The summer Asia–North America teleconnection and its modulation by ENSO in Community Atmosphere Model, version 5 (CAM5)

Kelsey Malloy,Ben P Kirtman

doi:10.1007/s00382-022-06205-4

Abstract

Seasonal forecasts of summer continental United States (CONUS) rainfall have relatively low skill, partly due to a lack of consensus about its sources of predictability. The East Asian monsoon (EAM) can excite a cross-Pacific Rossby wave train, also known as the Asia–North America (ANA) teleconnection. In this study, we analyze the ANA teleconnection in observations and model simulations from the Community Atmospheric Model, version 5 (CAM5), comparing experiments with prescribed climatological SSTs and prescribed observed SSTs. Observations indicate a statistically significant relationship between a strong EAM and increased probability of positive precipitation anomalies over the US west coast and the Plains-Midwest. The ANA teleconnection and CONUS rainfall patterns are improved in the CAM5 experiment with prescribed observed SSTs, suggesting that SST variability is necessary to simulate this teleconnection over CONUS. We find distinct ANA patterns between ENSO phases, with the La Niña-related patterns in CAM5 disagreeing with observations. Using linear steady-state quasi-geostrophic theory, we conclude that incorrect EAM forcing location greatly contributed to CAM5 biases, and jet stream disparities explained the ENSO-related biases. Finally, we compared EAM forcing experiments with different mean states using a simple dry nonlinear atmospheric general circulation model. Overall, the ANA pattern over CONUS and its modulation by ENSO forcing are well described by dry dynamics on seasonal-to-interannual timescales, including the constructive (destructive) interference between El Niño (La Niña) modulation and the ANA patterns over CONUS.

Highlights

The agricultural sector, water resource managers, and other preparedness agencies desire monthly-to-seasonal rainfall forecasts for their decision-making, including for many vulnerable regions of the continental United States (CONUS), such as the western U.S and Great Plains.there has been marginal success in providing reliable long-range forecasts of precipitation in the warm season (Becker et al 2014; Slater et al 2016; Hao et al 2018; Malloy and Kirtman 2020), mostly due to relatively weak atmospheric flow as well as weaker signals from El Niño-Southern Oscillation (ENSO) and the Madden-Julian Oscillation (MJO; Trenberth et al 1998; Zhou et al 2012; Tian et al 2017; Jha et al 2019; Hu et al 2020)
Note that we tested strong – weak East Asian monsoon (EAM) by running an experiment with positive heating forcing and an experiment with negative heating in EAM location. They have been excluded for the sake of brevity. We address both indirect and direct ENSO modulation to the EAM-forced response as we did with the linear QG solutions: Indirect ENSO modulation was assessed by adjusting the observed and CAM5_obsSST mean state based on surface temperature climatology composited during El Niño or La Niña months, and direct ENSO modulation was assessed by running experiments with both ENSO-related forcing and EAM forcing and subtracting that response by the original EAM-forced response
CAM5_obsSST simulation, F was conditioned on ENSO phase before solving for the Z250 response, i.e. F was input as the strong – weak EAM DIV250 anomaly during El Niño or La

Summary

Introduction

The agricultural sector, water resource managers, and other preparedness agencies desire monthly-to-seasonal rainfall forecasts for their decision-making, including for many vulnerable regions of the continental United States (CONUS), such as the western U.S and Great Plains. To understand the indirect ENSO influence on the ANA pattern in observations and the CAM5_obsSST simulation, F was conditioned on ENSO phase before solving for the Z250 response, i.e. F was input as the strong – weak EAM DIV250 anomaly during El Niño or La. Niña. Because this is a dry model, we can consider the time-mean DIV250 response (right column) as a proxy for large-scale precipitation patterns associated with the heating forcing. CONUS patterns in the dry AGCM with the CAM5_obsSST mean state are not simulated well, perhaps emphasizing the differences in the important processes behind the ANA pattern in observations and CAM5

Summary and Discussion

Findings

Data Availability Statement