CN116541391B - Real-time rapid generation method for northern hemisphere sea ice density data - Google Patents
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Abstract
The application provides a real-time rapid generation method of northern hemisphere sea ice concentration data, which generates longitude and latitude sea ice concentration data such as MWRI in a specified time period by using MWRI satellite orbit data to roll in real time; synthesizing longitude and latitude sea ice density data such as MWRI and OSISAF, VIRR, IMS sea ice data to obtain an observation field of sea ice density; and taking sea ice concentration forecast field data of ECMWF as a background field, effectively fusing an observation field and the background field by an STMAS method, and generating a northern hemisphere sea ice concentration fusion data product. The application has the beneficial effects that: and by utilizing the high-timeliness satellite orbit data, the longitude and latitude sea ice concentration products such as MWRI and the like are rapidly generated in a rolling way, and the timeliness of the fusion data source is improved. Meanwhile, the background field adopts the forecast field data of the high-timeliness mode. The aging of the observation field and the forecasting field is improved, and the rapid generation of the northern hemisphere sea ice density fusion product is ensured.
Description
Technical Field
The application belongs to the field of sea ice concentration data development, and particularly relates to a real-time sea ice concentration data generation method.
Background
As global climate warms, arctic sea ice is continuously melted, the shipping requirements of arctic 'silk road on ice' are vigorous, and the demand of high-resolution sea ice dense products of northern hemispheres for arctic navigation service is urgent.
At present, sea ice density fusion data used in arctic navigation are fused with various data source materials, and the data generation is stable and is not blocked by clouds. However, due to the long lag time of the daily sea ice concentration data of the important data source MWRI, the overall timeliness of the fusion product is low, and the high timeliness requirement cannot be completely met.
Disclosure of Invention
In view of the above, the present application aims to provide a method for real-time and rapid generation of northern hemisphere sea ice density data, so as to solve the above technical problems.
In order to achieve the above purpose, the technical scheme of the application is realized as follows:
the real-time and rapid generation method of the northern hemisphere sea ice density data comprises the following steps:
s1: generating longitude and latitude sea ice concentration data such as MWRI in a specified time period in real time by using the MWRI satellite orbit data;
s2: synthesizing longitude and latitude sea ice density data such as MWRI, OSISAF, VIRR sea ice density data and IMS sea ice coverage data to obtain an observation field of sea ice density;
s3: taking sea ice concentration forecast field data of ECMWF as a background field of fusion treatment;
s4: and effectively fusing the observation field and the background field by using an STMAS method to obtain the sea ice concentration fusion product.
Further, the process of generating the longitude and latitude sea ice density data of MWRI and the like in the specified time period in the step S1 is as follows:
s101: resampling the MWRI satellite orbit data to obtain 0.1 degree equal longitude and latitude resolution data by a nearest neighbor method;
s102: equal-longitude and latitude grid values of the track overlapping region are obtained by adopting an equal-weight method, and northern hemisphere sea ice concentration track synthesis data are generated;
s103: quality control is carried out on the track synthesized data by sea ice, sea and land distribution cooperative quality control method;
s104: the time of the rolling update frequency is set according to the number of the latest acquired satellite orbits.
S105: and (3) repeating the steps S101-S104, realizing rolling update of the northern hemisphere sea ice concentration data, and generating longitude and latitude sea ice concentration data such as MWRI in a specified time period.
Further, the data generation in step S1 specifies a time period longer than the time period for acquiring 3 pieces of MWRI track data.
Further, the time interval of the scroll update frequency in step S104 is greater than the time of adding 1 track data;
the data rolling update lag time is larger than the sum of the time length of the MWRI instrument observation data sent to the receiving station by the satellite and the time length of the MWRI instrument observation data processed to obtain the longitude and latitude sea ice concentration data of the MWRI and the like.
Further, the process of obtaining the sea ice concentration observation field in the step S2 is as follows:
correcting the deviation of MWRI and VIRR sea ice concentration data by taking OSISAF data as a reference, complementing the gaps around poles of satellite data by IMS data, and forming an observation field of sea ice concentration according to corrected error weights.
Further, in step S103, quality control is performed on the track composition data specifically as follows:
performing multi-element collaborative quality control processing by using high-resolution long-sequence sea ice, sea temperature data and sea-land distribution data;
the sea ice and sea temperature data are data of the same day and 5 days before and after the same day in a designated time period, and the daily sliding quality control processing is performed by using the sea ice and sea temperature data for a total of 11 days.
Further, longitude and latitude sea ice density data such as MWRI and the like used in step S2 and oscaf and VIRR sea ice density data are both sea ice density data of northern hemisphere, and IMS is northern hemisphere sea ice coverage data;
the ECMWF sea ice concentration forecast field data used in the step S3 is sea ice concentration data of the northern hemisphere.
Compared with the prior art, the sea ice density data real-time generation method has the following beneficial effects:
the original sea ice concentration fusion technical scheme is optimized, and the product aging is improved. By utilizing a high-timeliness wind cloud satellite sea ice density orbit product, a wind cloud satellite MWRI (metal wrap around) and other longitude and latitude sea ice density data rolling generation technology is developed, and the nearest neighbor MWRI and other longitude and latitude sea ice density data in a specified time period can be generated in a rolling mode according to requirements; compared with the prior daily wind cloud satellite MWRI sea ice concentration product generated at regular time, the technology can flexibly specify the data coverage time period, realizes the rapid rolling generation of data, and improves the generation timeliness of the wind cloud satellite MWRI data, thereby improving the overall timeliness of the fusion product.
According to the real-time generation method of sea ice concentration data, the sea ice, sea temperature and sea Liu Fenbu multi-element cooperative quality control scheme is adopted, so that the method is more comprehensive than the original single-element quality control scheme, and more unreasonable sea ice distribution can be detected and removed; the scheme is based on high-resolution long-sequence sea ice, sea temperature data and sea-land distribution data, daily sliding quality control processing is carried out on longitude and latitude sea ice density data such as MWRI after orbit synthesis, the method is finer than the original monthly quality control scheme, discontinuity caused by month replacement in the monthly quality control is eliminated, and accuracy of the data is guaranteed.
By utilizing the high-timeliness satellite orbit product, real-time longitude and latitude sea ice density data such as MWRI and the like are rapidly generated, and the timeliness is improved by more than 5 hours, so that the timeliness is greatly improved; and the high-aging sea ice density observation field is generated, the high-aging ECMWF sea ice density forecast field data is used as a background field, the high-aging sea ice density fusion product is generated by fusing the observation field and the background field, the aging of the observation field and the background field is obviously improved, and the rapid generation of the sea ice density fusion product is ensured.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application. In the drawings:
FIG. 1 is a flow chart of a method for generating sea ice concentration data in real time according to an embodiment of the application;
FIG. 2 is a schematic diagram of MWRI sea ice concentration orbit data according to an embodiment of the present application;
FIG. 3 is a graph showing daily track-up data for an MWRI according to an embodiment of the present application;
FIG. 4 is a graph showing daily derailment data of an MWRI according to an embodiment of the present application;
FIG. 5 is a chart showing the sea ice concentration data of the MWRI after orbit synthesis according to the embodiment of the present application;
fig. 6 is a schematic view of IMS sea ice coverage for sea ice quality control according to an embodiment of the present application;
FIG. 7 is a diagram of OISST sea temperature data for sea ice quality control according to an embodiment of the present application;
FIG. 8 is a diagram of sea-land distribution data for sea-ice quality control according to an embodiment of the present application;
fig. 9 is a schematic diagram of quality-controlled data of the density of sea ice with longitude and latitude, such as MWRI, according to an embodiment of the present application;
FIG. 10 is a schematic view of an observation field according to an embodiment of the present application;
FIG. 11 is a schematic view of a background field according to an embodiment of the present application;
FIG. 12 is a schematic diagram of a sea ice intensity fusion product according to an embodiment of the present application.
Detailed Description
It should be noted that, without conflict, the embodiments of the present application and features of the embodiments may be combined with each other.
The application will be described in detail below with reference to the drawings in connection with embodiments.
Embodiment one: the real-time and rapid generation method of the northern hemisphere sea ice density data comprises the following steps:
s1: generating longitude and latitude sea ice concentration data such as MWRI in a specified time period in real time by using the MWRI satellite orbit data;
s2: synthesizing longitude and latitude sea ice density data such as MWRI and OSISAF, VIRR, IMS sea ice data to obtain an observation field of sea ice density;
s3: taking sea ice concentration forecast field data of ECMWF as a background field of fusion treatment;
s4: and effectively fusing the observation field and the background field by using an STMAS method to obtain the sea ice concentration fusion product.
The method comprises the steps of carrying an MWRI cloud 3 series satellite, sending satellite MWRI instrument observation data to a receiving station, transmitting real-time MWRI orbit data to data processing equipment through processing, updating the latest obtained MWRI orbit data to the existing orbit data by the data processing equipment, and generating longitude and latitude sea ice concentration data such as MWRI in a specified time period in a rolling mode;
the time length of the appointed time period is larger than the sum of the time length of the MWRI instrument observation data transmitted to the receiving station by the satellite and the time length of the MWRI instrument observation data obtained by processing the MWRI instrument observation data.
The longitude and latitude sea ice concentration data of the MWRI and the like are the sea ice concentration data in a specified time period generated in real time, and the sea ice concentration data products with the same longitude and latitude in the nearest time period can be generated in a rolling mode according to requirements, so that the timeliness of wind and cloud satellite data source data is improved, the timeliness of observation field generation is improved, and the timeliness of integral generation of sea ice concentration fusion products is further improved.
The high-timeliness ECMWF (European middle weather forecast center) sea ice concentration forecast field data is used as a fusion background field, and the ECMWF sea ice concentration forecast field data has higher timeliness than background field data used in the prior art. The existing background field information has longer lag time, and the ECMWF sea ice concentration forecast field information has no lag compared with the prior art, so that the timeliness of the sea ice concentration fusion product can be greatly improved.
In the step S1, the MWRI sensor is mounted on an FY3 series polar orbit satellite, and fusion products are developed and used by FY3D satellite sea ice concentration orbit data, wherein the resolution of the data is 12km, and the coverage range of the data is a north-south hemisphere high latitude area.
The process of generating the longitude and latitude sea ice concentration data such as MWRI in the specified time period in the step S1 is as follows:
s101: resampling the MWRI satellite orbit data to obtain 0.1 degree equal longitude and latitude resolution data by a nearest neighbor method;
the processing method of resampling longitude and latitude of the track data and the like is a nearest neighbor method; i.e. the distance from the equal theodolite point A (jA, wA) to the surrounding original grid B (jB, wB) isWhen->The value of the longitude and latitude grid of the minimum time is equal to the value of the original grid; the calculation formula of the spherical distance between two points is as follows:
；
wherein R is the earth radius;
s102: equal-longitude and latitude grid values of the track overlapping region are obtained by adopting an equal-weight method, and northern hemisphere sea ice concentration track synthesis data are generated; calculating average values in longitude and latitude grids by using effective values (0-100) of sea ice density;
；
SIC is sea ice concentration, n is the number of coincident tracks;
the northern hemisphere sea ice density data after the longitude and latitude resampling and synthesizing processing generated by the processing is track synthesizing data;
s103: quality control is carried out on the track synthesized data by a sea ice, sea and land cooperative quality control method;
s104: on the data processing apparatus, the time of the scroll update frequency is set according to the number of newly acquired satellite orbits.
S105: and (3) repeating the steps S101-S104, realizing rolling update of the northern hemisphere sea ice concentration data, and generating longitude and latitude sea ice concentration data such as MWRI in a specified time period.
The time length of the data generation designated time period in step S1 is longer than the time length of acquiring 3 pieces of MWRI track data.
The time interval of the rolling update frequency in the step S104 is larger than the time of newly adding 1 track data; the data rolling update lag time is larger than the sum of the time length of the MWRI instrument observation data sent by the satellite to the receiving station and the time length of the MWRI instrument observation data processed to obtain the longitude and latitude sea ice concentration data of the MWRI and the like.
The MWRI apparatus used in this embodiment is mounted on three satellites of the cloud, each satellite runs around the earth for about 14 circles each day, about 14 ascending and 14 descending data are generated, and the ascending and descending data are synthesized to generate longitude and latitude sea ice concentration data of MWRI and the like.
The generating step of the observation field in the step S2 is as follows:
correcting the deviation of MWRI and VIRR sea ice concentration data by taking OSISAF data as a reference, complementing the gaps around poles of satellite data by IMS data, and generating a sea ice concentration observation field according to corrected error weight.
In step S103, the quality control of the track composition data is specifically as follows:
performing multi-element collaborative quality control processing by using high-resolution long-sequence sea ice, sea temperature data and sea-land distribution data;
the sea ice and sea temperature data are data of the same day, 5 days before and after the same day, and the daily sliding quality control processing is performed by using the sea ice and sea temperature data for a total of 11 days.
The method for generating northern hemisphere sea ice historical appearance range data by utilizing IMS sea ice data comprises the steps of adopting the IMS sea ice coverage data to generate sea ice historical appearance range quality control data, counting the maximum range of sea ice which appears for many years for 11 days before, after 5 days on the same day in a specified time period, and taking the sea ice exceeding the maximum range as error data.
The quality control processing is carried out on the sea ice density data synthesized by the tracks through the OISST sea temperature data, and the sea temperature quality control data of the sea ice density is manufactured by utilizing the OISST sea temperature data in 1991 to 2020. And counting the minimum sea temperature value of 11 days before and after 5 days of the current day of the specified time period of the position, wherein the minimum sea temperature value of the position exceeds 273K, and the sea ice value of the position is taken as error data.
And (3) performing quality control on sea ice density data synthesized by the tracks through sea and land distribution data with the resolution of 0.1 degrees, and removing sea ice data which are not in the ocean range.
And 3 quality control conditions of the sea ice, the sea temperature and the sea land are not met, namely, error data are judged, and the data are removed.
Quality control is carried out on MWRI orbit data, and error data in the following situations are well removed: sea ice concentration error values with larger areas appear in the middle-low latitude sea; there are significant sea ice error values near the coastline; sea ice problems occur on some land.
MWRI, OSISAF, IMS, VIRR sea ice data used in the application are northern hemisphere data;
the used high-aging ECMWF sea ice concentration forecast field data is northern hemisphere data;
the data volume of the northern hemisphere sea ice concentration data is smaller than that of global whole sea ice concentration data, and in the process of generating an observation field and fusing the observation field with a background field, the load pressure on a database and computing equipment is greatly reduced, and the timeliness of sea ice concentration fusion product generation is greatly improved.
Those of ordinary skill in the art will appreciate that the elements and method steps of each example described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both, and that the elements and steps of each example have been described generally in terms of functionality in the foregoing description to clearly illustrate this interchangeability of hardware and software. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the several embodiments provided in the present application, it should be understood that the disclosed methods and systems may be implemented in other ways. For example, the above-described division of units is merely a logical function division, and there may be another division manner when actually implemented, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted or not performed. The units may or may not be physically separate, and components shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiment of the present application.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present application, and not for limiting the same; although the application has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the application, and are intended to be included within the scope of the appended claims and description.
The foregoing description of the preferred embodiments of the application is not intended to be limiting, but rather is intended to cover all modifications, equivalents, alternatives, and improvements that fall within the spirit and scope of the application.
Claims (3)
1. The real-time and rapid generation method of the northern hemisphere sea ice density data is characterized by comprising the following steps of:
the method comprises the following steps:
s1: generating longitude and latitude sea ice concentration data such as MWRI in a specified time period in real time by using the MWRI satellite orbit data;
s2: synthesizing longitude and latitude sea ice density data such as MWRI, OSISAF, VIRR sea ice density data and IMS sea ice coverage data to obtain an observation field of sea ice density;
s3: taking sea ice concentration forecast field data of ECMWF as a background field of fusion treatment;
s4: effectively fusing an observation field and a background field by using an STMAS method to obtain a sea ice concentration fusion product;
the process of generating the longitude and latitude sea ice concentration data such as MWRI in the specified time period in the step S1 is as follows:
s101: resampling the MWRI satellite orbit data to obtain 0.1 degree equal longitude and latitude resolution data by a nearest neighbor method;
the processing method of resampling longitude and latitude of the track data and the like is a nearest neighbor method; i.e. the distance from the equal theodolite point A (jA, wA) to the surrounding original grid B (jB, wB) isWhen->The value of longitude and latitude grids such as the minimum time is equal to the value of the current original grid; the calculation formula of the spherical distance between two points is as follows
Wherein R is the earth radius;
s102: equal-longitude and latitude grid values of the track overlapping region are obtained by adopting an equal-weight method, and northern hemisphere sea ice concentration track synthesis data are generated; calculating average values in longitude and latitude grids by using effective values of sea ice density of 0-100;
SIC is sea ice concentration, n is coincident railA lane number;
the northern hemisphere sea ice density data after the longitude and latitude resampling and synthesizing processing generated by the processing is track synthesizing data;
s103: quality control is carried out on the track synthesized data by a sea ice, sea and land cooperative quality control method;
s104: setting the time of rolling update frequency according to the number of the latest acquired satellite orbits;
s105: repeating the steps S101-S104 to realize rolling update of the northern hemisphere sea ice concentration data and generate longitude and latitude sea ice concentration data such as MWRI in a specified time period;
the data in the step S1 are generated in real time, and the time length of the specified time period is longer than the time length of acquiring 3 pieces of MWRI track data;
the method comprises the steps of carrying an MWRI cloud 3 series satellite, sending satellite MWRI instrument observation data to a receiving station, transmitting real-time MWRI orbit data to data processing equipment through processing, updating the latest obtained MWRI orbit data to the existing orbit data by the data processing equipment, and generating longitude and latitude sea ice concentration data such as MWRI in a specified time period in a rolling mode;
the time length of the appointed time period is larger than the sum of the time length of the MWRI instrument observation data transmitted to the receiving station by the satellite and the time length of the MWRI instrument observation data obtained by processing the MWRI instrument observation data and the like;
the quality control of the track composition data in step S103 is specifically as follows:
performing multi-element collaborative quality control processing by using high-resolution long-sequence sea ice, sea temperature data and sea-land distribution data;
the sea ice and sea temperature data are data of the same day and 5 days before and after the same day in a designated time period, and the daily sliding quality control processing is carried out by using the sea ice and sea temperature data for a total of 11 days;
the method for generating northern hemisphere sea ice historical appearance range data by utilizing IMS sea ice data comprises the steps of adopting 4km resolution IMS and other area sea ice coverage data in 2005-2020 long time sequence to manufacture sea ice historical appearance range quality control data, counting the maximum range of sea ice which appears for 11 days in the same day as the 5 days before and after the specified time period for many years, and taking the sea ice exceeding the maximum range as error data;
quality control processing is carried out on sea ice density data synthesized by the tracks through OISST sea temperature data, and sea temperature quality control data of sea ice density is manufactured by utilizing OISST sea temperature data in 1991-2020; counting the minimum sea temperature value of 11 days before and after 5 days of the current position in the appointed time period, wherein the minimum sea temperature value of the current position exceeds 273K, and the sea ice value of the current position is used as error data;
quality control is carried out on sea ice density data synthesized by the track through sea-land distribution data with resolution of 0.1 degrees, and sea ice data which are not in the ocean range are removed;
if any one of the 3 quality control conditions of sea ice, sea temperature and sea land is not met, judging that the data is error data, and removing;
the longitude and latitude sea ice density data such as MWRI and the like used in the step S2 and OSISAF and VIRR sea ice density data are both northern hemisphere data, and IMS is northern hemisphere sea ice coverage data;
the ECMWF sea ice concentration forecast field data used in the step S3 is sea ice concentration data of the northern hemisphere.
2. The method for rapidly generating the northern hemisphere sea ice concentration data in real time according to claim 1, wherein the method comprises the following steps:
step S104, the time interval of the rolling update frequency is larger than the time of newly adding 1 track data;
the data rolling update lag time is larger than the sum of the time length of the MWRI instrument observation data sent by the satellite to the receiving station and the time length of the MWRI instrument observation data processed to obtain the longitude and latitude sea ice concentration data of the MWRI and the like.
3. The method for rapidly generating the northern hemisphere sea ice concentration data in real time according to claim 1, wherein the method comprises the following steps:
the process of obtaining the sea ice concentration observation field in the step S2 is as follows:
correcting the deviation of MWRI and VIRR sea ice concentration data by taking OSISAF data as a reference, complementing the gaps around poles of satellite data by IMS data, and generating an observation field of sea ice concentration according to corrected error weight.
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| KR20180136217A (en) * | 2017-06-14 | 2018-12-24 | 한국해양과학기술원 | Real-Time Mid-Term Prediction Method Of Sea-Ice Information In Arctic Sea Route |
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