Reanalyses – WDAC5

Overview Atmospheric Reanalyses MERRA-2 JRA ERA5 NCEP Task Team for Intercomparison of Reanalyses (TIRA)

MERRA-2 Motivation and Objectives Produce an ongoing, intermediate reanalysis for the satellite era using a recent version of GEOS-5 to (1) address known limitations of MERRA (c. 2008), and (2) provide a stepping stone to a future coupled Earth system reanalysis. Specifics: Incorporate modern satellite observation types not available to MERRA Reduce spurious trends and jumps related to changes in the observing system Reduce biases and imbalances in the water and energy cycles Test coupling GOES-5 meteorology with other Earth system components

The MERRA-2 data assimilation system GEOS-5.12.4 AGCM/GSI 3D-Var 0.5° x 0.625° x 72 hybrid-eta levels to 0.01 hPa MERRA MERRA-2 Evolution Updates to the AGCM and GSI AGCM Cubed-sphere dynamics Updated physics: limited deep convection, re-evap of rain, snow sublimation Improved glacier model and cryosphere albedos GSI Modern observations: GPSRO, NOAA-19, MetOp-A/B, S-NPP, SEVIRI, Aura OMI and MLS, capable for JPSS, MetOp-C Updated moisture control variable and background errors Bias correction for aircraft temperature observations TC Relocation Aerosol assimilation with radiative coupling to AGCM (direct effects) Constraints on dry mass and globally integrated water Corrected precipitation for land surface forcing and aerosol deposition Climate validation and other docs at: http://gmao.gsfc.nasa.gov/reanalysis/MERRA-2/docs/

GMAO Reanalysis Plans Future directions are consistent with the Integrated Earth System Analysis framework (IESA), which calls for coupled reanalyses including atmosphere, aerosols, land, ocean, and trace gas constituents. A prospective target is for a quarter-degree coupled reanalysis using 4D EnsVar atmospheric data assimilation. Ongoing development would include the following: Investigation of assimilating observed ice thickness (e.g., freeboard observed from CryoSat 2). Two-moment cloud physics for improved representation of mixed phase clouds GRACE land moisture assimilation Aerosol-on-snow deposition (impact on surface albedo). Improvement of snow hydrology over ice sheets

JRA-55 family To aid further study of the representation of low-frequency variability and trends in JRA-55, different types of product have been produced with the common base NWP system. JRA-55 (JMA) Full observing system reanalysis Available from JMA (http://jra.kishou.go.jp), DIAS, NCAR, NASA/ESGF S. Kobayashi et al. (2015), Harada et al. (2016) JRA-55C (MRI/JMA) Using conventional observations only Available from DIAS, NCAR C. Kobayashi et al. (2014) JRA-55AMIP (MRI/JMA) AMIP type run RMS errors of 2-day forecasts of geopotential height (gpm) at 500hPa averaged over the northern hemisphere Adapted and updated from C. Kobayashi (2014)

The next Japanese reanalysis JRA-3Q (pronounced as “Thank you!” in Japanese) Japanese Reanalysis for Three Quarters of a Century Provisional specifications Higher resolution: TL319L60 -> TL479L100 40 km in horizontal, 100 layers up to 0.01 hPa in vertical Extending the reanalysis period back in time Atmospheric reanalysis from 1948 (planned) to present New boundary conditions and forcing fields COBE-SST2 (from the beginning to 1981) MGDSST (satellite-based SST from 1982 onward) New observations Observations newly rescued and digitised by ERA-CLIM et al. Improved satellite observations through reprocessing JMA’s own tropical cyclone bogus

Data assimilation system JRA-55 JRA-3Q Base system JMA’s operational system as of December 2009 JMA’s operational system as of 2018 (planned) Horizontal resolution TL319 (~55 km) TL479 (~40 km) Vertical levels 60 levels up to 0.1 hPa 100 levels up to 0.01 hPa Analysis scheme 4D-Var (with the T106 inner resolution) (with the TL319 inner resolution) Radiative transfer model for satellite radiances RTTOV-9.3 RTTOV-10.2 (used in the current system) Improved accuracy Inclusion of the Zeeman effect Inclusion of GHGs variations GNSS-RO Refractivity (up to 30 km) Bending angle (up to 60 km)

Production schedule (as of January 2016) FY2015 FY2016 FY2017 FY2018 FY2019 FY2020 FY2021 FY2022 FY2023 Acquisition of observational data Preparation for JRA-3Q production AMIP ~10-year period AMIP JRA-3Q production Production of TC bogus (1948-1959) Development of TL479 system JRA-3Q production (1958-1990) Preliminary experiments Construction of exp system JRA-3Q production (1989-2020) Preparation for connection JRA-3Q near-real-time production Product release Prerelease Full release JRA-55 near-real-time production Parallel production

ERA5: the ERA-Interim replacement What is new in ERA5? ERA-Interim ERA5 Period 1979 - present Start of production August 2006 Jan 2016, complete record end 2017 Assimilation system 2006 technology Current state of the art Model input (radiation and surface) As in operations, (inconsistent sea surface temperature) Appropriate for climate, e.g., evolution greenhouse gases, volcanic eruptions, sea surface temperature and sea ice Spatial resolution 79 km globally 60 levels to 10 Pa 32 km globally 137 levels to 1 Pa Uncertainty estimate Based on a 10-member ensemble at 64 km Output frequency 6-hourly Analysis fields Hourly (three-hourly for the ensemble), Extended list of parameters ~ 5,000 Tera Byte Extra Observations Mostly ERA-40, GTS Various reprocessed CDRs, latest instruments Variational Bias corrections Satellite radiances Also ozone, aircraft, surface pressure ERA5: the ERA-Interim replacement

Hourly reanalysis fields Copernicus Climate Change Service The ERA5 archive in the make Hourly reanalysis fields ERA5 2-metre temperature compared to independent data Observation feedback archive

ESRL Single-Resolution EnKF Only System Conventional obs only in this system Possible R1 replacement Used for forecast IC for next cycle Generating new ensemble perturbations given the latest set of observations and a first-guess ensemble member 1 forecast Uses background error covariances computed from the ensemble member 1 analysis EnKF ensemble perturbations are "re-centered" around the high-res analysis EnKF member update T254L64 member 2 forecast member 2 analysis member 3 analysis member 3 forecast 1) Can you describe what happens in the box entitled "EnKF member update?" The EnKF is run at the late (GDAS) data cutoff, and updates every ensemble member using the EnKF algorithm, using background error covariances computed from the ensemble (no static component).   The GSI cannot be used to update the ensemble, since it only provides a single deterministic analysis (analagous to the mean of the EnKF ensemble). However, since the high-res hybrid analysis then replaces the EnKF ensemble mean analysis, effectively only the ensemble perturbations are cycled using the EnKF update.  You can think of the this update as doing the same thing as the current operational ETR scheme - it's generating new ensemble perturbations given the latest set of observations and a first-guess ensemble.  The ETR does this without using any observational information, just be rescaling and rotating the first-guess perturbations. 2) Exactly what is meant by "re-centering the ensemble around the analysis?" The high-resolution analysis computed by the GSI, using the first-guess ensemble to estimate background error covariances, replaces the ensemble EnKF analysis computed by the EnKF update step.  In other words, the EnKF ensemble perturbations are "re-centered" around the high-res analysis. 3) How are members 1-n of the analysis used (arrows going off page)? They are run forward by the GFS to form the first-guess ensemble for the next analysis time. 4) is it correct that the deterministic forecast is run off the analysis (bottom row)? Yes. Previous Cycle Current Update Cycle Faster than a similar hybrid since no waiting on one branch or the other Thanks to Jeff Whitaker

Global mean temperature diff CFSR-ERAI CFSR sat bias correction problems EnKF-ERAI Warm bias in low model top EnKF-CFSR

Task Team for Intercomparison of ReAnalysis White Paper developed with input from Michael Bosilovich, NASA GSFC GMAO Jean-Noël Thépaut, ECMWF Kazutoshi Onogi, JMA Arun Kumar, NOAA NCEP Dick Dee, ECMWF Otis Brown, NCSU and NOAA

TIRA Objectives Charged to develop an intercomparison Project To foster understanding and estimation of uncertainties in reanalysis data by intercomparison and other means To communicate new developments and best practices among the reanalyses producing centers To enhance the understanding of data and assimilation issues and their impact on uncertainties, leading to improved reanalyses for climate assessment To communicate the strengths and weaknesses of reanalyses, their fitness for purpose, and best practices in the use of reanalysis datasets by the scientific community

Tangible Activities Communication (support and continuation of reanalysis.org) Reanalysis Intercomparison Project Start with a template based on IPCC CREATE-IP provides technical support, CORE-CLIMAX provides methods Other WCRP projects coud provide support TIRA guides and provides structure Joint experimentation/work Consensus inventory of input observations, updated as new versions become available (incl SSTs, and other disciplinary data for eventual integration) Add standard output (facilitate inclusion in CREATE-IP) Contribute to deep understanding with center support

Potential Standing Members Atmospheric Reanalysis Developing Centers ECMWF, JMA, CMA, NCEP and GMAO WCRP Panels GEWEX, CLIVAR (likely GSOP), CLiC and SPARC (SRIP) Disciplinary – Land/Ocean/Cryo reanalyses Others? Regional reanalysis projects Reanalysis user communities? Wind Power

End of MERRA Surprise MERRA last data day 29 FEB 2016 Older CRTM not capable of using latest satellite observations, down to one polar orbiter in each of AM/PM. Updating would have caused discontinuity, and cost significant manpower Supercomputer was retired, would need manpower to port to new system Posted on MERRA WWW, announced at meetings and users mailing list, still, some users just finding out when no new data is showing up at the data center Renewable energy operational assessment of potential wind turbine locations