weather forecast Improving NOAA models for energy Stan Benjamin, Boulder, CO USA Joseph Olson, Curtis Alexander, Eric James,

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1 Lamont, OK X Obs radar 5h HRRR Forecast Improving NOAA weather forecast models for energy Stan Benjamin, Joseph Olson, Curtis Alexander, Eric James, Dave Turner, Melinda Marquis NOAA Earth System Research Laboratory Boulder, CO USA CREA Energy Innovations Summit 29 October 2018, Denver, CO 1

2 29 Oct CREA NOAA weather models - Stan Benjamin 2

3 Improving NOAA weather forecast models for energy Energy Converter Inverter Improving hourly updated RAP/HRRR models for renewable energy applications Improve understanding of physical processes (e.g., clouds & turbulence) Improve representation of these processes in NOAA weather models: Improve model physical parameterization schemes Improve data assimilation of observations for clouds, lower troposphere 29 Oct CREA NOAA weather models - Stan Benjamin Motivation Wind & solar are highly variable sources of energy; accurate forecasts are needed to integrate wind and solar energy into the electric grid. Also results in improved load prediction Benefits Reduce electricity costs (less penalties, less need for reserves) More stable electric grid (if forecasts are accurate) Reduction of CO2 can mitigate climate change 35h HRRR forecast valid 1100 MT Sat 27 Oct m winds (kts) Downward shortwave radiation (W/m**2) 3

4 High-performance Computing Prediction of High-Impact Weather Frequent, accurate observations Advanced Use (Assimilation) Of Observations Needs Advanced Numerical Weather Model

5 13km Rapid Refresh and 3km HRRR Hourly Updated NOAA models Hourly cycling model Advanced Radar and Cloud, Wind RAP Data Assimilation cycle Observations HRRR 29 Oct CREA NOAA weather models - Stan Benjamin 5

6 RAP/HRRR: NOAA Hourly-Updating Weather Forecast Suite 13-km Rapid Refresh (RAPv4) to 39h (July 2018) - July 2018 NOAA/National Weather Service upgrade Initial & Lateral Boundary Conditions Initial & Lateral Boundary Conditions 3-km High-Resolution Rapid Refresh Alaska (HRRR-AK) 36 hr (Jul 2018) 3-km High-Resolution Rapid Refresh (HRRRv3) to 36h (Jul 2018) Applications Severe weather Aviation/transportation Energy (load and variable gen) Hydrology/ Nat. Water Model All critically dependent on clouds 29 Oct CREA NOAA weather models - Stan Benjamin 6

7 HRRR Users and Applications Example: National Weather Service including Storm and Weather Prediction Centers (SPC and WPC) Aviation Weather Center (AWC) and FAA Command Center National Severe Storms Laboratory (NSSL) and Air Resources Laboratory (ARL) National Centers for Atmospheric Research (NCAR) and Lincoln Laboratory (LL) General Forecasting Load/Renewable Energy (wind/solar) Same-Day Decision Support Load/Renewable Energy (wind/solar) Day-Ahead Decision Support Severe Weather Severe Weather -Watches, Convective Outlooks Severe Weather Day 2 Outlooks QPF / hydro Aviation Tactical Planning Heavy rainfall/snowfall watches, National Water Model Aviation Strategic Planning Heavy rainfall/snowfall Day 2 Outlooks 0 2 hr 2 8 hrs 8 15 hrs hrs hrs Forecast Length 29 Oct CREA NOAA weather models - Stan Benjamin 7

8 Wind speeds at different heights by time of day Increase of wind speed with height depends on the prevailing meteorological conditions! local time 2400h mean wind speed (10 min average) Source: wettermast-hamburg.zmaw.de unstable and turbulent atmosphere during day stable atmosphere during night Courtesy: Gunnar Shaffer, Southwest Power Pool (Little Rock, AR) 29 Oct CREA NOAA weather models - Stan Benjamin 8

9 HRRR- NOAA operational HRRRX new version July 18 HRRRX (HRRRv3) more accurate than HRRRoperational Lamont, X OK 00z/15 Jan 12z/14 January HRRR runs Special 60m tower at Dept. of Energy observation site at Lamont 29 Oct CREA NOAA weather models - Stan Benjamin 9

10 Physics Development Emphasis: Sub- Grid Clouds MYNN PBL Explicit (Resolved) Clouds/Precipitation RAP and HRRR use the Thompson microphysics scheme with 5 hydrometeor types Sub-Grid (Unresolved) Clouds Adapted from Fig. 2 of Tompkins (2009) Assume PDF of s (saturation ratio) Retrieve Cloud Fraction, Cloud Condensate Parameterize: assume subgrid PDFs for thermodynamic variables Chaboureau-Bechtold (2002) Joseph Olson NOAA/ESRL/GSD 29 Oct CREA NOAA weather models - Stan Benjamin 10

11 HRRR Improved Convective Forecasts enabled by improved boundary-layer/cloud forecasts Experimental HRRRv3 13 hr fcst Valid 00 UTC 17 May 2017 Composite Reflectivity Observations 00 UTC 17 May 2017 Operational HRRRv2 13 hr fcst Valid 00 UTC 17 May 2017 More accurate convection along weakly-forced dryline Reflectivity Verification Better PBL -> better convective forecasts, outflows 29 Oct CREA NOAA weather models - Stan Benjamin 11

12 HRRR Ensemble Init 06 MT 06 June 2018: 27 hr forecasts HRRRE - 9 Members 27 hr forecasts Valid 15 UTC 07 June 2018 A few members depicted a scenario with sustained convection in OK MRMS obs reflectivity 15 UTC 07 June 29 Oct CREA NOAA weather models - Stan Benjamin 12

13 HRRRE Day Ahead Probability 10m wind > 50 kts Saturday evening 22z 7 Jun 02z 8 Jun From Fri morning 12z HRRRE run 29 Oct CREA NOAA weather models - Stan Benjamin 13

14 HRRR-Smoke model Smoke tracer added to HRRR Wildfire emissions and plume rise estimated in HRRR using real-time JPSS/VIIRS and MODIS fire radiative power data. HRRR-Smoke run experimentally in real time at NOAA/ESRL Global Systems Division. The forecast lead time is 36 hours. Four times a day (00, 06, 12 and 18UTC) a new forecast starts: Experimental forecast products from HRRR- Smoke used by NWS offices, air quality agencies and public. GOES- R RRRsmoke/ Oct CREA NOAA weather models - Stan Benjamin

15 Simulated reduction in downward solar radiation from smoke, 12MDT, 4 Sept June 2018 NOAA HRRR model - ESIG 1

16 What is still needed for improved wind/solar/load forecasts? Improved model representation of boundarylayer mixing and clouds. Improved data assimilation and improved 3-d observations over large multi-state areas. Probabilistic information for decision making from multiple ensemble members and from spatial and temporal averaging. The NOAA HRRR model is the backbone to improve Day-1-2 forecast models over the US. 29 Oct CREA NOAA weather models - Stan Benjamin 16