# Presentation: 519537

## 
Science and Technology Infusion Plan
for
Numerical Prediction

**Science and Technology Infusion Plan**
**for**
**Numerical Prediction**

**NWS S&T Committee**
**September 17, 2002**

***Jeff McQueen***

## Outline

**Team Composition**
**Vision**
**Key Service Gaps **
**Key NP Solutions**
**Outstanding R&D Needs**
**Infusion Strategy**
**Summary**

## Numerical PredictionTeam Composition

**Jeff McQueen – NWS/OST**
**Paul Dallavalle  – NWS/OST**
**Steve Koch – OAR/FSL**
**Ralph Petersen – NWS/NCEP**

**Dave Stensrud – OAR/NSSL**
**Stan Benjamin – OAR/FSL**
**Michael Smith – NWS/OHD**

## Numerical Prediction

**Ensembling & Postprocessing**

**Numerical Prediction**

**Drive Improved Applications**
**- ****Aviation, Marine, Hydro, Tropical, AQ...**

**Notes:**
Common (Medium) *  Extend the WRF concept to global modeling
*Provides the most efficient framework for future model development and
maintenance by reducing duplications.
*  Allows for full coupling between all environmental scales and processes.
*  Improve regional (and local) scale predictions by providing full coupling
between scales and highly  accurate global scale initial conditions and boundary
condition forcings with minimal interpolation error.

Resolution & improved physics: resolve storm-scale processes

## Numerical Prediction Pathway to Unified Common Model Framework

**2002**

**2007**

**2012**

**Global/Climate**

**2020**

**Ocean**

**Regional**

**Hydrologic**

**Hurricane**

**Hazards/AQ**

_***GFS***_

**ROFS**

_***Eta***_

_***RUC***_

_***SFM***_

**NOAH/**
**AHPS**

**Hysplit**

**GFDL**

_***Unified fully coupled ***_
_*** ***__***framework for***_
_***climate/weather/water***_

***time***

***Deterministic &Probabilistic***

_***Coupled ***_
_***Land-atm-ocean-ice***_
_***global model***_

_***Coupled***_
_***(L/A/H/AQ)***_
_***WRF Framework***_

***Deterministic &Probabilistic***

## Numerical PredictionKey Service Gaps 

**Improve Forecasts of Mesoscale Phenomena:**
***Severe Storm, Gravity Waves, Turbulence***
***Precip Types, Cloud, Surface Properties***
**Improve Confidence Levels and Range of Probabilities**
**More Accurate Warm and Cool Season QPF**
**Storm Track & Intensity Forecasts & Associated QPF**
**Improve Week Two to Seasonal Range Forecasting**
**Improved Forecasts of Global Ocean Conditions**
**Implement Air Quality Forecasts**

## Numerical PredictionKey Solutions

**Numerical Prediction***Key Solutions*

**Impact**

**Projected Solution**

## Numerical PredictionKey Solutions

***Provide Consistent Guidance***
***Support EPA Mission***

***Implement IOC  w/ Transition to Fully Coupled WRF-Chem***

***Implement Air Quality Forecasts***

***Increased Accuracy of    ENSO/SST Anomalies ***
***100% Ocean/Lake Coverage***
***Gulf stream position***

***Upgrade Global Ocean Data Assimilation System(GODAS) ******Coupled****** ***_**[ Land/Ocean/Ice GFS](slide28.xml)**_
***Upgrade Wave Model (10 km) ***
***Great Lakes System***

***Improve Forecasts of Global Ocean Conditions***

***Improve Week Two to Seasonal Forecasts of Temp/Precip/Hazards***

***GFS******, Global Ensembles***
***Seasonal Forecast Model***
***Coupled ***_**[ Ocean/](slide28.xml)**__**[Atm](slide28.xml)**__**[/Land](slide28.xml)**_

***Improve Long Range Forecasting***

***20% increase in Intensity***
***Marine: 20% Improvement***

***Hurricane WRF DA/Model***
***North Amer. WRF, GFS, HRW***
***Ensembles/ Targeted obs***

**Impact**

**Projected Solution**

**Service Gap**

***More Accurate Warm Season Precipitation***

***More Accurate Cool  Season Precipitation***

***North Amer. WRF, GFS***
***Ensembles/ Targeted obs***

***R/S  Resolved w/in 30km***
***Mtn QPF Resolved to 30km***

## Numerical Prediction Key S&T Solutions 

- Deployment

**Global, SREF**

**Probabilistic**

** ****WRF SREF**

**Multi-model***

**Hydrologic**

**Hybrid veg/soil **

**Distributed basin* **

**GFS T254**

**Global**

**Coupled* ocean/atm/land **

**Common* Global-30/ Regional-3**

**Adv. Assim. * NPOESS**

**Radar**

**Data    Assimilation**

**Cloud/GODAS**

**Regional/AQ**

**WRF: NA-8, RR, HRW**

**Eta, RUC,HRW**

**cpld AQ WRF-4***

**Ozone**

**Physics**

**Existing cloud physics**

**Explicit  cloud* & Adv physics**

**Coupled AQ**

- OTE

**Common* SFM/GFS**

**Climate**

**Global Ocean Model**

**AHPS**

**SFM T62**

**Eta/GFS MOS**

**Ensemble PDF**

**Neural Nets**

**Super Computing**

**80x**

**36x**

**14x**

**2x**

**9x**

**Notes:**
			Urgency		Justification
Advanced FDDA (High): Better use of HR data/needed to capture high res features

Adv Physics (High): Current physics designed for coarser res (>10km)

Coupling (High): For medium/long range forecasts. Ie: effects of ocean sst changes to drive sub-seasonal to climate patterns

WRF (High):  Platform for interactions with research and transition	
                       Facilitate efficient transition to ops.

Common (Medium): *  Extend the WRF concept to global modeling
	*Provides the most efficient framework for future model development and
	maintenance by reducing duplications.
	*  Allows for full coupling between all environmental scales and processes.
	*  Improve regional (and local) scale predictions by providing full coupling
	between scales and highly  accurate global scale initial conditions and boundary condition forcings with minimal interpolation error.

Multi-model (Medium): Improved ensemble diversity

!!!!

## Numerical Prediction  Outstanding R&D Needs

**Enhanced Methods to Assimilate Increasing Volume of Remote Sensed Data**
**Develop Small-scale Assimilation Techniques and Deploy Obs Database**
**Improve High Resolution Physics**
**Improved Hydrological-Ocean-Atmosphere coupling***** ***
**Develop Mesoscale Verification Techniques**
**Improved Methods to Convey Confidence Levels and Range of Probabilities**
***Reduced Model Biases***
***Merge Ensembles with High-Resolution Models ***

**Notes:**

Assimilation: We expect a 10,000 fold increase in satellite data in the next 10 years

Mesoscale Assimilation:  Better use of data to support future res. Requirements

HR physics: Eg: Reliable cloud-scale models, current physics were designed for coarser scale (greater
Than ~10 km) resolution

## Numerical Prediction  Infusion Strategy

**Emphasize Partnerships**
***WRF; ESMF (NOAA, NCAR, FAA,  AFWA, Navy, NASA, Universities)***
**Develop Common Architecture**** **
***Common Model/Data Assimilation Framework***
**WRF, Radiative Transfer Models, ESMF**
***Multi-disciplinary Coupled Codes ***
**Atmosphere, Hydrologic, Ocean, AQ**
***Teragrid Concept for Increased Data Nodes***
**Implement Modeling Testbed**
***JCSDA***
***NOAA/NCAR DTC***

**NWS**

**Aviation**

**Coastal**
**Marine**

**Severe**

**Observations**

**NWP**

**Climate**

**Satellite**

**Hurricane**

**Universities****,**
**Labs, Other**

**Universities,**
**Labs, Other**

## Numerical PredictionTowards a Common Modeling Infrastructure 

**Weather Research and Forecast (WRF) Model**
**State-of-the-Science, *****Common Infrastructure System***
**Supporting Advanced Regional- to Local-Scale Research & Operational Forecasting **
**More Effective and Timely Transition of Research                                          into Operations**
**Partners:  NOAA, NCAR, USAF, USN, FAA**
**Unified Global, Climate and Mesoscale       Numerical Forecast System**
**Improve Climate/Global/Weather predictions**
**	**

## Numerical Prediction WRF Framework  Supports Deterministic & Probabilistic Forecasts

**Numerical Prediction ***WRF Framework  Supports Deterministic &** Probabilistic Forecasts*

**WRF Core 2**

- GLOBAL

**(ESMF)**

**WRF Core 3**

**WRF Core 1**

**Data Assimilation**
**   **

**SREF**

**Initial**
** ****Conditions **
**& **
**Ensemble**
** ****Perturbations**

**Physics Options**

***Aviation Marine Tropical    Severe Storms Winter Wx***

***Hydrologic  Air Quality  Hazards***

**Notes:**
WRF framework also supports the probabilistic modeling developments.
Global models currently drive the regional model forecasts so is outside the WRF infrastructure
The various WRF cores will produce individual deterministic model forecasts for specific applications. These individual solutions would then make up the SREF.
In the upcoming years, we envision a common core for Climate/global/regional environmental applications.

## Numerical Prediction Infusion Strategy: Testbed

**Developmental**
**Test Centers**

**Operational**
**Test Centers**

**NCAR**

**OAR**

**NCEP**

**FNMOC**

**AFWA**

**Universities**
**&**
**Labs**

**WRF **
**Contributed **
**Code**

**WRF **
**Reference **
**Code**

**WRF **
**Operational **
**Code**

**NRL**

## Numerical Prediction Summary

**Numerical Prediction**** *****Summary***

**2007**

**2012**

**Increasing Performance**

**2020**

**2002**

_**R&D Needs**_
**Assimilation of Increasing Volume of Remote Sensed Data**
**Small-scale Assimilation Techniques**
**Improved Representation of Non-Hydrostatic Scale Physics ****	**
** ****Probabilistic Approaches**
**Mesoscale Verification Techniques**

- Supporting NWS Service missions

## Back Ups

** ****Roadmaps**
** ****Resolution Time-Series**
** ****Observational Needs**

## Data Assimilation Roadmap

## Numerical Prediction Roadmap

_***20002***_

_***2004***_

## Architecture Key S&T NP Timeline

- Deployment

- OTE

- DTE

- R&D

**GFS 95kL42  SREF 48kL50**

**Probabilistic**

**Multi-model 70kL60 SREF 12kL64**

**Ocean**

**North America (4x/day)**

**Cpld 80kL64 Annual**

**AGCM 381k28L  7mo-1/mon**

**Climate (1/mon)**

**SFM 95kL64**

**HRW (1x/day)**

**NMM 8kL64 48h/3 h**

**Global (4x/day)**

**GFS 55k64L**
**384h/3h**

**GFS 45k64L 384h /1h**

**Cpld 30kL100  **

**RUC 20kL50/12h**

**RRW (8x/day)**

**ROFS 20k/Atl 48h/ 24h**

**GFS 90kL42 SREF 18kL60**

**Eta 12k64L**
**84h/3h**

**RRW 11kL60/12h**

**RRW 8kL70/18h 12x**

**WRF 8k70L**
**84h/1h**

**WRF 4k/100L**
**96h/1h**

**WRF6kL70 48h/2 h**

**WRF 2k/100L 48h/1 h**

**ROFS 20k/glb 5 day**

**Cpld 20k/glb 2 week**

## Numerical Prediction AdvancesResolution and Ensemble Members

**2003**

**2007**

**2012**

**Physics**

**Dta Assim**

**Regional**

**Global**

**Numerical Prediction Advances****Resolution and Ensemble Members**

## Numerical Prediction AdvancesSupercomputing Increases

**Numerical Prediction Advances****Supercomputing Increases**

_***FY03: 1408 ***_
_***1.3 Ghz SP Processors***_

**Notes:**
Increasing volume of data (10000x)
200x increase in computer storage size...will need advanced data reduction, visualization techniques
Extract maximum information  given expected computer  increases (40x)

## Numerical PredictionKey Observational Gaps and S&T Solutions

| Observational GAP | Projected Solution | Expected Impact |
| --- | --- | --- |
| Mesoscale wind thru troposphere
 (highest res in PBL) | Better use of existing obs Enhanced ACARS/MDCRS
Space borne wind lidars, NPOESS
Upgrade NOAA profilers | Improved accuracy of short-term trop. Wind forecasts
 |
| Mesoscale moisture especially in PBL | WVSS-2/AMDAR upgrades
GPS IPW | Improved accuracy of short-term cloud, visibility, temperature forecasts |
| Improved observations in data sensitive areas | Targeted observations methods | Improved winter/tropical storm prediction |
| Improved cloud properties observations | Dual pole radars
88D superobs
GIFTS | Improved storm & cloud analysis and prediction |
| Improved  land/water/ snow surface roperties | NPOESS
 COOP modernization | Improved hydrologic & short term temperature forecasts  |

## Ensemble Forecasts

**Ensembles can provide**
**information on the likely**
**range of forecast parameters**
**and forecast uncertainty **
**to users**

**Mean value**

**Range**

**Ensemble**
**spread can**
**be used to **
**determine**
**how observational**
**data influences **
**neighboring **
**regions in**
**data assimilation**
**schemes**

## Next-Generation Operational Models

- Cloud-scale Modeling
- (dx = dy = 2 km, dz = 500 m, dt = 12 s, 160 x 160 x 20 km domain )
- Surface temperature, surface winds and cloud field at 2 hours

**Many Science and Technology Questions Remain**

## Potential Cloud-scale model benefits

**Notes:**
Storm-scale can help predict intensity changes/development of svr wx

## Numerical Prediction AdvancesDissemination Requirements2007

**Numerical Prediction Advances****Dissemination Requirements****2007**

## Current Operational Forecast Models

***Operational forecast models predict:***
**Mesoscale and synoptic flow patterns**
**Precipitation via parameterizations that are unable to resolve individual storms**
***Important storm-scale weather cannot be resolved******:***

## Towards a

- _[Towards a](slide8.xml)_
- _[Coupled](slide8.xml)_
- _[Modeling ](slide8.xml)_
- _[System](slide8.xml)_
*with*
*downscaling to*
*hydrology models*

***SST***
***PREDICTION***

***GENERAL***
***CIRCULATION***
***LATERAL***
***B.C.***

*REGIONAL*
*COUPLED*
*ATMOS-LAND*
*MODEL*
*10 - 30 km*

***PRECIP, Ts,***
***LAND-SFC***
***FORCING***

*REGIONAL*
*UNCOUPLED*
*LAND-HYDRO*
*MODEL*
*1-10 km*

***RUNOFF***
***SNOWPACK***
***STREAMFLOW***
***SOIL MOIST***

*GLOBAL*
*COUPLED*
*ATMOS-LAND*
*MODEL*
*30 - 100 km*

***GLOBAL***
***LAND***
***4DDA***

***GLOBAL***
***ATMOS***
***4DDA***

***GLOBAL***
***OCEAN***
***4DDA***

***REGIONAL***
***LAND***
***4DDA***

***REGIONAL***
***ATMOS***
***4DDA***

*GLOBAL*
*COUPLED*
*OCEAN-ATMOS*
*LAND MODEL*
*100 - 500 km*

## Slide 29