ALBERT

Description: Alfred Wegener (1880–1930) was a leading geophysicist, atmospheric scientist, and an Arctic explorer who is mainly remembered today for his contributions to the theory of continental drift. Less well known are his contributions to research on tornadoes in Europe. Published 100 years ago, Wegener’s 1917 book Wind- und Wasserhosen in Europa (Tornadoes and Waterspouts in Europe) is an impressive synthesis of knowledge on tornadoes and is considered the first modern pan-European tornado climatology, with 258 reports from 1456 to 1913. Unfortunately, Wegener’s book was overlooked after the 1950s amid declining interest in tornadoes by European researchers and meteorologists. The recent revival of tornado studies in Europe invites a reflection on Wegener’s book. Using a relatively small dataset, Wegener was able to describe characteristics of tornadoes (e.g., direction of movement, speed, rotation, formation mechanism), as well as their frequency of occurrence and climatology, comparable with the results from modern tornado climatologies. Wegener’s lasting scientific contributions to tornado research are presented in the context of European research on this topic. Specifically, his book showed the utility of reports from citizen scientists and inspired other researchers, namely, Johannes Letzmann, who continued to study European tornadoes after Wegener’s death.

Description: A major experimental drought research project entitled “Mechanisms and Early Warning of Drought Disasters over Northern China” (DroughtEX_China) was launched by the Ministry of Science and Technology of China in 2015. The objective of DroughtEX_China is to investigate drought disaster mechanisms and provide early-warning information via multisource observations and multiscale modeling. Since the implementation of DroughtEX_China, a comprehensive V-shape in situ observation network has been established to integrate different observational experiment systems for different landscapes, including crops in northern China. In this article, we introduce the experimental area, observational network configuration, ground- and air-based observing/testing facilities, implementation scheme, and data management procedures and sharing policy. The preliminary observational and numerical experimental results show that the following are important processes for understanding and modeling drought disasters over arid and semiarid regions: 1) the soil water vapor–heat interactions that affect surface soil moisture variability, 2) the effect of intermittent turbulence on boundary layer energy exchange, 3) the drought–albedo feedback, and 4) the transition from stomatal to nonstomatal control of plant photosynthesis with increasing drought severity. A prototype of a drought monitoring and forecasting system developed from coupled hydroclimate prediction models and an integrated multisource drought information platform is also briefly introduced. DroughtEX_China lasted for four years (i.e., 2015–18) and its implementation now provides regional drought monitoring and forecasting, risk assessment information, and a multisource data-sharing platform for drought adaptation over northern China, contributing to the global drought information system (GDIS).

Description: Fronts can be computed from gridded datasets such as numerical model output and reanalyses, resulting in automated surface frontal charts and climatologies. Defining automated fronts requires quantities (e.g., potential temperature, equivalent potential temperature, wind shifts) and kinematic functions (e.g., gradient, thermal front parameter, and frontogenesis). Which are the most appropriate to use in different applications remains an open question. This question is investigated using two quantities (potential temperature and equivalent potential temperature) and three functions (magnitude of the horizontal gradient, thermal front parameter, and frontogenesis) from both the context of real-time surface analysis and climatologies from 38 years of reanalyses. The strengths of potential temperature to identify fronts are that it represents the thermal gradients and its direct association with the kinematics and dynamics of fronts. Although climatologies using potential temperature show features associated with extratropical cyclones in the storm tracks, climatologies using equivalent potential temperature include moisture gradients within air masses, most notably at low latitudes that are unrelated to the traditional definition of a front, but may be representative of a broader definition of an airmass boundary. These results help to explain previously published frontal climatologies featuring maxima of fronts in the subtropics and tropics. The best function depends upon the purpose of the analysis, but Petterssen frontogenesis is attractive, both for real-time analysis and long-term climatologies, in part because of its link to the kinematics and dynamics of fronts. Finally, this study challenges the conventional definition of a front as an airmass boundary and suggests that a new, dynamically based definition would be useful for some applications.

Description: Tropical cyclones are some of the most devastating natural hazards and the “three beasts”—Harvey, Irma, and Maria—during the Atlantic hurricane season 2017 are recent examples. The European Centre for Medium-Range Weather Forecasts (ECMWF) is working on fulfilling its 2016–25 strategy in which early warnings for extreme events will be made possible by a high-resolution Earth system ensemble forecasting system. Several verification reports acknowledge deterministic and probabilistic tropical cyclone tracks from ECMWF as world leading. However, producing reliable intensity forecasts is still a difficult task for the ECMWF global forecasting model, especially regarding maximum wind speed. This article will put the ECMWF strategy into a tropical cyclone perspective and highlight some key research activities, using Harvey, Irma, and Maria as examples. We describe the observation usage around tropical cyclones in data assimilation and give examples of their impact. From a model perspective, we show the impact of running at 5-km resolution and also the impact of applying ocean coupling. Finally, we discuss the future challenges to tackle the errors in intensity forecasts for tropical cyclones.

Description: In the early days of television, most weathercasters lacked formal training in meteorology and instead relied on forecasts from other sources. Over the decades, degreed meteorologists became more common. A third category has recently emerged: people with certificates in broadcast meteorology from Mississippi State University (MSU). This certification and the related broadcast meteorology degrees from MSU provide weathercasters with an understanding of meteorology without advanced calculus or differential equations. This study makes no judgment on how a weathercaster’s education background might affect their on-air presentations but notes these courses are required by most guidelines for meteorological degrees, as well as the American Meteorological Society's Certified Broadcast Meteorologist (CBM) program. This study conducts a unique survey of television meteorologists using the education history listed on their station's website or LinkedIn. The backgrounds of 421 meteorologists were examined with the equivalent of a 94% response rate. Overall, 21% had a broadcast meteorology degree or certification from MSU, 64% had a traditional meteorology degree from MSU or another institution, 2% minored in meteorology or had military training, and 12% listed no or a partial education background in the field. Another way of viewing the data is that the MSU broadcast program alone has nearly as many graduates as the four largest traditional programs combined in our sample. These results were further broken down for various subsets of weathercasters, resulting in statistically significant variations by market size, region, ownership group, and gender.

Description: Researchers are producing an ever greater number of web-based climate data and analysis tools in support of natural resource research and management. Yet the apparent absence or underreporting of evaluation in the development of these applications has raised questions as to whether, by whom, and for what they are utilized, and, relatedly, whether they meet the rationale for their development. This paper joins recent efforts to address these questions by introducing one approach to evaluation—developmental evaluation—and reporting on its use in the evaluation of the Southwest Climate and Environmental Information Collaborative (SCENIC). A web interface under development at the Western Regional Climate Center, SCENIC provides access to climate data and analysis tools to environmental scientists in support of natural resource research and management in the southwestern United States. Evaluation findings highlight subtlety in the improvements necessary for ensuring a useful and usable application that could not have been ascertained in the absence of end-user feedback. We therefore urge researchers to systematically evaluate web-based climate data and analysis tools in the interest of ensuring their usefulness, usability, and fulfillment of the proposed rationale. In so doing, we recommend that researchers test and apply established evaluation frameworks, thereby engaging end users directly in the process of application development.

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

Description: During winter 2016/17, California experienced numerous heavy precipitation events linked to land-falling atmospheric rivers (ARs) that filled reservoirs and ended a severe, multiyear drought. These events also caused floods, mudslides, and debris flows, resulting in major socioeconomic disruptions. During 2–11 February 2017, persistent heavy precipitation in the northern Sierra Nevada culminated in a rapid increase in the water level on Lake Oroville, necessitating the activation of an emergency spillway for the first time since the Oroville Dam was installed and forcing the evacuation of 188,000 people. The precipitation, which mostly fell as rain due to elevated freezing levels, was focused on the western slope of the Sierra Nevada in connection with orographic forcing linked to two successive ARs. Heavy rain fell on saturated soils and a snowpack produced by antecedent storms and thereby resulted in excessive runoff into Lake Oroville that led to a damaged spillway and complicated reservoir operations.

Description: The best way to train the next wave of observational talent is through direct experience. In 2012 and again in 2014, students at St. Cloud State University (SCSU) welcomed deployments of professional atmospheric research equipment, allowing them to support and execute field projects. The Boundary Structure Experiments with Central Minnesota Profiling (BaSE CaMP) projects brought the Mobile Integrated Sounding System (MISS) from the National Center for Atmospheric Research’s (NCAR) Earth Observing Laboratory (EOL) to SCSU for a National Science Foundation–funded educational deployment. Its diverse instrumentation and ability to travel to interesting weather events and locations makes MISS extremely valuable for teaching students about both weather experiments and measurement strategies. In addition to the university project, outreach activities with MISS took place at high schools, regional conferences, and public events. MISS carries four instruments: a boundary layer wind profiler, a radio acoustic sounding system (RASS), radiosondes, and an instrumented 10-m tower. The type and time of MISS deployments were quite varied so students could participate around their class schedule, jobs, and other commitments. Each year the project had periods of fixed operations and mobile activity, where MISS was relocated to best observe current weather conditions. BaSE CaMP operations and results were incorporated into many classes in the meteorology program at SCSU. The original course request was for Radar and Satellite Meteorology, but other activities contributed to Atmospheric Dynamics, Physical Meteorology, and Meteorological Analysis Software courses.

Description: The ability of global climate models to simulate accurately marine stratiform clouds continues to challenge the atmospheric science community. These cloud types, which account for a large uncertainty in Earth’s radiation budget, are generally difficult to characterize due to their shallowness and spatial inhomogeneity. Previous work investigating marine boundary layer (MBL) clouds off the California coast has focused on clouds that form under the typical northerly flow regime during the boreal warm season. From about June through September, however, these northerly winds may reverse and become southerly as part of a coastally trapped disturbance (CTD). As the flow surges northward, it is accompanied by a broad cloud deck. Because these events are difficult to forecast, in situ observations of CTDs are few and far between, and little is known about their cloud physical properties. A climatological perspective of 23 CTD events—spanning the years from 2004 to 2016—is presented using several data products, including model reanalyses, buoys, and satellites. For the first time, satellite retrievals suggest that CTD cloud decks may play a unique role in the radiation budget due to a combination of aerosol sources that enhance cloud droplet number concentration and reduce cloud droplet effective radius. This particular type of cloud regime should therefore be treated differently than that which is more commonly found in the summertime months over the northeast Pacific Ocean. The potential influence of a coherent wind stress cycle on sea surface temperatures and sea salt aerosol is also explored.

Description: Atmospheric rivers (ARs) play vital roles in the western United States and related regions globally, not only producing heavy precipitation and flooding, but also providing beneficial water supply. This paper introduces a scale for the intensity and impacts of ARs. Its utility may be greatest where ARs are the most impactful storm type and hurricanes, nor’easters, and tornadoes are nearly nonexistent. Two parameters dominate the hydrologic outcomes and impacts of ARs: vertically integrated water vapor transport (IVT) and AR duration [i.e., the duration of at least minimal AR conditions (IVT ≥ 250 kg m–1 s–1)]. The scale uses an observed or predicted time series of IVT at a given geographic location and is based on the maximum IVT and AR duration at that point during an AR event. AR categories 1–5 are defined by thresholds for maximum IVT (3-h average) of 250, 500, 750, 1,000, and 1,250 kg m–1 s–1, and by IVT exceeding 250 kg m–1 s–1 continuously for 24–48 h. If the AR event duration is less than 24 h, it is downgraded by one category. If it is longer than 48 h, it is upgraded one category. The scale recognizes that weak ARs are often mostly beneficial because they can enhance water supply and snowpack, while stronger ARs can become mostly hazardous, for example, if they strike an area with antecedent conditions that enhance vulnerability, such as burn scars or wet conditions. Extended durations can enhance impacts. Short durations can mitigate impacts.

Description: El Niño and La Niña, the warm and cold phases of El Niño–Southern Oscillation (ENSO), cause significant year-to-year disruptions in global climate, including in the atmosphere, oceans, and cryosphere. Australia is one of the countries where its climate, including droughts and flooding rains, is highly sensitive to the temporal and spatial variations of ENSO. The dramatic impacts of ENSO on the environment, society, health, and economies worldwide make the application of reliable ENSO predictions a powerful way to manage risks and resources. An improved understanding of ENSO dynamics in a changing climate has the potential to lead to more accurate and reliable ENSO predictions by facilitating improved forecast systems. This motivated an Australian national workshop on ENSO dynamics and prediction that was held in Sydney, Australia, in November 2017. This workshop followed the aftermath of the 2015/16 extreme El Niño, which exhibited different characteristics to previous extreme El Niños and whose early evolution since 2014 was challenging to predict. This essay summarizes the collective workshop perspective on recent progress and challenges in understanding ENSO dynamics and predictability and improving forecast systems. While this essay discusses key issues from an Australian perspective, many of the same issues are important for other ENSO-affected countries and for the international ENSO research community.

Description: The daily precipitation data generated by dynamical models, including regional climate models, generally suffer from biases in distribution and spatial dependence. These are serious flaws if the data are intended to be applied to hydrometeorological studies. This paper proposes a scheme for correcting the biases in both aspects simultaneously. The proposed scheme consists of two steps: an aggregation step and a disaggregation step. The first one aims to obtain a smoothed precipitation pattern that must be retained in correcting the bias, and the second aims to make up for the deficient spatial variation of the smoothed pattern. In both steps, the Gaussian copula plays important roles since it not only provides a feasible way to correct the spatial correlation of model simulations but also can be extended for large-dimension cases by imposing a covariance function on its correlation structure. The proposed scheme is applied to the daily precipitation data generated by a regional climate model. We can verify that the biases are satisfactorily corrected by examining several statistics of the corrected data.

Description: In the past two decades, more than 150 jet engine power-loss and damage events have been attributed to a phenomenon known as ice crystal icing (ICI). Ingestion of large numbers of ice particles into the engine core are thought to be responsible for these events, which typically occur at high altitudes near large convective systems in tropical air masses. In recent years, scientists, engineers, aviation regulators, and airlines from around the world have collaborated to better understand the relevant meteorological processes associated with ICI events, solve critical engineering problems, develop new certification standards, and devise mitigation strategies for the aviation industry. One area of research is the development of nowcasting techniques based on available remote sensing technology and numerical weather prediction (NWP) models to identify areas of high ice water content (IWC) and enable the provision of alerts to the aviation industry. Multiple techniques have been developed using geostationary and polar-orbiting satellite products, NWP model fields, and ground-based radar data as the basis for high-IWC products. Targeted field experiments in tropical regions with high incidence of ICI events have provided data for product validation and refinement of these methods. Beginning in 2015, research teams have assembled at a series of annual workshops to exchange ideas and standardize methods for evaluating performance of high-IWC detection products. This paper provides an overview of the approaches used and the current skill for identifying high-IWC conditions. Recommendations for future work in this area are also presented.

Description: A series of large wildfires began over the terrain north of San Francisco, California, during the evening of 8 October 2017 and spread across nearly 250,000 acres, including areas near the towns of Santa Rosa and Napa. These “Wine Country” wildfires were the most destructive in California history, with 44 deaths; the loss of 9,000 buildings; damage to approximately 21,000 structures; $10 billion of insured losses; and substantially greater total economic loss. This paper describes the synoptic and mesoscale conditions that were associated with the wildfires, with strong, easterly “Diablo” winds playing a central role in both initiating and supporting the fires. The climatological conditions preceding the fires are reviewed, including near-normal precipitation and above-normal temperatures during the summer, as well as much above-normal precipitation the previous winter, which led to abundant dry grass that provided fuel for the wind-driven fires. High-resolution meteorological modeling realistically simulated the strong winds associated with this event. Importantly, operational mesoscale forecast models provided excellent forecasts of the high winds several days in advance. It appears that a vulnerable power system, urbanization of fire-prone areas, flammable invasive species, and poor communication of dangerous conditions contributed to this catastrophic event. The potential for mitigating or preventing such destructive wildfires using skillful weather prediction is examined, as well as the possible role of global warming.

Description: The complex orography of South Asia, including both the Himalayas and the Tibetan Plateau, renders the regional climate complex. How this climate, especially the monsoon circulations, will respond to the global warming process is important given the large population of the region. In a first step toward a contribution to the understanding of the expected impacts, a series of dynamically downscaled instrumental-era climate simulations for the Indian subcontinent are described and will serve as a basis for comparison against global warming simulations. Global simulations based upon the Community Earth System Model (CESM) are employed to drive a dynamical downscaling pipeline in which the Weather Research and Forecasting (WRF) Model is employed as regional climate model, in a nested configuration with two domains at 30- and 10-km resolution, respectively. The entire ensemble was integrated for 15 years (1980–94), with the global model representing a complete integration from the onset of Northern Hemisphere industrialization. Compared to CESM, WRF significantly improves the representation of orographic precipitation. Precipitation extremes are also characterized using extreme value analysis. To investigate the sensitivity of the South Asian summer monsoon simulation to different parameterization schemes, a small physics ensemble is employed. The Noah multiphysics (Noah-MP) land surface scheme reduces the summer warm bias compared to the Noah land surface scheme. Compared with the Kain–Fritsch cumulus scheme, the Grell-3 scheme produces an increased moisture bias at the first western rain barrier, whereas the Tiedtke scheme produces less precipitation over the subcontinent than observed. Otherwise the improvement of fit to the observations derived from applying the downscaling methodology is highly significant.

Description: Clouds play an important role in Arctic amplification. This term represents the recently observed enhanced warming of the Arctic relative to the global increase of near-surface air temperature. However, there are still important knowledge gaps regarding the interplay between Arctic clouds and aerosol particles, and surface properties, as well as turbulent and radiative fluxes that inhibit accurate model simulations of clouds in the Arctic climate system. In an attempt to resolve this so-called Arctic cloud puzzle, two comprehensive and closely coordinated field studies were conducted: the Arctic Cloud Observations Using Airborne Measurements during Polar Day (ACLOUD) aircraft campaign and the Physical Feedbacks of Arctic Boundary Layer, Sea Ice, Cloud and Aerosol (PASCAL) ice breaker expedition. Both observational studies were performed in the framework of the German Arctic Amplification: Climate Relevant Atmospheric and Surface Processes, and Feedback Mechanisms (AC) project. They took place in the vicinity of Svalbard, Norway, in May and June 2017. ACLOUD and PASCAL explored four pieces of the Arctic cloud puzzle: cloud properties, aerosol impact on clouds, atmospheric radiation, and turbulent dynamical processes. The two instrumented Polar 5 and Polar 6 aircraft; the icebreaker Research Vessel (R/V) Polarstern; an ice floe camp including an instrumented tethered balloon; and the permanent ground-based measurement station at Ny-Ålesund, Svalbard, were employed to observe Arctic low- and mid-level mixed-phase clouds and to investigate related atmospheric and surface processes. The Polar 5 aircraft served as a remote sensing observatory examining the clouds from above by downward-looking sensors; the Polar 6 aircraft operated as a flying in situ measurement laboratory sampling inside and below the clouds. Most of the collocated Polar 5/6 flights were conducted either above the R/V Polarstern or over the Ny-Ålesund station, both of which monitored the clouds from below using similar but upward-looking remote sensing techniques as the Polar 5 aircraft. Several of the flights were carried out underneath collocated satellite tracks. The paper motivates the scientific objectives of the ACLOUD/PASCAL observations and describes the measured quantities, retrieved parameters, and the applied complementary instrumentation. Furthermore, it discusses selected measurement results and poses critical research questions to be answered in future papers analyzing the data from the two field campaigns.

Description: There has been a recent wave of attention given to atmospheric bores in order to understand how they evolve and initiate and maintain convection during the night. This surge is attributable to data collected during the 2015 Plains Elevated Convection at Night (PECAN) field campaign. A salient aspect of the PECAN project is its focus on using multiple observational platforms to better understand convective outflow boundaries that intrude into the stable boundary layer and induce the development of atmospheric bores. The intent of this article is threefold: 1) to educate the reader on current and future foci of bore research, 2) to present how PECAN observations will facilitate aforementioned research, and 3) to stimulate multidisciplinary collaborative efforts across other closely related fields in an effort to push the limitations of prediction of nocturnal convection.

Description: This is a feasibility study on the use of dual-polarized radars to infer icing in terminal airspaces (TASs) of commercial airports. The amount and quality of radar coverage in each TAS is quantified as a function of its location, traffic, and vulnerability to icing. No airport has 100% of the TAS covered, but most high-traffic or high-icing airports have comparatively good coverage (between 70% and 90%). A common occurrence during icing is anomalous propagation as 79% of events had an inversion within the TAS. This leads to overestimates in the elevations of icing layers and can cause significant ground-clutter contamination, which can overwhelm the echo produced by precipitation. The effects of beam broadening were also considered. Typical dendrite growth and melting layers can only be resolved in part of the TAS part of the time, or not at all, as these layers are often shallower than the radar beam. Because most airports have coverage from multiple radars, use of a three-dimensional mosaic was investigated. This allows for an increase in the TAS coverage (generally between 5% and 15%) and partly mitigates some of the resolution issues, but the maxima within individual layers are somewhat reduced in the interpolation process. A series of recommendations is made to address the concerns raised by this investigation. These include using only icing tops (not bottoms) to identify areas of icing, use of data mining to retrieve precipitation echo in the presence of ground clutter, and including the beamwidth in radar mosaics.

Description: Commonly used disdrometers tend not to accurately measure concentrations of very small drops in the raindrop size distribution (DSD), either through truncation of the DSD at the small-drop end or because of large uncertainties on these measurements. Recent studies have shown that, as a result of these inaccuracies, many if not most ground-based disdrometers do not capture the “drizzle mode” of precipitation, which consists of large concentrations of small drops and is often separated from the main part of the DSD by a shoulder region. We present a technique for reconstructing the drizzle mode of the DSD from “incomplete” measurements in which the drizzle mode is not present. Two statistical moments of the DSD that are well measured by standard disdrometers are identified and used with a double-moment normalized DSD function that describes the DSD shape. A model representing the double-moment normalized DSD is trained using measurements of DSD spectra that contain the drizzle mode obtained using collocated Meteorological Particle Spectrometer and 2D video disdrometer instruments. The best-fitting model is shown to depend on temporal resolution. The result is a method to estimate, from truncated or uncertain measurements of the DSD, a more complete DSD that includes the drizzle mode. The technique reduces bias on low-order moments of the DSD that influence important bulk variables such as the total drop concentration and mass-weighted mean drop diameter. The reconstruction is flexible and often produces better rain-rate estimations than a previous DSD correction routine, particularly for light rain.

Description: A general drop size distribution (DSD) normalization method is formulated in terms of generalized power series relating any DSD moment to any number and combination of reference moments. This provides a consistent framework for comparing the variability of normalized DSD moments using different sets of reference moments, with no explicit assumptions about the DSD functional form (e.g., gamma). It also provides a method to derive any unknown moment plus an estimate of its uncertainty from one or more known moments, which is relevant to remote sensing retrievals and bulk microphysics schemes in weather and climate models. The approach is applied to a large dataset of disdrometer-observed and bin microphysics-modeled DSDs. As expected, the spread of normalized moments decreases as the number of reference moments is increased, quantified by the logarithmic standard deviation of the normalized moments, σ. Averaging σ for all combinations of reference moments and normalized moments of integer order 0–10, 42.9%, 81.3%, 93.7%, and 96.9% of spread are accounted for applying one-, two-, three-, and four-moment normalizations, respectively. Thus, DSDs can be well characterized overall using three reference moments, whereas adding a fourth reference moment contributes little independent information. The spread of disdrometer-observed DSD moments from uncertainty associated with drop count statistics generally lies between values of σ using two- and three-moment normalizations. However, this uncertainty has little impact on the derived DSD scaling relationships or σ when considered.

Description: Severe (〉2.5 cm) hail causes 〉$5 billion in damage annually in the United States. However, radar sizing of hail remains challenging. Typically, spheroids are used to represent hailstones in radar forward operators and to inform radar hail-sizing algorithms. However, natural hailstones can have irregular shapes and lobes; these details significantly influence the hailstone’s scattering properties. The high-resolution 3D structure of real hailstones was obtained using a laser scanner for hail collected during the 2016–17 Insurance Institute for Business and Home Safety (IBHS) Hail Field Study. Plaster casts of several record hailstones (e.g., Vivian, South Dakota, 2010) were also scanned. The S-band scattering properties of these hailstones were calculated with the discrete dipole approximation (DDA). For comparison, scattering properties of spheroidal approximations of each hailstone (with identical maximum and minimum dimensions and mass) were calculated with the T matrix. The polarimetric radar variables have errors when using spheroids, even for small hail. Spheroids generally have smaller variations in the polarimetric variables than the real hailstones. This increased variability is one reason why the correlation coefficient tends to be lower in observations than in forward-simulated cases using spheroids. Backscatter differential phase δ also is found to have large variance, particularly for large hailstones. Irregular hailstones with a thin liquid layer produce enhanced and more variable values for reflectivity factor at horizontal polarization ZHH, differential reflectivity ZDR, specific differential phase KDP, linear depolarization ratio (LDR), and δ compared with dry hailstones; is also significantly reduced.

Description: A statistical passive microwave intensity estimation (PMW-IE) algorithm for estimating the intensity of tropical cyclones (TCs) in the North Atlantic and northeastern and central Pacific basins is developed and tested. The algorithm is derived from Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) 85-GHz brightness temperatures and near-surface rain-rate retrievals to provide objective estimates of current maximum sustained surface winds (Vmax) and 6-h future Vmax of TCs. The full record of TRMM data (1998–2013) including 2326 TMI overpasses of 503 TCs is separated into dependent samples (1998–2010) for model development and independent samples (2011–13) for model verification. The best track intensities are used as dependent variables in a stepwise multiple-regression approach. Separately for each basin, three regression models are derived using selected 1) 85-GHz-only variables, 2) rain-rate-only variables, and 3) combined 85-GHz and rain variables. The algorithms are evaluated using independent samples and those with contemporaneous aircraft-reconnaissance measurements. Rain-only and combined models perform better than the 85-GHz-only model. Lower errors are found for estimating the 6-h future Vmax than estimating the current Vmax using all three models. This suggests that it is optimal to use passive-microwave-retrieved rain variables observed a few hours earlier to estimate TC intensity. The MAE (RMSE) of 6-h future Vmax is 9 (12) kt (1 kt ≈ 0.51 m s−1) when testing the combined models with ATL and EPA independent samples. Aircraft-reconnaissance-based independent samples yields a MAE of 9.6 kt and RMSE of 12.6 kt for estimating 6-h future Vmax.

Description: This paper describes the assumptions, equations, and procedures of the RheaG weather generator algorithm (WGA). RheaG was conceived for the generation of robust daily meteorological time series, whether in static or transient climate conditions. Here we analyze its performance in four Iberian locations—Bilbao, Barcelona, Madrid, and Sevilla—with differentiated climate characteristics. To validate the RheaG WGA, we compared observed and generated meteorological time series’ statistical properties of precipitation, maximum temperature, and minimum temperature for all four locations. We also compared observed and simulated rain events spell length probabilities in all four locations. Finally, RheaG includes two weather generation procedures: one in which monthly mean values for meteorological variables are unconstrained and one in which they are constrained according to a predefined baseline climate variability. Here, we compare the two weather generation procedures included in RheaG using the observed data from Barcelona. Our results present a high agreement in the statistical properties and the rain spell length probabilities between observed and generated meteorological time series. Our results show that RheaG accurately reproduces seasonal patterns of the observed meteorological time series for all four locations, and it is even able to differentiate two climatic seasons in Bilbao that are also present in the observed data. We find a trade-off between generation procedures in which the unconstrained procedure better reproduces the variability of monthly and yearly precipitation than the constrained one, but the constrained procedure is able to keep the same climatic signal across meteorological time series. Thus, the first procedure is more accurate, but the latter is able to maintain spatial autocorrelation among generated meteorological time series.

Description: Hail-bearing storms produce substantial socioeconomic impacts each year, yet challenges remain in forecasting the type of hail threat supported by a given environment and in using radar to estimate hail sizes more accurately. One class of hail threat is storms producing large accumulations of small hail (SPLASH). This paper presents an analysis of the environments and polarimetric radar characteristics of such storms. Thirteen SPLASH events were selected to encompass a broad range of geographic regions and times of year. Rapid Refresh model output was used to characterize the mesoscale environments associated with each case. This analysis reveals that a range of environments can support SPLASH cases; however, some commonalities included large precipitable water (exceeding that day’s climatological 90th-percentile values), CAPE 〈 2500 J kg−1, weak storm-relative wind speeds (17° km−1, the highest documented in precipitation at S band. Electromagnetic scattering calculations using the T-matrix method confirm that large quantities of small melting hail mixed with heavy rain can plausibly explain the observed radar signatures.

Description: In the western United States, water stored as mountain snowpack is a large percentage of the total water needed to meet the region’s demands, and it is likely that, as the planet continues to warm, mountain snowpack will decline. However, detecting such trends in the observational record is challenging because snowpack is highly variable in both space and time. Here, a method for characterizing mountain snowpack is developed that is based on fitting observed annual cycles of snow water equivalent (SWE) to a gamma-distribution probability density function. A new method for spatially interpolating the distribution’s fitting parameters to create a gridded climatology of SWE is also presented. Analysis of these data shows robust trends in the shape of the annual cycle of snowpack in the western United States. Over the 1982–2017 water years, the annual cycle of snowpack is becoming narrower and more Gaussian. A narrowing of the annual cycle corresponds to a shrinking of the length of the winter season, primarily because snowpack melting is commencing earlier in the water year. Because the annual cycle of snowpack at high elevations tends to be more skewed than at lower elevations, a more Gaussian shape suggests that snowpack is becoming more characteristic of that at lower elevations. Although no robust downward trends in annual-mean SWE are found, robust trends in the shape of the SWE annual cycle have implications for regional water resources.

Description: Use of the standard deviation σm of the drop mass distribution as one of the three parameters of raindrop size distribution (DSD) functions was introduced for application to disdrometer data supporting the Global Precipitation Measurement dual-frequency radar system. The other two parameters are a normalized drop number concentration Nw and the mass-weighted mean diameter Dm. This paper presents an evaluation of that formulation of the DSD functions, in two parts. First is a mathematical analysis showing that the procedure for estimating σm, along with the other DSD parameters, from disdrometer data is in essence another moment method. As such, it is subject to the biases and errors inherent in all moment methods. When the form of the DSD function is specified, it is inferior (like all moment methods) to the maximum likelihood technique for fitting parameters to sampled data. The second part is a series of sampling simulations illustrating the biases and errors involved in applying the formulation to the specific case of gamma DSDs. It leads to underestimates of σm and consequently to overestimates of the gamma shape parameter—with large root-mean-square errors. Comparison with maximum likelihood estimates shows the degree of improvement that could be obtained in the estimates of the shape parameter. The propensity to underestimate σm will be pervasive, and users of this DSD formulation should be cognizant of the biases and errors that can occur.

Description: A suite of modern atmospheric reanalyses is analyzed to determine how they represent North American supercell environments. This analysis is performed by comparing a database of Rapid Update Cycle (RUC-2) proximity soundings with profiles derived from the nearest grid point in each reanalysis. Parameters are calculated using the Sounding and Hodograph Analysis and Research Program in Python (SHARPpy), an open-source Python sounding-analysis package. Representation of supercell environments varies across the reanalyses, and the results have ramifications for climatological studies that use these datasets. In particular, thermodynamic parameters such as the convective available potential energy (CAPE) show the widest range in biases, with reanalyses falling into two camps. The North American Regional Reanalysis (NARR) and the Japanese 55-year Reanalysis (JRA-55) are similar to RUC-2, but other reanalyses have a substantial negative bias. The reasons for these biases vary and range from thermodynamic biases at the surface to evidence of convective contamination. Overall, it is found that thermodynamic biases feed back to other convective parameters that incorporate CAPE directly or indirectly via the effective layer. As a result, significant negative biases are found for indices such as the supercell composite parameter. These biases are smallest for NARR and JRA-55. Kinematic parameters are more consistent across the reanalyses. Given the issues with thermodynamic properties, better segregation of soundings by storm type is found for fixed-layer parameters than for effective-layer shear parameters. Although no reanalysis can exactly reproduce the results of earlier RUC-2 studies, many of the reanalyses can broadly distinguish between environments that are significantly tornadic versus nontornadic.

Description: There is growing interest in combining microphysical models and polarimetric radar observations to improve our understanding of storms and precipitation. Mapping model-predicted variables into the radar observational space necessitates a forward operator, which requires assumptions that introduce uncertainties into model–observation comparisons. These include uncertainties arising from the microphysics scheme a priori assumptions of a fixed drop size distribution (DSD) functional form, whereas natural DSDs display far greater variability. To address this concern, this study presents a moment-based polarimetric radar forward operator with no fundamental restrictions on the DSD form by linking radar observables to integrated DSD moments. The forward operator is built upon a dataset of 〉200 million realistic DSDs from one-dimensional bin microphysical rain-shaft simulations, and surface disdrometer measurements from around the world. This allows for a robust statistical assessment of forward operator uncertainty and quantification of the relationship between polarimetric radar observables and DSD moments. Comparison of “truth” and forward-simulated vertical profiles of the polarimetric radar variables are shown for bin simulations using a variety of moment combinations. Higher-order moments (especially those optimized for use with the polarimetric radar variables: the sixth and ninth) perform better than the lower-order moments (zeroth and third) typically predicted by many bulk microphysics schemes.

Description: This study aims to characterize the background physical processes in the development of those heavy precipitation clouds that contribute to the Tropical Rainfall Measuring Mission (TRMM) active and passive sensor differences. The combined global observation data from TRMM, CloudSat, and European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim) from 2006 to 2014 were utilized to address this issue. Heavy rainfall events were extracted from the top 10% of the rain events from the Precipitation Radar (PR) and TRMM Microwave Imager (TMI) rain-rate climatology. Composite analyses of CloudSat and ERA-Interim were conducted to identify the detailed cloud structures and the background environmental conditions. Over tropical land, TMI tends to preferentially detect deep isolated precipitation clouds for relatively drier and unstable environments, while PR identifies more organized systems. Over the tropical ocean, TMI identifies heavy rainfall events with notable convective organization and clear regional gradients between the western and eastern Pacific Ocean, while PR fails to capture the eastward shallowing of convective systems. The PR–TMI differences for the moist and stable environments are reversed over tropical land.

Description: Seasonal climate forecasts for an early warning of climate anomalies are produced by regional climate outlook forums (RCOF) worldwide. This study presents a verification of one of the earliest RCOF products, the precipitation outlook for the West African monsoon peak period (July–September). The basis of this outlook is countrywide precipitation forecasts from various statistical (downscaling) models, which are subjectively reinterpreted by experts on the basis of information from observed SST pattern analysis and global forecasts. The forecast quality was analyzed from 1998 to 2013 using a novel database of rain gauge measurements established for several West African countries, among other references. The analysis indicated skill for above normal and below normal on different spatial scales but also showed typical limitations of seasonal forecasting such as lack of sharpness and poor skill for near normal. A specific feature of the RCOF product is a strong overforecasting of near normal, very likely a result of the risk aversion of experts. To better illustrate the usefulness of the outlooks, they were evaluated with respect to a binary warning system by determining the maximum economic value Vmax. This verification indicated moderate valuable precipitation warnings for dry (Vmax = 0.39) and wet (Vmax = 0.34) years for four climatological zones (Sahel, Sudan–Sahel, Sudan, and Guinean) and five river basins (Volta, Senegal, and three Niger subbasins) but with strong regional differences (0.14 〈 Vmax 〈 0.54). The bootstrap analysis illustrated large uncertainties, indicating the relevance of uncertainty margins when seasonal forecast products with small sample sizes like RCOF outlooks are evaluated.

Description: To support the planning of future solar energy production in India, forthcoming changes in incoming surface solar radiation and the main physical factors contributing to the change were inferred from simulations performed with 27 global CMIP5 climate models. According to the multimodel-mean response, radiation diminishes by 0.5%–4% by the period 2030–59 (relative to 1971–2000), in tandem with strengthening aerosol and water vapor dimming. The largest reduction is anticipated for northern India. The evolution of incident radiation in the mid- and late twenty-first century depends substantially on the emission scenario. According to the representative concentration pathways RCP2.6 and RCP4.5, solar radiation would gradually recover close to the level that prevailed in the late twentieth century. This results from the peaking of aerosol loading before midcentury while the water vapor content continuously increases somewhat. Conversely, under RCP8.5, incident radiation would still decline, although more slowly than during the early century. This coincides with a substantial increase in atmospheric water vapor content and a modest decrease in aerosol forcing. In cloud forcing, multimodel-mean changes are minor, but divergence among the model simulations is substantial. Moreover, cloud forcing proved to be the factor that correlates most strongly with intermodel differences in the solar radiation response. Multimodel-mean changes in solar radiation are small and would not crucially affect the conditions of solar energy production. Nevertheless, some individual models simulate far more substantial reductions of up to ~10%.

Description: This study evaluates how well reanalyses represent daily and multiday accumulated precipitation (hereinafter daily PCP) over British Columbia, Canada (Part I evaluated 2-m temperature). Reanalyses are compared with observations from 66 meteorological stations distributed over the complex terrain of British Columbia, separated into climate regions by k-means clustering. Systematic error, two-sample χ2 statistic, and frequency of daily PCP occurrence are evaluated from the European Centre for Medium-Range Weather Forecasts (ECMWF) interim reanalysis (ERA-Interim), the Climate Forecast System Reanalysis (CFSR), the Japanese 55-year Reanalysis (JRA-55), and the latest Modern-Era Retrospective Analysis for Research and Applications (version 2; MERRA-2). The 2- and 30-yr return levels of daily PCP are estimated from a generalized extreme value (GEV) distribution fitted by the method of L moments, and their systematic errors are analyzed. JRA-55 and MERRA-2 generally outperform ERA-Interim and CFSR across all metrics. Biases are largely explained by poor reanalysis representation of terrain characteristics such as steepness, exposure, elevation, location of barriers, and wind speed and direction. Statistical stationarity of precipitation intensity and frequency over the 30-yr period is assessed by using confidence intervals and GEV distributions fitted with and without time-dependent parameters. It is determined that stationary distributions are sufficient to represent the climate of daily PCP for this region and time period.

Description: An objective mapping exercise simulating observations of temperature in the North Atlantic Ocean was used to assess the resolution capabilities of ocean acoustic tomography in combination with Argo floats. A set of basis functions for a basinwide area was obtained from a singular value decomposition of a covariance derived from an ocean state estimate. As demonstrated by the formal uncertainty estimates from the objective maps, Argo and tomography are complementary measurements. In several examples, each separately obtained uncertainty for determining large-scale monthly average temperature of about 50% of prior (resolved 75% of variance), while when both data were employed, uncertainties were reduced to about 25% of prior (resolved 94% of variance). Possible tomography configurations range from arrays that span specific regions to line arrays that supplement existing observations to arrays that span the Atlantic basin. A basinwide array consisting of two acoustic sources and seven receivers can be used to significantly reduce the uncertainties of estimated broad-scale temperature. An optimal observing system study would comprise simulated measurements in combination with data assimilation techniques and numerical ocean modeling. This objective map study, however, showed that the addition of tomography to the existing observing system could substantially reduce the uncertainties for estimated large-scale temperature. To the extent that tomography offers a 50% reduction in uncertainty at a fraction of the cost of the Argo program, it is a cost-effective contribution to the ocean observing system.

Description: A network of automated weather stations (AWS) with ceilometers can be used to detect sky conditions, aerosol dispersion, and mixing layer heights, in addition to the routine surface meteorological parameters (temperature, pressure, humidity, etc.). Currently, a dense network of AWSs that observe all of these parameters does not exist in the United States even though networks of them with ceilometers exist. These networks normally use ceilometers for determining only sky conditions. Updating AWS networks to obtain those nonstandard observations with ceilometers, especially mixing layer height, across the United States would provide valuable information for validating and improving weather/climate forecast models. In this respect, an aerosol-based mixing layer height detection method, called the combined-hybrid method, is developed and evaluated for its uncertainty characteristics for application in the United States. Four years of ceilometer data from the National Weather Service Ceilometer Proof of Concept Project taken in temperate, maritime polar, and hot/arid climate regimes are utilized in this evaluation. Overall, the method proved to be a strong candidate for estimating mixing layer heights with ceilometer data, with averaged uncertainties of 237 ± 398 m in all tested climate regimes and 69 ± 250 m when excluding the hot/arid climate regime.

Description: Data assimilation has been successfully used for meteorology for many years and is now used more and more for atmospheric composition issues (air quality analysis and forecast). The data assimilation of pollutants remains difficult and its deployment is currently in progress. It is thus difficult to have quantitative knowledge of what we can expect as the maximum benefit. In this study we propose a simple framework to make this quantification. In this first part, the gain of data assimilation is quantified using academic but realistic test cases over an urbanized polluted area and during a summertime period favorable to ozone formation. Different data assimilation configurations are tested, corresponding to different amounts of data available for assimilation. For ozone (O3) and nitrogen dioxide (NO2), it is shown that the benefit resulting from data assimilation lasts from a few hours to a possible maximum of 60 and 21 h, respectively. Maps of the number of hours are presented, spatializing the benefit of data assimilation.

Description: The stability and accuracy of weather radar reflectivity calibration are imperative for quantitative applications, such as rainfall estimation, severe weather monitoring and nowcasting, and assimilation in numerical weather prediction models. Various radar calibration and monitoring techniques have been developed, but only recently have integrated approaches been proposed, that is, using different calibration techniques in combination. In this paper the following three techniques are used: 1) ground clutter monitoring, 2) comparisons with spaceborne radars, and 3) the self-consistency of polarimetric variables. These techniques are applied to a C-band polarimetric radar (CPOL) located in the Australian tropics since 1998. The ground clutter monitoring technique is applied to each radar volumetric scan and provides a means to reliably detect changes in calibration, relative to a baseline. It is remarkably stable to within a standard deviation of 0.1 dB. To obtain an absolute calibration value, CPOL observations are compared to spaceborne radars on board TRMM and GPM using a volume-matching technique. Using an iterative procedure and stable calibration periods identified by the ground echoes technique, we improve the accuracy of this technique to about 1 dB. Finally, we review the self-consistency technique and constrain its assumptions using results from the hybrid TRMM–GPM and ground echo technique. Small changes in the self-consistency parameterization can lead to 5 dB of variation in the reflectivity calibration. We find that the drop-shape model of Brandes et al. with a standard deviation of the canting angle of 12° best matches our dataset.

Description: Strong in-cloud electric fields align ice particles that can be observed with polarization diversity radars. Radar data collected in the simultaneous transmission mode, wherein horizontally and vertically polarized waves are simultaneously transmitted and received (SHV), and in a mode whereby a single-polarization wave is transmitted and dual (orthogonal)-polarization waves are received simultaneously [linear depolarization (LDR) mode] are analyzed. The necessary time delay between the SHV and LDR modes for our radar was about 1–4 min. The data show that the areas of canted crystals from the LDR mode are larger than those from the SHV mode, thereby indicating that the LDR mode is more sensitive to canted ice cloud particles than the SHV mode. The data also demonstrate that the differential phase and correlation coefficient in the LDR mode are indicative of canted cloud crystals and that these variables often are more sensitive to canted crystals than the linear depolarization ratio studied earlier. Rapidly scanning radars such as those with a phased array antenna could operate sequentially in the SHV and LDR modes and thus better detect cloud volumes characterized by enhanced electric fields.

Description: Artificial neural networks (ANNs) applied to nonlinear wave ensemble averaging are developed and studied for Gulf of Mexico simulations. It is an approach that expands the conservative arithmetic ensemble mean (EM) from the NCEP Global Wave Ensemble Forecast System (GWES) to a nonlinear mapping that better captures the differences among the ensemble members and reduces the systematic and scatter errors of the forecasts. The ANNs have the 20 members of the GWES as input, and outputs are trained using observations from six buoys. The variables selected for the study are the 10-m wind speed (U10), significant wave height (Hs), and peak period (Tp) for the year of 2016. ANNs were built with one hidden layer using a hyperbolic tangent basis function. Several architectures with 12 different combinations of neurons, eight different filtering windows (time domain), and 100 seeds for the random initialization were studied and constructed for specific forecast days from 0 to 10. The results show that a small number of neurons are sufficient to reduce the bias, while 35–50 neurons produce the greatest reduction in both the scatter and systematic errors. The main advantage of the methodology using ANNs is not on short-range forecasts but at longer forecast ranges beyond 4 days. The nonlinear ensemble averaging using ANNs was able to improve the correlation coefficient on forecast day 10 from 0.39 to 0.61 for U10, from 0.50 to 0.76 for Hs, and from 0.38 to 0.63 for Tp, representing a gain of five forecast days when compared to the EM currently implemented.

Description: A nonlinear empirical method, called the generalized regression neural network with the fruit fly optimization algorithm (FOAGRNN), is proposed to estimate subsurface salinity profiles from sea surface parameters in the Pacific Ocean. The purpose is to evaluate the ability of the FOAGRNN methodology and satellite salinity data to reconstruct salinity profiles. Compared with linear methodology, the estimated salinity profiles from the FOAGRNN method are in better agreement with the measured profiles at the halocline. Sensitivity studies of the FOAGRNN estimation model shows that, when applied to various types of sea surface parameters, latitude is the most significant variable in estimating salinity profiles in the tropical Pacific Ocean (correlation coefficient R greater than 0.9). In comparison, sea surface temperature (SST) and height (SSH) have minimal effects on the model. Based on FOAGRNN modeling, Pacific Ocean three-dimensional salinity fields are estimated for the year 2014 from remote sensing sea surface salinity (SSS) data. The performance of the satellite-based salinity field results and possible sources of error associated with the estimation methodology are briefly discussed. These results suggest a potential new approach for salinity profile estimation derived from sea surface data. In addition, the potential utilization of satellite SSS data is discussed.

Description: The Wire Flyer towed vehicle is a new platform able to collect high-resolution water column sections. The vehicle is motivated by a desire to effectively capture spatial structures at the submesoscale. The vehicle fills a niche that is not achieved by other existing towed and repeat profiling systems. The Wire Flyer profiles up and down along a ship-towed cable autonomously using controllable wings for propulsion. At ship speeds between 2 and 5 kt (1.02–2.55 m s−1), the vehicle is able to profile over prescribed depth bands down to 1000 m. The vehicle carries sensors for conductivity, temperature, depth, oxygen, turbidity, chlorophyll, pH, and oxidation reduction potential. During normal operations the vehicle is typically commanded to cover vertical regions between 300 and 400 m in height with profiles that repeat at kilometer spacing. The vertical profiling speed can be user specified up to 150 m min−1. The high-density sampling capability at depths below the upper few hundred meters makes the vehicle distinct from other systems. During operations an acoustic modem is used to communicate with the vehicle to provide status information, data samples, and the ability to modify the sampling pattern. This paper provides an overview of the vehicle system, describes its operation, and presents results from several cruises.

Description: Atmospheric gravity waves are a kind of mesoscale disturbance, commonly found in the atmospheric system, that plays a key role in a series of mesospheric dynamic processes. When propagating to the upper atmosphere, the gravity waves will disturb the local temperature and density, and then modulate the intensity of the surrounding airglow radiation. As a result, the presence of gravity waves on a moonless night can usually cause the airglow to reveal ripple features in low-light images. In this paper we have applied a two-dimensional Stockwell transform technique (2DST) to airglow measurements from nighttime low-light images of the day–night band on the Suomi National Polar-Orbiting Partnership. To our knowledge this study is the first to measure localized mesospheric gravity wave brightness amplitudes, horizontal wavelengths, and propagation directions using such a method and data. We find that the method can characterize the general shape and amplitude of concentric gravity wave patterns, capturing the dominant features and directions with a good degree of accuracy. The key strength of our 2DST application is that our approach could be tuned and then automated in the future to process tens of thousands of low-light images, globally characterizing gravity wave parameters in this historically poorly studied layer of the atmosphere.

Description: Instantaneous liquid-equivalent snowfall rates S retrieved from CloudSat W-band cloud radar reflectivity Ze measurements are compared to estimates of S from operational Weather Surveillance Radar-1988 Doppler (WSR-88D) systems when the CloudSat satellite overflew the ground-based radar sites during spatially extensive nimbostratus snowfall events. For these comparisons, the ground-based radar measurements are interpolated to closely match in space and time spaceborne radar resolution volumes above ground clutter, thus avoiding uncertainties in deriving near-surface snowfall rates from measurements aloft by both radar types. Although typical uncertainties of both ground-based and spaceborne snowfall-rate retrieval approaches are quite high, the results from the standard optimal estimation CloudSat 2C-SNOW-PROFILE algorithm are on average in good agreement with the WSR-88D default snowfall algorithm results with correlation coefficients being around 0.8–0.85. The CloudSat standard optimal estimation snowfall-rate products are also shown to be in satisfactory agreement with retrievals from several simple W-band Ze–S relations suggested earlier. The snowfall rate and snow/ice water content (IWC) parameters from the CloudSat 2C-SNOW-PROFILE algorithm are highly interdependent. A tight relation between S and IWC is apparently introduced through the ice particle fall velocity assumption that is made in the reflectivity-based snowfall retrieval algorithm. This suggests that ice sedimentation rate estimates can also be deduced from applications of numerous empirical IWC–reflectivity relations derived previously for different cloud conditions when appropriate assumptions about fall velocities are made. Intercomparisons between different CloudSat snow/ice water content products indicated significant discrepancies in IWC values from different standard CloudSat retrieval algorithms.

Description: The ability to quickly and accurately model actual atmospheric conditions is essential to remote sensing analyses. Clouds present a particularly complex challenge, as they cover up to 70% of Earth’s surface, and their highly variable and diverse nature necessitates physics-based modeling. The Laser Environmental Effects Definition and Reference (LEEDR) is a verified and validated atmospheric propagation and radiative transfer code that creates physically realizable vertical and horizontal profiles of meteorological data. Coupled with numerical weather prediction (NWP) model output, LEEDR enables analysis, nowcasts, and forecasts for radiative effects expected for real-world scenarios. A recent development is the inclusion of the U.S. Air Force’s World-Wide Merged Cloud Analysis (WWMCA) cloud data in a new tool set that enables radiance calculations through clouds from UV to radio frequency (RF) wavelengths. This effort details the creation of near-real-time profiles of atmospheric and cloud conditions and the resulting radiative transfer analysis for virtually any wavelength(s) of interest. Calendar year 2015 data are analyzed to establish climatological limits for diffuse transmission in the 300–1300-nm band, and the impacts of various geometry, cloud microphysical, and atmospheric conditions are examined. The results show that 80% of diffuse band transmissions are estimated to fall between 0.248 and 0.889 under the assumptions of cloud homogeneity and maximum overlap and are sufficient for establishing diffuse transmission percentiles. The demonstrated capability provides an efficient way to extend optical wavelength cloud parameters across the spectrum for physics-based multiple-scattering effects modeling through cloudy and clear atmospheres, providing an improvement to atmospheric correction for remote sensing and cloud effects on system performance metrics.

Description: Doppler sodar is a technology used for acoustic-based remote sensing of the lower planetary boundary layer. Sodars are often used to measure wind profiles; however, they suffer from problems caused by noise (both acoustic and electrical) and echoes from fixed objects, which can bias radial velocity estimates. An experimental bistatic sodar was developed with 64 independent channels. The device enables flexible beamforming; beams can be tilted at the same angle irrelevant of frequency, a limitation in most commercial devices. This paper presents an alternative sodar signal-processing algorithm for wind profiling using a multifrequency stepped-chirp pulse. A noncoherent matched filter was used to analyze returned signals. The noncoherent matched filter combines radial velocity estimates from multiple frequencies into a single optimization. To identify and separate sources of backscatter, noise, and fixed echoes, a stochastic pattern-recognition technique, Gaussian mixture modeling, was used to postprocess the noncoherent matched filter data. This method allowed the identification and separation of different stochastic processes. After identification, noise and fixed echo components were removed and a clean wind profile was produced. This technique was compared with traditional spectrum-based radial velocity estimation methods, and an improvement in the rejection of fixed echo components was demonstrated; this is one of the major limitations of sodar performance when located in complex terrain and urban environments.

Description: Thunderstorms that produce surface hail accumulations, sometimes as large as 60 cm in depth, have significantly affected the residents of the Front Range and High Plains of Colorado and Wyoming by creating hazardous road conditions and endangering lives and property. To date, surface hail accumulation is not part of a routine forecasting or monitoring system. Extensive coordinated hail accumulation reports and operational products designed to identify deep hail accumulating storms in real time are lacking. Kalina et al. used dual-polarization WSR-88D radar observations to calculate hail depth and hail accumulations but never validated the algorithm. This study shows how 20 quality-controlled hail depth reports from the hail depth database built by the Colorado Hail Accumulation from Thunderstorms (CHAT) project are being used to validate the Kalina et al. radar-based hail accumulation algorithm for operational application. The validated algorithm shows increased correlations between radar-derived and reported accumulations for hail depth reports not included in the validation. Furthermore, increases in computational efficiency have allowed the improved algorithm to be used operationally. With an improved hail accumulation algorithm, thunderstorms that produce hail accumulations are more frequently detected than previously reported.

Description: Four different versions of the HAILCAST hail model have been tested as part of the 2014–16 NOAA Hazardous Weather Testbed (HWT) Spring Forecasting Experiments. HAILCAST was run as part of the National Severe Storms Laboratory (NSSL) WRF Ensemble during 2014–16 and the Community Leveraged Unified Ensemble (CLUE) in 2016. Objective verification using the Multi-Radar Multi-Sensor maximum expected size of hail (MRMS MESH) product was conducted using both object-based and neighborhood grid-based verification. Subjective verification and feedback was provided by HWT participants. Hourly maximum storm surrogate fields at a variety of thresholds and Storm Prediction Center (SPC) convective outlooks were also evaluated for comparison. HAILCAST was found to improve with each version due to feedback from the 2014–16 HWTs. The 2016 version of HAILCAST was equivalent to or exceeded the skill of the tested storm surrogates across a variety of thresholds. The post-2016 version of HAILCAST was found to improve 50-mm hail forecasts through object-based verification, but 25-mm hail forecasting ability declined as measured through neighborhood grid-based verification. The skill of the storm surrogate fields varied widely as the threshold values used to determine hail size were varied. HAILCAST was found not to require such tuning, as it produced consistent results even when used across different model configurations and horizontal grid spacings. Additionally, different storm surrogate fields performed at varying levels of skill when forecasting 25- versus 50-mm hail, hinting at the different convective modes typically associated with small versus large sizes of hail. HAILCAST was able to match results relatively consistently with the best-performing storm surrogate field across multiple hail size thresholds.

Description: Probabilistic ensemble-derived tornado forecasts generated from convection-allowing models often use hourly maximum updraft helicity (UH) alone or in combination with environmental parameters as a proxy for right-moving (RM) supercells. However, when UH occurrence is a condition for tornado probability generation, false alarm areas can occur from UH swaths associated with nocturnal mesoscale convective systems, which climatologically produce fewer tornadoes than RM supercells. This study incorporates UH timing information with the forecast near-storm significant tornado parameter (STP) to calibrate the forecast tornado probability. To generate the probabilistic forecasts, three sets of observed climatological tornado frequencies given an RM supercell and STP value are incorporated with the model output, two of which use UH timing information. One method uses the observed climatological tornado frequency for a given 3-h window to generate the probabilities. Another normalizes the observed climatological tornado frequency by the number of hail, wind, and tornado reports observed in that 3-h window compared to the maximum number of reports in any 3-h window. The final method is independent of when UH occurs and uses the observed climatological tornado frequency encompassing all hours. The normalized probabilities reduce the false alarm area compared to the other methods but have a smaller area under the ROC curve and require a much higher percentile of the STP distribution to be used in probability generation to become reliable. Case studies demonstrate that the normalized probabilities highlight the most likely area for evening RM supercellular tornadoes, decreasing the nocturnal false alarm by assuming a linear convective mode.

Description: We developed an approach for estimating river discharge and water depth from measurements of surface velocity and water surface elevation, based on analytical velocity–depth and velocity–slope relationships derived from the steady gravity–friction momentum balance and mass conservation. A key component in this approach is specifying the influence of bottom friction on the modeled depth-averaged flow. Accordingly, we considered two commonly used bottom friction parameterizations—a depth-independent Darcy friction coefficient and a depth-dependent friction coefficient based on the Manning’s roughness parameter. Assuming that the bottom friction coefficient is known, the unknown discharge was determined by minimizing the difference between the measured total head profile and the one determined from the velocity–slope relationship. The model performance and its sensitivity to key assumptions were evaluated using existing bathymetry data, and surface velocity and elevation observations obtained during field experiments on the Kootenai River near Bonners Ferry, Idaho, and the Hanford reach of the Columbia River. We found that the Manning’s friction parameterization provided superior depth and discharge estimates, compared to the Darcy friction law. For both steady and moderately unsteady flow, inversions based on the Manning’s friction provided discharge and thalweg depth estimates with relative errors not exceeding 5% and 12%, respectively.

Description: Spread and skill of mixed- and single-physics convection-allowing ensemble forecasts that share the same set of perturbed initial and lateral boundary conditions are investigated at a variety of spatial scales. Forecast spread is assessed for 2-m temperature, 2-m dewpoint, 500-hPa geopotential height, and hourly accumulated precipitation both before and after a bias-correction procedure is applied. Time series indicate that the mixed-physics ensemble forecasts generally have greater variance than comparable single-physics forecasts. While the differences tend to be small, they are greatest at the smallest spatial scales and when the ensembles are not calibrated for bias. Although differences between the mixed- and single-physics ensemble variances are smaller for the larger spatial scales, variance ratios suggest that the mixed-physics ensemble generates more spread relative to the single-physics ensemble at larger spatial scales. Forecast skill is evaluated for 2-m temperature, dewpoint temperature, and bias-corrected 6-h accumulated precipitation. The mixed-physics ensemble generally has lower 2-m temperature and dewpoint root-mean-square error (RMSE) compared to the single-physics ensemble. However, little difference in skill or reliability is found between the mixed- and single-physics bias-corrected precipitation forecasts. Overall, given that mixed- and single-physics ensembles have similar spread and skill, developers may prefer to implement single- as opposed to mixed-physics convection-allowing ensembles in future operational systems, while accounting for model error using stochastic methods.

Description: Wind warnings are the second-most-frequent advisory issued by the U.S. Air Force’s 45th Weather Squadron (45WS) at Cape Canaveral, Florida. Given the challenges associated with nowcasting convection in Florida during the warm season, improvements in 45WS warnings for convective wind events are desired. This study aims to explore the physical bases of dual-polarization radar signatures within wet downbursts around Cape Canaveral and identify signatures that may assist the 45WS during real-time convective wind nowcasting. Data from the 45WS’s C-band dual-polarization radar were subjectively analyzed within an environmental context, with quantitative wind measurements recorded by weather tower sensors for 32 threshold-level downbursts with near-surface winds ≥ 35 kt (1 kt ≈ 0.51 m s−1) and 32 null downbursts. Five radar signatures were identified in threshold-level downburst-producing storms: peak height of 1-dB differential reflectivity ZDR column, peak height of precipitation ice signature, peak reflectivity, height below 0°C level where ZDR increases to 3 dB within a descending reflectivity core (DRC), and vertical ZDR gradient within DRC. Examining these signatures directly in updraft–downdraft cycles that produced threshold-level winds yielded mean lead times of 20.0–28.2 min for cumulus and mature stage signatures and 12.8–14.9 min for dissipating stage signatures, with higher signature test values generally yielding higher skill scores. A conceptual test of utilizing signatures within earlier cells in multicell storms to indirectly predict the potential for intense downbursts in later cells was performed, which offered increased lead times and skill scores for an Eulerian forecast region downstream from the storm initiation location.

Description: The National Centers for Environmental Prediction have generated an 18-yr (1999–2016) subseasonal (weeks 3 and 4) reforecast to support the Climate Prediction Center’s operational mission. To create this reforecast, the subseasonal experiment version of the GEFS was run every Wednesday, initialized at 0000 UTC with 11 members. The Climate Forecast System Reanalysis (CFSR) and Global Data Assimilation System (GDAS) served as the initial analyses for 1999–2010 and 2011–16, respectively. The analysis of 2-m temperature error demonstrates that the model has a strong warm bias over the Northern Hemisphere (NH) and North America (NA) during the warm season. During the boreal winter, the 2-m temperature errors over NA exhibit large interannual and intraseasonal variability. For NA and the NH, weeks 3 and 4 errors are mostly saturated, with initial conditions having a negligible impact. Week 2 errors (day 11) are ~88.6% and 86.6% of their saturated levels, respectively. The 1999–2015 reforecast biases were used to calibrate the 2-m temperature forecasts in 2016, which reduces (increases) the systematic error (forecast skill) for NA, the NH, the Southern Hemisphere, and the tropics, with a maximum benefit for NA during the warm season. Overall, analysis adjustment for the CFSR period makes bias characteristics more consistent with the GDAS period over the NH and tropics and substantially improves the corresponding forecast skill levels. The calibration of the forecast using week 2 bias provides similar skill to using weeks 3 and 4 bias, promising the feasibility of using week 2 bias to calibrate the weeks 3 and 4 forecast. Our results also demonstrate that 10-yr reforecasts are an optimal training period. This is particularly beneficial considering limited computing resources.

Description: Under the National Monsoon Mission Project initiated by the government of India’s Ministry of Earth Sciences, an indigenous dynamical ensemble prediction system (EPS) has been developed at the Indian Institute of Tropical Meteorology based on the state-of-the-art Climate Forecast System Model version 2 (CFSv2) coupled model, for extended-range (~15–20 days in advance) prediction. The forecasts are generated for the entire year covering the southwest monsoon, the northeast monsoon, and the summer and winter seasons. As the forecast of rainfall is important during the southwest and northeast monsoon seasons, along with that of the temperature during the summer and winter seasons, the present study documents the deterministic as well as probabilistic skill of the EPS in predicting the results in the respective seasons, over various meteorological subdivisions throughout India, on a pentad-lead time scale. The EPS is found to be skillful in predicting rainfall during the southwest and northeast monsoon seasons, as well as temperature during the summer and winter seasons, across different subdivisions of India. In addition, the EPS is noted to be skillful in predicting selected extremes in rainfall and temperature. This affirms the reliability and usefulness of the present EPS from an operational perspective.

Description: This study assesses the skill of multimodel forecasts of 10-m wind speed, significant wave height, and mean wave period in the North Atlantic for the winter months. The 10-m winds from four North American multimodel ensemble models and three European Multimodel Seasonal-to-Interannual Prediction project (EUROSIP) models are used to force WAVEWATCH III experiments. Ten ensembles are used for each model. All three variables can be predicted using December initial conditions. The spatial maps of rank probability skill score are explained by the impact of the North Atlantic Oscillation (NAO) on the large-scale wind–wave relationship. Two winter case studies are investigated to understand the relationship between large-scale environmental conditions such as sea surface temperature, geopotential height at 500 hPa, and zonal wind at 200 hPa to the NAO and the wind–wave climate. The very strong negative NAO in 2008/09 was not well forecast by any of the ensembles while most models correctly predicted the sign of the event. This led to a poor forecast of the surface wind and waves. A Monte Carlo model combination analysis is applied to understand how many models are needed for a skillful multimodel forecast. While the grand multimodel ensemble provides robust skill, in some cases skill improves once some models are not included.

Description: Because of the perceived weather sensitivity of park visitation in Ontario, Canada, several previous assessments have examined the impact of climate change. However, these assessments have predominantly been based on modeling approaches (regression analysis). The current study uses a multiyear temporal climate-analog approach to reassess the impact of climate change on visitation to Pinery Provincial Park in southwestern Ontario based on the observed effects of historical climatic anomalies on park visitation from 2000 to 2016. Consideration was also given to major events such as the North American terror attacks on 11 September 2001 and the confounding effect that events such as this may have had on the results. There were no statistically significant relationships (at the 95% confidence level) between seasonal climatic anomalies and park visitation in Ontario during the winter or spring seasons. There was a weak statistical relationship between anomalously warm summer seasons and park visitation, when compared to summer seasons with climatically normal temperatures; however, the presence of nonclimatic variables may have confounded these results, producing a false positive. Autumn-season park visitation was most sensitive to climatic anomalies, with the warmest temperatures causing visitation to increase by 37%, the wettest conditions causing visitation to decrease by 11%, and the driest conditions resulting in a 24% increase. These observed seasonal temperature anomalies represent temporal climate analogs for projected climate change across the span of the twenty-first century. Thus, the results of this study suggest that previous assessments may have overestimated the positive impacts of projected climate change on park visitation in this region.

Description: In 2016, an exceptional drought and subsequent wildfires devastated the southeastern United States. Western North Carolina (WNC), a socioeconomically growing region that is dependent on revenue from tourism and agriculture, was particularly impacted by the events. The Southeast is not typically considered to be water vulnerable, and few studies have explored drought and wildfire in WNC. However, the region is projected to experience elevated water vulnerability as a result of rapid population growth and increased climatic variability. The recent events highlight the need for better understanding of water-related experiences and perceptions to inform proactive policies for risk mitigation in WNC. To evaluate stakeholder experiences and perceptions relating to the events in 2016, the authors conducted telephone interviews with key informants from a variety of sectors in two counties (Buncombe and Watauga) and then subjected their responses to content analysis. Informants frequently discussed themes relating to the “Natural Resources and Environment” code group, with responses revealing concerns about the health effects of smoke exposure, as well as water quantity. Other common topics of discussion for informants include water management, public awareness, and disaster severity. The prevalence of other themes varied by county, demonstrating the importance of local context. Surprisingly, informants rarely discussed risk in the context of increasing population and development, suggesting that current policies may inadequately address future risks. Stakeholders across all sectors placed substantial emphasis on information dissemination both within agencies and to the public. With a better understanding of key-informant experiences and perceptions, policymakers will be better equipped to address policy shortcomings as well as to prepare for future hazards.

Description: We summarize the potential nature and scope of economic effects of climate change in Alaska that have already occurred and are likely to become manifest over the next 30–50 years. We classified potential effects discussed in the literature into categories according to climate driver, type of environmental service affected, certainty and timing of the effects, and potential magnitude of economic consequences. We then described the nature of important economic effects and provided estimates of larger, more certain effects for which data were available. Largest economic effects were associated with costs to prevent damage, relocate, and replace infrastructure threatened by permafrost thaw, sea level rise, and coastal erosion. The costs to infrastructure were offset by a large projected reduction in space heating costs attributable to milder winters. Overall, we estimated that five relatively certain, large effects that could be readily quantified would impose an annual net cost of $340–$700 million, or 0.6%–1.3% of Alaska’s GDP. This significant, but relatively modest, net economic effect for Alaska as a whole obscures large regional disparities, as rural communities face large projected costs while more southerly urban residents experience net gains.

Description: Hurricane Irma was one of the strongest Atlantic hurricanes in history before landfall and caused a large evacuation. A total of 155 evacuees at interstate rest areas were asked to rank their concern about damage at their residence for six different geophysical hurricane hazards. Additionally, they were asked about their perceived maximum wind speeds (PMWS) and the wind speeds at which they thought damage would occur (DW) at their residence. These wind speeds were then compared to the actual peak wind gusts (APG) nearest to each resident’s location. Results show a significantly greater concern for wind and storm size, compared to other hazards (tornadoes, rainfall/flooding, storm surge, falling trees). The mean PMWS of evacuees was greater than the mean APG, suggesting widespread misperception of wind speeds. Furthermore, the mean APG was less than the mean DW, and the mean PMWS was also higher than the DW. Additional tests found no significant differences in wind perception between residents with previous storm experiences and no experience, and no significant differences between those who resided in mandatory evacuation zip codes and those who did not. These results suggest that wind speed risk is poorly understood, even though it is a high concern for evacuees from hurricanes. The communication of wind speed risk in forecasts should possibly be modified by placing greater emphasis on postlandfall impacts, wind speed decay after landfall, and wind speeds that cause damage to different types of residences.

Description: We investigate the role of moisture transport and recycling in characterizing two recent drought events in Texas (2011) and the Upper Midwest (2012) by analyzing the precipitation, evapotranspiration, precipitable water, and soil moisture data from the Climate Forecast System version 2 (CFSv2) analysis. Next, we evaluate the CFSv2 forecasts in terms of their ability to capture different drought signals as reflected in the analysis data. Precipitation from both sources is partitioned into recycled and advected components using a moisture accounting–based precipitation recycling model. All four variables reflected drought signals through their anomalously low values, while precipitation and evapotranspiration had the strongest signals. Drought in Texas was dominated by the differences in moisture transport, whereas in the Upper Midwest, the absence of strong precipitation-generating mechanisms was a crucial factor. Reduced advection from the tropical and midlatitude Atlantic contributed to the drought in Texas. The Upper Midwest experienced reduced contributions from recycling, terrestrial sources, the midlatitude Pacific, and the tropical Atlantic. In both cases, long-range moisture transport from oceanic sources was reduced during the corresponding drought years. June and August in Texas and July and August in the Upper Midwest were the driest months, and in both cases, drought was alleviated by the end of August. Moisture from terrestrial sources most likely contributed to alleviating drought intensity in such conditions, even with negative anomalies. The forecasts showed noticeable differences as compared to the analysis for multiple variables in both regions, which could be attributed to several factors as discussed in this paper.

Description: In this study, near-surface snow and graupel dynamics from formation to deposition are analyzed using WRF in a large-eddy configuration. The results reveal that a horizontal grid spacing of ≤50 m is required to resolve local orographic precipitation enhancement, leeside flow separation, and thereby preferential deposition. At this resolution, precipitation patterns across mountain ridges show a high temporal and spatial variability. Simulated and observed event-mean snow precipitation across three mountain ridges in the upper Dischma valley (Davos, Switzerland) for two precipitation events show distinct patterns, which are in agreement with theoretical concepts, such as small-scale orographic precipitation enhancement or preferential deposition. We found for our case study that overall terrain–flow–precipitation interactions increase snow accumulation on the leeward side of mountain ridges by approximately 26%–28% with respect to snow accumulation on the windward side of the ridge. Cloud dynamics and mean advection may locally increase precipitation on the leeward side of the ridge by up to about 20% with respect to event-mean precipitation across a mountain ridge. Analogously, near-surface particle–flow interactions, that is, preferential deposition, may locally enhance leeward snow precipitation on the order of 10%. We further found that overall effect and relative importance of terrain–flow–precipitation interactions are strongly dependent on atmospheric humidity and stability. Weak dynamic stability is important for graupel production, which is an essential component of solid winter precipitation. A comparison to smoothed measurements of snow depth change reveals a certain agreement with simulated precipitation across mountain ridges.

Description: Of the boundary conditions that affect the simulation of convective precipitation, soil moisture is one of the most important. In this study, we explore the impact of the soil moisture on convective precipitation, and factors affecting it, through an extensive numerical experiment based on four convective precipitation events that caused moderate to severe flooding in the Gard region of southern France. High-spatial-resolution (1 km) weather simulations were performed using the integrated atmospheric model Regional Atmospheric Modeling System/Integrated Community Limited Area Modeling System (RAMS/ICLAMS). The experimental framework included comparative analysis of five simulation scenarios for each event, in which we varied the magnitude and spatial distribution of the initial volumetric water content using realistic soil moisture fields with different spatial resolution. We used precipitation and surface soil moisture from radar and satellite sensors as references for the comparison of the sensitivity tests. Our results elucidate the complexity of the relationship between soil moisture and convective precipitation, showing that the control of soil water content on partitioning land surface heat fluxes has significant impacts on convective precipitation. Additionally, it is shown how different soil moisture conditions affect the modeled microphysical structure of the clouds, which translates into further changes in the magnitude and distribution of precipitation.

Description: Spatial coherency in atmospheric water vapor and rainfall and their association have been studied over the Indian subcontinent utilizing high spatiotemporal resolution data. Total column water vapor (TCWV) values derived from the Indian National Satellite (INSAT) system series (INSAT-3D) are first evaluated against data from an International GNSS Service (IGS) GPS receiver at Bangalore and the Global Precipitation Measurement Microwave Imager (GMI). The bias, correlation coefficient, and RMSE of TCWV between INSAT-3D and GMI show that, except for the south Bay of Bengal, the datasets compare well. The seasonal mean TCWV shows large values with lower standard deviation during the southwest monsoon (SWM) than in the northeast monsoon (NEM). Different temporal scales that contribute to the TCWV variance at a given point are quantified, and the variability due to 30–60-day oscillations is found to be dominant during both the monsoon seasons. TCWV and rainfall show good correspondence over the whole Indian subcontinent during both monsoon seasons except over the Arabian Sea and southern Myanmar regions, where large TCWV values show less rainfall during the SWM. On the whole, the spatial homogeneity and intergrid correlations in TCWV and rainfall are higher in NEM than in SWM. The decorrelation distance d0 for TCWV is found to be 10 times larger than that for rainfall, indicating that the rainfall homogeneity is generally limited to smaller areas. The large d0 values of TCWV are mainly due to the occurrence of source and sink processes at large spatial scales over those regions.

Description: This study presents a gridded meteorology intercomparison using the State of Hawaii as a testbed. This is motivated by the goal to provide the broad user community with knowledge of interproduct differences and the reasons differences exist. More generally, the challenge of generating station-based gridded meteorological surfaces and the difficulties in attributing interproduct differences to specific methodological decisions are demonstrated. Hawaii is a useful testbed because it is traditionally underserved, yet meteorologically interesting and complex. In addition, several climatological and daily gridded meteorology datasets are now available, which are used extensively by the applications modeling community, thus an intercomparison enhances Hawaiian specific capabilities. We compare PRISM climatology and three daily datasets: new datasets from the University of Hawai‘i and the National Center for Atmospheric Research, and Daymet version 3 for precipitation and temperature variables only. General conclusions that have emerged are 1) differences in input station data significantly influence the product differences, 2) explicit prediction of precipitation occurrence is crucial across multiple metrics, and 3) attribution of differences to specific methodological choices is difficult and limits the usefulness of intercomparisons. Because generating gridded meteorological fields is an elaborate process with many methodological choices interacting in complex ways, future work should 1) develop modular frameworks that allows users to easily examine the breadth of methodological choices, 2) collate available nontraditional high-quality observational datasets for true out-of-sample validation and make them publicly available, and 3) define benchmarks of acceptable performance for methodological components and products.

Description: The public debate around climate change is increasingly polarized. At the same time, the scientific consensus about the causes and consequences of climate change is strong. This inconsistency poses challenges for mitigation and adaptation efforts. The translation of uncertain numerical climate projections into simpler but ambiguous verbal frames may contribute to this polarization. In two experimental studies, we investigated 1) how “communicators” verbally frame a confidence interval regarding projected change in winter precipitation due to climate change (N = 512) and 2) how “listeners” interpret these verbal frames (N = 385). Both studies were preregistered at the Open Science Framework. Communicators who perceived the change as more severe chose a concerned rather than an unconcerned verbal frame. Furthermore, communicators’ verbal frames were associated with their more general beliefs, like political affiliation and environmental values. Listeners exposed to the concerned frame perceived climate change–induced precipitation change to be more severe than those receiving the unconcerned frame. These results are in line with two pilot studies (N = 298 and N = 393, respectively). Underlying general beliefs about climate and the environment likely shape public communication about climate in subtle ways, and thus verbal framing by the media, policymakers, and peers may contribute to public polarization on climate change.

Description: In the past few decades, there have been more extreme climate events occurring worldwide, including Canada, which has also suffered from many extreme precipitation events. In this paper, trend analysis, probability distribution functions, principal component analysis, and wavelet analysis were used to investigate the spatial and temporal patterns of extreme precipitation events of Canada. Ten extreme precipitation indices were calculated using long-term daily precipitation data (1950–2012) from 164 Canadian gauging stations. Several large-scale climate patterns such as El Niño–Southern Oscillation (ENSO), Pacific decadal oscillation (PDO), Pacific–North American (PNA), and North Atlantic Oscillation (NAO) were selected to analyze the relationships between extreme precipitation and climate indices. Convective available potential energy (CAPE), specific humidity, and surface temperature were employed to investigate potential causes of trends in extreme precipitation. The results reveal statistically significant positive trends for most extreme precipitation indices, which means that extreme precipitation of Canada has generally become more severe since the mid-twentieth century. The majority of indices display more increasing trends along the southern border of Canada while decreasing trends dominated the central Canadian Prairies. In addition, strong teleconnections are found between extreme precipitation and climate indices, but the effects of climate patterns differ from region to region. Furthermore, complex interactions of climate patterns with synoptic atmospheric circulations can also affect precipitation variability, and changes to the summer and winter extreme precipitation could be explained more by the thermodynamic impact and the combined thermodynamic and dynamic effects, respectively. The seasonal CAPE, specific humidity, and temperature are correlated to Canadian extreme precipitation, but the correlations are season dependent, which could be positive or negative.

Description: Data assimilation (DA) techniques have been widely applied to assimilate satellite-based soil moisture (SM) measurements into hydrologic models to improve streamflow simulations. However, past studies have reached mixed conclusions regarding the degree of runoff improvement achieved via SM state updating. In this study, a synthetic diagnostic framework is designed to 1) decompose the random error components in a hydrologic simulation, 2) quantify the error terms that originate from SM states, and 3) assess the effectiveness of SM DA to correct these random errors. The general framework is illustrated through a case study in which surface Soil Moisture Active Passive (SMAP) data are assimilated into a large-scale land surface model in the Arkansas–Red River basin. The case study includes systematic error in the simulated streamflow that imposes a first-order limit on DA performance. In addition, about 60% of the random runoff error originates directly from rainfall and cannot be corrected by SM DA. In particular, fast-response runoff dominates in much of the basin but is relatively unresponsive to state updating. Slow-response runoff is strongly controlled by the bottom-layer SM and therefore only modestly improved via the assimilation of surface measurements. Combined, the total runoff improvement in the synthetic analysis is small (

Description: This article analyzes SST remote forcing on the interannual variability of Sahel summer (June–September) moderate (below 75th percentile) and heavy (above 75th percentile) daily precipitation events during the period 1981–2016. Evidence is given that interannual variability of these events is markedly different. The occurrence of moderate daily rainfall events appears to be enhanced by positive SST anomalies over the tropical North Atlantic and Mediterranean, which act to increase low-level moisture advection toward the Sahel from the equatorial and north tropical Atlantic (the opposite holds for negative SSTs anomalies). In contrast, heavy and extreme daily rainfall events seem to be linked to El Niño–Southern Oscillation (ENSO) and Mediterranean variability. Under La Niña conditions and a warmer Mediterranean, vertical atmospheric instability is increased over the Sahel and low-level moisture supply from the equatorial Atlantic is enhanced over the area (the reverse is found for opposite-sign SST anomalies). Further evidence suggests that interannual variability of Sahel rainfall is mainly dominated by the extreme events. These results have implications for seasonal forecasting of Sahel moderate and heavy precipitation events based on SST predictors, as significant predictability is found from 1 to 4 months in advance.

Description: Hydrological forecasts with a high temporal and spatial resolution are required to provide the level of information needed by end users. So far high-resolution multimodel seasonal hydrological forecasts have been unavailable due to 1) lack of availability of high-resolution meteorological seasonal forecasts, requiring temporal and spatial downscaling; 2) a mismatch between the provided seasonal forecast information and the user needs; and 3) lack of consistency between the hydrological model outputs to generate multimodel seasonal hydrological forecasts. As part of the End-to-End Demonstrator for Improved Decision Making in the Water Sector in Europe (EDgE) project commissioned by the Copernicus Climate Change Service (ECMWF), this study provides a unique dataset of seasonal hydrological forecasts derived from four general circulation models [CanCM4, GFDL Forecast-Oriented Low Ocean Resolution version of CM2.5 (GFDL-FLOR), ECMWF Season Forecast System 4 (ECMWF-S4), and Météo-France LFPW] in combination with four hydrological models [mesoscale hydrologic model (mHM), Noah-MP, PCRaster Global Water Balance (PCR-GLOBWB), and VIC]. The forecasts are provided at daily resolution, 6-month lead time, and 5-km spatial resolution over the historical period from 1993 to 2012. Consistency in hydrological model parameterization ensures an increased consistency in the hydrological forecasts. Results show that skillful discharge forecasts can be made throughout Europe up to 3 months in advance, with predictability up to 6 months for northern Europe resulting from the improved predictability of the spring snowmelt. The new system provides an unprecedented ensemble of seasonal hydrological forecasts with significant skill over Europe to support water management. This study highlights the potential advantages of multimodel based forecasting system in providing skillful hydrological forecasts.

Description: Meteorological and hydrological droughts can bring different socioeconomic impacts. In this study, we investigated meteorological and hydrological drought characteristics and propagation using the standardized precipitation index (SPI) and standardized streamflow index (SSI), over the upstream and midstream of the Heihe River basin (UHRB and MHRB, respectively). The correlation analysis and cross-wavelet transform were adopted to explore the relationship between meteorological and hydrological droughts in the basin. Three modeling experiments were performed to quantitatively understand how climate change and human activities influence hydrological drought and propagation. Results showed that meteorological drought characteristics presented little difference between UHRB and MHRB, while hydrological drought events are more frequent in the MHRB. In the UHRB, there were positive relationships between meteorological and hydrological droughts, whereas drought events became less frequent but longer when meteorological drought propagated into hydrological drought. Human activities have obviously changed the positive correlation to negative in the MHRB, especially during warm and irrigation seasons. The propagation time varied with seasonal climate characteristics and human activities, showing shorter values due to higher evapotranspiration, reservoir filling, and irrigation. Quantitative evaluation showed that climate change was inclined to increase streamflow and propagation time, contributing from −57% to 63%. However, more hydrological droughts and shorter propagation time were detected in the MHRB because human activities play a dominant role in water consumption with contribution rate greater than (−)89%. This study provides a basis for understanding the mechanism of hydrological drought and for the development of improved hydrological drought warning and forecasting system in the HRB.

Description: The 2009 Atlanta flood was a historic event that resulted in catastrophic damage throughout the metropolitan area. The flood was the product of several hydrometeorological processes, including moist antecedent conditions, ample atmospheric moisture, and mesoscale training. Additionally, previous studies hypothesized that the urban environment of Atlanta altered the location and/or overall quantities of precipitation and runoff that ultimately produced the flood. This hypothesis was quantitatively evaluated by conducting a modeling case study that utilized the Weather Research and Forecasting Model. Two model runs were performed: 1) an urban run designed to accurately depict the flood event and 2) a nonurban simulation where the urban footprint of Atlanta was replaced with natural vegetation. Comparing the output from the two simulations revealed that interactions with the urban environment enhanced the precipitation and runoff associated with the flood. Specifically, the nonurban model underestimated the cumulative precipitation by approximately 100 mm in the area downwind of Atlanta where urban rainfall enhancement was hypothesized. This notable difference was due to the increased surface convergence observed in the urban simulation, which was likely attributable to the enhanced surface roughness and thermal properties of the urban environment. The findings expand upon previous research focused on urban rainfall effects since they demonstrate that urban interactions can influence mesoscale hydrometeorological characteristics during events with prominent synoptic-scale forcing. Finally, from an urban planning perspective, the results highlight a potential two-pronged vulnerability of urban environments to extreme rainfall, as they may enhance both the initial precipitation and subsequent runoff.

Description: Landslide event inventories are a vital resource for landslide susceptibility and forecasting applications. However, landslide inventories can vary in accuracy, availability, and timeliness as a result of varying detection methods, reporting, and data availability. This study presents an approach to use publicly available satellite data and open-source software to automate a landslide detection process called the Sudden Landslide Identification Product (SLIP). SLIP utilizes optical data from the Landsat-8 Operational Land Imager sensor, elevation data from the Shuttle Radar Topography Mission, and precipitation data from the Global Precipitation Measurement mission to create a reproducible and spatially customizable landslide identification product. The SLIP software applies change-detection algorithms to identify areas of new bare-earth exposures that may be landslide events. The study also presents a precipitation monitoring tool that runs alongside SLIP called the Detecting Real-Time Increased Precipitation (DRIP) model that helps to identify the timing of potential landslide events detected by SLIP. Using SLIP and DRIP together, landslide detection is improved by reducing problems related to accuracy, availability, and timeliness that are prevalent in the state of the art for landslide detection. A case study and validation exercise in Nepal were performed for images acquired between 2014 and 2015. Preliminary validation results suggest 56% model accuracy, with errors of commission often resulting from newly cleared agricultural areas. These results suggest that SLIP is an important first attempt in an automated framework that can be used for medium-resolution regional landslide detection, although it requires refinement before being fully realized as an operational tool.

Description: Changes in vegetation are known to have an impact on climate via biogeophysical effects such as changes in albedo and heat fluxes. Here, the effects of maximum afforestation and deforestation are studied over Europe. This is done by comparing three regional climate model simulations—one with present-day vegetation, one with maximum afforestation, and one with maximum deforestation. In general, afforestation leads to more evapotranspiration (ET), which leads to decreased near-surface temperature, whereas deforestation leads to less ET, which leads to increased temperature. There are exceptions, mainly in regions with little water available for ET. In such regions, changes in albedo are relatively more important for temperature. The simulated biogeophysical effect on seasonal mean temperature varies between 0.5° and 3°C across Europe. The effect on minimum and maximum temperature is larger than that on mean temperature. Increased (decreased) mean temperature is associated with an even larger increase (decrease) in maximum summer (minimum winter) temperature. The effect on precipitation is found to be small. Two additional simulations in which vegetation is changed in only one-half of the domain were also performed. These simulations show that the climatic effects from changed vegetation in Europe are local. The results imply that vegetation changes have had, and will have, a significant impact on local climate in Europe; the climatic response is comparable to climate change under RCP2.6. Therefore, effects from vegetation change should be taken into account when simulating past, present, and future climate for this region. The results also imply that vegetation changes could be used to mitigate local climate change.

Description: Persistent Lagrangian transport patterns at the ocean surface are revealed from climatological Lagrangian coherent structures (cLCSs) computed from daily climatological surface current velocities in the northwestern Gulf of Mexico (NWGoM). The climatological currents are computed from daily velocities produced by an 18-yr-long free-running submesoscale-permitting Nucleus for European Modelling of the Ocean (NEMO) simulation of the Gulf of Mexico. Despite the intense submesoscale variability produced by the model along the shelf break, which is found to be consistent with observations and previous studies, a persistent mesoscale attracting barrier between the NWGoM shelf and the deep ocean is effectively identified by a hook-like pattern associated with persistent strongly attracting cLCSs. Simulated tracer and satellite-tracked drifters originating over the shelf tend to be trapped there by the hook-like pattern as they spread cyclonically. Tracers and drifters originating beyond the shelf tend to be initially attracted to the hook-like pattern as they spread anticyclonically and eventually over the deep ocean. The findings have important implications for the mitigation of contaminant accidents such as oil spills.

Description: Turbulent processes in the ocean surface boundary layer (OSBL) play a key role in weather and climate systems. This study explores a Lagrangian analysis of wave-driven OSBL turbulence, based on a large-eddy simulation (LES) model coupled to a Lagrangian stochastic model (LSM). Langmuir turbulence (LT) is captured by Craik–Leibovich wave forcing that generates LT through the Craik–Leibovich type 2 (CL2) mechanism. Breaking wave (BW) effects are modeled by a surface turbulent kinetic energy flux that is constrained by wind energy input to surface waves. Unresolved LES subgrid-scale (SGS) motions are simulated with the LSM to be energetically consistent with the SGS model of the LES. With LT, Lagrangian autocorrelations of velocities reveal three distinct turbulent time scales: an integral, a dispersive mixing, and a coherent structure time. Coherent structures due to LT result in relatively narrow peaks of Lagrangian frequency velocity spectra. With and without waves, the high-frequency spectral tail is consistent with expectations for the inertial subrange, but BWs substantially increase spectral levels at high frequencies. Consistently, over short times, particle-pair dispersion results agree with the Richardson–Obukhov law, and near-surface dispersion is significantly enhanced because of BWs. Over longer times, our dispersion results are consistent with Taylor dispersion. In this case, turbulent diffusivities are substantially larger with LT in the crosswind direction, but reduced in the along-wind direction because of enhanced turbulent transport by LT that reduces mean Eulerian shear. Our results indicate that the Lagrangian analysis framework is effective and physically intuitive to characterize OSBL turbulence.

Description: The observation-based source terms available in the third-generation wave model WAVEWATCH III (i.e., the ST6 package for parameterizations of wind input, wave breaking, and swell dissipation terms) are recalibrated and verified against a series of academic and realistic simulations, including the fetch/duration-limited test, a Lake Michigan hindcast, and a 1-yr global hindcast. The updated ST6 not only performs well in predicting commonly used bulk wave parameters (e.g., significant wave height and wave period) but also yields a clearly improved estimation of high-frequency energy level (in terms of saturation spectrum and mean square slope). In the duration-limited test, we investigate the modeled wave spectrum in a detailed way by introducing spectral metrics for the tail and the peak of the omnidirectional wave spectrum and for the directionality of the two-dimensional frequency–direction spectrum. The omnidirectional frequency spectrum E(f) from the recalibrated ST6 shows a clear transition behavior from a power law of approximately f−4 to a power law of about f−5, comparable to previous field studies. Different solvers for nonlinear wave interactions are applied with ST6, including the Discrete Interaction Approximation (DIA), the more expensive Generalized Multiple DIA (GMD), and the very expensive exact solutions [using the Webb–Resio–Tracy method (WRT)]. The GMD-simulated E(f) is in excellent agreement with that from WRT. Nonetheless, we find the peak of E(f) modeled by the GMD and WRT appears too narrow. It is also shown that in the 1-yr global hindcast, the DIA-based model overestimates the low-frequency wave energy (wave period T 〉 16 s) by 90%. Such model errors are reduced significantly by the GMD to ~20%.

Description: We investigate the linear stability of intense baroclinic anticyclones, with a particular focus on the centrifugal (inertial) instability. Various vertical and radial velocity profiles are studied. The vertical profiles are such that the velocity is maximum at the surface. These profiles correspond to oceanic eddies such as submesoscale mixed-layer eddies or intense mesoscale eddies in the upper thermocline. The results show that the main characteristics of the centrifugal instability (growth rate, vertical wavelength) depend weakly on the baroclinic structure of the anticyclone. The dominant azimuthal wavenumber is for small Burger number (Bu) and for higher Bu, where Bu is the square root of the ratio of the deformation radius over the characteristic eddy radius where the velocity is maximum. The marginal stability limits of the centrifugal instability for the different velocity profiles collapse approximately on a single curve in the parameter space (Ro, Bu), where is the Rossby number, with being the maximum velocity. By means of an asymptotic analysis for short vertical wavelength, an explicit prediction for the marginal stability limit is derived for a wide range of velocity profiles. We then suggest to use, for most of oceanic anticyclones, the instability criterion valid for a Gaussian eddy: where is the Ekman number, H is the eddy depth, and ν is the turbulent viscosity at the ocean surface. Some baroclinic anticyclones can remain stable even if they have a core region of negative absolute vorticity provided that they are small enough. This formula explains the few observations of intense anticyclonic eddies having a negative core vorticity around .

Description: Using trajectories from acoustically tracked (RAFOS) floats in the Gulf of Mexico, we construct a geography of its Lagrangian circulation within the 1500–2500-m layer. This is done by building a Markov-chain representation of the Lagrangian dynamics. The geography is composed of weakly interacting provinces that constrain the connectivity at depth. The main geography includes two provinces of near-equal areas separated by a roughly meridional boundary. The residence time is about 4.5 (3.5) years in the western (eastern) province. The exchange between these provinces is effected through a slow cyclonic circulation, which is well constrained in the western basin by preservation of f/H, where f is the Coriolis parameter and H is depth. Secondary provinces of varied shapes covering smaller areas are identified with residence times ranging from about 0.4 to 1.2 years or so. Except for the main provinces, the deep Lagrangian geography does not resemble the surface Lagrangian geography recently inferred from satellite-tracked drifter trajectories. This implies disparate connectivity characteristics with potential implications for pollutant (e.g., oil) dispersal at the surface and at depth. Support for our results is provided by a Markov-chain analysis of satellite-tracked profiling (Argo) floats, which, while forming a smaller dataset and having seemingly different water-following characteristics than the RAFOS floats, replicate the main aspects of the Lagrangian geography. Our results find further validation in independent results from a chemical tracer release experiment.

Description: The diffusive layering (DL) form of double-diffusive convection cools the Atlantic Water (AW) as it circulates around the Arctic Ocean. Large DL steps, with heights of homogeneous layers often greater than 10 m, have been found above the AW core in the Eurasian Basin (EB) of the eastern Arctic. Within these DL staircases, heat and salt fluxes are determined by the mechanisms for vertical transport through the high-gradient regions (HGRs) between the homogeneous layers. These HGRs can be thick (up to 5 m and more) and are frequently complex, being composed of multiple small steps or continuous stratification. Microstructure data collected in the EB in 2007 and 2008 are used to estimate heat fluxes through large steps in three ways: using the measured dissipation rate in the large homogeneous layers; utilizing empirical flux laws based on the density ratio and temperature step across HGRs after scaling to account for the presence of multiple small DL interfaces within each HGR; and averaging estimates of heat fluxes computed separately for individual small interfaces (as laminar conductive fluxes), small convective layers (via dissipation rates within small DL layers), and turbulent patches (using dissipation rate and buoyancy) within each HGR. Diapycnal heat fluxes through HGRs evaluated by each method agree with each other and range from ~2 to ~8 W m−2, with an average flux of ~3–4 W m−2. These large fluxes confirm a critical role for the DL instability in cooling and thickening the AW layer as it circulates around the eastern Arctic Ocean.

Description: Large-amplitude mode-2 nonlinear internal waves were observed in 250-m-deep water on the Australian North West shelf. Wave amplitudes were derived from temperature measurements using three through-the-water-column moorings spaced 600 m apart in a triangular configuration. The moorings were deployed for 2 months during the transition period between the tropical monsoon and the dry season. The site had a 25–30-m-amplitude mode-1 internal tide that essentially followed the spring–neap tidal cycle. Regular mode-2 nonlinear wave trains with amplitudes exceeding 25 m, with the largest event exceeding 50 m, were also observed at the site. Overturning was observed during several mode-2 events, and the relatively high wave Froude number and steepness (0.15) suggested kinematic (convective) instability was likely to be the driving mechanism. The presence of the mode-2 waves was not correlated with the tidal forcing but rather occurred when the nonlinear steepening length scale was smaller than the distance from the generation region to the observation site. This steepening length scale is inversely proportional to the nonlinear parameter in the Korteweg–de Vries equation, and it varied by at least one order of magnitude under the evolving background thermal stratification over the observation period. Despite the complexity of the internal waves in the region, the nonlinear steepening length was shown to be a reliable indicator for the formation of large-amplitude mode-2 waves and the rarer occurrence of mode-1 large-amplitude waves. A local mode-2 generation mechanism caused by a beam interacting with a pycnocline is demonstrated using a fully nonlinear numerical solution.

Description: The complex structure of the vertical velocity field inside an anticyclonic eddy located just south of the Canary Islands is analyzed through a high-resolution ocean model. Based on the flow divergence, vertical velocity is decomposed into various forcing components. The analysis reveals that advection and stretching of vorticity are the most important forcing contributions to the vertical velocity within the eddy. In the mixed layer, a small-scale multipolar vertical velocity pattern dominates. This is the result of vertical mixing effects that enhance the surface vertical velocity by increasing the ageostrophic velocity profile. As a result, an ageostrophic secondary circulation arises that acts to restore thermal-wind balance, inducing strong vertical motions. Nonlinear Ekman pumping/suction patterns resemble the small-scale vertical velocity field, suggesting that nonlinear Ekman effects are important in explaining the complex vertical velocity, despite an overestimate of its magnitude. In the eddy thermocline, the vertical velocity is characterized by a dipolar pattern, which experiences changes in intensity and axisymmetrization with time. The dipolar vertical velocity distribution arises from the imbalance between the advection and stretching of the vorticity forcing terms. A vertical velocity dipole is also obtained by solving a generalized omega equation from density and horizontal velocity fields, which also shows a preponderance of the ageostrophic term. The ubiquity of dipolar vertical velocity distributions inside isolated anticyclones is supported by recent observational findings in the same oceanic region.

Description: The stability of a horizontally and vertically sheared surface jet is examined, with a focus on the vertical structure of the resultant eddies. Over a flat bottom, the instability is mixed baroclinic/barotropic, producing strong eddies at depth that are characteristically shifted downstream relative to the surface eddies. Baroclinic instability is suppressed over a large slope for retrograde jets (with a flow antiparallel to topographic wave propagation) and to a lesser extent for prograde jets (with flow parallel to topographic wave propagation), as seen previously. In such cases, barotropic (lateral) instability dominates if the jet is sufficiently narrow. This yields surface eddies whose size is independent of the slope but proportional to the jet width. Deep eddies still form, forced by interfacial motion associated with the surface eddies, but they are weaker than under baroclinic instability and are vertically aligned with the surface eddies. A sinusoidal ridge acts similarly, suppressing baroclinic instability and favoring lateral instability in the upper layer. A ridge with a 1-km wavelength and an amplitude of roughly 10 m is sufficient to suppress baroclinic instability. Surveys of bottom roughness from bathymetry acquired with shipboard multibeam echo sounding reveal that such heights are common beneath the Kuroshio, the Antarctic Circumpolar Current, and, to a lesser extent, the Gulf Stream. Consistent with this, vorticity and velocity cross sections from a 1/50° HYCOM simulation suggest that Gulf Stream eddies are vertically aligned, as in the linear stability calculations with strong topography. Thus, lateral instability may be more common than previously thought, owing to topography hindering vertical energy transfer.

Description: High-frequency radio Doppler surface current observations off the south shore of Oahu, Hawaii, are used to calculate the vorticity equation at a ~2-km spatial resolution in terms of a time-dependent and time-mean surface balance. First-order terms are mean advection of mean vorticity, vortex stretching, and a residual, which is treated as unquantified terms such as wind stress curl, bottom pressure torque, and noise. The most striking feature in the 2-yr time-mean vorticity balance is the anticorrelation between advection of vorticity and vortex stretching implying that potential vorticity (PV) advection is the most dominant mechanism in the area. Several terms in the depth-integrated vorticity balance were also estimated. The bottom pressure torque acts as a first-order term only in areas of shallow topography. A PV analysis resulted in the 50-m Penguin Bank steering the westward Hawaiian Lee Current.

Description: Based on analysis of observational data it has been suggested that a negative feedback of ice–ocean stress coupling may limit freshwater accumulation in the Beaufort Gyre (BG). In this paper we explore how this feedback can significantly contribute to BG stabilization in an anticyclonic wind regime. We use an ice–ocean model and turn on and off the feedback in simulations to elucidate the role of the feedback. When a persistent anticyclonic wind anomaly is applied over the BG, liquid freshwater content (FWC) increases because of enhanced Ekman downwelling. As a consequence, ocean surface geostrophic currents speed up. However, the spinup of sea ice is weaker than the acceleration of surface geostrophic currents during wintertime, because of strong sea ice internal stress when ice concentration is high and ice is thick. This leads to cyclonic anomalies in the ice–ocean relative velocity and stress over the BG. The resultant seasonal Ekman upwelling anomaly reduces freshwater accumulation by about 1/4 as compared to a simulation with the negative feedback turned off in a control experiment, with a reduction range of 1/10–1/3 in all experiments conducted. We show that the feedback is more effective when the model’s mesoscale eddy diffusivity is smaller or when sea ice internal stress is stronger. Finally, we argue that the ice–ocean stress feedback may become less significant as the Arctic warms and sea ice declines.

Description: A California Undercurrent eddy (Cuddy) was repeatedly surveyed using multiple Seagliders for over three months. Found and tracked off of the Washington–Vancouver Island coasts, this Cuddy traveled over 400 km, remaining between the 1000- and 2000-m isobaths, as it was swept along in poleward flow of the California Current System. Three Seagliders made repeat bisecting transects of the Cuddy core capturing its detailed three-dimensional structure in time. Its evolution was analyzed through comparison of 11 independent Cuddy “snapshots.” A two dimensional Gaussian model fit to the geopotential anomaly field for each snapshot allowed computation of dynamic fields inaccessible in Seaglider profiles alone. Results indicate that the Cuddy decayed as its core waters became less isolated over time: Cuddy total mechanical energy (kinetic + potential), salt content, and the magnitude of the core potential vorticity anomaly decreased. Core spice and dissolved oxygen variance increased tenfold, and thermohaline fine structure, suggestive of lateral intrusions, was observed progressively closer to the eddy core. The estimated gradient-wind balanced velocity field similarly weakened as the Rossby number decreased to 0.32 from an initial value of 0.48. The observed changes in eddy properties occurred as the Cuddy was exposed to changes in the background stratification and Coriolis parameter as it translated alongshore. Idealized modeling of eddy adjustment indicates that both erosion and changing background conditions are required to explain the observed eddy changes. Adjustment in response to both effects simultaneously leads to changes in eddy properties qualitatively consistent with those observed.

Description: In the decade or so below the Ozmidov wavenumber (N3/ε)1/2, that is, on scales between those attributed to internal gravity waves and isotropic turbulence, ocean and atmosphere measurements consistently find k1/3 horizontal wavenumber spectra for horizontal shear uh and horizontal temperature gradient Th and m−1 vertical wavenumber spectra for vertical shear uz and strain ξz. Dimensional scaling is used to construct model spectra below as well as above the Ozmidov wavenumber that reproduces observed spectral slopes and levels in these two bands in both vertical and horizontal wavenumber. Aspect ratios become increasingly anisotropic below the Ozmidov wavenumber until reaching ~O(f/N), where horizontal shear uh ~ f. The forward energy cascade below the Ozmidov wavenumber found in observations and numerical simulations suggests that anisotropic and isotropic turbulence are manifestations of the same nonlinear downscale energy cascade to dissipation, and that this turbulent cascade originates from anisotropic instability of finescale internal waves at horizontal wavenumbers far below the Ozmidov wavenumber. Isotropic turbulence emerges as the cascade proceeds through the Ozmidov wavenumber where shears become strong enough to overcome stratification. This contrasts with the present paradigm that geophysical isotropic turbulence arises directly from breaking internal waves. This new interpretation of the observations calls for new approaches to understand anisotropic generation of geophysical turbulence patches.

Description: Near-inertial oscillations (NIOs) on the inner Scotian shelf are studied using observations, a simple slab model, and two operational shelf circulation models. High-frequency radar and ADCP observations from December 2015 to February 2016 show that individual NIO events forced by time-varying wind stress typically lasted for three to four inertial periods. NIOs with speeds exceeding 0.25 m s−1 were observed in the offshore part of the study region, but their amplitudes decreased shoreward within ~40 km of the coast. The NIOs had spatial scales of ~80 and ~40 km in the alongshore and cross-shore directions, respectively. The NIO phases varied moving from west to east, consistent with the typical movement of winter storms across the study region. Evolving rotary spectral analysis reveals that the peak frequency fp of the NIOs varied with time by ~7% of the local inertial frequency. The variation in fp can be explained in part by local wind forcing as demonstrated by the slab model. The remaining variation in fp can be explained in part by variations in the background vorticity associated with changes in the strength and position of the Nova Scotia Current, an unstable baroclinic boundary current that runs along the coast to the southwest. Two operational shelf circulation models are used to examine the abovementioned features in the high-frequency-radar and ADCP observations. The models reproduce the spatial structure of the NIOs and, in a qualitative sense, the temporal variations of fp.

Description: A new approach to parameterizing subgrid-scale processes is proposed: The impact of the unresolved dynamics on the resolved dynamics (i.e., the eddy forcing) is represented by a series expansion in dynamical spatial modes that stem from the energy budget of the resolved dynamics. It is demonstrated that the convergence in these so-called energy modes is faster by orders of magnitude than the convergence in Fourier-type modes. Moreover, a novel way to test parameterizations in models is explored. The resolved dynamics and the corresponding instantaneous eddy forcing are defined via spatial filtering that accounts for the representation error of the equations of motion on the low-resolution model grid. In this way, closures can be tested within the high-resolution model, and the effects of different parameterizations related to different energy pathways can be isolated. In this study, the focus is on parameterizations of the baroclinic energy pathway. The corresponding standard closure in ocean models, the Gent–McWilliams (GM) parameterization, is also tested, and it is found that the GM field acts like a stabilizing direction in phase space. The GM field does not project well on the eddy forcing and hence fails to excite the model’s intrinsic low-frequency variability, but it is able to stabilize the model.

Description: Mixed triad wave–wave interactions between Rossby and gravity waves are analytically derived using the kinetic equation for models of different complexity. Two examples are considered: initially vanishing linear gravity wave energy in the presence of a fully developed Rossby wave field and the reversed case of initially vanishing linear Rossby wave energy in the presence of a realistic gravity wave field. The kinetic equation in both cases is numerically evaluated, for which energy is conserved within numerical precision. The results are validated by a corresponding ensemble of numerical model simulations supporting the validity of the weak-interaction assumption necessary to derive the kinetic equation. Since they are generated by nonresonant interactions only, the energy transfers toward the respective linear wave mode with vanishing energy are small in both cases. The total generation of energy of the linear gravity wave mode in the first case scales to leading order as the square of the Rossby number in agreement with independent estimates from laboratory experiments, although a part of the linear gravity wave mode is slaved to the Rossby wave mode without wavelike temporal behavior.

Description: Energy conversion routes are investigated in the western Mediterranean Sea from the eddy–mean flow interactions. The sources of eddy kinetic energy are analyzed by applying a regional formulation of the Lorenz energy cycle to 18 years of numerical simulation at eddy-resolving resolution (3.5 km), which allows for identifying whether the energy exchange between the mean and eddy flow is local or nonlocal. The patterns of energy conversion between the mean and eddy kinetic and potential energy are estimated in three subregions of the domain: the Alboran Sea, the Algerian Basin, and the northern basin. The spatial characterization of the energy routes hints at the physical mechanisms involved in maintaining the balance, suggesting that flow–topography interaction is strongly linked to eddy growth in most of the domain.