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Stefan Sobolowski, Gavin Gong, and Mingfang Ting

Abstract

Continental-scale snow cover represents a broad thermal forcing on monthly-to-intraseasonal time scales, with the potential to modify local and remote atmospheric circulation. A previous GCM study reported robust transient-eddy responses to prescribed anomalous North American (NA) snow cover. The same set of experiments also indicated a robust upper-level stationary wave response during spring, but the nature of this response was not investigated until now. Here, the authors diagnose a deep, snow-induced, tropospheric cooling over NA and hypothesize that this may represent a pathway linking snow to the stationary wave response. A nonlinear stationary wave model is shown to reproduce the GCM stationary wave response to snow more accurately than a linear model, and results confirm that diabatic cooling is the primary driver of the stationary wave response. In particular, the total nonlinear effects due to cooling, and its interactions with transient eddies and orography, are shown to be essential for faithful reproduction of the GCM response. The nonlinear model results confirm that direct effects due to transients and orography are modest. However, with interactions between forcings included, the total effects due to these terms make important contributions to the total response. Analysis of observed NA snow cover and stationary waves is qualitatively similar to the patterns generated by the GCM and linear/nonlinear stationary wave models, indicating that the snow-induced signal is not simply a modeling artifact. The diagnosis and description of a snow–stationary wave relationship adds to the understanding of stationary waves and their forcing mechanisms, and this relationship suggests that large-scale changes in the land surface state may exert considerable influence on the atmosphere over hemispheric scales and thereby contribute to climate variability.

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Raymond Sellevold, Stefan Sobolowski, and Camille Li

Abstract

There is an ongoing debate over whether accelerated Arctic warming [Arctic amplification (AA)] is altering the large-scale circulation responsible for the anomalous weather experienced by midlatitude regions in recent years. Among the proposed mechanisms is the idea that local processes associated with sea ice loss heat the lower troposphere at high latitudes, thus weakening the equator-to-pole temperature gradient and driving changes in quasi-stationary waves, the midlatitude jets, and storm tracks. It is further hypothesized that these circulation changes are conducive to persistent weather patterns. Because of the short observational record and large atmospheric internal variability, it is difficult to identify robust relationships and infer causality. Here, a simplified, linear, steady-state model is used to investigate the direct response of the midlatitude atmospheric circulation to thermal forcing in the Arctic. The results suggest that there is a weak midlatitude circulation response to an idealized, but representative, Arctic heating perturbation. Further, the stationary wave responses are shown to be well within the bounds of internal variability. A midlatitude response is excited if the idealized heating penetrates up to the tropopause. Such deep, persistent heating is not observed on average during the AA period but does suggest a pathway for Arctic–midlatitude linkages under specific conditions. This study adds to the growing body of work suggesting that warming in the lower troposphere associated with Arctic amplification is not currently a direct driver of anomalous midlatitude circulation changes.

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Stefan Sobolowski, Gavin Gong, and Mingfang Ting

Abstract

The radiative and thermal properties of widespread snow cover anomalies have the potential to modulate local and remote climate over monthly to seasonal time scales. In this study, physical and dynamical links between anomalous North American snow conditions and Northern Hemisphere climate are examined. A pair of 40-member ensemble AGCM experiments is run, with prescribed high- and low-snow forcings over North America during the course of an entire year (EY). The difference between the two ensemble averages reflects the climatic response to sustained EY snow forcing. Local surface responses over the snow forcing occur in all seasons, and a significant remote surface temperature response occurs over Eurasia during spring. A hemispheric-scale transient eddy response to EY forcing also occurs, which propagates downstream from the forcing region to Eurasia, and then reaches a maximum in extent and amplitude in spring. The evolution of this transient eddy response is indicative of considerable downstream development and is consistent with known storm-track dynamics. This transient response is shown to be a result of persistent steepened temperature gradients created by the anomalous snow conditions, which contribute to enhanced baroclinicity over the storm-track entrance regions. A second pair of experiments is run, with the prescribed high- and low-snow forcings over North America restricted to the fall season (FS). The dynamical response to FS forcing is muted compared to the EY scenario, suggesting that the seasonal timing and persistence of the snow forcing are essential for the remote teleconnection.

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Erik W. Kolstad, Stefan P. Sobolowski, and Adam A. Scaife

Abstract

Recent periods of extreme weather in Europe, such as the cold winter of 2009/10, have caused widespread impacts and were remarkable because of their persistence. It is therefore of great interest to improve the ability to forecast such events. Weather forecasts at midlatitudes generally show low skill beyond 5–10 days, but long-range forecast skill may increase during extended tropospheric blocking episodes or perturbations of the stratospheric polar vortex, which can affect midlatitude weather for several weeks at a time. Here a simple, linear approach is used to identify previously undocumented persistence in northern European summer and winter temperature anomalies in climate model simulations, corroborated by observations and reanalysis data. For instance, temperature anomalies of at least one standard deviation above or below climatology in March were found to be about 20%–120% more likely than normal if the preceding February was anomalous by 0.5–1.5 standard deviations (with the same sign). The corresponding range for April (i.e., persistence over two months) is between 20% and 80%. The persistence is observed irrespective of the data source or driving mechanisms, and the temperature itself is a more skillful predictor of the temperatures one month ahead than the stratospheric polar vortex or the NAO and even than both factors together. The results suggest potential to conditionally improve the skill of long-range forecasts and enhance recent advancements in dynamical seasonal prediction.

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Tobias Siegfried, Stefan Sobolowski, Pradeep Raj, Ram Fishman, Victor Vasquez, Kapil Narula, Upmanu Lall, and Vijay Modi

Abstract

Because of declining public investments in irrigation projects in India, the growth of irrigated agricultural production has increasingly become reliant on unsustainable allocation of groundwater. As a result, groundwater resources are increasingly depleted and their role in buffering climate variability is lost. Given future climate and food supply uncertainty under mounting population pressure, it is vital that the connections between climate variability, unsustainable irrigation practices, and their impacts on regional-scale agricultural production are quantified.

Here, the focus is on rice and maize production in the semiarid Telangana region in Andhra Pradesh, where the advent of inexpensive pump technology in the late twentieth century, coupled with governmentally subsidized electricity, has allowed year-round planting of water-intensive crops. Using a 35-yr climate and agricultural dataset from Telangana, nonlinear Gaussian process district-level regression models are developed to model dry-season irrigated area, which is a proxy for total groundwater use, in the function of climate-related predictors. The resulting models are able to accurately reproduce dry-season cropped area in most districts. Interannual climate variations play a significant role in determining groundwater use for irrigation. Nonlinear interactions between selected climate features are likely to influence irrigation water use significantly. These results suggest that the authors’ modeling approach, combined with monsoon predictions, allow the forecasting of cropped area and agricultural water requirements at seasonal time scales within the bounds of uncertainty. The usefulness of such data to decision makers and stakeholders is discussed, as they attempt to use scarce surface and subsurface water resources more efficiently and sustainably.

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Clio Michel, Camille Li, Isla R. Simpson, Ingo Bethke, Martin P. King, and Stefan Sobolowski

Abstract

El Niño–Southern Oscillation (ENSO) is a main driver of climate variability worldwide, but the presence of atmospheric internal variability makes accurate assessments of its atmospheric teleconnections a challenge. Here, we use a multimodel large ensemble of simulations to investigate the ENSO teleconnection response to a low global warming scenario that represents Paris Agreement targets. The ensemble comprises five atmospheric general circulation models with two experiments (present-day and +2°C) in which the same set of ENSO events is prescribed, which allows for quantification of the uncertainty in the ENSO response due to internal variability. In winter, the teleconnection during the positive ENSO phase features a strong negative anomaly in sea level pressure over the northeast Pacific (and vice versa for the negative phase); this anomaly shifts northeastward and strengthens in the warming experiment ensemble. At least 50–75 ENSO events are required to detect a significant shift or strengthening, emphasizing the need to adequately sample the internal variability to isolate the forced response of the ENSO teleconnection under a low warming scenario. Even more events may be needed if one includes other sources of uncertainty not considered in our experimental setup, such as changes in ENSO itself. Over North America, precipitation changes are generally more robust than temperature changes for the regions considered, despite large internal variability, and are shaped primarily by changes in atmospheric circulation. These results suggest that the observational period is likely too short for assessing changes in the ENSO teleconnection under Paris Agreement warming targets.

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Martin P. King, Ivana Herceg-Bulić, Ileana Bladé, Javier García-Serrano, Noel Keenlyside, Fred Kucharski, Camille Li, and Stefan Sobolowski

Abstract

Recent studies have indicated the importance of fall climate forcings and teleconnections in influencing the climate of the northern mid- to high latitudes. Here, we present some exploratory analyses using observational data and seasonal hindcasts, with the aim of highlighting the potential of the El Niño–Southern Oscillation (ENSO) as a driver of climate variability during boreal late fall and early winter (November and December) in the North Atlantic–European sector, and motivating further research on this relatively unexplored topic. The atmospheric ENSO teleconnection in November and December is reminiscent of the east Atlantic pattern and distinct from the well-known arching extratropical Rossby wave train found from January to March. Temperature and precipitation over Europe in November are positively correlated with the Niño-3.4 index, which suggests a potentially important ENSO climate impact during late fall. In particular, the ENSO-related temperature anomaly extends over a much larger area than during the subsequent winter months. We discuss the implications of these results and pose some research questions.

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Erik W. Kolstad, Oda N. Sofienlund, Hanna Kvamsås, Mathew A. Stiller-Reeve, Simon Neby, Øyvind Paasche, Marie Pontoppidan, Stefan P. Sobolowski, Håvard Haarstad, Stina E. Oseland, Lene Omdahl, and Snorre Waage

Abstract

Climate change yields both challenges and opportunities. In both cases, costly adaptations and transformations are necessary and desirable, and these must be based on realistic and relevant climate information. However, it is often difficult for climate scientists to communicate this information to decision-makers and stakeholders, and it can be equally difficult for such actors to interpret and put the information to use. In this essay, we discuss experiences and present recommendations for scientists producing climate services. The basis is our work in several climate service projects. One of them aimed to provide local-scale climate data for municipalities in western Norway and to explore how the data were interpreted and implemented. The project was first based solely on climate science expertise, and the participants did not have sufficient competence on coproduction and knowledge about the regulatory and political landscape in which municipalities operate. Initially, we also subscribed to an outdated idea of climate services, where knowledge providers (climate scientists) “deliver” their information to knowledge users (e.g., municipal planners). Increasingly, as stressed in the literature on coproduction of knowledge, we learned that climate service should be an iterative process where actionable information is coproduced through two-way dialogue. On the basis of these and other lessons learned the hard way, we provide a set of concrete recommendations on how to embed the idea of coproduction from the preproposal stage to beyond the end of climate service projects.

Open access