Note: PRIORITY USE CASES / themes

1. Aviation
2. Hydrometeorology
3. Climate science

Institutional Use Cases

These use cases are meant to document a set of scenarios/stories that may be used to identify requirements on a conceptual model to meet institutional goals of today and the future. Within the conceptual modelling activity, they will be used to identify the information types and queries that are required, in order to develop a common domain model that enables interoperability and re-use between the main stakeholder communities (operational meteorology, aviation meteorology, research, climate, EC INSPIRE).

Actors

Actors in the use cases below include:

• Operational MET Provider
• Commercial MET Provider
• MET Research Institution
• The general public
• Air Traffic Managment (ATM) System
• ATM System Maintainer
• MET Data Verification System

Another set of use cases focussed on view services/WMS can be found at the page WmsInteropExperimentUseCases.

Exclusions

• The following factors should be excluded from the use-cases (for now) as we are attempting to define the conceptual data models rather than the entire system environment for data management:

1. data publication
2. data discovery
3. format concerns - i.e. choice of binary XML for efficient transfer
4. ...

• Our focus should be on:

1. information content
2. user communities who need to interact with the data
3. query expression to access the data

Use Cases

These are the harmonised use cases for the MetOcean DWG and INSPIRE TWG AC-MF (Thematic Working Group on Atmospheric Conditions and Meteorological Features). Each use case is owned by an individual. Where there is a correspondence between the MetOcean and INSPIRE use cases, then a single use case will be developed and used by both modeling groups.

MetOcean Use Case	INSPIRE Use Case	Editor / Owner	Category	Notes on Harmonisation
1: Future Aviation	-	AaronBraeckel	Aviation
2: Current Aviation	-	PeterTrevelyan	Aviation
3: Severe Weather Warning Service	-	BruceWright	Emergency Response	Original use case focussed on routine severe weather forecasting kept.
4: Multi-Model Ensemble Forecasting to Reduce or Mitigate Impacts of Landfalling Hurricane	-	JohnSchattel	Emergency Response
5: Routine Decision Support for Winter Highways Maintenance	-	FredericGuillaud	Routine Decision Support
6: Seasonal, Decadal & Climate Prediction Impact Assessment	IUC4: Use of Climate Change Scenarios	BruceWright	Routine Decision Support	UC6 extended into decadal & climate prediction, with removal of climate record and specific example of agriculture in India
7: Climate Assessment based on Past Data	IUC3: Climate Assessment (past data)	JeremyTandy	Routine Decision Support	UC7 re-focussed climatology, with removal of climate prediction and specific example of economic development in sub-saharan Africa
8: Integration of Weather Data with Efforts to Combat Wildfires	-	JohnSchattel	Emergency Response	Renamed to make this specific to Wild Fires, as Emergency Response covered in other uses cases
9: Sustained Environmental Science Campaign	-	AndrewWoolf	Environmental Science Campaign
10: Automated Steering of High-resolution Local Weather Forecast Models	-	BenDomenico	Routine Forecast Production
11. Flood Forecasting	IUC2: Flood Forecasting	TBD	Emergency Response	UC11 extended to cover range of flooding forecasting scenarios, not just use ensembles. Interface with Hydrology (i.e. OGC Hydrology DWG and INSPIRE Annex 1 Hydrography TWG) needs to be carefully managed
12:Plume Forecasting in Support of Emergency Response	IUC1: Use of Meteorology in Support of Emergency Response (Plume Forecasting)	BruceWright	Emergency Response	As the INSPIRE use case is now specific to Plume forecasting, it has been included as a new case on the harmonised list

Use Case Categories

Below is a proposal to categorise the use cases, with a further sub-categorisation, with details, where known.

Category	Sub-category	Further Detail	MetOcean Use Case
Aviation	Future Aviation	Airport Weather, Optimal Flight Path	1: Future Aviation
	Current Aviation		2: Current Aviation
Routine Forecast Production	?	?	10: Automated Steering of High-resolution Local Weather Forecast Models
Emergency Response	Severe Weather Elements	Wind, Rain, Snow, Ice, Extreme High or Low Temperatures, Thunderstorms, Tornadoes	3: Severe Weather Warning Service
	Hurricane	Track, Intensity, Landfall. Probabalistic, often using ensembles	4: Multi-Model Ensemble Forecasting to Reduce or Mitigate Impacts of Landfalling Hurricane
	River Flooding	Fluvial, but including Flash-Flood (in 'River Canyons') and Longer Term Flooding	11. Flood Forecasting
	Coastal Flooding	Height of Surge, Height of 'Total Water', Probability of Exceedence of Thresholds. "Storm-Surge" is the interaction of tides with action of wind and pressure; negative surges also important as a shipping hazard; Probabalistic estimates are obtained from ensembles	-
	Avalanche	Risk of Occurence	-
	Wildfire	Trigger Risk, Spread	8: Integration of Weather Data with Efforts to Combat Wildfires
	Plume	Fire, Chemical Release, Nuclear Release, Volcanic Eruption, Saharan dust (e.g. methodology for the identification of natural african dust episodes in PM10 and PM2.5, as the exceedances of the PM10 daily limit value need reporting under EU air quality legislation)	12:Plume Forecasting in Support of Emergency Response
Routine Decision Support	Forecast-based Decision Support	Most meteorological parameters	5: Routine Decision Support for Winter Highways Maintenance
	Climate Prediction Based Decision Support	Primarily temperature, Precipitation	6: Seasonal, Decadal & Climate Prediction Impact Assessment
	Climatology Based Decision Support	Most meteorological parameters	7: Climate Assessment based on Past Data
Environmental Science Campaign	Short Environmental Science Campaign	Small number ot organisations, lasting only a few days	-
	Sustained Environmental Science Campaign	Large international activity, involving a large number of organsations, lasting months	9: Sustained Environmental Science Campaign

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UC1: future aviation scenarios derived from NextGen Net Enabled Weather (NNEW) and Single European Sky (SESAR)

Current Owner	AaronBraeckel
Summary	Weather Providers jointly disseminate a distributed, standards-based set of authoritative products for aviation decision-making
User communities/actors	Operational MET Provider, ATM System, Commercial MET Provider, MET Research Institution, MET Data Verification System
Information types	Surface observations, area forecasts (e.g., AIRMETs, SIGMETs), aerial observations, radar observations, satellite, model data (wind, temperature, relative humidity, etc.), gridded aviation products (turbulence, icing, ceiling, visibility, convection, etc.), alerts
Query types	Retrieve data by geographic area, retrieve data by flight path (4-D trajectory), retrieve time series, discover authoritative data source, discover data provider for data product, discover service metadata, discover product metadata, discover ontological associations between weather information, subscribe for filtered weather data, subscribe for metadata updates

• NextGen_Net-Enabled_Weather_IT_CONOPS-Dec_8_2009.doc - This describes system-level use cases and below, and does not go very far into institutional goals

• This document attempts to describe the system by defining a set of non-overlapping examples such as:

1. 1.1.10 Integrating data from onboard aircraft weather radar into the 4D Wx cube
2. 1.1.11 Retrieve icing forecast product for aerodrome 'x'
3. 1.1.12 Retrieve wind-speed & direction forecast product for aerodrome 'x'
4. 1.1.13 Retrieve PIREPs for a flight path
5. 1.1.14 Retrieve turbulence conditions for a flight path
6. 1.1.15 Retrieve most severe wind conditions along a flight path
7. 1.1.16 Subscribe to volcanic ash alerts (AIR/SIGMET) for a specified flight path
8. 1.1.22 One month subscription to METAR data along a flight path
9. 1.1.23 Long-term subscription to icing hazards within 50-miles of aerodrome 'x'

• The main pair of 'host' use-cases seem to be:

1. 1.1.17 Monitor hazards in terminal approach airway
2. 1.1.18 Determine the optimal flight path deviation to minimize aviation hazards

• The former use-case (1.1.17) is similar to the Airport Weather use-case identified by BenDomenico - GALEON Airport Weather Use Case This document describes a weather data use case that involves examples of most of the atmospheric sciences data types. The use case and data categories are examined in terms of the various standard interfaces and protocols that could be involved in documenting the datasets and making the data and metadata available via standards-based web services.

• the latter use-case (1.1.18) should enable us to assert all kinds of complex issues around building a single 4D trajectory which has been synthesized from multiple 'domains' in the 4D Wx cube. Issues arise in terms of identifying the 'best-data' to choose where overlapping data sets are available; which has the priority? which is the best quality? etc.

UC2: current aviation operational meteorology services

Current Owner	PeterTrevelyan
Summary	Operational aviation is, in the main, underataken by specialist forecasters. These forecasters not only create forecast observations i.e. TAFS, but create a number of charts using observations, satellite and radar imagery and last, but not least NWP (numerical weather prediction data
User communities/actors	Operational MET Provider, ATM System, Commercial MET Provider, MET Research Institution, MET Data Verification System, Operational aviation forecaster
Information types	Surface observations, area forecasts (e.g., AIRMETs, SIGMETs), aerial observations, radar observations, satellite, model data (wind, temperature, relative humidity, etc.), gridded aviation products (turbulence, icing, ceiling, visibility, convection, etc.), alerts
Query types	Retrieve data by geographic area, retrieve data by flight path (4-D trajectory), retrieve time series, discover data provider for data product, discover service metadata, subscribe for filtered weather data and alert if cricitcal threshold reached.

• Development of ...

1. TAF, Many TAFS are now created using a "first guess" approach using site specific forecasts. The TAFS are then amended and by an aviation forecaster.
2. METARs are often created using an automatic component e.g temperature, but require an observer for cloud and current weather.
3. Low-level aviation charts; these charts are currently drawn by hand, but some have first guess objects e.g jet stream. These charts will increasingly be automated and in the not to distant future the "first guess weather objects" derived from NWP grids will be used without any further amendment. These charts will include text and bespoke graphics. It is likely that in the next ten years they will cease to be of any real use as the direct use of gridded data becomes more common.
4. WAFC aviation charts are similar to the low level charts, but include extra fields such as CAT (Clear Air Turbulence). These objects, including jets, tropopause heights and temperatures and convection will be increasingly created directly from the gridded data. In the next ten years the use of graphics to depict significant weather will diminish as the direct use of NWP data increases. It is important to remember that pictures are really only for qualitative use rather than quantative. The future of WAFC will with the exchange of aviation grids such as icing, turbulence etc as flight planning tools can use them directly.

UC3: Severe Weather Warning Service

Current Owner	BruceWright
Summary	Routine work at NMHSs in order to provide decision makers and citizens with accurate assessment on meteorological or hydrological hazards, observed or forecasted. This includes post-processing and visualization of observations and simulations results at all the scales, sensible weather objects diagnostic and vizualization. Finally, the forecaster delivers consumer-oriented reports or alerts.
User communities/actors	Forecaster at operational Meteorological and Hydrological Services (NMHSs), emergency decision-makers, citizens.
Information types	Observation's results of the physical properties of the atmosphere, usually classified according to the sensor type and the originating platform : ground observation (synoptic station, buoy, ...), upper air observation (radar, dropsond, aircraft), space observation (satellite). Results (often gridded data) of data assimilation, simulations or statistical processes at all the scales. Sensible weather objects (often dynamic features) at all the scales (and any other atmospheric patterns) detected or diagnosed. Consumer-oriented alerts and report.
Query types	Discover product and service metadata, retrieve spatio-temporal subsets (including time series) to be visualized, retrieve avaibility of spatio-temporal subsets, ask for processing (more or less complexes) on datasets, subscribe for data or metadata updates (including data quality or confidence).

• National-Weather-Service-operational-forecasting-for-severe-weather-warning-service.rtf - this use case is an attempt to collate much of the operational forecasting activity from observations collection through to global, regional and ensemble forecasting in support of an operational service delivery. I would have liked to add more details on the parameters that are exchanged within datasets, but I've run out of steam this evening! I also apologize in advance if I've got aspects of this activity wrong (subtly or otherwise) - I am an engineer rather than meteorologist I welcome additions to this version 0.1 -- JeremyTandy - 04 Feb 2010

• ThunderstormMonitoringServiceUseCase.doc - Use-case describing a thunderstorm risk monitoring service for the benefit of customers like farmers, green keepers, roadwork managers or outdoor festivals decision makers. This use-case involves "Sensible Weather Objects" data (automated diagnostic, forecaster assessment / enhancement , and delivery) FredericGuillaud - 10 Feb 2010

UC4: multi-model ensemble forecasting to reduce or mitigate impacts of landfalling hurricane

Current Owner	JohnSchattel
Summary	To deal with the uncertainties of a land falling hurricane/typhoon, multi-model ensembles (crisis area model) and probabilistic ocean and atmospheric forecast data provide useful decision support information
User communities/actors	Operational and commercial weather services (forecasters), Emergency response managers (government, industry, non-governmental relief organizations), aviation interests, the Public
Information types	Grids of numerous surface and upper-air atmospheric parameters over 14-day duration at 6-hour intervals, surface gridded analyses and upper-air observations, grids of ocean wave and storm surge for 24-hour window with an hourly temporal resolution, point-based probability distributions, images of storm inundation and probabilistic hurricane track
Query types	Operational weather service’s data collection and processing centre retrieves large volumes of model grids; forecaster workstation retrieves and displays grids of resulting multi-model consensus forecast; Emergency Manager’s Geographical Information System retrieves a subset of a storm surge grid; aviation community uses a flight planning tool to request and display TAF, METAR, and turbulence data; relief organization retrieves all warning advisories for their geographical area of responsibility, the public uses a web browser to display images of hurricane track

• multi-model_ensemble_forecasting_to_reduce_or_mitigate_impacts_of_potential_landfalling_hurricane.rtf - Draft use-case loosely based on a THORPEX / TIGGE scenario using multi-model ensembles to better predict the arrival of a landfalling hurricane. The use-case concludes by indicating how the operational forecasting services support the relief operation in the wake of the hurricane -- JeremyTandy - 06 Feb 2010

• More details of the processes undertaken by the forecasting centre assessing the potential hurricane landfall using probabilistic data can be found here: LandfallingHurricane (courtesy of JohnSchattel - based on scenario from NWS)

UC5: Routine Decision Support for Winter Highways Maintenance

Current Owner	FredericGuillaud
Summary	De-icing decision support service to highway maintenance organizations during a winter season to optimise use of resource, whilst ensuring safety
User communities/actors	Commercial Road Sensor Operator, Local Government Organizations Responsible for Highway Maintenance, Forecasting Centre, Road User
Information types	Road sensors observations, surface (synoptic) observations, radar imagery (precipitation), satellite imagery, gridded forecasts (high-resolution, including ensembles, downscaling, nowcasts), site-specific forecasts (including intelligent interpolation, specialist road surface modelling, statistical correction, forecaster modification), forecaster guidance (text), alerts (of threshold exceedence), road surface thermal mapping (from vehicle-mounted sensors), routes (road segment geometries), verification statistics, licencing conditions on sensor observations
Query types	Retrieve data by geographic area, retrieve data by route, retrieve data for set of points, retrieve time series (for any of the previous 3), retrieve route or site metadata, retrieve go / no go response (to ‘grit’ road) based on agreed business rules, subscribe to alerting service, speak to a forecaster

• winter_maintenance_of_highways_infrastructure.rtf: Use-case describing delivery of a de-icing decision support service to highway maintenance organizations during a winter season -- JeremyTandy - 06 Feb 2010

UC6: Climate Impacts

Current Owner	BruceWright
Summary	Use predictions of the future climate (with past climate data as a baseline) to assess the impacts and risks to particular organisations or systems. The process includes the baselining current climate risk for the specific domain against past data , and analysing the future climate risk using climate predictions, to allow the identification of adpation strategies.
User communities/actors	Climate consultants, User Communities including a wide range of organisation with interests such as Water, Agriculture, Food production, Ecosystems, Biodiversity, Utiltiies, Transport, Energy, Health, Economics, Natural disasters, Security
Information types	Primarily temperature & precipitation (but potentially a wide range of other parameter, eg. wind, humidity, pressure), in the form of long term averages (e.g. 10 year & 30 year), extremes and probabilities of exceeding threshold (of interest to the particular organisation/system). Data sources include climatalogical observation records, gridded climatologies, re-analyses, seasonal forecasts, decadal forecasts climate predictions (out to 2100).
Query types	TBA

Details of this use case are provided here: ClimateImpacts

UC7: Climate assessment based on past data

Current Owner	JeremyTandy
Summary	Correlation of climate models with historical weather events using data-assimilation methods to drive reanalyses. Enhanced past climate (climatological) data can be applied to diverse areas including Planning, Building, Agriculture, Energy, Communications, Human Health
User communities/actors	Data capture analysts, Climate researchers, Data archive custodians, Educators & students, Risk modelers
Information types	TBA
Query types	TBA

• This usecase is based on the acitivities of the Atmospheric Circulation Reconstruction over Earth (ACRE) initiative http://www.met-acre.org. In order to support the INSPIRE TWG, the ACRE scenario described here will be completemented by a number of user-stories of how to USE the past data / climatology for decision support. Details of this use case are provided here: ClimateAssessmentBasedOnPastData

UC8: Integration of Weather Data with Efforts to Combat Wildfires

Current Owner	JohnSchattel
Summary	Integration of weather data with efforts to combat wildfires improves the efficiency and effectiveness of emergency responder’s ability to protect lives and property
User communities/actors	Emergency response meteorologist, Emergency response managers, and Emergency response personnel
Information types	Mesoscale network surface observations (e.g. wind, humidity, temperature), weather satellite imagery, weather radar imagery, lightning imagery, probabilistic mesoscale model output including grids and probability time series valid at model grid points
Query types	Geographically subset and retrieve surface observations from a database, retrieve and zoom (which may trigger the retrieval of finer resolution data) weather satellite, radar, lightning images, retrieve model grids and model grid point data, issue annotations for imagery

• CaliforniaFireCase

• Also - the GEOSS African Wildfire Scenario is illustrative ... http://www.youtube.com/watch?v=3uh3cpULBQY

UC9: sustained environmental science campaign - e.g. International Polar Year

Current Owner	AndrewWoolf
Summary
User communities/actors
Information types
Query types

• Polar Year Use Case (word doc)

UC10: Automated Steering of High-resolution Local Weather Forecast Models

Current Owner	BenDomenico
Summary
User communities/actors
Information types
Query types

• Automated System for Steering High-resolution Models: This document describes a system of data and processing services that can be seen as a set of weather data use cases. The system has been in operation for a number of years and involved orchestrating several data and processing services. However, the system was built at a time when international interface standards were not mature enough for use in this context. At this point though, it may be worth revisiting this existing, operating system to asses whether it can serve as a model for the kind of system one would like to construct using standard protocols and interfaces.

UC11: Riverine Flood Forecasting using Meteorological Ensemble Forecasts

Current Owner	TBD
Summary
User communities/actors
Information types
Query types

N.B. tie-in with HydrologyDWG

(This is written by a meteorologist, so hydrologists may have to correct anything that jars.)

A large rainfall event, perhaps covering more than one watershed, causes a rise in river levels. As the rain runs off the land, river levels rise. Hydrological river basin models indicate severe flooding downstream requiring emergency action by the relevant authorities, such as evacuation and emergency flood defences.

In long rivers with relatively slow run off, observing the rainfall gives adequate prediction for downstream levels. However, if the run-off is fast and the river short and steep, a forecast of the rainfall could be used.

To give a probability estimate, an ensemble of parallel forecasts, say 50, are performed using marginally different starting conditions, but all within the range of observational errors. These are fed into a similar number of runs of the hydrological models to give a series of forecasts whose range and distribution can be used to assign probabilities of resulting scenarios.

A “Poor Man’s” version of this can be performed with one run of a well-understood meteorological forecast model, which then redistributes the forecast rainfall into a series of possible profiles to feed into the hydrological models. The distribution of the profiles would be based on historical statistics. This would not capture the extreme, unique, events that might occur, whereas the full ensemble might. It is well known that meteorological ensembles need to be diverse as possible the capture the full possible range of extreme events. This can be achieved by ensuring the full range of starting conditions, and also using a variety of models.

-- ChrisLittle - 22 Feb 2010

• FlashFloodWarningSystemUCDraft.doc: Sub-case on Flash-Flood urban warning integrated system (INSPIRE UC2 related)

-- FredericGuillaud - 16 Jul 2010

• INSPIRE TWG AC-MF Use Case 2 - Flood forecasting short and medium range (Raymond Sluiter, Version 1.0, July 2010)

Added by BruceWright - 19 Jul 2010

UC12: Plume Forecasting in Support of Emergency Response

Current Owner	BruceWright
Summary	Prediction of plume for Fire (e.g. fire at a chemical plant or oil refinery), Chemical Release (e.g. chemical spillage or a road traffic accident in which a hazardous substance has either escaped or ignited), Biological Incidents (e.g. foot & mouth, blue tongue), Nuclear Release (e.g. accident at nuclear power plant), Volcanic Eruption (i.e. prediction of ash plume), covering the evolution over a wide range of timescales in support of Emergency Services to allow safe approach, plan evacuations, etc.
User communities/actors	Citizens (General Public), "Category 1 Responders" (e.g. emergency services, local authorities, health service bodies), "Category 2 Responders" (e.g. health and safety bodies, transport and utility companies), Emergency services strategic command and control centre (e.g. Gold Command in UK), Central government crisis response committee (Cabinet Office Briefing Room (e.g. COBR in UK), Forecast advisors (e.g. Public Weather Service (PWS) Advisors at Met Office), Forecast production unit (e.g. Environment Monitoring and Response Centre (EMARC) at the Met Office)
Information types	TBA
Query types	TBA

Details of this use case are provided here: PlumeForecastingForEmergencyResponse

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Note on Harmonisation of the INSPIRE TWG AC-MF and OGC Met-Ocean DWG Conceptual Modelling use cases

JeremyTandy and BruceWright reviewed the INSPIRE Thematic Working Group for Atmospheric Conditions & Meteorological Geographical Features (TWG AC-MF) use cases (currently 4) and the OGC Met-Ocean Domain Working Group (MO.DWG) Conceptual Modelling use cases. This resulted in the harmonised use cases above.

However, there are still a number of potential issues with this set:

• "3: Use of Meteorology in Support of Emergency Response" is now rather large, with multiple interests
• The owners are not necessarily well aligned with INSPIRE TWG current allocation of work

So this is still very much an initial proposal for those members of both the MO.DWG and the TWG AC-MF to comment on or revise.

Other Use Case Information

Previously linked under UC8:

• As general background, please see the attached presentation which describes two emergency response scenarios that the UK Met Office have faced in previous years: PDF or PowerPoint -- JeremyTandy - 06 Feb 2010

From the original UC6: seasonal forecasting for agriculture in India (JeremyTandy)

• seasonal_forecasting_for_agriculture_in_India.rtf: High-level use case indicating how seasonal forecasts and climate records might support micro-insurance services for rural agriculture

From the original UC7: climate impact assessment for economic development in sub-saharan Africa (JeremyTandy)

• [climate_impact_assessment_for_economic_development_in_sub-saharan_Africa.rtf: High-level use case indicating how future climate predictions & historical reanalyses may support an economic development project. I must point out this this use-case is hypothetical and lacks any real knowledge on my part. This use case could be inaccurate or misleading! Please update the text to help convert this scenario into something that resembles reality.

Original version of use case harmonisation for information only:

• Harmonised TWG AC-MF & Met-Ocean DWG Use Cases