Bulletin of the American Meteorological Society

doi: 10.1175/1520-0477-96.1.fmipmid: N/A

Yu, Tian-You; Parsons, David; Nakakita, Eiichi; Tsuda, Toshitaka; Ishikawa, Hirohiko

doi: 10.1175/BAMS-D-14-00027.1pmid: N/A

doi: 10.1175/1520-0477-96.1.11pmid: N/A

Van Den Besselaar, Else J. M.; Klein Tank, Albert M. G.; Van Der Schrier, Gerard; Abass, Mariama S.; Baddour, Omar; Van Engelen, Aryan F.V.; Freire, Andrea; Hechler, Peer; Laksono, Bayu Imbang; Iqbal, Bayu Imbang; Jilderda, Rudmer; Foamouhoue, Andre Kamga; Kattenberg, Arie; Leander, Robert;

Zhang, Fuqing; Weng, Yonghui

doi: 10.1175/BAMS-D-13-00231.1pmid: N/A

Performance in the prediction of hurricane intensity and associated hazards has been evaluated for a newly developed convection-permitting forecast system that uses ensemble data assimilation techniques to ingest high-resolution airborne radar observations from the inner core. This system performed well for three of the ten costliest Atlantic hurricanes: Ike (2008), Irene (2011), and Sandy (2012). Four to five days before these storms made landfall, the system produced good deterministic and probabilistic forecasts of not only track and intensity, but also of the spatial distributions of surface wind and rainfall. Averaged over all 102 applicable cases that have inner-core airborne Doppler radar observations during 2008–2012, the system reduced the day-2-to-day-4 intensity forecast errors by 25%–28% compared to the corresponding National Hurricane Center’s official forecasts (which have seen little or no decrease in intensity forecast errors over the past two decades). Empowered by sufficient computing resources, advances in both deterministic and probabilistic hurricane prediction will enable emergency management officials, the private sector, and the general public to make more informed decisions that minimize the losses of life and property.

Morrow, Betty H.; Lazo, Jeffrey K.; Rhome, Jamie; Feyen, Jesse

doi: 10.1175/BAMS-D-13-00197.1pmid: N/A

Storm surge associated with tropical and extratropical cyclones has a long history of causing death and destruction along our coastlines. With more than 123 million people living in coastal shoreline areas and much of the densely populated Atlantic and Gulf coastal areas less than 10 ft (∼3 m) above mean sea level, the threat has never been greater. In this article, we summarize and integrate the most intensive series of studies completed to date on communication of storm surge risk. These were primarily geographically focused stakeholder surveys for evaluating the storm surge communication perceptions and preferences of forecasters, broadcast meteorologists, public officials, and members of the public—each a primary user group for storm surge forecasts. According to findings from seven surveys, each group strongly supports the National Weather Service (NWS) issuing watches and warnings for storm surge, whether associated with tropical cyclones (TC) or extratropical (ET) cyclones. We discuss results on public understanding of storm surge vulnerability, respondents’ preferences for separate storm surge information products, and initial assessments of potential storm surge warning text and graphics. Findings from the research reported here are being used to support relevant NWS decisions, including a storm surge watch and warning product that has been approved for use on an experimental basis in 2015 and the National Hurricane Center (NHC) issuance of local surge inundations maps on an experimental basis in 2014.

Stiller-Reeve, Mathew Alexander; Syed, Md. Abu; Spengler, Thomas; Spinney, Jennifer A.; Hossain, Rumana

doi: 10.1175/BAMS-D-13-00144.1pmid: N/A

The monsoon onset is a critical event in the Bangladesh calendar, especially for the domestic agricultural sector. Providing information about the monsoon onset for the past, present, and future has potential benefit for a country so vulnerable to changes in climate. But, when does the monsoon start? To produce any scientific information about monsoon onsets, lengths, and withdrawals, we first need to apply a monsoon definition to our data. Choosing a scientific definition is not such a simple exercise in Bangladesh. Different definitions lead to different monsoon onsets and thereby also monsoon lengths. If a climate application aims to provide information about the monsoon onset, then we need to understand how the people who might use this information perceive the monsoon onset. We then need to understand how their perceptions compare with previous scientific work. In this study we carried out a structured questionnaire in six rural regions around Bangladesh and asked the local agriculturists how they defined the monsoon and when they thought it started. It turns out that the agriculturists and previous scientific publications do not necessarily agree. Our results do not undermine previous scientific work on the monsoon in Bangladesh, but they do carry an important message about how we should design, implement, and evaluate climate applications in Bangladesh that encompass the monsoon onset.

MacPhee, David; Canetto, Silvia Sara

doi: 10.1175/BAMS-D-12-00215.1pmid: N/A

Past studies suggest that the atmospheric sciences may have the fewest women of all geosciences occupations. The purpose of this study was to document the representation of women in the academic atmospheric sciences, specifically women’s representation among faculty in U.S. atmospheric sciences doctoral programs. A second purpose was to describe the demographic profile, educational preparation, and occupational destination of atmospheric sciences graduate students—as a way to gauge the characteristics and progress of women potentially in the pipeline for academic positions. Data on atmospheric sciences faculty ( N = 813) were collected from the websites of 34 doctoral programs. Women constituted 17% of tenure-track and tenured atmospheric sciences faculty. Most departments (53%) had two or fewer female tenure-track or tenured faculty members. The proportion of female faculty members declined as academic rank increased. Institutional data for graduate students ( N = 1,153) at a subset of these programs showed that at matriculation, women represented 39% of the students. The typical provenience disciplines of atmospheric sciences graduate students were majors with a low participation of women. Finally, significantly fewer women than men completed their doctoral degrees or pursued academic careers upon completion of the doctorate. Only 20% of doctoral degree completers who chose academia were women. Based on these findings and those of related studies, we forecast a persisting scarcity of female faculty members in U.S. atmospheric sciences doctoral programs.

Ashouri, Hamed; Hsu, Kuo-Lin; Sorooshian, Soroosh; Braithwaite, Dan K.; Knapp, Kenneth R.; Cecil, L. Dewayne; Nelson, Brian R.; Prat, Olivier P.

doi: 10.1175/BAMS-D-13-00068.1pmid: N/A

A new retrospective satellite-based precipitation dataset is constructed as a climate data record for hydrological and climate studies. Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks–Climate Data Record (PERSIANN-CDR) provides daily and 0.25° rainfall estimates for the latitude band 60°S–60°N for the period of 1 January 1983 to 31 December 2012 (delayed present). PERSIANN-CDR is aimed at addressing the need for a consistent, long-term, high-resolution, and global precipitation dataset for studying the changes and trends in daily precipitation, especially extreme precipitation events, due to climate change and natural variability. PERSIANN-CDR is generated from the PERSIANN algorithm using GridSat-B1 infrared data. It is adjusted using the Global Precipitation Climatology Project (GPCP) monthly product to maintain consistency of the two datasets at 2.5° monthly scale throughout the entire record. Three case studies for testing the efficacy of the dataset against available observations and satellite products are reported. The verification study over Hurricane Katrina (2005) shows that PERSIANN-CDR has good agreement with the stage IV radar data, noting that PERSIANN-CDR has more complete spatial coverage than the radar data. In addition, the comparison of PERSIANN-CDR against gauge observations during the 1986 Sydney flood in Australia reaffirms the capability of PERSIANN-CDR to provide reasonably accurate rainfall estimates. Moreover, the probability density function (PDF) of PERSIANN-CDR over the contiguous United States exhibits good agreement with the PDFs of the Climate Prediction Center (CPC) gridded gauge data and the Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA) product. The results indicate high potential for using PERSIANN-CDR for long-term hydroclimate studies in regional and global scales.

Tan, Jianguo; Yang, Limin; Grimmond, C. S. B.; Shi, Jianping; Gu, Wen; Chang, Yuanyong; Hu, Ping; Sun, Juan; Ao, Xiangyu; Han, Zhihui

doi: 10.1175/BAMS-D-13-00216.1pmid: N/A

Observations of atmospheric conditions and processes in cities are fundamental to understanding the interactions between the urban surface and weather/climate, improving the performance of urban weather, air quality, and climate models, and providing key information for city end users (e.g., decision makers, stakeholders, public). In this paper, Shanghai’s Urban Integrated Meteorological Observation Network (SUIMON) and some examples of intended applications are introduced. Its characteristics include being multipurpose (e.g., forecast, research, service), multifunction (e.g., high-impact weather, city climate, special end users), multiscale (e.g., macro/meso, urban, neighborhood, street canyon), multivariable (e.g., thermal, dynamic, chemical, biometeorological, ecological), and multiplatform (e.g., radar, wind profiler, ground based, satellite based, in situ observation/sampling). Underlying SUIMON is a data management system to facilitate exchange of data and information. The overall aim of the network is to improve coordination strategies and instruments, to identify data gaps based on science- and user-driven requirements, and to intelligently combine observations from a variety of platforms by using a data assimilation system that is tuned to produce the best estimate of the current state of the urban atmosphere.