Towards operational joint river flow and precipitation ensemble verification: considerations and strategies given limited ensemble records
Towards operational joint river flow and precipitation ensemble verification: considerations and strategies given limited ensemble records
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面向业务联合河流流量和降水集合验证：考虑到有限集合记录的考虑因素和策略
DOI：
10.1016/j.jhydrol.2019.123966
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发表时间：
2019
影响因子：
6.4
通讯作者：
Anderson S
中科院分区：
文献类型：
--
作者：
Anderson S
联合验证的河流流量和降水合奏框架的开发和演示英国最终用于业务洪水预报设置。河流流量集合是从分布式水文模型（G2 G模型）中获得的，使用15分钟降水累积的集合作为1 km网格的输入。降水集合包括来自气象局统一模型的业务数值天气预报（NWP）预报。每小时和每日的降水积累进行了验证，并讨论了定时误差和水文响应的背景下，不同的积累期的相关性。降水观测误差的影响进行了研究，通过比较雨量计和雷达派生的降水估计的验证结果。核查的挑战，只使用有限的记录降水合奏，从一个系统，最近才开始运作，得到解决。在现有总体数据的情况下，介绍了获得更可靠的核查统计数据的方法，并以2015年12月为例进行了演示。对于降水，使用百分位阈值来确保给定数量的阈值交叉事件，以便使用列联表和导出的技能分数进行分析。对于河流流量，洪水阈值与业务洪水指导的相关性较小。相反，给定的罕见性（重现期）的流量阈值的波动被用作洪水严重程度的替代措施。在区域尺度上，河流流量和降水验证分析被认为是依赖于所考虑的位置。这与降水量的变化有关。对于河流，集水特性-特别是集水面积-被认为是核查的关键影响因素。它演示了如何使用这种行为，以获得更强大的河流流量验证统计在次区域尺度。
A framework for joint verification of river flow and precipitation ensembles is developed and demonstrated over Britain for eventual use in an operational flood forecasting setting. The river flow ensembles are obtained from a distributed hydrological model, the G2G model, using an ensemble of 15 min precipitation accumulations as input on a 1 km grid. The precipitation ensemble consists of operational Numerical Weather Prediction (NWP) forecasts from the Met Office Unified Model. Both hourly and daily precipitation accumulations are verified, and the relevance of different accumulation periods discussed in the context of timing errors and hydrological response. The implications of precipitation observation error are investigated by comparing verification results from raingauge- and radar-derived precipitation estimates. Challenges of verification using only a limited record of precipitation ensembles, from a system only relatively recently made operational, are addressed. Methods of obtaining more robust verification statistics, given the available ensembles, are presented and demonstrated for an example period in December 2015. For precipitation, percentile thresholds are used to ensure a given number of threshold crossing events for analysis using a contingency table and derived skill scores. For river flow, percentiles thresholds are of less relevance to operational flood guidance. Instead, exceedance of a flow threshold of given rarity (return-period) is used as a surrogate measure of flood severity. At the regional scale, both river flow and precipitation verification analyses are found to be dependent on the locations considered. This is linked to variations in precipitation amount. For river flows, catchment properties – and in particular catchment size – are found to be a key influence on verification. It is demonstrated how such behaviour can be used to obtain more-robust river flow verification statistics at sub-regional scales.
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影响因子：
3
作者：
J. Thielen;J. Schaake;R. Hartman;R. Buizza
通讯作者：
J. Thielen;J. Schaake;R. Hartman;R. Buizza
DOI：
--
发表时间：
2016-12
期刊：
--
影响因子：
--
作者：
T. Marsh;C. Kirby;K. Muchan;L. Barker;E. Henderson;J. Hannaford
通讯作者：
T. Marsh;C. Kirby;K. Muchan;L. Barker;E. Henderson;J. Hannaford
影响因子：
6.4
作者：
Bell, V. A.;Kay, A. L.;Reynard, N. S.
通讯作者：
Reynard, N. S.
DOI：
--
发表时间：
2017
期刊：
影响因子：
--
作者：
M. Mittermaier;G. Csima
通讯作者：
G. Csima
英国和爱尔兰新的极端月降雨量总计：2015 年 12 月
DOI：
--
发表时间：
2016
期刊：
影响因子：
--
作者：
S. Burt
通讯作者：
S. Burt