Chapter 12 Weather Analysis and Forecasting A dangerous Job? • Francisco Arias Olivera was a popular TV personality in a small Peruvian town (Sicuani) Population (21K). One day Francisco forecast a two-inch rainfall but instead they got 19 inches of rain. The local river flooded the town washing away 250 homes and killing 17. Outraged citizens stormed the TV station, and lynched Francisco. Six people charged with his murder were released after pleading justifiable homicide. Rumor has it that the TV station still has not hired another Weather Forecaster. Why make a forecast? • Forecasts are issued to save lives, save property and crops and to tell us what to expect in our atmospheric environment. • Who among us does not look at the weather at some time or other during the week? Science or Art? • Weather forecasters are responsible for predicting weather accurately so thousands (if not millions) of people will know what to expect in the weather. • But weather forecasting is not an exact science…every now and then we fail to get it right. There is hard science behind every weather forecast: primitive equations, computer models, calibrated equipment etc. However, there is an art in making a forecast, interpreting the current and forecast conditions. The atmosphere is not a “Closed” system. We cannot track every short wave or minor perturbation in the atmosphere. Acquisition of Weather Information • Over 130 nations • Over 10,000 land sites and hundreds of ship observations report each day • All in a common format • WMO is responsible for the international exchange of weather data and certifies that observation procedures do not vary among nations • Weather info from all over the world is transmitted electronically to NCEP located in Camp Springs Maryland. • NCEP relays the weather info to various public and private agencies for use in preparing local, regional and global forecasts. NCEP • Comprised of 9 centers which provide a wide variety of national and international weather guidance products to National Weather Service field offices, government agencies, emergency managers, private sector meteorologists, and meteorological organizations and societies throughout the world. NCEP is a critical national resource in national and global weather prediction. NCEP is the starting point for nearly all weather forecasts in the United States. • Office of the Director Aviation Weather Center Climate Prediction Center Environmental Modeling Center Hydrometeorological Prediction Center NCEP Central Operations Ocean Prediction Center Space Environment Center Storm Prediction Center Tropical Prediction Center Climate Prediction Center The Modern Forecaster • Has access to hundreds of maps, charts, vertical atmospheric profiles (soundings), satellite images, Doppler Radar, etc. • Many radio and TV stations hire private meteorologists or meteorological companies to make their own forecasts with the aid of NCEP products. • Some stations use untrained announcers to simply read forecasts from the National Weather Service or private companies (Accu Weather) Forecasting Methods and Tools • In the 50s many short ranged forecasts where made by moving the existing systems along at a steady rate (up two over one) • In late 70s and into the mid 80s many weather maps and charts were still plotted and analyzed by hand • Modern Computers and present observing techniques make today’s forecasts much easier and better than those of the past. Numerical Weather Prediction • Each day many thousands of observations transmitted to NCEP are fed into high speed computers that are used to prepare Numerical Weather Predictions. • Computers analyze data and use it to predict the weather. • Routine daily forecasting of weather by the computer has come to be known as Numerical Weather Prediction • Atmospheric models – simulation of the atmosphere’s behavior by mathematical equations SOME HISTORY • 1755 – Euler develops first equation of fluid mechanics. • 1827 and 1845 – Navier-Stokes add molecular viscosity terms to fluid equations. • 1904 – Bjerknes proposes a paradigm shift from empirical forecasts to ones applying basic laws of physics. • 1922 – L. F. Richardson calculates using crude method first numerical forecast using the primitive equations (PE). – 6 weeks to crank out a 6 hour forecast – Pressure calc an order of magnitude in error Richardson’s vision and today UK MET Office NEC supercomputer L.F. Richardson, 1922 “Imagine a large hall like a theatre, except that the circles and the galleries go right round through the space usually occupied by the stage. The walls of this chamber are painted to form a map of the globe. The ceiling represents the north polar regions, the tropics in the upper circle, and the antarctic in the pit. A myriad computers are at work upon the weather of the part of the map where each sits, but each computer attends only to one equation or part of an equation. The work of each region is co-ordinated by an official of higher rank. Numerous little “night signs” display the instantaneous values so that neighbouring computers can read them. From the floor of the pit a tall pillar rises to half the height of the hall. It carries a large pulpit on its top. In this sits the man in charge of the whole theatre. One of his duties is to maintain a uniform speed of progress in all parts of the globe. In this respect he is like the conductor of an orchestra in which the instruments are slide-rules and calculating machines. But instead of waving a baton he turns a beam of rosy light upon any region that is running ahead of the rest, and a beam of blue light upon those who are behindhand. Four senior clerks at the central pulpit are collecting the future weather as its is being computed, and despatching it by pneumatic carrier to a quiet room. There it will be coded and telephoned to the radio transmitting stations” THE COMPUTER AGE • Computers arrive in 1940’s • Von Neumann, Charney, Rossby, Eliassen, and Platzman attempt to use computer resources to solve PE. – Realized need to simplify due to scarce computer resources. • 1950 – first successful numerical forecast – Took 24 hours to crank out a 24 hour forecast • 1952 – Computer technology advances cut 24 hour forecast time to 5 minutes • 1954 – Services for JNWPU. Attempt baroclinic model run and not successful (no skill over empirical methods) • 1963 – First successful baroclinic model 6-level PE. • 1976 – Limited Fine Mesh model started up. Some skill, phased out in 1994. THE COMPUTER REVOLUTION • 1980 – 12-level Global Spectral Model – Consists of 2 parts • Aviation – forecasts in support of aircraft out to 5 days • MRF – Medium Range Forecast out to 15 days – 14 minutes runtime/day = 3.5 hours for 15 day forecast • 1990 – Nested Grid Model (NGM) introduced • Early 90’s – ETA Model introduced – 32 km resolution and 45 layers • 1999 – Meso-ETA introduced – 10 km horiz grid, 60 layers Numerical Weather Prediction • How is a forecast made today? The forecast process • 1. Gather observations for the globe to define the “current state” of the atmosphere Collect observations Perform quality control • 2. Use these observations in a model that describes how the the atmosphere changes with time Data assimilation • 3. Take this as the “current” state of the atmosphere and run the same model into the future Stop after 24, 48, 72 hours and interpret weather forecast! The Forecast Process Users of weather forecasts • Media- Television, radio, • Entertainment- outdoor newspapers, internet events – Widely use in public and – Winds, rain (Hogmanay) private sectors • Agriculture & Fishing • Transport – Airlines- fog, visibility, – Frost, rainfall; winds, severe weather visibility – Ships- winds, storms, • Recreation- mountaineering, visibility sailing – Railways- winds, flooding – Winds, rain, cloud level; – Roads- snow (gritting), winds visibility flooding • Military • Energy – Visibility, winds – Heat waves/cold spells when energy demand levels • Construction change – Rainfall, winds The forecast cycle over 24 hours 00 Data gathering Quality control 18 06 Assimilation Forecast 12 Observational data gathering Observation types-surface data: Temperature, humidity, pressure, wind Observation types- radiosondes: wind, temperature, humidity at vertical levels Observation types-aircraft: temperature and wind along route Observation types-satellite: geostationary images: winds Observation types-satellite: polar orbiting: temperature profiles Observations- important points • In a 6-hour period receive >100,000 observations of: – Temperature, wind speed and direction,surface pressure, humidity • For some data types transformation performed – e.g. radiances temperatures • Data types have different geographical coverage, vertical structure and temporal distribution – Surface observations are sparser coverage in SH – Only certain observations types give vertical profiles – Surface stations report at ~6 hourly intervals. Satellite data are continuous Quality control- 1.check data • Check all data have reasonable values – No 100oC temperatures or negative winds • Check values are consistent – T >= Td • Check displacement of ships and buoys – e.g.-ship data over land • Check for agreement with neighbours: – Compare with adjacent stations-buddy check – Performed relative to background forecast- to account for different weather systems at two locations Reject bad data Quality control –2. assign errors • Assign errors to data retained • Calculate observation error which depends on data type/instrument • Calculate background error= error at a given location dependent on synoptic situation (fast or slow moving systems) and data coverage • Observational error and background error combined error estimate Data assimilation • Observations and their error estimates are “assimilated” into the model: 1. Interpolate observations onto model horizontal and vertical grid 2. Combine latest observations with previous=background forecast 3. Perform adjustments 1. Interpolation • Incorporate irregular observations into model grid • Model grid has many shells with regular horizontal grid in each shell OPTIMUM INTERPOLATION X X X X Each ob must be corrected for: Time Location X Quality Compared to those around it and to previous forecasts O = Model Grid Points This is done for over 6 million obs per day X = Observations 2. Combine new observations with previous forecast • adjusts the model background field -the forecast from the previous model run- towards the new data received from observations • Include observational errors to determine how reliable these new data are • Process is very complex (adjustments often needed) and known as variational analysis • Data assimilation can take 30% of the computational effort Data assimilation- schematic 3. Adjustments • Observations and background forecast are not always consistent: – pressure gradient from background forecast may imply a different wind from that observed – horizontal temperature gradients from background forecast may imply a different thermal wind (wind shear) • Failure to deal with these discrepancies causes models to fail catastrophically • An adjustment process is used to iteratively (over short time-steps) reduce discrepancies to a minimum An “analysis” of the current state of the atmosphere • We now have the best possible estimate of the current state of the atmosphere on a regular grid over the whole world. • This is called an analysis • The process of making the forecast can now begin ECMWF European Center for Medium Range Weather Forecast Reading England Vertical coordinate- All models use discrete vertical levels, just like horizontal grid points. The obvious choice is for a vertical coordinate, height or pressure, is not in common use because it is numerically difficult to cope with a sloping lower boundary. Instead, modelers generally use some variation of sigma coordinates (name after the greek letter), with the lowest level following the Earth’s surface and higher model levels defined as being some fraction of a distance (in pressure) from the ground to the top of the atmosphere. Pronostic Chart (PROG) • NWP provides a series of charts or numerical output for a specified period, 12, 24, 36, 48, 72 hours etc out to 7 to 10 days in some cases longer 16-30 days. • The final forecast chart representing the atmosphere for a specified time in the future is called a PROG Two surface pressure and precipitation progs for 2000 EST, September 29, 2003 – 48 hours into the future. Prog on left is Navy Operational Global Atmospheric Prediction System (NOGAPS) model, whereas prog on right is the Global Forecast System (GFS) model from NCEP Why Forecasts go Wrong@#!! • Flaws in computer models limit the accuracy of the forecast • Models idealize the atmosphere, making certain assumptions that may be correct in some instances, but wrong in others. • Data sparse regions of the world leave gaps in our observations • Models cannot accurately interpret many factors that influence weather, may not handle terrain features well, may not have the resolution to “get the local weather right” • Chaos Theory – a butterfly flaps his wings in a rainforest in South America and your forecast in Asheville goes to pot. Small disturbances in the atmosphere, not picked up by the model, can ruin your forecast Tools for Forecasting the Weather Advanced Weather Interactive Processing System - AWIPS Can process DOPPLER, ASOS, ingest models, etc. Handles and displays obs and weather maps. WSR-88 Doppler Radar • Doppler radar data from Melbourne, Florida, on March 25, 1992, during a severe hailstorm that caused $60 million in damages in the Orlando area. In the table near the top of the display, the hail algorithm determined that there was 100 percent probability that the storm was producing hail and severe hail. The algorithm also estimated the maximum size of the hailstones to be greater than 3 inches. A forecaster can project the movement of the storm and adequately warn those areas in the immediate path of severe weather. NEXRAD WSR-88D Doppler Radar Profiler winds for California Upper air sounding • A sounding of air temperature, dew point, and winds at Pittsburgh, PA, on January 14, 1999. Looking at this sounding, a forecaster would see that saturated air extends up to about 820 mb. The forecaster would also observe that below-freezing temperatures only exist in a shallow layer near the surface and that the freezing rain presently falling over the Pittsburgh area would continue or possibly change to rain, as cold easterly surface winds are swinging around to warmer southwesterly winds aloft Major Types of Satellites Geostationary Polar Orbiting Very important for covering vast areas of globe. 70% of earth is water…very few surface observations over the oceans GOES (Geostationary Operational Environmental Satellite) • Orbital period exactly matches the rotation of the earth • Altitude of 35,800 km • Appears to "hover" over one spot on the Earth's equator. Global GOES Coverage GOES-10 GOES-WEST GOES-CENTRAL GOES-EAST (GOES-10) (GOES-11) (GOES-8) GOES Images POES • Altitudes usually range from 700 to 800 km • Satellites in this category include; NOAA, DMSP, Landsat, and SPOT • Slightly more than 14 orbits in a single day. POES ORBIT COVERAGE Meteorological Uses • Cloud cover, types, obstructions to visibility • Tropical Cyclones • Low pressure systems at sea • Winds velocity • Rain rates • Sea heights Other Forecasting Methods • Persistence Forecast – easiest way to make a forecast. Simply predict future weather will be the same as present weather. • Steady-state or trend Forecast – uses the principle that surface weather systems tend to move in the same direction and at approximately the same speed as they have been moving. Today using this method for very short duration forecasts is called “nowcasting”. • Analogue Method – relies on the fact that the existing features on a weather chart (or series of charts) may strongly resemble features that produced certain forecast conditions in the past. “I’ve seen this situation before, and this is what happened” Other Forecasting Methods • Ensemble forecasting – approach based on running several forecast models – or different versions (simulations) of a single model – each beginning with slightly different weather information to reflect errors inherent in the measurements. If at the end of a specified time, the models match each other fairly well, the forecaster can issue a forecast with high confidence…if they don’t match…well… Other Forecasting Methods • Climatological forecast – a forecast based on the climatology (average weather) of a particular region. I.e. It rarely ever rains in Los Angeles in July and August. Stats from all past years indicated it is not prudent to forecast much rain in these months. • Probability forecast – a forecast of the probability of occurrence of one or more of a mutually exclusive set of weather conditions. Probability Forecast • Probability of a "White Christmas" - one inch or more of snow on the ground - based on a 30-year average. The probabilities do not include the mountainous areas in the western United States. Accuracy and skill in forecasting • 12-24 hour forecasts are quite accurate • 1-3 day forecasts are fairly good • 7-10 days are getting better but still often fall into the “smoke and mirrors” category. • What qualifies as a right or wrong forecast? If I forecast 65oF for a max temp tomorrow and we get 66oF – did I blow it?? • We say a forecast shows skill when it is more accurate than a forecast based only on persistence or climatology. • Today we often accurately predict large scale weather events many days in advance (major snow storms, blizzards, hurricane strikes) Book of Signs • Theophrastus, student of Aristotle, 300 BC compiled all sorts of weather indicators in his “Book of Signs” • Ways to foretell the weather by examining natural signs: shape of clouds, intensity at which a fly bites. • Our own folklore: “halo around the moon portends rain” • Do you have some knowledge or experience that can help foretell weather in mid latitude? Weather forecasting using surface charts • Surface weather map for 6:00 A.M. Tuesday. Dashed lines indicate positions of weather features six hours ago. Areas shaded green are receiving precipitation. Determining the Movement of Weather Systems (Rules of Thumb) • For short intervals, storms and fronts tend to move in the same direction and at the approx. same speed as they did during the previous 6 hours – unless there is reason to indicate otherwise. • Lows tend to move in the direction that parallels the isobars in the warm air ahead of the cold front • Lows tend to move toward the region of greatest surface pressure drop, highs tend to move toward the region of greatest surface pressure rise. • Surface pressure systems tend to move in the same direction as the wind at 5500 m – the 500 mb level. The speed at which the surface systems move is about ½ the speed of the winds at this level.