North American extreme temperature events and related large scale meteorological patterns: a review of statistical methods, dynamics, modeling, and trends

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

North American extreme temperature events and related large scale meteorological patterns: a review of statistical methods, dynamics, modeling, and trends

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

Structure and bonding of methyl alkali metal molecules

We have carried out a theoretical investigation of the methyl alkali metals C

Cryo-electron tomography reveals that dynactin recruits a team of dyneins for processive motility

AbstractA key player in the intracellular trafficking network is cytoplasmic dynein, a protein complex that transports molecular cargo along microtubule tracks. It has been shown that vertebrate dynein’s movement becomes strikingly enhanced upon interacting with a cofactor named dynactin and one of several cargo-adapters, such as BicaudalD2. However, the mechanisms responsible for this increase in transport efficiency are not well understood, largely due to a lack of structural information. We used cryo-electron tomography to visualize the first 3-dimensional structure of the intact dynein-dynactin complex bound to microtubules. Our structure reveals that the dynactin-cargo-adapter complex recruits and binds to two dimeric cytoplasmic dyneins. Interestingly, the dynein motor organization closely resembles that of axonemal dynein, suggesting that cytoplasmic dynein and axonemal dyneins may utilize similar mechanisms to coordinate multiple motors. We propose that grouping dyneins onto a single dynactin scaffold promotes collective force production as well as unidirectional processive motility. These findings provide a structural platform that facilitates a deeper biochemical and biophysical understanding of dynein regulation and cellular transport.</jats:p