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Richard G. Gudgel, Anthony Rosati, and C. T. Gordon

Abstract

The sensitivity of a coupled general circulation model (CGCM) to tropical marine stratocumulus (MSc) clouds and low-level clouds over the tropical land is examined. The hypothesis that low-level clouds play an important role in determining the strength and position of the Walker circulation and also on the strength and phase of the El Niño–Southern Oscillation (ENSO) is studied using a Geophysical Fluid Dynamics Laboratory (GFDL) experimental prediction CGCM. In the Tropics, a GFDL experimental prediction CGCM exhibits a strong bias in the western Pacific where an eastward shift in the ascending branch of the Walker circulation diminishes the strength and expanse of the sea surface temperature (SST) warm pool, thereby reducing the east–west SST gradient, and effectively weakening the trade winds. These model features are evidence of a poorly simulated Walker circulation, one that mirrors a “perpetual El Niño” state. One possible factor contributing to this bias is a poor simulation of MSc clouds in the eastern equatorial Pacific (which are essential to a proper SST annual cycle). Another possible contributing factor might be radiative heating biases over the land in the Tropics, which could, in turn, have a significant impact on the preferred locations of maximum convection in the Tropics. As a means of studying the sensitivity of a CGCM to both MSc clouds and to varied radiative forcing over the land in the Tropics, low-level clouds obtained from the International Satellite Cloud Climatology Project (ISCCP) are prescribed. The experiment sets consist of one where clouds are fully predicted, another where ISCCP low-level clouds are prescribed over the oceans alone, and a third where ISCCP low-level clouds are prescribed both over the global oceans and over the tropical landmasses. A set of ten 12-month hindcasts is performed for each experiment.

The results show that the combined prescription of interannually varying global ocean and climatological tropical land low-level clouds into the CGCM results in a much improved simulation of the Walker circulation over the Pacific Ocean. The improvement to the tropical circulation was also notable over the Indian and Atlantic basins as well. These improvements in circulation led to a considerable increase in ENSO hindcast skill in the first year by the CGCM. These enhancements were a function of both the presence of MSc clouds over the tropical oceans and were also due to the more realistic positioning of the regions of maximum convection in the Tropics. This latter model feature was essentially a response to the change in radiative forcing over tropical landmasses associated with a reduction in low cloud fraction and optical depth when ISCCP low-level clouds were prescribed there. These results not only underscore the importance of a reasonable representation of MSc clouds but also point out the considerable impact that radiative forcing over the tropical landmasses has on the simulated position of the Walker circulation and also on ENSO forecasting.

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Hiroyuki Murakami, Gabriele Villarini, Gabriel A. Vecchi, Wei Zhang, and Richard Gudgel

Abstract

Retrospective seasonal forecasts of North Atlantic tropical cyclone (TC) activity over the period 1980–2014 are conducted using a GFDL high-resolution coupled climate model [Forecast-Oriented Low Ocean Resolution (FLOR)]. The focus is on basin-total TC and U.S. landfall frequency. The correlations between observed and model predicted basin-total TC counts range from 0.4 to 0.6 depending on the month of the initial forecast. The correlation values for U.S. landfalling activity based on individual TCs tracked from the model are smaller and between 0.1 and 0.4. Given the limited skill from the model, statistical methods are used to complement the dynamical seasonal TC prediction from the FLOR model. Observed and predicted TC tracks were classified into four groups using fuzzy c-mean clustering to evaluate the model’s predictability in observed classification of TC tracks. Analyses revealed that the FLOR model has the highest skill in predicting TC frequency for the cluster of TCs that tracks through the Caribbean and the Gulf of Mexico.

New hybrid models are developed to improve the prediction of observed basin-total TC and landfall TC frequencies. These models use large-scale climate predictors from the FLOR model as predictors for generalized linear models. The hybrid models show considerable improvements in the skill in predicting the basin-total TC frequencies relative to the dynamical model. The new hybrid model shows correlation coefficients as high as 0.75 for basinwide TC counts from the first two lead months and retains values around 0.50 even at the 6-month lead forecast. The hybrid model also shows comparable or higher skill in forecasting U.S. landfalling TCs relative to the dynamical predictions. The correlation coefficient is about 0.5 for the 2–5-month lead times.

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Wei Zhang, Gabriel A. Vecchi, Gabriele Villarini, Hiroyuki Murakami, Richard Gudgel, and Xiaosong Yang

Abstract

This study attempts to improve the prediction of western North Pacific (WNP) and East Asia (EA) landfalling tropical cyclones (TCs) using modes of large-scale climate variability [e.g., the Pacific meridional mode (PMM), the Atlantic meridional mode (AMM), and North Atlantic sea surface temperature anomalies (NASST)] as predictors in a hybrid statistical–dynamical scheme, based on dynamical model forecasts with the GFDL Forecast-Oriented Low Ocean Resolution version of CM2.5 with flux adjustments (FLOR-FA). Overall, the predictive skill of the hybrid model for the WNP TC frequency increases from lead month 5 (initialized in January) to lead month 0 (initialized in June) in terms of correlation coefficient and root-mean-square error (RMSE). The hybrid model outperforms FLOR-FA in predicting WNP TC frequency for all lead months. The predictive skill of the hybrid model improves as the forecast lead time decreases, with values of the correlation coefficient increasing from 0.56 for forecasts initialized in January to 0.69 in June. The hybrid models for landfalling TCs over the entire East Asian (EEA) coast and its three subregions [i.e., southern EA (SEA), middle EA (MEA), and northern EA (NEA)] dramatically outperform FLOR-FA. The correlation coefficient between predicted and observed TC landfall over SEA increases from 0.52 for forecasts initialized in January to 0.64 in June. The hybrid models substantially reduce the RMSE of landfalling TCs over SEA and EEA compared with FLOR-FA. This study suggests that the PMM and NASST/AMM can be used to improve statistical/hybrid forecast models for the frequencies of WNP or East Asia landfalling TCs.

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Hiroyuki Murakami, Gabriel A. Vecchi, Thomas L. Delworth, Karen Paffendorf, Liwei Jia, Richard Gudgel, and Fanrong Zeng
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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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Wei Zhang, Gabriel A. Vecchi, Gabriele Villarini, Hiroyuki Murakami, Thomas Delworth, Liwei Jia, Richard Gudgel, and Fanrong Zeng

Abstract

This study aims to assess the connections between El Niño–Southern Oscillation (ENSO) and tropical cyclones near Guam (GuamTCs) using the state-of-the-art Geophysical Fluid Dynamics Laboratory (GFDL) Forecast-Oriented Low Ocean Resolution version of CM2.5 (FLOR). In observations, more (fewer) GuamTCs occur in El Niño (La Niña) years, and the ENSO–GuamTC connections arise from TC genesis locations in ENSO phases. The observed ENSO–GuamTC connections are realistically simulated in the two control experiments that use two versions of FLOR: the standard version and another with flux adjustments (FLOR-FA). The ENSO–GuamTC connections in FLOR-FA are closer to observations than those in FLOR because of a better representation of TC genesis during ENSO phases. The physical mechanisms underlying the observed ENSO–GuamTC connections are further supported in the long-term control experiments with FLOR and FLOR-FA. The ENSO–GuamTC connections in sea surface temperature (SST)- and sea surface salinity (SSS)-restoring experiments with FLOR 1990 strongly resemble the observations, suggesting the ENSO–GuamTC connections arise substantially from the forcing of SST. The prediction skill of FLOR-FA for GuamTC frequency is quite promising in terms of correlation and root-mean-square error and is higher than that of FLOR for the period 1980–2014. This study shows the capability of global climate models (FLOR and FLOR-FA) in simulating the linkage between ENSO and TC activity near a highly localized region (i.e., Guam) and in predicting the frequency of TCs at the subbasin scale.

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Gabriel A. Vecchi, Ming Zhao, Hui Wang, Gabriele Villarini, Anthony Rosati, Arun Kumar, Isaac M. Held, and Richard Gudgel

Abstract

Skillfully predicting North Atlantic hurricane activity months in advance is of potential societal significance and a useful test of our understanding of the factors controlling hurricane activity. In this paper, a statistical–dynamical hurricane forecasting system, based on a statistical hurricane model, with explicit uncertainty estimates, and built from a suite of high-resolution global atmospheric dynamical model integrations spanning a broad range of climate states is described. The statistical model uses two climate predictors: the sea surface temperature (SST) in the tropical North Atlantic and SST averaged over the global tropics. The choice of predictors is motivated by physical considerations, as well as the results of high-resolution hurricane modeling and statistical modeling of the observed record. The statistical hurricane model is applied to a suite of initialized dynamical global climate model forecasts of SST to predict North Atlantic hurricane frequency, which peaks during the August–October season, from different starting dates. Retrospective forecasts of the 1982–2009 period indicate that skillful predictions can be made from as early as November of the previous year; that is, skillful forecasts for the coming North Atlantic hurricane season could be made as the current one is closing. Based on forecasts initialized between November 2009 and March 2010, the model system predicts that the upcoming 2010 North Atlantic hurricane season will likely be more active than the 1982–2009 climatology, with the forecasts initialized in March 2010 predicting an expected hurricane count of eight and a 50% probability of counts between six (the 1966–2009 median) and nine.

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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, Xiaosong Yang, Gabriel Vecchi, Richard Gudgel, Thomas Delworth, Stephan Fueglistaler, Pu Lin, Adam A. Scaife, Seth Underwood, and Shian-Jiann Lin

Abstract

This study explores the role of the stratosphere as a source of seasonal predictability of surface climate over Northern Hemisphere extratropics both in the observations and climate model predictions. A suite of numerical experiments, including climate simulations and retrospective forecasts, are set up to isolate the role of the stratosphere in seasonal predictive skill of extratropical near-surface land temperature. It is shown that most of the lead-0-month spring predictive skill of land temperature over extratropics, particularly over northern Eurasia, stems from stratospheric initialization. It is further revealed that this predictive skill of extratropical land temperature arises from skillful prediction of the Arctic Oscillation (AO). The dynamical connection between the stratosphere and troposphere is also demonstrated by the significant correlation between the stratospheric polar vortex and sea level pressure anomalies, as well as the migration of the stratospheric zonal wind anomalies to the lower troposphere.

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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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