Rapid Refreshand 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 HRRRNOAA hourly updated models

NCEP Production Suite Review 3-4 December 2013Rapid Refresh / HRRR 4

13km Rapid Refresh (RAP)

(mesoscale)

3km HRRR (storm-scale)

High-Resolution Rapid Refresh Scheduled NCEPImplementation Q3 2014

Version 2 – scheduled NCEP implementationQ2 (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 RefreshHourly Update Cycle

1-hrfcst

1-hrfcst

1-hrfcst

11 12 13Time (UTC)

AnalysisFields

3DVARObs

3DVARObs

Back-groundFields

Partial cycle atmospheric fields – introduce GFS information 2x/dayCycle hydrometeorsFully cycle all land-sfc fields(soil temp, moisture, snow)

Hourly Observations RAP 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 - CONUS 1km

Lightning (proxy reflectivity) NLDN, GLD360

Aircraft (V,T) 2-15K

Aircraft - WVSS (RH) 0-800

Surface/METAR (T,Td,V,ps,cloud, vis, wx)

2200- 2500

Buoys/ships (V, ps) 200-400

GOES AMVs (V) 2000- 4000

AMSU/HIRS/MHS radiances Used

GOES cloud-top press/temp 13km

GPS – Precipitable water 260

WindSat scatterometer 2-10K

Observations Used

GSI Hybrid

ESRL/GSD RAP 2013Uses GFS 80-member ensemble

Available four times per day valid at 03z, 09z, 15z, 21z

GSI Hybrid

GSI HM Anx

DigitalFilter

18 hr fcst

GSI Hybrid

GSI HM Anx

DigitalFilter

1 hr

fcs

tGSI HM

Anx

DigitalFilter

18 hr fcst

13z 14z 15z

13 kmRAP

Cycle

1 hr

fcs

t

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

1994 - 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.

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TX 2 m Temperature Analysis