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The community of simpler climate model users is broad, engaged, and highly multidisciplinary. However, this community presently lacks a rallying point for developing a sustainable modeling suite that can seamlessly switch between minimalist and state-of-the-art dycores and physics packages. NCAR is the center of open-source Earth System Modeling in the U.S.A. and has a long history of facilitating the development of community models that are used both for state-of-the-art climate projections and as research tools by the university community. The Community Earth System Model (CESM) is one of NCAR’s flagship models and forms a nexus for NCAR’s strong links with the university community. Through the development of cyberinfrastructure and research tools, CESM represents the ideal platform on which to build idealized configurations of the coupled ocean-land-atmosphere system with a range of simplifications. This CSSI grant (NSF Award# 2004575) is funding the development of new capabilities in the cyberinfrastructure of NCAR’s Community Earth System Model (CESM) to enable scientists to easily create and configure coupled experiments. This infrastructure includes a new simpler model query tool and user-friendly toolchain that allows idealized CESM experiments to be readily accessed and experiments to be easily customized., NSF Award #2004575

One of the greatest uncertainties when it comes to future projections of regional climate is how the large-scale atmospheric circulation will change (Shepherd 2014). While there is a general consensus among models on a zonal mean poleward shifting of the mid-latitude westerlies and associated storm tracks (Yin 2005; Kidston and Gerber 2010; Chang et al. 2012; Swart and Fyfe 2012; Wilcox et al. 2012; Barnes and Polvani 2013), there is a large spread in the magnitude of this response. In addition to this zonal mean, poleward shifting view, there are more localized changes in the circulation associated with altered stationary wave patterns (Stephenson and Held 1993; Joseph et al. 2004; Simpson et al. 2014). For many of these predicted changes, we do not have a good physical understanding of the mechanisms that produce them, or the factors that govern their uncertainty. The stratosphere and how it is expected to change in the future is one source of uncertainty, among many, in future tropospheric mid-latitude circulation change. There are a variety of ways in which the stratosphere’s mean state, variability and composition may impact on tropospheric climate change. Instead of providing an exhaustive review of this topic, we focus on the role of changes in the extra-tropical mean state of the stratosphere in future projections of tropospheric mid-latitude climate by considering two particular aspects. For the Northern Hemisphere we discuss the impact of uncertainty in future changes in the stratospheric polar vortex on tropospheric climate change. For the Southern Hemisphere we discuss the relative roles of stratospheric ozone depletion and changing greenhouse gas concentrations on the future evolution of the Southern Hemisphere mid-latitude jet stream.

Multidecadal variability in the North Atlantic jet stream in general circulation models (GCMs) is compared with that in reanalysis products of the twentieth century. It is found that almost all models exhibit multidecadal jet stream variability that is entirely consistent with the sampling of white noise year-to-year atmospheric fluctuations. In the observed record, the variability displays a pronounced seasonality within the winter months, with greatly enhanced variability toward the late winter. This late winter variability exceeds that found in any GCM and greatly exceeds expectations from the sampling of atmospheric noise, motivating the need for an underlying explanation. The potential roles of both external forcings and internal coupled ocean–atmosphere processes are considered. While the late winter variability is not found to be closely connected with external forcing, it is found to be strongly related to the internally generated component of Atlantic multidecadal variability (AMV) in sea surface temperatures (SSTs). In fact, consideration of the seasonality of the jet stream variability within the winter months reveals that the AMV is far more strongly connected to jet stream variability during March than the early winter months or the winter season as a whole. Reasoning is put forward for why this connection likely represents a driving of the jet stream variability by the SSTs, although the dynamics involved remain to be understood. This analysis reveals a fundamental mismatch between late winter jet stream variability in observations and GCMs and a potential source of long-term predictability of the late winter Atlantic atmospheric circulation.

Presentation slides from the plenary session on Scientific Quality organized by the ESIP Information Quality Cluster (IQC). The IQC has formally defined information quality as a combination of the following four aspects of quality, spanning the full life cycle of data products: 1. Scientific quality; 2. Product quality; 3. Stewardship quality; and 4. Service quality.The purpose of this session was to focus on scientific quality, and especially on uncertainty. A panel of invited speakers from a variety of Earth science disciplines addressed questions such as: How is uncertainty determined and characterized in the products of their research or application? What are the major side effects and limitations of common statistical techniques used to quantify and characterize uncertainty? What is the impact of uncertainty on the quality of their data products? How is data uncertainty accounted for when multiple sources of data are spliced and woven into a single product? How do they document and convey the information about uncertainty to other scientific users? What is the best way of conveying uncertainty to the (possibly skeptical) public? This session provided expert knowledge from different perspectives on a relatively focused topic–Data Uncertainty–that is extremely challenging but critical in both establishing and elevating the user communities’ confidence in Earth Science data. ​The session was followed by a breakout session of the IQC with an additional invited presentation and detailed discussion among the speakers and attendees. Hopefully, ​these presentations will lead to a community-wide discussion on the problems, challenges, and solutions to a wide range of issues surrounding data uncertainty.

Extreme temperature events take thousands of lives every year and are a threat to agriculture and the biosphere. Therefore, it is essential that climate models be able to accurately reproduce the statistics of these extreme events and provide accurate predictions for how the probability of extreme events is expected to change in the future. This study analyzed the accuracy of the Community Atmosphere Model 5 (CAM5) in modeling the distribution of extreme temperature events through statistical analysis and comparisons with the MERRA-2 reanalysis (our observational dataset). In regions where CAM was deficient in its representation of daily temperature variability, the dynamical processes that underlie the variability in these regions were contrasted and compared between CAM5 and MERRA-2 to understand the reason for these deficiencies. In particular, it was found that the variance of daily timescale surface temperatures in the winter season (December, January, February) over northwest North America in CAM were considerably higher than in MERRA-2. This large variance seems to be due, in large part, to strong circulation anomalies in the model. This leads to a stronger temperature gradient from north to south in the region of interest, which results in increased advection of cold air from the north into the northwestern part of North America.

A critical aspect of human-induced climate change is how it will affect precipitation around the world. Broadly speaking, warming increases atmospheric moisture holding capacity, intensifies moisture transports and makes sub-tropical dry regions drier and tropical and mid-to-high-latitude wet regions wetter. Extra-tropical precipitation patterns vary strongly with longitude, however, owing to the control exerted by the storm tracks and quasi-stationary highs and lows or stationary waves. Regional precipitation change will, therefore, also depend on how these aspects of the circulation respond. Current climate models robustly predict a change in the Northern Hemisphere (NH) winter stationary wave field that brings wetting southerlies to the west coast of North America, and drying northerlies to interior southwest North America and the eastern Mediterranean. Here we show that this change in the meridional wind field is caused by strengthened zonal mean westerlies in the sub-tropical upper troposphere, which alters the character of intermediate-scale stationary waves. Thus, a robust and easily understood model response to global warming is the prime cause of these regional wind changes. However, the majority of models probably overestimate the magnitude of this response because of biases in their climatological representation of the relevant waves, suggesting that winter season wetting of the North American west coast will be notably less than projected by the multi-model mean.

Previous studies have extensively investigated the impact of Arctic sea ice anomalies on the midlatitude circulation and associated surface climate in winter. However, there is an ongoing scientific debate regarding whether and how sea ice retreat results in the observed cold anomaly over the adjacent continents. We present a robust “cold Siberia” pattern in the winter following sea ice loss over the Barents-Kara seas in late autumn in an advanced atmospheric general circulation model, with a well-resolved stratosphere. Additional targeted experiments reveal that the stratospheric response to sea ice forcing is crucial in the development of cold conditions over Siberia, indicating the dominant role of the stratospheric pathway compared with the direct response within the troposphere. In particular, the downward influence of the stratospheric circulation anomaly significantly intensifies the ridge near the Ural Mountains and the trough over East Asia. The persistently intensified ridge and trough favor more frequent cold air outbreaks and colder winters over Siberia. This finding has important implications for improving seasonal climate prediction of midlatitude cold events. The results also suggest that the model performance in representing the stratosphere-troposphere coupling could be an important source of the discrepancy between recent studies.