I am using the 3-hourly 3B42-V6 rainfall rates from TRMM. How can I convert these 3-hourly rainfall rate (mm/hour) to total daily rainfall (mm/day)?
The 3B42-V6 rain rate is a 3-hourly average centered at the middle of each 3-hour period (i.e., 0Z, 3Z, 6Z, 9Z, 12Z, 15Z, 18Z, and 21Z). To convert these rainfall rates to total daily rainfall, first multiply each 3-hourly rainfall rate by 3 hours, to get the total rainfall for each 3-hour period. Then, for your desired 24-hour-day begin and end times, sum all the 3-hourly total rainfalls in your defined 24-hour period, to get the total daily rainfall.
What are the values for latitude and longitude in TRMM 3B42 and 3B43 HDF data files?
The data in the HDF file are written in the following order, (-49.875, -179.875), (-49.625, -179.875), (-49.375, -179.875), (-49.125, -179.875)......(49.875, -179.875), (-49.875, -179.625), (-49.625, -179.625)...... The dimension for longitude is 1440 and the dimension for latitude is 400. The value used to indicate missing data is "-9999.9".
Where can I find more information on the TRMM Data Set?
More information on the TRMM instruments and science can be found at the GES DISC/DAAC TRMM Data Web site: http://disc.sci.gsfc.nasa.gov/precipitation/
How current are the TRMM data?
The GES DISC/DAAC receives, under normal circumstances, processed standard orbital/swath data products about 2-3 days after satellite data acquisition, depending on the level of processing required. In addition to this ongoing collection of data, archives of older data are maintained.
What is the GES DISC/DAAC Search and Order Web Interface?
As of August 31, 2009, the GES DISC/DAAC data search and order interface is Mirador. For an introduction to how Mirador works, the Mirador FAQ may be useful.
Where can I find some documentation describing TRMM and TRMM data?
Information about TRMM and TRMM data can be found in:
Where can I find some information describing the TRMM algorithms?
Information about algorithms used for the TRMM products can be found in the Algorithm Status Page, where the links to the products take you to brief descriptions of the status of the products and, for some products, key references.
I would like to receive all new files generated for a data product, over a given time period, at a specified time interval (e.g., weekly). Can I set up a procedure by which specified data will be sent to me automatically?
Yes, just contact help@disc.gsfc.nasa.gov (or 301-614-5224, voice; or 301-614-5268, fax) and request a "subscription." Information that would be needed from you are data product(s) desired, begin date, and end date. You will receive an email notification whenever data are ready for FTP pickup.
How are the daily products computed from 3B42RT and Version 6 3B42 in TOVAS?
These daily products are computed by averaging all the estimates available in the eight observation times of a given UTC day, namely 00, 03, ..., 21 UTC. Formally, this "day" covers the period from 2230 UTC of the previous day through 2230 UTC of the given day. Other "day" products can be computed interactively for 3B42RT and Version 6 3B42 by specifying similar 8-period runs of data. For example, a day that starts at 09 UTC can be approximated by taking data from 09 UTC of one day through 06 UTC of the next. At present, there is no capability in TOVAS for a more exact approximation of a "day" for these data sets.
What’s the key documentation describing the 3B42RT and Version 6 3B42 products?
The paper describing the 3B42RT (real-time) and Version 6 3B42 (research quality) of the TRMM Multi-satellite Precipitation Analysis (TMPA) products is accessible at Huffman, G.J., R.F. Adler, D.T. Bolvin, G. Gu, E.J. Nelkin, K.P. Bowman, Y. Hong, E.F. Stocker, and D.B. Wolff, 2007, The TRMM Multi-satellite Precipitation Analysis: Quasi-Global, Multi-Year, Combined-Sensor Precipitation Estimates at Fine Scale. J. Hydrometeor., 8(1), 38-55. Technical documentation is also available for the research product and real-time product, as is a WHATSNEW file, which contains recent notices about issues with the RT product.
What’s the difference between the real time and research products of the TRMM Multi-satellite Precipitation Analysis (TMPA)?
Version 6 research products are the "real" TRMM products. They are produced a month at a time, available about 2-3 weeks after the end of the month. The upgrade to Version 6 happened in Spring/Summer 2005. The next version (Version 7) is due out in late 2009, at which time the entire record will be reprocessed from January 1998 through the then-current time. Institutionally, TRMM has been joined by a successor project, Global Precipitation Measurement (GPM), which has a nominal launch date of 2013. In the GPM era, some combination-product successor to the TMPA is a high priority. So there is a strong likelihood for a long run of a consistent (via episodic reprocessing) product.
The real-time (RT) products, representing an experimental testbed, are posted for the public due to the high demand for such information. Except for processing failures, the RT products are not reprocessed. The last major upgrade occurred in February 2005, so the processing scheme since then has been relatively consistent. The next upgrade, scheduled for the end of this year (2008), will attempt to make the RT relatively consistent with Version 6 research products. For continuity, however, the data files will also include a precipitation field that is "more or less" the old RT result.
Whenever possible, users are urged to take advantage of the improved quality of the research products. Some operational applications, however, cannot wait for the research products, and the RT products are intended for those application users.
What are the caveats in using TRMM Multi-satellite Precipitation Analysis (TMPA) products?
The following are some caveats in using TMPA:
-
The key caveat is that all of the TMPA products are research products, not "operational" in the sense of hot spares, contingency plans, and backup machines waiting to take over in the event of a failure. Looking back through the RT news, the prospective user should get the sense that the system could run for months at a time, but if there's a network failure or a disk crash, it might take days to fix, particularly over weekends or holidays.
- The TMPA is a gridded product, which is different from the point rain gauge data more familiar to some users. On the other hand, grid values might be more appropriate for certain applications than are point values from rain gauges.
- Although the TMPA analysis scheme is consistent for the time period of a given version, the suite of input data varies. For example, there is less of the (higher-quality) microwave data before 2001 or so; the infrared data are on a coarser grid in 1998-1999; gauge sites report individually, and, therefore, are subject to availability issues, particularly in developing countries.
- Occurrence of precipitation over land tends to be underestimated, because satellite schemes tend to miss light precipitation and precipitation that is enhanced by flow lifting over mountains.
- Occurrence and amount of precipitation in some, but not all, coastal areas tend to be underestimated. Conversely, arid coastal areas (oceans and lakes) sometimes show persistent artifacts. Both effects are due to issues in the input microwave estimates.
- The RT amounts tend to be biased high in warm-season convective weather due to biases in the input microwave estimates.
- The Version 6 amounts tend to be biased low in regions of complex terrain due to gauge-location biases toward lower elevations.
Can I see an example of a GrADS ctl file for TRMM Level-3 HDF data?
The following example of a ctl file may be useful to TRMM data users familiar with GrADS.
DSET ^3A12.070101.6.HDF
DTYPE hdfsds
TITLE This is only a test UNDEF -9999.9
XDEF 720 LINEAR -179.7500000 0.5000000
YDEF 160 linear -39.7500000 0.5000000
ZDEF 14 LEVELS 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 5.0 6.0 8.0 10.0 14.0 18.0
TDEF 1 LINEAR jan2007 1mo
VARS 8
surfaceRain=>sfcr 1 z,x,y surface rain
convectRain=>convr 1 z,x,y convection rain
stratiformRain=>stratr 1 z,x,y stratiform rain
cldWater=>cldw 14 t,z,x,y cloud water
precipWater=>precipw 14 t,z,x,y precipitable water
cldIce=>cldi 14 t,z,x,y cloud ice
precipIce=>precipi 14 t,z,x,y precipitable ice
latentHeat=>heat 14 t,z,x,y latent heat
ENDVARS
How do I extract time information from the TRMM 3B42 file name?
In a TRMM 3B42 file name (e.g., 3B42.980115.0.6.HDF.Z) the "0" in the file name following the date (MMDD) indicates the midpoint of a 3-hour interval. In the example filename, the "0" indicates 00:00Z. So the data in this file were acquired commencing at 22:30Z (1/14/1998) and ending at 1:30Z (1/15/1998). The precipitation quantity is the average rain rate calculated over this 3-hour interval. Note that the "Z" in the filename indicates that the file is compressed with Unix compression and does not designate a time. Thus, the 3B42 filename template is 3B42.YYMMDD.<midpoint of a 3-hour interval>.<version #>.HDF.Z
How can I read the TRMM binary files in TOVAS?
The following read program in Fortran can be applied to all the TRMM TOVAS binary files. For some data products, an adjustment to the array size is needed.
* TOVAS binary read program
real data(1440,400) real lon(1440) real lat(400)
c
open(10,file='3B43.040101.6.precipitation.bin',
+ access='DIRECT',status='OLD',recl=1440*400)
c
read(10,rec=1)((data(ii,jj), ii=1, 1440), jj=1,400)
c
do 10 ii=1,1440
do 10 jj=1,400
lon(ii) = -179.875+0.25*(ii-1)
lat(jj) = 49.875-0.25*(jj-1) write(*,*)lon(ii),lat(jj),data(ii,jj)
10 continue c
close(10)
c
end
* end binary read program
How can I convert mm/hr in TRMM 3B43 to mm/month?
Because the total days in each month are different, mm/hr is used for easy comparison. Since the 3B43 product is a monthly average, you could simply do the conversion by multiplying the hourly rain rate with the total hours in that month.
Is there any software to convert radiance to brightness temperature?
VIRS L1B Radiance Converter
The 1B01 Calibration software creates an alternative VIRS L1B product. It converts the 1B01 radiances to percent albedo for visible channels and to brightness temperatures for thermal channels. The output has the same HDF format as the 1B01 product and all 1B01 parameters except radiances are carried over.
The software is written in c. The PPS/TSDIS toolkit and a few HDF routines are used and included in this software package.
The VIRS L1B converter can be obtained using the PPS/TSDIS anonymous FTP site:
UNIX> cd ~
UNIX> ftp ftp-tsdis.gsfc.nasa.gov
user: anonymous
password: enter your e-mail address
FTP> cd pub/convertvirs
FTP> mget 1B01CALTB.tar
FTP> quit
What are the values for the lats and lons in TRMM 3B42 and 3B43 HDF data files?
The data in the HDF file are written in the following order:
(-49.875, -179.875), (-49.625, -179.875), (-49.375, -179.875), (-49.125, -179.875)......(49.875, -179.875), (-49.875, -179.625), (-49.625, -179.625)......
The dimension for longitude is 1440 and latitude 400. The missing data value is, -9999.9
How come there are missing or empty orbital data files?
Please refer to our TRMM Satellite Data Outages Page.
For the TRMM 2A25 data product, Is the 80th level located at 250m height, 79th at 500m ...and so on ...?
The range bin numbers in the output of 2A25 are all relative to the Earth's ellipsoid with the ellipsoid range bin corresponding to 79. For example, if the range bin number is 75, its height from the ellipsoid is (79-75)*0.25 = 1.0 km. This number is NOT the height above the actual surface.
For other 2A25 related caveats, please read:
http://trmm.gsfc.nasa.gov/2a25.html
For TRMM 3B43, 3B42, it seems there are two datasets (HDF and binary) with different latitude, longitude arrangements. Is this true? Which one should I use?
Yes and both are arranged differently. The HDF is the standard TRMM archive format and data are written in the following order, (-49.875, -179.875), (-49.625, -179.875), (-49.375, -179.875)...... The binary are written for GrADS (a free popular software used in climate and weather communities) and in (-49.875,-179.875), (-49.875,-179.625), (-49.875,-179.375°W)...... Apparently if you are a GrADS user, you should use the binary. Otherwise, there is a list of software in http://disc.sci.gsfc.nasa.gov/precipitation/secondary/tools
What is "relative error" in the TRMM 3B42 and 3B43 data sets?
The "relative error" is the random error discussed below.
The accuracy of the precipitation products can be broken into systematic departures from the true answer (bias) and random fluctuations about the true answer (sampling), as discussed in Huffman (1997). The former are the biggest problem for climatological averages, since they will not average out. For short averaging periods, however, the low number of samples and/or algorithmic inaccuracies tend to present a more serious problem for individual microwave data sets. That is, the sampling is spotty enough that the collection of values over, say, one day may not be representative of the true distribution of precipitation over the day. For VAR, the sampling is good, but the algorithm likely has substantial RMS error due to the weak physical connection between IR Tb's and precipitation.
Accordingly, the "random error" is assumed to be dominant, and estimates could be computed as discussed in Huffman (1997). Random error cannot be corrected. The "bias error" is likely small, or at least contained. This is less true over land, where the lower-frequency microwave channels are not useful for precipitation estimation with our current state of knowledge. The state of the art at the monthly scale is reflected in the study by Smith et al. (2006). Studies of the sub-monthly bias have not yet been performed.
More details can be found in the references listed below. The first linked article is freely available online from the Journal of Applied Meteorology; the second linked article is to the paper abstract, as the full text article requires a journal subscription (Journal of Hydrometeorology) or single-use fee for access.
Huffman, G.J., 1997: Estimates of root-mean-square random error contained in finite sets of estimated precipitation (PDF). J. Appl. Meteor., 36, 1191-1201.
Smith, T.M., P.A. Arkin, J.J. Bates, G.J. Huffman, 2006: Estimating bias of satellite-based precipitation estimates. (Abstract - link to full text) J. Hydrometeor., 7(5), 841-856.
What is the geographic coordinate reference system in TRMM products?
TRMM data product pixels are geolocated according to the WGS-84 ellipsoid model.
Can you show me how to read TRMM 3B42 or 3B43 data in Matlab?
Here are codes to read TRMM 3B42 binary files and TRMM 3B42 or 3B43 HDF files.
---
% This program is to read a TRMM 3B42 daily binary file
fid = fopen('3B42_daily.2009.05.31.6.bin', 'r');
a = fread(fid, 'float','b');
fclose(fid)
data = a';
count = 1;
for i_lat = 1:400
for j_lon = 1:1440
lat = -49.875 + 0.25*(i_lat - 1)
lon = -179.875 + 0.25*(j_lon - 1)
daily_rain_total = data(count)
count = count + 1;
end
end
---
% This sample program is to read TRMM L3 HDF4 data
precipitation = hdfread('3B43.090101.6A.HDF', '/DATA_GRANULE/PlanetaryGrid/precipitation');
count = 1;
for i_lon = 1:1440
for j_lat = 1:400
lat = -49.875 + 0.25*(j_lat - 1)
lon = -179.875 + 0.25*(i_lon - 1)
rain = precipitation(count)
count = count + 1;
end
end
Return to FAQ Contents
|
Atmos Composition
