What brings new MERRA2 Half-step forward towards new Reanalysis generation

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What brings new MERRA2 Half-step forward towards new Reanalysis generation Data and analysis: Pau Casso & Gil Lizcano Speaking: Pep Moreno Get in touch:gil.lizcano@vortex.es

Next 12 minutes AGENDA Reanalysis and Wind Industry (Users) VORTEX MERRA2 & Changes WInd Conditions times series modeling Quality Assessments MERRA2 & Quality Usage & Best Practice What s next Q&A Working with Model data

Background: Reanalysis viewed by the Wind Industry 1/ Driver for mesoscale modeling Virtual times series, greenfield, regional mapping, site-specific & micrositing 2/ Long-term reference Virtual time series Long-term average 80m Wind Speed at 100m resolution Source: WRF Downscaling driving by CFS/CFSR - VORTEX

Background: Reanalysis viewed by the Wind Industry MOTIVATION: Global Market Needs CREDENTIALS: High Correlation with Observations EXAMPLES: Downscaling Products Bank acceptance Tenders Publications Sessions on Specialized Fora Moments of panic when MERRA went offline Global Long-term average 80m Wind Speed Distribution at 9KM resolution Source: WRF Downscaling driving by CFS/CFSR - VORTEX

Background: Reanalysis viewed by the Wind Industry REANALYSIS MERRA ERA-Interim CFS-CFSR MERRA2 ERA5 Generation Third 3.5 * Fourth Long-term Reference Usage Mesoscale downscaling driver +++ ++ - +++ + ++ +++ + Popular for Easy access to data Better correlation Offshore (EU) Accurate downscaling results Resolution Hourly / 0.5 x 0.667 72 levels 4xday 0.75 x0.75 72 levels Hourly 0.5 x 0.5 64 level Hourly 0.5 x 0.667 72 levels Hourly 30Km (/2) 137 levels (X2) Latency (weeks) 4 12 1 2 User Notes Overall good correlation Arrived late * Inconsistent SFC but Consistent 3D fields Aerosol Assimilation Deterministic & Ensemble (10 members) * Personal Opinion

MERRA2, headlines MISSION Operational since Feb/2016 Development as a (fast) replacement to MERRA: Observing data was becoming obsolete MERRA Radiative Model was in danger Migration to a new HPC Lifecycle ~ 5 years (at least) No plans for MERRA3 * Important: REANALYSIS are CLIMATE products for a wide CLIMATE users Community (*) An atmosphere chemistry oriented product should follow covering aerosol satellite period, 2000 onwards (TBC)

MERRA2, headlines CHANGES Newest Satellite missions (much more obs data) First to inject aerosol remote sensing data Latest NASA GEOS-5 GCM Cube sphere grid (same effective resolution) Changes in PBL/Turbulence schemes More wind over the Oceans (roughness vs stress) Stronger pressure gradients and winds around fronts and tropical cyclones Wetter atmosphere Changes to the background gravity wave drag. (see reference) [1] Development of the GEOS-5 atmospheric general circulation model: evolution from MERRA to MERRA2 A. Molod1, L. Takacs2, M. Suarez3, and J. Bacmeister4 http://www.geosci-model-dev.net/8/1339/2015/gmd-8-1339-2015.pdf [2] MERRA-2: Initial Evaluation of the Climate Bosilovich et al http://gmao.gsfc.nasa.gov/pubs/tm/docs/bosilovich803.pdf [3] The GEOS-5 Atmospheric General Circulation Model: Mean Climate and Development from MERRA to Fortuna Andrea Molod, Lawrence Takacs, Max Suarez, Julio Bacmeister, In-Sun Song, and Andrew Eichmann http://gmao.gsfc.nasa.gov/pubs/docs/tm28.pdf

MERRA2, differences Interannual Variability Annual Correlation (R2) MERRA vs MERRA2 1996-2015 Monthly Variability www.vortex.es

MERRA2, differences Change in Interannual Variability Interannual Variability Differences (STD of Annual Anomalies) MERRA2 [%] - MERRA [%] 10m. www.vortex.es

MERRA2, validation Climate Quality Daily cycles averages Annual cycle Inter-annual variability Extreme events Passport / Credentials Match the observed data -> Correlation (R 2 ) Time consistent (Visual inspection / Test / Dig inside) Events Amplitude (OBS period = extreme anomaly ) Usage context (Tuning / Bias correction /MCP / Recalibration) Factual +++ ++ + +

MERRA2, validation Model data MERRA Wind Speeds, 50 m, hourly MERRA2 Wind Speeds, 50m, hourly DOWNSCALING STREAMS (WRF 3kM) Measurements: Wind mast data Industry standards hourly time series Quality check At least 12 consecutive months periods Over 240 sites

MERRA2, validation No significant changes in correlation ( as whole) Hourly R2 Q10 Q25 Median Q75 Q90 MERRA 0.42 0.56 0.62 0.72 0.76 MERRA2 0.47 0.56 0.62 0.73 0.72 Daily R2 Q10 Q25 Median Q75 Q90 MERRA 0.63 0.69 0.76 0.84 0.92 MERRA2 0.67 0.73 0.79 0.86 0.93 Monthly R2 Q10 Q25 Median Q75 Q90 MERRA 0.52 0.75 0.87 0.93 0.99 MERRA2 0.67 0.78 0.86 0.91 0.98

MERRA2, validation Mean Bias [m/s] Q10 Q25 Median Q75 Q90 MERRA 1.2 1.9 2.7 3.7 4.4 MERRA2 1.0 1.9 2.5 3.7 4.5 Mean Bias[m/s] Q10 Q25 Median Q75 Q90 MERRA + WRF 0.3 0.5 0.8 1.1 1.6 MERRA2+ WRF 0.3 0.4 0.8 1.1 1.6 Selection Criteria (*): R2 Monthly >0.85 & R2 Daily > 0.75 MERRA MERRA2 WRF-MERRA WRF-MERRA2 WRF-CFS Pass 45 % 47% 67% 68% 71%

Working with modeled data What brings new MERRA2 Northern Hemisphere speaking, no much change Lower variability and difference annual and monthly correlation patterns: Africa (Ethiopia) Mexico, North Chile & SE-NE Brazil Ontario region Western China India (South) Verification against data: Globally, similar R2 factors & bias ranges Verification missed data for some critical regions Downscaling keep adding value to save model data for wind industry users

last slide Challenges are in our backend (end users) WANTED: LT validation Uncertainty and Error USE: KNOWLEDGE: Integrate model & observations Dealing Multiple sources Transitions between projects Consistency over time Climate Knowledge & Perceptions Global Long-term average 80m Wind Speed Distribution at 9KM resolution Source: WRF Downscaling driving by CFS/CFSR - VORTEX

What brings new MERRA2 Half-step forward towards new Reanalysis generation Get in touch: gil.lizcano@vortex.es