 case.&lt;/p&gt;&lt;p&gt;Our results indicated that the model successfully reproduced the difference of the lightning frequency between the two heavy rain events. Our analyses elucidated that the difference in the lightning frequency was originated from the difference in the vertical distribution of the charged graupel, and as consequence, the vertical structure of the charge separation rate and the charge density.&lt;/p&gt;

Application of SpectralWeather to prediction of flood and extreme rain events in the Maritime Continent

2021 ◽  
Author(s):  
Beata Latos ◽  
Thierry Lefort ◽  
Maria K. Flatau ◽  
Piotr J. Flatau ◽  
Dariusz B. Baranowski ◽  
...  
Keyword(s):  
Natural Hazards ◽  
Mesoscale Convective System ◽  
Heavy Rain ◽  
Convective System ◽  
Kelvin Wave ◽  
Maritime Continent ◽  
Equatorial Wave ◽  
Extreme Rain ◽  
Rain Events ◽  
Tropical Weather

&lt;p&gt;Monitoring of equatorial wave activity and understanding their nature is of high priority for scientists, weather forecasters and policy makers because these waves and their interactions can serve as precursors for weather-driven natural hazards, such as extreme rain and flood events. We studied such precursors of the January 2019 heavy rain and deadly flood in the central Maritime Continent region of southwest Sulawesi, Indonesia. It is shown that a convectively coupled Kelvin wave (CCKW) and a convectively coupled equatorial Rossby wave (CCERW) embedded within the larger-scale envelope of the Madden-Julian Oscillation (MJO), contributed to the onset of a mesoscale convective system. The latest developed over the Java Sea and propagated onshore, resulting in extreme rain and devastating flood.&amp;#160;&lt;/p&gt;&lt;p&gt;For the analysis of the January 2019 flood, we explored large datasets and detected interesting features to find multivariate relationships through visualization. We used SpectralWeather &amp;#8211; a new tool supporting tropical weather training, research and forecasting, easily accessible at https://www.spectralweather.com. Extending Cameron Beccario's earth.nullschool.net project, SpectralWeather focuses on spectral decomposition of meteorological and oceanic fields into equatorial waves &amp;#8211; CCKW, MJO, CCERW and Mixed Rossby-Gravity waves. SpectralWeather uses ECMWF ERA5 reanalysis at several levels, NASA GPM rainfall datasets, OMI OLR index, NEMO SST, AVISO sea surface height, and OSCAR currents.&lt;/p&gt;&lt;p&gt;This new visualization tool can help to quantify and understand factors triggering natural hazards in the global tropics. We will discuss its interface and available features, based on the example of the January 2019 Sulawesi flood and other flood and extreme rain events in the Maritime Continent.&amp;#160;&amp;#160;&amp;#160;&lt;/p&gt;

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