Power Industry Requirements for Atmospheric and Oceanic...

Economic ApplicationsThe First Thorpex Science Symposium

Montreal, Canada6 December 2004

Economic ApplicationsThe First Thorpex Science Symposium

Montreal, Canada6 December 2004

Mary Altalo, Chief ScientistEnterprise Solutions

Science Applications International CorporationMcLean Virginia, 22102

703-676-8432, [email protected]

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Your IT Business Partner to the Future

ConceptsConcepts

Markets are Diverse- Vertical DomainFunctional Areas are Similar- Cross cuttingNeeds are Universal- developed and developingDependencies between Weather and OperationsSequential Decision Making and Error PropagationCase Studies in the Energy IndustryCase Studies in the Tourism IndustryCase Study in Emergency ManagementCase Study for Developing Nations

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Provider-User ConceptProvider-User Concept

Data and Information

Knowledge andaction

ProvidersPush

UsersPull

Partnership

--Interpret user Interpret user Needs Needs

--SensitizeSensitizeMarket researchMarket research

Added Value

ResourceManagement Business

Research GovernmentTHORPEX National MetOcean Services

Technology goals Development Goals

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Dual-Use Market StructureDual-Use Market Structure

ResearchCommunity

GovernmentPolicy

Business(Domain orVerticals)

Natural Resourcemanagement

•Energy

•Water

•Tourism & Leisure

•Health

•Construction

•Transport

•Financial Services

•Defense

•Agriculture

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Thorpex and Functional Business Operations

Thorpex and Functional Business Operations

Critical Cross Cutting Functions for the Ensemble ForecastSupply/Demand Forecasting across All sectors (tactical)Revenue/Earnings/Shareholder value Forecasting (strategic)Incident (Emergency) Management (tactical)Policy Formulation and Governance (Strategic)

ProvidesAdvance Situational Awarenessfor Decision Support ( situation influence modeling, consequence assessment and Tactical Decision aids) for Optimal operational response (dispatch)Leading to Proactive Management Strategies and Policies

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Other sectorsOther sectors------other usesother uses

Case Studies:The Power Industry

Case Studies:The Power Industry

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MinutesMinutes

HoursHours

DaysDays

6 6 –– 10 Days10 Days

8 8 –– 14 Days14 Days

MonthsMonthsSeasonsSeasons YearsYears Forecast

UncertaintyForecast

Uncertainty

Fore

cast

Unc

erta

inty

Fore

cast

Unc

erta

inty

Forecast Lead TimeForecast Lead Time

••Load balancingLoad balancing••Electricity pricing/ tradingElectricity pricing/ trading••Outage/surge Outage/surge mngtmngt..••“Intelligent” infrastructure“Intelligent” infrastructure••“Neck metering”“Neck metering”••Dispatch managementDispatch management••Hazard responseHazard response••Platform operationsPlatform operations

••Customer billing serviceCustomer billing service••Pump load forecastingPump load forecasting••Fuel supply forecastingFuel supply forecasting••Energy switching strategyEnergy switching strategy••Distributed Distributed generatgenerat. . mngtmngt..••Maintenance schedulingMaintenance scheduling••Sequestration timingSequestration timing••Inventory managementInventory management••Pipeline throughput Pipeline throughput mngtmngt..••Tariff callingTariff calling

••Utility grid managementUtility grid management••Wind generation dispatch Wind generation dispatch ••HydoHydo supply managementsupply management••Ship/tanker routingShip/tanker routing••Refining operations Refining operations mngtmngt..••Pipeline laying logistics Pipeline laying logistics

••Sales/earnings forecastingSales/earnings forecasting••Energy storage replenishment strategiesEnergy storage replenishment strategies••“Flexible” energy production and delivery“Flexible” energy production and delivery••Storage requirements needs assessmentStorage requirements needs assessment••Storage logistics planningStorage logistics planning••Regional Energy Regional Energy mngtmngt. planning. planning••Stockpile planningStockpile planning••Seasonal demand forecastsSeasonal demand forecasts••Delivery rate settingDelivery rate setting••HydoHydo regional water regional water mngtmngt. Strategy. Strategy••Compliance projections estimatesCompliance projections estimates

••Infrastructure designInfrastructure design••Regional infrastructure planRegional infrastructure plan••New storage capacity plansNew storage capacity plans••Mitigation strategy designMitigation strategy design••Plant/ infrastructure sitingPlant/ infrastructure siting••Energy grid adaptation plansEnergy grid adaptation plans••Energy policy settingEnergy policy setting

Energy Operations Aided by Energy Operations Aided by Reductions in Environmental Reductions in Environmental Forecast Uncertainty Forecast Uncertainty

Critical forecast periodsSub day, 2-4 day, 90 day

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U.S. Utilities “Trial” AreasNOAA Funded Programs

U.S. Utilities “Trial” AreasNOAA Funded Programs

Entergy

MD PUCMEMA

Con Ed

SUNY

SDGE

CEC

PacifiCorp

The Northeast Energy Network Performance

Analysis

The Northeast Energy Network Performance

Analysis

University ofNew Hampshire

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The Setting for the Stakeholder Assessment

The Setting for the Stakeholder Assessment

New England Grid Operator (ISO NE) – weather impacts on short term load forecastingMajor Urban Utility (Con Ed) – weather impacts on distribution system loadsMajor state owned end user (SUNY)– use of weather forecasting to control day ahead electric prices and manage natural gas and electricity costs at state facilities

INTER and INTRA-REGIONAL ANALYSIS:

Independent Systems Operators

SITE SPECIFIC END-USERS:STATE CAMPUSES

LOCAL ASSESSMENTlarge Urban

utility

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Overall GoalOverall Goal

Examine the value of improvement in weather/climate forecast accuracy to major stakeholders in the Electric Power Value Chain (Sellers, Distributors, Buyers)Determine the precise requirements of the stakeholders for the improvements of decisions-”what do you do?”Establish the Impact of forecast accuracy on the operation and planning decisions of the IndustryExamine and Improve the Decision Support Tools of the User community to “institutionalize” informationDevelop the Stakeholder Advocacy through Awareness raising and Capability Building

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Diagnostic Approach to Assessing Vulnerability and Risk

Diagnostic Approach to Assessing Vulnerability and Risk

Project Objectives

Identify optimal NOAAproduct definitions supportingEnergy industry planningrequirements

Project Objectives


Task 1.Base CaseSituation Assessment•Project Initiation•Define Current Practice•Define Planning Needs•Evaluate current dataStrengths and weaknesses

Task 2.Gap Analysis•Apply “Perfect Case”•Identify Gaps•Evaluate NOAA Prototypes

Task 3.Cost-Benefit•Identify costs and benefits•Review and select methodology•Apply Methodology•Recommend Ideal/Most •Optimal Product

Planning Requirements•Load forecast•Short-term pricing•Load flow management•Power purchases


Cost

Marginal Benefits/Decisions

AttractiveProducts

Not AttractiveProducts

Weather InformationSupply Curve

PractitionersPanel•NE ISO•Con Edison•PJM•SUNY


Data Providers

(NOAA NWS, OAR,

ARL, FSL,, EPA,

NCEP, NASA)

Data Inter

mediaries

(EarthSat, W

NI, AWS)

Level of Analysis:

Inter-/Intra RegionalDistributionEnd-customer

Planning Area

Scen

ario

Project Objectives


Project Objectives










Cost

Marginal Benefits/Decisions

AttractiveProducts

Not AttractiveProducts

Weather InformationSupply Curve



Data Providers

(NOAA NWS, OAR,

ARL, FSL,, EPA,

NCEP, NASA)

Data Inter

mediaries

(EarthSat, W

NI, AWS)

Level of Analysis:


Planning Area

Scen

ario

Level of Analysis:


Planning Area

Scen

ario

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Key Utility functions/decisions at Risk from inaccurate weather/climate dataKey Utility functions/decisions at Risk from inaccurate weather/climate data

Load Balancing-single utility and gridGeneration commitment-fuel mix choice and seamless integration (fossil fuel, hydro, wind)Dispatch scheduling

Power MarketingCash tradingPower pricingFuel pricing and procurement

Tariff SchedulingLineman and repair crew dispatchPump Load ForecastingNatural Gas Storage ManagementRevenue ProjectionsInfrastructure siting- fossil and renewablesManagement strategic planningSubstation Scheduling/maintenanceEmergency Management-Trimming and storm team dispatch

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Weather Information “Flow” on the Decision Process and Value Chain: Risk Reduction Areas

Weather Information “Flow” on the Decision Process and Value Chain: Risk Reduction Areas

INFORMATION KNOWLEDGE ACTION OUTCOMES IMPACTSDATA

scheduling and load balancingasset management and replacemententerprise wide contingency and financial planningdemand reduction and price responsive loadsRevenue forecastingcongestion management

NMSOther

Weather/Climate

forecasts

Weather Data/modelproducts

PresentValue-Added

Service Providers

WeatherDataFormatting

Short

Mid

Long term

Load Forecasting

WeatherDataPre-Processing

WeatherInformationIntegration

WeatherInformation Evaluation

•Improved profit•Increased Efficiency•Improved reliability•Increased safety•Decreased Liability•Decreased Risk•Decreased Exposure

WeatherDecisionSupport

Operational Decisions Management goals

Weather Data Analysis and IT Services: Quantify, source, cost and reduce weather data error

Load Model Error Analysis: ImproveSoftware and Support

Decision Analysis, Dependencies and Support Tools

Economic/Performance Valuation of Weather Error Impacts

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Electricity Demand Model Error -Neural Net Diagnostics

Electricity Demand Model Error -Neural Net Diagnostics

Power Demand Forecast Model- AANSLFF, RER Metrix, etc. or ensemble

Weather Forecast Model- AVN, MRF, etc or ensemble

Skill of the Environmental Forecast Impacts the Skill of the Power demand forecast

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Diagnostics ApproachDiagnostics Approach

Fiscal loss (blown forecast)Imbalance of supply-demandLow skill of demand model

Weather errorUncaptured event –

seabreeze, frontsImprove Model or

observationsEnsemblesEnsembles

validate

Beta Test

Install

(Alpha test)

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Urban Utility Case Study Findings 1: Significant load error due to high impact weather

Urban Utility Case Study Findings 1: Significant load error due to high impact weather

Weather Variance (%) Summer 2002 over Service Territory

-6.0%

-4.0%

-2.0%

0.0%

2.0%

4.0%

6.0%

8.0%

10.0%

1-Jul

8-Jul

15-Ju

l22

-Jul

29-Ju

l5-A

ug12

-Aug

19-A

ug26

-Aug

Date

Varia

nce

Weather Variance (%)*

Most utilities calculate weather error in MW as well as percentage of variance of the load. Analysis indicates that on some days, variance in the load forecast in MW may be solely due to weather error. This appears to be from events or unmodeled mesoscalefeatures such as back door fronts, sea breeze and afternoon thunderstorms. SAIC estimates of cost of such events can be greater than $10M

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Principle Causes of Uncertainty on Energy Operations and Planning

Principle Causes of Uncertainty on Energy Operations and Planning

Uncaptured WIND Events Delta Breeze- Cal ISOLake effects- Salt Lake City- Pacificorp, Great Lakes- SUNY BuffaloSeabreeze- NE ISO, EntergyFrontal passage- 2-4 day

Uncaptured PRECIPITATION EventsRain vs. snow/iceRegional day ahead error in precipitation- PacificorpAfternoon thunderstormsMarine Layer, fog- SDG&EDrought and flood, flash floodHumidity

Uncaptured CLIMATE EventsClimate outlooks –weather events frequencyEl Nino and seasonal eventsDecadal oscillations- NAO

Accuracy/RESOLUTION- Spatial, temporalSub grid levelTargeted watershed level, Nodal, congestion and populationTopographic Effects- microzonesHourly changes during eventsDew Point

Load Model Error50% load error at certain event periodsCan’t incorporate probabilities/ ensembles

Sub-optimal UseDew Point, cloud cover, wind speedNeed for decision aids

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Key Cost Findings2002-2003 NOAA Northeast Energy

Key Cost Findings2002-2003 NOAA Northeast Energy

“The project estimated that the benefits of improving day ahead weather forecast accuracy by one degree F or by reducing forecasting error by 50% for days 2-7 is:

• --$20-25 million per year for a regional transmission authority• --$1-2 million/year for a major distribution utility.

Optimal use of weather information could yield savings of $8–18 million/year for a major university system (electric and natural gas).

If these savings were generalized to other regional transmission organizations, large statewide colleges and universities and regional transmission authorities the total savings would be for the Northeast Region:

-- $100-140 million/year for ISO’s--$30-60 million for regional electric distribution companies.-- $38-67 million for Statewide university campuses

HOWEVER capturing the “HIGH Impact events” will yield significantly higher savings (10’s millions/day).- seabreeze, backdoor fronts, afternoon showers

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Case Studies 2 and 3 Case Studies 2 and 3

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West Coast Power West Coast Power

•Load balancing Problems

•Coastal winds•Coastal fog•Microclimates•El Nino

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Cal ISO Mean Daily Forecast ErrorCal ISO Mean Daily Forecast Error

Delta breeze and weather/load forecast errors contribute to major errors in prediction of Delta Breeze effects.Delta breeze is defined as the conditions when the wind speed is > 12 knots and the direction is between 190 degrees and 280 degrees.Delta Breeze can change load by 500MWDirect Costs: 250k per breeze day; 40 events per year

Mean Forecast Error, 2003

-4000

-3000

-2000

-1000

0

1000

2000

5/18

/200

3

6/1/

2003

6/15

/200

3

6/29

/200

3

7/13

/200

3

7/27

/200

3

8/10

/200

3

8/24

/200

3

9/7/

2003

9/21

/200

3

10/5

/200

3

Day

MW Series1

Delta Breeze events

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Relationship of Weather Uncertainty and Cost: Grid Operating CompaniesRelationship of Weather Uncertainty and Cost: Grid Operating Companies

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Case Study : Cal ISO Weather Forecast Error and Potential Cost $7M

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Ensemble Forecast Performance at the Cal ISOEnsemble Forecast Performance at the Cal ISO

Objective – To determine whether an ensemble based probabilistic forecast would outperform the forecast products currently used by the Cal ISOApproach –

Construct several (5) one-day-ahead multi-model ensemble forecast products Test in the Cal ISO Load Forecast Operation to determine the “performance” of the improved probabilistic product.reanalysis of the past load and weather error (summers of 2002,2003)retrospective analysis of the financial impact of load imbalance. Two sets of performance metrics - technical performance or skill of the weather forecast model. The second is for the financialperformance of the ensemble as it is transformed into a businessforecast through the load forecasting process.

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Savings to Cal ISO by EnsemblesSavings to Cal ISO by Ensembles

Relative costs of PF1 package forecasts versus the Cal ISO surrogate forecasts for days in May and June 2002, a positive value represents a savings of using PF1.

May and June 2002

-0.2

-0.1

0

0.1

0.2

0.3

0.4

0.5

0.6

5/22/2

002

5/23/2

002

5/24/2

002

5/25/2

002

5/26/2

002

5/27/2

002

5/28/2

002

5/29/2

002

5/30/2

002

5/31/2

002

6/1/200

26/2

/2002

6/3/200

26/4

/2002

6/5/200

26/6

/2002

6/7/200

26/8

/2002

6/9/200

26/1

0/200

26/1

1/200

26/1

2/200

26/1

3/200

26/1

4/200

26/1

5/200

26/2

2/200

26/2

3/200

26/2

4/200

26/2

5/200

26/2

6/200

26/2

7/200

26/2

8/200

26/2

9/200

26/3

0/200

2

Rel

ativ

e C

osts

L.A. Smith, Altalo,& Ziehmann (2004) Predictive distributions from an Ensemble of Forecasts: Extracting Electricity Demand From Imperfect Weather Models. PhysicaD, (in review)

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Ensembles and Reduction of Load Forecast Error

Ensembles and Reduction of Load Forecast Error

1. More information is contained in the existing weather data stream that can be gleaned from an ensemble based approach.

2. This new information can save up to 50% of the weather error related costs by getting the forecast right during peak periods.

3. It works in relation to the cost curve and allows a forecaster to hedge risk based on fact not on “gut feeling”.

4. This new added information gives utility organizations an additional way to mitigate weather –related risks inherent in the load forecasting process.

5. The significant economic savings reported for 2003 is found to be even larger in the corresponding drop-one-out analysis for 2002; PF1 is shown to save about $15 million over current method, with a loss of about $5 million over perfect weather information

From Altalo, M. and L.Smith, Environmental Finance, October 2004

Emergency ManagementEmergency Management

State of Maryland Emergency Management Agencies (MEMA) and The Public Utilities Commission (PUC)

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The “worst nightmare” according to Dr. Richard Schaeffer, head of the PUC is that the Governor’s office calls and asks “what is going on and when will services be restored?” and they don’t know Thus the need for “Situational Awareness”more than just environmental awareness-It is

the status of the operations of power, water, communications, police, pipeline, toxic spill etc.Need probabilities of strikes for action

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The Power of Linking Decision Support Tools to get a Solution Set

The Power of Linking Decision Support Tools to get a Solution Set

Severe Weather/Climate/Ocean Forecast + Impact Assessment on Operations +

Emergency Power Dispatch Management

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The Solution: Linking Weather Forecast Simulation Tools with Emergency Response Simulation Tools for Severe Weather

Emergency Energy Management

The Solution: Linking Weather Forecast Simulation Tools with Emergency Response Simulation Tools for Severe Weather

Emergency Energy Management

Storm Tracking with simulation tool-predict hurricane landfall

Emergency preparedness with “CATS”(consequence assessment tool set)Locate critical energy assets, estimate damage and position for relief

Expert “Grid”Management Situational Awareness and Power RestorationManagement Tool

Data-Information Knowledge Action and Outcomes

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“Chem-Bio Weather” Forecasts and Dispersion Models Predict Hazards and Allows Mitigation“Chem-Bio Weather” Forecasts and Dispersion Models Predict Hazards and Allows Mitigation

Recreation and Tourism Industry Needs for

Probabilistic Weather/Climate

Information

Recreation and Tourism Industry Needs for

Probabilistic Weather/Climate

Information

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Diverse StructureDiverse Structure

1. Hospitality- Food service- Accommodation

2. Distribution - Travel Agents- Tour operators

3. Transport and Infrastructure-Aviation-Marine

4. Visitor Attractions- Man-made (theme parks, marinas, golf courses)- Natural (e.g. natural parks, coast, lakes)

5. Host city/infrastructure- Olympics

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.

MinutesMinutes

HoursHours

DaysDays

6 6 –– 10 Days10 Days

8 8 –– 14 Days14 Days

MonthsMonthsSeasonsSeasons YearsYears Forecast

UncertaintyForecast

Uncertainty

Fore

cast

Unc

erta

inty

Fore

cast

Unc

erta

inty

Forecast Lead TimeForecast Lead Time••Building energy Building energy mngtmngt..••Disaster risk Disaster risk mngtmngt..••Daily staff briefingsDaily staff briefings••Daily guest informationDaily guest information••“Intelligent” infrastructure“Intelligent” infrastructure••CruiseshipCruiseship positioningpositioning••SnowmakingSnowmaking

••Fuel supply procurementFuel supply procurement••Backup generation plansBackup generation plans••Marketing (brochure , Marketing (brochure , radio, ) developmentradio, ) development••Annual insurance reviewAnnual insurance review••Inventory managementInventory management••Cruiseline destination Cruiseline destination planningplanning••Convention “bidding”Convention “bidding”••Premium/deductible Premium/deductible settingsetting

••Hotel group managementHotel group management••Cruise ship routing & ETACruise ship routing & ETA••Outdoor activities planningOutdoor activities planning•• Transportation logisticsTransportation logistics••Maintenance schedulingMaintenance scheduling••Staff schedulingStaff scheduling••“Conditions” forecasts“Conditions” forecasts

••Sales/earnings forecastingSales/earnings forecasting••Stock pricingStock pricing••Food service/supply procurementFood service/supply procurement••Group properties budgetingGroup properties budgeting••Unit price setting Unit price setting ••Rev par estimationRev par estimation••Seasonal “occupancy” forecastsSeasonal “occupancy” forecasts••Delivery rate settingDelivery rate setting••Compliance reportingCompliance reporting

••Infrastructure designInfrastructure design••Landscape designLandscape design••Access planningAccess planning••Regional infrastructure planRegional infrastructure plan••New hotel capacity plansNew hotel capacity plans••Mitigation strategy designMitigation strategy design••Infrastructure sitingInfrastructure siting••Building code settingBuilding code setting••Development Master Development Master planning and revisitplanning and revisit\\••Regional Policy plansRegional Policy plans••Federal Policy DevelopmentFederal Policy Development

Recreation/ Tourism Operations Aided Recreation/ Tourism Operations Aided by Reductions in Environmental by Reductions in Environmental Forecast Uncertainty Forecast Uncertainty

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RECREATION & TOURISM INDUSTRY PERFORMANCE METRICS:The Business Models

Revenue per available room (RevPar) Accommodation sector Occupancy rates Accommodation sectorOccupancy percentage Accommodation sectorAverage Daily Rates (ADR) Accommodation sectorComparative Operating Rates (COR) Accommodation sectorGross Operating Profit (% before fees) Across the industryEconomic Impact Assessment Across the industry

Financial rate of Return (FRR)Economic Rate of Return (ERR)

International arrivals[1] Travel sectorJourneys made Travel sector

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Environmental Information in the Operational Business Models

Environmental Information in the Operational Business Models

o Average daily temperatureo Average Annual temperatureo January rainfall in incheso July rainfall in incheso Snowfall in Incheso Number of Heating degree-days (Last 30 years)o Number of Cooling degree-days (Last 30 years)o Wind speed in Miles per Hour (Annual average)o Annual number of days sunny or partly sunnyo Elevation (Mean feet above sea level)o Wave heighto Current speed and direction

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Utilities-Energy Pricing & 4hr forecasts of temp./ sea breeze - Scottish Power

Oil and Gas- Regional Energy infrastructure master planning and climate/ocean conditions - BP

Construction- Building codes & standards with 20 year heat/ precipitation/sea level forecasts-Building Research Establishment

Leisure - Revenue projections and seasonal temperature/ppt forecasts–The Starwood Group, Europe/Africa

Finance – Financial Risk Rating Index and air/water quality and climate forecasts- SERM Rating Agency

Health and EM- Coastal metropolitan health alert planning and met/AQ forecasting

INDUSTRY TRIALS”Observing System Product Performance Assessment in

Business Operations and Policy Development

ConstructionTrials

Oil and GasTrials

Hotel Trials

Power UtilitiesTrials

FinancialServices

Trials

Health and RiskManagement

Trials

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Starwood Hotel TrialMarbella, Spain

CEOStrategic Planning

Marketing/Sales Operations

Finance-RevenueManager

Procurement Development

Business Forecasting-1,6,12mo,5yRevenue Projection-RevPARYeild Management ModelsDemand & Capacity ForecastingImplement Rev Mngt StrategyMarket analysis

Environmental ConditionsObserving System

Products

* temp amd ppt forecastsat 1mo, 60 mo, 12 mo

and 5 year time periods

Shareholders

•Can seasonal environmental information improve the accuracy of Revenue Forecasting in the Iberian Peninsula?

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“Industry Trials” for African Business Needs

“Industry Trials” for African Business Needs

Tourism and Leisure- Revenue Forecasting and Unit Pricing Power Utilities –Energy Grid/Dispatch Management and temperature and ppt forecastingOil and Gas- Platform scheduling and wave height forecastsHealth and EM-Disease Prediction and Seasonal to interannual ppt forecastsFinance- Insurance and UnderwritingTransport- Port security, congestion managementConstruction- Sustainable Housing and materials

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Candidate Industry TrialsBusiness Country Institution Information

Requirements

OTT, Starwood 1-2 week forecast, Seasonal Prediction

Now casting, Event Monitoring, 2-4 day forecasting

Wave, Winds, Storm tracking, Sub-surface currents,

Seasonal predictions (Temp, Pres), 1-2 weak forecasts,

Historical Climate Info, Seasonal predictions, 1day -2week forecast

Waves, Currents, Winds, Storms

Sort term forecasting, Seasonal predictions, Inter-annual (Temp, Pres)

Pres, Event monitoring, Now-cast, Waves, surface and sub-surface currents

Lightning, winds, storms

Zambezi water Authority

Shell, Sonatrach

MDSC, MARA, Medical Centres

UNEP-FI, GENSEC

Port Athoroties, Container shipping companies

Bouygues, Bovis Lend Lease

Anglo AmericanSeabed mining companies

Rascom

Needs

Tourism & Leisure

NEPAD Pilot, Tunisia

More atmospheric and ocean observations-remote sensing

Power & Utilities

Mozambique, Zambia, Zimbabwe (Hydro power)

More radar coverage, Coastal Buoys & weather stations, Downscaling and models nesting, Bathymetry, Thorpex

Oil & Gas Nigeria, Algeria Dispersion Models, more ocean observations, moorings and drifters

Health & EM Burkina-Faso , South Africa

Ocean, Global atmospheric observations.

Finance South Africa Global atmospheric observations, Remote atmospheric observations

Transport Abidjan, Accra, Cotonou

More Over and In ocean sensors, Improved surface models

Construction SA More Over and In ocean sensors, Improved surface models

Mining SA, RDC Spatial resolution models, moorings

Telecoms JHB Lightning networks,

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Developing Countries Applications : Cost impacts of climate induced hydroelectric power failure in Ethiopia

(extensions from IRI study)

Developing Countries Applications : Cost impacts of climate induced hydroelectric power failure in Ethiopia

(extensions from IRI study)

Ethiopian Electric and Power Corporation – 97% hydro from Koka DamMitigate flash flood hazards and identify periods of water scarcity- risk analysisIncorporate surface variables (ppt, t) into hydrological forecastSkill score of climate forecastsDam capacity impacted by erosion in basinFlash floods and water releasing schemes from dams by Ministry of Water ResourcesDuring drought power rationing leads to revenue loss -Linkage effect of power production and customer revenue loss -$8M, enough to destabilize the economy

RecommendationsEEPCo must include seasonal forecasts into its long term plan

– Produce power demand scenarios based on seasonal rainfall outlooksDevelopment of future models hydro parameters be included in addition to meteorological variablesCombine variability of rainfall and complex topography and behavior of rainfall on subgrid level

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Relative costs for developing and developed Nations

Relative costs for developing and developed Nations

8M to Ethiopia is enough to destabilize the economy8M to California causes minor institutional discomfort

PRIORITY MUST BE DEVELOPING NATIONS---WHO WILL PAY FOR THEIR COSTS

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