# Presentation: 551499

## Implementation Brief: Real-Time Mesoscale Analysis (RTMA)

**Implementation Brief:**** Real-Time Mesoscale Analysis (RTMA)**

- Geoff.DiMego@noaa.gov
- 301-763-8000 ext7221
- 9 August 2006

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**Where the Nation’s climate and weather services begin**

## T O P I C S

- Backgroud and Expectations
- Precipitation RTMA
- RUC Downscaling
- 2D-VAR RTMA
- OSIP
- Parallel Testing

## Background

- WR SOO/DOH IFPS White Paper provided recommendations:
**Develop a national real-time, gridded verification system**
- Provide full-resolution NCEP model grids
**Produce objective, bias-corrected model grids for WFO use**
- Implement methods to objectively downscale forecast grids
**Incorporate climatology grids into the GFE process**
- Deliver short and medium-range ensemble grids
**Produce NDFD-matching gridded MOS**
- Modify the GFE software to ingest real-time data
- Optimize ways to tap forecaster expertise

## Glahn-Livesey Verification Meeting:Need to Verify NDFD – Grid vs Analysis

**Insufficient density of obs for grid vs point verification of NDFD alone**
**No 00 hr analysis in NDFD**
**Need centrally produced “analysis of record” (DiMego’s application of a term used in FGGE)**
**No funds available**

**National Digital Forecast Database (NDFD)**
- A national database of digital weather forecast information
- Designed to meet the basic weather information needs of industry, media, commercial weather services,  academia, and the public
- 3 hour to 7 day lead time

## First Steps Toward an AOR

**A Community Meeting on Real-time and Retrospective Mesoscale Objective Analysis**
**Convened by NWS’ Seattle SOO Brad Colman and University of Utah’s John Horel**
**June 2004 in Boulder**
**AOR program should develop and implement suite of consistent sensible weather analysis products using current and future technologies.**
**Mesoscale Analysis Committee (MAC) established August 2004 by Jack Hayes Director, NWS Office of Science and Technology**

## Mesoscale Analysis Committee (MAC)

- Robert Aune, NOAA/NESDIS University of Wisconsin Space Sciences & Engineering Center
- Stanley Benjamin, Forecast Systems Laboratory
- Craig Bishop, Naval Research Laboratory
- Keith A. Brewster, Center for Analysis and Prediction of Storms The University of Oklahoma
- Brad Colman (Committee Co-chair), NOAA/National Weather Service -- Seattle
- Christopher Daly, Spatial Climate Analysis Climate Service Oregon State University
- Geoff DiMego, NOAA/NWS National Centers for Environmental Prediction
- Joshua P. Hacker, National Center for Atmospheric Research
- John Horel (Committee Co-chair), Department of Meteorology, University of Utah
- Dongsoo Kim, National Climatic Data Center
- Steven Koch, Forecast Systems Laboratory
- Steven Lazarus, Florida Institute of Technology
- Jennifer Mahoney, Aviation Division Forecast Systems Laboratory
- Tim Owen, National Climatic Data Center
- John Roads, Scripps Institution of Oceanography
- David Sharp, NOAA/National Weather Service -- Melbourne
- Ex Officio:
- Andy Edman, Science & Technology Committee representative
- LeRoy Spayd, Meteorological Services Division representative
- Gary Carter, Office of Hydrology representative
- Kenneth Crawford, COOP/ISOS representative

## Steps Toward an AOR Strategy

- MAC Committee meeting in Silver Spring in October 2004 to define needs and development strategy for AOR
- Distinct requirements become clear:
- Real-time for forecasters – hourly within ~30 min
- Best analysis for verification – time is no object
- Long-term history for local climatology

## Three Phase Strategy for AOR

- Phase I – Real-time Mesoscale Analysis
- Hourly within ~30 minutes
- Prototype for AOR
- _NCEP/EMC and GSD volunteer to build first phase:_
- _NCEP/EMC’s Stage II National Precipitation Analysis_
- _NCEP/EMC 2D-Var of 2m Temperature, 2m Dew Point and 10 m wind plus analysis uncertainty_
- _GSD provide downscaled (RUC 13 – NDFD 5) first guess_
- _NESDIS provide GOES-based Equivalent Cloud Amount_
- Phase II – Analysis of Record
- Best analysis possible
- Time is no object
- Phase III – Reanalysis
- Apply mature AOR retrospectively
- 30 year time history of AORs

## NWS’ Integrated Work Team (IWT)

- Lee Anderson (co-chair), OST PMB
- Brad Colman (co-chair), WFO  SEA
- Fred Branski, OCIO
- Geoff DiMego, NCEP EMC
- Brian Gockel, OST MDL
- Dave Kitzmiller, OHD
- Chuck Kluepfel, OCWWS Performance Branch
- Art Thomas, OCWWS
- Al Wissman, OOS

## Analysis of Record

- A comprehensive set of the best possible analyses of the atmosphere at high spatial and temporal resolution with particular attention placed on weather and climate conditions near the surface

## Expectation

- In OCWWS – SREC poll of NWS Forecast Offices, AOR is top ranked priority two-years running
- In 2005, RTMA was accepted for inclusion in AWIPS build OB7.2 scheduled for deployment in Fall 2006

## Phase I: The Real-Time Mesoscale Analysis (RTMA)

## RTMA Procedure

- Temperature & dew point at 2 m & wind at 10 m
- RUC forecast/analysis (13 km) is downscaled by GSD to 5 km NDFD grid
- Downscaled RUC used as first-guess in NCEP’s 2DVar analysis of ALL surface observations
- Estimate of analysis error/uncertainty
- Precipitation – NCEP Stage II analysis
- Sky cover – NESDIS GOES sounder effective cloud amount

## RTMA Logistics

- Hourly within ~30 minutes
- 5 km NDFD grid in GRIB2
- Operational at NCEP Q3 FY2006
- Distribution of analyses and estimate of analysis error/uncertainty via AWIPS SBN as part of OB7.2 upgrade – end of CY2006
- Archived at NCDC

## Precipitation RTMA

- Ying Lin’s existing Stage 2 National Precipitation Analysis hourly product
- Timely  ~35min after each hour
- High resolution ~4 km HRAP grid
- Interpolate Stage 2 product to 5 km NDFD grid to create the RTMA Precipitation analysis product
- Since April 19, 2005_[http://wwwt.emc.ncep.noaa.gov/mmb/ylin/pcpanl/precip_rtma_aor.html](http://wwwt.emc.ncep.noaa.gov/mmb/ylin/pcpanl/precip_rtma_aor.html)_
- Became operational 13Z 28 June 2006

## Hourly Gages Available for Stage II Precipitation Analysis

## Precipitation AnalysisHRAP grid versus NDFD grid

## NCEP RTMA Precipitation Analysis

- NCEP Stage II (real-time) and Stage IV (delayed) precipitation analyses are produced on the 4-km Hydrologic Rainfall Analysis Project grid
- The existing multi-sensor (gauge and radar) Stage II precipitation analysis available 35 minutes past the hour
- RTMA is mapped to the 5 km NDFD grid and converted to GRIB2
- Upgrade plan including OHD analysis + improved gauge QC from GSD
- Primary contact: Ying Lin, NCEP/EMC
**http://wwwt.emc.ncep.noaa.gov/mmb/ylin/pcpanl/**

- ORIGINAL

- NDFD GRIB2

## NESDIS’ GOES Effective Cloud Amount

- Derived ECA from GOES-12

- ECA from GRIB2 file – 5km grid

- GOES-12 IR image (11um)

-  Effective Cloud Amount (ECA, %)
-  Derived from GOES sounder
-  Mapped onto 5-km NDFD grid
-  Converted to GRIB2 for NDGD
-  Contacts: Jaime Daniels NESDIS

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_**NESDIS’ GOES Effective Cloud Amount**_

## RTMA-RUC downscaling

- NOAA-ESRL-GSD
- Stan Benjamin
- John Brown

- NCEP-EMC
- Geoff Manikin

-  Original code – 28 June 2005 – part of 13-km RUC package
-  Revised code – 11 July 2006 – part of 2006 RUC package
-  Review of RTMA-RUC downscaled grids in winter/spring 2006 by NWS, EMC, GSD
-  New topo, roughness length grids now used, improved code for extrapolation vs. interpolation, coastlines

## Why RUC for First Guess

**Hourly update frequency **
**Characteristics of RUC grids appropriate for RTMA/AoR**
-   Hourly mesoscale analysis (digital filter essential)
-   Designed to fit observations (within expected error)
- (incl. Sfc 2m temp (as ), dewpoint, altimeter, wind )
-   Consistent with full-physics 1-h forecast
- (most important in physics – PBL, land-surface)
-   Accounting for local PBL depth in assimilation of surface data
-   Accounting of land-water contrast
-   Assimilation of METAR cloud, vis, current wx
-   Assimilation of full mesonet obs (except winds)
-   Assimilation of GPS PW, PBL profiler
-   QC criteria for mesonet different than METARs
-   Assimilation of GOES cloud-top data into initial fields of 3-d hydrometeors (5 types)

## Outline of original EMC/GSD (then FSL) proposal

- Combined approach
-  Step 1.  Full model-based 1-h (or less) assimilation cycle at coarser resolution (e.g., current 13km RUC  13-km RR)
-  Step 2. Non-model downscaling using ~2.5-5km topography, land-use, roughness length, land/water
-  Step 3. Analysis w/ high-resolution observations – Mesonet/METAR inc. cloud/vis.., radar, satellite

- RUC analysis

- 2.5-5km downscaled
- grids

- 2.5-5km analysis

- background

## RUC downscaling to RTMA background

-  Runs as extra module at end of RUC post-processing code for both 0-h and 1-h data, 1-h RUC is currently used for RTMA background
-  All diagnostics ready on 13km grid
-  Horizontal and vertical interpolation components for downscaling to 5-km
-  Use of 5-km RTMA high-resolution terrain
-  Use of 5-km roughness-length on RTMA grid (from WRF Standard Initialization program) to more sharply define land-water contrast on 5-km RTMA grid
-  Variables – p, z, 2-m T/Td/q, u/v, wind gust, ceiling, visibility

## RTMA-RUC downscaling

- Step 1 - Horizontal component
- Bilinearly interpolate RUC grids to RTMA 5-km
- Variables – p, z, 2-m T/Td/q, u/v, wind gust, ceiling, visibility
- Use 5-km roughness length to estimate RTMA water point values (2mT/Td, u/v) from nearby RUC water points – maintain appropriate coastal gradients using high-res RTMA land-water

## RTMA-RUC downscaling

- 2.  Step 2 – Vertical component
- 2-m temp (most critical part of RTMA downscaling)
- If z-RUC > z-RTMA
- Use local lapse rate from native RUC lowest 25 mb, constrained between dry adiabatic and isothermal
- If z-RUC < z-RTMA
- Interpolate from native RUC levels, but maintain inversion such that 2mT-RTMA does exceed 2mT-RUC in this condition
- 2-m dewpoint, wind, wind gust
- Use similar techniques dependent on z-RUC/z-RTMA, with different constraints for each
- (More discussed at AMS on RUC-RTMA downscaling)

## RUC-RTMA downscaling

-  to detailed RTMA background

- RTMA 2dVAR update

## RUC-RTMA downscaling

-  to detailed RTMA background

- RTMA 2dVAR update

## Example of revision in RTMA-RUC downscaling based on 2006 review

*Example of revision in RTMA-RUC downscaling based on 2006 review*
- Revised code to generate downscaled
- NDFD 1st guess constrains the upward
- extrapolation that previously led to too
- warm 2-m temps over high terrain
- during early morning inversions

- Diffs

## Why 2DVar solution?

- 2DVar is subset of NCEP’s more general 3DVar Grid-point Statistical Interpolation (GSI)
- Connected to state-of-the-art unified GSI development at NCEP / JCSDA
- 2DVar is already running in NAM (low risk)
- Anisotropy built into 2DVar provides way to restrict influence of obs based on
- Elevation (terrain height – NAM & ADAS in WR)
- Future use of potential temperature
- 2DVar is fast enough to run overtop of hourly RUC in tight NCEP Production suite
- Can provide estimate of analysis uncertainty
- Can assess analysis “accuracy” via built-in cross-validation

## The RTMA 2D-Var is a special application ofNCEP’s Gridpoint Statistical Interpolation (GSI)

- http://wwwt.emc.ncep.noaa.gov/gmb/treadon/gsi/documents/presentations/1st_gsi_orientation/

**1****st**** GSI User Orientation   4-5 January 2005**

**Cross-Validation**

## NCEP obtains full complement of observations

- Conventional through TOC
- Mesonets through MADIS (FSL)
- MesoWest will be critical alternate path to MADIS during AOR due to their ability to store and forward “old” data transmitted in bursts from some sites/networks (may have better QC as well)

## ALL Surface Obs = 89126 total

## SFCSHP+ADPSFC Obs = 10843

## of which METAR Obs = 8543

## All Mesonet Obs = 78283

## of which AWS Obs = 35565

## Mesonet Issues

- Mesonets comprise majority of obs _but_ they are not as good as other conventional sfc ob sources
- No mesonet winds not used in current RUC (or NAM) due to slow wind bias
- GSD has constructed a “Uselist” of acceptable networks based on overall siting strategies etc.
- GSD Uselist is applied in the RTMA
- Continuing need for scrutiny of mesonet quality
- Data volumes arriving at NCEP from MADIS are deficient to run analysis in time for targetted 30 minute delivery
- Temporarily moved ob dump to H+30 to get sufficient obs – leads to delivery at H+42

## GSI: Nonlinear Quality Control

-  Next to be tried will be the GSI’s nonlinear QC procedure

## Error Correlations for Valley Ob (SLC) Location Plotted Over Utah Topography

- _Anisotropic_ Correlation:
- obs' influence restricted to
- areas of similar elevation

- _Isotropic_ Correlation:
- obs' influence extends up mountain slope

## Example of 2DVar/RTMA analysis increment for temp

- Isotropic

- Anisotropic

## Estimates of RTMA Analysis Error / Uncertainty

- Reflect Obs density, Obs quality and Background quality
- Not direct from GSI but it will be possible to estimate it:

## Wind Direction and Wind Speed Analysis Uncertainty

## Cross-Validation in GSI and the RTMA’s 2D-VAR

- Cross-validation
- Withhold small percentage of obs from analysis
- Validate analysis at those withheld obs
- Only way to verify analysis for analysis sake
- Now built into GSI
- Can withhold and internally compare analysis
- Baseline CV also computed internally based on a simple single-pass Cressman scheme
- Future performance metrics will be based on improvement over this Baseline

## OSIP Process / Progress

- IWT Team led by OS&T’s Lee Anderson
- Three Phase Analysis of Record (AOR)
- _[Need Identification Document (NID)](https://osip.nws.noaa.gov/osip/projectDetail.php?document=6676)_ 03/14/2005
- _[Statement of Need (SON)](https://osip.nws.noaa.gov/osip/projectDetail.php?document=6673)_ 05/04/2005
- _[CONOPS/ORD](https://osip.nws.noaa.gov/osip/projectDetail.php?document=9992)_ 12/16/2005
- _[Project Plan (PP)](https://osip.nws.noaa.gov/osip/projectDetail.php?document=13076)_ 07/10/2006

## OSIP Process / Progress

- Real Time Mesoscale Analysis (RTMA = Phase 1 of AOR)
- _[Statement of Need (SON)](https://osip.nws.noaa.gov/osip/projectDetail.php?document=12656)_ 05/24/2006
- _[Project Plan (PP)](https://osip.nws.noaa.gov/osip/projectDetail.php?document=13077)_ 07/10/2006
- _[CONOPS/ORD](https://osip.nws.noaa.gov/osip/projectDetail.php?document=12659)_ 05/24/2006
- _[Business Case (BUS)](https://osip.nws.noaa.gov/osip/projectDetail.php?document=12739)_ 05/25/2006
- _[Requirement Specification (REQ)](https://osip.nws.noaa.gov/osip/projectDetail.php?document=12644)_ 05/08/2006

## RTMA Testing

- Manuel Pondeca built RTMA 2D-Var system and Dennis Keyser built special obs dumps
- Started running hourly in real-time in December 2005
- Output grids in GRIB2 format on NCEP’s ftp server
- Test files picked up by field evaluators and by TOC and SOC for testing for OB7.2

## RTMA Evaluation Website

- _[http://www.emc.ncep.noaa.gov/mmb/rtma/](http://www.emc.ncep.noaa.gov/mmb/rtma/)_
- Established 24 Jan. 2006 by Geoff Manikin
- 7 geographical sub-regions displayed:
-     NE, DC, FL, MW, TX, NW and SW
- 3 analysis field displays: 2 m Temperature,
-     2 m Dew Point  and 10 m Wind
- 4 analysis increment displays: 2 m Temp,
-     2 m Dew Point, 10 m Wind Speed and
-     10 m Vector Wind

## RTMA Webpage - Legend

## TX 2 m Temperature Analysis

## TX 2 m Temperature Analysis

## TX 2 m Temperature Increment

## RTMA Field Evaluation

- The IFPS Science Steering Team (ISST) has coordinated the distribution of the parallel datasets to the field
- WR SSD took the lead on providing installation materials
- WR is retrieving, parsing and distributing the datasets to the other CONUS regions
- Each region distributes the datasets to the WFOs via LDM
- Data is displayable in AWIPS/D2D and GFE
- ISST is conducting a field evaluation similar to that of the DGEX implementation
- Web based response form
- Evaluation has been focused data quality issues with T, Td, and Wind and will expand to QPE
- Data delivery has not been a focus to this point

## Multiple Stage Evaluation

- Field evaluation is still ongoing
- Initial stage (April – August)
- ISST members (2 per region), 4 select sites, and Regions
- Evaluate overall dataset quality
- Second stage (August – )
- Expand the number of field sites
- Continued quality evaluation
- Evaluate the delivery and daily usability of the datasets

## Initial Evaluation

- Direct feedback to the developers from the ISST, regions and other evaluators has resulted in substantial improvements to the dataset quality
- Smaller scale quality issues are still being addressed
- Currently, use in operations is limited due to the current delivery schedule
- Evaluation has been limited to the SOOs

## Next Phase

- The complete evaluation of the RTMA goes beyond the quality of the dataset
- Consistent/Reliable delivery of the RTMA to the field is vital to its continued improvement
- Transfer of the RTMA to operational status will greatly increase the daily usage in operations and is the next important step in the RTMA evolution