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Assimilation of rain and cloud-affected microwave radiances at ECMWF. Alan Geer, Peter Bauer, Philippe Lopez Thanks to: Deborah Salmond, Niels Bormann, Bill Bell, Chris O’Dell, Graeme Kelly. Rain and cloud in NWP. Improved initial conditions lead to improved forecasts
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Assimilation of rain and cloud-affected microwave radiances at ECMWF Alan Geer, Peter Bauer, Philippe Lopez Thanks to: Deborah Salmond, Niels Bormann, Bill Bell, Chris O’Dell, Graeme Kelly IPWG, Beijing, 13-17 October 2008
Rain and cloud in NWP • Improved initial conditions lead to improved forecasts • Variational assimilation (e.g. 4D-Var) is used to generate these initial conditions by combining a first guess forecast with observations: • Conventional: Weather stations, radiosondes, aircraft • Satellite: Infrared, microwave, scatterometer, atmospheric motion vectors • Need more information on temperature, pressure, winds and humidity everywhere, but particularly in cloudy and rainy regions • Need information on the cloud and rain themselves. But aren’t clouds and rain transient phenomenon? • Directly useful for short range forecasting • The presence or absence of cloud or rain can be used to help infer the temperature, pressure, wind and moisture structure of the atmosphere to benefit longer term forecasts • If comparison to the observations reveals shortcomings in the cloud and rain models, they will have to be improved IPWG, Beijing, 13-17 October 2008
Assimilation of microwave imagers at ECMWF • 1998 - SSM/I TCWV assimilation from 1D-Var in clear skies over oceans • 2003 - Direct 4D-Var of clear-sky SSM/I • 2005 - 1D+4D-Var of rainy SSM/I • Bauer et al. , QJRMetS, 2006a,b,c • 2007-8 - AMSR-E, TMI added in rainy and clear sky • 2009? - direct assimilation of all-sky radiances in 4D-Var IPWG, Beijing, 13-17 October 2008
ECMWF’s current rain and cloud assimilation approach: 1D+4D-Var • Clear sky SSM/I radiances are directly assimilated in 4D-Var • Cloudy and rainy SSM/I radiances have been assimilated operationally at ECMWF since 28th June 2005, over sea only, using a 1D+4D-Var method: • 1D-Var retrieves T and q profiles and surface windspeed • 1D-Var observation operator includes: • simplified large-scale and convective cloud schemes • Microwave radiative transfer • TCWV retrievals are assimilated in 4D-Var IPWG, Beijing, 13-17 October 2008
Tephigram – temperature and humidity Cloud ice / water Cloud fraction Rain/snow IPWG, Beijing, 13-17 October 2008
Quality of 1D+4D-Var rain retrievals: near-instantaneous colocations First guess Retrieval SSM/I retrieval compared to mean of PR footprints within ± 7.5 minutes and 25km Geer, Bauer, Lopez, QJRMetS, latest issue, 2008 IPWG, Beijing, 13-17 October 2008
Quality of 1D+4D-Var rain retrievals: correlation coefficients Geer, Bauer, Lopez, QJRMetS, latest issue, 2008 IPWG, Beijing, 13-17 October 2008
Forecast scores: 1D+4D-Var rainy assimilation RMSE against operational analyses Vector wind Relative humidity South Tropics North Limited observing system Limited observing system plus 1D+4D-Var Full observing system without 1D+4D-Var Full observing system Kelly et al., Mon. Weath. Rev., July, 2008 IPWG, Beijing, 13-17 October 2008
Emissive reflector biases • All conical-scanning microwave imagers (TMI, SSMI, SSMIS, AMSR-E … ) incorporate a spinning reflector • If the reflector is emissive: • Unfortunately a common situation: • SSMIS – Bill Bell, 2008, IEEE • TMI – Frank Wentz, 2001, IEEE Reflector emissivity IPWG, Beijing, 13-17 October 2008
SSM/I AMSR-E First guess departure [K] TMI IPWG, Beijing, 13-17 October 2008
TMI reflector temperature estimated from first guess departure biases Estimated reflector temperature [K] IPWG, Beijing, 13-17 October 2008
Radiative transfer biases in cloud and rain Modelled cloud liquid water (at SSM/I observation locations; 12hrs of data) 37v Obs – FG departure [K] (after moist physics improvements; CMAX cloud overlap) 37v Obs – FG departure [K] (after moist physics improvements; CMEAN cloud overlap) IPWG, Beijing, 13-17 October 2008
RTTOV-SCATT – Two independent column approximation:Tb = (1 - Cmax ) × Tb(clear) + Cmax× Tb(cloudy) RTTOV fast radiative transfer Forecast model – 1 grid point Cloudy column Clear column TOA Cmax Cloud Cmax Surface IPWG, Beijing, 13-17 October 2008
RTTOV-SCATT – revised version:Tb = (1 - Cmean ) × Tb(clear) + Cmean× Tb(cloudy) RTTOV fast radiative transfer Forecast model – 1 grid point Cloudy column Clear column TOA Cmean Cloud Cmax Surface IPWG, Beijing, 13-17 October 2008
Modelled cloud liquid water (at SSM/I observation locations; 12hrs of data) 37v Obs – FG departure [K] (after moist physics improvements; CMAX cloud overlap) 37v Obs – FG departure [K] (after moist physics improvements; CMEAN cloud overlap) IPWG, Beijing, 13-17 October 2008
All-sky, direct 4D-Var assimilation • In contrast to 1D+4D-Var, the full information content of the observations is assimilated: • Surface temperature and winds • Cloud and precipitation • Total column water vapour • A unified assimilation: • All sky conditions (rainy, cloudy, clear) are treated in the same assimilation stream IPWG, Beijing, 13-17 October 2008
RMS forecast errors: relative humiditynormalised difference (all-sky 4D-Var - 33r1 control) degradation 10th Aug to 4th Sept 2007: 18 to 26 samples verified against own analyses. improvement IPWG, Beijing, 13-17 October 2008
Departure statistics: SSM/I obs- FG mean IPWG, Beijing, 13-17 October 2008
Summary 1 - issues • Emissive reflectors • TMI suffers from emissive reflector bias • AMSR-E also? • Be careful when creating multi-instrument products • Recommendations for instrument builders: • Need to build non-emissive reflectors • Need for accurate measurements of reflector skin temperature • Radiative transfer in rain and cloud • Move from “maximum” to “weighted average” cloud fraction • Better agreement with 10 independent column approach and with observations IPWG, Beijing, 13-17 October 2008
Summary 2 - assimilation • 1D+4D-Var assimilation of rain- and cloud- affected SSM/I radiances • Operational since June 2005 but only the TCWV information content is currently used • Positive impact on forecast scores for tropical moisture and winds • Impact is comparable to clear sky microwave imager assimilation. • Good quality rain retrievals (compared to PR) • Direct 4D-Var assimilation of all-sky radiances (clear, cloudy, rainy) • Full information content of the observations is assimilated • Improved forecasts compared to previous system • To be made operational early 2009 IPWG, Beijing, 13-17 October 2008