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

MAUSAM ◽  
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.

Investigation of PR and TMI Version 6 and Version 7 Rainfall Algorithms in Landfalling Tropical Cyclones Relative to the NEXRAD Stage-IV Multisensor Precipitation Estimate Dataset

2013 ◽  
Vol 52 (12) ◽  
pp. 2809-2827 ◽  
Author(s):  
Joseph P. Zagrodnik ◽  
Haiyan Jiang
Keyword(s):  
Tropical Cyclones ◽  
Stage Iv ◽  
Tropical Rainfall Measuring Mission ◽  
Heavy Rain ◽  
Light Rain ◽  
Hourly Rainfall ◽  
Wide Range ◽  
Landfalling Tropical Cyclones ◽  
Rain Rates ◽  
Rainfall Estimates

AbstractRainfall estimates from versions 6 (V6) and 7 (V7) of the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) 2A25 and Microwave Imager (TMI) 2A12 algorithms are compared relative to the Next Generation Weather Radar (NEXRAD) Multisensor Precipitation Estimate stage-IV hourly rainfall product. The dataset consists of 252 TRMM overpasses of tropical cyclones from 2002 to 2010 within a 230-km range of southeastern U.S. Weather Surveillance Radar-1988 Doppler (WSR-88D) sites. All rainfall estimates are averaged to a uniform 1/7° square grid. The grid boxes are also divided by their TMI surface designation (land, ocean, or coast). A detailed statistical analysis is undertaken to determine how changes to the TRMM rainfall algorithms in the latest version (V7) are influencing the rainfall retrievals relative to ground reference data. Version 7 of the PR 2A25 is the best-performing algorithm over all three surface types. Over ocean, TMI 2A12 V7 is improved relative to V6 at high rain rates. At low rain rates, the new ocean TMI V7 probability-of-rain parameter creates ambiguity in differentiating light rain (≤0.5 mm h−1) and nonraining areas. Over land, TMI V7 underestimates stage IV more than V6 does at a wide range of rain rates, resulting in an increased negative bias. Both versions of the TMI coastal algorithm are also negatively biased at both moderate and heavy rain rates. Some of the TMI biases can be explained by uncertain relationships between rain rate and 85-GHz ice scattering.

Convective and Rainfall Properties of Tropical Cyclone Inner Cores and Rainbands from 11 Years of TRMM Data

2013 ◽  
Vol 141 (2) ◽  
pp. 431-450 ◽  
Author(s):  
Haiyan Jiang ◽  
Ellen M. Ramirez ◽  
Daniel J. Cecil
Keyword(s):  
Tropical Cyclone ◽  
Tropical Cyclones ◽  
Radial Distribution ◽  
Inner Core ◽  
Tropical Rainfall Measuring Mission ◽  
Passive Microwave ◽  
Rainfall Characteristics ◽  
Tropical Rainfall

Abstract Convective and rainfall properties of tropical cyclones (TCs) are statistically quantified by using Tropical Rainfall Measuring Mission (TRMM) data from December 1997 to December 2008. A semimanual method is used to divide the TC raining area into inner core (IC), inner rainband (IB), and outer rainband (OB) regions. Precipitation features (PFs) within these regions are compared for their convective vigor and rainfall characteristics based on passive microwave, infrared, radar, and lightning properties. Strong convective signatures are generally found more often in precipitation features in the IC region, less often in the IB region, and least often in the OB region when examining features with sizes greater than 1000 km2. However, at the very strong end of the convective spectrum, the magnitude of ice scattering signatures in OB features tends to be comparable and even stronger than that in IC features. The flash density when normalized by the raining area is about 2–3 times higher in IC features than that in OB features for all TCs except for category-1–2 hurricanes, in which the flash density is comparable for IC and OB features. The flash count per raining area in IB features is a factor of 2 (4) lower than that in OB (IC) features for all TC intensity categories on average. This confirms the bimodal radial distribution of flash density as suggested by previous studies. However, instead of a weaker maximum in the IC region and a stronger maximum in the OB region, this study finds a stronger maximum in the IC region and a weaker maximum in the OB region.

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

2005 ◽  
Vol 20 (4) ◽  
pp. 456-464 ◽  
Author(s):  
Stanley Q. Kidder ◽  
John A. Knaff ◽  
Sheldon J. Kusselson ◽  
Michael Turk ◽  
Ralph R. Ferraro ◽  
...  
Keyword(s):  
Tropical Cyclones ◽  
Heavy Rainfall ◽  
Rain Rate ◽  
Tropical Rainfall ◽  
History Of ◽  
Potential Trap ◽  
Landfalling Tropical Cyclones ◽  
Inland Flooding ◽  
Threat To Life

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.

scholarly journals Statistical Prediction of Integrated Kinetic Energy in North Atlantic Tropical Cyclones

2014 ◽  
Vol 142 (12) ◽  
pp. 4646-4657 ◽  
Author(s):  
Michael E. Kozar ◽  
Vasubandhu Misra
Keyword(s):  
Tropical Cyclone ◽  
Kinetic Energy ◽  
Tropical Cyclones ◽  
North Atlantic ◽  
Storm Track ◽  
Statistical Prediction ◽  
Normal Regression ◽  
Spike Model ◽  
Training Interval ◽  
Training Exercises

Abstract Integrated kinetic energy (IKE) is a useful quantity that measures the size and strength of a tropical cyclone wind field. As a result, it is inherently related to the destructive potential of these powerful storms. In most current operational settings, there are limited resources designed to assess the IKE of a tropical cyclone because storm track and maximum intensity are typically prioritized. Therefore, to complement existing forecasting tools, a statistical scheme is created to project fluctuations of IKE in North Atlantic tropical cyclones for several forecast intervals out to 72 h. The resulting scheme, named Statistical Prediction of Integrated Kinetic Energy (SPIKE), utilizes multivariate normal regression models trained on environmental and storm-related predictors from all North Atlantic tropical cyclones occurring from 1990 to 2011. During this training interval, SPIKE outperforms persistence and is capable of explaining more than 80% of observed variance in total IKE values at a forecast interval of 12 h, trailing down to just below 60% explained variance at an interval of 72 h. The skill of the SPIKE model is evaluated further using bootstrapping exercises in order to gauge the predictive abilities of the statistical scheme. In addition, the performance of the SPIKE model is also evaluated for the 2012 Atlantic hurricane season, which notably falls outside of the training interval. Ultimately, the validation exercises return shared variance scores similar to those found in the training exercises, serving as a proof of concept that the SPIKE model can be used to project IKE values when given accurate predictor data.

Tropical Cyclogenesis Associated with Kelvin Waves and the Madden–Julian Oscillation

2011 ◽  
Vol 139 (9) ◽  
pp. 2723-2734 ◽  
Author(s):  
Carl J. Schreck ◽  
John Molinari
Keyword(s):  
Tropical Cyclone ◽  
Tropical Cyclones ◽  
North Pacific ◽  
Western North Pacific ◽  
Diabatic Heating ◽  
Kelvin Waves ◽  
Tropical Cyclogenesis ◽  
Madden Julian Oscillation ◽  
Convective Envelope

The Madden–Julian oscillation (MJO) influences tropical cyclone formation around the globe. Convectively coupled Kelvin waves are often embedded within the MJO, but their role in tropical cyclogenesis remains uncertain. This case study identifies the influences of the MJO and a series of Kelvin waves on the formation of two tropical cyclones. Typhoons Rammasun and Chataan developed in the western North Pacific on 28 June 2002. Two weeks earlier, conditions had been unfavorable for tropical cyclogenesis because of uniform trade easterlies and a lack of organized convection. The easterlies gave way to equatorial westerlies as the convective envelope of the Madden–Julian oscillation moved into the region. A series of three Kelvin waves modulated the development of the westerlies. Cyclonic potential vorticity (PV) developed in a strip between the growing equatorial westerlies and the persistent trade easterlies farther poleward. Rammasun and Chataan emerged from the apparent breakdown of this strip. The cyclonic PV developed in association with diabatic heating from both the MJO and the Kelvin waves. The tropical cyclones also developed during the largest superposition of equatorial westerlies from the MJO and the Kelvin waves. This chain of events suggests that the MJO and the Kelvin waves each played a role in the development of Rammasun and Chataan.

The Tropical Rainfall Potential (TRaP) Technique. Part II: Validation

2005 ◽  
Vol 20 (4) ◽  
pp. 465-475 ◽  
Author(s):  
Ralph Ferraro ◽  
Paul Pellegrino ◽  
Michael Turk ◽  
Wanchun Chen ◽  
Shuang Qiu ◽  
...  
Keyword(s):  
Information Service ◽  
Storm Track ◽  
Stage Iv ◽  
Retrieval Algorithm ◽  
Maximum Rainfall ◽  
Tropical Rainfall ◽  
Hourly Rainfall ◽  
Potential Trap ◽  
Eta Model ◽  
Rainfall Estimates

Abstract Satellite analysts at the Satellite Services Division (SSD) of the National Environmental, Satellite, Data, and Information Service (NESDIS) routinely generate 24-h rainfall potential for all tropical systems that are expected to make landfall within 24 to at most 36 h and are of tropical storm or greater strength (>65 km h−1). These estimates, known as the tropical rainfall potential (TRaP), are generated in an objective manner by taking instantaneous rainfall estimates from passive microwave sensors, advecting this rainfall pattern along the predicted storm track, and accumulating rainfall over the next 24 h. In this study, the TRaPs generated by SSD during the 2002 Atlantic hurricane season have been validated using National Centers for Environmental Prediction (NCEP) stage IV hourly rainfall estimates. An objective validation package was used to generate common statistics such as correlation, bias, root-mean-square error, etc. It was found that by changing the minimum rain-rate threshold, the results could be drastically different. It was determined that a minimum threshold of 25.4 mm day−1 was appropriate for use with TRaP. By stratifying the data by different criteria, it was discovered that the TRaPs generated using Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) rain rates, with its optimal set of measurement frequencies, improved spatial resolution, and advanced retrieval algorithm, produced the best results. In addition, the best results were found for TRaPs generated for storms that were between 12 and 18 h from landfall. Since the TRaP is highly dependent on the forecast track of the storm, selected TRaPs were rerun using the observed track contained in the NOAA/Tropical Prediction Center (TPC) “best track.” Although some TRaPs were not significantly improved by using this best track, significant improvements were realized in some instances. Finally, as a benchmark for the usefulness of TRaP, comparisons were made to Eta Model 24-h precipitation forecasts as well as three climatological maximum rainfall methods. It was apparent that the satellite-based TRaP outperforms the Eta Model in virtually every statistical category, while the climatological methods produced maximum rainfall totals closer to the stage IV maximum amounts when compared with TRaP, although these methods are for storm totals while TRaP is for a 24-h period.

scholarly journals Ground Validation for the Tropical Rainfall Measuring Mission (TRMM)

2005 ◽  
Vol 22 (4) ◽  
pp. 365-380 ◽  
Author(s):  
David B. Wolff ◽  
D. A. Marks ◽  
E. Amitai ◽  
D. S. Silberstein ◽  
B. L. Fisher ◽  
...  
Keyword(s):  
Tropical Rainfall Measuring Mission ◽  
Rain Gauge ◽  
Marshall Islands ◽  
Error Statistics ◽  
Tropical Rainfall ◽  
Nasa Goddard Space ◽  
Ground Validation ◽  
Microwave Imager ◽  
Rain Rates ◽  
Good Agreement

Abstract An overview of the Tropical Rainfall Measuring Mission (TRMM) Ground Validation (GV) Program is presented. This ground validation (GV) program is based at NASA Goddard Space Flight Center in Greenbelt, Maryland, and is responsible for processing several TRMM science products for validating space-based rain estimates from the TRMM satellite. These products include gauge rain rates, and radar-estimated rain intensities, type, and accumulations, from four primary validation sites (Kwajalein Atoll, Republic of the Marshall Islands; Melbourne, Florida; Houston, Texas; and Darwin, Australia). Site descriptions of rain gauge networks and operational weather radar configurations are presented together with the unique processing methodologies employed within the Ground Validation System (GVS) software packages. Rainfall intensity estimates are derived using the Window Probability Matching Method (WPMM) and then integrated over specified time scales. Error statistics from both dependent and independent validation techniques show good agreement between gauge-measured and radar-estimated rainfall. A comparison of the NASA GV products and those developed independently by the University of Washington for a subset of data from the Kwajalein Atoll site also shows good agreement. A comparison of NASA GV rain intensities to satellite retrievals from the TRMM Microwave Imager (TMI), precipitation radar (PR), and Combined (COM) algorithms is presented, and it is shown that the GV and satellite estimates agree quite well over the open ocean.

scholarly journals Hurricane GPROF: An Optimized Ocean Microwave Rainfall Retrieval for Tropical Cyclones

2016 ◽  
Vol 33 (7) ◽  
pp. 1539-1556 ◽  
Author(s):  
Paula J. Brown ◽  
Christian D. Kummerow ◽  
David L. Randel
Keyword(s):  
Tropical Cyclones ◽  
Vertical Profile ◽  
Rain Rate ◽  
Tropical Rainfall Measuring Mission ◽  
Initial Assessment ◽  
Trmm Precipitation ◽  
Microwave Imager ◽  
One Year ◽  
Trmm Microwave Imager ◽  
Rain Rates

AbstractThe Goddard profiling algorithm (GPROF) is an operational passive microwave retrieval that uses a Bayesian scheme to estimate rainfall. GPROF 2014 retrieves rainfall and hydrometeor vertical profile information based upon a database of profiles constructed to be simultaneously consistent with Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and TRMM Microwave Imager (TMI) observations. A small number of tropical cyclones are in the current database constructed from one year of TRMM data, resulting in the retrieval performing relatively poorly for these systems, particularly for the highest rain rates. To address this deficiency, a new database focusing specifically on hurricanes but consisting of 9 years of TRMM data is created. The new database and retrieval procedure for TMI and GMI is called Hurricane GPROF. An initial assessment of seven tropical cyclones shows that Hurricane GPROF provides a better estimate of hurricane rain rates than GPROF 2014. Hurricane GPROF rain-rate errors relative to the PR are reduced by 20% compared to GPROF, with improvements in the lowest and highest rain rates especially. Vertical profile retrievals for four hydrometeors are also enhanced, as error is reduced by 30% compared to the GPROF retrieval, relative to PR estimates. When compared to the full database of tropical cyclones, Hurricane GPROF improves the RMSE and MAE of rain-rate estimates over those from GPROF by about 22% and 27%, respectively. Similar improvements are also seen in the overall rain-rate bias for hurricanes in the database, which is reduced from 0.20 to −0.06 mm h−1.

Sign in / Sign up

Export Citation Format

Share Document