The soil water index （SWI） from satellite remote sensing and the observational soil moisture from agricultural meteorological stations in eastern China are used to retrieve soil moisture. The analysis of correlation...The soil water index （SWI） from satellite remote sensing and the observational soil moisture from agricultural meteorological stations in eastern China are used to retrieve soil moisture. The analysis of correlation coefficient （CORR）, root-mean-square-error （RMSE） and bias （BIAS） shows that the retrieved soil moisture is convincible and close to the observation. The method can overcome the difficulties in soil moisture observation on a large scale and the retrieved soil moisture may reflect the distribution of the real soil moisture objectively. The retrieved soil moisture is used as an initial scheme to replace initial conditions of soil moisture （NCEP） in the model MM5V3 to simulate the heavy rainfall in 1998. Three heavy rainfall processes during 13-14 June, 18-22 June, and 21-26 July 1998 in the Yangtze River valley are analyzed. The first two processes show that the intensity and location of simulated precipitation from SWI are better than those from NCEP and closer to the observed values. The simulated heavy rainfall for 21-26 July shows that the update of soil moisture initial conditions can improve the model＇s performance. The relationship between soil moisture and rainfall may explain that the stronger rainfall intensity for SWI in the Yangtze River valley is the result of the greater simulated soil moisture from SWI prior to the heavy rainfall date than that from NCEP, and leads to the decline of temperature in the corresponding area in the heavy rainfall days. Detailed analysis of the heavy rainfall on 13-14 June shows that both land-atmosphere interactions and atmospheric circulation were responsible for the heavy ralnfall, and it shows how the SWI simulation improves the simulation. The development of mesoscale systems plays an important role in the simulation regarding the change of initial soil moisture for SWI.展开更多
The leaf area index(LAI) is a critical biophysical variable that describes canopy geometric structures and growth conditions.It is also an important input parameter for climate,energy and carbon cycle models.The scali...The leaf area index(LAI) is a critical biophysical variable that describes canopy geometric structures and growth conditions.It is also an important input parameter for climate,energy and carbon cycle models.The scaling effect of the LAI has always been of concern.Considering the effects of the clumping indices on the BRDF models of discrete canopies,an effective LAI is defined.The effective LAI has the same function of describing the leaf density as does the traditional LAI.Therefore,our study was based on the effective LAI.The spatial scaling effect of discrete canopies significantly differed from that of continuous canopies.Based on the directional second-derivative method of effective LAI retrieval,the mechanism responsible for the spatial scaling effect of the discrete-canopy LAI is discussed and a scaling transformation formula for the effective LAI is suggested in this paper.Theoretical analysis shows that the mean values of effective LAIs retrieved from high-resolution pixels were always equal to or larger than the effective LAIs retrieved from corresponding coarse-resolution pixels.Both the conclusions and the scaling transformation formula were validated with airborne hyperspectral remote sensing imagery obtained in Huailai County,Zhangjiakou,Hebei Province,China.The scaling transformation formula agreed well with the effective LAI retrieved from hyperspectral remote sensing imagery.展开更多
The sea surface salinity(SSS) is a key parameter in monitoring ocean states. Observing SSS can promote the understanding of global water cycle. This paper provides a new approach for retrieving sea surface salinity fr...The sea surface salinity(SSS) is a key parameter in monitoring ocean states. Observing SSS can promote the understanding of global water cycle. This paper provides a new approach for retrieving sea surface salinity from Soil Moisture and Ocean Salinity(SMOS) satellite data. Based on the principal component regression(PCR) model, SSS can also be retrieved from the brightness temperature data of SMOS L2 measurements and Auxiliary data. 26 pair matchup data is used in model validation for the South China Sea(in the area of 4?–25?N, 105?–125?E). The RMSE value of PCR model retrieved SSS reaches 0.37 psu(practical salinity units) and the RMSE of SMOS SSS1 is 1.65 psu when compared with in-situ SSS. The corresponding Argo daily salinity data during April to June 2013 is also used in our validation with RMSE value 0.46 psu compared to 1.82 psu for daily averaged SMOS L2 products. This indicates that the PCR model is valid and may provide us with a good approach for retrieving SSS from SMOS satellite data.展开更多
On the basis of the joint estimated 1-h precipitation from Changde, Jingzhou, and Yichang Doppler radars as well as Wuhan digital radar, and the retrieved wind fields from Yichang and Jingzhou Doppler radars, a series...On the basis of the joint estimated 1-h precipitation from Changde, Jingzhou, and Yichang Doppler radars as well as Wuhan digital radar, and the retrieved wind fields from Yichang and Jingzhou Doppler radars, a series of numerical experiments with an advanced regional η-coordinate model （AREM） under different model initial schemes, i.e., Grapes-3DVAR, Barnes objective analysis, and Barnes-3DVAR, are carried out for a torrential rain process occurring along the Yangtze River in the 24-h period from 2000 BT 22 July 2002 to investigate the effects of the Doppler-radar estimated rainfall and retrieved winds on the rainfall forecast. The main results are as follows： （1） The simulations are obviously different under three initial schemes with the same data source （the radiosounding and T213L31 analysis）. On the whole, Barnes-3DVAR, which combines the advantages of the Barnes objective analysis and the Grapes-3DVAR method, gives the best simulations： well-simulated rain band and clear mesoscale structures, as well as their location and intensity close to observations. （2） Both Barnes-3DVAR and Grapes-3DVAR schemes are able to assimilate the Doppler-radar estimated rainfall and retrieved winds, but differences in simulation results are very large, with Barnes-3DVAR＇s simulation much better than Grapes-3DVAR＇s. （3） Under Grapes- 3DVAR scheme, the simulation of 24-h rainfall is improved obviously when assimilating the Doppler-radar estimated precipitation into the model in compared with the control experiment; but it becomes a little worse when assimilating the Doppler-radar retrieved winds into the model, and it becomes worse obviously when assimilating the Doppler-radar estimated precipitation as well as retrieved winds into the model. However, the simulation is different under Barnes-3DVAR scheme. The simulation is improved to a certain degree no matter assimilating the estimated precipitation or retrieved winds, or both of them. The result is the best when assimilating both of them into the展开更多
Satellite data obtained over synoptic data-sparse regions such as an ocean contribute toward improving the quality of the initial state of limited-area models. Background error covariances are crucial to the proper di...Satellite data obtained over synoptic data-sparse regions such as an ocean contribute toward improving the quality of the initial state of limited-area models. Background error covariances are crucial to the proper distribution of satellite-observed information in variational data assimilation. In the NMC （National Meteorological Center） method, background error covariances are underestimated over data-sparse regions such as an ocean because of small differences between different forecast times. Thus, it is necessary to reconstruct and tune the background error covariances so as to maximize the usefulness of the satellite data for the initial state of limited-area models, especially over an ocean where there is a lack of conventional data. In this study, we attempted to estimate background error covariances so as to provide adequate error statistics for data-sparse regions by using ensemble forecasts of optimal perturbations using bred vectors. The background error covariances estimated by the ensemble method reduced the overestimation of error amplitude obtained by the NMC method. By employing an appropriate horizontal length scale to exclude spurious correlations, the ensemble method produced better results than the NMC method in the assimilation of retrieved satellite data. Because the ensemble method distributes observed information over a limited local area, it would be more useful in the analysis of high-resolution satellite data. Accordingly, the performance of forecast models can be improved over the area where the satellite data are assimilated.展开更多
Objective:To investigate cumulative live birth rate (cLBR) per oocyte retrieval in infertile patients aged 40 years and over undergoing their first in vitro fertilization/intracytoplasmic sperm injection cycles and to...Objective:To investigate cumulative live birth rate (cLBR) per oocyte retrieval in infertile patients aged 40 years and over undergoing their first in vitro fertilization/intracytoplasmic sperm injection cycles and to identify the possible predictors.Methods:A total of 1,613 patients at a university hospital in China from January 2013 to May 2017 were enrolled in this retrospective study.All data for fresh and subsequent frozen-thawed cycles were analyzed.Multivariate logistic regression analysis with stepwise selection of possible predictors for cLBR was performed,and Loess curve was constructed to determine the association between cLBR and the number of oocytes retrieved.Results:cLBR significantly increased with the number of oocytes retrieved and reached up to 75% when > 20 oocytes were retrieved (P<0.001).Variables of antral follicle count (AFC) and the number of oocytes retrieved were selected using multiple logistic regression analysis with stepwise selection to predict the significance of cLBR.cLBR demonstrated an obvious upward trend as the number of oocytes retrieval increased in the Loess curve.Conclusions:For patients aged 40 years and over,AFC and the number of oocytes retrieved were two key predictors for cLBR and maximization of ovarian reserve exploitation was pivotal to increase the chance of live birth.展开更多
BACKGROUND The prognostic value of quantitative assessments of the number of retrieved lymph nodes(RLNs)in gastric cancer(GC)patients needs further study.AIM To discuss how to obtain a more accurate count of metastati...BACKGROUND The prognostic value of quantitative assessments of the number of retrieved lymph nodes(RLNs)in gastric cancer(GC)patients needs further study.AIM To discuss how to obtain a more accurate count of metastatic lymph nodes(MLNs)based on RLNs in different pT stages and then to evaluate patient prognosis.METHODS This study retrospectively analyzed patients who underwent GC radical surgery and D2/D2+LN dissection at the Cancer Hospital of Harbin Medical University from January 2011 to May 2017.Locally weighted smoothing was used to analyze the relationship between RLNs and the number of MLNs.Restricted cubic splines were used to analyze the relationship between RLNs and hazard ratios(HRs),and X-tile was used to determine the optimal cutoff value for RLNs.Patient survival was analyzed with the Kaplan-Meier method and log-rank test.Finally,HRs and 95%confidence intervals were calculated using Cox proportional hazards models to analyze independent risk factors associated with patient outcomes.RESULTS A total of 4968 patients were included in the training cohort,and 11154 patients were included in the validation cohort.The smooth curve showed that the number of MLNs increased with an increasing number of RLNs,and a nonlinear relationship between RLNs and HRs was observed.X-tile analysis showed that the optimal number of RLNs for pT1-pT4 stage GC patients was 26,31,39,and 45,respectively.A greater number of RLNs can reduce the risk of death in patients with pT1,pT2,and pT4 stage cancers but may not reduce the risk of death in patients with pT3 stage cancer.Multivariate analysis showed that RLNs were an independent risk factor associated with the prognosis of patients with pT1-pT4 stage cancer(P=0.044,P=0.037,P=0.003,P<0.001).CONCLUSION A greater number of RLNs may not benefit the survival of patients with pT3 stage disease but can benefit the survival of patients with pT1,pT2,and pT4 stage disease.For the pT1,pT2,and pT4 stages,it is recommended to retrieve 26,31 and 45 LNs,respectively.展开更多
基金This study was supported by the 973 Project(Grant No.2001CB309404)the National Natural Science Foundation of China(Grant No.40333031).
文摘The soil water index （SWI） from satellite remote sensing and the observational soil moisture from agricultural meteorological stations in eastern China are used to retrieve soil moisture. The analysis of correlation coefficient （CORR）, root-mean-square-error （RMSE） and bias （BIAS） shows that the retrieved soil moisture is convincible and close to the observation. The method can overcome the difficulties in soil moisture observation on a large scale and the retrieved soil moisture may reflect the distribution of the real soil moisture objectively. The retrieved soil moisture is used as an initial scheme to replace initial conditions of soil moisture （NCEP） in the model MM5V3 to simulate the heavy rainfall in 1998. Three heavy rainfall processes during 13-14 June, 18-22 June, and 21-26 July 1998 in the Yangtze River valley are analyzed. The first two processes show that the intensity and location of simulated precipitation from SWI are better than those from NCEP and closer to the observed values. The simulated heavy rainfall for 21-26 July shows that the update of soil moisture initial conditions can improve the model＇s performance. The relationship between soil moisture and rainfall may explain that the stronger rainfall intensity for SWI in the Yangtze River valley is the result of the greater simulated soil moisture from SWI prior to the heavy rainfall date than that from NCEP, and leads to the decline of temperature in the corresponding area in the heavy rainfall days. Detailed analysis of the heavy rainfall on 13-14 June shows that both land-atmosphere interactions and atmospheric circulation were responsible for the heavy ralnfall, and it shows how the SWI simulation improves the simulation. The development of mesoscale systems plays an important role in the simulation regarding the change of initial soil moisture for SWI.
基金supported by the National Natural Science Foundation of China(Grant Nos.91025006,40871186,40730525)National Basic Research Program of China(Grant No.2007CB714402)National High Technology Research and Development Program of China(Grant Nos.2009AA12Z143,2009AA122103)
文摘The leaf area index(LAI) is a critical biophysical variable that describes canopy geometric structures and growth conditions.It is also an important input parameter for climate,energy and carbon cycle models.The scaling effect of the LAI has always been of concern.Considering the effects of the clumping indices on the BRDF models of discrete canopies,an effective LAI is defined.The effective LAI has the same function of describing the leaf density as does the traditional LAI.Therefore,our study was based on the effective LAI.The spatial scaling effect of discrete canopies significantly differed from that of continuous canopies.Based on the directional second-derivative method of effective LAI retrieval,the mechanism responsible for the spatial scaling effect of the discrete-canopy LAI is discussed and a scaling transformation formula for the effective LAI is suggested in this paper.Theoretical analysis shows that the mean values of effective LAIs retrieved from high-resolution pixels were always equal to or larger than the effective LAIs retrieved from corresponding coarse-resolution pixels.Both the conclusions and the scaling transformation formula were validated with airborne hyperspectral remote sensing imagery obtained in Huailai County,Zhangjiakou,Hebei Province,China.The scaling transformation formula agreed well with the effective LAI retrieved from hyperspectral remote sensing imagery.
基金supported by the National Natural Science Foundation of China under project 41275013the National High-Tech Research and development program of China under project 2013AA09A506-4the National Basic Research Program under project 2009CB723903
文摘The sea surface salinity(SSS) is a key parameter in monitoring ocean states. Observing SSS can promote the understanding of global water cycle. This paper provides a new approach for retrieving sea surface salinity from Soil Moisture and Ocean Salinity(SMOS) satellite data. Based on the principal component regression(PCR) model, SSS can also be retrieved from the brightness temperature data of SMOS L2 measurements and Auxiliary data. 26 pair matchup data is used in model validation for the South China Sea(in the area of 4?–25?N, 105?–125?E). The RMSE value of PCR model retrieved SSS reaches 0.37 psu(practical salinity units) and the RMSE of SMOS SSS1 is 1.65 psu when compared with in-situ SSS. The corresponding Argo daily salinity data during April to June 2013 is also used in our validation with RMSE value 0.46 psu compared to 1.82 psu for daily averaged SMOS L2 products. This indicates that the PCR model is valid and may provide us with a good approach for retrieving SSS from SMOS satellite data.
基金Supported by the Natural Science Foundation of Hubei under Grant No. 2003ABA009the National "Ten-Five" Key Science and Technology Project under Grant No. 2001BA607Bthe "National Key Developing Program for Basic Science" Project under Grant No. 2004CB418307.
文摘On the basis of the joint estimated 1-h precipitation from Changde, Jingzhou, and Yichang Doppler radars as well as Wuhan digital radar, and the retrieved wind fields from Yichang and Jingzhou Doppler radars, a series of numerical experiments with an advanced regional η-coordinate model （AREM） under different model initial schemes, i.e., Grapes-3DVAR, Barnes objective analysis, and Barnes-3DVAR, are carried out for a torrential rain process occurring along the Yangtze River in the 24-h period from 2000 BT 22 July 2002 to investigate the effects of the Doppler-radar estimated rainfall and retrieved winds on the rainfall forecast. The main results are as follows： （1） The simulations are obviously different under three initial schemes with the same data source （the radiosounding and T213L31 analysis）. On the whole, Barnes-3DVAR, which combines the advantages of the Barnes objective analysis and the Grapes-3DVAR method, gives the best simulations： well-simulated rain band and clear mesoscale structures, as well as their location and intensity close to observations. （2） Both Barnes-3DVAR and Grapes-3DVAR schemes are able to assimilate the Doppler-radar estimated rainfall and retrieved winds, but differences in simulation results are very large, with Barnes-3DVAR＇s simulation much better than Grapes-3DVAR＇s. （3） Under Grapes- 3DVAR scheme, the simulation of 24-h rainfall is improved obviously when assimilating the Doppler-radar estimated precipitation into the model in compared with the control experiment; but it becomes a little worse when assimilating the Doppler-radar retrieved winds into the model, and it becomes worse obviously when assimilating the Doppler-radar estimated precipitation as well as retrieved winds into the model. However, the simulation is different under Barnes-3DVAR scheme. The simulation is improved to a certain degree no matter assimilating the estimated precipitation or retrieved winds, or both of them. The result is the best when assimilating both of them into the
基金funded by the Korea Meteorological Administration Research and Development Program under Grant RACS 2010-2016supported by the Brain Korea 21 project of the Ministry of Education and Human Resources Development of the Korean government
文摘Satellite data obtained over synoptic data-sparse regions such as an ocean contribute toward improving the quality of the initial state of limited-area models. Background error covariances are crucial to the proper distribution of satellite-observed information in variational data assimilation. In the NMC （National Meteorological Center） method, background error covariances are underestimated over data-sparse regions such as an ocean because of small differences between different forecast times. Thus, it is necessary to reconstruct and tune the background error covariances so as to maximize the usefulness of the satellite data for the initial state of limited-area models, especially over an ocean where there is a lack of conventional data. In this study, we attempted to estimate background error covariances so as to provide adequate error statistics for data-sparse regions by using ensemble forecasts of optimal perturbations using bred vectors. The background error covariances estimated by the ensemble method reduced the overestimation of error amplitude obtained by the NMC method. By employing an appropriate horizontal length scale to exclude spurious correlations, the ensemble method produced better results than the NMC method in the assimilation of retrieved satellite data. Because the ensemble method distributes observed information over a limited local area, it would be more useful in the analysis of high-resolution satellite data. Accordingly, the performance of forecast models can be improved over the area where the satellite data are assimilated.
基金This study was supported by the National Natural Science Foundation of China (81871214,81801449)the National Key R&D Program of China (2017YFC1001603)the Medical Scientific Technology Research Foundation of Guangdong Province of China (A20200226)。
文摘Objective:To investigate cumulative live birth rate (cLBR) per oocyte retrieval in infertile patients aged 40 years and over undergoing their first in vitro fertilization/intracytoplasmic sperm injection cycles and to identify the possible predictors.Methods:A total of 1,613 patients at a university hospital in China from January 2013 to May 2017 were enrolled in this retrospective study.All data for fresh and subsequent frozen-thawed cycles were analyzed.Multivariate logistic regression analysis with stepwise selection of possible predictors for cLBR was performed,and Loess curve was constructed to determine the association between cLBR and the number of oocytes retrieved.Results:cLBR significantly increased with the number of oocytes retrieved and reached up to 75% when > 20 oocytes were retrieved (P<0.001).Variables of antral follicle count (AFC) and the number of oocytes retrieved were selected using multiple logistic regression analysis with stepwise selection to predict the significance of cLBR.cLBR demonstrated an obvious upward trend as the number of oocytes retrieval increased in the Loess curve.Conclusions:For patients aged 40 years and over,AFC and the number of oocytes retrieved were two key predictors for cLBR and maximization of ovarian reserve exploitation was pivotal to increase the chance of live birth.
基金Supported by the Nn 10 Program of Harbin Medical University Cancer Hospital,No.Nn 10 PY 2017-03.
文摘BACKGROUND The prognostic value of quantitative assessments of the number of retrieved lymph nodes(RLNs)in gastric cancer(GC)patients needs further study.AIM To discuss how to obtain a more accurate count of metastatic lymph nodes(MLNs)based on RLNs in different pT stages and then to evaluate patient prognosis.METHODS This study retrospectively analyzed patients who underwent GC radical surgery and D2/D2+LN dissection at the Cancer Hospital of Harbin Medical University from January 2011 to May 2017.Locally weighted smoothing was used to analyze the relationship between RLNs and the number of MLNs.Restricted cubic splines were used to analyze the relationship between RLNs and hazard ratios(HRs),and X-tile was used to determine the optimal cutoff value for RLNs.Patient survival was analyzed with the Kaplan-Meier method and log-rank test.Finally,HRs and 95%confidence intervals were calculated using Cox proportional hazards models to analyze independent risk factors associated with patient outcomes.RESULTS A total of 4968 patients were included in the training cohort,and 11154 patients were included in the validation cohort.The smooth curve showed that the number of MLNs increased with an increasing number of RLNs,and a nonlinear relationship between RLNs and HRs was observed.X-tile analysis showed that the optimal number of RLNs for pT1-pT4 stage GC patients was 26,31,39,and 45,respectively.A greater number of RLNs can reduce the risk of death in patients with pT1,pT2,and pT4 stage cancers but may not reduce the risk of death in patients with pT3 stage cancer.Multivariate analysis showed that RLNs were an independent risk factor associated with the prognosis of patients with pT1-pT4 stage cancer(P=0.044,P=0.037,P=0.003,P<0.001).CONCLUSION A greater number of RLNs may not benefit the survival of patients with pT3 stage disease but can benefit the survival of patients with pT1,pT2,and pT4 stage disease.For the pT1,pT2,and pT4 stages,it is recommended to retrieve 26,31 and 45 LNs,respectively.
