Lightning data assimilation in the Rapid Refresh and evaluation of lightning diagnostics from HRRR runs Steve Weygandt, Ming Hu, Curtis Alexander, Stan.

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Presentation transcript:

Lightning data assimilation in the Rapid Refresh and evaluation of lightning diagnostics from HRRR runs Steve Weygandt, Ming Hu, Curtis Alexander, Stan Benjamin, Eugene McCaul 1 NOAA ESRL, Global Systems Division, Assimilation and Modeling Branch 1 USRA, Huntsville, AL NO LTG assim WITH LTG assim +1h RAP forecast 02z 26 Jan 2012

— Advanced community codes (ARW and GSI) — Retain key features from RUC analysis / model system (hourly cycle, radar DFI assimilation, cloud analysis) — RAP guidance for aviation, severe weather, energy applications Rapid Refresh and HRRR NOAA hourly updated models Rapid Refresh-13 RUC-13 RUC  Rapid Refresh (01 May 2012) Rapid Refresh v2 — Many improvements, target NCEP implement early 2014 HRRR – Runs as nest within RAP v2 NCEP GSD HRRR-3

RAP: Data assimilation engine for HRRR 3 RAP Data Assimilation cycle Observations Hourly cycling model HRRR

Rapid Refresh Hourly Update Cycle 1-hr fcst 1-hr fcst 1-hr fcst Time (UTC) Analysis Fields 3DVAR Obs 3DVAR Obs Back- ground Fields Partial cycle atmospheric fields – introduce GFS information 2x/day Fully cycle all land-sfc fields Hourly ObservationsRAP 2012 N. Amer Rawinsonde (T,V,RH)120 Profiler – NOAA Network (V)21 Profiler – 915 MHz (V, Tv)25 Radar – VAD (V)125 Radar reflectivity - CONUS2km Lightning (proxy reflectivity)NLDN, GLD360 Aircraft (V,T)2-15K Aircraft - WVSS (RH)0-800 Surface/METAR (T,Td,V,ps,cloud, vis, wx) Buoys/ships (V, ps) Mesonet (T, Td, V, ps)flagged GOES AMVs (V) AMSU/HIRS/MHS radiancesUsed GOES cloud-top pressure/temp13km GPS – Precipitable water WindSat scatterometer2-10K

Radar reflectivity assimilation Digital filter-based reflectivity assimilation initializes ongoing precipitation regions Forward integration,full physics with radar-based latent heating -20 min -10 min Initial +10 min + 20 min RUC / RAP HRRR model forecast Backwards integration, no physics Initial fields with improved balance, storm-scale circulation + RUC/RAP Convection suppression

Rapid Refresh (GSI + ARW) reflectivity assimilation example Low-level Convergence Upper-level Divergence K=4 U-comp. diff (radar - norad) K=17 U-comp. diff (radar - norad) NSSL radar reflectivity (dBZ) 14z 22 Oct 2008 Z = 3 km

Objectives for different model resolutions Parameterized convection (13-km RAP) - storm detection in radar coverage voids Explicit convection resolving (~3-km) Very high-resolution (1-km and less) - Specification of sub-storm-scale features - Fusion of dual-pol radar data and total lightning mapper data to specify detailed microphysics Methods Use as proxy reflectivity, specify latent heat Variational / ensemble methods Assimilation of lightning data

1.Map lightning density to proxy reflectivity -- sum ground flashes per grid-box over 40 min period (-30  +10 min) REFL max = min [ 40, 15 + (2.5)(LTG)] Sin distribution in vertical RAP assimilation of lightning data LTG and REFL max REFL max and vertical REFL profile OLD specified relationship: NEW seasonally averaged empirical relationships:

Summer Winter OLD specification in RUC NEW Seasonally dependent empirical Lightning Flash Rate  max reflectivity

SUMMER Reflectivity profile as a function of column maximum reflectivity Max dbz Max dbz Max dbz Max dbz 30-35

WINTER Reflectivity profile as a function of column maximum reflectivity Max dbz Max dbz Max dbz Max dbz 45-50

44 dBz 36 dBz 40 dBz 30 dBz Max dbz Max dbz Max dbz Max dbz AVERAGE Reflectivity profile as a function of column maximum reflectivity Summer Winter Summer Winter Summer Winter Summer Winter

Applications lightning DA technique Can apply technique to lightning data and satellite-based indicators of convective initiation  GLD-360 lightning data -- good long-range coverage Especially helpful for oceanic convection  SATCAST cloud top cooling rate data -- good Convective Initiation (CI) indicator Avoiding model delay in storm development SATCAST  work by Tracy Smith using data provided by John Mecikalski proxy flash rate = - 2 x cloud-top cooling rate (K/15 min)

Radar coverage Observed reflectivity Sat obs 24 Apr z Latent heating- based temperature tendency No radar echo No radar coverage Lightning flash rate 16z Rapid Refresh oceanic lightning assimilation example

Observed reflectivity Sat obs 24 Apr z No radar echo No radar coverage Rapid Refresh oceanic lightning assimilation example with LTG NO LTG LTG DA  slight impact on RAP forecast storm clusters 16z +1h GSD RAP forecasts 17z 16z

21z 9 Jan Prim 19z + 2h fcst Dev 19z + 2h fcst ~ 11z LTG 1915z LTG NO LTG assim WITH LTG assim Radar

Assimilation of “satcast” cloud-top cooling rate CI-indicator data 17z SATCAST cooling rate (K / 15 min) 18z IR image 18z 5 July 2012 Cloud-top cooling rate helpful for initializing developing convection in GSD RAP retro tests 5 July 2012

WITH satcast assim NO satcast assim 18z+1h 19z Obs Reflect Assimilation of “Satcast” cooling rates provides more realistic short-range forecast of convective initiation and development

18z+2h 20z Assimilation of “Satcast” cooling rates provides more realistic short-range forecast of convective initiation and development Obs Reflect WITH satcast assim NO satcast assim

Experimental HRRR lightning forecast guidance McCaul algorithm LTG1 Graupel flux a -15 C (cores) LTG2 Vertical integrated ice (anvils) LTG LTG1* LTG2* 2011 version: scale core by anvil 2012 version: scale anvil by core

Components of combined lightning threat (LTG3) (2011 version) 01z LTG2 LTG1 LTG3 Flases / km^2 / 5min

HRRR Combined lightning threat (LTG3) vs. radar and NALMA 23z HRRR LTG3 Obs radar NALMA lightning 19z + 4h (North Alabama Lightning Map- ping Array)

HRRR Combined lightning threat (LTG3) vs. radar and NALMA 00z Obs radar NALMA lightning HRRR LTG3 19z + 5h (North Alabama Lightning Map- ping Array)

HRRR Combined lightning threat (LTG3) vs. radar and NALMA 01z Obs radar NALMA lightning HRRR LTG3 19z + 6h (North Alabama Lightning Map- ping Array)

1800z LTG2 LTG3 Lightning threat components (2012) Refl. 18z+3h Forecast 10 Jan 2013 LTG1 Flases / km^2 / 5min

1800z LTG2 LTG3 Lightning threat components (2012) Refl. 18z+6h Forecast 10 Jan 2013 LTG1 Flases / km^2 / 5min

1800z LTG2 LTG3 Lightning threat components (2012) Refl. 18z+9h Forecast 10 Jan 2013 LTG1 Flases / km^2 / 5min

1800z Refl. 18z+12h Forecast 10 Jan 2013 LTG2 LTG1 LTG3 Lightning threat components (2012) Flases / km^2 / 5min

Summary Preliminary evaluation of impact from assimilation of two novel convection indicators:  GLD-360 lightning data -- good long-range coverage Helpful for oceanic convection  Satcast cloud top cooling rate data -- good CI Avoid model delay in storm development Preliminary look at lightning parameters from HRRR 3-km forecasts Qualitative assessment ongoing Plan HRRR runs from RAP w/ and w/o LTG, satcast