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A dataset of ≥10℃ accumulated temperature of field stations in Chinese typical ecosystems from 2001 to 2015
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: 2018 - 10 - 15
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Abstract & Keywords
Abstract: Thermal resources are the important basis for the division of natural areas and natural belts, and the important natural resource for agricultural production. They are usually characterized by the temperature and the accumulated temperature. 10°C is the starting temperature suitable for the growth of thermophilic plants, and it is also the temperature at which the cool crops grow rapidly and the perennial crops begin to accumulate dry matter at a fast rate. The ≥10℃ accumulated temperature and its corresponding duration are used to measure the agro-climatic production potential of a region and to be an important basis for the introduction and cultivation system reform by agricultural production department and researchers. Based on the daily average automatic observation temperature data of Chinese Ecosystem Research Network (CERN) and by using the 5-day moving average method, a dataset of ≥10℃ accumulated temperature in Chinese typical ecosystems from 2001 to 2015 was established, which includes the accumulated temperature, effective accumulated temperature and duration of ≥10℃ for 35 field stations covering major ecosystems of China such as agriculture, forest, grassland, desert, wetland, lake and bay. It will support the research on national or regional temporal and spatial distribution of accumulated temperature.
Keywords: ecosystem; ≥10℃ accumulated temperature; field station; thermal resources
Dataset Profile
English titleA dataset of ≥10℃ accumulated temperature of field stations in Chinese typical ecosystems from 2001 to 2015
Corresponding authorSu Wen (suw@igsnrr.ac.cn)
Data author(s)Su Wen
Time range2001 – 2015
Geographical scope35 field stations of Chinese Ecosystem Research Network (CERN), including Hailun, Shenyang, Luancheng, Ansai, Yucheng, Changwu, Fengqiu, Changshu, Yanting, Lasa, Taoyuan, Yingtan, Qianyanzhou, Changbaishan, Beijing, Maoxian, Gonggashan, Huitong, Dinghushan, Heshan, Ailaoshan, Xishuangbanna, Inner Mongolia, Haibei, Fukang, Naiman, Ordos, Linze, Cele, Shapotou, Sanjiang, Taihu, Donghu, Dayawan, Jiaozhouwan.
Data volume497 records
Data format.xlsx
Data service systemhttp://www.sciencedb.cn/dataSet/handle/664
Source(s) of fundingNational Key R&D Program of China(2017YFC0503803);Science and technology service network Initiative of Chinese Academy of Sciences(STS Plan,KFJ-SW-STS-168)
Dataset/Database compositionThe data is stored in an Excel file which is composed of two sheets. The “Accumulated Temperature Data” sheet stores the accumulated temperature data of 35 field stations from 2001 to 2015, with a total of 497 records; The “Information of field stations” sheet stores the basic background information for 35 stations.
1.   Introduction
Thermal resources are the important basis for the division of natural areas and natural belts, and the important natural resource for agricultural production. They are usually characterized by the temperature and the accumulated temperature. The accumulated temperature is the sum of average daily temperature during a certain period of time. It is widely used in the practice of agricultural production, which is significant for agricultural climate zoning, rational allocation of crops, crop phenology prediction, pest and disease prediction, etc..1.2.3.4. In the context of global warming, more and more researchers employ the accumulated temperature as an important indicator to explore the spatial and temporal variation of national or regional agricultural thermal resources, and the impact of thermal resource changes on agricultural production.1.3.5.6.7.8.9.10.
Ecosystems are at the heart of the biosphere, which is most active and closely related to human activities in the earth surface system. Chinese Ecosystem Research Network (CERN) was established in 1988. Currently, it consists of 44 field stations, 5 sub-centers and 1 synthesis center. The stations encompass diverse ecosystems in China, including agriculture, forest, grassland, desert, lake, bay, wetland, karst and urban ecosystems, and distribute in China's major climate zones and economic type regions.11.One of the core missions of CERN is to implement long-term ecological monitoring of ecological processes and their environmental controlling factors of China’s ecosystems. Since 1998, the field stations of CERN continuously measure and record more than 300 monitoring variations in hydrological, pedological, atmospheric and biological elements of ecosystems according to the standard monitoring protocols.12.Each station sets up a meteorological observation site to obtain meteorological data in a place that can reflect the characteristics of meteorological elements of a large range around the station.13.
At present, the researches on accumulated temperature are mainly based on the temperature data from meteorological observing stations of China Meteorological Administration (CMA). The meteorological data of CERN’s field stations not only reflects the meteorological conditions of the stations, but also represents the average meteorological conditions of certain range.14.Therefore, it is an important supplement to the data of CMA’s stations. Based on this, the dataset of accumulated temperature of CERN’s stations has been established to support the research on national or regional temporal and spatial distribution of accumulated temperature.
2.   Data collection and processing
Automatic observation is the main method of ecological observation. Automatic weather stations have been set up in the field stations to continuously measure the meteorological elements. Raw data obtained by the instruments is processed into standardized reports by the data processing software developed by the atmospheric sub-center, and reported to the atmospheric sub-center every year. The sub-center examines the data and submits the data that meets the requirements of the specification to the synthesis center. The synthesis center loads the data into the database and publishes it to the public. In 2005, a manual weather station was set up in each field station, and the observation data is also regularly submitted, reviewed, and released.
This dataset is based on the automatic observation temperature data because of its long time series, and the manual observation data and the meteorological data from the stations of CMA were adopted as the auxiliary data. Detailed processes are shown in Figure 1.


Fig.1   Construction flow of accumulated temperature dataset
2.1   Data source
HMP45D temperature and humidity sensor produced by Vaisala Company of Finland is used to measure the air temperature in each field station. This sensor is also used by the meteorological observing network of CMA.15 The raw data is stored in a daily data file in the data logger every hour, and then the daily and monthly average and total value are calculated by the data processing software.13.14.
The temperature data of most field stations began in 1998. Considering the uneven quality of data in the initial stage of observation, the period of the accumulated temperature dataset has been delimited to 2001-2015. The daily average temperature data of automatic observation from 35 field stations (Table 1) with more than 10 years of observation data has been selected as the basic data. This data was downloaded from the long-term monitoring database of CERN data resource service website (http://www.cnern.org.cn) and the manual observation data was also from this website. The daily temperature data of adjacent weather stations of CMA came from the National Meteorological Information Center, and the period is from 2001 to 2004.
2.2   Abnormal data culling
The original data has been subjected to quality control of the atmospheric sub-center each year, including physical extreme value inspection, historical extreme value inspection, internal consistency check, time consistency check, etc.,14.and the apparent error data have been eliminated. In order to correct all errors and extremely suspicious data as much as possible, data quality checks were carried out around long-term sequence comparison and multi-site comparison (see Chapter 4 for details), and the error data detected are removed.
2.3   Data interpolation
Due to instrument failures, human factors, quality inconsistency and other reasons, some temperature data of each station are missing, resulting in incomplete time series of daily temperatures. In order to ensure the integrity and continuity of the accumulated temperature data, the missing temperature data need to be interpolated to obtain a complete data sequence.
A regression equation for the temperature series of the field station and correlative temperature series with good data integrity has been established to interpolate the basic temperature data. From 2005 to 2015, the daily manual observation temperature data of the field stations was selected as the reference data, and from 2001 to 2004, the reference data was the daily temperature data of the nearby meteorological station of CMA. The unary linear regression equation for the daily temperature data of a field station and the reference data sequence was established, and the reference data was used to fill in the missing data. All regression equations have a high degree of fitting which R2 is greater than 0.96 from 2001 to 2004 and above 0.98 from 2005 to 2015, and all pass the significance test. The data interpolation rates of each field station are shown in Table 1.
Table 1   Basic information of the field station and the data interpolation rate
Station
name
Station codeEcological typeLocation of meteorological observation siteData interpolation rate(%)
Longitude(°)latitude(°)Elevation(m)2001-20042005-2015
HailunHLAAgriculture126.9347.4523410.951.92
ShenyangSYAAgriculture123.3741.524237.174.63
LuanchengLCAAgriculture114.6937.8950.123.0718.67
AnsaiASAAgriculture109.3336.86103331.554.21
YuchengYCAAgriculture116.5736.83222.745.20
ChangwuCWAAgriculture110.6835.2412204.934.16
FengqiuFQAAgriculture114.5535.0267.59.864.63
ChangshuCSAAgriculture120.7031.553.17.121.57
YantingYGAAgriculture105.4631.274201.235.08
TaoyuanTYAAgriculture111.4428.9310617.111.67
YingtanYTAAgriculture116.9328.214519.993.31
LasaLSAAgriculture91.3429.6836884.63
QianyanzhouQYAAgriculture115.0626.7553.51.371.00
ChangbaishanCBFForest128.1042.357387.942.99
BeijingBJFForest115.4339.97124824.985.00
MaoxianMXFForest103.9031.7018912.54
GonggashanGGFForest102.0029.5830003.358.66
HuitongHTFForest109.6126.8555710.136.67
DinghushanDHFForest112.5523.1610033.472.36
HeshanHSFForest112.9022.687513.623.24
XishuangbannaBNFForest101.2621.935650.551.54
Inner MongoliaNMGGrassland116.7143.64118713.695.80
HaibeiHBGGrassland101.3137.61320022.454.80
FukangFKDdesert87.9344.3047518.147.64
NaimanNMDdesert120.7042.9335814.994.28
OrdosESDdesert110.1939.4913009.36
LinzeLZDdesert110.1339.3513841.05
CeleCLDdesert80.4337.0113033.41
ShapotouSPDdesert105.0137.47134015.335.92
SanjiangSJMwetland133.5047.595512.732.94
TaihuTHLlake120.2231.421020.740.77
DonghuDHLlake114.3530.55210.57
DayawanDYBBay114.9122.99402.331.24
JiaozhouwanJZBBay120.2736.051513.0715.48
2.4   Accumulated temperature calculation
The accumulated temperature commonly used in agricultural production has two types: active accumulated temperature and effective accumulated temperature. The daily average temperature equal to or greater than the biological lower limit temperature is called the active temperature; the sum of the active temperatures in a certain period is the active accumulated temperature. The difference between the activity temperature and the biological lower limit temperature is called the effective temperature, and the sum of the effective temperatures for a certain period of time is the effective accumulated temperature.16.
10℃ is the starting temperature suitable for the growth of thermophilic plants, and it is also the temperature at which the cool crops grow rapidly and the perennial crops begin to accumulate dry matter at a faster rate. The accumulated temperature greater than and equal to 10℃ and its corresponding duration are used to measure the agro-climatic production potential of a region and to be an important basis for the introduction and cultivation system reform by agricultural production department and researchers.3.7.17.Therefore, this dataset sets the threshold temperature for calculating the accumulated temperature as 10℃, and uses the 5-day moving average method to calculate the active accumulated temperature, effective accumulated temperature and duration. The calculation method is as follows.
(1) Determine the beginning and ending date of daily temperature greater than and equal to 10℃
In a year, the longest period in which the 5-day moving average is greater than or equal to 10℃ is selected. In the first 5 days of this period, the first day with a daily average temperature greater than or equal to 10℃ is selected as the beginning date. In the last 5 days, the last day with an average temperature greater than or equal to 10℃ is selected as the ending date.16.18.
(2) Compile a computer program to calculate the accumulated temperature and the duration
The active accumulated temperature is the sum of the daily average temperatures from the beginning date to the ending date calculated with following equation:
 
\({\mathrm{T}}_{\mathrm{a}}=\sum _{\mathrm{i}=1}^{\mathrm{n}}{\mathrm{T}}_{\mathrm{i}}\)(1)
Where Ta is the actively accumulated temperature (℃); Ti is the average temperature on day i (℃), when Ti<10℃, Ti=0; n is the number of days in the calculation period.
Calculate the sum of the difference between the daily average temperature and 10℃ from the beginning date to the ending date according to the following equation, and the effective accumulated temperature is obtained.
 
\({\mathrm{T}}_{\mathrm{e}}=\sum _{\mathrm{i}=1}^{\mathrm{n}}{\left(\mathrm{T}}_{\mathrm{i}}-10\right)\)(2)
In the equation above, Te is the effective accumulated temperature (℃); Ti is the average temperature on day i (℃), when Ti<10℃, Ti=10; n is the number of days in the calculation period.
The number of days between the beginning date and the end date is accumulated to obtain the duration of daily temperature greater than and equal to 10℃.
3.   Sample description
The data is stored in an Excel file which is composed of two sheets. The “Accumulated Temperature Data” sheet stores the accumulated temperature data of 35 field stations from 2001 to 2015, with a total of 497 records; The “Information of field stations” sheet stores the basic background information for 35 stations. See Table 2 and Table 3 for the specific field names, types, and examples contained in these two sheets.
Table 2   The content of “Accumulated Temperature Data” sheet
Field nameUnitData typesample
Station codecharacterASA
YearNumber2001
Active accumulated temperatureNumber3110.1
Effective accumulated temperatureNumber1530.1
Beginning datecharacter2001-4-27
Ending datecharacter2001-10-6
DurationdayNumber163
Table 3   The content of “Information of field stations” sheet
Field nameunitData typeSample
Station namecharacterAnsai Station
Station codecharacterASA
LocationcharacterDun Tan, Ansai County, Yanan City, Shaanxi Province
Ecosystem typecharacterAgriculture
Longitude of meteorological observation site°Number109.33
Latitude of meteorological observation site°Number36.86
Elevation of meteorological observation sitemNumber1033
Brief description of regional representativenesscharacterAnsai station is located in the typical loess hilly and gully region in the middle of the Loess plateau. It is in the interlaced zone of loess and sandy loess, in the transition region from semi-humid to semi-arid of warm temperate zone, in the forest-steppe ecotone from warm temperate deciduous broad-leaved forest to dry steppe, and it is also a typical serious soil erosion area affected by human activities. It is typical for carrying out scientific research and experimental demonstration of soil and water conservation and ecological environment construction for the various land types and the abundant resources.




Fig. 2   Changes in ≥10℃ accumulated temperature of HaiLun station and Yingtan station for 2001-2015
Figure 2 shows the variation of active accumulated temperature and effective accumulated temperature greater than and equal to 10℃ of Hailun station and Yingtan station from 2001 to 2015.
4.   Quality control
In order to improve the accuracy, authenticity and reliability of the data, the basic data has been checked by means of “partner test”, which compares the meteorological elements of one or more nearby stations that are similar in climate.19.
The 2001-2004 temperature data was checked by comparing the daily temperature of the field station with a nearby meteorological station of CMA. The temperature anomalies of the tow stations were compared to eliminate the inherent gap of the data between the two stations, and the data with the difference between the two stations exceeding 2.5℃ was regarded as the erroneous data.19.
The temperature data for 2005-2015 was compared with the manual observation data. The data of the field station with an anomaly difference of more than 2.5℃ was regarded as suspicious data, and then the data of the adjacent meteorological station of CMA was used to determine whether it was erroneous data.
5.   Usage notes
This dataset collects the accumulated temperature greater than and equal to 10℃ for 35 field stations of CERN from 2001 to 2015, covering major ecosystems of China such as agriculture, forest, grassland, desert, wetland, lake and bay. It provides a new data source for relevant researchers to study on regional or national spatio-temporal pattern and variation characteristics of accumulated temperature greater than and equal to 10℃, and further to support a more comprehensive disclosure of the pattern of thermal resource allocation, planning and adjustment of planting structure and crop layout, and formulation of agricultural sustainable development planning.
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Data citation
Su W. A dataset of ≥10℃ accumulated temperature of field stations in Chinese typical ecosystems from 2001 to 2015. Science Data Bank, DOI: 10.11922/sciencedb.664(2019).
Article and author information
How to cite this article
Su W. A dataset of ≥10℃ accumulated temperature of field stations in Chinese typical ecosystems from 2001 to 2015. China Scientific Data 4(2018). DOI: 10.11922/csdata.2018.0065.zh
Su Wen
Contribution: data processing and paper writing.
suw@igsnrr.ac.cn
bachelor, senior engineer, area: Ecoinformatics.
National Key R&D Program of China(2017YFC0503803);Science and technology service network Initiative of Chinese Academy of Sciences(STS Plan,KFJ-SW-STS-168)
Publication records
Published: March 28, 2019 ( VersionsEN4
Released: Oct. 24, 2018 ( VersionsZH2
Published: March 28, 2019 ( VersionsZH3
References
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