Verification of TMI-Adjusted Rainfall Analyses of Tropical Cyclones at ECMWF Using TRMM Precipitation Radar

2005 ◽  
Vol 44 (11) ◽  
pp. 1677-1690 ◽  
Author(s):  
A. Benedetti ◽  
P. Lopez ◽  
E. Moreau ◽  
P. Bauer ◽  
V. Venugopal
Keyword(s):  
Tropical Cyclones ◽  
Tropical Rainfall Measuring Mission ◽  
Heavy Rain ◽  
Radar Data ◽  
Skill Score ◽  
Precipitation Radar ◽  
Statistical Measures ◽  
Model Background ◽  
Trmm Precipitation ◽  
Rain Rates

Abstract A validation of passive microwave–adjusted rainfall analyses of tropical cyclones using spaceborne radar data is presented. This effort is part of the one-dimensional plus four-dimensional variational (1D+4D-Var) rain assimilation project that is being carried out at the European Centre for Medium-Range Weather Forecasts (ECMWF). Brightness temperatures or surface rain rates from the Tropical Rainfall Measuring Mission (TRMM) satellite are processed through a 1D-Var retrieval to derive values of total column water vapor that can be ingested into the operational ECMWF 4D-Var. As an indirect validation, the precipitation fields produced at the end of the 1D-Var minimization process are converted into equivalent radar reflectivity at the frequency of the TRMM precipitation radar (13.8 GHz) and are compared with the observations averaged at model resolution. The averaging process is validated using a sophisticated downscaling/upscaling approach that is based on wavelet decomposition. The precipitation radar measurements are ideal for this validation exercise, being approximately collocated with but completely independent of the TRMM Microwave Imager (TMI) radiometer measurements. Qualitative and statistical comparisons between radar observations and retrievals from the TMI-derived surface rain rates and from TMI radiances are made using 17 well-documented tropical cyclone occurrences between January and April of 2003. Several statistical measures, such as bias, root-mean-square error, and Heidke skill score, are introduced to assess the 1D-Var skill as well as the model background skill in producing a realistic rain distribution. Results show a good degree of skill in the retrievals, especially near the surface and for medium–heavy rain. The model background produces precipitation in the domain that is sometimes in excess with respect to the observations, and it often shows an error in the location of precipitation maxima. Differences between the two 1D-Var approaches are not large enough to make final conclusions regarding the advantages of one method over the other. Both methods are capable of redistributing the rain patterns according to the observations. It appears, however, that the brightness temperature approach is in general more effective in increasing precipitation amounts at moderate-to-high rainfall rates.

scholarly journals Validation of TRMM Precipitation Radar through Comparison of Its Multiyear Measurements with Ground-Based Radar

2009 ◽  
Vol 48 (4) ◽  
pp. 804-817 ◽  
Author(s):  
Liang Liao ◽  
Robert Meneghini
Keyword(s):  
Tropical Rainfall Measuring Mission ◽  
Heavy Rain ◽  
Radar Data ◽  
Precipitation Radar ◽  
Convective Storms ◽  
Conditional Mean ◽  
Conditional Basis ◽  
Trmm Precipitation ◽  
Rain Rates ◽  
Overlap Area

Abstract A procedure to accurately resample spaceborne and ground-based radar data is described and then is applied to the measurements taken from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and the ground-based Weather Surveillance Radar-1988 Doppler (WSR-88D or WSR) for the validation of the PR measurements and estimates. Through comparisons with the well-calibrated, nonattenuated WSR at Melbourne, Florida, for the period 1998–2007, the calibration of the PR aboard the TRMM satellite is checked using measurements near the storm top. Analysis of the results indicates that the PR, after taking into account differences in radar reflectivity factors between the PR and WSR, has a small positive bias of 0.8 dB relative to the WSR, implying a soundness of the PR calibration in view of the uncertainties involved in the comparisons. Comparisons between the PR and WSR reflectivities are also made near the surface for evaluation of the attenuation-correction procedures used in the PR algorithms. It is found that the PR attenuation is accurately corrected in stratiform rain but is underestimated in convective rain, particularly in heavy rain. Tests of the PR estimates of rainfall rate are conducted through comparisons in the overlap area between the TRMM overpass and WSR scan. Analyses of the data are made both on a conditional basis, in which the instantaneous rain rates are compared only at those pixels at which both the PR and WSR detect rain, and an unconditional basis, in which the area-averaged rain rates are estimated independently for the PR and WSR. Results of the conditional rain comparisons show that the PR-derived rain is about 9% greater and 19% less than the WSR estimates for stratiform and convective storms, respectively. Overall, the PR tends to underestimate the conditional mean rain rate by 8% for all rain categories, a finding that conforms to the results of the area-averaged rain (unconditional) comparisons.

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.

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.

Morphology, Intensity, and Rainfall Production of MJO Convection: Observations from DYNAMO Shipborne Radar and TRMM

2015 ◽  
Vol 72 (2) ◽  
pp. 623-640 ◽  
Author(s):  
Weixin Xu ◽  
Steven A. Rutledge
Keyword(s):  
Mesoscale Convective System ◽  
Tropical Rainfall Measuring Mission ◽  
Radar Data ◽  
Convective System ◽  
Precipitation Radar ◽  
Convective Systems ◽  
Trmm Pr ◽  
Mesoscale Convective ◽  
Trmm Precipitation

Abstract This study uses Dynamics of the Madden–Julian Oscillation (DYNAMO) shipborne [Research Vessel (R/V) Roger Revelle] radar and Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) datasets to investigate MJO-associated convective systems in specific organizational modes [mesoscale convective system (MCS) versus sub-MCS and linear versus nonlinear]. The Revelle radar sampled many “climatological” aspects of MJO convection as indicated by comparison with the long-term TRMM PR statistics, including areal-mean rainfall (6–7 mm day−1), convective intensity, rainfall contributions from different morphologies, and their variations with MJO phase. Nonlinear sub-MCSs were present 70% of the time but contributed just around 20% of the total rainfall. In contrast, linear and nonlinear MCSs were present 10% of the time but contributed 20% and 50%, respectively. These distributions vary with MJO phase, with the largest sub-MCS rainfall fraction in suppressed phases (phases 5–7) and maximum MCS precipitation in active phases (phases 2 and 3). Similarly, convective–stratiform rainfall fractions also varied significantly with MJO phase, with the highest convective fractions (70%–80%) in suppressed phases and the largest stratiform fraction (40%–50%) in active phases. However, there are also discrepancies between the Revelle radar and TRMM PR. Revelle radar data indicated a mean convective rain fraction of 70% compared to 55% for TRMM PR. This difference is mainly due to the reduced resolution of the TRMM PR compared to the ship radar. There are also notable differences in the rainfall contributions as a function of convective intensity between the Revelle radar and TRMM PR. In addition, TRMM PR composites indicate linear MCS rainfall increases after MJO onset and produce similar rainfall contributions to nonlinear MCSs; however, the Revelle radar statistics show the clear dominance of nonlinear MCS rainfall.

Distributions of Shallow to Very Deep Precipitation–Convection in Rapidly Intensifying Tropical Cyclones

2015 ◽  
Vol 28 (22) ◽  
pp. 8791-8824 ◽  
Author(s):  
Cheng Tao ◽  
Haiyan Jiang
Keyword(s):  
Tropical Cyclones ◽  
Inner Core ◽  
Deep Convection ◽  
Tropical Rainfall Measuring Mission ◽  
Intensity Change ◽  
Latent Heating ◽  
Precipitation Radar ◽  
Trmm Pr ◽  
Radar Echo ◽  
Trmm Precipitation

Abstract Shear-relative distributions of four types of precipitation/convection in tropical cyclones (TCs) are statistically analyzed using 14 years of Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) data. The dataset of 1139 TRMM PR overpasses of tropical storms through category-2 hurricanes over global TC-prone basins is divided by future 24-h intensity change. It is found that increased and widespread shallow precipitation (defined as where the 20-dBZ radar echo height <6 km) around the storm center is a first sign of rapid intensification (RI) and could be used as a predictor of the onset of RI. The contribution to total volumetric rain and latent heating from shallow and moderate precipitation (20-dBZ echo height between 6 and 10 km) in the inner core is greater in RI storms than in non-RI storms, while the opposite is true for moderately deep (20-dBZ echo height between 10 and 14 km) and very deep precipitation (20-dBZ echo height ≥14 km). The authors argue that RI is more likely triggered by the increase of shallow–moderate precipitation and the appearance of more moderately to very deep convection in the middle of RI is more likely a response or positive feedback to changes in the vortex. For RI storms, a cyclonic rotation of frequency peaks from shallow (downshear right) to moderate (downshear left) to moderately and very deep precipitation (upshear left) is found and may be an indicator of a rapidly strengthening vortex. A ring of almost 90% occurrence of total precipitation is found for storms in the middle of RI, consistent with the previous finding of the cyan and pink ring on the 37-GHz color product.

scholarly journals Improving Satellite-Based Subhourly Surface Rain Estimates Using Vertical Rain Profile Information

2019 ◽  
Vol 20 (5) ◽  
pp. 1015-1026 ◽  
Author(s):  
Nobuyuki Utsumi ◽  
Hyungjun Kim ◽  
F. Joseph Turk ◽  
Ziad. S. Haddad
Keyword(s):  
Rain Rate ◽  
Tropical Rainfall Measuring Mission ◽  
Rain Gauge ◽  
Rain Gauge Data ◽  
Rain Gauges ◽  
Gauge Data ◽  
Surface Rain Rate ◽  
Trmm Precipitation ◽  
Time Lagged ◽  
Rain Rates

Abstract Quantifying time-averaged rain rate, or rain accumulation, on subhourly time scales is essential for various application studies requiring rain estimates. This study proposes a novel idea to estimate subhourly time-averaged surface rain rate based on the instantaneous vertical rain profile observed from low-Earth-orbiting satellites. Instantaneous rain estimates from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) are compared with 1-min surface rain gauges in North America and Kwajalein atoll for the warm seasons of 2005–14. Time-lagged correlation analysis between PR rain rates at various height levels and surface rain gauge data shows that the peak of the correlations tends to be delayed for PR rain at higher levels up to around 6-km altitude. PR estimates for low to middle height levels have better correlations with time-delayed surface gauge data than the PR’s estimated surface rain rate product. This implies that rain estimates for lower to middle heights may have skill to estimate the eventual surface rain rate that occurs 1–30 min later. Therefore, in this study, the vertical profiles of TRMM PR instantaneous rain estimates are averaged between the surface and various heights above the surface to represent time-averaged surface rain rate. It was shown that vertically averaged PR estimates up to middle heights (~4.5 km) exhibit better skill, compared to the PR estimated instantaneous surface rain product, to represent subhourly (~30 min) time-averaged surface rain rate. These findings highlight the merit of additional consideration of vertical rain profiles, not only instantaneous surface rain rate, to improve subhourly surface estimates of satellite-based rain products.

scholarly journals Precipitation Clouds Delineation Scheme in Tropical Cyclones and Its Validation Using Precipitation and Cloud Parameter Datasets from TRMM

2018 ◽  
Vol 57 (4) ◽  
pp. 821-836 ◽  
Author(s):  
FengJiao Chen ◽  
ShaoXue Sheng ◽  
ZhengQing Bao ◽  
HuaYang Wen ◽  
LianSheng Hua ◽  
...  
Keyword(s):  
Tropical Cyclones ◽  
Tropical Rainfall Measuring Mission ◽  
Probability Of Detection ◽  
Liquid Water Path ◽  
Near Surface ◽  
Cloud Parameters ◽  
Infrared Measurements ◽  
Trmm Precipitation ◽  
Cloud Parameter ◽  
Probability Of Precipitation

AbstractUtilizing the cloud parameters derived from the Tropical Rainfall Measuring Mission (TRMM) Visible and Infrared Scanner and the near-surface rainfall detected by the TRMM Precipitation Radar, the differences of cloud parameters for precipitating clouds (PCs) and nonprecipitating clouds (NPCs) are examined in tropical cyclones (TCs) during daytime from June to September 1998–2010. A precipitation delineation scheme that is based on cloud parameter thresholds is proposed and validated using the independent TC datasets in 2011 and observational datasets from Terra/MODIS. Statistical analysis of these results shows that the differences in the effective radius of cloud particles Re are small for PCs and NPCs, while thick clouds with large cloud optical thickness (COT) and liquid water path (LWP) can be considered as candidates for PCs. The probability of precipitation increases rapidly as the LWP and COT increase, reaching ~90%, whereas the probability of precipitation reaches a peak value of only 30% as Re increases. The combined threshold of a brightness temperature at 10.8 μm (BT4) of 270 K and an LWP of 750 g m−2 shows the best performance for precipitation discrimination at the pixel levels, with the probability of detection (POD) reaching 68.2% and false-alarm ratio (FAR) reaching 31.54%. From MODIS observations, the composite scheme utilizing BT4 and LWP also proves to be a good index, with POD reaching 77.39% and FAR reaching 24.2%. The results from this study demonstrate a potential application of real-time precipitation monitoring in TCs utilizing cloud parameters from visible and infrared measurements on board geostationary weather satellites.

scholarly journals Impact of Misrepresentation of Freezing-Level Height by the TRMM Algorithm on Shallow Rain Statistics over India and Adjoining Oceans

2013 ◽  
Vol 52 (9) ◽  
pp. 2001-2008 ◽  
Author(s):  
K. Saikranthi ◽  
T. Narayana Rao ◽  
B. Radhakrishna ◽  
S. Vijaya Bhaskara Rao
Keyword(s):  
Tropical Rainfall Measuring Mission ◽  
Precipitation Radar ◽  
Study Region ◽  
Freezing Level ◽  
Northwestern India ◽  
Trmm Precipitation ◽  
Radar Measurements ◽  
The Impact ◽  
The Himalaya ◽  
Level Height

AbstractThe estimation of freezing level-height (FLH) by the Tropical Rainfall Measuring Mission (TRMM) algorithm is evaluated, against several other data sources, over India and adjoining oceans. It is observed that the TRMM algorithm either underestimates or overestimates the FLH [relative to radiosonde- and ECMWF Interim Re-Analysis (ERA)-derived FLH] at latitudes > 20°N over India. The agreement between the FLHs obtained from ERA and radiosonde and the TRMM-derived brightband height suggests that usage of ERA-derived FLH may improve shallow rain statistics. The impact of misrepresentation of FLH by the TRMM algorithm on shallow rain statistics is assessed by using 13 yr of TRMM precipitation radar measurements. It is noted that the misidentification of FLH alone affects (mostly underestimates) the shallow rain occurrence and rain fraction by 3%–8% over the study region. The magnitude of underestimation is large over the southern slopes of the Himalaya, the northern plains, and in northwestern India. TRMM identifies most of the shallow rain (30%–50%) as cold rain in regions where the underestimation of FLH is high. This situation could introduce some error in the correction of reflectivity for attenuation and in the retrieval of latent heat profiles.

scholarly journals Satellite Microwave Surface Observations in Tropical Cyclones

2010 ◽  
Vol 138 (2) ◽  
pp. 421-437 ◽  
Author(s):  
Yves Quilfen ◽  
Bertrand Chapron ◽  
Jean Tournadre
Keyword(s):  
Wind Speed ◽  
Tropical Cyclones ◽  
Rain Rate ◽  
Microwave Radiometer ◽  
Surface Wind ◽  
Tropical Rainfall Measuring Mission ◽  
Heavy Rain ◽  
Surface Wind Speed ◽  
Microwave Measurements ◽  
Dual Frequency

Abstract Sea surface estimates of local winds, waves, and rain-rate conditions are crucial to complement infrared/visible satellite images in estimating the strength of tropical cyclones (TCs). Satellite measurements at microwave frequencies are thus key elements of present and future observing systems. Available for more than 20 years, passive microwave measurements are very valuable but still suffer from insufficient resolution and poor wind vector retrievals in the rainy conditions encountered in and around tropical cyclones. Scatterometer and synthetic aperture radar active microwave measurements performed at the C and Ku band on board the European Remote Sensing (ERS), the Meteorological Operational (MetOp), the Quick Scatterometer (QuikSCAT), the Environmental Satellite (Envisat), and RadarSat satellites can also be used to map the surface wind field in storms. Their accuracy is limited in the case of heavy rain and possible saturation of the microwave signals is reported. Altimeter dual-frequency measurements have also been shown to provide along-track information related to surface wind speed, wave height, and vertically integrated rain rate at about 6-km resolution. Although limited for operational use by their dimensional sampling, the dual-frequency capability makes altimeters a unique satellite-borne sensor to perform measurements of key surface parameters in a consistent way. To illustrate this capability two Jason-1 altimeter passes over Hurricanes Isabel and Wilma are examined. The area of maximum TC intensity, as described by the National Hurricane Center and by the altimeter, is compared for these two cases. Altimeter surface wind speed and rainfall-rate observations are further compared with measurements performed by other remote sensors, namely, the Tropical Rainfall Measuring Mission instruments and the airborne Stepped Frequency Microwave Radiometer.

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