Hans Huang: WRFDA 2013 overview 1 DA WRFDA 2013 Overview Hans Huang NCAR Acknowledgements: WRFDA team and many visitors, NCAR, CWB, AirDat, NRL, BMB, NSF-OPP, AFWA, NSF-AGS, USWRP, NASA, PSU, CAA, KMA, EUMETSAT

Hans Huang: WRFDA 2013 overview 2 DA WRFDA Goal: Community WRF DA system for regional/global research/operations deterministic/probabilistic applications Techniques: 3D-Var 4D-Var (regional) Ensemble DA Hybrid Variational/Ensemble DA Model: WRF (ARW, NMM, Global) Observations: Conv.+Sat.+Radar (+Bogus) Supported by NCAR/ESSL/MMM/DAS

Hans Huang: WRFDA 2013 overview 3 DA

Hans Huang: WRFDA 2013 overview 4 DA WRFDA tutorials WRFDA online tutorial and user guide July NCAR Feb NCAR July NCAR Aug NCAR July NCAR July NCAR. 18 April South Korea Oct Nanjing, China. 10 April Seoul, South Korea. 16 April Busan, South Korea Oct Bangkok, Thailand. 21 April Seoul, South Korea. The next: July 2013

Hans Huang: WRFDA 2013 overview 5 DA WRFDA v3.5 Release date: April 2013 New features: – Support for data from additional satellite instruments: METOP: Infrared Atmospheric Sounding Interferometer (IASI) Suomi NPP: Advanced Technology Microwave Sounder (ATMS) FY3: Microwave Temperature Sounder (MWTS) and Microwave Humidity Sounder (MWHS) – Direct wind speed/direction assimilation – ETKF code updated and documentation added – Support for new ECMWF cloud detection scheme – Allowing variable number of inner-loop cost function minimizations for each outer-loop

Hans Huang: WRFDA 2013 overview 6 DA  In-Situ: -Surface (SYNOP, METAR, SHIP, BUOY) -Upper air (TEMP, PIBAL, AIREP, ACARS, TAMDAR) Remotely sensed retrievals: -Atmospheric Motion Vectors (geo/polar) -GPS refractivity (e.g. COSMIC) -Ground-based GPS Total Precipitable Water (PW)/Zenith Total Delay (ZTD) -SATEM thickness -Scatterometer oceanic surface winds -SSM/I oceanic surface wind speed and TPW -Radar radial velocities and reflectivities -Satellite temperature/humidity/thickness profiles -Stage IV precipitation/rain rate data (4D-Var) -Wind profiler wind profiles  Satellite radiances (using RTTOV or CRTM): – HIRS NOAA-16, NOAA-17, NOAA-18, NOAA-19, METOP-A – AMSU-A NOAA-15, NOAA-16, NOAA-18, NOAA-19, EOS-Aqua, METOP-A – AMSU-B NOAA-15, NOAA-16, NOAA-17 – MHS NOAA-18, NOAA-19, METOP-A – AIRS EOS-Aqua – SSMIS DMSP-16, DMSP-17, DMSP-18 – IASIMETOP-A – ATMSSuomi-NPP – MWTSFY-3 – MWHSFY-3 Bogus: – TC bogus – Global bogus WRFDA Observations New, v3.5

Hans Huang: WRFDA 2013 overview 7 DA Planned and ongoing work (I) (after WRFDA v3.5) WRFPLUS and 4DVAR optimization Revision of the energy norm used by FSO Background error covariance improvements – Smoothing options at various stages of GEN_BE – Use of u, v, T, ps and RH as control variables for convective scale DA – GEN_BE 2.0 development and documumentation More satellite platform/instruments – CrIS – GOES sounder and GOES imager – MSG SEVIRI – GCOM-W1 AMSR2 – Update RTTOV and CRTM interfaces for their latest release versions – GPS RO DA More options for vertical data thinning Nonlocal GPS RO parallelization

Hans Huang: WRFDA 2013 overview 8 DA Planned and ongoing work (II) (after WRFDA v3.5) Radar data assimilation development – An indirect radar reflectivity DA scheme – Radar DA with WRFDA 4DVAR Dual-resolution hybrid DA WRFDA online thinning for conventional data Blending backgrounds or analyses using a spatial filter Displacement analysis Multivariate cloud analysis Ensemble Variational Integrated Lanczos (EVIL)

Hans Huang: WRFDA 2013 overview 9 DA Assimilation of Wind Speed and Direction Observations Xiang-Yu Huang 1, Feng Gao 1,2, Neil A. Jacobs 3, Hongli Wang 1 1 National Center for Atmospheric Research, Boulder, Colorado, USA 2 Nanjing University of Information Science & Technology, Nanjing, Jiangsu, China 3 AirDat LLC, Morrisville, North Carolina, USA

Hans Huang: WRFDA 2013 overview 10 DA All current DA systems turn sp and dir to u and v before assimilating them, assuming observation errors in u and v are known and not correlated. Many observing systems observe wind speed (sp) and direction (dir); should be more straightforward to derive obs sp and dir errors and assume them uncorrelated. Wind direction observation errors vary significantly in space and time (e.g. small at the jet level, large close to surface) and should influence the analysis results. WRFDA is the only DA system which has an option to assimilate wind sp and dir observations taking the sp and dir observation errors into account. Introduction

Hans Huang: WRFDA 2013 overview 11 DA A simple illustration (probably simplified too much) (Over Simplified) Assumptions: Wind component (sp,dir) or (u,v) can be analyzed univariately; The background error and observational error are the same. Assimilate u and v (asm_uv): Assimilate sp and dir (asm_sd):

Hans Huang: WRFDA 2013 overview 12 DA From the same background and observations, asm_uv and asm_sd produce very different analyses!

Hans Huang: WRFDA 2013 overview 13 DA From the same background and observations, asm_uv produces weaker winds than asm_sd does!

Hans Huang: WRFDA 2013 overview 14 DA Single observation experiments using WRFDA and observation errors estimated from a previous data study (without the over simplified assumptions)

Hans Huang: WRFDA 2013 overview 15 DA Again, now using WRFDA, asm_uv produces weaker winds than asm_sd does! From WRFDA single ob experiments From the highly simplified solutions

Hans Huang: WRFDA 2013 overview 16 DA WRFDA analysis increments asm_uv asm_sd U V U V Vector

Hans Huang: WRFDA 2013 overview 17 DA Observing system simulation experiments Nature run: 6 km grid space with 57 vertical levels Observations – simulated wind observations at every 30x30 th grid across 12 standard pressure levels 0000 UTC 15 Dec. – 0000 UTC 20 Dec Cycle run: 18 km grid space with 43 vertical levels 6 h full-cycle from 0000 UTC 16 Dec h forecasts are generated every 6 h Boundary condition: FNL for nature run GFS forecast for cycle experiments Background Errors – cv5 by NMC Verification: against nature run

Hans Huang: WRFDA 2013 overview 18 DA Verification scores sp v u dir

Hans Huang: WRFDA 2013 overview 19 DA Concluding remarks for the wind DA study A new formulation for assimilating wind speed and direction observations is presented and compared with the traditional formulation for assimilating u and v. Simple illustrations are used to show the differences and single pair observation experiments with WRFDA qualitatively confirm the differences. OSSEs show potential benefits of the new formulation. Real observation experiments are ongoing. Huang, X.-Y., Gao, F., Jacobs, N. and Wang, H Assimilation of wind speed and direction observations: a new formulation and results from idealized experiments. Tellus A, 65, 19936,