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'My fascination with meteorology and its related sciences stems from my love for remote sensing technology. This enthusiasm ignited in my youth when my father, a radiology doctor, showed me [...]

The article provides an overview of the use of Global Navigation Satellite System (GNSS) polarimetric radio occultation (PRO) measurements for weather prediction and applications. It summarizes a workshop that brought together participants from various countries to discuss the status and potential of PRO. The article highlights the benefits of PRO in improving weather forecasts and validating cloud microphysical processes. It also discusses ongoing experiments and the potential use of PRO observations in weather forecasting, climate modeling, and evaluating satellite precipitation products. The article also mentions the consideration of future constellations of small satellites for PRO measurements. [Extracted from the article]

'We are in the process of generating mid-twenty-first-century simulations of supercells and are hopeful to use our existing methods on those data, as well as continue to study additional perils, [...]

The Excessive Rainfall Outlook (ERO) from the Weather Prediction Center (WPC) has long played an important role in messaging potential flash flood events, but has seldom appeared in the literature. [...]

Satellite observations are vital for weather forecasts, climate monitoring, and environmental studies. In recent years, there has been a concerted effort to develop methods for quantifying and representing errors associated [...]

Flash floods are defined as a rapid rise of water into a normally dry area within minutes to hours of the causative event. Predicting flash floods driven by excessive rainfall [...]

Forecasts of weather hazards are complex, often containing multiple pieces of information about the nature of the threat. There is a seemingly endless amount of information forecasters can include in [...]

On 13 April 2022, the Russian warship Moskva was hit by two Ukrainian Neptune anti-ship missiles in the Black Sea, leading to its demise. Before launching an anti-ship missile, a target must first be detected and positioned, for example, by an accompanying radar system. However, when the missiles hit the Moskva she was well beyond the normal radar horizon of any ground-based radar system, making the ship undetectable under normal circumstances. Using meteorological reanalysis data, we show that at the time of the missile launch the prevailing weather conditions allowed a ground-based radar to detect targets far beyond the normal radar horizon through anomalous propagation conditions. During such conditions, the atmospheric index of refraction decreases rapidly with height, making electromagnetic radiation bend downward to, partly or fully, compensate the curvature of the Earth. The results show that atmospheric conditions must be considered carefully, even during warfare, as their impact on radar wave propagation can be considerable. [ABSTRACT FROM AUTHOR]

Cold fog forms via various thermodynamic, dynamic, and microphysical processes when the air temperature is less than 0°C. It occurs frequently during the cold season in the western United States yet is challenging to detect using standard observations and is very difficult to predict. The Cold Fog Amongst Complex Terrain (CFACT) project was conceived to investigate the life cycle of cold fog in mountain valleys. The overarching goals of the CFACT project are to 1) investigate the life cycle of cold-fog events over complex terrain with the latest observation technology, 2) improve microphysical parameterizations and visibility algorithms used in numerical weather prediction (NWP) models, and 3) develop data assimilation and analysis methods for current and next-generation (e.g., subkilometer scale) NWP models. The CFACT field campaign took place in Heber Valley, Utah, during January and February 2022, with support from NSF's Lower Atmospheric Observing Facilities (managed by NCAR's Earth Observing Laboratory), the University of Utah, and Ontario Technical University. A network of ground-based and aerial in situ instruments and remote sensing platforms were used to obtain comprehensive measurements of thermodynamic profiles, cloud microphysics, aerosol properties, and environmental dynamics. Nine intensive observation periods (IOPs) explored various mountainous weather and cold-fog conditions. Field observations, NWP forecasts, and large-eddy simulations provided unprecedented data sources to help understand the mechanisms associated with cold-fog weather and to identify and mitigate numerical model deficiencies in simulating winter weather over mountainous terrain. This article summarizes the CFACT field campaign, its observations, and challenges during the field campaign, including real-time fog prediction issues and future analysis. [ABSTRACT FROM AUTHOR]

Potential temperature and static energy are both useful quantities for understanding our atmosphere, yet static energy receives much less attention in weather science relative to climate science. Bridging this conceptual gap is important, as there is a pressing need for our communities to work together to understand and predict changing weather patterns in a warming world. Here we provide evidence for this gap in usage in American Meteorological Society journal publications and in introductory textbooks. We then describe key benefits of static energy for explaining basic concepts in atmospheric science. We encourage scientists and educators unfamiliar with static energy to familiarize themselves with the concept and consider incorporating it into their science and teaching. [ABSTRACT FROM AUTHOR]

The winds blowing on the ocean surface drive ocean currents. Heat and freshwater gained from or lost to the atmosphere create density differences in the ocean that also create currents. [...]

'We will continue to develop the Czech meteorological glossary. Since our ability to correctly identify equivalents of Czech terms in other languages is limited, we hope for international cooperation in [...]

Aerosol particles play a fundamental role in the Earth's climate by either interacting directly with solar radiation or indirectly acting as cloud seeds [cloud condensation nuclei (CCN) or ice nucleating [...]

BAMS spoke with Andrew N. Staniforth about his new book, Global Atmospheric and Oceanic Modelling: Fundamental Equations (Cambridge University Press). Before his retirement in 2014, Staniforth led the research and [...]

'When I was a kid, I was quite interested in severe weather phenomena, such as thunderstorms and typhoons, and curious about the underlying causes. In college, many of my classmates [...]

We developed five prototype convection-allowing model ensemble visualization products with the goal of improving depictions of the timing of winter weather hazards. These products are interactive, web-based plots visualizing probabilistic onset times and durations of intense snowfall rates, probabilities of heavy snow at rush hour, periods of heightened impacts, and mesoscale snowband probabilities. Prototypes were evaluated in three experimental groups coordinated by the Weather Prediction Center (WPC) Hydrometeorological Testbed (HMT), with a total of 53 National Weather Service (NWS) forecasters. Forecasters were asked to complete a simple forecast exercise for a snowfall event, with a control group using the Storm Prediction Center's (SPC) High-Resolution Ensemble Forecast (HREF) system viewer, and an experimental group using both the HREF viewer and the five experimental graphics. Forecast accuracy was similar between the groups, but the experimental group exhibited smaller mean absolute error for snowfall duration forecasts. A series of Likert-scale questions saw participants respond favorably to all of the products and indicated that they would use them in operational forecasts and in communicating information to core partners. Forecasters also felt that the new products improved their comprehension of ensemble spread and reduced the time required to complete the forecasting exercise. Follow-up plenary discussions reiterated that there is a high demand for ensemble products of this type, though a number of potential improvements, such as greater customizability, were suggested. Ultimately, we demonstrated that social science methods can be effectively employed in the atmospheric sciences to yield improved visualization products. [ABSTRACT FROM AUTHOR]

We applied social science research principles to develop a suite of probabilistic winter weather forecasting visualizations for High-Resolution Ensemble Forecast (HREF) system output. This was achieved through an iterative, dialogic process with U.S. National Weather Service (NWS) forecasters to design nine new web-based, interactive products aimed toward improving visualizations of winter weather event magnitudes, characteristics, and timing. These products were influenced by feedback from a preliminary focus group, which emphasized the importance of product credibility, contextualization, and scalability. In a follow-up discussion, winter weather forecasting experts found the event timing products to have the greatest utility due to their association with impact-decision support services (IDSS). Furthermore, forecasters assessed snowfall rates as the most impactful variable rather than snowfall totals and radar reflectivity. The timing products include plots of probabilistic snowfall onset time and duration, rush hour intersection probabilities, and a combination meteogram. The onset and duration plots visualize the ensemble-average onset time and duration of a specified snowfall rate, as demonstrated in previous works, but with the addition of uncertainty information by visualizing the earliest, most likely, and latest potential onset times as well as the shortest, most likely, and longest potential durations. The rush hour product visualizes the probability of exceeding a specified snowfall rate during local commutes, and the combination meteogram allows rapid identification of high-impact periods by encoding probabilities of precipitation, precipitation-type probabilities, and average rates into one graphical tool. Examples of these interactive products are maintained on our companion website: www.visweather.com/bams2023. [ABSTRACT FROM AUTHOR]

It is common when speaking colloquially to describe climate as the average weather, which implies weather is the driver and climatic averages are a passive by-product of it, but it is useful to reframe this toward weather being the "expression" of climate. That is, a region's climate defines the range of weather it might experience (including the extent and frequency of extremes). In this framing, weather is driven by a region's climate. A changing climate then, necessarily, is experienced as a change in local weather events--often most visibly through changes in the extent or frequency of extreme weather. [ABSTRACT FROM AUTHOR]

Post-wildfire debris flows (PFDF) threaten life and property in western North America. They are triggered by short-duration, high-intensity rainfall. Following a wildfire, rainfall thresholds are developed that, if exceeded, indicate high likelihood of a PFDF. Existing weather forecast products allow forecasters to identify favorable atmospheric conditions for rainfall intensities that may exceed established thresholds at lead times needed for decision-making (e.g., =24 h). However, at these lead times, considerable uncertainty exists regarding rainfall intensity and whether the high-intensity rainfall will intersect the burn area. The approach of messaging on potential hazards given favorable conditions is generally effective in avoiding unanticipated PFDF impacts, but may lead to "messaging fatigue" if favorable triggering conditions are forecast numerous times, yet no PFDF occurs (i.e., false alarm). Forecasters and emergency managers need additional tools that increase their confidence regarding occurrence of short-duration, high-intensity rainfall as well as tools that tie rainfall forecasts to potential PFDF outcomes. We present a concept for probabilistic tools that evaluate PFDF hazards by coupling a high-resolution (1-km), large (100-member) ensemble 24-h precipitation forecast at 5-min resolution with PFDF likelihood and volume models. The observed 15-min maximum rainfall intensities are captured within the ensemble spread, though in highest ~10% of members. We visualize the model output in several ways to demonstrate most likely and most extreme outcomes and to characterize uncertainty. Our experiment highlights the benefits and limitations of this approach, and provides an initial step toward further developing situational awareness and impact-based decision-support tools for forecasting PFDF hazards. [ABSTRACT FROM AUTHOR]

SIGNIFICANCE STATEMENT: During the COVID-19 pandemic in 2020 and 2021, numerous peer-reviewed scientific journal articles were published quickly to understand how weather conditions might influence the spread of COVID-19. Unfortunately, many of these articles contained weaknesses or flaws that affected the reliability and accuracy of their results. One flaw in particular meant that weather on the day when the COVID-19 case was reported was used rather than weather on the day the infection occurred. Although science can correct itself through various means, we found that these flaws were usually not identified nor corrected. Our study hopes to shed light on the problems with these articles and offer recommendations for publishing such research so that these problems are not repeated during future pandemics. Numerous studies were published quickly in 2020 and 2021 to understand the effect of weather variables on the spread of COVID-19. We examined 289 peer-reviewed empirical publications, focusing on their characteristics and a critical analysis of their quality. Of the 289 publications, 280 (97%) reported an association between one or more weather variables and the transmission of COVID-19. Of those 289 publications, 109 publications (38%) did not consider any time lag between suspected infections and reporting of the COVID-19 cases, meaning that they examined the weather on the day when the COVID-19 case was reported, rather than the day when the infection occurred. The publications used data from as few as 7 days, with an average of 123 days. Most of these data were collected early in the pandemic when the temperatures were rising as the seasons transitioned from winter to summer in the Northern Hemisphere, making it difficult to determine the subtle effects of the weather on spread. Furthermore, the average time between submission and acceptance was 85 days, but the 10 most-cited publications—all in Science of the Total Environment—were accepted within 10 days of submission, with three accepted on the submission date. Twenty-four review articles were published in 2020 and 2021, with few providing critical reflection on strengths and weaknesses of the literature. Our analysis revealed errors in the publications that were not identified or rectified by corrigenda, comment–reply exchanges, or retractions. This article concludes with recommendations on publishing during future pandemics, as well as best practices for publishing research on weather and COVID-19 transmission. [ABSTRACT FROM AUTHOR]

Testbeds have become integral to advancing the transfer of knowledge and capabilities from research to operational weather forecasting in many parts of the world. The first high-impact weather testbed in tropical Africa was recently carried out through the African Science for Weather Information and Forecasting Techniques (SWIFT) program, with participation from researchers and forecasters from Senegal, Ghana, Nigeria, Kenya, the United Kingdom, and international and pan-African organizations. The testbed aims were to trial new forecasting and nowcasting products with operational forecasters, to inform future research, and to act as a template for future testbeds in the tropics. The African SWIFT testbed integrated users and researchers throughout the process to facilitate development of impact-based forecasting methods and new research ideas driven both by operations and user input. The new products are primarily satellite-based nowcasting systems and ensemble forecasts at global and regional convection-permitting scales. Neither of these was used operationally in the participating African countries prior to the testbed. The testbed received constructive, positive feedback via intense user interaction including fishery, agriculture, aviation, and electricity sectors. After the testbed, a final set of recommended standard operating procedures for satellite-based nowcasting in tropical Africa have been produced. The testbed brought the attention of funding agencies and organizational directors to the immediate benefit of improved forecasts. Delivering the testbed strengthened the partnership between each country's participating university and weather forecasting agency and internationally, which is key to ensuring the longevity of the testbed outcomes. [ABSTRACT FROM AUTHOR]

The 2023 NOAA Hazardous Weather Testbed Spring Forecasting Experiment What: Within a hybrid framework of in-person and virtual participation, over 125 forecasters and researchers engaged in real-time, experimental severe weather forecasting activities and model evaluations, which included 1) the Rapid Refresh Forecast System, 2) the Model for Prediction Across Scales, 3) the Warn-on-Forecast System, and 4) innovative postprocessing strategies. When: 1 May-2 June 2023 Where: Norman, Oklahoma, and Online. [ABSTRACT FROM AUTHOR]

BAMS spoke with Steve LaDochy and Mike Witiw about their book, Fire and Rain: California's Changing Weather and Climate. LaDochy is professor emeritus of geography, geology, and environment at California [...]

The Council of the American Meteorological Society invites members of the AMS to submit nominations for the Society Awards, Lecturers, Named Symposia, Fellows, Honorary members, and nominees for elective Officers [...]

Nearly half of California's annual precipitation comes from a handful of atmospheric river (AR) events. These ARs are vital for replenishing water supplies but often are also responsible for flooding. [...]

Neil Jacobs holds up a peacock bass caught on one of his handmade tarpon flies this spring in a canal next to the National Hurricane Center in Miami, Florida. 'When [...]

The 2021 northwest Pacific marine heatwave was favored by the atmospheric and oceanic conditions; changes in the mean climate due to anthropogenic warming made the event 43 times more likely. [ABSTRACT FROM AUTHOR]

The North American monsoon generates heavy rainfall across the southwestern United States between July and September, delivering beneficial moisture to the region and creating hazards that affect public and personal safety. The monsoon thus has the rapt attention of the public and science community, providing an opportunity to improve weather and climate literacy and public engagement in science. Engaging the public to forecast weather and climate phenomenon through contests offers an innovative way to reach diverse audiences and increase weather and climate literacy. We describe a "Monsoon Fantasy Forecasting" game conducted in 2021 with approximately 300 participants. The game that engaged the public in the forecasting of monthly rainfall at cities in Arizona, New Mexico, and Texas. We report on the game's interactive design, results, and feedback. We show that the game attracted a diverse audience who was not the typical weather and climate enthusiast, and we provide suggestive results that the game may have influenced the players information-seeking behaviors. We argue that activities that provoke people to observe and think routinely about climate can help educate and build awareness about weather and climate issues. [ABSTRACT FROM AUTHOR]

BC aerosols from the fire emissions absorb solar radiation and heat the air, which enhances the updraft over the MC Westerly anomaly weakens the trade wind and the tropical east-west [...]

The Canadian Rockies are a triple-continental divide, whose high mountains are drained by major snow-fed and rain-fed rivers flowing to the Pacific, Atlantic, and Arctic Oceans. The objective of the April–June 2019 Storms and Precipitation Across the continental Divide Experiment (SPADE) was to determine the atmospheric processes producing precipitation on the eastern and western sides of the Canadian Rockies during springtime, a period when upslope events of variable phase dominate precipitation on the eastern slopes. To do so, three observing sites across the divide were instrumented with advanced meteorological sensors. During the 13 observed events, the western side recorded only 25% of the eastern side's precipitation accumulation, rainfall occurred rather than snowfall, and skies were mainly clear. Moisture sources and amounts varied markedly between events. An atmospheric river landfall in California led to moisture flowing persistently northward and producing the longest duration of precipitation on both sides of the divide. Moisture from the continental interior always produced precipitation on the eastern side but only in specific conditions on the western side. Mainly slow-falling ice crystals, sometimes rimed, formed at higher elevations on the eastern side (>3 km MSL), were lifted, and subsequently drifted westward over the divide during nonconvective storms to produce rain at the surface on the western side. Overall, precipitation generally crossed the divide in the Canadian Rockies during specific spring-storm atmospheric conditions although amounts at the surface varied with elevation, condensate type, and local and large-scale flow fields. [ABSTRACT FROM AUTHOR]

The Arctic environment is changing, increasing the vulnerability of local communities and ecosystems, and impacting its socio-economic landscape. In this context, weather and climate prediction systems can be powerful tools to support strategic planning and decision-making at different time horizons. This article presents several success stories from the H2020 project APPLICATE on how to advance Arctic weather and seasonal climate prediction, synthesizing the key lessons learned throughout the project and providing recommendations for future model and forecast system development. [ABSTRACT FROM AUTHOR]

'I encourage students to talk to as many folks as possible. Start to develop your network early by having some informal conversations with people within your university. There are also [...]

Interested in contributing to the AMS Weather Band website or online community? For more on how to submit features, photos/videos, and interviews related to weather, water, and climate, visit the [...]

We introduce the Dutch East India Company "day registers" as one of the world's longest known pre-nineteenth-century corporate chronicles (1652–1791) containing near-continuous, systematic, noninstrumental daily weather information for Cape Town, South Africa. This transcript provides the longest-known continuous seventeenth- to eighteenth-century daily weather record for Africa and the Southern Hemisphere. An 18-yr (1773–91) climate chronology from this record is presented, thus providing unique insight to the late-eighteenth-century climate of Cape Town. Extraction of daily weather information for basic statistical analysis includes precipitation, wind, sky conditions, and accounts of storms, drought, and floods. From this, we provide monthly and annual number of rain days, a rain index (relative rainfall amount), hot and cold days, and occurrence of storm-strength winds. Results show extreme weather and climate variability in Cape Town during the mid- to late 1780s. [ABSTRACT FROM AUTHOR]

The High-Latitude Measurement of Snowfall (HiLaMS) campaign explored variability in snowfall properties and processes at meteorologically distinct field sites located in Haukeliseter, Norway, and Kiruna, Sweden, during the winters of 2016/17 and 2017/18, respectively. Campaign activities were founded upon the sensitivities of a low-cost, core instrumentation suite consisting of Micro Rain Radar, Precipitation Imaging Package, and Multi-Angle Snow Camera. These instruments are highly portable to remote field sites and, considered together, provide a unique and complementary set of snowfall observations including snowflake habit, particle size distributions, fall speeds, surface snowfall accumulations, and vertical profiles of radar moments and snow water content. These snow-specific parameters, used in combination with existing observations from the field sites such as snow gauge accumulations and ambient weather conditions, allow for advanced studies of snowfall processes. HiLaMS observations were used to 1) successfully develop a combined radar and in situ microphysical property retrieval scheme to estimate both surface snowfall accumulation and the vertical profile of snow water content, 2) identify the predominant snowfall regimes at Haukeliseter and Kiruna and characterize associated macrophysical and microphysical properties, snowfall production, and meteorological conditions, and 3) identify biases in the HARMONIE-AROME numerical weather prediction model for forecasts of snowfall accumulations and vertical profiles of snow water content for the distinct snowfall regimes observed at the mountainous Haukeliseter site. HiLaMS activities and results suggest value in the deployment of this enhanced snow observing instrumentation suite to new and diverse high-latitude locations that may be underrepresented in climate and weather process studies. [ABSTRACT FROM AUTHOR]

Great advances in meteorological science were made in the late eighteenth century. In particular, meteorological instruments were carried on ships and the first systematic meteorological readings over the oceans were made. One of these collections of instrumental meteorological readings was carried out by the Malaspina expedition (1789-94), organized by the Spanish Crown to study its vast possessions around the world. We have recovered meteorological variables such as air temperature (maximum and minimum), atmospheric pressure (maximum and minimum), wind (intensity and direction), and appearance (state of the sky) from the documentation generated by the explorers during the journey. In total, nearly 13,000 instrumental data have been digitized and rescued from this maritime expedition. The comparison of daily temperature and pressure observations with reanalysis and weather stations data shows a good overall agreement. Moreover, apparent discrepancies during several anchored periods have allowed for testing the consistency and quality of these early instrumental marine weather readings. [ABSTRACT FROM AUTHOR]

The National Hurricane Center (NHC)'s forecast cone is popular and simple. It's by far the most viewed forecast-communication graphic. Hurricane Ian showed us, however, that the cone's simplicity is also [...]

S. Trivikrama Rao-retired director of the Atmospheric Modeling and Analysis Division of the B EPA and an AMS CCM, Fellow, and winner of the Award for Outstanding Contributions to Applied [...]

One of the most intense air mass transformations on Earth happens when cold air flows from frozen surfaces to much warmer open water in cold-air outbreaks (CAOs), a process captured beautifully in satellite imagery. Despite the ubiquity of the CAO cloud regime over high-latitude oceans, we have a rather poor understanding of its properties, its role in energy and water cycles, and its treatment in weather and climate models. The Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) was conducted to better understand this regime and its representation in models. COMBLE aimed to examine the relations between surface fluxes, boundary layer structure, aerosol, cloud, and precipitation properties, and mesoscale circulations in marine CAOs. Processes affecting these properties largely fall in a range of scales where boundary layer processes, convection, and precipitation are tightly coupled, which makes accurate representation of the CAO cloud regime in numerical weather prediction and global climate models most challenging. COMBLE deployed an Atmospheric Radiation Measurement Mobile Facility at a coastal site in northern Scandinavia (69°N), with additional instruments on Bear Island (75°N), from December 2019 to May 2020. CAO conditions were experienced 19% (21%) of the time at the main site (on Bear Island). A comprehensive suite of continuous in situ and remote sensing observations of atmospheric conditions, clouds, precipitation, and aerosol were collected. Because of the clouds' well-defined origin, their shallow depth, and the broad range of observed temperature and aerosol concentrations, the COMBLE dataset provides a powerful modeling testbed for improving the representation of mixed-phase cloud processes in large-eddy simulations and large-scale models. [ABSTRACT FROM AUTHOR]

'After completing my national service, I continued to pursue opportunities for professional development, including attending conferences and workshops on topics such as climate change, atmospheric physics, and weather forecasting. These [...]

Alan Sealls, the Gulf Coast's chief meteorologist at WPMI NBC 15, is retiring from television in January 2024. Sealls has been delivering weather forecasts in the Mobile, Alabama, market as [...]

--JINGFANG FAN of Beijing Normal University and the Potsdam Institute for Climate Impact Research, on teleconnections, which he describes as 'how climate events in one part of the world can [...]

Floods resulting from extreme rainstorms can be very costly and deadly; thus, understanding such extreme events is very important. Knowledge of weather and climate extremes is also important in determining [...]

Reading the Glass: A Captain's View of Weather, Water, and Life on Ships by Elliot Rappaport (Dutton Publishing) Elliot Rappaport, a professional captain of traditional sailing ships, has spent three [...]

National Center for Atmospheric Research (NCAR) scientist Richard Rotunno has been elected as a new member of the National Academy of Sciences, a distinguished honor given to those who have [...]

Global urban population is projected to double by 2050. This rapid urbanization is the driver of economic growth but has environmental challenges. To that end, there is an urgent need to understand, simulate, and disseminate information about extreme events, routine city operations, and long-term planning decisions. This paper describes an effort underway in India involving an interdisciplinary community of meteorology, hydrology, air quality, and computer science from national and international institutes. The urban collaboratory is a system of systems for simulating weather, hydrology, air quality, health, energy, transport, and economy and its interactions. Study and prediction of urban events involve multiscale observations and cross-sector models, heterogeneous data management, and enormous computing power. The consortia program (NSM_Urban) is part of "weather ready cities," under the aegis of India's National Supercomputing Mission. The ecosystem "Urban Environment Science to Society" (UES2S) builds on the integrated cyberinfrastructure with a science gateway for community research and end-user service with modeling and interoperable data. The collaboratory has urban computing, stakeholder participation, and a coordinated means to scaffold projects and ideas into operational tools. It discusses the design and the utilization of high-performance computing (HPC) as a science cloud platform for bridging urban environment and data science, participatory stakeholder applications, and decision-making. The system currently integrates models for high-impact urban weather, flooding, air quality, and simulating street- and building-scale wind flow and dispersion. The program with the work underway is ripe for interfacing with regional and international partners, and this paper provides an avenue toward that end. [ABSTRACT FROM AUTHOR]