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Minobe, S, Kuwano-Yoshida A, Komori N, Xie SP, Small RJ.  2008.  Influence of the Gulf Stream on the troposphere. Nature. 452:206-U51.   10.1038/nature06690   Abstract
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Minobe, S, Miyashita M, Kuwano-Yoshida A, Tokinaga H, Xie S-P.  2010.  Atmospheric Response to the Gulf Stream: Seasonal Variations. Journal of Climate. 23:3699-3719.   10.1175/2010jcli3359.1   Abstract
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Merrifield, AL, Xie SP.  2016.  Summer US surface air temperature variability: controlling factors and AMIP simulation biases. Journal of Climate. 29:5123-5139.   10.1175/jcli-d-15-0705.1   AbstractWebsite

This study documents and investigates biases in simulating summer surface air temperature (SAT) variability over the continental United States in the Atmospheric Model Intercomparison Project (AMIP) experiment from phase 5 of the Coupled Model Intercomparison Project (CMIP5). Empirical orthogonal function (EOF) and multivariate regression analyses are used to assess the relative importance of circulation and the land surface feedback at setting summer SAT over a 30-yr period (1979-2008). Regions of high SAT variability are closely associated with midtropospheric highs, subsidence, and radiative heating accompanying clear-sky conditions. The land surface exerts a spatially variable influence on SAT through the sensible heat flux and is a second-order effect in the high-variability centers of action (COAs) in observational estimates. The majority of the AMIP models feature high SAT variability over the central United States, displaced south and/or west of observed COAs. SAT COAs in models tend to be concomitant and strongly coupled with regions of high sensible heat flux variability, suggesting that excessive land-atmosphere interaction in these models modulates U.S. summer SAT. In the central United States, models with climatological warm biases also feature less evapotranspiration than ERA-Interim but reasonably reproduce observed SAT variability in the region. Models that overestimate SAT variability tend to reproduce ERA-Interim SAT and evapotranspiration climatology. In light of potential model biases, this analysis calls for careful evaluation of the land-atmosphere interaction hot spot region identified in the central United States. Additionally, tropical sea surface temperatures play a role in forcing the leading EOF mode for summer SAT in models. This relationship is not apparent in observations.

Merrifield, A, Lehner F, Xie SP, Deser C.  2017.  Removing Circulation Effects to Assess Central US Land-Atmosphere Interactions in the CESM Large Ensemble. Geophysical Research Letters. 44:9938-9946.   10.1002/2017gl074831   AbstractWebsite

Interannual variability of summer surface air temperature (SAT) in the central United States (U.S.) is influenced by atmospheric circulation and land surface feedbacks. Here a method of dynamical adjustment is used to remove the effects of circulation on summer SAT variability over North America in the Community Earth System Model Large Ensemble. The residual SAT variability is shown to reflect thermodynamic feedbacks associated with land surface conditions. In particular, the central U.S. is a hot spot of land-atmosphere interaction, with residual SAT accounting for more than half of the total SAT variability. Within the hot spot, residual SAT anomalies show higher month-to-month persistence through the warm season and a redder spectrum than dynamically induced SAT anomalies. Residual SAT variability in this region is also shown to be related to preseason soil moisture conditions, surface flux variability, and local atmospheric pressure anomalies.

Mei, W, Kamae Y, Xie SP, Yoshida K.  2019.  Variability and predictability of North Atlantic hurricane frequency in a large ensemble of high-resolution atmospheric simulations. Journal of Climate. 32:3153-3167.   10.1175/jcli-d-18-0554.1   AbstractWebsite

Variability of North Atlantic annual hurricane frequency during 1951-2010 is studied using a 100-member ensemble of climate simulations by a 60-km atmospheric general circulation model that is forced by observed sea surface temperatures (SSTs). The ensemble mean results well capture the interannual-to-decadal variability of hurricane frequency in best track data since 1970, and suggest that the current best track data might underestimate hurricane frequency prior to 1966 when satellite measurements were unavailable. A genesis potential index (GPI) averaged over the main development region (MDR) accounts for more than 80% of the SST-forced variations in hurricane frequency, with potential intensity and vertical wind shear being the dominant factors. In line with previous studies, the difference between MDR SST and tropical mean SST is a useful predictor; a 1 degrees C increase in this SST difference produces 7.05 +/- 1.39 more hurricanes. The hurricane frequency also exhibits strong internal variability that is systematically larger in the model than observations. The seasonal-mean environment is highly correlated among ensemble members and contributes to less than 10% of the ensemble spread in hurricane frequency. The strong internal variability is suggested to originate from weather to intraseasonal variability and nonlinearity. In practice, a 20-member ensemble is sufficient to capture the SST-forced variability.

Mei, W, Xie SP, Zhao M.  2014.  Variability of tropical cyclone track density in the North Atlantic: Observations and high-resolution simulations. Journal of Climate. 27:4797-4814.   10.1175/jcli-d-13-00587.1   AbstractWebsite

Interannual-decadal variability of tropical cyclone (TC) track density over the North Atlantic (NA) between 1979 and 2008 is studied using observations and simulations with a 25-km-resolution version of the High Resolution Atmospheric Model (HiRAM) forced by observed sea surface temperatures (SSTs). The variability on decadal and interannual time scales is examined separately. On both time scales, a basinwide mode dominates, with the time series being related to variations in seasonal TC counts. On decadal time scales, this mode relates to SST contrasts between the tropical NA and the tropical northeast Pacific as well as the tropical South Atlantic, whereas on interannual time scales it is controlled by SSTs over the central eastern equatorial Pacific and those over the tropical NA. The temporal evolution of the spatial distribution of track density is further investigated by normalizing the track density with seasonal TC counts. On decadal time scales, two modes emerge: one is an oscillation between track density over the U.S. East Coast and midlatitude ocean and that over the Gulf of Mexico and the Caribbean Sea and the other oscillates between low and middle latitudes. They might be driven by the preceding winter North Atlantic Oscillation and concurrent Atlantic meridional mode, respectively. On interannual time scales, two similar modes are present in observations but are not well separated in HiRAM simulations. Finally, the internal variability and predictability of TC track density are explored and discussed using HiRAM ensemble simulations. The results suggest that basinwide total TC counts/days are much more predictable than local TC occurrence, posing a serious challenge to the prediction and projection of regional TC threats, especially the U.S. landfall hurricanes.

Mei, W, Xie SP.  2016.  Intensification of landfalling typhoons over the northwest Pacific since the late 1970s. Nature Geoscience. 9:753-+.   10.1038/ngeo2792   AbstractWebsite

Intensity changes in landfalling typhoons are of great concern to East and Southeast Asian countries(1). Regional changes in typhoon intensity, however, are poorly known owing to inconsistencies among different data sets(2-8). Here, we apply cluster analysis to bias-corrected data and show that, over the past 37 years, typhoons that strike East and Southeast Asia have intensified by 12-15%, with the proportion of storms of categories 4 and 5 having doubled or even tripled. In contrast, typhoons that stay over the open ocean have experienced only modest changes. These regional changes are consistent between operational data sets. To identify the physical mechanisms, we decompose intensity changes into contributions from intensification rate and intensification duration. We find that the increased intensity of landfalling typhoons is due to strengthened intensification rates, which in turn are tied to locally enhanced ocean surface warming on the rim of East and Southeast Asia. The projected ocean surface warming pattern under increasing greenhouse gas forcing suggests that typhoons striking eastern mainland China, Taiwan, Korea and Japan will intensify further. Given disproportionate damages by intense typhoons(1), this represents a heightened threat to people and properties in the region.

Mei, W, Xie SP, Zhao M, Wang YQ.  2015.  Forced and internal vriability of tropical cyclone track density in the Western North Pacific. Journal of Climate. 28:143-167.   10.1175/jcli-d-14-00164.1   AbstractWebsite

Forced interannual-to-decadal variability of annual tropical cyclone (TC) track density in the western North Pacific between 1979 and 2008 is studied using TC tracks from observations and simulations by a 25-km-resolution version of the GFDL High-Resolution Atmospheric Model (HiRAM) that is forced by observed sea surface temperatures (SSTs). Two modes dominate the decadal variability: a nearly basinwide mode, and a dipole mode between the subtropics and lower latitudes. The former mode links to variations in TC number and is forced by SST variations over the off-equatorial tropical central North Pacific, whereas the latter might be associated with the Atlantic multidecadal oscillation. The interannual variability is also controlled by two modes: a basinwide mode driven by SST anomalies of opposite signs located in the tropical central Pacific and eastern Indian Ocean, and a southeast-northwest dipole mode connected to the conventional eastern Pacific ENSO. The seasonal evolution of the ENSO effect on TC activity is further explored via a joint empirical orthogonal function analysis using TC track density of consecutive seasons, and the analysis reveals that two types of ENSO are at work. Internal variability in TC track density is then examined using ensemble simulations from both HiRAM and a regional atmospheric model. It exhibits prominent spatial and seasonal patterns, and it is particularly strong in the South China Sea and along the coast of East Asia. This makes an accurate prediction and projection of TC landfall extremely challenging in these regions. In contrast, basin-integrated metrics (e.g., total TC counts and TC days) are more predictable.

Mei, W, Lien CC, Lin II, Xie SP.  2015.  Tropical cyclone-induced ocean response: A comparative study of the South China Sea and tropical Northwest Pacific*(,+). Journal of Climate. 28:5952-5968.   10.1175/jcli-d-14-00651.1   AbstractWebsite

The thermocline shoals in the South China Sea (SCS) relative to the tropical northwest Pacific Ocean (NWP), as required by geostrophic balance with the Kuroshio. The present study examines the effect of this difference in ocean state on the response of sea surface temperature (SST) and chlorophyll concentration to tropical cyclones (TCs), using both satellite-derived measurements and three-dimensional numerical simulations. In both regions, TC-produced SST cooling strongly depends on TC characteristics (including intensity as measured by the maximum surface wind speed, translation speed, and size). When subject to identical TC forcing, the SST cooling in the SCS is more than 1.5 times that in the NWP, which may partially explain weaker TC intensity on average observed in the SCS. Both a shallower mixed layer and stronger subsurface thermal stratification in the SCS contribute to this regional difference in SST cooling. The mixed layer effect dominates when TCs are weak, fast-moving, and/or small; and for strong and slow-moving TCs or strong and large TCs, both factors are equally important. In both regions, TCs tend to elevate surface chlorophyll concentration. For identical TC forcing, the surface chlorophyll increase in the SCS is around 10 times that in the NWP, a difference much stronger than that in SST cooling. This large regional difference in the surface chlorophyll response is at least partially due to a shallower nutricline and stronger vertical nutrient gradient in the SCS. The effect of regional difference in upper-ocean density stratification on the surface nutrient response is negligible. The total annual primary production increase associated with the TC passage estimated using the vertically generalized production model in the SCS is nearly 3 times that in the NWP (i.e., 6.4 +/- 0.4 x 10(12) versus 2.2 +/- 0.2 x 10(12) g C), despite the weaker TC activity in the SCS.

Meehl, GA, Hu AX, Santer BD, Xie SP.  2016.  Contribution of the Interdecadal Pacific Oscillation to twentieth-century global surface temperature trends. Nature Climate Change. 6:1005-1008.   10.1038/nclimate3107   AbstractWebsite

Longer-term externally forced trends in global mean surface temperatures (GMSTs) are embedded in the background noise of internally generated multidecadal variability(1). A key mode of internal variability is the Interdecadal Pacific Oscillation (IPO), which contributed to a reduced GMST trend during the early 2000s(1-3). We use a novel, physical phenomenon-based approach to quantify the contribution from a source of internally generated multidecadal variability-the IPO-to multidecadal GMST trends. Here we show that the largest IPO contributions occurred in its positive phase during the rapidwarming periods from 1910-1941 and 1971-1995, with the IPO contributing 71% and 75%, respectively, to the difference between the median values of the externally forced trends and observed trends. The IPO transition from positive to negative in the late-1990s contributed 27% of the discrepancy between model median estimates of the forced part of the GMST trend and the observed trend from 1995 to 2013, with additional contributions that are probably due to internal variability outside of the Pacific(4) and an externally forced response from small volcanic eruptions(5). Understanding and quantifying the contribution of a specific source of internally generated variability-the IPO-to GMST trends is necessary to improve decadal climate prediction skill.

Matsumura, S, Huang G, Xie S-P, Yamazaki K.  2010.  SST-Forced and Internal Variability of the Atmosphere in an Ensemble GCM Simulation. Journal of the Meteorological Society of Japan. 88:43-62.   10.2151/jmsj.2010-104   Abstract
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Maloney, ED, Jiang XA, Xie SP, Benedict JJ.  2014.  Process-oriented diagnosis of East Pacific warm pool intraseasonal variability. Journal of Climate. 27:6305-6324.   10.1175/jcli-d-14-00053.1   AbstractWebsite

June-October east Pacific warm pool intraseasonal variability (ISV) is assessed in eight atmospheric general circulation simulations. Complex empirical orthogonal function analysis is used to document the leading mode of 30-90-day precipitation variability in the models and Tropical Rainfall Measuring Mission observations. The models exhibit a large spread in amplitude of the leading mode about the observed amplitude. Little relationship is demonstrated between the amplitude of the leading mode and the ability of models to simulate observed north-northeastward propagation. Several process-oriented diagnostics are explored that attempt to distinguish why some models produce superior ISV. A diagnostic based on the difference in 500-850-hPa averaged relative humidity between the top 5% and the bottom 10% of precipitation events exhibits a significant correlation with leading mode amplitude. Diagnostics based on the vertically integrated moist entropy budget also demonstrate success at discriminating models with strong and weak variability. In particular, the vertical component of gross moist stability exhibits a correlation with amplitude of -0.9, suggesting that models in which convection and associated divergent circulations are less efficient at discharging moisture from the column are better able to sustain strong ISV. Several other diagnostics are tested that show no significant relationship with leading mode amplitude, including the warm pool mean surface zonal wind, the strength of surface flux feedbacks, and 500-850-hPa averaged relative humidity for the top 1% of rainfall events. Vertical zonal wind shear and 850-hPa zonal wind do not appear to be good predictors of model success at simulating the observed northward propagation pattern.

Maloney, ED, Xie SP.  2013.  Sensitivity of tropical intraseasonal variability to the pattern of climate warming. Journal of Advances in Modeling Earth Systems. 5:32-47.   10.1029/2012ms000171   AbstractWebsite

An aquaplanet general circulation model is used to assess the sensitivity of intraseasonal variability to the pattern of sea surface temperature (SST) warming. Three warming patterns are used. Projected SST warming at the end of the 21st century from the Geophysical Fluid Dynamics Laboratory Climate Model 2.1 is one pattern, and zonally symmetric and globally uniform versions of this warming perturbation that have the same global mean SST change are the other two. Changes in intraseasonal variability are sensitive to the pattern of SST warming, with significant decreases in Madden-Julian oscillation (MJO)-timescale precipitation and wind variability for a zonally symmetric warming, and significant increases in MJO precipitation amplitude for a globally uniform warming. The amplitude of the wind variability change does not scale directly with precipitation, but is instead mediated by increased tropical dry static stability associated with SST warming. The patterned SST simulations have a zonal mean SST warming that maximizes on the equator, which fosters increased equatorial boundary layer convergence and also increases equatorial SST relative to the rest of the tropics. Both factors support increased convection, reflected in reduced gross moist stability (GMS). Mean precipitation is decreased and GMS is increased in the off-equatorial Eastern Hemisphere near 10 degrees S in the patterned warming simulations, where the strongest MJO-related intraseasonal precipitation variability is preferred in both the model and observations. It is argued that future changes in MJO activity may be sensitive to the pattern of SST warming, although these results should not be interpreted as a prediction of how MJO activity will change in future climate.

Ma, J, Xie SP, Xu HM.  2017.  Intermember variability of the summer northwest Pacific subtropical anticyclone in the ensemble forecast. Journal of Climate. 30:3927-3941.   10.1175/jcli-d-16-0638.1   AbstractWebsite

The accurate prediction of the East Asian summer monsoon (EASM) remains a major challenge for the climate research community. The northwest Pacific (NWP) subtropical anticyclone (NWPSA) is the dominant feature of the EASM low-level circulation variability. This study identifies two coupled modes between intermember anomalies of the NWPSA and sea surface temperature (SST). The first mode features SST anomalies over the tropical Pacific. This tropical Pacific mode has little impact on East Asian climate. The second mode features a strong coupling between SST in the north Indian Ocean (NIO)-NWP and NWPSA, with large impacts on East Asia. This resembles the Indo-western Pacific Ocean capacitor (IPOC) mode of interannual variability. Major differences exist in temporal evolution of the intermember SST spread between the equatorial Pacific and NIO. In the equatorial Pacific, the intermember SST spread grows gradually with lead time, while the spread of SST and low-level zonal wind grow rapidly from May to June in the NIO. The rapid growth over the NIO is due to positive feedback arising from the coupling between intermember anomalies of SST and winds. In post-El Nino summer, the intermember spread in equatorial Pacific SST forecast represents the variations in the timing of the El Nino phase transition. The late decay of El Nino relates to SST cooling and an anomalous cyclonic circulation over the South China Sea (SCS) but with little impact on East Asian climate. Thus, a better representation of the IPOC mode of regional ocean-atmosphere interaction over the NIO-NWP holds the key to improving the reliability of seasonal forecast of East Asian climate.

Ma, J, Xie S-P, Kosaka Y.  2012.  Mechanisms for Tropical Tropospheric Circulation Change in Response to Global Warming. Journal of Climate. 25:2979-2994.   10.1175/jcli-d-11-00048.1   Abstract
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Ma, J, Xie SP, Xu HM.  2017.  Contributions of the North Pacific Meridional Mode to Ensemble Spread of ENSO Prediction. Journal of Climate. 30:9167-9181.   10.1175/jcli-d-17-0182.1   AbstractWebsite

Seasonal prediction of El Nino-Southern Oscillation (ENSO) employs the ensemble method, which samples the uncertainty in initial conditions. While much attention has been given to the ensemble mean, the ensemble spread limits the reliability of the forecast. Spatiotemporal coevolution of intermember anomalies of sea surface temperature (SST) and low-level winds over the Pacific is examined in ensemble hindcasts. Two types of evolution of intermember SST anomalies in the equatorial Pacific are identified. The first features an apparent southwestward propagation of the SST spread from the subtropical northeastern Pacific southeast of Hawaii to the central equatorial Pacific in boreal winter-spring, indicative of the precursor effect of the North Pacific meridional mode (NPMM) on ENSO variability. Extratropical atmospheric variability generates ensemble spread in ENSO through wind-evaporation-SST (WES) in the subtropical northeastern Pacific and then Bjerknes feedback on the equator. In the second type, ensemble spread grows in the equatorial Pacific with a weak contribution from the subtropical southeastern Pacific in summer. Thus, the extratropical influence on ENSO evolution is much stronger in the Northern Hemisphere than in the Southern Hemisphere. The growth of Nino-4 SST ensemble spread shows a strong seasonality. In hindcasts initialized in September-March, the Nino-4 SST spread grows rapidly in January-April, stabilizes in May-June, and grows again in July-September. The rapid growth of the Nino-4 SST spread in January-April is due to the arrival of NPMM, while the slowdown in May-June and rapid growth in July-September are attributable primarily to the seasonality of equatorial ocean-atmosphere interaction. NPMM contributes to the ensemble spread in equatorial Pacific SST, limiting the reliability of ENSO prediction.