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贵州省冬季错季蔬菜气候适宜性区划研究 总被引：1，自引：0，他引：1
《贵州气象》2017,(6)
利用贵州85个气象观测站1987—2016年逐日气温资料,根据冬季错季蔬菜种植的气候适宜性指标,应用GIS技术和气候要素空间分布回归模型对冬季错季蔬菜种植进行气候精细化区划。结果表明:适宜区主要分布在黔西南州东部、南部边缘及罗甸县、赤水市等低海拔地区;较适宜区主要分布在黔西南州东部和南部、黔南州南部的海拔1 000 m以下地区及黔东南州南部、遵义市北部的海拔600 m以下地区;其余地区均不适宜种植冬季错季蔬菜。 相似文献
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CMIP3气候模式对东亚冬季大气环流模拟能力的评估 总被引：1，自引：0，他引：1
利用1960—1999年ECMWF月平均再分析资料(ERA40)和耦合模式比较计划(Phase 3 of the CoupledModel Intercomparison Project,简称CMIP3)21个气候耦合模式对20世纪气候模拟试验的模式结果,从气候态和年际变化两个方面,评估了CMIP3气候模式对东亚冬季大气环流的模拟能力。结果表明:(1)模式对东亚地区冬季海平面气压、850 hPa纬向风、经向风和500 hPa高度场气候态的模拟存在不同程度的偏差,但均能较好模拟出上述要素气候态的空间分布特征。总体而言,模式对500 hPa高度场气候态的模拟效果最好,而对850 hPa经向风的模拟效果较差。(2)模式基本上能抓住近40年来东亚地区冬季500 hPa高度场的主要变化特征,但基本上不能模拟出冬季海平面气压、850 hPa纬向风和经向风的变化特征。此外,模式对阿留申低压、蒙古高压和东亚冬季风强度的变化特征几乎没有模拟能力。 相似文献
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GIS在衢州市茶叶种植气候区划中的应用 总被引：1，自引：1，他引：1
建立了衢州市数字高程模型（DEM），利用气候要素推算模型和GIS的离散点插植，建立与DEM同分辨率的栅格图。由此利用小网格推算衢州农业气候资源的立体分布，分析研究茶叶种植气候区划，获得较好的效果，对茶叶种植有一定意义。 相似文献
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通过对全省1961-2004年冬季共44年的气温资料分析得出，2004年冬季是青海省有气象记录以来偏暖幅度最大的冬季。本用冬季累计积雪量、500hPa环流形势、500hPa高原指数、500hPa副高面积指数等分析了形成这种大幅度偏暖的气候成因。 相似文献
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GIS支持下的陕西省农业气候资源可视化管理系统 总被引：1，自引：0，他引：1
基于CITYSTAR地理信息系统的GISOCXACTIVEX控件，采用VB语言进行GIS的应用开发，实现了对陕西省气候资源数字图像的查询和管理。通过该系统的应用，可给出陕西省境内任一网格单元（空间分辨率为500×500m）的地理位置、地形地貌、气候要素、主要经济作物适生状况等14项空间数据属性值，对充分利用当地的自然资源，发展特色经济有一定的指导意义。 相似文献
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近50年中国风速变化多气候模式模拟检验 总被引：3，自引：0，他引：3
近年来,随着气候模式研究的快速发展,全球气候模式在模拟20世纪气候和气候变化特征,尤其是在模拟温度、降水等要素特征和变化及其人类活动对这些要素的影响等方面取得了丰硕的成果.然而,全球气候模式对近地层风速的模拟情况如何,目前仍缺少分析和检验.本文利用中国区域近地层风速观测资料,检验评估了参与IPCC AR4"20世纪气候耦合模式模拟"(20C3M)的19个伞球气候模式和国家气候中心新一代伞球气候模式(BCC_CSM1.0.1)模拟的1956-1999年中国近地层(10m)风速及其变化的模拟能力.研究发现,20个伞球气候模式基本上都能模拟出中国多年年(或季)平均风速分布状况,但模式模拟的平均风速一般小于观测值,尤以观测风速较大的北部和西北部地区模拟值偏小显著.气候模式模拟秋冬季风速分布的能力强于模拟夏春季的能力.模式基本上能模拟出冬、春季平均风速大于夏、秋季平均风速,但是模拟不出春、冬、夏、秋季平均风速依次减小的季节变化特征.模式及模式集成难以模拟出观测到的近50年中国年(或季)平均风速明显减小的变化趋势,少数模式能模拟出年(或季)平均风速略呈减小的变化趋势,但与观测值比相差约一个量级.模式对北部和西南部地区平均风速的变化模拟效果较好,而模式难以模拟东南-南部地区风速变化特征. 相似文献
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本文通过对四川省广安市近50年冬季气候资料的聚类分析,研究冷冬气候的演变规律;结合太阳黑子活动资料、夏季极端异常气候事件分析,发现广安市异常冷冬年的发生发展和一月太阳黑子活动存在着密切的相关关系,与本市盛夏期间极端气候事件有明显的周期性对应关系;从而探索得出对异常冷冬年的短期气候预测方法,为准确预测冷冬,特别是预测异常冷冬将发挥重要的作用。 相似文献
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Pinki Mondal Meha Jain Andrew W. Robertson Gillian L. Galford Christopher Small Ruth S. DeFries 《Climatic change》2014,126(1-2):61-76
India is predicted to be one of the most vulnerable agricultural regions to future climate changes. Here, we examined the sensitivity of winter cropping systems to inter-annual climate variability in a local market and subsistence-based agricultural system in central India, a data-rich validation site, in order to identify the climate parameters to which winter crops – mainly wheat and pulses in this region – might be sensitive in the future. We used satellite time-series data to quantify inter-annual variability in multiple climate parameters and in winter crop cover, agricultural census data to quantify irrigation, and field observations to identify locations for specific crop types. We developed three mixed-effect models (250 m to 1 km scale) to identify correlations between crop cover (wheat and pulses) and twenty-two climate and environmental parameters for 2001-2013. We find that winter daytime mean temperature (November–January) is the most significant factor affecting winter crops, irrespective of crop type, and is negatively associated with winter crop cover. With pronounced winter warming projected in the coming decades, effective adaptation by smallholder farmers in similar landscapes would require additional strategies, such as access to fine-scale temperature forecasts and heat-tolerant winter crop varieties. 相似文献
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Developing a likely climate scenario from multiple regional climate model simulations with an optimal weighting factor 总被引：1，自引：0，他引：1
This study presents a performance-based comprehensive weighting factor that accounts for the skill of different regional climate models (RCMs), including the effect of the driving lateral boundary condition coming from either atmosphere–ocean global climate models (AOGCMs) or reanalyses. A differential evolution algorithm is employed to identify the optimal relative importance of five performance metrics, and corresponding weighting factors, that include the relative absolute mean error (RAME), annual cycle, spatial pattern, extremes and multi-decadal trend. Based on cumulative density functions built by weighting factors of various RCMs/AOGCMs ensemble simulations, current and future climate projections were then generated to identify the level of uncertainty in the climate scenarios. This study selected the areas of southern Ontario and Québec in Canada as a case study. The main conclusions are as follows: (1) Three performance metrics were found essential, having the greater relative importance: the RAME, annual variability and multi-decadal trend. (2) The choice of driving conditions from the AOGCM had impacts on the comprehensive weighting factor, particularly for the winter season. (3) Combining climate projections based on the weighting factors significantly increased the consistency and reduced the spread among models in the future climate changes. These results imply that the weighting factors play a more important role in reducing the effects of outliers on plausible future climate conditions in regions where there is a higher level of variability in RCM/AOGCM simulations. As a result of weighting, substantial increases in the projected warming were found in the southern part of the study area during summer, and the whole region during winter, compared to the simple equal weighting scheme from RCM runs. This study is an initial step toward developing a likelihood procedure for climate scenarios on a regional scale using equal or different probabilities for all models. 相似文献
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A. Jost D. Lunt M. Kageyama A. Abe-Ouchi O. Peyron P. J. Valdes G. Ramstein 《Climate Dynamics》2005,24(6):577-590
The analyses of low-resolution models simulations of the last glacial maximum (LGM, 21 kyr BP) climate have revealed a large
discrepancy between all the models and pollen-based palaeoclimatic reconstructions. In general, the models are too warm relative
to the observations, especially in winter, where the difference is of the order of 10°C over western Europe. One of the causes
of this discrepancy may be related to the low spatial resolution of these models. To assess the impact of using high-resolution
models on simulated climate sensitivity, we use three approaches to obtain high-resolution climate simulations over Europe:
first an atmospheric general circulation model (AGCM) with a stretched grid over Europe, second a homogeneous T106 AGCM (high
resolution everywhere on the globe) and last a limited area model (LAM) nested in a low-resolution AGCM. With all three methods,
we have performed simulations of the European climate for present and LGM conditions, according to the experimental design
recommended by the Palaeoclimate Modeling Intercomparison Project (PMIP). Model results have been compared with updated pollen-based
palaeoclimatic indicators for temperature and precipitation that were initially developed in PMIP. For each model, a low-resolution
global run was also performed. As expected, the low-resolution simulations underestimate the large cooling indicated by pollen
data, especially in winter, despite revised slightly warmer reconstructions of the temperatures of the coldest month, and
show results in the range of those obtained in PMIP with similar models. The two high-resolution AGCMs do not improve the
temperature field and cannot account for the discrepancy between model results and data, especially in winter. However, they
are able to reproduce trends in precipitation more closely than their low-resolution counterparts do, but the simulated climates
are still not as arid as depicted by the data. Conversely, the LAM temperature results compare well with climate reconstructions
in winter but the simulated hydrological cycle is not consistent with the data. Finally, these results are discussed in regard
of other possible causes for discrepancies between models and palaeoclimatic reconstructions for the LGM European climate. 相似文献
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文章介绍了海洋气象导航发展的必然性及其气象航线选择的原理和影响因素。结合中央气象台海洋气象导航中心近10年来的实船导航业务，分析了北印度洋气候对冬、夏季航线选择的影响因素，指出应结合北印度洋的冬、夏季气候变化及地形特点选择不同的气象航线。该文为在实际工作中根据不同的季节及船型情况选择不同的航线、规避大风和巨浪出现频率高的区域，以及保持良好的航行条件提供了依据。 相似文献
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用新疆北部阿勒泰站1954—2010年资料,分析致灾大雪5个气候因子的概率风险。在模糊信息扩散理论初步分析的基础上,进行综合分析试验。试验表明,在未知理论分布的情况下,模糊信息扩散法对雪灾气候因子的概率风险分析可靠简便,缺点粗糙。进一步的理论分布分析,发现冬季大雪(≥6mm)日数、最大雪深、日最大降雪量、冬季降雪量、大于等于10cm雪深日数的理论分布模型,具有Gamma分布特征,通过α=0.001的相关系数显著性检验。分析不同界限雪深日数的气候因素族的概率密度分布,发现其具有双峰型特征,不属于常规典型分布,其理论分布有待深入研究。提出的Gamma分布,分析计算的步骤、方法有实际应用价值。试验确定的具有Gamma分布特征的几个雪灾气候因子,对于从理论上认识雪灾气候风险具有重要意义。 相似文献
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基于CMIP5模式的中国气候变化敏感性预估与分析 总被引：4，自引：0，他引：4
以CMIP5提供的26个全球气候系统模式的温度和降水数据为基础,采用区域气候变化指数(Regional Climate Change Index,RCCI)分析中国的不同区域对21世纪气候变化响应的敏感性。结果表明,三种排放情景(RCP 2.6、RCP 4.5、RCP 8.5)下,21世纪全期,气候变化最敏感的区域分布在西藏地区,其次为我国西北地区以及东北地区,气候变化敏感性最低的区域分布在我国内蒙古中东部、华北地区以及长江中下游一带,且高排放情景对应更高的气候变化敏感性。对RCCI指数贡献因子分析结果表明,对中国气候变化敏感性贡献的大小依次为Δσ_TΔσ_pΔRRWAF。冬夏两季温度变化的大值区与RCCI指数的大致区分布一致,RCCI大小的分布很大程度上由温度变化的敏感性决定。而夏季降水变化的大值区主要出现在西藏地区、华南地区和东北地区,冬季降水变化的大值区则主要出现在黄河以南长江以北的中原地区以及东北地区。 相似文献