Wintertime nutrients in the North Atlantic—new approaches and implications for new production estimates

Observations of wintertime nutrient concentrations in surface waters are scarce in the temperate and subarctic North Atlantic Ocean. Three new methods of their estimation from spring or early summer observations are described and evaluated. The methods make use of a priori knowledge of the vertical distribution of oxygen saturation and empirical relationships between nutrient concentrations and oxygen saturation. A south–north increase in surface water winter nutrient concentration is observed. Winter nitrate concentrations range from very low levels of about 0.5 μmol dm⁻³ at 33°N to about 13.5 μmol dm⁻³ at 60°N. Previous estimates of winter nitrate concentrations have been overestimates by up to 50%. At the Biotrans Site (47°N, 20°W), a typical station in the temperate Northeast Atlantic, a mean winter nitrate concentration of 8 μmol dm⁻³ is estimated, compared to recently published values between 11 and 12.5 μmol dm⁻³. It is shown that most of the difference is due to a contribution of remineralised nitrate that had not been recognized in previous winter nutrient estimates. Mesoscale variation of wintertime nitrate concentrations at Biotrans are moderate (less than ±15% of the regional mean value of about 8 μmol dm⁻³). Interannual variation of the regional mean is small, too. In the available dataset, there was only 1 year with a significantly lower regional mean winter nitrate concentration (7 μmol dm⁻³), presumably due to restricted deep mixing during an atypically warm winter. The significance of winter nitrate estimates for the assessment of spring-bloom new production and the interpretation of bloom dynamics is evaluated. Applying estimates of wintertime nitrate concentrations of this study, it is found that pre-bloom new production (0.275 mol N m⁻²) at Biotrans almost equals spring-bloom new production (0.3 mol N m⁻²). Using previous estimates of wintertime nitrate yields unrealistically high estimates of pre-bloom new production (1.21–1.79 mol N m⁻²) which are inconsistent with observed levels of primary production and the seasonal development of biomass.     

Regional yield estimation for winter wheat with MODIS-NDVI data in Shandong, China

The significance of crop yield estimation is well known in agricultural management and policy development at regional and national levels. The primary objective of this study was to test the suitability of the method, depending on predicted crop production, to estimate crop yield with a MODIS-NDVI-based model on a regional scale. In this paper, MODIS-NDVI data, with a 250 m resolution, was used to estimate the winter wheat (Triticum aestivum L.) yield in one of the main winter-wheat-growing regions. Our study region is located in Jining, Shandong Province. In order to improve the quality of remote sensing data and the accuracy of yield prediction, especially to eliminate the cloud-contaminated data and abnormal data in the MODIS-NDVI series, the Savitzky–Golay filter was applied to smooth the 10-day NDVI data. The spatial accumulation of NDVI at the county level was used to test its relationship with winter wheat production in the study area. A linear regressive relationship between the spatial accumulation of NDVI and the production of winter wheat was established using a stepwise regression method. The average yield was derived from predicted production divided by the growing acreage of winter wheat on a county level. Finally, the results were validated by the ground survey data, and the errors were compared with the errors of agro-climate models. The results showed that the relative errors of the predicted yield using MODIS-NDVI are between −4.62% and 5.40% and that whole RMSE was 214.16 kg ha⁻¹ lower than the RMSE (233.35 kg ha⁻¹) of agro-climate models in this study region. A good predicted yield data of winter wheat could be got about 40 days ahead of harvest time, i.e. at the booting-heading stage of winter wheat. The method suggested in this paper was good for predicting regional winter wheat production and yield estimation.     

青藏高原冬小麦田辐射能量收支的初步研究

通过对青藏高原冬小麦田净全辐射各分量的观测资料分析，论述了净全辐射及其各分量的日变化特征；计算得出冬小麦抽穗—乳熟期麦田平均反射率为13.3%，净全辐射占总辐射百分率:白天75%，包括夜间67.4%；指出了净全辐射和总辐射间存在良好的线性关系，给出了由总辐射计算净全辐射的经验公式。     

Global scale annual and semi-annual variations of daytime NmF2 in the high solar activity years

The annual and semi-annual variations of the ionosphere are investigated in the present paper by using the daytime F2 layer peak electron concentration (NmF2) observed at a global ionosonde network with 104 stations. The main features are outlined as follows. (1) The annual variations are most pronounced at magnetic latitudes of 40–60° in both hemispheres, and usually manifest as winter anomalies; Below magnetic latitude of 40° as well as in the tropical region they are much weaker and winter anomalies that are not obvious. (2) The semi-annual variations, which are usually peak in March or April in most regions, are generally weak in the near-pole regions and strong in the far-pole regions of both hemispheres. (3) Compared with their annual components, the semi-annual variations in the tropical region are more significant.In order to explain the above results, we particularly analyze the global atomic/molecular ratio of [O/N2] at the F2 layer peak height by the MSIS90 model. The results show that the annual variation of [O/N2] is closely related with that of NmF2 prevailing in mid-latitudes and [O/N2] annual variation usually may lead to the winter anomalies of NmF2 occurring in the near-pole region. Moreover, NmF2 semi-annual variations appearing in the tropical region also have a close relationship with the variation of [O/N2]. On the other hand, the semi-annual variations of NmF2 in the far-pole region cannot be simply explained by that of [O/N2], but the variation of the solar zenith angle may also have a significant contribution.     

Reductions of PM<Subscript>2.5</Subscript> in Beijing-Tianjin-Hebei urban agglomerations during the 2008 Olympic Games

The Atmospheric Environmental Monitoring Network successfully undertook the task of monitoring the atmospheric quality of Beijing and its surrounding area during the 2008 Olympics.The results of this monitoring show that high concentrations of PM2.5 pollution exhibited a regional pattern during the monitoring period(1 June-30 October 2008).The PM2.5 mass concentrations were 53 μg m 3,66 μg m 3,and 82 μg m 3 at the background site,in Beijing,and in the Beijing-Tianjin-Hebei urban agglomerations,respectively.The PM2.5 levels were lowest during the 2008 Olympic Games(8-24 August):35 μg m 3 at the background site,42 μg m 3 in Beijing and 57 μg m 3 in the region.These levels represent decreases of 49%,48%,and 56%,respectively,compared to the prophase mean concentration before the Olympic Games.Emission control measures contributed 62%-82% of the declines observed in Beijing,and meteorological conditions represented 18%-38%.The concentration of fine particles met the goals set for a "Green Olympics."     

北京奥运会期间NO2浓度降低原因分析

2002～2008年,北京市城区和近郊8月的NO2月均浓度大体呈现逐年下降趋势,其中前5年二者均以每年约10%的降幅下降,2008年发生显著下降,降幅达40%左右。利用嵌套网格空气质量模式系统(NAQPM/IAP),采用敏感性试验方法,评估了气象条件与污染控制措施对北京奥运会期间大气NO2浓度降低的影响,评估不同污染控制措施对NO2浓度降低的作用。研究结果表明,污染控制措施是NO2浓度降低的主要影响因素,其中面源的污染控制措施对于NO2浓度降低的作用最明显。     

冬奥赛场卫星和地基微波辐射计气温廓线观测对比和验证

利用探空站数据对北京和张家口冬奥赛场周边地区的地基微波辐射计和FY 4A大气垂直探测仪资料进行验证分析。选取2020年全年FY 4A大气垂直探测仪资料以及2020年12月至2021年3月期间对冬奥赛事有重要影响的寒潮前后、雾霾和沙尘暴这3种不同天气现象下探测得到的气温廓线数据进行个例分析。结果表明：在晴空条件下,地基微波辐射计和FY 4A大气垂直探测仪探测大气垂直气温的精度较高,平均相关系数达到0.97,低层大气（500 hPa以下）较高层大气探测结果的一致性较好;大气污染对探测精度产生一定影响,其中PM2.5产生的影响较小,PM10的提高对FY 4A大气垂直探测仪的探测产生较大影响,尤其是发生沙尘暴时,星载探测仪无法对低层大气进行探测。经过对比和验证,卫星探测作为补充探测手段,可以与地基微波辐射计互相补充,尤其是在空间覆盖和时间分辨率上具备一定优势,但在有云和沙尘暴的天气条件下无法对低层大气开展探测;地基微波辐射计可以对一个地点的大气垂直参数开展不间断的探测,与探空站数据的一致性较高。卫星探测和地基微波辐射计均可以为冬奥赛事提供高时间分辨率的探测数据,为数值天气预报提供有力的数据支撑。     

水分和氮肥对冬小麦产量的影响及其调控技术

通过对冬小麦进行不同水分等级和不同施氮量的控制试验,利用数理统计和数学分析方法,从水分利用效率和经济效益角度,分析了水分和氮素对冬小麦产量的影响及其相互作用的关系,提出了河南省冬小麦砂壤土的水肥配置模式,经生产检验,这种模式是可行的。     

地下水浅埋条件下冬小麦和大豆土壤水分动态预报模型研究

用统计方法和水量平衡法推导出江淮地区潜水蒸发经验计算模型。利用农田水分平衡原理分别在江淮地区建立了引入潜水蒸发量和没有引入潜水蒸发量的冬小麦和大豆土壤水分动态预报模型,并对这两种模型在地下水浅埋条件下的预报准确度进行比较。1980年的比较结果是:当预报时效为10天时,两种作物7个时段的土壤水分平均绝对误差前者为8.2 mm,后者为20.1 mm,平均相对误差分别为2.8%和6.8%。引入潜水蒸发量后,冬小麦和大豆土壤水分动态预报模型的预报准确度明显提高。     

冬季中国近海海表温度的长期升高及其对中国降水的影响

利用1962—2011年HadISST海表温度资料和中国160站逐月降水等资料通过回归和相关分析等方法,分析了中国近海冬季海表温度(SST)的长期升高及其与中国冬季降水的关系。研究表明,近50年来中国近海冬季海表温度呈现明显的长期升高趋势。进一步分析发现,中国近海冬季海表温度的升高与长江中下游及以南地区冬季降水的增加存在显著的相关。最后,利用全球大气环流模式(CAM5.1)模拟研究了近海海温长期升高对中国降水的影响,模式模拟结果很好地验证了观测结果,表明中国近海冬季海表温度的长期升高确实对中国冬季降水存在影响。