The atmosphere is vast and complex and it is impossible to accurately monitor every part of it, so inevitably there are gaps in those observations. As a result, something can be missed or just not observed fully enough. A forecast for seven days from now will probably change before that day arrives. However, as our understanding of the atmosphere improves, alongside advances in computer technology, forecasts further into the future are becoming more accurate.
The Met Office says its four-day forecast is now as accurate as a one-day forecast was 30 years ago. And longer forecasts can still give a good steer on general trends, such as whether it will be wetter or drier than average. We can also use computers to model how our climate, rather than the day-to-day weather, might look many decades into the future.
Some weather patterns are particularly challenging when it comes to an accurate forecast for an individual location. Showers are such small-scale weather features, it is hard to predict exactly where they will develop. You may think the forecast was wrong because you were expecting showers but did not see any, whereas just a mile down the road there was a torrential thunderstorm.
There is more than one answer to the question "What will the weather do tomorrow? Many different organisations across the world produce weather forecasts, using different computer programs to do so. Some may predict a band of rain arriving somewhere at , while others may have it arriving after midnight. Different media organisations take weather forecasts from different providers and, depending on who you favour, you might see differences if you compare one to the other.
Statistical Method: Regression equations or other advanced relationships are formed between various weather elements and the subsequent climate in this method of weather forecasting.
Predictions or weather criteria are usually chosen based on a potential physical interaction with the predictants. Numerical Weather Prediction Techniques: Numerical weather prediction definition states that it forecasts weather using statistical models of the atmosphere and oceans dependent on current weather conditions. The action of the atmosphere is expressed in this system by a series of equations based on physical laws governing airflow, air pressure, and other data.
The method has been shown to be optimal for medium-term forecasts. A weather forecast is made up of three steps: observation and analysis, extrapolation to determine the state of the atmosphere in the future, and estimation of specific variables.
One method of qualitative extrapolation is to conclude the weather features will continue to travel in the same direction as they have been. Observation and analysis. Typically, these numerical models begin with data collected between the hours of and UTC 7 A. Eastern Standard Time, respectively. Furthermore, some "initialization" routines slightly change the data when it enters a prediction model only for that model.
Since more computing time is taken to do the work, the more precise the approximation, the more expensive the model is to use. There, a cutting-edge supercomputer is tasked with operating four primary models.
Two of the styles are concerned with North America and its environs. The other two versions surround the entire globe in a standardized manner. Each domain has a basic model that is intended for fast computation as an early update even though machine problems occur. For each domain, the other model is more comprehensive, giving a better solution at a higher cost. The first conceptual model of the life cycle of a surface cyclone showed that cyclonic storms typically formed along fronts, that is, boundaries between cold and warm air masses.
The model showed that precipitation is associated with active cold and warm fronts, and that this precipitation wraps around the cyclone as it intensifies. Though subsequent work demonstrated that fronts are not crucial to cyclogenesis, the Norwegian frontal cyclone model is still used in weather map analyses. See also: Cyclone ; Front. It was not until the late s that routine aerological observations had a substantial impact on forecasting. By the s, qualitatively reasonable numerical forecasts of the atmosphere were produced.
Numerical weather prediction techniques, in addition to being applied to short-range weather prediction, are used in such research studies as air-pollutant transport and the effects of greenhouse gases on global climate change.
See also: Air pollution ; Greenhouse effect ; Jet stream ; Upper-atmosphere dynamics. Though numerical forecasts continue to improve, statistical forecast techniques, once used exclusively with observational data available at the time of the forecast, are now used in conjunction with numerical output to predict the weather.
Statistical methods, based upon a historical comparison of actual weather conditions with large samples of output from the same numerical model, routinely play a role in the prediction of surface temperatures and precipitation probabilities. The recognition that small, barely detectable differences in the initial analysis of a forecast model often lead to very large errors in a 12—h forecast has led to experiments with ensemble forecasting.
This method uses results from several numerical forecasts to produce the statistical mean and standard deviation of the forecasts. Success with ensemble forecasting suggests it can be a useful tool in enhancing prediction skill and in assessing the atmosphere's predictability. See also: Dynamic meteorology. The best weather forecasts result from application of the synoptic method to the latest numerical and statistical information.
The forecaster has an ever-increasing number of valuable tools with which to work. Numerical forecast models, owing to faster computers, are capable of explicitly resolving mesoscale weather systems.
Geostationary satellites allow for continuous tracking of such dangerous weather systems as hurricanes Fig. The increased routine use of Doppler radar, automated commercial aircraft observations, and use of data derived from wind and temperature profiler soundings promise to give added capability in tracking and forecasting mesoscale weather disturbances.
Very high-frequency and ultrahigh-frequency Doppler radars may be used to provide detailed wind soundings. These wind profilers, if located sufficiently close to one another, will allow for the hourly tracking of mesoscale disturbances aloft. Ground- and satellite-based microwave radiometric measurements are being used to construct temperature and moisture soundings of the atmosphere. The assimilation of such data at varying times in the numerical model forecast cycle offers the promise of improved prediction and improved utilization of data and products by forecasters assisted by increasingly powerful interactive computer systems.
Medium-range forecasts, ranging up to two weeks, may be improved from knowledge of forecast skill in relationship to the form of the planetary-scale atmospheric circulation.
See also: Doppler radar ; Mesometeorology ; Meteorological radar ; Meteorological rocket ; Meteorological satellites ; Radar meteorology ; Satellite meteorology. Numerical weather prediction is the prediction of weather phenomena by the numerical solution of the equations governing the motion and changes of condition of the atmosphere.
The laws of motion of the atmosphere may be expressed as a set of partial differential equations relating the temporal rates of change of the meteorological variables to their instantaneous distribution in space. These equations are developed in dynamic meteorology. In principle, a prediction for a finite time interval can be obtained by summing a succession of infinitesimal time changes of the meteorological variables, each of which is determined by their distribution at a given instant of time.
However, the nonlinearity of the equations and the complexity and multiplicity of the data make this process impossible in practice. Instead, it is necessary to resort to numerical approximation techniques in which successive changes in the variables are calculated for small but finite time intervals over a domain spanning part or all of the atmosphere. Even so, the amount of computation is vast, and numerical weather prediction remained only a dream until the advent of the modern computer.
The accuracy of numerical weather prediction depends on 1 an understanding of the physical laws of atmospheric behavior; 2 the ability to define through observations and analysis the state of the atmosphere at the initial time of the forecast; and 3 the accuracy with which the solutions of the continuous equations describing the rate of change of atmospheric variables are approximated by numerical means. For such space and time scales, the poorly understood energy sources and frictional dissipative forces may be approximated by relatively simple formulations, and rather coarse horizontal resolutions — km or 60— mi may be used.
Great progress has been made in improving the accuracy of numerical weather prediction models. Forecasts for three, four, and five days have steadily improved. Because of the increasing accuracy of numerical forecasts, numerical models have become the basis for medium-range 1—10 days forecasts made by the weather services of most countries. See also: Mesometeorology. If, to the standard dynamic variables, the density of water vapor is added, it becomes possible to predict clouds and precipitation in addition to the air motion.
When a parcel of air containing a fixed quantity of water vapor ascends, it expands adiabatically and cools until it becomes saturated. Continued ascent produces clouds and precipitation. The most successful predictions made by this method are obtained in regions of strong rising motion, whether induced by forced orographic ascent or by horizontal convergence in well-developed cyclones.
The physics and mechanics of the convective cloud-formation process make the prediction of convective cloud and showery precipitation more difficult. In , the first operational numerical weather prediction model was introduced at the National Meteorological Center. This simplified barotropic model consisted of only one layer, and therefore it could model only the temporal variation of the mean vertical structure of the atmosphere.
By the early s, the speed of computers had increased sufficiently to permit the development of multilevel usually about 10—20 models that could resolve the vertical variation of the wind, temperature, and moisture. These multilevel models predicted the fundamental meteorological variables for large scales of motion.
Global models with horizontal resolutions as fine as km mi are used by weather services in several countries. Global numerical weather prediction models require powerful supercomputers to complete a day forecast in a reasonable amount of time. For example, a day forecast with a layer global model with horizontal resolution of km 90 mi requires approximately 10 12 calculations.
A supercomputer capable of performing 10 8 arithmetic operations per second would then require 10 4 s or 2. See also: Supercomputer. While global models were being implemented for operational weather prediction 1—10 days in advance, similar research models were being developed that could be applied for climate studies by running for much longer time periods.
The extension of numerical predictions to long time intervals many years requires a more accurate numerical representation of the energy transfer and turbulent dissipative processes within the atmosphere and at the air-earth boundary, as well as greatly augmented computing-machine speeds and capacities. With state-of-the-art computers, it is impossible to run global climate models with the same high resolution as numerical weather prediction models; for example, a hundred-year climate simulation with the numerical weather prediction model that requires 2.
Therefore, climate models must be run at lower horizontal resolutions than numerical weather prediction models typically km or mi. Predictions of mean conditions over the large areas resolvable by climate models are feasible because it is possible to incorporate into the prediction equations estimates of the energy sources and sinks—estimates that may be inaccurate in detail but generally correct in the mean.
Thus, long-term simulations of climate models with coarse horizontal resolutions have yielded simulations of mean circulations that strongly resemble those of the atmosphere. These simulations have been useful in explaining the principal features of the Earth's climate, even though it is impossible to predict the daily fluctuations of weather for extended periods.
Climate models have also been used successfully to explain paleoclimatic variations, and are being applied to predict future changes in the climate induced by changes in the atmospheric composition or characteristics of the Earth's surface due to human activities.
See also: Climate history ; Climate modification. Although the relatively coarse grids in global models are necessary for economical reasons, they are sources of two major types of forecast error. First, the truncation errors introduced when the continuous differential equations are replaced with approximations of finite resolution cause erroneous behavior of the scales of motion that are resolved by the models.
Second, the neglect of scales of motion too small to be resolved by the mesh for example, thunderstorms may cause errors in the larger scales of motion. In an effort to simultaneously reduce both of these errors, models with considerably finer meshes have been tested. However, the price of reducing the mesh has been the necessity of covering smaller domains in order to keep the total computational effort within computer capability. Thus the main operational limited-area model run at the National Meteorological Center has a mesh length of approximately 80 km 50 mi on a side and covers a limited region approximately two times larger than North America.
Because the side boundaries of this model lie in meteorologically active regions, the variables on the boundaries must be updated during the forecast. A typical procedure is to interpolate these required future values on the boundary from a coarse-mesh global model that is run first.
Although this method is simple in concept, there are mathematical problems associated with it, including overspecification of some variables on the fine mesh. Nevertheless, limited-area models have made significant improvements in the accuracy of short-range numerical forecasts over the United States. Even the small mesh sizes of the operational limited-area models are far too coarse to resolve the detailed structure of many important atmospheric phenomena, including hurricanes, thunderstorms, sea- and land-breeze circulations, mountain waves, and a variety of air-pollution phenomena.
Considerable effort has gone into developing specialized research models with appropriate mesh sizes to study these and other small-scale systems. Thus, fully three-dimensional hurricane models with mesh sizes of 8 km 5 mi simulate many of the features of real hurricanes. On even smaller scales, models with horizontal resolutions of a few hundred meters reproduce many of the observed features in the life cycle of thunderstorms and squall lines.
It would be misleading, however, to imply that models of these phenomena differ from the large-scale models only in their resolution. In fact, physical processes that are negligible on large scales become important for some of the phenomena on smaller scales.
For example, the drag of precipitation on the surrounding air is important in simulating thunderstorms, but not for modeling large scales of motion. Thus the details of precipitation processes, condensation, evaporation, freezing, and melting must be incorporated into realistic cloud models. In another class of special models, chemical reactions between trace gases are considered.
For example, in models of urban photochemical smog, predictive equations for the concentration of oxides of nitrogen, oxygen, ozone, and reactive hydrocarbons are solved. These equations contain transport and diffusion effects by the wind as well as reactions with solar radiation and other gases.
Such air-chemistry models become far more complex than atmospheric models as the number of constituent gases and permitted reactions increases. See also: Computer programming ; Digital computer ; Model theory. Surface meteorological observations are routinely collected from a vast continental data network, with the majority of these observations obtained from the middle latitudes of both hemispheres.
Commercial ships of opportunity, military vessels, and moored and drifting buoys provide similar in-place measurements from oceanic regions, although the data density is biased toward the principal global shipping lanes.
Information on winds, pressure, temperature, and moisture throughout the troposphere and into the stratosphere is routinely collected from 1 balloon-borne instrumentation packages radiosonde observations and commercial and military aircraft which sample the free atmosphere directly; 2 ground-based remote-sensing instrumentation such as wind profilers vertically pointing Doppler radars , the National Weather Service Doppler radar network, and lidars; and 3 special sensors deployed on board polar orbiting or geostationary satellites.
The remotely sensed observations obtained from meteorological satellites have been especially helpful in providing crucial measurements of areally and vertically averaged temperature, moisture, and winds in data-sparse mostly oceanic regions of the world.
Such measurements are necessary to accommodate modern numerical weather prediction practices and to enable forecasters to continuously monitor global storm such as hurricane activity. See also: Lidar ; Meteorological instrumentation ; Radar meteorology. At major operational weather prediction centers such as the National Center for Environmental Prediction NCEP, formerly known as the National Meteorological Center or the European Centre for Medium Range Weather Forecasts, ECMWF , the global meteorological observations are routinely collected, quality-checked, and mapped for monitoring purposes by humans responsible for overseeing the forecast process.
At NCEP and ECMWF and other centers the global observational data stream is further machine-processed in order to prepare a full three-dimensional set of global surface and upper air analyses of selected meteorological fields at representative time periods.
The typical horizontal and vertical resolution of the globally gridded analyses is about km 60 mi and 25—50 hectapascals millibars , respectively. Preparation of these analyses requires a first-guess field from the previous numerical model forecast against which the updated observations are quality-checked and objectively analyzed to produce an updated global gridded set of meteorological analyses. These updated analyses are modified as part of a numerical procedure designed to ensure that the gridded meteorological fields are dynamically consistent and suitable for direct computation in the new forecast cycle.
This data assimilation, analysis, and initialization procedure, known as four-dimensional data assimilation, was at one time performed four times daily at the standard synoptic times of , , , and UTC. The four-dimensional data assimilation is performed almost continuously, given that advanced observational technologies such as wind profilers; automated surface observations; automated aircraft-measured temperature, moisture, and wind observations have ensured the availability of observations at other than the standard synoptic times mentioned above.
An example is the rapid update cycle RUC mesoscale analysis and forecast system used at NCEP to produce real-time surface and upper air analyses over the United States and vicinity every 3 h and short-range out to 12 h forecasts.
The rapid update cycle system takes advantage of high-frequency data assimilation techniques to enable forecasters to monitor rapidly evolving mesoscale weather features. The forecast models used at NCEP and ECMWF and the other operational prediction centers are based upon the primitive equations that govern hydrodynamical and thermodynamical processes in the atmosphere.
The closed set of equations consists of the three momentum equations east-west, north-south, and the vertical direction , a thermodynamic equation, an equation of state, a continuity equation, and an equation describing the hydrological cycle.
Physical processes such as the seasonal cycle in atmospheric radiation, solar and long-wave radiation, the diurnal heating cycle over land and water, surface heat, moisture and momentum fluxes, mixed-phase effects in clouds, latent heat release associated with stratiform and convective precipitation, and frictional effects are modeled explicitly or computed indirectly by means of parametrization techniques.
A commonly used vertical coordinate in operational prediction models is the sigma coordinate, defined as the ratio of the pressure at any point in the atmosphere to the surface station pressure.
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