Models of daily rainfall cross-correlation for the United Kingdom
Models of daily rainfall cross-correlation for the United Kingdom
复制标题
英国每日降雨量互相关模型
DOI：
10.1016/j.envsoft.2013.06.001
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发表时间：
2013
影响因子：
4.9
通讯作者：
Burton A
中科院分区：
文献类型：
--
作者：
Burton A
非常需要能够生成当前时空天气情景或缩小尺度的未来气候预测的自动化易用工具。这些工具将极大地支持对城市基础设施、河流集水区和水资源等系统的危害、风险和可靠性的分析。然而，根据选定情景的特性自动设定这些模型的参数，需要对点和空间统计数据进行定性。虽然点的统计数据，如平均日降雨量，可以通过地图来描述，但空间属性，如互相关，根据一对样本点而变化，理想情况下，应该对每一对可能的位置都可用。对于这样的属性简单的自动表示需要为任何对location.To解决这个需要简单的经验模型开发的滞后零互相关距离（XCD）的英国日降雨量的属性。误差和一致性检查后，日降雨时间序列的1961-1990年期间，从143雨量计被用来计算观测XCD属性。一个三参数的双指数表达式，然后拟合到适当的数据分区假设各向同性和分段均匀XCD属性。开发了三种模型：1）国家季节模型; 2）按日历月划分的国家模型; 3）按英国9个气候区域和日历月划分的区域模型。这些模型提供了在英国的任何两个位置的滞后零互相关属性的估计。这些互相关模型可以促进自动化的空间降雨建模工具的发展。这是通过执行区域模型到一个空间建模框架，并通过应用到两个模拟域（均为10 000平方公里），一个在英格兰西北部和英格兰东南部。所需的点统计量一般都很好地模拟和一个很好的匹配之间发现模拟和观察XCD properties.The模型开发这里是简单的实现，包括数据误差的校正，预先计算的计算效率，提供平滑的样本变异所产生的零星覆盖的观察和可重复的。它们可用于参数化空间降雨模型在英国和方法很可能是很容易适应世界其他地区。
Automated easy-to-use tools capable of generating spatial-temporal weather scenarios for the present day or downscaled future climate projections are highly desirable. Such tools would greatly support the analysis of hazard, risk and reliability of systems such as urban infrastructure, river catchments and water resources. However, the automatic parameterization of such models to the properties of a selected scenario requires the characterization of both point and spatial statistics. Whilst point statistics, such as the mean daily rainfall, may be described by a map, spatial properties such as cross-correlation vary according to a pair of sample points, and should ideally be available for every possible pair of locations. For such properties simple automatic representations are needed for any pair of locations.To address this need simple empirical models are developed of the lag-zero cross-correlation-distance (XCD) properties of United Kingdom daily rainfall. Following error and consistency checking, daily rainfall timeseries for the period 1961–1990 from 143 raingauges are used to calculate observed XCD properties. A three parameter double exponential expression is then fitted to appropriate data partitions assuming isotropic and piecewise-homogeneous XCD properties. Three models are developed: 1) a national aseasonal model; 2) a national model partitioned by calendar month; and 3) a regional model partitioned by nine UK climatic regions and by calendar month. These models provide estimates of lag-zero cross-correlation properties of any two locations in the UK.These cross-correlation models can facilitate the development of automated spatial rainfall modelling tools. This is demonstrated through implementation of the regional model into a spatial modelling framework and by application to two simulation domains (both ∼10,000 km2), one in north-west England and one in south-east England. The required point statistics are generally well simulated and a good match is found between simulated and observed XCD properties.The models developed here are straightforward to implement, incorporate correction of data errors, are pre-calculated for computational efficiency, provide smoothing of sample variability arising from sporadic coverage of observations and are repeatable. They may be used to parameterise spatial rainfall models in the UK and the methodology is likely to be easily adaptable to other regions of the world.
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DOI：
10.1002/joc.1160
发表时间：
2005
期刊：
International Journal of Climatology
影响因子：
--
作者：
M. Perry;D. Hollis
通讯作者：
D. Hollis
DOI：
10.1016/j.envsoft.2008.04.003
发表时间：
2008-12
期刊：
Environ. Model. Softw.
影响因子：
--
作者：
A. Burton;C. Kilsby;H. Fowler;P. Cowpertwait;P. O'Connell
通讯作者：
A. Burton;C. Kilsby;H. Fowler;P. Cowpertwait;P. O'Connell
用于评估气候变化下城市洪水灾害的随机降雨模型
DOI：
--
发表时间：
2010
期刊：
BHS Third International Symposium, Managing Consequences of a Changing Global Environment
影响因子：
--
作者：
Burton A
通讯作者：
Burton A
1961-2009 年英国极端降雨的更新区域频率分析
DOI：
--
发表时间：
2010
期刊：
影响因子：
--
作者：
Mervyn Jones;H. Fowler;C. Kilsby;S. Blenkinsop
通讯作者：
S. Blenkinsop
在多个地点生成降雨量和温度情景：来自地中海的示例
DOI：
--
发表时间：
2002
期刊：
影响因子：
--
作者：
J. Palutikof;C. Goodess;S. Watkins;T. Holt
通讯作者：
T. Holt