Rapid Refresh and RTMA

RUC: AKA-Rapid Refresh A major issue is how to assimilate and use the rapidly increasing array of off-time or continuous observations (not a 00 and 12 UTC world anymore! Want very good analyses and very good short- term forecasts (1-3-6 hr) The RUC/RR ingests and assimilates data hourly, and then makes short-term forecasts Uses the WRF model…which uses a hybrid sigma/isentropic vertical coordinate Resolution: Rapid Refresh: 13 km and 50 levels, High Resolution Rapid Refresh (3 km)

Rapid Refresh and HRRR NOAA hourly updated models NCEP Production Suite Review3-4 December 2013Rapid Refresh / HRRR 4 13km Rapid Refresh (RAP) (mesoscale) 3km HRRR (storm-scale) High-Resolution Rapid Refresh Scheduled NCEP Implementation Q Version 2 – scheduled NCEP implementation Q2 (currently 28 Jan) RAP HRRR

RAPv2 Prediction System Overview Hourly updated mesoscale analyses / forecasts WRF-ARW model (Grell-3 cumulus param, Thompson microphysics, RUC-Smirnova land-surface, MYNN PBL scheme) GSI hybrid analysis using 80-member global ensemble 13-km, 50 levels, 24 cycles/day – each run out to 18 hours 6-hour catch-up “partial” cycle run twice per day from GFS Output grids: 13, 20, and 40 km CONUS, 32 km full domain, 11 km Alaska, 16 km Puerto Rico Use and downstream dependencies Used by SPC, AWC, WPC, NWS FOs, FAA, energy industry, and others for short-range forecasts and hourly analyses Downscaled RAP serves as first guess for RTMA RAP serves as initial condition for SREF members RAP will be used to initialize Hi-Res Rapid Refresh (HRRR)

Rapid Refresh Hourly Update Cycle 1-hr fcst 1-hr fcst 1-hr fcst Time (UTC) Analysi s Fields 3DVA R Obs 3DVA R Obs Back- groun d Fields Partial cycle atmospheric fields – introduce GFS information 2x/day Cycle hydrometeors Fully cycle all land-sfc fields (soil temp, moisture, snow) Hourly ObservationsRAP 2013 N. Amer Rawinsonde (T,V,RH)120 Profiler – NOAA Network (V)21 Profiler – 915 MHz (V, Tv)25 Radar – VAD (V)125 Radar reflectivity - CONUS1km 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) GOES AMVs (V) AMSU/HIRS/MHS radiancesUsed GOES cloud-top press/temp13km GPS – Precipitable water260 WindSat scatterometer2-10K Observations Used

GSI Hybrid ESRL/GSD RAP 2013 Uses GFS 80-member ensemble Available four times per day valid at 03z, 09z, 15z, 21z GSI Hybrid GSI HM Anx Digital Filter 18 hr fcst GSI Hybrid GSI HM Anx Digital Filter 1 hr fcst GSI HM Anx Digital Filter 18 hr fcst 13z 14z 15z 13 km RAP Cycle 1 hr fcst 80-member GFS EnKF Ensemble forecast valid at 15Z (9-hr fcst from 6Z) 18 hr fcst RAPv2 Hybrid Data Assimilation

RUC History – NCEP (NMC) implementations First operational implementation of RUC - 60km resolution, 3-h cycle 1998 – 40km resolution, 1-h cycle, - cloud physics, land-sfc model 2002 – 20km resolution - addition of GOES cloud data in assimilation 2003 – Change to 3dVAR analysis from previous OI (April) 2004 – Vertical advection, land use (April) PBL-depth for surface assimilation (September) 2005 – 13km resolution, new obs, new model physics (June) 2011 – WRF-based Rapid Refresh w/ GSI to replace RUC

Rapid Refresh: 13 km and larger domain

High-Resolution Rapid Refresh: 3 km, 1 hr, smaller domain

RTMA (Real Time Mesoscale Analysis System) NWS New Mesoscale Analysis System for verifying model output and human forecasts.

Real-Time Mesoscale Analysis RTMA Downscales a short-term forecast to fine- resolution terrain and coastlines and then uses observations to produce a fine-resolution analysis. Performs a 2-dimensional variational analysis (2d-var) using current surface observations, including mesonets, and scatterometer winds over water, using short-term forecast as first guess. Provides estimates of the spatially-varying magnitude of analysis errors Also includes hourly Stage II precipitation estimates and Effective Cloud Amount, a GOES derived product Either a 5-km or 2.5 km analysis.

RTMA The RTMA depends on a short-term model forecast for a first guess, thus the RTMA is affected by the quality of the model's analysis/forecast system CONUS first guess is downscaled from a 1- hour RR forecast. Because the RTMA uses mesonet data, which is of highly variable quality due to variations in sensor siting and sensor maintenance, observation quality control strongly affects the analysis.

Why does NWS want this? Gridded verification of their gridded forecasts (NDFD) Serve as a mesoscale Analysis of Record (AOR) For mesoscale forecasting and studies.

23 TX 2 m Temperature Analysis