Long-term simulation of China’s climate data-establishment and validation of the dynamic free-scale model

doi:10.3969/j.issn.1000-2006.2013.06.017

DAI Jinsong, CAO Lin, WANG Guibin

Journal of Nanjing Forestry University (Natural Sciences Edition） ›› 2013, Vol. 37 ›› Issue (06) : 82-88.

PDF(1412655 KB)

Journal of Nanjing Forestry University (Natural Sciences Edition） ›› 2013, Vol. 37 ›› Issue (06) : 82-88. DOI: 10.3969/j.issn.1000-2006.2013.06.017

Long-term simulation of China’s climate data-establishment and validation of the dynamic free-scale model

DAI Jinsong, CAO Lin^*, WANG Guibin

Author information +

History +

Abstract

The free-scale climate data plays an important role as basic data in projecting future forest growth and distribution, and analyzing the responses and adaptation of forest ecosystems on climate change. In this paper, by using multi-source long term static scale climate data, the free-scale climate data model in China was established in terms of a new downscaling algorithm by combining the bilinear distance-weighted interpolation and elevation adjustment; the baseline climate data was validated by historical climate data from 302 in the nationwide. The results indicated that the correlations between geographic variables and temperature variables were high, fitting effects of elevation adjustment functions were all significant(R² greater than 0.91). Through downscaling, the baseline data not only improved the spatial resolution, but also the data accuracy. Since the relationships between precipitation variables and geographic variables were not strong enough to develop elevation adjustment functions, they were only adjusted by bilinear distance-weigthed interpolation, but the improvements still remained. The algorithm overlaied the historical and projected climate anomalies to free-scale baseline data ensured the data integrity in the missing values regions and maintained the accuracy. However, attentions should be paid to the fact that, given the randomness and volatility of the climate environment as well as the influnces of micro-climate and vegatation, the estimated accuracy of average value in a long term would be much more reliable.

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

DAI Jinsong, CAO Lin, WANG Guibin. Long-term simulation of China’s climate data-establishment and validation of the dynamic free-scale model[J]. Journal of Nanjing Forestry University (Natural Sciences Edition）. 2013, 37(06): 82-88 https://doi.org/10.3969/j.issn.1000-2006.2013.06.017

References

[1] 朱建华, 侯振宏, 张小全. 气候变化对中国林业的影响与应对策略[J]. 林业经济, 2009(11): 78-83.Zhu J H, Hou Z H, Zhang X Q. The impacts of climate change on chinese forestry and its adaptation proposals[J]. Forestry Economics, 2009(11): 78-83.
[2] Mbogga M S, Hamann A, Wang T. Historical and projected climate data for natural resource management in western Canada[J]. Agricultural and Forest Meteorology, 2009,149(5): 881-890.
[3] Simpson J J, Hufford G L, Daly C, et al. Comparing maps of mean monthly surface temperature and precipitation for Alaska and adjacent areas of Canada produced by two different methods[J]. Arctic, 2005,58(2): 137-161.
[4] David T Price, Daniel W McKenney, Ian A Nalderm, et al. a comparison of two statistical methods for spatial interpolation of Canadian monthly mean climate data[J]. Agricultural and Forest Meteorology, 2000,101: 81-94.
[5] Milewska E J, Hopkinson R F, Niitsoo A. Evaluation of geo-referenced grids of 1961—1990 Canadian temperature and precipitation normals[J]. Atmosphere-Ocean, 2005,43(1): 49-75.
[6] Hutchinson M F. Interpolating mean rainfall using thinplate smoothing splines[J]. International Journal of Geographical Information Systems, 1995,9(4): 385-403.
[7] Hutchinson M F, Gessler P E. Splines-more than just a smooth interpolator[J]. Geoderma, 1994,62: 45-47.
[8] Mitchell T D, Jones P D. An improved method of constructing a database of monthly climate observations and associated high-resolution grids[J]. International Journal of Climatology, 2005,25(6): 693-712.
[9] McKenney D W, Pedlar J H, Papadopol P, et al. The development of 1901-2000 historical monthly climate models for Canada and the United States[J]. Agricultural and Forest Meteorology, 2006,138(1-4): 69-81.
[10] 刘志红, Tim R McVicar, Li LingTao, 等. 基于ANUSPLIN的时间序列气象要素空间插值[J]. 西北农林科技大学学报: 自然科学版, 2008,36(10): 227-234.Liu Z H, Tim R McVicar, Li L T, et al. Interpolation for time series of meteorological variables using ANUSPLIN[J]. Journal of Northwest A & F University: Natural Sciences Edition, 2008, 36(10): 227-234.
[11] 钱永兰, 吕厚荃, 张艳红. 基于ANUSPLIN软件的逐日气象要素插值方法应用与评估[J]. 气象与环境学报, 2010,26(2): 7-14.Qian Y L, Lv H Q, Zhang Y H. Application and assessment of spatial interpolation method on daily meteorological elements based on ANUSPLIN software[J]. Journal of Meteorology and Environment, 2010, 26(2): 7-14.
[12] Daly C. Guidelines for assessing the suitability of spatial climate data sets[J]. International Journal of Climatology, 2006,26(6): 707-721.
[13] Daly C, Gibson W P, Taylor G H, et al. A knowledge-based approach to the statistical mapping of climate[J]. Climate Research, 2002,22(2): 99-113.
[14] 韩庆红, 陈渭民, 王普才, 等. PRISM在松花江流域降水分布中的应用研究[J]. 南京气象学院学报, 2006,29(1): 56-61.Han Q H, Chen W M, Wang P C, et al. Application of PRISM spatial interpolation to the precipitation distribution in the Songhuajiang river basin[J]. Journal of Nanjing Institute of Meteorology, 2006,29(1): 56-61.
[15] 赵登忠, 张万昌, 刘三超. 基于DEM的地理要素PRISM空间内插研究[J]. 地理科学, 2004,24(2): 205-211.Zhao D Z, Zhang W C, Liu S C. Interpolation of meteorological data based on DEM using PRISM model[J]. Scientia Geographica Sinica, 2004,24(2): 205-211.
[16] 朱华忠, 罗天祥, Daly C. 中国高分辨率温度和降水模拟数据的验证[J]. 地理研究, 2003,22(3): 349-359.Zhu H Z, Luo T X, Daly C. Validation of simulated grid data sets of China’s temperature and precipitation with high spatial resolution[J]. Geographical Research, 2003,22(3): 349-359.
[17] Rehfeldt G E, Ying C C, Spittlehouse D L, et al. Genetic responses to climate in Pinus contorta: niche breadth, climate change, and reforestation[J]. Ecological Monographs, 1999,69(3): 375-407.
[18] Hamann A, Wang T L. Models of climatic normals for genecology and climate change studies in British Columbia[J]. Agricultural and Forest Meteorology, 2005,128(3-4): 211-221.
[19] Wang T, Hamann A, Spittlehouse D L, et al. Development of scale-free climate data for western Canada for use in resource management[J]. International Journal of Climatology, 2006,26(3): 383-397.
[20] Wang T, Hamann A, Spittlehouse D L, et al. Climate WNA-high-resolution spatial climate data for western north America[J]. Journal of Applied Meteorology and Climatology, 2012,51(1): 16-29.

PDF(1412655 KB)

Accesses

Citation

Detail

Sections

Recommended

The full text is translated into English by AI, aiming to facilitate reading and comprehension. The core content is subject to the explanation in Chinese.

www.nldxb.njfu.edu.cn

Edited ＆ Published by Editorial Department of Nanjing Forestry University(Natural Sciences Edition)
Address： No.159 Longpan Road,Nanjing 210037 Jiangsu,P.R.China
E-mail ：xuebao@njfu.edu.cn , xuebao@njfu.com.cn
Telephone +86-25-85428247,85427076
Distributed by China International Book Trading Corporation P.O. Box 399, Beijing ,P.R. China

〈

〉

Please choose a citation manager

Content to export