Search Results

You are looking at 1 - 4 of 4 items for :

  • Author or Editor: Tom Delworth x
  • Journal of Climate x
  • All content x
Clear All Modify Search
Tom Delworth
Full access
Yong-Fei Zhang, Mitchell Bushuk, Michael Winton, Bill Hurlin, Xiaosong Yang, Tom Delworth, and Liwei Jia


The current GFDL seasonal prediction system achieved retrospective sea ice extent (SIE) skill without direct sea ice data assimilation. Here we develop sea ice data assimilation, shown to be a key source of skill for seasonal sea ice predictions, in GFDL’s next-generation prediction system, the Seamless System for Prediction and Earth System Research (SPEAR). Satellite sea ice concentration (SIC) observations are assimilated into the GFDL Sea Ice Simulator version 2 (SIS2) using the ensemble adjustment Kalman filter (EAKF). Sea ice physics is perturbed to form an ensemble of ice–ocean members with atmospheric forcing from the JRA-55 reanalysis. Assimilation is performed every 5 days from 1982 to 2017 and the evaluation is conducted at pan-Arctic and regional scales over the same period. To mitigate an assimilation overshoot problem and improve the analysis, sea surface temperatures (SSTs) are restored to the daily Optimum Interpolation Sea Surface Temperature version 2 (OISSTv2). The combination of SIC assimilation and SST restoring reduces analysis errors to the observational error level (~10%) from up to 3 times larger than this (~30%) in the free-running model. Sensitivity experiments show that the choice of assimilation localization half-width (190 km) is near optimal and that SIC analysis errors can be further reduced slightly either by reducing the observational error or by increasing the assimilation frequency from every 5 days to daily. A lagged-correlation analysis suggests substantial prediction skill improvements from SIC initialization at lead times of less than 2 months.

Restricted access
Yohan Ruprich-Robert, Rym Msadek, Frederic Castruccio, Stephen Yeager, Tom Delworth, and Gokhan Danabasoglu


The climate impacts of the observed Atlantic multidecadal variability (AMV) are investigated using the GFDL CM2.1 and the NCAR CESM1 coupled climate models. The model North Atlantic sea surface temperatures are restored to fixed anomalies corresponding to an estimate of the internally driven component of the observed AMV. Both models show that during boreal summer the AMV alters the Walker circulation and generates precipitation anomalies over the whole tropical belt. A warm phase of the AMV yields reduced precipitation over the western United States, drier conditions over the Mediterranean basin, and wetter conditions over northern Europe. During boreal winter, the AMV modulates by a factor of about 2 the frequency of occurrence of El Niño and La Niña events. This response is associated with anomalies over the Pacific that project onto the interdecadal Pacific oscillation pattern (i.e., Pacific decadal oscillation–like anomalies in the Northern Hemisphere and a symmetrical pattern in the Southern Hemisphere). This winter response is a lagged adjustment of the Pacific Ocean to the AMV forcing in summer. Most of the simulated global-scale impacts are driven by the tropical part of the AMV, except for the winter North Atlantic Oscillation–like response over the North Atlantic–European region, which is driven by both the subpolar and tropical parts of the AMV. The teleconnections between the Pacific and Atlantic basins alter the direct North Atlantic local response to the AMV, which highlights the importance of using a global coupled framework to investigate the climate impacts of the AMV. The similarity of the two model responses gives confidence that impacts described in this paper are robust.

Full access
Siegfried Schubert, David Gutzler, Hailan Wang, Aiguo Dai, Tom Delworth, Clara Deser, Kirsten Findell, Rong Fu, Wayne Higgins, Martin Hoerling, Ben Kirtman, Randal Koster, Arun Kumar, David Legler, Dennis Lettenmaier, Bradfield Lyon, Victor Magana, Kingtse Mo, Sumant Nigam, Philip Pegion, Adam Phillips, Roger Pulwarty, David Rind, Alfredo Ruiz-Barradas, Jae Schemm, Richard Seager, Ronald Stewart, Max Suarez, Jozef Syktus, Mingfang Ting, Chunzai Wang, Scott Weaver, and Ning Zeng


The U.S. Climate Variability and Predictability (CLIVAR) working group on drought recently initiated a series of global climate model simulations forced with idealized SST anomaly patterns, designed to address a number of uncertainties regarding the impact of SST forcing and the role of land–atmosphere feedbacks on regional drought. The runs were carried out with five different atmospheric general circulation models (AGCMs) and one coupled atmosphere–ocean model in which the model was continuously nudged to the imposed SST forcing. This paper provides an overview of the experiments and some initial results focusing on the responses to the leading patterns of annual mean SST variability consisting of a Pacific El Niño–Southern Oscillation (ENSO)-like pattern, a pattern that resembles the Atlantic multidecadal oscillation (AMO), and a global trend pattern.

One of the key findings is that all of the AGCMs produce broadly similar (though different in detail) precipitation responses to the Pacific forcing pattern, with a cold Pacific leading to reduced precipitation and a warm Pacific leading to enhanced precipitation over most of the United States. While the response to the Atlantic pattern is less robust, there is general agreement among the models that the largest precipitation response over the United States tends to occur when the two oceans have anomalies of opposite signs. Further highlights of the response over the United States to the Pacific forcing include precipitation signal-to-noise ratios that peak in spring, and surface temperature signal-to-noise ratios that are both lower and show less agreement among the models than those found for the precipitation response. The response to the positive SST trend forcing pattern is an overall surface warming over the world’s land areas, with substantial regional variations that are in part reproduced in runs forced with a globally uniform SST trend forcing. The precipitation response to the trend forcing is weak in all of the models.

It is hoped that these early results, as well as those reported in the other contributions to this special issue on drought, will serve to stimulate further analysis of these simulations, as well as suggest new research on the physical mechanisms contributing to hydroclimatic variability and change throughout the world.

Full access