Estimation of the mean depth of boreal lakes for use in numerical weather prediction and climate modelling
Estimation of the mean depth of boreal lakes for use in numerical weather prediction and climate modelling
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DOI：
10.3402/tellusa.v66.21510
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发表时间：
2014-01-01
影响因子：
2
通讯作者：
Doganovsky, Arkady
中科院分区：
文献类型：
--
作者：
Choulga, Margarita;Kourzeneva, Ekaterina;Doganovsky, Arkady
湖泊影响大气边界层的结构，从而影响当地天气和气候。数值天气预报和气候模式应通过参数化考虑它们的影响。为了参数化，还需要模型外部的湖泊特征数据。最重要的参数是湖的深度。全球湖泊深度数据库GLDB（Global Lake Database）是为数值预报和气候模拟中的湖泊参数化而开发的。本研究的主要目的是通过间接估计北方地区湖泊的平均深度来升级GLDB，这取决于它们的地质起源。为此，使用了构造板块图、地质地貌图和第四纪沉积物图。通过一种创新的算法对地图数据进行处理，得出了141个被认为具有类似起源的湖泊的地质区域。为了获得每个选定区域的典型平均湖深，从全球土地退化数据库获得并分析了统计数据。该研究的主要成果是一个新版本的GLDB与典型的平均湖深的估计包括在内。该产品的潜在用户是数值预报和气候模式。
Lakes influence the structure of the atmospheric boundary layer and, consequently, the local weather and local climate. Their influence should be taken into account in the numerical weather prediction (NWP) and climate models through parameterisation. For parameterisation, data on lake characteristics external to the model are also needed. The most important parameter is the lake depth. Global database of lake depth GLDB (Global Lake Database) is developed to parameterise lakes in NWP and climate modelling. The main purpose of the study is to upgrade GLDB by use of indirect estimates of the mean depth for lakes in boreal zone, depending on their geological origin. For this, Tectonic Plates Map, geological, geomorphologic maps and the map of Quaternary deposits were used. Data from maps were processed by an innovative algorithm, resulting in 141 geological regions where lakes were considered to be of kindred origin. To obtain a typical mean lake depth for each of the selected regions, statistics from GLDB were gained and analysed. The main result of the study is a new version of GLDB with estimations of the typical mean lake depth included. Potential users of the product are NWP and climate models.