scholarly journals Extreme precipitation over Indonesian maritime continent: Uncertainties in satellite estimation and its relationship with low storm top height extreme

2018 ◽  
Author(s):  
Sekaranom A.B.
Keyword(s):  
Extreme Precipitation ◽  
Land Surface ◽  
Tropical Rainfall Measuring Mission ◽  
Middle Part ◽  
Lower Amount ◽  
Maritime Continent ◽  
Near Surface ◽  
Low Cloud ◽  
Microwave Imager ◽  
Rain Rates

This paper aims to explain the uncertainties in satellite rainfall estimation due to existence of very high near surface rain, but with relatively low cloud top height over Indonesian maritime continent (MC). More than 15 years of satellite precipitation data recorded by tropical rainfall measuring mission (TRMM) were used in this analysis. The result reveals a large discrepancy between the active precipitation radar (PR 2A25) and passive microwave imager (TMI 2A12) over land surface. PR identifies low storm top height associated with large downward increase of radar reflectivity. In contrast, TMI identifies large ice scattering associated with higher storm top height, but with lower rain rates near surface. Further investigation identifies larger relative humidity and upward vertical velocity at middle part of the troposphere for the low storm height extremes. This condition represents a larger condensation around 300-500 hPa level, but less for the upper part. As a result, it produces lower amount of ice at the upper troposphere, contrasting to the type of extreme precipitation identified by TMI.

scholarly journals A Comparison of TRMM Microwave Techniques for Detecting the Diurnal Rainfall Cycle

2006 ◽  
Vol 7 (4) ◽  
pp. 687-704 ◽  
Author(s):  
Victoria L. Sanderson ◽  
Chris Kidd ◽  
Glenn R. McGregor
Keyword(s):  
Tropical Rainfall Measuring Mission ◽  
Time Of Day ◽  
Precipitation Radar ◽  
Near Surface ◽  
Diurnal Rainfall ◽  
Microwave Imager ◽  
Microwave Techniques ◽  
Trmm Microwave Imager ◽  
Rain Rates ◽  
Climatic Signals

Abstract This paper uses rainfall estimates retrieved from active and passive microwave data to investigate how spatially and temporally dependent algorithm biases affect the monitoring of the diurnal rainfall cycle. Microwave estimates used in this study are from the Tropical Rainfall Measuring Mission (TRMM) and include the precipitation radar (PR) near-surface (2A25), Goddard Profiling (GPROF) (2A12), and PR–TRMM Microwave Imager (TMI) (2B31) rain rates from the version 5 (v5) 3G68 product. A rainfall maximum is observed early evening over land, while oceans generally show a minimum in rainfall during the morning. Comparisons of annual and seasonal mean hourly rain rates and harmonics at both global and regional scales show significant differences between the algorithms. Relative and absolute biases over land vary according to the time of day. Clearly, these retrieval biases need accounting for, either in the physics of the algorithm or through the provision of accurate error estimates, to avoid erroneous climatic signals and the discrediting of satellite rainfall estimations.

Comparison of TRMM-Derived Rainfall Products for General and Extreme Rains over the Maritime Continent

2017 ◽  
Vol 56 (7) ◽  
pp. 1867-1881 ◽  
Author(s):  
Andung Bayu Sekaranom ◽  
Hirohiko Masunaga
Keyword(s):  
Rain Rate ◽  
Tropical Rainfall Measuring Mission ◽  
Maritime Continent ◽  
Brightness Temperatures ◽  
Extreme Rain ◽  
Trmm Precipitation ◽  
Precipitation Analysis ◽  
Microwave Imager ◽  
Trmm Microwave Imager ◽  
Rain Rates

AbstractProperties of the rain estimation differences between Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) 2A25, TRMM Microwave Imager (TMI) 2A12, and TRMM Multisatellite Precipitation Analysis (TMPA) 3B42 are investigated with a focus on distinguishing between nonextreme and extreme rains over the Maritime Continent from 1998 to 2014. Statistical analyses of collocated TMI 1B11 85-GHz polarization-corrected brightness temperatures, PR 2A23 storm-top heights, and PR 2A25 vertical rain profiles are conducted to identify possible sources of the differences. The results indicate that a large estimation difference exists between PR and TMI for the general rain rate (extreme and nonextreme events). The PR–TMI rain-rate differences are larger over land and coast than over ocean. When extreme rain is isolated, a higher frequency of occurrence is identified by PR over ocean, followed by TMI and TMPA. Over land, TMI yields higher rain frequencies than PR with an intermediate range of rain rates (between 15 and 25 mm h−1), but it gives way to PR for the highest extremes. The turnover at the highest rain rates arises because the heaviest rain depicted by PR does not necessarily accompany the strongest ice-scattering signals, which TMI relies on for estimating precipitation over land and coast.

scholarly journals Simulating the Effects of Land Surface Characteristics on Planetary Boundary Layer Parameters for a Modeled Landfalling Tropical Cyclone

Atmosphere ◽  
2022 ◽  
Vol 13 (1) ◽  
pp. 138
Author(s):  
Yu Wang ◽  
Corene J. Matyas
Keyword(s):  
Tropical Cyclone ◽  
Land Surface ◽  
Friction Velocity ◽  
Inner Core ◽  
Sensible Heat Flux ◽  
Surface Characteristics ◽  
Near Surface ◽  
Land Surfaces ◽  
Rain Rates ◽  
Land Surface Characteristics

This study examined whether varying moisture availability and roughness length for the land surface under a simulated Tropical Cyclone (TC) could affect its production of precipitation. The TC moved over the heterogeneous land surface of the southeastern U.S. in the control simulation, while the other simulations featured homogeneous land surfaces that were wet rough, wet smooth, dry rough, and dry smooth. Results suggest that the near-surface atmosphere was modified by the changes to the land surface, where the wet cases have higher latent and lower sensible heat flux values, and rough cases exhibit higher values of friction velocity. The analysis of areal-averaged rain rates and the area receiving low and high rain rates shows that simulations having a moist land surface produce higher rain rates and larger areas of low rain rates in the TC’s inner core. The dry and rough land surfaces produced a higher coverage of high rain rates in the outer regions. Key differences among the simulations happened as the TC core moved over land, while the outer rainbands produced more rain when moving over the coastline. These findings support the assertion that the modifications of the land surface can influence precipitation production within a landfalling TC.

Diurnal and Seasonal Lightning Variability over the Gulf Stream and the Gulf of Mexico

2015 ◽  
Vol 72 (7) ◽  
pp. 2657-2665 ◽  
Author(s):  
Katrina S. Virts ◽  
John M. Wallace ◽  
Michael L. Hutchins ◽  
Robert H. Holzworth
Keyword(s):  
Gulf Of Mexico ◽  
Diurnal Cycle ◽  
Gulf Stream ◽  
Land Surface ◽  
Southeastern United States ◽  
Surface Wind ◽  
Tropical Rainfall Measuring Mission ◽  
Sea Breeze ◽  
Near Surface ◽  
Early Evening

Recent observations from the World Wide Lightning Location Network (WWLLN) reveal a pronounced lightning maximum over the warm waters of the Gulf Stream that exhibits distinct diurnal and seasonal variability. Lightning is most frequent during summer (June–August). During afternoon and early evening, lightning is enhanced just onshore of the coast of the southeastern United States because of daytime heating of the land surface and the resulting sea-breeze circulations and convection. Near-surface wind observations from the Quick Scatterometer (QuikSCAT) satellite indicate divergence over the Gulf of Mexico and portions of the Gulf Stream at 1800 LT, at which time lightning activity is suppressed there. Lightning frequency exhibits a broad maximum over the Gulf Stream from evening through noon of the following day, and QuikSCAT wind observations at 0600 LT indicate low-level winds blowing away from the continent and converging over the Gulf Stream. Over the northern Gulf of Mexico, lightning is most frequent from around sunrise through late morning. During winter, lightning exhibits a weak diurnal cycle over the Gulf Stream, with most frequent lightning during the evening. Precipitation rates from a 3-hourly gridded dataset that incorporates observations from Tropical Rainfall Measuring Mission (TRMM), as well as other satellites, exhibit a diurnal cycle over the Gulf Stream that lags the lightning diurnal cycle by several hours.

scholarly journals On the Land–Ocean Contrast of Tropical Convection and Microphysics Statistics Derived from TRMM Satellite Signals and Global Storm-Resolving Models

2016 ◽  
Vol 17 (5) ◽  
pp. 1425-1445 ◽  
Author(s):  
Toshi Matsui ◽  
Jiun-Dar Chern ◽  
Wei-Kuo Tao ◽  
Stephen Lang ◽  
Masaki Satoh ◽  
...  
Keyword(s):  
Deep Convection ◽  
Tropical Rainfall Measuring Mission ◽  
Atmospheric Model ◽  
Evaluation Framework ◽  
Convective Precipitation ◽  
Modeling Framework ◽  
Near Surface ◽  
Microwave Scattering ◽  
Microwave Imager ◽  
Multiscale Modeling Framework

Abstract A 14-yr climatology of Tropical Rainfall Measuring Mission (TRMM) collocated multisensor signal statistics reveals a distinct land–ocean contrast as well as geographical variability of precipitation type, intensity, and microphysics. Microphysics information inferred from the TRMM Precipitation Radar and Microwave Imager show a large land–ocean contrast for the deep category, suggesting continental convective vigor. Over land, TRMM shows higher echo-top heights and larger maximum echoes, suggesting taller storms and more intense precipitation, as well as larger microwave scattering, suggesting the presence of more/larger frozen convective hydrometeors. This strong land–ocean contrast in deep convection is invariant over seasonal and multiyear time scales. Consequently, relatively short-term simulations from two global storm-resolving models can be evaluated in terms of their land–ocean statistics using the TRMM Triple-Sensor Three-Step Evaluation Framework via a satellite simulator. The models evaluated are the NASA Multiscale Modeling Framework (MMF) and the Nonhydrostatic Icosahedral Cloud Atmospheric Model (NICAM). While both simulations can represent convective land–ocean contrasts in warm precipitation to some extent, near-surface conditions over land are relatively moister in NICAM than MMF, which appears to be the key driver in the divergent warm precipitation results between the two models. Both the MMF and NICAM produced similar frequencies of large CAPE between land and ocean. The dry MMF boundary layer enhanced microwave scattering signals over land, but only NICAM had an enhanced deep convection frequency over land. Neither model could reproduce a realistic land–ocean contrast in deep convective precipitation microphysics. A realistic contrast between land and ocean remains an issue in global storm-resolving modeling.

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.

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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