11 th JCSDA Science Workshop on Satellite Data Assimilation Latest Developments on the Assimilation of Cloud-Affected Satellite Observations Tom Auligné.

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Presentation transcript:

11 th JCSDA Science Workshop on Satellite Data Assimilation Latest Developments on the Assimilation of Cloud-Affected Satellite Observations Tom Auligné National Center for Atmospheric Research Acknowledgments: Gael Descombes, Greg Thompson, Francois Vandenberghe, Dongmei Xu (NCAR) Thomas Nehrkorn, Brian Woods (AER) Funding provided by the Air Force Weather Agency 1

Introduction Approaches for the use of cloud-affected radiances Nowcasting COP + advection 3D cloud fraction + WRF dynamical transport Oklahoma U. / GSI-RR cloud analysis Expansion of analysis control variable Total water + linearized physics Microphysical variables 2

Introduction Approaches for the use of cloud-affected radiances in NWP Nowcasting COP + advection 3D cloud fraction + WRF dynamical transport Oklahoma U. / GSI-RR cloud analysis Expansion of analysis control variable Total water + linearized physics Microphysical variables (WRF Data Assimilation) 3

Outline Control Variable Transform Multivariate Background Error Covariances Hybrid Ensemble/Variational Displacement Analysis Processing of Cloudy Satellite Observations Experimental Demonstration 4

Outline Control Variable Transform Multivariate Background Error Covariances Hybrid Ensemble/Variational Displacement Analysis Processing of Cloudy Satellite Observations Experimental Demonstration 5

Pseudo Single Observation Test (PSOT) Multivariate covariances for qc, qr, qi, qsn Binning option: dynamical cloud mask Vertical and Horizontal autocorrelations via Recursive Filters 3D Variance 6

Outline Control Variable Transform Multivariate Background Error Covariances Hybrid Ensemble/Variational Displacement Analysis Processing of Cloudy Satellite Observations Experimental Demonstration 7

NEW ALGORITHM: update of the ensemble perturbations inside the Variational analysis through Lanczos minimization (without external EnKF) NEW ALGORITHM: update of the ensemble perturbations inside the Variational analysis through Lanczos minimization (without external EnKF) Ensemble covariance included in 3D/4DVar through state augmentation (Lorenc 2003, Wang et al. 2008, Fairbairn et al., 2012) Ensemble/Variational Integrated Localized (EVIL) with 8

Outline Control Variable Transform Multivariate Background Error Covariances Hybrid Ensemble/Variational Displacement Analysis Processing of Cloudy Satellite Observations Experimental Demonstration 9

Forecast Calibration & Alignment Hurricane Katrina OSSE Synthetic observations (TCPW) Balanced displacement Nehrkorn et al., MWR 2013 (submitted) 10

Outline Control Variable Transform Multivariate Background Error Covariances Hybrid Ensemble/Variational Displacement Analysis Processing of Cloudy Satellite Observations Experimental Demonstration 11

Unified processing for Radiances and COP Retrievals VarBC: Variational Bias Correction (unchanged predictors) Revisited QC: extended Gross and First-Guess check (to conserve cloudy data) Huber Norm: robust definition of observation error Land Surface: T skin introduced as a sink variable Field of View: advanced interpolation scheme CRTM Jacobians: rescaled base state (floor and ceiling values for cloud parameters) Middle Loop: Multiple re-linearizations of obs. operator Unified Processing of Cloud-affected Satellite data 12

Observation Background Radiance (GOES imgr channel 4) AIRS, IASI, AMSU-A, AMSU-B, MHS, HIRS, SSMI/S BUFR files from NCEP MODIS HDF files (Terra & Aqua) from NASA GOES Sndr ASCII files (E & W) from Uwisc. GOES Imgr NetCDF files from NCAR/RAL Cloud-Affected Radiances 13

Observation Background Log 10 (COD) (GOES imgr) Log 10 (COD) (GOES imgr) GOES Imgr NetCDF files from Uwisc. MODIS NetCDF files from AFWA with (Benedetti and Janiskova, MWR 2008) Cloud Optical Properties 14

Unified processing for Radiances and COP Retrievals VarBC: Variational Bias Correction (unchanged predictors) Revisited QC: extended Gross and First-Guess check (to conserve cloudy data) Huber Norm: robust definition of observation error Land Surface: T skin introduced as a sink variable Field of View: advanced interpolation scheme CRTM Jacobians: rescaled base state (floor and ceiling values for cloud parameters) Middle Loop: Multiple re-linearizations of obs. operator Unified Processing of Cloud-affected Satellite data 15

Unified processing for Radiances and COP Retrievals VarBC: Variational Bias Correction (unchanged predictors) Revisited QC: extended Gross and First-Guess check (to conserve cloudy data) Huber Norm: robust definition of observation error Land Surface: T skin introduced as a sink variable Field of View: advanced interpolation scheme CRTM Jacobians: rescaled base state (floor and ceiling values for cloud parameters) Middle Loop: Multiple re-linearizations of obs. operator Unified Processing of Cloud-affected Satellite data 16

Unified processing for Radiances and COP Retrievals VarBC: Variational Bias Correction (unchanged predictors) Revisited QC: extended Gross and First-Guess check (to conserve cloudy data) Huber Norm: robust definition of observation error Land Surface: T skin introduced as a sink variable Field of View: advanced interpolation scheme CRTM Jacobians: rescaled base state (floor and ceiling values for cloud parameters) Middle Loop: Multiple re-linearizations of obs. operator Unified Processing of Cloud-affected Satellite data 17

Huber Norm: robust observation errors Figure from Fisher (2008) Innovations Normalized Obs Weight Distribution of innovations 18

Unified processing for Radiances and COP Retrievals VarBC: Variational Bias Correction (unchanged predictors) Revisited QC: extended Gross and First-Guess check (to conserve cloudy data) Huber Norm: robust definition of observation error Land Surface: T skin introduced as a sink variable Field of View: advanced interpolation scheme CRTM Jacobians: rescaled base state (floor and ceiling values for cloud parameters) Middle Loop: Multiple re-linearizations of obs. operator Unified Processing of Cloud-affected Satellite data 19

Unified processing for Radiances and COP Retrievals VarBC: Variational Bias Correction (unchanged predictors) Revisited QC: extended Gross and First-Guess check (to conserve cloudy data) Huber Norm: robust definition of observation error Land Surface: T skin introduced as a sink variable Field of View: advanced interpolation scheme CRTM Jacobians: rescaled base state (floor and ceiling values for cloud parameters) Middle Loop: Multiple re-linearizations of obs. operator Unified Processing of Cloud-affected Satellite data 20

Satellite Field of View (FoV) interpolation Calculate polygons (ellipses) List model grid points inside ellipse Use average input for CRTM Currently testing for AIRS and IASI Calculate polygons (ellipses) List model grid points inside ellipse Use average input for CRTM Currently testing for AIRS and IASI 21

Unified processing for Radiances and COP Retrievals VarBC: Variational Bias Correction (unchanged predictors) Revisited QC: extended Gross and First-Guess check (to conserve cloudy data) Huber Norm: robust definition of observation error Land Surface: T skin introduced as a sink variable Field of View: advanced interpolation scheme CRTM Jacobians: rescaled base state (floor and ceiling values for cloud parameters) Middle Loop: Multiple re-linearizations of obs. operator Unified Processing of Cloud-affected Satellite data 22

Unified processing for Radiances and COP Retrievals VarBC: Variational Bias Correction (unchanged predictors) Revisited QC: extended Gross and First-Guess check (to conserve cloudy data) Huber Norm: robust definition of observation error Land Surface: T skin introduced as a sink variable Field of View: advanced interpolation scheme CRTM Jacobians: rescaled base state (floor and ceiling values for cloud parameters) Middle Loop: Multiple re-linearizations of obs. operator Unified Processing of Cloud-affected Satellite data 23

Cost Function First GuessSecond GuessThird Guess First Analysis Second Analysis AIRS Window Channel #787 3DVar Middle loop 24

First Guess Second Guess Third Guess Observation Update of q cloud, q ice in WRF Observations AIRS Window Channel #787 25

Outline Control Variable Transform Multivariate Background Error Covariances Hybrid Ensemble/Variational Displacement Analysis Processing of Cloudy Satellite Observations Experimental Demonstration 26

WRF-ARW model, CONUS 15km, Thompson microphysics First Guess = Mean of 50-memb ens. from EnKF expt (Romine) Single analysis at 20012/06/03 (12UTC), 5 middle-loops GOES-Imager: Radiances (Thompson) & COD (Uwisc.) CTRL no DA COD Cloud Optical Depth (3DVar) FCACloud Optical Depth (Displacement) 3DVARRadiances (3DVar) EVIL Radiances (Hybrid) Experimental Framework 27

Incremental fit to obs Cloud Optical Depth 3DVar EVIL Radiances Obs 28

q cloud Level 10 Analysis increments CODFCA 3DVAREVIL 29

q cloud Level 10 Analysis increments CODFCA 3DVAREVIL 30

0.12° 0.25° 0.5° 1°2°3° Multi-scale verification 31

Multi-scale verification AnalysisForecast EVIL 3DVAR CTRL Impact of all-sky radiances on forecast up to 3-4h Best forecast with EVIL system Impact of all-sky radiances on forecast up to 3-4h Best forecast with EVIL system EVIL 3DVAR CTRL 32

Conclusion Expansion of analysis vector to clouds Multivariate, flow-dependent background errors Displacement pre-processing Updated processing of cloud-affected satellite data (bias correction, QC, interpolation, RTM, middle-loop) Sustained impact in short-term forecast More work required… 33