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Thomas L. Delworth, Fanrong Zeng, Liping Zhang, Rong Zhang, Gabriel A. Vecchi, and Xiaosong Yang

Abstract

The relationship between the North Atlantic Oscillation (NAO) and Atlantic sea surface temperature (SST) variability is investigated using models and observations. Coupled climate models are used in which the ocean component is either a fully dynamic ocean or a slab ocean with no resolved ocean heat transport. On time scales less than 10 yr, NAO variations drive a tripole pattern of SST anomalies in both observations and models. This SST pattern is a direct response of the ocean mixed layer to turbulent surface heat flux anomalies associated with the NAO. On time scales longer than 10 yr, a similar relationship exists between the NAO and the tripole pattern of SST anomalies in models with a slab ocean. A different relationship exists both for the observations and for models with a dynamic ocean. In these models, a positive (negative) NAO anomaly leads, after a decadal-scale lag, to a monopole pattern of warming (cooling) that resembles the Atlantic multidecadal oscillation (AMO), although with smaller-than-observed amplitudes of tropical SST anomalies. Ocean dynamics are critical to this decadal-scale response in the models. The simulated Atlantic meridional overturning circulation (AMOC) strengthens (weakens) in response to a prolonged positive (negative) phase of the NAO, thereby enhancing (decreasing) poleward heat transport, leading to broad-scale warming (cooling). Additional simulations are used in which heat flux anomalies derived from observed NAO variations from 1901 to 2014 are applied to the ocean component of coupled models. It is shown that ocean dynamics allow models to reproduce important aspects of the observed AMO, mainly in the Subpolar Gyre.

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Xinrong Wu, Shaoqing Zhang, Zhengyu Liu, Anthony Rosati, Thomas L. Delworth, and Yun Liu

Abstract

Because of the geographic dependence of model sensitivities and observing systems, allowing optimized parameter values to vary geographically may significantly enhance the signal in parameter estimation. Using an intermediate atmosphere–ocean–land coupled model, the impact of geographic dependence of model sensitivities on parameter optimization is explored within a twin-experiment framework. The coupled model consists of a 1-layer global barotropic atmosphere model, a 1.5-layer baroclinic ocean including a slab mixed layer with simulated upwelling by a streamfunction equation, and a simple land model. The assimilation model is biased by erroneously setting the values of all model parameters. The four most sensitive parameters identified by sensitivity studies are used to perform traditional single-value parameter estimation and new geographic-dependent parameter optimization. Results show that the new parameter optimization significantly improves the quality of state estimates compared to the traditional scheme, with reductions of root-mean-square errors as 41%, 23%, 62%, and 59% for the atmospheric streamfunction, the oceanic streamfunction, sea surface temperature, and land surface temperature, respectively. Consistently, the new parameter optimization greatly improves the model predictability as a result of the improvement of initial conditions and the enhancement of observational signals in optimized parameters. These results suggest that the proposed geographic-dependent parameter optimization scheme may provide a new perspective when a coupled general circulation model is used for climate estimation and prediction.

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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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Liping Zhang, Thomas L. Delworth, Xiaosong Yang, Richard G. Gudgel, Liwei Jia, Gabriel A. Vecchi, and Fanrong Zeng

Abstract

This study explores the potential predictability of the Southern Ocean (SO) climate on decadal time scales as represented in the GFDL CM2.1 model using prognostic methods. Perfect model predictability experiments are conducted starting from 10 different initial states, showing potentially predictable variations of Antarctic bottom water (AABW) formation rates on time scales as long as 20 years. The associated Weddell Sea (WS) subsurface temperatures and Antarctic sea ice have potential predictability comparable to that of the AABW cell. The predictability of sea surface temperature (SST) variations over the WS and the SO is somewhat smaller, with predictable scales out to a decade. This reduced predictability is likely associated with stronger damping from air–sea interaction. As a complement to this perfect predictability study, the authors also make hindcasts of SO decadal variability using the GFDL CM2.1 decadal prediction system. Significant predictive skill for SO SST on multiyear time scales is found in the hindcast system. The success of the hindcasts, especially in reproducing observed surface cooling trends, is largely due to initializing the state of the AABW cell. A weak state of the AABW cell leads to cooler surface conditions and more extensive sea ice. Although there are considerable uncertainties regarding the observational data used to initialize the hindcasts, the consistency between the perfect model experiments and the decadal hindcasts at least gives some indication as to where and to what extent skillful decadal SO forecasts might be possible.

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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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Hiroyuki Murakami, Gabriel A. Vecchi, Thomas L. Delworth, Andrew T. Wittenberg, Seth Underwood, Richard Gudgel, Xiaosong Yang, Liwei Jia, Fanrong Zeng, Karen Paffendorf, and Wei Zhang

Abstract

The 2015 hurricane season in the eastern and central Pacific Ocean (EPO and CPO), particularly around Hawaii, was extremely active, including a record number of tropical cyclones (TCs) and the first instance of three simultaneous category-4 hurricanes in the EPO and CPO. A strong El Niño developed during the 2015 boreal summer season and was attributed by some to be the cause of the extreme number of TCs. However, according to a suite of targeted high-resolution model experiments, the extreme 2015 EPO and CPO hurricane season was not primarily induced by the 2015 El Niño tropical Pacific warming, but by warming in the subtropical Pacific Ocean. This warming is not typical of El Niño, but rather of the Pacific meridional mode (PMM) superimposed on long-term anthropogenic warming. Although the likelihood of such an extreme year depends on the phase of natural variability, the coupled GCM projects an increase in the frequency of such extremely active TC years over the next few decades for EPO, CPO, and Hawaii as a result of enhanced subtropical Pacific warming from anthropogenic greenhouse gas forcing.

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Liwei Jia, Gabriel A. Vecchi, Xiaosong Yang, Richard G. Gudgel, Thomas L. Delworth, William F. Stern, Karen Paffendorf, Seth D. Underwood, and Fanrong Zeng

Abstract

This study investigates the roles of radiative forcing, sea surface temperatures (SSTs), and atmospheric and land initial conditions in the summer warming episodes of the United States. The summer warming episodes are defined as the significantly above-normal (1983–2012) June–August 2-m temperature anomalies and are referred to as heat waves in this study. Two contrasting cases, the summers of 2006 and 2012, are explored in detail to illustrate the distinct roles of SSTs, direct radiative forcing, and atmospheric and land initial conditions in driving U.S. summer heat waves. For 2012, simulations with the GFDL atmospheric general circulation model reveal that SSTs play a critical role. Further sensitivity experiments reveal the contributions of uniform global SST warming, SSTs in individual ocean basins, and direct radiative forcing to the geographic distribution and magnitudes of warm temperature anomalies. In contrast, for 2006, the atmospheric and land initial conditions are the key drivers. The atmospheric (land) initial conditions play a major (minor) role in the central and northwestern (eastern) United States. Because of changes in radiative forcing, the probability of areal-averaged summer temperature anomalies over the United States exceeding the observed 2012 anomaly increases with time over the early twenty-first century. La Niña (El Niño) events tend to increase (reduce) the occurrence rate of heat waves. The temperatures over the central United States are mostly influenced by El Niño/La Niña, with the central tropical Pacific playing a more important role than the eastern tropical Pacific. Thus, atmospheric and land initial conditions, SSTs, and radiative forcing are all important drivers of and sources of predictability for U.S. summer heat waves.

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Hiroyuki Murakami, Gabriel A. Vecchi, Gabriele Villarini, Thomas L. Delworth, Richard Gudgel, Seth Underwood, Xiaosong Yang, Wei Zhang, and Shian-Jiann Lin

Abstract

Skillful seasonal forecasting of tropical cyclone (TC; wind speed ≥17.5 m s−1) activity is challenging, even more so when the focus is on major hurricanes (wind speed ≥49.4 m s−1), the most intense hurricanes (category 4 and 5; wind speed ≥58.1 m s–1), and landfalling TCs. This study shows that a 25-km-resolution global climate model [High-Resolution Forecast-Oriented Low Ocean Resolution (FLOR) model (HiFLOR)] developed at the Geophysical Fluid Dynamics Laboratory (GFDL) has improved skill in predicting the frequencies of major hurricanes and category 4 and 5 hurricanes in the North Atlantic as well as landfalling TCs over the United States and Caribbean islands a few months in advance, relative to its 50-km-resolution predecessor climate model (FLOR). HiFLOR also shows significant skill in predicting category 4 and 5 hurricanes in the western North Pacific and eastern North Pacific, while both models show comparable skills in predicting basin-total and landfalling TC frequency in the basins. The improved skillful forecasts of basin-total TCs, major hurricanes, and category 4 and 5 hurricane activity in the North Atlantic by HiFLOR are obtained mainly by improved representation of the TCs and their response to climate from the increased horizontal resolution rather than by improvements in large-scale parameters.

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Wei Zhang, Gabriel A. Vecchi, Hiroyuki Murakami, Thomas L. Delworth, Karen Paffendorf, Liwei Jia, Gabriele Villarini, Rich Gudgel, Fanrong Zeng, and Xiaosong Yang
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Karin van der Wiel, Sarah B. Kapnick, Gabriel A. Vecchi, William F Cooke, Thomas L. Delworth, Liwei Jia, Hiroyuki Murakami, Seth Underwood, and Fanrong Zeng

Abstract

Precipitation extremes have a widespread impact on societies and ecosystems; it is therefore important to understand current and future patterns of extreme precipitation. Here, a set of new global coupled climate models with varying atmospheric resolution has been used to investigate the ability of these models to reproduce observed patterns of precipitation extremes and to investigate changes in these extremes in response to increased atmospheric CO2 concentrations. The atmospheric resolution was increased from 2° × 2° grid cells (typical resolution in the CMIP5 archive) to 0.25° × 0.25° (tropical cyclone permitting). Analysis has been confined to the contiguous United States (CONUS). It is shown that, for these models, integrating at higher atmospheric resolution improves all aspects of simulated extreme precipitation: spatial patterns, intensities, and seasonal timing. In response to 2 × CO2 concentrations, all models show a mean intensification of precipitation rates during extreme events of approximately 3%–4% K−1. However, projected regional patterns of changes in extremes are dependent on model resolution. For example, the highest-resolution models show increased precipitation rates during extreme events in the hurricane season in the U.S. Southeast; this increase is not found in the low-resolution model. These results emphasize that, for the study of extreme precipitation there is a minimum model resolution that is needed to capture the weather phenomena generating the extremes. Finally, the observed record and historical model experiments were used to investigate changes in the recent past. In part because of large intrinsic variability, no evidence was found for changes in extreme precipitation attributable to climate change in the available observed record.

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