CN113075751A - Method and system for fusing observation data in short-term forecasting - Google Patents
Method and system for fusing observation data in short-term forecasting Download PDFInfo
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Abstract
The application discloses a method and a system for fusing observation data in a short-term forecasting process, wherein the method comprises the following steps: step 1: acquiring meteorological site observation data in real time; step 2: fusing the observation data in the step 1 into a mode forecasting field of a corresponding time in the short-term forecasting system to obtain a mode forecasting result; and step 3: carrying out multi-factor extrapolation prediction based on the mode prediction result obtained in the step (2) to obtain an extrapolation result; and 4, step 4: and (4) outputting a final forecasting result based on the mode forecasting result in the step (2) and the extrapolation result in the step (3) according to the type and the duration of the forecasted product. The invention adopts a real-time data fusion and extrapolation short-circuit forecasting system to carry out the fusion assimilation and extrapolation forecasting technical research of regional ground observation data in a numerical forecasting product, the fusion meteorological site observation in the short-circuit forecasting system has good effect on short-circuit forecasting, and the resolution, rolling frequency and accuracy of conventional elements and rainfall are greatly improved.
Description
Technical Field
The invention belongs to the technical field of power grid meteorological prediction, and relates to a method and a system for fusing observation data in short-term forecasting.
Background
The requirements of power grid production on the early warning precision and accuracy of meteorological services and the influence analysis of meteorological factors on power grid production are increasingly urgent, but the weather forecast and early warning contents are not effectively combined with the power grid. At present, weather forecasts and weather early warning information issued by all weather early warning systems are completely the same as or slightly changed from early warning information issued by weather departments facing the social public, actual requirements of power grid production are not considered, the weather information provided by the weather departments generally takes the day as a unit, the requirements of different production, operation, maintenance and emergency periods of a power grid on the weather information cannot be met, the precision of the weather forecasts in the aspects of space and geography cannot meet the requirements of the power grid production, and the existing problems are more obvious.
At present, data fusion analysis in the short-term and forthcoming weather forecast at home and abroad is performed fusion and analysis based on weather basic data, data fusion is performed by means of a fusion extrapolation flow field method, an extrapolation method, a mode forecast weighting method and the like, and a near-ground weather element forecast product with high resolution, high frequency rolling and high accuracy required by power grid weather forecast and early warning cannot be provided.
Disclosure of Invention
In order to overcome the defects in the prior art, the application provides a method and a system for fusing observation data in the short-term forecasting.
In order to achieve the above purpose, the invention adopts the following technical scheme:
a method for fusing observation data in a short-term forecast is characterized by comprising the following steps:
the method comprises the following steps:
step 1: acquiring meteorological site observation data in real time;
step 2: fusing the observation data in the step 1 into a mode forecasting field of a corresponding time in the short-term forecasting system to obtain a mode forecasting result;
and step 3: carrying out multi-factor extrapolation prediction based on the mode prediction result obtained in the step (2) to obtain an extrapolation result;
and 4, step 4: and (4) outputting a final forecasting result based on the mode forecasting result in the step (2) and the extrapolation result in the step (3) according to the type and the duration of the forecasted product.
The invention further comprises the following preferred embodiments:
preferably, in the step 1, meteorological station observation data are obtained by adopting automatic station multi-element observation, radar QPE observation and satellite cloud picture observation;
the meteorological station observation data obtained by the automatic station multi-element observation comprises: the temperature, the humidity, the rainfall, the wind direction, the wind speed description and the wind direction description of the position of the station are obtained;
the meteorological site observation data acquired by the radar QPE observation comprise: the vertical distribution of wind, atmospheric turbulence and atmospheric stability in a clear-air atmosphere;
the meteorological site observation data acquired by satellite cloud picture observation comprises: high altitude large-scale water vapor situation and cloud amount condition.
Preferably, the short-term forecasting system in step 2 generates a three-dimensional analysis field and a short-term proximity forecasting field of temperature, humidity and wind per hour, a two-dimensional cloud amount analysis field and a forecasting field per hour, a precipitation analysis field and an adjacent forecasting field every 15 minutes, and an hourly convection diagnosis analysis field and a forecasting field based on fusion analysis of numerical forecasting, terrain and earth surface, satellite radar and observation data.
Preferably, in step 3, the forecast elements of the multi-element extrapolation forecast include: temperature 2 meters off the ground, relative humidity 2 meters off the ground, three-dimensional wind field, surface temperature, normal precipitation, convective precipitation, gust and convective diagnostic parameters.
Preferably, step 3 is specifically:
and (4) forecasting the future moving speed and intensity change of the weather system in a time-wise extension mode according to the mode forecasting result obtained in the step (2).
Preferably, in step 4,
for the production of precipitation forecasts,
the extrapolation result of the step 3 is adopted for the final forecast result within 3 hours in 0-3 hours;
3-12 hours, the final forecast result within the time length of 3 hours is not contained, and a fusion result of the mode forecast result in the step 2 and the extrapolation result in the step 3 is adopted;
for a non-precipitation forecast product,
the final forecast result within the time length of 6 hours in 0-6 hours is subjected to extrapolation by the step 3;
and (3) the final forecast result within the time length of 6-12 hours without 12 hours is subjected to extrapolation forecast result and numerical forecast fusion result in the step 3.
The invention also discloses a system for fusing the observation data in the short-term forecasting, which comprises the following steps:
the observation data acquisition module is used for acquiring observation data of the meteorological station in real time;
the mode forecasting module is used for fusing the observation data into a mode forecasting field of a corresponding time in the short-term forecasting system to obtain a mode forecasting result;
the extrapolation module is used for developing multi-factor extrapolation prediction based on the mode prediction result to obtain an extrapolation result;
and the fusion forecasting module is used for outputting a final forecasting result based on the mode forecasting result and the extrapolation result according to the type and the duration of the forecasted product.
The beneficial effect that this application reached:
the invention adopts a real-time data fusion and extrapolation short-circuit forecasting system to carry out fusion assimilation and extrapolation forecasting technical research of regional ground observation data in a numerical forecasting product, is characterized by fusing the observation data in real time to a corresponding temporal mode forecasting field, carries out multi-element extrapolation forecasting based on a motion vector of a fused analysis field and mode forecasting, has good effect on short-circuit forecasting by fusing meteorological site observation in the short-circuit forecasting system, and greatly improves the resolution, rolling frequency and accuracy of conventional elements (temperature, wind speed, wind direction, humidity and the like) and precipitation after assimilating and fusing meteorological sites and radar data along a power grid of a forecasting region by applying the short-circuit forecasting system.
Drawings
FIG. 1 is a flow chart of the method of the present invention;
FIG. 2 is a comparison between the predicted wind speed aging and the observed value after adding station observation data fusion and not adding station observation data fusion in the short-term forecasting system;
FIG. 3 is a comparison between the wind direction aging and observation values with forecast after adding station observation data fusion and not adding station observation data fusion in the short-term forecasting system;
FIG. 4 is a comparison between the predicted aging and observed values of the temperature after the fusion of station observation data and the fusion of non-station observation data in the short-term forecasting system;
FIG. 5 is a comparison between the predicted aging and observed values of relative humidity after the fusion of station observation data and the fusion of non-station observation data in the short-term forecasting system;
FIG. 6 is a graph of the increase in absolute error of relative humidity as a function of forecast age;
FIG. 7 is a curve showing the time-dependent increase of absolute temperature error at 2m from the ground;
FIG. 8 is a curve of the time-dependent growth of the absolute error of wind speed 10m above the ground;
FIG. 9 is a curve of the time-dependent growth of the absolute error of the wind direction 10m from the ground along with the forecast;
FIG. 10 is a diagram illustrating the effect of precipitation forecasting in the forecasting region according to the present invention.
Detailed Description
The present application is further described below with reference to the accompanying drawings. The following examples are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present application is not limited thereby.
As shown in fig. 1, the method for fusing observation data in the short-term forecasting of the present invention includes the following steps:
step 1: acquiring meteorological site observation data in real time;
in specific implementation, meteorological station observation data are obtained by adopting a mode of automatic station multi-element observation, radar QPE (quantitative precipitation estimation) observation and satellite cloud picture observation;
the meteorological station observation data obtained by the automatic station multi-element observation comprises: the temperature, the humidity, the rainfall, the wind direction, the wind speed description and the wind direction description of the position of the station are obtained;
the meteorological site observation data acquired by the radar QPE observation comprise: the vertical distribution of atmospheric dynamics parameters such as wind, atmospheric turbulence and atmospheric stability in clear air atmosphere;
the meteorological site observation data acquired by satellite cloud picture observation comprises: high altitude large-scale water vapor situation and cloud amount condition.
Step 2: fusing the observation data in the step 1 into a mode forecasting field of a corresponding time in the short-term forecasting system to obtain a mode forecasting result;
the short-term forecasting system is also called an international forecasting numerical simulation system (INCA) and is a forecasting system formed by utilizing key technologies such as new-generation weather radar quality control, three-dimensional jigsaw puzzle, wind field inversion, precipitation estimation and the like.
And 2, generating a three-dimensional analysis field and a short-time approach prediction field of temperature, humidity and wind per hour, a two-dimensional cloud cover analysis field and a prediction field per hour, a precipitation analysis field and an adjacent prediction field every 15 minutes, and an hourly convection diagnosis analysis field and a prediction field by the short-time approach prediction system based on the fusion analysis of numerical prediction, terrain and earth surface, satellite radar and observation data.
The numerical forecast refers to a method for predicting the atmospheric motion state and weather phenomenon in a certain time period by using a large-scale computer to perform numerical calculation under certain initial value and boundary conditions according to the actual atmospheric conditions, and is the basis of the method.
The numerical prediction initialization includes a plurality of methods including static initialization, dynamic iteration, normal wave method, variation method and the like, and aims to achieve or approach the balance of a wind pressure field so as to eliminate false gravity inertia waves.
The boundary conditions are two: one is a vertical boundary condition, the other is a horizontal boundary condition, generally, a vertical boundary limit assignment is required, the horizontal boundary must be artificially given a boundary condition, and the boundary condition has a fixed boundary condition, a boundary condition with a normal speed of zero and the like, which are reprocessing of observed or analyzed values, specific analysis of specific situations and no fixed single method.
And step 3: and (3) carrying out multi-factor extrapolation prediction based on the mode prediction result obtained in the step (2) to obtain an extrapolation result, which specifically comprises the following steps:
and (4) forecasting the future moving speed and intensity change of the weather system in a time-wise extension mode according to the mode forecasting result obtained in the step (2).
A calculation method is extended in a time-sequential manner, which can be roughly explained as a mode similar to loop iteration, and the forecast result iteration is used for forecasting future meteorological development changes.
Extrapolation is used to predict the movement and intensity of the high and low pressure systems and grooves and ridges.
The forecast elements of the multi-element extrapolation forecast include: 2m temperature off the ground, 2m relative humidity off the ground, three-dimensional wind field, surface temperature, normal precipitation, convective precipitation, gust and convective diagnostic parameters;
convective precipitation refers to strong precipitation caused by a short-time strong convection process, and is mainly different from ordinary precipitation in whether a squall line exists or not, wherein the precipitation is scoped, and the convective precipitation is short-time local precipitation of the squall line.
Gusts refer to short term, high wind processes resulting from squall line processes, typically above level 8.
And 4, step 4: outputting a final forecasting result based on the mode forecasting result of the step 2 and the extrapolation result of the step 3 according to the type and the duration of the forecasted product;
and 2-9, analyzing the output of the step 2, wherein the comparison between the wind speed, wind direction, temperature and relative humidity and the observation values after the station observation data fusion is added and the station observation data fusion is not added in the short-term forecasting system is respectively shown in the graphs 2-5.
The comparison between the observed values and the wind speed, the wind direction, the temperature and the relative humidity obtained after the meteorological site observation data and the non-meteorological site observation data are fused in the short-term forecasting system obviously shows that after the meteorological site observation data are added, the element forecasting and the live observation of the short-term forecasting system tend to be consistent in the first 6 hours, and after 6 hours, the effect of the fused meteorological site observation data in the short-term forecasting system is weakened.
As can be seen from the sensitivity tests in FIGS. 2-5, the fusion of the meteorological site observation data in the short-term forecasting system has a good effect on the short-term forecasting.
The regional mode field data (BJRUC) of the short-term forecasting product and the synchronized input short-term forecasting system and the conventional observation data of 119 national weather stations in the province are subjected to statistical comparison analysis of the same parameters, and the influence of data assimilation on the ground element forecasting performance is tested.
FIGS. 6-9 are curves of absolute errors of relative humidity, air temperature 2m above the ground, wind speed 10m, and wind direction 10m, respectively, with the time-dependent increase of the prediction, where NWP PCST and NOWCASTING respectively represent numerical prediction and fusion prediction of the present invention, and FIGS. 6-9 show that: forecasting the forecast errors of the temperature, the humidity, the wind speed and the wind direction slowly increase from the analysis time to 12 hours, and the forecast absolute error increase condition of the INCA system of each element is as follows:
the temperature is increased from 0.3 degrees to 1.5 degrees, the relative humidity error is increased from 3 percent to 10 percent, the wind speed is increased from 0.3m/s to 1.8m/s, and the wind direction is increased from 30 degrees to 50 degrees;
the prediction accuracy is equivalent to the application level of INCA in Austria, and the effect of INCA prediction of each element is superior to the numerical prediction result.
According to the analysis verification of the figures 2-9, the extrapolation results are used as the short-term (0-3 hours of precipitation, 0-6 hours of others) relatively reliable and real, and the extrapolation results of the 3-12 and 6-12 hours of time periods are slightly poor in accuracy relative to the short-term forecast;
the target of the short-term forecasting aims at the summer strong convection process, the occurrence of the summer strong convection generally has the phenomena of short-term strong precipitation, thunderstorm strong wind, tornado, hail, squall lines and the like, and the strong precipitation is the main expression form of the occurrence of the domestic strong convection at present, so the forecasting products are discussed as precipitation and non-precipitation.
Specifically, the method comprises the following steps:
for the production of precipitation forecasts,
the extrapolation result of the step 3 is adopted for the final forecast result within 3 hours in 0-3 hours;
3-12 hours, the final forecast result within the time length of 3 hours is not contained, and a fusion result of the mode forecast result in the step 2 and the extrapolation result in the step 3 is adopted;
for a non-precipitation forecast product,
the final forecast result within the time length of 6 hours in 0-6 hours is subjected to extrapolation by the step 3;
and (3) the final forecast result within the time length of 6-12 hours without 12 hours is subjected to extrapolation forecast result and numerical forecast fusion result in the step 3.
The fusion is an algorithm or a model of meteorological data processing, can be understood as a result of mode prediction and extrapolation prediction smoothing, and can be directly applied.
Analyzing the output of the step 4 to obtain a diagram 10, namely, the rainfall forecast effect test in a forecast area of the invention, wherein NWP and NOWC respectively represent NWP PCST: numerical prediction, NOWCASTING: fusion forecasting;
and (3) displaying the inspection result of the precipitation lattice site field:
the hourly TS score of the short-term forecasting system gradually decreases from 0.74 to 0.51 in 12 hours, the hourly TS score of light rain decreases from 0.7 to 0.45 in 12 hours, the hourly TS score of moderate rain decreases from 0.35 to 0.1 in 6 hours, and the hourly TS score of heavy rain decreases from 0.1 to 0.03 in two hours;
the TS score for any precipitation grade is higher for INCA than for numerical forecast precipitation.
Through the statistical test and analysis, after the short-term forecasting system is applied to assimilate and fuse thousands of regional station data and 14 radar data of a forecasting region, the forecasting effect of conventional factors (temperature, wind speed, wind direction, humidity and the like) and rainfall is improved, and the effect of the short-term forecasting system is optimal compared with the effect of a background field BJRUC accessed by the short-term forecasting system within the forecasting time of 12 hours.
The present applicant has described and illustrated embodiments of the present invention in detail with reference to the accompanying drawings, but it should be understood by those skilled in the art that the above embodiments are merely preferred embodiments of the present invention, and the detailed description is only for the purpose of helping the reader to better understand the spirit of the present invention, and not for limiting the scope of the present invention, and on the contrary, any improvement or modification made based on the spirit of the present invention should fall within the scope of the present invention.
Claims (7)
1. A method for fusing observation data in a short-term forecast is characterized by comprising the following steps:
the method comprises the following steps:
step 1: acquiring meteorological site observation data in real time;
step 2: fusing the observation data in the step 1 into a mode forecasting field of a corresponding time in the short-term forecasting system to obtain a mode forecasting result;
and step 3: carrying out multi-factor extrapolation prediction based on the mode prediction result obtained in the step (2) to obtain an extrapolation result;
and 4, step 4: and (4) outputting a final forecasting result based on the mode forecasting result in the step (2) and the extrapolation result in the step (3) according to the type and the duration of the forecasted product.
2. The method of claim 1, wherein the observation data is fused in the nowcast forecast, and the method further comprises:
in the step 1, acquiring meteorological station observation data by adopting automatic station multi-element observation, radar QPE observation and satellite cloud picture observation;
the meteorological station observation data obtained by the automatic station multi-element observation comprises: the temperature, the humidity, the rainfall, the wind direction, the wind speed description and the wind direction description of the position of the station are obtained;
the meteorological site observation data acquired by the radar QPE observation comprise: the vertical distribution of wind, atmospheric turbulence and atmospheric stability in a clear-air atmosphere;
the meteorological site observation data acquired by satellite cloud picture observation comprises: high altitude large-scale water vapor situation and cloud amount condition.
3. The method of claim 1, wherein the observation data is fused in the nowcast forecast, and the method further comprises:
and 2, generating a three-dimensional analysis field and a short-time approach prediction field of temperature, humidity and wind per hour, a two-dimensional cloud cover analysis field and a prediction field per hour, a precipitation analysis field and an adjacent prediction field every 15 minutes, and an hourly convection diagnosis analysis field and a prediction field by the short-time approach prediction system based on the fusion analysis of numerical prediction, terrain and earth surface, satellite radar and observation data.
4. The method of claim 1, wherein the observation data is fused in the nowcast forecast, and the method further comprises:
in step 3, the forecast elements of the multi-element extrapolation forecast comprise: temperature 2 meters off the ground, relative humidity 2 meters off the ground, three-dimensional wind field, surface temperature, normal precipitation, convective precipitation, gust and convective diagnostic parameters.
5. The method of claim 1, wherein the observation data is fused in the nowcast forecast, and the method further comprises:
the step 3 specifically comprises the following steps:
and (4) forecasting the future moving speed and intensity change of the weather system in a time-wise extension mode according to the mode forecasting result obtained in the step (2).
6. The method of claim 1, wherein the observation data is fused in the nowcast forecast, and the method further comprises:
in the step 4, the process of the method,
for the production of precipitation forecasts,
the extrapolation result of the step 3 is adopted for the final forecast result within 3 hours in 0-3 hours;
3-12 hours, the final forecast result within the time length of 3 hours is not contained, and a fusion result of the mode forecast result in the step 2 and the extrapolation result in the step 3 is adopted;
for a non-precipitation forecast product,
the final forecast result within the time length of 6 hours in 0-6 hours is subjected to extrapolation by the step 3;
and (3) the final forecast result within the time length of 6-12 hours without 12 hours is subjected to extrapolation forecast result and numerical forecast fusion result in the step 3.
7. A system for fusion of observations in nowcasting according to any one of claims 1 to 6, comprising:
the system comprises:
the observation data acquisition module is used for acquiring observation data of the meteorological station in real time;
the mode forecasting module is used for fusing the observation data into a mode forecasting field of a corresponding time in the short-term forecasting system to obtain a mode forecasting result;
the extrapolation module is used for developing multi-factor extrapolation prediction based on the mode prediction result to obtain an extrapolation result;
and the fusion forecasting module is used for outputting a final forecasting result based on the mode forecasting result and the extrapolation result according to the type and the duration of the forecasted product.
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