We propose to use a hierarchy of GFDL high-resolution climate models to improve our understanding of the climate of the Caribbean Sea and Gulf of Mexico (“Intra-Americas Seas”, or “IAS”), including its influence on climate-scale variations and changes in Atlantic hurricane activity and North American drought. Because of the complex, mutli-scale oceanographic, atmospheric and coupled air-sea phenomena that characterize the IAS region, we will focus on both atmospheric and oceanic climate, and their interactions. We will explore the sensitivity of the simulation of the mean climate and climate variations in the IAS to changes in resolution and parameterization in the context of the coupled GFDL high-resolution models. The role of remote influences on climate in the IAS will be explored, assessing oceanic and atmospheric teleconnections by performing “data override” and “partial coupling” experiments with the climate models. Analogous perturbations to the coupled model will be used to explore the influence of the IAS on remote climate through atmospheric and oceanic processes. We will focus particularly on the influence of the IAS on North Atlantic hurricanes and on drought over North America. Predictability of the climate variations and teleconnections from the IAS will be explored using initialized prediction experiments using the GFDL high-resolution modeling system.
The principal hypotheses to be tested are i) increased resolution and high-order numerics in global coupled climate models improve simulation of mean climate and variations of the Intra-Americas Seas, ii) remote, large-scale factors (e.g., ENSO and the Atlantic Meridional Overturning Circulation) drive variations and changes in the IAS through atmospheric and oceanic bridges, iii) changes in oceanic circulation and atmospheric convection in the IAS have a detectable influence on remote oceanic and atmospheric conditions, iv) modeled climate variations in the IAS modulate North American drought and North Atlantic tropical cyclone activity in the North Atlantic, v) the improved representation of drivers of IAS variability (e.g., ENSO and AMM) and the mean climate of the IAS in higher resolution models leads to enhanced predictive capacity for regional climate due from initialization and response to radiative forcing. The proposed work should improve our understanding and ability to model a key area of the global climate system, and the model simulations performed in this study and analysis of them will be beneficial to the high-resolution climate model development.
Relevance to NOAA’s long-term goal and to the competition: This work will contribute to NOAA’s long-term goal of climate adaptation and mitigation through improving our ability to model, predict and understand climate extremes over North America. The IAS is a principal moisture source for rainfall over much of the southeastern and central US, provides a warm water energy source to tropical cyclones and is key in the development of tornadic activity over the US. Therefore improved understanding, modeling and prediction of this key region is necessary to understanding likely changes in droughts, landfalling tropical cyclones and tornadic activity over the US, and help inform adaptation strategies. Though the IAS is influential to climate and extremes, “state-of-the-art global models have very large mean bias and erroneous variability over the [IAS] region,” according to the IAS Climate Processes (IASCliP) Modeling Working Group (Misra et al. 2010). This proposal seeks to use higher resolution models to help remedy this important limitation to our current modeling capability.