JEDI Applications Jedi Academy IV, Monterey CA 26 th February 2020
JEDI Applications • Numerical weather prediction (global and regional) • Marine data assimilation (ocean and sea-ice) * • Constituent data assimilation * • Land and snow data assimilation * * JCSDA project directives
NWP Projects • FV3 (GEOS, GFS, FV3SAR) – cubed sphere • MPAS – icosahedral • UM – lat/lon • LFRic – cubed sphere • Neptune – cubed sphere • WRF – regional Future • FV3SAR • Hurricane
FV3-JEDI CRTM Core repositories BUMP OOPS SABER RTTOV FV3-JEDI overlaps the generic interfaces, methods, IODA applications and configuration of the JEDI system with models UFO … that use the FV3 dynamical core. It aims to implement various NCDIAG JEDI data assimilation applications directly on the cubed sphere grid. FV3- repositories JEDI-LM FV3-JEDI FV3- FV3-JEDI- TOOLS Specifically it implements geometry, states and increments, JEDI parallel IO, variable changes, interpolation to observation FEMPS locations, the forecast model tangent linear and adjoint and the ability to advance the nonlinear model. It also provides specific unit testing, example configuration scripts for running GFS applications and infrastructure for building JEDI with the Models GEOS forecast models. GEOS GFS GSD Aero/Chem Chem
FV3-JEDI Interfaces OOPS abstract applications and interfaces Application Forecast EnDA 4DEnVar EnKF … 4DVar H(x) layer Linear Observation Observation Background State Increment … Model Operator Space Error MAGIC UFO IODA SABER FV3-JEDI SOCA QG Model Specific implementations FV3 Generic Generic implementations GEOS, GFS, FV3SAR, GEOS-CHEM, GFS GSDChem, GFDL
FV3 Model interfacing status Milestone GFS GEOS FV3 Solo ✓ 3DEnVar ✓ ✓ 4DEnsVar NA ✓ ✓ ✓ 4DVar ✘ ✓ 4DVar with linear physics NA ✓ Ensemble H(X) ✓ ✓ ✓ 4D H(x) in-core ✓ Multiple outer loops (IO) ✓ ✘ ✓ Multiple outer loops in-core ✓ Multiple resolutions ✓ EDA ✘ ✘ ✓ (simple B) Multiple resolution outer loops
In core data assimilation – H(x) GFS C768 (~12km) forecast model called from FV3- • JEDI for 6 hour window beginning 2019-11-18 18Z. GFS v16 model. • GEOS-R ABI Background from operations. Channel 9 • H(x) calculated in core as a post processor of the • model step, no storing of 4D State anywhere. Interpolation is from C768 cubed sphere grid to • observation locations. AMSU-A Satellite NOAA 19 winds Channel 9
In core data assimilation – 4DVar • C768 background (from ops) and forecast. Native grid and resolution observer. • Pure ensemble B matrix from C384 (25km) 40 • member ensemble (from ops). C192 (50km) increment. • • All AMSU-A NOAA 19 (~20,000 obs). 3 hour window • 2 outer loops in-core . • • BUMP for localization, interpolation etc.
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MPAS-JEDI For MPAS the focus is on Cloud Analysis and Forecasting (CAF) • Important, unsolved problem for data assimilation § Multivariate: Can’t analyze cloud in isolation from other fields § Multiscale: Fast/small scales with sensitive dependence on slower, larger scales § Reliance on remotely sensed observations with strongly nonlinear forward operators § Substantial errors in both forecast models and observation operators • Not a priority application for existing operational global DA systems • CAF is a top priority for the USAF.
MPAS-JEDI PANDA-C PANDA-C = Prediction and Data Assimilation for Cloud USAF funded • Joint NCAR-JCSDA project • Coordination with Met Office • MPAS-JEDI: extended cycling higher res, many PEs MPAS-JEDI, prototype II Aug 1 Feb 15 Nov 1 JEDI automated testing static B MPAS-JEDI, prototype I Oct 1 Feb 15 Aug 1 cycling w/ AMSU-A PANDA-C demo EnVar cycling demo all-sky MW, IR Dec 1 May 1 Jan 15 May 1 Today 2018 2020 May Aug Nov Feb May Aug Nov Feb May Dec 17 Mar 1 NGMS: JEDI for DA, OPS LFRic-JEDI, prototype I Jul 1 ExaDA for JEDI Apr 1 NGMS: continue w/ JEDI
MPAS Cycling Experiments • 6-hourly cycling for 15 April-15 May 2018, 120-km MPAS mesh • Observations from NCEP/EMC • Processing, “pre-QC,” and bias correction of radiances from GSI • EnVar (pure ensemble) • First background is 6-h forecast from GFS analysis (18Z 14 April 2018) • 20 ensemble members, 6-h forecasts from GEFS ICs • Localization: 2000 km, 5 vertical levels • Running on 36 processors (NCAR cheyenne)
Effects of AMSU-A Assimilation • Forecast fit (m/s) to GFS analysis, 300-hPa meridional wind, NH extratropics NH extratropics SH extratropics
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