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Motoyoshi Ikeda 《极地研究(英文版)》2008,19(2):212-217
The sea ice cover in the Arctic Ocean has been reducing and hit the low record in the summer of 2007. The anomaly was extremely large in the Pacific sector. The sea level height in the Bering Sea vs. the Greenland Sea has been analyzed and compared with the current meter data through the Bering Strait. A recent peak existed as a consequence of atmospheric circulation and is considered to contribute to inflow of the Pacific Water into the Arctic Basin. The timing of the Pacific Water inflow matched with the sea ice reduction in the Pacific sector and suggests a significant increase in heat flux. This component should be included in the model prediction for answering the question when the Arctic sea ice becomes a seasonal ice cover. 相似文献
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地表温度是地表能量平衡、区域和全球尺度地表物理过程的一个重要因子。为了辨析中国西北干旱区“天山湿岛”——伊犁河谷的地表温度时空分异,采用趋势分析法和空间数据统计法,探讨了2001-2014年不同土地利用/覆盖类型下地表温度时空变化规律,分析地表温度的时空分异特征及原因。结果表明:(1) MODIS LST产品的精度(平均R2=0.90)能够满足伊犁河谷地表温度时空变化分析的要求;(2)空间上,地表温度呈现出中部高四周低的变化趋势,高温区面积约占总面积的41%,低温区面积约占总面积的23%;时间上,伊犁河谷平均地表温度的年际波动较大,以2013年、2006年、2007年和2008年尤为突出;地表温度的年内变化呈现出单峰型分布,地表温度高值集中在3-8月,最高值出现在7月;(3)不同土地利用/覆盖类型下年均地表温度分布的总体特征为建设用地最高,稀疏草地、旱地等次之,冰川/积雪最低;(4)伊犁河谷地表温度变化趋势呈严重减少、基本不变和轻微增加区域面积分别占5%、37%和26%,以基本不变和轻微增加为主。伊犁河谷地表温度时空变化不仅受大尺度气候变化影响,还受土地类型差异影响,两者共同构成了不同地理区域及景观的温场格局,绿色植被对地表温度时空分布具有重要的调节作用。 相似文献
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The spatially explicit reconstruction of historical land-cover datasets plays an important role in studying the climatic and ecological effects of land-use and land-cover change(LUCC). Using potential natural vegetation(PNV) and satellite-based land use data, we determined the possible maximum distribution extent of forest cover in the absence of human disturbance. Subsequently, topography and climate factors were selected to assess the suitability of land for cultivation. Finally, a historical forest area allocation model was devised on the basis of the suitability of land for cultivation. As a case study, we used the historical forest area allocation model to reconstruct forest cover for 1780 and 1940 in Northeast China with a 10-km resolution. To validate the model, we compared satellite-based forest cover data with our reconstruction for 2000. A one-sample t-test of absolute bias showed that the two-tailed significance was 0.12, larger than the significant level 0.05, suggesting that the model has strong ability to capture the spatial distribution of forests. In addition, we calculated the relative difference of our reconstruction at the county scale for 1780 in Northeast China. The number of counties whose relative difference ranged from-30% to 30% is 99, accounting for 74.44% of all counties. These findings demonstrated that the provincial forest area could be transformed into forest cover maps well using the model. 相似文献
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融雪期雪层融雪水的运移及流出过程模拟乃是国际冰雪水文学研究的难点之一,准确模拟融雪水的出流过程对于春季融雪型洪水的预报具有重要作用。本研究基于EM50、农业小环境监测仪和一些常规监测手段,获取了典型融雪期雪层的雪粒径、雪深及日气温数据,利用Excel、DPS、Arcgis及SPSS等分析软件对数据进行综合处理,并采用回归分析对融雪水的出流条件进行了建模分析,利用神经网络模型对模拟结果进行检验。结果表明:积温可作为融雪水外流的参考性指标,用于融雪水外流过程的预测分析;雪粒径和雪深都与融雪水外流积温条件存在显著相关性,且相关系数0.96;逐步回归可以很好地模拟融雪水外流的积温条件,模拟的误差仅为124.5℃·min,时间误差为15 min,模拟效果良好。该研究对于进一步探讨融雪期雪层融雪水的出流规律、开展雪层融雪水运移过程的数值模拟等工作具有重要意义。 相似文献
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Received date: -- Revised date: -- Foundation item: Under the auspices of the National Natural Science Foundation of China 《地理学报(英文版)》2000,(3)
1 Introduction1.1 Introduction to Liaocheng PrefectureLiaocheng
Prefecture lies in northwest of Shandong Province and slightly north to the center of the Huang-Huai-Hai Plain with latitudes between 35(47'N and 37(02'N and longitudes between 115(16'E and 116(32'E. Administratively, it consists of two cities (Liaocheng and Linqing) and six counties (Yanggu, Shenxian, Chiping, Dong'e, Guanxian and Gaotang). It covers a total area of 8590 km2 with a maximum distance of 114 km from eas… 相似文献
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【Title】
There are knowledge gaps in our understanding of vegetation responses to multi-scale climate-related variables in tropical/subtropical mountainous islands in the Asia-Pacific region. Therefore, this study investigated inter-annual vegetation dynamics and regular/irregular climate patterns in Taiwan. We applied principal component analysis (PCA) on 11 years (2001~2011) of high-dimensional monthly photosynthetically active vegetation cover (PV) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and investigated the relationships between spatiotemporal patterns of the eigenvectors and loadings of each component through time and multi-scale climate-related variations. Results showed that the first five components contributed to 96.4% of the total variance. The first component (PC1, explaining 94.5% of variance) loadings, as expected, were significantly correlated with the temporal dynamics of the PV (r = 0.94), which was mainly governed by regional climate. The temporal loadings of PC2 and PC3 (0.8% and 0.6% of variance, respectively) were significantly correlated with the temporal dynamics of the PV of forests (r = 0.72) and the farmlands (r = 0.80), respectively. The low-order components (PC4 and PC5, 0.3% and 0.2% of variance, respectively) were closely related to the occurrence of drought (r = 0.49) and to irregular ENSO associated climate anomalies (r = -0.54), respectively. Pronounced correlations were also observed between PC5 and the Southern Oscillation Index (SOI) with one to three months of time lags (r = -0.35 ~ -0.43, respectively), revealing biophysical memory effects on the time-series pattern of the vegetation through ENSO-related rainfall patterns. Our findings reveal that the sensitivity of the ecosystems in this tropical/subtropical mountainous island may not only be regulated by regional climate and human activities but also be susceptible to large-scale climate anomalies which are crucial and comparable to previous large scale analyses. This study demonstrates that PCA can be an effective tool for analyzing seasonal and inter-annual variability of vegetation dynamics across this tropical/subtropical mountainous islandin the Pacific Ocean, which provides an opportunity to forecast the responses and feedbacks of terrestrial environments to future climate scenarios. 相似文献
There are knowledge gaps in our understanding of vegetation responses to multi-scale climate-related variables in tropical/subtropical mountainous islands in the Asia-Pacific region. Therefore, this study investigated inter-annual vegetation dynamics and regular/irregular climate patterns in Taiwan. We applied principal component analysis (PCA) on 11 years (2001~2011) of high-dimensional monthly photosynthetically active vegetation cover (PV) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and investigated the relationships between spatiotemporal patterns of the eigenvectors and loadings of each component through time and multi-scale climate-related variations. Results showed that the first five components contributed to 96.4% of the total variance. The first component (PC1, explaining 94.5% of variance) loadings, as expected, were significantly correlated with the temporal dynamics of the PV (r = 0.94), which was mainly governed by regional climate. The temporal loadings of PC2 and PC3 (0.8% and 0.6% of variance, respectively) were significantly correlated with the temporal dynamics of the PV of forests (r = 0.72) and the farmlands (r = 0.80), respectively. The low-order components (PC4 and PC5, 0.3% and 0.2% of variance, respectively) were closely related to the occurrence of drought (r = 0.49) and to irregular ENSO associated climate anomalies (r = -0.54), respectively. Pronounced correlations were also observed between PC5 and the Southern Oscillation Index (SOI) with one to three months of time lags (r = -0.35 ~ -0.43, respectively), revealing biophysical memory effects on the time-series pattern of the vegetation through ENSO-related rainfall patterns. Our findings reveal that the sensitivity of the ecosystems in this tropical/subtropical mountainous island may not only be regulated by regional climate and human activities but also be susceptible to large-scale climate anomalies which are crucial and comparable to previous large scale analyses. This study demonstrates that PCA can be an effective tool for analyzing seasonal and inter-annual variability of vegetation dynamics across this tropical/subtropical mountainous islandin the Pacific Ocean, which provides an opportunity to forecast the responses and feedbacks of terrestrial environments to future climate scenarios. 相似文献
30.
References: 《极地研究(英文版)》2007,18(1):54-62
Chinese meteorological satellite FY-1D can obtain global data from four spectral channels which include visible channel(0.58-0.68 μm) and infrared channels(0.84-0.89 μm,10.3-11.3 μm,11.5-12.5 μm).2366 snow and ice samples,2024 cloud samples,1602 land samples and 1648 water samples were selected randomly from Arctic imageries.Land and water can be detected by spectral features.Snow-ice and cloud can be classified by textural features.The classifier is Bayes classifier.By synthesizing five d ays classifying result of Arctic snow and ice cover area,complete Arctic snow and ice cover area can be obtained.The result agrees with NOAA/NESDIS IMS products up to 70%. 相似文献