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Tropical Cyclone related Precipitation Feature - Global Hydrology Resource Center (ODIS id: 1471)

This resource is online Last check was 04/05/2024 03:34
First entry: 22/01/2021 Last update: 03/07/2021
Submitter/Owner of this record Mr. Cristian Muñoz Mas ( OceanExpert : 30291 )
Submitter/Owner Role IODE Secretariat
Datasource URL https://ghrc.nsstc.nasa.gov/tcpf/index.html
Parent Project URL https://earthdata.nasa.gov/
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English name Tropical Cyclone related Precipitation Feature - Global Hydrology Resource Center
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Acronym TCPF - GHRC
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Abstract There has been a major improvement in tropical cyclone (TC) track forecasting in the past decade. However, the prediction of TC intensity change and rainfall is still challenging, and of immense practical importance. One of the critical questions in TC research is what the necessary and sufficient conditions are for TC intensification, and especially rapid intensification (RI). Favorable large-scale environmental conditions that are near-universally agreed to be necessary include: warm sea surface temperature (SST), high low- to mid-level moisture, and low vertical wind shear. Other factors such as high ocean heat content (Shay et al. 2000), enhanced heat and moisture flux (Bosart et al. 2000), and whether a TC is well below its maximum potential intensity (Kaplan and DeMaria 2003) were also found to be related to RI. Defining sufficient conditions is still controversial, especially the possible role of intense convective events. Early studies suggested that hot towers (Simpson et al. 1998) and convective bursts (Steranka et al. 1986) near the eye are related to TC intensity change. Recent modeling studies (Hendricks et al. 2004, and Montgomery et al. 2006) proposed that intense vortical hot towers may be a missing link in the chain of events that transforms a mid-level vortex into a near-surface vortex, initiating TC genesis and perhaps also RI. This model-based result needs to be evaluated by observational studies not only on a case-study base, but more importantly in a statistical manner. A previous observational study (Cecil and Zipser 1999) presented evidence that a relationship exists between intense convection and TC intensity using the 85 GHz ice-scattering signature observed by SSM/I, but that the total rain rate in the inner core has a better relationship. Recent observational studies also found that the chance of TC intensification increases when one or more hot towers exist in the eyewall using a limited subset of TRMM precipitation radar data (Kelley et al. 2004) and WSR-88D radar data (Kelley et al. 2005). Yet uncertainties remain and additional quantification with a larger database is highly desirable. In recent decades, fresh water flooding has become one of the main threats to human life when a TC makes landfall (Rappaport 2000). The rainfall climatology and persistence model (R-CLIPER, Tuleya et al. 2007) is one of the major tools used by the National Hurricane Center (NHC) for TC rainfall forecasts. The operational R-CLIPER uses radial distributions of azimuthally averaged TC rain rates derived from satellite to construct an instantaneous rainfall footprint as a function of storm intensity (Lonfat et al. 2007). The improvement of the statistical rainfall prediction technique highly relies on satellite-based rainfall estimations. The Tropical Rainfall Measuring Mission (TRMM, Kummerow et al., 1998) marks the first time that TCs in all ocean basins can be viewed by high resolution down-looking precipitation radar. After 12 years of successful operation, TRMM measurements, along with other NASA satellite measurements such as QuikSCAT and numerical model-based reanalysis, have provided invaluable sources of TC data for the study of TC intensification, rainfall, and environment. The University of Utah TRMM Precipitation Feature database (UU TRMM PF) provides a very useful tool to analyze convective intensity over the global tropics using several TRMM-observed proxies. For studying TCs, a subset of the UU TRMM PF database is built, called the Tropical Cyclone related Precipitation Feature (TCPF) database, with TC best track information incorporated into it.
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