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Douglas J. Parker
,
Alan M. Blyth
,
Steven J. Woolnough
,
Andrew J. Dougill
,
Caroline L. Bain
,
Estelle de Coning
,
Mariane Diop-Kane
,
Andre Kamga Foamouhoue
,
Benjamin Lamptey
,
Ousmane Ndiaye
,
Paolo Ruti
,
Elijah A. Adefisan
,
Leonard K. Amekudzi
,
Philip Antwi-Agyei
,
Cathryn E. Birch
,
Carlo Cafaro
,
Hamish Carr
,
Benard Chanzu
,
Samantha J. Clarke
,
Helen Coskeran
,
Sylvester K. Danuor
,
Felipe M. de Andrade
,
Kone Diakaria
,
Cheikh Dione
,
Cheikh Abdoulahat Diop
,
Jennifer K. Fletcher
,
Amadou T. Gaye
,
James L. Groves
,
Masilin Gudoshava
,
Andrew J. Hartley
,
Linda C. Hirons
,
Ishiyaku Ibrahim
,
Tamora D. James
,
Kamoru A. Lawal
,
John H. Marsham
,
J. N. Mutemi
,
Emmanuel Chilekwu Okogbue
,
Eniola Olaniyan
,
J. B. Omotosho
,
Joseph Portuphy
,
Alexander J. Roberts
,
Juliane Schwendike
,
Zewdu T. Segele
,
Thorwald H. M. Stein
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Andrea L. Taylor
,
Christopher M. Taylor
,
Tanya A. Warnaars
,
Stuart Webster
,
Beth J. Woodhams
, and
Lorraine Youds

Abstract

Africa is poised for a revolution in the quality and relevance of weather predictions, with potential for great benefits in terms of human and economic security. This revolution will be driven by recent international progress in nowcasting, numerical weather prediction, theoretical tropical dynamics, and forecast communication, but will depend on suitable scientific investment being made. The commercial sector has recognized this opportunity and new forecast products are being made available to African stakeholders. At this time, it is vital that robust scientific methods are used to develop and evaluate the new generation of forecasts. The Global Challenges Research Fund (GCRF) African Science for Weather Information and Forecasting Techniques (SWIFT) project represents an international effort to advance scientific solutions across the fields of nowcasting, synoptic and short-range severe weather prediction, subseasonal-to-seasonal (S2S) prediction, user engagement, and forecast evaluation. This paper describes the opportunities facing African meteorology and the ways in which SWIFT is meeting those opportunities and identifying priority next steps. Delivery and maintenance of weather forecasting systems exploiting these new solutions requires a trained body of scientists with skills in research and training, modeling and operational prediction, and communications and leadership. By supporting partnerships between academia and operational agencies in four African partner countries, the SWIFT project is helping to build capacity and capability in African forecasting science. A highlight of SWIFT is the coordination of three weather forecasting “Testbeds”—the first of their kind in Africa—which have been used to bring new evaluation tools, research insights, user perspectives, and communications pathways into a semioperational forecasting environment.

Open access
Lars van Galen
,
Oscar Hartogensis
,
Imme Benedict
, and
Gert-Jan Steeneveld

Abstract

We report on redesigning the undergraduate course in synoptic meteorology and weather forecasting at Wageningen University (the Netherlands) to meet the current-day requirements for operational forecasters. Weather strongly affects human activities through its impact on transportation, energy demand planning, and personal safety, especially in the case of weather extremes. Numerical weather prediction (NWP) models have developed rapidly in recent decades, with reasonably high scores, even on the regional scale. The amount of available NWP model output has sharply increased. Hence, the role and value of the operational weather forecaster has evolved into the role of information selector, data quality manager, storyteller, and product developer for specific customers. To support this evolution, we need new academic training methods and tools at the bachelor’s level. Here, we present a renewed education strategy for our weather forecasting class, called Atmospheric Practical, including redefined learning outcomes, student activities, and assessments. In addition to teaching the interpretation of weather maps, we underline the need for twenty-first-century skills like dealing with open data, data handling, and data analysis. These skills are taught using Jupyter Python Notebooks as the leading analysis tool. Moreover, we introduce assignments about communication skills and forecast product development as we aim to benefit from the internationalization of the classroom. Finally, we share the teaching material presented in this paper for the benefit of the community.

Full access
Kristin M. Calhoun
,
Kodi L. Berry
,
Darrel M. Kingfield
,
Tiffany Meyer
,
Makenzie J. Krocak
,
Travis M. Smith
,
Greg Stumpf
, and
Alan Gerard

Abstract

NOAA’s Hazardous Weather Testbed (HWT) is a physical space and research framework to foster collaboration and evaluate emerging tools, technology, and products for NWS operations. The HWT’s Experimental Warning Program (EWP) focuses on research, technology, and communication that may improve severe and hazardous weather warnings and societal response. The EWP was established with three fundamental hypotheses: 1) collaboration with operational meteorologists increases the speed of the transition process and rate of adoption of beneficial applications and technology, 2) the transition of knowledge between research and operations benefits both the research and operational communities, and 3) including end users in experiments generates outcomes that are more reliable and useful for society. The EWP is designed to mimic the operations of any NWS Forecast Office, providing the opportunity for experiments to leverage live and archived severe weather activity anywhere in the United States. During the first decade of activity in the EWP, 15 experiments covered topics including new radar and satellite applications, storm-scale numerical models and data assimilation, total lightning use in severe weather forecasting, and multiple social science and end-user topics. The experiments range from exploratory and conceptual research to more controlled experimental design to establish statistical patterns and causal relationships. The EWP brought more than 400 NWS forecasters, 60 emergency managers, and 30 broadcast meteorologists to the HWT to participate in live demonstrations, archive events, and data-denial experiments influencing today’s operational warning environment and shaping the future of warning research, technology, and communication for years to come.

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Lili Zeng
,
Gengxin Chen
,
Ke Huang
,
Ju Chen
,
Yunkai He
,
Fenghua Zhou
,
Yikai Yang
,
Zhanlin Liang
,
Qihua Peng
,
Rui Shi
,
Tilak Priyadarshana Gamage
,
Rongyu Chen
,
Jian Li
,
Zhenqiu Zhang
,
Zewen Wu
,
Linghui Yu
, and
Dongxiao Wang

Abstract

As an important part of the Indo-Pacific warm pool, the Indian Ocean has great significance for research on the Asian monsoon system and global climate change. From the 1960s onward, several international and regional programs have led to important new insights into the Indian Ocean. The eastern Tropical Indian Ocean Observation Network (TIOON) was established in 2010. The TIOON consists of two parts: large-scope observations and moored measurements. Large-scope observations are performed by the eastern Tropical Indian Ocean Comprehensive Experiment Cruise (TIO-CEC). Moored measurements are executed by the TIOON mooring array and the hydrological meteorological buoy. By 2019, 10 successful TIO-CEC voyages had been accomplished, making this mission the most comprehensive scientific investigation in China. The TIO-CEC voyages have collected temperature/salinity profiles, GPS radiosonde profiles, and other observations in the Indian Ocean. To supplement the existing buoy array in the Indian Ocean, an enhanced TIOON mooring array consisting of eight subthermocline acoustic Doppler current profiler (ADCP) moorings, was established since 2013. The TIOON mooring equipped with both upward-looking and downward-looking WHLS75K ADCP provide valuable current monitoring information to depth of 1,000 m in the Indian Ocean. To improve air–sea interaction monitoring, two real-time hydrological–meteorological buoys were deployed in 2019 and 2020 in the equatorial Indian Ocean. A better understanding of the Indian Ocean requires continuous and long-term observations. The TIOON program and other aspiring field investigation programs will be promoted in the future.

Full access
A. Marshak
,
A. Ackerman
,
A. M. da Silva
,
T. Eck
,
B. Holben
,
R. Kahn
,
R. Kleidman
,
K. Knobelspiesse
,
R. Levy
,
A. Lyapustin
,
L. Oreopoulos
,
L. Remer
,
O. Torres
,
T. Várnai
,
G. Wen
, and
J. Yorks

Abstract

Aerosol properties are fundamentally different near clouds than away from clouds. This paper reviews the current state of knowledge of aerosol properties in the near-low-cloud environment and quantitatively compares them with aerosols far from clouds, according to remote sensing observations. It interprets observations of aerosol properties from different sensors using satellite, aircraft, and ground-based observations. The correlation (and anticorrelation) between proximity to cloud and aerosol properties is discussed. Retrieval artifacts in the near-cloud environment are demonstrated and quantified for different sensor attributes and environmental conditions. Finally, the paper describes the possible corrections for near-cloud enhancement in remote sensing retrievals. This study is timely in view of science definition studies for NASA’s Aerosol, Cloud, Convection and Precipitation (ACCP) mission, which will also seek to directly link aerosol properties to nearby clouds.

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Yuan Yang
,
Ming Pan
,
Peirong Lin
,
Hylke E. Beck
,
Zhenzhong Zeng
,
Dai Yamazaki
,
Cédric H. David
,
Hui Lu
,
Kun Yang
,
Yang Hong
, and
Eric F. Wood

Abstract

Better understanding and quantification of river floods for very local and “flashy” events calls for modeling capability at fine spatial and temporal scales. However, long-term discharge records with a global coverage suitable for extreme events analysis are still lacking. Here, grounded on recent breakthroughs in global runoff hydrology, river modeling, high-resolution hydrography, and climate reanalysis, we developed a 3-hourly river discharge record globally for 2.94 million river reaches during the 40-yr period of 1980–2019. The underlying modeling chain consists of the VIC land surface model (0.05°, 3-hourly) that is well calibrated and bias corrected and the RAPID routing model (2.94 million river and catchment vectors), with precipitation input from MSWEP and other meteorological fields downscaled from ERA5. Flood events (above 2-yr return) and their characteristics (number, spatial distribution, and seasonality) were extracted and studied. Validations against 3-hourly flow records from 6,000+ gauges in CONUS and daily records from 14,000+ gauges globally show good modeling performance across all flow ranges, good skills in reconstructing flood events (high extremes), and the benefit of (and need for) subdaily modeling. This data record, referred as Global Reach-Level Flood Reanalysis (GRFR), is publicly available at https://www.reachhydro.org/home/records/grfr.

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Emily V. Fischer
,
Brittany Bloodhart
,
Kristen Rasmussen
,
Ilana B. Pollack
,
Meredith G. Hastings
,
Erika Marin-Spiotta
,
Ankur R. Desai
,
Joshua P. Schwarz
,
Stephen Nesbitt
, and
Deanna Hence

Abstract

Sexual harassment in field settings brings unique challenges for prevention and response, as field research occurs outside “typical” workplaces, often in remote locations that create additional safety concerns and new team dynamics. We report on a project that has 1) trained field project participants to recognize, report, and confront sexual harassment, and 2) investigated the perceptions, attitudes, and experiences of field researchers regarding sexual harassment. Precampaign surveys from four major, multi-institutional, domestic, and international field projects indicate that the majority of sexual harassment reported prior to the field campaigns was hostile work environment harassment, and women were more likely to be the recipients, on average reporting two to three incidents each. The majority of those disclosing harassment indicated that they coped with past experiences by avoiding their harasser or downplaying incidents. Of the incidences reported (47) in postcampaign surveys of the four field teams, all fell under the category of hostile work environment and included incidents of verbal, visual, and physical harassment. Women’s harassment experiences were perpetrated by men 100% of the time, and the majority of the perpetrators were in more senior positions than the victims. Men’s harassment experiences were perpetrated by a mix of women and men, and the majority came from those at the same position of seniority. Postproject surveys indicate that the training programs (taking place before the field projects) helped participants come away with more positive than negative emotions and perceptions of the training, the leadership, and their overall experiences on the field campaign.

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Xiaoduo Pan
,
Xuejun Guo
,
Xin Li
,
Xiaolei Niu
,
Xiaojuan Yang
,
Min Feng
,
Tao Che
,
Rui Jin
,
Youhua Ran
,
Jianwen Guo
,
Xiaoli Hu
, and
Adan Wu

Abstract

The Tibetan Plateau, known as the world’s “Third Pole” due to its high altitude, is experiencing rapid, intense climate change, similar to and even far more than that occurring in the Arctic and Antarctic. Scientific data sharing is very important to address the challenges of better understanding the unprecedented changes in the Third Pole and their impacts on the global environment and humans. The National Tibetan Plateau Data Center (TPDC, http://data.tpdc.ac.cn) is one of the first 20 national data centers endorsed by the Ministry of Science and Technology of China in 2019 and features the most complete scientific data for the Tibetan Plateau and surrounding regions, hosting more than 3,500 datasets in diverse disciplines. Fifty datasets featuring high-mountain observations, land surface parameters, near-surface atmospheric forcing, cryospheric variables, and high-profile article-associated data over the Tibetan Plateau, frequently being used to quantify the hydrological cycle and water security, early warning assessments of glacier avalanche disasters, and other geoscience studies on the Tibetan Plateau, are highlighted in this manuscript. The TPDC provides a cloud-based platform with integrated online data acquisition, quality control, analysis, and visualization capability to maximize the efficiency of data sharing. The TPDC shifts from the traditional centralized architecture to a decentralized deployment to effectively connect Third Pole–related data from other domestic and international data sources. As an embryo of data sharing and management over extreme environment in the upcoming “big data” era, the TPDC is dedicated to filling the gaps in data collection, discovery, and consumption in the Third Pole, facilitating scientific activities, particularly those featuring extensive interdisciplinary data use.

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Adam L. Houston
,
Lisa M. PytlikZillig
, and
Janell C. Walther

Abstract

Inclusion of unmanned aircraft systems (UAS) into the weather surveillance network has the potential to improve short-term (<1 day) weather forecasts through direct integration of UAS-collected data into the forecast process and assimilation into numerical weather prediction models. However, one of the primary means by which the value of any new sensing platform can be assessed is through consultation with principal stakeholders. National Weather Service (NWS) forecasters are principal stakeholders responsible for the issuance of short-term forecasts. The purpose of the work presented here is to use results from a survey of 630 NWS forecasters to assess critical data gaps that impact short-term forecast accuracy and explore the potential role of UAS in filling these gaps. NWS forecasters view winter precipitation, icing, flood, lake-effect/lake-enhanced snow, turbulence, and waves as the phenomena principally impacted by data gaps. Of the 10 high-priority weather-related characteristics that need to be observed to fill critical data gaps, 7 are either measures of precipitation or related to precipitation-producing phenomena. The three most important UAS capabilities/characteristics required for useful data for weather forecasting are real-time or near-real-time data, the ability to integrate UAS data with additional data gathered by other systems, and UASs equipped with cameras to verify forecasts and monitor weather. Of the three operation modes offered for forecasters to consider, targeted surveillance is considered to be the most important compared to fixed site profiling or transects between fixed sites.

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James O. Pinto
,
Debbie O’Sullivan
,
Stewart Taylor
,
Jack Elston
,
C. B. Baker
,
David Hotz
,
Curtis Marshall
,
Jamey Jacob
,
Konrad Barfuss
,
Bruno Piguet
,
Greg Roberts
,
Nadja Omanovic
,
Martin Fengler
,
Anders A. Jensen
,
Matthias Steiner
, and
Adam L. Houston

Abstract

The boundary layer plays a critical role in regulating energy and moisture exchange between the surface and the free atmosphere. However, the boundary layer and lower atmosphere (including shallow flow features and horizontal gradients that influence local weather) are not sampled at time and space scales needed to improve mesoscale analyses that are used to drive short-term model predictions of impactful weather. These data gaps are exasperated in remote and less developed parts of the world where relatively cheap observational capabilities could help immensely. The continued development of small, weather-sensing uncrewed aircraft systems (UAS), coupled with the emergence of an entirely new commercial sector focused on UAS applications, has created novel opportunities for partially filling this observational gap. This article provides an overview of the current level of readiness of small UAS for routinely sensing the lower atmosphere in support of national meteorological and hydrological services (NMHS) around the world. The potential benefits of UAS observations in operational weather forecasting and numerical weather prediction are discussed, as are key considerations that will need to be addressed before their widespread adoption. Finally, potential pathways for implementation of weather-sensing UAS into operations, which hinge on their successful demonstration within collaborative, multi-agency-sponsored testbeds, are suggested.

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