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G. S. Bhat, G. A. Vecchi, and S. Gadgil

Abstract

The Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) with the capability of measuring sea surface temperature (SST) in the presence of clouds, has been providing an unprecedented view of tropical basin-scale SST variability. In this paper, an assessment of the accuracy of the SST derived from TMI over the Bay of Bengal using in situ data collected from moored buoys and research ships, is presented. The authors find that TMI captures the evolution of the SST of the bay on seasonal time scales with reasonable accuracy. The mean difference between the SST from TMI and buoys is less than 0.1°C, and the rms difference is about 0.6°C. The time scales of the intraseasonal variation of the TMI SST are realistic. However, the amplitude of the SST variation on the intraseasonal scale is overestimated by a factor of about 1.3 when compared to buoy data. It is observed that the SST derived from TMI tends to be lower during periods with deep convection or winds stronger than 10 m s−1, or both. There is better agreement during weak conditions of convection/wind. This leads to a cold bias during convectively active periods when running average SST time series are constructed from SSTs retrieved from the TMI.

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W. Zhang, G. A. Vecchi, H. Murakami, G. Villarini, and L. Jia

Abstract

This study investigates the association between the Pacific meridional mode (PMM) and tropical cyclone (TC) activity in the western North Pacific (WNP). It is found that the positive PMM phase favors the occurrence of TCs in the WNP while the negative PMM phase inhibits the occurrence of TCs there. Observed relationships are consistent with those from a long-term preindustrial control experiment (1000 yr) of a high-resolution TC-resolving Geophysical Fluid Dynamics Laboratory (GFDL) Forecast-Oriented Low Ocean Resolution (FLOR) coupled climate model. The diagnostic relationship between the PMM and TCs in observations and the model is further supported by sensitivity experiments with FLOR. The modulation of TC genesis by the PMM is primarily through the anomalous zonal vertical wind shear (ZVWS) changes in the WNP, especially in the southeastern WNP. The anomalous ZVWS can be attributed to the responses of the atmosphere to the anomalous warming in the northwestern part of the PMM pattern during the positive PMM phase, which resembles a classic Matsuno–Gill pattern. Such influences on TC genesis are strengthened by a cyclonic flow over the WNP. The significant relationship between TCs and the PMM identified here may provide a useful reference for seasonal forecasting of TCs and interpreting changes in TC activity in the WNP.

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Ángel G. Muñoz, Xiaosong Yang, Gabriel A. Vecchi, Andrew W. Robertson, and William F. Cooke

Abstract

This study proposes an integrated diagnostic framework based on atmospheric circulation regime spatial patterns and frequencies of occurrence to facilitate the identification of model systematic errors across multiple time scales. To illustrate the approach, three sets of 32-yr-long simulations are analyzed for northeastern North America and for the March–May season using the Geophysical Fluid Dynamics Laboratory’s Low Ocean–Atmosphere Resolution (LOAR) and Forecast-Oriented Low Ocean Resolution (FLOR) coupled models; the main difference between these two models is the horizontal resolution of the atmospheric model used. Regime-dependent biases are explored in the light of different atmospheric horizontal resolutions and under different nudging approaches. It is found that both models exhibit a fair representation of the observed circulation regime spatial patterns and frequencies of occurrence, although some biases are present independently of the horizontal resolution or the nudging approach and are associated with a misrepresentation of troughs centered north of the Great Lakes and deep coastal troughs. Moreover, the intraseasonal occurrence of certain model regimes is delayed with respect to observations. On the other hand, interexperiment differences in the mean frequencies of occurrence of the simulated weather types, and their variability across multiple time scales, tend to be negligible. This result suggests that low-resolution models could be of potential use to diagnose and predict physical variables via their simulated weather type characteristics.

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Xiaosong Yang, G. A. Vecchi, T. L. Delworth, K. Paffendorf, L. Jia, R. Gudgel, F. Zeng, and Seth D. Underwood
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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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John G. Dwyer, Suzana J. Camargo, Adam H. Sobel, Michela Biasutti, Kerry A. Emanuel, Gabriel A. Vecchi, Ming Zhao, and Michael K. Tippett

Abstract

This study investigates projected changes in the length of the tropical cyclone season due to greenhouse gas increases. Two sets of simulations are analyzed, both of which capture the relevant features of the observed annual cycle of tropical cyclones in the recent historical record. Both sets use output from the general circulation models (GCMs) of either phase 3 or phase 5 of the CMIP suite (CMIP3 and CMIP5, respectively). In one set, downscaling is performed by randomly seeding incipient vortices into the large-scale atmospheric conditions simulated by each GCM and simulating the vortices’ evolution in an axisymmetric dynamical tropical cyclone model; in the other set, the GCMs’ sea surface temperature (SST) is used as the boundary condition for a high-resolution global atmospheric model (HiRAM). The downscaling model projects a longer season (in the late twenty-first century compared to the twentieth century) in most basins when using CMIP5 data but a slightly shorter season using CMIP3. HiRAM with either CMIP3 or CMIP5 SST anomalies projects a shorter tropical cyclone season in most basins. Season length is measured by the number of consecutive days that the mean cyclone count is greater than a fixed threshold, but other metrics give consistent results. The projected season length changes are also consistent with the large-scale changes, as measured by a genesis index of tropical cyclones. The season length changes are mostly explained by an idealized year-round multiplicative change in tropical cyclone frequency, but additional changes in the transition months also contribute.

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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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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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Rym Msadek, T. L. Delworth, A. Rosati, W. Anderson, G. Vecchi, Y.-S. Chang, K. Dixon, R. G. Gudgel, W. Stern, A. Wittenberg, X. Yang, F. Zeng, R. Zhang, and S. Zhang

Abstract

Decadal prediction experiments were conducted as part of phase 5 of the Coupled Model Intercomparison Project (CMIP5) using the GFDL Climate Model, version 2.1 (CM2.1) forecast system. The abrupt warming of the North Atlantic Subpolar Gyre (SPG) that was observed in the mid-1990s is considered as a case study to evaluate forecast capabilities and better understand the reasons for the observed changes. Initializing the CM2.1 coupled system produces high skill in retrospectively predicting the mid-1990s shift, which is not captured by the uninitialized forecasts. All the hindcasts initialized in the early 1990s show a warming of the SPG; however, only the ensemble-mean hindcasts initialized in 1995 and 1996 are able to reproduce the observed abrupt warming and the associated decrease and contraction of the SPG. Examination of the physical mechanisms responsible for the successful retrospective predictions indicates that initializing the ocean is key to predicting the mid-1990s warming. The successful initialized forecasts show an increased Atlantic meridional overturning circulation and North Atlantic Current transport, which drive an increased advection of warm saline subtropical waters northward, leading to a westward shift of the subpolar front and, subsequently, a warming and spindown of the SPG. Significant seasonal climate impacts are predicted as the SPG warms, including a reduced sea ice concentration over the Arctic, an enhanced warming over the central United States during summer and fall, and a northward shift of the mean ITCZ. These climate anomalies are similar to those observed during a warm phase of the Atlantic multidecadal oscillation, which is encouraging for future predictions of North Atlantic climate.

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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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