Change institution. Rent or Buy article Get time limited or full article access on ReadCube. References 1. Close banner Close. Email address Sign up. Get the most important science stories of the day, free in your inbox. They zip around our planet from pole to pole 14 times per day. Because they orbit while the Earth is rotating below, these satellites can see every part of Earth twice each day.
By watching these global weather patterns, polar orbiting satellites can help meteorologists accurately predict long-term forecasts—up to 7 days in the future. Polar orbiting satellites get a complete view of Earth each day by orbiting from pole to pole.
Because the Earth spins, the satellite sees a different part of Earth with each orbit. It captures a picture of the entire planet as a series of wedges that then be pieced back together, as in the image above. It provides space weather alerts and forecasts while also monitoring the amounts of solar energy absorbed by Earth every day. These factors are important in making air quality forecasts.
Polar orbiting satellites provide the information most useful for long-term weather forecasting. The use of these observations was beneficial in the southern hemisphere but not in the northern, where these data were even ignored for a while, because of the greater availability of upper-air radiosonde data.
Noteworthy improvements in forecasting were achieved with the introduction of the three-dimensional variational assimilation 3D VAR procedure in , followed by the four-dimensional variant 4D VAR in In this assimilation process, all data within a hour period are used simultaneously in one global iterative estimation process.
The 4D VAR aims to find the hour forecast that best fits the available observations. The single most significant improvement in the forecast accuracy of numerical models during the past decade can be attributed to changes in the way that vertical sounding observations specifically TIROS Operational Vertical Sounder data from satellites were used in data assimilation.
This development was spearheaded by work done at the U. At the WMO's Commission for Basic Systems meeting in St Petersburg in , 7 twenty recommendations were advanced for the evolution and further improvement of the space-based subsystem of the Global Observing System. These proposals call for the calibration of instruments and more timely data with a greater temporal and spatial resolution. More specifically, satellite agencies should continue to provide and improve vertical air-temperature and radiance profiles, sea-surface temperatures, humidity and wind profiles, sea-surface wind data, estimates of precipitation, aerosol distribution and accurate measurements of cloud-top and cloud-base heights.
Numerical weather-prediction models play a dominant part in the second phase of the weather forecasting process. Six basic, or primitive, equations are used to describe the dynamical processes in the atmosphere.
The hydrostatic equation is an approximation of the real atmosphere and is valid only for horizontal scales greater than 20 km. Much of the energy driving atmospheric motions comes from long-wave radiation. These processes include incident solar radiation, outgoing long-wave radiation, turbulence, friction, the formation, occurrence and influence of clouds, convective activities, and the absorption of energy by land and water surfaces.
Bengtsson 2 gives a comprehensive account of the history of NWP, dividing its development into four phases. The first is characterized by the ongoing evolution of barotropic and simple baroclinic models over limited spatial areas. The second phase covers the period from to the mids, when hemispheric models based on the primitive equations describing the dynamical motions of the atmosphere were gradually implemented.
In addition, models simulating the general circulation of the atmosphere were developed. The useful predictive skill of these models over most of the northern hemisphere was extended from a day or two in the s to about three days through the s and s.
During the third phase, the integration domain was extended over the whole globe and models to resolve climate simulations became feasible. This was achieved by the establishment of a global observing system and the rapid increase in computing power. The fourth phase, starting in the early s, was driven by the enormous increase in computing power available. More focus was placed on efforts to reduce errors in the initial state of the model. Operational forecasts have improved greatly since the turn of the century.
These advances came about through better data assimilation, the greater numbers of improved satellite observations, refinements in the way physical processes are represented, and from superior vertical and horizontal resolution in the models. Global models with a horizontal resolution of 40 km and with 60 vertical levels became a reality, so that useful predictions of about 7 days were achieved for both hemispheres.
Figure 3 shows recent improvements in the accuracy of mean sea-level pressure predictions, for three, four and five days ahead, of the ECMWF NWP model for the southern hemisphere. The three-day prediction for the northern hemisphere is shown for comparison.
This meant that the effective horizontal resolution was improved to 25 km and vertical levels were increased to The mean verification scores, which measure accuracy, were generally better for the higher-resolution model.
Burger to Sweden. This represented a major increase in computing power. As part of the procurement of the system, the Weather Bureau obtained a five-level, primitive-equation model for the southern hemisphere together with a data-analysis program based on pattern recognition techniques.
This NWP system was operated from early to mid Model-output fields became freely available and the Weather Bureau was obliged to use the numerical guidance of the U. The operational use of these products improved weather forecasting in South Africa significantly, particularly up to four days in advance. Thus, this model enabled the Weather Bureau to predict, three days ahead, the September floods over KwaZulu-Natal and the floods over the central parts of the country.
While the NWP products from Washington and Bracknell were used in all the forecasting offices in South Africa, the operation of locally developed NWP models during this time was less effective. The Weather Bureau acquired a new hemisphere model to replace the old Primitive Equation Hemisphere model, but the rest of the system analysis, assimilation and postprocessing procedures had to be developed in-house. A lack of the requisite skills and of an adequate computer hampered the project and jeopardised the implementation of the new model.
At the time, the Weather Bureau obtained a complete suite of forecasting programs from the U. National Weather Service. The prediction model in the suite was the current state-of-the-art, 'step-mountain', the so called Eta-model. The model was last upgraded in July , when the horizontal resolution was 32 km and the vertical levels had been increased to The root-mean-square error RMSE of the hour prediction of the mean sea-level pressure diminished to an average of 2.
To merge successful A. This new technique let the authors use standard machine learning techniques, developed for 2-D images, for weather forecasting.
The authors then tested their model by predicting the global height of the hectopascal pressure, a standard variable in weather forecasting, every 12 hours for a full year.
A recent paper , which included Weyn as a co-author, introduced WeatherBench as a benchmark test for data-driven weather forecasts. On that forecasting test, developed for three-day forecasts, this new model is one of the top performers.
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