Discussion on the Assessment Method of Wind Energy Resources by Using Regional Meteorological Data

The exploitation status of wind energy resources was analyzed, and the distribution of wind energy resources and regional meteorological stations were introduced, and then the assessment method of wind energy resources by using data from regional meteorological station was studied taking Huangjin Regional Meteorological Station in Xinning County in Hunan Province for example, besides, corresponding software was compiled. By means of SQL database and program, the method was used simply and easily and had positive meaning for the development of wind energy resources and excavation of wind farm in inland region.

Characteristics of the Regional Meteorological Drought Events in Southwest China During 1960–2010

An objective identifi cation technique for regional extreme events （OITREE） and the daily composite-drought index （CI） at 101 stations in Southwest China （including Sichuan, Yunnan, Guizhou, and Chongqing） are used to detect regional meteorological drought events between 1960 and 2010. Values of the parameters of the OITREE method are determined. A total of 87 drought events are identifi ed, including 9 extreme events. The 2009-2010 drought is the most serious in Southwest China during the past 50 years. The regional meteorological drought events during 1960-2010 generally last for 10-80 days, with the longest being 231 days. Droughts are more common from November to next April, and less common in the remaining months. Droughts occur more often and with greater intensity in Yunnan and southern Sichuan than in other parts of Southwest China. Strong （extreme and severe） regional meteorological drought events can be divided into fi ve types. The southern type has occurred most frequently, and Yunnan is the area most frequently stricken by extreme and severe drought events. The regional meteorological drought events in Southwest China have increased in both frequency and intensity over the study period, and the main reason appears to be a signifi cant decrease in precipitation over this region, but a simultaneous increase in temperature also contributes.

DETECTION OF FOREST FIRE IN DA HINGGAN LING REGION BY METEOROLOGICAL SATELLITE

From May 6 to June 2,1987,a huge forest fire broke out and raged for 28 days in Da Hinggan Ling region in far Northeast China,causing heavy loss of life and property,which claims the biggest forest fire disaster in Chinese history.The fire drew attention of the whole of China and was also concerned by many other countries.How were the meteorological satellites used in the detection of the forest fire?This paper elaborates the principles and methods of the fire detection using meteorological satellites,so that to sum up the experience and to increase the ability of forest fire detection.

Estimation model of winter wheat disease based on meteorological factors and spectral information

Wheat scab(WS,Fusarium head blight),one of the most severe diseases of winter wheat in Yangtze-Huaihe river region,whose monitoring and timely forecasting at large scale would help to optimize pesticide spraying and achieve the purpose of reducing yield loss.In the present study,remote sensing monitoring on WS was conducted in 4 counties in Yangtze-Huaihe river region.Sensitive factors of WS were selected to establish the remote sensing estimation model of winter wheat scab index(WSI)based on interactions between spectral information and meteorological factors.The results showed that:1)Correlations between the daily average temperature(DAT)and daily average relative humidity(DAH)at different time scales and WSI were significant.2)There were positive linear correlations between winter wheat biomass,leaf area index(LAI),leaf chlorophyll content(LCC)and WSI.3)NDVI(normalized difference vegetation index),RVI(ratio vegetation index)and DVI(difference vegetation index)which had a good correlation with LAI,biomass and LCC,respectively,and could be used to replace them in modeling.4)The estimated values of the model were consistent with the measured values(RMSE=5.3%,estimation accuracy=90.46%).Estimation results showed that the model could efficiently estimate WS in Yangtze-Huaihe river region.