Weather Forecasting Principles I Isaac Mugume Lecturer Notes MET 2202 April 6, 2017 Isaac Mugume (Mak) Lecture No.02 April 6, 2017 1 / 52
Review of Previous Lecture Isaac Mugume (Mak) Lecture No.02 April 6, 2017 2 / 52
Meaning of weather forecasting The process of weather forecasting consists predicting the future conditions of the atmosphere. It is the prime role of a national weather agency. These forecasts are needed by the general public, government, military and aviation among others. Example of forecasts include: short and medium term forecasts; tailored forecasts; aviation forecasts and forecast analyses Isaac Mugume (Mak) Lecture No.02 April 6, 2017 3 / 52
Importance of weather forecasting Weather forecast help to: mitigate loses for example helping companies plan ahead; save lives; reduce damage to crops; give the public information in regard to coming atmospheric conditions reduce potential damage to property Weather data The weather data such as daily temperature and precipitation reports is important for ground truth and forecast verification as well as in put data in models. The sources of weather data are: surface observations, weather radar, aircraft reports of winds, observations from upper air balloons and satellite data, fixed and drifting buoys, ship observations. Isaac Mugume (Mak) Lecture No.02 April 6, 2017 4 / 52
Weather data collection tools Figure: The automatic weather station Isaac Mugume (Mak) Lecture No.02 April 6, 2017 5 / 52
Weather data collection tools... Figure: The buoy Isaac Mugume (Mak) Lecture No.02 April 6, 2017 6 / 52
Quality of weather observations The quality of weather observations along with appropriate temporal and spatial coverage is necessary for skillful forecasts. However, even with high quality observations, there is a limit to predictability beyond a couple of weeks ahead. Good quality observations are necessary in a rapidly changing atmosphere. The richness of observations can also assist to improve weather prediction for example observations at different heights and observations considering all the weather parameters. Isaac Mugume (Mak) Lecture No.02 April 6, 2017 7 / 52
Process of weather data transmission WMO 1 Member states have the obligation to share data and metadata with other members of WMO. Two types of data have been identified by the agreements: essential and additional data. A minimum set of essential data has to be made available with free and unrestricted access. However Members may include more information under the essential category than just the minimal set. 1 Source:http://www.wmo.int/pages/themes/climate/climate data management exchan Isaac Mugume (Mak) Lecture No.02 April 6, 2017 8 / 52
Process of weather data transmission Figure: The data sharing Isaac Mugume (Mak) Lecture No.02 April 6, 2017 9 / 52
Process of weather data transmission The exchange of weather data between national meteorological and hydrometeorological services is important for applications such as weather and climate monitoring as well as weather and climate predictions or advisories. The weather data is also available for storage and use in scientific research applications. The data centers are linked to the Global Telecommunication System (GTS) of WMO Information System (WIS). Isaac Mugume (Mak) Lecture No.02 April 6, 2017 10 / 52
Length of forecast period Weather forecasting is normally for a short period but extended periods are known as outlooks. Nowcasts which are forecasts valid over a period of 0 2 hours ahead and is normally based on observations (e.g. radar, satellite images and surface observations); short-range forecast are valid for a period of 0 60 hours; medium-range forecast are valid over 3 7 days and are usually generated using medium range models such as ECMWF or GFS. Isaac Mugume (Mak) Lecture No.02 April 6, 2017 11 / 52
Forms of weather prediction Deterministic prediction We expect partly cloudy conditions in morning developing into afternoon showers for areas around Lake Victoria A deterministic forecast is one that gives specific values of meteorological variables such as temperature, wind direction, wind speed, rainfall amount rainfall duration, atmospheric pressure etc. It is normally made by extrapolating the current atmospheric state forward in time using fixed set of laws. Since the atmosphere is chaotic and non-linear, deterministic forecasts are thus limited and are normally of less value considering forecasts for lead time after about 2weeks ahead. Isaac Mugume (Mak) Lecture No.02 April 6, 2017 12 / 52
Ensemble prediction Ensemble is the combination of different forecasting tools/methods to produce a forecast. The individual forecast tools/methods making up ensemble are known as ensemble members. Ensemble forecasts can be made from multi model ensemble, time lagged ensemble, perturbing model physics or combining all. If all the runs give same forecasts, the atmosphere is considered to be insensitive to perturbations and the confidence of the forecast is higher. Ensemble prediction does not necessarily lead to accurate forecasts but helps to give the confidence in using the forecasts. Ensemble forecast helps in generating probabilities instead of using deterministic forecasts but its major challenge is communicating the uncertainties in a comprehensible way to the users. Isaac Mugume (Mak) Lecture No.02 April 6, 2017 13 / 52
Deterministic & Ensemble prediction Deterministic Forecasts: It will be sunny tomorrow in Soroti A probabilistic prediction can be: There is an 80% chance of sunny conditions in Soroti tomorrow Probabilistic prediction can give economic benefit to industries like insurance companies that are interested in weather related hedging. Isaac Mugume (Mak) Lecture No.02 April 6, 2017 14 / 52
The probability to use in probabilistic forecasts For station X, when wind is blowing from the south, available data shows that eight out of ten days had sunny days the next day. We can note that there is an 80% chance of sunny conditions tomorrow for station X. Seven out of ten ensemble members predicted rainfall tomorrow for a station Y. We can note that this is a 70% chance of rainfall tomorrow Isaac Mugume (Mak) Lecture No.02 April 6, 2017 15 / 52
Predictability of Atmosphere Weather forecasting is an initial value problem that is affected by many physical processes. It is important to include these processes as much as possible in order to obtain skillful prediction. An error in initial conditions could result in different forecasts as described by Lorenz. An implication of different initial conditions could imply that a slight perturbation in the atmosphere could result in a very different evolution of weather systems. Isaac Mugume (Mak) Lecture No.02 April 6, 2017 16 / 52
Predictability of Atmosphere... The forecast made will normally begin to diverge with increasing forecast lead time. The limit of predictability beyond a given period increases with space and time Worse still is that it is hard to precisely determine when the prediction begin to diverge or when it becomes useless. For rapidly varying atmospheric conditions, prediction for long lead times can become a big challenge. Studies about limit of predictability note that deterministic prediction beyond 14days is less useful. It is the non linear nature of the atmosphere; model uncertainty; and imperfect knowledge of initial state that introduces limit to predictability Isaac Mugume (Mak) Lecture No.02 April 6, 2017 17 / 52
Predicting climate Due to limits of predictability, longer periods such as a month, season can not be predicted in deterministic or probabilistic terms. The variables predicted are predicted in expected conditions such Normal, Above Normal, Below Normal. The Uganda National Meteorological Authority uses the terms above as: Normal to indicate that the conditions will within ±25% of the normal conditions; Below normal to indicate that the conditions will be below 75% of the normal conditions and Above normal to indicate that the conditions will be above 125% of the normal conditions; Isaac Mugume (Mak) Lecture No.02 April 6, 2017 18 / 52
The weather forecasting process The forecast is a process that involves: collecting weather observations from different locations; quality control; incorporating the observations as initial conditions; using a model to extrapolate the atmosphere forward; analyzing the forecast; post processing and production of the forecast and dissemination. It is also important to continuously appraise the forecast products using performance measures that measure error and bias Isaac Mugume (Mak) Lecture No.02 April 6, 2017 19 / 52
The weather forecasting process Figure: The forecasting process Isaac Mugume (Mak) Lecture No.02 April 6, 2017 20 / 52
Factors to consider in forecasting 1 The terrain: the general terrain is important as it has the possibility of modifying local weather. The presence of water bodies can introduce land and sea breezes. 2 Presence of clouds: presence of clouds has ability of obscuring insolation and thus can result to low maximum temperatures during the day and higher minimum temperatures at night. 3 Wind: wind has the ability to advect moisture to and from a given location and can affect precipitation. Wind can also lead to mechanical turbulence, mixing warm and cold air. At night and in the presence of calm conditions, radiation cooling is possible. 4 Instability: if the atmosphere is unstable, convection is likely to develop and if the atmosphere is moist, clouds can develop. Isaac Mugume (Mak) Lecture No.02 April 6, 2017 21 / 52
Factors to consider in forecasting... It is important to know the weather associated with common observed weather patterns. For example, cold fronts are normally associated with narrow bands of showers, anticyclones are normally associated with fine weather. It is also important to have a clear comprehension of the development and movement of the governing weather systems such as the high pressure centers and cyclones.. Isaac Mugume (Mak) Lecture No.02 April 6, 2017 22 / 52
Today s Lecture April 6, 2017 Isaac Mugume (Mak) Lecture No.02 April 6, 2017 23 / 52
Quality of a good forecast A good forecast is subjective depending on who is the judge. To a forecaster s point of view, a good forecast is one that is accurate. To the public, it is one that will yield a favorable weather conditions for it to execute its business. But the public is also mindful of the accuracy of the forecast. Isaac Mugume (Mak) Lecture No.02 April 6, 2017 24 / 52
Quality of a good forecast... A good forecast should be one that is: 1 Consistent: consistence means that if you reproduce the forecast using the previous tools, you should be in position to get the same forecast 2 Of high quality: the quality of forecast refers to how the forecast compares with actual observations. 3 value of forecast: the value attached to the forecast is in relation to gains or loses that can be realized by using the forecast. The value of the forecast increases if it has been consistently accurate. 4 Timely: generated with sufficient lead time to enable useful planning including taking precautionary measures. Isaac Mugume (Mak) Lecture No.02 April 6, 2017 25 / 52
Chapter Two Introduction to Weather Analysis and Forecasting Weather analysis Weather reports Scientific weather forecasting Traditional weather forecasting systems Isaac Mugume (Mak) Lecture No.02 April 6, 2017 26 / 52
Weather analysis We have experienced a hot and sunny day due to the sky that has been clear all day. We expect the sky to remain clear at night and also expect unusually low night temperatures Isaac Mugume (Mak) Lecture No.02 April 6, 2017 27 / 52
Weather analysis... Weather analysis involves: examining the current state of the atmosphere; explaining the type of weather occurring and where it is taking place; understanding of how the weather became the way it is. Continuity is key during weather analysis and subsequent forecasting. It is also necessary that current weather should be measured accurately and should be completed in short time. Isaac Mugume (Mak) Lecture No.02 April 6, 2017 28 / 52
Weather reports The weather scientists prepare a couple of weather reports for different users. The most common ones are such as: SYNOP: METAR; TAF; SPECI: Isaac Mugume (Mak) Lecture No.02 April 6, 2017 29 / 52
SYNOP The SYNOP is a meteorological report for surface observations usually made at standard hours e.g. 0000Z, 0300Z, 0600Z, 0900Z, 1200Z, 1500Z, 1800Z, 2100Z It normally records: air temperature (dry bulb & wet bulb), visibility, clouds, pressure & pressure tendency, wind and derived quantities (i.e. VP, RH and DP). Data in SYNOP is transmitted globally so that forecasters can obtain a synoptic view of the globe the data plotted on the weather chart using the station plot model is obtained from SYNOP Isaac Mugume (Mak) Lecture No.02 April 6, 2017 30 / 52
SYNOP... Try decoding Isaac Mugume (Mak) Lecture No.02 April 6, 2017 31 / 52
METAR A METAR is a meteorological aviation routine weather report. it is usually used for aerodrome and made hourly or at 30 minutes interval it contains: report nature, location, date and time of observation, wind direction and speed, visibility, cloud type and height, temperature and pressure. It is important to frequently contact the METAR to understand the weather trend at aerodrome Isaac Mugume (Mak) Lecture No.02 April 6, 2017 32 / 52
METAR... Isaac Mugume (Mak) Lecture No.02 April 6, 2017 33 / 52
SPECI The SPECI is a special report prepared between METAR reporting times when significant weather of predefined criteria occurs such as drastic decline in visibility, start or stop of heavy rain. The format of the SPECI is the same like the METAR. The SPECI should have an identifier i.e. SPECI at the beginning of the report Isaac Mugume (Mak) Lecture No.02 April 6, 2017 34 / 52
TAF The TAF is Terminal Aerodrome Forecast which consists of expected meteorological conditions significant to aviation at an airport terminal for a given period. While preparing TAF, the forecaster should be aware of: 1 not provide greater details for operationally insignificant weather; 2 there will be successive amendments but should not just write for writing sake; 3 the most critical TAF period for operationally significant weather Isaac Mugume (Mak) Lecture No.02 April 6, 2017 35 / 52
TAF... Isaac Mugume (Mak) Lecture No.02 April 6, 2017 36 / 52
Additionally, the forecaster should consult prediction from different operational numerical models and incorporate: local effects; METARs; climatology; locally derived forecast rules; pilot reports (PIREPs) There are common terms used in TAF: TEMPO meaning temporary changes expected; BECMG meaning becoming; FM meaning from and PROB meaning probability Isaac Mugume (Mak) Lecture No.02 April 6, 2017 37 / 52
Weather forecasting Weather forecasting is a problem that requires to understand (explain) what is happening (also known as analysis) and state what is going to happen (forecast). The NOAA states the three basic methods of weather forecasting: persistence, experience and computer modeling. Isaac Mugume (Mak) Lecture No.02 April 6, 2017 38 / 52
Persistence method The persistence method considers that weather conditions will not change much and that the next forecast will largely be like to day. e.g. It will be sunny tomorrow like today The persistence methods works in slowly changing weather and possibly in very short forecast periods. It is thus not good for longer periods e.g. weeks or years. Figure: The persistent forecast method Isaac Mugume (Mak) Lecture No.02 April 6, 2017 39 / 52
Persistence method... to use persistence method, the forecast can analyze the METAR and if the conditions are not changing appreciably then he/she could probably consider persistence the forecaster could also look out for tendencies such as pressure tendency as indicators of varying weather conditions additionally, the forecaster could look our at the behavior of semi permanent weather systems like cyclones and anticyclones to see how they are changing. Isaac Mugume (Mak) Lecture No.02 April 6, 2017 40 / 52
Experience method The experience method considers that the weather conditions observed in history will repeat. e.g. When we have fog in the morning, it is likely that the day will be sunny The experience methods works for forecasters having long experience of the location and knowing the climatology of the area. It is also not good for longer periods but can work for short-time weather predictions. Although the experience method works most of the time, it can lead to false forecast if something new happens. Isaac Mugume (Mak) Lecture No.02 April 6, 2017 41 / 52
Use of Trends The trend method considers that weather systems are changing at a given rate the method also assumes that the rate will be maintained the method thus works well if the systems continue to vary at the same rate and in same direction the trend system fails to work if the systems slow down, change intensity, change direction or speed up. Example: Horizontal Visibility (in m) for the last 4 hours has been observed as: 8000, 7000, 6000, 5000. Determine the horizontal visibility for the next two hours Isaac Mugume (Mak) Lecture No.02 April 6, 2017 42 / 52
Use of models The model works well as it tries to incorporate the behavior of the system governing the evolution of weather. The major problem that affects models is if the desired input data is not available or is of poor quality. Additionally models may fail to predict new something new or a rare event. Examples of major numerical weather prediction models include: UK MET office, ECMWF, AROME-France, COSMO-by German etc. Isaac Mugume (Mak) Lecture No.02 April 6, 2017 43 / 52
Traditional methods of weather forecasting There are natural indicators that people developed over time to give a clue about coming weather / season. These have become known as indigenous knowledge system of weather and climate forecasting. The methods include the constellation of stars, behavior of animal, cloud cover and type, blossoming of certain trees, presence or absence of reptiles and migration of bird species. Isaac Mugume (Mak) Lecture No.02 April 6, 2017 44 / 52
Traditional methods of weather forecasting... Some methods of traditional knowledge systems approach to weather forecasting are given. 1 Red sky: the sky in the morning was taken to imply approach of bad weather and reddening of the sky in the evening to imply fair weather. This was coupled with determination of humidity by considering a hallo around the moon or sun. The science underpinning reddening is that it indicates the presence of particles in the atmosphere which scatter solar radiation. 2 Sea weed: sailors used the appearance of sea weed to indicate the presence of humidity. Sea weed blossoming indicated presence of humidity while drying of the sea weed indicated dry atmosphere. The sea weed thus gave a clue on upcoming rainfall season. Isaac Mugume (Mak) Lecture No.02 April 6, 2017 45 / 52
Traditional methods of weather forecasting... Additional methods of traditional knowledge systems approach to weather forecasting include: 1 Wind direction: the wind direction has been also used as an indicator of an approaching seasons or approaching weather. The wind direction was traditionally observed from blowing smoke or leaves. 2 Frogs: the presence of frogs indicated wet season and disappearance frogs a dry season has set in. 3 Night stars: the presence of stars at night was used as indicator of a cold night. Scientifically this implies clear sky and all stored radiation is lost to space thus leading to surface cooling. Other traditional weather forecasting indicators include the timing of fruiting by certain local trees, the water level in streams and ponds. Isaac Mugume (Mak) Lecture No.02 April 6, 2017 46 / 52
Chapter Three The weather charts Isaac Mugume (Mak) Lecture No.02 April 6, 2017 47 / 52
The weather charts present an analysis of the state of the atmosphere and are sometimes known as weather maps. These charts are prepared at different levels, surface chart, upper level charts (850hPa, 700hPa, 500hPa, 300hPa, 250hPa, 200hPa) Isaac Mugume (Mak) Lecture No.02 April 6, 2017 48 / 52
The surface chart The surface weather chart is usually known as synoptic weather map. It is a weather chart showing the state of the atmosphere over a large area of the given time. When analyzed, it has isolines e.g. isobars to give a clear and wider view of current weather conditions its biggest drawback is it has a lot of subjectivity during analysis Isaac Mugume (Mak) Lecture No.02 April 6, 2017 49 / 52
Station plot model The station plot model is used internationally to condense the different weather elements into visual groupings for each station. Raw weather data for individual stations is plotted on a map following a station plot model. It is a model that displays different types of numbers into visual groupings. The central circle, represents the station. The shading of the circle indicates cloud cover at the station while unshaded circle indicates clear skies. Isaac Mugume (Mak) Lecture No.02 April 6, 2017 50 / 52
Station plot model... Some parameters e.g. present or current weather, sky cover, winds are represented on a station model using symbols. These symbols include wind barbs, which use lines and flags to represent wind speeds. These lines and flags are oriented in the opposite direction in the Southern Hemisphere compared to the Northern Hemisphere. The long barb indicates wind of 10Kts, a short barb wind of 5Kts and a shaded barb indicating wind of about 50Kts. Isaac Mugume (Mak) Lecture No.02 April 6, 2017 51 / 52
Station plot model... The other weather parameters in the station model are represented numerically. Pressure is abbreviated as a three-number code, with the last digit representing the decimal. If the first number of the pressure reported on the station model is 4 or less, the sea level pressure is the number provided by placing a 10 in front of the three-number code and putting the decimal point in front of the last digit (e.g., 415 corresponds to 1041.5 mb). If the first number on the model is 6 or more, the sea level pressure is the number provided by placing a 9 in front of the three-number code (697 corresponds to a sea level pressure of 969.7 mb). Isaac Mugume (Mak) Lecture No.02 April 6, 2017 52 / 52