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1.
短期气候预测的主要对象是气温和降水的月、季平均量和总量,需要做预报是因为它们有年际变率,但是年际变率究竟有多少是可以被预报出来的呢？通常情况下将总的年际变率划分为主要来源于大气下边界条件持续性外源强迫引起的可预报成分和由于大气内部不稳定性产生的日际天气振荡引起的不可预报成分,前者称气候信号,后者称气候噪声,我们用两个成分的方差之比给出潜在可预报性的测度。本文用低频白噪声延伸法估计了吉林省夏季（6～8月）降水量潜在可预报的气候信号方差和天气噪声方差。结果表明,我省各地均存在潜在可预报性信号。以绝对误差小于均方差0．68倍做为预报正确的标准,我省70%的站预报正确率上限达60％以上。 相似文献
2.
云南地区季降水量和气温的潜在可预报性分析 总被引：1，自引：1，他引：0
利用云南地区42年气候资料,使用低频白噪声延伸法和方差分析方法,估计了该地区季节降水量和季节气温的气候噪声方差和潜在可预报性。分析结果表明：（1）云南季降水量的气候噪声方差随着季节降水量的增加而增加,空间上主要是由南往北减小,夏季降水量的气候噪声方差显著大于其他季节,季气温的气候噪声方差则随着季节气温的减小而增加,空间上春、冬季由东往西减小而夏、秋季由南往北增加;冬季气温的气候噪声方差显著大于其他季节;（2）云南季降水量和季气温的潜在可预报性同样具有显著的季节变化和空间变化,云南春季的降水量和气温的潜在可预报性均显著大于其他季节,夏季降水量和气温的潜在可预报性均较其他三个季节小;春、秋季降水量潜在可预报性西部大于东部,夏季北部大于南部,冬季则是南部大于北部,云南季气温除夏季外均是西部大于东部。（3）季风和冷空气活动可能对云南地区的季降水量和气温的潜在可预报性有重要影响。 相似文献
3.
中国季降水量的气候噪声和潜在可预报性估计 总被引：2，自引：1，他引：1
利用中国130个测站1961—2004年的日降水量资料,使用低频白噪声延伸法和方差分析法估计了中国季降水量的气候噪声方差和潜在可预报性。结果表明：中国季降水量的气候噪声方差由南向北、由沿海向内陆逐渐减小,且有明显的季节变化,夏季最高,其次是春秋季,冬季最小,而且内陆的季节变化比东南沿海的季节变化显著。季降水量的潜在可预报性有较大的季节和区域差异,但总体来说,全国大部分地区的季降水量是潜在可预报的。以绝对误差小于均方差0.68倍作为预测正确标准,全国大部分地区季降水量的预报正确率上限为50%-60%。 相似文献
4.
国外关于年代际气候变率的研究 总被引：28，自引：2，他引：26
文中指出在气候变率与可预报性研究计划中,列出年代际气候变率及可预报性研究子计划充分显示出这个问题的重要性,回顾并总结了近年来年代际气候变率的研究成果,特别对全球气候变暖、海气相互作用、温盐环流、自然气候变率和ＥＮＳＯ的年代际变率的研究几个重点问题进行了讨论,最后对年代际气候变率研究今后的发展方向提出了看法。 相似文献
5.
我国的降水资源及其稳定性与潜在可预报性（Ⅱ）潜在可预报性 总被引：5，自引：0，他引：5
本文探讨了年降水量气候噪声估计的方法，并利用我国分布较均匀的１６２个测站１９６０－１９９１年降水资料，讨论了年降水量的潜在可预报性，以便进一步研究月，季降水量的可预报性。结果得出；黄河以南和长江流域的广大地区，特别是四川东部和江淮地区，是我国降水量气候噪声最大的地区；华北，西北以及华南地区降水量的潜在可预报性较大黄河以南和长江流域中下游地区降水量的潜在可预报性较小。 相似文献
6.
年代际气候预测计划（DCPP）是第六次国际耦合模式比较计划（CMIP6）的子计划之一,其目标是利用多模式开展气候系统年代际预测、可预测性和变率机制研究。DCPP设计了3组试验,即年代际回报试验、预报试验以及理解年代际变率机制和可预测性的敏感性试验。目前有21个模式拟参与DCPP计划,其中包括5个来自中国的模式。DCPP将推动解决气候系统从年际到年代际尺度预测相关的多项科学问题,评估当前气候预测系统预报技巧,挖掘潜在可预报性,研究长时间尺度气候变率形成机制,提供对科学和社会有用的预测产品。 相似文献
7.
中国月平均温度的气候噪声和潜在可预报性 总被引：9，自引：1，他引：8
利用中国74个测站1960～1991年日平均温度研究了中国月平均温度的气候噪声和潜在可预报性。气候噪声是在Yamamoto等人的思想基础上设计的方法估计的,而潜在可预报性则是用月平均温度的年际变化与自然变化（气候噪声）之比表示的。一般情况下中国月平均温度的气候噪声随纬度和高度增加而增加,并随季节变化而变化。来自西伯利亚和蒙古的变性大陆干冷气团对气候噪声有很大的影响,一般而言,海洋对气候噪声起着调节和减弱作用（除了热带海洋在春秋过渡季节外）。月平均温度的潜在可预报性有较大的季节和区域差异。但总的来说中国月平均温度在α＝0．10的统计显著性水平上是潜在可预报的。这些结果表明由于气候噪声和潜在可预报性有季节和区域的差异,所以不能要求用一个气候模式在任何时候对每一地区都得到满意的结果。要对各月的气候进行预报,需根据不同月份至少不同季节建立区域气候模式可能更有发展前景。 相似文献
8.
文章介绍了1997年第22届气候诊断年会，着重讨论了如下5个问题：1997年的厄尔尼诺预报、年代际气候变率、美洲季风与亚洲季风、季度气候预测、气候可预报性研究。 相似文献
9.
根据辽宁省61个气象站1961—2020年逐日气温和降水量数据，对比分析1991—2020年和1981—2010年新旧气候平均值变化及对辽宁省气候业务的影响。结果表明：1—11月平均气温、平均最高气温、平均最低气温均升高；10—12月降水量增幅最大。年及四季平均气温、平均最高和最低气温均升高，增幅自东部和西部山区向中部平原地区增大，中部区域增幅最为显著；平均气温和平均最高气温均以春季增幅最大，平均最低气温夏季增幅最大。年、夏季和秋季降水量减少，春季和冬季增加；7—8月降水量总体减少，东部山区和大连沿海地区降水量增加；7月下旬—8月上旬降水量增加，辽宁西部和南部地区增幅最大，为5%～6%，北部地区增幅最小。气候平均值改变后，四季平均气温及降水量评价等级均发生了变化。 相似文献
10.
基于NCEP/NCAR再分析资料,利用信噪比(SNR)方法研究了南海夏季风强度潜在可预报性的年代际变化,结果表明:南海夏季风强度潜在可预报性在20世纪80年代出现了由潜在可预报性偏低位相向偏高位相的年代际转折。进一步的研究发现,南海夏季风强度潜在可预报性和东印度洋—西太平洋(EIOWP)的海表温度(SST)存在明显的正相关。当EIOWP区域SST年际变率较大时,对南海夏季风影响较强,使得南海夏季风的外部信号增强,从而提高了潜在可预报性;当EIOWP区域SST年际变率较小时,对南海夏季风影响较弱,南海夏季风的外部信号进而减弱,潜在可预报性降低。 相似文献
11.
Ian M. Ferguson Philip B. Duffy Thomas J. Phillips Xu Liang John A. Dracup Siegfried Schubert Philip Pegion 《Climate Dynamics》2011,36(3-4):739-752
In order to improve seasonal-to-interannual precipitation forecasts and their application by decision makers, there is a clear need to understand when, where, and to what extent seasonal precipitation anomalies are driven by potentially predictable surface–atmosphere interactions versus to chaotic interannual atmospheric dynamics. Using a simple Monte Carlo approach, interannual variability and linear trends in the SST-forced signal and potential predictability of boreal winter precipitation anomalies is examined in an ensemble of twentieth century AGCM simulations. Signal and potential predictability are shown to be non-stationary over more than 80% of the globe, while chaotic noise is shown to be stationary over most of the globe. Correlation analysis with respect to magnitudes of the four leading modes of global SST variability suggests that interannual variability and trends in signal and potential predictability over 35% of the globe is associated with ENSO-related SST variability; signal and potential predictability are not significantly associated with SST modes characterized by a global SST trend, North Atlantic SST variability, and North Pacific SST variability, respectively. Results suggest that mechanisms other than SST variability contribute to the non-stationarity of signal and noise characteristics of hydroclimatic variability over mid- and high-latitude regions. 相似文献
12.
David P. Rowell 《Climate Dynamics》2005,25(7-8):837-849
A scenario of European climate change for the late twenty-first century is described, using a high-resolution state-of-the-art
model. A time-slice approach is used, whereby the atmospheric general circulation model, HadAM3P, was integrated for two periods,
1960–1990 and 2070–2100, using the SRES A2 scenario. For the first time an ensemble of such experiments was produced, along
with appropriate statistical tests for assessing significance. The focus is on changes to the statistics of seasonal means,
and includes analysis of both multi-year means and interannual variance. All four seasons are assessed, and anomalies are
mapped for surface air temperature, precipitation and snow mass. Mechanisms are proposed where these are dominated by straightforward
local processes. In winter, the largest warming occurs over eastern Europe, up to 7°C, mean snow mass is reduced by at least
80% except over Scandinavia, and precipitation increases over all but the southernmost parts of Europe. In summer, temperatures
rise by 6–9°C south of about 50°N, and mean rainfall is substantially reduced over the same area. In spring and autumn, anomalies
tend to be weaker, but often display patterns similar to the preceding season, reflecting the inertia of the land surface
component of the climate system. Changes in interannual variance are substantial in the solsticial seasons for many regions
(note that for precipitation, variance estimates are scaled by the square of the mean). In winter, interannual variability
of near-surface air temperature is considerably reduced over much of Europe, and the relative variability of precipitation
is reduced north of about 50°N. In summer, the (relative) interannual variance of both variables increases over much of the
continent. 相似文献
13.
Estimating the potential predictability of Australian surface maximum and minimum temperature 总被引：1，自引：1，他引：0
A study is made of the potential predictability of seasonal means in Australian surface maximum and minimum temperature using
monthly data from December 1950 to November 2000. Because the usual assumption of stationarity cannot be applied to the observations
at all stations and for all seasons, a modification to an existing methodology is proposed. Here, we show that, to a first
order, monthly mean variances within a season can be modeled by a linear relationship, and inter-monthly correlations can
be assumed to be stationary. The intraseasonal component of variability can then be estimated using monthly data. Removing
the intraseasonal variance from the total interannual variance allows an estimate of the potential predictability to be made.
Surface maximum and minimum temperature has high potential predictability over most of northern Australia in the four main
seasons. However, there is high potential predictability only in some of the four seasons for the centre and south of Australia.
Surface minimum temperature is generally more potentially predictable than surface maximum temperature. The spatial and temporal
patterns of potential predictability are generally consistent with published patterns of hindcast skill from a statistical
forecast scheme. A comparison between the intraseasonal variance of Australian surface maximum and minimum temperature estimated
using the stationary variance assumption and the linear assumptions showed qualitatively and quantitatively similar patterns
of distribution. 相似文献
14.
15.
Response of the mean global vegetation distribution to interannual climate variability 总被引：1，自引：0，他引：1
Michael Notaro 《Climate Dynamics》2008,30(7-8):845-854
The impact of interannual variability in temperature and precipitation on global terrestrial ecosystems is investigated using
a dynamic global vegetation model driven by gridded climate observations for the twentieth century. Contrasting simulations
are driven either by repeated mean climatology or raw climate data with interannual variability included. Interannual climate
variability reduces net global vegetation cover, particularly over semi-arid regions, and favors the expansion of grass cover
at the expense of tree cover, due to differences in growth rates, fire impacts, and interception. The area burnt by global
fires is substantially enhanced by interannual precipitation variability. The current position of the central United States’
ecotone, with forests to the east and grasslands to the west, is largely attributed to climate variability. Among woody vegetation,
climate variability supports expanded deciduous forest growth and diminished evergreen forest growth, due to difference in
bioclimatic limits, leaf longevity, interception rates, and rooting depth. These results offer insight into future ecosystem
distributions since climate models generally predict an increase in climate variability and extremes.
CCR Contribution # 941 相似文献
16.
The role of spring Wyrtki jets in modulating the equatorial Indian Ocean and the regional climate is an unexplored problem. The source of interannual variability in the spring Wyrtki jets is explored in this study. The relationship between intraseasonal and interannual variability from 1958 to 2008 and its relation with Indian Summer Monsoon is further addressed. Analysis reveals that the interannual variability in spring Wyrtki jets is controlled significantly by their intraseasonal variations. These are mostly defined by a single intraseasonal event of duration 20 days or more which either strengthens or weakens the seasonal mean jet depending on its phase. The strong spring jets are driven by such intraseasonal westerly wind bursts lasting for 20-days or more, whereas the weak jets are driven by weaker intraseasonal westerlies. During the years of strong jets, the conventional westward phase propagation of Wyrtki jets is absent and instead there is an eastward phase propagation indicating the possible role of Madden Julian Oscillation (MJO) in strengthening the spring Wyrtki jets. These strong intraseasonal westerly wind bursts with eastward phase propagation during strong years are observed mainly in late spring and have implications on June precipitation over the Indian and adjoining land mass. Anomalously strong eastward jets accumulate warm water in the eastern equatorial Indian Ocean (EIO), leading to anomalous positive upper ocean heat content and supporting more local convection in the east. This induces subsidence over the Indian landmass and alters monsoon rainfall by modulating monsoon Hadley circulation. In case of weak current years such warm anomalies are absent over the eastern EIO. Variations in the jet strength are found to have strong impact on sea level anomalies, heat content, salinity and sea surface temperature over the equatorial and north Indian Ocean making it a potentially important player in the north Indian Ocean climate variability. 相似文献
17.
应用国家气候中心气候系统模式 (BCC_CSM1.0),在给定温室气体、太阳常数、硫酸盐气溶胶、火山灰等外强迫数据的条件下,对19世纪末到20世纪气候进行模拟。对降水模拟结果的检验表明:BCC_CSM1.0模式能够模拟出全球降水的基本气候状态、季节变化、季节内振荡、年际变化等特征。模拟结果显示:与CMAP及CRU观测分析资料相比基本一致,全球陆地降水在过去一个多世纪中存在上升趋势。同时,模式也存在不足和需要改进之处:模拟降水的时空分布与观测不一致;我国东部地区的雨带季节转变较观测偏快;主要雨带位置较观测偏西、偏北;夏季青藏高原东北侧有虚假的降水中心;热带季节内振荡较实际偏弱;降水年际变率较观测略大,主要发生在降水较明显的热带。BCC_CSM1.0模式模拟的全球陆地降水以及欧亚、亚洲、中国大陆 (中国东部、江南、华北等地区) 平均降水与近105年由观测所得的CRU资料基本一致,但多数地区比观测略偏低。模拟的全球陆地、中国东部、江南、华北等地区的降水趋势也与CRU资料一致;模拟的全球陆地降水在过去105年中有明显的上升趋势,与CRU资料相比,上升趋势更强,但在欧亚、亚洲、中国范围内模拟的降水趋势与观测有一定的差异。 相似文献
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19.
基于青藏高原春季感热异常信号的中国东部夏季降水统计预测模型 总被引：3，自引：0，他引：3
使用1980-2014年由青藏高原中东部的地面气象观测台站观测资料计算得到的地表感热通量以及中国东部高分辨率的降水格点资料,在年代际变化和年际变率两个时间尺度上,使用最大协方差分析方法研究了青藏高原春季感热与中国东部夏季6、7和8月降水的关系,基于最大协方差关联因子的时间尺度分解回归分析方法建立了一个降水统计预测模型。青藏高原春季感热的各个关联预报因子与中国东部夏季各月降水的相关分析表明,在年代际成分中,6、7和8月在中国东部绝大部分地区均存在显著相关,方差贡献分别为75.6%、99.9%和79.7%;在年际成分中,相关区域在6月是华南地区、华北沿海地区和江淮流域,7月是华南地区西南部、长江流域、东北地区东南部和黄河中下游地区,8月是东北地区和华南地区西部,方差贡献分别为42.7%、43.4%和32.0%。预测模型的解释方差分析和后报试验检验表明,7月对整个中国东部地区预测效果最好,6月主要在长江以南地区,而8月主要在东北地区和华南地区西部预测效果较好。该预测模型能很好描述青藏高原春季感热与中国东部夏季各月降水的关联性,并对局地降水实现较好的定量预测,具有在短期气候预测业务应用的价值。 相似文献