Evaluation and Parameter Optimization of Monthly Net Long-Wave Radiation Climatology Methods in China
<p>Distribution of the nineteen radiation stations in China.</p> "> Figure 2
<p>Evolution of daily net long-wave radiation for the period from January 1993 to December 2012 at Beijing (<b>a</b>) and Ejin Banner (<b>b</b>).</p> "> Figure 3
<p>Correlation between the standard and estimated monthly net long-wave radiation based on the seven existing empirical formulas (<b>a</b>) Brunt; (<b>b</b>) Penman; (<b>c</b>) Bepлянд; (<b>d</b>) FAO24; (<b>e</b>) FAO56-PM; (<b>f</b>) Deng Genyun; (<b>g</b>) Tong Hongliang) and CERES data (<b>h</b>) at the nineteen radiation stations.</p> "> Figure 4
<p>Correlation between the standard and validated monthly net long-wave radiation (<b>a</b>) national formula; (<b>b</b>) regional formula) at the nineteen radiation stations.</p> "> Figure 5
<p>Cumulative frequency of MAPE between the standard and estimated monthly net long-wave radiation based on the nine empirical formulas and the CERES data.</p> "> Figure 6
<p>RMSE of the regional, Deng Genyun, and Tong Hongliang formulas compared with the standard net long-wave radiation at nineteen stations in China.</p> ">
Abstract
:1. Introduction
2. Data and Methods
2.1. Data
2.2. Methods
2.2.1. Empirical Formulas
2.2.2. Analytical Methods
3. Results and Discussion
3.1. Assessment of the Existing Rnl Empirical Formulas
3.2. Establishment of Optimal Rnl Empirical Formulas
4. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
References
- Rodskjer, N. Net long-wave radiation at Uppsala, Sweden. Theor. Appl. Climatol. 1979, 27, 189–192. [Google Scholar] [CrossRef]
- Zhou, S.Z.; Zhang, R.R.; Zhang, C. Meteorology and Climatology; Higher Education Press: Beijing, China, 1990; pp. 40–42. [Google Scholar]
- Jimenez, J.I.; Alados-Arboledas, L.; Castro-Diez, Y.; Ballester, G. On the estimation of long–wave radiation flux from clear skies. Theor. Appl. Climatol. 1987, 38, 37–42. [Google Scholar] [CrossRef]
- Trnka, M.; Zalud, Z.; Eitzinger, J.; Dubrovský, M. Global solar radiation in Central European lowlands estimated by various empirical formulae. Agric. For. Meteorol. 2005, 131, 54–76. [Google Scholar] [CrossRef]
- Angstrom, A.K. On the variation of the atmosphere radiation. Gerl. Beitr. Geophys. 1925, 4, 21–145. [Google Scholar]
- Brunt, D. Notes on radiation in the atmosphere. I. Quart. J. R. Meteor. Soc. 1932, 58, 389–420. [Google Scholar] [CrossRef]
- Lu, B. Probe into the calculating method of evaporation capacity in Poyang Lake. Jiangxi Hydraul. Sci. Technol. 1994, 20, 347–354. [Google Scholar]
- Penman, H.L. Natural Evaporation from Open Water, Bare Soil and Grass. Proc. R. Soc. 1948, A193, 120–145. [Google Scholar] [CrossRef]
- Swinbank, W.C. Long–wave radiation from clear skies. Quart. J. R. Meteorol. Soc. 1963, 89, 339–348. [Google Scholar] [CrossRef]
- Idso, S.B.; Jackson, R.D. Thermal radiation from the atmosphere. J. Geophys. Res. 1969, 74, 5397–5403. [Google Scholar] [CrossRef]
- Doorenbos, J.; Pruitt, W.O. Guidelines for Predicting Crop. Water Requirements; Food and Agriculture Organization of the United Nations: Rome, Italy, 1977; p. 27. [Google Scholar]
- Allen, R.G.; Perreira, L.S.; Raes, D. Crop. Evapotranspiration: Guidelines for Computing Crop. Water Requirements; Food and Agriculture Organization of the United Nations: Rome, Italy, 1998; pp. 51–52. [Google Scholar]
- Matsui, H. Comparison of net longwave radiation equation in penman–type evapotranspiration equation. Trans. Jap. Soc. Irrig. Drain. Rural Eng. 2011, 78, 531–536. [Google Scholar]
- Matsui, H.; Osawa, K. Calibration effects of the net longwave radiation equation in Penman—Type methods at Tateno, Japan. Hydrol. Res. Lett. 2015, 9, 113–117. [Google Scholar] [CrossRef]
- Tong, H.L. A climatic calculation method for the evaporation power in China. J. Nanjing Inst. Meteorol. 1989, 12, 19–33. [Google Scholar]
- Deng, G.Y. A climatic calculative method of evaporation from open water. Acta Meteorol. Sin. 1979, 37, 87–96. [Google Scholar]
- Ji, G.L.; Jiang, H.; Zha, S.F. The computation and some distribution characteristics of effective radiation over the Qinghai–Xizang Plateau and its adjacent areas. Plateau Meteorol. 1987, 6, 141–149. [Google Scholar]
- Li, R.; Zhao, L.; Wu, T.H.; Wu, X.D.; Xiao, Y.; Du, Y.Z.; Qin, Y.H. The impacts of net long–wave radiation on the surface soil thermal regimes over the Qinghai–Tibetan Plateau, China. Environ. Earth Sci. 2016. [Google Scholar] [CrossRef]
- Reed, R.K. Variations in oceanic net long-wave radiation caused by atmospheric thermal structure. J. Geophys. Res. Atmos. 1975, 80, 3819–3820. [Google Scholar] [CrossRef]
- Reed, R.K. On estimation of net long–wave radiation from the oceans. J. Geophys. Res. Atmos. 1976, 81, 5793–5794. [Google Scholar] [CrossRef]
- Siegel, D.A.; Dickey, T.D. Variability of net longwave radiation over the eastern North Pacific Ocean. J. Geophys. Res. Atmos. 1986, 91, 7657–7666. [Google Scholar] [CrossRef]
- Allan, R.P.; Slingo, A. Simulated long–wave clear–sky irradiance over the ocean: Spatial and temporal variability 1979–1993. Phys. Chem. Earth 1998, 23, 599–604. [Google Scholar] [CrossRef]
- Zapadka, T.; Woźniak, S.B.; Woźniak, B. A simple formula for the net long–wave radiation flux in the southern Baltic Sea. Oceanologia 2001, 43, 265–277. [Google Scholar]
- Zapadka, T.; Woźniak, B.; Dera, J. A more accurate formula for calculating the net longwave radiation flux in the Baltic Sea. Oceanologia 2007, 49, 449–470. [Google Scholar]
- Yao, Y.J.; Zhao, S.H.; Zhang, Y.H.; Jia, K.; Liu, M. Spatial and Decadal Variations in Potential Evapotranspiration of China Based on Reanalysis Datasets during 1982–2010. Atmosphere 2014, 5, 737–754. [Google Scholar] [CrossRef]
- Gao, G.; Chen, D.L.; Ren, G.Y.; Chen, Y.; Liao, Y.M. Spatial and temporal variations and controlling factors of potential evapotranspiration in China: 1956–2000. J. Geogr. Sci. 2006, 16, 3–12. [Google Scholar] [CrossRef]
- Xu, C.Y.; Gong, L.; Tong, J.; Chen, D. Decreasing reference evapotranspiration in a warming climate—A case of Changjiang (Yangtze) river catchment during 1970–2000. Adv. Atmos. Sci. 2006, 23, 513–520. [Google Scholar] [CrossRef]
- Li, Z.L.; Li, Z.J.; Xu, Z.X.; Zhou, X. Temporal variations of reference evapotranspiration in Heihe River basin of China. Hydrol. Res. 2013, 44, 904–916. [Google Scholar] [CrossRef]
- Shi, Z.J.; Xu, L.H.; Yang, X.H.; Shan, N. Trends in reference evapotranspiration and its attribution over the past 50 years in the Loess Plateau, China: Implications for ecological projects and agricultural production. Stoch. Environ. Res. Risk A 2016, 31, 1–17. [Google Scholar] [CrossRef]
- Zhang, X.Q.; Ren, Y.; Yin, J.; Zheng, D. Spatial and temporal variation patterns of reference evapotranspiration across the Qinghai–Tibetan Plateau during 1971–2004. J. Geophys. Res. 2009. [Google Scholar] [CrossRef]
- Zhang, Y.Q.; Liu, C.M.; Tang, Y.H.; Yang, Y.H. Trends in pan evaporation and reference and actual evapotranspiration across the Tibetan Plateau. J. Geophys. Res. 2007. [Google Scholar] [CrossRef]
- Gao, Z.D.; He, J.S.; Dong, K.B.; Bian, X.D.; Li, X. Sensitivity study of reference crop evapotranspiration during growing season in the West Liao River basin, China. Theor. Appl. Climatol. 2016, 124, 1–17. [Google Scholar] [CrossRef]
- Huo, Z.L.; Shi, H.B.; Chen, Y.X.; Qu, Z.Y. Spatiotemporal variation and dependence analysis of ET0 in north arid and cold region. Trans. Chin. Soc. Agric. Eng. 2004, 20, 60–63. [Google Scholar]
- CERES EBAF-Surface Product. Available online: https://ceres.larc.nasa.gov/products.php? product=EBAF-Surface (accessed on 6 May 2017).
- Sun, Z.A.; Weng, D.M. Climatological calculation and distributional features of effective radiation over China part II: Empirical computation method and distributional features. J. Nanjing Inst. Meteorol. 1986, 4, 335–347. [Google Scholar]
- Zhu, X.C.; Qiu, X.F.; Zeng, Y.; He, Y.J.; Liu, H.B. The research on the estimation method of effective radiation in China based on remote sensing data. J. Yunnan Univ. 2014, 36, 674–682. [Google Scholar]
- Cao, W.; Duan, C.F.; Yang, T.M.; Liu, R.N. The evaluation and parameter optimization of surface effective radiation climatology model. Acta Meteorol. Sin. 2016, 74, 947–958. [Google Scholar]
- Weng, D.M.; Feng, Y.H. Analysis on the characteristics of effective radiation and atmospheric radiation in summer on the Tibetan Plateau. Chin. Sci. Bull. 1984, 13, 796–799. [Google Scholar]
- Bian, L.G.; Lu, L.H.; Lu, C.G.; Chen, Y.J.; Gao, Z.Q. The characteristics of radiation balance components of the Tibetan Plateau in the summer of 1998. Chin. J. Atmos. Sci. 2001, 25, 577–588. [Google Scholar]
- Sun, Z.A.; Weng, D.M. Climatological calculation and distributional features of effective radiation over China part I: Theoretical discussion of calculation methodology. J. Nanjing Inst. Meteorol. 1986, 3, 228–238. [Google Scholar]
- Li, R.; Zhao, L.; Ding, Y.J.; Shen, Y.P.; Ji, G.L.; Liu, G.Y.; Du, E.J.; Xiao, Y.; Sun, L.C.; Liu, Y.; et al. Variations of Surface Effective Radiation and Its Effect on Superficial Ground Temperatures on Tibetan Plateau. J. Glaciol. Geocryol. 2011, 33, 1022–1032. [Google Scholar]
- Lhomme, J.P.; Vacher, J.J.; Rocheteau, A. Estimating downward long–wave radiation on the Andean Altiplano. Agric. For. Meteorol. 2007, 145, 139–148. [Google Scholar] [CrossRef]
- Stone, R.J. Improved statistical procedure for the evaluation of solar radiation estimation models. Sol. Energy 1993, 5, 289–291. [Google Scholar] [CrossRef]
- Jacovides, C.P.; Kontoyiannis, H. Statistical procedures for the evaluation of evapotranspiration computing models. Agric. Water Manag. 1995, 27, 365–371. [Google Scholar] [CrossRef]
- Itenfisu, D.; Elliott, R.L.; Allen, R.G.; Walter, I.A. Comparison of reference evapotranspiration calculation as part of the ASCE standardization effort. J. Irrig. Drain. Eng. 2003, 129, 440–448. [Google Scholar] [CrossRef]
- Duan, C.F.; Cao, W.; Huang, Y.; Wen, H.Y.; Liu, J.J. Effect of time resolution of meteorological variables on estimation of reference evapotranspiration. Trans. Chin. Soc. Agric. Eng. 2015, 31, 158–164. [Google Scholar]
- Yin, Y.H.; Wu, S.H.; Zheng, D.; Yang, Q.Y. Radiation calibration of FAO56 Penman–Monteith model to estimate reference crop evapotranspiration in China. Agric. Water Manag. 2008, 95, 77–84. [Google Scholar] [CrossRef]
- Bilbao, J.; De Miguel, A. Estimation of daylight downward longwave atmospheric irradiance under clear-sky and all-sky conditions. J. Appl. Meteorol. Clim. 2007, 46, 878–889. [Google Scholar] [CrossRef]
No. | Station | Latitude (°N) | Longitude (°E) | Elevation (m) | Observed Period | Standard Rnl (W/m2) |
---|---|---|---|---|---|---|
1 | Beijing | 39.80 | 116.47 | 31.3 | 1993–2012 | 76.0 |
2 | Chengdu | 30.67 | 104.02 | 506.1 | 1993–2003 | 40.4 |
3 | Ejin Banner | 41.95 | 101.07 | 940.5 | 1993–2012 | 121.5 |
4 | Golmud | 36.42 | 94.92 | 2807.6 | 1993–2012 | 106.4 |
5 | Guangzhou | 23.22 | 113.48 | 70.7 | 1993–2012 | 44.7 |
6 | Harbin | 45.75 | 126.77 | 142.3 | 1993–2012 | 73.9 |
7 | Kashgar | 39.47 | 75.98 | 1289.4 | 1993–2012 | 90.8 |
8 | Kunming | 25.00 | 102.65 | 1888.1 | 1993–2012 | 71.2 |
9 | Lanzhou | 36.05 | 103.88 | 1517.2 | 1993–2004 | 81.0 |
10 | Lhasa | 29.67 | 91.13 | 3648.9 | 1993–2012 | 116.1 |
11 | Mohe | 52.97 | 122.52 | 433.0 | 1993–2012 | 65.3 |
12 | Sanya | 18.22 | 109.58 | 419.4 | 1993–2012 | 64.6 |
13 | Shanghai | 31.40 | 121.45 | 5.5 | 1993–2012 | 55.0 |
14 | Shenyang | 41.73 | 123.52 | 49.0 | 1993–2012 | 74.0 |
15 | Urumuqi | 43.78 | 87.65 | 935.0 | 1993–2012 | 85.1 |
16 | Wenjiang | 30.75 | 103.87 | 547.7 | 2004–2012 | 40.3 |
17 | Wuhan | 30.60 | 114.05 | 23.6 | 1993–2012 | 48.6 |
18 | Yuzhong | 35.87 | 104.15 | 1874.4 | 2005–2012 | 86.9 |
19 | Zhengzhou | 34.72 | 113.65 | 110.4 | 1993–2012 | 64.2 |
Formulas | Equations | No. | |
---|---|---|---|
Brunt | (3) | ||
Penman | (4) | ||
Bepлянд | (5) | ||
FAO24 | (6) | ||
FAO56-PM | (7) | ||
Deng Genyun | (8) | ||
Tong Hongliang | Plain | (9) | |
Plateau | (10) | ||
(11) |
Formulas | R | MBE (W/m2) | MABE (W/m2) | MAPE (%) | RMSE (W/m2) |
---|---|---|---|---|---|
Brunt | 0.762 | –15.152 | 21.061 | 30.266 | 26.420 |
Penman | 0.809 | –6.280 | 15.662 | 22.068 | 19.972 |
Bepлянд | 0.795 | –29.302 | 29.707 | 39.294 | 34.967 |
FAO24 | 0.817 | –30.733 | 30.913 | 39.826 | 36.116 |
FAO56-PM | 0.809 | –32.771 | 32.904 | 42.078 | 38.426 |
Deng Genyun | 0.860 | –14.441 | 17.871 | 20.965 | 24.606 |
Tong Hongliang | 0.827 | –10.027 | 15.107 | 19.562 | 20.092 |
CERES | 0.814 | –11.941 | 16.454 | 21.819 | 21.612 |
Order | 1 | 2 | 3 | 4 | 5 | 6 | 7 | |
---|---|---|---|---|---|---|---|---|
Station | ||||||||
Beijing | Deng | Penman | Tong | Brunt | Bepлянд | FAO24 | FAO56 | |
Chengdu | Deng | Tong | Penman | Brunt | FAO24 | FAO56 | Bepлянд | |
Ejin Banner | Penman | Brunt | Tong | Deng | Bepлянд | FAO24 | FAO56 | |
Golmud | Tong | Penman | Brunt | Deng | Bepлянд | FAO24 | FAO56 | |
Guangzhou | Tong | Deng | Penman | FAO24 | FAO56 | Brunt | Bepлянд | |
Harbin | Deng | Penman | Tong | Brunt | Bepлянд | FAO24 | FAO56 | |
Kashgar | Tong | Deng | Penman | Brunt | Bepлянд | FAO24 | FAO56 | |
Kunming | Tong | Deng | Penman | Brunt | Bepлянд | FAO24 | FAO56 | |
Lanzhou | Tong | Penman | Deng | Brunt | Bepлянд | FAO24 | FAO56 | |
Lhasa | Penman | Tong | Brunt | Deng | Bepлянд | FAO24 | FAO56 | |
Mohe | Deng | Tong | Penman | Bepлянд | Brunt | FAO24 | FAO56 | |
Sanya | Deng | Tong | Penman | FAO24 | FAO56 | Bepлянд | Brunt | |
Shanghai | Deng | Tong | Penman | Brunt | FAO24 | FAO56 | Bepлянд | |
Shenyang | Deng | Penman | Tong | Brunt | Bepлянд | FAO24 | FAO56 | |
Urumuqi | Tong | Penman | Brunt | Deng | Bepлянд | FAO24 | FAO56 | |
Wenjiang | Deng | Tong | Penman | Brunt | FAO24 | Bepлянд | FAO56 | |
Wuhan | Tong | Deng | Penman | Brunt | FAO24 | FAO56 | Bepлянд | |
Yuzhong | Tong | Penman | Brunt | Deng | Bepлянд | FAO24 | FAO56 | |
Zhengzhou | Deng | Tong | Penman | Brunt | Bepлянд | FAO24 | FAO56 |
Formulas | Stations Used to Modeling | Equations | Area Recommended to Use |
---|---|---|---|
National formula | The whole of 19 stations listed in Table 1 | Entire China | |
Regional formulas | Beijing, Chengdu, Guangzhou, Harbin, Kunming, Mohe, Sanya, Shanghai, Shenyang, Wenjiang, Wuhan, Zhengzhou | Eastern area of China | |
Ejin Banner, Kashgar, Lanzhou, Urumuqi, Yuzhong | Northwestern area of China | ||
Golmud, Lhasa | Tibetan Plateau |
Errors | MBE (W/m2) | MABE (W/m2) | MAPE (%) | RMSE (W/m2) | |||||
---|---|---|---|---|---|---|---|---|---|
Station | National Formula | Regional Formula | National Formula | Regional Formula | National Formula | Regional Formula | National Formula | Regional Formula | |
Beijing | 6.062 | 1.667 | 10.999 | 9.451 | 16.468 | 13.755 | 13.351 | 11.810 | |
Chengdu | –1.433 | 1.334 | 6.062 | 5.836 | 16.010 | 16.199 | 7.966 | 7.624 | |
Ejin Banner | –12.760 | –13.870 | 18.317 | 17.545 | 13.930 | 13.189 | 24.460 | 24.263 | |
Golmud | –3.966 | 5.671 | 12.389 | 11.556 | 11.915 | 12.353 | 14.804 | 14.069 | |
Guangzhou | 5.987 | 5.674 | 8.893 | 7.633 | 20.530 | 18.814 | 11.586 | 9.817 | |
Harbin | –3.596 | –6.722 | 12.149 | 12.168 | 16.021 | 15.571 | 16.292 | 17.012 | |
Kashgar | 5.154 | 8.064 | 17.366 | 17.258 | 22.973 | 22.674 | 21.290 | 20.924 | |
Kunming | 1.398 | –2.003 | 9.133 | 8.477 | 13.311 | 12.088 | 11.855 | 11.515 | |
Lanzhou | 0.351 | 2.086 | 9.911 | 9.901 | 12.237 | 12.639 | 12.457 | 12.432 | |
Lhasa | –18.152 | –7.855 | 22.229 | 17.911 | 18.108 | 16.064 | 28.025 | 22.961 | |
Mohe | 3.857 | 0.545 | 13.355 | 12.485 | 23.368 | 21.043 | 15.959 | 15.323 | |
Sanya | 1.840 | –1.887 | 11.359 | 10.700 | 20.029 | 17.944 | 14.247 | 13.530 | |
Shanghai | 2.543 | 1.367 | 7.671 | 7.269 | 15.863 | 14.885 | 9.821 | 9.129 | |
Shenyang | –0.560 | –4.246 | 14.871 | 14.330 | 21.271 | 19.592 | 19.251 | 19.291 | |
Urumuqi | –3.449 | –1.969 | 14.216 | 12.875 | 17.866 | 16.649 | 19.326 | 17.657 | |
Wenjiang | –3.927 | –0.925 | 7.595 | 6.844 | 19.754 | 19.035 | 9.127 | 8.562 | |
Wuhan | 8.449 | 7.134 | 12.434 | 11.451 | 27.807 | 26.069 | 15.069 | 14.104 | |
Yuzhong | –8.907 | –7.817 | 16.649 | 16.280 | 17.119 | 17.388 | 22.734 | 20.804 | |
Zhengzhou | –0.046 | –1.610 | 9.437 | 9.092 | 15.097 | 14.193 | 11.984 | 11.786 | |
Average | –1.113 | –0.808 | 12.370 | 11.530 | 17.878 | 16.850 | 15.769 | 14.874 |
Formulas | R | MBE (W/m2) | MABE (W/m2) | MAPE (%) | RMSE (W/m2) |
---|---|---|---|---|---|
Regional | 0.870 | –0.590 | 11.536 | 16.601 | 15.432 |
Deng Genyun | 0.860 | –14.441 | 17.871 | 20.965 | 24.606 |
Tong Hongliang | 0.827 | –10.027 | 15.107 | 19.562 | 20.092 |
© 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Cao, W.; Duan, C.; Shen, S.; Yao, Y. Evaluation and Parameter Optimization of Monthly Net Long-Wave Radiation Climatology Methods in China. Atmosphere 2017, 8, 94. https://doi.org/10.3390/atmos8060094
Cao W, Duan C, Shen S, Yao Y. Evaluation and Parameter Optimization of Monthly Net Long-Wave Radiation Climatology Methods in China. Atmosphere. 2017; 8(6):94. https://doi.org/10.3390/atmos8060094
Chicago/Turabian StyleCao, Wen, Chunfeng Duan, Shuanghe Shen, and Yun Yao. 2017. "Evaluation and Parameter Optimization of Monthly Net Long-Wave Radiation Climatology Methods in China" Atmosphere 8, no. 6: 94. https://doi.org/10.3390/atmos8060094