This proposal outlines a collaborative effort by the national center for atmospheric research (ncar), texas a & m university (tamu), and the university of wisconsin at madison (UW) to advance…

This $419,055 federal Project Grant awarded by the National Oceanic and Atmospheric Administration (NOAA) under the Climate and Atmospheric Research program (CFDA 11.431) supports a collaborative research effort between the National Center for Atmospheric Research (NCAR), Texas A&M University, and the University of Wisconsin-Madison. The project aims to advance understanding of how increased model resolution can improve seasonal to decadal predictability of sea surface temperatures in the tropical Pacific and associated impacts on continental U.S. hydroclimate. The research will involve diagnostic analysis of existing high-resolution and coarse-resolution climate model simulations to isolate the processes and mechanisms that contribute to improved prediction skill at higher resolutions. This work is expected to guide future climate model and prediction system development efforts to extend seasonal to decadal predictability limits and provide more actionable climate science for decision-making.

This proposal outlines a collaborative effort by the national center for atmospheric research (ncar), texas a & m university (tamu), and the university of wisconsin at madison (UW) to advance understanding of deficient process representation in current coarse resolution climate prediction systems that results in an underestimation of predictability limits. This goal will be pursued by focusing on how increased model horizontal resolution improves prediction skill for sea surface temperature (SST) in the tropical pacific and, by extension, for hydroclimate over the continental united states. The proposal aims to build on recent advances in decadal climate prediction achieved through the use of a high-resolution configuration of the community earth system model (cesm), in which the ocean and atmosphere component models are run at ~10 KM and ~25 KM resolution, respectively. Preliminary hypotheses for why high resolution (HR) delivers improved prediction skill and signal-to-noise characteristics compared to low resolution (LR; ~100 KM resolution) will be explored through diagnostic analysis of existing HR and LR simulations. There are a number of relevant processes that may exhibit sensitivity to resolution that require an in-depth evaluation in existing HR and LR companion simulations, including: ocean heat uptake and transport, local coupled SST feedbacks (such as SST-cloud and windevaporation- SST feedbacks), and flow-topography interactions. Decadal prediction sensitivity experiments will be performed to isolate the skill impacts of increased resolution in the ocean and atmosphere, improved ocean initialization, and representation of the blocking effects of central and south american mountain ranges. Other experiments to isolate the role of particular processes will be designed as hypotheses become refined over the course of the project. The expected outcome of the project is a deeper understanding of which processes, in particular, require focused attention in order to extend seasonal to decadal predictability limits in standard (coarse) resolution prediction systems. The proposed work will improve US climate predictions and advance understanding of global climate variability and predictability by clarifying what mechanisms and processes must be well-represented to improve predictions of multiyear-to-decadal tropical pacific change. This project is directly in line with NOAA CPO program objectives as IT will guide model and prediction system development efforts needed to provide actionable climate science that informs decision making.