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Andrew K. Dow, Eli M. Dow, Thomas D. Fitzsimmons, and Maurice M. Materise

Abstract

Researchers studying large-scale questions in hydrology, oceanography, and meteorology can work with existing data through myriad platforms that provide access to remote datasets and render said information in various graphical outputs for interpretation and analysis. A survey of 30 publicly available hydrometeorological data platforms reviews the current state of the art in water-data discovery and visualization. Such platforms best meet the needs of a diverse user community by providing valuable data content, facilitating data exchange, and supporting visual analysis. To provide datasets of value to wider audiences, data providers can emphasize building datasets that are not only voluminous but also proportionally content rich in geographic, temporal, and measurement breadth, through integration of complementary datasets and coordinated data collection programs. In support of efficient data interchange, including software-driven integration of complementary content, data providers should increase adoption of web services to share data, along with machine-readable formats. In addition, this work surveys best practices in visualization and advocates for graphical user interface features that provide the flexibility required to integrate heterogeneous datasets by both novice and expert end users. Features that stand out as particularly useful include comprehensive content filters for customizable data queries, multiparameter plotting, statistical analysis tools, and predictive visualization. Effective combination of comprehensive—as well as voluminous—content, widely implemented standards for efficient data interchange, and appropriate visualization flexibility in the next generation of tools provided as software services will empower a wide user community, spanning laypersons, students, and researchers.

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Ronald E. Stewart, Julie M. Thériault, and William Henson

Abstract

This article examines the types of winter precipitation that occur near 0°C, specifically rain, freezing rain, freezing drizzle, ice pellets, snow pellets, and wet snow. It follows from a call by M. Ralph et al. for more attention to be paid to this precipitation since it represents one of the most serious wintertime quantitative precipitation forecasting (QPF) issues. The formation of the many precipitation types involves ice-phase and/or liquid-phase processes, and thresholds in the degree of melting and/or freezing often dictate the types occurring at the surface. Some types can occur simultaneously so that, for example, ensuing collisions between supercooled raindrops and ice pellets that form ice pellet aggregates can lead to substantial reductions in the occurrence of freezing rain at the surface, and ice crystal multiplication processes can lead to locally produced ice crystals in the subfreezing layer below inversions. Highly variable fall velocities within the background temperature and wind fields of precipitation-type transition regions lead to varying particle trajectories and significant alterations in the distribution of precipitation amount and type at the surface. Physically based predictions that account for at least some of the phase changes and particle interactions are now in operation. Outstanding issues to be addressed include the impacts of accretion on precipitation-type formation, quantification of melting and freezing rates of the highly variable precipitation, the consequences of collisions between the various types, and the onset of ice nucleation and its effects. The precipitation physics perspective of this article furthermore needs to be integrated into a comprehensive understanding involving the surrounding and interacting environment.

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Randal Koster

Abstract

At the land surface, higher soil moisture levels generally lead to both increased evaporation for a given amount of incoming radiation (increased “evaporation efficiency”) and increased runoff for a given amount of precipitation (increased “runoff efficiency”). Evaporation efficiency and runoff efficiency can thus be said to vary with each other, motivating the development of a unique hydroclimatic analysis framework. Using a simple water balance model fitted, in different experiments, with a wide variety of functional forms for evaporation and runoff efficiency, the author transforms net radiation and precipitation fields into fields of streamflow that can be directly evaluated against observations. The optimal combination of the functional forms—the combination that produces the most skillful streamflow simulations—provides an indication for how evaporation and runoff efficiencies vary with each other in nature, a relationship that can be said to define the overall character of land surface hydrological processes, at least to the first order. The inferred optimal relationship is represented herein as a curve in “efficiency space” and should be valuable for the evaluation and development of GCM-based land surface models, which by this measure are often found to be suboptimal.

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Linda Stalker Prokopy, Lois Wright Morton, J. Gordon Arbuckle Jr., Amber Saylor Mase, and Adam K. Wilke

Abstract

Understanding U.S. agricultural stakeholder views about the existence of climate change and its causes is central to developing interventions in support of adaptation and mitigation. Results from surveys conducted with six Midwestern stakeholder groups [corn producers, agricultural advisors, climatologists, extension educators, and two different cross-disciplinary teams of scientists funded by the U.S. Department of Agriculture–National Institute of Food and Agriculture (USDA–NIFA)] reveal striking differences. Individuals representing these groups were asked in 2011/12 to “select the statement that best reflects your beliefs about climate change.” Three of five answer options included the notion that climate change is occurring but for different reasons (mostly human activities; mostly natural; more or less equally by natural and human activities). The last two options were “there is not sufficient evidence to know with certainty whether climate change is occurring or not” and “climate change is not occurring.” Results reveal that agricultural and climate scientists are more likely to believe that climate change is mostly due to human activities (50%–67%) than farmers and advisors (8%–12%). Almost a quarter of farmers and agricultural advisors believe the source of climate change is mostly natural causes, and 22%–31% state that there is not sufficient evidence to know with certainty whether it is occurring or not. This discrepancy in beliefs creates challenges for communicating climate science to agricultural stakeholders in ways that encourage adaptation and mitigation. Results suggest that engagement strategies that reduce threats to worldviews and increase public dialogue could make climate information more relevant to stakeholder groups with different belief structures.

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Florian Rauser, Peter Gleckler, and Jochem Marotzke

Abstract

We discuss the current code of practice in the climate sciences to routinely create climate model ensembles as ensembles of opportunity from the newest phase of the Coupled Model Intercomparison Project (CMIP). We give a two-step argument to rethink this process. First, the differences between generations of ensembles corresponding to different CMIP phases in key climate quantities are not large enough to warrant an automatic separation into generational ensembles for CMIP3 and CMIP5. Second, we suggest that climate model ensembles cannot continue to be mere ensembles of opportunity but should always be based on a transparent scientific decision process. If ensembles can be constrained by observation, then they should be constructed as target ensembles that are specifically tailored to a physical question. If model ensembles cannot be constrained by observation, then they should be constructed as cross-generational ensembles, including all available model data to enhance structural model diversity and to better sample the underlying uncertainties. To facilitate this, CMIP should guide the necessarily ongoing process of updating experimental protocols for the evaluation and documentation of coupled models. With an emphasis on easy access to model data and facilitating the filtering of climate model data across all CMIP generations and experiments, our community could return to the underlying idea of using model data ensembles to improve uncertainty quantification, evaluation, and cross-institutional exchange.

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Ramón de Elía

Scientists engaged in climate modeling activities have become accustomed to the specificities of their field and hence less conscious of aspects that may be perplexing to outsiders. This is a natural consequence of the widespread compartmentalization of sciences, but the case of climate sciences is somewhat particular: a large part of the science is carried out downstream from model simulations, situating this community in a particular place of responsibility to overcome communicational difficulties.

This essay attempts to sketch some characteristics and practices proper to climate modeling that are both particularly thorny to convey and of relevance for most users (here understood to be professionals with a solid general scientific background, as in the case of those involved in impact and adaptation studies). Issues difficult to communicate are of many kinds, but those about which even climate modelers may feel baffled are particularly troublesome. It is argued here that in a community heavily invested on mutual trust, not only users but also the entire climate modeling community may benefit from increased scrutiny of its foundations.

Also discussed are examples of possible research avenues that may help to strengthen climate modeling foundations and credentials, and hence increase our capacity to deliver more intelligible and trustworthy climate information to sophisticated users.

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John P. Dawson, Bryan J. Bloomer, Darrell A. Winner, and Christopher P. Weaver

Particulate matter (PM) air pollution is a serious public health issue for the United States. While there is a growing body of evidence that climate change will partially counter the effectiveness of future precursor emission reductions to reduce ozone (O3) air pollution, the links between PM and climate change are more complex and less understood. This paper discusses what we currently understand about the potential sensitivity of PM episodes to climate-change-related shifts in air pollution meteorology, in the broader context of the emissions and atmospheric chemistry drivers of PM. For example, initial studies have focused largely on annual average concentrations of inorganic aerosol species. However, the potential for future changes in the occurrence of PM episodes, and their underlying meteorological drivers, are likely more important to understand and remain highly uncertain. In addition, a number of other poorly understood factors interact with these likely critical meteorological changes. These include changes in emissions from wildfires, as well as atmospheric processing of organic aerosol precursor chemicals. More work is needed to support the management of the health and environmental risks of climate-induced changes in PM. We suggest five priorities for the research community to address based on the current state of the literature.

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Mark S. Brooks

Climate services can help society manage climate-related risk and capitalize on favorable conditions by providing data analysis, data products, and scientific expertise. Meeting society's needs requires matching them with ongoing scientific research. Despite the best of intentions, some research never makes it into operational products or services. Likewise, some societal needs are never met and scientific capabilities never realized. The three E's of climate services—engagement, entrepreneurship, and evaluation—can help climate service providers bridge this research-to-operations “valley of death” and create valuable, innovative climate services for our nation. This essay aims to stimulate such progress in the climate services enterprise.

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Bart van den Hurk, Martin Best, Paul Dirmeyer, Andy Pitman, Jan Polcher, and Joe Santanello

No abstract available.

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Lee Tryhorn and Art DeGaetano

No Abstract available.

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