Spot Weather Forecasts: Improving Utilization, Communication, and Perceptions of Accuracy in Sophisticated User Groups

2017 ◽  
Vol 9 (2) ◽  
pp. 215-226 ◽  
Author(s):  
Tamara U. Wall ◽  
Timothy J. Brown ◽  
Nicholas J. Nauslar
Keyword(s):  
Prescribed Fire ◽  
Wildland Fire ◽  
Forecast Accuracy ◽  
Weather Forecast ◽  
Weather Conditions ◽  
The United States ◽  
Weather Forecasts ◽  
Improving Accuracy ◽  
Sophisticated User ◽  
Weather Service

Abstract Spot weather forecasts (SWFs) are issued by Weather Service offices throughout the United States and are primarily for use by wildfire and prescribed fire practitioners for monitoring local-scale weather conditions. This paper focuses on use of SWFs by prescribed fire practitioners. Based on qualitative, in-depth interviews with fire practitioners and National Weather Service forecasters, this paper examines factors that influence perceptions of accuracy and utilization of SWFs. Results indicate that, while several well-understood climatological, topographical, and data-driven factors influence forecast accuracy, social factors likely have the greater impact on perceptions of accuracy, quantitative accuracy, and utilization. These include challenges with building and maintaining relationships between forecasters and fire managers, communication issues around updating SWFs, and communicating forecast confidence and uncertainty. Operationally, improved quantitative skill in a forecast is always desirable, but key opportunities for improving accuracy and utilization of these forecasts lie in 1) enhancing the processes and mechanisms for communication between a Weather Forecast Office and fire practitioners—before, during, and after an SWFs is issued—and 2) working with the wildland fire community to experiment with forecast uncertainty and confidence information in SWFs and evaluate impacts of these approaches.

Effectiveness of prescribed fire as a fuel treatment in Californian coniferous forests

2009 ◽  
Vol 18 (2) ◽  
pp. 165 ◽  
Author(s):  
Nicole M. Vaillant ◽  
Jo Ann Fites-Kaufman ◽  
Scott L. Stephens
Keyword(s):  
Prescribed Fire ◽  
Forest Structure ◽  
Tree Mortality ◽  
Wildland Fire ◽  
Fire Behavior ◽  
Weather Conditions ◽  
Fire Effects ◽  
The United States ◽  
Behavior Modeling ◽  
Fuel Loads

Effective fire suppression and land use practices over the last century have altered forest structure and increased fuel loads in many forests in the United States, increasing the occurrence of catastrophic wildland fires. The most effective methods to change potential fire behavior are to reduce surface fuels, increase the canopy base height and reduce canopy bulk density. This multi-tiered approach breaks up the continuity of surface, ladder and crown fuels. Effectiveness of fuel treatments is often shown indirectly through fire behavior modeling or directly through monitoring wildland fire effects such as tree mortality. The present study investigates how prescribed fire affected fuel loads, forest structure, potential fire behavior, and modeled tree mortality at 90th and 97.5th percentile fire weather conditions on eight National Forests in California. Prescription burning did not significantly change forest structure at most sites. Total fuel loads (litter, duff, 1, 10, 100, and 1000-h) were reduced by 23 to 78% across the sites. The reduction in fuel loads altered potential fire behavior by reducing fireline intensity and increasing torching index and crowning index at most sites. Predicted tree mortality decreased after treatment as an effect of reduced potential fire behavior and fuel loads. To use limited fuel hazard reduction resources efficiently, more effort could be placed on the evaluation of existing fire hazards because several stands in the present study had little potential for adverse fire effects before prescribed fire was applied.

scholarly journals How Can Existing Ground-Based Profiling Instruments Improve European Weather Forecasts?

2019 ◽  
Vol 100 (4) ◽  
pp. 605-619 ◽  
Author(s):  
A. J. Illingworth ◽  
D. Cimini ◽  
A. Haefele ◽  
M. Haeffelin ◽  
M. Hervo ◽  
...  
Keyword(s):  
Real Time ◽  
Traffic Control ◽  
Positive Impact ◽  
Weather Forecast ◽  
Weather Conditions ◽  
Time Data ◽  
Weather Forecasts ◽  
Forecast Models ◽  
Wind Lidar ◽  
Microwave Radiometers

Abstract To realize the promise of improved predictions of hazardous weather such as flash floods, wind storms, fog, and poor air quality from high-resolution mesoscale models, the forecast models must be initialized with an accurate representation of the current state of the atmosphere, but the lowest few kilometers are hardly accessible by satellite, especially in dynamically active conditions. We report on recent European developments in the exploitation of existing ground-based profiling instruments so that they are networked and able to send data in real time to forecast centers. The three classes of instruments are i) automatic lidars and ceilometers providing backscatter profiles of clouds, aerosols, dust, fog, and volcanic ash, the last two being especially important for air traffic control; ii) Doppler wind lidars deriving profiles of wind, turbulence, wind shear, wind gusts, and low-level jets; and iii) microwave radiometers estimating profiles of temperature and humidity in nearly all weather conditions. The project includes collaboration from 22 European countries and 15 European national weather services, which involves the implementation of common operating procedures, instrument calibrations, data formats, and retrieval algorithms. Currently, data from 265 ceilometers in 19 countries are being distributed in near–real time to national weather forecast centers; this should soon rise to many hundreds. One wind lidar is currently delivering real time data rising to 5 by the end of 2019, and the plan is to incorporate radiometers in 2020. Initial data assimilation tests indicate a positive impact of the new data.

scholarly journals A Review of Community Smoke Exposure from Wildfire Compared to Prescribed Fire in the United States

2018 ◽  
Author(s):  
Kathleen M. Navarro ◽  
Don Schweizer ◽  
John R. Balmes ◽  
Ricardo Cisneros
Keyword(s):  
United States ◽  
Particulate Matter ◽  
Land Management ◽  
Prescribed Fire ◽  
Wildland Fire ◽  
The United States ◽  
Smoke Exposure ◽  
Management Tool ◽  
Wildfire Smoke ◽  
Scientific Papers

Prescribed fire, intentionally ignited low-intensity fires, and managed wildfires, wildfires that are allowed to burn for land management benefit, could be used as a land management tool to create forests that are resilient to wildland fire. This could lead to fewer large catastrophic wildfires in the future. However, we must consider the public health impacts of the smoke that is emitted from wildland and prescribed fire. The objective of this synthesis is to examine the differences in ambient community-level exposures to particulate matter (PM2.5) from smoke in the United States from two smoke exposure scenarios – wildfire fire and prescribed fire. A systematic search was conducted to identify scientific papers to be included in this review. Web of Science Core Collection and PubMed for scientific papers, and Google Scholar were used to identify any grey literature or reports to be included in this review. Sixteen studies that examined particulate matter exposure from smoke were identified for this synthesis – nine wildland fire studies and seven prescribed fire studies. PM2.5 concentrations from wildfire smoke were found to be significantly lower than reported PM2.5 concentrations from prescribed fire smoke. Wildfire studies focused on assessing air quality impacts to communities that were nearby fires and urban centers that were far from wildfires. However, the prescribed fire studies used air monitoring methods that focused on characterizing exposures and emissions directly from and next to the burns. This review highlights a need for a better understanding of wildfire smoke impact over the landscape. It is essential for properly assessing population exposure to smoke from different fire types.

The United States National Weather Service Real-Time Flood Forecasting

2017 ◽  
Author(s):  
Pedro J. Restrepo
Keyword(s):  
Real Time ◽  
Snow Water Equivalent ◽  
Weather Forecast ◽  
The United States ◽  
Flood Forecasting ◽  
Federal State ◽  
National Weather Service ◽  
Precipitation Temperature ◽  
Snow Water ◽  
Weather Service

The U.S. National Weather Service (NWS) is the agency responsible for flood forecasting. Operational flow forecasting at the NWS is carried out at the 13 river forecasting centers for main river flows. Flash floods, which occur in small localized areas, are forecast at the 122 weather forecast offices. Real-time flood forecasting is a complex process that requires the acquisition and quality control of remotely sensed and ground-based observations, weather and climate forecasts, and operation of reservoirs, water diversions, and returns. Currently used remote-sense observations for operational hydrologic forecasts include satellite observations of precipitation, temperature, snow cover, radar observations of precipitation, and airborne observations of snow water equivalent. Ground-based observations include point precipitation, temperature, snow water equivalent, soil moisture and temperature, river stages, and discharge. Observations are collected by a number of federal, state, municipal, tribal and private entities, and transmitted to the NWS on a daily basis. Once the observations have been checked for quality, a hydrologic forecaster uses the Community Hydrologic Prediction System (CHPS), which takes care of managing the sequence of models and their corresponding data needs along river reaches. Current operational forecasting requires an interaction between the forecaster and the models, in order to adjust differences between the model predictions and the observations, thus improving the forecasts. The final step in the forecast process is the publication of forecasts.

scholarly journals Usefulness of the United States National Weather Service Radar Display as Rated by Website Users

2018 ◽  
Vol 10 (4) ◽  
pp. 673-691 ◽  
Author(s):  
Michelle E. Saunders ◽  
Kevin D. Ash ◽  
Jennifer M. Collins
Keyword(s):  
United States ◽  
Spatial Clustering ◽  
Weather Radar ◽  
Weather Conditions ◽  
Radar Data ◽  
The United States ◽  
Perceived Usefulness ◽  
National Weather Service ◽  
Weather Information ◽  
Weather Service

Abstract Weather radar is now widely viewed by the general public in the United States via television, computers/tablets, and smartphones. Anyone can consult near-real-time maps and animations of weather radar data when weather conditions are a factor. However, the usefulness of weather radar data for each user depends on a complex interaction of factors. There have been few studies providing conceptual arguments and empirical data to better understand what the most important factors are and to comprehend patterns of public weather radar use across the United States. The first part of this research provides a basic conceptual framework for research investigating the usefulness of weather radar displays as a source of weather information and as a decision aid. The second part aims to uncover several factors that influence the perceived usefulness rating of the National Weather Service (NWS) website’s weather radar display at both national and regional levels using variables gathered from the 2014 NWS customer satisfaction survey alongside relevant geographic and climatological variables. Data analyses include spatial clustering and ordinal regression utilized within a generalized linear model methodology. Overall, respondents who are more familiar with the NWS and their products, as well as those who indicate they are more likely to take action based on information provided by the NWS, are more likely to find the NWS radar display useful. Geographically, the NWS radar display is most useful to persons residing in the southern United States. Lightning is the most important hazard associated with higher radar usefulness ratings.

scholarly journals Increase success rate of weather forecasts for the airfield by integration of measurements of meteorological parameters of the atmosphere

2019 ◽  
Vol 22 (5) ◽  
pp. 43-53
Author(s):  
E. A. Bolelov
Keyword(s):  
Temperature Profile ◽  
Meteorological Parameters ◽  
Weather Forecast ◽  
Aviation Industry ◽  
High Quality ◽  
Weather Forecasts ◽  
Meteorological Systems ◽  
Reliable Knowledge ◽  
Weather Service

Accuracy of aviation weather forecasts is one of the main indicators characterizing the quality of meteorological support of flights. A significant influence of the quality of meteorological support on flight safety and regularity is confirmed by the results of the annual tests conducted by the Federal Agency for Air Transport of Russia and "Aviamettelecom of Roshydromet". Currently, the quality of meteorological support of flights is still at a low level compared to countries that are recognized leaders in the aviation industry. To develop high-quality weather forecasts for the airfield weather service requires a large amount of information, which is based on the data of meteorological measurements and observations obtained by aerodrome meteorological systems. The lack of reliable information about the value of meteorological parameters of the atmosphere does not allow the weather man to form a qualitative weather forecast, so there are cases when the weather forecaster of the airfield weather service gives a reinsurance forecast. At the same time modern airfield meteorological systems have sufficiently advanced systems and devices for measuring the parameters of the atmosphere. The full use of all the advantages of these systems for the development of high-quality weather forecasts and, therefore, to improve their accuracy can be achieved through integrated processing of the meteorological information received. The most important characteristic of the atmosphere is the air temperature at aircraft flying altitudes. Reliable knowledge of the temperature profile largely determines the justification of weather forecasts and forecasts of dangerous weather events for aviation. The article considers, as an example, the algorithm of complex processing of information about the temperature profile in the aerodrome area, the structural scheme of the algorithm is obtained and te results of modeling the temperature profile and its complex evaluation are presented.

scholarly journals Site-specific analog weather-forecast system for northwest Himalaya, India

2008 ◽  
Vol 49 ◽  
pp. 224-230 ◽  
Author(s):  
Dan Singh ◽  
Amreek Singh ◽  
Ashwagosha Ganju
Keyword(s):  
Weather Forecasting ◽  
Forecast Accuracy ◽  
Weather Forecast ◽  
Analog Model ◽  
Site Specific ◽  
Northwest Himalaya ◽  
Weather Forecasts ◽  
The Past ◽  
Weather Events ◽  
Weather Situation

AbstractIn an analog weather-forecasting procedure, recorded weather in the past analogs corresponding to the current weather situation is used to predict future weather. Consistent with the procedure, a theoretical framework is developed to predict weather at a specific site in the Pir Panjal range of the northwest Himalaya, India, using surface weather observations of the past ten winters (1991/92 to 2001/02) 3 days in advance. Weather predictions were made as snow day with quantitative snowfall category or no-snow day, for day1 through day3. As currently deployed, the procedure routinely provides a 3 day point weather forecast as guidance information to a weather and avalanche forecaster. Forecasts by analog model are evaluated by the various accuracy measures achieved for an independent dataset of three winters (2002/03 to 2004/05). The results indicate that weather forecasts by analog model are quite reliable, in that forecast accuracy corresponds closely to the relative frequencies of observed weather events. Moreover, qualitative weather (snow day or no-snow day) and quantitative categorical snowfall forecasts (quantitative snowfall category for snow day) are better than reference forecasts based on persistence and climatology for day1 predictions. Site-specific snowfall forecast guidance may play a major role in assessing avalanche danger, and accordingly formulating an avalanche forecast for a given area in advance.

Weather on the Go: An Assessment of Smartphone Mobile Weather Application Use among College Students

2018 ◽  
Vol 99 (11) ◽  
pp. 2245-2257 ◽  
Author(s):  
Minh D. Phan ◽  
Burrell E. Montz ◽  
Scott Curtis ◽  
Thomas M. Rickenbach
Keyword(s):  
United States ◽  
College Students ◽  
Undergraduate Students ◽  
Information Acquisition ◽  
Weather Forecast ◽  
The United States ◽  
Southeast United States ◽  
Weather Forecasts ◽  
Weather Information ◽  
Device Technology

AbstractMillions of people in the United States regularly acquire information from weather forecasts for a wide variety of reasons. The rapid growth in mobile device technology has created a convenient means for people to retrieve this data, and in recent years, mobile weather applications (MWAs) have quickly gained popularity. Research on weather sources, however, has been unable to sufficiently capture the importance of this form of information gathering. As use of these apps continues to grow, it is important to gain insight on the usefulness of MWAs to consumers. To better examine MWA preferences and behaviors relating to acquired weather information, a survey of 308 undergraduate students from three different universities throughout the southeast United States was undertaken. Analyses of the survey showed that smartphone MWAs are the primary weather forecast source among college students. Additionally, MWA users tend to seek short-term forecast information, like the hourly forecast, from their apps. Results also provide insight into daily MWA use by college students as well as perceptions of and preferential choices for specific MWA features and designs. The information gathered from this study will allow other researchers to better evaluate and understand the changing landscape of weather information acquisition and how this relates to the uses, perceptions, and values people garner from forecasts. Organizations that provide weather forecasts have an ever-growing arsenal of resources to disseminate information, making research of this topic extremely valuable for future development of weather communication technology.

scholarly journals Pesonalising weather forecasts using AI techniques

2021 ◽  
Author(s):  
Dimitrios Stamoulis ◽  
Panos Giannopoulos
Keyword(s):  
General Public ◽  
Visual Representations ◽  
Weather Forecast ◽  
Weather Conditions ◽  
Scientific Data ◽  
Receiver Side ◽  
Weather Forecasts ◽  
Personal Level ◽  
The Individual ◽  
Over Time

<p>Communicating the scientific data of the weather forecasts to the general public has always been a challenge. Using computer graphics’ visual representations to convey the message to television viewers and through weather apps and websites has certainly helped a lot to popularize the weather forecast consumption by the general public. However, these representations are not information rich since they are abstraction; moreover they are not always very actionable on the receiver side to help one decide how s/he will “live” the forecast weather conditions. Therefore, there is a need to personalize the forecast based on past user experience and personal needs. The forecast has to become more human- and needs-oriented and more focused to the particular requirements of each individual person. The challenge is to move from providing the abstraction of atmospheric information to a real sense of how the weather will "feel" to the individual.</p><p>We therefore propose a new co-creation process in which the audience is called on to provide a daily feedback on how they lived the weather conditions personally, so that, “my personal forecast” can be produced making the forecast more actionable on the user side. Preliminary, but more personalized, such attempts include the “feels like” temperature forecasts. To arrive at the “my personal forecast”, AI-based recommender systems need to be applied, using fuzzy logic as the appropriate method for the user to express how s/he actually lived personally lived weather conditions every day. Over time this information can then be used to transform science-based descriptions of weather conditions into a sense of how the weather will be experienced at a personal level.</p>

scholarly journals Megafires on the Southern Great Plains

2019 ◽  
pp. 164-179 ◽  
Author(s):  
T. Todd Lindley ◽  
Douglas A. Speheger ◽  
Matthew A. Day ◽  
Gregory P. Murdoch ◽  
Bradley R. Smith ◽  
...  
Keyword(s):  
Great Plains ◽  
Wildland Fire ◽  
Management Strategies ◽  
Weather Conditions ◽  
Fire Spread ◽  
The United States ◽  
Fire Policy ◽  
Southern Great Plains ◽  
Antecedent Precipitation ◽  
Complex Phenomena

A global increase in megafires has occurred since the mid-1990s. Defined as wildfires that burn more than 405 km2 (100 000 ac), megafires are complex phenomena with wide ranging societal impacts. In the United States, scientific literature and wildland fire policy has traditionally focused upon megafires in forests of the American West. However, megafires also pose a significant threat to life and property on the southern Great Plains. The southern Great Plains is characterized by grass-dominated prairie and is climatologically prone to dry and windy weather, which facilitates extreme rates of fire spread leading to some of the largest wildfires in North America. This study documents 16 megafires on the plains of New Mexico, Texas, Oklahoma, and Kansas between 2006 and 2018. Most of these megafires occurred during southern Great Plains wildfire outbreaks, or plains firestorms, characterized by fire-effective low-level thermal ridges. Fuel and weather conditions supporting the 2006–2018 plains megafires are quantified by antecedent precipitation anomalies, fuel moisture, Energy Release Component, relative humidity, sustained wind speed, and temperature percentiles. Three modes of plains megafire evolution are identified by the analyses as short-duration, long-duration, and hybrid. Abrupt wind shifts and carryover fire in heavy dead fuels dictate megafire potential and evolutionary type. The presented analyses define favorable fuel and weather conditions that allow forecasters to discriminate megafire environments from typical plains fire episodes. Further, predictive signals for plains megafire conceptual model types can improve anticipation of southern Great Plains megafire evolution, threats, and management strategies.

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