The Tropical Rainfall Potential (TRaP) Technique. Part I: Description and Examples

Abstract Inland flooding caused by heavy rainfall from landfalling tropical cyclones is a significant threat to life and property. The tropical rainfall potential (TRaP) technique, which couples satellite estimates of rain rate in tropical cyclones with track forecasts to produce a forecast of 24-h rainfall from a storm, was developed to better estimate the magnitude of this threat. This paper outlines the history of the TRaP technique, details its current algorithms, and offers examples of its use in forecasting. Part II of this paper covers verification of the technique.

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A case study for cyclone ‘Aila’ for forecasting rainfall using satellite derived rain rate data

MAUSAM ◽

10.54302/mausam.v64i1.656 ◽

2022 ◽

Vol 64 (1) ◽

pp. 77-82

Author(s):

HABIBURRAHAMAN BISWAS ◽

P.K. KUNDU ◽

D. PRADHAN

Keyword(s):

Tropical Cyclone ◽

Tropical Cyclones ◽

Storm Track ◽

Tropical Rainfall Measuring Mission ◽

Tropical Rainfall ◽

Cyclone Aila ◽

Potential Trap ◽

Landfalling Tropical Cyclones ◽

Rain Rates

caxky dh [kkM+h esa cuus ,oa tehu ls Vdjkus okys pØokrh; rwQkuksa ds ifj.kkeLo:i Hkkjh o"kkZ dh otg ls if’pe caxky ds rV lesr Hkkjr ds iwohZ rV ds yksxksa dh tku eky dks dkQh [krjk jgrk gSA tehu ls Vdjkus okys m".kdfVca/kh; pØokrh rwQkuksa dh otg ls gksus okyh o"kkZ dh ek=k dk iwokZuqeku djuk cgqr dfBu gSA m".kdfVca/kh; pØokrh; rwQkuksa ds nk;js esa vkus okys o"kkZ okys {ks=ksa esa laHkkfor pØokrh; rwQku ls gksus okys o"kkZ lap;u dk iwokZuqeku djus ds fy, mixzg ls izkIr o"kkZ njksa dk mi;ksx fd;k tk ldrk gSA bl 'kks/k i= esa ‘vkbyk’ ds m".kdfVca/kh; o"kkZ ekiu fe’ku ¼Vh- vkj- ,e- ,e-½] mixzg o"kkZ nj vk¡dM+ksa rFkk rwQku ds ns[ks x, ekxZ dk mi;ksx djrs gq, m".kdfVca/kh; pØokr ‘vkbyk’ ds tehu ls Vdjkus ls 24 ?kVsa igys rVh; LVs’kuksa ij o"kkZ dk vkdyu djus dk iz;kl fd;k x;k gSA la;qDr jkT; vesfjdk esa fodflr lqifjfpr rduhd ds vk/kkj ij m".kdfVca/kh; pØokr ‘vkbyk’ ds tehu ls Vdjkus ds 24 ?kaVs igys m".kdfVca/kh; o"kkZ foHko ¼Vh- vkj- ,- ih-½ iwokZuqeku fo’ks"k :i ls rwQku dh fn’kk ds lkeus vkus okys rVh; {ks=ksa ds fy, vPNh o"kkZ dk iwokZuqeku miyC/k djkrk gSA Major threat to the life and property of people on the east coast of India, including West Bengal Coast, is due to very heavy rainfall from landfalling tropical cyclones originated over Bay of Bengal. Forecasting magnitude of rainfall from landfalling tropical cyclones is very difficult. Satellite derived rain rates over the raining areas of tropical cyclones can be used to forecast potential tropical cyclone rainfall accumulations. In the present study, an attempt has been made to estimate 24 hours rainfall over coastal stations before landfall of tropical Cyclone ‘Aila’ using Tropical Rainfall Measuring Mission (TRMM) satellite rain rates data and observed storm track of Aila. Forecast Tropical Rainfall Potential (TRaP), 24 hours prior to landfall for the tropical cyclone ‘Aila’ based on well known technique developed in USA, provides a good rainfall forecast especially for the coastal areas lying at the head of direction of the storm.

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The Inland Maintenance and Reintensification of Tropical Storm Bill (2015) Part 1: Contributions of the Brown Ocean Effect

Journal of Hydrometeorology ◽

10.1175/jhm-d-20-0150.1 ◽

2021 ◽

Author(s):

Ryann A. Wakefield ◽

Jeffrey B. Basara ◽

J. Marshall Shepherd ◽

Noah Brauer ◽

Jason C. Furtado ◽

...

Keyword(s):

Tropical Cyclones ◽

Land Surface ◽

Heavy Rainfall ◽

Tropical Storm ◽

Sea Surface ◽

Ocean Effect ◽

Novel Approaches ◽

Landfalling Tropical Cyclones ◽

Water Vapor Budget

AbstractLandfalling tropical cyclones (TCs) often decay rapidly due to a decrease in moisture and energy fluxes over land when compared to the ocean surface. Occasionally, however, these cyclones maintain intensity or reintensify over land. Post-landfall maintenance and intensification of TCs over land may be a result of fluxes of moisture and energy derived from anomalously wet soils. These soils act similarly to a warm sea surface, in a phenomenon coined the “Brown Ocean Effect.” Tropical Storm (TS) Bill (2015) made landfall over a region previously moistened by anomalously heavy rainfall and displayed periods of reintensification and maintenance over land. This study evaluates the role of the Brown Ocean Effect on the observed maintenance and intensification of TS Bill using a combination of existing and novel approaches, including the evaluation of precursor conditions at varying temporal scales and making use of composite backward trajectories. Comparisons were made to landfalling TCs with similar paths that did not undergo TC maintenance and/or intensification (TCMI) as well as to TS Erin (2007), a known TCMI case. We show that the antecedent environment prior to TS Bill was similar to other known TCMI cases, but drastically different from the non-TCMI cases analyzed in this study. Furthermore, we show that contributions of evapotranspiration to the overall water vapor budget were non-negligible prior to TCMI cases and that evapotranspiration along storm inflow was significantly (p<0.05) greater for TCMI cases than non-TCMI cases suggesting a potential upstream contribution from the land surface.

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Recent global decrease in the inner-core rain rate of tropical cyclones

Nature Communications ◽

10.1038/s41467-021-22304-y ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Shifei Tu ◽

Jianjun Xu ◽

Johnny C. L. Chan ◽

Kian Huang ◽

Feng Xu ◽

...

Keyword(s):

Water Vapor ◽

Numerical Model ◽

Surface Temperature ◽

Tropical Cyclones ◽

Heavy Rainfall ◽

Rain Rate ◽

Inner Core ◽

Atmospheric Stability ◽

Outer Region ◽

The Other

AbstractHeavy rainfall is one of the major aspects of tropical cyclones (TC) and can cause substantial damages. Here, we show, based on satellite observational rainfall data and numerical model results, that between 1999 and 2018, the rain rate in the outer region of TCs has been increasing, but it has decreased significantly in the inner-core. Globally, the TC rain rate has increased by 8 ± 4% during this period, which is mainly contributed by an increase in rain rate in the TC outer region due to increasing water vapor availability in the atmosphere with rising surface temperature. On the other hand, the rain rate in the inner-core of TCs has decreased by 24 ± 3% during the same period. The decreasing trend in the inner-core rain rate likely results mainly from an increase in atmospheric stability.

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Diurnal Cycle of Rainfall Associated with Landfalling Tropical Cyclones in China from Rain Gauge Observations

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-16-0335.1 ◽

2017 ◽

Vol 56 (9) ◽

pp. 2595-2605 ◽

Cited By ~ 8

Author(s):

Hao Hu ◽

Yihong Duan ◽

Yuqing Wang ◽

Xinghai Zhang

Keyword(s):

Tropical Cyclones ◽

Diurnal Cycle ◽

Rain Rate ◽

Inner Core ◽

Outer Region ◽

Rain Gauge ◽

Core Region ◽

The Core ◽

Storm Center ◽

Landfalling Tropical Cyclones

AbstractThe diurnal variation of rainfall over China associated with landfalling tropical cyclones (TCs) is investigated using hourly rain gauge observations obtained from 2425 conventional meteorological stations in China. Records between 12 h prior to landfall and 12 h after landfall of 450 landfalling TCs in China from 1957 to 2014 are selected as samples. The harmonic analysis shows an obvious diurnal signal in TC rainfall with a rain-rate peak in the early morning and a minimum in the afternoon. The diurnal cycle in the outer region (between 400- and 900-km radii from the storm center) is found to be larger than in the core region (within 400 km of the storm center). This could be attributed to the effect of land on the inner core of the storms as the diurnal cycle is distinct in the core region well before landfall. As the result of this diurnal cycle, TCs making landfall at night tend to have cumulative precipitation, defined as the precipitation cumulated from the time at landfall to 12 h after landfall, about 30% larger than those making landfall around noon or afternoon. Moreover, the radial propagation of the diurnal cycle in TC rain rate, which has been a controversial phenomenon in some previous studies with remote sensing observations, was not present in this study that is based on rain gauge observations. Results also show that the diurnal signal has little dependence on the storm intensity 12 h prior to landfall.

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Data Assimilation of High-Resolution Satellite Rainfall Product Improves Rainfall Simulation Associated with Landfalling Tropical Cyclones in the Yangtze River Delta

Remote Sensing ◽

10.3390/rs12020276 ◽

2020 ◽

Vol 12 (2) ◽

pp. 276 ◽

Cited By ~ 1

Author(s):

Jie Wang ◽

Youpeng Xu ◽

Long Yang ◽

Qiang Wang ◽

Jia Yuan ◽

...

Keyword(s):

Tropical Cyclones ◽

Yangtze River ◽

Heavy Rainfall ◽

Wrf Model ◽

Yangtze River Delta ◽

Rainfall Events ◽

Precipitation Product ◽

Landfalling Tropical Cyclones ◽

Heavy Rainfall Events ◽

The Yangtze River Delta

Floods caused by heavy rainfall events associated with landfalling tropical cyclones (TCs) represent a major risk for the Yangtze River Delta (YRD) region of China. Accurate extreme precipitation forecasting, at long lead times, is crucial for the improvement of flood prevention and warning. However, accurate prediction of timing, location, and intensity of the heavy rainfall events is a major challenge for the Numerical Weather Prediction (NWP). In this study, high-resolution satellite precipitation products like Global Precipitation Measurement (GPM) are evaluated at the hourly timescale, and the optimal Integrated Multi-satellite Retrievals for GPM (IMERG) precipitation product is selected and applied to directly assimilate into the Weather Research and Forecasting (WRF) model via the four-dimensional variational (4D-Var) method. The TC Jondari and Rumbia events of August 2018 are evaluated to analyze the performance of the WRF model with the 4D-Var method assimilated IMERG precipitation product (DA-IMERG) and the conventional observation (DA-CONV) for real-time heavy rainfall forecasting. The results indicate that (1) IMERG precipitation products were larger and wetter than the observed precipitation values over YRD. By comparison, the performance of “late” run precipitation product (IMERG-L) was the closest to the observation data with lower deviation and higher detection capability; (2) DA-IMERG experiment substantially affected the magnitude of the WRF model primary variables, which changed the precipitation pattern of the TC heavy rain. (3) DA-IMERG experiment further improved the forecast of heavy rainbands and relatively reduced erroneous detection rate than CTL and DA-CONV experiments at the grid scale. Meanwhile, the DA-IMERG experiment has a better fractions skill score (FSS) value (especially in the threshold of 10 mm/h) than DA-CONV for TC Jondari and Rumbia at the spatial scale, while it shows a lower performance than CTL and DA-CONV experiments when the threshold is lower than the 5 mm/h for the TC Rumbia.

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A Potential Risk Index Dataset for Landfalling Tropical Cyclones over the Chinese Mainland (PRITC dataset V1.0)

Advances in Atmospheric Sciences ◽

10.1007/s00376-021-0365-y ◽

2021 ◽

Vol 38 (10) ◽

pp. 1791-1802

Author(s):

Peiyan Chen ◽

Hui Yu ◽

Kevin K. W. Cheung ◽

Jiajie Xin ◽

Yi Lu

Keyword(s):

Tropical Cyclones ◽

Potential Risk ◽

Risk Index ◽

Chinese Mainland ◽

Current Version ◽

Term Trend ◽

The Chinese Mainland ◽

Landfalling Tropical Cyclones ◽

Long Term Trend

AbstractA dataset entitled “A potential risk index dataset for landfalling tropical cyclones over the Chinese mainland” (PRITC dataset V1.0) is described in this paper, as are some basic statistical analyses. Estimating the severity of the impacts of tropical cyclones (TCs) that make landfall on the Chinese mainland based on observations from 1401 meteorological stations was proposed in a previous study, including an index combining TC-induced precipitation and wind (IPWT) and further information, such as the corresponding category level (CAT_IPWT), an index of TC-induced wind (IWT), and an index of TC-induced precipitation (IPT). The current version of the dataset includes TCs that made landfall from 1949–2018; the dataset will be extended each year. Long-term trend analyses demonstrate that the severity of the TC impacts on the Chinese mainland have increased, as embodied by the annual mean IPWT values, and increases in TCinduced precipitation are the main contributor to this increase. TC Winnie (1997) and TC Bilis (2006) were the two TCs with the highest IPWT and IPT values, respectively. The PRITC V1.0 dataset was developed based on the China Meteorological Administration’s tropical cyclone database and can serve as a bridge between TC hazards and their social and economic impacts.

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On the Relationship between Intensity and Rainfall Distribution in Tropical Cyclones Making Landfall over China

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-16-0334.1 ◽

2017 ◽

Vol 56 (10) ◽

pp. 2883-2901 ◽

Cited By ~ 26

Author(s):

Zifeng Yu ◽

Yuqing Wang ◽

Haiming Xu ◽

Noel Davidson ◽

Yandie Chen ◽

...

Keyword(s):

Tropical Cyclones ◽

Rain Rate ◽

Vertical Wind Shear ◽

Intensity Change ◽

Total Rainfall ◽

Rainfall Distribution ◽

Rain Area ◽

Maximum Rainfall ◽

Rain Rates ◽

The Relationship

AbstractTRMM satellite 3B42 rainfall estimates for 133 landfalling tropical cyclones (TCs) over China during 2001–15 are used to examine the relationship between TC intensity and rainfall distribution. The rain rate of each TC is decomposed into axisymmetric and asymmetric components. The results reveal that, on average, axisymmetric rainfall is closely related to TC intensity. Stronger TCs have higher averaged peak axisymmetric rain rates, more averaged total rain, larger averaged rain areas, higher averaged rain rates, higher averaged amplitudes of the axisymmetric rainfall, and lower amplitudes of wavenumbers 1–4 relative to the total rainfall. Among different TC intensity change categories, rapidly decaying TCs show the most rapid decrease in both the total rainfall and the axisymmetric rainfall relative to the total rain. However, the maximum total rain, maximum rain area, and maximum rain rate are not absolutely dependent on TC intensity, suggesting that stronger TCs do not have systematically higher maximum rain rates than weaker storms. Results also show that the translational speed of TCs has little effect on the asymmetric rainfall distribution in landfalling TCs. The maximum rainfall of both the weaker and stronger TCs is generally located downshear to downshear left. However, when environmental vertical wind shear (VWS) is less than 5 m s−1, the asymmetric rainfall maxima are more frequently located upshear and onshore, suggesting that in weak VWS environments the coastline could have a significant effect on the rainfall asymmetry in landfalling TCs.

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RELATIONSHIP BETWEEN HIMAWARI-8-DERIVED OVERSHOOTING TOPS AND EXTREME WEATHER EVENTS IN SOUTHEAST ASIA

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xli-b7-325-2016 ◽

2016 ◽

Vol XLI-B7 ◽

pp. 325-327

Author(s):

H. M. Park ◽

M. A. Kim ◽

J. Im

Keyword(s):

Heavy Rainfall ◽

Rain Rate ◽

Deep Convection ◽

Weather Prediction ◽

Extreme Weather Events ◽

Strong Wind ◽

Atmospheric Conditions ◽

Machine Learning Methods ◽

Weather Events ◽

Strong Convection

Severe weathers such as heavy rainfall, floods, strong wind, and lightning are closely related with the strong convection activities of atmosphere. Overshooting tops sometimes occur by deep convection above tropopause, penetrating into the lower stratosphere. Due to its high potential energy, the detection of OT is crucial to understand the climatic phenomena. Satellite images are useful to detect the dynamics of atmospheric conditions using cloud observation. This study used machine learning methods for extracting OTs. The reference cases were built using CloudSat, CALIPSO, and Numerical Weather Prediction (NWP) data with Himawari-8 imagery. As reference cases, 11 OT events were detected. The aim of this study is the investigation of relationship between OTs cases and the occurrences of heavy rainfall. For investigation of OT effects, TRMM daily rain rate data (mm/hr) were collected and averaged at 25 km intervals until 250km from the center of OT cases. As the result, precipitation rate clearly coincides with the distance from the center of OT occurrence.

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