Lecture
Synoptic analysis — is a method of studying atmospheric processes over large territories for the purpose of preparing a weather forecast. It is based on a comprehensive assessment of data from weather stations, satellites, radiosondes, and other sources, displayed on synoptic charts.
The word «synoptic» comes from the Greek synoptikos — «able to see everything at once». This method makes it possible to:
Assess the current atmospheric situation.
Identify the dynamics of weather systems (cyclones, fronts, anticyclones).
Prepare a weather forecast based on the movement and transformation of these systems.
| Tool | Purpose |
|---|---|
| Synoptic charts | Display pressure, fronts, precipitation, temperature |
| Aerological diagrams | Show the vertical profile of the atmosphere |
| Satellite imagery | Record cloud cover, convection centers, frontal zones |
| Radar data | Track precipitation and thunderstorm phenomena |
Key elements studied in synoptic meteorology:
Air masses — large volumes of air with homogeneous properties.
Atmospheric fronts — boundaries between air masses.
Cyclones and anticyclones — areas of low and high pressure.
Pressure troughs and ridges — elongated pressure zones that affect wind and precipitation.
Jet streams — fast air currents in the upper troposphere.
Comprehensiveness — analysis of all available data.
Three-dimensionality — taking into account the vertical structure of the atmosphere.
Historical continuity — tracking changes over time.
A forecast consists of two stages:
Forecasting the synoptic situation — determining the future position of objects (fronts, cyclones, etc.).
Forecasting weather conditions — based on the position of the objects, temperature, precipitation, wind, and other parameters are assessed.
For an accurate one-day forecast, information is needed from a territory with a radius of about 1000 km, and for a two-day forecast — already 2000 km or more.
Continuous changes in the state of the weather are related, first and foremost, to the processes of the general circulation of the atmosphere.
In connection with changes in the weather, weather services have been established. In Russia this is the Hydrometeorological Center. Its tasks include:
1) timely notification of weather changes
2) providing short-term and long-term weather forecasts.
All meteorological data arrive at the Hydrometeorological Center from observation stations; this data is processed and plotted on a synoptic chart. Synoptic charts show the actual state of the atmosphere at a specific moment of observation: the distribution and characteristics of air masses and fronts; the location and properties of pressure systems; the type and location of cloud cover; the presence of precipitation; the distribution of temperatures, and so on. The charts are compiled from surface and upper-air observations. Analysis of synoptic charts makes it possible to obtain weather information for virtually any region of the globe.
The main and more labor-intensive task, however, is not reporting on current weather but forecasting expected changes, above all over a shorter period (1 – 2 days). In other words, it is necessary to determine how, over the next several tens of hours, synoptic objects (pressure systems, fronts, and air masses) will move and change.
At present, improvement in forecast quality is achieved through the use of computational forecasting methods — numerical time integration of the equations of atmospheric dynamics and thermodynamics, making extensive use of initial values of meteorological quantities.
It is far more difficult to give a long-range forecast (for a ten-day period, a month, a season, a year); the degree of accuracy in this case is inevitably lower than for short-term forecasts. For long-range forecasting, analysis of daily synoptic charts is no longer suitable. It becomes necessary to generalize charts over various periods of time.
Long-range forecasts are based on the analysis of synoptic charts over a certain period of time, proceeding from the assumption that similar subsequent development follows from the initial conditions in the real case. However, such assumptions are quite conditional, since small changes in the initial conditions can lead to an entirely different course of the process.
Data discreteness — observations may be lacking between stations.
Processing delay — the complexity of collecting and analyzing information.
Inability to cover oceans and hard-to-reach regions — ¾ of the Earth's surface is covered by water.
These limitations are partially compensated for by the use of interpolation, extrapolation, and also satellite and radar information.
Comments