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Anand Gnanadesikan
and
Whit G. Anderson

Abstract

Ocean water clarity affects the distribution of shortwave heating in the water column. In a one-dimensional time-mean sense, increased clarity would be expected to cool the surface and heat subsurface depths as shortwave radiation penetrates deeper into the water column. However, wind-driven upwelling, boundary currents, and the seasonal cycle of mixing can bring water heated at depth back to the surface. This warms the equator and cools the subtropics throughout the year while reducing the amplitude of the seasonal cycle of temperature in polar regions. This paper examines how these changes propagate through the climate system in a coupled model with an isopycnal ocean component focusing on the different impacts associated with removing shading from different regions. Increasing shortwave penetration along the equator causes warming to the south of the equator. Increasing it in the relatively clear gyres off the equator causes the Hadley cells to strengthen and the subtropical gyres to shift equatorward. Increasing shortwave penetration in the less clear regions overlying the oxygen minimum zones causes the cold tongue to warm and the Walker circulation to weaken. Increasing shortwave penetration in the high-latitude Southern Ocean causes an increase in the formation of mode water from subtropical water. The results suggest that more attention be paid to the processes distributing heat below the mixed layer.

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Adele K. Morrison
,
Stephen M. Griffies
,
Michael Winton
,
Whit G. Anderson
, and
Jorge L. Sarmiento

Abstract

The Southern Ocean plays a dominant role in anthropogenic oceanic heat uptake. Strong northward transport of the heat content anomaly limits warming of the sea surface temperature in the uptake region and allows the heat uptake to be sustained. Using an eddy-rich global climate model, the processes controlling the northward transport and convergence of the heat anomaly in the midlatitude Southern Ocean are investigated in an idealized 1% yr−1 increasing CO2 simulation. Heat budget analyses reveal that different processes dominate to the north and south of the main convergence region. The heat transport northward from the uptake region in the south is driven primarily by passive advection of the heat content anomaly by the existing time mean circulation, with a smaller 20% contribution from enhanced upwelling. The heat anomaly converges in the midlatitude deep mixed layers because there is not a corresponding increase in the mean heat transport out of the deep mixed layers northward into the mode waters. To the north of the deep mixed layers, eddy processes drive the warming and account for nearly 80% of the northward heat transport anomaly. The eddy transport mechanism results from a reduction in both the diffusive and advective southward eddy heat transports, driven by decreasing isopycnal slopes and decreasing along-isopycnal temperature gradients on the northern edge of the peak warming.

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Hyeong-Seog Kim
,
Gabriel A. Vecchi
,
Thomas R. Knutson
,
Whit G. Anderson
,
Thomas L. Delworth
,
Anthony Rosati
,
Fanrong Zeng
, and
Ming Zhao

Abstract

Global tropical cyclone (TC) activity is simulated by the Geophysical Fluid Dynamics Laboratory (GFDL) Climate Model, version 2.5 (CM2.5), which is a fully coupled global climate model with a horizontal resolution of about 50 km for the atmosphere and 25 km for the ocean. The present climate simulation shows a fairly realistic global TC frequency, seasonal cycle, and geographical distribution. The model has some notable biases in regional TC activity, including simulating too few TCs in the North Atlantic. The regional biases in TC activity are associated with simulation biases in the large-scale environment such as sea surface temperature, vertical wind shear, and vertical velocity. Despite these biases, the model simulates the large-scale variations of TC activity induced by El Niño–Southern Oscillation fairly realistically. The response of TC activity in the model to global warming is investigated by comparing the present climate with a CO2 doubling experiment. Globally, TC frequency decreases (−19%) while the intensity increases (+2.7%) in response to CO2 doubling, consistent with previous studies. The average TC lifetime decreases by −4.6%, while the TC size and rainfall increase by about 3% and 12%, respectively. These changes are generally reproduced across the different basins in terms of the sign of the change, although the percent changes vary from basin to basin and within individual basins. For the Atlantic basin, although there is an overall reduction in frequency from CO2 doubling, the warmed climate exhibits increased interannual hurricane frequency variability so that the simulated Atlantic TC activity is enhanced more during unusually warm years in the CO2-warmed climate relative to that in unusually warm years in the control climate.

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Salvatore Pascale
,
Simona Bordoni
,
Sarah B. Kapnick
,
Gabriel A. Vecchi
,
Liwei Jia
,
Thomas L. Delworth
,
Seth Underwood
, and
Whit Anderson

Abstract

The impact of atmosphere and ocean horizontal resolution on the climatology of North American monsoon Gulf of California (GoC) moisture surges is examined in a suite of global circulation models (CM2.1, FLOR, CM2.5, CM2.6, and HiFLOR) developed at the Geophysical Fluid Dynamics Laboratory (GFDL). These models feature essentially the same physical parameterizations but differ in horizontal resolution in either the atmosphere (≃200, 50, and 25 km) or the ocean (≃1°, 0.25°, and 0.1°). Increasing horizontal atmospheric resolution from 200 to 50 km results in a drastic improvement in the model’s capability of accurately simulating surge events. The climatological near-surface flow and moisture and precipitation anomalies associated with GoC surges are overall satisfactorily simulated in all higher-resolution models. The number of surge events agrees well with reanalyses, but models tend to underestimate July–August surge-related precipitation and overestimate September surge-related rainfall in the southwestern United States. Large-scale controls supporting the development of GoC surges, such as tropical easterly waves (TEWs), tropical cyclones (TCs), and trans-Pacific Rossby wave trains (RWTs), are also well captured, although models tend to underestimate the TEW and TC magnitude and number. Near-surface GoC surge features and their large-scale forcings (TEWs, TCs, and RWTs) do not appear to be substantially affected by a finer representation of the GoC at higher ocean resolution. However, the substantial reduction of the eastern Pacific warm sea surface temperature bias through flux adjustment in the Forecast-Oriented Low Ocean Resolution (FLOR) model leads to an overall improvement of tropical–extratropical controls on GoC moisture surges and the seasonal cycle of precipitation in the southwestern United States.

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Gabriel A. Vecchi
,
Rym Msadek
,
Whit Anderson
,
You-Soon Chang
,
Thomas Delworth
,
Keith Dixon
,
Rich Gudgel
,
Anthony Rosati
,
Bill Stern
,
Gabriele Villarini
,
Andrew Wittenberg
,
Xiaosong Yang
,
Fanrong Zeng
,
Rong Zhang
, and
Shaoqing Zhang
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Wei Zhang
,
Gabriel A. Vecchi
,
Hiroyuki Murakami
,
Thomas Delworth
,
Andrew T. Wittenberg
,
Anthony Rosati
,
Seth Underwood
,
Whit Anderson
,
Lucas Harris
,
Richard Gudgel
,
Shian-Jiann Lin
,
Gabriele Villarini
, and
Jan-Huey Chen

Abstract

This study aims to assess whether, and the extent to which, an increase in atmospheric resolution of the Geophysical Fluid Dynamics Laboratory (GFDL) Forecast-Oriented Low Ocean Resolution version of CM2.5 (FLOR) with 50-km resolution and the High-Resolution FLOR (HiFLOR) with 25-km resolution improves the simulation of the El Niño–Southern Oscillation (ENSO)–tropical cyclone (TC) connections in the western North Pacific (WNP). HiFLOR simulates better ENSO–TC connections in the WNP including TC track density, genesis, and landfall than FLOR in both long-term control experiments and sea surface temperature (SST)- and sea surface salinity (SSS)-restoring historical runs (1971–2012). Restoring experiments are performed with SSS and SST restored to observational estimates of climatological SSS and interannually varying monthly SST. In the control experiments of HiFLOR, an improved simulation of the Walker circulation arising from more realistic SST and precipitation is largely responsible for its better performance in simulating ENSO–TC connections in the WNP. In the SST-restoring experiments of HiFLOR, more realistic Walker circulation and steering flow during El Niño and La Niña are responsible for the improved simulation of ENSO–TC connections in the WNP. The improved simulation of ENSO–TC connections with HiFLOR arises from a better representation of SST and better responses of environmental large-scale circulation to SST anomalies associated with El Niño or La Niña. A better representation of ENSO–TC connections in HiFLOR can benefit the seasonal forecasting of TC genesis, track, and landfall; improve understanding of the interannual variation of TC activity; and provide better projection of TC activity under climate change.

Full access
Gabriel A. Vecchi
,
Rym Msadek
,
Whit Anderson
,
You-Soon Chang
,
Thomas Delworth
,
Keith Dixon
,
Rich Gudgel
,
Anthony Rosati
,
Bill Stern
,
Gabriele Villarini
,
Andrew Wittenberg
,
Xiasong Yang
,
Fanrong Zeng
,
Rong Zhang
, and
Shaoqing Zhang

Abstract

Retrospective predictions of multiyear North Atlantic Ocean hurricane frequency are explored by applying a hybrid statistical–dynamical forecast system to initialized and noninitialized multiyear forecasts of tropical Atlantic and tropical-mean sea surface temperatures (SSTs) from two global climate model forecast systems. By accounting for impacts of initialization and radiative forcing, retrospective predictions of 5- and 9-yr mean tropical Atlantic hurricane frequency show significant correlations relative to a null hypothesis of zero correlation. The retrospective correlations are increased in a two-model average forecast and by using a lagged-ensemble approach, with the two-model ensemble decadal forecasts of hurricane frequency over 1961–2011 yielding correlation coefficients that approach 0.9. These encouraging retrospective multiyear hurricane predictions, however, should be interpreted with care: although initialized forecasts have higher nominal skill than uninitialized ones, the relatively short record and large autocorrelation of the time series limits confidence in distinguishing between the skill caused by external forcing and that added by initialization. The nominal increase in correlation in the initialized forecasts relative to the uninitialized experiments is caused by improved representation of the multiyear tropical Atlantic SST anomalies. The skill in the initialized forecasts comes in large part from the persistence of a mid-1990s shift by the initialized forecasts, rather than from predicting its evolution. Predicting shifts like that observed in 1994/95 remains a critical issue for the success of multiyear forecasts of Atlantic hurricane frequency. The retrospective forecasts highlight the possibility that changes in observing system impact forecast performance.

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Gabriel A. Vecchi
,
Rym Msadek
,
Whit Anderson
,
You-Soon Chang
,
Thomas Delworth
,
Keith Dixon
,
Rich Gudgel
,
Anthony Rosati
,
Bill Stern
,
Gabriele Villarini
,
Andrew Wittenberg
,
Xiasong Yang
,
Fanrong Zeng
,
Rong Zhang
, and
Shaoqing Zhang
Full access
Hiroyuki Murakami
,
Gabriel A. Vecchi
,
Seth Underwood
,
Thomas L. Delworth
,
Andrew T. Wittenberg
,
Whit G. Anderson
,
Jan-Huey Chen
,
Richard G. Gudgel
,
Lucas M. Harris
,
Shian-Jiann Lin
, and
Fanrong Zeng

Abstract

A new high-resolution Geophysical Fluid Dynamics Laboratory (GFDL) coupled model [the High-Resolution Forecast-Oriented Low Ocean Resolution (FLOR) model (HiFLOR)] has been developed and used to investigate potential skill in simulation and prediction of tropical cyclone (TC) activity. HiFLOR comprises high-resolution (~25-km mesh) atmosphere and land components and a more moderate-resolution (~100-km mesh) sea ice and ocean component. HiFLOR was developed from FLOR by decreasing the horizontal grid spacing of the atmospheric component from 50 to 25 km, while leaving most of the subgrid-scale physical parameterizations unchanged. Compared with FLOR, HiFLOR yields a more realistic simulation of the structure, global distribution, and seasonal and interannual variations of TCs, as well as a comparable simulation of storm-induced cold wakes and TC-genesis modulation induced by the Madden–Julian oscillation (MJO). Moreover, HiFLOR is able to simulate and predict extremely intense TCs (Saffir–Simpson hurricane categories 4 and 5) and their interannual variations, which represents the first time a global coupled model has been able to simulate such extremely intense TCs in a multicentury simulation, sea surface temperature restoring simulations, and retrospective seasonal predictions.

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Liwei Jia
,
Xiaosong Yang
,
Gabriel A. Vecchi
,
Richard G. Gudgel
,
Thomas L. Delworth
,
Anthony Rosati
,
William F. Stern
,
Andrew T. Wittenberg
,
Lakshmi Krishnamurthy
,
Shaoqing Zhang
,
Rym Msadek
,
Sarah Kapnick
,
Seth Underwood
,
Fanrong Zeng
,
Whit G. Anderson
,
Venkatramani Balaji
, and
Keith Dixon

Abstract

This study demonstrates skillful seasonal prediction of 2-m air temperature and precipitation over land in a new high-resolution climate model developed by the Geophysical Fluid Dynamics Laboratory and explores the possible sources of the skill. The authors employ a statistical optimization approach to identify the most predictable components of seasonal mean temperature and precipitation over land and demonstrate the predictive skill of these components. First, the improved skill of the high-resolution model over the previous lower-resolution model in seasonal prediction of the Niño-3.4 index and other aspects of interest is shown. Then, the skill of temperature and precipitation in the high-resolution model for boreal winter and summer is measured, and the sources of the skill are diagnosed. Last, predictions are reconstructed using a few of the most predictable components to yield more skillful predictions than the raw model predictions. Over three decades of hindcasts, the two most predictable components of temperature are characterized by a component that is likely due to changes in external radiative forcing in boreal winter and summer and an ENSO-related pattern in boreal winter. The most predictable components of precipitation in both seasons are very likely ENSO-related. These components of temperature and precipitation can be predicted with significant correlation skill at least 9 months in advance. The reconstructed predictions using only the first few predictable components from the model show considerably better skill relative to observations than raw model predictions. This study shows that the use of refined statistical analysis and a high-resolution dynamical model leads to significant skill in seasonal predictions of 2-m air temperature and precipitation over land.

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