More Like this

1. Characteristics, Evolution, and Formation of Cold Air Outbreaks in the Great Plains of the United States

   https://doi.org/10.1175/JCLI-D-21-0772.1  

   Millin, Oliver T. ; Furtado, Jason C. ; Basara, Jeffrey B. ( July 2022 , Journal of Climate)

   Wintertime cold air outbreaks (CAOs) in the Great Plains of the United States have significant socioeconomic, environmental, and infrastructural impacts; the events of December 1983 and February 2021 are key examples of this. Previous studies have investigated CAOs in other parts of North America, particularly the eastern United States, but the development of CAOs in the Great Plains and their potential subseasonal-to-seasonal (S2S) predictability have yet to be assessed. This study first identifies 37 large-scale CAOs in the Great Plains between 1950 and 2021, before examining their characteristics, evolution, and driving mechanisms. These events occur under two dominant weather regimes at event onset: one set associated with anomalous ridging over Alaska and the other set associated with anomalous pan-Arctic ridging. Alaskan ridge CAOs evolve quickly (i.e., on synoptic time scales) and involve stratospheric wave reflection. Conversely, Arctic high CAOs are preceded by weak stratospheric polar vortex conditions several weeks prior to the event. Both categories of CAOs feature anomalous upward wave activity flux from Siberia, with downward wave activity flux over Canada seen only in the Alaskan ridge CAOs. The rapid development of the Alaskan ridge CAOs, also linked with a North Pacific wave train and anomalous wave activitymore »flux from the central Pacific, suggests that these events could be forced by tropical modes of variability. These findings present evidence that different forcing mechanisms, with contrasting time scales, may produce distinct sources of predictability for these CAOs on the S2S time scale.

   « less
2. S2S Prediction in GFDL SPEAR: MJO Diversity and Teleconnections

   https://doi.org/10.1175/BAMS-D-21-0124.1  

   Xiang, Baoqiang ; Harris, Lucas ; Delworth, Thomas L. ; Wang, Bin ; Chen, Guosen ; Chen, Jan-Huey ; Clark, Spencer K. ; Cooke, William F. ; Gao, Kun ; Huff, J. Jacob ; et al ( February 2022 , Bulletin of the American Meteorological Society)

   Abstract A subseasonal-to-seasonal (S2S) prediction system was recently developed using the GFDL Seamless System for Prediction and Earth System Research (SPEAR) global coupled model. Based on 20-yr hindcast results (2000–19), the boreal wintertime (November–April) Madden–Julian oscillation (MJO) prediction skill is revealed to reach 30 days measured before the anomaly correlation coefficient of the real-time multivariate (RMM) index drops to 0.5. However, when the MJO is partitioned into four distinct propagation patterns, the prediction range extends to 38, 31, and 31 days for the fast-propagating, slow-propagating, and jumping MJO patterns, respectively, but falls to 23 days for the standing MJO. A further improvement of MJO prediction requires attention to the standing MJO given its large gap with its potential predictability (38 days). The slow-propagating MJO detours southward when traversing the Maritime Continent (MC), and confronts the MC prediction barrier in the model, while the fast-propagating MJO moves across the central MC without this prediction barrier. The MJO diversity is modulated by stratospheric quasi-biennial oscillation (QBO): the standing (slow-propagating) MJO coincides with significant westerly (easterly) phases of QBO, partially explaining the contrasting MJO prediction skill between these two QBO phases. The SPEAR model shows its capability, beyond the propagation, in predicting theirmore »initiation for different types of MJO along with discrete precursory convection anomalies. The SPEAR model skillfully predicts the observed distinct teleconnections over the North Pacific and North America related to the standing, jumping, and fast-propagating MJO, but not the slow-propagating MJO. These findings highlight the complexities and challenges of incorporating MJO prediction into the operational prediction of meteorological variables.« less
3. Subseasonal predictability of the North Atlantic Oscillation

   https://doi.org/10.1088/1748-9326/abe781  

   Albers, John R. ; Newman, Matthew ( March 2021 , Environmental Research Letters)

   Skillfully predicting the North Atlantic Oscillation (NAO), and the closely related northern annular mode (NAM), on ‘subseasonal’ (weeks to less than a season) timescales is a high priority for operational forecasting centers, because of the NAO’s association with high-impact weather events, particularly during winter. Unfortunately, the relatively fast, weather-related processes dominating total NAO variability are unpredictable beyond about two weeks. On longer timescales, the tropical troposphere and the stratosphere provide some predictability, but they contribute relatively little to total NAO variance. Moreover, subseasonal forecasts are only sporadically skillful, suggesting the practical need to identify the fewer potentially predictable events at the time of forecast. Here we construct an observationally based linear inverse model (LIM) that predicts when, and diagnoses why, subseasonal NAO forecasts will be most skillful. We use the LIM to identify those dynamical modes that, despite capturing only a fraction of overall NAO variability, are largely responsible for extended-range NAO skill. Predictable NAO events stem from the linear superposition of these modes, which represent joint tropical sea-surface temperature-lower stratosphere variability plus a single mode capturing downward propagation from the upper stratosphere. Our method has broad applicability because both the LIM and the state-of-the-art European Centre for Medium-Rangemore »Weather Forecasts Integrated Forecast System (IFS) have higher (and comparable) skill for the same set of predicted high skill forecast events, suggesting that the low-dimensional predictable subspace identified by the LIM is relevant to real-world subseasonal NAO predictions.

   « less
4. The Consistency of MJO Teleconnection Patterns on Interannual Time Scales

   https://doi.org/10.1175/JCLI-D-19-0510.1  

   Tseng, Kai-Chih ; Maloney, Eric ; Barnes, Elizabeth A. ( May 2020 , Journal of Climate)

   The Madden–Julian oscillation (MJO) excites strong variations in extratropical geopotential heights that modulate extratropical weather, making the MJO an important predictability source on subseasonal to seasonal time scales (S2S). Previous research demonstrates a strong similarity of teleconnection patterns across MJO events for certain MJO phases (i.e., pattern consistency) and increased model ensemble agreement during these phases that is beneficial for extended numerical weather forecasts. However, the MJO’s ability to modulate extratropical weather varies greatly on interannual time scales, which brings extra uncertainty in leveraging the MJO for S2S prediction. Few studies have investigated the mechanisms responsible for variations in the consistency of MJO tropical–extratropical teleconnections on interannual time scales. This study uses reanalysis data, ensemble simulations of a linear baroclinic model, and a Rossby wave ray tracing algorithm to demonstrate that two mechanisms largely determine the interannual variability of MJO teleconnection consistency. First, the meridional shift of stationary Rossby wave ray paths indicates increases (decreases) in the MJO’s extratropical modulation during La Niña (El Niño) years. Second, a previous study proposed that the constructive interference of Rossby wave signals caused by a dipole Rossby wave source pattern across the subtropical jet during certain MJO phases produces a consistent MJO teleconnection.more »However, this dipole feature is less clear in both El Niño and La Niña years due to the extension and contraction of MJO convection, respectively, which would decrease the MJO’s influence in the extratropics. Hence, considering the joint influence of the basic state and MJO forcing, this study suggests a diminished potential to leverage the MJO for S2S prediction in El Niño years.

   « less
5. Propagation of Thermohaline Anomalies and Their Predictive Potential along the Atlantic Water Pathway

   https://doi.org/10.1175/JCLI-D-20-1007.1  

   Langehaug, H. R. ; Ortega, P. ; Counillon, F. ; Matei, D. ; Maroon, E. ; Keenlyside, N. ; Mignot, J. ; Wang, Y. ; Swingedouw, D. ; Bethke, I. ; et al ( April 2022 , Journal of Climate)

   Abstract We assess to what extent seven state-of-the-art dynamical prediction systems can retrospectively predict winter sea surface temperature (SST) in the subpolar North Atlantic and the Nordic seas in the period 1970–2005. We focus on the region where warm water flows poleward (i.e., the Atlantic water pathway to the Arctic) and on interannual-to-decadal time scales. Observational studies demonstrate predictability several years in advance in this region, but we find that SST skill is low with significant skill only at a lead time of 1–2 years. To better understand why the prediction systems have predictive skill or lack thereof, we assess the skill of the systems to reproduce a spatiotemporal SST pattern based on observations. The physical mechanism underlying this pattern is a propagation of oceanic anomalies from low to high latitudes along the major currents, the North Atlantic Current and the Norwegian Atlantic Current. We find that the prediction systems have difficulties in reproducing this pattern. To identify whether the misrepresentation is due to incorrect model physics, we assess the respective uninitialized historical simulations. These simulations also tend to misrepresent the spatiotemporal SST pattern, indicating that the physical mechanism is not properly simulated. However, the representation of the pattern ismore »slightly degraded in the predictions compared to historical runs, which could be a result of initialization shocks and forecast drift effects. Ways to enhance predictions could include improved initialization and better simulation of poleward circulation of anomalies. This might require model resolutions in which flow over complex bathymetry and the physics of mesoscale ocean eddies and their interactions with the atmosphere are resolved. Significance Statement In this study, we find that dynamical prediction systems and their respective climate models struggle to realistically represent ocean surface temperature variability in the eastern subpolar North Atlantic and Nordic seas on interannual-to-decadal time scales. In previous studies, ocean advection is proposed as a key mechanism in propagating temperature anomalies along the Atlantic water pathway toward the Arctic Ocean. Our analysis suggests that the predicted temperature anomalies are not properly circulated to the north; this is a result of model errors that seems to be exacerbated by the effect of initialization shocks and forecast drift. Better climate predictions in the study region will thus require improving the initialization step, as well as enhancing process representation in the climate models.« less