scholarly journals Cross Validation of Rainfall Characteristics Estimated from the TRMM PR, a Combined PR–TMI Algorithm, and a C-POL Ground Radar during the Passage of Tropical Cyclone and Nontropical Cyclone Events over Darwin, Australia

2018 ◽  
Vol 35 (12) ◽  
pp. 2339-2358 ◽  
Author(s):  
Anil Deo ◽  
S. Joseph Munchak ◽  
Kevin J. E. Walsh
Keyword(s):  
Tropical Cyclone ◽  
Tropical Rainfall Measuring Mission ◽  
Rainfall Rate ◽  
Rainfall Characteristics ◽  
Significant Difference ◽  
Median Volume ◽  
Precipitation Type ◽  
Correct Direction ◽  
Microwave Imager ◽  
Trmm Microwave Imager

AbstractThis study cross validates the radar reflectivity Z; the rainfall drop size distribution parameter (median volume diameter Do); and the rainfall rate R estimated from the Tropical Rainfall Measuring Mission (TRMM) satellite Precipitation Radar (PR), a combined PR and TRMM Microwave Imager (TMI) algorithm (COM), and a C-band dual-polarized ground radar (GR) for TRMM overpasses during the passage of tropical cyclone (TC) and non-TC events over Darwin, Australia. Two overpass events during the passage of TC Carlos and 11 non-TC overpass events are used in this study, and the GR is taken as the reference. It is shown that the correspondence is dependent on the precipitation type whereby events with more (less) stratiform rainfall usually have a positive (negative) bias in the reflectivity and the rainfall rate, whereas in the Do the bias is generally positive but small (large). The COM reflectivity estimates are similar to the PR, but it has a smaller bias in the Do for most of the greater stratiform events. This suggests that combining the TMI with the PR adjusts the Do toward the “correct” direction if the GR is taken as the reference. Moreover, the association between the TRMM estimates and the GR for the two TC events, which are highly stratiform in nature, is similar to that observed for the highly stratiform non-TC events (there is no significant difference), but it differs considerably from that observed for the majority of the highly convective non-TC events.

scholarly journals Regional Differences in Overland Rainfall Estimation from PR-Calibrated TMI Algorithm

2005 ◽  
Vol 44 (2) ◽  
pp. 189-205 ◽  
Author(s):  
Tufa Dinku ◽  
Emmanouil N. Anagnostou
Keyword(s):  
Regional Differences ◽  
Rain Rate ◽  
Central Africa ◽  
Tropical Rainfall Measuring Mission ◽  
Error Statistics ◽  
Southern Plains ◽  
Significant Difference ◽  
Current Algorithm ◽  
Microwave Imager ◽  
Trmm Microwave Imager

Abstract The Tropical Rainfall Measuring Mission (TRMM) satellite carries a combination of active [precipitation radar (PR)] and multichannel passive microwave [the TRMM Microwave Imager (TMI)] sensors, which advance our ability to estimate rainfall over land. Rain retrieval from the TRMM PR is associated with an unprecedented accuracy and resolution but is limited in terms of sampling because of the narrow PR swath width (215 km). TMI provides wider coverage (760 km), but its observations are associated with a more complex relationship to precipitation in comparison with PR (especially over land). The PR rain estimates are used here for calibrating an overland TMI rain algorithm. The algorithm consists of 1) multichannel-based rain screening and convective/stratiform (C/S) classification schemes, and 2) nonlinear (linear) regressions for the rain-rate retrieval of stratiform (convective) rain regimes. This study examines regional differences in the algorithm performance. Four geographic regions consisting of central Africa (AFC), the Amazon (AMZ), the U.S. southern Plains (USA), and the Ganges–Brahmaputra–Meghna River basin (GBM) in south Asia are selected. Data from three summer months of 2000 and 2001 are used for calibration; validation is done using summer 2002 data. The current algorithm is also compared with the latest [version 6 (V6)] TRMM 2A12 product in terms of rain detection, and rain-rate retrieval error statistics on the basis of PR reference rainfall. The performance of the algorithm is different for the different regions. For instance, the reduction in random error (relative to 2A12 V6) is about 24%, 36%, 57%, and 165% for USA, AFC, AMZ, and GBM, respectively. However, significant difference between global (the four regions combined) and regional calibration is observed only for the GBM region.

scholarly journals Tropical Cyclone Diurnal Cycle as Observed by TRMM

2016 ◽  
Vol 144 (8) ◽  
pp. 2793-2808 ◽  
Author(s):  
Kenneth D. Leppert ◽  
Daniel J. Cecil
Keyword(s):  
Tropical Cyclone ◽  
Tropical Cyclones ◽  
Diurnal Cycle ◽  
Inner Core ◽  
Deep Layer ◽  
Tropical Rainfall Measuring Mission ◽  
Local Standard ◽  
Intensity Changes ◽  
Microwave Imager ◽  
Trmm Microwave Imager

Abstract Previous work has indicated a clear, consistent diurnal cycle in rainfall and cold cloudiness coverage around tropical cyclones. This cycle may have important implications for structure and intensity changes of these storms and the forecasting of such changes. The goal of this paper is to use passive and active microwave measurements from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and Precipitation Radar (PR), respectively, to better understand the tropical cyclone diurnal cycle throughout a deep layer of a tropical cyclone’s clouds. The composite coverage by PR reflectivity ≥20 dBZ at various heights as a function of local standard time (LST) and radius suggests the presence of a diurnal signal for radii <500 km through a deep layer (2–10-km height) of the troposphere using 1998–2011 Atlantic tropical cyclones of at least tropical storm strength. The area covered by reflectivity ≥20 dBZ at radii 100–500 km peaks in the morning (0130–1030 LST) and reaches a minimum 1030–1930 LST. Radii between 300 and 500 km tend to reach a minimum in coverage closer to 1200 LST before reaching another peak at 2100 LST. The inner core (0–100 km) appears to be associated with a single-peaked diurnal cycle only at upper levels (8–10 km) with a maximum at 2230–0430 LST. The TMI rainfall composites suggest a clear diurnal cycle at all radii between 200 and 1000 km with peak rainfall coverage and rain rate occurring in the morning (0130–0730 LST).

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.

Changes in TRMM Rainfall due to the Orbit Boost Estimated from Buoy Rain Gauge Data

2007 ◽  
Vol 24 (9) ◽  
pp. 1598-1607 ◽  
Author(s):  
Jeremy D. DeMoss ◽  
Kenneth P. Bowman
Keyword(s):  
Sampling Error ◽  
Tropical Rainfall Measuring Mission ◽  
Rain Gauge ◽  
Rain Gauge Data ◽  
Rain Gauges ◽  
Rate Dependent ◽  
Wide Range ◽  
The Mean ◽  
Microwave Imager ◽  
Trmm Microwave Imager

Abstract During the first three-and-a-half years of the Tropical Rainfall Measuring Mission (TRMM), the TRMM satellite operated at a nominal altitude of 350 km. To reduce drag, save maneuvering fuel, and prolong the mission lifetime, the orbit was boosted to 403 km in August 2001. The change in orbit altitude produced small changes in a wide range of observing parameters, including field-of-view size and viewing angles. Due to natural variability in rainfall and sampling error, it is not possible to evaluate possible changes in rainfall estimates from the satellite data alone. Changes in TRMM Microwave Imager (TMI) and the precipitation radar (PR) precipitation observations due to the orbit boost are estimated by comparing them with surface rain gauges on ocean buoys operated by the NOAA/Pacific Marine Environment Laboratory (PMEL). For each rain gauge, the bias between the satellite and the gauge for pre- and postboost time periods is computed. For the TMI, the satellite is biased ∼12% low relative to the gauges during the preboost period and ∼1% low during the postboost period. The mean change in bias relative to the gauges is approximately 0.4 mm day−1. The change in TMI bias is rain-rate-dependent, with larger changes in areas with higher mean precipitation rates. The PR is biased significantly low relative to the gauges during both boost periods, but the change in bias from the pre- to postboost period is not statistically significant.

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.

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.

scholarly journals Investigating Seasonal PR–TMI Calibration Differences

2008 ◽  
Vol 25 (7) ◽  
pp. 1228-1237
Author(s):  
Tufa Dinku ◽  
Emmanouil N. Anagnostou
Keyword(s):  
Amazon Basin ◽  
Southeastern United States ◽  
Tropical Rainfall Measuring Mission ◽  
Validation Dataset ◽  
Precipitation Radar ◽  
Seasonal Differences ◽  
Geographic Regions ◽  
Microwave Imager ◽  
Trmm Microwave Imager ◽  
Rain Retrieval

Abstract Seasonal differences in the calibration of overland passive microwave rain retrieval are investigated using Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and precipitation radar (PR). Four geographic regions from southern Africa, South Asia, the Amazon basin, and the southeastern United States are selected. Three seasons are compared for each region. Two scenarios of algorithm calibration are considered. In the first, the parameter sets are derived by calibrating the TMI algorithm with PR in each season. In the second scenario, common parameter sets are derived from the combined dataset of all three seasons. The parameter sets from both scenarios are then applied to the validation dataset of each season to determine the effect of seasonal calibration. Furthermore, calibration parameters from one season are also applied to another season, and results are compared against those derived using the season’s own parameters. Appreciable seasonal differences are observed for the U.S. region, while there are no significant differences between using individual seasonal calibration and the all-season calibration for the other regions. However, using one season’s parameter set to retrieve rainfall for another season is associated with increased uncertainty. It is also shown that the performance of the retrieval varies by season.

scholarly journals Microwave Rainfall Estimation over Coasts

2005 ◽  
Vol 22 (5) ◽  
pp. 497-512 ◽  
Author(s):  
Jeffrey R. McCollum ◽  
Ralph R. Ferraro
Keyword(s):  
Tropical Rainfall Measuring Mission ◽  
Radar Rainfall ◽  
The Public ◽  
Earth Observing System ◽  
Temperature Criterion ◽  
Previous Algorithm ◽  
Microwave Imager ◽  
Trmm Microwave Imager ◽  
Rain Rates ◽  
Microwave Data

Abstract The microwave coastal rain identification procedure that has been used by NASA for over 10 yr, and also more recently by NOAA, for different instruments beginning with the Special Sensor Microwave Imager (SSM/I), is updated for use with Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and Advanced Microwave Scanning Radiometer (AMSR)-[Earth Observing System (EOS)] E microwave data. Since the development of the SSM/I algorithm, a wealth of both space-based and ground-based radar-rainfall estimates have become available, and here some of these data are used with collocated TMI and AMSR-E data to improve the estimation of coastal rain areas from microwave data. Two major improvements are made. The first involves finding the conditions where positive rain rates should be estimated rather than leaving the areas without estimates as in the previous algorithm. The second is a modification to the final step of the rain identification method; previously, a straight brightness temperature cutoff was used, but this is modified to a polarization-corrected temperature criterion. These modifications are made for the TRMM version 6 product release and the third (1 September) release of AMSR-E products to the public, both in 2004. The modifications are slightly different for each of these two sensors.

scholarly journals Comparisons of Instantaneous TRMM Ground Validation and Satellite Rain-Rate Estimates at Different Spatial Scales

2008 ◽  
Vol 47 (8) ◽  
pp. 2215-2237 ◽  
Author(s):  
David B. Wolff ◽  
Brad L. Fisher
Keyword(s):  
Rain Rate ◽  
Spatial Scales ◽  
Tropical Rainfall Measuring Mission ◽  
Heavy Rain ◽  
Global Ocean ◽  
Ground Validation ◽  
Microwave Imager ◽  
Rain Events ◽  
Trmm Microwave Imager ◽  
Rain Rates

Abstract This study provides a comprehensive intercomparison of instantaneous rain rates observed by the two rain sensors aboard the Tropical Rainfall Measuring Mission (TRMM) satellite with ground data from two regional sites established for long-term ground validation: Kwajalein Atoll and Melbourne, Florida. The satellite rain algorithms utilize remote observations of precipitation collected by the TRMM Microwave Imager (TMI) and the Precipitation Radar (PR) aboard the TRMM satellite. Three standard level II rain products are generated from operational applications of the TMI, PR, and combined (COM) rain algorithms using rain information collected from the TMI and the PR along the orbital track of the TRMM satellite. In the first part of the study, 0.5° × 0.5° instantaneous rain rates obtained from the TRMM 3G68 product were analyzed and compared to instantaneous Ground Validation (GV) program rain rates gridded at a scale of 0.5° × 0.5°. In the second part of the study, TMI, PR, COM, and GV rain rates were spatiotemporally matched and averaged at the scale of the TMI footprint (∼150 km2). This study covered a 6-yr period (1999–2004) and consisted of over 50 000 footprints for each GV site. In the first analysis, the results showed that all of the respective rain-rate estimates agree well, with some exceptions. The more salient differences were associated with heavy rain events in which one or more of the algorithms failed to properly retrieve these extreme events. Also, it appears that there is a preferred mode of precipitation for TMI rain rates at or near 2 mm h−1 over the ocean. This mode was noted over ocean areas of Kwajalein and Melbourne and has been observed in TRMM tropical–global ocean areas as well.

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