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Modeling seasonal variations of subsurface chlorophyll maximum in South China Sea

In the South China Sea(SCS), the subsurface chlorophyll maximum(SCM) is frequently observed while the mechanisms of SCM occurrence have not been well understood. In this study, a 1-D physical-biochemical coupled model was used to study the seasonal variations of vertical profiles of chlorophyll-a(Chl-a) in the SCS. Three parameters(i.e., SCM layer(SCML) depth, thickness, and intensity) were defined to characterize the vertical distribution of Chl-a in SCML and were obtained by fitting the vertical profile of Chl-a in the subsurface layer using a Gaussian function. The seasonal variations of SCMs are reproduced reasonably well compared to the observations. The annual averages of SCML depth, thickness, and intensity are 75 ± 10 m, 31 ± 6.7 m, and 0.37 ± 0.11 mg m-3, respectively. A thick, close to surface SCML together with a higher intensity occurs during the northeastern monsoon. Both the SCML thickness and intensity are sensitive to the changes of surface wind speed in winter and summer, but the surface wind speed exerts a minor influence on the SCML depth; for example, double strengthening of the southwestern monsoon in summer can lead to the thickening of SCML by 46%, the intensity decreasing by 30%, and the shoaling by 6%. This is because part of nutrients are pumped from the upper nutricline to the surface mixed layer by strong vertical mixing. Increasing initial nutrient concentrations by two times will increase the intensity of SCML by over 80% in winter and spring. The sensitivity analysis indicates that light attenuation is critical to the three parameters of SCM. Decreasing background light attenuation by 20% extends the euphotic zone, makes SCML deeper(~20%) and thicker(12% – 41%), and increases the intensity by over 16%. Overall, the depth of SCML is mainly controlled by light attenuation, and the SCML thickness and intensity are closely associated with wind and initial nitrate concentration in the SCS.     

The Soil Moisture and Net Primary Production Affected by CO_2 and Climate Change Using a Coupled Model

In this paper, a coupled model was used to estimate the responses of soil moisture and net primary production of vegetation （NPP） to increasing atmospheric CO2 concentration and climate change. The analysis uses three experiments simulated by the second-generation Earth System Model （CanESM2） of the Canadian Centre for Climate Modelling and Analysis （CCCma）, which are part of the phase 5 of the Coupled Model Intercomparison Project （CMIP5）. The authors focus on the magnitude and evolution of responses in soil moisture and NPP using simulations modeled by CanESM, in which the individual effects of increasing CO2 concentration and climate change and their combined effect are separately accounted for. When considering only the single effect of climate change, the soil moisture and NPP have a linear trend of 0.03 kg m^-2 yr^-1 and-0.14 gC m^- 2 yr^-2, respec- tively. However, such a reduction in the global NPP results from the decrease of NPP at lower latitudes and in the Southern Hemisphere, although increased NPP has been shown in high northern latitudes. The largest negative trend is located in the Amazon basin at -1.79 gC m^-2 yr^-2. For the individual effect of increasing CO2 concentration, both soil moisture and NPP show increases, with an elevated linear trend of 0.02 kg m^-2 yr^-1 and 0.84 gC m^-2 yr^-2, respectively. Most regions show an increasing NPP, except Alaska. For the combined effect of increasing atmospheric CO2 and climate change, the increased soil moisture and NPP exhibit a linear trend of 0.04 kg m^2 yr^-1 and 0.83 gC m^2 yr^-2 at a global scale. In the Amazon basin, the higher reduction in soil moisture is illustrated by the model, with a linear trend of-0.39 kg m^-2 yr^-1, for the combined effect. Such a change in soil moisture is caused by a weakened Walker circulation simulated by this coupled model, compared with the single effect of increasing CO2 concentration （experiment M2）, and a consequence of the reduction in NPP is also shown in this area, with a linear trend of-     

分段多项式拟合在动三轴试验数据处理中的应用

动三轴采集的试验数据点(剪应变与动剪模量和阻尼比之间)具有离散性和有限性,为方便应用需要对数据点进行拟合,但现有经验公式不一定很好吻合试验数据。为得到不同剪应变与对应的动剪模量和阻尼比之间的关系,本文利用最小二乘原理,对渤海某海洋平台地基土进行动三轴试验获得的动剪模量、阻尼比与剪切应变的数据进行了分段多项式的拟合。数据处理过程是先对剪应变值进行了压缩处理,然后再分段低次多项式拟合,得到多项式拟合参数。通过此项改进解决了正规方程解中的病态问题,且拟合效果良好。     

东海西部陆架海域水团的季节特征分析

On the basis of the CTD data and the modeling results in the winter and summer of 2009, the seasonal characteristics of the water masses in the western East China Sea shelf area were analyzed using a cluster analysis method. The results show that the distributions and temperature-salinity characteristics of the water masses in the study area are of distinct seasonal difference. In the western East China Sea shelf area, there are three water masses during winter, i.e., continental coastal water（CCW）, Taiwan Warm Current surface water（TWCSW） and Yellow Sea mixing water（YSMW）, but four ones during summer, i.e., the CCW, the TWCSW, Taiwan Warm Current deep water（TWCDW） and the YSMW. Of all, the CCW, the TWCSW and the TWCDW are all dominant water masses. The CCW, primarily characterized by a low salinity, has lower temperature, higher salinity and smaller spatial extent in winter than in summer. The TWCSW is warmer, fresher and smaller in summer than in winter, and it originates mostly from the Kuroshio surface water（KSW） northeast of Taiwan, China and less from the Taiwan Strait water during winter, but it consists of the strait water and the KSW during summer. The TWCDW is characterized by a low temperature and a high salinity, and originates completely in the Kuroshio subsurface water northeast of Taiwan.     

山东荣成天鹅湖大叶藻形态和生长的季节性变化研究

2012年8月至2013年7月,作者逐月对天鹅湖大叶藻(Zostera marina L.)的形态特征、植株密度、生物量和生产力进行了监测。结果表明,大叶藻周年株高最高值和最低值分别出现在7月和1月;叶鞘高度、叶鞘宽度和叶宽的最高值均出现在7月,叶鞘高度最低值出现在1月,叶鞘宽度和叶宽最低值均出现在2月;大叶藻顶枝、侧枝和花枝的周年密度最大值分别出现在6月、4月和5月,最小值分别出现在1月、8月和7月;单株生物量和地上部分生物量最大值均出现在7月,地下部分出现在10月,而单株生物量和地上部分生物量最小值均出现在1月,地下部分生物量最小值出现在3月;单株地上和地下生产力最大值均出现在6月,最小值则分别出现在1月和2月。分析显示,大叶藻在冬季由于水温较低导致生长缓慢,且植株较小,在春季随水温上升,生长开始加快。水温在夏初达到大叶藻的最适生长水温,大叶藻的生物量和初级生产力达到最高值,而夏末和初秋由于水温过高导致大叶藻个体生物量、密度和初级生产力开始降低。这种季节性变化与水温的季节性变化密切相关。     

不同土壤水分对向日葵光合光响应的影响

以食用向日葵为试验材料,大田试验采取人为控制土壤水分在胁迫、适宜和过湿 (土壤田间持水量的40%~54.9%,55%~69.9%和70%~90%) 条件下,研究了向日葵3个生育期 (二对真叶—花序形成期、花序形成—开花期、开花—成熟期) 的光合光响应特性。结果表明:在试验设置光强条件下,各生育期净光合速率随着光合有效辐射的增加而增加,同等的光合有效辐射下净光合速率也随着土壤水分的减少依次降低,尤其是随着光合有效辐射的增大愈加明显。土壤湿度对最大净光合速率和表观量子效率的影响并不是同步的,最大净光合速率随着土壤湿度的增加而增大,而表观量子效率在一定程度的水分胁迫情况下出现最大值。不同的土壤水分含量对光补偿点和光饱和点影响不同,光饱和点随着土壤水分的增加而增加,光补偿点却相反,表明水分胁迫使向日葵可利用光的范围缩小,而适宜水分则扩大了光的利用范围,更有利于干物质积累。暗呼吸速率随着植物的生长进程逐渐降低,不同生育期的水分胁迫均导致暗呼吸速率降低。     

Heat budget of the south-central equatorial Pacific in CMIP3 models

ABSTRACT Using data from 17 coupled models and nine sets of corresponding Atmospheric Model Intercomparison Project （AMIP） results, we investigated annual and seasonal variation biases in the upper 50 m of the south-central equatorial Pacific, with a focus on the double-ITCZ bias, and examined the causes for the amplitude biases by using heat budget analysis. The results showed that, in the research region, most of the models simulate SSTs that are higher than or similar to observed. The simulated seasonal phase is close to that observed, but the amplitudes of more than half of the model results are larger than or equal to observations. Heat budget analysis demonstrated that strong shortwave radiation in individual atmospheric models is the main factor that leads to high SST values and that weak southward cold advection is an important mechanism for maintaining a high SST. For seasonal circulation, large surface shortwave radiation amplitudes cause large SST amplitudes.     

Chinese Contribution to CMIP5：An Overview of Five Chinese Models’Performances

An overview of Chinese contribution to Coupled Model Intercomparison Project-Phase 5 （CMIP5） is presented. The performances of five Chinese Climate/Earth System Models that participated in the CMIP5 pro ject are assessed in the context of climate mean states, seasonal cycle, intraseasonal oscillation, interan-nual variability, interdecadal variability, global monsoon, Asian-Australian monsoon, 20th-century historical climate simulation, climate change pro jection, and climate sensitivity. Both the strengths and weaknesses of the models are evaluated. The models generally show reasonable performances in simulating sea surface tem-perature （SST） mean state, seasonal cycle, spatial patterns of Madden-Julian oscillation （MJO） amplitude and tropical cyclone Genesis Potential Index （GPI）, global monsoon precipitation pattern, El Ni-no-Southern Oscillation （ENSO）, and Pacific Decadal Oscillation （PDO） related SST anomalies. However, the perfor-mances of the models in simulating the time periods, amplitude, and phase locking of ENSO, PDO time periods, GPI magnitude, MJO propagation, magnitude of SST seasonal cycle, northwestern Pacific mon-soon and North American monsoon domains, as well as the skill of large-scale Asian monsoon precipitation need to be improved. The model performances in simulating the time evolution and spatial pattern of the 20th-century global warming and the future change under representative concentration pathways pro jection are compared to the multimodel ensemble of CMIP5 models. The model discrepancies in terms of climate sensitivity are also discussed.     

2021年夏季中国大陆涝渍灾害时空分布分析

涝渍害是中国除干旱以外对农作物影响最严重的气象灾害,涝渍害的发生和发展对人民的生命和财产安全以及农作物的生长发育产生巨大的影响。2021年7月至8月间,中国北方多地降水达到历史观测极值,而相应时期地面的涝渍害发生和发展状况及其时空特征并未得到有效研究。因此,本研究首先利用中国大陆土壤水分站点日数据和被动微波遥感卫星SMAP反演土壤水分日产品获取中国高精度表层土壤湿度数据（0—10 cm）;随后,结合田间持水量数据计算土壤表层相对含水量。在此基础上,以连续10 d土壤相对含水量大于等于90%为标准,分析中国大陆2021年7月1日—8月25日的涝渍害时空分布情况。结果表明：（1）融合后的土壤水分产品较原始的SMAP微波土壤水分产品精度具有明显的提高;（2）中国东北地区水稻田种植区的土壤相对含水量大于等于90%的最长持续天数均为56 d,土壤的水分长期处于饱和状态,说明了本文方法能够较为准确的反应出土壤涝渍害的情况;（3）中国东北及华北地区受灾较为严重,其中黑龙江的西部和河北、河南、山东发生的涝渍面积最大。中国大陆耕地部分受涝渍灾害区域占到总耕地面积的1/2左右,重灾区面积为1.940×10⁵ km²;（4）黑龙江的西部及河北、河南、山东等地较往年降水偏多,这与涝渍害受灾区基本吻合。