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Andrew D. Magee, Anthony S. Kiem, and Andrew M. Lorrey

Abstract

Tropical cyclones (TCs) produce extreme winds, large waves, storm surges, intense rainfall and flooding and account for almost 75% of natural disasters across the Southwest Pacific (SWP) region. The island nations and territories across the SWP rely on seasonal TC outlooks for insights into possible risks for the coming TC season. Launched in July 2020, the Long-Range Tropical Cyclone Outlook for the Southwest Pacific (TCO-SP) provides deterministic (frequency) and probabilistic (likelihood) TC outlooks for 12 sub-regional and island-scale locations up to four months (July) before the start of the SWP TC season (November-April). Following TCO-SP’s first season of operation, this study (i) outlines the process of generating and communicating TCO-SP outlooks, (ii) provides a post-season validation of TCO-SP performance on the 2020/21 SWP TC season and (iii) reports on the results of a questionnaire used to determine end-user needs and user-perceived usefulness of TCO-SP. Post-season validation indicates that TCO-SP successfully predicted a near-normal SWP TC season. Island- and regional-scale guidance also performed well, with an average skill score of 54% across all regions. Analysis of responses to a TCO-SP questionnaire revealed a diverse and global user-base that indicate the core features of TCO-SP (island-scale/regional-scale outlooks, regular monthly updates and an outlook lead-time up to four months before the start of the TC season) are particularly useful. TCO-SP will continue to innovate to deliver reliable and trusted TC outlooks with a goal to reduce disaster risk and increase resilience across the SWP region.

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Benjamin F. Zaitchik, Judy Omumbo, Rachel Lowe, Maarten van Aalst, Liana O. Anderson, Erich Fischer, Charlotte Norman, Joanne Robbins, Rosa Barciela, Juli Trtanj, Rosa von Borries, and Jürg Luterbacher
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Ruping Mo

Abstract

The model of atmospheric river (AR) has been around since the 1990s. A closely related model is the warm conveyor belt (WCB) developed in the 1970s. A look further back in time, a phenomenon known as “moist tongue” was intensively investigated in the late 1930s and early 1940s by Rossby and his collaborators using the innovation of isentropic analysis. This article aims to establish a historical perspective on the development of moist tongue model and its relevance to the current models of WCBs and ARs. As it turns out, moist tongue was identified as an extension of moist air into a region of lower moisture content on the selected isentropic charts. Most moist tongues are driven by large-scale cyclonic and anticyclonic eddies, and are often accompanied by surface cold fronts in close proximity. Ahead of the moist tongues, areas of continuous precipitation are caused mainly by the motion of moist air up the steep isentropic slopes over warm fronts or topographical features. In the warm season, the mere presence of a moist tongue could be sufficient to give thunderstorms. A reanalysis dataset is used to re-examine the structures and evolutions of two moist tongue events in 1936. It is shown that not all but some of the moist tongues fit well with the modern conceptual models of WCB and AR. These two case studies also serve to elucidate the usefulness of using the reanalysis data to investigate historical high-impact weather events that were poorly understood due to the lack of observational data.

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Xiang Xiao, Yangyang Xu, Xiaorui Zhang, Fan Wang, Xiao Lu, Zongwei Cai, Guy Brasseur, and Meng Gao

Abstract

Climate change and air pollution are two intimately interlinked global concerns. The frequency, intensity and duration of heatwaves are projected to increase globally under future climate change. A growing body of evidence indicates that health risks associated with the joint exposure to heatwaves and air pollution can be greater than that due to individual factors. However, the co-occurrences of heat and air pollution extremes in China remain less explored in the observational records. Here we investigate the spatial pattern and temporal trend of frequency, intensity, and duration of co-occurrences of heat and air pollution extremes using China’s nationwide observations of hourly PM2.5 and O3, and the ERA5 reanalysis dataset over 2013–2020. We identify a significant increase in the frequency of co-occurrences of wet-bulb temperature (Tw) and O3 exceedances (beyond a certain predefined threshold), mainly in the Beijing-Tianjin-Hebei (BTH) region (up by 4.7 days decade-1) and the Yangtze River Delta (YRD). In addition, we find that the increasing rate (compared to the average levels during the study period) of joint exceedance is larger than the rate of Tw and O3 itself. For example, Tw and O3 co-extremes increased by 7.0% in BTH, higher than the percentage increase of each at 0.9% and 5.5%, respectively. We identify same amplification for YRD. This ongoing upward trend in the joint occurrence of heat and O3 extremes should be recognized as an emerging environmental issue in China, given the potentially larger compounding impact to public health.

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Ziqiang Ma, Jintao Xu, Yaoming Ma, Siyu Zhu, Kang He, Shengjun Zhang, Weiqiang Ma, and Xiangde Xu

Abstract

Accurate long-term precipitation information is critical for understanding the mechanisms behind how precipitation couples with Earth’s water fluxes, energy balances, and biogeochemical cycles across space–time scales under the changing climate. This study proposes a novel approach (Daily Total Volume Controlled Merging and Disaggregation Algorithm, DTVCMDA) for generating a new long-term precipitation dataset, AERA5-Asia (0.1°, 1 hourly, 1981–2015, Asia; “AERA5” is a combination of the “A” from APHRODITE and the “ERA5” from ERA5-Land; for abbreviations, see the Appendix), by comprehensively considering the characteristics of the high spatiotemporal resolutions and continuity of the ERA5-Land dataset and the high quality of the APHRODITE dataset; the AERA5-Asia back extensions (0.1°, 1 hourly, 1951–1980, Asia) will soon be available. The main conclusions include, but are not limited to, the following: (1) AERA5-Asia provides time series of precipitation of sufficient resolutions, length, consistency, continuity, and quality over Asia.(2) AERA5-Asia substantially outperforms ERA5-Land and IMERG-Final in terms of both magnitudes and occurrences of precipitation events in Mainland China, especially the systematic biases. For instance, the Bias of ERA5-Land, IMERG-Final, and AERA5-Asia against ground gauge-based observations in Mainland China are ∼20%, ∼11%, and ∼5%, respectively. (3) AERA5-Asia performs notably better than ERA5-Land and IMERG-Final against ground gauge-based observations in regional extreme rainfall systems (e.g., two typhoon events, Trami and Usagi). (4) AERA5-Asia should prove to be a useful precipitation dataset for addressing various key climatological and hydrological research questions that require precipitation data with longer spans and finer resolutions (0.1°, 1 hourly).

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Chad W. Hecht, Allison C. Michaelis, Andrew C. Martin, Jason M. Cordeira, Forest Cannon, and F. Martin Ralph
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Natasha MacBean, Hannah Liddy, Tristan Quaife, Jana Kolassa, and Andrew Fox
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Joel Lisonbee, Elizabeth Ossowski, Meredith Muth, Veva Deheza, and Amanda Sheffield
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Michael P. Jensen, James H. Flynn, Laura M. Judd, Pavlos Kollias, Chongai Kuang, Greg McFarquhar, Raj Nadkarni, Heath Powers, and John Sullivan
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Anna M. Wilson, Alison Cobb, F. Martin Ralph, Vijay Tallapragada, Chris Davis, James Doyle, Luca Delle Monache, Florian Pappenberger, Carolyn Reynolds, Aneesh Subramanian, Forest Cannon, Jason Cordeira, Jennifer Haase, Chad Hecht, David Lavers, Jonathan J. Rutz, and Minghua Zheng
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