A Community Meeting on Real-time and Retrospective Mesoscale Objective Analysis: An Analysis of Record Summit Can research and operations work together on this problem? Can research and operations work together on this problem? Are there clearly definable requirements and objectives? Are there clearly definable requirements and objectives? Can we make a compelling argument? Can we make a compelling argument? If so, to look beyond here – what next? If so, to look beyond here – what next?

The First Step: Translating Needs to Requirements Many applications require the current and past states of the atmosphere near the surface at high spatial and temporal resolution. Many applications require the current and past states of the atmosphere near the surface at high spatial and temporal resolution. What does an analysis of record represent? What does an analysis of record represent? Can one analysis of record meet all needs? Can one analysis of record meet all needs? Local analyses vs. national productsLocal analyses vs. national products Real-time vs. retrospective analysesReal-time vs. retrospective analyses Resolution issuesResolution issues What spatial and temporal resolution? What spatial and temporal resolution? Averages vs. extremes in time/space? Averages vs. extremes in time/space? Parameter issues (temperature, precipitation, etc.)Parameter issues (temperature, precipitation, etc.)

To what extent can these requirements be met given existing scientific understanding, technologies, and resources? To what extent can these requirements be met given existing scientific understanding, technologies, and resources? What can be learned from the scientific literature and current applications?What can be learned from the scientific literature and current applications? What are the strengths and weaknesses of existing methodologies?What are the strengths and weaknesses of existing methodologies? What observational data sets are most critical?What observational data sets are most critical? What limitations are imposed by the existing and future observational data assets vs. those available in the past?What limitations are imposed by the existing and future observational data assets vs. those available in the past? What limitations are imposed by an underlying model? Sensitivity to boundary layer parameterizations, soil moisture, clouds, etc.?What limitations are imposed by an underlying model? Sensitivity to boundary layer parameterizations, soil moisture, clouds, etc.? What are the realistic options for real-time and retrospective analyses within the next year or two?What are the realistic options for real-time and retrospective analyses within the next year or two? Are there some aspects that are easier to accomplish than others? Real-time vs. retrospective? Specific variables (temperature vs. precipitation)Are there some aspects that are easier to accomplish than others? Real-time vs. retrospective? Specific variables (temperature vs. precipitation) How can the quality of analyses be assessed? What are appropriate measures of skill?How can the quality of analyses be assessed? What are appropriate measures of skill? The Second Step: Science, Technology, and Resource Inventory

What are the critical scientific issues that must be faced in order to successfully develop quality analyses at high spatial/temporal resolution? What are the critical scientific issues that must be faced in order to successfully develop quality analyses at high spatial/temporal resolution? What additional R&D and resources are needed? What additional R&D and resources are needed? Possible outcomes of this meeting? Possible outcomes of this meeting? USWRP report based on recommendations from workshop and additional feedback from operational, research, and user communitiesUSWRP report based on recommendations from workshop and additional feedback from operational, research, and user communities Permanent NOAA/USWRP committee formed to continue advocacy for analysis of recordPermanent NOAA/USWRP committee formed to continue advocacy for analysis of record Propose fast-track implementation plan to provide AOR soonPropose fast-track implementation plan to provide AOR soon Develop long-term clearly-defined project plan with compelling argumentsDevelop long-term clearly-defined project plan with compelling arguments Propose funding opportunities and resources be sought to facilitate research projects from NWS, NSF, and other agenciesPropose funding opportunities and resources be sought to facilitate research projects from NWS, NSF, and other agencies Advocate long-term funding from NOAA/NWS and other agencies for implementation of AOR beginning FY 07Advocate long-term funding from NOAA/NWS and other agencies for implementation of AOR beginning FY 07 The Third Step: Recommendations and Outcomes

Meeting Format Overview talks (operations and research) Overview talks (operations and research) Review talks from recent USWRP workshops Review talks from recent USWRP workshops Plenary sessions Plenary sessions Current capabilitiesCurrent capabilities Data specific applicationsData specific applications Kalman Filter applicationsKalman Filter applications Future strategies (EMC, FSL)Future strategies (EMC, FSL) Breakout groups Breakout groups Operational requirementsOperational requirements Data and verificationData and verification Assimilation strategies and techniquesAssimilation strategies and techniques

Analysis of Record Issues: Operational Perspective Brad Colman NOAA/National Weather Service Seattle, Washington

Key questions What is driving the current operational demand for a skillful, real-time mesoscale objective analysis? What is driving the current operational demand for a skillful, real-time mesoscale objective analysis? What are the specific requirements of a real-time effort to meet these demands? What are the specific requirements of a real-time effort to meet these demands? Where can science and/or analysis capabilities influence or help define specific forecast elements? Where can science and/or analysis capabilities influence or help define specific forecast elements?

Your National Weather Service Goes Digital

National Digital Forecast Database (NDFD) A national database of digital weather forecast information A national database of digital weather forecast information Designed to meet the fundamental weather information needs of industry, media, commercial weather services, academia, and public Designed to meet the fundamental weather information needs of industry, media, commercial weather services, academia, and public Includes multiple delivery formats, e.g., via the web for user-selectable location specific forecasts or downloadable National data files Includes multiple delivery formats, e.g., via the web for user-selectable location specific forecasts or downloadable National data files

National Digital Forecast Database Mosaic forecasts for the entire country or regional domains Mosaic forecasts for the entire country or regional domains Public, marine and other products available Public, marine and other products available Can be integrated with GIS mapping Can be integrated with GIS mapping It’s aggressive and represents a major paradigm shift in the way field forecasters produce their forecasts.

Interactive Forecast Preparation System (IFPS) Grid resolution (variable) Grid resolution (variable) 5 km today, 2.5 km being discussed within the next year (down to a “neighborhood” scale)5 km today, 2.5 km being discussed within the next year (down to a “neighborhood” scale) Basic building block for the weather element grids is 5 x 5 km spatial and 1 hour temporalBasic building block for the weather element grids is 5 x 5 km spatial and 1 hour temporal Numerical weather prediction inputs Numerical weather prediction inputs Relatively coarse horizontal and verticalRelatively coarse horizontal and vertical “SmartInit” process to downscale and generate sensible elements“SmartInit” process to downscale and generate sensible elements Integration of point MOS guidanceIntegration of point MOS guidance Forecaster inputs and adjustments Forecaster inputs and adjustments Generally iterative (w/o fresh model data)Generally iterative (w/o fresh model data) Graphical editing toolsGraphical editing tools “SmartTool” scripts“SmartTool” scripts

So, what is missing from this new forecast process? A forecast matching (or defining) analysis for: A forecast matching (or defining) analysis for: VerificationVerification A starting point for short-term forecastsA starting point for short-term forecasts Resource management decisionsResource management decisions Other operational applications: Other operational applications: Retrospective analyses and climate (25 years?)Retrospective analyses and climate (25 years?) MOS and other post-processing techniquesMOS and other post-processing techniques Analysis of Record!

Analysis of Record NWS motivation: Real-time seamless verification Real-time seamless verification Provide forecasters useful feedback Provide forecasters useful feedback Give forecasters a way to assess the initialization and performance of NWP models Give forecasters a way to assess the initialization and performance of NWP models Serves as input to the GFE for use in short- term forecasts Serves as input to the GFE for use in short- term forecasts Contributes to the ongoing development of a gridded climatology Contributes to the ongoing development of a gridded climatology Building block for new MOS applications Building block for new MOS applications Hydrology applications Hydrology applications

But, this is also a community problem Mesoscale model development and verification Mesoscale model development and verification Transportation management Transportation management Emergency management and response Emergency management and response Hindcast testing of data assimilation schemes Hindcast testing of data assimilation schemes Private sector requirements Private sector requirements Homeland defense Homeland defense Regional climate studies Regional climate studies Etc. Etc.

Surface Transportation Weather Observational Requirements Paul A. Pisano Team Leader, Road Weather Management Federal Highway Administration

Surface Transportation Weather - Requirements The surface transportation forecast challenge: Fine-scale models with the horizontal resolution of a transportation corridor (e.g., an interstate highway) More detailed forecast output in the Nowcast timeframe (0-3 hr) Update rates on the order of minutes The ability to assimilate vast quantities of real-time mobile data Specialized sub-processes that predict such roadway hazards as: Precipitation start/stop times Precipitation type and phase changes Roadway icing (precipitation accumulation) Roadway icing (frost deposition and black ice formation) Reduced visibility in fog, precipitation or smoke Driver level wind direction and speed Driver level wind character (gustiness)

Key questions What is driving the current operational demand for a skillful, real-time mesoscale objective analysis? What is driving the current operational demand for a skillful, real-time mesoscale objective analysis? What are the specific requirements of a real-time effort to meet these demands? What are the specific requirements of a real-time effort to meet these demands? Where can science and/or analysis capabilities influence or help define specific forecast elements? Where can science and/or analysis capabilities influence or help define specific forecast elements?

Core parameters for Initial Operating Capability of NDFD max/min temp max/min temp temperature temperature dew point dew point relative humidity* relative humidity* max/min RH * max/min RH * heat index* heat index* wind chill* wind chill* floating PoP12 floating PoP12 prob of precip. (12h)* prob of precip. (12h)* sky cover sky cover wind direction and speed wind direction and speed * Indicates a derived parameter wind gusts (>10 kts over sustained) wind gusts (>10 kts over sustained) 20 ft. wind * (NWS regional option) 20 ft. wind * (NWS regional option) Lightning Activity Level (LAL) Lightning Activity Level (LAL) weather (type, intnsty, prob/covrg) weather (type, intnsty, prob/covrg) snow amount snow amount significant wave height significant wave height visibility visibility

General Forecast Element Matrix The 0-hour field is missing – we feel this should be an actual product

Considerations: Considerations: Be at the same resolution (both spatial and temporal) as the forecast gridsBe at the same resolution (both spatial and temporal) as the forecast grids Incorporate data from all sources: RAWS, COOP, satellite, radar, lightning detectionIncorporate data from all sources: RAWS, COOP, satellite, radar, lightning detection Be as independent from the NWP models as possibleBe as independent from the NWP models as possible Potential directions: Potential directions: A collaborative effort will likely be needed between the NWS, ERL, private sector, and universitiesA collaborative effort will likely be needed between the NWS, ERL, private sector, and universities Opportunities for outsourcing should be exploredOpportunities for outsourcing should be explored External peer-review process will be beneficialExternal peer-review process will be beneficial A long-term effort is required for optimal skill. But work should begin now on initial fast-track capabilityA long-term effort is required for optimal skill. But work should begin now on initial fast-track capability

Key questions What is driving the current operational demand for a skillful, real-time mesoscale objective analysis? What is driving the current operational demand for a skillful, real-time mesoscale objective analysis? What are the specific requirements of a real-time effort to meet these demands? What are the specific requirements of a real-time effort to meet these demands? Where can science and/or analysis capabilities influence or help define specific forecast elements? Where can science and/or analysis capabilities influence or help define specific forecast elements?

What do science and objective analysis techniques tell us about: presenting a gridded forecast to users? presenting a gridded forecast to users? Grid-box average vs. grid-point?Grid-box average vs. grid-point? expressing uncertainty within the grid box?expressing uncertainty within the grid box? deriving sensible weather elements from raw NWP output? deriving sensible weather elements from raw NWP output? weather elements that are uniquely defined by techniques and/or measurements? weather elements that are uniquely defined by techniques and/or measurements? Sky cover (METAR cig limitations, satellite, etc.)Sky cover (METAR cig limitations, satellite, etc.) Wind and wind gustsWind and wind gusts Maximum and minimum temperaturesMaximum and minimum temperatures

AMS 1 st National Weather and Climate Enterprise Partnership Summit Follows from NRC report “Fair Weather, Effective Partnerships in Weather and Climate Services.” Follows from NRC report “Fair Weather, Effective Partnerships in Weather and Climate Services.” Part of AMS effort to serve as a neutral host Part of AMS effort to serve as a neutral host 27/28 July 2004, Dallas-Fort Worth 27/28 July 2004, Dallas-Fort Worth “Developing a National Mesoscale Observing Network: Fundamental Questions.” “Developing a National Mesoscale Observing Network: Fundamental Questions.” Targets the process necessary to achieve a National mesoscale network Targets the process necessary to achieve a National mesoscale network

Critical Questions (1) What can be learned from the literature and applications of existing methodologies as far as benefits and limitations of a particular approach that may be advocated for an analysis of record? (2) What are the critical issues that must be faced in order to successfully develop a quality analysis of record at spatial scales of km every hour? (3) Are there some aspects of an analysis of record effort that are more straightforward to accomplish than others, i.e., specific variables (temperature vs. precipitation), real-time analyses vs. retrospective analyses? (4) To what extent will the analysis of record be constrained by limitations of the existing and future observational data base vs. that available in the past? What observational data sets do we view to be most critical? (5) To what extent will the analysis of record be constrained by limitations of an underlying model? Sensitivity to boundary layer parameterizations, soil moisture, clouds, etc.? (6) What are appropriate measures to assess the skill of an analysis of record on these spatial and temporal scales? (7) What are the resource implications of a particular method?

EMC’s AOR Concept Can’t just apply 2-D analysis (variational or otherwise) to surface data - we might have 10,000’s of mesonet/surface obs, B U T we have millions of AOR grid points Can’t just apply 2-D analysis (variational or otherwise) to surface data - we might have 10,000’s of mesonet/surface obs, B U T we have millions of AOR grid points Need a 3-D forecast model to obtain temporally consistent solution dictated among observed data, terrain & lower boundary forcing and synoptic forcing Need a 3-D forecast model to obtain temporally consistent solution dictated among observed data, terrain & lower boundary forcing and synoptic forcing Propose to apply tried & true NCEP 4-D data assimilation technique of forecast-analysis cycle at high resolution (~2 km) with cost cutting measures to make feasible in production Propose to apply tried & true NCEP 4-D data assimilation technique of forecast-analysis cycle at high resolution (~2 km) with cost cutting measures to make feasible in production

EMC’s AOR Concept NCEP’s 4DDA will (like the EDAS) use NCEP’s 4DDA will (like the EDAS) use Full complexity of NOAH Land-Surface ModelFull complexity of NOAH Land-Surface Model Assimilation of observed precipitation data to ensure lower-boundary states are optimalAssimilation of observed precipitation data to ensure lower-boundary states are optimal NCEP will use WRF-NMM as assimilating model to efficiently include NCEP will use WRF-NMM as assimilating model to efficiently include Nonhydrostatic effects in the dynamicsNonhydrostatic effects in the dynamics Terrain following coordinate (hybrid sigma- pressure replaces step-mountain eta)Terrain following coordinate (hybrid sigma- pressure replaces step-mountain eta) Nudging (not in any of NCEP current models)Nudging (not in any of NCEP current models)

EMC’s AOR Concept AOR’s emphasis is on sensible weather elements AOR’s emphasis is on sensible weather elements Focus AOR on surface & sensible weather where we have majority of mesoscale observations Focus AOR on surface & sensible weather where we have majority of mesoscale observations To save cost, reduce vertical resolution away from surface (run with levels instead of current 60 levels) To save cost, reduce vertical resolution away from surface (run with levels instead of current 60 levels) To compensate for less vertical, nudge prediction away from sfc to an existing solution provided by operational North American Mesoscale run (currently 12 km Eta but 10 km WRF-NMM by late FY2005) To compensate for less vertical, nudge prediction away from sfc to an existing solution provided by operational North American Mesoscale run (currently 12 km Eta but 10 km WRF-NMM by late FY2005)

Analysis of Record ISST has identified this as our number one priority ISST has identified this as our number one priority Immediate goal: Determine operational requirements, science and R&D issues that need to be addressed, potential roadblocks, and strategy for implementation. Need to get this on a fast track! Immediate goal: Determine operational requirements, science and R&D issues that need to be addressed, potential roadblocks, and strategy for implementation. Need to get this on a fast track!

National Digital Forecast Database targets a spectrum of weather information users More weather data More weather data Higher resolution forecasts Higher resolution forecasts Visual displays of probability Visual displays of probability User-defined products create business opportunities User-defined products create business opportunities Different Products for Different Customers TODAY...RAIN LIKELY. SNOW LIKELY ABOVE 2500 FEET. SNOW ACCUMULATION BY LATE AFTERNOON 1 TO 2 INCHES ABOVE 2500 FEET. COLDER WITH HIGHS 35 TO 40. SOUTHEAST WIND 5 TO 10 MPH SHIFTING TO THE SOUTHWESTEARLY THIS AFTERNOON. CHANCE OF PRECIPITATION 70%. The public, emergency managers and city planners use WWW. graphic products for detailed forecasts Commercial weather companies & emergency managers use grids to generate tailored products Radio stations & public read text forecasts

User-Generated Products New Forecasting Process InteractiveInteractive CollaborativeCollaborative Information OrientedInformation Oriented NWS Automated Products Text Graphic Digital Voice TODAY...RAIN LIKELY. SNOW LIKELY ABOVE 2500 FEET. SNOW ACCUMULATION BY LATE AFTERNOON 1 TO 2 INCHES ABOVE 2500 FEET. COLDER WITH HIGHS 35 TO 40. SOUTHEAST WIND 5 TO 10 MPH SHIFTING TO THE SOUTHWESTEARLY THIS AFTERNOON. CHANCE OF PRECIPITATION 70%. National Digital Forecast Database Local Digital Forecast Database Field Offices National Centers Collaborate Data and Science Focus National Centers Model Guidance Grids

Traditional Forecasting Process Schedule DrivenSchedule Driven Product OrientedProduct Oriented Labor IntensiveLabor Intensive National Centers Generate Graphical Products National Centers Model Guidance Field Offices Type Text Products TODAY...RAIN LIKELY. SNOW LIKELY ABOVE 2500 FEET. SNOW ACCUMULATION BY LATE AFTERNOON 1 TO 2 INCHES ABOVE 2500 FEET. COLDER WITH HIGHS 35 TO 40. SOUTHEAST WIND 5 TO 10 MPH SHIFTING TO THE SOUTHWESTEARLY THIS AFTERNOON. CHANCE OF PRECIPITATION 70%. MARYLAND EASTERN SHORE EASTON PTCLDYCLOUDYPTCLDYPTCLDYSUNNYPTCLDY 60/5263/5465/4755/4055/3750/33 POP 20POP 20POP 20POP 20POP 10POP 10 MARYLAND EASTERN SHORE EASTON PTCLDYCLOUDYPTCLDYPTCLDYSUNNYPTCLDY 60/5263/5465/4755/4055/3750/33 POP 20POP 20POP 20POP 20POP 10POP 10 U.S. Drought Monitor Excessive Heat Products Threats Assessments

Taking Advantage of Technology Our Goal: To develop a new forecasting process and delivery system that will provide you with new and enhanced forecasts and multiple ways to receive NWS weather information

Surface Transportation Weather - Observations Better data sampling of the boundary Layer as a basis to resolve complex forecasting issues near the surface. New sampling technologies include (but are not limited to): Differential GPS/Integrated Precipitable Water RADNET “gap-filling, low-power” Phased Array Radars Driver level visibility and road obscurations from new CCTV algorithms Better freezing/frozen liquid equivalent observations from new sensor technologies (e.g., new Hot-Plate Precipitation Sensors) In-Vehicle sensors (air & road temperature, surface friction, precipitation rate, etc)