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All-sky assimilation of microwave sounder radiances

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Presentation on theme: "All-sky assimilation of microwave sounder radiances"— Presentation transcript:

1 All-sky assimilation of microwave sounder radiances
Alan Geer, Niels Bormann, Fabrizio Baordo, Heather Lawrence, Cristina Lupu, Stephen English 6th WMO Workshop on the Impact of Various Observing Systems

2 FSOI ECMWF OPS: 1 November 2015 to 7 March 2016
Total FSOI [%] by type of observation Total FSOI [%] by instrument November 2015 to March 2016 (cy41r1) IR 2 x IASI, AIRS, CrIS, 1 x HIRS, MTSAT-2/Himawari-8, GOES-13/15, MET-7/10 MW WV All-sky: SSMIS, AMSR-2, GMI, 4 x MHS Clear-sky: ATMS, MWHS-FY3B MW T 6 x AMSU-A, ATMS AMVs 5 x Geos (MTSAT-2/Himawari-8, GOES-13/15, MET-7/10) MODIS, NOAA-AVHRR, MetOp-A/B, Dual MetOp GPS-RO MetOp-A/B, GRACE A, COSMIC-1/2/5, TerraSAR-X, TanDEM-X SCAT MetOp-A/B Ozone AURA OMI, NOAA-18 SBUV-2, MetOp-A/B GOME-2 MHS assimilated in all-sky since 12 May 2015

3 Outline All-sky approach Challenges and ingredients
Forecast impact of MW humidity sounders: clear-sky vs all-sky Mechanisms Conclusions 6th WMO Workshop on the Impact of Various Observing Systems

4 Outline All-sky approach Challenges and ingredients
Forecast impact of MW humidity sounders: clear-sky vs all-sky Mechanisms Conclusions 6th WMO Workshop on the Impact of Various Observing Systems

5 All-sky assimilation components in 4D-Var
*FG, T+12, background… Observation minus first-guess* departures in clear, cloudy and precipitating conditions Observation operator including cloud and precipitation (RTTOV) - TL/Adjoint Moist physics - TL/Adjoint Forecast model - TL/Adjoint Control variables (winds and mass at start of assimilation window) optimised by 4D-Var Rest of the global observing system Background constraint 6th WMO Workshop on the Impact of Various Observing Systems

6 Operational all-sky assimilation at ECMWF: developments
2005 2010 2015 1D+4D-Var cloudy SSMI All-sky radiances from imaging channels on SSMI, and later SSMIS, TMI, AMSR-E, GMI, AMSR-2 All-sky radiances from q-sounding channels on SSMI/S and later MHS All-sky radiances from FY-3C MWHS-2 4D-Var assimilation system Increasingly high-quality first guess RTTOV-SCATT TL and adjoint moist physics New effective cloud fraction DDA scattering for snow Better consistency with nonlinear model 6th WMO Workshop on the Impact of Various Observing Systems

7 183 GHz clear-sky weighting functions (e.g., MHS)
183±1 183±3 183±7 or 190 Tom Greenwald 6th WMO Workshop on the Impact of Various Observing Systems

8 Outline All-sky approach Challenges and ingredients
Forecast impact of MW humidity sounders: clear-sky vs all-sky Mechanisms Conclusions 6th WMO Workshop on the Impact of Various Observing Systems

9 Better radiative transfer
Key ingredient 1: Better radiative transfer Observations Mie simulations DDA simulations Until recently, RTTOV-SCATT used Mie theory to determine bulk optical properties of frozen hydrometeors. Liu (2008, BAMS): Discrete Dipole Approximation (DDA) scattering database Implementation in RTTOV-SCATT: Geer and Baordo (2014, AMT) Result: We can consider all-sky assimilation in convective areas at frequencies above 30 GHz for the first time 6th WMO Workshop on the Impact of Various Observing Systems Slide 9

10 The biggest issue: representing cloud and precipitation in models
Observations TB [K] MHS 183±3 GHz June 12th 2013 ECMWF FG TB [K] 6th WMO Workshop on the Impact of Various Observing Systems

11 The biggest issue: representing cloud and precipitation in models
Why such large errors? Poor predictability and/or representivity of cloud and precipitation, particularly in convective situations Accuracy of forecast model’s cloud and precipitation parametrization Accuracy of the observation operator (scattering radiative transfer simulations) Observations ECMWF FG 6th WMO Workshop on the Impact of Various Observing Systems

12 Key ingredient 2: Treating the uncertainty in model representation of clouds
Observations ECMWF FG MHS 183±3 GHz adaptive observation error from a “symmetric error model” [K] →Assign higher observation error where observations or FG indicate clouds..

13 Outline All-sky approach Challenges and ingredients
Forecast impact of MW humidity sounders: clear-sky vs all-sky Mechanisms Conclusions 6th WMO Workshop on the Impact of Various Observing Systems

14 Impact of microwave humidity sounders at day 4 – on top of the otherwise full observing system
Clear-sky Change in RMS error of vector wind Verified against own analysis Blue = error reduction (good) Based on 346 forecasts Cross hatching indicates 95% confidence All-sky 6th WMO Workshop on the Impact of Various Observing Systems

15 Observation fits – global Normalised change in std. dev. of FG dep.
All-sky microwave WV Clear-sky microwave WV 100% = control (no microwave WV) AMSU-A GPSRO SATOB (AMVs) Radiosonde q Conventional wind Radiosonde T Improvement Improvement Improvement 6th WMO Workshop on the Impact of Various Observing Systems

16 Outline All-sky approach Challenges and ingredients
Forecast impact of MW humidity sounders: clear-sky vs all-sky Mechanisms Conclusions 6th WMO Workshop on the Impact of Various Observing Systems

17 Single observation experiment: Water vapour in the presence of cloud, 183±1 GHz
GOES 10μm Dundee receiving station Metop-B MHS 183±1 GHz 06Z, 15 Aug 2013 37°S 113°W Observation rejected in old `clear-sky’ approach 6th WMO Workshop on the Impact of Various Observing Systems

18 Single observation experiment
TB [K] FG depar [K] 6th WMO Workshop on the Impact of Various Observing Systems

19 Single observation experiment
TB [K] UTH signal ~20K Cloud signal ~1K FG allsky – FG clear [K] 6th WMO Workshop on the Impact of Various Observing Systems

20 Single observation experiment
Assimilate only the single 183 ±1 GHz observation marked in preceding slides. Start Time of observation Assimilation window UTH increment ( hPa mean RH) 6th WMO Workshop on the Impact of Various Observing Systems

21 →Adjustment of the dynamics in 4DVAR
Single observation experiment Assimilate only the single 183 ±1 GHz observation marked in preceding slides. →Adjustment of the dynamics in 4DVAR Start Time of observation Assimilation window UTH increment ( hPa mean RH) Humidity reduction at observation time generated by changes in wind (and other dynamical variables) 1000km away, 9h earlier! Zonal wind increment at 400 hPa 6th WMO Workshop on the Impact of Various Observing Systems

22 Microwave humidity observations on their own
6th WMO Workshop on the Impact of Various Observing Systems

23 Assimilate only all-sky WV sounding observations (4 MHS, 1 SSMIS) 66 different analyses and forecasts, always from a full-observing system FG T+12 RMS forecast error reduction 100% = full observing system 0% = no observations -100% = worse than that! Storm track winds: to 50% Tropical winds: to 30%

24 Assimilate only microwave T-sounding obs (6 AMSU-A, ATMS) 66 different analyses and forecasts, always from a full-observing system FG T+12 RMS forecast error reduction 100% = full observing system 0% = no observations -100% = worse than that! Storm track winds: to 60% Tropical winds: to 10%

25 Outline All-sky approach Challenges and ingredients
Forecast impact of MW humidity sounders: clear-sky vs all-sky Mechanisms Conclusions 6th WMO Workshop on the Impact of Various Observing Systems

26 Conclusions The extension of the use of MW humidity-sounding radiances to all-sky leads to a significant improvement of the forecast impact in the ECMWF system. The main mechanism is improved dynamical adjustments to fit cloud/humidity features. New microwave humidity sounders (MWHS-2, SAPHIR) are now being included in the all-sky framework. 6th WMO Workshop on the Impact of Various Observing Systems

27 Latest addition to all-sky assimilation: MWHS-2 on FY-3C
Sounding capabilities at 183 GHz and – for the first time – 118 GHz Assimilated operationally at ECMWF since 4 April 2016 Impact on forecast error of 500 hPa geopotential: Southern Hemisphere Northern Hemisphere Improvement in forecast accuracy Forecast day Forecast day 6th WMO Workshop on the Impact of Various Observing Systems Slide 27

28 Conclusions The extension of the use of MW humidity-sounding radiances to all-sky leads to a significant improvement of the forecast impact in the ECMWF system. The main mechanism is improved dynamical adjustments to fit cloud/humidity features. New microwave humidity sounders (MWHS-2, SAPHIR) are now being included in the all-sky framework. Over the years, there have been significant benefits from the all- sky approach for model physics developments (not covered here). 6th WMO Workshop on the Impact of Various Observing Systems

29 Future directions for all-sky assimilation
Further incremental improvements: More instruments converted to all-sky Observation error modelling refinements to observation error model, scale-representativeness correlations Further developments of observation operator Deal with the asymmetry in moistening and drying increments Data assimilation developments, such as renewed focus on humidity control variable, as well as a possible cloud control variable Challenges: cloud-affected temperature channels (e.g., AMSU-A), visible wavelengths, ensembles…? 6th WMO Workshop on the Impact of Various Observing Systems

30 Backup 6th WMO Workshop on the Impact of Various Observing Systems

31 Key ingredient 2: Symmetric error models
FG departure standard deviation is a function of the “symmetric cloud amount” – the average of observed and simulated cloud An error model is fitted to (or binned from) the FG departures Cloud predictors: 37 GHz polarisation difference (imagers) Scattering index (land, MHS) [K] Mean of observed and FG cloud Normalised FG departure Constant error is non-Gaussian Adaptive error is more Gaussian 6th WMO Workshop on the Impact of Various Observing Systems

32 FSO for MHS as a function of cloudiness
Mean FSO per observation by channel (sea only, as percentage of the total FSO for MHS), Dec 2015 – Feb 2016 183 ± 1 GHz → Good contributions from clear and cloud-affected data 183 ± 3 GHz 183 ± 7 GHz Increase in cloud contribution Increase in cloud contribution 6th WMO Workshop on the Impact of Various Observing Systems

33 Forecast impact of all-sky assimilation of microwave WV Compared to clear-sky assimilation; 4 MHS & 1 SSMI/S; 2 x 3 months Change in vector wind RMS error SH Tropics NH All-sky MW WV – No MW WV Clear-sky MW WV – No MW WV 6th WMO Workshop on the Impact of Various Observing Systems

34 Bad Impact of all-sky microwave humidity sounders and imagers - on top of the otherwise full observing system 2-3% impact on day 3 and 5 dynamical forecasts Change in RMS error of vector wind Verified against own analysis Blue = error reduction (good) Based on 342 to 350 forecasts Cross hatching indicates 95% confidence Good 6th WMO Workshop on the Impact of Various Observing Systems

35 Monthly mean biases at 37 GHz (sensitive to cloud, water vapour and rain) SSMIS channel 37v, December 2014 – all data over ocean, including observations usually removed by QC Bias [K] Lack of supercooled liquid water in cold air outbreaks Diurnal cycle and water content of marine stratocumulus (Kazumori et al., 2015) 6th WMO Workshop on the Impact of Various Observing Systems

36 FSOI ECMWF OPS: 1 November 2015 to 7 March 2016

37 FSOI per obs ECMWF OPS: 1 November 2015 to 7 March 2016

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