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Food security is a key pillar of environmental security yet remains one of the world's greatest challenges. Its obverse, food insecurity, negatively impacts health and well-being, drives mass migration, and undermines national security and global sustainable development. Ensuring food security is a delicate balance of myriad concerns within the atmospheric and Earth sciences, agronomy and agriculture engineering, social sciences, economics, monitoring, and policymaking. A Food Security Presidential Session at the American Meteorological Society's (AMS) 2022 Annual Meeting brought together experts across disciplines to tackle issues at the nexus of weather, climate, and food security. The starkest takeaway was the realization that, despite its importance and clear roles for the atmospheric and climate sciences, food security has not been a focus for the AMS community. The aim of this paper is to build on the perspectives shared by this expert panel and to identify overlapping issues and key points of intersection between the food-security community and AMS. We examine 1) the interactions between weather, climate, and the food system and how they influence food security; 2) the time and spatial scales of food security decision support that match weather and climate phenomena; 3) the role of both providers and users of information as well as decision-makers in improving research to operations for food security; and 4) the opportunities for the AMS community to address food security. We conclude that, moving forward, the AMS community is well-positioned to scale up its engagement across the global food system to address existing scientific needs and technology gaps to improve global food security. SIGNIFICANCE STATEMENT: We examine how members of the AMS community can help ensure global food security, whether they are engaged in the physical and social sciences or the realms of policy and society. Inspired by the messages of panelists at a Presidential Forum on Food Security at the 2022 AMS Annual Meeting, we gather their perspectives and those of experts working in the various relevant fields and find that there are roles for everyone across the AMS—from providing forecasts of the hydrometeorological variables used in food security outlooks to converting data to knowledge and engaging with stakeholders and decision-makers. We make concrete suggestions to ensure the AMS and its members are fully engaged in feeding the world. [ABSTRACT FROM AUTHOR]

Reprints of articles about meteorology research published in 2007 issues of "Weather and Forecasting", "Journal of Climate," and "Journal of Atmospheric and Oceanic Technology" are presented. They are "Performance Assessment of the World Wide Lightning Location Network (WWLLN), Using the Los Alamos Sferic Array (LASA) as Ground Truth", "How Well Do We Understand and Evaluate Climate Change Feedback Processes?," and "Developing Tools for Nowcasting Storm Severity".

Instrumental data from the pre–Industrial Revolution period are important to -understand climate change. In this paper, the observations made by the French missionary J. Amiot in present-day central Beijing during 1757–62 were processed and analyzed. The observations represent the earliest continuous dataset of meteorological records found in China that have been digitized recently. Comparisons between the Amiot annual temperature range and extreme values with modern observations showed that the observations were read at approximately 0800 and 1500 local solar time (LST) in a well-ventilated outdoor site. The daily maximum, minimum, and mean temperatures (T-max, T-min, and T-mean, respectively) during 1757–62 were determined by examining the relationship between temperature at 0800 and 1500 LST and T-max, T-min, and T-mean in modern reference series. Nearly 260 years ago, Beijing's climate was typical of an inland temperate monsoon zone with annual T-mean, annual mean T-max, and annual mean T-min being 11.5°, 17.8°, and 6.1°C, respectively; further, the temperatures did not vary considerably from the 1951–1980 temperatures, but differed evidently compared to relatively recent decades (1981–2020). The difference was larger than the magnitudes of global and regional temperature changes. Thus, climate warming since the pre–Industrial Revolution period in the urban areas of Beijing has dominantly occurred over the last four decades. Uncertainties related to the thermometer and observational conditions 260 years ago and the interpolation method used have also been discussed in this paper. [ABSTRACT FROM AUTHOR]

The article offers information on several studies related to meteorology. One of the studies focuses on the use and performance of Weather Research and Forecting (WRF) as a regional climate model. The other study states that with the decrease in environmental temperature the ability of tropical cyclones to shed angular momentum from the core is also increased. Another study suggests a strong link between the regional heat waves observed in 2006 and the global climate change.

Projections of changes in tropical cyclone (TC) characteristics under climate change are of great interest to those affected by TCs. In a recent paper, Knutson et al. combined a large number of previous results to produce projections consisting of distributions of possible future TC frequencies, intensities, and rainfall rates. These distributions provide a great resource for users of TC information. However, to apply the distributions to impacts models may require the user to solve a number of technical challenges including modeling correlations, fitting distributions, interpolation, and converting the projections to properties at landfall. I consider the frequency and intensity changes, and implement solutions for each of these challenges using a combination of recently published research and a new methodology. This allows me to produce a dataset of TC projections that give frequency changes as a function of landfall region and intensity. Mean intensity changes can then be derived from frequency changes. The projections are presented in a format that allows them to be used in impacts models without further processing. The interpolation and landfall adjustments tend to increase the frequency changes. As a result, my projections give increasing mean frequencies of hurricane-strength landfalling TCs in four out of six global basins, with mean frequencies increasing by up to 16% for a 2°C increase in global mean surface temperature. My projections are highly uncertain, but include uncertainty estimates. They are designed to be a useful resource for anyone interested in possible future TC frequencies and intensities. [ABSTRACT FROM AUTHOR]

The Global Energy and Water Cycle Exchanges (GEWEX) project was created more than 30 years ago within the framework of the World Climate Research Programme (WCRP). The aim of this initiative was to address major gaps in our understanding of Earth's energy and water cycles given a lack of information about the basic fluxes and associated reservoirs of these cycles. GEWEX sought to acquire and set standards for climatological data on variables essential for quantifying water and energy fluxes and for closing budgets at the regional and global scales. In so doing, GEWEX activities led to a greatly improved understanding of processes and our ability to predict them. Such understanding was viewed then, as it remains today, essential for advancing weather and climate prediction from global to regional scales. GEWEX has also demonstrated over time the importance of a wider engagement of different communities and the necessity of international collaboration for making progress on understanding and on the monitoring of the changes in the energy and water cycles under ever increasing human pressures. This paper reflects on the first 30 years of evolution and progress that has occurred within GEWEX. This evolution is presented in terms of three main phases of activity. Progress toward the main goals of GEWEX is highlighted by calling out a few achievements from each phase. A vision of the path forward for the coming decade, including the goals of GEWEX for the future, are also described. [ABSTRACT FROM AUTHOR]

The unique characteristics of land–air coupling and troposphere–stratosphere interaction over the Tibetan Plateau (TP), the highest landform in the world, play a vital role in weather and climate on regional and global scales. Although a great deal of research has been carried out, large gaps remain in our understanding of TP land–air coupling and its climate effects, due to a lack of observations and the issue of model biases. To address these obstacles, a 10-yr national research program entitled "Changes in the Land–Air Coupled System over the Tibetan Plateau and its Impacts on Global Climate (LASTPIC)" was launched by the National Natural Science Foundation of China in January 2014. What LASTPIC does revolves around three aspects: TP land–air coupled processes; TP's influence on global climate; and reanalysis and model. This paper mainly focuses on the data collection, scientific understanding, and model development of LASTPIC in terms of TP land–atmosphere–ocean coupling and its global climate impacts since program's inception. [ABSTRACT FROM AUTHOR]

The article presents a research study of the Galápagos Island and its effect on the El Nião-Southern Oscillation (ENSO). ENSO is considered as one of the climate oscillations on Earth. The researchers used an ocean general circulating model and a hybrid coupled model of the tropical Pacific Ocean to examine the effects of the Galápagos Island on ENSO. Results such as the shift lead by the island in the ENSO period from biennial to quasi-quadrinneal are presented. Also, further studies in relation to the subject are encouraged.

The article reports on the climate impacts of anthropogenic carbon dioxide emissions. In its Fourth Assessment Report, the Intergovernmental Panel on Climate Change (IPCC) suggests that about 50 percent of a carbon dioxide increase will be removed from the atmosphere within 30 years. It is reported that the logarithmic relationship between carbon dioxide and its radiative forcing implies that the time scale at which atmospheric temperature declines will be longer.

Regional climate modeling addresses our need to understand and simulate climatic processes and phenomena unresolved in global models. This paper highlights examples of current approaches to and innovative uses of regional climate modeling that deepen understanding of the climate system. High-resolution models are generally more skillful in simulating extremes, such as heavy precipitation, strong winds, and severe storms. In addition, research has shown that fine-scale features such as mountains, coastlines, lakes, irrigation, land use, and urban heat islands can substantially influence a region's climate and its response to changing forcings. Regional climate simulations explicitly simulating convection are now being performed, providing an opportunity to illuminate new physical behavior that previously was represented by parameterizations with large uncertainties. Regional and global models are both advancing toward higher resolution, as computational capacity increases. However, the resolution and ensemble size necessary to produce a sufficient statistical sample of these processes in global models has proven too costly for contemporary supercomputing systems. Regional climate models are thus indispensable tools that complement global models for understanding physical processes governing regional climate variability and change. The deeper understanding of regional climate processes also benefits stakeholders and policymakers who need physically robust, high-resolution climate information to guide societal responses to changing climate. Key scientific questions that will continue to require regional climate models, and opportunities are emerging for addressing those questions. [ABSTRACT FROM AUTHOR]

The Third Pole (TP) is experiencing rapid warming and is currently in its warmest period in the past 2,000 years. This paper reviews the latest development in multidisciplinary TP research associated with this warming. The rapid warming facilitates intense and broad glacier melt over most of the TP, although some glaciers in the northwest are advancing. By heating the atmosphere and reducing snow/ice albedo, aerosols also contribute to the glaciers melting. Glacier melt is accompanied by lake expansion and intensification of the water cycle over the TP. Precipitation has increased over the eastern and northwestern TP. Meanwhile, the TP is greening and most regions are experiencing advancing phenological trends, although over the southwest there is a spring phenological delay mainly in response to the recent decline in spring precipitation. Atmospheric and terrestrial thermal and dynamical processes over the TP affect the Asian monsoon at different scales. Recent evidence indicates substantial roles that mesoscale convective systems play in the TP's precipitation as well as an association between soil moisture anomalies in the TP and the Indian monsoon. Moreover, an increase in geohazard events has been associated with recent environmental changes, some of which have had catastrophic consequences caused by glacial lake outbursts and landslides. Active debris flows are growing in both frequency of occurrences and spatial scale. Meanwhile, new types of disasters, such as the twin ice avalanches in Ali in 2016, are now appearing in the region. Adaptation and mitigation measures should be taken to help societies' preparation for future environmental challenges. Some key issues for future TP studies are also discussed. [ABSTRACT FROM AUTHOR]

This article presents a brief account of scientific research into solar geoengineering in India in the last decade. In recent years, solar geoengineering has been proposed as an option to ameliorate the detrimental impacts of climate change in case the required emissions reductions do not take place rapidly. Hundreds of research papers have been published in the last decade by both natural and social scientists on the feasibility, effectiveness, cost, and risks, and the ethical, legal, social, political, and governance dimensions of geoengineering. Most of this research is conducted in the developed world, and very little research or discussion has taken place in the global South. However, it has been argued in several forums that the developing world should have a central role in solar-geoengineering research, discussion, and evaluation for political and moral reasons. We present here a brief account of the Indian scientific research into solar geoengineering. Climate modeling constitutes the major component of this geoengineering-relevant climate science research. The recent funding initiative by the Department of Science and Technology—the main funding agency for scientific research in India—in support of geoengineering modeling research and its efforts to bring natural, social, and political scientists together for an evaluation of solar geoengineering at meetings are also discussed. Finally, the directions for future scientific research into geoengineering in India are a lso discussed. [ABSTRACT FROM AUTHOR]

Information about several papers discussed at the Climate Resilient Grid: A Forum on Energy, Climate, and the Grid conference held June 14-15, 2017 in Asheville, North Carolina. Topics focused on the use of environmental and climate data for meeting needs in energy delivery and bringing new renewables online, specifically the use of environmental information in asset planning, use of renewables to build an adaptive infrastructure, and role of climate change in energy delivery.

This paper describes the Stratospheric Aerosol Geoengineering Large Ensemble (GLENS) project, which promotes the use of a unique model dataset, performed with the Community Earth System Model, with the Whole Atmosphere Community Climate Model as its atmospheric component [CESM1(WACCM)], to investigate global and regional impacts of geoengineering. The performed simulations were designed to achieve multiple simultaneous climate goals, by strategically placing sulfur injections at four different locations in the stratosphere, unlike many earlier studies that targeted globally averaged surface temperature by placing injections in regions at or around the equator. This advanced approach reduces some of the previously found adverse effects of stratospheric aerosol geoengineering, including uneven cooling between the poles and the equator and shifts in tropical precipitation. The 20-member ensemble increases the ability to distinguish between forced changes and changes due to climate variability in global and regional climate variables in the coupled atmosphere, land, sea ice, and ocean system. We invite the broader community to perform in-depth analyses of climate-related impacts and to identify processes that lead to changes in the climate system as the result of a strategic application of stratospheric aerosol geoengineering. [ABSTRACT FROM AUTHOR]

Strong winds crossing elevated terrain and descending to its lee occur over mountainous areas worldwide. Winds fulfilling these two criteria are called foehn in this paper although different names exist depending on the region, the sign of the temperature change at onset, and the depth of the overflowing layer. These winds affect the local weather and climate and impact society. Classification is difficult because other wind systems might be superimposed on them or share some characteristics. Additionally, no unanimously agreed-upon name, definition, nor indications for such winds exist. The most trusted classifications have been performed by human experts. A classification experiment for different foehn locations in the Alps and different classifier groups addressed hitherto unanswered questions about the uncertainty of these classifications, their reproducibility, and dependence on the level of expertise. One group consisted of mountain meteorology experts, the other two of master's degree students who had taken mountain meteorology courses, and a further two of objective algorithms. Sixty periods of 48 h were classified for foehn–no foehn conditions at five Alpine foehn locations. The intra-human-classifier detection varies by about 10 percentage points (interquartile range). Experts and students are nearly indistinguishable. The algorithms are in the range of human classifications. One difficult case appeared twice in order to examine the reproducibility of classified foehn duration, which turned out to be 50% or less. The classification dataset can now serve as a test bed for automatic classification algorithms, which—if successful—eliminate the drawbacks of manual classifications: lack of scalability and reproducibility. [ABSTRACT FROM AUTHOR]

The time scales of the Paris Climate Agreement indicate urgent action is required on climate policies over the next few decades, in order to avoid the worst risks posed by climate change. On these relatively short time scales the combined effect of climate variability and change are both key drivers of extreme events, with decadal time scales also important for infrastructure planning. Hence, in order to assess climate risk on such time scales, we require climate models to be able to represent key aspects of both internally driven climate variability and the response to changing forcings. In this paper we argue that we now have the modeling capability to address these requirements—specifically with global models having horizontal resolutions considerably enhanced from those typically used in previous Intergovernmental Panel on Climate Change (IPCC) and Coupled Model Intercomparison Project (CMIP) exercises. The improved representation of weather and climate processes in such models underpins our enhanced confidence in predictions and projections, as well as providing improved forcing to regional models, which are better able to represent local-scale extremes (such as convective precipitation). We choose the global water cycle as an illustrative example because it is governed by a chain of processes for which there is growing evidence of the benefits of higher resolution. At the same time it comprises key processes involved in many of the expected future climate extremes (e.g., flooding, drought, tropical and midlatitude storms). [ABSTRACT FROM AUTHOR]

Urban areas are responsible for a substantial proportion of anthropogenic carbon emissions around the world. As global populations increasingly reside in cities, the role of urban emissions in determining the future trajectory of carbon emissions is magnified. Consequently, a number of research efforts have been started in the United States and beyond, focusing on observing atmospheric carbon dioxide (CO2) and relating its variations to carbon emissions in cities. Because carbon emissions are intimately tied to socioeconomic activity through the combustion of fossil fuels, and many cities are actively adopting emission reduction plans, such urban carbon research efforts give rise to opportunities for stakeholder engagement and guidance on other environmental issues, such as air quality. This paper describes a research effort centered in the Salt Lake City, Utah, metropolitan region, which is the locus for one of the longest-running urban CO2 networks in the world. The Salt Lake City area provides a rich environment for studying anthropogenic emissions and for understanding the relationship between emissions and socioeconomic activity when the CO2 observations are enhanced with a) air quality observations, b) novel mobile observations from platforms on light-rail public transit trains and a news helicopter, c) dense meteorological observations, and d) modeling efforts that include atmospheric simulations and high-resolution emission inventories. Carbon dioxide and other atmospheric observations are presented, along with associated modeling work. Examples in which the work benefited from and contributed to the interests of multiple stakeholders (e.g., policymakers, air quality managers, municipal government, urban planners, industry, and the general public) are discussed. [ABSTRACT FROM AUTHOR]

The National Center for Atmospheric Research (NCAR) operates a state-of-the-art S-band dual-polarization Doppler radar (S-Pol) for the National Science Foundation (NSF). This radar has some similar and some distinguishing characteristics to the National Weather Service (NWS) operational Weather Surveillance Radar-1988 Doppler Polarimetric (WSR-88DP). One key difference is that the WSR-88DP is used for operational purposes where rapid 360° volumetric scanning is required to monitor rapid changes in storm characteristics for nowcasting and issuing severe storm warnings. Since S-Pol is used to support the NSF research community, it usually scans at much slower rates than operational radars. This results in higher resolution and higher data quality suitable for many research studies. An important difference between S-Pol and the WSR-88DP is S-Pol's ability to use customized scan strategies including scanning on vertical surfaces ([range–height indicators (RHIs)], which are presently not done by WSR-88DPs. RHIs provide high-resolution microphysical structures of convective storms, which are central to many research studies. Another important difference is that the WSR-88DP simultaneously transmits horizontal (H) and vertical (V) polarized pulses. In contrast, S-Pol typically transmits alternating H and V pulses, which results in not only higher data quality for research but also allows for the cross-polar signal to be measured. The cross-polar signal provides estimates of the linear depolarization ratio (LDR) and the co- to cross-correlation coefficient that give additional microphysical information. This paper presents plots and interpretations of high-quality, high-resolution polarimetric data that demonstrate the value of S-Pol's polarimetric measurements for atmospheric research. [ABSTRACT FROM AUTHOR]

Over much of the globe, the temporal extent of meteorological records is limited, yet a wealth of data remains in paper or image form in numerous archives. To date, little attention has been given to the role that students might play in efforts to rescue these data. Here we summarize an ambitious research-led, accredited teaching experiment in which undergraduate students successfully transcribed more than 1,300 station years of daily precipitation data and associated metadata across Ireland over the period 1860–1939. We explore i) the potential for integrating data rescue activities into the classroom, ii) the ability of students to produce reliable transcriptions and, iii) the learning outcomes for students. Data previously transcribed by Met Éireann (Ireland's National Meteorological Service) were used as a benchmark against which it was ascertained that students were as accurate as the professionals. Details on the assignment, its planning and execution, and student-aids used are provided. The experience highlights the benefits that can accrue for data rescue through innovative collaboration between national meteorological services and academic institutions. At the same time, students have gained valuable learning outcomes and firsthand understanding of the processes that underpin data rescue and analysis. The success of the project demonstrates the potential to extend data rescue in the classroom to other universities, thus providing both an enriched learning experience for the students and a lasting legacy to the scientific community. [ABSTRACT FROM AUTHOR]

Ouranos is a nonprofit consortium launched in 2002 with the mandate to provide climate services to its governmental, academic, and private partners. These services have focused on the impacts of climate change in the province of Québec, the identification of vulnerabilities and opportunities associated with the future climate, and the assessment of adaptation options. This paper discusses the experience and insights acquired at Ouranos over the last 10 years in building climate scenarios in support of these impact and adaptation studies. Most of this work is aimed at making climate science intelligible and useful for end users, and the paper describes approaches to developing climate scenarios that are tailored to the needs and level of climate expertise of different user categories. The experience has shown that a group of professionals dedicated to scenario construction and user support is a key element in the delivery of effective climate services. [ABSTRACT FROM AUTHOR]

The European Reanalysis of Global Climate Observations 2 (ERA-CLIM2) is a European Union Seventh Framework Project started in January 2014 and due to be completed in December 2017. It aims to produce coupled reanalyses, which are physically consistent datasets describing the evolution of the global atmosphere, ocean, land surface, cryosphere, and the carbon cycle. ERA-CLIM2 has contributed to advancing the capacity for producing state-of-the-art climate reanalyses that extend back to the early twentieth century. ERA-CLIM2 has led to the generation of the first European ensemble of coupled ocean, sea ice, land, and atmosphere reanalyses of the twentieth century. The project has funded work to rescue and prepare observations and to advance the data-assimilation systems required to generate operational reanalyses, such as the ones planned by the European Union Copernicus Climate Change Service. This paper summarizes the main goals of the project, discusses some of its main areas of activities, and presents some of its key results. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The Arctic is a vital component of the global climate, and its rapid environmental evolution is an important element of climate change around the world. To detect and diagnose the changes occurring to the coupled Arctic climate system, a state-of-the-art synthesis for assessment and monitoring is imperative. This paper presents the Arctic System Reanalysis, version 2 (ASRv2), a multiagency, university-led retrospective analysis (reanalysis) of the greater Arctic region using blends of the polar-optimized version of the Weather Research and Forecasting (Polar WRF) Model and WRF three-dimensional variational data assimilated observations for a comprehensive integration of the regional climate of the Arctic for 2000-12. New features in ASRv2 compared to version 1 (ASRv1) include 1) higher-resolution depiction in space (15-km horizontal resolution), 2) updated model physics including subgrid-scale cloud fraction interaction with radiation, and 3) a dual outer-loop routine for more accurate data assimilation. ASRv2 surface and pressure-level products are available at 3-hourly and monthly mean time scales at the National Center for Atmospheric Research (NCAR). Analysis of ASRv2 reveals superior reproduction of near-surface and tropospheric variables. Broadscale analysis of forecast precipitation and site-specific comparisons of downward radiative fluxes demonstrate significant improvement over ASRv1. The high-resolution topography and land surface, including weekly updated vegetation and realistic sea ice fraction, sea ice thickness, and snow-cover depth on sea ice, resolve finescale processes such as topographically forced winds. Thus, ASRv2 permits a reconstruction of the rapid change in the Arctic since the beginning of the twenty-first century-complementing global reanalyses. ASRv2 products will be useful for environmental models, verification of regional processes, or siting of future observation networks. [ABSTRACT FROM AUTHOR]

This paper presents the background, scientific objectives, experimental design, and preliminary achievements of the Third Tibetan Plateau (TP) Atmospheric Scientific Experiment (TIPEX-III) for 8-10 years. It began in 2013 and has expanded plateau-scale observation networks by adding observation stations in data-scarce areas; executed integrated observation missions for the land surface, planetary boundary layer, cloud-precipitation, and troposphere-stratosphere exchange processes by coordinating ground-based, air-based, and satellite facilities; and achieved noticeable progress in data applications. A new estimation gives a smaller bulk transfer coefficient of surface sensible heat over the TP, which results in a reduction of the possibly overestimated heat intensity found in previous studies. Summer cloud-precipitation microphysical characteristics and cloud radiative effects over the TP are distinguished from those over the downstream plains. Warm rain processes play important roles in the development of cloud and precipitation over the TP. The lower-tropospheric ozone maximum over the northeastern TP is attributed to the regional photochemistry and long-range ozone transports, and the heterogeneous chemical processes of depleting ozone near the tropopause might not be a dominant mechanism for the summer upper-tropospheric-lower-stratospheric ozone valley over the southeastern TP. The TP thermodynamic function not only affects the local atmospheric water maintenance and the downstream precipitation and haze events but also modifies extratropical atmospheric teleconnections like the Asia-Pacific Oscillation, subtropical anticyclones over the North Pacific and Atlantic, and temperature and precipitation over Africa, Asia, and North America. These findings provide new insights into understanding land-atmosphere coupled processes over the TP and their effects, improving model parameterization schemes, and enhancing weather and climate forecast skills. [ABSTRACT FROM AUTHOR]

The study of Decadal Climate Variability (DCV) and Predictability is the interdisciplinary endeavor to characterize, understand, attribute, simulate, and predict the slow, multiyear variations of climate at global (e.g., the recent slowdown of global mean temperature rise in the early 2000s) and regional (e.g., decadal modulation of hurricane activity in the Atlantic, ongoing drought in California or in the Sahel in the 1970s-80s, etc.) scales. This study remains very challenging despite decades of research, extensive progress in climate system modeling, and improvements in the availability and coverage of a wide variety of observations. Considerable obstacles in applying this knowledge to actual predictions remain. This short article is a succint review paper about DCV and predictability. Based on listed issues and priorities, it also proposes a unifying theme referred to as "drivers of teleconnectivity" as a backbone to address and structure the core DCV research challenge. This framework goes beyond a preoccupation with changes in the global mean temperature and directly addresses the regional impacts of external (natural and anthropogenic) climate forcing and internal climate interactions; it thus explicitly deals with the societal needs for region-specific climate information. Such a framework also enables the integration of efforts in a large international research community toward advancing the observation, characterization, understanding, and prediction of DCV. Recommendations to make progress are provided as part of the contribution of the CLIVAR "DCVP Research Focus" group. [ABSTRACT FROM AUTHOR]

Information about several papers discussed in the Global Energy and Water Exchanges project (GEWEX) Convection-Permitting Climate Modeling Workshop held on September 6-8, 2016 in Boulder, Colorado, is presented. Topics discussed include the impacts of climate change and climate variability on society, use of convection-permitting models and the role of mesoscale processes in the climate system.

The article presents abstracts of papers included in the current issue of the "Bulletin of the American Meteorological Society," with topics such as regional climate change simulations, influence of the polar vortex on the weather and the distribution of rain gauges across the globe.

This fifth edition of explaining extreme events of the previous year (2015) from a climate perspective continues to provide evidence that climate change is altering some extreme event risk. Without exception, all the heat-related events studied in this year's report were found to have been made more intense or likely due to human-induced climate change, and this was discernible even for those events strongly influenced by the 2015 El Niño. Furthermore, many papers in this year's report demonstrate that attribution science is capable of separating the effects of natural drivers including the strong 2015 El Niño from the influences of long-term human-induced climate change. Other event types investigated include cold winters, tropical cyclone activity, extreme sunshine in the United Kingdom, tidal flooding, precipitation, drought, reduced snowpack in the U.S. mountain west, arctic sea ice extent, and wildfires in Alaska. Two studies investigated extreme cold waves and monthly-mean cold conditions over eastern North America during 2015, and find these not to have been symptomatic of human-induced climate change. Instead, they find the cold conditions were caused primarily by internally generated natural variability. One of these studies shows winters are becoming warmer, less variable, with no increase in daily temperature extremes over the eastern United States. Tropical cyclone activity was extreme in 2015 in the western North Pacific (WNP) as measured by accumulated cyclone energy (ACE). In this report, a study finds that human-caused climate change largely increased the odds of this extreme cyclone activity season. The 2015 Alaska fire season burned the second largest number of acres since records began in 1940. Investigators find that human-induced climate change has increased the likelihood of a fire season of this severity. Confidence in results and ability to quickly do an attribution analysis depend on the "three pillars" of event attribution: the quality of the observational record, the ability of models to simulate the event, and our understanding of the physical processes that drive the event and how they are being impacted by climate change. A result that does not find a role for climate change may be because one or more of these three elements is insufficient to draw a clear conclusion. As these pillars are strengthened for different event types, confidence in the presence and absence of a climate change influence will increase. This year researchers also link how changes in extreme event risk impact human health and discomfort during heat waves, specifically by looking at the role of climate change on the wet bulb globe temperature during a deadly heat wave in Egypt. This report reflects a growing interest within the attribution community to connect attribution science to societal impacts to inform risk management through "impact attribution." Many will watch with great interest as this area of research evolves in the coming years. INSET: EDITORIAL AND PRODUCTION TEAM. [ABSTRACT FROM AUTHOR]

This paper reviews recent research on tropical cyclones and climate change from the perspective of event risk—the physical behavior of storms; vulnerability—the characteristics of a system that create the potential for impacts, but are independent of event risk; and also outcome risk—the integration of considerations of vulnerability with event risk to characterize an event that causes losses. The paper concludes that with no trend identified in various metrics of hurricane damage over the twentieth century, it is exceedingly unlikely that scientists will identify large changes in historical storm behavior that have significant societal implications, though scientists may identify discernible changes in storm behavior. Looking to the future, until scientists conclude a) that there will be changes to storms that are significantly larger than observed in the past, b) that such changes are correlated to measures of societal impact, and c) that the effects of such changes are significant in the context of inexorable growth in population and property at risk, then it is reasonable to conclude that the significance of any connection of human-caused climate change to hurricane impacts necessarily has been and will continue to be exceedingly small. [ABSTRACT FROM AUTHOR]

Using satellite remote sensing techniques to take quantitative observations of the climate system will advance our knowledge and ability to model the climate system and its changes. Polar-orbiting satellite records of global land surface skin temperature (LST) observations have high coverage and quality. Although limited in accuracy, and to a few years in length, these measurements are extremely useful because they are improvements on existing data. This paper introduces a global, long-duration satellite diurnal cycle dataset of LST for 1981–98. LST measurements from National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) sensors are generally only twice per day for most areas and suffer problems such as cloud contamination and orbital drift. These problems are corrected using the algorithms developed by Jin and Dickinson, Jin, and Jin and Treadon, and consequently provide a long-term, monthly, global 8-km land surface skin temperature diurnal cycle dataset (LSTD) for temporally consistent LST records. As a unique and independent resource, LSTD is valuable for studying the land surface climate and for evaluating model performance. For the first time, in this paper, the diurnal, seasonal, and interannual variations of LST are presented as a prototype use of this dataset. In addition, LSTD is compared with the National Centers for Environmental Prediction (NCEP)–National Center for Atmospheric Research (NCAR) re-analysis, in situ air temperature, the NOAA's Television Infrared Observation Satellite (TIROS) Operational Vertical Sounder (TOVS) observations, and shows encouraging consistencies on major features. These consistencies suggest that LSTD will be very valuable for climate change study. [ABSTRACT FROM AUTHOR]

The MacKenzie Global Energy and Water Cycle Experiment (GEWEX) Study, Phase 1, seeks to improve understanding of energy and water cycling in the Mackenzie River basin (MRB) and to initiate and test atmospheric, hydrologic, and coupled models that will project the sensitivity of these cycles to climate change and to human activities. Major findings from the study are outlined in this paper. Absorbed solar radiation is a primary driving force of energy and water, and shows dramatic temporal and spatial variability. Cloud amounts feature large diurnal, seasonal, and interannual fluctuations. Seasonality in moisture inputs and outputs is pronounced. Winter in the northern MRB features deep thermal inversions. Snow hydrological processes are very significant in this high-latitude environment and are being successfully modeled for various landscapes. Runoff processes are distinctive in the major terrain units, which is important to overall water cycling. Lakes and wetlands compose much of MRB and are prominent as hydrologic storage systems that must be incorporated into models. Additionally, they are very efficient and variable evaporating systems that are highly sensitive to climate variability. Mountainous high-latitude subbasins comprise a mosaic of land surfaces with distinct hydrological attributes that act as variable source areas for runoff generation. They also promote leeward cyclonic storm generation. The hard rock terrain of the Canadian Shield exhibits a distinctive energy flux regimen and hydrologic regime. The MRB has been warming dramatically recently, and ice breakup and spring outflow into the Polar Sea has been occurring progressively earlier. This paper presents initial results from coupled atmospheric–hydrologic modeling and delineates distinctive cold region inputs needed for developments in regional and global climate modeling. [ABSTRACT FROM AUTHOR]

Land use and land cover change (LULCC) significantly influences the climate system. Hence, to prepare the nation for future climate change and variability, a sustained assessment of LULCC and its climatic impacts needs to be undertaken. To address this objective, not only do we need to determine contemporary trends in land use and land cover that affect, or are affected by, weather and climate but also identify sectors and regions that are most affected by weather and climate variability. Moreover, it is critical that we recognize land cover and regions that are most vulnerable to climate change and how end-use practices are adapting to climate change. This paper identifies a series of steps that need to be undertaken to address these key items. In addition, national-scale institutional capabilities are identified and discussed. Included in the discussions are challenges and opportunities for collaboration among these institutions for a sustained assessment. [ABSTRACT FROM AUTHOR]

Climate research, monitoring, prediction, and related services rely on accurate observations of the atmosphere, land, and ocean, adequately sampled globally and over sufficiently long time periods. The Global Climate Observing System, set up under the auspices of United Nations organizations and the International Council for Science to help ensure the availability of systematic observations of climate, developed the concept of essential climate variables (ECVs). ECV data records are intended to provide reliable, traceable, observation-based evidence for a range of applications, including monitoring, mitigating, adapting to, and attributing climate changes, as well as the empirical basis required to understand past, current, and possible future climate variability. The ECV concept has been broadly adopted worldwide as the guiding basis for observing climate, including by the United Nations Framework Convention on Climate Change (UNFCCC), WMO, and space agencies operating Earth observation satellites. This paper describes the rationale for these ECVs and their current selection, based on the principles of feasibility, relevance, and cost effectiveness. It also provides a view of how the ECV concept could evolve as a guide for rational and evidence-based monitoring of climate and environment. Selected examples are discussed to highlight the benefits, limitations, and future evolution of this approach. The article is intended to assist program managers to set priorities for climate observation, dataset generation and related research: for instance, within the emerging Global Framework for Climate Services (GFCS). It also helps the observation community and individual researchers to contribute to systematic climate observation, by promoting understanding of ECV choices and the opportunities to influence their evolution. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The Feldbach region in southeast Austria, characteristic for experiencing a rich variety of weather and climate patterns, has been selected as the focus area for a pioneering weather and climate observation network at very high resolution: The WegenerNet comprises 151 meteorological stations measuring temperature, precipitation, and other parameters, in a tightly spaced grid within an area of about 20 km × 15 km centered near the city of Feldbach (46.93°N, 15.90°E). With its stations about every 2 km2, each with 5-min time sampling, the network provides regular measurements since January 2007, after a pilot phase, until 2010, meanwhile in an operational manner. Quality-controlled station time series and gridded field data (spacing 200 m × 200 m) are available in near-real time (data latency less than 1-2 h) for visualization and download via a data portal (; detailed information is available via ). This paper introduces the WegenerNet from its design and setup via its processing system and data products to showing example results. The latter include extreme weather event examples, climate variability over the 5-yr period from 2007 to 2011, and an example of calibration support to coupled climate-hydrology modeling. The network is set to serve as a long-term monitoring and validation facility for weather and climate research and applications. Uses include validation of nonhydrostatic models operated at 1-km-scale resolution and of statistical downscaling techniques (in particular for precipitation), validation of weather radar and satellite data, study of orography-climate relationships, and many others. [ABSTRACT FROM AUTHOR]

Climate has been recognized to have direct and indirect impact on society and economy, both in the long term and daily life. The challenge of understanding the climate system, with its variability and changes, is enormous and requires a joint long-term international commitment from research and governmental institutions. An important international body to coordinate worldwide climate monitoring efforts is the World Meteorological Organization (WMO). The Global Climate Observing System (GCOS) has the mission to provide coordination and the requirements for global observations and essential climate variables (ECVs) to monitor climate changes. The WMO-led activity on Sustained, Coordinated Processing of Environmental Satellite Data for Climate Monitoring (SCOPE-CM) is responding to these requirements by ensuring a continuous and sustained generation of climate data records (CDRs) from satellite data in compliance with the principles and guidelines of GCOS. SCOPE-CM represents a new partnership between operational space agencies to coordinate the generation of CDRs. To this end, pilot projects for different ECVs, such as surface albedo, cloud properties, water vapor, atmospheric motion winds, and upper-tropospheric humidity, have been initiated. The coordinated activity on land surface albedo involves the operational meteorological satellite agencies in Europe [European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT)], in Japan [the Japan Meteorological Agency (JMA)], and in the United States [National Oceanic and Atmospheric Administration (NOAA)]. This paper presents the first results toward the generation of a unique land surface albedo CDR, involving five different geostationary satellite positions and approximately three decades of data starting in the 1980s, and combining close to 30 different satellite instruments. INSET: SATELLITE DATA ARCHIVES: JMA, EUMETSAT, AND NOAA. [ABSTRACT FROM AUTHOR]

The North American Regional Climate Change Assessment Program (NARCCAP) is an international effort designed to investigate the uncertainties in regional-scale projections of future climate and produce high-resolution climate change scenarios using multiple regional climate models (RCMs) nested within atmosphere-ocean general circulation models (AOGCMs) forced with the Special Report on Emission Scenarios (SRES) A2 scenario, with a common domain covering the conterminous United States, northern Mexico, and most of Canada. The program also includes an evaluation component (phase I) wherein the participating RCMs, with a grid spacing of 50 km, are nested within 25 years of National Centers for Environmental Prediction-Department of Energy (NCEP-DOE) Reanalysis II. This paper provides an overview of evaluations of the phase I domain-wide simulations focusing on monthly and seasonal temperature and precipitation, as well as more detailed investigation of four subregions. The overall quality of the simulations is determined, comparing the model performances with each other as well as with other regional model evaluations over North America. The metrics used herein do differentiate among the models but, as found in previous studies, it is not possible to determine a "best" model among them. The ensemble average of the six models does not perform best for all measures, as has been reported in a number of global climate model studies. The subset ensemble of the two models using spectral nudging is more often successful for domain-wide root-mean-square error (RMSE), especially for temperature. This evaluation phase of NARCCAP will inform later program elements concerning differentially weighting the models for use in producing robust regional probabilities of future climate change. [ABSTRACT FROM AUTHOR]

How to understand and reason about uncertainty in climate science is a topic that is receiving increasing attention in both the scientific and philosophical literature. This paper provides a perspective on exploring ways to understand, assess, and reason about uncertainty in climate science, including application to the Intergovernmental Panel on Climate Change (IPCC) assessment reports. Uncertainty associated with climate science and the science-policy interface presents unique challenges owing to the complexity of the climate system itself, the potential for adverse socioeconomic impacts of climate change, and the politicization of proposed policies to reduce societal vulnerability to climate change. The challenges to handling uncertainty at the science- policy interface are framed using the 'monster' metaphor, whereby attempts to tame the monster are described. An uncertainty lexicon is provided that describes the natures and levels of uncertainty and ways of representing and reasoning about uncertainty. Uncertainty of climate models is interpreted in the context of model inadequacy, uncertainty in model parameter values, and initial condition uncertainty. This article examines the challenges of building confidence in climate models and, in particular, the issue of confidence in simulations of the twenty-first-century climate. The treatment of uncertainty in the IPCC assessment reports is examined, including the IPCC Fourth Assessment Report conclusion regarding the attribution of climate change in the latter half of the twentieth century. Ideas for monster-taming strategies are discussed for institutions, individual scientists, and communities. [ABSTRACT FROM AUTHOR]

To better understand variability in weather and climate, it is vital to address past atmospheric circulation. This need requires meteorological information not just from the surface but also at upper levels. Current global upper-level datasets only reach back to the 1940s or 1950s and do not cover some important periods in the first half of the twentieth century. Extending the observational record is therefore considered important in order to analyze climate variability in the past and verify global climate models used to predict future climate change. Although earlier upper-air data from platforms such as radio-sondes, aircraft, pilot balloons, registering balloons, and kites are available from various sources, no systematic compilation and quality assessment of upper-level data prior to the International Geophysical Year (1957/58) has ever been performed. Here we present the Comprehensive Historical Upper-Air Network (CHUAN). It is a consistent global historical upper-air dataset that has been derived from heterogeneous data available from various sources as well as from newly digitized data. This paper describes the CHUAN dataset, the metadata, the quality control procedures, and the relationship to existing datasets. Some examples are given of its usefulness for analyzing weather and climate during the first half of the twentieth century. The CHUAN dataset comprises 3987 station records worldwide or about 16.4 million profiles (of which 12.6 million are before 1958 and 5.3 million, primarily from pilot balloons, are before 1948). A monthly mean version can be downloaded from the World Wide Web (). A supplement to this article is available online: DOI: [ABSTRACT FROM AUTHOR]

The article focuses on the detailed analysis of the Greenland Flow Distortion Experiment (GFDex) and its aircraft-based observations, on the coastal seas of Greenland and Iceland. The study investigates both the local and remote flow distortion effects and the occurrence of strong winds and intense mesoscale weather systems around the coastal seas. The observations gathered for the experiment include a reverse tip jet, polar mesoscale cyclone, and, barrier winds. An overview of the aircraft-based observations and the logistics of GFDex is offered, along with the case study papers conducted by other researchers. Meanwhile, the researchers of the experiment predicts that GFDex will contribute to wider understanding in the areas of meteorology and the atmospheric and climate system. INSETS: THE FACILITY FOR AIRBORNE ATMOSPHERIC MEASUREMENTS;ICING.

Trustworthy probabilistic projections of regional climate are essential for society to plan for future climate change, and yet, by the nonlinear nature of climate, finite computational models of climate are inherently deficient in their ability to simulate regional climatic variability with complete accuracy. How can we determine whether specific regional climate projections may be untrustworthy in the light of such generic deficiencies? A calibration method is proposed whose basis lies in the emerging notion of seamless prediction. Specifically, calibrations of ensemble-based climate change probabilities are derived from analyses of the statistical reliability of ensemble-based forecast probabilities on seasonal time scales. The method is demonstrated by calibrating probabilistic projections from the multimodel ensembles used in the Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC), based on reliability analyses from the seasonal forecast Development of a European Multimodel Ensemble System for Seasonal-to-Interannual Prediction (DEMETER) dataset. The focus in this paper is on climate change projections of regional precipitation, though the method is more general. [ABSTRACT FROM AUTHOR]

Efforts are being made to develop new paradigms for climate change adaptation policy at both the national and the international levels. However, progress in vulnerability and adaptation research has not been matched by advancement on practical policy initiatives. The complexity of the challenge to develop methods and means to support adaptation to climate change necessitates a diversity of approaches. This diversity is healthy, and yet it is possible to define some key characteristics and tools that can promote practical outcomes. In this paper, some methodologies that have proved successful are reviewed. These include a mapping of contextual circumstances, an appreciation for multiple perspectives, and the importance of a "boundary object" in forging strong interactions among project participants. Further, a toolkit of approaches for natural scientists is presented. This toolkit can be used to organize work in collaboration with stakeholders and other participants and can help overcome barriers to a meaningful contribution to the policy process. Fundamentally, this challenge will require approaches that are more grounded in meaning, narration, and reflection. [ABSTRACT FROM AUTHOR]

A 25-yr (1981–2005) time series of daily latent and sensible heat fluxes over the global ice-free oceans has been produced by synthesizing surface meteorology obtained from satellite remote sensing and atmospheric model reanalyses outputs. The project, named Objectively Analyzed Air-Sea Fluxes (OAFlux), was developed from an initial study of the Atlantic Ocean that demonstrated that such data synthesis improves daily flux estimates over the basin scale. This paper introduces the 25-yr heat flux analysis and documents variability of the global ocean heat flux fields on seasonal, interannual, decadal, and longer time scales suggested by the new dataset. The study showed that, among all the climate signals investigated, the most striking is a long-term increase in latent heat flux that dominates the data record. The globally averaged latent heat flux increased by roughly 9 W m-2 between the low in 1981 and the peak in 2002, which amounted to about a 10% increase in the mean value over the 25-yr period. Positive linear trends appeared on a global scale, and were most significant over the tropical Indian and western Pacific warm pool and the boundary current regions. The increase in latent heat flux was in concert with the rise of sea surface temperature, suggesting a response of the atmosphere to oceanic forcing. [ABSTRACT FROM AUTHOR]

The article discusses the comments to the published paper "Hurricanes and Global Warming— Potential Linkages and Consequences." The 2005 North Atlantic hurricane season experienced the largest number of named storms, hurricanes, and the only year with three category five storms on record including the most intense Wilma, Rita in the Gulf of Mexico, and the most costly storm Katrina. The relationships between tropical cyclones and global climate change are the subject of many science studies and researches. The science and social complexity of this together with the effects and causes in society are discussed.

The U.S. Historical Climate Network is a subset of surface weather observation stations selected from the National Weather Service cooperative station network. The criteria used to select these stations do not sufficiently address station exposure characteristics. In addition, the current metadata available for cooperative network stations generally do not describe site exposure characteristics in sufficient detail. This paper focuses on site exposures with respect to air temperature measurements. A total of 57 stations were photographically surveyed in eastern Colorado, comparing existing exposures to the standards endorsed by the World Meteorological Organization. The exposures of most sites surveyed, including U.S. Historical Climate Network sites, were observed to fall short of these standards. This raises a critical question about the use of many Historical Climate Network sites in the development of long-term climate records and the detection of climate trends. Some of these sites clearly have poor exposures and therefore should be considered for removal from the Historical Climate Network. Candidate replacement sites do exist and should be considered for addition into the network to replace the removed sites. Documentation as performed for this study should be conducted worldwide in order to determine the extent of spatially nonrepresentative exposures and possible temperature biases. [ABSTRACT FROM AUTHOR]

Improving the simulation of regional climate change is one of the high-priority areas of climate study because regional information is needed for climate change impact assessments. Such information is especially important for the region covered by the East Asian monsoon where there is high variability in both space and time. To this end, the Regional Climate Model Intercomparison Project (RMIP) for Asia has been established to evaluate and improve regional climate model (RCM) simulations of the monsoon climate. RMIP operates under joint support of the Asia–Pacific Network for Global Change Research (APN), the Global Change System for Analysis, Research and Training (START), the Chinese Academy of Sciences, and several projects of participating nations. The project currently involves 10 research groups from Australia, China, Japan, South Korea, and the United States, as well as scientists from India, Italy, Mongolia, North Korea, and Russia. RMIP has three simulation phases: March 1997–August 1998, which covers a full annual cycle and extremes in monsoon behavior; January 1989–December 1998, which examines simulated climatology; and a regional climate change scenario, involving nesting with a global model. This paper is a brief report of RMIP goals, implementation design, and some initial results from the first phase studies. [ABSTRACT FROM AUTHOR]

Comments on the report 'Detection and Attribution of Recent Climate Change: A Status Report.' Errors in the section 'Paleoclimate proxies'; Issues related to the erroneous conclusions of the paper; Use of the paleoclimatic data.

This paper comments on the article about the awareness of the risks of an abrupt change in climate related to human influences on the climate system. Specifically, it identifies the growth in economic damages associated with weather and climate events in the United States, as evidence of trends in extreme events, arguing the rising costs associated with weather volatility provide another derived indicator of the state of the climate system. The rising costs of disasters are important, and so too is human influence on climate. Research on the societal dimensions of disasters shows that over recent decades the impacts of disasters on society do show an increase, whether measured by economics.

An introduction to the journal is presented in which the editor discusses papers published within the issue about different extreme climate events.

The response of the various climatic processes to climate change can amplify (positive feedback) or damp (negative feedback) the initial temperature perturbation. An example of a positive feedback is the surface albedo feedback: when the surface temperature rises, part of the ice and snow melts, leading to an increase in the solar radiation absorbed by the surface and to an enhanced surface warming. Positive feedbacks can lead to instability. On Venus, for example, a positive feedback is thought to have evolved into a runaway greenhouse effect. However, positive feedbacks can exist in stable systems. This paper presents a simple representation of a positive feedback in both a stable and an unstable system. A simple experimental device based on a scale principle is introduced to illustrate the positive feedback and its stabilization or runaway regimes. Stabilization can be achieved whether the amplitude of the positive feedback declines (e.g., 'saturation' of the feedback) or remains constant. The device can also be used to illustrate the existence of tipping points, which are threshold values beyond which the amplification due to feedbacks or the stability of the system suddenly changes. The physical equations of the device are established in the framework of the feedback analysis. Key features to understand why a positive feedback does not necessarily lead to a runaway effect are described. The analogy between the different components of the device and those of the climate system is established. Finally, the contribution of individual feedbacks to the total climate response is addressed. [ABSTRACT FROM AUTHOR]