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1. Monthly Modulations of ENSO Teleconnections: Implications for Potential Predictability in North America

   https://doi.org/10.1175/JCLI-D-20-0391.1  

   Chapman, William E. ; Subramanian, Aneesh C. ; Xie, Shang-Ping ; Sierks, Michael D. ; Ralph, F. Martin ; Kamae, Youichi ( March 2021 , Journal of Climate)

   null (Ed.)

   Abstract Using a high-resolution atmospheric general circulation model simulation of unprecedented ensemble size, we examine potential predictability of monthly anomalies under El Niño Southern Oscillation (ENSO) forcing and back-ground internal variability. This study reveals the pronounced month-to-month evolution of both the ENSO forcing signal and internal variability. Internal variance in upper-level geopotential height decreases (∼ 10%) over the North Pacific during El Niño as the westerly jet extends eastward, allowing forced signals to account for a greater fraction of the total variability, and leading to increased potential predictability. We identify February and March of El Niño years as the most predictable months using a signal-to-noise analysis. In contrast, December, a month typically included in teleconnection studies, shows little-to-no potential predictability. We show that the seasonal evolution of SST forcing and variability leads to significant signal-to-noise relationships that can be directly linked to both upper-level and surface variable predictability for a given month. The stark changes in forced response, internal variability, and thus signal-to-noise across an ENSO season indicate that subseasonal fields should be used to diagnose potential predictability over North America associated with ENSO teleconnections. Using surface air temperature and precipitation as examples, this study provides motivation to pursue ‘windows of forecast opportunity’, in which statistical skill can be developed, tested, and leveraged to determine times and regions in which this skill may be elevated. 

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2. Easterly Waves in the East Pacific during the OTREC 2019 Field Campaign

   https://doi.org/10.1175/JAS-D-21-0128.1  

   ( November 2021 , Journal of the Atmospheric Sciences)

   Easterly waves (EWs) are off-equatorial tropical synoptic disturbances with a westward phase speed between 11 and 14 m s⁻¹. Over the east Pacific in boreal summer, the combination of EWs and other synoptic disturbances, plus local mechanisms associated with sea surface temperature (SST) gradients, define the climatological structure of the intertropical convergence zone (ITCZ). The east Pacific ITCZ has both deep and shallow convection that is linked to deep and shallow meridional circulations, respectively. The deep convection is located around 9°N over warm SSTs. The shallow convection is located around 6°N and is driven by the meridional SST gradient south of the ITCZ. This study aims to document the interaction between east Pacific EWs and the deep and shallow meridional circulations during the Organization of Tropical East Pacific Convection (OTREC) field campaign in 2019 using field campaign observations, ERA5, and satellite precipitation. We identified three EWs during the OTREC period using precipitation and dynamical fields. Composite analysis shows that the convectively active part of the EW enhances ITCZ deep convection and is associated with an export of column-integrated moist static energy (MSE) by vertical advection. The subsequent convectively suppressed, anticyclonic part of the EW produces an increase of moisture and column-integrated MSE by horizontal advection that likely enhances shallow convection and the shallow overturning flow at 850 hPa over the southern part of the ITCZ. Therefore, EWs appear to strongly modulate shallow and deep circulations in the east Pacific ITCZ.

    

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3. Impacts of Projected Arctic Sea Ice Loss on Daily Weather Patterns over North America

   https://doi.org/10.1175/JCLI-D-23-0389.1  

   Gervais, Melissa ; Sun, Lantao ; Deser, Clara ( February 2024 , Journal of Climate)

   Future Arctic sea ice loss has a known impact on Arctic amplification (AA) and mean atmospheric circulation. Furthermore, several studies have shown it leads to a decreased variance in temperature over North America. In this study, we analyze results from two fully coupled Community Earth System Model (CESM) Whole Atmosphere Community Climate Model (WACCM4) simulations with sea ice nudged to either the ensemble mean of WACCM historical runs averaged over the 1980–99 period for the control (CTL) or projected RCP8.5 values over the 2080–99 period for the experiment (EXP). Dominant large-scale meteorological patterns (LSMPs) are then identified using self-organizing maps applied to winter daily 500-hPa geopotential height anomalies () over North America. We investigate how sea ice loss (EXP − CTL) impacts the frequency of these LSMPs and, through composite analysis, the sensible weather associated with them. We find differences in LSMP frequency but no change in residency time, indicating there is no stagnation of the flow with sea ice loss. Sea ice loss also acts to de-amplify and/or shift thethat characterize these LSMPs and their associated anomalies in potential temperature at 850 hPa. Impacts on precipitation anomalies are more localized and consistent with changes in anomalous sea level pressure. With this LSMP framework we provide new mechanistic insights, demonstrating a role for thermodynamic, dynamic, and diabatic processes in sea ice impacts on atmospheric variability. Understanding these processes from a synoptic perspective is critical as some LSMPs play an outsized role in producing the mean response to Arctic sea ice loss.

   The goal of this study is to understand how future Arctic sea ice loss might impact daily weather patterns over North America. We use a global climate model to produce one set of simulations where sea ice is similar to present conditions and another that represents conditions at the end of the twenty-first century. Daily patterns in large-scale circulation at roughly 5.5 km in altitude are then identified using a machine learning method. We find that sea ice loss tends to de-amplify these patterns and their associated impacts on temperature nearer the surface. Our methodology allows us to probe more deeply into the mechanisms responsible for these changes, which provides a new way to understand how sea ice loss can impact the daily weather we experience.

    

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4. Teleconnections Governing the Interannual Variability of Great Plains Low-Level Jets in May

   https://doi.org/10.1175/JCLI-D-20-0451.1  

   Agrawal, Shubhi ; Ferguson, Craig R. ; Bosart, Lance ; Burrows, D. Alex ( March 2021 , Journal of Climate)

   null (Ed.)

   Abstract A spectral analysis of Great Plains 850-hPa meridional winds (V850) from ECMWF’s coupled climate reanalysis of 1901-2010 (CERA-20C) reveals that their warm season (April-September) interannual variability peaks in May with 2-6 year periodicity, suggestive of an underlying teleconnection influence on low-level jets (LLJs). Using an objective, dynamical jet classification framework based on 500-hPa wave activity, we pursue a large scale teleconnection hypothesis separately for LLJs that are uncoupled (LLJUC) and coupled (LLJC) to the upper-level jet stream. Differentiating between jet types enables isolation of their respective sources of variability. In the South Central Plains (SCP), May LLJCs account for nearly 1.6 times more precipitation and 1.5 times greater V850 compared to LLJUCs. Composite analyses of May 250-hPa geopotential height (Z250) conditioned on LLJC and LLJUC frequencies highlight a distinct planetary-scale Rossby wave pattern with wavenumber-five, indicative of an underlying Circumglobal Teleconnection (CGT). An index of May CGT is found to be significantly correlated with both LLJC ( r = 0.62) and LLJUC ( r = −0.48) frequencies. Additionally, a significant correlation is found between May LLJUC frequency and NAO ( r = 0.33). Further analyses expose decadal scale variations in the CGT-LLJC(LLJUC) teleconnection that are linked to the PDO. Dynamically, these large scale teleconnections impact LLJ class frequency and intensity via upper-level geopotential anomalies over the western U.S. that modulate near-surface geopotential and temperature gradients across the SCP. 

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5. Climatology of Lake-Effect Snow Days Along the Southern Shore of Lake Michigan: What Is the Sensitivity to Environmental Factors and Snowband Morphology?

   https://doi.org/10.3389/frwa.2022.826293  

   Clark, Craig A. ; Metz, Nicholas D. ; Goebbert, Kevin H. ; Ganesh-Babu, Bharath ; Ballard, Nolan ; Blackford, Andrew ; Bottom, Andrew ; Britt, Catherine ; Carmer, Kelly ; Davis, Quenten ; et al ( March 2022 , Frontiers in Water)

   The Laurentian Great Lakes have substantial influences on regional climatology, particularly with impactful lake-effect snow events. This study examines the snowfall, cloud-inferred snow band morphology, and environment of lake-effect snow days along the southern shore of Lake Michigan for the 1997–2017 period. Suitable days for study were identified based on the presence of lake-effect clouds assessed in a previous study and extended through 2017, combined with an independent classification of likely lake-effect snow days based on independent snowfall data and weather map assessments. The primary goals are to identify lake-effect snow days and evaluate the snowfall distribution and modes of variability, the sensitivity to thermodynamic and flow characteristics within the upstream sounding at Green Bay, WI, and the influences of snowband morphology. Over 300 lake-effect days are identified during the study period, with peak mean snowfall within the lake belt extending from southwest Michigan to northern Indiana. Although multiple lake-effect morphological types are often observed on the same day, the most common snow band morphology is wind parallel bands. Relative to days with wind parallel bands, the shoreline band morphology is more common with a reduced lower-tropospheric zonal wind component within the upstream sounding at Green Bay, WI, as well as higher sea-level pressure and 500-hPa geopotential height anomalies to the north of the Great Lakes. Snowfall is sensitive to band morphology, with higher snowfall for shoreline band structures than for wind parallel bands, especially due south of Lake Michigan. Snowfall is also sensitive to thermodynamic and flow properties, with a greater sensitivity to temperature in southwest Michigan and to flow properties in northwest Indiana. 

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