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Dive into the research topics where Rebecca E. Morss is active.

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Featured researches published by Rebecca E. Morss.


Bulletin of the American Meteorological Society | 2005

Flood Risk, Uncertainty, and Scientific Information for Decision Making: Lessons from an Interdisciplinary Project

Rebecca E. Morss; Olga V. Wilhelmi; Mary W. Downton; Eve Gruntfest

The magnitude of flood damage in the United States, combined with the uncertainty in current estimates of flood risk, suggest that society could benefit from improved scientific information about flood risk. To help address this perceived need, a group of researchers initiated an interdisciplinary study of climate variability, scientific uncertainty, and hydrometeorological information for flood-risk decision making, focused on Colorados Rocky Mountain Front Range urban corridor. We began by investigating scientific research directions that were likely to benefit flood-risk estimation and management, through consultation with climatologists, hydrologists, engineers, and planners. In doing so, we identified several challenges involved in generating new scientific information to aid flood management in the presence of significant scientific and societal uncertainty. This essay presents lessons learned from this study, along with our observations on the complex interactions among scientific information, unc...


Bulletin of the American Meteorological Society | 1999

The North Pacific Experiment (NORPEX-98): Targeted Observations for Improved North American Weather Forecasts

Rolf H. Langland; Zoltan Toth; Ronald Gelaro; Istvan Szunyogh; M. A. Shapiro; Sharanya J. Majumdar; Rebecca E. Morss; G. D. Rohaly; Christopher S. Velden; Nicholas A. Bond; Craig H. Bishop

Abstract The objectives and preliminary results of an interagency field program, the North Pacific Experiment (NORPEX), which took place between 14 January and 27 February 1998, are described. NORPEX represents an effort to directly address the issue of observational sparsity over the North Pacific basin, which is a major contributing factor in short-range (less than 4 days) forecast failures for land-falling Pacific winter-season storms that affect the United States, Canada, and Mexico. The special observations collected in NORPEX include approximately 700 targeted tropospheric soundings of temperature, wind, and moisture from Global Positioning System (GPS) dropsondes obtained in 38 storm reconnaissance missions using aircraft based primarily in Hawaii and Alaska. In addition, wind data were provided every 6 h over the entire North Pacific during NORPEX, using advanced and experimental techniques to extract information from multispectral geostationary satellite imagery. Preliminary results of NORPEX dat...


Weather and Forecasting | 2008

Communicating Uncertainty in Weather Forecasts: A Survey of the U.S. Public

Rebecca E. Morss; Julie L. Demuth; Jeffrey K. Lazo

Abstract Weather forecasts are inherently uncertain, and meteorologists have information about weather forecast uncertainty that is not readily available to most forecast users. Yet effectively communicating forecast uncertainty to nonmeteorologists remains challenging. Improving forecast uncertainty communication requires research-based knowledge that can inform decisions on what uncertainty information to communicate, when, and how to do so. To help build such knowledge, this article explores the public’s perspectives on everyday weather forecast uncertainty and uncertainty information using results from a nationwide survey. By contributing to the fundamental understanding of laypeople’s views on forecast uncertainty, the findings can inform both uncertainty communication and related research. The article uses empirical data from a nationwide survey of the U.S. public to investigate beliefs commonly held among meteorologists and to explore new topics. The results show that when given a deterministic tem...


Monthly Weather Review | 2000

The Effect of Targeted Dropsonde Observations during the 1999 Winter Storm Reconnaissance Program

Istvan Szunyogh; Z. Toth; Rebecca E. Morss; Sharanya J. Majumdar; Brian J. Etherton; Craig H. Bishop

Abstract In this paper, the effects of targeted dropsonde observations on operational global numerical weather analyses and forecasts made at the National Centers for Environmental Prediction (NCEP) are evaluated. The data were collected during the 1999 Winter Storm Reconnaissance field program at locations that were found optimal by the ensemble transform technique for reducing specific forecast errors over the continental United States and Alaska. Two parallel analysis–forecast cycles are compared; one assimilates all operationally available data including those from the targeted dropsondes, whereas the other is identical except that it excludes all dropsonde data collected during the program. It was found that large analysis errors appear in areas of intense baroclinic energy conversion over the northeast Pacific and are strongly associated with errors in the first-guess field. The “signal,” defined by the difference between analysis–forecast cycles with and without the dropsonde data, propagates at an...


Monthly Weather Review | 2000

A Comparison of Probabilistic Forecasts from Bred, Singular-Vector, and Perturbed Observation Ensembles

Thomas M. Hamill; Chris Snyder; 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. Relativ...


Bulletin of the American Meteorological Society | 2009

300 Billion served: Sources, perceptions, uses, and values of weather forecasts

Jeffrey K. Lazo; Rebecca E. Morss; Julie L. Demuth

Abstract Understanding the publics 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...


Bulletin of the American Meteorological Society | 2010

Collaboration of the weather and climate communities to advance subseasonal-to-seasonal prediction.

Gilbert Brunet; M. A. Shapiro; Brian J. Hoskins; Mitch Moncrieff; Randall M. Dole; George N. Kiladis; Ben P. Kirtman; Andrew C. Lorenc; Brian Mills; Rebecca E. Morss; Saroja Polavarapu; David C. Rogers; John C. Schaake; J. Shukla

The World Weather Research Programme (WWRP) and the World Climate Research Programme (WCRP) have identified collaborations and scientific priorities to accelerate advances in analysis and prediction at subseasonalto-seasonal time scales, which include i) advancing knowledge of mesoscale–planetary-scale interactions and their prediction; ii) developing high-resolution global–regional climate simulations, with advanced representation of physical processes, to improve the predictive skill of subseasonal and seasonal variability of high-impact events, such as seasonal droughts and floods, blocking, and tropical and extratropical cyclones; iii) contributing to the improvement of data assimilation methods for monitoring and predicting used in coupled ocean–atmosphere–land and Earth system models; and iv) developing and transferring diagnostic and prognostic information tailored to socioeconomic decision making. The document puts forward specific underpinning research, linkage, and requirements necessary to achi...


Journal of the Atmospheric Sciences | 2001

Idealized Adaptive Observation Strategies for Improving Numerical Weather Prediction

Rebecca E. Morss; Kerry A. Emanuel; Chris Snyder

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.


Weather and Forecasting | 2007

An In-Person Survey Investigating Public Perceptions of and Responses to Hurricane Rita Forecasts along the Texas Coast

Fuqing Zhang; Rebecca E. Morss; Jason A. Sippel; T. K. Beckman; N. C. Clements; N. L. Hampshire; J. N. Harvey; J. M. Hernandez; Z. C. Morgan; R. M. Mosier; Shuguang Wang; S. D. Winkley

Abstract Hurricane Rita made landfall near the Texas–Louisiana border in September 2005, causing major damage and disruption. As Rita approached the Gulf Coast, uncertainties in the storm’s track and intensity forecasts, combined with the aftermath of Hurricane Katrina, led to major evacuations along the Texas coast and significant traffic jams in the broader Houston area. This study investigates the societal impacts of Hurricane Rita and its forecasts through a face-to-face survey with 120 Texas Gulf Coast residents. The survey explored respondents’ evacuation decisions prior to Hurricane Rita, their perceptions of hurricane risk, and their use of and opinions on Hurricane Rita forecasts. The vast majority of respondents evacuated from Hurricane Rita, and more than half stated that Hurricane Katrina affected their evacuation decision. Although some respondents said that their primary reason for evacuating was local officials’ evacuation order, many reported using information about the hurricane to evalua...


Weather, Climate, and Society | 2010

Storm Surge and ''Certain Death'': Interviews with Texas Coastal Residents following Hurricane Ike

Rebecca E. Morss; Mary H. Hayden

Hurricane Ike made landfall near Galveston, Texas, on 13 September 2008 as a large category 2 storm that generated significant storm surge and flooding. This article presents findings from an empirical case study of Texas coastal residents’ perceptions of hurricane risk, protective decision making, and opinions of hurricane forecasts related to Hurricane Ike. The results are based on data from interviews with 49 residents affected by Hurricane Ike, conducted approximately five weeks after landfall. While most interviewees were aware that Ike was potentially dangerous, many were surprised by how much coastal flooding the hurricane caused and the resulting damage. For many—even long-time residents—Ike was a learning experience. As the hurricane approached, interviewees and their households made complex, evolving preparation and evacuation decisions. Although evacuation orders were an important consideration for some interviewees, many obtained information about Ike frequently from multiple sources to evaluate their own risk and make protective decisions. Given the storm surge and damage Ike caused, a number of interviewees believed that Ike’s classification on the Saffir‐Simpson scale did not adequately communicate the risk Ike posed. The ‘‘certain death’’ statement issued by the National Weather Service helped convince several interviewees to evacuate. However, others had strong negative opinions of the statement that may negatively influence their interpretation of and response to future warnings. As these findings indicate, empirical studies of how intended audiences obtain, interpret, and use hurricane forecasts and warnings provide valuable knowledge that can help design more effective ways to convey hurricane risk.

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Julie L. Demuth

National Center for Atmospheric Research

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Jeffrey K. Lazo

National Center for Atmospheric Research

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Heather Lazrus

National Center for Atmospheric Research

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Chris Snyder

National Center for Atmospheric Research

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Olga V. Wilhelmi

National Center for Atmospheric Research

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Ann Bostrom

University of Washington

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Craig H. Bishop

United States Naval Research Laboratory

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Kenneth M. Anderson

University of Colorado Boulder

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Kerry A. Emanuel

Massachusetts Institute of Technology

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