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Evaluation of the albedo parameterization of the Canadian Lake Ice Model and MODIS albedo products during the ice cover season

机译:在冰盖季节评估加拿大湖冰模型和MODIS反照率产品的反照率参数

摘要

Snow and lake ice have very high albedos compared to other surfaces found in nature. Surface albedo is an important component of the surface energy budget especially when albedos are high since albedo governs how much shortwave radiation is absorbed or reflected at a surface. In particular, snow and lake ice albedos have been shown to affect the timing of lake ice break-up. Lakes are found throughout the Northern Hemisphere and lake ice has been shown to be sensitive to climatic variability. Therefore, the modelling of lake ice phenology, using lake ice models such as the Canadian Lake Ice Model (CLIMo), is important to the study of climatic variability in the Arctic and sub-Arctic regions and accurate snow and lake ice albedo measurements are required to ensure the accuracy of the simulations. However, snow and lake ice albedo can vary from day-to-day depending on factors such as air temperature, presence of impurities, age, and composition. Some factors are more difficult than others to model (e.g. presence of impurities). It would be more straight forward to just gather field measurements, but such measurements would be costly and lakes can be in remote locations and difficult to access. Instead, CLIMo contains an albedo parameterization scheme that models the evolution of snow and lake ice albedo in its simulations. However, parts of the albedo parameterization are based on sea-ice observations (which inherently have higher albedos due to brine inclusions) and the albedo parameterization does not take ice type (e.g. clear ice or snow ice) into account. Satellite remote sensing via the Moderate Resolution Imaging Spectroradiometer (MODIS) provides methods for retrieving albedo that may help enhance CLIMo’s albedo parameterization.CLIMo’s albedo parameterization as well the MODIS daily albedo products (MOD10A1 and MYD10A1) and 16-day product (MCD43A3) were evaluated against in situ albedo observations made over Malcolm Ramsay Lake near Churchill, Manitoba, during the winter of 2012. It was found that the snow albedo parameterization of CLIMo performs well when compared to average in situ observations, but the bare ice parameterization overestimated bare ice albedo observations. The MODIS albedo products compared well when evaluated against the in situ albedo observations and were able to capture changes in albedo throughout the study period. The MODIS albedo products were also compared against CLIMo’s melting ice parameterization, because the equipment had to be removed from the lake to prevent it from falling into the water during the melt season. Cloud cover interfered with the MODIS observations, but the comparison suggests that MODIS albedo products retrieved higher albedo values than the melting ice parameterization of CLIMo. The MODIS albedo products were then integrated directly into CLIMo in substitution of the albedo parameterization to see if they could enhance break-up date (ice off) simulations. MODIS albedo retrievals (MOD10A1, MYD10A1, and MCD43A3) were collected over Back Bay, Great Slave Lake (GSL) near Yellowknife, Northwest Territories, from 2000-2011. CLIMo was then run with and without the MODIS albedos integrated and compared against MODIS observed break-up dates. Simulations were also run under three difference snow cover scenarios (0%, 68%, and 100% snow cover). It was found that CLIMo without MODIS albedos performed better with the 0% snow cover scenario than with the MODIS albedos integrated in. Both simulations (with and without MODIS albedos) performed well with the snow cover scenarios. The MODIS albedo products slightly improved CLIMo break-up simulations when integrated up to a month in advance of actual lake ice break-up for Back Bay. With the MODIS albedo products integrated into CLIMo, break-up dates were simulated within 3-4 days of MODIS observed break-up. CLIMo without the MODIS albedos still performed very well simulating break-up within 4-5 days of MODIS observed break-up. It is uncertain whether this was a significant improvement or not with such a small study period and with the investigation being conducted at a single site (Back Bay). However, it has been found that CLIMo performs well with the original albedo parameterization and that MODIS albedos could potentially complement lake-wide break-up simulations in future studies.
机译:与自然界中的其他表面相比,雪和湖冰的反照率非常高。表面反照率是表面能收支的重要组成部分,特别是当反照率很高时,因为反照率决定着表面吸收或反射了多少短波辐射。特别是,雪和湖冰反照率已显示出会影响湖冰破裂的时间。在整个北半球都发现了湖泊,湖冰已显示出对气候变化敏感。因此,使用诸如加拿大湖冰模型(CLIMo)之类的湖冰模型对湖冰物候进行建模,对于研究北极和亚北极地区的气候变异性至关重要,因此需要准确的雪和湖冰反照率测量值以确保仿真的准确性。但是,雪和湖冰的反照率每天可能会变化,具体取决于诸如气温,杂质的存在,年龄和成分等因素。有些因素比其他因素更难建模(例如,杂质的存在)。仅收集现场测量值会更直接,但是这样的测量值会很高,并且湖泊可能位于偏远地区并且难以进入。相反,CLIMo包含一个反照率参数化方案,该方案在其模拟中模拟了雪和湖冰反照率的演变。但是,反照率参数化的某些部分基于海冰观测值(由于盐水夹杂物,其固有地具有更高的反照率),并且反照率参数化未考虑冰类型(例如,晴冰或雪冰)。通过中等分辨率成像光谱仪(MODIS)进行的卫星遥感提供了检索反照率的方法,这些方法可能有助于增强CLIMo的反照率参数设置。针对2012年冬季在马尼托巴省丘吉尔附近的马尔科姆·拉姆齐湖进行的原位反照率观测,评估了CLIMo的反照率参数化以及MODIS每日反照率产品(MOD10A1和MYD10A1)和16天产品(MCD43A3)。与平均原位观测值相比,CLIMo的雪反照率参数设置表现良好,但是裸冰参数设置高估了裸冰反照率观测值。当与原位反照率观测值进行评估时,MODIS反照率产品比较好,并且能够在整个研究期间捕获反照率的变化。 MODIS反照率产品也与CLIMo的融冰参数进行了比较,因为必须将设备从湖泊中移出以防止在融化季节掉入水中。云盖干扰了MODIS的观测,但是比较表明,MODIS反照率产品的反照率值高于CLIMo的融冰参数化。然后将MODIS反照率产品直接集成到CLIMo中,以代替反照率参数化,以查看它们是否可以增强分手日期(冰消融)模拟。从2000年至2011年,在西北地区耶洛奈夫附近的大奴湖(GSL)后湾上收集了MODIS反照率取反(MOD10A1,MYD10A1和MCD43A3)。然后在集成和不集成MODIS反射率的情况下运行CLIMo,并与观察到的MODIS分手日期进行比较。在三种不同的积雪场景(0%,68%和100%积雪)下也进行了模拟。结果发现,在没有MODIS反射率的情况下,CLIMo在0%积雪情况下的性能要优于在其中集成MODIS反射率的情况。两种模拟(有和没有MODIS反射率)在积雪情况下均表现良好。当与后海湾的实际湖冰破裂提前一个月集成时,MODIS反照率产品会稍微改善CLIMO破裂模拟。通过将MODIS反照率产品集成到CLIMo中,可以在MODIS观察到的破裂后3-4天内模拟破裂日期。没有MODIS反射率的CLIMo在观察到MODIS的破裂后4-5天内仍能很好地模拟破裂。在如此短的研究期间内,并在单个站点(后湾)进行调查,尚不确定这是否是一项重大改进。但是,已经发现CLIMo在原始反照率参数化方面表现良好,而MODIS反照率可能会在未来的研究中补充整个湖面的破碎模拟。

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    Svacina Nicolas Andreas;

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  • 年度 2013
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