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1. Prediction of Diverse Boreal Summer Intraseasonal Oscillation in the GFDL SPEAR Model

   https://doi.org/10.1175/JCLI-D-23-0601.1  

   Xiang, Baoqiang ; Wang, Bin ; Chen, Guosen ; Delworth, Thomas L. ( April 2024 , Journal of Climate)

   Boreal summer intraseasonal oscillation (BSISO) is a primary source of predictability for summertime weather and climate on the subseasonal-to-seasonal (S2S) time scale. Using the GFDL SPEAR S2S prediction system, we evaluate the BSISO prediction skills based on 20-yr (2000–19) hindcast experiments with initializations from May to October. It is revealed that the overall BSISO prediction skill using all hindcasts reaches out to 22 days as measured by BSISO indices before the bivariate anomalous correlation coefficient (ACC) drops below 0.5. Results also show that the northeastward-propagating canonical BSISO (CB) event has a higher prediction skill than the northward dipole BSISO (DB) event (28 vs 23 days). This is attributed to CB’s more periodic nature, resulting in its longer persistence, while DB events are more episodic accompanied by a rapid demise after reaching maximum enhanced convection over the equatorial Indian Ocean. From a forecaster’s perspective, a precursory strong Kelvin wave component in the equatorial western Pacific signifies the subsequent development of a CB event, which is likely more predictable. Investigation of individual CB events shows a large interevent spread in terms of their prediction skills. For CB, the events with weaker and fluctuating amplitude during their lifetime have relatively lower prediction skills likely linked to their weaker convection–circulation coupling. Interestingly, the prediction skills of individual CB events tend to be relatively higher and less scattered during late summer (August–October) than those in early summer (May–July), suggestive of the seasonal modulation on the evolution and predictability of BSISO.

   The advance of subseasonal-to-seasonal (S2S) prediction largely depends on dynamical models’ ability to predict some major intrinsic modes in the climate system, including the boreal summer intraseasonal oscillation (BSISO). Using a newly developed S2S prediction system, we thoroughly evaluated its performance in predicting BSISO, and revealed the skill dependence on the BSISO propagation diversity. Here we provide physical explanations of what influences the BSISO predictions and identify different precursory signals for two types of BSISO, which have important implications for operational forecasts.

    

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2. The Weakening of the Stratospheric Polar Vortex and the Subsequent Surface Impacts as Consequences to Arctic Sea Ice Loss

   https://doi.org/10.1175/JCLI-D-23-0128.1  

   Liang, Yu-Chiao ; Kwon, Young-Oh ; Frankignoul, Claude ; Gastineau, Guillaume ; Smith, Karen L. ; Polvani, Lorenzo M. ; Sun, Lantao ; Peings, Yannick ; Deser, Clara ; Zhang, Ruonan ; et al ( January 2024 , Journal of Climate)

   This study investigates the stratospheric response to Arctic sea ice loss and subsequent near-surface impacts by analyzing 200-member coupled experiments using the Whole Atmosphere Community Climate Model version 6 (WACCM6) with preindustrial, present-day, and future sea ice conditions specified following the protocol of the Polar Amplification Model Intercomparison Project. The stratospheric polar vortex weakens significantly in response to the prescribed sea ice loss, with a larger response to greater ice loss (i.e., future minus preindustrial) than to smaller ice loss (i.e., future minus present-day). Following the weakening of the stratospheric circulation in early boreal winter, the coupled stratosphere–troposphere response to ice loss strengthens in late winter and early spring, projecting onto a negative North Atlantic Oscillation–like pattern in the lower troposphere. To investigate whether the stratospheric response to sea ice loss and subsequent surface impacts depend on the background oceanic state, ensemble members are initialized by a combination of varying phases of Atlantic multidecadal variability (AMV) and interdecadal Pacific variability (IPV). Different AMV and IPV states combined, indeed, can modulate the stratosphere–troposphere responses to sea ice loss, particularly in the North Atlantic sector. Similar experiments with another climate model show that, although strong sea ice forcing also leads to tighter stratosphere–troposphere coupling than weak sea ice forcing, the timing of the response differs from that in WACCM6. Our findings suggest that Arctic sea ice loss can affect the stratospheric circulation and subsequent tropospheric variability on seasonal time scales, but modulation by the background oceanic state and model dependence need to be taken into account.

   This study uses new-generation climate models to better understand the impacts of Arctic sea ice loss on the surface climate in the midlatitudes, including North America, Europe, and Siberia. We focus on the stratosphere–troposphere pathway, which involves the weakening of stratospheric winds and its downward coupling into the troposphere. Our results show that Arctic sea ice loss can affect the surface climate in the midlatitudes via the stratosphere–troposphere pathway, and highlight the modulations from background mean oceanic states as well as model dependence.

    

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3. Contrasting Ocean–Atmosphere Dynamics Mediate Flood Hazard across the Mississippi River Basin

   https://doi.org/10.1175/EI-D-22-0015.1  

   Muñoz, Samuel E. ; Hamilton, Brynnydd ; Parazin, B. ( January 2023 , Earth Interactions)

   The Mississippi River basin drains nearly one-half of the contiguous United States, and its rivers serve as economic corridors that facilitate trade and transportation. Flooding remains a perennial hazard on the major tributaries of the Mississippi River basin, and reducing the economic and humanitarian consequences of these events depends on improving their seasonal predictability. Here, we use climate reanalysis and river gauge data to document the evolution of floods on the Missouri and Ohio Rivers—the two largest tributaries of the Mississippi River—and how they are influenced by major modes of climate variability centered in the Pacific and Atlantic Oceans. We show that the largest floods on these tributaries are preceded by the advection and convergence of moisture from the Gulf of Mexico following distinct atmospheric mechanisms, where Missouri River floods are associated with heavy spring and summer precipitation events delivered by the Great Plains low-level jet, whereas Ohio River floods are associated with frontal precipitation events in winter when the North Atlantic subtropical high is anomalously strong. Further, we demonstrate that the El Niño–Southern Oscillation can serve as a precursor for floods on these rivers by mediating antecedent soil moisture, with Missouri River floods often preceded by a warm eastern tropical Pacific (El Niño) and Ohio River floods often preceded by a cool eastern tropical Pacific (La Niña) in the months leading up peak discharge. We also use recent floods in 2019 and 2021 to demonstrate how linking flood hazard to sea surface temperature anomalies holds potential to improve seasonal predictability of hydrologic extremes on these rivers.

    

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4. The North Pacific Pacemaker Effect on Historical ENSO and Its Mechanisms

   https://doi.org/10.1175/JCLI-D-19-0040.1  

   Amaya, Dillon J. ; Kosaka, Yu ; Zhou, Wenyu ; Zhang, Yu ; Xie, Shang-Ping ; Miller, Arthur J. ( October 2019 , Journal of Climate)

   Studies have indicated that North Pacific sea surface temperature (SST) variability can significantly modulate El Niño–Southern Oscillation (ENSO), but there has been little effort to put extratropical–tropical interactions into the context of historical events. To quantify the role of the North Pacific in pacing the timing and magnitude of observed ENSO, we use a fully coupled climate model to produce an ensemble of North Pacific Ocean–Global Atmosphere (nPOGA) SST pacemaker simulations. In nPOGA, SST anomalies are restored back to observations in the North Pacific (>15°N) but are free to evolve throughout the rest of the globe. We find that the North Pacific SST has significantly influenced observed ENSO variability, accounting for approximately 15% of the total variance in boreal fall and winter. The connection between the North and tropical Pacific arises from two physical pathways: 1) a wind–evaporation–SST (WES) propagating mechanism, and 2) a Gill-like atmospheric response associated with anomalous deep convection in boreal summer and fall, which we refer to as the summer deep convection (SDC) response. The SDC response accounts for 25% of the observed zonal wind variability around the equatorial date line. On an event-by-event basis, nPOGA most closely reproduces the 2014/15 and the 2015/16 El Niños. In particular, we show that the 2015 Pacific meridional mode event increased wind forcing along the equator by 20%, potentially contributing to the extreme nature of the 2015/16 El Niño. Our results illustrate the significant role of extratropical noise in pacing the initiation and magnitude of ENSO events and may improve the predictability of ENSO on seasonal time scales.

    

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5. Remote effects of Tibetan Plateau spring land temperature on global subseasonal to seasonal precipitation prediction and comparison with effects of sea surface temperature: the GEWEX/LS4P Phase I experiment

   https://doi.org/10.1007/s00382-023-06905-5  

   Xue, Yongkang ; Diallo, Ismaila ; Boone, Aaron A. ; Zhang, Yang ; Zeng, Xubin ; Lau, William K. M. ; Neelin, J. David ; Yao, Tandong ; Tang, Qi ; Sato, Tomonori ; et al ( August 2023 , Climate Dynamics)

   The prediction skill for precipitation anomalies in late spring and summer months—a significant component of extreme climate events—has remained stubbornly low for years. This paper presents a new idea that utilizes information on boreal spring land surface temperature/subsurface temperature (LST/SUBT) anomalies over the Tibetan Plateau (TP) to improve prediction of subsequent summer droughts/floods over several regions over the world, East Asia and North America in particular. The work was performed in the framework of the GEWEX/LS4P Phase I (LS4P-I) experiment, which focused on whether the TP LST/SUBT provides an additional source for subseasonal-to-seasonal (S2S) predictability. The summer 2003, when there were severe drought/flood over the southern/northern part of the Yangtze River basin, respectively, has been selected as the focus case. With the newly developed LST/SUBT initialization method, the observed surface temperature anomaly over the TP has been partially produced by the LS4P-I model ensemble mean, and 8 hotspot regions in the world were identified where June precipitation is significantly associated with anomalies of May TP land temperature. Consideration of the TP LST/SUBT effect has produced about 25–50% of observed precipitation anomalies in most hotspot regions. The multiple models have shown more consistency in the hotspot regions along the Tibetan Plateau-Rocky Mountain Circumglobal (TRC) wave train. The mechanisms for the LST/SUBT effect on the 2003 drought over the southern part of the Yangtze River Basin are discussed. For comparison, the global SST effect has also been tested and 6 regions with significant SST effects were identified in the 2003 case, explaining about 25–50% of precipitation anomalies over most of these regions. This study suggests that the TP LST/SUBT effect is a first-order source of S2S precipitation predictability, and hence it is comparable to that of the SST effect. With the completion of the LS4P-I, the LS4P-II has been launched and the LS4P-II protocol is briefly presented.

    

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