Chin J Plan Ecolo ›› 2015, Vol. 39 ›› Issue (6): 541-553.doi: 10.17521/cjpe.2015.0052

• Orginal Article •     Next Articles

Microclimate of forests across East Asia biomes: 1. Radiation and energy balance

TAN Zheng-Hong1,*(), YU Gui-Rui2, ZHOU Guo-Yi3, HAN Shi-Jie4, HSIA Yue-Joe5, MAEDA Takashi6, KOSUGI Yoshiko7, YAMANOI Katsumi8, LI Sheng-Gong2, OHTA Takeshi9, HIRATA Ryuichi10, YASUDA Yukio11, NAKANO Takashi12, KOMINAMI Yuji13, KITAMURA Kenzo14, MIZOGUCHI Yasuko12, LIAO Zhi-Yong1, ZHAO Jun-Fu1, YANG Lian-Yan1   

  1. 1Key Laboratory of Tropical Forest Ecology, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Kunming 650223, China
    2Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    3South China Botanical Garden, Chinese Academy of Sciences, Guangzhou 510650, China
    4Shenyang Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China
    5College of Environmental Studies, Dong Hwa University, Hualien 97401, Taiwan, China
    6Environmental Management Research Institute, National Institute of Advanced Industrial Science and Technology, Tsukuba 305-8569, Japan
    7Graduate School Agriculture, Kyoto University, Kyoto 606-8501, Japan
    8Hokkaido Research Center, Forestry and Forest Products Research Institute, Sapporo 062-8516, Japan
    9Graduate School of Bioagricultural Sciences, Nagoya University, Nagoya 464-8601, Japan
    10Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba 305-8506, Japan
    11Tohoku Research Center, Forestry and Forest Products Research Institute, Iwate 020-0123, Japan
    12Department of Meteorological Environment, Forestry and Forest Products Research Institute, Tsukuba 305-8687, Japan
    13Kansai Research Center, Forestry and Forest Products Research Institute, Kyoto 612-0855, Japan
    14Kyushu Research Center, Forestry and Forest Products Research Institute, Kumamoto 860-0862, Japan
  • Received:2014-10-09 Accepted:2015-03-31 Online:2015-07-02 Published:2015-06-01
  • Contact: Zheng-Hong TAN
  • About author:

    # Co-first authors

Abstract: <i>Aims</i>

Forest microclimate is the local environment generated through the interaction between regional climate and forest structure. Studies on forest microclimate not only have theoretical significances in ecology but also practical meanings in forest management practices and wood production. Radiation budget and energy balance is the basis for microclimate. Few studies have performed the radiatoin budget and energy balance analysis at regional scale. Here, we focused at this for the East Asia.


A total of 17 forest sites in the East Asia across biomes were used in this study. Measurements on solar radiation, long-wave radiation, net radiation, sensible heat flux, latent heat flux, and soil heat flux were compiled in the context of radiation and energy conservation. The annual variations of radiation and energy components were analyzed by site. Mean annual radiation and energy were related to latitude. The radiation and energy conservation equations were established for each forest biome by the multi-site block averages.

<i>Important findings</i>

Forest radiation properties (i.e. solar radiation, net radiation, albedo) showed a linear trend with latitude among the sites. For example, the solar radiation and latitude relationship is: y = 6205 - 42.15x (p < 0.01), indicating that solar radiation decreases with latitude at a rate of 42 MJ per degree with a theoretical maximum of 6205 MJ. A more significant relationship was found between net radiation and latitude: y = 4340 - 45.60x (r = -0.89, p < 0.0001). The radiation and energy budgets of boreal, temperate, subtropical and tropical forest were established. Evapotranspiration fraction (EF) was highly correlated with precipitation (P) as: EF = 0.7098(1 - exp(-0.0026P)) (R2 = 0.7451, p < 0.0001). Subtropical forest showed a unique pattern in this cross-biome analysis but needs further studies in the future.

Key words: subtropical forest, latitude trend, evapotranspiration fraction, solar radiation, energy partitioning

Table 1

Site characteristics of the 16 sites in this study"

Fig. 1

Changes in annual mean air temperature with latitude."

Fig. 2

The annual cycle of solar radiation above forest canopy across forest biomes. A, SKT for boreal forest. B, TMK for temperate forest. C, DHS for subtropical forest. D, PSO for tropical forest. Each value is the daily sum of multi-year means. Site information sees Table 1."

Fig. 3

The annual cycle of net radiation above forest canopy across forest biomes. A, SKT for boreal forest. B, TMKfor temperate forest. C, DHS for subtropical forest. D, PSO for tropical forest. Each value is the daily sum of multi-year means. Site information sees Table 1."

Fig. 4

The annual cycle of albedo above forest canopy across forest biomes. A, SKT for boreal forest. B, TMK for temperate forest. C, DHS for subtropical forest. D, PSO for tropical forest. Each value is the daily average of multi-year means. Site information sees Table 1."

Fig. 5

The annual cycle of Bowen ratio above forest canopy across forest biomes. A, SKT for boreal forest. B, TMK for temperate forest. C, DHS for subtropical forest. D, PSO for tropical forest. Each value is the daily sum of multi-year means. Site information sees Table 1."

Fig. 6

The annual cycle of soil heat flux above forest canopy across forest biomes. A, SKT for boreal forest. B, TMK for temperate forest. C, DHS for subtropical forest. D, PSO for tropical forest. Each value is the daily average of multi-year means. Site information sees Table 1."

Table 2

Summary of the forest radiation and energy properties"

Solar radiation
Upward shortwave radiation (MJ·m-2·a-1)
Net radiation
Net longwave radiation losses (MJ·m-2·a-1)
Soil heat flux (MJ·m-2·a-1)
Bowen ratio
Evapotranspiration fraction
1 YLF 2 988 400 1 675 913 - 0.26 0.56 1.26 0.44
2 YPF 3 645 571 1 941 1 133 - 0.24 0.53 - -
3 SKT 5 397 537 2 060 2 800 -85 0.10 0.38 2.53 0.28
4 SAP 4 661 882 2 340 1 439 -10 0.20 0.50 0.27 0.78
5 TMK 4 197 625 2 490 1 082 -2 0.15 0.59 0.65 0.60
6 CBS 5 012 - 2 323 - - - 0.46 0.68 0.59
7 API 4 024 758 1 999 1 276 -22 0.19 0.50 0.28 0.77
8 KWG 4 813 482 2 401 1 930 -23 0.10 0.50 0.31 0.75
9 FJY 5 120 556 3 006 1 558 15 0.10 0.59 0.31 0.75
10 YMS 4 580 632 2 824 1 124 - 0.14 0.62 - -
11 KHW 4 935 432 3 151 1 352 - 0.09 0.64 0.35 0.73
12 QYZ 4 189 - 2 707 - - - 0.65 0.43 0.69
13 CLM 3 834 373 2 559 902 -18 0.10 0.67 0.70 0.58
14 DHS 4 551 349 2 815 1 387 -28 0.08 0.62 0.54 0.65
15 MKL 6 380 845 4 273 1 262 -38 0.13 0.67 0.45 0.68
16 SKR 6 185 816 3 918 1 451 -15 0.13 0.63 0.70 0.58
17 PSO 6 255 701 4 547 1 007 -30 0.11 0.73 0.46 0.68

Fig. 7

The dependence of radiation on latitude. A, solar radiation (Rn). B, net radiation (Rg). C, ratio between net and solar radiation (Rg / Rn). D, albedo. Each value in the plot represents the annual sums."

Fig. 8

Relationships between evapotranspiration fraction (EF) and precipitation (P). CLM site was not included in the regression."

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