The Influence of Arctic-Lower-Latitude Interactions on Weather and Climate Variability: Mechanisms, Predictability, and Prediction

This file contains (metadata) information on the datasets created as well as those existing datasets and models used by the project indicated in the title. The overall goal of this collaborative project was to investigate the tropical and mid-latitude (collectively referred to as lower latitudes) oc...

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Bibliographic Details
Main Authors: Gokhan Danabasoglu, Young-Oh Kwon
Format: Dataset
Language:unknown
Published: Arctic Data Center 2023
Subjects:
Online Access:https://doi.org/10.18739/A24M91C1V
Description
Summary:This file contains (metadata) information on the datasets created as well as those existing datasets and models used by the project indicated in the title. The overall goal of this collaborative project was to investigate the tropical and mid-latitude (collectively referred to as lower latitudes) oceanic and atmospheric drivers of regional Arctic changes as well as the Arctic impacts on the Northern Hemisphere climate and weather variability, using a combination of available observations and state-of-the-art climate models, to improve our understanding of the fundamental dynamics, modeling capabilities, and capacity for prediction. The primary foci were on how the Arctic influences the lower latitude climate changes through atmospheric connections, and on evaluation of and enhancing capacity for seasonal-to-decadal predictions in the Arctic and over the Northern Hemisphere. To address the first focus area, we performed several sets of ensemble simulations using a state-of-the-art atmospheric model forced by different sea-ice and sea surface temperature conditions. We also performed additional sets of ensemble simulations with the Community Earth System Model (CESM) with the sea-ice conditions set to preindustrial, present day, and future conditions, respectively. For the second focus area, we used existing datasets from the Community Earth System Model version 1 (CESM1): CESM1 Large Ensemble and CESM1 Decadal Prediction Large Ensemble. The primary methods used include a maximum covariance analysis (MCA) to examine the lagged atmospheric circulation response to Arctic sea ice concentration variability at interannual time scales and a lead-time dependent drift removal method to extract anomalies to determine prediction skill.