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Sergi Gonzalez, Manuel Bañon, José V. Albero, Ramón Larramendi, Hermenegildo Moreno, Francisco Vasallo, Pablo Sanz, Antonio Quesada, and Ana Justel

Abstract

The Antarctic Plateau is one of the land areas with the largest gaps in surface weather observations on Earth, gaps that are usually filled with simulations provided by climate models. However, these simulated values must be ground-validated, which is particularly difficult and costly in remote polar regions. We designed and developed a Mobile Automatic Weather Station (M-AWS) which, on board a zero-emissions polar vehicle, recorded a large set of ground measurements that could be used to evaluate numerical weather simulations in an inexpensive way during the Year of Polar Prediction Southern Hemisphere Special Observing Period (YOPP). The M-AWS registered several weather variables over a transect of 2538 km in the East Antarctic Plateau. These meteorological data were also used by other scientific projects that were part of the expedition and for improving weather forecasting during the mission. The innovative design of the M-AWS overcame the main challenges imposed by the harsh conditions of a voyage in one of the world’s most extreme regions.

Free access
Kristen Averyt, Justin D. Derner, Lisa Dilling, Rafael Guerrero, Linda Joyce, Shannon McNeeley, Elizabeth McNie, Jeffrey Morisette, Dennis Ojima, Robin O’Malley, Dannele Peck, Andrea J. Ray, Matt Reeves, and William Travis

Abstract

Federal investments by U.S. agencies to enhance climate resilience at regional scales grew over the past decade (2010s). To maximize efficiency and effectiveness in serving multiple sectors and scales, it has become critical to leverage existing agency-specific research, infrastructure, and capacity while avoiding redundancy. We discuss lessons learned from a multi-institutional “regional climate response collaborative” that comprises three different federally supported climate service entities in the Rocky Mountain west and northern plains region. These lessons include leveraging different strengths of each partner, creating deliberate mechanisms to increase cross-entity communication and joint ownership of projects, and placing a common priority on stakeholder-relevant research and outcomes. We share the conditions that fostered successful collaboration, which can be transferred elsewhere, and suggest mechanisms for overcoming potential barriers. Synergies are essential for producing actionable research that informs climate-related decisions for stakeholders and ultimately enhances climate resilience at regional scales.

Open access
Andrew D. Gronewold, Vincent Fortin, Robert Caldwell, and James Noel

Abstract

Monitoring, understanding, and forecasting the hydrologic cycle of large freshwater basins often requires a broad suite of data and models. Many of these datasets and models, however, are susceptible to variations in monitoring infrastructure and data dissemination protocols when watershed, political, and jurisdictional boundaries do not align. Reconciling hydrometeorological monitoring gaps and inconsistencies across the international Laurentian Great Lakes–St. Lawrence River basin is particularly challenging because of its size and because the basin’s dominant hydrologic feature is the vast surface waters of the Great Lakes.

For tens of millions of Canadian and U.S. residents that live within the Great Lakes basin, seamless binational datasets are needed to better understand and predict coastal water-level fluctuations and other conditions that could potentially threaten human and environmental health. Binational products addressing this need have historically been developed and maintained by the Coordinating Committee on Great Lakes Basic Hydraulic and Hydrologic Data (Coordinating Committee). The Coordinating Committee recently held its one-hundredth semiannual meeting and reflected on a range of historical accomplishments while setting goals for future work. This article provides a synthesis of those achievements and goals. Particularly significant legacy and recently developed datasets of the Coordinating Committee include historical Great Lakes surface water elevations, basin-scale tributary inflow to the Great Lakes, and basin-scale estimates of both over-lake and over-land precipitation. Moving forward, members of the Coordinating Committee will work toward customizing state-of-the-art hydrologic and meteorological forecasting systems across the entire Great Lakes basin and toward promoting their products and protocols as templates for successful binational coordination across other large binational freshwater basins.

Open access
Gerald L. Potter, Laura Carriere, Judy Hertz, Michael Bosilovich, Daniel Duffy, Tsengdar Lee, and Dean N. Williams

Abstract

This paper describes the repackaging and consistent distribution of the world’s major atmospheric and oceanic reanalyses. It also presents examples of the usefulness of examining multiple reanalyses. This service will make it much easier for anybody using reanalysis to access multiple datasets using an approach similar to that of phase 5 of the Coupled Model Intercomparison Project (CMIP5). Experienced users as well as students will find the standardized formatted data convenient to use.

Open access
Phu Nguyen, Andrea Thorstensen, Soroosh Sorooshian, Kuolin Hsu, Amir Aghakouchak, Hamed Ashouri, Hoang Tran, and Dan Braithwaite

Abstract

Little dispute surrounds the observed global temperature changes over the past decades. As a result, there is widespread agreement that a corresponding response in the global hydrologic cycle must exist. However, exactly how such a response manifests remains unsettled. Here we use a unique recently developed long-term satellite-based record to assess changes in precipitation across spatial scales. We show that warm climate regions exhibit decreasing precipitation trends, while arid and polar climate regions show increasing trends. At the country scale, precipitation seems to have increased in 96 countries, and decreased in 104. We also explore precipitation changes over 237 global major basins. Our results show opposing trends at different scales, highlighting the importance of spatial scale in trend analysis. Furthermore, while the increasing global temperature trend is apparent in observations, the same cannot be said for the global precipitation trend according to the high-resolution dataset, PERSIANN-CDR, used in this study.

Open access
Adrian M. Tompkins, María Inés Ortiz De Zárate, Ramiro I. Saurral, Carolina Vera, Celeste Saulo, William J. Merryfield, Michael Sigmond, Woo-Sung Lee, Johanna Baehr, Alain Braun, Amy Butler, Michel Déqué, Francisco J. Doblas-Reyes, Margaret Gordon, Adam A. Scaife, Yukiko Imada, Masayoshi Ishii, Tomoaki Ose, Ben Kirtman, Arun Kumar, Wolfgang A. Müller, Anna Pirani, Tim Stockdale, Michel Rixen, and Tamaki Yasuda
Open access
Alexander Baklanov, Dominik Brunner, Gregory Carmichael, Johannes Flemming, Saulo Freitas, Michael Gauss, Øystein Hov, Rohit Mathur, K. Heinke Schlünzen, Christian Seigneur, and Bernhard Vogel

Abstract

Online coupled meteorology–atmospheric chemistry models have greatly evolved in recent years. Although mainly developed by the air quality modeling community, these integrated models are also of interest for numerical weather prediction and climate modeling, as they can consider both the effects of meteorology on air quality and the potentially important effects of atmospheric composition on weather. This paper summarizes the main conclusions from the “Symposium on Coupled Chemistry–Meteorology/Climate Modelling: Status and Relevance for Numerical Weather Prediction, Air Quality and Climate Research,” which was initiated by the European COST Action ES1004 “European Framework for Online Integrated Air Quality and Meteorology Modelling (EuMetChem).” It offers a brief review of the current status of online coupled meteorology and atmospheric chemistry modeling and a survey of processes relevant to the interactions between atmospheric physics, dynamics, and composition. In addition, it highlights scientific issues and emerging challenges that require proper consideration to improve the reliability and usability of these models for three main application areas: air quality, meteorology (including weather prediction), and climate modeling. It presents a synthesis of scientific progress in the form of answers to nine key questions, and provides recommendations for future research directions and priorities in the development, application, and evaluation of online coupled models.

Open access
Marika M. Holland and Donald Perovich

Abstract

Arctic sea ice has undergone significant change with large reductions in thickness and areal extent over the historical record. Numerical models project sea ice loss to continue for the foreseeable future, with the possibility of September ice-free conditions later this century. Understanding the mechanisms behind ice loss and its consequences for the larger Arctic and global systems is important if we are to anticipate and plan for the future. Meeting this challenge requires the collective and collaborative insights of scientists investigating the system from numerous perspectives. One impediment to progress has been a disconnect between the observational and modeling research communities. Advancing the science requires enhanced integration between these communities and more collaborative approaches to understanding Arctic sea ice loss. This paper discusses a successful effort to further these aims: a weeklong sea ice summer camp held in Barrow, Alaska (now known as Utqiaġvik), in May 2016. The camp brought together 25 participants who were a heterogeneous mix of observers and modelers from 13 different institutions at career stages from graduate students to senior researchers. The summer camp provided an accelerated program on sea ice observations and models and also fostered future collaborative interdisciplinary activities. A dialogue with Barrow community members was initiated in order to further understand the local consequences of Arctic sea ice loss. The discussion herein describes lessons learned from this activity and paths forward to advance the understanding and prediction of Arctic climate change.

Open access
Edward Maibach, Raphael Mazzone, Robert Drost, Teresa Myers, Keith Seitter, Katharine Hayhoe, Bob Ryan, Joe Witte, Ned Gardiner, Susan Hassol, Jeffrey K. Lazo, Bernadette Placky, Sean Sublette, and Heidi Cullen

Abstract

Findings from the most recent surveys of TV weathercasters—which are methodologically superior to prior surveys in a number of important ways—suggest that weathercasters’ views of climate change may be rapidly evolving. In contrast to prior surveys, which found many weathercasters who were unconvinced of climate change, newer results show that approximately 80% of weathercasters are convinced of human-caused climate change. A majority of weathercasters now indicate that climate change has altered the weather in their media markets over the past 50 years, and many feel there have also been harmful impacts to water resources, agriculture, transportation resources, and human health. Nearly all weathercasters—89%—believe their viewers are at least slightly interested in learning about local impacts. The majority of weathercasters are interested in reporting on local impacts, including extreme precipitation and flooding, drought and water shortages, extreme heat events, air quality, and harm to local wildlife, crops and livestock, and human health; and nearly half had reported on the local impacts in at least one channel over the past 12 months. Thus, it appears that a strong majority of weathercasters are now convinced that human-caused climate change is happening, many feel they are already witnessing harmful impacts in their communities, and many are beginning to explore ways of educating their viewers about these local impacts of global climate change. We believe that the role of local climate educator will soon become a normative practice for broadcast meteorologists—adding a significant and important new role to their job descriptions.

Open access
Nihanth W. Cherukuru, Ronald Calhoun, Tim Scheitlin, Matt Rehme, and Raghu Raj Prasanna Kumar

Abstract

Mixed reality taps into intuitive human perception by merging computer-generated views of digital objects (or flow fields) with natural views. Digital objects can be positioned in 3D space and can mimic real objects in the sense that walking around the object produces smoothly changing views toward the other side. Only recently have advances in gaming graphics advanced to the point that views of moving 3D digital objects can be calculated in real time and displayed together with digital video streams. Auxiliary information can be positioned and timed to give the viewer a deeper understanding of a scene; for example, a pilot landing an aircraft might “see” zones of shear or decaying vortices from previous heavy aircraft. A rotating digital globe might be displayed on a table top to demonstrate the evolution of El Niño. In this article, the authors explore a novel mixed reality data visualization application for atmospheric science data, present the methodology using game development platforms, and demonstrate a few applications to help users quickly and intuitively understand evolving atmospheric phenomena.

Full access