Ocean variability is a dominant source of remote rainfall predictability, but in many cases the physical mechanisms driving this predictability are not fully understood. This study examines how ocean mesoscales (i.e., the Gulf Stream SST front) affect decadal southeast US (SEUS) rainfall, arguing that the local imprint of large-scale…

In the South Pacific Ocean, upper and lower Circumpolar Deep Water (UCDW and LCDW, respectively) occupy the deep layers; however, the presence and fate of these two water masses in the western equatorial Pacific have been mostly based on sparse measurements in both space and time. In this study, unprecedented deep measurements from three…

Understanding the root causes of forecast errors and occasional very poor forecasts is essential but difficult. In this paper we investigate the relative importance of initial conditions and model formulation for medium‐range errors in 500 hPa geopotential height. The question is addressed by comparing forecasts produced with ECMWF‐IFS and NCEP…

Intermittent transitions between turbulent and nonturbulent states are ubiquitous in the stable atmospheric surface layer (ASL). Data from two field experiments in Utqiaġvik, Alaska, and from direct numerical simulations are used to probe these state transitions so as to (i) identify statistical metrics for the detection of intermittency, (ii)…

General circulation models use subgrid‐scale (SGS) parameterizations to represent the effects of unresolved mesoscale eddies on large‐scale motions. Most of the current SGS parameterizations are based on a theoretical understanding of transient eddies, where the mean flow is a temporal average. In this work, we use a spatial filtering analysis…

Climate change is warming the ocean and impacting lower trophic level (LTL) organisms. Marine ecosystem models can provide estimates of how these changes will propagate to larger animals and impact societal services such as fisheries, but at present these estimates vary widely. A better understanding of what drives this inter-model variation…

Motivated by the ongoing debates about the relative contribution of specific North African dust sources to the transatlantic dust transport to the Amazon Basin, the current study integrates a suite of satellite observations into a novel trajectory analysis framework to investigate dust transport from the leading two North African dust sources,…

A review of the experimental protocol and motivation for DYAMOND, the first intercomparison project of global storm-resolving models, is presented. Nine models submitted simulation output for a 40-day (1 August–10 September 2016) intercomparison period. Eight of these employed a tiling of the sphere that was uniformly less than 5 km. By…

Improving the seasonal prediction of tropical cyclone (TC) activity demands a robust analysis of the prediction skill and the inherent predictability of TC activity. Using the resampling technique, this study analyzes a state‐of‐the‐art prediction system and offers a robust assessment of when and where the seasonal prediction of TC activity is…

Climate models often show errors in simulating and predicting tropical cyclone (TC) activity, but the sources of these errors are not well understood. This study proposes an evaluation framework and analyzes three sets of experiments conducted using a seasonal prediction model developed at the Geophysical Fluid Dynamics Laboratory (GFDL). These…