Quantification of Uncertainty in Water Vapor Atmospheric Motion Vectors, and the Effect on Data Assimilation and OSSEs

Measurements of the three-dimensional distribution of horizontal winds have been identified as a priority for future space-based observing systems. While space-borne Doppler wind lidar (DWL) is commonly viewed as the gold standard for clear-air measurements of winds, there are inherent limitations on DWL spatial and temporal sampling. Atmospheric motion vectors (AMVs) derived from sequences of images (e.g., of clouds, water vapor, and/or other trace gases) constitute a complementary source of wind information that can be obtained over larger areas and with potentially higher frequency in time. In this presentation we focus on AMVs derived by tracking gradients in satellite-retrieved water vapor fields.

Observing system simulation experiments (OSSEs) have been used to quantify the anticipated impact of a new set of measurements on weather prediction. Forecast OSSEs are useful, in that they measure the effectiveness of a set of measurements in the context of the current global observing system. However, if the results of a forecast OSSE are to be credible, measurement uncertainty must be assessed and quantified. In the case of AMVs derived from water vapor retrievals, sources of uncertainty include: noise in the observed radiances, errors in the methodology used to estimate (retrieve) water vapor from space, and errors in the feature tracking algorithm.

We have conducted a set of experiments designed to produce a robust characterization of the uncertainty in water vapor AMVs. We find that AMV uncertainties are state-dependent, and are a strong function of the underlying water vapor and wind fields. We conduct a number of forecast OSSEs using various assumptions on AMV uncertainty, and assess the degree to which state-dependent uncertainties affect the interpretation of the results. While the results are specific to assimilation of water vapor AMVs, they have implications for the assimilation of AMVs derived from clouds and other trace gases.