The Life Cycle of Northern Hemisphere Downward Wave Coupling between the Stratosphere and Troposphere

The life cycle of Northern Hemisphere downward wave coupling between the stratosphere and troposphere via wave reflection is analyzed. Downward wave coupling events are defined by extreme negative values of a wave coupling index based on the leading principal component of the daily wave-1 heat flux at 30 hPa. The life cycle occurs over a 28-day period. In the stratosphere there is a transition from positive to negative total wave-1 heat flux and westward to eastward phase tilt with height of the wave-1 geopotential height field. In addition, the zonal-mean zonal wind in the upper stratosphere weakens leading to negative vertical shear. Following the evolution in the stratosphere there is a shift toward the positive phase of the North Atlantic Oscillation (NAO) in the troposphere. The pattern develops from a large westward-propagating wave-1 anomaly in the high-latitude North Atlantic sector. The subsequent equatorward propagation leads to a positive anomaly in midlatitudes. The near-surface temperature and circulation anomalies are consistent with a positive NAO phase. The results suggest that wave reflection events can directly influence tropospheric weather. Finally, winter seasons dominated by extreme wave coupling and stratospheric vortex events are compared. The largest impacts in the troposphere occur during the extreme negative seasons for both indices, namely seasons with multiple wave reflection events leading to a positive NAO phase or seasons with major sudden stratospheric warmings (weak vortex) leading to a negative NAO phase. The results reveal that the dynamical coupling between the stratosphere and NAO involves distinct dynamical mechanisms that can only be characterized by separate wave coupling and vortex indices

Northeast Colorado Extreme Rains Interpreted in a Climate Change Context

The probability for an extreme five-day September rainfall event over northeast Colorado, as was observed in early September 2013, has likely decreased due to climate change

On the Control of the Residual Circulation and Stratospheric Temperatures in the Arctic by Planetary Wave Coupling

It is well established that interannual variability of eddy (meridional) heat flux near the tropopause controls the variability of Arctic lower-stratospheric temperatures during spring via a modification of the strength of the residual circulation. While most studies focus on the role of anomalous heat flux values, here the impact of total (climatology plus anomaly) negative heat flux events on the Arctic stratosphere is investigated. Utilizing the Interim ECMWF Re-Analysis (ERA-Interim) dataset, it is found that total negative heat flux events coincide with a transient reversal of the residual circulation and cooling of the Arctic lower stratosphere. The negative events weaken the seasonally averaged adiabatic warming. The analysis provides a new interpretation of the winters of 1997 and 2011, which are known to have the lowest March Arctic lower-stratospheric temperatures in the satellite era. While most winters involve positive and negative heat flux extremes, the winters of 1997 and 2011 are unique in that they only involved extreme negative events. This behavior contributed to the weakest adiabatic downwelling in the satellite era and suggests a dynamical contribution to the extremely low temperatures during those winters that could not be accounted for by diabatic processes alone. While it is well established that dynamical processes contribute to the occurrence of stratospheric sudden warming events via extreme positive heat flux events, the results show that dynamical processes also contribute to cold winters with subsequent impact on Arctic ozone loss. The results highlight the importance of interpreting stratospheric temperatures in the Arctic in the context of the dynamical regime with which they are associated

A New Look at Stratospheric Sudden Warmings. Part II: Evaluation of Numerical Model Simulations

The simulation of major midwinter stratospheric sudden warmings (SSWs) in six stratosphere-resolving general circulation models (GCMs) is examined. The GCMs are compared to a new climatology of SSWs, based on the dynamical characteristics of the events. First, the number, type, and temporal distribution of SSW events are evaluated. Most of the models show a lower frequency of SSW events than the climatology, which has a mean frequency of 6.0 SSWs per decade. Statistical tests show that three of the six models produce significantly fewer SSWs than the climatology, between 1.0 and 2.6 SSWs per decade. Second, four process-based diagnostics are calculated for all of the SSW events in each model. It is found that SSWs in the GCMs compare favorably with dynamical benchmarks for SSW established in the first part of the study. These results indicate that GCMs are capable of quite accurately simulating the dynamics required to produce SSWs, but with lower frequency than the climatology. Further dynamical diagnostics hint that, in at least one case, this is due to a lack of meridional heat flux in the lower stratosphere. Even though the SSWs simulated by most GCMs are dynamically realistic when compared to the NCEP–NCAR reanalysis, the reasons for the relative paucity of SSWs in GCMs remains an important and open question

The remarkably strong Arctic stratospheric polar vortex of Winter 2020: links to record-breaking arctic oscillation and ozone loss

The Northern Hemisphere (NH) polar winter stratosphere of 2019/2020 featured an exceptionally strong and cold stratospheric polar vortex. Wave activity from the troposphere during December–February was unusually low, which allowed the polar vortex to remain relatively undisturbed. Several transient wave pulses nonetheless served to help create a reflective configuration of the stratospheric circulation by disturbing the vortex in the upper stratosphere. Subsequently, multiple downward wave coupling events took place, which aided in dynamically cooling and strengthening the polar vortex. The persistent strength of the stratospheric polar vortex was accompanied by an unprecedentedly positive phase of the Arctic Oscillation in the troposphere during January–March, which was consistent with large portions of observed surface temperature and precipitation anomalies during the season. Similarly, conditions within the strong polar vortex were ripe for allowing substantial ozone loss: The undisturbed vortex was a strong transport barrier, and temperatures were low enough to form polar stratospheric clouds for over 4 months into late March. Total column ozone amounts in the NH polar cap decreased and were the lowest ever observed in the February–April period. The unique confluence of conditions and multiple broken records makes the 2019/2020 winter and early spring a particularly extreme example of two‐way coupling between the troposphere and stratosphere

Anatomy of an Extreme Event

© Copyright 2013 American Meteorological Society (AMS). Permission to use figures, tables, and brief excerpts from this work in scientific and educational works is hereby granted provided that the source is acknowledged. Any use of material in this work that is determined to be “fair use” under Section 107 of the U.S. Copyright Act September 2010 Page 2 or that satisfies the conditions specified in Section 108 of the U.S. Copyright Act (17 USC §108, as revised by P.L. 94-553) does not require the AMS’s permission. Republication, systematic reproduction, posting in electronic form, such as on a web site or in a searchable database, or other uses of this material, except as exempted by the above statement, requires written permission or a license from the AMS. Additional details are provided in the AMS Copyright Policy, available on the AMS Web site located at (https://www.ametsoc.org/) or from the AMS at 617-227-2425 or [email protected] record-setting 2011 Texas drought/heat wave is examined to identify physical processes, underlying causes, and predictability. October 2010–September 2011 was Texas’s driest 12-month period on record. While the summer 2011 heat wave magnitude (2.9°C above the 1981–2010 mean) was larger than the previous record, events of similar or larger magnitude appear in preindustrial control runs of climate models. The principal factor contributing to the heat wave magnitude was a severe rainfall deficit during antecedent and concurrent seasons related to anomalous sea surface temperatures (SSTs) that included a La Niña event. Virtually all the precipitation deficits appear to be due to natural variability. About 0.6°C warming relative to the 1981–2010 mean is estimated to be attributable to human-induced climate change, with warming observed mainly in the past decade. Quantitative attribution of the overall human-induced contribution since preindustrial times is complicated by the lack of a detected century-scale temperature trend over Texas. Multiple factors altered the probability of climate extremes over Texas in 2011. Observed SST conditions increased the frequency of severe rainfall deficit events from 9% to 34% relative to 1981–2010, while anthropogenic forcing did not appreciably alter their frequency. Human-induced climate change increased the probability of a new temperature record from 3% during the 1981–2010 reference period to 6% in 2011, while the 2011 SSTs increased the probability from 4% to 23%. Forecasts initialized in May 2011 demonstrate predictive skill in anticipating much of the SST-enhanced risk for an extreme summer drought/heat wave over Texas

Quantifying stratospheric biases and identifying their potential sources in subseasonal forecast systems

Funding: The work of Rachel W.-Y. Wu is funded through ETH grant ETH-05 19-1. Support from the Swiss National Science Foundation through projects PP00P2_170523 and PP00P2_198896 to Daniela I. V. Domeisen is gratefully acknowledged. Chaim I. Garfinkel and Chen Schwartz are supported by the ISF–NSFC joint research program (grant no. 3259/19). The work of Marisol Osman was supported by UBACyT20020170100428BA and PICT-2018-03046 projects. The work of Alvaro de la Cámara is funded by the Spanish Ministry of Science and Innovation through project PID2019-109107GB-I00. Blanca Ayarzagüena and Natalia Calvo acknowledge the support of the Spanish Ministry of Science and Innovation through the JeDiS (RTI2018-096402-B-I00) project. Froila M. Palmeiro and Javier García-Serrano have been partially supported by the Spanish ATLANTE project (PID2019-110234RB-C21) and Ramón y Cajal program (RYC-2016-21181), respectively. Neil P. Hindley and Corwin J. Wright are supported by UK Natural Environment Research Council (NERC), grant number NE/S00985X/1. Corwin J. Wright is also supported by a Royal Society University Research Fellowship UF160545. Seok-Woo Son and Hera Kim are supported by the Basic Science Research Program through the National Research Foundation of Korea (2017R1E1A1A01074889). his material is based upon work supported by the US Department of Energy, Office of Science, Office of Biological and Environmental Research (BER), Regional and Global Model Analysis (RGMA) component of the Earth and Environmental System Modeling program under award no. DE-SC0022070 and National Science Foundation (NSF) IA 1947282. This work was also supported by the National Center for Atmospheric Research (NCAR), which is a major facility sponsored by the NSF under cooperative agreement no. 1852977. Pu Lin is supported by award NA18OAR4320123 from the National Oceanic and Atmospheric Administration (NOAA), U.S. Department of Commerce. Zachary D. Lawrence was partially supported under NOAA award NA20NWS4680051; Zachary D. Lawrence and Judith Perlwitz also acknowledge support from US federally appropriated funds.The stratosphere can be a source of predictability for surface weather on timescales of several weeks to months. However, the potential predictive skill gained from stratospheric variability can be limited by biases in the representation of stratospheric processes and the coupling of the stratosphere with surface climate in forecast systems. This study provides a first systematic identification of model biases in the stratosphere across a wide range of subseasonal forecast systems. It is found that many of the forecast systems considered exhibit warm global-mean temperature biases from the lower to middle stratosphere, too strong/cold wintertime polar vortices, and too cold extratropical upper-troposphere/lower-stratosphere regions. Furthermore, tropical stratospheric anomalies associated with the Quasi-Biennial Oscillation tend to decay toward each system's climatology with lead time. In the Northern Hemisphere (NH), most systems do not capture the seasonal cycle of extreme-vortex-event probabilities, with an underestimation of sudden stratospheric warming events and an overestimation of strong vortex events in January. In the Southern Hemisphere (SH), springtime interannual variability in the polar vortex is generally underestimated, but the timing of the final breakdown of the polar vortex often happens too early in many of the prediction systems. These stratospheric biases tend to be considerably worse in systems with lower model lid heights. In both hemispheres, most systems with low-top atmospheric models also consistently underestimate the upward wave driving that affects the strength of the stratospheric polar vortex. We expect that the biases identified here will help guide model development for subseasonal-to-seasonal forecast systems and further our understanding of the role of the stratosphere in predictive skill in the troposphere.Peer reviewe

Quantifying stratospheric biases and identifying their potential sources in subseasonal forecast systems

The stratosphere can be a source of predictability for surface weather on timescales of several weeks to months. However, the potential predictive skill gained from stratospheric variability can be limited by biases in the representation of stratospheric processes and the coupling of the stratosphere with surface climate in forecast systems. This study provides a first systematic identification of model biases in the stratosphere across a wide range of subseasonal forecast systems. It is found that many of the forecast systems considered exhibit warm global-mean temperature biases from the lower to middle stratosphere, too strong/cold wintertime polar vortices, and too cold extratropical upper-troposphere/lower-stratosphere regions. Furthermore, tropical stratospheric anomalies associated with the Quasi-Biennial Oscillation tend to decay toward each system\u27s climatology with lead time. In the Northern Hemisphere (NH), most systems do not capture the seasonal cycle of extreme-vortex-event probabilities, with an underestimation of sudden stratospheric warming events and an overestimation of strong vortex events in January. In the Southern Hemisphere (SH), springtime interannual variability in the polar vortex is generally underestimated, but the timing of the final breakdown of the polar vortex often happens too early in many of the prediction systems. These stratospheric biases tend to be considerably worse in systems with lower model lid heights. In both hemispheres, most systems with low-top atmospheric models also consistently underestimate the upward wave driving that affects the strength of the stratospheric polar vortex. We expect that the biases identified here will help guide model development for subseasonal-to-seasonal forecast systems and further our understanding of the role of the stratosphere in predictive skill in the troposphere

Climate Science Special Report: Fourth National Climate Assessment (NCA4), Volume I

New observations and new research have increased our understanding of past, current, and future climate change since the Third U.S. National Climate Assessment (NCA3) was published in May 2014. This Climate Science Special Report (CSSR) is designed to capture that new information and build on the existing body of science in order to summarize the current state of knowledge and provide the scientific foundation for the Fourth National Climate Assessment (NCA4)