Operational Meteorologists Research Articles

SIFTing through satellite imagery with the Satellite Information Familiarization Tool

The Satellite Information Familiarization Tool (SIFT) is an open-source, multi-platform graphical user interface designed to easily display spectral and temporal sequences of geostationary satellite imagery. The Advanced Baseline Imager (ABI) and Advanced Himawari Imager (AHI) on the “new generation” of geostationary satellites collect imagery with a spatial resolution four times greater than previously available. Combined with the increased number of spectral bands and more frequent imaging, the new series imagers collect approximately 60 times more data. Given the resulting large file sizes, the development of SIFT is a multiyear effort to make those satellite imagery data files accessible to the broad community of students, scientists, and operational meteorologists. To achieve the objective of releasing software that provides an intuitive user experience to complement optimum performance on consumer-grade computers, SIFT was built to leverage modern graphics processing units (GPUs) through existing open-source Python packages, and runs on the three major operating systems: Windows, Mac, and Linux. The United States National Weather Service funded the development of SIFT to help enhance the satellite meteorology acumen of their operational meteorologists. SIFT has basic image visualization capabilities and enables the fluid animation and interrogation of satellite images, creation of Red-Green-Blue (RGB) composites and algebraic combinations of multiple spectral bands, and comparison of imagery with numerical weather prediction output. Open for community development, SIFT users and features continue to grow. SIFT is freely available with short tutorials and a user guide online. The mandate for the software, its development, realized applications, and envisioned role in science and training are explained.

Is a Consistent Message Achievable?: Defining “Message Consistency” for Weather Enterprise Researchers and Practitioners

ABSTRACTAlthough both research and practice contend that message consistency is a critical component of effective risk communication, neither provide systematic evidence demonstrating if, when, and where consistency matters. For this reason, meteorologists view message consistency as both a relevant research and operational concern. To address these concerns, members of the weather enterprise organized conference sessions, panels, webinars, and workshops to achieve message consistency, but were unable to make progress without a definition. Fortunately, research scholars in the fields of psychology and communication studies offer important theoretical insights for defining message consistency. As such, this paper takes an important first step by combining the needs of operational meteorologists with insights from social science research to offer a definition of message consistency for the weather enterprise. While it is logical to present both a definition and a recommendation on how to achieve message consistency, the systematic review revealed various research limitations and practical constraints that call into question the feasibility of achieving it. To further bridge research and practice, this paper recommends that researchers and practitioners collaboratively develop a message consistency evaluation process for the weather enterprise. A persistent community effort will shed light on when, where, and under which circumstances consistency is necessary, and more importantly, move us one step closer toward achieving a more consistent message within the weather enterprise.

Weathering the Storms: Workplace Wellbeing, Mental Health, and the U.S. Meteorologist

Mental health is a topic of increasing interest and concern across the weather enterprise amidst a backdrop of funding cuts, extreme storms, and longer, more involved work hours. The present study therefore investigated wellbeing in the meteorological workplace. Participants (N= 389), professional meteorologists (n = 360) and professionally-employed meteorology students (n = 29), voluntarily participated in a Qualtrics-hosted online survey and responded to a number of measures representing a broad range of mental health variables. These individuals fell into three employment sectors: U.S. National Weather Service (NWS), Broadcast (television weather), and Other (a combination of academic, private sector, military, and non-NWS operational meteorologists). Individual differences emerged between meteorological sectors in personality and the subjective wellbeing domains of burnout, job satisfaction, and anxiety. Broadcasters were significantly more burnt-out at work and personally, were higher in extraversion, and were highest in anxiety. NWS meteorologists were most burnt-out in working with partners. The Other category of meteorologists showed more agreeableness and greater job satisfaction than broadcasters and those in the NWS. There was no cross-sector difference, however, in traits that might be relatively uniform among meteorologists: Grit, life satisfaction, self-concept clarity, subjective happiness, stress, and depression. Results are discussed in terms of consequences for meteorologists’ mental health and emotional wellbeing as well as the future of the field.

The changing role of operational meteorologists

The Bureau of Meteorology is changing the way forecasts are produced, from a labour-intensive approach to a more streamlined approach. We describe the essence of the new forecast process using a case study to demonstrate a situation in which meteorologists use their professional judgement to modify what would otherwise be a largely automated forecast service.

Developing a hazard‐impact model to support impact‐based forecasts and warnings: The Vehicle OverTurning (VOT) Model

AbstractImpact‐based weather warnings have been issued by the Met Office since 2011. The National Severe Weather Warning Service (NSWWS) uses a risk matrix combining the level of impacts the weather may cause and the likelihood of those impacts occurring to define a warning level. The impact assessment can be considered subjective being predominantly based on meteorologist expertise and experience of past high‐impact weather events and discussions with local advisors. The Vehicle OverTurning (VOT) model is a prototype Hazard Impact Model developed to test the hypothesis that risk models can be run in real time for short‐term weather‐related hazards. The method intends to provide an objective, consistent assessment of potential risk to road users in Great Britain during high‐wind events. It aims to support the production of NSWWS wind warnings by highlighting areas of the road network that are at risk of disruption due to vehicles overturning. The VOT model does this by combining probabilistic hazard information with vulnerability and exposure data to produce a risk of vehicle overturning forecast. The model is being demonstrated with operational meteorologists at the Met Office. Initial reviews of the model's output indicate that the scientific approach used in this prototype can identify routes with a higher risk of vehicle overturning, associated with strong wind events. Ad hoc feedback from forecasters support the authors’ belief that the risk modelling approach is useful to operational meteorologists when issuing weather warnings.

Tropical–Mid-Latitude Interactions: Case Study of an Inland-Penetrating Atmospheric River During a Major Winter Storm Over North America

ABSTRACTA detailed analysis is performed on an inland-penetrating atmospheric river (AR) driven by and coupled to a Colorado cyclone in the first week of February 2016. This winter weather system was initiated by a trough of low pressure moving across the Rocky Mountains from the California coast. The low-level jet ahead of the trough was capable of extracting water vapour from the Gulf of Mexico to feed a cyclone on the lee side of the Rocky Mountaains, and the jet stream eventually transformed into a powerful AR. The warm, moist flow from the south produced a narrow band of heavy precipitation along the major axis of the AR across the central and eastern United States and generated significant freezing rain in parts of the northeastern United States and eastern Canada as the AR flowed over the warm front. It is suggested that, in an operational weather forecasting and warning environment, ARs can be easily identified by using the vertically integrated horizontal water vapour transport, and the major AR contribution to heavy precipitation can be estimated from the horizontal moisture convergence. It is demonstrated that the AR analysis in this case can assist operational meteorologists in understanding and conceptualizing winter storm development and the associated high-impact weather pattern. The operational predictability of this winter storm and its possible teleconnection with the Madden–Julian Oscillation (MJO) are also investigated. Our lagged composite analysis reveals that a statistically significant increase in water vapour transport from the Gulf of Mexico over the North American continent could occur about 10–20 days after the MJO-related convection anomaly reaches the tropical Indian Ocean.

It's not hot air: Using GOES‐16 infrared window bands to diagnose adjacent summertime air masses

The first in the next‐generation series of the US Geostationary Operational Environmental Satellites system (GOES), GOES‐16, is providing improved quality satellite imagery of atmospheric phenomena and land features over the Americas and the Atlantic Ocean, benefitting scientists and operational meteorologists. A frontal passage separating distinct air masses for a typical warm season case over the Upper Midwest on August 30, 2017, is examined in a discussion on the value of GOES‐16 infrared window band imagery. The “split window” difference between the 10.3 and 12.3 μm long wave infrared bands, a traditional approach to characterizing visually low‐level water vapour in cloud‐free scenes, is compared with the 3.9 μm short wave infrared window band for identifying two distinct air masses. Surface station temperatures and dew points confirm modest moisture pooling ahead of the southward‐moving front. These window bands are not new to the geostationary orbit, but with GOES‐16, they are available at higher bit depths and at better spatial, spectral and temporal resolutions. This makes identifying and analysing fronts and air masses more apparent compared with legacy imagery, particularly during the day if properly enhanced. While a hindrance to quantitative approaches, solar contamination in the 3.9 μm band can be beneficial to analysts performing this task visually.

Shining light on sky cover during a total solar eclipse

Sky cover is a unique parameter because its quantification is subject to the perspective of the observer or characteristics of the observing instrumentation. Forecasting sky cover provided a professional challenge to operational meteorologists seeking to offer a refined forecast beyond numerical weather prediction guidance along the path of totality resulting from a solar eclipse traversing North America on August 21, 2017. A routine analysis with which to monitor subtle trends in sky cover and compare sky cover forecasts is also not widely available. This contribution reviews 1-h gridded forecasts of sky cover from the United States National Weather Service (NWS) on the eclipse day and compares them with hourly satellite and surface sky observations for an area of interest over the southeastern United States. An inconsistency between the real-time mesoscale analysis (RTMA) and the NWS National Digital Forecast Database is revealed during the eclipse totality. A satellite-to-satellite comparison of the adjusted average cloud top emissivity over this same area reveals how resolution and algorithm improvements to next-generation satellite imagers may alter the RTMA of total cloud cover in the latest era of Geostationary Operational Environmental Satellites (GOES), starting with the GOES-16 Advanced Baseline Imager.

Severe weather over the Highveld of South Africa during November 2016

November months are notorious for severe weather over the Highveld of South Africa. November 2016 was no exception and a large number of severe events occurred. Very heavy rainfall, large hail and tornadoes were reported. The aim of this paper is to compare the synoptic circulation of November 2016 with the long-term mean November circulation and to investigate some sounding derived parameters. Furthermore, a few of the severe weather events are described in detail. The surface temperatures and dewpoint temperatures were found to be higher than normal resulting in increased conditional instability over the Highveld. Low-level moisture originated over the warm Mozambique Channel and the 500 hPa temperature trough was located favourably over the Highveld; further east than normal. The combination of these factors and weak steering winds resulted in flash flooding on the 9th while favourable wind shear conditions caused the development of a tornado on 15 November. The favourable circulation patterns and moisture gave rise to an atmosphere in which severe weather was a possibility, and the awareness of such factors is used as one of many tools when considering the severe weather forecast. The consideration of the daily variables derived from sounding data were good precursors for the prediction of severe thunderstorm development over the Highveld during November 2016. It is recommended that an operational meteorologist incorporates upper air sounding data into the forecasting process and not to rely on numerical prediction models exclusively.

Hotplate precipitation gauge calibrations and field measurements

Abstract. First introduced in 2003, approximately 70 Yankee Environmental Systems (YES) hotplate precipitation gauges have been purchased by researchers and operational meteorologists. A version of the YES hotplate is described in Rasmussen et al. (2011; R11). Presented here is testing of a newer version of the hotplate; this device is equipped with longwave and shortwave radiation sensors. Hotplate surface temperature, coefficients describing natural and forced convective sensible energy transfer, and radiative properties (longwave emissivity and shortwave reflectance) are reported for two of the new-version YES hotplates. These parameters are applied in a new algorithm and are used to derive liquid-equivalent accumulations (snowfall and rainfall), and these accumulations are compared to values derived by the internal algorithm used in the YES hotplates (hotplate-derived accumulations). In contrast with R11, the new algorithm accounts for radiative terms in a hotplate's energy budget, applies an energy conversion factor which does not differ from a theoretical energy conversion factor, and applies a surface area that is correct for the YES hotplate. Radiative effects are shown to be relatively unimportant for the precipitation events analyzed. In addition, this work documents a 10 % difference between the hotplate-derived and new-algorithm-derived accumulations. This difference seems consistent with R11's application of a hotplate surface area that deviates from the actual surface area of the YES hotplate and with R11's recommendation for an energy conversion factor that differs from that calculated using thermodynamic theory.

Comparison of Satellite-, Model-, and Radiosonde-Derived Convective Available Potential Energy in the Southern Great Plains Region

AbstractConvective available potential energy (CAPE) is one of the physical quantities used by operational meteorologists when issuing severe-weather convective watches and warnings. Recent advances in satellite technology could provide timely observations of atmospheric temperature and water vapor profiles over the continental United States, but only limited validation exists in the literature to characterize uncertainties in CAPE derived from the new satellite sensors. In this study, 10 years of Vaisala, Inc., RS92 radiosonde observations from the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site were matched to overpasses of the NASA Aqua satellite that were made from January 2005 through December 2014. Vertical profiles of temperature and water vapor from the NASA Atmospheric Infrared Sounder (AIRS) were extracted in a region surrounding the DOE ARM SGP central facility near Lamont, Oklahoma. Surface-based CAPE was computed using software consistent with methods used by the National Weather Service Storm Prediction Center. The one-to-one correspondence of the AIRS-derived CAPE with the ARM-radiosonde-derived CAPE has a correlation coefficient of only 0.34. Substitution of the ARM-radiosonde surface values into the AIRS profiles improves the correlation to 0.95. The use of AIRS profiles above the surface level provides surface-based CAPE values that are very similar to those computed from Vaisala radiosondes. These results suggest that a merging of surface observations with satellite-derived thermodynamic profiles could make better use of the satellite spatial coverage and temporal sampling for estimation of CAPE in near–real time.

HOW A MARINE METEOROLOGIST CAN HELP YOUR OFFSHORE OIL AND GAS OPERATIONS? OR WHY USE A MARINE METEOROLOGIST?

INTRODUCTION Companies that must perform ocean transport, services, or construction should use a marine meteorologist when time means money. I have been involved in marine and tropical marine weather forecasting, hindcasting, and research for 40 years and the key to getting the most out of your marine meteorologist is communication. Weather Research Center has found that a good communication system between your operational teams and marine meteorologist operations can help to avoid or minimize costly weather impacts. Your meteorologist should be a Board Certified Consulting Meteorologist [CCM], a meteorologist recommended by the American Meteorological Society, a Royal Meteorological Society Chartered Meteorologist [CMet], or a Qualified Environmental Professional [QEP] by the Institute for Professional Environmental Practice. The key to understanding the impact of weather on your operations is to have dialogue where you communicate to the marine meteorologists your critical operating limits, weather wind...

Women in meteorology

Women in meteorology

From months to minutes – exploring the value of high‐resolution rainfall observation and prediction during the UK winter storms of 2013/2014

ABSTRACTAs the societal impacts of hazardous weather and other environmental pressures grow, the need for integrated predictions that can represent the numerous feedbacks and linkages between sub‐systems is greater than ever. This was well illustrated during winter 2013/2014 when a prolonged series of deep Atlantic depressions over a 3 month period resulted in damaging wind storms and exceptional rainfall accumulations. The impact on livelihoods and property from the resulting coastal surge and river and surface flooding was substantial. This study reviews the observational and modelling toolkit available to operational meteorologists during this period, which focusses on precipitation forecasting months, weeks, days and hours ahead of time. The routine availability of high‐resolution (km scale) deterministic and ensemble rainfall predictions for short‐range weather forecasting as well as weather‐resolving seasonal prediction capability represent notable landmarks that have resulted from significant progress in research and development over the past decade. Latest results demonstrated that the suite of global and high‐resolution UK numerical weather prediction models provided excellent guidance during this period, supported by high‐resolution observations networks, such as weather radar, which proved resilient in difficult conditions. The specific challenges for demonstrating this performance for high‐resolution precipitation forecasts are discussed. Despite their good operational performance, there remains a need to further develop the capability and skill of these tools to fully meet user needs and to increase the value that they deliver. These challenges are discussed, notably to accelerate the progress towards understanding the value that might be delivered through more integrated environmental prediction.

Design and Development of a Drifting Buoy for Gathering Environmental Data

Operational meteorologists and Oceanographers rely on real-time environmental data to run their numerical prediction models, even carry on the research. The ground station network is dense and the data of good quality, but there is not enough environmental data from the oceans, particularly in data-sparse areas not covered by commercial ships reporting environmental data. A drifting ocean buoy is described. The drifter consists of three main components: a surface float, a tether assembly and a dimensionally-stable drogue. It utilizes a drag structure which follows the water mass of the ocean as it flows in the form of the ocean current, and which also has an aerodynamically shaped low wind drag mast to minimize wind induced errors in ocean current drift measurements; the drag structure also being stable and resistant to heaving (pitch and roll) so as to maintain a mast carried antenna above the water even at high sea states.

The SAARC STORM: A Coordinated Field Experiment on Severe Thunderstorm Observations and Regional Modeling over the South Asian Region

This article describes a unique field experiment on Severe Thunderstorm Observations and Regional Modeling (STORM) jointly undertaken by eight South Asian countries. Several pilot field experiments have been conducted so far, and the results are analyzed. The field experiments will continue through 2016. The STORM program was originally conceived for understanding the severe thunderstorms known as nor'westers that affect West Bengal and the northeastern parts of India during the pre-monsoon season. The nor'westers cause loss of human lives and damage to properties worth millions of dollars annually. Since the neighboring South Asian countries are also affected by thunderstorms, the STORM program is expanded to cover the South Asian countries under the South Asian Association for Regional Cooperation (SAARC). It covers all the SAARC countries (Afghanistan, Bangladesh, Bhutan, India, Maldives, Nepal, Pakistan, and Sri Lanka) in three phases. Some of the science plans (monitoring the life cycle of nor'westers/severe thunderstorms and their three-dimensional structure) designed to understand the interrelationship among dynamics, cloud microphysics, and electrical properties in the thunderstorm environment are new to severe weather research. This paper describes the general setting of the field experiment and discusses preliminary results based on the pilot field data. Typical lengths and the intensity of squall lines, the speed of movements, and cloud-top temperatures and their heights are discussed based on the pilot field data. The SAARC STORM program will complement the Severe Weather Forecast Demonstration Project (SWFDP) of the WMO. It should also generate large-scale interest for fueling research among the scientific community and broaden the perspectives of operational meteorologists and researchers.

Principles and applications of dual-polarization weather radar. Part III: Artifacts

With the new data collected with polarimetric radars comes a set of new data quality issues and artifacts. It is important for these artifacts to be recognized and understood as such, thereby allowing operational meteorologists to focus on the interpretation of the physically important observations. In this third part of the series, artifacts found in polarimetric radar data are described and explained. These include attenuation and differential attenuation, nonuniform beam filling, depolarization streaks, and three-body scattering signatures. Examples of each are given, along with explanations of what they mean, and how they may be used to provide some information about a storm and its microphysics.

Classification and Conceptual Models for Heavy Snowfall Events over East Vancouver Island of British Columbia, Canada

AbstractThe East Vancouver Island region on the west coast of Canada is prone to heavy snow in winter due to its unique geographical setting, which involves complicated interactions among the atmosphere, ocean, and local topography. The challenge for operational meteorologists is to distinguish a weather system that produces extreme snow amounts from one that produces modest amounts in this region. In this study, subjective, objective, and hybrid classification techniques are used to analyze the characteristics of 81 snowstorms observed in this region over a 10-yr period (2000–09). It is demonstrated that there are four principal weather patterns (occluded front, lee low, warm advection, and convective storm) conducive to heavy snow in East Vancouver Island. The occluded front pattern is the most ubiquitous for producing snow events, while the lee low pattern is the most extreme snow producer that poses the biggest forecast challenge.Based on the identified weather patterns and a further investigation of five key weather ingredients, four conceptual models are developed to illustrate the meteorological processes leading to significant snowfalls in East Vancouver Island. These conceptual models have the potential to help meteorologists better understand and identify weather systems that would produce heavy snowfalls in this region and, therefore, improve forecasting and warning performance.

Comparison and Analyses of Existing Objective, Quantificational Blocking Indices

There are existing objective, quantitative blocking indices that could be classified into five types: the departure method, the Tibaldi and Molteni（TM） method, the dynamical index(PV-θindex), the dynamical potential vorticity (PV) based index, and the circumfluent type method. Persistent blocking highs can be associated with destructive weather including low temperatures, snowfall, and anomalous freezing from January 1st to February 2nd 2008 in China. Using the daily reanalysis data provided by NCEP/NCAR, the merits and flaws of these five objective methods are studied individually, including the intensity、size and frequency of block. Generally speaking, each method has both advantages and clearly identifiable limitations because of the mathematical formulation for each objective blocking index. Based on the merits and flaws of these blocking indices summarized in this study, investigators and operational meteorologists could apply these blocking indices better if they can select an index compatible with their study objectives, or improve upon and innovate a new method.

The Impact of Evaporation on Polarimetric Characteristics of Rain: Theoretical Model and Practical Implications

Abstract Soon, the National Weather Service’s Weather Surveillance Radar-1988 Doppler (WSR-88D) network will be upgraded to allow dual-polarization capabilities. Therefore, it is imperative to understand and identify microphysical processes using the polarimetric variables. Though melting and size sorting of hydrometeors have been investigated, there has been relatively little focus devoted to the impacts of evaporation on the polarimetric characteristics of rainfall. In this study, a simple explicit bin microphysics one-dimensional rainshaft model is constructed to quantify the impacts of evaporation (neglecting the collisional processes) on vertical profiles of polarimetric radar variables in rain. The results of this model are applicable for light to moderate rain (<10 mm h−1). The modeling results indicate that the amount of evaporation that occurs in the subcloud layer is strongly dependent on the initial shape of the drop size distribution aloft, which can be assessed with polarimetric measurements. Understanding how radar-estimated rainfall rates may change in height due to evaporation is important for quantitative precipitation estimates, especially in regions far from the radar or in regions of complex terrain where low levels may not be adequately sampled. In addition to quantifying the effects of evaporation, a simple method of estimating the amount of evaporation that occurs in a given environment based on polarimetric radar measurements of the reflectivity factor ZH and differential reflectivity ZDR aloft is offered. Such a technique may be useful to operational meteorologists and hydrologists in estimating the amount of precipitation reaching the surface, especially in regions of poor low-level radar coverage such as mountainous regions or locations at large distances from the radar.