CN113158139A - Downscale product error calculation method for satellite observation rainfall data - Google Patents
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Abstract
The invention discloses a downscale product error calculation method for satellite observation rainfall data, which comprises the following steps: dividing a target drainage basin into a plurality of grid units, acquiring each grid unit where a ground observation station is located in each grid unit, calculating the space weight value of the urbanization index of all grid units where the ground observation station is located and the error between the downscale product of satellite observation rainfall data and the ground station observation rainfall data, calculating the time weight value of rainfall observation quantity acquired by the ground observation station at each moment, and further calculating the error of the downscale product of satellite observation target drainage basin rainfall data when the space distribution and the time distribution are taken into account. The method provided by the invention is simple, and the error result of the calculated downscale product for the satellite rainfall observation data is high in accuracy and good in reliability.
Description
Technical Field
The invention relates to the technical field of hydrology, in particular to a downscale product error calculation method for satellite observation rainfall data.
Background
The satellite rainfall observation has the advantages of wide coverage range and high automation degree as a novel rainfall observation means. However, the resolution of the satellite rainfall observation data is usually not high, and the spatial resolution of the satellite rainfall observation data needs to be improved by combining a downscaling algorithm to generate a downscaling product of the satellite rainfall observation data so as to further improve the applicability of the satellite rainfall observation data. In recent years, downscale products for satellite rainfall observation data are continuously abundant, and how to select proper downscale products for satellite rainfall observation data according to rainfall spatio-temporal characteristics of application areas becomes an important problem to be solved urgently.
The method for evaluating the error of the downscale product of the satellite rainfall data is widely applied at home and abroad by taking the rainfall data observed by the ground observation station as a true value to evaluate the error of the downscale product of the satellite rainfall data. However, most of the existing error evaluation methods for the scale-down products of satellite rainfall data do not consider the rainfall space-time distribution characteristics of application areas, and the accuracy of calculation results is poor. In fact, for errors of the same magnitude, it is more dangerous to occur in regions with high urbanization degree and in periods of concentrated rainfall. If the condition cannot be taken into account in the error evaluation process of the downscale products of the satellite observation rainfall data, the error caused by the downscale products of the selected satellite observation rainfall data is often too large, and timely and effective rainfall observation information cannot be provided for densely populated urban areas, so that the probability of missing report of the occurrence of the rainstorm secondary disaster is increased, and certain hidden danger is brought to the prevention and treatment of the rainstorm secondary disaster.
How to quantify the space-time distribution characteristics of the downscale products of the satellite observation rainfall data in the application area, and selecting the appropriate downscale products of the satellite observation rainfall data according to local conditions, thereby improving the capacity of coping with the rainstorm secondary disaster to a certain extent, and being one of the key points and difficulties in the development process of the downscale products of the satellite observation rainfall data.
In order to further promote the development of the downscale product of the satellite observation rainfall data, a downscale product error evaluation method of the satellite observation rainfall data under the condition of uneven rainfall spatial-temporal distribution needs to be studied more deeply.
The town index (NDBI) is an important index which is obtained by carrying out normalization calculation based on spectral data provided by the satellite remote sensing image and reflects the town construction level. Generally, the larger the town index, the higher the level of urbanization, the denser the population, and the greater the importance of preventing floods from rainstorm. The rain peak is the most concentrated part in the rainfall process, the rainfall intensity is higher, and the fast rising flood is more easily generated. Therefore, to further evaluate the precision of the downscale product of the satellite observation rainfall data, the space-time distribution characteristics of errors of the rainfall downscale product are considered on the basis of the town index and the rain peak. Therefore, for the defects in the existing error evaluation method for the downscale product of the satellite rainfall data, how to quantify the time-space distribution characteristics of rainfall in the error evaluation process of the downscale product of the satellite rainfall data is considered, so that the reliability of the error evaluation of the downscale product of the satellite rainfall data is improved, and the problem needs to be solved by the inventor.
Disclosure of Invention
The purpose of the invention is as follows: the downscale product error calculation method of the satellite observation rainfall data is provided, wherein the downscale product error calculation method takes the space-time distribution characteristics of rainfall downscale product errors into consideration, and the accuracy is high.
The technical scheme is as follows: the invention provides a downscaling product error calculation method for satellite observation rainfall data, which is characterized in that the downscaling product error calculation method is used for acquiring the downscaling product error of satellite observation target river basin rainfall data, and comprises the following steps:
step 1: dividing the target drainage basin into a plurality of grid units based on the digital elevation data of the target drainage basin, and then entering step 2;
step 2: acquiring each grid unit where the ground observation station is located in each grid unit, and then entering step 3;
and step 3: respectively executing the step A and the step B aiming at each grid unit N, N is 1,2 … N, N is the total number of the grid units where the ground observation station is located, and further obtaining the spatial weight values of the urbanization indexes of all the grid units where the ground observation station is located and the errors between the down-scale products of the satellite observation rainfall data and the rainfall observation data of the ground observation station:
step A: urbanization index mu according to grid cell nnCombining the urbanization indexes of the grid units where other ground observation stations except the grid unit n are locatedCalculating a spatial weight value U of a urbanization index of a grid cell nn；
And B: acquiring error ErrorItem between a downscale product of rainfall data observed by a satellite of the grid unit n and rainfall data observed by a ground observation station at preset time ii,n；
Acquiring time weight values of rainfall observations collected by a ground observation station at each moment according to the rainfall observations collected by the ground observation station at each preset moment;
entering the step 4;
and 4, step 4: and acquiring errors ErrorIndex of the downscale product of the rainfall data of the satellite observation target river basin when considering spatial distribution and time distribution according to the spatial weight values of the urbanization indexes of all grid units where the ground observation station is located, errors between the downscale products of the rainfall data observed by the satellite and the rainfall data observed by the ground observation station, and time weight values of the rainfall observed quantities acquired by the ground observation station at preset moments.
Further, in step a, according to the formula:
obtaining a spatial weight value U of a urbanization index of a grid cell nn；
Wherein Acc mu is cumulative urbanization index mumThe urbanization index of the mth orthogonal grid unit obtained after the target drainage basin is divided is shown, and M is the total number of the grid units obtained after the target drainage basin is divided.
Further, in step B, according to the formula:
ErrorItemi,n＝WPi,n-Pi,n
acquiring each grid unit n at preset each momentError ErrorItem at ii,n；
Wherein, WPi,nA downscaling product for satellite observation rainfall data at the moment i for the grid unit n; pi,nObserving rainfall data for the ground observation station of the grid unit n at the moment i; where i is 0,1 … T, and T is a preset total time value.
Further, in step 3, according to the formula:
acquiring time weight value F of rainfall observed quantity acquired by ground observation station at preset time ii；
Where Accp is the cumulative rainfall.
Further, in step 4, according to the formula:
acquiring error ErrorIndex of a downscale product of rainfall data of a satellite observation target river basin when spatial distribution and time distribution are taken into account;
wherein alpha isiAnd (3) calculating the error of the space distribution of the downscaling product for observing the rainfall data of the target river basin for the satellite. .
Has the advantages that: compared with the prior art, the method provided by the invention constructs the time and space distribution of the downscale product error of the satellite rainfall observation data, quantifies the influence of the urbanization index on the downscale product error of the satellite rainfall observation data, further adopts different weights in the time and space dimensions to further optimize the error calculation of the downscale product of the satellite rainfall observation data, and improves the precision and reliability of the calculation result, and the method can be timely and conveniently popularized and applied in the downscale product error calculation of the satellite rainfall observation data due to the time taken into account; the method mainly utilizes the existing observation station to observe rainfall data, the data source is stable and reliable, the function relation between variables in the method is clear, and the method is favorable for fast and accurate calculation of the downscale product error of satellite rainfall observation data. .
Drawings
FIG. 1 is a flow chart of a computing method provided in accordance with an embodiment of the present invention;
FIG. 2 is a schematic view of a watershed provided according to an embodiment of the invention;
FIG. 3 is a schematic diagram of spatial weights provided according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of temporal weights provided according to an embodiment of the invention;
fig. 5 is a schematic diagram of an error after accounting for spatial weights according to an embodiment of the present invention.
Detailed Description
The invention 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 invention is not limited thereby.
Referring to fig. 1, the method provided by the present invention includes the steps of:
step 1: and (3) dividing the target drainage basin into a plurality of orthogonal grid units based on the digital elevation data of the target drainage basin, and then entering the step 2.
Step 2: and (3) acquiring each grid unit where the ground observation station is located in each grid unit, and then entering the step 3.
And step 3: respectively executing the step A and the step B aiming at each grid unit N, N is 1,2 … N, N is the total number of the grid units where the ground observation stations are located, further obtaining the space weight values of the urbanization indexes of all the grid units where the ground observation stations are located and the errors between the down-scale products of the satellite observation rainfall data and the ground observation station observation rainfall data, and then entering the step 4:
step A: urbanization index mu according to grid cell nnAnd calculating the spatial weight value U of the urbanization index of the grid unit n by combining the urbanization indexes of the grid units where other ground observation stations except the grid unit n are positionedn。
Specifically, according to the following formula:
obtaining a spatial weight value U of a urbanization index of a grid cell nn；
Wherein Acc mu is cumulative urbanization index mumThe urbanization index of the mth orthogonal grid unit obtained by dividing the target basin may be extracted from the satellite picture, where M is the total number of grid units obtained by dividing the target basin, and M is 0.1 … M.
Based on the method, the spatial weight distribution RasterIndex of the urbanization index of each grid unit where the ground observation station is located can be obtained;
RasterIndex＝{U0,U1…,Un…UN}
namely: and carrying out normalization processing on the urbanization indexes so as to obtain the spatial weight distribution of the urbanization indexes of each grid unit where the ground observation station is located.
And B: acquiring error ErrorItem between a downscale product of rainfall data observed by a satellite of the grid unit n and rainfall data observed by a ground observation station at preset time ii,n。
Specifically, according to the following formula:
ErrorItemi,n＝WPi,n-Pi,n
acquiring the error ErrorItem of each grid cell n at each preset time ii,nThat is, ErrorItem is obtained according to the above methodi,n，ErrorItemi,nI.e., the error between the down-scaled production of satellite observed rainfall data and the bottom surface site observed data in grid cell n at time i.
Wherein, WPi,nThe scale reduction product of the satellite observation rainfall data at the moment i is the grid unit n, namely the value of the scale reduction product of the satellite observation rainfall data in the grid unit with the number n at the moment i; pi,nObserving rainfall data for the grid unit n at the time of i, namely observing the value of a downscale product of the rainfall data in the grid unit with the number of n at the time of i;
according to the method, the Error between the downscale product of the rainfall data observed by the satellite and the observation data of the bottom station is obtained when each grid unit where the ground grid unit is located is at each moment, and the Error space-time distribution matrix Error can be obtained based on each Error.
According to the rainfall observed quantity P collected by the ground observation station at each preset moment iiAcquiring time weight values F of rainfall observed quantities acquired by the ground observation station at each moment iiWhere i is 0,1 … T, and T is a preset total time value.
Specifically, rainfall observation data at each preset moment is acquired by acquiring rainfall observation data of ground observation stations in the previous rainfall process of a target basin, and then a rainfall observation data sequence TimEP is constructed:
TimeP＝{P0,P1,P2…PT}
wherein, PTObserved rainfall data at time T; according to the formula:
acquiring time weight value F of rainfall observed quantity acquired by ground observation station at preset time ii；
Where Accp is the cumulative rainfall.
According to the time weight value of the rainfall observation at each moment, a time weight distribution TimeIndex can be constructed.
And 4, step 4: according to the space weight values of the urbanization indexes of all grid units where the ground observation station is located, the errors between the downscale products of the satellite observation rainfall data and the rainfall observation data of the ground observation station, and the time weight value F of the rainfall observation quantity collected by the ground observation station at each preset moment iiAnd obtaining the error ErrorIndex of the downscale product of the rainfall data of the satellite observation target river basin when the spatial distribution and the time distribution are taken into consideration.
According to the formula:
and acquiring error ErrorIndex of the downscale product of the rainfall data of the satellite observation target river basin when spatial distribution and time distribution are taken into account, namely, the comprehensive index of the downscale product of the satellite observation rainfall data after time weight is taken into account.
Wherein alpha isiAnd (3) calculating the error of the downscaling product of the rainfall data of the target river basin observed by the satellite when the spatial distribution is calculated, namely, the error after the spatial weight is considered.
Taking the Changchua river basin of Zhejiang province as an example, the schematic diagram of the river basin is shown in FIG. 2, the river basin is located in the northwest of Zhejiang province, and the main Changchua stream and the tributary Tianmu stream are called as the divided river after the Chinese stream meets the Chinese stream in the city of Lingan. The watershed is high in the northwest and low in the southeast, and belongs to the mountainous area in the west of Zhejiang. The watershed water system is developed, the riverbed mainly comprises sand gravel, rocks and large stones are more arranged at the bend of the rapid beach, and the upstream is steep and tortuous; the downstream is wide and shallow, the shoal has multiple streams and is rapid, the water level is suddenly expanded and falls, and the river has the characteristics of mountain stream rivers. Belongs to subtropical monsoon climate, has abundant rainfall and obvious change in four seasons. In early spring season of 3-4 months, the ground is full of southeast wind, generally, continuous and thin rain is mostly reduced, and the precipitation is gradually increased, which is called spring rain period; in 5-7 months, during late spring and early summer, the warm-wet Taiping ocean high-pressure air mass is gradually propelled to the continent, and the frontal surface is often stopped or swung above the flow area, so that continuous rainfall is caused, and the rainfall intensity is high and the amount is large, which is called plum rainy period; in 7-9 months of summer, the weather is hot, the wind is in the south, the thunderstorm and typhoon rain are prevalent; in 10-11 months, the weather is mainly clear; in 12-2 months, in cold winter, the ground is prevailing in the northern wind, cloudy weather and low temperature, and rain and snow weather can appear. The average precipitation of the basin for many years is 1638.2 mm.
The method for calculating the downscaling product error of the satellite rainfall observation data of the drainage basin comprises the following steps:
step one, normalizing the urbanization index to obtain a spatial weight distribution RasterIndex, wherein the spatial weight distribution is shown in figure 3, and the method specifically comprises the following steps:
1) dividing the drainage basin into a series of orthogonal grid units, and calculating a spatial cumulative urbanization index Acc mu;
in the formula: m represents the number of the orthogonal grid units after the watershed is divided, and the number is changed from 0 to M, wherein M is the total number of the grid units; mu.smThe urbanization index μ in the grid cell with the number m can be extracted from the satellite picture.
2) Normalizing the urbanization index mu to obtain a spatial weight distribution RasterIndex;
RasterIndex＝{U0,U1…,Un…UN}
in the formula: u shapekNormalized township index, i.e. null, in grid cell numbered mThe inter-weight, m, varies from 0 to N.
Step two, extracting a rainfall observation data sequence TimeP containing a rain peak according to the rainfall data observed by the ground station, and normalizing the rainfall moment by moment in the rainfall observation data sequence to obtain a Time weight distribution Time _ Index, which specifically comprises the following steps:
1) taking a rainfall of the Changchua river basin starting from No. 15/2008 as an example, observing rainfall data based on a ground station in the rainfall process, and extracting to obtain a rainfall observation data sequence TimEP containing a rain peak;
TimeP＝{P0,P1,P2…PT}
in the formula: pTAnd sequentially classifying the rainfall at the T moment to obtain a rainfall observation data sequence TimEP.
2) Calculating an accumulated rainfall AccP in a T period;
in the formula: i represents the time, changing from 0 to T.
3) Normalizing the rainfall by time in the rainfall observation data sequence to obtain a time weight distribution TimeIndex, wherein a schematic diagram of the time weight distribution is shown in FIG. 4;
TimeIndex＝{F0,F1…,Fi…FT}
in the formula: fiThe amount of rainfall after normalization at time i, i.e. the temporal weight,
i varies from 0 to T.
Step three, calculating an Error space-time distribution matrix Error of the downscale product of the satellite observation rainfall data based on the downscale product of the satellite observation rainfall data and the ground station observation rainfall data, and specifically comprising the following steps:
1) identifying the grid Cell where the ground observation station is located, and calculating the grid Cell of the Cell at the time of the time iError ErrorItem between downscale product of satellite observed rainfall data and ground site observed rainfall datai,n；
ErrorItemi,n＝WPi,n-Pi,n
In the formula: n is the number of the grid Cell containing the ground observation station, and is from 0 to N. WPi,nThe value of a downscale product of rainfall data observed by the satellite at the moment i in a grid unit with the number n; pi,nObserving the value of rainfall data in the grid unit with the number n for the ground station at the moment i; ErrorItemi,nObserving the error of the downscale product of rainfall data for the satellite in the grid unit with the number of n at the moment i;
2) and traversing the time term and the space term according to the method, and calculating to obtain an Error space-time distribution matrix Error.
And step four, calculating to obtain a comprehensive Error Index ErrorIndex of a downscale product of satellite observation rainfall data by combining the Error space-Time distribution matrix Error, the spatial weight distribution RasterIndex and the Time weight distribution Time _ Index.
The method specifically comprises the following steps:
1) space error index alpha of downscale product for calculating and obtaining satellite observation rainfall dataiI.e. the error after considering the spatial weight, the error result is shown in fig. 5;
in the formula: u shapenIs the value of the spatial weight in the grid cell numbered n, αiIs a spatial error indicator at time i.
2) Calculating a comprehensive error index ErrorIndex of a downscaling product of the satellite observation rainfall data with the time weight taken into consideration;
for a rainfall starting from No. 12 at No. 15 of No. 6 of 2008, the comprehensive error index ErrorIndex of the rainfall is 5.52 calculated in the Changchua basin.
The invention has the beneficial effects that: the downscale product error calculation method for satellite rainfall observation data provided by the invention is characterized by space-time distribution of downscale product errors of satellite rainfall observation data, and effects of towns and rain peaks in downscale product error evaluation of satellite rainfall observation data are quantified, so that errors of downscale products of satellite rainfall observation data are further analyzed by adopting different weights in time and space dimensions. Therefore, the precision and the reliability of the calculation result are ensured, and the method can be popularized and applied to the error calculation of the downscale product for satellite observation rainfall data in time and conveniently. The existing rainfall site observation data are mainly utilized, the data source is stable and reliable, the functional relation among variables in the method is clear, the fast automatic calculation of the downscale product error of the satellite rainfall observation data is facilitated, the calculation result is objective and reasonable, and the deep development of the satellite rainfall observation research can be further promoted.
The above description is only a preferred embodiment of the present invention, and it will be apparent to those skilled in the art that various modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be considered as the protection scope of the present invention.
Claims (5)
1. A downscaling product error calculation method for satellite observation rainfall data is characterized by being used for obtaining downscaling product errors of satellite observation target basin rainfall data, and the method comprises the following steps:
step 1: dividing the target drainage basin into a plurality of grid units based on the digital elevation data of the target drainage basin, and then entering step 2;
step 2: acquiring each grid unit where the ground observation station is located in each grid unit, and then entering step 3;
and step 3: respectively executing the step A and the step B aiming at each grid unit N, N is 1,2 … N, N is the total number of the grid units where the ground observation station is located, and further obtaining the spatial weight values of the urbanization indexes of all the grid units where the ground observation station is located and the errors between the down-scale products of the satellite observation rainfall data and the rainfall observation data of the ground observation station:
step A: urbanization index mu according to grid cell nnAnd calculating the spatial weight value U of the urbanization index of the grid unit n by combining the urbanization indexes of the grid units where other ground observation stations except the grid unit n are positionedn；
And B: acquiring error ErrorItem between a downscale product of rainfall data observed by a satellite of the grid unit n and rainfall data observed by a ground observation station at preset time ii,n；
Acquiring time weight values of rainfall observations collected by a ground observation station at each moment according to the rainfall observations collected by the ground observation station at each preset moment;
entering the step 4;
and 4, step 4: and acquiring errors ErrorIndex of the downscale product of the rainfall data of the satellite observation target river basin when considering spatial distribution and time distribution according to the spatial weight values of the urbanization indexes of all grid units where the ground observation station is located, errors between the downscale products of the rainfall data observed by the satellite and the rainfall data observed by the ground observation station, and time weight values of the rainfall observed quantities acquired by the ground observation station at preset moments.
2. The method for calculating the downscaling product error of the satellite observed rainfall data according to claim 1, wherein in the step A, according to a formula:
acquisition gridSpatial weight value U of urbanization index of unit nn；
Wherein Acc mu is cumulative urbanization index mumThe urbanization index of the mth orthogonal grid unit obtained after the target drainage basin is divided is shown, and M is the total number of the grid units obtained after the target drainage basin is divided.
3. The method of claim 1, wherein in step B, the method comprises:
ErrorItemi,n＝WPi,n-Pi,n
acquiring the error ErrorItem of each grid cell n at each preset time ii,n；
Wherein, WPi,nA downscaling product for satellite observation rainfall data at the moment i for the grid unit n; pi,nObserving rainfall data for the ground observation station of the grid unit n at the moment i; where i is 0,1 … T, and T is a preset total time value.
4. The method for calculating the downscaling production error of the satellite observed rainfall data according to claim 1, wherein in step 3, according to a formula:
acquiring time weight value F of rainfall observed quantity acquired by ground observation station at preset time ii；
Where Accp is the cumulative rainfall.
5. The method for calculating the downscaling production error of the satellite observed rainfall data according to claim 1, wherein in step 4, according to a formula:
acquiring error ErrorIndex of a downscale product of rainfall data of a satellite observation target river basin when spatial distribution and time distribution are taken into account;
wherein alpha isiAnd (3) calculating the error of the space distribution of the downscaling product for observing the rainfall data of the target river basin for the satellite.
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