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Weather and Climate

Weather and Climate Lecture 14 28 April 2008 Forecasting If you know where the low [or the high] is now You should be able to guess your future weather You should be able to guess your future temperature It moves to your north or west Winds will shift to the south

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Weather and Climate

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  1. Weather and Climate Lecture 14 28 April 2008 Forecasting

  2. If you know where the low [or the high] is now • You should be able to guess your future weather • You should be able to guess your future temperature

  3. It moves to your north or west Winds will shift to the south Any frozen precipitation will likely turn to rain or drizzle By the time the cold air arrives, moisture is gone It moves to your south or east Winds will shift from easterly to northerly to northwesterly Frozen precipitation will continue Cold air will arrive A Low is Approaching

  4. Problem: Steering Flow will evolve with time, changing wind Which way will this storm move?

  5. Where will low move?

  6. Problems: • Low may change directions, or slow down, especially when it’s occluding • Low may leave, but clouds stay behind • Upper levels affect surface (dry slots) • Computer simulations can do a great job of describing the future evolution of the weather Solution

  7. Why are forecasts important? Weather forecasts play a role in the everyday decisions that an average person makes.

  8. Who employs Weather Forecasters? • Government • Military • Private Forecasting Companies • Energy Companies • TV stations • Insurance Companies • Airlines • Recreational Industries • Agricultural Companies • And many more! Many entities need accurate weather information

  9. How does a weather forecaster make a forecast?

  10. The Current Weather • Before a weather forecast can be made, the forecaster has to know the current state of the atmosphere. • You can’t predict if you don’t know your starting point!! • How do we know the current state of the atmosphere?

  11. Distribution of Observations

  12. Distribution of Observations

  13. Distribution of Observations

  14. Distribution of Observations The individual satellite paths are obvious!

  15. Distribution of Observations

  16. Comments on previous slides: • Not many observations over the ocean • What does this mean if you live just west of an ocean? Will you know the structure of the feature that is bearing down on you? • Fewer ‘obs’ in southern Hemisphere compared to northern hemisphere • Partly because there’s more ocean there • Also fewer aircraft flights

  17. Even if the storm is over the ocean, sometimes you can infer a lot from its structures on a satellite image (This storm is likely extremely strong with strong winds)

  18. Still… • Knowledge of the present structure won’t help make an accurate forecast • It does give you an accurate start • But the state of the atmosphere will change in ways you might not be able to predict given the initial conditions • Must turn to Numerical Weather Prediction

  19. Numerical Weather Prediction • Approximate weather (wind, temperature, relative humidity) at points on the globe • Use mathematics to describe the evolution of the weather • Solve equations on a computer Note the grid – values are defined at every point on the grid

  20. Lewis Fry Richardson • Visionary Meteorologist who devised a scheme to create forecasts numerically during WWI (he was an ambulance driver) • Published a book describing the methods • Abandoned meteorology when War Departments became too interested in his work

  21. Why use computers? • Computers excel at repetitive calculations • It would take a team of mathematicians or meteorologists years to produce the millions of calculations that go into a single forecast!

  22. Air Flow is governed by equations • Equations can be approximated by computations on grid points in a model • Step the model forward in time -- you produce a forecast • Different computer models have different assumptions and will yield different results

  23. Two Models Valid at the Same Time Different models make different assumptions about aspects of the weather. Or, they have different resolutions. Result: different forecast outcomes. Overall agreement is usually okay

  24. How does forecast change with time? If sequential model runs show similar results, you should forecast that event with more confidence

  25. What if there are big differences between two different models or between sequential runs of the same model? Don’t forecast with a lot of confidence in that case: Emphasize what you know, and mention the possibilities

  26. How Can A Person Improve Numerical Model Forecasts?

  27. The Human Element • Humans have great pattern recognition skills • Forecaster will identify the deterioration of a forecast long before the model simulation does • Compare model forecast to satellite images and current surface observations • Adjust for known model biases

  28. Why Do Numerical Forecasts Go Awry?

  29. MANY reasons • Small scale features poorly resolved in models and must be parameterized • Large scale features are not reproduced with 100% accuracy • Initial fields of model contain significant errors in horizontal and vertical

  30. What is the high on the east coast is actually stronger than analyzed? How will that affect the evolution of errors in the subsequent forecast?

  31. Sometimes, the computer simulation dies (or is obviously wrong), or it cannot be transmittedIf there are problems with numerical weather prediction models, what other methods can a forecaster use?

  32. Persistence Forecast Persistence assumes tomorrow is a carbon copy of today

  33. Steady State or Trend Method Things are changing at a fixed rate that doesn’t change with time

  34. Meteogram (Meteorogram) You could use the information on this chart to predict weather on the 20th or 21st by assuming that the evolution of the weather will resemble the previous days’ evolutions.

  35. Trend Forecasting • If today is a bit warmer than yesterday, then tomorrow will be a bit warmer than today • If the pressure is falling now, the pressure will continue to fall tomorrow • Changes just keep going out in time without alteration

  36. Analogue Method • Used when a weather map depicts features similar to an event observed in the past. • Also called “pattern recognition”. • While weather systems may look similar they are never exactly the same.

  37. Similar paths, but Different strengths Still -- use ‘old’ path to forecast weather during ‘new’ storm

  38. Ensemble Forecasting • Use one set of computer code (One model) • Start the forecast at the same time, but add small perturbations to the initial field, and see what impact those perturbations have on the subsequent forecast • This tells you something about the predictability of the atmosphere…You might be in a region where no matter how the fields are perturbed, the forecast remains the same…or you may be somewhere where forecasts change dramatically This is the focus of most current advances in NWP

  39. Ensemble Forecasts • Statistical approach to forecasting: what forecast scenario is most likely? • Use one numerical model, perturb initial conditions, and see what happens. • In the maps on the next page, you see two 500-mb height contours; close together at 00h (initial time), but they diverge some by 3.5 days (84h) and diverge even more by 240h (10 days). • Still – are there regions where even at 10 days the different model simulations suggest similar weather?

  40. Are you forecasting for a place where the forecast spread is high or low?

  41. If you’re forecasting for someplace that’s not predictable, you change the definitiveness of your wording!

  42. Ensemble Forecasting You can also use different models, with the same initial fields, and see how each model describes the evolution of the atmosphere

  43. Climatological Forecasting Think about Phoenix, AZ.......if you had to make a forecast for tomorrow, would you forecast rain or sunshine? A climatological forecast is based solely on what the climate records indicate for that location.

  44. Probability Forecasting • Relies heavily on climatological data. Chance of a White Christmas

  45. Forecast for Today • Persistence: (A repeat of Sunday) • Climatological: Cool with a shower, high 62 • Trend: Compare Saturday and Sunday and extrapolate to Monday • Think about the assumptions in this type of forecast: are they valid? • How often is a day ‘normal’ at your location? • (This means you have to know what normal is! • Will be changes continue from day to day?

  46. How accurate are model forecasts? • 12 to 24 hour forecasts are usually quite accurate • 1 to 3 days is pretty good • 3 to 5 days better than flipping a coin • 3.5 days is where 1 day was 30+ years ago • beyond 7 days relies mostly on climatology • For a forecast to have “skill” it must be better than a forecast of persistence or climatology

  47. Rules of Thumb • Experience is the best tool a forecaster has! • Thus many forecasters rely on “rules of thumb”. What is a “rule of thumb”?

  48. Meteorological Rules of Thumb • Will it rain/snow? • look at the -5o C isotherm on 850mb chart • look at the 540 ‘thickness’ line • Will it be cloudy or clear? • On 700mb chart look for relative humidities >70% • What will the overnight low be? • take the 5pm dew point temperature

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