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Rip currents are poorly understood by the public and thus a leading cause of weather-related fatalities in the United States. Individuals who speak languages other than English, such as Spanish-speaking communities, have been historically underserved by communication efforts for natural hazards and thus are at additional risk from rip currents. In response, the National Weather Service (NWS) has developed rip current outreach tools translated into Spanish in recent years, though their efficacy has not been systematically tested. We therefore surveyed members of the Spanish-speaking community in the New York City area to gain insights into how the NWS two-page rip current informational brochure is working and possible improvements to be made. The English version of the brochure was also tested, and the results from the two languages were compared. Quantitative survey results indicate that while both brochures are generally effective, several changes could be made to improve clarity, especially for Spanish speakers, who found more issues with the Spanish version. For example, the translation of the term rip current itself used by the NWS, "corrientes de resaca," was determined to be confusing by some Spanish speakers, as were other pieces of text with complex scientific terms. Moreover, certain graphics contained in the brochure were difficult to understand for users in both languages. The results of this work can be used by the NWS and other agencies to improve their Spanish risk communication tools and can also be used as a guide when translating scientific information into other languages. Significance Statement: Rip currents, narrow channels of fast-moving water that can pull swimmers away from the shore, are among the leading weather-related killers in the United States yet are poorly understood by the public. Recent efforts to reduce society's vulnerability to rip currents include the translation of outreach materials from English to Spanish. This study evaluated a new National Weather Service Spanish rip current informational brochure and compared it to the English version. The results show that while both the English and Spanish brochures were generally effective at communicating risk, the Spanish version had more issues, primarily surrounding the translation of scientific terms and phrases. Findings from this research can help guide scientists in designing improved non-English severe weather outreach products. [ABSTRACT FROM AUTHOR]

Coastal water level information is crucial for understanding flood occurrences and changing risks. Here, we validate the preliminary version (0.9) of NOAA's Coastal Ocean Reanalysis (CORA), which is a 43-year reanalysis (1979-2021) of hourly coastal water levels for the Gulf of Mexico and Atlantic Ocean (i.e., the Gulf and East Coast region, or GEC). CORA-GEC v0.9 was conducted by the Renaissance Computing Institute using the coupled ADCIRC+SWAN coastal circulation and wave model. The model uses an unstructured mesh of nodes with varying spatial resolution that averages 400 m near the coast and is much coarser in the open ocean. Water level variations associated with tides and meteorological forcing are explicitly modeled, while lower-frequency water level variations are included by dynamically assimilating observations from NOAA's National Water Level Observation Network. We compare CORA to water level observations that were either assimilated or not, and find that the reanalysis generally performs better than a state-of-the-art global ocean reanalysis (GLORYS12) in capturing the variability on monthly, seasonal, and interannual timescales as well as the long-term trend. The variability of hourly non-tidal residuals is also shown to be well resolved in CORA when compared to water level observations. Lastly, we present a case study of extreme water levels and coastal inundations around Miami, Florida to demonstrate an application of CORA for studying flood risks. Our assessment suggests that NOAA's CORA-GEC v0.9 provides valuable information on water levels and flooding occurrence from 1979-2021 in areas that are experiencing changes across multiple time scales. CORA potentially can enhance flood risk assessment along parts of the U.S. Coast that do not have historical water level observations. [ABSTRACT FROM AUTHOR]

Climate classification is a commonly used tool to simplify, visualize and make sense of an otherwise unwieldy amount of climate data in applied climate science research. Typically, these classifications have stemmed from one of two perspectives, either a circulation‐to‐environment (C2E) approach, or an environment‐to‐circulation approach (E2C), each with advantages and drawbacks. This research discusses a novel environment‐to‐circulation‐to‐environment (ECE) perspective to applied climate classification, and develops a specific ECE methodology that utilizes canonical correlation and discriminant analysis—the CANDECE method. The benefits of the ECE approach generally, and the CANDECE methodology specifically, are demonstrated in applying climate classification to aid in modelling anomalous water levels (AWLs) along portions of the East and West coasts of the United States. Results show that the CANDECE method performs better than two traditional classification methods (k‐means and self‐organizing maps [SOMs]) at relating AWLs to their broad‐scale atmospheric setups, especially with regard to both high and low extreme AWLs. It is further demonstrated that, compared with the West coast, the CANDECE method is particularly advantageous along the southeastern US coast, where the primary modes of atmospheric variability (which drive the classifications produced by SOMs and k‐means) do not align with the relevant circulation‐based factors driving AWL variability. While AWLs were utilized for demonstrating the ECE proof‐of‐concept herein, ECE and CANDECE are designed to be useful for any climate application. [ABSTRACT FROM AUTHOR]

Realistic representation of monthly sea level anomalies in coastal regions has been a challenge for global ocean reanalyses. This is especially the case in coastal regions where sea levels are influenced by western boundary currents such as near the U.S. Atlantic Coast and the Gulf of Mexico. For these regions, most ocean reanalyses compare poorly to observations. Problems in reanalyses include errors in data assimilation and horizontal resolutions that are too coarse to simulate energetic currents like the Gulf Stream and Loop Current System. However, model capabilities are advancing with improved data assimilation and higher resolution. Here, we show that some current-generation ocean reanalyses produce monthly sea level anomalies with improved skill when compared to satellite altimetry observations of sea surface heights. Using tide gauge observations for coastal verification, we find the highest skill associated with the GLORYS12 and HYCOM ocean reanalyses. Both systems assimilate altimetry observations and have eddy-resolving horizontal resolutions (1/12°). We found less skill in three other ocean reanalyses (ACCESS-S2, ORAS5, and ORAP6) with coarser, though still eddy-permitting, resolutions (1/4°). The operational reanalysis from ECMWF (ORAS5) and their pilot reanalysis (ORAP6) provide an interesting comparison because the latter assimilates altimetry globally and with more weight, as well as assimilating ocean observations over continental shelves. We find these attributes associated with improved skill near many tide gauges. We also assessed an older reanalysis (CFSR), which has the lowest skill likely due to its lower resolution (1/2°) and lack of altimetry assimilation. ACCESS-S2 likewise does not assimilate altimetry, although its skill is much better than CFSR and only somewhat lower than ORAS5. Since coastal flooding is influenced by sea level anomalies, the recent development of skilful ocean reanalyses on monthly timescales may be useful for better understanding the physical processes associated with flood risks. [ABSTRACT FROM AUTHOR]