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In the Upper Colorado River Basin, agriculture is a major contributor to Utah’s economy, which may be stressed due to the changing climate. In this study, two data-mining techniques and interview data are used to explore how climate variability affects agricultural production and the way the farmers have been adapting their practices to these changes. In the first part of the study, we used multilinear regression and random forest regression to understand the relationship between climate and agricultural production using temperature, precipitation, water availability, hay production, and cattle herd size. The quantitative results showed weak relations among variables. In the second part of the study, we interviewed ranchers to fill the gaps in the quantitative analysis. Over the 35 years (1981–2015), the quantitative analysis shows that temperature has affected cattle and hay production more than precipitation. Among non-climatic variables, resource availability and commodity prices are the most important factors that influence year-to-year production. Farmers are well-aware of these effects and have adapted accordingly. They have changed irrigation practices, cropping patterns, and are experimenting to produce a hybrid species of cattle, that are resilient to a hotter temperature and can use a wider variety of forage. 

Abstract Explosive cyclones (ECs), defined as extratropical cyclones that experience normalized pressure drops of at least 24 hPa in 24 h, are impactful weather events in the North Atlantic sector, but year-to-year changes in the frequency and impacts of these storms are sizeable. To analyze the sources of this interannual variability, we track cases of ECs and dissect them into two spatial groups: those that formed near the east coast of North America (coastal) and those in the north central Atlantic (high latitude). The frequency of high-latitude ECs is strongly correlated with the North Atlantic Oscillation, a well-known feature, whereas coastal EC frequency is statistically linked with an atmospheric wave train emanating from the North Pacific in the last 30 years. This wave train pattern of alternating high and low pressure is associated with heightened upper-level divergence and Eady growth rates along the east coast of North America, likely resulting in a stronger correspondence between the atmospheric wave train and coastal EC frequency. Using coupled model experiments, we show that the tropical and North Pacific oceans are an important factor for this atmospheric wave train and the subsequent enhancement of seasonal baroclinicity in the North Atlantic. 

In recent years, a pair of large-scale circulation patterns consisting of an anomalous ridge over northwestern North America and trough over northeastern North America was found to accompany extreme winter weather events such as the 2013–2015 California drought and eastern U.S. cold outbreaks. Referred to as the North American winter dipole (NAWD), previous studies have found both a marked natural variability and a warming-induced amplification trend in the NAWD. In this study, we utilized multiple global reanalysis datasets and existing climate model simulations to examine the variability of the winter planetary wave patterns over North America and to better understand how it is likely to change in the future. We compared between pre- and post-1980 periods to identify changes to the circulation variations based on empirical analysis. It was found that the leading pattern of the winter planetary waves has changed, from the Pacific–North America (PNA) mode to a spatially shifted mode such as NAWD. Further, the potential influence of global warming on NAWD was examined using multiple climate model simulations. 

Abstract Periods of water surplus and deficit in Northern California follow a pronounced quasi‐decadal cycle. This cycle is largely driven by the frequency of atmospheric rivers (ARs), affecting the region’s wet and dry periods. Our analyses demonstrate that the quasi‐decadal cycle of AR frequency relies on moisture transport associated with the position and intensity of the Aleutian Low. In observations, the Aleutian Low is shown to covary with tropical Pacific sea surface temperature anomalies. A modeling experiment, which incorporates ocean observations from the equatorial Pacific into the fully coupled climate model, provides support that the quasi‐decadal cycle of the Aleutian Low is forced by the tropical Pacific. Subsequently, the tropical Pacific modulates the wet season moisture transport toward California on decadal time scales, affecting AR frequency. These results provide metrics for improving interannual‐to‐decadal prediction of AR activity, which drives hydrological cycles in Northern California. 

The El Niño–Southern Oscillation (ENSO), which originates in the Pacific, is the strongest and most well-known mode of tropical climate variability. Its reach is global, and it can force climate variations of the tropical Atlantic and Indian Oceans by perturbing the global atmospheric circulation. Less appreciated is how the tropical Atlantic and Indian Oceans affect the Pacific. Especially noteworthy is the multidecadal Atlantic warming that began in the late 1990s, because recent research suggests that it has influenced Indo-Pacific climate, the character of the ENSO cycle, and the hiatus in global surface warming. Discovery of these pantropical interactions provides a pathway forward for improving predictions of climate variability in the current climate and for refining projections of future climate under different anthropogenic forcing scenarios.