In this article, the extension to three dimensions (3D) of the blending technique that has been widely used in two dimensions (2D) to calibrate ocean chlorophyll is presented. The results thus obtained revealed a very...In this article, the extension to three dimensions (3D) of the blending technique that has been widely used in two dimensions (2D) to calibrate ocean chlorophyll is presented. The results thus obtained revealed a very high degree of efficiency when predicting observed values of ocean chlorophyll. The mean squared difference between the predicted and observed values of ocean chlorophyll when 3D technique was used fell far below the tolerance level which was set to the difference between satellite and observed in-situ values. The resulting blended field did not only provide better predictions of the in situ observations in areas where bottle samples cannot be obtained but also provided a smooth variation of the distribution of ocean chlorophyll throughout the year. An added advantage is its computational efficiency since data that would have been treated at least four times would be treated only once. With the advent of these results, it is believed that the modelling of the ocean life cycle will become more realistic.展开更多
Microwave radiances from passive polar-orbiting radiometers have been,until recently,assimilated in the Met Office global numerical weather prediction system after the scenes significantly affected by atmospheric scat...Microwave radiances from passive polar-orbiting radiometers have been,until recently,assimilated in the Met Office global numerical weather prediction system after the scenes significantly affected by atmospheric scattering are discarded.Recent system upgrades have seen the introduction of a scattering-permitting observation operator and the development of a variable observation error using both liquid and ice water paths as proxies of scattering-induced bias.Applied to the Fengyun 3 Microwave Temperature Sounder 2(MWTS-2)and the Microwave Humidity Sounder 2(MWHS-2),this methodology increases the data usage by up to 8%at 183 GHz.It also allows for the investigation into the assimilation of MWHS-2118 GHz channels,sensitive to temperature and lower tropospheric humidity,but whose large sensitivity to ice cloud have prevented their use thus far.While the impact on the forecast is mostly neutral with small but significant short-range improvements,0.3%in terms of root mean square error,for southern winds and low-level temperature,balanced by 0.2%degradations of short-range northern and tropical low-level temperature,benefits are observed in the background fit of independent instruments used in the system.The lower tropospheric temperature sounding Infrared Atmospheric Sounding Interferometer(IASI)channels see a reduction of the standard deviation in the background departure of up to 1.2%.The Advanced Microwave Sounding Unit A(AMSU-A)stratospheric sounding channels improve by up to 0.5%and the Microwave Humidity Sounder(MHS)humidity sounding channels improve by up to 0.4%.展开更多
为了验证风云三号D星MERSI传感器的气溶胶光学厚度(AOD)数据对地面PM_(2.5)的污染过程预报的效果,本文基于WRF-Chem(Weather Research and Forecasting model coupled with Chemistry)大气化学模式和三维变分同化方法,针对2020-02-10—2...为了验证风云三号D星MERSI传感器的气溶胶光学厚度(AOD)数据对地面PM_(2.5)的污染过程预报的效果,本文基于WRF-Chem(Weather Research and Forecasting model coupled with Chemistry)大气化学模式和三维变分同化方法,针对2020-02-10—2020-02-12中国北方地区的一次PM_(2.5)重污染过程,进行了同化和预报试验研究。同化数据来自常规地面站点的PM_(2.5)浓度数据和风云三号D星MERSI传感器的气溶胶光学厚度(AOD)数据。控制试验不同化任何资料,3组同化试验分别为仅同化地面PM_(2.5),仅同化卫星AOD,以及同时同化PM_(2.5)和卫星AOD两种资料。结果表明,3组同化试验都可以有效提高初始场准确率,以地面PM_(2.5)作为检验标准,仅同化PM_(2.5)、仅同化AOD、同时同化两种资料相对于控制试验,初始场的平均偏差分别降低54.9%、21.9%和49.0%,平均相关系数分别提升51.4%、16.0%和34.0%,平均均方根误差分别降低50.6%、17.2%和42.3%。以卫星AOD作为检验标准,3组同化试验相对于控制试验,初始场的平均偏差分别降低37.6%、78.4%和83%,平均均方根误差分别降低31.6%、62.2%和65.2%。同化后的初始场对预报有显著的改进,改进持续时间达24 h,以地面PM_(2.5)作为检验标准,同时同化两种资料的试验对24 h预报的平均偏差减少19.7%,相关系数提升8.8%,均方根误差减少17.2%;以卫星AOD作为检验标准,24 h预报的平均偏差减少40.1%,相关系数提升25.9%,均方根误差降低34.7%。试验结论为,相对于仅同化地面PM_(2.5)资料,同化风云卫星AOD资料可以提升后期预报效果。展开更多
Data acquisition and preprocessing is a core course on digital intelligence at Wuhan University that is designed to cultivate students’understanding of data sources and improve preprocessing methods.The course aims a...Data acquisition and preprocessing is a core course on digital intelligence at Wuhan University that is designed to cultivate students’understanding of data sources and improve preprocessing methods.The course aims at fostering digital thinking and literacy and enhancing intelligent computing skills.This study examined digital intelligence education and reform practices integrated into the data acquisition and preprocessing course,which covered web data,social sensing data,remote sensing data,sensor network data,unmanned aerial vehicle data,and 3D data.Moreover,the study explored the development and implementation of the course’s teaching platform,which was based on the open geospatial engine.展开更多
文摘In this article, the extension to three dimensions (3D) of the blending technique that has been widely used in two dimensions (2D) to calibrate ocean chlorophyll is presented. The results thus obtained revealed a very high degree of efficiency when predicting observed values of ocean chlorophyll. The mean squared difference between the predicted and observed values of ocean chlorophyll when 3D technique was used fell far below the tolerance level which was set to the difference between satellite and observed in-situ values. The resulting blended field did not only provide better predictions of the in situ observations in areas where bottle samples cannot be obtained but also provided a smooth variation of the distribution of ocean chlorophyll throughout the year. An added advantage is its computational efficiency since data that would have been treated at least four times would be treated only once. With the advent of these results, it is believed that the modelling of the ocean life cycle will become more realistic.
基金This work was supported by the UK-China Research&Innovation Partnership Fund through the Met Office Climate Science for Service Partnership(CSSP)China as part of the Newton Fund.
文摘Microwave radiances from passive polar-orbiting radiometers have been,until recently,assimilated in the Met Office global numerical weather prediction system after the scenes significantly affected by atmospheric scattering are discarded.Recent system upgrades have seen the introduction of a scattering-permitting observation operator and the development of a variable observation error using both liquid and ice water paths as proxies of scattering-induced bias.Applied to the Fengyun 3 Microwave Temperature Sounder 2(MWTS-2)and the Microwave Humidity Sounder 2(MWHS-2),this methodology increases the data usage by up to 8%at 183 GHz.It also allows for the investigation into the assimilation of MWHS-2118 GHz channels,sensitive to temperature and lower tropospheric humidity,but whose large sensitivity to ice cloud have prevented their use thus far.While the impact on the forecast is mostly neutral with small but significant short-range improvements,0.3%in terms of root mean square error,for southern winds and low-level temperature,balanced by 0.2%degradations of short-range northern and tropical low-level temperature,benefits are observed in the background fit of independent instruments used in the system.The lower tropospheric temperature sounding Infrared Atmospheric Sounding Interferometer(IASI)channels see a reduction of the standard deviation in the background departure of up to 1.2%.The Advanced Microwave Sounding Unit A(AMSU-A)stratospheric sounding channels improve by up to 0.5%and the Microwave Humidity Sounder(MHS)humidity sounding channels improve by up to 0.4%.
文摘为了验证风云三号D星MERSI传感器的气溶胶光学厚度(AOD)数据对地面PM_(2.5)的污染过程预报的效果,本文基于WRF-Chem(Weather Research and Forecasting model coupled with Chemistry)大气化学模式和三维变分同化方法,针对2020-02-10—2020-02-12中国北方地区的一次PM_(2.5)重污染过程,进行了同化和预报试验研究。同化数据来自常规地面站点的PM_(2.5)浓度数据和风云三号D星MERSI传感器的气溶胶光学厚度(AOD)数据。控制试验不同化任何资料,3组同化试验分别为仅同化地面PM_(2.5),仅同化卫星AOD,以及同时同化PM_(2.5)和卫星AOD两种资料。结果表明,3组同化试验都可以有效提高初始场准确率,以地面PM_(2.5)作为检验标准,仅同化PM_(2.5)、仅同化AOD、同时同化两种资料相对于控制试验,初始场的平均偏差分别降低54.9%、21.9%和49.0%,平均相关系数分别提升51.4%、16.0%和34.0%,平均均方根误差分别降低50.6%、17.2%和42.3%。以卫星AOD作为检验标准,3组同化试验相对于控制试验,初始场的平均偏差分别降低37.6%、78.4%和83%,平均均方根误差分别降低31.6%、62.2%和65.2%。同化后的初始场对预报有显著的改进,改进持续时间达24 h,以地面PM_(2.5)作为检验标准,同时同化两种资料的试验对24 h预报的平均偏差减少19.7%,相关系数提升8.8%,均方根误差减少17.2%;以卫星AOD作为检验标准,24 h预报的平均偏差减少40.1%,相关系数提升25.9%,均方根误差降低34.7%。试验结论为,相对于仅同化地面PM_(2.5)资料,同化风云卫星AOD资料可以提升后期预报效果。
文摘Data acquisition and preprocessing is a core course on digital intelligence at Wuhan University that is designed to cultivate students’understanding of data sources and improve preprocessing methods.The course aims at fostering digital thinking and literacy and enhancing intelligent computing skills.This study examined digital intelligence education and reform practices integrated into the data acquisition and preprocessing course,which covered web data,social sensing data,remote sensing data,sensor network data,unmanned aerial vehicle data,and 3D data.Moreover,the study explored the development and implementation of the course’s teaching platform,which was based on the open geospatial engine.
