Superobbing and Thinning Scales for All-sky Humidity Sounder Assimilation

David I. Duncan aEuropean Centre for Medium-Range Weather Forecasts, Reading, United Kingdom

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Niels Bormann aEuropean Centre for Medium-Range Weather Forecasts, Reading, United Kingdom

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Alan J. Geer aEuropean Centre for Medium-Range Weather Forecasts, Reading, United Kingdom

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Peter Weston aEuropean Centre for Medium-Range Weather Forecasts, Reading, United Kingdom

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Abstract

Humidity sounder radiances are currently thinned to 110 km spacing prior to assimilation at ECMWF and used with no averaging applied. In this paper, the thinning scale and possible averaging of all-sky humidity sounder observations into “superobs” are considered. The short- and medium-range forecast impacts of changing the thinning and averaging scales of humidity sounder radiances prior to the data assimilation are investigated separately and then together. Superobbing acts as a low-pass filter and provides smoother images of departures, decreasing the effective sensor noise and thus the standard deviation of background departures, marginally for 183GHz channels (5-15%) and significantly for 118GHz channels (5-55%). Observations are thus more representative of the model effective resolution, with a better utilisation of total information content than thinning native-resolution radiances, as less information is discarded. Whether changed in isolation or combination, the additions of data via superobbing and finer thinning are both shown to markedly improve background fits to independent observations, indicative of better short-range forecasts of humidity and improved winds via the 4D-Var tracer effect. Wind forecasts in the Southern Hemisphere are slightly improved in the medium-range. A final configuration is tested at the resolution of the current operational model, with humidity sounder radiances averaged into 50 km superobs with 70 km spacing. This provides about 140% more radiances for assimilation and more finely detailed maps to analyse mesoscale features. The forecast impact of this change is larger in testing with higher model and data assimilation resolutions, showing the scale-dependence of such decisions and the expected performance in an operational configuration.

© 2024 American Meteorological Society. This is an Author Accepted Manuscript distributed under the terms of the default AMS reuse license. For information regarding reuse and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: David I. Duncan, david.duncan@ecmwf.int

Abstract

Humidity sounder radiances are currently thinned to 110 km spacing prior to assimilation at ECMWF and used with no averaging applied. In this paper, the thinning scale and possible averaging of all-sky humidity sounder observations into “superobs” are considered. The short- and medium-range forecast impacts of changing the thinning and averaging scales of humidity sounder radiances prior to the data assimilation are investigated separately and then together. Superobbing acts as a low-pass filter and provides smoother images of departures, decreasing the effective sensor noise and thus the standard deviation of background departures, marginally for 183GHz channels (5-15%) and significantly for 118GHz channels (5-55%). Observations are thus more representative of the model effective resolution, with a better utilisation of total information content than thinning native-resolution radiances, as less information is discarded. Whether changed in isolation or combination, the additions of data via superobbing and finer thinning are both shown to markedly improve background fits to independent observations, indicative of better short-range forecasts of humidity and improved winds via the 4D-Var tracer effect. Wind forecasts in the Southern Hemisphere are slightly improved in the medium-range. A final configuration is tested at the resolution of the current operational model, with humidity sounder radiances averaged into 50 km superobs with 70 km spacing. This provides about 140% more radiances for assimilation and more finely detailed maps to analyse mesoscale features. The forecast impact of this change is larger in testing with higher model and data assimilation resolutions, showing the scale-dependence of such decisions and the expected performance in an operational configuration.

© 2024 American Meteorological Society. This is an Author Accepted Manuscript distributed under the terms of the default AMS reuse license. For information regarding reuse and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: David I. Duncan, david.duncan@ecmwf.int
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