Rapid Update CycleRUC RUC A major issue is

Rapid Update Cycle-RUC

RUC • A major issue is how to assimilate and use the rapidly increasing array of offtime 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 ingests and assimilates data hourly, and then makes short-term forecasts • Uses the MAPS mesoscale model…which uses a hybrid sigma/isentropic vertical coordinate • Resolution: 13 km and 50 levels

Domain

13 km RUC Terrain elevation - 100 m interval

Observations used in RUC Data Type ~Number Freq. -------------------------Rawinsonde 80 /12 h NOAA profilers 30 / 1 h VAD winds 110 -130 / 1 h Aircraft (V, temp) 1400 -4500 / 1 h Surface/METAR 1500 -1700 / 1 h Buoy/ship 100 -150 / 1 h GOES precip water 1500 -3000 / 1 h GOES cloud winds 1000 -2500 / 1 h GOES cloud-top pres 10 km res / 1 h SSM/I precip water 1000 -4000 / 6 h -------------------------GPS precip water ~300 / 1 h Mesonet ~5000 / 1 h METAR-cloud-vis-wx ~1500 / 1 h -------------------------

RUC History – NCEP (NMC) implementations 1994 - First operational implementation of RUC - 60 km resolution, 3 -h cycle 1998 – 40 km resolution, 1 -h cycle, - cloud physics, land-sfc model 2002 – 20 km resolution - addition of GOES cloud data in assimilation 2003 – Change to 3 d. VAR analysis from previous OI (April) 2004 – Vertical advection, land use (April) PBL-depth for surface assimilation (September) 2005 – 13 km resolution, new obs, new model physics (June) 2011 – WRF-based Rapid Refresh w/ GSI to replace RUC

WRF RUC • A new version of RUC has been developed, that uses the WRF model instead of the MAPS model. Called the Rapid Refresh. Now running, will replace RUC this year.

Rapid Refresh: 13 km but 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.

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 (2 d-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 RUC 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.

RTMA 2 d. VAR update RUC-RTMA downscaling 22 to detailed RTMA background

RTMA 2 d. VAR update RUC-RTMA downscaling 23 to detailed RTMA background

TX 2 m Temperature Analysis 24

TX 2 m Temperature Analysis 25

TX 2 m Temperature Increment 26