A54C-04:
Global Tpw and Uth Trends Inferred from 10 Years of Hiirs and MODIS Data

Friday, 19 December 2014: 5:00 PM
Eva Erzsebet Borbas1, Paul Menzel1, Richard Frey2, Andrew K Heidinger3 and Nicholas Bearson1, (1)University of Wisconsin Madison, Madison, WI, United States, (2)CIMSS/UW-Madison, Evansville, WI, United States, (3)NOAA/NESDIS, Madison, WI, United States
Abstract:
The HIRS and MODIS (MOD07) TPW and UTH algorithm retrieves total column precipitable water vapor and integrated high (UTH), mid, and low layer tropospheric humidity. It is a statistical regression (Seemann et al 2003 and 2008) developed from an atmospheric profile data base (SeeBor, Borbas et al, 2005) that consists of geographically and seasonally distributed radiosonde, ozonesonde, and ECMWF ReAnalysis data. TPW and UTH are determined for clear sky radiances measured by HIRS (at 20km and later 10km resolution) and MODIS (5km resolution) over land and ocean both day and night.

The Space Time Gridding (STG) framework is used to calculate daily and monthly composites of the moisture properties. It has two components. (1) Space gridding where geophysical properties are first filtered based on a set of criteria (e.g. time of day, etc.) and then aggregated into equal-angle grid cells. (2) Time gridding where daily statistics are computed from the aggregate of pixels in each grid cell. Longer–term, such as monthly, statistics are derived from the daily gridded statistics.

The HIRS and MODIS TPW and UTH products are binned into a global map of 0.5 degree lat-lon boxes daily, compiled into monthly amounts, and inspected for trends over a 10-year time period (2000-2009). The HIRS and MODIS TPW data is also compared to the NASA NVAP dataset.