Slow response of surface water temperature to fast atmospheric variability reveals mixing heterogeneity in a deep lake

Marina Amadori*, Mariano Bresciani, Claudia Giardino, Henk A. Dijkstra

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Slow and long-term variations of sea surface temperature anomalies have been interpreted as a red-noise response of the ocean surface mixed layer to fast and random atmospheric perturbations. How fast the atmospheric noise is damped depends on the mixed layer depth. In this work we apply this theory to determine the relevant spatial and temporal scales of surface layer thermal inertia in lakes. We fit a first order auto-regressive model to the satellite-derived Lake Surface Water Temperature (LSWT) anomalies in Lake Garda, Italy. The fit provides a time scale, from which we determine the mixed layer depth. The obtained result shows a clear spatial pattern resembling the morphological features of the lake, with larger values (7.18± 0.3 m) in the deeper northwestern basin, and smaller values (3.18 ± 0.24 m) in the southern shallower basin. Such variations are confirmed by in-situ measurements in three monitoring points in the lake and connect to the first Empirical Orthogonal Function of satellite-derived LSWT and chlorophyll-a concentration. Evidence from our case study open a new perspective for interpreting lake-atmosphere interactions and confirm that remotely sensed variables, typically associated with properties of the surface layers, also carry information on the relevant spatial and temporal scales of mixed-layer processes.

Original languageEnglish
Article number8459
JournalScientific Reports
Volume14
Issue number1
DOIs
Publication statusPublished - Dec 2024

Bibliographical note

Publisher Copyright:
© The Author(s) 2024.

Funding

The authors are grateful to Elisa Calamita and Laura Carrea for insightful discussions, data and scripts sharing. This work is part of an ESA funded Climate Change Initiative project (Contract No. 40000125030/18/I-NB) that aims to exploit the long-term global Earth Observation record to produce Essential Climate Variables (ECVs) supporting the United Nations Framework Convention on Climate Change (UNFCCC).

FundersFunder number
United Nations Framework Convention on Climate Change
European Space Agency40000125030/18/I-NB

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