Approximation of ice phenology of Maine lakes using Aqua MODIS surface temperature data

IF 2.7 3区 环境科学与生态学 Q2 ECOLOGY
Ecosphere Pub Date : 2024-09-09 DOI:10.1002/ecs2.70000
Sophia K. Skoglund, Abdou Rachid Bah, Hamidreza Norouzi, Kathleen C. Weathers, Holly A. Ewing, Bethel G. Steele, Linda C. Bacon
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Abstract

Studies of lake ice phenology have historically relied on limited in situ data. Relatively few observations exist for ice out and fewer still for ice in, both of which are necessary to determine the temporal extent of ice cover. Satellite data provide an opportunity to better document patterns of ice phenology across landscapes and relate them to the climatological drivers behind changing ice phenology. We developed a model, the Cumulative Sum Method (CSM), that uses daytime and nighttime surface temperature observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor on board the Earth-observing Aqua satellite to approximate ice in (the onset of ice cover) and ice out from training datasets of 13 and 58 Maine lakes, respectively, during the 2002/2003 through 2017/2018 ice seasons. Ice in was signaled by reaching a threshold of cumulative negative degrees following the first day of the season below 0°C. Ice out was signaled by reaching a threshold of cumulative positive degrees following the first day of the year above 0°C. The comparison of observed and remotely sensed ice-in dates showed relative agreement with a correlation coefficient of 0.71 and a mean absolute error (MAE) of 9.8 days. Ice-out approximations had a correlation coefficient of 0.67 and an MAE of 8.8 days. Lakes smaller in surface area and nearer the Atlantic coast had the greatest error in approximation. Application of the CSM to 20 additional lakes in Maine produced a comparable ice-out MAE of 8.9 days. Ice-out model performance was weaker for the warmest years; there was a larger MAE of 12.0 days when the model was applied to the years 2019–2023 for the original 58 lakes. The development of this model, which utilizes daily satellite data, demonstrates the promise of remote sensing for quantifying ice phenology over short, temporal scales, and wider geographic regions than can be observed in situ, and allows exploration of the influence of surface temperature patterns on the process and timing of ice in and ice out.

Abstract Image

利用 Aqua MODIS 表面温度数据对缅因州湖泊冰层物候进行近似分析
对湖冰物候的研究历来依赖于有限的现场数据。出冰期的观测数据相对较少,入冰期的观测数据更少,而这两种观测数据都是确定冰盖时间范围所必需的。卫星数据提供了一个机会,可以更好地记录不同地貌的冰层物候模式,并将其与冰层物候变化背后的气候驱动因素联系起来。我们开发了一种累积总和法(CSM)模型,利用地球观测水卫星上的中分辨率成像分光仪(MODIS)传感器的昼夜表面温度观测数据,从 2002/2003 年至 2017/2018 年冰季期间缅因州 13 个湖泊和 58 个湖泊的训练数据集中分别推算出冰期(冰覆盖的开始)和冰期(冰覆盖的结束)。在冰季第一天气温低于 0°C 后,达到累计负温度阈值即为结冰。冰期结束的信号是在当年第一天气温超过 0°C 后达到累积正度数的临界值。对观测到的结冰日期和遥感到的结冰日期进行比较,结果显示两者相对吻合,相关系数为 0.71,平均绝对误差为 9.8 天。出冰近似值的相关系数为 0.67,平均绝对误差为 8.8 天。表面积较小且靠近大西洋海岸的湖泊的近似值误差最大。将 CSM 应用于缅因州的另外 20 个湖泊,可得出 8.9 天的冰期最大近似误差。最热年份的结冰模型性能较弱;将该模型应用于最初 58 个湖泊的 2019-2023 年时,最大近似误差为 12.0 天。该模型的开发利用了每日卫星数据,展示了遥感技术在短时间尺度和比现场观测更广的地理区域内量化冰层物候的前景,并可探索地表温度模式对冰层入冰和出冰过程和时间的影响。
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来源期刊
Ecosphere
Ecosphere ECOLOGY-
CiteScore
4.70
自引率
3.70%
发文量
378
审稿时长
15 weeks
期刊介绍: The scope of Ecosphere is as broad as the science of ecology itself. The journal welcomes submissions from all sub-disciplines of ecological science, as well as interdisciplinary studies relating to ecology. The journal''s goal is to provide a rapid-publication, online-only, open-access alternative to ESA''s other journals, while maintaining the rigorous standards of peer review for which ESA publications are renowned.
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