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Evaluating the Accuracy of a Gridded Near-Surface Temperature Dataset over Mainland China

1,2,3,*, 1,2,3,*, 1,2,3, 1,2,3 and 1,2,3
1
Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences, Beijing 100081, China
2
National Engineering Laboratory of Efficient Crop Water Use and Disaster Reduction, Beijing 100081, China
3
Key Laboratory of Agricultural Environment, Ministry of Agriculture, Beijing 100081, China
*
Authors to whom correspondence should be addressed.
Atmosphere 2019, 10(5), 250; https://doi.org/10.3390/atmos10050250
Received: 31 March 2019 / Revised: 18 April 2019 / Accepted: 23 April 2019 / Published: 7 May 2019
(This article belongs to the Section Climatology and Meteorology)
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Abstract

High-resolution meteorological data products are crucial for agrometeorological studies. Here, we study the accuracy of an important gridded dataset, the near-surface temperature dataset from the 5 km × 5 km resolution China dataset of meteorological forcing for land surface modeling (published by the Beijing Normal University). Using both the gridded dataset and the observed temperature data from 590 meteorological stations, we calculate nine universal meteorological indices (mean, maximum, and minimum temperatures of daily, monthly, and annual data) and five agricultural thermal indices (first frost day, last frost day, frost-free period, and ≥0 °C and ≥10 °C active accumulated temperature, i.e., AAT0 and AAT10) of the 11 temperature zones over mainland China. Then, for each meteorological index, we calculate the root mean square errors (RMSEs), correlation coefficient and climate trend rates of the two datasets. The results show that the RMSEs of these indices are usually lower in the north subtropical, mid-subtropical, south subtropical, marginal tropical and mid-tropical zones than in the plateau subfrigid, plateau temperate, and plateau subtropical mountains zones. Over mainland China, the AAT0, AAT10, and mean and maximum temperatures calculated from the gridded data show the same climate trends with those derived from the observed data, while the minimum temperature and its derivations (first frost day, last frost day, and frost-free period) show the opposite trends in many areas. Thus, the mean and maximum temperature data derived from the gridded dataset are applicable for studies in most parts of China, but caution should be taken when using the minimum temperature data. View Full-Text
Keywords: climate trend; data evaluation; high-resolution meteorological dataset; root mean square error climate trend; data evaluation; high-resolution meteorological dataset; root mean square error
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Qiu, M.; Liu, B.; Liu, Y.; Zhang, Y.; Han, S. Evaluating the Accuracy of a Gridded Near-Surface Temperature Dataset over Mainland China. Atmosphere 2019, 10, 250.

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