All-sky assimilation of microwave humidity sounders
Geer, Alan ; Baordo, Fabrizio ; Bormann, Niels ; English, Stephen
All-sky assimilation of microwave imager observations, sensitive mainly to the lower troposphere, has been operational since 2009 (Bauer et al., 2010). The new addition is the microwave humidity sounding channels at 183 GHz which are a core capability of the European and US polar-orbiting operational meteorological satellites. These channels were previously assimilated using the ‘clear-sky’ method: in other words, all cloud-affected observations had to be discarded. All-sky assimilation allows a more complete use of the data, particularly in the winter storm tracks. The direct information content of microwave humidity sounders is humidity, cloud and precipitation, but when they are used inside any four-dimensional variational data assimilation system (hereafter referred to as 4D-Var) they also provide information on wind and temperature. Particularly in the mid-latitude upper troposphere, strong humidity and cloud gradients offer a chance to infer wind and mass information from the moisture fields. Indeed, the latest upgrade has its main benefit in the wind and geopotential forecasts, which are significantly improved out to at least day 4. We can see the microwave humidity observations as an important part of the observing system, improving the large-scale analysis of wind and mass and benefitting forecast scores into the medium range. Though it is good that forecasts are being improved, it is important to know why it is happening. It could be that we now have better geographical coverage of uppertropospheric water vapour in dynamically interesting cloudy regions. The assimilation of cloud and precipitation could itself be benefitting the forecasts. More crucially, we need to know if we are directly inferring winds from the humidity, cloud and precipitation fields or whether the benefit comes through some more subtle aspect of the data assimilation system. All-sky assimilation may be beginning to derive information that has historically come from cloud motion vectors. The more we understand the all-sky assimilation, the more we will know how best to use satellite observations in the future – whether as atmospheric motion vectors, clearsky or all-sky radiances. In this article we make a start on investigating these questions.
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