scholarly journals Anomaly-Based Weather Analysis versus Traditional Total-Field-Based Weather Analysis for Depicting Regional Heavy Rain Events

2016 ◽  
Vol 31 (1) ◽  
pp. 71-93 ◽  
Author(s):  
Weihong Qian ◽  
Ning Jiang ◽  
Jun Du
Keyword(s):  
Heavy Rain ◽  
Total Field ◽  
Structure Approach ◽  
Rain Area ◽  
Diagnostic Parameters ◽  
Weather Events ◽  
Pros And Cons ◽  
Rain Events ◽  
Abnormal Weather ◽  
Atmospheric Variables

Abstract Although the use of anomaly fields in the forecast process has been shown to be useful and has caught forecasters’ attention, current short-range (1–3 days) weather analyses and forecasts are still predominantly total-field based. This paper systematically examines the pros and cons of anomaly- versus total-field-based approaches in weather analysis using a case from 1 July 1991 (showcase) and 41 cases from 1998 (statistics) of heavy rain events that occurred in China. The comparison is done for both basic atmospheric variables (height, temperature, wind, and humidity) and diagnostic parameters (divergence, vorticity, and potential vorticity). Generally, anomaly fields show a more enhanced and concentrated signal (pattern) directly related to surface anomalous weather events, while total fields can obscure the visualization of anomalous features due to the climatic background. The advantage is noticeable in basic atmospheric variables, but is marginal in nonconservative diagnostic parameters and is lost in conservative diagnostic parameters. Sometimes a mix of total and anomaly fields works the best; for example, in the moist vorticity when anomalous vorticity combines with total moisture, it can depict the heavy rain area the best when comparing to either the purely total or purely anomalous moist vorticity. Based on this study, it is recommended that anomaly-based weather analysis could be a valuable supplement to the commonly used total-field-based approach. Anomalies can help a forecaster to more quickly identify where an abnormal weather event might occur as well as more easily pinpoint possible meteorological causes than a total field. However, one should not use the anomaly structure approach alone to explain the underlying dynamics without a total field.

scholarly journals Incorporating the Effects of Moisture into a Dynamical Parameter: Moist Vorticity and Moist Divergence

2015 ◽  
Vol 30 (6) ◽  
pp. 1411-1428 ◽  
Author(s):  
Weihong Qian ◽  
Jun Du ◽  
Xiaolong Shan ◽  
Ning Jiang
Keyword(s):  
Potential Vorticity ◽  
Eastern China ◽  
Heavy Rain ◽  
Systematic Evaluation ◽  
Rain Event ◽  
Dynamical Parameter ◽  
Rain Area ◽  
Moisture Effects ◽  
Moist Potential Vorticity ◽  
Rain Events

Abstract Properly including moisture effects into a dynamical parameter can significantly increase the parameter’s ability to diagnose heavy rain locations. The relative humidity–based weighting approach used to extend the moist potential vorticity (MPV) to the generalized moist potential vorticity (GMPV) is analyzed and demonstrates such an improvement. Following the same approach, two new diagnostic parameters, moist vorticity (MV) and moist divergence (MD), have been proposed in this study by incorporating moisture effects into the traditional vorticity and divergence. A regional heavy rain event that occurred along the Yangtze River on 1 July 1991 is used as a case study, and 41 daily regional heavy rain events during the notorious flooding year of 1998 in eastern China are used for a systematic evaluation. Results show that after the moisture effects were properly incorporated, the improved ability of all three parameters to capture a heavy rain area is significant (statistically at the 99% confidence level): the GMPV is improved over the MPV by 194%, the MD over the divergence by 60%, and the MV over the vorticity by 34% in terms of the threat score (TS). The average TS is 0.270 for the MD, 0.262 for the MV, and 0.188 for the GMPV. Application of the MV and MD to assess heavy rain potential is not intended to replace a complete, multiscale forecasting methodology; however, the results from this study suggest that the MV and MD could be used to postprocess a model forecast to potentially improve heavy rain location predictions.

scholarly journals A review: anomaly based versus full-field based weather analysis and forecasting

2021 ◽  
pp. 1-52
Author(s):  
Weihong Qian ◽  
Jun Du ◽  
Yang Ai
Keyword(s):  
Model Prediction ◽  
Heavy Rain ◽  
Societal Impact ◽  
Seasonal Forecasts ◽  
Field Methods ◽  
Weather System ◽  
Full Field ◽  
Diagnostic Parameters ◽  
Weather Events ◽  
Typhoon Tracks

AbstractComparisons between anomaly and full-field methods have been carried out in weather analysis and forecasting over the last decade. Evidence from these studies has demonstrated the superiority of anomaly to full-field in the following four aspects: depiction of weather systems, anomaly forecasts, diagnostic parameters and model prediction. To promote the use and further discussion of the anomaly approach, this article summarizes those findings.After examining many types of weather events, anomaly weather maps show at least five advantages in weather system depiction: (1) less vagueness in visually connecting the location of an event with its associated meteorological conditions; (2) clearer and more complete depictions of vertical structures of a disturbance; (3) easier observation of time and spatial evolution of an event and its interaction or connection with other weather systems; (4) simplification of conceptual models by unifying different weather systems into one pattern; and (5) extension of model forecast length due to earlier detection of predictors. Anomaly verification is also mentioned. The anomaly forecast is useful for raising one’s awareness of potential societal impact. Combining the anomaly forecast with an ensemble is emphasized, where a societal impact index is discussed. For diagnostic parameters, two examples are given: an anomalous convective instability index for convection, and seven vorticity and divergence related parameters for heavy rain. Both showed positive contributions from the anomalous fields. For model prediction, the anomaly version of the beta-advection model consistently outperformed its full-field version in predicting typhoon tracks with clearer physical explanation. Application of anomaly global models to seasonal forecasts is also reviewed.

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;

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