Validation of lacustrine proxy system modeling for Arctic lakes
Abstract
Lake sediments are widespread archives of multivariate Arctic climate data. Lacustrine proxies, which indirectly record multiple climate-influenced aspects of lake environments, can be directly compared to climate model output using physically based proxy system models (PSMs). If well tuned, PSMs can also be used to place quantitative constraints on the climate variables causing past proxy changes. However, lake PSMs, which incorporate the general physics common to most lakes, have not been extensively validated at high latitudes, where lakes are defined by strong seasonality and compressed periods of hydrological activity and proxy synthesis. Furthermore, the remote nature of the Arctic means that many lakes from which paleoclimate proxy records are generated have little long-term observational data, preventing robust validation of modern PSM simulations and hindering the application of PSMs to the interpretation of paleoclimate records. Here, we evaluate the performance of a lake model for three relatively well-monitored Arctic lakes located in western Svalbard, western Greenland, and northern Alaska. We model daily-resolution lake water temperatures, hydrologic balance, and lake water isotopes through recent decades, forced by 6-hourly resolution ERA-5 climate variables and precipitation isotope values from the Online Isotopes in Precipitation Calculator (OIPC). We quantitatively assess model performance through comparison of model output to time series of lake temperature and water level, and intermittent measurements of lake water isotopes. For each lake, we perform a suite of sensitivity tests in which we vary the values of poorly constrained settings within the model and runoff parameterization using a Latin Hypercube approach. Based on these analyses, we provide recommendations for which modern measurements are most essential to collect in the field when coring remote and unmonitored Arctic lakes for paleoclimate records in order to facilitate tuning the PSM.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2021
- Bibcode:
- 2021AGUFMPP55A0639C