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

Author:

Skoglund Sophia K.1ORCID,Bah Abdou Rachid2,Norouzi Hamidreza23,Weathers Kathleen C.1ORCID,Ewing Holly A.4ORCID,Steele Bethel G.1ORCID,Bacon Linda C.5

Affiliation:

1. Cary Institute of Ecosystem Studies Millbrook New York USA

2. Earth and Environmental Sciences The Graduate Center of City University of New York (CUNY) New York New York USA

3. Department of Construction Management and Civil Engineering Technology New York City College of Technology, CUNY Brooklyn New York USA

4. Program in Environmental Studies Bates College Lewiston Maine USA

5. Maine Department of Environmental Protection Augusta Maine USA

Abstract

AbstractStudies 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.

Funder

National Science Foundation

Publisher

Wiley

Reference56 articles.

1. Auburn Water District/Lewiston Water Division (AWD/LWD) M. P.Dillingham L.Worthing D.Fortin C.Curtis M.Vashon andE.Kidd.2022.Ice Phenology Lake Auburn Maine USA 1836‐2022 ver 1. Environmental Data Initiative.https://doi.org/10.6073/pasta/b9ade8a730255643c0b8f58c92486704.

2. Extreme events, trends, and variability in Northern Hemisphere lake-ice phenology (1855–2005)

3. Lake ice phenology in Berlin-Brandenburg from 1947–2007: observations and model hindcasts

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