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Thomas M. Hamill, Chris Snyder, and Rebecca E. Morss

Abstract

The statistical properties of analysis and forecast errors from commonly used ensemble perturbation methodologies are explored. A quasigeostrophic channel model is used, coupled with a 3D-variational data assimilation scheme. A perfect model is assumed.

Three perturbation methodologies are considered. The breeding and singular-vector (SV) methods approximate the strategies currently used at operational centers in the United States and Europe, respectively. The perturbed observation (PO) methodology approximates a random sample from the analysis probability density function (pdf) and is similar to the method performed at the Canadian Meteorological Centre. Initial conditions for the PO ensemble are analyses from independent, parallel data assimilation cycles. Each assimilation cycle utilizes observations perturbed by random noise whose statistics are consistent with observational error covariances. Each member’s assimilation/forecast cycle is also started from a distinct initial condition.

Relative to breeding and SV, the PO method here produced analyses and forecasts with desirable statistical characteristics. These include consistent rank histogram uniformity for all variables at all lead times, high spread/skill correlations, and calibrated, reduced-error probabilistic forecasts. It achieved these improvements primarily because 1) the ensemble mean of the PO initial conditions was more accurate than the mean of the bred or singular-vector ensembles, which were centered on a less-skilful control initial condition—much of the improvement was lost when PO initial conditions were recentered on the control analysis; and 2) by construction, the perturbed observation ensemble initial conditions permitted realistic variations in spread from day to day, while bred and singular-vector perturbations did not. These results suggest that in the absence of model error, an ensemble of initial conditions performs better when the initialization method is designed to produce random samples from the analysis pdf. The perturbed observation method did this much more satisfactorily than either the breeding or singular-vector methods.

The ability of the perturbed observation ensemble to sample randomly from the analysis pdf also suggests that such an ensemble can provide useful information on forecast covariances and hence improve future data assimilation techniques.

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Hyun Mee Kim, Michael C. Morgan, and Rebecca E. Morss

Abstract

The structure and evolution of analysis error and adjoint-based sensitivities [potential enstrophy initial singular vectors (SVs) and gradient sensitivities of the forecast error to initial conditions] are compared following a cyclone development in a three-dimensional quasigeostrophic channel model. The results show that the projection of the evolved SV onto the forecast error increases during the evolution.

Based on the similarities of the evolved SV to the forecast error, use of the evolved SV is suggested as an adaptive observation strategy. The use of the evolved SV strategy for adaptive observations is evaluated by performing observation system simulation experiments using a three-dimensional variational data assimilation scheme under the perfect model assumption. Adaptive strategies using the actual forecast error, gradient sensitivity, and initial SV are also tested. The observation system simulation experiments are implemented for five simulated synoptic cases with two different observation spacings and three different configurations of adaptive observation location densities (sparse, dense, and mixed), and the impact of the adaptive strategies is compared with that of the nonadaptive, fixed observations.

The impact of adaptive strategies varies with the observation density. For a small number of observations, several of the adaptive strategies tested reduce forecast error more than the nonadaptive strategy. For a large number of observations, it is more difficult to reduce forecast errors using adaptive observations. The evolved SV strategy performs as well as or better than the adjoint-based strategies for both observation densities. The impact of using the evolved SVs rather than the adjoint-based sensitivities for adaptive observation purposes is larger in the situation of a large number of observation stations for which the forecast error reduction by adjoint- based adaptive strategies is difficult.

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Julie L. Demuth, Jeffrey K. Lazo, and Rebecca E. Morss

Abstract

Past research has shown that individuals vary in their attitudes and behaviors regarding weather forecast information. To deepen knowledge about these variations, this article explores 1) patterns in people’s sources, uses, and perceptions of everyday weather forecasts; and 2) relationships among people’s sources, uses, and perceptions of forecasts, their personal characteristics, and their experiences with weather and weather forecasts. It does so by performing factor and regression analysis on data from a nationwide survey of the U.S. public, combined with other data. Forecast uses factored into planning for leisure activities and for work/school-related activities, while knowing what the weather will be like and planning how to dress remained separate. Forecast parameters factored into importance of precipitation parameters and of temperature-related parameters, suggesting that these represent conceptually different constructs. Regression analysis showed that the primary drivers for how often people obtain forecasts are what they use forecasts for and their perceived importance of and confidence in forecast information. People’s forecast uses are explained in large part by their frequency of obtaining forecasts and their perceived importance of temperature-related and precipitation forecast information. This suggests that that individuals’ frequency of obtaining forecasts, forecast use, and importance of forecast parameters are closely interrelated. Sociodemographic characteristics and, to a lesser extent, weather-related experience also influence some aspects of people’s forecast sources, uses, and perceptions. These findings continue to build understanding of variations among weather forecast users, which can help weather information providers improve communication of forecasts to better meet users’ needs.

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Rebecca E. Morss, Kathleen A. Miller, and Maxine S. Vasil

Abstract

Observations of the current state of the atmosphere are a major input to production of modern weather forecasts. As a result, investments in observations are a major component of public expenditures related to weather forecasting. Consequently, from both a meteorological and societal perspective, it is desirable to select an appropriate level of public investment in observations. Although the meteorological community has discussed optimal investment in observations for more than three decades, it still lacks a practical, systematic framework for analyzing this issue. This paper presents the basic elements of such a framework, using an economic approach. The framework is then demonstrated using an example for radiosonde observations and numerical weather forecasts. In presenting and demonstrating the framework, the paper also identifies gaps in existing knowledge that must be addressed before a more complete economic evaluation of investment in observations can be implemented.

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300 Billion Served

Sources, Perceptions, Uses, and Values of Weather Forecasts

Jeffrey K. Lazo, Rebecca E. Morss, and Julie L. Demuth

Understanding the public's sources, perceptions, uses, and values of weather forecasts is integral to providing those forecasts in the most societally beneficial manner. To begin developing this knowledge, we conducted a nationwide survey with more than 1,500 respondents to assess 1) where, when, and how often they obtain weather forecasts; 2) how they perceive forecasts; 3) how they use forecasts; and 4) the value they place on current forecast information. Our results indicate that the average U.S. adult obtains forecasts 115 times per month, which totals to more than 300 billion forecasts per year by the U.S. public. Overall, we find that respondents are highly satisfied with forecasts and have decreasing confidence in forecasts as lead time increases. Respondents indicated that they use forecasts across a range of decision-making contexts. Moreover, nearly three-quarters stated that they usually or always use forecasts simply to know what the weather will be like. Using a simplified valuation approach, we estimate the value of current weather forecast information to be approximately $286 per U.S. household per year, or $31.5 billion total per year value to U.S. households. This compares favorably with total U.S. public and private sector meteorology costs of $5.1 billion a year. To better support the provision of societally beneficial weather information, we advocate for well-designed periodic evaluations of the public's sources, perceptions, uses, and values of weather forecasts. These should include investigations of other important topics such as interpretations of hazardous weather warnings and presentation of uncertainty information.

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Rebecca E. Morss, Kerry A. Emanuel, and Chris Snyder

Abstract

Adaptive sampling uses information about individual atmospheric situations to identify regions where additional observations are likely to improve weather forecasts of interest. The observation network could be adapted for a wide range of forecasting goals, and it could be adapted either by allocating existing observations differently or by adding observations from programmable platforms to the existing network. In this study, observing strategies are explored in a simulated idealized system with a three-dimensional quasigeostrophic model and a realistic data assimilation scheme. Using simple error norms, idealized adaptive observations are compared to nonadaptive observations for a range of observation densities.

The results presented show that in this simulated system, the influence of both adaptive and nonadaptive observations depends strongly on the observation density. For sparse observation networks, the simple adaptive strategies tested are beneficial: adaptive observations can, on average, reduce analysis and forecast errors more than the same number of nonadaptive observations, and they can reduce errors by a given amount using fewer observational resources. In contrast, for dense observation networks it is much more difficult to benefit from adapting observations, at least for the data assimilation method used here. The results suggest that the adaptive strategies tested are most effective when the observations are adapted regularly and frequently, giving the data assimilation system as many opportunities as possible to reduce errors as they evolve. They also indicate that ensemble-based estimates of initial condition errors may be useful for adaptive observations. Further study is needed to understand the extent to which the results from this idealized study apply to more complex, more realistic systems.

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Ann Bostrom, Rebecca E. Morss, Jeffrey K. Lazo, Julie L. Demuth, Heather Lazrus, and Rebecca Hudson

Abstract

The study reported here explores how to enhance the public value of hurricane forecast and warning information by examining the entire warning process. A mental models research approach is applied to address three risk management tasks critical to warnings for extreme weather events: 1) understanding the risk decision and action context for hurricane warnings, 2) understanding the commonalities and conflicts in interpretations of that context and associated risks, and 3) exploring the practical implications of these insights for hurricane risk communication and management. To understand the risk decision and action context, the study develops a decision-focused model of the hurricane forecast and warning system on the basis of results from individual mental models interviews with forecasters from the National Hurricane Center (n = 4) and the Miami–South Florida Weather Forecast Office (n = 4), media broadcasters (n = 5), and public officials (n = 6), as well as a group decision-modeling session with a subset of the forecasters. Comparisons across professionals reveal numerous shared perceptions, as well as some critical differences. Implications for improving extreme weather event forecast and warning systems and risk communication are threefold: 1) promote thinking about forecast and warning decisions as a system, with informal as well as formal elements; 2) evaluate, coordinate, and consider controlling the proliferation of forecast and warning information products; and 3) further examine the interpretation and representation of uncertainty within the hurricane forecast and warning system as well as for users.

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Alan E. Stewart, Jeffrey K. Lazo, Rebecca E. Morss, and Julie L. Demuth

Abstract

The authors used data from a sample of 1465 adults living in the United States to perform a confirmatory factor analysis on the Weather Salience Questionnaire (WxSQ), a 29-item instrument designed to measure the ways in which weather is psychologically significant for people. The original measurement model of the WxSQ was confirmed in the present sample. Additional work also was performed to create a WxSQ short form consisting of seven items. The authors then examined the relationship of weather salience with the respondents’ climate zones of residence and several other weather-related attitudes and behaviors that were assessed in the national sample. People residing in continental and temperate climates expressed significantly more weather salience than those living in dry climates. Further, weather salience was significantly and positively related to the following: 1) the frequency with which people sought weather information and forecasts, 2) the frequency of seeking weather information during the day, 3) the frequency of using forecasts to plan daily activities, 4) seeking weather information for wider geographic areas, and 5) the use of precipitation and temperature forecasts. Weather salience also was significantly and positively related to the confidence people expressed about National Weather Service forecasts and to the perceived importance of these forecasts. The results imply that peoples’ level of weather salience, at least in part, affects their uses of weather information and their confidence in it. These results support the validity of the WxSQ and also reveal some of the psychological bases of people’s perceptions and uses of weather information.

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Cara L. Cuite, Rachael L. Shwom, William K. Hallman, Rebecca E. Morss, and Julie L. Demuth

Abstract

Evacuation before severe coastal storms is a critical tool for keeping coastal residents safe. Effective messaging of evacuations could help save lives, but there is little evidence-based guidance on the advantages or disadvantages of specific messaging. Ideally, evacuation messages would convince those most at risk to evacuate and those who do not need to evacuate to stay in their homes. Using an online survey of 1716 coastal residents in Connecticut, New Jersey, and New York, this study randomly assigned respondents to message conditions in each of two hypothetical storm scenarios. Results from the first scenario indicate that those who saw mandatory evacuation messages had higher evacuation intentions than those who saw advisory messages, and both of those messages resulted in slightly higher evacuation intentions than voluntary evacuation messages. However, voluntary messages resulted in lower evacuation intentions for those that did not live in evacuation zones compared to those who did live in evacuation zones, which may help reduce shadow evacuation. In the second scenario, identifying an evacuation area by the municipality name or the individual’s street name resulted in similar evacuation intentions across all participants. Messages identifying an evacuation area by “flood zone” or “flood-prone area” resulted in equally high evacuation intentions for those who believe they live in a flood zone, but these messages suppressed evacuation intentions for those who do not believe they live in a flood zone. This indicates that such messages could also be an effective approach for reducing shadow evacuation. Implications for risk communicators and emergency managers are discussed.

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Heather Lazrus, Betty H. Morrow, Rebecca E. Morss, and Jeffrey K. Lazo

Abstract

Risk communication may accentuate or alleviate the vulnerability of people who have particular difficulties responding to the threat of hazards such as hurricanes. The process of risk communication involves how hazard information is received, understood, and responded to by individuals and groups. Thus, risk communication and vulnerability interact through peoples' knowledge, attitudes, and practices. This study explores risk communication with several groups that may be at particular risk of hurricane impacts: older adults, newer residents, and persons with disabilities. Focus groups conducted in Miami, Florida, examined how members of these groups express their own vulnerability or agency in terms of receiving, interpreting, and responding to hurricane risk information. Findings indicate that people's interactions with risk information are deeply contextual and are facilitated by their individual agency to cope with their vulnerabilities.

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