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ARIANE MIDDEL, SAUD ALKHALED, FLORIAN A. SCHNEIDER, BJOERN HAGEN, and PAUL COSEO

Abstract

Cities increasingly recognize the importance of shade to reduce heat stress and adopt urban forestry plans with ambitious canopy goals. Yet, the implementation of tree and shade plans often faces maintenance, water use, and infrastructure challenges. Understanding the performance of natural and non-natural shade is critical to support active shade management in the built environment. We conducted hourly transects in Tempe, Arizona with the mobile human-biometeorological station MaRTy on hot summer days to quantify the efficacy of various shade types. We sampled sun-exposed reference locations and shade types grouped by urban form, lightweight/engineered shade, and tree species over multiple ground surfaces. We investigated shade performance during the day, at peak incoming solar, peak air temperature, and after sunset using three thermal metrics: the difference between a shaded and sun-exposed location in air temperature (ΔTa), surface temperature (ΔTs), and mean radiant temperature (ΔTMRT). ΔTa did not vary significantly between shade groups, but ΔTMRT spanned a 50°C range across observations. At daytime, shade from urban form most effectively reduced Ts and TMRT, followed by trees and lightweight structures. Shade from urban form performed differently with changing orientation. Tree shade performance varied widely; native and palm trees were least effective, while non-native trees were most effective. All shade types exhibited heat retention (positive ΔTMRT) after sunset. Based on the observations, we developed characteristic shade performance curves that will inform the City of Tempe’s design guidelines towards using “the right shade in the right place” and form the basis for the development of microclimate zones (MCSz).

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Kenneth J. Davis, Edward V. Browell, Sha Feng, Thomas Lauvaux, Michael D. Obland, Sandip Pal, Bianca C. Baier, David F. Baker, Ian T. Baker, Zachary R. Barkley, Kevin W. Bowman, Yu Yan Cui, A. Scott Denning, Joshua P. DiGangi, Jeremy T. Dobler, Alan Fried, Tobias Gerken, Klaus Keller, Bing Lin, Amin R. Nehrir, Caroline P. Normile, Christopher W. O’Dell, Lesley E. Ott, Anke Roiger, Andrew E. Schuh, Colm Sweeney, Yaxing Wei, Brad Weir, Ming Xue, and Christopher A. Williams

Abstract

The Atmospheric Carbon and Transport (ACT) – America NASA Earth Venture Suborbital Mission set out to improve regional atmospheric greenhouse gas (GHG) inversions by exploring the intersection of the strong GHG fluxes and vigorous atmospheric transport that occurs within the midlatitudes. Two research aircraft instrumented with remote and in situ sensors to measure GHG mole fractions, associated trace gases, and atmospheric state variables collected 1140.7 flight hours of research data, distributed across 305 individual aircraft sorties, coordinated within 121 research flight days, and spanning five, six-week seasonal flight campaigns in the central and eastern United States. Flights sampled 31 synoptic sequences, including fair weather and frontal conditions, at altitudes ranging from the atmospheric boundary layer to the upper free troposphere. The observations were complemented with global and regional GHG flux and transport model ensembles. We found that midlatitude weather systems contain large spatial gradients in GHG mole fractions, in patterns that were consistent as a function of season and altitude. We attribute these patterns to a combination of regional terrestrial fluxes and inflow from the continental boundaries. These observations, when segregated according to altitude and air mass, provide a variety of quantitative insights into the realism of regional CO2 and CH4 fluxes and atmospheric GHG transport realizations. The ACT-America data set and ensemble modeling methods provide benchmarks for the development of atmospheric inversion systems. As global and regional atmospheric inversions incorporate ACT-America’s findings and methods, we anticipate these systems will produce increasingly accurate and precise sub-continental GHG flux estimates.

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Adam A. Scaife, Elizabeth Good, Ying Sun, Zhongwei Yan, Nick Dunstone, Hong-Li Ren, Chaofan Li, Riyu Lu, Peili Wu, Zongjian Ke, Zhuguo Ma, Kalli Furtado, Tongwen Wu, Tianjun Zhou, Tyrone Dunbar, Chris Hewitt, Nicola Golding, Peiqun Zhang, Rob Allan, Kirstine Dale, Fraser C. Lott, Peter A. Stott, Sean Milton, Lianchun Song, and Stephen Belcher

Abstract

We present results from the first 6 years of this major UK government funded project to accelerate and enhance collaborative research and development in climate science, forge a strong strategic partnership between UK and Chinese climate scientists and demonstrate new climate services developed in partnership. The development of novel climate services is described in the context of new modelling and prediction capability, enhanced understanding of climate variability and change, and improved observational datasets. Selected highlights are presented from over three hundred peer reviewed studies generated jointly by UK and Chinese scientists within this project. We illustrate new observational datasets for Asia and enhanced capability through training workshops on the attribution of climate extremes to anthropogenic forcing. Joint studies on the dynamics and predictability of climate have identified new opportunities for skilful predictions of important aspects of Chinese climate such as East Asian Summer Monsoon rainfall. In addition, the development of improved modelling capability has led to profound changes in model computer codes and climate model configurations, with demonstrable increases in performance. We also describe the successes and difficulties in bridging the gap between fundamental climate research and the development of novel real time climate services. Participation of dozens of institutes through sub-projects in this programme, which is governed by the Met Office Hadley Centre, the China Meteorological Administration and the Institute of Atmospheric Physics, is creating an important legacy for future collaboration in climate science and services.

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Eric Rappin, Rezaul Mahmood, Udaysankar Nair, Roger A. Pielke Sr., William Brown, Steve Oncley, Joshua Wurman, Karen Kosiba, Aaron Kaulfus, Chris Phillips, Emilee Lachenmeier, Joseph Santanello Jr., Edward Kim, and Patricia Lawston-Parker

Abstract

Extensive expansion in irrigated agriculture has taken place over the last half century. Due to increased irrigation and resultant land use land cover change, the central United States has seen a decrease in temperature and changes in precipitation during the second half of 20th century. To investigate the impacts of widespread commencement of irrigation at the beginning of the growing season and continued irrigation throughout the summer on local and regional weather, the Great Plains Irrigation Experiment (GRAINEX) was conducted in the spring and summer of 2018 in southeastern Nebraska. GRAINEX consisted of two, 15-day intensive observation periods. Observational platforms from multiple agencies and universities were deployed to investigate the role of irrigation in surface moisture content, heat fluxes, diurnal boundary layer evolution, and local precipitation.

This article provides an overview of the data collected and an analysis of the role of irrigation in land-atmosphere interactions on time scales from the seasonal to the diurnal. The analysis shows that a clear irrigation signal was apparent during the peak growing season in mid-July. This paper shows the strong impact of irrigation on surface fluxes, near-surface temperature and humidity, as well as boundary layer growth and decay.

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Leslie A. Duram

Abstract

Previous research indicates the importance of interdisciplinary approaches when teaching about climate change. Specifically, social science perspectives allow students to understand the policy, economic, cultural, and personal influences that impact environmental change. This article describes one such college course that employed active-learning techniques. Course topics included: community resilience, environmental education, historical knowledge timeline, climate justice, social vulnerability, youth action, science communication, hope versus despair, misinformation, and climate refugees. To unify these concepts, engaging activities were developed that specifically address relevant individual, local, state, national, and international climate resilience themes. Students assessed their personal climate footprint, explored social/cultural influences, wrote policy requests to relevant local/state government officials, studied national policy options, and learned about previous global initiatives. The course culminated in a mock global climate summit, which was modeled on a Conference of the Parties (COP) to the United Nations Framework Convention on Climate Change (UNFCCC). This final activity required each student to prepare a policy report and represent a nation in negotiating a multilateral climate agreement. It is accepted that climate change education must include physical data on the impacts of anthropogenic emissions. It is also essential that students appreciate the interdisciplinary nature of climate adaptations, become hopeful about addressing change, and gain skills necessary to engage as informed climate citizens.

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Josh Welty and Xubin Zeng

Abstract

Snowmelt is an essential process for the health and sustenance of numerous communities and ecosystems across the globe, though it also presents potential hazards when ablation processes are exceedingly rapid. Using 4 km daily snow water equivalent, temperature, and precipitation data for three decades (1988-2017), here we provide a broad characterization of extreme snowmelt episodes over the conterminous U.S. in terms of magnitude, timing, and coincident synoptic weather patterns. Larger magnitude extreme snowmelt events usually coincide with minimal precipitation and elevated temperatures. However, certain regions, particularly mountainous regions and the northeast U.S., exhibit greater likelihood of extreme snowmelt events during pronounced rain-on-snow events. During snowmelt extremes, snowmelt rate often exceeds precipitation in many regions. Meteorological patterns and associated water vapor transport most directly connected to extreme events over different regions are classified via a machine learning technique. Over the 30-year study period, there is a weakly increasing trend in the frequency of extremes, though this does not necessarily signify an increase in snowmelt magnitudes.

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Wouter Dorigo, Stephan Dietrich, Filipe Aires, Luca Brocca, Sarah Carter, Jean-François Cretaux, David Dunkerley, Hiroyuki Enomoto, René Forsberg, Andreas Güntner, Michaela I. Hegglin, Rainer Hollmann, Dale F. Hurst, Johnny A. Johannessen, Chris Kummerow, Tong Lee, Kari Luojus, Ulrich Looser, Diego G. Miralles, Victor Pellet, Thomas Recknagel, Claudia Ruz Vargas, Udo Schneider, Philippe Schoeneich, Marc Schröder, Nigel Tapper, Valery Vuglinsky, Wolfgang Wagner, Lisan Yu, Luca Zappa, Michael Zemp, and Valentin Aich

Abstract

Life on Earth vitally depends on the availability of water. Human pressure on freshwater resources is increasing, as is human exposure to weather-related extremes (droughts, storms, floods) caused by climate change. Understanding these changes is pivotal for developing mitigation and adaptation strategies. The Global Climate Observing System (GCOS) defines a suite of Essential Climate Variables (ECVs), many related to the water cycle, required to systematically monitor the Earth's climate system. Since long-term observations of these ECVs are derived from different observation techniques, platforms, instruments, and retrieval algorithms, they often lack the accuracy, completeness, resolution, to consistently to characterize water cycle variability at multiple spatial and temporal scales.

Here, we review the capability of ground-based and remotely sensed observations of water cycle ECVs to consistently observe the hydrological cycle. We evaluate the relevant land, atmosphere, and ocean water storages and the fluxes between them, including anthropogenic water use. Particularly, we assess how well they close on multiple temporal and spatial scales. On this basis, we discuss gaps in observation systems and formulate guidelines for future water cycle observation strategies. We conclude that, while long-term water-cycle monitoring has greatly advanced in the past, many observational gaps still need to be overcome to close the water budget and enable a comprehensive and consistent assessment across scales. Trends in water cycle components can only be observed with great uncertainty, mainly due to insufficient length and homogeneity. An advanced closure of the water cycle requires improved model-data synthesis capabilities, particularly at regional to local scales.

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Michael J. Irvin

Abstract

Kites have been used as weather sensing solutions for over 250 years. The fact that they are simpler to operate and train on than alternative aerial systems, their ability to keep station at a fixed point for a long term, simplified altitude control, and the ease of retrieving their payload attribute to their growing appeal in atmospheric research. NASA, Toyota, and the School of Mechanical and Aerospace Engineering Oklahoma State University are active in developing and deploying high-altitude inflatable kite systems for atmospheric boundary layer (ABL) research—crucial to advancing the accuracy of weather forecasting. Improvements in kite design, as well as instrumentation and supporting infrastructure, are key to further accelerating the use of kites in atmospheric research. The work underway by these researchers is intended to be a deliberate step in the evolutionary development of these beneficial systems.

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I.-I. Lin, Robert F. Rogers, Hsiao-Ching Huang, Yi-Chun Liao, Derrick Herndon, Jin-Yi Yu, Ya-Ting Chang, Jun A. Zhang, Christina M. Patricola, Iam-Fei Pun, and Chun-Chi Lien

Abstract

Devastating Japan in October 2019, Supertyphoon (STY) Hagibis was an important typhoon in the history of the Pacific. A striking feature of Hagibis was its explosive RI (rapid intensification). In 24 h, Hagibis intensified by 100 kt, making it one of the fastest-intensifying typhoons ever observed. After RI, Hagibis’s intensification stalled. Using the current typhoon intensity record holder, i.e., STY Haiyan (2013), as a benchmark, this work explores the intensity evolution differences of these 2 high-impact STYs.

We found that the extremely high pre-storm sea surface temperature reaching 30.5°C, deep/warm pre-storm ocean heat content reaching 160 kJ cm−2, fast forward storm motion of ~8 ms−1, small during-storm ocean cooling effect of ~ 0.5C, significant thunderstorm activity at its center, and rapid eyewall contraction were all important contributors to Hagibis’s impressive intensification. There was 36% more air-sea flux for Hagibis’s RI than for Haiyan’s.

After its spectacular RI, Hagibis’s intensification stopped, despite favorable environments. Haiyan, by contrast, continued to intensify, reaching its record-breaking intensity of 170 kt. A key finding here is the multiple pathways that storm size affected the intensity evolution for both typhoons. After RI, Hagibis experienced a major size expansion, becoming the largest typhoon on record in the Pacific. This size enlargement, combined with a reduction in storm translational speed, induced stronger ocean cooling that reduced ocean flux and hindered intensification. The large storm size also contributed to slower eyewall replacement cycles (ERCs), which prolonged the negative impact of the ERC on intensification.

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Joshua Wurman, Karen Kosiba, Brian Pereira, Paul Robinson, Andrew Frambach, Alycia Gilliland, Trevor White, Josh Aikins, Robert J. Trapp, Stephen Nesbitt, Maiana N. Hanshaw, and Jon Lutz

Abstract

The Flexible Array of Radars and Mesonets (FARM) Facility is an extensive mobile/quickly-deployable (MQD) multiple-Doppler radar and in-situ instrumentation network.

The FARM includes four radars: two 3-cm dual-polarization, dual-frequency (DPDF), Doppler On Wheels DOW6/DOW7, the Rapid-Scan DOW (RSDOW), and a quickly-deployable (QD) DPDF 5-cm COW C-band On Wheels (COW).

The FARM includes 3 mobile mesonet (MM) vehicles with 3.5-m masts, an array of rugged QD weather stations (PODNET), QD weather stations deployed on infrastructure such as light/power poles (POLENET), four disdrometers, six MQD upper air sounding systems and a Mobile Operations and Repair Center (MORC).

The FARM serves a wide variety of research/educational uses. Components have deployed to >30 projects during 1995-2020 in the USA, Europe, and South America, obtaining pioneering observations of a myriad of small spatial and temporal scale phenomena including tornadoes, hurricanes, lake-effect snow storms, aircraft-affecting turbulence, convection initiation, microbursts, intense precipitation, boundary-layer structures and evolution, airborne hazardous substances, coastal storms, wildfires and wildfire suppression efforts, weather modification effects, and mountain/alpine winds and precipitation. The radars and other FARM systems support innovative educational efforts, deploying >40 times to universities/colleges, providing hands-on access to cutting-edge instrumentation for their students.

The FARM provides integrated multiple radar, mesonet, sounding, and related capabilities enabling diverse and robust coordinated sampling of three-dimensional vector winds, precipitation, and thermodynamics increasingly central to a wide range of mesoscale research.

Planned innovations include S-band On Wheels NETwork (SOWNET) and Bistatic Adaptable Radar Network (BARN), offering more qualitative improvements to the field project observational paradigm, providing broad, flexible, and inexpensive 10-cm radar coverage and vector windfield measurements.

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