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NASA NTRS2008

Contributions of TRMM and GPM to GEOSS

Two international satellite missions have a major role in the development of global precipitation data under the auspices of the Global Earth Observation System of Systems (GEOSS) to meet the needs of several Societal Benefit Areas set forth by the Group on Earth Observations (GEO). One is the joint U.S.-Japan Tropical Rainfall Measuring Mission (TRMM), launched in 1997, which provides combined radar/radiometer measurements to serve as a benchmark for tropical precipitation measurements by passive microwave radiometers and has played a key role in the development of the current generation of multi-satellite global rainfall products. The other is the Global Precipitation Measurement (GPM) Mission, an international satellite mission to be launched in 2013 to deliver the next-generation global precipitation observations from a constellation of dedicated and operational microwave sensors. GPM is a science mission with integrated applications goals aimed at (1) advancing the knowledge of the global water/energy cycle variability and freshwater availability and (2) improving weather, climate, and hydrological prediction capabilities through more accurate and frequent measurements of global precipitation. The GPM Mission is currently a partnership between NASA and the Japan Aerospace Exploration Agency (JAXA), with additional partners in satellite constellation and ground validation under discussion. With NASA and JAXA science team activities providing the framework and infrastructures for international collaboration on satellite inter-calibration, retrieval algorithm development, and ground validation, GPM has been identified as the cornerstone for the development of the Precipitation Constellation for the Committee on Earth Observation Satellites (CEOS). An overview of current accomplishments by TRMM and anticipated contributions by GPM to GEOSS activities will be presented.

Hou, Arthur Y.↗

NASA NTRS2009

Alongfront Variability of Precipitation Associated with a Midlatitude Frontal Zone: TRMM Observations and MM5 Simulation

On 19 February 2001, the Tropical Rainfall Measuring Mission (TRMM) satellite observed complex alongfront variability in the precipitation structure of an intense cold-frontal rainband. The TRMM Microwave Imager brightness temperatures suggested that, compared to the northern and southern ends of the rainband, a greater amount of precipitation ice was concentrated in the middle portion of the rainband where the front bowed out. A model simulation conducted using the fifth-generation Pennsylvania State University National Center for Atmospheric Research (PSU NCAR) Mesoscale Model (MM5) is examined to explain the distribution of precipitation associated with the cold-frontal rainband. The simulation reveals that the enhanced precipitation ice production and the implied mean ascent along the central part of the front were associated with a synergistic interaction between a low-level front and an upper-level front associated with an intrusion of high-PV stratospheric air. The low-level front contributed to an intense bow-shaped narrow cold-frontal rainband (NCFR). The upper-level front was dynamically active only along the central to northern portion of the NCFR, where the upper-level PV advection and Q-vector convergence were most prominent. The enhanced mean ascent associated with the upper-level front contributed to a wide cold-frontal rainband (WCFR) that trailed or overlapped with the NCFR along its central to northern segments. Because of the combination of the forcing from both lower- and upper-level fronts, the ascent was deepest and most intense along the central portion of the front. Thus, a large concentration of precipitation ice, attributed to both the NCFR and WCFR, was produced.

Han, Mei↗

NASA NTRS2010

Utilizing TRMM to Analyze Sea Breeze Thunderstorm Patterns During El Nino Southern Oscillations and Their Effects upon Available Fresh Water for South Florida Agricultural Planning and Management

Water is in high demand for farmers regardless of where you go. Unfortunately, farmers in southern Florida have fewer options for water supplies than public users and are often limited to using available supplies from surface and ground water sources which depend in part upon variable weather patterns. There is an interest by the agricultural community about the effect weather has on usable surface water, however, research into viable weather patterns during La Nina and El Nino has yet to be researched. Using rainfall accumulation data from NASA Tropical Rainfall Measurement Mission (TRMM) satellite, this project s purpose was to assess the influence of El Nino and La Nina Oscillations on sea breeze thunderstorm patterns, as well as general rainfall patterns during the summer season in South Florida. Through this research we were able to illustrate the spatial and temporal variations in rainfall accumulation for each oscillation in relation to major agricultural areas. The study period for this project is from 1998, when TRMM was first launched, to 2009. Since sea breezes in Florida typically occur in the months of May through October, these months were chosen to be the months of the study. During this time, there were five periods of El Nino and two periods of La Nina, with a neutral period separating each oscillation. In order to eliminate rainfall from systems other than sea breeze thunderstorms, only days that were conducive to the development of a sea breeze front were selected.

Cooley, Clayton↗

NASA NTRS2010

Analysis of TRMM-LIS Lightning and Related Microphysics Using a Cell-Scale Database

Previous studies of tropical lightning activity using Tropical Rainfall Measurement Mission (TRMM) Lightning Imaging Sensor (LIS) data performed analyses of lightning behavior over mesoscale "feature" scales or over uniform grids. In order to study lightning and the governing ice microphysics intrinsic to thunderstorms at a more process-specific scale (i.e., the scale over which electrification processes and lightning occur in a "unit" thunderstorm), a new convective cell-scale database was developed by analyzing and refining the University of Utah's Precipitation Features database and retaining precipitation data parameters computed from the TRMM precipitation radar (PR), microwave imager (TMI) and LIS instruments. The resulting data base was to conduct a limited four-year study of tropical continental convection occurring over the Amazon Basin, Congo, Maritime Continent and the western Pacific Ocean. The analysis reveals expected strong correlations between lightning flash counts per cell and ice proxies, such as ice water path, minimum and average 85GHz brightness temperatures, and 18dBz echo top heights above the freezing level in all regimes, as well as regime-specific relationships between lighting flash counts and PR-derived surface rainfall rates. Additionally, radar CFADs were used to partition the 3D structure of cells in each regime at different flash counts. The resulting cell-scale analyses are compared to previous mesoscale feature and gridded studies wherever possible.

Leroy, Anita↗

NASA NTRS2011

Quantifying Errors in TRMM-Based Multi-Sensor QPE Products Over Land in Preparation for GPM

Determining uncertainties in satellite-based multi-sensor quantitative precipitation estimates over land of fundamental importance to both data producers and hydro climatological applications. ,Evaluating TRMM-era products also lays the groundwork and sets the direction for algorithm and applications development for future missions including GPM. QPE uncertainties result mostly from the interplay of systematic errors and random errors. In this work, we will synthesize our recent results quantifying the error characteristics of satellite-based precipitation estimates. Both systematic errors and total uncertainties have been analyzed for six different TRMM-era precipitation products (3B42, 3B42RT, CMORPH, PERSIANN, NRL and GSMap). For systematic errors, we devised an error decomposition scheme to separate errors in precipitation estimates into three independent components, hit biases, missed precipitation and false precipitation. This decomposition scheme reveals hydroclimatologically-relevant error features and provides a better link to the error sources than conventional analysis, because in the latter these error components tend to cancel one another when aggregated or averaged in space or time. For the random errors, we calculated the measurement spread from the ensemble of these six quasi-independent products, and thus produced a global map of measurement uncertainties. The map yields a global view of the error characteristics and their regional and seasonal variations, reveals many undocumented error features over areas with no validation data available, and provides better guidance to global assimilation of satellite-based precipitation data. Insights gained from these results and how they could help with GPM will be highlighted.

Peters-Lidard, Christa D.↗

NASA NTRS2014

Developing GIOVANNI-based Online Prototypes to Intercompare TRMM-Related Global Gridded-Precipitation Products

New online prototypes have been developed to extend and enhance the previous effort by facilitating investigation of product characteristics and intercomparison of precipitation products in different algorithms as well as in different versions at different spatial scales ranging from local to global without downloading data and software. Several popular Tropical Rainfall Measuring Mission (TRMM) products and the TRMM Composite Climatology are included. In addition, users can download customized data in several popular formats for further analysis. Examples show product quality problems and differences in several monthly precipitation products. It is seen that differences in daily and monthly precipitation products are distributed unevenly in space and it is necessary to have tools such as those presented here for customized and detailed investigations. A simple time series and two area maps allow the discovery of abnormal values of 3A25 in one of the months. An example shows a V-shaped valley issue in the Version 6 3B43 time series and another example shows a sudden drop in 3A25 monthly rain rate, all of which provide important information when the products are used for long-term trend studies. Future plans include adding more products and statistical functionality in the prototypes.

data analysis↗

NASA NTRS2018

Latent Heating from TRMM and GPM Measurement

The Goddard Convective-Stratiform Heating (CSH) algorithm, used to estimate cloud heating in support of the Tropical Rainfall Measuring Mission (TRMM), is upgraded in support of the Global Precipitation Measurement mission (GPM). The algorithm is required to use look-uptables (LUTs) from cloud-resolving model (CRM) simulations from the Goddard Cumulus Ensemble model (GCE). This paper will present the heating retrievals from the Goddard CSH algorithm in the TRMM and GPM using precipitation products (rainfall, radar reflectivity).

Latent Heating↗

NASA NTRS2021

Goddard Latent Heating Retrieval Algorithm for TRMM and GPM

The Goddard Convective-Stratiform Heating (CSH) algorithm has been used to retrieve latent heating (LH) associated with clouds and cloud systems in support of the Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Measurement (GPM) mission. The CSH algorithm requires the use of a cloud-resolving model (CRM) to simulate LH profiles to build look-up tables (LUTs). In this paper we describe the current V6 CSH and its differences/similarities versus the previous V5 CSH. Long-term CRM simulations are conducted to identify the impact of CRM resolution and the convective-stratiform separation method on LH structure/profiles. The TRMM and GPM Combined algorithm derived surface rainfall rates and their associated precipitation properties are the input to the CSH algorithm. Since there is no direct measurement of LH structure, the performance of the CSH V6 algorithm is examined by comparing its vertically-integrated heating (or equivalent surface rainfall rate) against the surface rainfall rate derived from the TRMM/GPM Combined algorithm. The results suggest the CSH three-month and zonal mean equivalent surface rain rates are in good agreement with the Combined rates over the ITCZ region; the agreement is best over ocean. CSH three-month and zonal mean equivalent surface rain rates are larger than the Combined rates over land in both the tropics and sub-tropics. CSH three-month mean equivalent surface rainfall rates also have local differences with the Combined rates that can be smoothed by area averaging to larger horizontal resolutions (from the CSH standard grid of 0.25° × 0.25° to 0.5° × 0.5° or 1.0° × 1.0°). CSH equivalent surface rainfall rates have more light rain rates but less larger rain rates compared to the GPM Combined surface rain rates.

Latent heating retrieval↗

NASA NTRSDate not supplied

CERES BiDirectional Scans (BDS) data in HDF (CER_BDS_TRMM-PFM_Edition1)

Each BiDirectional Scans (BDS) data product contains twenty-four hours of Level-1b data for each CERES scanner instrument mounted on each spacecraft. The BDS includes samples taken in normal and short Earth scan elevation profiles in both fixed and rotating azimuth scan modes (including space, internal calibration, and solar calibration views). The BDS contains Level-0 raw (unconverted) science and instrument data as well as the geolocated converted science and instrument data. The BDS contains additional data not found in the Level-0 input file, including converted satellite position and velocity data, celestial data, converted digital status data, and parameters used in the radiance count conversion equations. The following CERES BDS data sets are currently available: CER_BDS_TRMM-PFM_Edition1 CER_BDS_Terra-FM1_Edition1 CER_BDS_Terra-FM2_Edition1 CER_BDS_Terra-FM1_Edition2 CER_BDS_Terra-FM2_Edition2 CER_BDS_Aqua-FM3_Edition1 CER_BDS_Aqua-FM4_Edition1 CER_BDS_Aqua-FM3_Edition2 CER_BDS_Aqua-FM4_Edition2 CER_BDS_Aqua-FM3_Edition1-CV CER_BDS_Aqua-FM4_Edition1-CV CER_BDS_Terra-FM1_Edition1-CV CER_BDS_Terra-FM2_Edition1-CV. [Location=GLOBAL] [Temporal_Coverage: Start_Date=1997-12-27; Stop_Date=2000-12-31] [Spatial_Coverage: Southernmost_Latitude=-90; Northernmost_Latitude=90; Westernmost_Longitude=-180; Easternmost_Longitude=180] [Data_Resolution: Temporal_Resolution=1 day; Temporal_Resolution_Range=Daily - < Weekly].

SHORTWAVE FILTERED RADIANCE UPWARDS↗

NASA NTRS2013

Assessment of Evolving TRMM-Based Real-Time Precipitation Estimation Methods and Their Impacts on Hydrologic Prediction in a High-Latitude Basin

The real-time availability of satellite-derived precipitation estimates provides hydrologists an opportunity to improve current hydrologic prediction capability for medium to large river basins. Due to the availability of new satellite data and upgrades to the precipitation algorithms, the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis real-time estimates (TMPA-RT) have been undergoing several important revisions over the past ten years. In this study, the changes of the relative accuracy and hydrologic potential of TMPA-RT estimates over its three major evolving periods were evaluated and inter-compared at daily, monthly and seasonal scales in the high-latitude Laohahe basin in China. Assessment results show that the performance of TMPA-RT in terms of precipitation estimation and streamflow simulation was significantly improved after 3 February 2005. Overestimation during winter months was noteworthy and consistent, which is suggested to be a consequence from interference of snow cover to the passive microwave retrievals. Rainfall estimated by the new version 6 of TMPA-RT starting from 1 October 2008 to present has higher correlations with independent gauge observations and tends to perform better in detecting rain compared to the prior periods, although it suffers larger mean error and relative bias. After a simple bias correction, this latest dataset of TMPA-RT exhibited the best capability in capturing hydrologic response among the three tested periods. In summary, this study demonstrated that there is an increasing potential in the use of TMPA-RT in hydrologic streamflow simulations over its three algorithm upgrade periods, but still with significant challenges during the winter snowing events.

hydrologic prediction↗

NASA NTRS2013

Statistical and Hydrological Evaluation of TRMM-Based Multi-Satellite Precipitation Analysis over the Wangchu Basin of Bhutan: Are the Latest Satellite Precipitation Products 3B42V7 Ready for Use in Ungauged Basins?

The objective of this study is to quantitatively evaluate the successive Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) products and further to explore the improvements and error propagation of the latest 3B42V7 algorithm relative to its predecessor 3B42V6 using the Coupled Routing and Excess Storage (CREST) hydrologic model in the mountainous Wangchu Basin of Bhutan. First, the comparison to a decade-long (2001-2010) daily rain gauge dataset reveals that: 1) 3B42V7 generally improves upon 3B42V6s underestimation both for the whole basin (bias from -41.15 to -8.38) and for a 0.250.25 grid cell with high-density gauges (bias from -40.25 to 0.04), though with modest enhancement of correlation coefficients (CC) (from 0.36 to 0.40 for basin-wide and from 0.37 to 0.41 for grid); and 2) 3B42V7 also improves its occurrence frequency across the rain intensity spectrum. Using the CREST model that has been calibrated with rain gauge inputs, the 3B42V6-based simulation shows limited hydrologic prediction NSCE skill (0.23 in daily scale and 0.25 in monthly scale) while 3B42V7 performs fairly well (0.66 in daily scale and 0.77 in monthly scale), a comparable skill score with the gauge rainfall simulations. After recalibrating the model with the respective TMPA data, significant improvements are observed for 3B42V6 across all categories, but not as much enhancement for the already well-performing 3B42V7 except for a reduction in bias (from -26.98 to -4.81). In summary, the latest 3B42V7 algorithm reveals a significant upgrade from 3B42V6 both in precipitation accuracy (i.e., correcting the underestimation) thus improving its potential hydrological utility. Forcing the model with 3B42V7 rainfall yields comparable skill scores with in-situ gauges even without recalibration of the hydrological model by the satellite precipitation, a compensating approach often used but not favored by the hydrology community, particularly in ungauged basins.

TRMM↗

NASA NTRS2013

Rain Characteristics and Large-Scale Environments of Precipitation Objects with Extreme Rain Volumes from TRMM Observations

This study adopts a "precipitation object" approach by using 14 years of Tropical Rainfall Measuring Mission (TRMM) Precipitation Feature (PF) and National Centers for Environmental Prediction (NCEP) reanalysis data to study rainfall structure and environmental factors associated with extreme heavy rain events. Characteristics of instantaneous extreme volumetric PFs are examined and compared to those of intermediate and small systems. It is found that instantaneous PFs exhibit a much wider scale range compared to the daily gridded precipitation accumulation range. The top 1% of the rainiest PFs contribute over 55% of total rainfall and have 2 orders of rain volume magnitude greater than those of the median PFs. We find a threshold near the top 10% beyond which the PFs grow exponentially into larger, deeper, and colder rain systems. NCEP reanalyses show that midlevel relative humidity and total precipitable water increase steadily with increasingly larger PFs, along with a rapid increase of 500 hPa upward vertical velocity beyond the top 10%. This provides the necessary moisture convergence to amplify and sustain the extreme events. The rapid increase in vertical motion is associated with the release of convective available potential energy (CAPE) in mature systems, as is evident in the increase in CAPE of PFs up to 10% and the subsequent dropoff. The study illustrates distinct stages in the development of an extreme rainfall event including: (1) a systematic buildup in large-scale temperature and moisture, (2) a rapid change in rain structure, (3) explosive growth of the PF size, and (4) a release of CAPE before the demise of the event.

TRMM↗

NASA NTRS2016

Detecting Climate Signals in Precipitation Extremes from TRMM (1998-2013) - Increasing Contrast Between Wet and Dry Extremes During the "Global Warming Hiatus"

We investigate changes in daily precipitation extremes using Tropical Rainfall Measuring Mission (TRMM) data (1998-2013), which coincides with the "global warming hiatus." Results show a change in probability distribution functions of local precipitation events (LPEs) during this period consistent with previous global warming studies, indicating increasing contrast between wet and dry extremes, with more intense LPE, less moderate LPE, and more dry (no rain) days globally. Analyses for land and ocean separately reveal more complex and nuanced changes over land, characterized by a strong positive trend (+12.0% per decade, 99% confidence level (c.l.)) in frequency of extreme LPEs over the Northern Hemisphere extratropics during the wet season but a negative global trend (−6.6% per decade, 95% c.l.) during the dry season. A significant global drying trend (3.2% per decade, 99% c.l.) over land is also found during the dry season. Regions of pronounced increased dry events include western and central U.S., northeastern Asia, and Southern Europe/Mediterranean.

Precipitation↗

NASA NTRS2017

Precipitating Cloud Characteristics During Changma as Seen in TRMM PR Observations

The climatological characteristics of precipitating clouds during Changma, the summer rainy period in the Korean Peninsula, were investigated using the Precipitation Radar (PR) on the Tropical Rainfall Measuring Mission (TRMM) satellite. This investigation was further augmented with reanalysis data. Specifically, Changma clouds are compared with post-Changma clouds. Similarities and differences in cloud properties between the two periods are discussed based on seasonal changes in thermodynamic environments. For convective clouds migrating along the Changma (stationary) front, rain intensity is much stronger and cloud height is relatively higher than during any other summer period, including post-Changma. Convective rain clouds have a large seasonal variability, even during summer. The seasonal variability in rain parameters related to convective rain type appears to be due to the thermodynamic and dynamic environments.

precipitation↗

NASA NTRS2021

Validation of Satellite-Based Precipitation Products from TRMM to GPM

The global precipitation measurement mission (GPM) has been in operation for seven years and continues to provide a vast quantity of global precipitation data at finer temporospatial resolutions with improved accuracy and coverage. GPM’s signature algorithm, the integrated multisatellite retrievals for GPM (IMERG) is a next-generation of precipitation product expected for wide variety of research and operational applications. This study evaluates the latest version (V06B) of IMERG and its predecessor, the tropical rainfall measuring mission (TRMM) multisatellite precipitation (TMPA) 3B42 (V7) using ground-based and gauge-corrected multiradar multisensor system (MRMS) precipitation products over the conterminous United States (CONUS). The spatial distributions of all products are analyzed. The error characteristics are further examined for 3B42 and IMERG in winter and summer by an error decomposition approach, which partitions total bias into hit bias, biases due to missed precipitation and false precipitation. The volumetric and categorical statistical metrics are used to quantitatively evaluate the performance of the two satellite-based products. All products show a similar precipitation climatology with some regional differences. The two satellite-based products perform better in the eastern CONUS than in the mountainous Western CONUS. The evaluation demonstrates the clear improvement in IMERG precipitation product in comparison with its predecessor 3B42, especially in reducing missed precipitation in winter and summer, and hit bias in winter, resulting in better performance in capturing lighter and heavier precipitation.

MRMS↗

NASA NTRS1988

TRMM ground truth in a monsoon environment - Darwin, Australia

A ground truth station for the Tropical Rainfall Measuring Mission (TRMM) is described. The station is situated in Darwin, Australia in a monsoon environment typical for Southeast Asia. The climatological features of the site, and the Darwin observational program are examined. The instruments and operations at the station are discussed, including a Doppler radar making full upper tropospheric soundings every 12 hrs and wind soundings every 6 hrs, and a mesoscale raingauge and surface observing network operating continuously through the summer monsoon seasons. The spatial and temporal characteristics of rainfall in the area and an outline of the research objectives of the program are presented.

Keenan, T. D.↗

NASA NTRS1989

The ground truth analysis of rain gauge data for the TRMM project

As a part of the Tropical Rainfall Measuring Missioin (TRMM) ground truth program to determine the diurnal variability of the area wide rain rates, the rain rate PDFs, and their effect on the area integral algorithm, rain rate data have been collected from a network of gages located in the area near the Cape Canaveral and Kennedy Space Center, in the period beginning in September 1987. In the preliminary statistical analysis, based on the rain rates derived from the eleven gages, the seasonal diurnal rainfall and network averaged rain rates are determined. The analysis was performed in two steps: determination of the hourly and daily rain accumulations and rain rates; and computation of the fraction of hourly and daily rain rates that exceed a particular threshold, and analysis of the hourly and daily rain rate PDFs for the network. The results indicate that there are diurnal and seasonal variations in the components which determine the network rain rate PDFs.

Kowalewsky, Karen J.↗

NASA NTRS1993

Some thoughts on future rain mapping missions (TRMM follow-on)

The release of latent heat of condensation is the largest internal energy source of the atmosphere. Latent heating is most significant during the precipitation process. Our knowledge of the distribution of precipitation is poor. It is only well observed within limited areas of the globe. Over the oceans, for example, it is known only to within a factor of two. Thus, there are strong scientific requirements for observations of precipitation from instruments on board a satellite. The Tropical Rainfall Measuring Mission (TRMM) will be the first satellite to measure rainfall with adequate accuracy and provide information about the vertical distribution of precipitation, not only in tropics and subtropics, but to plus or minus 35 degrees of latitude. There is a need for the continuity of rain observations for climate modeling purposes and to expand observations to cover more of the globe than simply plus or minus 35 degrees latitude.

Theon, John S.↗