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Between 2014 and 2018, the National Oceanic and Atmospheric Administration conducted the NOAA Satellite Observing System Architecture (NSOSA) study to plan for the next generation of operational environmental satellites. The study generated some important questions that could be addressed by observing system simulation experiments (OSSEs). This paper describes a series of OSSEs in which benefits to numerical weather prediction from existing observing systems are combined with enhancements from potential future capabilities. Assessments include the relative value of the quantity of different types of thermodynamic soundings for global numerical weather applications. We compare the relative impact of several sounding configuration scenarios for infrared (IR), microwave (MW), and radio occultation (RO) observing capabilities. The main results are 1) increasing the revisit rate for satellite radiance soundings produces the largest benefits but at a significant cost by requiring an increase in the number of polar-orbiting satellites from 2 to 12; 2) a large positive impact is found when the number of RO soundings per day is increased well beyond current values and other observations are held at current levels of performance; 3) RO can be used as a mitigation strategy for lower MW/IR sounding revisit rates, particularly in the tropics; and 4) smaller benefits result from increasing the horizontal resolution along the track of the satellites of MW/IR satellite radiances. Furthermore, disaggregating IR and MW instruments into six evenly distributed sun-synchronous orbits is slightly more beneficial than when the same instruments are combined and collocated on three separate orbits. SIGNIFICANCE STATEMENT: The results of this paper are significant because they inform decision-makers about the future configuration of the NOAA's environmental satellite constellation, which serves millions of diverse users. [ABSTRACT FROM AUTHOR]

The Madden–Julian oscillation (MJO) identified by Madden and Julian in the early 1970s has been well recognized as the most prominent intraseasonal signal in the tropics. Its discovery and its relationship with other weather phenomena such as tropical cyclones (TCs) are among the most significant advancements in modern meteorology with broad and far-reaching impacts. The original study by Madden and Julian used radiosonde data on Canton Island, and their spectral analysis revealed the signal of a 40–50-day oscillation. It has come to our attention that an earlier study by Xie et al. published in a Chinese journal documented an oscillatory signal of a 45-day period using radiosonde data from several stations between 70° and 125°E in the tropics. The 40–50-day signal found by Xie et al. is strikingly evident without any filtering. Xie et al. identified that occurrences of TCs are correlated with the 40–50-day variation of low-level westerlies at these stations. The original figures in Xie et al.'s article were hand drawn. Their results are verified using data from a longer period of 1958–70. The 40–50-day oscillation in the monsoon westerlies and its relationship with the occurrence of TCs are confirmed and further expanded upon. This study serves the purpose of bringing recognition to the community of the identification of a 40–50-day signal published in Chinese in 1963 and the discovery of the correlation between MJO phases and TC genesis three decades earlier than studies on this subject published outside China. [ABSTRACT FROM AUTHOR]

This paper provides an introduction to a new tool that is designed to provide operationally useful vulnerability information to National Weather Service (NWS) Weather Forecasting Offices (WFOs). The Brief Vulnerability Overview Tool (BVOT) is a shapefile containing local known, spatially specific, and weather-hazard-related vulnerabilities in a format that is easily integrated into the existing forecasting, warning, and decision support responsibilities and tasks of NWS WFO meteorologists. The methods for gathering vulnerability data and then building a BVOT for a WFO leverage and strengthen the relationships that NWS WFOs already have with their local emergency managers (EMs) and core partners to work together to identify operationally useful, local vulnerability knowledge. The BVOT is populated with discrete, known vulnerabilities to provide NWS meteorologists spatial situational awareness of those people, places, and things of greatest concern to their core partners. Crucially, the BVOT is a subsample of all potential vulnerabilities; its primary purpose is to make meteorologists aware of those weather-hazard-specific vulnerabilities that, as we posed to them, "keep them awake at night." Here, we describe the development of the BVOT as a social science–informed operational tool; how the BVOT methods have evolved and how it can be integrated into the culture of the NWS as a tool for building and maintaining relationships with partners; and how the BVOT is designed to be used and its impact on operational decision-making as observed in NOAA's Hazardous Weather Testbed. SIGNIFICANCE STATEMENT: Operational meteorologists in the National Weather Service often rely on everyday knowledge of vulnerabilities to shape their messaging to communities threatened by hazardous weather. This study seeks to test methods that will permit meteorologists to work with local communities and emergency managers to collect knowledge about local vulnerabilities so that they can be formally shared and integrated into everyday operations. The results of this research provide an illustrative pathway demonstrating how social science–informed research can be used to improve meteorological operations. Future work should investigate how other findings from social science can be translated into real, operational impacts. [ABSTRACT FROM AUTHOR]

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]

Artificial intelligence (AI) can be used to improve performance across a wide range of Earth system prediction tasks. As with any application of AI, it is important for AI to be developed in an ethical and responsible manner to minimize bias and other effects. In this work, we extend our previous work demonstrating how AI can go wrong with weather and climate applications by presenting a categorization of bias for AI in the Earth sciences. This categorization can assist AI developers to identify potential biases that can affect their model throughout the AI development life cycle. We highlight examples from a variety of Earth system prediction tasks of each category of bias. SIGNIFICANCE STATEMENT: As artificial intelligence (AI) grows in popularity, its methods are being applied to a wide range of Earth system prediction tasks. Although AI can facilitate more accurate prediction at many tasks, it is not without potential pitfalls, especially if the developers are not as familiar with its potential drawbacks. In this paper, we provide a classification system for the types of bias that one is likely to see in applying AI to Earth sciences. Our classification system will assist current and future AI developers to recognize where their AI system or data are biased so they can take steps to alleviate this bias. [ABSTRACT FROM AUTHOR]

The Yarlung Zsangbo Grand Canyon (YGC) is an important pathway for water vapor transport from southern Asia to the Tibetan Plateau (TP). This area exhibits one of the highest frequencies of convective activity in China, and precipitation often induces natural disasters in local communities, which can dramatically affect their livelihoods. In addition, the produced precipitation gives rise to vast glaciers and large rivers around the YGC. In 2018, the Second Tibetan Plateau Scientific Expedition and Research Program tasked a research team to conduct an "investigation of the precipitation process in the water vapor channel of the Yarlung Zsangbo Grand Canyon" (INVC) in the southeastern TP. This team subsequently established a comprehensive observation system of land–air interaction, water vapor, clouds, and rainfall activity in the YGC. This paper introduces the developed observation system and summarizes the preliminary results obtained during the first two years of the project. Using this INVC observation network, herein, we focus on the development of rainfall events on the southeastern TP. This project also helps to monitor geohazards in the key area of the Sichuan–Tibet railway, which traverses the northern YGC. The observation datasets will benefit future research on mountain meteorology. [ABSTRACT FROM AUTHOR]

The article discusses the process of evaluating manuscripts submitted to the American Meteorological Society. Manuscripts must meet the formatting standards prior to peer review. If it does not meet the standards, instruction are sent to the authors with a request to revise and resubmit the paper. After meeting the qualifications, papers undergo the peer-review process, wherein they are subjected to the scrutiny of experts in field to ensure high quality. Among the standards evaluated in the peer review process include originality, absence of significant errors in analysis and interpretation and scientific objectivity. After the review, the papers are returned to the editors for acceptance or rejection and one accepted, they go through copying, technical editing and publishing.

The article presents updates related to climatology and weather studies in the U.S. Research reveals the significance of using the cloud-resolving model simulations in forecasting the dangers of lightning. Meanwhile, several climate scientists are searching for the best method in estimating the peak surface winds of a hurricane. Moreover, it also looks on the effectiveness of the latest multiple-Doppler tornado detection in determining the upcoming tornadoes.

The article offers news briefs in the U.S. Australian radiosondes monitor a large area of the Southern Hemisphere have experienced so many changes that unadjusted temperature trends of the bulk atmosphere computed from their soundings are suspect. Quantification of carbon exchange in forest ecosystems needs a unique sampling strategy. Strong vertical wind shear usually will weaken even mature hurricanes.

The article discusses the research which emphasizes a potential break in the tornado warning dissemination system utilized in the U.S. in 2008. The researchers measured the fatality rates caused by tornadoes that occurred between sunset and sunrise from 1880-2007 to investigate the human vulnerability to nocturnal tornadoes. Spatial analyses show that vulnerability of the nocturnal tornado is not distributed uniformly across the U.S., in which the South region is at much greater risk for nocturnal events.

The article reports developments related to meteorology. A study which examines the total lightning signatures of thunderstorm intensity over North Texas provides insight into the processes responsible for severe weather damaging straight-line winds and tornadoes. Changes in storm intensity can be predicted through the convective structure of the eyewall of a mature hurricane. Bayesian statistical models were developed for number of tropical cyclones using data from 1966-2006.

The article offers world news briefs related to meteorology. The subrotors and the internal structure of the parent rotor lifts off the surface and breakdown along the edge of the lee wave through Kelvin-Helmholtz like instability. Greenland extends one quarter of the distance between the North Pole and Equator averaging 1.5 kilometer (km) in height and reaching skyward more than 3.5 km. The Global Precipitation Climatology Project (GPCP) offers the opportunity to analyze climate variation.

The article assesses the usefulness of synthetic vortex insertion prior to the extratropical transition of hurricanes. Significant improvements in the wind and precipitation patterns within the storm at landfall were observed in the atmospheric model with vortex insertion employed in the initial conditions. The numerical hindcasts employing the technique resolved a particular forecast dilemma involving interaction of Hurricane Michael with a preexisting area of low pressure to its north. Operational forecast models at the time had incorrectly developed the northern low at the expense of the hurricane, while the opposite occurred in reality and in the numerical simulations run in hindcast mode.

The article offers news briefs related to climatology. A cold tongue which is a narrow band of cool sea surface temperature (SST) is one of the salient features in the equatorial Pacific Ocean. Two of the factors that contributed to the weather-forecasting errors increase in time are the amplification uncertainties of nonlinearities in the initial state of the atmosphere and the model deficiencies leading the model to predict the wrong rate of change for even the most certain initial conditions. INSETS: DUDE, WE'RE, LIKE, PROTESTING;PLEASED TO ZAP YOU.

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".

The polar-orbiting meteorological satellites operating in an observing system composed of early morning (EM), midmorning (AM), and afternoon (PM) orbits are extremely important to global numerical weather prediction (NWP). Following the proposal of World Meteorological Organization (WMO), the China Meteorological Administration (CMA) launched Fengyun-3E (FY-3E), the world's first EM-orbit meteorological satellite for civil use, on 5 July 2021. With 11 scientific instruments on board, FY-3E is capable of providing atmospheric sounding, low-light imaging, sea surface wind detection, and space weather monitoring. Six months after launch, we have finished the postlaunch test for all the payloads. This paper presents the FY-3E data obtained during the 6-month test period, their performance, and key geophysical products driven ready for downstream applications. Experiments have been conducted to better disseminate the sounding data within the 6-h NWP assimilation window. Further efforts have been made to benefit data application for severe weather monitoring, diurnal cycle of Earth data, quasi-continuous sun monitoring for space weather, and climate research. [ABSTRACT FROM AUTHOR]

The global positioning system dropwindsonde has provided thousands of high-resolution kinematic and thermodynamic soundings in and around tropical cyclones (TCs) since 1997. These data have revolutionized the understanding of TC structure, improved forecasts, and validated observations from remote sensing platforms. About 400 peer-reviewed studies on TCs using these data have been published to date. This paper reviews the history of dropwindsonde observations, changes to dropwindsonde technology since it was first used in TCs in 1982, and how the data have improved forecasting and changed our understanding of TCs. [ABSTRACT FROM AUTHOR]

Numerical weather prediction models operate on grid spacings of a few kilometers, where deep convection begins to become resolvable. Around this scale, the emergence of coherent structures in the planetary boundary layer, often hypothesized to be caused by cold pools, forces the transition from shallow to deep convection. Yet, the kilometer-scale range is typically not resolved by standard surface operational measurement networks. The measurement campaign Field Experiment on Submesoscale Spatio-Temporal Variability in Lindenberg (FESSTVaL) aimed at addressing this gap by observing atmospheric variability at the hectometer-to-kilometer scale, with a particular emphasis on cold pools, wind gusts, and coherent patterns in the planetary boundary layer during summer. A unique feature was the distribution of 150 self-developed and low-cost instruments. More specifically, FESSTVaL included dense networks of 80 autonomous cold pool loggers, 19 weather stations, and 83 soil sensor systems, all installed in a rural region of 15-km radius in eastern Germany, as well as self-developed weather stations handed out to citizens. Boundary layer and upper-air observations were provided by eight Doppler lidars and four microwave radiometers distributed at three supersites; water vapor and temperature were also measured by advanced lidar systems and an infrared spectrometer; and rain was observed by a X-band radar. An uncrewed aircraft, multicopters, and a small radiometer network carried out additional measurements during a 4-week period. In this paper, we present FESSTVaL's measurement strategy and show first observational results including unprecedented highly resolved spatiotemporal cold-pool structures, both in the horizontal as well as in the vertical dimension, associated with overpassing convective systems. [ABSTRACT FROM AUTHOR]

The modeling of weather and climate has been a success story. The skill of forecasts continues to improve and model biases continue to decrease. Combining the output of multiple models has further improved forecast skill and reduced biases. But are we exploiting the full capacity of state-of-the-art models in making forecasts and projections? Supermodeling is a recent step forward in the multimodel ensemble approach. Instead of combining model output after the simulations are completed, in a supermodel individual models exchange state information as they run, influencing each other's behavior. By learning the optimal parameters that determine how models influence each other based on past observations, model errors are reduced at an early stage before they propagate into larger scales and affect other regions and variables. The models synchronize on a common solution that through learning remains closer to the observed evolution. Effectively a new dynamical system has been created, a supermodel, that optimally combines the strengths of the constituent models. The supermodel approach has the potential to rapidly improve current state-of-the-art weather forecasts and climate predictions. In this paper we introduce supermodeling, demonstrate its potential in examples of various complexity, and discuss learning strategies. We conclude with a discussion of remaining challenges for a successful application of supermodeling in the context of state-of-the-art models. The supermodeling approach is not limited to the modeling of weather and climate, but can be applied to improve the prediction capabilities of any complex system, for which a set of different models exists. [ABSTRACT FROM AUTHOR]

A unique, high-resolution, hydroclimate reanalysis, 40-plus-year (October 1979–September 2021), 4 km (named as CONUS404), has been created using the Weather Research and Forecasting Model by dynamically downscaling of the fifth-generation European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis of the global climate dataset (ERA5) over the conterminous United States. The paper describes the approach for generating the dataset, provides an initial evaluation, including biases, and indicates how interested users can access the data. The motivation for creating this National Center for Atmospheric Research (NCAR)–U.S. Geological Survey (USGS) collaborative dataset is to provide research and end-user communities with a high-resolution, self-consistent, long-term, continental-scale hydroclimate dataset appropriate for forcing hydrological models and conducting hydroclimate scientific analyses over the conterminous United States. The data are archived and accessible on the USGS Black Pearl tape system and on the NCAR supercomputer Campaign storage system. [ABSTRACT FROM AUTHOR]

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.

The article presents a study which examines the effect of synoptic-scale forcing on the stratospheric sudden warnings (SSWs) in 2006 in the U.S. The researchers used the meteorological fields from Goddard Earth Observing System (GEOS)-4 analyses in determining such effects. The study found out that stratospheric polar displaced off the pole due to earlier minor warming events. The researchers also suggest that there is a need for further investigation to determine the kind of fraction of major SSWs are initiated.

The article focuses on contribution of Yoshikazu Sasaki to the development of variational method of data assimilation. It highlights Sasaki's training in physics and the application of calculus of variations to relativity and quantum mechanics. Moreover, the author argues on fundamental difference of variational methods introduced by Sasaki as well as the meteorological community introduced by Arnt Eliassen to the stochastic approach to data assimilation. Furthermore, a study on the link between tropical cyclones and fronts is also discussed.

Heat is one of the most serious hazards in the world as it affects human health and is extremely dangerous to vulnerable populations such as the elderly, people with preexisting cardiovascular or respiratory conditions, and even healthy people with prolonged sunlight exposure during heat waves. As the globe has warmed over the past several decades, extreme heat has become more frequent and intense than ever before, and Africa, especially the Sahel in West Africa, is one of the regions of the world where heat is a major public health concern exacerbated by livelihood activities during the heat season. Yet, there is a major gap in monitoring and forecasting heat waves in Africa. This paper describes NOAA's role in enabling heat–health early warning in Africa, working with meteorological services and health professionals. Emphasis is on real-time heat wave forecasting at week 2, including the postprocessing of the NCEP model outputs, and providing the information to the meteorological services in Africa to serve as guidance in national heat wave forecasts. In addition, the paper describes the end-to-end process of heat hazard outlooks and translating the forecasts into early action and early planning to reduce heat risk to human health. Furthermore, the paper addresses the very important aspect of capacity development tailored at enhancing forecasters' skills to prepare and issue heat wave forecasts and training of a cadre of health professionals to work with meteorologists to coproduce heat–health bulletins and to issue heat–health early warnings. [ABSTRACT FROM AUTHOR]

Flooding, including inland and coastal flooding, is one of the most devastating and costly natural hazards in Canada, Mexico, and the United States. Recent research conducted by an international team has focused on understanding the true and comprehensive economic costs of floods, with an eye toward addressing their impacts, allocating adequate resources for monitoring and preparedness, and building resilient communities. Flood-costing methods vary greatly among federal and subnational jurisdictions across the three North American countries. Because the rigor and consistency of existing datasets across the three countries vary significantly, it is also difficult to determine the economic impacts of cross-border events. This paper aims to critically analyze the research methods used to conduct this trinational project and develop recommendations for enhancing impacts of such work in the future. We discuss three major research barriers: gaps in knowledge and research capacity, differences in data collation and analysis methods across the three countries, and linguistic barriers in working across disciplines and economic sectors. We also explore how the COVID-19 pandemic significantly added to these three barriers. We propose creation of new institutional mechanisms that can play a major role in developing comprehensive, consistent, and cohesive data gathering approaches in Canada, Mexico, and the United States. [ABSTRACT FROM AUTHOR]

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 presence of persistent heavy fog in northern India during winter creates hazardous situations for transportation systems and disrupts the lives of about 400 million people. The meteorological factors responsible for its genesis and predictability are not yet completely understood in this region. Given its high potential for socioeconomic impact, there is a pressing need for extensive research that understands the inherently complex nature of the phenomena through field observations and modeling exercises. WiFEX is a first-of-its-kind multi-institutional initiative dealing with intensive ground-based measurement campaigns for developing a suitable fog forecasting capability under the aegis of the smart cities mission of India. Measuring campaigns were conducted during the 2015–20 winters at the Indira Gandhi International Airport, New Delhi, covering more than 90 dense fog events. The field experiments involved extensive suites of in situ instruments and gathered simultaneous observations of micrometeorological conditions, radiative fluxes, turbulence, droplet/aerosol microphysics, aerosol optical properties, fog water chemistry, and vertical thermodynamical structure to describe the environmental stability in which fog develops. An operational modeling framework, the WRF Model, was set up to provide fog predictions during the measurement campaign. These field observations helped to interpret the strengths and deficiencies in the numerical modeling framework. Four scientific objectives were pursued: (i) the life cycle of optically thin and thick fog, (ii) microphysical properties in the polluted boundary layer, (iii) fog water chemistry, gas–aerosol partitioning during the fog life cycle, and (iv) numerical prediction of fog. This paper presents an overview of WiFEX and a synthesis of selected observational and modeling analyses/findings related to the abovementioned scientific topics. [ABSTRACT FROM AUTHOR]

Ten years, 16 fully coupled global models, and hundreds of research papers later, the North American Multimodel Ensemble (NMME) monthly-to-seasonal prediction system is looking ahead to its second decade. The NMME comprises both real-time, initialized predictions and a substantial research database; both retrospective and real-time forecasts are archived and freely available for research and development. Many U.S.-based and international entities, both private and public, use NMME data for regional or otherwise tailored forecasts. The system's built-in evolution, with new models gradually replacing older ones, has been demonstrated to gradually improve the skill of 2-m temperature and sea surface temperature, although precipitation prediction remains a difficult problem. This paper reviews some of the NMME-based contributions to seasonal climate prediction research and applications, progress on scientific understanding of seasonal prediction and multimodel ensembles, and new techniques. Several prediction-oriented aspects are explored, including model representation of observed trends and the underprediction of below-average temperature. We discuss potential new directions, such as higher-resolution models, hybrid statistical–dynamical techniques, or prediction of environmental hazards such as coastal flooding and the risk of mosquito-borne diseases. [ABSTRACT FROM AUTHOR]

The Excessive Rainfall Outlook (ERO), issued operationally from the Weather Prediction Center (WPC), serves the Weather and Water Enterprise and decision-makers with probabilistic guidance and messaging context out to 3 days for excessive rainfall leading to impacts, including flash flooding. Eighty-three percent of all flood-related damages and 39% of all flood-related fatalities reported in Storm Data from 2010 to 2020 occurred in or near an ERO High Risk. Given that a High Risk is issued on only 4% of days, the presence of such risk can serve as an important step in raising situational awareness of a greater likelihood of a damaging and deadly flash flood day. This paper details the operational construction of the ERO at WPC and discusses the role of the ERO in the National Weather Service collaborative forecast process for heavy rainfall. Case studies where the ERO achieved a High Risk are presented for the deadly Montecito, California, flash flood and debris flow (2018) and Hurricane Harvey (2017). More broadly, challenges are highlighted which could be overcome by research to further improve ERO utility. [ABSTRACT FROM AUTHOR]

Meteorological extremes on the seasonal time scale have received increased attention due to their relevance for society and economy. A recently developed approach to identify seasonal extremes is applied here to ERA5 reanalyses from 1950 to 2020 to identify hot and cold, wet and dry, and stormy and calm extreme seasons globally. The approach consists of (i) fitting a statistical model to seasonal mean values (of temperature, precipitation, and wind speed) at each grid point, (ii) selecting a local return period threshold above which seasonal mean values are deemed extreme, and (iii) forming spatially coherent extreme season objects. The paper introduces the ERA5 extreme season explorer, an open-access web portal enabling researchers to visualize and download extreme season objects of any of the six types in their region of interest, for further investigating their underlying dynamics, statistical properties, and impacts. To illustrate the potential of our extreme season objects, we first discuss the top 10 cold winters in ERA5 globally and then focus on an unusual triple-compound extreme season in winter 1953/54 in Europe, which was simultaneously extremely cold, dry, and calm. We show that detailed analysis of weather system dynamics, including cyclones, blocks, jets, and Rossby waves, provides important insight into the processes leading to extreme seasons. In summary, this study presents for the first time a catalogue of objectively identified extreme seasons in the last decades, shows exemplarily how large-scale dynamics can lead to such seasons, and with the help of the explorer supports the community in accelerating research in this important area at the interface of weather and climate dynamics. [ABSTRACT FROM AUTHOR]

Winter storms are disruptive to society and the economy, and they often cause significant injuries and deaths. Innovations in winter storm forecasting have occurred across the value chain over the past two decades, from physical understanding, to observations, to model forecasts, to postprocessing, to forecaster knowledge and interpretation, to products and services, and ultimately to decision support. These innovations enable more accurate and consistent forecasts, which are increasingly being translated into actionable information for decision-makers. This paper reviews the current state of winter storm forecasting in the context of the U.S. National Weather Service operations and describes a potential future state. Given predictability limitations, a key challenge of winter storm forecasting has been characterizing uncertainty and communicating the forecast in ways that are understandable and useful to decision-makers. To address this challenge, particular focus is placed on establishing a probabilistic framework, with probabilistic hazard information serving as a foundation for winter storm decision support services. The framework is guided by social science research to ensure effective communication of risk to meet users' needs. Solutions to gaps impeding progress in winter storm forecasting are highlighted, including better understanding of mesoscale phenomenon, the need for better ensemble calibration, a rigorous and consistent database of observed impacts, and linking multiparameter probabilities (e.g., probability of intense snowfall rates at rush hour) with users' information needs and decisions. [ABSTRACT FROM AUTHOR]

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]

Aerosol properties are fundamentally different near clouds than away from clouds. This paper reviews the current state of knowledge of aerosol properties in the near-low-cloud environment and quantitatively compares them with aerosols far from clouds, according to remote sensing observations. It interprets observations of aerosol properties from different sensors using satellite, aircraft, and ground-based observations. The correlation (and anticorrelation) between proximity to cloud and aerosol properties is discussed. Retrieval artifacts in the near-cloud environment are demonstrated and quantified for different sensor attributes and environmental conditions. Finally, the paper describes the possible corrections for near-cloud enhancement in remote sensing retrievals. This study is timely in view of science definition studies for NASA's Aerosol, Cloud, Convection and Precipitation (ACCP) mission, which will also seek to directly link aerosol properties to nearby clouds. [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]

Climate variability on subseasonal to interannual time scales has significant impacts on our economy, society, and Earth's environment. Predictability for these time scales is largely due to the influence of the slowly varying climate anomalies in the oceans. The importance of the global oceans in governing climate variability demonstrates the need to monitor and forecast the global oceans in addition to El Niño–Southern Oscillation in the tropical Pacific. To meet this need, the Climate Prediction Center (CPC) of the National Centers for Environmental Prediction (NCEP) initiated real-time global ocean monitoring and a monthly briefing in 2007. The monitoring covers observations as well as forecasts for each ocean basin. In this paper, we introduce the monitoring and forecast products. CPC's efforts bridge the gap between the ocean observing system and the delivery of the analyzed products to the community. We also discuss the challenges involved in ocean monitoring and forecasting, as well as the future directions for these efforts. [ABSTRACT FROM AUTHOR]

Microburst wind shear has caused or contributed to a significant number of aviation accidents. Since 1943, wind shear accidents have been responsible for more than 1,400 fatalities worldwide, including over 400 deaths in the United States between 1973 and 1985. In this paper, we describe one of the more successful and societally impactful research-to-operations (R2O) programs in atmospheric science history. The remarkable R2O journey included the discovery of microburst wind shear in the late 1970s and early 1980s, the scientific efforts to understand this phenomenon and its impact on aircraft operations, the development of a wind shear training program for pilots, and the rapid development, testing, and implementation of wind shear detection systems that successfully saved lives and property. The article includes a chronological description of the wind shear research and development program, key milestones toward implementation, and the research-to-operations best practices employed for successful technology transfer. [ABSTRACT FROM AUTHOR]

The Copernicus Atmosphere Monitoring Service (CAMS), part of the European Union's Earth observation program Copernicus, entered operations in July 2015. Implemented by the European Centre for Medium-Range Weather Forecasts (ECMWF) as a truly European effort with over 23,500 direct data users and well over 200 million end users worldwide as of March 2022, CAMS delivers numerous global and regional information products about air quality, inventory-based emissions and observation-based surface fluxes of greenhouse gases and from biomass burning, solar energy, ozone and UV radiation, and climate forcings. Access to CAMS products is open and free of charge via the Atmosphere Data Store. The CAMS global atmospheric composition analyses, forecasts, and reanalyses build on ECMWF's Integrated Forecasting System (IFS) and exploit over 90 different satellite data streams. The global products are complemented by coherent higher-resolution regional air quality products over Europe derived from multisystem analyses and forecasts. CAMS information products also include policy support such as quantitative impact assessment of short- and long-term pollutant-emission mitigation scenarios, source apportionment information, and annual European air quality assessment reports. Relevant CAMS products are cited and used for instance in IPCC Assessment Reports. Providing dedicated support for users operating smartphone applications, websites, or TV bulletins in Europe and worldwide is also integral to the service. This paper presents key achievements of the CAMS initial phase (2014–21) and outlines some of its new components for the second phase (2021–28), e.g., the new Copernicus anthropogenic CO2 emissions Monitoring and Verification Support capacity that will monitor global anthropogenic emissions of key greenhouse gases. [ABSTRACT FROM AUTHOR]

A hyperspectral infrared (IR) sounder from geostationary orbit provides nearly continuous measurements of atmospheric thermodynamic and dynamic information within a weather cube, specifically the atmospheric temperature, moisture, and wind information at different pressure levels that are critical for improving high-impact weather (HIW) nowcasting and numerical weather prediction (NWP). Geostationary hyperspectral IR sounders (GeoHIS) have been on board China's Fengyun-4 series since 2016 and will be on board Europe's Meteosat Third Generation (MTG) series in the 2024 time frame; the United States and other countries are also planning to include GeoHIS instruments on their next generation of geostationary weather satellites. Although availability of on-orbit GeoHIS data are limited currently, studies have been conducted and progress has been made on developing the applications of high-temporal-resolution GeoHIS observations. These include but are not limited to deriving three-dimensional wind fields for nowcasting and NWP applications, trending atmospheric instability for warning in preconvective environments, conducting impact studies with data from the experimental Geostationary Interferometric Infrared Sounder (GIIRS) on board Fengyun-4A, preparing observing system simulation experiments (OSSEs), and monitoring diurnal variation of atmospheric composition. This paper provides an overview of the current applications of GeoHIS, discusses the data processing challenges, and provides perspectives on future development. The purpose is to provide direction on utilization of the current and assist preparation for the upcoming GeoHIS observations for nowcasting, NWP and other applications. [ABSTRACT FROM AUTHOR]

Since 2017, the Northern Australia Climate Program (NACP) has assisted the pastoral grazing industry to better manage drought risk and climate variability. The NACP funding is sourced from the beef cattle industry, government, and academia, representing the program's broad range of aims and target beneficiaries. The program funds scientists in the United Kingdom and Australia, in addition to extension advisers called "Climate Mates" across a region that supports 15 million head of cattle. Many Climate Mates are employed in the cattle sector and have existing relationships in their communities and capacity to meaningfully engage with the program's intended beneficiaries—red meat producers. The NACP is a prime example of a successful end-to-end program, integrating climate model improvements (research) with tailored forecast products (development), through to direct stakeholder engagement (extension), on-ground application of technologies (adoption), and improvement in industry and community resilience (impact). The climate information needs of stakeholders also feed back to the research and development components, ensuring the scientific research directly addresses end-user requirements. For any scientific research program, ensuring that research output has measurable real-world impact represents a key challenge. This is more difficult in cases where the scientific research is several steps away from the customer's needs. This paper gives an overview of the NACP and research highlights, discussing how the end-to-end framework could be adapted and applied in other regions and industries. It seeks to provide a roadmap for other groups to follow to produce more targeted research with identifiable real-world benefits. [ABSTRACT FROM AUTHOR]

Keywords: History EN History 827 833 7 12/12/22 20221101 NES 221101 In discussing the early history of the National Weather Service (NWS) and its predecessor agencies, [24] make several critical errors and confound the historical record surrounding Cleveland Abbe, one of the key figures in the history of the nation's weather service. In August 1888, for example, Abbe responded to a letter from journalist and meteorological kite experimenter William A. Eddy, who wrote to Abbe to fact-check an article he had written about the history of the weather service. Cleveland Abbe Papers, General Correspondence, 1850 - 1916, Manuscript Division, Library of Congress, Box 8. 2 Abbe, C., 1892: The modern weather bureau. In his letter, [11] erroneously suggested that Abbe had approached Chief Signal Officer Gen. Albert J. Myer prior to the creation of the service "with a proposition to include weather reports with information forwarded from signal stations" and that the weather service had been organized by Abbe. [Extracted from the article]

Ice habit diagrams published prior to 2009—and many since—do not accurately describe in situ observations of ice shapes as a function of temperature and moisture. Laboratory studies and analysis of field observations by Bailey and Hallett in a series of papers in 2002, 2004, and 2009 corrected several errors from earlier studies, but their work has not been widely disseminated. We present a new, simplified diagram based on Bailey and Hallett's work that focuses on several ice growth forms arising from the underlying surface processes by which mass is added to a crystal: tabular, columnar, branched, side branched, two types of polycrystalline forms, and a multiple growth regime at low ice supersaturations. To aid interpretation for a variety of applications, versions of the ice growth diagram are presented in terms of relative humidity with respect to water as well as the traditional formats of relative humidity with respect to ice and vapor density excess. These diagrams are intended to be understandable and useful in classroom settings at the sophomore undergraduate level and above. The myriad shapes of pristine snow crystals can be described as the result of either a single growth form or a sequence of growth forms. Overlays of data from upper-air soundings on the ice growth diagrams aid interpretation of expected physical properties and processes in conditions of ice growth. [ABSTRACT FROM AUTHOR]

The Arctic is warming at more than twice the rate of the global average. This warming is influenced by clouds, which modulate the solar and terrestrial radiative fluxes and, thus, determine the surface energy budget. However, the interactions among clouds, aerosols, and radiative fluxes in the Arctic are still poorly understood. To address these uncertainties, the Ny-Ålesund Aerosol Cloud Experiment (NASCENT) study was conducted from September 2019 to August 2020 in Ny-Ålesund, Svalbard. The campaign's primary goal was to elucidate the life cycle of aerosols in the Arctic and to determine how they modulate cloud properties throughout the year. In situ and remote sensing observations were taken on the ground at sea level, at a mountaintop station, and with a tethered balloon system. An overview of the meteorological and the main aerosol seasonality encountered during the NASCENT year is introduced, followed by a presentation of first scientific highlights. In particular, we present new findings on aerosol physicochemical and molecular properties. Further, the role of cloud droplet activation and ice crystal nucleation in the formation and persistence of mixed-phase clouds, and the occurrence of secondary ice processes, are discussed and compared to the representation of cloud processes within the regional Weather Research and Forecasting Model. The paper concludes with research questions that are to be addressed in upcoming NASCENT publications. [ABSTRACT FROM AUTHOR]

The paper describes the observational and modeling efforts performed under the Bolzano Tracer Experiment (BTEX). BTEX focused on the basin surrounding the city of Bolzano, at the junction of three tributary valleys on the southern side of the Alps, to characterize the ground-level impact of pollutants emitted by a waste incinerator close to the city, and atmospheric factors controlling dispersion processes in the whole basin, under different winter weather situations. As part of the experiment, two controlled releases of a passive gas tracer (sulfur hexafluoride, SF6) were performed through the stack of the incinerator on 14 February 2017 at two different times, starting respectively at 0700 and 1245 LST, representative of distinct phases of the daily cycle. Samples of ambient air were collected at target sites, and later analyzed using a mass spectrometer, allowing a detectability limit down to 30 ppt. Meanwhile, meteorological conditions were continuously monitored by means of a high-resolution, nonconventional network of ground-based instruments, including 15 weather stations, one temperature profiler, one sodar, and one Doppler wind lidar. Data from the above measurements represent one of the rare examples of integrated datasets available to the community for the characterization of dispersion processes in a typical mountainous environment. In particular, they offered a reference benchmark for testing and calibrating a series of combined numerical modeling suites for weather prediction and pollutant dispersion simulation in such a complex terrain, as shown in the paper. [ABSTRACT FROM AUTHOR]

The Joint Typhoon Warning Center (JTWC) utilized new space-based environmental monitoring (SBEM) data alongside traditional data to adjust JTWC tropical cyclone (TC) intensity and structure estimates during production of the official 2019 Best Track dataset. Intensity estimates from multiple platforms such as Advanced Microwave Scanning Radiometer-2 (AMSR2), the Soil Moisture Active Passive (SMAP) and Soil Moisture and Ocean Salinity (SMOS) radiometers, and synthetic aperture radar (SAR), along with objective Dvorak and satellite consensus algorithms, not only aided the poststorm best track (BT) process, but also provided robust data that supported real-time analysis and forecasting. This summary attempts to communicate with the TC community the extent to which these new data affected the 2019 official BT data, how JTWC utilized these new data in the poststorm BT process, and provide examples of how these data influenced forecaster decision-making in real time. This paper makes no attempt to validate the accuracy of the wind speed estimates from these methods (SAR, SMAP/SMOS, or AMSR2) and does not outline the entirety of the JTWC process for determining TC intensity, but it does outline, briefly, the impact of these new datasets on the final JTWC BT intensity estimates and on real-time analysis. These methodologies are valuable sources of cyclone intensity estimates in an otherwise data-sparse area of responsibility, and in many cases provide critical data not captured by traditional methods alone, which are detailed further in this summary. [ABSTRACT FROM AUTHOR]

There is great interest in improving our understanding of the respective roles of the ocean and atmosphere in variability and change in weather and climate. Due to the sparsity of sustained observing sites in the open ocean, information about the air–sea exchanges of heat, freshwater, and momentum is often drawn from models. In this paper observations from three long-term surface moorings deployed in the trade wind regions of the Pacific and Atlantic Oceans are used to compare observed means and low-passed air–sea fluxes from the moorings with coincident records from three atmospheric reanalyses (ERA5, NCEP-2, and MERRA-2) and from CMIP6 coupled models. To set the stage for the comparison, the methodologies of maintaining the long-term surface moorings, known as ocean reference stations (ORS), and assessing the accuracies of their air–sea fluxes are described first. Biases in the reanalyses' means and low-passed wind stresses and net air–sea heat fluxes are significantly larger than the observational uncertainties and in some case show variability in time. These reanalyses and most CMIP6 models fail to provide as much heat into the ocean as observed. In the discussion and conclusions section, long-term observing sites in the open ocean are seen as essential, independent benchmarks not only to document the coupling between the atmosphere and ocean but also to promote collaborative efforts to assess and improve the ability of models to simulate air–sea fluxes. [ABSTRACT FROM AUTHOR]

There are a couple of reasons to stimulate a discussion about the definition of clouds. One reason is that the American Meteorological Society (AMS) and the World Meteorological Organization (WMO) define clouds differently, and that in two aspects. AMS defines clouds as visible objects, and WMO as perceivable objects. Furthermore, AMS includes all minute particles independent of their nature and composition whereas WMO considers only such minute particles that consist of water, ice, or a mixture of both. Additionally, the so-called invisible or subvisible clouds are perceivable objects in the definition of WMO but not of AMS. Clouds can be observed by humans and be detected by active and passive sensors from ground and space. The detection limits of instruments span more than two orders of magnitude in visible optical thickness ranging from about 0.001 from satellite lidar (in case of horizontal and vertical averaging or 0.07 for single lidar shots) to about 0.3 to 0.45 for multispectral satellite imaging spectrometers. Human observers see clouds when their optical thickness is larger than about 0.03 at day and 0.05 at night. This paper gives a brief overview of cloud detection from ground and space and of the occurrence, characteristics, and impacts of subvisible clouds. Pros and cons of these definitions are discussed, followed by a proposal for a more precise definition. This definition is, like those of AMS and WMO, a one-parametric definition and does not cover all aspects of clouds. [ABSTRACT FROM AUTHOR]

This paper makes a case for why Hawaii is the rainbow capital of the world. It begins by briefly touching on the cultural and historical significance of rainbows in Hawaii. Next it provides an overview of the science behind the rainbow phenomenon, which provides context for exploring the meteorology that helps explain the prevalence of Hawaiian rainbows. Last, the paper discusses the art and science of chasing rainbows. [ABSTRACT FROM AUTHOR]