利用2015年大连地区7个主要气象站的地面气温、降水、风向风速和相对湿度观测资料,针对东北区域中尺度数值模式(Weather Research and Forecast,WRF)产品中常规天气要素进行检验分析,了解掌握WRF模式对不同天气要素的预报能力,以期为天...利用2015年大连地区7个主要气象站的地面气温、降水、风向风速和相对湿度观测资料,针对东北区域中尺度数值模式(Weather Research and Forecast,WRF)产品中常规天气要素进行检验分析,了解掌握WRF模式对不同天气要素的预报能力,以期为天气预报业务中WRF模式产品的订正提供参考。结果表明:WRF模式产品的气温预报准确率整体上08时起报的比20时起报的稍好,最低气温预报效果比最高气温稍好,且WRF模式对升温和降温的趋势预报较好,具有一定参考性。WRF模式产品的降水预报准确率相对较高; WRF模式对风向的预报准确率可以达到50%左右,而风速的预报准确率可以达到60%—70%;大雾天气的预报,可以相应参考WRF模式的相对湿度。展开更多
The present paper investigates the relationship between the global radiative forcing (GRF) and global annual climatic variability. The relation between the GRF and global annual changes in the operational weather and ...The present paper investigates the relationship between the global radiative forcing (GRF) and global annual climatic variability. The relation between the GRF and global annual changes in the operational weather and climatic parameters is uncovered. There are several datasets which have been used to challenge this goal. The NCEP/NCAR Reanalysis dataset of several meteorological elements, such as air temperature, wind, surface pressure, outgoing long wave radiation, precipitation rate and geopotential height at level 500 hPa, etc. for the globe for the period (1948-2012), has been used. Furthermore, the GRF data for greenhouse gases through the period (1979-2010) has been used. Also, datasets of climatic indices NAO, SOI, El Nino 3.4 and SST during the period (1948-2012) have been used through this study. Time series analysis, anomaly and correlation coefficient technique methods have been used to analyze the datasets. The results reveal that there is an outstanding positive correlation coefficient (more than +0.80) between GRF and the global annual weather elements of surface air temperature, temperature and geopotential height at level 500 hPa, precipitation rate and sea surface temperature. CO2 has a significant correlation coefficient (+0.89) with the outcomes longwave radiation and sea surface temperature. There is a significant relationship between the global annual variability of weather and climatic elements and GHGs, global warming and climatic indices, NAO, SOI, El Nino 3.4 and SST.展开更多
文摘利用2015年大连地区7个主要气象站的地面气温、降水、风向风速和相对湿度观测资料,针对东北区域中尺度数值模式(Weather Research and Forecast,WRF)产品中常规天气要素进行检验分析,了解掌握WRF模式对不同天气要素的预报能力,以期为天气预报业务中WRF模式产品的订正提供参考。结果表明:WRF模式产品的气温预报准确率整体上08时起报的比20时起报的稍好,最低气温预报效果比最高气温稍好,且WRF模式对升温和降温的趋势预报较好,具有一定参考性。WRF模式产品的降水预报准确率相对较高; WRF模式对风向的预报准确率可以达到50%左右,而风速的预报准确率可以达到60%—70%;大雾天气的预报,可以相应参考WRF模式的相对湿度。
文摘The present paper investigates the relationship between the global radiative forcing (GRF) and global annual climatic variability. The relation between the GRF and global annual changes in the operational weather and climatic parameters is uncovered. There are several datasets which have been used to challenge this goal. The NCEP/NCAR Reanalysis dataset of several meteorological elements, such as air temperature, wind, surface pressure, outgoing long wave radiation, precipitation rate and geopotential height at level 500 hPa, etc. for the globe for the period (1948-2012), has been used. Furthermore, the GRF data for greenhouse gases through the period (1979-2010) has been used. Also, datasets of climatic indices NAO, SOI, El Nino 3.4 and SST during the period (1948-2012) have been used through this study. Time series analysis, anomaly and correlation coefficient technique methods have been used to analyze the datasets. The results reveal that there is an outstanding positive correlation coefficient (more than +0.80) between GRF and the global annual weather elements of surface air temperature, temperature and geopotential height at level 500 hPa, precipitation rate and sea surface temperature. CO2 has a significant correlation coefficient (+0.89) with the outcomes longwave radiation and sea surface temperature. There is a significant relationship between the global annual variability of weather and climatic elements and GHGs, global warming and climatic indices, NAO, SOI, El Nino 3.4 and SST.
