The first version of the Brazilian Oceano- graphic Modeling and Observation Network （REMO） ocean data assimilation system into the Hybrid Coordi- nate Ocean Model （HYCOM） （RODAS H） has recently been constructed ...The first version of the Brazilian Oceano- graphic Modeling and Observation Network （REMO） ocean data assimilation system into the Hybrid Coordi- nate Ocean Model （HYCOM） （RODAS H） has recently been constructed for research and operational purposes. The system is based on a multivariate Ensemble Optimal Interpolation （EnOI） scheme and considers the high fre- quency variability of the model error co-variance matrix. The EnOl can assimilate sea surface temperature （SST）, satellite along-track and gridded sea level anomalies （SLA）, and vertical profiles of temperature （T） and salinity （S） from Argo. The first observing system experiment was carried out over the Atlantic Ocean （78°S-50°N, 100°W-20°E） with HYCOM forced with atmospheric reanalysis from 1 January to 30 June 2010. Five integra- tions were performed, including the control run without assimilation. In the other four, different observations were assimilated： SST only （A SST）; Argo T-S profiles only （AArgo）; along-track SLA only （A_SLA）; and all data employed in the previous runs （A_All）. The A_SST, A_Argo, and A_SLA runs were very effective in improv- ing the representation of the assimilated variables, but they had relatively little impact on the variables that were not assimilated. In particular, only the assimilation of S was able to reduce the deviation of S with respect to ob- servations. Overall, the A_All run produced a good analy- sis by reducing the deviation of SST, T, and S with respect to the control run by 39%, 18%, and 30%, respectively, and by increasing the correlation of SLA by 81%.展开更多
In an effort to assess the impact of the individual component of meteorological observations （ground-based CPS precipitable water vapor, automatic and conventional meteorological observations） on the torrential rain...In an effort to assess the impact of the individual component of meteorological observations （ground-based CPS precipitable water vapor, automatic and conventional meteorological observations） on the torrential rain event in 4-5 July 2000 in Beijing （with the 24-h accumulated precipitation reaching 240 mm）, 24-h observation system experiments are conducted numerically by using the MM5/WRF 3DVAR system and the nonhydrostatic MM5 model. Results indicate that, because the non-conventional GPS observations are directly assimilated into the initial analyses by 3DVAR system, better initial fields and 24-h simulation for the severe precipitation event are achieved than those under the MM5/Litter_R objective analysis scheme. Further analysis also shows that the individual component of meteorological observation network plays their special positive role in the improvement of initial field analysis and forecasting skills. 3DVAR scheme with or without radiosonde and pilot observation has the most significant influence on numerical simulation, and automatic and conventional surface meteorological observations rank second. After acquiring the supplement information from the other meteorological observations, the ground-based GPS precipitable water vapor data can more obviously reflect initial field assimilation and precipitation forecast. By incorporating the groundbased CPS precipitable water vapor data into the 3DVAR analyses at the initial time, the threat scores （TS） with thresholds of 1, 5, 10, and 20 mm are increased by 1%-8% for 6- and 24-h accumulated precipitation observations, respectively. This work gives one helpful example that assesses the impact of individual component of the existing meteorological observation network on the high influence weather event using 3DVAR numerical system.展开更多
基金financially supported by the Brazilian State oil company Petróleo Brasileiro S. A. (Petrobras) and Agência Nacional de Petróleo (ANP), Gás Natural e Biocombustíveis, Brazil, via the Oceanographic Modeling and Observation Network (REMO)support of the Coordenao de Aperfeioamento de Pessoal de Nível Superior (CAPES), Ministry of Education of Brazil (Proc. BEX 3957/13-6)
文摘The first version of the Brazilian Oceano- graphic Modeling and Observation Network （REMO） ocean data assimilation system into the Hybrid Coordi- nate Ocean Model （HYCOM） （RODAS H） has recently been constructed for research and operational purposes. The system is based on a multivariate Ensemble Optimal Interpolation （EnOI） scheme and considers the high fre- quency variability of the model error co-variance matrix. The EnOl can assimilate sea surface temperature （SST）, satellite along-track and gridded sea level anomalies （SLA）, and vertical profiles of temperature （T） and salinity （S） from Argo. The first observing system experiment was carried out over the Atlantic Ocean （78°S-50°N, 100°W-20°E） with HYCOM forced with atmospheric reanalysis from 1 January to 30 June 2010. Five integra- tions were performed, including the control run without assimilation. In the other four, different observations were assimilated： SST only （A SST）; Argo T-S profiles only （AArgo）; along-track SLA only （A_SLA）; and all data employed in the previous runs （A_All）. The A_SST, A_Argo, and A_SLA runs were very effective in improv- ing the representation of the assimilated variables, but they had relatively little impact on the variables that were not assimilated. In particular, only the assimilation of S was able to reduce the deviation of S with respect to ob- servations. Overall, the A_All run produced a good analy- sis by reducing the deviation of SST, T, and S with respect to the control run by 39%, 18%, and 30%, respectively, and by increasing the correlation of SLA by 81%.
基金Supported by project of the Ministry of Science and Technology under Nos.2005DIB3J098,2003DFB00011 and 2002BA904B05,project of the Beijing New Star under No.H013610330119,and projects of Beijing Municipal Science Technology Commission under Nos.H010510120119 and H020620250330,and project of GPS application of Beijing Meteorological Bureau.
文摘In an effort to assess the impact of the individual component of meteorological observations （ground-based CPS precipitable water vapor, automatic and conventional meteorological observations） on the torrential rain event in 4-5 July 2000 in Beijing （with the 24-h accumulated precipitation reaching 240 mm）, 24-h observation system experiments are conducted numerically by using the MM5/WRF 3DVAR system and the nonhydrostatic MM5 model. Results indicate that, because the non-conventional GPS observations are directly assimilated into the initial analyses by 3DVAR system, better initial fields and 24-h simulation for the severe precipitation event are achieved than those under the MM5/Litter_R objective analysis scheme. Further analysis also shows that the individual component of meteorological observation network plays their special positive role in the improvement of initial field analysis and forecasting skills. 3DVAR scheme with or without radiosonde and pilot observation has the most significant influence on numerical simulation, and automatic and conventional surface meteorological observations rank second. After acquiring the supplement information from the other meteorological observations, the ground-based GPS precipitable water vapor data can more obviously reflect initial field assimilation and precipitation forecast. By incorporating the groundbased CPS precipitable water vapor data into the 3DVAR analyses at the initial time, the threat scores （TS） with thresholds of 1, 5, 10, and 20 mm are increased by 1%-8% for 6- and 24-h accumulated precipitation observations, respectively. This work gives one helpful example that assesses the impact of individual component of the existing meteorological observation network on the high influence weather event using 3DVAR numerical system.
