Seasonal forecast skill of upper-ocean heat content in coupled high-resolution systems.

Autor(en)

Ronan McAdam, Simona Masina, Magdalena Balmaseda, Silvio Gualdi, Retish Senan, Michael Mayer

Abstrakt

Ocean heat content (OHC) anomalies typically persist for several months, making this variable a vital component of seasonal predictability in both the ocean and the atmosphere. However, the ability of seasonal forecasting systems to predict OHC remains largely untested. Here, we present a global assessment of OHC predictability in two state-of-the-art and fully-coupled seasonal forecasting systems. Overall, we find that dynamical systems make skilful seasonal predictions of OHC in the upper 300 m across a range of forecast start times, seasons and dynamical environments. Predictions of OHC are typically as skilful as predictions of sea surface temperature (SST), providing further proof that accurate representation of subsurface heat contributes to accurate surface predictions. We also compare dynamical systems to a simple anomaly persistence model to identify where dynamical systems provide added value over cheaper forecasts; this largely occurs in the equatorial regions and the tropics, and to a greater extent in the latter part of the forecast period. Regions where system performance is inadequate include the sub-polar regions and areas dominated by sharp fronts, which should be the focus of future improvements of climate forecasting systems.

Organisation(en)

Institut für Meteorologie und Geophysik

Externe Organisation(en)

Euro-Mediterranean Centre for Climate Change (CMCC), European Centre for Medium-Range Weather Forecasts (ECMWF)

Journal

Climate Dynamics

Band

58

Seiten

3335-3350

Anzahl der Seiten

16

ISSN

0930-7575

DOI

https://doi.org/10.1007/s00382-021-06101-3

Publikationsdatum

01-2022

Peer-reviewed

Ja

ÖFOS 2012

105206 Meteorologie

Schlagwörter

Link zum Portal

https://ucrisportal.univie.ac.at/de/publications/seasonal-forecast-skill-of-upperocean-heat-content-in-coupled-highresolution-systems(cd59cf89-617d-4dfe-9182-bd926789759e).html