Liang Yu-Chiao

No Thumbnail Available
Last Name
First Name

Search Results

Now showing 1 - 9 of 9
  • Article
    Amplified seasonal cycle in hydroclimate over the Amazon river basin and its plume region
    (Nature Research, 2020-09-01) Liang, Yu-Chiao ; Lo, Min-Hui ; Lan, Chia-Wei ; Seo, Hyodae ; Ummenhofer, Caroline C. ; Yeager, Stephen G. ; Wu, Ren-Jie ; Steffen, John D.
    The Amazon river basin receives ~2000 mm of precipitation annually and contributes ~17% of global river freshwater input to the oceans; its hydroclimatic variations can exert profound impacts on the marine ecosystem in the Amazon plume region (APR) and have potential far-reaching influences on hydroclimate over the tropical Atlantic. Here, we show that an amplified seasonal cycle of Amazonia precipitation, represented by the annual difference between maximum and minimum values, during the period 1979–2018, leads to enhanced seasonalities in both Amazon river discharge and APR ocean salinity. An atmospheric moisture budget analysis shows that these enhanced seasonal cycles are associated with similar amplifications in the atmospheric vertical and horizontal moisture advections. Hierarchical sensitivity experiments using global climate models quantify the relationships of these enhanced seasonalities. The results suggest that an intensified hydroclimatological cycle may develop in the Amazonia atmosphere-land-ocean coupled system, favouring more extreme terrestrial and marine conditions.
  • Article
    Impacts of Arctic sea ice on cold season atmospheric variability and trends estimated from observations and a multimodel large ensemble
    (American Meteorological Society, 2021-09-24) Liang, Yu-Chiao ; Frankignoul, Claude ; Kwon, Young-Oh ; Gastineau, Guillaume ; Manzini, Elisa ; Danabasoglu, Gokhan ; Suo, Lingling ; Yeager, Stephen G. ; Gao, Yongqi ; Attema, Jisk J. ; Cherchi, Annalisa ; Ghosh, Rohit ; Matei, Daniela ; Mecking, Jennifer V. ; Tian, Tian ; Zhang, Ying
    To examine the atmospheric responses to Arctic sea ice variability in the Northern Hemisphere cold season (from October to the following March), this study uses a coordinated set of large-ensemble experiments of nine atmospheric general circulation models (AGCMs) forced with observed daily varying sea ice, sea surface temperature, and radiative forcings prescribed during the 1979–2014 period, together with a parallel set of experiments where Arctic sea ice is substituted by its climatology. The simulations of the former set reproduce the near-surface temperature trends in reanalysis data, with similar amplitude, and their multimodel ensemble mean (MMEM) shows decreasing sea level pressure over much of the polar cap and Eurasia in boreal autumn. The MMEM difference between the two experiments allows isolating the effects of Arctic sea ice loss, which explain a large portion of the Arctic warming trends in the lower troposphere and drive a small but statistically significant weakening of the wintertime Arctic Oscillation. The observed interannual covariability between sea ice extent in the Barents–Kara Seas and lagged atmospheric circulation is distinguished from the effects of confounding factors based on multiple regression, and quantitatively compared to the covariability in MMEMs. The interannual sea ice decline followed by a negative North Atlantic Oscillation–like anomaly found in observations is also seen in the MMEM differences, with consistent spatial structure but much smaller amplitude. This result suggests that the sea ice impacts on trends and interannual atmospheric variability simulated by AGCMs could be underestimated, but caution is needed because internal atmospheric variability may have affected the observed relationship.
  • Article
    Could the North Pacific Oscillation be modified by the initiation of the East Asian winter monsoon?
    (American Meteorological Society, 2020-02-21) Tseng, Yu-Heng ; Ding, Ruiqiang ; Zhao, Sen ; Kuo, Yi-chun ; Liang, Yu-Chiao
    This study investigates the modulation of North Pacific Oscillation (NPO) variability upon initiation of the East Asian winter monsoon (EAWM). The data show that the initiation of EAWM in the Philippine Sea strongly connects to the southern lobe variability of the NPO in January followed by a basin-scale oceanic Victoria mode pattern. No apparent connection was found for the northern lobe of the NPO when the ENSO signals are removed. The strengthening of the EAWM in November interacts with the Kuroshio front and generates a low-level heating source in the Philippine Sea. Significant Rossby wave sources are then formed in the lower to midtroposphere. Wave ray tracing analyses confirm the atmospheric teleconnection established by the Rossby wave propagation in the mid- to upper troposphere. Analyses of the origin of wave trajectories from the Philippine Sea show a clear eastward propagating pathway that affects the southern lobe of the NPO from the southern lobe of the western Pacific pattern at 500 hPa and above on the time scale of 20 days. No ray trajectories from the lower troposphere can propagate eastward to influence the central-eastern subtropical Pacific. The wave propagation process is further supported by the coupled model experiments.
  • Article
    Quantification of the arctic sea ice-driven atmospheric circulation variability in coordinated large ensemble simulations
    (American Geophysical Union, 2019-12-26) Liang, Yu‐Chiao ; Kwon, Young-Oh ; Frankignoul, Claude ; Danabasoglu, Gokhan ; Yeager, Stephen G. ; Cherchi, Annalisa ; Gao, Yongqi ; Gastineau, Guillaume ; Ghosh, Rohit ; Matei, Daniela ; Mecking, Jennifer V. ; Peano, Daniele ; Suo, Lingling ; Tian, Tian
    A coordinated set of large ensemble atmosphere‐only simulations is used to investigate the impacts of observed Arctic sea ice‐driven variability (SIDV) on the atmospheric circulation during 1979–2014. The experimental protocol permits separating Arctic SIDV from internal variability and variability driven by other forcings including sea surface temperature and greenhouse gases. The geographic pattern of SIDV is consistent across seven participating models, but its magnitude strongly depends on ensemble size. Based on 130 members, winter SIDV is ~0.18 hPa2 for Arctic‐averaged sea level pressure (~1.5% of the total variance), and ~0.35 K2 for surface air temperature (~21%) at interannual and longer timescales. The results suggest that more than 100 (40) members are needed to separate Arctic SIDV from other components for dynamical (thermodynamical) variables, and insufficient ensemble size always leads to overestimation of SIDV. Nevertheless, SIDV is 0.75–1.5 times as large as the variability driven by other forcings over northern Eurasia and Arctic.
  • Article
    Autumn Arctic Pacific sea ice dipole as a source of predictability for subsequent spring Barents Sea ice condition
    (American Meteorological Society, 2020-12-23) Liang, Yu-Chiao ; Kwon, Young-Oh ; Frankignoul, Claude
    This study uses observational and reanalysis datasets in 1980–2016 to show a close connection between a boreal autumn sea ice dipole in the Arctic Pacific sector and sea ice anomalies in the Barents Sea (BS) during the following spring. The September–October Arctic Pacific sea ice dipole variations are highly correlated with the subsequent April–May BS sea ice variations (r = 0.71). The strong connection between the regional sea ice variabilities across the Arctic uncovers a new source of predictability for spring BS sea ice prediction at 7-month lead time. A cross-validated linear regression prediction model using the Arctic Pacific sea ice dipole with 7-month lead time is demonstrated to have significant prediction skills with 0.54–0.85 anomaly correlation coefficients. The autumn sea ice dipole, manifested as sea ice retreat in the Beaufort and Chukchi Seas and expansion in the East Siberian and Laptev Seas, is primarily forced by preceding atmospheric shortwave anomalies from late spring to early autumn. The spring BS sea ice increases are mostly driven by an ocean-to-sea ice heat flux reduction in preceding months, associated with reduced horizontal ocean heat transport into the BS. The dynamical linkage between the two regional sea ice anomalies is suggested to involve positive stratospheric polar cap anomalies during autumn and winter, with its center slowly moving toward Greenland. The migration of the stratospheric anomalies is followed in midwinter by a negative North Atlantic Oscillation–like pattern in the troposphere, leading to reduced ocean heat transport into the BS and sea ice extent increase.
  • Article
    Terrestrial water storage anomalies emphasize interannual variations in global mean sea level during 1997-1998 and 2015-2016 El Nino Events
    (American Geophysical Union, 2021-09-07) Kuo, Yan-Ning ; Lo, Min-Hui ; Liang, Yu-Chiao ; Tseng, Yu-Heng ; Hsu, Chia-Wei
    Interannual variations in global mean sea level (GMSL) closely correlate with the evolution of El Niño-Southern Oscillation. However, GMSL differences occur in extreme El Niños; for example, in the 2015–2016 and 1997–1998 El Niños, the peak GMSL during the mature stage of the former (9.00 mm) is almost 2.5 times higher than the latter (3.72 mm). Analyses from satellite and reanalysis data sets show that the disparity in GMSL is primarily due to barystatic (ocean mass) changes. We find that the 2015–2016 event developed not purely as an Eastern Pacific El Niño event but with Central Pacific (CP) El Niño forcing. CP El Niños contribute to a stronger negative anomaly of global terrestrial water storage and subsequent higher barystatic heights. Our results suggest that the mechanism of hydrology-related interannual variations of GMSL should be further emphasized, as more CP El Niño events are projected to occur.
  • Article
    Arctic troposphere warming driven by external radiative forcing and modulated by the Pacific and Atlantic
    (American Geophysical Union, 2022-12-04) Suo, Lingling ; Gao, Yongqi ; Gastineau, Guillaume ; Liang, Yu‐Chiao ; Ghosh, Rohit ; Tian, Tian ; Zhang, Ying ; Kwon, Young‐Oh ; Matei, Daniela ; Otterå, Odd Helge ; Yang, Shuting
    During the past decades, the Arctic has experienced significant tropospheric warming, with varying decadal warming rates. However, the relative contributions from potential drivers and modulators of the warming are yet to be further quantified. Here, we utilize a unique set of multi‐model large‐ensemble atmospheric simulations to isolate the respective contributions from the combined external radiative forcing (ERF‐AL), interdecadal Pacific variability (IPV), Atlantic multidecadal variability (AMV), and Arctic sea‐ice concentration changes (ASIC) to the warming during 1979–2013. In this study, the ERF‐AL impacts are the ERF impacts directly on the atmosphere and land surface, excluding the indirect effects through SST and SIC feedback. The ERF‐AL is the primary driver of the April–September tropospheric warming during 1979–2013, and its warming effects vary at decadal time scales. The IPV and AMV intensify the warming during their transitioning periods to positive phases and dampen the warming during their transitioning periods to negative phases. The IPV impacts are prominent in winter and spring and are stronger than AMV impacts on 1979–2013 temperature trends. The warming impacts of ASIC are generally restricted to below 700 hPa and are strongest in autumn and winter. The combined effects of these factors reproduce the observed accelerated and step‐down Arctic warming in different decades, but the intensities of the reproduced decadal variations are generally weaker than in the observed.
  • Article
    Simulated contribution of the interdecadal Pacific oscillation to the west Eurasia cooling in 1998–2013
    (IOP Publishing, 2022-08-30) Suo, Lingling ; Gastineau, Guillaume ; Gao, Yongqi ; Liang, Yu-Chiao ; Ghosh, Rohit ; Tian, Tian ; Zhang, Ying ; Kwon, Young-Oh ; Otterå, Odd Helge ; Yang, Shuting ; Matei, Daniela
    Large ensemble simulations with six atmospheric general circulation models involved are utilized to verify the interdecadal Pacific oscillation (IPO) impacts on the trend of Eurasian winter surface air temperatures (SAT) during 1998–2013, a period characterized by the prominent Eurasia cooling (EC). In our simulations, IPO brings a cooling trend over west-central Eurasia in 1998–2013, about a quarter of the observed EC in that area. The cooling is associated with the phase transition of the IPO to a strong negative. However, the standard deviation of the area-averaged SAT trends in the west EC region among ensembles, driven by internal variability intrinsic due to the atmosphere and land, is more than three times the isolated IPO impacts, which can shadow the modulation of the IPO on the west Eurasia winter climate.
  • Article
    Forcing and impact of the Northern Hemisphere continental snow cover in 1979–2014
    (European Geosciences Union, 2023-05-23) Gastineau, Guillaume ; Frankignoul, Claude ; Gao, Yongqi ; Liang, Yu-Chiao ; Kwon, Young-Oh ; Cherchi, Annalisa ; Ghosh, Rohit ; Manzini, Elisa ; Matei, Daniela ; Mecking, Jennifer ; Suo, Lingling ; Tian, Tian ; Yang, Shuting ; Zhang, Ying
    The main drivers of the continental Northern Hemisphere snow cover are investigated in the 1979–2014 period. Four observational datasets are used as are two large multi-model ensembles of atmosphere-only simulations with prescribed sea surface temperature (SST) and sea ice concentration (SIC). A first ensemble uses observed interannually varying SST and SIC conditions for 1979–2014, while a second ensemble is identical except for SIC with a repeated climatological cycle used. SST and external forcing typically explain 10 % to 25 % of the snow cover variance in model simulations, with a dominant forcing from the tropical and North Pacific SST during this period. In terms of the climate influence of the snow cover anomalies, both observations and models show no robust links between the November and April snow cover variability and the atmospheric circulation 1 month later. On the other hand, the first mode of Eurasian snow cover variability in January, with more extended snow over western Eurasia, is found to precede an atmospheric circulation pattern by 1 month, similar to a negative Arctic oscillation (AO). A decomposition of the variability in the model simulations shows that this relationship is mainly due to internal climate variability. Detailed outputs from one of the models indicate that the western Eurasia snow cover anomalies are preceded by a negative AO phase accompanied by a Ural blocking pattern and a stratospheric polar vortex weakening. The link between the AO and the snow cover variability is strongly related to the concomitant role of the stratospheric polar vortex, with the Eurasian snow cover acting as a positive feedback for the AO variability in winter. No robust influence of the SIC variability is found, as the sea ice loss in these simulations only drives an insignificant fraction of the snow cover anomalies, with few agreements among models.