Sub-seasonal to Seasonal Hindcasts of Stratospheric Sudden Warming by BCC_CSM1.1(m):A Comparison with ECMWF

This study focuses on model predictive skill with respect to stratospheric sudden warming(SSW) events by comparing the hindcast results of BCC_CSM1.1(m) with those of the ECMWF's model under the sub-seasonal to seasonal prediction project of the World Weather Research Program and World Climate Research Program. When the hindcasts are initiated less than two weeks before SSW onset, BCC_CSM and ECMWF show comparable predictive skill in terms of the temporal evolution of the stratospheric circumpolar westerlies and polar temperature up to 30 days after SSW onset. However, with earlier hindcast initialization, the predictive skill of BCC_CSM gradually decreases, and the reproduced maximum circulation anomalies in the hindcasts initiated four weeks before SSW onset replicate only 10% of the circulation anomaly intensities in observations. The earliest successful prediction of the breakdown of the stratospheric polar vortex accompanying SSW onset for BCC_CSM(ECMWF) is the hindcast initiated two(three) weeks earlier. The predictive skills of both models during SSW winters are always higher than that during non-SSW winters, in relation to the successfully captured tropospheric precursors and the associated upward propagation of planetary waves by the model initializations. To narrow the gap in SSW predictive skill between BCC_CSM and ECMWF, ensemble forecasts and error corrections are performed with BCC_CSM. The SSW predictive skill in the ensemble hindcasts and the error corrections are improved compared with the previous control forecasts.

Progress of MJO Prediction at CMA from Phase I to Phase II of the Sub-Seasonal to Seasonal Prediction Project

As one of the participants in the Subseasonal to Seasonal(S2S)Prediction Project,the China Meteorological Administration(CMA)has adopted several model versions to participate in the S2S Project.This study evaluates the models’capability to simulate and predict the Madden-Julian Oscillation(MJO).Three versions of the Beijing Climate Center Climate System Model(BCC-CSM)are used to conduct historical simulations and re-forecast experiments(referred to as EXP1,EXP1-M,and EXP2,respectively).In simulating MJO characteristics,the newly-developed high-resolution BCC-CSM outperforms its predecessors.In terms of MJO prediction,the useful prediction skill of the MJO index is enhanced from 15 days in EXP1 to 22 days in EXP1-M,and further to 24 days in EXP2.Within the first forecast week,the better initial condition in EXP2 largely contributes to the enhancement of MJO prediction skill.However,during forecast weeks 2–3,EXP2 shows little advantage compared with EXP1-M because the increased skill at MJO initial phases 6–7 is largely offset by the degraded skill at MJO initial phases 2–3.Particularly at initial phases 2–3,EXP1-M skillfully captures the wind field and Kelvin-wave response to MJO convection,leading to the highest prediction skill of the MJO.Our results reveal that,during the participation of the CMA models in the S2S Project,both the improved model initialization and updated model physics played positive roles in improving MJO prediction.Future efforts should focus on improving the model physics to better simulate MJO convection over the Maritime Continent and further improve MJO prediction at long lead times.

Sub-Seasonal Predictability of the Northeast China Cold Vortex in BCC and ECMWF S2S Model Forecasts for 2006-2021

As an important atmospheric circulation system in the mid-high latitudes of East Asia,the Northeast China cold vortex(NCCV)substantially influences weather and climate in this region.So far,systematic assessment on the performance of numerical prediction of the NCCVs has not been carried out.Based on the Beijing Climate Centre(BCC)and the ECMWF model hindcast and forecast data that participated in the Sub-seasonal to Seasonal(S2S)Prediction Project,this study systematically examines the performance of both models in simulating and forecasting the NCCVs at the sub-seasonal timescale.The results demonstrate that the two models can effectively capture the seasonal variations in the intensity,active days,and spatial distribution of NCCVs;however,the duration of NCCVs is shorter and the intensity is weaker in the models than in the observations.Diagnostic analysis shows that the differences in the intensity and location of the East Asian subtropical westerly jet and the wave train pattern from North Atlantic to East Asia may be responsible for the deficient simulation of NCCV events in the S2S models.Nonetheless,in the deterministic forecasts,BCC and ECMWF provide skillful prediction on the anomalous numbers of NCCV days and intensity at a lead time of 4-5(5-6)pentads,and the skill limit of the ensemble mean is 1-2 pentads longer than that of individual members.In the probabilistic forecasts of daily NCCV activities,BCC and ECMWF exhibit a forecasting skill of approximately 7 and 11 days,respectively;both models show seasonal dependency in the simulation performance and forecast skills of NCCV events,with better performance in winter than in summer.The results from this study provide helpful references for further improvement of the S2S prediction of NCCVs.

连续两个生长季大气CO2浓度升高对银杏希尔反应活力和叶绿体ATP酶活性的影响

近年来,随着温室气体浓度不断上升,有关CO2浓度升高对植物影响的研究已取得一定进展,但CO2浓度升高对植物光合作用的影响需要从生理生化水平上进一步深入的研究。以沈阳城市森林树种银杏(Ginkgobiloba L.)为研究对象,利用开顶式气室研究连续两个生长季大气CO2浓度升高对银杏光合特性的影响。结果表明,在大气CO2浓度为700μmol.mol-1条件下,与对照相比,第1个生长季CO2处理的银杏叶片净光合速率极显著增加(P<0.01),希尔反应活力极显著增大(P<0.01)、Ca2+/Mg2+-ATP酶活性显著(P<0.05)或极显著增强(P<0.01)、光合产物淀粉的含量极显著增多(P<0.01);第2生长季CO2处理的银杏叶片净光合速率显著增加(P<0.05),希尔反应活力在通气60d时极显著(P<0.01)增大,Ca2+/Mg2+-ATP酶活性在处理30d时显著降低(P<0.05),淀粉含量增多。与第1个生长季相比,第2个生长季CO2处理的银杏叶片净光合速率降低,希尔反应活力减小,Ca2+/Mg2+-ATP酶活性减弱,叶绿素含量增多,淀粉含量减少。试验中出现了光合适应现象。

Seed and Wasp Production in the Mutualism of Figs and Fig Wasps

Figs (Moracea: Ficus) and fig wasps (Hymenoptera: Chlocloids: Agaonideae) depend on each other to complete their reproduction. Monoecious fig species and their pollinating wasps are in conflict over the use of fig ovaries which can either produce one seed or one wasp. From observation on Ficus virens Ait., we showed that female flowers with outer layer of ovaries (near to the wall of syconium) had no significant difference from that with inner and interval layer of ovaries (near to the syconium cavity), in which most seeds and wasps were produced. This meant that fig tree provided the same potential resource for seed and wasps production. Observation indicated that there was usually only one foundress in syconium at female flower phase and no com- petition pollinators. Measurement of the style length of female flowers and the ovipositor of pollinators indicated that most ovaries could be reached by pollinator’s ovipositor. However, at the male flower phase, production of seeds was significantly more than that of wasps including non-pollinating wasps but there was no significant difference between seed and pollinating wasp production when without non-pollinating wasps produced. This result indicated that non-pollinating wasps competed ovaries not with seeds but with pollinating wasps for ovipositing. Bagged experiment showed that the sampling fig species was not self-sterile which was important for figs and wasps to survive bad season. Seed production in self-pollinated figs was not significantly different from total wasps in- cluding non-pollinating ones. This might be related with the weaker competition among wasps since bagged figs were not easy to reach by wasps from outside.

Progress and Prospects of Research on Subseasonal to Seasonal Variability and Prediction of the East Asian Monsoon

Subseasonal to seasonal(S2S)variability represents the atmospheric disturbance on the 10–90-day timescale,which is an important bridge linking weather and climate.In 2015,China Meteorological Administration(CMA)listed the S2S prediction project that was initiated by WMO programs three years ago as one of its key tasks.After five years of research,significant progress has been made on the mechanisms of the East Asian monsoon(EAM)S2S variability,related impact of climate change,as well as the predictability on the S2S timescale of numerical models.The S2S variability of the EAM is closely linked to extreme persistent climate events in China and is an important target for seasonal climate prediction.However,under the influence of global warming and the interactions among climate systems,the S2S variability of the EAM is so complex that its prediction remains a great challenge.This paper reviews the past achievement and summarizes the recent progress in research of the EAM S2S variability and prediction,including characteristics of the main S2S modes of the EAM,their impact on the extreme events in China,effects of external and internal forcing on the S2S variability,as well as uncertainties of climate models in predicting the S2S variability,with a focus on the progress achieved by the S2S research team of the Chinese Academy of Meteorological Sciences.The present bottlenecks,future directions,and critical research recommendations are also analyzed and presented.

“Unit 2 My favourite season” Part A Let’s spell教学设计

【教材内容】人教版PEP五年级下册第二单元A部分的Let’s spell(拼读课)。【教学过程】1.Gr eet i ng and war mi ng-up第一阶段:问候和热身(1)师生问候。(2)欣赏并跟唱歌曲《The Rainbow Song》,在听歌之前提出问题"How many colors can you see?What are they?"。