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Joseph E. Trujillo-Falcón
,
Orlando Bermúdez
,
Krizia Negrón-Hernández
,
John Lipski
,
Elizabeth Leitman
, and
Kodi Berry

Abstract

According to recent Census data, the Hispanic or Latino population represents nearly 1 in 5 Americans today, where 71.1% of these individuals speak Spanish at home. Despite increased efforts among the weather enterprise, establishing effective risk communication strategies for Spanish-speaking populations has been an uphill battle. No frameworks exist for translating weather information into the Spanish language, nor are there collective solutions that address this problem within the weather world. The objective of this article is threefold. First, the current translation issue in Spanish is highlighted. Through research conducted at the NOAA/NWS Storm Prediction Center, situations are revealed where regional varieties of Spanish contributed to inconsistent risk messaging across the bilingual weather community. Second, existing resources are featured so that interested readers are aware of ongoing efforts to translate weather information into Spanish. Organizations within the weather service, like the NWS Multimedia Assistance in Spanish Team and the NWS Spanish Outreach Team, are highlighted for their pioneer work on Spanish weather communication. Last, a framework for translation standardization in the atmospheric sciences is introduced, along with future initiatives that are being sought by NWS and AMS to enhance Spanish hazardous weather communication.

Full access
Cheng Liu
,
Meng Gao
,
Qihou Hu
,
Guy P. Brasseur
, and
Gregory R. Carmichael

Abstract

Monitoring and modeling/predicting air pollution are crucial to understanding the links between emissions and air pollution levels, to supporting air quality management, and to reducing human exposure. Yet, current monitoring networks and modeling capabilities are unfortunately inadequate to understand the physical and chemical processes above ground and to support attribution of sources. We highlight the need for the development of an international stereoscopic monitoring strategy that can depict three-dimensional (3D) distribution of atmospheric composition to reduce the uncertainties and to advance diagnostic understanding and prediction of air pollution. There are three reasons for the implementation of stereoscopic monitoring: 1) current observation networks provide only partial view of air pollution, and this can lead to misleading air quality management actions; 2) satellite retrievals of air pollutants are widely used in air pollution studies, but too often users do not acknowledge that they have large uncertainties, which can be reduced with measurements of vertical profiles; and 3) air quality modeling and forecasting require 3D observational constraints. We call on researchers and policymakers to establish stereoscopic monitoring networks and share monitoring data to better characterize the formation of air pollution, optimize air quality management, and protect human health. Future directions for advancing monitoring and modeling/predicting air pollution are also discussed.

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David Mayers
and
Christopher Ruf

Abstract

MTrack is an automated algorithm that determines the center location (latitude and longitude) of a tropical cyclone from a scalar wind field derived from satellite observations. Accurate storm centers are useful for operational forecasting of tropical cyclones and for their reanalysis (e.g., research on storm surge modeling). Currently, storm center fixes have significantly larger errors for weak, disorganized storms. The MTrack algorithm presented here improves storm centers in some of those cases. It is also automated and, therefore, less subjective than manual fixes made by forecasters. The MTrack algorithm, which was originally designed to work with CYGNSS wind speed measurements, is applied to SMAP winds for the first time. The average difference between MTrack and Best Track storm center locations is 21, 36, and 46 km for major hurricanes, category 1–2 hurricanes, and tropical storms, respectively. MTrack is shown to operate successfully when a storm is only partially sampled by the observing satellite and when the eye of the storm is not resolved.

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Evert I. F. de Bruijn
,
Fred C. Bosveld
,
Siebren de Haan
, and
Albert A.M. Holtslag

Abstract

We report about a new third-party observation, namely, wind measurements derived from hot-air balloon (HAB) tracks. We first compare the HAB winds with wind measurements from a meteorological tower and a radio acoustic wind profiler, both situated at the topographically flat observatory near Cabauw, the Netherlands. To explore the potential of this new type of wind observation in other topographies, we present an intriguing HAB flight in Austria with a spectacular mountain–valley circulation. Subsequently, we compare the HAB data with a numerical weather prediction (NWP) model during 2011–13 and the standard deviation of the wind speed is 2.3 m s−1. Finally, we show results from a data assimilation feasibility experiment that reveals that HAB wind information can have a positive impact on a hindcasted NWP trajectory.

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Bo-Wen Shen
,
Roger A. Pielke Sr.
,
Xubin Zeng
,
Jong-Jin Baik
,
Sara Faghih-Naini
,
Jialin Cui
, and
Robert Atlas

Abstract

Over 50 years since Lorenz’s 1963 study and a follow-up presentation in 1972, the statement “weather is chaotic” has been well accepted. Such a view turns our attention from regularity associated with Laplace’s view of determinism to irregularity associated with chaos. In contrast to single-type chaotic solutions, recent studies using a generalized Lorenz model (GLM) have focused on the coexistence of chaotic and regular solutions that appear within the same model using the same modeling configurations but different initial conditions. The results, with attractor coexistence, suggest that the entirety of weather possesses a dual nature of chaos and order with distinct predictability. In this study, based on the GLM, we illustrate the following two mechanisms that may enable or modulate two kinds of attractor coexistence and, thus, contribute to distinct predictability: 1) the aggregated negative feedback of small-scale convective processes that can produce stable nontrivial equilibrium points and, thus, enable the appearance of stable steady-state solutions and their coexistence with chaotic or nonlinear oscillatory solutions, referred to as the first and second kinds of attractor coexistence; and 2) the modulation of large-scale time-varying forcing (heating) that can determine (or modulate) the alternative appearance of two kinds of attractor coexistence. Based on our results, we then discuss new opportunities and challenges in predictability research with the aim of improving predictions at extended-range time scales, as well as subseasonal to seasonal time scales.

Open access
Gerald L Potter
,
George J. Huffman
,
David T. Bolvin
,
Michael G. Bosilovich
,
Judy Hertz
, and
Laura E. Carriere

ABSTRACT

We introduce a simple method for detecting changes, both transient and persistent, in reanalysis and merged satellite products due to both natural climate variability and changes to the data sources/analyses used as input. This note demonstrates this Histogram Anomaly Time Series (HATS) method using tropical ocean daily precipitation from MERRA-2 and from GPCP One-Degree Daily (1DD) precipitation estimates. Rather than averaging over space or time, we create a time series display of histograms for each increment of data (such as a day or month). Regional masks such as land–ocean can be used to isolate particular domains. While the histograms reveal subtle structures in the time series, we can amplify the signal by computing the histogram’s anomalies from its climatological seasonal cycle. The qualitative analysis provided by this scheme can then form the basis for more quantitative analyses of specific features, both real and analysis induced. As an example, in the tropical oceans the analysis clearly identifies changes in the time series of both reanalysis and observations that may be related to changing inputs.

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Rachel Dryden
and
M. Granger Morgan

Abstract

Hurricane Harvey and other recent weather extremes stimulated extensive public discourse about the role of anthropogenic climate change in amplifying, or otherwise modifying, such events. In tandem, the scientific community has made considerable progress on statistical “climate attribution.” However, explaining these statistical methods to the public has posed challenges. Using appropriately designed “spinner boards,” we find that even members of the general public who do not understand the difference between weather and climate are readily able to understand basic concepts of attribution and explain those concepts to others. This includes both understanding and explaining the way in which the probability of an extreme weather event may increase as a result of climate change and explaining how the intensity of hurricanes can be increased. If properly developed and used by TV weather forecasters and news reporters, this method holds the potential to significantly improve public understanding of climate attribution.

Free access
Paul W. Staten
,
Kevin M. Grise
,
Sean M. Davis
,
Kristopher B. Karnauskas
,
Darryn W. Waugh
,
Amanda C. Maycock
,
Qiang Fu
,
Kerry Cook
,
Ori Adam
,
Isla R. Simpson
,
Robert J Allen
,
Karen Rosenlof
,
Gang Chen
,
Caroline C. Ummenhofer
,
Xiao-Wei Quan
,
James P. Kossin
,
Nicholas A. Davis
, and
Seok-Woo Son

Abstract

Over the past 15 years, numerous studies have suggested that the sinking branches of Earth’s Hadley circulation and the associated subtropical dry zones have shifted poleward over the late twentieth century and early twenty-first century. Early estimates of this tropical widening from satellite observations and reanalyses varied from 0.25° to 3° latitude per decade, while estimates from global climate models show widening at the lower end of the observed range. In 2016, two working groups, the U.S. Climate Variability and Predictability (CLIVAR) working group on the Changing Width of the Tropical Belt and the International Space Science Institute (ISSI) Tropical Width Diagnostics Intercomparison Project, were formed to synthesize current understanding of the magnitude, causes, and impacts of the recent tropical widening evident in observations. These working groups concluded that the large rates of observed tropical widening noted by earlier studies resulted from their use of metrics that poorly capture changes in the Hadley circulation, or from the use of reanalyses that contained spurious trends. Accounting for these issues reduces the range of observed expansion rates to 0.25°–0.5° latitude decade‒1—within the range from model simulations. Models indicate that most of the recent Northern Hemisphere tropical widening is consistent with natural variability, whereas increasing greenhouse gases and decreasing stratospheric ozone likely played an important role in Southern Hemisphere widening. Whatever the cause or rate of expansion, understanding the regional impacts of tropical widening requires additional work, as different forcings can produce different regional patterns of widening.

Free access
Anthony Arguez
,
Shannan Hurley
,
Anand Inamdar
,
Laurel Mahoney
,
Ahira Sanchez-Lugo
, and
Lilian Yang
Free access
Neil F. Laird
and
Nicholas D. Metz
Free access