GC33H-04
Sampling Impacts on the NVAP-M Global Water Vapor Climate Data Record

Wednesday, 16 December 2015: 14:25
3005 (Moscone West)
Thomas H Vonder Haar1, John Michael Forsythe2 and Heather Q Cronk2, (1)Colorado State University, Fort Collins, CO, United States, (2)Cooperative Institute for Research in the Atmosphere, Fort Collins, CO, United States
Abstract:
Atmospheric water vapor is a fundamental ingredient both for regulating climate as a greenhouse gas and as a necessary precursor for high impact weather events such as heavy precipitation. Water vapor concentration varies geographically because of its close linkage with surface temperature and as a component of synoptic and mesoscale weather systems. Satellite observations provide the only means to quantify the global occurrence and variability of water vapor. In common with other long-term climate data records such as clouds and precipitation, intercalibrating and blending diverse measurements of water vapor to create a consistent record through time is a challenge.

The NASA Making Earth Science Data Records for Research Environments (MEaSUREs) program supported the development of the NASA Water Vapor Project (NVAP-M) dataset. The dataset was released to the science community in 2013 via the NASA Langley Atmospheric Science Data Center. The dataset is a global (land and ocean) water vapor dataset created by merging multiple satellite infrared and microwave sources of atmospheric water vapor along with surface data to form global gridded fields of total and layered precipitable water vapor. NVAP-M spans 22 years (1988-2009) of data.

The challenges in creating this multisensor, multidecadal satellite-driven climate data record are illustrative of challenges for all satellite climate data records. While advances in sensor intercalibration and retrieval algorithms have improved the quality of the global water vapor climate data record, uncertainties arise due to sampling biases of the input sensors. These biases are particularly evident on a regional scale, in cloudy regions or over desert surfaces. The changing mixture of sensors with varying sensitivity to clear/cloudy, land/ocean and even day/night conditions can lead to different results on trends and variability of water vapor. We explore this variability via the NVAP-M data set. Connections and collaborations with the international Global Energy and Water Exchanges (GEWEX) Water Vapor Assessment (G-VAP) effort will be presented.