scholarly journals Relating Passive 37-GHz Scattering to Radar Profiles in Strong Convection

2011 ◽  
Vol 50 (1) ◽  
pp. 233-240 ◽  
Author(s):  
Daniel J. Cecil
Keyword(s):  
Central Africa ◽  
Tropical Rainfall Measuring Mission ◽  
The United States ◽  
Phase Layer ◽  
Tropical Ocean ◽  
Convective Systems ◽  
Freezing Level ◽  
Brightness Temperatures ◽  
Microwave Imager ◽  
Ice Water

Abstract Tropical Rainfall Measuring Mission (TRMM) Microwave Imager and precipitation radar measurements are examined for strong convective systems. Storms having similar values of minimum 37-GHz polarization-corrected temperature (PCT) are grouped together, and their vertical profiles of maximum radar reflectivity are composited. Lower 37-GHz PCT corresponds to stronger radar profiles (high reflectivity through a deep layer), but characteristic profiles for a given 37-GHz PCT are different for deep tropical ocean, deep tropical land, subtropical ocean, and subtropical land regions. Tropical oceanic storms have a sharper decrease of reflectivity just above the freezing level than storms from other regions with the same brightness temperature. Storms from subtropical land regions have the slowest decrease of reflectivity with height and the greatest mixed-phase-layer ice water content (IWC). Linear fits of 37-GHz PCT versus IWC for each region are used to scale the brightness temperatures. Counts of storms with these scaled brightness temperatures below certain thresholds suggest that not as many of the strongest storms occur in central Africa as in subtropical parts of South America, the United States, and central Asia.

Origins of Heavy Precipitation Biases in the TRMM PR and TMI Products Assessed with CloudSat and Reanalysis Data

2019 ◽  
Vol 58 (1) ◽  
pp. 37-54 ◽  
Author(s):  
Andung Bayu Sekaranom ◽  
Hirohiko Masunaga
Keyword(s):  
Heavy Rainfall ◽  
Tropical Rainfall Measuring Mission ◽  
Heavy Precipitation ◽  
Reanalysis Data ◽  
Observation Data ◽  
Tropical Ocean ◽  
Rainfall Events ◽  
Convective Systems ◽  
Microwave Imager ◽  
Heavy Rainfall Events

AbstractThis study aims to characterize the background physical processes in the development of those heavy precipitation clouds that contribute to the Tropical Rainfall Measuring Mission (TRMM) active and passive sensor differences. The combined global observation data from TRMM, CloudSat, and European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim) from 2006 to 2014 were utilized to address this issue. Heavy rainfall events were extracted from the top 10% of the rain events from the Precipitation Radar (PR) and TRMM Microwave Imager (TMI) rain-rate climatology. Composite analyses of CloudSat and ERA-Interim were conducted to identify the detailed cloud structures and the background environmental conditions. Over tropical land, TMI tends to preferentially detect deep isolated precipitation clouds for relatively drier and unstable environments, while PR identifies more organized systems. Over the tropical ocean, TMI identifies heavy rainfall events with notable convective organization and clear regional gradients between the western and eastern Pacific Ocean, while PR fails to capture the eastward shallowing of convective systems. The PR–TMI differences for the moist and stable environments are reversed over tropical land.

scholarly journals A Cloud and Precipitation Feature Database from Nine Years of TRMM Observations

2008 ◽  
Vol 47 (10) ◽  
pp. 2712-2728 ◽  
Author(s):  
Chuntao Liu ◽  
Edward J. Zipser ◽  
Daniel J. Cecil ◽  
Stephen W. Nesbitt ◽  
Steven Sherwood
Keyword(s):  
Imaging System ◽  
Central Africa ◽  
Tropical Rainfall Measuring Mission ◽  
Intensity Measures ◽  
Microwave Brightness Temperature ◽  
Freezing Level ◽  
Maximum Reflectivity ◽  
Horizontal Size ◽  
Microwave Imager ◽  
Feature Database

Abstract An event-based method of analyzing the measurements from multiple satellite sensors is presented by using observations of the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR), Microwave Imager (TMI), Visible and Infrared Scanner (VIRS), and Lightning Imaging System (LIS). First, the observations from PR, VIRS, TMI, and LIS are temporally and spatially collocated. Then the cloud and precipitation features are defined by grouping contiguous pixels using various criteria, including surface rain, cold infrared, or microwave brightness temperature. The characteristics of measurements from different sensors inside these features are summarized. Then, climatological descriptions of many properties of the identified features are generated. This analysis method condenses the original information of pixel-level measurements into the properties of events, which can greatly increase the efficiency of searching and sorting the observed historical events. Using the TRMM cloud and precipitation feature database, the regional variations of rainfall contribution by features with different size, intensity, and PR reflectivity vertical structure are shown. Above the freezing level, land storms tend to have larger 20-dBZ area and reach higher altitude than is the case for oceanic storms, especially those land storms over central Africa. Horizontal size and the maximum reflectivity of oceanic storms decrease with altitude. For land storms, these intensity measures increase with altitude between 2 km and the freezing level and decrease more slowly with altitude above the freezing level than for ocean storms.

Combined Radar and Radiometer Analysis of Precipitation Profiles for a Parametric Retrieval Algorithm

2005 ◽  
Vol 22 (7) ◽  
pp. 909-929 ◽  
Author(s):  
Hirohiko Masunaga ◽  
Christian D. Kummerow
Keyword(s):  
A Priori ◽  
Three Dimensional ◽  
Tropical Rainfall Measuring Mission ◽  
Dimensional Structure ◽  
Retrieval Algorithm ◽  
Brightness Temperatures ◽  
Precipitation Measurement ◽  
Microwave Imager ◽  
Trmm Microwave Imager ◽  
Global Precipitation

Abstract A methodology to analyze precipitation profiles using the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and precipitation radar (PR) is proposed. Rainfall profiles are retrieved from PR measurements, defined as the best-fit solution selected from precalculated profiles by cloud-resolving models (CRMs), under explicitly defined assumptions of drop size distribution (DSD) and ice hydrometeor models. The PR path-integrated attenuation (PIA), where available, is further used to adjust DSD in a manner that is similar to the PR operational algorithm. Combined with the TMI-retrieved nonraining geophysical parameters, the three-dimensional structure of the geophysical parameters is obtained across the satellite-observed domains. Microwave brightness temperatures are then computed for a comparison with TMI observations to examine if the radar-retrieved rainfall is consistent in the radiometric measurement space. The inconsistency in microwave brightness temperatures is reduced by iterating the retrieval procedure with updated assumptions of the DSD and ice-density models. The proposed methodology is expected to refine the a priori rain profile database and error models for use by parametric passive microwave algorithms, aimed at the Global Precipitation Measurement (GPM) mission, as well as a future TRMM algorithms.

Rain Retrieval from TMI Brightness Temperature Measurements Using a TRMM PR–Based Database

2006 ◽  
Vol 45 (3) ◽  
pp. 455-466 ◽  
Author(s):  
Nicolas Viltard ◽  
Corinne Burlaud ◽  
Christian D. Kummerow
Keyword(s):  
Brightness Temperature ◽  
Rain Rate ◽  
Tropical Rainfall Measuring Mission ◽  
High Standard ◽  
Brightness Temperatures ◽  
Trmm Pr ◽  
Microwave Imager ◽  
Point To Point ◽  
Trmm Microwave Imager ◽  
Test Database

Abstract This study focuses on improving the retrieval of rain from measured microwave brightness temperatures and the capability of the retrieved field to represent the mesoscale structure of a small intense hurricane. For this study, a database is constructed from collocated Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and the TRMM Microwave Imager (TMI) data resulting in about 50 000 brightness temperature vectors associated with their corresponding rain-rate profiles. The database is then divided in two: a retrieval database of about 35 000 rain profiles and a test database of about 25 000 rain profiles. Although in principle this approach is used to build a database over both land and ocean, the results presented here are only given for ocean surfaces, for which the conditions for the retrieval are optimal. An algorithm is built using the retrieval database. This algorithm is then used on the test database, and results show that the error can be constrained to reasonable levels for most of the observed rain ranges. The relative error is nonetheless sensitive to the rain rate, with maximum errors at the low and high ends of the rain intensities (+60% and −30%, respectively) and a minimum error between 1 and 7 mm h−1. The retrieval method is optimized to exhibit a low total bias for climatological purposes and thus shows a high standard deviation on point-to-point comparisons. The algorithm is applied to the case of Hurricane Bret (1999). The retrieved rain field is analyzed in terms of structure and intensity and is then compared with the TRMM PR original rain field. The results show that the mesoscale structures are indeed well reproduced even if the retrieved rain misses the highest peaks of precipitation. Nevertheless, the mesoscale asymmetries are well reproduced and the maximum rain is found in the correct quadrant. Once again, the total bias is low, which allows for future calculation of the heat sources/sinks associated with precipitation production and evaporation.

Storm Morphology and Rainfall Characteristics of TRMM Precipitation Features

2006 ◽  
Vol 134 (10) ◽  
pp. 2702-2721 ◽  
Author(s):  
Stephen W. Nesbitt ◽  
Robert Cifelli ◽  
Steven A. Rutledge
Keyword(s):  
Tropical Rainfall Measuring Mission ◽  
Annual Rainfall ◽  
Size Spectrum ◽  
Regional Variability ◽  
Rain Area ◽  
Convective Systems ◽  
Mesoscale Convective ◽  
Trmm Precipitation ◽  
Microwave Imager ◽  
Almost All

Abstract Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR), TRMM Microwave Imager (TMI), and Visible and Infrared Scanner (VIRS) observations within the Precipitation Feature (PF) database have been analyzed to examine regional variability in rain area and maximum horizontal extent of rainfall features, and role of storm morphology on rainfall production (and thus modes where vertically integrated heating occurs). Particular attention is focused on the sampling geometry of the PR and the resulting impact on PF statistics across the global Tropics. It was found that 9% of rain features extend to the edge of the PR swath, with edge features contributing 42% of total rainfall. However, the area (maximum dimension) distribution of PR features is similar to the wider-swath TMI up until a truncation point of nearly 30 000 km2 (250 km), so a large portion of the feature size spectrum may be examined using the PR as with past ground-based studies. This study finds distinct differences in land and ocean storm morphology characteristics, which lead to important differences in rainfall modes regionally. A larger fraction of rainfall comes from more horizontally and vertically developed PFs over land than ocean due to the lack of shallow precipitation in both relative and absolute frequency of occurrence, with a trimodal distribution of rainfall contribution versus feature height observed over the ocean. Mesoscale convective systems (MCSs) are found to be responsible for up to 90% of rainfall in selected land regions. Tropicswide, MCSs are responsible for more than 50% of rainfall in almost all regions with average annual rainfall exceeding 3 mm day−1. Characteristic variability in the contribution of rainfall by feature type is shown over land and ocean, which suggests new approaches for improved convective parameterizations.

scholarly journals Differences of Rainfall Estimates over Land by Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) and TRMM Microwave Imager (TMI)—Dependence on Storm Height

2005 ◽  
Vol 44 (3) ◽  
pp. 367-383 ◽  
Author(s):  
Fumie A. Furuzawa ◽  
Kenji Nakamura
Keyword(s):  
Tropical Rainfall Measuring Mission ◽  
Local Times ◽  
Precipitation Radar ◽  
Tropical Rainfall ◽  
Convective Rain ◽  
Brightness Temperatures ◽  
Trmm Precipitation ◽  
Microwave Imager ◽  
Trmm Microwave Imager ◽  
Orbit Data

Abstract It is well known that precipitation rate estimation is poor over land. Using the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and TRMM Microwave Imager (TMI), the performance of the TMI rain estimation was investigated. Their differences over land were checked by using the orbit-by-orbit data for June 1998, December 1998, January 1999, and February 1999, and the following results were obtained: 1) Rain rate (RR) near the surface for the TMI (TMI-RR) is smaller than that for the PR (PR-RR) in winter; it is also smaller from 0900 to 1800 LT. These dependencies show some variations at various latitudes or local times. 2) When the storm height is low (<5 km), the TMI-RR is smaller than the PR-RR; when it is high (>8 km), the PR-RR is smaller. These dependencies of the RR on the storm height do not depend on local time or latitude. The tendency for a TMI-RR to be smaller when the storm height is low is more noticeable in convective rain than in stratiform rain. 3) Rain with a low storm height predominates in winter or from 0600 to 1500 LT, and convective rain occurs frequently from 1200 to 2100 LT. Result 1 can be explained by results 2 and 3. It can be concluded that the TMI underestimates rain with low storm height over land because of the weakness of the TMI algorithm, especially for convective rain. On the other hand, it is speculated that TMI overestimates rain with high storm height because of the effect of anvil rain with low brightness temperatures at high frequencies without rain near the surface, and because of the effect of evaporation or tilting, which is indicated by a PR profile and does not appear in the TMI profile. Moreover, it was found that the PR rain for the cases with no TMI rain amounted to about 10%–30% of the total but that the TMI rain for the cases with no PR rain accounted for only a few percent of the TMI rain. This result can be explained by the difficulty of detecting shallow rain with the TMI.

The Diurnal Cycle of Rainfall and Convective Intensity according to Three Years of TRMM Measurements

2003 ◽  
Vol 16 (10) ◽  
pp. 1456-1475 ◽  
Author(s):  
Stephen W. Nesbitt ◽  
Edward J. Zipser
Keyword(s):  
Diurnal Cycle ◽  
Tropical Rainfall Measuring Mission ◽  
Early Morning ◽  
Convective Systems ◽  
Rain Gauges ◽  
Mesoscale Convective ◽  
Late Evening ◽  
Microwave Imager ◽  
Trmm Microwave Imager ◽  
Rain Rates

Abstract The Tropical Rainfall Measuring Mission (TRMM) satellite measurements from the precipitation radar and TRMM microwave imager have been combined to yield a comprehensive 3-yr database of precipitation features (PFs) throughout the global Tropics (±36° latitude). The PFs retrieved using this algorithm (which number nearly six million Tropicswide) have been sorted by size and intensity ranging from small shallow features greater than 75 km2 in area to large mesoscale convective systems (MCSs) according to their radar and ice scattering characteristics. This study presents a comprehensive analysis of the diurnal cycle of the observed precipitation features' rainfall amount, precipitation feature frequency, rainfall intensity, convective–stratiform rainfall portioning, and remotely sensed convective intensity, sampled Tropicswide from space. The observations are sorted regionally to examine the stark differences in the diurnal cycle of rainfall and convective intensity over land and ocean areas. Over the oceans, the diurnal cycle of rainfall has small amplitude, with the maximum contribution to rainfall coming from MCSs in the early morning. This increased contribution is due to an increased number of MCSs in the nighttime hours, not increasing MCS areas or conditional rain rates, in agreement with previous works. Rainfall from sub-MCS features over the ocean has little appreciable diurnal cycle of rainfall or convective intensity. Land areas have a much larger rainfall cycle than over the ocean, with a marked minimum in the midmorning hours and a maximum in the afternoon, slowly decreasing through midnight. Non-MCS features have a significant peak in afternoon instantaneous conditional rain rates (the mean rain rate in raining pixels), and convective intensities, which differs from previous studies using rain rates derived from hourly rain gauges. This is attributed to enhancement by afternoon heating. MCSs over land have a convective intensity peak in the late afternoon, however all land regions have MCS rainfall peaks that occur in the late evening through midnight due to their longer life cycle. The diurnal cycle of overland MCS rainfall and convective intensity varies significantly among land regions, attributed to MCS sensitivity to the varying environmental conditions in which they occur.

scholarly journals Constructing a Multifrequency Passive Microwave Hail Retrieval and Climatology in the GPM Domain

2019 ◽  
Vol 58 (9) ◽  
pp. 1889-1904 ◽  
Author(s):  
Sarah D. Bang ◽  
Daniel J. Cecil
Keyword(s):  
United States ◽  
Brightness Temperature ◽  
Microwave Radiometer ◽  
Central Africa ◽  
Tropical Rainfall Measuring Mission ◽  
The United States ◽  
Low Earth Orbit ◽  
Passive Microwave ◽  
Central United States ◽  
Microwave Data

AbstractLarge hail is a primary contributor to damages and loss around the world, in both agriculture and infrastructure. The sensitivity of passive microwave radiometer measurements to scattering by hail led to the development of proxies for severe hail, most of which use brightness temperature thresholds from 37-GHz and higher-frequency microwave channels on board weather satellites in low-Earth orbit. Using 16+ years of data from the Tropical Rainfall Measuring Mission (TRMM; 36°S–36°N), we pair TRMM brightness temperature–derived precipitation features with surface hail reports in the United States to train a hail retrieval on passive microwave data from the 10-, 19-, 37-, and 85-GHz channels based on probability curves fit to the microwave data. We then apply this hail retrieval to features in the Global Precipitation Measurement (GPM) domain (from 69°S to 69°N) to develop a nearly global passive microwave–based climatology of hail. The extended domain of the GPM satellite into higher latitudes requires filtering out features that we believe are over icy and snowy surface regimes. We also normalize brightness temperature depression by tropopause height in an effort to account for differences in storm depth between the tropics and higher latitudes. Our results show the highest hail frequencies in the region of northern Argentina through Paraguay, Uruguay, and southern Brazil; the central United States; and a swath of Africa just south of the Sahel. Smaller hot spots include Pakistan, eastern India, and Bangladesh. A notable difference between these results and many prior satellite-based studies is that central Africa, while still active in our climatology, does not rival the aforementioned regions in retrieved hailstorm frequency.

scholarly journals An Updated TRMM Composite Climatology of Tropical Rainfall and Its Validation

2014 ◽  
Vol 27 (1) ◽  
pp. 273-284 ◽  
Author(s):  
Jian-Jian Wang ◽  
Robert F. Adler ◽  
George J. Huffman ◽  
David Bolvin
Keyword(s):  
Pacific Ocean ◽  
Tropical Rainfall Measuring Mission ◽  
Global Precipitation Climatology Project ◽  
Mean Value ◽  
Passive Microwave ◽  
Control Measures ◽  
Tropical Ocean ◽  
Tropical Rainfall ◽  
Uncertainty Estimates ◽  
Microwave Imager

Abstract An updated 15-yr Tropical Rainfall Measuring Mission (TRMM) composite climatology (TCC) is presented and evaluated. This climatology is based on a combination of individual rainfall estimates made with data from the primary TRMM instruments: the TRMM Microwave Imager (TMI) and the precipitation radar (PR). This combination climatology of passive microwave retrievals, radar-based retrievals, and an algorithm using both instruments simultaneously provides a consensus TRMM-based estimate of mean precipitation. The dispersion of the three estimates, as indicated by the standard deviation σ among the estimates, is presented as a measure of confidence in the final estimate and as an estimate of the uncertainty thereof. The procedures utilized by the compositing technique, including adjustments and quality-control measures, are described. The results give a mean value of the TCC of 4.3 mm day−1 for the deep tropical ocean belt between 10°N and 10°S, with lower values outside that band. In general, the TCC values confirm ocean estimates from the Global Precipitation Climatology Project (GPCP) analysis, which is based on passive microwave results adjusted for sampling by infrared-based estimates. The pattern of uncertainty estimates shown by σ is seen to be useful to indicate variations in confidence. Examples include differences between the eastern and western portions of the Pacific Ocean and high values in coastal and mountainous areas. Comparison of the TCC values (and the input products) to gauge analyses over land indicates the value of the radar-based estimates (small biases) and the limitations of the passive microwave algorithm (relatively large biases). Comparison with surface gauge information from western Pacific Ocean atolls shows a negative bias (~16%) for all the TRMM products, although the representativeness of the atoll gauges of open-ocean rainfall is still in question.

Rainfall Contributions from Precipitation Systems with Different Sizes, Convective Intensities, and Durations over the Tropics and Subtropics

2011 ◽  
Vol 12 (3) ◽  
pp. 394-412 ◽  
Author(s):  
Chuntao Liu
Keyword(s):  
Grid Point ◽  
Tropical Rainfall Measuring Mission ◽  
Life Cycles ◽  
Diurnal Variations ◽  
Diurnal Cycles ◽  
Brightness Temperatures ◽  
Seasonal And Diurnal Variations ◽  
Microwave Imager ◽  
Rain Events ◽  
The Tropics

Abstract The rainfall contributions from precipitation features (PFs) with full spectra of different sizes and convective intensities over the tropics and subtropics are summarized using 12 yr of version 6 Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) and Microwave Imager (TMI) observations. Regional, seasonal, and diurnal variations of the rainfall contributions from various PFs are shown, with the global distribution of the sizes, PR echo tops, maximum heights of 30 dBZ, and minimum TMI 85-GHz brightness temperatures of PFs above which contribute half of the rainfall in each 2° × 2° region. Though the results from radar and microwave observations generally agree with each other, some large differences exist over land. Seasonal variations of sizes and intensities of precipitation systems are found over the northeast Pacific, northern SPCZ, and some land areas in addition to the well-known monsoon regions. The diurnal cycles of rainfall over land and ocean are interpreted with the combinations of life cycles of various precipitation systems, using the diurnal variations of rainfall contributions from precipitation systems with different sizes and intensities. The long-duration rainfall events with more than four consecutive 3-h periods with rain at a grid point are identified from 11 yr of TRMM 3B42 products. These “12-h rain events” contribute a larger proportion of the total rainfall over ocean than over land. They are mostly correlated with precipitation systems with large sizes and intense convection. However, they can also be caused by some shallow persistent precipitation systems, such as those over the northeast slope of the Andes in Peru in spring and fall and over the west coast of India in summer.

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