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This paper surveys the current state of knowledge regarding large-scale meteorological patterns (LSMPs) associated with short-duration (less than 1 week) extreme precipitation events over North America. In contrast to teleconnections, which are typically defined based on the characteristic spatial variations of a meteorological field or on the remote circulation response to a known forcing, LSMPs are defined relative to the occurrence of a specific phenomenon—here, extreme precipitation—and with an emphasis on the synoptic scales that have a primary influence in individual events, have medium-range weather predictability, and are well-resolved in both weather and climate models. For the LSMP relationship with extreme precipitation, we consider the previous literature with respect to definitions and data, dynamical mechanisms, model representation, and climate change trends. There is considerable uncertainty in identifying extremes based on existing observational precipitation data and some limitations in analyzing the associated LSMPs in reanalysis data. Many different definitions of “extreme” are in use, making it difficult to directly compare different studies. Dynamically, several types of meteorological systems—extratropical cyclones, tropical cyclones, mesoscale convective systems, and mesohighs—and several mechanisms—fronts, atmospheric rivers, and orographic ascent—have been shown to be important aspects of extreme precipitation LSMPs. The extreme precipitation is often realized through mesoscale processes organized, enhanced, or triggered by the LSMP. Understanding of model representation, trends, and projections for LSMPs is at an early stage, although some promising analysis techniques have been identified and the LSMP perspective is useful for evaluating the model dynamics associated with extremes.

The second West African Monsoon Modeling and Evaluation Project Experiment (WAMME II) is designed to improve understanding of the possible roles and feedbacks of sea surface temperature (SST), land use land cover change (LULCC), and aerosols forcings in the Sahel climate system at seasonal to decadal scales. The project's strategy is to apply prescribed observationally based anomaly forcing, i.e., "idealized but realistic" forcing, in simulations by climate models. The goal is to assess these forcings' effects in producing/amplifying seasonal and decadal climate variability in the Sahel between the 1950s and the 1980s, which is selected to characterize the great drought period of the last century. This is the first multi-model experiment specifically designed to simultaneously evaluate such relative contributions. The WAMME II models have consistently demonstrated that SST forcing is a major contributor to the 20th century Sahel drought. Under the influence of the maximum possible SST forcing, the ensemble mean of WAMME II models can produce up to 60% of the precipitation difference during the period. The present paper also addresses the role of SSTs in triggering and maintaining the Sahel drought. In this regard, the consensus of WAMME II models is that both Indian and Pacific Ocean SSTs greatly contributed to the drought, with the former producing an anomalous displacement of the Intertropical Convergence Zone (ITCZ) before the WAM onset, and the latter mainly contributes to the summer WAM drought. The WAMME II models also show that the impact of LULCC forcing on the Sahel climate system is weaker than that of SST forcing, but still of first order magnitude. According to the results, under LULCC forcing the ensemble mean of WAMME II models can produces about 40% of the precipitation difference between the 1980s and the 1950s. The role of land surface processes in responding to and amplifying the drought is also identified. The results suggest that catastrophic consequences are likely to occur in the regional Sahel climate when SST anomalies in individual ocean basins and in land conditions combine synergistically to favor drought.

In late December of 2022 and the first half of January 2023, an unprecedented series of atmospheric rivers (ARs) produced near-record heavy rains and flooding over much of California. Here, we employ the NASA GEOS AGCM run in a "replay" mode, together with more idealized simulations with a stationary wave model, to identify the remote forcing regions, mechanisms, and underlying predictability of this flooding event. In particular, the study addresses the underlying causes of a persistent positive Pacific–North American (PNA)-like circulation pattern that facilitated the development of the ARs. We show that the pattern developed in late December as a result of vorticity forcing in the North Pacific jet exit region. We further provide evidence that this vorticity forcing was the result of a chain of events initiated in mid-December with the development of a Rossby wave (as a result of forcing linked to the MJO) that propagated from the northern Indian Ocean into the North Pacific. As such, both the initiation of the event and the eventual development of the PNA depended critically on internally generated Rossby wave forcings, with the North Pacific jet playing a key role. This, combined with contemporaneous SST (La Niña) forcing that produced a circulation response in the AGCM that was essentially opposite to the positive PNA, underscores the fundamental lack of predictability of the event at seasonal time scales. Forecasts produced with the GEOS-coupled model suggest that useful skill in predicting the PNA and extreme precipitation over California was in fact limited to lead times shorter than about 3 weeks. [ABSTRACT FROM AUTHOR]

The relationship between leading atmospheric teleconnection patterns and Greenland Ice Sheet (GrIS) temperature, precipitation, and surface mass balance (SMB) are investigated for the last 36 summers (1979-2014) based on Modern-Era Retrospective analysis for Research and Applications version 2 reanalyses. The results indicate that the negative phase of both the North Atlantic Oscillation (NAO) and Arctic Oscillation, associated with warm and dry conditions for the GrIS, lead to SMB decreases within 0-1 months. Furthermore, the positive phase of the East Atlantic (EA) pattern often lags the negative NAO, reflecting a dynamical linkage between these modes that acts to further enhance the warm and dry conditions over the GrIS, leading to a favorable environment for enhanced surface mass loss. The development of a strong negative NAO in combination with a strong positive EA in recent years leads to significantly larger GrIS warming compared to when the negative NAO occurs in combination with a negative or weak positive EA (0.69 K versus 0.13 K anomaly). During 2009 and 2011, weakened (as compared to conditions during the severe surface melt cases of 2010 and 2012) local high pressure blocking produced colder northerly flow over the GrIS inhibiting warming despite the occurrence of a strong negative NAO, reflecting an important role for the EA during those years. In particular, the EA acts with the NAO to enhance warming in 2010 and 2012, and weaken high pressure blocking in 2009 and 2011. In general, high pressure blocking primarily impacts the western areas of the GrIS via advective temperature increases, while changes in net surface radiative fluxes account for both western and eastern GrIS temperature changes.

The objective of this paper is to review statistical methods, dynamics, modeling efforts, and trends related to temperature extremes, with a focus upon extreme events of short duration that affect parts of North America. These events are associated with large scale meteorological patterns (LSMPs). The statistics, dynamics, and modeling sections of this paper are written to be autonomous and so can be read separately. Methods to define extreme events statistics and to identify and connect LSMPs to extreme temperature events are presented. Recent advances in statistical techniques connect LSMPs to extreme temperatures through appropriately defined covariates that supplement more straightforward analyses. Various LSMPs, ranging from synoptic to planetary scale structures, are associated with extreme temperature events. Current knowledge about the synoptics and the dynamical mechanisms leading to the associated LSMPs is incomplete. Systematic studies of: the physics of LSMP life cycles, comprehensive model assessment of LSMP-extreme temperature event linkages, and LSMP properties are needed. Generally, climate models capture observed properties of heat waves and cold air outbreaks with some fidelity. However they overestimate warm wave frequency and underestimate cold air outbreak frequency, and underestimate the collective influence of low-frequency modes on temperature extremes. Modeling studies have identified the impact of large-scale circulation anomalies and land–atmosphere interactions on changes in extreme temperatures. However, few studies have examined changes in LSMPs to more specifically understand the role of LSMPs on past and future extreme temperature changes. Even though LSMPs are resolvable by global and regional climate models, they are not necessarily well simulated. The paper concludes with unresolved issues and research questions.

Although a theory of the climatology of tropical cyclone formation remains elusive, high-resolution climate models can now simulate many aspects of tropical cyclone climate.

The global characteristics of tropical cyclones (TCs) simulated by several climate models are analyzed and compared with observations. The global climate models were forced by the same sea surface temperature (SST) fields in two types of experiments, using climatological SST and interannually varying SST. TC tracks and intensities are derived from each model's output fields by the group who ran that model, using their own preferred tracking scheme; the study considers the combination of model and tracking scheme as a single modeling system, and compares the properties derived from the different systems. Overall, the observed geographic distribution of global TC frequency was reasonably well reproduced. As expected, with the exception of one model, intensities of the simulated TC were lower than in observations, to a degree that varies considerably across models. Key Points: Multimodel comparison of tropical cyclone activity in global climate models Geographic distribution of the TC activity is similar to observed Most models produce tropical cyclones weaker than observed

Sea ice fraction (SIF) over the Ross/Amundsen/Bellingshausen Sea (RAB) are investigated using the Modern-Era Retrospective Analysis for Research and Application, Version 2 (MERRA-2), focusing on the differences in time-lagged response to ENSO between the late 20th (1980–2000, L20) and the early 21st century (2001–2021, E21). The findings suggest that the typical Antarctic response to ENSO is influenced by changes in ENSO type/intensity, highlighting the need for caution when investigating the Antarctic teleconnection. Time-lagged regressions onto the mature phase of El Niño reveal that the SIF decrease and SST increase over the RAB is relatively weaker in E21 and most pronounced at 0–4 months lag. Conversely, the SIF in L20 continues to decline and reaches its peak at two-season lag (5–7 months). Tropospheric wind, pressure, and wave activity in response to El Niño in L20 show a zonally oriented high/low-pressure areas with two-season lag, enhancing the poleward flow that plays a key role in sea ice melt in the RAB, while this pattern in E21 is insignificant at the same lag. This study suggests that stronger (weaker) and more eastern (central) Pacific ENSOs on average in L20 (E21) are associated with this decadal change in the SIF response to ENSO. [ABSTRACT FROM AUTHOR]

Much of Siberia experienced exceptional warmth during the spring of 2020, which followed an unusually warm winter over the same region. Here, we investigate the drivers of the spring warmth from the perspective of atmospheric dynamics and remote influences, focusing on monthly-time-scale features of the event. We find that the warm anomalies were associated with separate quasi-stationary Rossby wave trains emanating from the North Atlantic in April and May. The wave trains are shown to be extreme manifestations of the dominant modes of spring subseasonal meridional wind variability over the Northern Hemisphere. Using a large ensemble of simulations from NASA’s GEOS atmospheric model, in which the model is constrained to remain close to observations over selected regions, we further elucidate the remote drivers of the unusual spring temperatures in Siberia. In both April and May, the wave trains were likely forced from an upstream region including eastern North America and the western North Atlantic. Analysis with a stationary wave model shows that transient vorticity flux forcing over and downwind of the North Atlantic, which is strongly related to storm activity caused by internal variability, is key to generating the wave trains, suggesting limited subseasonal predictability of the Rossby waves and hence the exceptional Siberian warmth. Our observational and model analyses also suggest that anomalous tropical atmospheric heating contributed to the unusual warmth in Siberia through a teleconnection involving upper-troposphere dynamics and the mean meridional circulation. This tropical–extratropical teleconnection offers a possible physical mechanism by which anthropogenic climate change influenced the extreme Siberian warmth. [ABSTRACT FROM AUTHOR]