The modification of the typhoon rainfall climatology model  in Taiwan

Abstract. This study is focused on the modification of a typhoon rainfall climatological model, by using the dataset up to 2006 and including data collected from rain gauge stations established after the 921 earthquake (1999). Subsequently, the climatology rainfall models for westward- and northward-moving typhoons are established by using the typhoon track classification from the Central Weather Bureau. These models are also evaluated and examined using dependent cases collected between 1989 and 2006 and independent cases collected from 2007 to 2011. For the dependent cases, the average total rainfall at all rain gauge stations forecasted using the climatology rainfall models for westward- (W-TRCM12) and northward-moving (N-TRCM12) typhoons is superior to that obtained using the original climatological model (TRCM06). Model W-TRCM12 significantly improves the precipitation underestimation of model TRCM06. The independent cases show that model W-TRCM12 provides better accumulated rainfall forecasts and distributions than model TRCM06. A climatological model for accompanied northeastern monsoons (A-TRCM12) for special typhoon types has also been established. The current A-TRCM12 model only contains five historical cases and various typhoon combinations can cause precipitation in different regions. Therefore, precipitation is likely to be significantly overestimated and high false alarm ratios are likely to occur in specific regions. For example, model A-TRCM12 significantly overestimates the rainfall forecast for Typhoon Mitag, an independent case from 2007. However, it has a higher probability of detection than model TRCM06. From a disaster prevention perspective, a high probability of detection is much more important than a high false alarm ratio. The modified models can contribute significantly to operational forecast.

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Applying Satellite-Estimated Storm Rotation Speed to Improve Typhoon Rainfall Potential Technique

Weather and Forecasting ◽

10.1175/2007waf2006101.1 ◽

2008 ◽

Vol 23 (2) ◽

pp. 259-269 ◽

Cited By ~ 10

Author(s):

Gin-Rong Liu ◽

Chun-Chieh Chao ◽

Czu-Yi Ho

Keyword(s):

Rotation Speed ◽

Rain Gauge ◽

Northwestern Pacific ◽

Correlation Technique ◽

Accumulated Rainfall ◽

Typhoon Rainfall ◽

Potential Trap ◽

Spiral Rainbands ◽

Microwave Imager ◽

Cross Correlation Technique

Abstract Heavy rainfall from typhoons or tropical cyclones often causes inland flooding and mudslides that threaten lives and property. In this study, Special Sensor Microwave Imager (SSM/I) satellite data observed from 2000 to 2004 were used to calculate the rainfall rates of different typhoons in the northwestern Pacific. Geostationary weather satellite infrared images were also applied to estimate the typhoon rotation speed via the maximum cross-correlation technique. By including such information in the tropical rainfall potential (TRaP) technique, an improved typhoon rainfall potential technique can be constructed. Considering the fact that a typhoon’s spiral rainbands move constantly, half-hourly or hourly infrared data observed from geostationary weather satellites were used to calculate the revolving speed, which was subsequently used to predict the rainband movement over the next hour. After comparing the predicted rainfall potential with the rain gauge data of Taiwan’s small offshore islands, it was found that this new method can improve the typhoon’s accumulated rainfall by approximately 40% over the original TRaP method. Therefore, to produce a more accurate short-term typhoon rainfall forecast, it is very important to factor in the satellite-estimated storm rotation speed.

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Development and Evaluation of Mei-Yu Season Quantitative Precipitation Forecasts in Taiwan River Basins Based on a Conceptual Climatology Model

Weather and Forecasting ◽

10.1175/waf-d-11-00098.1 ◽

2012 ◽

Vol 27 (3) ◽

pp. 586-607 ◽

Cited By ~ 5

Author(s):

Chung-Chieh Wang ◽

Chu-Ying Kung ◽

Cheng-Shang Lee ◽

George Tai-Jen Chen

Keyword(s):

Heavy Rainfall ◽

Statistical Tests ◽

River Basins ◽

Short Wave ◽

Rain Gauge ◽

Quantitative Precipitation Forecasts ◽

Southern Taiwan ◽

Upper Level ◽

Central Weather Bureau ◽

Rainfall Climatology

Abstract Using rain gauge data during 134 mei-yu frontal cases in May–June 1991–2006, a rainfall climatology in relation to the positions of fronts every 0.5° in Taiwan is obtained, showing widespread precipitation with maxima over windward mountain slopes associated with frontal passages. For six major river basins, rainfall characteristics and synoptic factors are further analyzed to build a conceptual climatology model for short-term quantitative precipitation forecasts (QPFs). The four basins in central–southern Taiwan exhibit increased heavy-rainfall frequencies (>25%) roughly from 2° south to 1° north of the front, while the two basins in northern Taiwan have lower frequencies with different characteristics mainly due to the differences in their topography. The synoptic factors in the checklist employed by the Central Weather Bureau and important to heavy rainfall are identified for each of the six basins through statistical tests and their threat score (TS). These factors include those related to mei-yu fronts, low-level jets and moisture, upper-level divergence–diffluence, and short-wave troughs. A conceptual climatology model that uses both synoptic and probability forecasting guidance is developed, and in practice the average rainfall climatology is replaced by one obtained for heavy-rainfall periods if either of the two guidance schemes indicates heavy-rainfall possibility. This model for 0–6- and 0–12-h QPFs is also evaluated for its usefulness using cases during the 2007–08 seasons. With typical TSs of 0.2–0.3 (for heavy rainfall), this approach outperforms simple climatology in all six basins especially toward higher thresholds (about 20–50 mm) and for 12-h events, where it also shows advantages over model QPFs in southern Taiwan. Thus, the model can provide useful information for operational use.

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Comprehensive Comparisons of State-of-the-Art Gridded Precipitation Estimates for Hydrological Applications over Southern China

Remote Sensing ◽

10.3390/rs12233997 ◽

2020 ◽

Vol 12 (23) ◽

pp. 3997

Author(s):

Zhen Gao ◽

Bensheng Huang ◽

Ziqiang Ma ◽

Xiaohong Chen ◽

Jing Qiu ◽

...

Keyword(s):

Southern China ◽

Temporal Distribution ◽

Rain Gauge ◽

Vital Role ◽

Probability Of Detection ◽

Precipitation Estimates ◽

Accumulated Rainfall ◽

Daily Scale ◽

Global Precipitation ◽

Better Than

Satellite-based precipitation estimates with high quality and spatial-temporal resolutions play a vital role in forcing global or regional meteorological, hydrological, and agricultural models, which are especially useful over large poorly gauged regions. In this study, we apply various statistical indicators to comprehensively analyze the quality and compare the performance of five newly released satellite and reanalysis precipitation products against China Merged Precipitation Analysis (CMPA) rain gauge data, respectively, with 0.1° × 0.1° spatial resolution and two temporal scales (daily and hourly) over southern China from June to August in 2019. These include Precipitation Estimates from Remotely Sensed Information using Artificial Neural Networks Cloud Classification System (PERSIANN-CCS), European Center for Medium-Range Weather Forecasts Reanalysis v5 (ERA5-Land), Fengyun-4 (FY-4A), Global Satellite Mapping of Precipitation (GSMaP), and Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG). Results indicate that: (1) all five products overestimate the accumulated rainfall in the summer, with FY-4A being the most severe; additionally, FY-4A cannot capture the spatial and temporal distribution characteristics of precipitation over southern China. (2) IMERG and GSMaP perform better than the other three datasets at both daily and hourly scales; IMERG correlates slightly better than GSMaP against CMPA data, while it performs worse than GSMaP in terms of probability of detection (POD). (3) ERA5-Land performs better than PERSIANN-CCS and FY-4A at daily scale but shows the worst correlation coefficient (CC), false alarm ratio (FAR), and equitable threat score (ETS) of all precipitation products at hourly scale. (4) The rankings of overall performance on precipitation estimations for this region are IMERG, GSMaP, ERA5-Land, PERSIANN-CCS, and FY-4A at daily scale; and IMERG, GSMaP, PERSIANN-CCS, FY-4A, and ERA5-Land at hourly scale. These findings will provide valuable feedback for improving the current satellite-based precipitation retrieval algorithms and also provide preliminary references for flood forecasting and natural disaster early warning.

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Long-Term Performance Metrics for National Weather Service Tornado Warnings

Weather and Forecasting ◽

10.1175/waf-d-18-0120.1 ◽

2018 ◽

Vol 33 (6) ◽

pp. 1501-1511 ◽

Cited By ~ 21

Author(s):

Harold E. Brooks ◽

James Correia

Keyword(s):

False Alarm ◽

Lead Time ◽

Performance Metrics ◽

Warning System ◽

Probability Of Detection ◽

False Alarms ◽

National Weather Service ◽

False Alarm Ratio ◽

Tornado Warnings ◽

Weather Service

Abstract Tornado warnings are one of the flagship products of the National Weather Service. We update the time series of various metrics of performance in order to provide baselines over the 1986–2016 period for lead time, probability of detection, false alarm ratio, and warning duration. We have used metrics (mean lead time for tornadoes warned in advance, fraction of tornadoes warned in advance) that work in a consistent way across the official changes in policy for warning issuance, as well as across points in time when unofficial changes took place. The mean lead time for tornadoes warned in advance was relatively constant from 1986 to 2011, while the fraction of tornadoes warned in advance increased through about 2006, and the false alarm ratio slowly decreased. The largest changes in performance take place in 2012 when the default warning duration decreased, and there is an apparent increased emphasis on reducing false alarms. As a result, the lead time, probability of detection, and false alarm ratio all decrease in 2012. Our analysis is based, in large part, on signal detection theory, which separates the quality of the warning system from the threshold for issuing warnings. Threshold changes lead to trade-offs between false alarms and missed detections. Such changes provide further evidence for changes in what the warning system as a whole considers important, as well as highlighting the limitations of measuring performance by looking at metrics independently.

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An approach of constant false alarm ratio for improved target tracking

Scientific Technical Review ◽

10.5937/str2003017r ◽

2020 ◽

Vol 70 (3) ◽

pp. 17-23

Author(s):

Zvonko Radosavljević ◽

Dejan Ivković

Keyword(s):

False Alarm ◽

Tracking Error ◽

Probability Of Detection ◽

Interacting Multiple Model ◽

Multiple Model ◽

Moving Targets ◽

False Alarm Ratio ◽

Motion Models ◽

Areas Of Interest

Each radar has the function of surveillance of certain areas of interest. In particular, the radar also has the function of tracking moving targets in that territory with some probability of detection, which depends on the type of detector. Constant false alarm ratio (CFAR) is a very commonly used detector. Changing the probability of target detection can directly affect the quality of tracking the moving targets. The paper presents the theoretical basis of the influence of CFAR detectors on the quality of tracking, as well as an approach to the selection of CFAR detectors, CATM CFAR, which enables better monitoring by the Interacting Multiple Model (IMM) algorithm with two motion models. Comparative analysis of CA and CATM algorithm realized by numerical simulations has shown that CATM CFAR gives less tracking error with proportionally the same computer resources.

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Synthesis of an algorithm for increasing the detection range of signals from radio-electronic means by means of radio control based on the estimated-correlation-compensation processing of signals with an unknown shape and additive noise in the receiving channel

Achievements of Modern Radioelectronics ◽

10.18127/j20700784-202102-07 ◽

2021 ◽

Author(s):

А.А. Boldyrev ◽

А.А. Buben’shikov ◽

D.I. Boldyrev

Keyword(s):

False Alarm ◽

Rapid Development ◽

Internal Noise ◽

Probability Of Detection ◽

Detection Range ◽

Signal Noise ◽

Radio Electronic ◽

Wide Range ◽

Technical Systems

In modern conditions of rapid development of telecommunication technologies radio engineering means of different function are used everywhere in all spheres of ability to live of the person. Thus organizational-technical systems of civil appointment and power departments use the wide nomenclature of radio-electronic means of various classes with a wide spectrum of parameters, kinds of radiations and operating modes. In turn, it causes formation of difficult electromagnetic conditions in administrative-industrial regions and their near environment. The primary goal of services of radio control in these conditions is control over correctness of use by organizational-technical systems of the allocated resource of a radiofrequency spectrum and the parameters radiating of radio-electronic means. One of the main difficulties with which means of radio control in the course of the analysis of electromagnetic conditions in the set territorial area face a considerable quantity of radiating radio-electronic means with various parameters in a wide range of the relation a signal/noise, and also presence of stirring influence of any hindrances is. These factors make rigid demands to indicators of quality of functioning of panoramic detectors-direction finders which make a basis of mobile and stationary means of radio control. One of the basic indicators of quality of panoramic detectors-direction finders of means of radio control is range of detection of the radio-electronic means, defined by the set level of sensitivity and demanded values of probabilities of detection and a false alarm. Authors in article result results of working out of algorithm of increase of range of detection of signals by means of radio control on the basis of an estimated-correlation-compensatory way of measurement and indemnification of average capacity of additive hindrances in the reception channel. By results of the researches spent in article it is shown that: the increase in average capacity of cumulative external inadvertent and deliberate hindrances for the set typical initial data leads in VHF a range to reduction of range of detection of radio-electronic means not less, than in 1,4 times from the demanded; at demanded value of probability of detection, for example, and probabilities of a false alarm, at relative level of external set of a hindrance the panoramic detectors-direction finder of means of radio control with the realised procedure of measurement and indemnification of average value of capacity (dispersion) of inadvertent, deliberate hindrances and internal noise allows to lower the requirement to the threshold relation a signal/(noise) (on pressure) more, than in 1,3 times that will allow to approach value of range of detection to a reference value.

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Measuring Hydrometeors with a Precipitation Microphysical Characteristics Sensor: Calibration and Field Measurements

Advances in Meteorology ◽

10.1155/2017/3049792 ◽

2017 ◽

Vol 2017 ◽

pp. 1-16 ◽

Cited By ~ 1

Author(s):

Yuntao Hu ◽

Xichuan Liu ◽

Taichang Gao ◽

Xiaojian Shu

Keyword(s):

Field Measurements ◽

Rain Gauge ◽

Sensor Calibration ◽

Threshold Method ◽

Fall Velocity ◽

Axis Ratio ◽

Measurement Results ◽

Accumulated Rainfall ◽

Typical Shape ◽

Particle Imaging

Aiming at the simultaneous measurement of the size, shape, and fall velocity of precipitation particles in the natural environment, we present here a new ground-based precipitation microphysical characteristics sensor (PMCS) based on the particle imaging velocimetry technology. The PMCS can capture autocorrelated images of precipitation particles by double-exposure in one frame, by which the size, axis ratio, and fall velocity of precipitation particles can be calculated. The PMCS is calibrated by a series of glass balls with certain diameters under varying light conditions, and a self-adaptive threshold method is proposed. The shape, axis ratio, and fall velocity of raindrops were calculated and discussed based on the field measurement results of PMCS. The typical shape of large raindrop is an oblate ellipsoid, the axis ratio of raindrops decreases linearly with the diameter, the fall velocity of raindrops approaches its asymptote, and the above observed results are in good agreement with the empirical models; the synchronous observation of a PMCS, an OTT PARSIVEL disdrometer, and a rain gauge shows that the PMCS is able to measure the rain intensity, accumulated rainfall, and drop size distribution with high accuracy. These results have validated the performance of PMCS.

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Improving an Extreme Rainfall Detection System with GPM IMERG data

Remote Sensing ◽

10.3390/rs11060677 ◽

2019 ◽

Vol 11 (6) ◽

pp. 677 ◽

Cited By ~ 10

Author(s):

Paola Mazzoglio ◽

Francesco Laio ◽

Simone Balbo ◽

Piero Boccardo ◽

Franca Disabato

Keyword(s):

Detection System ◽

Extreme Rainfall ◽

Rain Gauge ◽

Probability Of Detection ◽

Mean Annual Precipitation ◽

Extreme Rainfall Events ◽

Rainfall Events ◽

Time Aggregation ◽

Spatial Coverage ◽

Rainfall Detection

Many studies have shown a growing trend in terms of frequency and severity of extreme events. As never before, having tools capable to monitor the amount of rain that reaches the Earth’s surface has become a key point for the identification of areas potentially affected by floods. In order to guarantee an almost global spatial coverage, NASA Global Precipitation Measurement (GPM) IMERG products proved to be the most appropriate source of information for precipitation retrievement by satellite. This study is aimed at defining the IMERG accuracy in representing extreme rainfall events for varying time aggregation intervals. This is performed by comparing the IMERG data with the rain gauge ones. The outcomes demonstrate that precipitation satellite data guarantee good results when the rainfall aggregation interval is equal to or greater than 12 h. More specifically, a 24-h aggregation interval ensures a probability of detection (defined as the number of hits divided by the total number of observed events) greater than 80%. The outcomes of this analysis supported the development of the updated version of the ITHACA Extreme Rainfall Detection System (ERDS: erds.ithacaweb.org). This system is now able to provide near real-time alerts about extreme rainfall events using a threshold methodology based on the mean annual precipitation.

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Bias Adjustment of Satellite Precipitation Estimation Using Ground-Based Observation: Mei-Yu Front Case Studies in Taiwan

Asia-Pacific Journal of Atmospheric Sciences ◽

10.1007/s13143-019-00152-7 ◽

2019 ◽

Vol 56 (3) ◽

pp. 485-492 ◽

Cited By ~ 2

Author(s):

Nan-Ching Yeh ◽

Yao-Chung Chuang ◽

Hsin-Shuo Peng ◽

Kuo-Lin Hsu

Keyword(s):

Regression Analysis ◽

Correlation Coefficient ◽

High Elevation ◽

Rainfall Estimation ◽

Target Region ◽

Satellite Precipitation ◽

Local Correction ◽

Precipitation Estimation ◽

Accumulated Rainfall ◽

Central Weather Bureau

AbstractThe Global Satellite Mapping of Precipitation (GSMaP) was used to estimate the accumulated rainfall in May from the Mei-Yu front in Taiwan. Rainfall estimation from GSMaP during 2002–2017 were evaluated using more than 400 local gauge observations, collected from the Taiwan Central Weather Bureau (CWB). Studies have demonstrated that the GSMaP rainfall estimation estimates can be biased, depending on the target region, elevation, and season. In this experiment, we have evaluated GSMaP over three elevation ranges. The GSMaP systemic errors for each elevation range were identified and corrected using regression analysis. The results indicated that GSMaP estimation can be improved significantly through adjustment over three elevation ranges (elevation less than 50 m, elevation of 50–100 m, and elevation higher than 100 m). For these three elevation ranges, the correlation coefficient between the GSMaP estimations and CWB rainfall data was 0.76, 0.78, and 0.59, respectively. This indicated that the GSMaP estimation was more accurate for low-elevation regions than high-elevation regions. After the proposed approaches were employed to correct the errors, the bias errors were respectively improved by 5.64(13.7%), 7.33(38.4%) and 10.52(31.2%) mm for low-, mid- and high-elevation regions. This study demonstrated that the local correction approaches can be used to improve GSMaP estimation of Mei-Yu rainfall in Taiwan.

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Deep Learning for Precipitation Estimation from Satellite and Rain Gauges Measurements

Remote Sensing ◽

10.3390/rs11212463 ◽

2019 ◽

Vol 11 (21) ◽

pp. 2463

Author(s):

Arthur Moraux ◽

Steven Dewitte ◽

Bruno Cornelis ◽

Adrian Munteanu

Keyword(s):

Deep Learning ◽

Multiscale Analysis ◽

Mean Squared Error ◽

Rain Gauge ◽

Probability Of Detection ◽

Precipitation Rate ◽

Rain Gauges ◽

Squared Error ◽

Precipitation Estimation ◽

Deep Learning Model

This paper proposes a multimodal and multi-task deep-learning model for instantaneous precipitation rate estimation. Using both thermal infrared satellite radiometer and automatic rain gauge measurements as input, our encoder–decoder convolutional neural network performs a multiscale analysis of these two modalities to estimate simultaneously the rainfall probability and the precipitation rate value. Precipitating pixels are detected with a Probability Of Detection (POD) of 0.75 and a False Alarm Ratio (FAR) of 0.3. Instantaneous precipitation rate is estimated with a Root Mean Squared Error (RMSE) of 1.6 mm/h.

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