NCEP Production Suite Review 9 December 2015 Radar Reflectivity Data Assimilation: Applications in NOAA’s hourly Updating Rapid Refresh (RAP) and High-Resolution Rapid (HRRR) NOAA/ESRL/GSD/EMB Curtis Alexander, David Dowell, Steve Weygandt, Stan Benjamin, Ming Hu, Tanya Smirnova

RAP and HRRR Radar DA History Key RAP/HRRR Development 2007 CONUS 3-D Radar Mosaic Developed by NSSL 2009 Radar reflectivity assimilation in 13-km operational RUC 2012 Radar reflectivity assimilation in 13-km operational RAP 2013 Radar reflectivity assimilation in 3-km experimental HRRR 2014 Radar reflectivity assimilation in 3-km operational HRRR 2016 Radar radial velocity assimilation in 13-km RAPv3 2016 Radar radial velocity assimilation in 3-km HRRRv3 (experimental) NCEP Production Suite Review RAP/HRRR Radar DA 09 December 2015

Radar Reflectivity Data Assimilation Radar Observations (WSR-88D) Reflectivity = SUM(Rain, Snow, Hail, etc…) Not a direct observation of individual hydrometeors and/or distributions Model Forecasts (WRF-ARW) Reflectivity = Diagnostic variable ESTIMATE Hydrometeors are prognostic variables in microphysical schemes Reflectivity observation type does not correspond to a state variable Underdetermined problem!!!! Assimilation Options: Variational/Ensemble DA of precipitation hydrometeors Non-variational specification of precipitation hydrometeors Model forcing function Additive Noise Latent Heat Nudging

HRRRv2 Initialization from RAPv3 13 km RAP 13z 14z 15z Obs GFS Ens Obs GFS Ens GFS Ens Obs GSI Hybrid GSI Hybrid GSI Hybrid HM Obs HM Obs HM Obs GSI HM Anx GSI HM Anx GSI HM Anx 1 hr fcst 1 hr fcst Refl Obs Refl Obs Refl Obs Digital Filter Digital Filter Digital Filter 18 hr fcst 18 hr fcst 18 hr fcst Obs GFS Ens 3 km HRRR 3-km Interp 1 hr pre-fcst GSI Hybrid Increased weight of GFS ensemble in RAP Introduction in HRRR HMObs GSI HM Anx Refl Obs 15 hr fcst

Rapid Refresh and HRRR Radar Reflectivity Assimilation Radar Data Assimilation: Focus On Reflectivity Only Pre-Process Radar Reflectivity Observations Uses NCEP 3-D CONUS MRMS 1-km Reflectivity Mosaic Horizontally and vertically interpolate reflectivity observations onto analysis grid O(1-10) CPUs in a few minutes Transform Radar Reflectivity Observations To Latent Heating Rates Reads observations and writes model input O(1-10) CPUs in a few minutes Apply Latent Heating Rates During WRF-ARW Model Integration Within forward portion of digital filtering (RAP) or in pre-forecast hour (HRRR) First few minutes of RAP integration or O(10) min for HRRR NCEP Production Suite Review RAP/HRRR Radar DA 09 December 2015

Rapid Refresh and HRRR Radar Reflectivity Assimilation Transform Radar Reflectivity Observations To Latent Heating Rates LH = Latent Heating Rate (K/s) p = Pressure Lv = Latent heat of vaporization Lf = Latent heat of fusion Rd = Dry gas constant cp = Specific heat of dry air at constant p f[Ze] = Reflectivity factor converted to rain/snow condensate t = Time period of condensate formation (600s i.e. 10 min) Focus on how much, how long and where to apply latent heating… NCEP Production Suite Review RAP/HRRR Radar DA 09 December 2015

Rapid Refresh and HRRR Radar Reflectivity Assimilation Transform Radar Reflectivity Observations To Latent Heating Rates How Much? Namelist Option: radar_latent_heat_time_period Time period (min) over which condensate formation assumed to have occurred or “t” = 5.0 min (double forcing) = 10.0 min (RAP) = 20.0 min (HRRR - half forcing) = 30.0 min (third forcing) Latent Heating Rate (K/s) 3-D Observed Reflectivity (dBZ) NCEP Production Suite Review RAP/HRRR Radar DA 09 December 2015

Rapid Refresh and HRRR Radar Reflectivity Assimilation Transform Radar Reflectivity Observations To Latent Heating Rates Where? Namelist Option: convection_refl_threshold Observed reflectivity threshold above which the latent heating is directly specified = 35.0 dBZ (convection only) = 28.0 dBZ (RAP and HRRR) = 20.0 dBZ (warm rain) Latent Heating Rate (K/s) 3-D Observed Reflectivity (dBZ) NCEP Production Suite Review RAP/HRRR Radar DA 09 December 2015

Rapid Refresh and HRRR Radar Reflectivity Assimilation Apply Latent Heating Rates During WRF-ARW Model Integration How Long? WRF Namelist Option: runlength_dfi_fwd Determines the duration of simulation time (min) when radar-specified latent heating rates are applied = 1x20.0 min (RAP) = 4x15.0 min (HRRR) Latent Heating Rate (K/s) 3-D Observed Reflectivity (dBZ) NCEP Production Suite Review RAP/HRRR Radar DA 09 December 2015

Radar Reflectivity Assimilation Rapid Refresh and HRRR Radar Reflectivity Assimilation Model Pre-Forecast Time (min) -60 -15 -45 -30 Model Integrations Observed Radar Valid at -45 Valid at -30 Valid at -15 Valid at 0 Observed Reflectivity ≤ 0 dBZ : Observed Reflectivity ≥ 28 dBZ : Zero heating rate to suppress spurious model precipitation. Positive heating rate to promote convective development. 0 dBZ < Observed Reflectivity < 28 dBZ : No radar coverage: Model microphysics heating rate preserved. During the 1-hour pre-forecast, reflectivity observations are used to specify latent heating rates (microphysics temperature tendency) in each previous 15-min period:

Radar Reflectivity Assimilation Rapid Refresh and HRRR Radar Reflectivity Assimilation Model Pre-Forecast Time (min) -60 -15 -45 -30 Model Integrations Observed Radar Valid at -45 Valid at -30 Valid at -15 Valid at 0 Depth of minimum reflectivity must exceed 200 mb when background temp < 5 ˙C (avoids identifying bright bands as convection) Vertically builds (extrapolates) temperature tendencies below radar horizon to model PBL top (avoids “disemboweled” precipitating features) Will keep convective parameterization (if present) deactivated for 30 min into free forecast if “no echo” in radar coverage (attempts to suppress convection) NCEP Production Suite Review RAP/HRRR Radar DA 09 December 2015

Radar Reflectivity Data Assimilation Skill from Reflectivity Data Assimilation HRRR Forecast Skill for Reflectivity (30 dBZ) Critical Success Index X 100  Less Skill More Skill  radar data assimilation in RAP and HRRR Essential for predicting clouds, precipitation, and other local phenomena no radar data assimilation Forecast Length (Hours) Radar DA retention into forecast period approximately 4-6 hrs NCEP Production Suite Review RAP/HRRR Radar DA 09 December 2015

Radar Reflectivity Data Assimilation Changing Strength (how much) of Latent Heating HRRR – RUC third HRRR – RAP third HRRR – RAP full HRRR – RUC full HRRR – RAP double 20-km 30dBZ CSI 20-km 30dBZ BIAS  Lower Higher  Optimal Increasing skill with more forcing But also higher bias… NCEP Production Suite Review RAP/HRRR Radar DA 09 December 2015

Radar Reflectivity Assimilation HRRR (and RAP) Future Milestones HRRR Milestones HRRR (and RAP) Future Milestones Reflectivity 00z init 00z 12 Aug 2011 RAP HRRR no radar RAP HRRR RADAR Convergence Cross-Section Rapid convective spin-up with 13-km radar data NCEP Production Suite Review RAP/HRRR Radar DA 09 December 2015 14

Radar Reflectivity Assimilation HRRR (and RAP) Future Milestones HRRR Milestones HRRR (and RAP) Future Milestones Reflectivity Reflectivity +1h fcst 01z 12 Aug 2011 RAP HRRR no radar RAP HRRR RADAR Convergence Cross-Section Rapid convective spin-up with 13-km radar data NCEP Production Suite Review RAP/HRRR Radar DA 09 December 2015 15

Improved 0-2 hr Convective Fcsts Radar Obs 05:00z 18 May 2013 05z + 0 min 0-hr fcst 3-km radar DA 0-hr fcst NO 3-km radar DA NCEP Production Suite Review RAP/HRRR Radar DA 09 December 2015

Improved 0-2 hr Convective Fcsts 15-min fcst NO 3-km radar DA Radar Obs 05:15z 18 May 2013 05z + 15 min 15-min fcst 3-km radar DA 15-min fcst NO 3-km radar DA NCEP Production Suite Review RAP/HRRR Radar DA 09 December 2015

Improved 0-2 hr Convective Fcsts 30-min fcst NO 3-km radar DA Radar Obs 05:30z 18 May 2013 05z + 30 min 30-min fcst 3-km radar DA 30-min fcst NO 3-km radar DA NCEP Production Suite Review RAP/HRRR Radar DA 09 December 2015

Improved 0-2 hr Convective Fcsts 45-min fcst NO 3-km radar DA Radar Obs 05:45z 18 May 2013 05z + 45 min 45-min fcst 3-km radar DA 45-min fcst NO 3-km radar DA NCEP Production Suite Review RAP/HRRR Radar DA 09 December 2015

Improved 0-2 hr Convective Fcsts Radar Obs 06:00z 18 May 2013 05z + 1 hour 1-hr fcst 3-km radar DA 1-hr fcst NO 3-km radar DA NCEP Production Suite Review RAP/HRRR Radar DA 09 December 2015

Improved 0-2 hr Convective Fcsts 1-hr 30m fcst NO 3-km radar DA Radar Obs 06:30z 18 May 2013 05z + 1:30 min 1-hr 30m fcst 3-km radar DA 1-hr 30m fcst NO 3-km radar DA NCEP Production Suite Review RAP/HRRR Radar DA 09 December 2015

Improved 0-2 hr Convective Fcsts Radar Obs 07:00z 18 May 2013 05z + 2hr min 2-hr fcst 3-km radar DA 2-hr fcst NO 3-km radar DA NCEP Production Suite Review RAP/HRRR Radar DA 09 December 2015

Reflectivity Forecast Skill Rapid Refresh and HRRR Reflectivity Forecast Skill Stats for east of 100°W longitude (good radar coverage for verification) Average CSI for Reflectivity ≥ 35 dBZ More skill at short lead times – radar reflectivity DA has greatest impact More skill in evening and overnight hours – after convective initiation/upscale growth More skill in strongly forced environments – more favorable mesoscale environment Spring (Apr-June) Strongly forced environments Summer (July-Sept) Weakly forced environments More skill at short lead times. More skill in evening and overnight hours. More skill at short lead times. Less skill More skill

Radar Reflectivity Assimilation Rapid Refresh and HRRR Radar Reflectivity Assimilation Observations Map to cloud field No cloud Cloud Unknown Merge cloud field Update hydrometeors based on the cloud field Last opportunity for corrections from observations

Radar Reflectivity Assimilation Rapid Refresh and HRRR Radar Reflectivity Assimilation Summary: RAP and HRRR use three-dimensional observed radar reflectivities as a proxy for latent heating through specification (replacement) of the model’s microphysics temperature tendencies Advantages: Computationally inexpensive that can run “in-line” with model integration and offers several adjustable parameters for case/user specific applications Often improves short-term forecast skill including reflectivity and precipitation Limitations: Can lead to high forecast bias (precip, reflectivity) early in forecast period in some strongly-forced situations or during periods of decaying convection Effective mostly after convective initiation when convective coverage is increasing Convective suppression is limited in capability for explicit convection applications…mesoscale forcing dominates NCEP Production Suite Review RAP/HRRR Radar DA 09 December 2015

HRRRv3 Initialization NCEP Production Suite Review RAP/HRRR Radar DA 3 km HRRR Refl Obs Refl Obs Obs GSI Hybrid GSI Hybrid GSI Hybrid 1 hr pre-fcst 1 hr pre-fcst RAP Ens RAP Ens HM Obs HM Obs GSI HM Anx GSI HM Anx GSI HM Anx 18 hr fcst 18 hr fcst Hourly full-atmosphere cycling More effective ensemble data assimilation (RAP) No longer “spinning up” convection in first hour(s) More balanced state should permit more even bias across shorter lead times NCEP Production Suite Review RAP/HRRR Radar DA 09 December 2015

HRRRv4 Initialization NCEP Production Suite Review RAP/HRRR Radar DA 3 km HRRR HRRR Ens All Obs HRRR Ens HRRR Ens All Obs All Obs GSI Hybrid GSI Hybrid GSI Hybrid 1 hr fcst 1 hr fcst 18 hr fcst 18 hr fcst All hydrometeors included in variational/ensemble data assimilation More advanced data assimilation ensemble (HRRR) NCEP Production Suite Review RAP/HRRR Radar DA 09 December 2015

Possible HRRR storm-scale ensemble system HRRR Milestones HRRR (and RAP) Future Milestones Prototype 3-km storm-scale HRRR ensemble domain Single core (ARW) Ensemble DA Stochastic physics HRRR domain Assimilation Forecast 40 members 6 members 1 hr forecast 12 hr forecast 24 fcsts / day 24 fcsts / day 2 nodes / member 60 nodes / member RAP v2 domain RAP v3 expanded domain More accurate storm-details from ensemble data assimilation