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Kelvin K. Droegemeier University of Oklahoma 29 September 2010 Weather and Climate Prediction How Clear is the Crystal Ball?
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How Many of You Have Been Impacted by Weather in the Past 6 Months?
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How Many of You Have Been Impacted by Climate Change in the Past 6 Months?
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Weather, Climate, and Our Economy 40% of the $10T US GDP is Weather & Climate- Sensitive Dutton (2002) $2-3B Spent Annually On Both Weather/Climate Research and Operations
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n Cargo shipping –Most expeditious route can save $40,000 per voyage – thousands of ships travel continuously! –Examples n High temperature and humidity can cause grain to germinate in cargo holds n Ships affected differently by wavelength of ocean swells n Commercial aviation –Single diversion averages $10,000 per domestic flight –Not unusual for one carrier to have 70 diversions at a hub for a single weather event (1-2 hours) –Cost is $700,000 per event –Industry loses $1-2 B per year due to weather Specific Examples Source: Weathernews, Inc.
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About 50% of the loss is deemed preventable with better weather and climate forecasts!
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Weather vs Climate
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Source: Oklahoma Climatological Survey
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Weather vs Climate
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Weather and Climate are Becoming Blurred minute hour day week month year century millennium Where is the dividing line between weather and climate????
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Have You Ever Wondered… If astronomers can predict the occurrence of comets decades in advance, why can’t meteorologists predict the weather even 2 weeks from now?
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Peterson (2010) Time and Space Scales…
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Copyright © 2003 WGN-TV Computer Models are the Primary Source of Information for All Weather & Climate Predictions
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The Prediction Process Analyze Results Compare and Verify Observe the Atmosphere Identify and Apply Physical Laws Create a Mathematical Model Create and Run a Computer Model
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The Prediction Process Analyze Results Compare and Verify Observe the Atmosphere Identify and Apply Physical Laws Create a Mathematical Model Create and Run a Computer Model
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Observe the Atmosphere Upper-AirBalloons Satellites NEXRADDopplerRadar Commercial Aircraft AutomatedSurfaceNetworks
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The Prediction Process Analyze Results Compare and Verify Identify and Apply Physical Laws Create a Mathematical Model Create and Run a Computer Model Observe the Atmosphere
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Identify & Apply Physical Laws F=ma
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The Prediction Process Analyze Results Compare and Verify Create a Mathematical Model Create and Run a Computer Model Observe the Atmosphere Identify and Apply Physical Laws
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Create a Mathematical Model
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The Prediction Process Analyze Results Compare and Verify Create and Run a Computer Model Observe the Atmosphere Identify and Apply Physical Laws Create a Mathematical Model
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Create Computer Model
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n Solve highly nonlinear partial differential equations n East/West Wind n North/South Wind n Vertical Wind n Temperature n Water Vapor n Cloud Water n Precipitating Water n Cloud Ice n Graupel n Hail n Surface Temperature n Surface Moisture n Soil Temperature n Soil Moisture n Sub-Grid Turbulence Run the Computer Model
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n Over the course of a single forecast, the computer model solves billions of equations n Requires the fastest supercomputers in the world -- capable of performing trillions of calculations each second Run the Computer Model
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The Prediction Process Analyze Results Compare and Verify Observe the Atmosphere Identify and Apply Physical Laws Create a Mathematical Model Create and Run a Computer Model
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A Typical Forecast From Today’s Operational Models
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What Models (and Forecasters) Do Well Today n Probability and type of thunderstorms 12-24 hours n Local winter storm events (lake effect) 12-24 hours n Wind, clouds, probability and type of precipitation, frontal passage, temperature out to 48 hours n General trends out to around 10 days (location of weather systems)
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What Models (and Forecasters) Do NOT Do Well Today n Locating and timing of thunderstorm development and decay n Type and timing of winter precipitation n Amount and location of rainfall, especially from thunderstorms – and uncertainty n Hurricane landfall
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Like Politics, Weather is Local!!
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A Foundational Question... explicitly predict this type of weather? Can computer forecast technology...
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Example : March 28, 2000 Fort Worth Tornadic Storms
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Tornado
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NWS 12-hr Computer Forecast Valid at 6 pm CDT No Explicit Evidence of Precipitation in North Texas
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Reality Was Quite Different!
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6 pm 7 pm8 pm Radar Hourly Radar Observations (Fort Worth Shown by the Pink Star)
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6 pm 7 pm8 pm Radar Fcst With Radar Data 2 hr 3 hr 4 hr Xue et al. (2003) Fort Worth
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As a Forecaster Worried About This Reality… 7 pm
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As a Forecaster Worried About This Reality… How Much Trust Would You Place in This Model Forecast? 3 hr 7 pm
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Forecast #1 Forecast #2 Forecast #3 Forecast #5 Forecast #4 Actual Radar
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Probability of Intense Precipitation Model Forecast Radar Observations
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The Million Dollar Question: Will Computer Models Ever Be Able to Predict Tornadoes?
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Warn on Explicit Forecast?
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What About Climate??
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Humans Have Transformed Earth! City Lights from Space
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“Concentrations of atmospheric greenhouse gases … have continued to increase as a result of human activities”
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“The global-average surface temperature has increased over the 20th century by 0.6±0.2ºC” From the Hadley Centre, UK Source: IPCC
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“Reconstructions of climate data for the last 1000 years... indicate this warming was unusual and is unlikely to be entirely natural in origin”
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“Most of the observed warming over the last 50 years is likely to have been due to the increase in greenhouse gas concentrations” Runs with NCAR climate model
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“The projected rate of warming is much larger than the observed changes during the 20th century and is very likely to be without precedent during at least the last 10,000 years”
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Seasonal Number of Favorable Severe Environments
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US Central Plains Region
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Normalized Joint CAPE - Shear Distributions Central United States
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Continued Reliance Upon Models IPCC
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Global “Warming” isn’t the Only Issue: Precipitation!!!
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Mean Global Energy Consumption, 2001 (Total 13.2 TW; US is 3.2 TW) GasHydroRenew 4.66 2.89 2.98 0.285 1.24 0.286 0.92 0 1 2 3 4 5 TW OilCoalBiomassNuclear Nate Lewis, Caltech
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By the Year 2050 By the Year 2050 n Perhaps 9 billion people n >6 billion tons per year of greenhouse gases n >60 million tons per year or urban pollutants n Withdrawing 30% of available fresh water n Converting 65% of frontier forests n 80% of people live in cities n 70% of people live within 50 miles of a coast n 25% near earthquake faults n 2% within 1 meter of mean sea level T. Killeen, NCAR
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N. Lewis Caltech
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~160,000 km 2 of Photovoltaic Devices Would Meet US Energy Needs 3.3 TW C. Somerville, Stanford
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(in the U.S. in 2002) 1-4¢ 2.3-5.0¢ 6-8¢ 5-7¢ Now the Bad News! 6-7¢ 25-50¢ Cost, ¢/kW-hr 0 5 10 15 20 25 CoalGasOilWindNuclearSolar N. Lewis, Caltech No storage
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Sources of Carbon-Free Power: Estimated Consumption of 25 TW by 2050 n Nuclear (fission and fusion) –1 new plant every 2 days for next 50 years –Terrestrial base of Uranium fuel = 10 years n Would need to mine U from sea water (700 x terrestrial resource base) N. Lewis Caltech
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Peering into the Crystal Ball n Weather forecasting and severe weather warning are about to experience a quantum leap in capability – prediction accuracy and quantification of uncertainty (Warn on Forecast) n International agreement exists about global warming and its cause – but the honest answer is that we don’t know what the future hold apart from what our models tell us – and they’re imperfet n Failure to diversify energy portfolio could mean substantial changes in our way of life – we’ll know in the next 20 years
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