Uncrewed surface vehicles (USVs) called Saildrones have been utilized to collect in situ meteorological observations at the air-sea interface in the Arctic, a rapidly changing region where obtaining ground truth data is challenging. Air-sea fluxes of latent and sensible heat are important components of the positive feedback loop involving sea ice melt and higher ocean temperatures. However, little work has been done to validate Arctic fluxes in numerical models with ground truth data. This research compares USV data with forecasts generated by the Global Forecast System (GFS) and Global Ensemble Forecast System (GEFS). The analysis of latent and sensible heat fluxes, along with their related state variables, assesses the accuracy of predictions by the GFS and GEFS products and reveals insights into sources of error in flux predictions. Surprising differences between deterministic and ensemble model errors indicate that Arctic forecasts may be particularly sensitive to certain model attributes. The study identifies biases in the models and highlights potential areas for forecast improvement, informing how better predictions of the Arctic environment can be developed.
Speaker Bio
Hope Hunter is a third-year EWES PhD student working in Dr. Hannah Horowitz’s group. She received her B.A. in Mathematics from the College of Wooster. Her research aims to gain insights into the changing Arctic atmosphere through the analysis of observational data, integrating measurements across modalities and resolutions. Other research interests of hers include developing statistical methodologies for spatiotemporal data analysis, model validation, and promoting Indigenous data sovereignty.
