不同时间尺度下冻融灌区地下水埋深CAR模型优选

为提高冻融灌区地下水埋深的预测精度,探索不同时间尺度数据源对地下水埋深预测的影响,以河套灌区永济灌域为研究区域,针对地下水埋深在时间序列上表现的滞后性和非线性,建立了不同时间尺度(月、季、年)CAR模型,并进行了不同输入变量CAR模型的差异性分析。结果表明:季尺度数据源CAR模型拟合效果明显优于月尺度数据源CAR模型和年尺度数据源CAR模型,拟合效果较好的季尺度数据源CAR模型的决定系数(R^2)、Nash-Sutcliffe系数(Ens)和均方根误差(RMSE)分别为0.936、0.934和0.046 m,较拟合效果较差的月尺度数据源CAR模型各项指标分别提高了11.30%、11.86%和降低了32.35%。仅考虑冻融期气温的CAR模型明显优于考虑气温的CAR模型和不考虑气温的CAR模型。冻融灌区最优地下水预测模型为季尺度数据源且仅考虑冻融期气温的CAR模型,其R^2为0.941,Ens为0.940,RMSE为0.044 m,模拟精度较高。

地学论文审稿中的数据分析

检查与分析各类数据是论文评审的重要步骤。通过分类整理《地理学报》近 3 0 0 0份审稿意见 ,发现审稿中需要检查的数据问题主要包括 :数据的即时程度、时间尺度、空间范围、抽样密度、选取类型、采集与测试的条件和方法等 6方面内容。通过与 10 0多位审稿专家和作者讨论 。

Seasonal variation of the Taiwan Warm Current Water and its underlying mechanism

Based on the historical observed data and the modeling results,this paper investigated the seasonal variations in the Taiwan Warm Current Water(TWCW)using a cluster analysis method and examined the contributions of the Kuroshio onshore intrusion and the Taiwan Strait Warm Current(TSWC)to the TWCW on seasonal time scales.The TWCW has obviously seasonal variation in its horizontal distribution,T-S characteristics and volume.The volume of TWCW is maximum(13746 km^3)in winter and minimum(11397 km^3)in autumn.As to the contributions to the TWCW,the TSWC is greatest in summer and smallest in winter,while the Kuroshio onshore intrusion northeast of Taiwan Island is strongest in winter and weakest in summer.By comparison,the Kuroshio onshore intrusion make greater contributions to the Taiwan Warm Current Surface Water(TWCSW)than the TSWC for most of the year,except for in the summertime(from June to August),while the Kuroshio Subsurface Water(KSSW)dominate the Taiwan Warm Current Deep Water(TWCDW).The analysis results demonstrate that the local monsoon winds is the dominant factor controlling the seasonal variation in the TWCW volume via Ekman dynamics,while the surface heat fl ux can play a secondary role via the joint ef fect of baroclinicity and relief.

Evaluating the impact of spatio-temporal scale on CPUE standardization

This study focused on the quantitative evaluation of the impact of the spatio-temporal scale used in data collection and grouping on the standardization of CPUE(catch per unit effort).We used the Chinese squid-jigging fishery in the northwestern Pacific Ocean as an example to evaluate 24 scenarios at different spatio-temporal scales,with a combination of four levels of temporal scale(weekly,biweekly,monthly,and bimonthly)and six levels of spatial scale(longitude×latitude:0.5°×0.5°,0.5°×1°,0.5°×2°,1°×0.5°,1°×1°,and 1°×2°).We applied generalized additive models and generalized linear models to analyze the24 scenarios for CPUE standardization,and then the differences in the standardized CPUE among these scenarios were quantified.This study shows that combinations of different spatial and temporal scales could have different impacts on the standardization of CPUE.However,at a fine temporal scale(weekly)different spatial scales yielded similar results for standardized CPUE.The choice of spatio-temporal scale used in data collection and analysis may create added uncertainty in fisheries stock assessment and management.To identify a cost-effective spatio-temporal scale for data collection,we recommend a similar study be undertaken to facilitate the design of effective monitoring programs.

Long-term variability of the sharp thermocline in the Yellow and East China Seas

Based on observed temperature data since the 1950s, long-term variability of the summer sharp thermocline in the Yellow Sea Cold Water Mass （YSCWM） and East China Sea Cold Eddy （ECSCE） areas is examined. Relationships between the thermocline and atmospheric and oceanic forcing were investigated using multiyear wind, Kuroshio discharge and air temperature data. Results show that： 1） In the YSCWM area, thermocline strength shows about 4-year and 16-year period oscillations. There is high correlation between summer thermocline strength and local atmospheric temperature in summer and the previous winter; 2） In the ECSCE area, interannual oscillation of thermocline strength with about a 4-year period （stronger in El Nifio years） is strongly correlated with that of local wind stress. A transition from weak to strong thermocline during the mid 1970s is consistent with a 1976/1977 climate shift and Kuroshio volume transport; 3） Long-term changes of the thermocline in both regions are mainly determined by deep layer water, especially on the decadal timescale. However, surface water can modify the thermocline on an interannual timescale in the YSCWM area.

Self-Similar Characteristic for the Ramp Structures of Wind Speed

Time series of wind speed are composed of large and small ramp structures. Data analysis reveals a power law relation between the linear slope of ramp structures and the time scale. This suggests that these ramp structures of wind speed have a self-similar characteristic. The lower limit of the self-similar scale range was 2 s. The upper limit is unexpectedly large at 27 rain. Data are collected from grassland, city, and lake areas. Although these data have different underlying surfaces, all of them clearly show a power law relation, with slight differences in their power exponents.

The variation of the estimated GPS instrumental bias and its possible connection with ionospheric variability

Based on the analysis of the satellite DCB data estimated by our method and the Center for Orbit Determination in Europe(CODE)from 1999 to 2011,the features of the temporal variation of differential code biases(DCB)are studied.Summarily,there are three types of variations in DCB on different time scales.The first one is the day-to-day variation that exhibits more obviously in solar maximum years.The second one is the variation with about one year periodic variation that behaves more obviously from 1999 to 2004.The last one is the monotonously descending tendency from 1999 to 2010.Considering the basic ionospheric approximation in DCB estimation method,the features of the variability of the ionospheric morphology from 1999to 2010 are also displayed based on the ionospheric characteristic parameters.It can be concluded that the day-to-day and annual variation of the estimated global positioning system(GPS).DCB is related to the ionospheric variability.The variation of DCBs on solar cycle time scale includes the real hardware DCBs and pseudo-DCBs induced by ionospheric variation.No doubt,these kinds of"pseudo"variations of DCB will affect the precision of ionospheric total electron content(TEC)derived from the GPS data.In addition,this study is helpful for evaluating the influence of ionospheric weather on TEC derivation and is also useful for developing one estimation method of DCB with more stability and precision through introducing a more practical ionospheric model.