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Summary: This document contains descriptions of the
standard products of the Tropical Rainfall Measuring Mission (TRMM) and
information on accessing the data. The TRMM standard products include
measurements from satellite and ground-based sensors and geophysical parameters
derived from them. The sensor meaurements include visible and infrared
radiance, microwave brightness temperature, radar reflectivity, surface radar
volume scans, and rain gauge and disdrometer data. The derived geophysical
products include vertical rain and hydrometeor profiles, rain type, radar
backscatter cross section, raindrop size distribution, rain gauge rain rates,
and five-day and monthly average rain rates. The TRMM satellite, launched in
November 1997 and covering the latitude belt between approximately 38 degree N
to 38 degree S, has a designed three-year mission life.
Acknowledgment:
The distribution of this data set is funded by NASA's Earth Science Enterprise
(ESE). The data are not copyrighted; however, we request that when you
publish data or results using these data, please send a copy of your
publication to Help Desk, Goddard DAAC, Code 610.2, NASA GSFC, Greenbelt, MD
20771 or email the reference of your publication to daacuso@daac.gsfc.nasa.gov.
Please acknowledge as follows:
The data used in this study were acquired as part of the Tropical
Rainfall Measuring Mission (TRMM). The algorithms were developed by the TRMM
Science Team. The data were processed by the TRMM Science Data and Information
System (TSDIS) and the TRMM office; they are archived and distributed by the
Goddard Distributed Active Archive Center. TRMM is an international project
jointly sponsored by the Japan National Space Development Agency (NASDA) and
the US National Aeronautics and Space Administration (NASA) Office of Earth
Sciences.
Table of Contents:
TRMM is a comprehensive and systematic program designed to increase the extent and accuracy of tropical rainfall measurement. The
TRMM science program involving some 3 dozen national and international scientists consists of a broad research effort which includes
development of cloud models, rain retrieval algorithms for the space sensors, use of TRMM measurements with other satellite data to
improve sampling, a surface-based verification system, and a TRMM science data and information system (TSDIS).
The table below summarizes the TRMM standard products available at the Goddard DAAC. Level 1 products are the VIRS calibrated
radiances, the TMI brightness temperatures, and the PR return power and reflectivity measurements. Level 2 products are derived
geophysical parameters at the same resolution and location as those of the Level 1 source data. Level 3 products are the time-averaged
parameters mapped onto a uniform space-time grid.
TRMM Products at the Goddard DAAC
| | Visible Infrared Scanner | TRMM
Microwave Imager | Precipitation
Radar | Combined Products | Ground Validation
(GV) |
|---|
| Level 1 | Visible & IR
radiances | Microwave brightness temperatures |
Radar return power & reflectivity |
NA | Cal. radar reflectivity at each
GV site |
| Level 2 | NA |
TMI profile for CLW, prec. water, cloud ice, prec. ice,
latent heat, & surface rain | PR surface cross-section
& path attenuation, rain type, storm, & freezing height; PR profile for
rain rate, reflec., attenuation, & rain top/bottom height |
Rain rate, drop size dist. parameters, path integrated
attenuation | Rain existence, rain map, rain type, 3-D
reflectivity, rain gauge, disdrometer |
| Level 3 | NA |
TMI monthly rainfall, rain rate, rain frequency, &
freezing height | PR monthly surface rain total, rain
profile at 2, 4, 6, 10 & 15 km, fractional rain, storm height
histogram, snow ice layer, surface rain rate, & path
attenuation | Monthly surface rainfall, CLW, rain
water, cloud ice, & grauples; combined instruments calibration, global
gridded rainfall | Rain map, 3-D map |
- Global Precipitation Data
(Available via anonymous FTP)
-
- Arkin & Janowiak GPI:
IR-Based Monthly Rainfall for the GPCP
Chang SSM/I Derived Monthly
Rain Indices for the GPCP
GPCC Rain Gauge Analysis
for the GPCP
GPCP Version 2 Combined
Precipitation Data Set
Jaeger Global Monthly Mean
Precipitation
Legates Surface & Ship
Observations of Precipitation
NOAA/NASA SSM/I Pathfinder
Precipitation
-
- Interdisciplinary Hydrology Data Collections
(Available via anonymous FTP)
-
- SSM/I Surface Turbulent Fluxes
Satellite Retrieved Sea Surface Radiation Budget
GPCC Global Rain Gauge Analysis
Tropical Rainfall Measuring Mission (TRMM)
Robert Adler
Jun Awaka
William Barnes
Alfred T.C. Chang
Long Chiu
Brad Ferrier
Bradford Fisher
Toshio iguchi
Christian Kummerow
Robert meneghini
James Shiue
Eric Smith
HYDROLOGY DATA SUPPORT TEAM
GSFC DAAC
hydrology@daac.gsfc.nasa.gov
Phone: (301) 614-5224
FAX (301) 614-5268
Distributed Active Archive Center
Code 610.2
NASA Goddard Space Flight Center
Greenbelt, MD 20771
USA
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The June 1998 interim release includes most level 1 TRMM standard products.
- Level 1A data
-
The VIRS and TMI Level 1A products (1A-01 and 1A-11, respectively) consist
of two files each: a product file and a Standard Format Data Unit (SFDU) header
file. The Level 1A file is a concatenation of header record, spacecraft
attitude packets, sensor (VIRS/TMI) housekeeping data packets, sensor
(VIRS/TMI) science data packets, Quality and Accounting Capsules (QACs), and
Missing Data Unit List (MDUL). The Level 1A PR file (1A-21) is a concatenation
of a TSDIS header, spacecraft attitude packets, PR housekeeping data packets,
PR science data packets, calibration coefficients, QACs, and MDUL. The Goddard
DAAC does not archive the Level 1A PR product.
- Level 1 algorithms
-
The VIRS calibration algorithm (1B-01) converts the digital counts collected by
VIRS to spectral radiance. Bands 1 and 2 measure solar radiation, and bands 3,
4, and 5 measure emitted thermal (IR) radiance. The calibration of the solar
bands uses the VIRS counts from viewing the moon or the sun through a solar
diffuser, together with zero radiance collected from a space view. Calibration
parameters are calculated once 1 -4 weeks. The IR bands are calibrated for each
scan line using data from the internal blackbody and space view. These two
points and a quadratic term determined pre-launch are used to generate a count
vs. radiance curve for the IR bands. Additional corrections are generated
from differences in emittance of the two sides of the scan mirror, out-of-band
transmittance, scan angle modulation, 1/f noise, black body temperature
variations due to views of the sensor cavity and the Earth, detector
temperature variations, and sensor temperature changes.
The TMI calibration algorithm (1B-11) converts the radiometer counts to antenna
temperatures by applying a linear relationship of the form Ta = c1 + c2 x count.
The coefficients are provided by the instrument contractor. Antenna temperatures
are corrected for cross-polarization and spill over to produce brightness
temperatures (Tb), but no antenna beam pattern correction or sample to pixel
averaging are performed. Temperatures are provided at 104 scan positions for
the low frequency channels and 208 scan positions at 85 GHz. There are four
samples per pixel (3 -dB beamwidth) at 10 GHz, two samples at 19, 22, and 37
GHz, and one sample per pixel for the 85 GHz.
The PR calibration algorithm (1B-21) converts the counts of radar
echoes and noise levels into engineering values (power) and outputs the radar
echo power and noise power separately. The algorithm also detects and flags the
range bin with return power that exceeds a pre-determined threshold value.
The PR reflectivity algorithm (1C-21) converts the power and noise estimates
from 1B-21 to radar reflectivity factors (Z-factors). In order to reduce
output data volume, only pixels with power that exceeds the minimum echo
detected in 1B-21 are converted and stored.
GV product 1B-51 consists of raw radar data in polar coordinate
scans at the original spatial and temporal resolution of the data collected by
the radar. The data are reformatted to the HDF format. Two additional procedures
are applied to reduce data size. Scan data at a range beyond 230 km and
spectral width data available from WSR-88 radars are not archived. Only radar
data for the GV direct data (DD) sites (Houston, TX; Melbourne, FL; Darwin,
Australia; and Kwajalein, Marshal Islands) are available. All volume scans are
kept for this product.
The QC reflectivity algorithm (1C-51) further truncates 1B-51 from a
range of 230 km to 200 km. In addition, a threshold Z-factor (-15 dBZ) is
applied to the reflectivity data, a quality control (QC) mask which
identifies pixels that need further processing is generated, and a
correction mask for the pixels identified above is generated. This product
(1C-51) is archived for all GV radars. All volume scans are
kept when there is a satellite overpass; otherwise, only one volume scan
every 30 minutes is kept. Satellite overpass is defined as the time period
during which the sub-satellite point is within 700 km of the radar, and
the overpass time is within +/-30 minutes.
- Level 2 satellite algorithms
-
There is no Level 2 algorithm for VIRS, only one algorithm for TMI, three
algorithms for PR, and one combined TMI/PR algorithm.
The TMI profiling algorithm (2A-12) generates vertical profiles of hydrometeors
from TMI brightness temperatures by blending the radiometric data with dynamical
cloud models. For each pixel, the algorithm assigns a surface type
(land/ocean/coast) and a freezing height; and computes profiles of hydrometeors
(cloud liquid, cloud ice, water vapor, etc.), comprising 14 vertical levels,
and surface rain rate.
The sigma zero algorithm (2A-21) inputs the PR power (1B-21) and computes an
estimate of the path attenuation and its reliability by using the surface as
reference target. It also computes the spatial and temporal statistics of the
surface scattering cross section and classifies the cross sections into
land/ocean and rain/no rain categories.
The PR qualitative algorithm (2A-23) inputs PR reflectivities (1C-21) and
returns a rain/no rain decision based on echo structure. When rain is present,
a storm height is calculated. If a bright band is detected, the height of the
bright band is also given.
The PR profile algorithm (2A-25) estimates hydrometeor profiles for each radar
beam. Rainfall rates are given for each resolution cell (4 km x 4 km x 250 m)
of the PR. Inputs for this algorithm include PR reflectivity (1C-21), sigma
zero (2A-21), and PR qualitative (2A-23).
The TRMM combined algorithm (2B-31) combines data from the TMI and PR to produce
the best rain estimate for TRMM. Currently, it uses the low frequency channels
of TMI to find the total path attenuation. This information is used to
constrain the radar equation. Inputs for this algorithm include TMI radiance
(1B-11), PR reflectivity (1C-21), and PR qualitative (2A-23).
- Level 2 GV algorithms
- The radar site rain map algorithm (2A-53) produces instantaneous rain rate
maps at 2 km x 2 km resolution from GV Quality controlled radar reflectivity
(1C-51), by using an appropriate reflectivity-rain rate (Z-R) relation.
The radar site convective/stratiform map algorithm (2A-54) classifies the
surface precipitation as convective or stratiform from QC radar reflectivity
(1C-51).
Using the radar site convective/stratiform map (2A-54), the rain existence
algorithm (2A-52) determines the fraction of the radar field of view which has
detectable precipitation.
The radar site 3-D reflectivity algorithm (2A-55) interpolates the
instantaneous reflectivities of a radar volume scan onto a 3-dimensional
Cartesian grid with 1.5 km vertical and 2 km horizontal resolutions. In addition
to the 3-D gridded reflectivity, the product includes mean reflectivity and
distribution at each height. The frequency distribution are provided in the
form of contoured frequency by altitude diagrams (CFADs). Vertical profiles for
the CFADs are further classified into land/ocean, convective/stratiform/anvil
rain types.
In addition to the above four Level 2 GV products, time series of the rain
gauge data are available. The rain gauge algorithm (2A-56)
converts the raw rain gauge data into average and peak minute rain rates,
if rain is present in the minute interval.
- Level 3 satellite algorithms
- The TMI monthly surface rainfall algorithm (3A-11) estimates monthly rain
from the histogram of the brightness temperatures obtained from TMI calibration
(1B-11). This histogram is matched to a log-normally
distributed rain rate distribution via a rain rate-brightness temperature
relation. A beam-filling correction is applied to account for the non-uniformly
filled field-of-view of the TMI sensor. Outputs are monthly surface rain rates
and freezing heights for 5 x 5 degree grid boxes.
The PR monthly rain structure algorithm (3A-25) accumulates several important
products derived from PR reflectivities (1C-21) and Level 2 PR products (2A-21,
2A-23, and 2A-25). Its outputs include rain rate accumulation over a month for
5 x 5 degree grid boxes at heights of 2 and 4 km, histograms of radar and
meteorological parameters, fraction of rain and bright band area, and
correlations between the various radar and meteorological parameters.
The PR monthly surface rainfall algorithm (3A-26) computes monthly rainfall,
at the surface and three vertical levels, for 5 x 5 degree grid boxes,
using a statistical technique. This technique uses multiple thresholds of
rain rate that are within the dynamic range of the PR. The rain rate
distribution is then fitted to a log-normal or gamma distribution.
The GV monthly rainfall map algorithm (3A-54) and GV 5-day rainfall map
algorithm (3A-53) accumulate 2 km x 2 km instantaneous rainfall from all
radars at a site for a month and for five days, respectively. The input for
both algorithms is the radar site rain map (2A-53).
The monthly 3-D structure algorithm (3A-55) computes the mean reflectivity and
frequency distribution of reflectivity at each height from the gridded 3-D
reflectivity (2A-55). The frequency distributions, provided in CFADs, are
presented for the total, land/ocean, convective/stratiform/anvil rain.
The combined monthly rainfall structure algorithm (3B-31) uses the output from
the combined rainfall structure (2B-31) to calibrate TMI rainfall structure
(2A-12) on a monthly basis. To accomplish this, the TMI rainfall structure
data are subsampled to the combined rainfall structure (2B-31) and calibration
coefficients computed for the region of overlap. The outputs consist of surface
rainfall, the number of satellite visits to the grid box, confidence, five
classes of hydrometeors, and latent heating at 14 vertical layers.
The combined instrument rain calibration algorithm (3B-42) uses combined rain
structure (2B-31) and VIRS calibration (1B-01) to adjust IR estimates from
geosynchronous IR observations. Global estimates are made by adjusting the GOES
Precipitation Index (GPI) to the TRMM estimates. The output is rainfall for
1 x 1 degree grid boxes for a 5-day (pentad) period.
The global rainfall algorithm (3B-43) combines the TRMM estimates; the
calibrated IR generated by combined instrument rain calibration (3B-42); gridded
SSM/I estimates from TRMM algorithm developers; and global gridded rain gauge
data from CAMS, produced by NOAA's Climate Prediction Center and/or global
rain gauge product, produced by the Global Precipitation Climatology Center
(GPCC).
...
TRMM satellite data for each orbit are stored on board and
transmitted to the ground via the NASA's Tracking and Data Relay Satellite System (TDRSS.) The TRMM science data are
processed by the Precipitation Processing System (PPS) also formerly known as the TRMM Science Data and Information System (TSDIS) into standard products. These
products are transferred to the Goddard DAAC for archival and
distribution.
...
The average operating altitude for TRMM was changed from 350 to 403 kilometers during the period of August 7-24, 2001.
Because of this orbit boost maneuver, algorithms of post-boost TRMM PR (Precipitation Radar) products have been changed.
Here are the Caveats for Post-boost PR Products from TRMM PR algorithm scientists.
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The file formats for TRMM Level 1, Level 2, and level 3 data
products are described below. These products are stored in the Hierarchical
Data Format (HDF).
The four data structures used for TRMM data products are:
- Swath structure
The swath structure was designed by
EOSDIS (EOS Data and Information System) to store satellite data that
are organized by scans. This data structure is used for Levels 1B, 1C, 2A,
and 2B satellite products. The swath structure is contained in a Vgroup, with
the name SwathData and the class SwathData. The SwathData Vgroup includes
SwathStructure, Scan Time, Geolocation, scan data, and IFOV data. For all
of these objects, the scan dimension has the least rapidly varying index.
SwathStructure is a text block which specifies which geolocations and times
apply to which elements of the IFOV data. The Scan
Time is a Vdata (8-byte float or several integers whose sizes sum to 8 bytes).
The Geolocation is an SDS containing latitude and longitude (4-byte float).
Scan data are data that apply to the whole scan and can take the form of one
or more Vdatas or SDSs. The IFOV data occur at every pixel or at regular
pixel intervals (e.g., every 10 pixels) and take the form of one or more SDSs.
- Planetary grid structure
The planetary grid structure was designed by EOSDIS to store earth-
located grids. A grid is an array of grid boxes, rather than grid points.
This data structure is used for Levels 3A and 3B satellite products. The
planetary grid structure occupies part of a file. This structure is contained
in a Vgroup, with the name PlanetaryGrid and the class PlanetaryGrid. The
PlanetaryGrid Vgroup includes one GridStructure, one or more Data Grids,
and other Data.
GridStructure is a single Vdata which allows the geometric interpretation
of the grids. GridStructure is an object that mimics an attribute,
since HDF has not yet defined attributes for Vgroups. This imitation of
an attribute is implemented as a Vdata with the name GridStructure and
the class "Attr0.0", one field named "VALUES," number type of DFNT_CHAR8,
and order equal to the length of the text. This specification of
GridStructure anticipates the HDF development of attributes for Vgroups.
The maximum expected size for GridStructure is 5000 bytes.
- Radar grid structure
The radar grid structure is a structure used to store TRMM GV Level-2 and
Level-3 grids which are defined by TSDIS. The grid is equivalent to the
grid created by the NCAR SPRINT software and does not correspond to any
standard projection. It is neither equal area nor equal angle. The grid
is an array of grid points, rather than grid boxes. It has a fixed
horizontal distance between grid points and an odd number of grid points
in the x and y directions. The origin is in the central grid point of the
lowest grid plane. Distances along the x and y directions are measured on
a flat plane tangent to the earth's surface directly below the origin. The
z distances are measured from mean sea level, perpendicular to this tangent
plane. The x dimension coincides with east-west only along the x-direction
grid line that intersects the origin. Similarly, the y dimension coincides
with north-south only along the y-direction grid line that intersects the
origin, and the z dimension coincides with vertical only directly above the
origin. The constant z grid planes follow the curvature of the earth.
- Radar structure
The radar structure is simply the navigation information within the
GV Level-1B and Level-1C product formats. The information to geolocate
(radar latitude and longitude and the range, elevation, and azimuth of
each bin) are contained in the formats.
For detailed information, please see
PPS (formerly TSDIS) file specifications
(http://pps.gsfc.nasa.gov/tsdis_redesign/SelectedDocs.html).
A general description of data granularity as it applies to the IMS can be found in the
EOSDIS Glossary.
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TRMM standard products can be ordered from the Goddard DAAC. Data currently
available can be accessed from the
TRMM Data Search and Order
Web Interface.
In addition to the standard products, the Goddard DAAC also will provide,
as part of its value-added TRMM support to facilitate analysis and processing
by users, certain special products, including:
- Orbital gridded products, e.g., for the TMI Hydrometeor Profile standard
product, a 0.5 degree by 0.5 degree resolution special product
- Geographical subsets of the orbital gridded products
- Parameter subsets of selected standard products
- Satellite and ground radar coincident subsetted products for the Ground
Validation sites
Data sets will be distributed via FTP. Potential TRMM data users,
especially those with specific needs, are urged to contact the
Hydrology Data Support Team:
hydrology@daac.gsfc.nasa.gov
.
Help Desk
Goddard DAAC, Code 610.2
NASA Goddard Space Flight Center
Greenbelt, MD 20771
daacuso@daac.gsfc.nasa.gov
Quick Looks - OnLine TMI Quick Look images
TMI quick-looks available online. Each quick-look is generated at a resolution
of 1/4 degree, thus generating an image of 1440x720 pixels, or a file size of about 500k.
TSDIS - TRMM Science Data and Information System
The real-time processing and post-processing of the TRMM science data is performed by the TRMM
Science Data and Information System (TSDIS). Working with the TRMM principal investigators and
science algorithm developers, TSDIS maintains the operational science data processing system and
ensures the timely processing of all TRMM science instrument data. During routine operations, raw
instrument data is received in near real-time by TSDIS and then processed by the first tier of science
algorithms to produce calibrated, swath-level instrument data. Using this calibrated, swath-level
instrument data, the second tier of algorithms are used to compute geophysical parameters, such as
precipitation rate, also at the swath-level resolution. At the final stage of TSDIS processings, the third
tier algorithms produce gridded geophysical parameters from the first- and second-tier instrument data.
All TRMM products are archived and distributed by the Goddard Distributed Active Archive Center
(DAAC). For further information concerning TSDIS operations go to ths TSDIS homepage.
DAAC - Distributed Active Archive System
The operational archiving and distribution to the public of all TRMM science data products is provided
by the Goddard Distributed Active Archive Center (DAAC). In addition to archiving and distributing
the TRMM science data, the DAAC also provides necessary information and support for manipulating
these data files, which are provided in NCSA's Hierarchical Data Format (HDF). These files are
generally distributed online. FInally, the DAAC provides front-line support for any questions
concerning the TRMM science data. TO obtain TRMM science data, go to the Goddard DAAC
homepage.
Tropical Rainfall Measuring Mission (TRMM)
trmm_dataset.gd.html
...
Map of TRMM Satellite Coverage showing permanent ground validation stations
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The mission had a designed life of three years from launch on November 28, 1997. An orbit boost in August, 2001 has added a projected three additional years to the mission.
The satellite acquires approximately 16 orbits of data per day for mapping tropical rainfall between latitudes
of 38 degrees north and south of the equator.
| Satellite
Products
|
|---|
| TSDIS ID | Description | Data Product | Product Type |
1A-01
1B-01 | Raw/Calibrated VIRS(0.63, 1.6, 3.75,10.8, and 12 um)radiances at 2.2 km resolution, over a 720 km swath | Visible and Infrared Radiance | Raw/Calibrated sensor data |
1A-11
1B-11 | Calibrated TMI (10.65, 19.35, 21,37, and 85.5 GHz) brightness temperatures at 5-45 km resolution, over a 760 km swath
| Microwave Brightness Temperature | Calibrated sensor data |
| 1B-21 | Calibrated PR (13.8 Radar Power GHz) power at 4 km horizontal and 250 m vertical resolutions, over a 220 km swath
| Radar Power | Calibrated sensor data |
| 1B-51 | GV Radar | Radar Power | GV Reflectivity GV Differential Reflectivity ZDR |
| 1C-21 | PR (13.8 GHz) reflectivity at 4 km horizontal and 250 m vertical resolutions, over a 220 km swath
| Radar Reflectivity | Calibrated sensor data |
| 2A-12 | Hydrometeor (cloud liquid water,precipitation water,
cloud ice,
precipitation ice)
profiles in 14
layers at 21 km
horizontal
resolution along
with latent heat and
surface rain, over a
760 km swath
| Hydrometeor Vertical Profile | Vertical structure of rainfall |
| 2A-21 | PR (13.8 GHz) normalized surface cross section at 4
km horizontal
resolution, and path
attenuation in case
of rain, over a 220
km swath
| Radar Surface Cross-Section | Surface reflectivity [?] |
| 2A-23 | Rain type; freezing and bright band
heights from PR
(13.8 GHz) at 4 km
resolution, over a
220 km swath
| Radar Qualitative | Qualitative data |
| 2A-25 | PR (13.8 GHz) rain rate, reflectivity, attenuation,
profiles at 250 m
vertical and 4 km
horizontal
resolutions, over a
220 km swath
| Radar Rainfall Vertical Profile | Vertical structure of rainfall |
| 2B-31 | Combined PR/TMI rain rate and path integrated
attenuation at 250 m
vertical and 4 km
horizontal
resolutions, over a
220 km swath
| Combined Rainfall Vertical Profile | Vertical structure of rainfall |
| 3A-11 | Rain rate,conditional rain rate, rain frequency
and freezing height
over latitude band
from 38 degree N
to 38 degree S
from TMI
| Monthly 5 x 5 Degree Oceanic Rainfall | Surface rainfall |
| 3A-25 | Total and conditional rain rate, radar reflectivity, path integrated
attenuation at 2, 4,
6, 10, 15 km for
convective and
stratiform rain;
storm, freezing and
bright band heights
and snow-ice layer
depth over latitude
band from 38 degree
N to 38 degree S
from PR
| Monthly 5 x 5 Degree and 0.5 x 0.5 Degree Spaceborne Radar Rainfall | Vertical structure of rainfall |
| 3A-26 | Rain rate
probability
distribution at
surface, 2 and 4 km
over latitude band
from 38 degree N
to 38 degree S
from PR
| Monthly 5 x 5 Degree Surface Rain Accumulation | Surface rainfall |
| 3B-31 | Rain rate, cloud
liquid water, rain
water, cloud ice,
grauples at 14
levels over latitude
band from 38 degree
N to 38 degree S
from PR and TMI
| Monthly 5 x 5 Degree Combined Rainfall | Vertical structure of rainfall |
| 3B-42 | Calibrated
geosynchronous IR
rain rate using TRMM
estimates
| 5 day 1 x 1 Degree TRMM and Other-GPI Calibration Rainfall | TRMM and other sources rainfall |
| 3B-43 | Merged rain rate from TRMM, geosynchronous SSM/I, rain gauges IR, | 5 day 1 x 1 Degree TRMM and Other Sources Rainfall | TRMM and other sources rainfall |
| Ground Validation
Products
|
|---|
| TSDIS ID | Description | Data Product | Product Type |
|---|
| 1B-51 | Volume scan of radar
reflectivity,
differential
reflectivity and
mean velocity (if
available) truncated
at 230 km range
| Radar Reflectivity atOriginal Radar Resolution, Coordinate, and Sampling | Calibrated sensor data |
| 1C-51 | Volume scan of
calibrated radar
reflectivity and
differential
reflectivity (if
available) and
corresponding QC
masks, truncated at
200 km range
[* Volume scans at
radar sampling
within half hour of
TRMM satellite
coincidence]
| Half-Hourly(*)Calibrated Radar Reflectivity at Original Radar Resolution and Coordinate | Calibrated sensor data |
| 2A-52 | Percent of rain in
radar volume scan
[* Volume scans
at radar sampling
within half hour of
TRMM satellite
coincidence] | Half-Hourly(*) Rain Existence | Qualitative data |
| 2A-53 | Instantaneous rain rate over an area of 300 km x 300 km for single radar
sites, and 724 km x
658 km for Texas and
512 km x 704 km for
Florida multiple
radar sites
[* Volume scans at
radar sampling
within half hour
of TRMM satellite
coincidence]
| Half-Hourly(*) 2 km Radar Site Rain Map | Rain map |
| 2A-54 | Instantaneous rain type classification over an area of 300 km x 300 km for single radar sites,
and 724 km x 658 km
for Texas and 512km
x 704 km for Florida
multiple radar sites
[* Volume scans
at radar sampling
within half hour of
TRMM satellite
coincidence]
| Half-Hourly(*) 2 km Radar Site Convective/Stratiform Rain Map | Convective/stratiform map |
| 2A-55 | Instantaneous radar reflectivity and vertical profile statistics over an area of 300 km x 300
km for single radar
sites, and 724 km x
658 km for Texas and
512 km x 704 km for
Florida multiple
radar sites
[* Volume scans at
radar sampling
within half hour
of TRMM satellite
coincidence]
| Half-Hourly(*) 2 km Horizontal and 1.5 km Vertical Radar Site 3-D Reflectivity | Vertical structure of radar echo |
| 2A-56 | Time series of rain
gauge rain rates
over the radar site
rain gauge network
| One Minute Average and Peak Rain Gauge Rain Rate | In situ data |
| 3A-53 | Surface rain total from ground radar | 5-Day 2 km Ground Radar Site Rain Map | Rain map |
| 3A-54 | Surface rain total from ground radar | Monthly 2 km Ground Radar Site Rain Map | Rain map |
| 3A-55 | Vertical profile of
reflectivity and
contoured frequency
by altitude diagrams
for stratiform,
convective, and
anvil rain over land
and water
| Monthly 2 km Radar Site 3-D Rain Map | Vertical structure of radar echo |
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A broad and integrated observational program of precipitation and related
climate research designed to meet the specific science validation objectives
established by the TRMM science team and consistent with
program requirements established by NASA Headquarters was designed and implemented by the TRMM Office and specifically includes these objectives:
- organize a Global Validation Program (GVP) consisting of 10 or more
ground validation sites throughout the tropics (see map below);
- improve measurement techniques (e.g., rain gauges, disdrometers, acoustics);
- improve radar rain estimation techniques (e.g., radar/reflectivity
algorithms, dual polarization and dual frequency applications);
- investigate microwave attenuation techniques (e.g., from satellite
transponders and surface links);
- precipitation research (e.g., characterization of precipitating systems,
precipitation physics, etc);
- develop representative rainfall climatologies from existing sources
of data;
- development of quality control, processing and analysis software for
radar, rain gauge and disdrometer data;
- support the ground validation science team, the global validation sites,
and the TRMM science team;
- quality control, catalog, and archive all acquired radar, rain gauge,
and related data;
- participate in the planning and execution of all TRMM sponsored field
experiments related to the validation of TRMM observations.
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In order to satisfy opposing requirements for early data
distribution and the highest possible data quality, TRMM has reprocessed all
products with improved algorithms approximately once per year. This section,
aside from presenting general product information, updates the performance of each
algorithm as information becomes available to the science team. Data users
should check this site before working with any TRMM data, and occasionally
thereafter as more informaton becomes available. All information is tied to the
data version number as distributed by the DAAC.
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Designed for TRMM Validation, this series of experiments
provides ground truth for use in algorithm development for the
Tropical Rainfall Measuring Mission (TRMM), a NASA and
National Space Development Agency of Japan (NASDA) coordinated
mission that launched the TRMM satellite on 28 November 1997
with a unique complement of sensors to remotely observe
rainfall throughout the global tropics.
The TRMM global validation effort consisted of five field campaigns, TEFLUNA, SCSMEX, TEFLUNB,
TRMM-LBA, and KWAJEX that were designed and implemented by the TRMM Office.
Or
- Initial Orbit parameters for the TRMM satellite:
- Orbit Injection 380 km, +/- 10 km
- Nominal Mission Altitude 350 km, +/- 1.25 km
- Inclination 35 deg, +/- 0.1 deg
- Orbital Period 91.538 +/- 0.026 min
- Eccentricity .00054, +/- 2.0 x 10^-6 nominal
- Argument of Perigee 90 deg, +/- 2.0 deg
- Post-boost Orbit parameters for the TRMM satellite:
- Orbit Injection 380 km, +/- 10 km
- Nominal Mission Altitude 403 km, +/- 1.25 km
- Inclination 35 deg, +/- 0.1 deg
- Orbital Period 91.538 +/- 0.026 min
- Eccentricity .00054, +/- 2.0 x 10^-6 nominal
- Argument of Perigee 90 deg, +/- 2.0 deg
The Tropical Rainfall Measuring Mission (TRMM) is a joint space project with Japan. TRMM is designed to measure tropical precipitation
and its variation from a low-inclination orbit combining a suite of sensors to overcome many of the limitations of remote sensors previously
used for such measurements from space. The TRMM Science Team, under the leadership of a Goddard Project Scientist, determined that a
fundamental objective of TRMM was to understand the role of latent heat in driving the circulation of the global atmosphere. With the
inclusion of a rain radar, TRMM will provide the first opportunity to estimate the vertical profile of the latent heat that is released through
condensation. The tropical precipitation and consequent heating are concentrated in the Equatorial Intertropical Convergence Zone (ITCZ),
(Figure 1). The TRMM rainfall data is particularly important for studies of the global hydrological cycle and for testing the realism of
climate models, and their ability to simulate and predict climate accurately on the seasonal time scale. Other scientific issues such as the
effects of El Nio on climate could be addressed with a reliable, extended time series of tropical rainfall observations as well.
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The TRMM orbit is circular and is at an altitude of 218 nautical miles (350 km) and an inclination of
35 degrees to the Equator
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Precipitation Radar (PR)
TRMM Microwave Imager (TMI)
Visible Infrared Scanner (VIRS)
Clouds and Earths Radiant Energy System (CERES)
Lightning Imaging Sensor (LIS)
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The TRMM satellite carries five sensors:
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The Precipitation Radar (PR) determines the vertical
distribution of precipitation by measuring the "radar
reflectivity" of the cloud system and the weakening of a signal as it
passes through the precipitation. A unique feature of the PR is the
measurement of rain over land, where passive microwave channels are less
effective.
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The TRMM Microwave Imager (TMI) is a multichannel radiometer, whose
signals in combination can measure rainfall quite accurately over oceans and
somewhat less accurately over the land. The TMI and PR data yields
the primary precipitation data sets.
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The Visible Infrared Scanner (VIRS) measures radiance in
five bandwidths from the visible through the infrared spectral regions.
Scientists use Infrared (IR) data to make rough estimates of tropical
precipitation. The VIRS, PR and TMI data improve the techniques by which
scientists use IR data from other satellites to calculate rainfall. This is
the third component of TRMM's rain package.
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The Lightning Imaging Sensor (LIS) is an optical telescope and
filter imaging system that investigates the distribution and variability of
both atmospheric and cloud-to-ground lightning over the Earth. These
instruments contribute to our understanding of storm dynamics and correlate
to levels of precipitation and the release of latent heat.
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The Clouds and the Earth's Radiant Energy System (CERES) is a
visible/infrared sensor designed especially to measure energy rising from the
surface of the Earth and the atmosphere including its constituents (e.g., clouds
and aerosols). This energy, when balanced with the energy received by the Earth
from the Sun, constitutes the Earth's radiation budget. Understanding the radiation
budget from the top of the atmosphere to the Earth's surface, is important to
understanding climate and its variability.
Figure 2. The TRMM satellite and scanning geometries of the precipitation radar (PR), the visible and infrared radiometer (VIRS)
and the TRMM microwave imager (TMI) are illustrated along with an outline of the mission profile. The three sensors comprise the
"rain package." The Earth radiation and lightning sensors (CERES and LIS, respectively) are located behind the two-meter-square
PR antenna. (Illustration courtesy of Japan's National Space Development Agency - NASDA).
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| | Visible Infrared Scanner | TRMM
Microwave Imager | Precipitation Radar |
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| Frequency/Wavelength | 0.63,
1.6, 3.75, 10.8, 12 um | 10.65, 19.35, 37.0, 85.5
GHz dual polarization, 22.235 GHz vertical polarization |
13.8 GHz horizontal polarization |
| Scanning Mode | Cross
track | Conical | Cross track
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| Ground Resolution | 2.1
km | Ranges from 5 km at 85.5 GHz to 45 km at 10.65
GHz | 4.3 km at nadir |
| Swath Width | 720 km |
760 km | 220 km |
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Greenstone, R., 1992: Bibliography of TRMM-related publication through 1991.
On file at TRMM office. Mail code 910.1, Goddard Space Flight Center, NASA,
Greenbelt, MD. 20771.
Simpson, J. (Ed.), 1988: TRMM: A Satellite Mission to Measure Tropical
Rainfall, Report of the Science Steering Group. National Aeronautics and
Space Administration, Goddard Space Flight Center, Greenbelt, MD.
20771, 94 pp.
Simpson, J.S., C. Kummerow, W.-K. Tao, and R.F. Adler, 1996: On the Tropical
Rainfall Measuring Mission (TRMM). Meteorol. Atmo. Phys., 60, 19-36.
TRMM Satellite Products-Related:
Adler, R.F., G.J. Huffman, and P.R. Keehn, 1994: Global rain estimates from
microwave-adjusted geosynchronous IR data. Remote Sens. Rev., 11, 125-152.
Arkin, P.A., and B.N. Meisner, 1987: The relationship between large-scale
convective rainfall and cold cloud over the Western Hemisphere during
1982-1984. Mon. Wea. Rev., 115, 51-74.
Bell, T., L. Abdullah, R. Martin, G. North, 1990: Sampling errors for
satellite derived tropical rainfall: Monte Carlo study using a space-time
stochastic model. J. Geophys. Res., 95D, 2195-2205.
Braun, S.A., and R.A. Houze, Jr., 1995: Diagnosis of hydrometeor profiles
from area-mean vertical-velocity data. Quart. J. Roy. Meteor. Soc., 121, 23-53.
GPCC, 1992: Monthly precipitation estimates based on gauge measurements on the
continents for the year 1987 (preliminary results) and future requirements.
WMO/WCRP and DWD, Rep. No. DWD/K7/WZN-1992/08-1, 20 pp.
Iguchi, T., and R. Meneghini, 1994: Intercomparison of single frequency
methods for retrieving a vertical rain profile from airborne or spaceborne
data. J. Atmos. Oceanic Technol., 11, 1507-1516.
Kummerow, C., and L. Giglio, 1994a: A passive microwave technique for
estimating rainfall and vertical structure information from space,
Part I: Algorithm description. J. Appl. Meteor., 33, 3-18.
Kummerow, C., and L. Giglio, 1994b: A passive microwave technique for
estimating rainfall and vertical structure information from space,
Part II: Application to SSM/I data. J. Appl. Meteor. 33, 19-34.
Raymond, D.J., 1994: Convective processes and tropical atmospheric
circulations. Quart. J. Roy. Meteor. Soc., 120, 1431-1455.
Rosenfeld, D., D.B. Wolff, and E. Amitai, 1994: The window probability
matching method for rainfall measurements with radar. J. Appl. Meteor., 33,
682-693.
Shin, K-S., and G. North, 1988: Sampling error study for rainfall estimate
by satellite using a stochastic model. J. Appl. Meteor. 28, 1218-1231.
Steiner, M., R.A. Houze, Jr., and S.E. Yuter, 1995: Climatological
characterization of three-dimensional storm structure from operational
radar and raingauge data. J. Appl. Meteor., 34, 1978-2007.
Takahashi N., H. Kumagai, H. Hanado, T. Kozu, and K. Okamoto, 1995: The
CRL airborne multiparameter precipitation radar (CAMPR) and the first
observation results, Preprints of the 27th Conference on Radar Meteorology,
pp. 83-85.
Tao, W.K., and J. Simpson, 1993: The Goddard Cumulus Ensemble Model.
Part I: Model description. Terrestrial, Atmospheric and Oceanic
Sciences, 4, 35-72.
Wilheit, T., R. Adler, A. Chang, C. Kummerow, S. Avery, W. Berg, J. Ferriday,
E. Barrett, C. Kidd, D. Kniveton, P. Bauer, N. Grody, S. Goodman, R. Spencer,
A. Mugnai, W. Olson, G. Petty, A. Shibata, and E. Smith, 1994: Algorithms for
the retrieval of rainfall from passive microwave measurements. Remote Sensing
Reviews, 11, 1-32.
Wilheit, T.T., A.T.C. Chang, and L.S. Chiu, 1991: Retrieval of monthly
rainfall indices from microwave radiometric measurements using probability
distribution functions. J. Atmo. Oceanic Tech., 8, 118-136.
TRMM GV Products-Related:
Atlas, D., D. Rosenfeld, and D. Short, 1990: The estimate of convective
rainfall by area integrals. Part I: The theoretical and empirical basis.
J. Geophys. Res., 95, 2153-2160.
Chiu, L.S., 1988: Rain estimation from satellites: Areal rainfall-rain area
relation. Proceedings, The 3rd Conference on Satellite Meteorology and
Oceanography. AMS, Anaheim, Calif., Feb. 1-5, 1988, 363-369.
Churchill, D.D., and R.A. Houze, 1984: Development and structure of winter
Monsoon cloud clusters on 10 December 1978. J. Atmos. Sci., 41, 933-960.
Doneaud, A.A., P.L. Smith, A.S. Dennis, and S. Sengupta, 1981: A simple
method for estimating convective rain volume over an area. Water Resour.
Res., 17, 1676-1682.
Kedem, B., L.S. Chiu, and Z. Karni, 1990: An analysis of the threshold method
for measuring area average rainfall. J. Appl. Meteor., 29, 3-20.
Kedem, B., H. Paxiopoulos, X. Guan, and D.A. Short, 1994: A probability
distribution model for rain rate. J. Appl. Meteor., 33, 1486-1493.
Krajewski, W.F., and J.A. Smith, 1991: On the estimation of climatological
Z-R relationships. J. Appl. Met., 30, 1436-1445.
Morrissey, M.L., and J.S. Greene, 1991: The Pacific atoll raingauge data set.
Planetary Geosci. Div. Contrib. 648, Univ. of Hawaii, Honolulu, HI, USA, 45 pp.
Rogers, R.R., 1971: The effect of variable target reflectivity on weather radar
measurements. Quart. J. Roy. Met. Soc., 97, 154-167.
Rosenfeld, D., E. Amitai, and D.B. Wolff, 1995: Improved accuracy of radar
WPMM estimated rainfall upon application of objective classification criteria
with radar. J. Appl. Meteor., 34, 212-223.
Rosenfeld, D., D. Atlas, and D.A. Short, 1990: The estimation of convective
rainfall by area integrals. Part II: The height-area threshold (HART) method.
J. Geophys. Res. Atmos., 95, 2161-2176.
Short, D.A., K. Shimizu, and B. Kedem, 1993: Optimal thresholds for the
estimation of area rain rate moments by the threshold method. J. Appl. Meteor.,
32, 182-192.
Steiner, M., R.A. Houze, Jr., 1993: Three-dimensional validation at TRMM
ground truth sites: Some early results from Darwin, Australia. Preprints, 26th
Int. Conf. on Radar Meteorology, Norman, OK, Amer. Meteor. Soc., 417-420.
Thiele, O.W. (Ed.), 1987: On requirements for a satellite mission to measure
tropical rainfall. National Aeronautics and Space Administration, Research
Publication, NASA RP-1183, Washington, DC, 49 pp.
Tokay, A., and D.A. Short, 1996: Evidence from tropical raindrop spectra of
the origin rain from stratiform versus convective clouds. J. Appl. Meteor., 35,
355-371.
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Atmos Composition
