Daily Total Radiation Model Based on Air Pollution Index

Yu Li; Shen Shuanghe; Tao Sulin; Li Meng; Ding Conghui

doi:10.11898/1001-7313.20150304

Vol.26, NO.3, 2015

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Article Navigation > Journal of Applied Meteorological Science > 2015 > 26(3): 291-299

Yu Li, Shen Shuanghe, Tao Sulin, et al. Daily total radiation model based on air pollution index. J Appl Meteor Sci, 2015, 26(3): 291-299. DOI: 10.11898/1001-7313.20150304.

Citation:

Yu Li, Shen Shuanghe, Tao Sulin, et al. Daily total radiation model based on air pollution index. J Appl Meteor Sci, 2015, 26(3): 291-299. DOI: 10.11898/1001-7313.20150304.

Yu Li, Shen Shuanghe, Tao Sulin, et al. Daily total radiation model based on air pollution index. J Appl Meteor Sci, 2015, 26(3): 291-299. DOI: 10.11898/1001-7313.20150304.

Citation:

Yu Li, Shen Shuanghe, Tao Sulin, et al. Daily total radiation model based on air pollution index. J Appl Meteor Sci, 2015, 26(3): 291-299. DOI: 10.11898/1001-7313.20150304.

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Daily Total Radiation Model Based on Air Pollution Index

DOI: 10.11898/1001-7313.20150304

Yu Li^{1,2
,
,},
Shen Shuanghe²,
Tao Sulin^1,2,
Li Meng^1,2,
Ding Conghui^1,2

1.
Weather Disaster Collaborative Innovation Center, Nanjing University of Information Science & Technology, Nanjing 210044
2.
College of Applied Meteorology, Nanjing University of Information Science & Technology, Nanjing 210044

Received Date: 2014-12-01
Rev Recd Date: 2015-03-04
Publish Date: 2015-05-31

Abstract

Abstract

Solar radiation is the primary energy source of various physical processes in the natural environment, the basic force of driving formation and evolution of weather and climate. It's one of the most important natural factors in many scientific fields. However, compared with temperature and precipitation, solar radiation data are rather deficient in China, and thus it is necessary to seek a new way to calculate it by using the routine meteorological variables. With the rapid development of the national economy and the continuous expansion of cities, the air quality of some large and medium-sized cities has been gradually worsening. However, these effects are often neglected in radiation model, which may cause great errors in the solar radiation calculation. Therefore, a more precise solar radiation model which regards air pollution index as a dominant factor is built to improve model simulation accuracy. By analyzing the statistical analyses about observations of 23 nationwide sites from 2001 to 2012, the model is established for assessment of daily radiation with nonlinear regression method, which is called DSRM-Y. The model includes three independent variables: Daily temperature range, astronomical percentage of sunshine and air pollution index. Meanwhile, to check the simulation effect, results of DSRM-Y are compared with those of a previous model called DSRM-C. Results show a significant negative correlation between two essential factors of air pollution index and daily solar radiation. In addition, a good fitting effect is expressed in scattering diagram, mean bias error, root mean square error and error analysis of daily total radiation between calculated and measured values. The application result of DSRM-Y at Xining, Shanghai and Kunming indicates, as the air pollution index rises, the daily solar radiation weakens in all three sites. In terms of model comparison, the root mean square error of DSRM-Y is less than that of DSRM-C for all sites, indicating DSRM-Y performs better.
- daily solar radiation;
- air pollution index;
- diurnal temperature range;
- astronomical percentage of sunshine

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References(26)

Figures and Tables

Fig. 1 Spatial distribution of mean bias error (a) and root mean square error (b)(unit:MJ·m^-2·d^-1) of daily total radiation simulated by DSRM-Y from 2001 to 2010

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Fig. 2 Daily total radiation predicted by DSRM-Y from 2011 to 2012

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Fig. 3 Changes of estimated solar radiation with P at Xining, Shanghai and Kunming stations

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Fig. 4 Comparison between root mean square errors of daily solar radiation by DSRM-C and DSRM-Y from 2001 to 2010

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Table 1 Empirical coefficients in DSRM-Y and R² for each station

站点	N	a	b	c	d	R²
大连	2530	0.511	0.023	0.137	-0.316	0.930
福州	1815	0.424	0.049	0.168	-0.438	0.898
广州	1886	0.445	0.081	0.072	-1.059	0.838
贵阳	1387	0.560	0.074	0.165	-0.499	0.782
哈尔滨	2282	0.447	0.021	0.212	-0.241	0.952
海口	1771	0.507	0.011	0.175	-0.835	0.794
杭州	1832	0.446	0.049	0.160	-0.477	0.902
合肥	2235	0.466	0.019	0.207	-0.497	0.912
济南	2609	0.468	0.035	0.169	-0.773	0.909
昆明	2123	0.509	0.022	0.183	-0.211	0.775
拉萨	2295	0.481	0.061	0.166	-0.118	0.899
南昌	1973	0.480	0.050	0.104	-0.643	0.874
南京	2165	0.493	0.042	0.138	-0.585	0.904
南宁	1880	0.416	0.039	0.205	-0.610	0.853
汕头	2110	0.426	0.035	0.183	-0.166	0.865
上海	2163	0.436	0.032	0.211	-0.555	0.876
沈阳	2539	0.463	0.010	0.223	-0.074	0.929
天津	2820	0.495	0.010	0.209	-0.269	0.874
乌鲁木齐	2351	0.573	0.049	0.047	-0.191	0.937
武汉	2140	0.481	0.054	0.120	-0.904	0.897
西宁	2230	0.493	0.028	0.193	-0.155	0.952
长春	2423	0.528	0.031	0.140	-0.456	0.947
长沙	1727	0.429	0.052	0.102	-0.482	0.818

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Table 2 E_aa and E_ar of daily solar radiation simulated by DSRM-Y from 2001 to 2010

站点	E_aa/(MJ·m^-2·d^-1)	E_ar/%
大连	1.19	8.31
福州	1.05	5.89
广州	1.02	6.28
贵阳	1.49	7.80
哈尔滨	1.08	7.70
海口	1.36	7.28
杭州	1.17	6.75
合肥	1.15	7.19
济南	1.31	8.81
昆明	1.34	7.22
拉萨	1.17	5.63
南昌	1.36	8.16
南京	1.18	6.92
南宁	1.08	5.91
汕头	1.11	6.10
上海	1.34	8.13
沈阳	1.19	8.21
天津	1.64	11.20
乌鲁木齐	1.31	8.23
武汉	1.24	7.72
西宁	1.02	6.02
长春	1.08	7.82
长沙	1.50	9.32

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Table 3 E_aa and E_ar of daily solar radiation predicted by DSRM-Y from 2011 to 2012

站点	E_aa/(MJ·m^-2·d^-1)	E_ar/%
大连	1.32	8.98
福州	1.63	7.59
广州	1.40	7.77
贵阳	3.23	12.65
哈尔滨	3.19	35.01
海口	1.50	7.49
杭州	1.12	5.84
合肥	1.16	6.25
济南	2.14	10.64
昆明	1.31	6.78
拉萨	1.31	6.64
南昌	1.88	8.49
南京	1.06	5.78
南宁	1.20	6.56
汕头	1.28	6.56
上海	1.17	6.03
沈阳	1.43	8.64
天津	1.35	9.01
乌鲁木齐	2.28	15.89
武汉	1.16	6.24
西宁	1.29	7.24
长春	1.08	7.02
长沙	1.46	7.90

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