11 Aug 2023
| 11 Aug 2023
Uncertainty in Mapping Climate Change-Related Flooding Risk to Residential Property Values
Quyen Nguyen
University of Otago, Dunedin, New Zealand
Antoni Moore
University of Otago, Dunedin, New Zealand
Ivan Diaz-Rainey
University of Otago, Dunedin, New Zealand
Griffith University, Australia
Greg Bodeker
Bodeker Scientific, Alexandra, New Zealand
Simon C. Cox
GNS Science, Dunedin, New Zealand
Murray Cadzow
University of Otago, Dunedin, New Zealand
Paul Thorsnes
University of Otago, Dunedin, New Zealand
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Owyn Aitken, Antoni Moore, Ivan Diaz-Rainey, Quyen Nguyen, Simon Cox, and Greg Bodeker
Abstr. Int. Cartogr. Assoc., 7, 4, https://doi.org/10.5194/ica-abs-7-4-2024, https://doi.org/10.5194/ica-abs-7-4-2024, 2024
Antoni Moore
Abstr. Int. Cartogr. Assoc., 7, 106, https://doi.org/10.5194/ica-abs-7-106-2024, https://doi.org/10.5194/ica-abs-7-106-2024, 2024
Antoni Moore, Quyen Nguyen, Ivan Diaz-Rainey, Greg Bodeker, Simon Cox, and Owyn Aitken
Abstr. Int. Cartogr. Assoc., 7, 107, https://doi.org/10.5194/ica-abs-7-107-2024, https://doi.org/10.5194/ica-abs-7-107-2024, 2024
Malte Meinshausen, Carl-Friedrich Schleussner, Kathleen Beyer, Greg Bodeker, Olivier Boucher, Josep G. Canadell, John S. Daniel, Aïda Diongue-Niang, Fatima Driouech, Erich Fischer, Piers Forster, Michael Grose, Gerrit Hansen, Zeke Hausfather, Tatiana Ilyina, Jarmo S. Kikstra, Joyce Kimutai, Andrew D. King, June-Yi Lee, Chris Lennard, Tabea Lissner, Alexander Nauels, Glen P. Peters, Anna Pirani, Gian-Kasper Plattner, Hans Pörtner, Joeri Rogelj, Maisa Rojas, Joyashree Roy, Bjørn H. Samset, Benjamin M. Sanderson, Roland Séférian, Sonia Seneviratne, Christopher J. Smith, Sophie Szopa, Adelle Thomas, Diana Urge-Vorsatz, Guus J. M. Velders, Tokuta Yokohata, Tilo Ziehn, and Zebedee Nicholls
Geosci. Model Dev., 17, 4533–4559, https://doi.org/10.5194/gmd-17-4533-2024, https://doi.org/10.5194/gmd-17-4533-2024, 2024
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The scientific community is considering new scenarios to succeed RCPs and SSPs for the next generation of Earth system model runs to project future climate change. To contribute to that effort, we reflect on relevant policy and scientific research questions and suggest categories for representative emission pathways. These categories are tailored to the Paris Agreement long-term temperature goal, high-risk outcomes in the absence of further climate policy and worlds “that could have been”.
Aleksandra Stanczak and Antoni Moore
Abstr. Int. Cartogr. Assoc., 6, 247, https://doi.org/10.5194/ica-abs-6-247-2023, https://doi.org/10.5194/ica-abs-6-247-2023, 2023
Igor Drecki and Antoni Moore
Abstr. Int. Cartogr. Assoc., 6, 57, https://doi.org/10.5194/ica-abs-6-57-2023, https://doi.org/10.5194/ica-abs-6-57-2023, 2023
Antoni B. Moore
Abstr. Int. Cartogr. Assoc., 6, 171, https://doi.org/10.5194/ica-abs-6-171-2023, https://doi.org/10.5194/ica-abs-6-171-2023, 2023
Leroy J. Bird, Matthew G. W. Walker, Greg E. Bodeker, Isaac H. Campbell, Guangzhong Liu, Swapna Josmi Sam, Jared Lewis, and Suzanne M. Rosier
Geosci. Model Dev., 16, 3785–3808, https://doi.org/10.5194/gmd-16-3785-2023, https://doi.org/10.5194/gmd-16-3785-2023, 2023
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Deriving the statistics of expected future changes in extreme precipitation is challenging due to these events being rare. Regional climate models (RCMs) are computationally prohibitive for generating ensembles capable of capturing large numbers of extreme precipitation events with statistical robustness. Stochastic precipitation generators (SPGs) provide an alternative to RCMs. We describe a novel single-site SPG that learns the statistics of precipitation using a machine-learning approach.
Antoni B. Moore and Mike J. Smith
Abstr. Int. Cartogr. Assoc., 3, 210, https://doi.org/10.5194/ica-abs-3-210-2021, https://doi.org/10.5194/ica-abs-3-210-2021, 2021
Aleksandra Stanczak and Antoni Moore
Abstr. Int. Cartogr. Assoc., 3, 277, https://doi.org/10.5194/ica-abs-3-277-2021, https://doi.org/10.5194/ica-abs-3-277-2021, 2021
Brian Nathan, Stefanie Kremser, Sara Mikaloff-Fletcher, Greg Bodeker, Leroy Bird, Ethan Dale, Dongqi Lin, Gustavo Olivares, and Elizabeth Somervell
Atmos. Chem. Phys., 21, 14089–14108, https://doi.org/10.5194/acp-21-14089-2021, https://doi.org/10.5194/acp-21-14089-2021, 2021
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The MAPM project showcases a method to improve estimates of PM2.5 emissions through an advanced statistical technique that is still new to the aerosol community. Using Christchurch, NZ, as a test bed, measurements from a field campaign in winter 2019 are incorporated into this new approach. An overestimation from local inventory estimates is identified. This technique may be exported to other urban areas in need.
Greg E. Bodeker, Jan Nitzbon, Jordis S. Tradowsky, Stefanie Kremser, Alexander Schwertheim, and Jared Lewis
Earth Syst. Sci. Data, 13, 3885–3906, https://doi.org/10.5194/essd-13-3885-2021, https://doi.org/10.5194/essd-13-3885-2021, 2021
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Ozone in Earth's atmosphere has undergone significant changes since first measured systematically from space in the late 1970s. The purpose of the paper is to present a new, spatially filled, global total column ozone climate data record spanning from October 1978 to December 2016. The database is compiled from measurements from 17 different satellite-based instruments where offsets and drifts between the instruments have been corrected using ground-based measurements.
Ethan R. Dale, Stefanie Kremser, Jordis S. Tradowsky, Greg E. Bodeker, Leroy J. Bird, Gustavo Olivares, Guy Coulson, Elizabeth Somervell, Woodrow Pattinson, Jonathan Barte, Jan-Niklas Schmidt, Nariefa Abrahim, Adrian J. McDonald, and Peter Kuma
Earth Syst. Sci. Data, 13, 2053–2075, https://doi.org/10.5194/essd-13-2053-2021, https://doi.org/10.5194/essd-13-2053-2021, 2021
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MAPM is a project whose goal is to develop a method to infer particulate matter (PM) emissions maps from PM concentration measurements. In support of MAPM, we conducted a winter field campaign in New Zealand. In addition to two types of instruments measuring PM, an array of other meteorological sensors were deployed, measuring temperature and wind speed as well as probing the vertical structure of the lower atmosphere. In this article, we present the measurements taken during this campaign.
Greg E. Bodeker and Stefanie Kremser
Atmos. Chem. Phys., 21, 5289–5300, https://doi.org/10.5194/acp-21-5289-2021, https://doi.org/10.5194/acp-21-5289-2021, 2021
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This paper presents measures of the severity of the Antarctic ozone hole covering the period 1979 to 2019. The paper shows that while the severity of Antarctic ozone depletion grew rapidly through the last two decades of the 20th century, the severity declined thereafter and faster than expected from declines in stratospheric concentrations of the chlorine- and bromine-containing chemical compounds that destroy ozone.
James Keeble, Birgit Hassler, Antara Banerjee, Ramiro Checa-Garcia, Gabriel Chiodo, Sean Davis, Veronika Eyring, Paul T. Griffiths, Olaf Morgenstern, Peer Nowack, Guang Zeng, Jiankai Zhang, Greg Bodeker, Susannah Burrows, Philip Cameron-Smith, David Cugnet, Christopher Danek, Makoto Deushi, Larry W. Horowitz, Anne Kubin, Lijuan Li, Gerrit Lohmann, Martine Michou, Michael J. Mills, Pierre Nabat, Dirk Olivié, Sungsu Park, Øyvind Seland, Jens Stoll, Karl-Hermann Wieners, and Tongwen Wu
Atmos. Chem. Phys., 21, 5015–5061, https://doi.org/10.5194/acp-21-5015-2021, https://doi.org/10.5194/acp-21-5015-2021, 2021
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Stratospheric ozone and water vapour are key components of the Earth system; changes to both have important impacts on global and regional climate. We evaluate changes to these species from 1850 to 2100 in the new generation of CMIP6 models. There is good agreement between the multi-model mean and observations, although there is substantial variation between the individual models. The future evolution of both ozone and water vapour is strongly dependent on the assumed future emissions scenario.
Ruud J. Dirksen, Greg E. Bodeker, Peter W. Thorne, Andrea Merlone, Tony Reale, Junhong Wang, Dale F. Hurst, Belay B. Demoz, Tom D. Gardiner, Bruce Ingleby, Michael Sommer, Christoph von Rohden, and Thierry Leblanc
Geosci. Instrum. Method. Data Syst., 9, 337–355, https://doi.org/10.5194/gi-9-337-2020, https://doi.org/10.5194/gi-9-337-2020, 2020
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This paper describes GRUAN's strategy for a network-wide change of the operational radiosonde from Vaisala RS92 to RS41. GRUAN's main goal is to provide long-term data records that are free of inhomogeneities due to instrumental effects, which requires proper change management. The approach is to fully characterize differences between the two radiosonde types using laboratory tests, twin soundings, and ancillary data, as well as by drawing from the various fields of expertise available in GRUAN.
Antoni B. Moore and Bin Jiang
Abstr. Int. Cartogr. Assoc., 1, 256, https://doi.org/10.5194/ica-abs-1-256-2019, https://doi.org/10.5194/ica-abs-1-256-2019, 2019
Aleksandra Stanczak and Antoni Moore
Abstr. Int. Cartogr. Assoc., 1, 348, https://doi.org/10.5194/ica-abs-1-348-2019, https://doi.org/10.5194/ica-abs-1-348-2019, 2019
Corinna Kloss, Marc von Hobe, Michael Höpfner, Kaley A. Walker, Martin Riese, Jörn Ungermann, Birgit Hassler, Stefanie Kremser, and Greg E. Bodeker
Atmos. Meas. Tech., 12, 2129–2138, https://doi.org/10.5194/amt-12-2129-2019, https://doi.org/10.5194/amt-12-2129-2019, 2019
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Are regional and seasonal averages from only a few satellite measurements, all aligned along a specific path, representative? Probably not. We present a method to adjust for the so-called
sampling biasand investigate its influence on derived long-term trends. The method is illustrated and validated for a long-lived trace gas (carbonyl sulfide), and it is shown that the influence of the sampling bias is too small to change scientific conclusions on long-term trends.
Jordis S. Tradowsky, Gregory E. Bodeker, Richard R. Querel, Peter J. H. Builtjes, and Jürgen Fischer
Earth Syst. Sci. Data, 10, 2195–2211, https://doi.org/10.5194/essd-10-2195-2018, https://doi.org/10.5194/essd-10-2195-2018, 2018
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A best-estimate data set of the temperature profile above the atmospheric measurement facility at Lauder, New Zealand, has been developed. This site atmospheric state best estimate (SASBE) combines atmospheric measurements made at two locations and includes an estimate of uncertainty on every data point. The SASBE enhances the value of measurements made by a reference-quality climate observing network and may be used for a variety of purposes in research and education.
Birgit Hassler, Stefanie Kremser, Greg E. Bodeker, Jared Lewis, Kage Nesbit, Sean M. Davis, Martyn P. Chipperfield, Sandip S. Dhomse, and Martin Dameris
Earth Syst. Sci. Data, 10, 1473–1490, https://doi.org/10.5194/essd-10-1473-2018, https://doi.org/10.5194/essd-10-1473-2018, 2018
Jonathan Conway, Greg Bodeker, and Chris Cameron
Atmos. Chem. Phys., 18, 8065–8077, https://doi.org/10.5194/acp-18-8065-2018, https://doi.org/10.5194/acp-18-8065-2018, 2018
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Strong westerly winds occur in the stratosphere during winter and spring. These winds, the polar vortex, limit how much air is mixed between mid- and high-latitudes. We present a new view of the polar vortex mixing barrier in the Southern Hemisphere, revealing a frequent double-walled barrier with two distinct regions of weak mixing. This double-walled structure is expected to alter the spatial and temporal variation of trace gas concentrations (e.g. ozone) across the polar vortex.
Stefanie Kremser, Jordis S. Tradowsky, Henning W. Rust, and Greg E. Bodeker
Atmos. Meas. Tech., 11, 3021–3029, https://doi.org/10.5194/amt-11-3021-2018, https://doi.org/10.5194/amt-11-3021-2018, 2018
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We investigate the feasibility of quantifying the difference in biases of two instrument types (i.e. radiosondes) by flying the old and new instruments on alternating days, so-called interlacing, to statistically derive the systematic biases between the instruments. While it is in principle possible to estimate the difference between two instrument biases from interlaced measurements, the number of required interlaced flights is very large for reasonable autocorrelation coefficient values.
Elizabeth C. Weatherhead, Jerald Harder, Eduardo A. Araujo-Pradere, Greg Bodeker, Jason M. English, Lawrence E. Flynn, Stacey M. Frith, Jeffrey K. Lazo, Peter Pilewskie, Mark Weber, and Thomas N. Woods
Atmos. Chem. Phys., 17, 15069–15093, https://doi.org/10.5194/acp-17-15069-2017, https://doi.org/10.5194/acp-17-15069-2017, 2017
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Satellite overlap is often carried out as a check on the stability of the data collected. We looked at how length of overlap influences how much information can be derived from the overlap period. Several results surprised us: the confidence we could have in the matchup of two records was independent of the offset, and understanding of the relative drift between the two satellite data sets improved significantly with 2–3 years of overlap. Sudden jumps could easily be confused with drift.
Jared Lewis, Greg E. Bodeker, Stefanie Kremser, and Andrew Tait
Geosci. Model Dev., 10, 4563–4575, https://doi.org/10.5194/gmd-10-4563-2017, https://doi.org/10.5194/gmd-10-4563-2017, 2017
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The Ensemble Projections Incorporating Climate model uncertainty (EPIC) method uses climate pattern scaling to expand a small number of daily maximum and minimum surface temperature projections into an ensemble that captures the structural uncertainty between climate models. The method is useful for providing projections of changes in climate to users wishing to investigate the impacts of climate change in a probabilistic and computationally efficient way.
Leon S. Friedrich, Adrian J. McDonald, Gregory E. Bodeker, Kathy E. Cooper, Jared Lewis, and Alexander J. Paterson
Atmos. Chem. Phys., 17, 855–866, https://doi.org/10.5194/acp-17-855-2017, https://doi.org/10.5194/acp-17-855-2017, 2017
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Information from long-duration balloons flying in the Southern Hemisphere stratosphere during 2014 as part of X Project Loon are used to assess the quality of a number of different reanalyses. This work assesses the potential of the X Project Loon observations to validate outputs from the reanalysis models. In particular, we examined how the model winds compared with those derived from the balloon GPS information. We also examined simulated trajectories compared with the true trajectories.
Ulrike Langematz, Franziska Schmidt, Markus Kunze, Gregory E. Bodeker, and Peter Braesicke
Atmos. Chem. Phys., 16, 15619–15627, https://doi.org/10.5194/acp-16-15619-2016, https://doi.org/10.5194/acp-16-15619-2016, 2016
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The extent of anthropogenically driven Antarctic ozone depletion prior to 1980 is examined using transient chemistry–climate model simulations from 1960 to 2000 with prescribed changes of ozone depleting substances in conjunction with observations. All models show a long-term, halogen-induced negative trend in Antarctic ozone from 1960 to 1980, ranging between 26 and 50 % of the total anthropogenic ozone depletion from 1960 to 2000. A stronger ozone decline of 56 % was estimated from observation.
N. R. P. Harris, B. Hassler, F. Tummon, G. E. Bodeker, D. Hubert, I. Petropavlovskikh, W. Steinbrecht, J. Anderson, P. K. Bhartia, C. D. Boone, A. Bourassa, S. M. Davis, D. Degenstein, A. Delcloo, S. M. Frith, L. Froidevaux, S. Godin-Beekmann, N. Jones, M. J. Kurylo, E. Kyrölä, M. Laine, S. T. Leblanc, J.-C. Lambert, B. Liley, E. Mahieu, A. Maycock, M. de Mazière, A. Parrish, R. Querel, K. H. Rosenlof, C. Roth, C. Sioris, J. Staehelin, R. S. Stolarski, R. Stübi, J. Tamminen, C. Vigouroux, K. A. Walker, H. J. Wang, J. Wild, and J. M. Zawodny
Atmos. Chem. Phys., 15, 9965–9982, https://doi.org/10.5194/acp-15-9965-2015, https://doi.org/10.5194/acp-15-9965-2015, 2015
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Trends in the vertical distribution of ozone are reported for new and recently revised data sets. The amount of ozone-depleting compounds in the stratosphere peaked in the second half of the 1990s. We examine the trends before and after that peak to see if any change in trend is discernible. The previously reported decreases are confirmed. Furthermore, the downward trend in upper stratospheric ozone has not continued. The possible significance of any increase is discussed in detail.
K. Kreher, G. E. Bodeker, and M. Sigmond
Atmos. Chem. Phys., 15, 7653–7665, https://doi.org/10.5194/acp-15-7653-2015, https://doi.org/10.5194/acp-15-7653-2015, 2015
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This manuscript aims to answer the following question: which of the existing sites engaged in upper-air temperature measurements are best located to detect expected future trends within the shortest time possible? To do so, we explore one objective method for selecting the optimal locations for detecting projected 21st century trends and then demonstrate a similar technique for objectively selecting optimal locations for detecting expected future trends in total column ozone.
G. E. Bodeker and S. Kremser
Atmos. Meas. Tech., 8, 1673–1684, https://doi.org/10.5194/amt-8-1673-2015, https://doi.org/10.5194/amt-8-1673-2015, 2015
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This paper discusses, and demonstrates, the methodology for reliably determining long-term trends in upper air climate data records and how measurement uncertainties should be used in trend analyses. A pedagogical approach is taken whereby numerical recipes for key parts of the trend analysis process are explored. The paper describes the construction of linear least squares regression models for trend analysis and the boot-strapping approach to determine the uncertainty on the derived trends.
F. Tummon, B. Hassler, N. R. P. Harris, J. Staehelin, W. Steinbrecht, J. Anderson, G. E. Bodeker, A. Bourassa, S. M. Davis, D. Degenstein, S. M. Frith, L. Froidevaux, E. Kyrölä, M. Laine, C. Long, A. A. Penckwitt, C. E. Sioris, K. H. Rosenlof, C. Roth, H.-J. Wang, and J. Wild
Atmos. Chem. Phys., 15, 3021–3043, https://doi.org/10.5194/acp-15-3021-2015, https://doi.org/10.5194/acp-15-3021-2015, 2015
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Understanding ozone trends in the vertical is vital in terms of assessing the success of the Montreal Protocol. This paper compares and analyses the long-term trends in stratospheric ozone from seven new merged satellite data sets. The data sets largely agree well with each other, particularly for the negative trends seen in the early period 1984-1997. For the 1998-2011 period there is less agreement, but a clear shift from negative to mostly positive trends.
A. A. Penckwitt, G. E. Bodeker, P. Stoll, J. Lewis, T. von Clarmann, and A. Jones
Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amtd-8-235-2015, https://doi.org/10.5194/amtd-8-235-2015, 2015
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A. Parrish, I. S. Boyd, G. E. Nedoluha, P. K. Bhartia, S. M. Frith, N. A. Kramarova, B. J. Connor, G. E. Bodeker, L. Froidevaux, M. Shiotani, and T. Sakazaki
Atmos. Chem. Phys., 14, 7255–7272, https://doi.org/10.5194/acp-14-7255-2014, https://doi.org/10.5194/acp-14-7255-2014, 2014
M. Rex, S. Kremser, P. Huck, G. Bodeker, I. Wohltmann, M. L. Santee, and P. Bernath
Atmos. Chem. Phys., 14, 6545–6555, https://doi.org/10.5194/acp-14-6545-2014, https://doi.org/10.5194/acp-14-6545-2014, 2014
S. Kremser, G. E. Bodeker, and J. Lewis
Geosci. Model Dev., 7, 249–266, https://doi.org/10.5194/gmd-7-249-2014, https://doi.org/10.5194/gmd-7-249-2014, 2014
V. F. Sofieva, J. Tamminen, E. Kyrölä, T. Mielonen, P. Veefkind, B. Hassler, and G.E. Bodeker
Atmos. Chem. Phys., 14, 283–299, https://doi.org/10.5194/acp-14-283-2014, https://doi.org/10.5194/acp-14-283-2014, 2014
S. Brönnimann, J. Bhend, J. Franke, S. Flückiger, A. M. Fischer, R. Bleisch, G. Bodeker, B. Hassler, E. Rozanov, and M. Schraner
Atmos. Chem. Phys., 13, 9623–9639, https://doi.org/10.5194/acp-13-9623-2013, https://doi.org/10.5194/acp-13-9623-2013, 2013
H. Garny, G. E. Bodeker, D. Smale, M. Dameris, and V. Grewe
Atmos. Chem. Phys., 13, 7279–7300, https://doi.org/10.5194/acp-13-7279-2013, https://doi.org/10.5194/acp-13-7279-2013, 2013
B. Hassler, P. J. Young, R. W. Portmann, G. E. Bodeker, J. S. Daniel, K. H. Rosenlof, and S. Solomon
Atmos. Chem. Phys., 13, 5533–5550, https://doi.org/10.5194/acp-13-5533-2013, https://doi.org/10.5194/acp-13-5533-2013, 2013
P. E. Huck, G. E. Bodeker, S. Kremser, A. J. McDonald, M. Rex, and H. Struthers
Atmos. Chem. Phys., 13, 3237–3243, https://doi.org/10.5194/acp-13-3237-2013, https://doi.org/10.5194/acp-13-3237-2013, 2013
G. E. Bodeker, B. Hassler, P. J. Young, and R. W. Portmann
Earth Syst. Sci. Data, 5, 31–43, https://doi.org/10.5194/essd-5-31-2013, https://doi.org/10.5194/essd-5-31-2013, 2013
