Based on the reforecasts from ve models of the Subseasonal to Seasonal(S2S)Prediction project,the S2S prediction skill of surface soil moisture(SM)over East Asia during May September is evaluated against ERA-Interim.R...Based on the reforecasts from ve models of the Subseasonal to Seasonal(S2S)Prediction project,the S2S prediction skill of surface soil moisture(SM)over East Asia during May September is evaluated against ERA-Interim.Results show that good prediction skill of SM is generally 510 forecast days prior over southern and northeastern China in the majority of models.Over the Tibetan Plateau and northwestern China,only the ECMWF model has good prediction skill 20 days in advance.Generally,better prediction skill tends to appear over wet regions rather than dry regions.In terms of the seasonal variation of SM prediction skill,some diffierences are noticed among the models,but most of them show good prediction skill during September.Furthermore,the significant positive correlation between the prediction skill of SM and ENSO index indicates modulation by ENSO of the S2S prediction of SM.When there is an El Nino(a La Nina)event,the SM prediction skill over eastern China tends to be high(low).Through evaluation of the S2S prediction skill of SM in these models,it is found that the prediction skill of SM is lower than that of most atmospheric variables in S2S forecasts.Therefore,more attention needs to be given to the S2S forecasting of land processes.展开更多
An effective improvement on the empirical orthogonal function(EOF)–based bias correctionmethod for seasonal forecasts is proposed in this paper,by introducing a stepwise regression method into the process of EOF time...An effective improvement on the empirical orthogonal function(EOF)–based bias correctionmethod for seasonal forecasts is proposed in this paper,by introducing a stepwise regression method into the process of EOF time series correction.Using 30-year(1981–2010)hindcast results from IAP AGCM4.1(the latest version of this model),the improved method is validated for the prediction of summer(June–July–August)rainfall anomalies in Southeast China.The results in terms of the pattern correction coefficient(PCC)of rainfall anomalies shows that the 30-year-averaged prediction skill improves from 0.01 to 0.06 with the original correction method,and to 0.29 using the improved method.The applicability in real-time prediction is also investigated,using 2016 summer rainfall prediction as a test case.With a PCC of 0.59,the authors find that the new correction method significantly improves the prediction skill;the PCC using the direct prediction of the model is?0.04,and using the old bias correction method it is 0.37.展开更多
Rwanda is a landlocked country in central-eastern Africa.As a country highly dependent on rain-fed agriculture,Rwanda is vulnerable to rainfall variability.Observational data show that there are two rainy seasons in R...Rwanda is a landlocked country in central-eastern Africa.As a country highly dependent on rain-fed agriculture,Rwanda is vulnerable to rainfall variability.Observational data show that there are two rainy seasons in Rwanda,i.e.,the long rainy season and the short rainy season.This study mainly focuses on the dominant intraseasonal rainfall mode during the long rainy season(February-May),and evaluates the forecast skill for the intraseasonal variability(ISV)over Rwanda and its surrounding regions in a state-of-the-art dynamic model.During the long rainy season,observational results reveal that the dominant intraseasonal rainfall mode in Rwanda exhibits a significant variability on the 10-25-day time scale.One-point-correlation analysis further unveils that the 10-25-day intraseasonal rainfall variability in Rwanda co-varies with that in its adjacent areas,indicating that the overall 10-25-day rainfall variability in Rwanda and its adjacent regions(8°S-3°N,29°-37°E)should be considered collectively when studying the dominant intraseasonal rainfall variability in Rwanda.Composite results show that the development of the 10-25-day rainfall variability is associated with the anomalous westerly wind in Rwanda and its surrounding regions,which may trace back to a pair of westward-propagating equatorial Rossby waves.Based on the observational findings,an ISO_rainfall_index and an ISO_wind_index are proposed for quantitatively evaluating the forecast skill.The ECMWF model has a comparable skill in predicting the wind index and the rainfall index,with both indices showing a skill of 18 days.展开更多
Dickensian prose is known for its picturesque and haunting style in setting depiction unveiling the oneiric and uncanny quality of the city of London. One of the most underrated Christmas Books, The Chimes （1844）, p...Dickensian prose is known for its picturesque and haunting style in setting depiction unveiling the oneiric and uncanny quality of the city of London. One of the most underrated Christmas Books, The Chimes （1844）, proves to be an excellent example of a new fairy tale portraying the pervasion of two spheres： the realm of fantasy and the truth. The narrator exposes the correlation between the disturbing vision of the animated metropolis and the protagonist＇s hallucinatory fancy caused by his inner unrest and agitation, questioning the boundary between the dream and reality and the limits of perception. Despite the technical restraints of the seasonal miniature＇s construction, Dickens succeeded in capturing the hero＇s psychology and the spirit of the city through the medium of anthropomorphising the inanimate, employing the supernatural, and implementing powerful, semantically loaded images of London corresponding well with the protagonist＇s inner dilemmas. The narrative strategy balancing on the edge of dream and reality employed in the carol does not only expose the creative skills of the novelist, but also the potential of The Chimes as an embryonic novel展开更多
基金supported by the National Key R&D Program of China [grant number 2016YFA0602100]
文摘Based on the reforecasts from ve models of the Subseasonal to Seasonal(S2S)Prediction project,the S2S prediction skill of surface soil moisture(SM)over East Asia during May September is evaluated against ERA-Interim.Results show that good prediction skill of SM is generally 510 forecast days prior over southern and northeastern China in the majority of models.Over the Tibetan Plateau and northwestern China,only the ECMWF model has good prediction skill 20 days in advance.Generally,better prediction skill tends to appear over wet regions rather than dry regions.In terms of the seasonal variation of SM prediction skill,some diffierences are noticed among the models,but most of them show good prediction skill during September.Furthermore,the significant positive correlation between the prediction skill of SM and ENSO index indicates modulation by ENSO of the S2S prediction of SM.When there is an El Nino(a La Nina)event,the SM prediction skill over eastern China tends to be high(low).Through evaluation of the S2S prediction skill of SM in these models,it is found that the prediction skill of SM is lower than that of most atmospheric variables in S2S forecasts.Therefore,more attention needs to be given to the S2S forecasting of land processes.
基金jointly supported by the National Key Research and Development Program of China [grant number2016YFC0402702]the Key Project of the Meteorological Public Welfare Research Program [grant number GYHY201406021]the National Natural Science Foundation of China [grant numbers 41575095 and 41661144032]
文摘An effective improvement on the empirical orthogonal function(EOF)–based bias correctionmethod for seasonal forecasts is proposed in this paper,by introducing a stepwise regression method into the process of EOF time series correction.Using 30-year(1981–2010)hindcast results from IAP AGCM4.1(the latest version of this model),the improved method is validated for the prediction of summer(June–July–August)rainfall anomalies in Southeast China.The results in terms of the pattern correction coefficient(PCC)of rainfall anomalies shows that the 30-year-averaged prediction skill improves from 0.01 to 0.06 with the original correction method,and to 0.29 using the improved method.The applicability in real-time prediction is also investigated,using 2016 summer rainfall prediction as a test case.With a PCC of 0.59,the authors find that the new correction method significantly improves the prediction skill;the PCC using the direct prediction of the model is?0.04,and using the old bias correction method it is 0.37.
基金jointly supported by the National Key Research and Development Program of China[grant number 2019YFC1510004]and the LASG Open Project.
文摘Rwanda is a landlocked country in central-eastern Africa.As a country highly dependent on rain-fed agriculture,Rwanda is vulnerable to rainfall variability.Observational data show that there are two rainy seasons in Rwanda,i.e.,the long rainy season and the short rainy season.This study mainly focuses on the dominant intraseasonal rainfall mode during the long rainy season(February-May),and evaluates the forecast skill for the intraseasonal variability(ISV)over Rwanda and its surrounding regions in a state-of-the-art dynamic model.During the long rainy season,observational results reveal that the dominant intraseasonal rainfall mode in Rwanda exhibits a significant variability on the 10-25-day time scale.One-point-correlation analysis further unveils that the 10-25-day intraseasonal rainfall variability in Rwanda co-varies with that in its adjacent areas,indicating that the overall 10-25-day rainfall variability in Rwanda and its adjacent regions(8°S-3°N,29°-37°E)should be considered collectively when studying the dominant intraseasonal rainfall variability in Rwanda.Composite results show that the development of the 10-25-day rainfall variability is associated with the anomalous westerly wind in Rwanda and its surrounding regions,which may trace back to a pair of westward-propagating equatorial Rossby waves.Based on the observational findings,an ISO_rainfall_index and an ISO_wind_index are proposed for quantitatively evaluating the forecast skill.The ECMWF model has a comparable skill in predicting the wind index and the rainfall index,with both indices showing a skill of 18 days.
文摘Dickensian prose is known for its picturesque and haunting style in setting depiction unveiling the oneiric and uncanny quality of the city of London. One of the most underrated Christmas Books, The Chimes （1844）, proves to be an excellent example of a new fairy tale portraying the pervasion of two spheres： the realm of fantasy and the truth. The narrator exposes the correlation between the disturbing vision of the animated metropolis and the protagonist＇s hallucinatory fancy caused by his inner unrest and agitation, questioning the boundary between the dream and reality and the limits of perception. Despite the technical restraints of the seasonal miniature＇s construction, Dickens succeeded in capturing the hero＇s psychology and the spirit of the city through the medium of anthropomorphising the inanimate, employing the supernatural, and implementing powerful, semantically loaded images of London corresponding well with the protagonist＇s inner dilemmas. The narrative strategy balancing on the edge of dream and reality employed in the carol does not only expose the creative skills of the novelist, but also the potential of The Chimes as an embryonic novel
