Atmospheric data assimilation is a process that incorporates observational data into numerical atmospheric models with consideration of both observation and model errors.Conventional global assimilated data sets currently contain significant errors in primary hydrological fields, such as precipitation and evaporation, especially in the tropics.Part of these errors is related to relatively coarse precipitation observations.The TRMM-derived rainfall and total precipitable water (TPW) estimates may be used to constrain these fields in assimilation systems, and make improvements on assimilated data sets.
Atmospheric scientists at Goddard Space Flight Center NASA have successfully developed analysis techniques to bring TRMM rainfall observations into their global numerical model, called the Terra Goddard Earth Observation System (GEOS) data assimilation system (DAS).By assimilating the 6-hour averaged TMI surface rain and other TPW data into the Terra GEOS-DAS, they found that not only the primary hydrological fields, but also key climate parameters, such as clouds and radiation, have been improved significantly.
The following figures illustrate the good job that Terra GEOS-DAS did for super-Typhoon Paka (December 10, 1997) assimilation.The top one is the observed Paka imagery, where red color denotes the thick clouds around the typhoon center. The bottom panel shows the assimilated surface wind and pressure field resulting from assimilating TMI and TPW into the GEOS-DAS system.Compared with the middle panel, which was produced by the same GEOS-DAS system but without using TMI and TPW data, the bottom one clearly indicates an intensive low surface pressure and strong wind convergence at Paka's position.
Courtesy TRMM Data Assimilation, NASA
TMI is a multi-channel dual polarized, conically scanning passive microwave radiometer. The frequencies for dual polarization are at 10.65, 19.35, 37, and 85.5 GHZ, and at 21 GHZ for the vertical polarization. TMI is designed to provide quantitative rainfall information over a wide swath.By carefullymeasuring the minute amounts of microwave energy emitted by the Earth and its atmosphere, TMI is able to quantify the water vapor, the cloud water, and the rainfall intensity in the atmosphere.
TMI measurements also have been used to derive sea surface temperature (SST).Scientists have emphasized the great role of TMI SST data in the monitoringand the forecast of tropical weather and climate, because the microwave radiation penetrates clouds with little loss of signal, and thereby provides an uninterrupted view of the ocean surface.Currently GDAAC does not archive the TMI sea surface temperature data, but users can find TMI SST data and information through the Remote Sensing System.
For the current released data there are five TRMM standard products derived from TMI, namely 1B-11, 2A12, 2B31, 3A11, and 3B31. The beginning number denotes the data processing level: level one data are radiances, level two is instantaneous geophysical parameters, and level three is integrated grid-averaged data.2A-12 data provides surface rain and hydrometeors profiles, and 2B31 combine TMI profiles with that of precipitation radar. There two data sets have been described in the "Cloud and Precipitation Formation" topic above. 3A-11 data are the TMI monthly mean product, consisting of surface rain rate, rain frequency, and freezing height.3B31 algorithm uses the combined rainfall structure (2B31) to calibrate TMI rainfall structure (2A12) on a monthly basis. The outputs consist of monthly mean surface rainfall and hydrometeors profiles at 14 layers, see "Cloud and Precipitation Formation" topic above.
Monthly mean surface rainfall for 1999 .Data: TRMM 3B31, TMI and PR combined. Data are at a 5o longitude x 5o latitude resolution.These figures are plotted by using GrADS, and the contour levels are the same as that in the figures of TRMM 3B43 for ENSO study topic above. The precipitation patterns are comparable, but the differences in the center values are perceptible. Note that TRMM 3B43 has a high 1o x 1o spatial resolution.