CN115269568A - Method for developing data set of oceanographic anchorage buoy - Google Patents

Method for developing data set of oceanographic anchorage buoy Download PDF

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CN115269568A
CN115269568A CN202210710048.6A CN202210710048A CN115269568A CN 115269568 A CN115269568 A CN 115269568A CN 202210710048 A CN202210710048 A CN 202210710048A CN 115269568 A CN115269568 A CN 115269568A
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quality control
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sea
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李肖霞
李凤
雷勇
张雨潇
刘圆
张志龙
李哲
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CMA Meteorological Observation Centre
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Abstract

The invention relates to the field of sea area data measurement, and particularly discloses a method for developing a data set of an ocean weather anchorage buoy, which comprises the following steps of: s1, meteorological element quality control; s2, controlling the quality of hydrological elements; wherein, S1, meteorological element quality control includes: s11, detecting lack; s12, checking a climatological limit value; s13, checking a climate extreme value; s14, checking internal consistency; s15, checking time consistency; s16, manually surveying errors; s2, hydrologic element quality control comprises the following steps: s21, preprocessing data; s22, checking data rationality; s23, checking internal consistency; and S24, bayesian consistency check. The meteorological element quality control module is used for performing quality control on meteorological data of the anchorage buoy, the hydrological element quality control module is used for performing quality control on sea temperature data of the anchorage buoy, reasonably judging and identifying data with poor quality such as error data and suspicious data, classifying and grading identification results, meeting application requirements of different grades, and improving application benefits of the data under different requirements.

Description

Method for developing data set of oceanographic anchorage buoy
Technical Field
The invention relates to the field of sea area data measurement, in particular to a method for developing a data set of an ocean weather anchorage buoy.
Background
The anchorage buoy is an important component of a sea-based observation system, and can stably monitor the change conditions of meteorological elements and hydrological information of key sea areas for a long time. A plurality of anchorage buoys are built in offshore areas such as Bohai sea, yellow sea and east sea in China, but data integration is never performed, a quality control method is optimized based on meteorological element observation data of the offshore anchorage buoys in China, quality control links are perfected, quality control algorithms of the anchorage buoys in China are improved, a standard data set of the offshore anchorage buoys in China is formed, the current situation that the offshore standard data set of the offshore weather in China is lost is changed, and a standard is provided for development and application of subsequent marine meteorological data.
The observation data of the anchorage buoy comprises hourly observation data of meteorological elements such as air temperature, air pressure, wind speed and visibility and hydrological elements such as sea temperature, and the principles of the meteorological elements and the hydrological elements are different, so different quality control schemes need to be made.
Disclosure of Invention
The invention aims to overcome the defect that anchoring buoy data in the prior art is not classified, and provides a method for developing a meteorology ocean anchoring buoy data set.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows:
a method for developing a data set of an oceanographic anchorage buoy comprises the following steps:
s1, meteorological element quality control;
s2, controlling the quality of hydrological elements;
wherein, S1, meteorological element quality control includes:
s11, detecting lack;
s12, checking a climate limit value;
s13, checking a climate extreme value;
s14, checking internal consistency;
s15, checking time consistency;
s16, manually surveying mistakes;
s2, hydrologic element quality control comprises the following steps:
s21, preprocessing data;
s22, checking data rationality;
s23, checking internal consistency;
and S24, bayesian consistency check.
Further, S11. Defect detection:
and checking whether the observed data is missing data, wherein when the observed data does not pass the missing detection, the corresponding quality control code is 8, and the missing data is not subjected to subsequent detection.
Further, S12, checking a climate limit value:
it is checked whether the data exceeds a critical value of a meteorological element which it is not possible to exceed from a climatological point of view. The result of the climate limit value inspection is as follows: if the data is correct or wrong, the corresponding quality control code is '0' or '2', and the wrong data is not subjected to subsequent check.
Further, S13, checking a climate extreme value:
and in a designated sea area and time domain range, carrying out climate extreme value inspection on the data according to the historical climate statistical value. The result of the climate extreme value check is as follows: if the data is correct or suspicious, the corresponding quality control code is '0' or '1', and suspicious data is reserved for further quality control.
Further, S14, internal consistency check:
whether the relation among the meteorological element records observed at the same time accords with certain physical relation or not is checked, and the method is mainly used for checking the internal consistency among the similar elements. The internal consistency check results are: if the result is correct or suspicious, the corresponding quality control code is '0' or '1', and suspicious data is reserved for further quality control.
Further, S15, time consistency check:
whether the change of the meteorological records in a certain time range has a specific rule or not is checked, the change of meteorological elements has a certain rule, and the change is possible to be abnormal when jumping occurs or the change is not changed for a long time, so that the maximum allowable change rate check and the minimum required change rate check are required to be carried out.
Further, S16, manually surveying errors:
the manual error investigation result is as follows: correct or incorrect, the corresponding quality control code is "0" or "2".
Further, S21, data preprocessing:
in the data acquisition and transmission process, data repetition can be caused when the data are subjected to repeated data transmission, longitude or latitude are different by a certain distance in the preprocessing, homologous data in similar time are regarded as repeated data, and for a series of repeated data, the data in the queue are retained or all the repeated data in the queue are deleted based on the sea surface temperature difference condition.
Further, S22, data reasonableness checking:
carrying out rationality check on the error data that the longitude and latitude and the sea temperature in the data of the anchorage buoy exceed the effective range and the condition that the sea temperature value appears in a land site, setting reasonable longitude and latitude and sea surface temperature reasonable range, rejecting unreasonable data and deleting unreasonable positioning data, wherein the data rationality check result is as follows: if the data is correct or wrong, the corresponding quality control code is '0' or '2', and the wrong data is not subjected to subsequent check.
Further, S23, internal consistency check:
checking the peak value appearing in the continuous sea surface temperature data sequence, judging the rationality of the time or space change gradient of the peak value, setting the maximum change gradient value of the sea surface temperature in time and space in the sea surface temperature change gradient rationality check, setting different threshold values aiming at different sea areas in consideration of the normal fluctuation existing between continuous records caused by instrument noise, thus eliminating abnormal values, and the internal consistency check result is as follows: if the data is correct or wrong, the corresponding quality control code is '0' or '2', and the wrong data is not subjected to subsequent check;
s24, bayesian consistency check:
using an objective quality control method based on Bayesian theory, taking a high-resolution sea surface temperature analysis product obtained by processing satellite remote sensing sea surface temperature data by an optimal interpolation method as a background field, calculating the probability density of sea temperature errors, setting relevant parameters based on experience and sensitivity analysis, obtaining Bayesian interval estimation, deleting data outside a drop zone, and obtaining a Bayesian consistency check result: if correct or incorrect, the corresponding quality control code is "0" or "2".
The invention has the beneficial effects that: according to the method, the meteorological element quality control module is used for performing quality control on meteorological data of the anchorage buoy, the hydrological element quality control module is used for performing quality control on sea temperature data of the anchorage buoy, reasonably judging and identifying data with poor quality such as error data and suspicious data, classifying and grading identification results, formulating a file organization mode according to requirements, outputting an anchorage buoy data set, and performing grading application on the anchorage buoy data, so that application requirements of different grades are met, and application benefits of the data under different requirements are improved.
Drawings
FIG. 1 is a schematic flow chart of meteorological element quality control according to the present invention;
FIG. 2 is a schematic flow chart of the quality control of hydrological elements of the present invention;
FIG. 3 is a temperature timing diagram before quality control of a northern sea area site;
FIG. 4 is a temperature timing diagram after the quality control of the northern sea area station;
FIG. 5 is a pressure timing diagram before the quality control of the northern sea area station;
FIG. 6 is a timing diagram of the air pressure after the quality control of the northern sea area station.
Detailed Description
As shown in fig. 1 and 2, a method for developing a data set of an ocean weather anchorage buoy comprises the following steps:
s1, meteorological element quality control;
s2, controlling the quality of hydrological factors;
wherein, S1, meteorological element quality control includes:
s11, detecting lack;
s12, checking a climate limit value;
s13, checking a climate extreme value;
s14, checking internal consistency;
s15, checking time consistency;
s16, manually surveying mistakes;
s2, hydrologic element quality control comprises the following steps:
s21, preprocessing data;
s22, checking data rationality;
s23, checking internal consistency;
and S24, bayesian consistency check.
Firstly, defining a quality control code, and after the data of the anchorage buoy is subjected to quality control, identifying the data with different qualities to meet different use requirements, so that the quality control code is defined firstly.
The quality control codes and their meanings are specified in the following table:
quality control code Means of
0 Correction of
1 Suspicious
2 Error(s) in
8 Absence survey
Wherein, S11. Lack detection:
and checking whether the observed data is missing data, wherein when the observed data does not pass the missing detection, the corresponding quality control code is 8, and the missing data is not subjected to subsequent detection.
Further, S12, checking a climate limit value:
determining a climatological limit value: the climatological characteristics of marine meteorological elements of the anchorage buoy in China are analyzed, and the climatological limit value of the anchorage buoy is determined by combining the industry standard of the anchorage buoy, the functional specification requirement book, the design principle and the equipment performance.
It is checked whether the data exceeds a critical value of a meteorological element which it is not possible to exceed from a climatological point of view. The result of the climate limit value inspection is as follows: if the data is correct or wrong, the corresponding quality control code is '0' or '2', and the wrong data is not subjected to subsequent check.
Further, S13, checking a climate extreme value:
determining a climate extreme value: dividing offshore areas of China according to Bohai sea, yellow sea, east sea and south sea, performing seasonal classification according to spring (3-5 months), summer (6-8 months), autumn (9-11 months) and winter (12-2 months) and respectively counting historical climatic extreme values of meteorological elements such as air temperature, air pressure, air speed and visibility in 2016-2020 years;
the climate extreme value inspection is to perform the climate extreme value inspection on the data according to historical climate statistical values in a designated sea area and time domain range. The result of the climate extreme value check is as follows: if the data is correct or suspicious, the corresponding quality control code is '0' or '1', and suspicious data is reserved for further quality control.
Further, S14. Internal consistency check:
whether the relation among the meteorological element records observed at the same time accords with certain physical relation or not is checked, and the method is mainly used for checking the internal consistency among the similar elements. The internal consistency check results are: if the result is correct or suspicious, the corresponding quality control code is '0' or '1', and suspicious data is reserved for further quality control.
The internal consistency algorithm for each element is listed below:
Figure BDA0003707483380000061
further, S15, time consistency check:
the time consistency check refers to checking whether the change of the weather record in a certain time range has a specific rule or not. The change of weather elements such as air temperature, air pressure and the like has a certain rule, and the abnormal condition can occur when jumping occurs or the change is not changed for a long time, so that the maximum allowable change rate check and the minimum required change rate check are carried out.
(1) Maximum allowable rate of change of meteorological element
The difference between the current observed value and the previous value is checked to see if it is less than a specified maximum allowable rate of change. In extreme weather conditions, the meteorological variables may change unusually, in which case the correct data may be greater than or equal to the specified maximum allowable rate of change, and further verified.
(2) Minimum rate of change check of meteorological elements
The indication value updating period of the observation value is 1h, the minimum change rate of the meteorological observation value is specified, the data of the anchor buoy data set is hour historical data, the conditions that clock data change in hours and hour integral point data are not changed exist, so that the minimum change rate detection is innovatively provided with an identification method for sequentially detecting the difference between the current observation value and the previous value, the difference between the current observation value and the next value and the difference between the previous observation value and the previous three values, and the observation values are not passed if the three detections are not passed, the observation value is judged to be failed.
The time consistency check results are: if the result is correct or suspicious, the corresponding quality control code is 0 or 1, and suspicious data are reserved for further quality control.
Further, S16, manually surveying errors:
as shown in fig. 3, 4, 5, and 6, in order to improve the accuracy of the anchor buoy, the quality control result needs to be manually corrected. The anchorage buoy needs to be periodically overhauled, so that the lack of measurement can exist for a long time, and therefore when the anchorage buoy is newly arranged, manual investigation on observation data is needed to judge the initial data quality, so that subsequent quality control can be conveniently carried out; under extreme weather conditions, the change rate of meteorological variables is possibly greater than or equal to the specified maximum allowable change rate, and manual error investigation needs to be carried out on observation data;
the manual error investigation result is as follows: if correct or incorrect, the corresponding quality control code is "0" or "2".
Further, S21, data preprocessing:
in the data acquisition and transmission process, data repetition is caused when the data are subjected to repeated supplementary transmission, the longitudes or the latitudes are different by a certain distance in the preprocessing, homologous data in the similar time are regarded as repeated data, and for a series of repeated data, the data in the queue are retained or all the repeated data in the queue are deleted based on the sea surface temperature difference condition.
Further, S22, data reasonableness checking:
carrying out rationality check on the error data of longitude and latitude and sea temperature exceeding the effective range in the data of the anchorage buoy and the condition that the sea temperature value appears in a land site, setting reasonable latitude and longitude and sea surface temperature ranges, eliminating unreasonable data, and deleting data with unreasonable positioning (such as a land site with a sea surface temperature measurement value), wherein the data rationality check result is as follows: if the data is correct or wrong, the corresponding quality control code is '0' or '2', and the wrong data is not subjected to subsequent check.
Further, S23, internal consistency check:
checking the peak value appearing in the continuous sea surface temperature data sequence, judging the time or space change gradient rationality, setting the maximum change gradient value of the sea surface temperature in time and space in the sea surface temperature change gradient rationality check, setting different threshold values aiming at different sea areas in consideration of the normal fluctuation existing between continuous records caused by instrument noise, thus eliminating abnormal values, and the internal consistency check result is as follows: if the data is correct or wrong, the corresponding quality control code is '0' or '2', and the wrong data is not subjected to subsequent check.
S24, bayesian consistency check:
using an objective quality control method based on Bayesian theory, taking a high-resolution sea surface temperature analysis product obtained by processing satellite remote sensing sea surface temperature data by an optimal interpolation method as a background field, calculating the probability density of sea temperature errors, setting relevant parameters based on experience and sensitivity analysis, obtaining Bayesian interval estimation, deleting data outside a drop zone, and obtaining a Bayesian consistency check result: if correct or incorrect, the corresponding quality control code is "0" or "2".
After the quality control is carried out on the anchorage buoy observation data and the correct quality control code is marked, a data set structure and a file organization mode are formulated according to requirements, a data set entity file of the marine meteorological anchorage buoy of China is formed, and a corresponding data set description file, a data set station information file, a format description file and a metadata file are made according to the content of a data set.
Wherein the data set content comprises:
all data in the data set are put in an entity file, the observation data of all sites and corresponding data quality control codes of one element per month are a file, and the file is named as 'OCEN _ MOORED _ CHN _ FTM-XXX-YYYYMM.TXT', wherein 'XXX' is an element code, 'YYYYYYYYY' is a year, and 'MM' is a month.
Element code XXX illustrates: TEM indicates air temperature, WIN indicates wind direction and wind speed, PRS indicates air pressure, VIS indicates visibility, and SST indicates sea temperature.
The dataset structure includes:
the data set comprises four folders of datasets, description, documents and metadata, wherein:
a) The data sets store data set entity files, five subdirectories including TEM (air temperature), WIN (wind direction and wind speed), PRS (air pressure), VIS (visibility) and SST (sea temperature) are arranged below the data sets, and each element data set entity is stored respectively.
b) The description stores a data set description document.
c) documents store data set station information files and format description files.
d) metadata stores metadata documents.
The data set entity file organization mode is as follows:
Figure BDA0003707483380000091
in conclusion, the meteorological element quality control module of the method is used for performing quality control on meteorological data of the anchorage buoy, the hydrological element quality control module is used for performing quality control on sea temperature data of the anchorage buoy, reasonably judging and identifying poor-quality data such as error data and suspicious data, classifying and grading identification results, formulating a file organization mode according to requirements to output an anchorage buoy data set, and grading application is performed on the anchorage buoy data, so that application requirements of different grades are met, and application benefits of the data under different requirements are improved.
The foregoing shows and describes the general principles, essential features, and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are merely illustrative of the principles of the invention, but various changes and modifications may be made without departing from the spirit and scope of the invention, which is defined by the appended claims. The scope of the invention is defined by the appended claims and equivalents thereof.

Claims (10)

1. A method for developing a data set of an ocean weather anchorage buoy is characterized by comprising the following steps:
s1, meteorological element quality control;
s2, controlling the quality of hydrological elements;
wherein, S1, meteorological element quality control includes:
s11, detecting lack;
s12, checking a climate limit value;
s13, checking a climate extreme value;
s14, checking internal consistency;
s15, checking time consistency;
s16, manually surveying errors;
s2, hydrological element quality control comprises the following steps:
s21, preprocessing data;
s22, checking data rationality;
s23, checking internal consistency;
and S24, bayesian consistency check.
2. The method for developing the oceanographic anchorage buoy data set according to claim 1, wherein S11. The absence detection:
and checking whether the observed data is missing data, wherein when the observed data does not pass the missing data checking, the corresponding quality control code is 8, and the missing data is not subjected to subsequent checking.
3. The method for developing the oceanographic anchorage buoy data set according to claim 1, wherein S12. Climate limit value inspection:
it is checked whether the data exceeds a critical value of a meteorological element which it is not possible to exceed from a climatological point of view. The result of the climate limit value inspection is as follows: if the data is correct or wrong, the corresponding quality control code is '0' or '2', and the wrong data is not subjected to subsequent check.
4. The method for developing the data set of the oceanographic anchorage buoy according to claim 1, wherein S13. Climate extreme value inspection:
and in a designated sea area and time domain range, carrying out climate extreme value inspection on the data according to the historical climate statistical value. The result of the climate extreme value inspection is as follows: if the result is correct or suspicious, the corresponding quality control code is '0' or '1', and suspicious data is reserved for further quality control.
5. The method for developing the data set of the oceanographic anchorage buoy of claim 1, wherein S14. Internal consistency check:
whether the relation among the meteorological element records observed at the same time accords with certain physical relation or not is checked, and the method is mainly used for checking the internal consistency among the similar elements. The internal consistency check results are: if the data is correct or suspicious, the corresponding quality control code is '0' or '1', and suspicious data is reserved for further quality control.
6. The method for developing the data set of the oceanographic anchorage buoy according to claim 1, wherein S15. Time consistency check:
whether the change of the meteorological records in a certain time range has a specific rule or not is checked, the change of the meteorological elements has a certain rule, and the abnormal condition can occur when jumping occurs or the change is not changed for a long time, so that the maximum allowable change rate check and the minimum required change rate check need to be carried out.
7. The method for developing the data set of the oceanographic anchorage buoy as claimed in claim 1, wherein S16. Manual survey:
the manual error investigation result is as follows: if correct or incorrect, the corresponding quality control code is "0" or "2".
8. The method for developing the data set of the oceanographic anchorage buoy according to claim 1, wherein S21. Data preprocessing:
in the data acquisition and transmission process, data repetition is caused when the data are subjected to repeated supplementary transmission, the longitudes or the latitudes are different by a certain distance in the preprocessing, homologous data in the similar time are regarded as repeated data, and for a series of repeated data, the data in the queue are retained or all the repeated data in the queue are deleted based on the sea surface temperature difference condition.
9. The method for developing the data set of the oceanographic anchorage buoy according to claim 1, wherein S22. Data rationality inspection:
carrying out rationality check on the error data that the longitude and latitude and the sea temperature in the data of the anchorage buoy exceed the effective range and the condition that the sea temperature value appears in a land site, setting reasonable longitude and latitude and sea surface temperature reasonable range, rejecting unreasonable data and deleting unreasonable positioning data, wherein the data rationality check result is as follows: if the data is correct or wrong, the corresponding quality control code is '0' or '2', and the wrong data is not subjected to subsequent check.
10. The method for developing the data set of the oceanographic anchorage buoy of claim 1, wherein S23. Internal consistency check:
checking the peak value appearing in the continuous sea surface temperature data sequence, judging the rationality of the time or space change gradient of the peak value, setting the maximum change gradient value of the sea surface temperature in time and space in the sea surface temperature change gradient rationality check, setting different threshold values aiming at different sea areas in consideration of the normal fluctuation existing between continuous records caused by instrument noise, thus eliminating abnormal values, and the internal consistency check result is as follows: if the data is correct or wrong, the corresponding quality control code is '0' or '2', and the wrong data is not subjected to subsequent check;
s24, bayesian consistency check:
using an objective quality control method based on Bayes theory, taking a high-resolution sea surface temperature analysis product obtained by processing satellite remote sensing sea surface temperature data by an optimal interpolation method as a background field, calculating the probability density of sea temperature errors, setting relevant parameters based on experience and sensitivity analysis, obtaining Bayes interval estimation, deleting data outside a drop area, and obtaining a Bayes consistency check result: if correct or incorrect, the corresponding quality control code is "0" or "2".
CN202210710048.6A 2022-06-22 2022-06-22 Method for developing data set of oceanographic anchorage buoy Pending CN115269568A (en)

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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116955515A (en) * 2023-08-04 2023-10-27 福建省气象信息中心(福建省气象档案馆) Site position information inspection method and system in meteorological observation data

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116955515A (en) * 2023-08-04 2023-10-27 福建省气象信息中心(福建省气象档案馆) Site position information inspection method and system in meteorological observation data
CN116955515B (en) * 2023-08-04 2024-04-05 福建省气象信息中心(福建省气象档案馆) Site position information inspection method and system in meteorological observation data

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