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Andrew D. King
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Mitchell T. Black
,
David J. Karoly
, and
Andrew D. King
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Sophie C. Lewis
,
Andrew D. King
, and
Sarah E. Perkins-Kirkpatrick

Abstract

The term “new normal” has been used in scientific literature and public commentary to contextualize contemporary climate events as an indicator of a changing climate due to enhanced greenhouse warming. A new normal has been used broadly but tends to be descriptive and ambiguously defined. Here we review previous studies conceptualizing this idea of a new climatological normal and argue that this term should be used cautiously and with explicit definition in order to avoid confusion. We provide a formal definition of a new climate normal relative to present based around record-breaking contemporary events and explore the timing of when such extremes become statistically normal in the future model simulations. Applying this method to the record-breaking global-average 2015 temperatures as a reference event and a suite of model climate models, we determine that 2015 global annual-average temperatures will be the new normal by 2040 in all emissions scenarios. At the regional level, a new normal can be delayed through aggressive greenhouse gas emissions reductions. Using this specific case study to investigate a climatological new normal, our approach demonstrates the greater value of the concept of a climatological new normal for understanding and communicating climate change when the term is explicitly defined. This approach moves us one step closer to understanding how current extremes will change in the future in a warming world.

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Andrew D. King
,
David J. Karoly
, and
Geert Jan van Oldenborgh
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Kimberley J. Reid
,
Ian Simmonds
,
Claire L. Vincent
, and
Andrew D. King

Abstract

Australian northwest cloudbands (NWCBs) are continental-scale bands of continuous cloud that stretch from northwest to southeast Australia. In earlier studies, where the characteristics of NWCBs and their relationship with precipitation were identified from satellite imagery, there was considerable uncertainty in the results due to limited quality and availability of data. The present study identifies NWCBs from 31 years of satellite data using a pattern-matching algorithm. This new climatology is the longest record based entirely on observations. Our findings include a strong annual cycle in NWCB frequency, with a summer maximum and winter minimum, and a statistically significant increase in annual NWCB days over the period 1984–2014. Physical mechanisms responsible for NWCB occurrences are explored to determine whether there is a fundamental difference between summer and winter NWCBs as hypothesized in earlier studies. Composite analyses are used to reveal that a key difference between these is their genesis mechanisms. Whereas summer NWCBs are triggered by cyclonic disturbances, winter NWCBs tend to form when meridional sea surface temperature gradients trigger baroclinic instability. It was also found that while precipitation is enhanced over parts of Australia during a cloudband day, it is reduced in other regions. During a cloudband day, precipitation extremes are more likely over northwest, central, and southeast Australia, while the probability of extreme precipitation decreases in northeast and southwest Australia. Additionally, cold fronts and NWCBs can interact, leading to enhanced rainfall over Australia.

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Andrew D. King
,
Mitchell T. Black
,
David J. Karoly
, and
Markus G. Donat
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David J. Karoly
,
Mitchell T. Black
,
Andrew D. King
, and
Michael R. Grose
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Kimberley J. Reid
,
Andrew D. King
,
Todd P. Lane
, and
Debra Hudson

Abstract

Studies of atmospheric rivers (ARs) over Australia have, so far, only focused on northwest cloudband–type weather systems. Here we perform a comprehensive analysis of AR climatology and impacts over Australia that includes not only northwesterly systems, but easterly and extratropical ARs also. We quantify the impact of ARs on mean and extreme rainfall including assessing how the origin location of ARs can alter their precipitation outcomes. We found a strong relationship between ARs and extreme rainfall in the agriculturally significant Murray–Daring basin region. We test the hypothesis that the tropical and subtropical originating ARs we observe in Australasia differ from canonical extratropical ARs by examining the vertical structure of ARs grouped by origin location. We found that in the moisture abundant tropics and subtropics, wind speed drives the intensity of ARs, while in the extratropics, the strength of an AR is largely determined by moisture availability. Finally, we examine the modulation of AR frequency by different climate modes. We find weak (but occasionally significant) correlations between ARs frequency and El Niño–Southern Oscillation, the Indian Ocean dipole, and the southern annular mode. However, there is a stronger relationship between the phases of the Madden–Julian oscillation and tropical AR frequency, which is an avenue for potential skill in forecasting ARs on subseasonal time scales.

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Peter Uhe
,
Dann Mitchell
,
Paul D. Bates
,
Myles R. Allen
,
Richard A. Betts
,
Chris Huntingford
,
Andrew D. King
,
Benjamin M. Sanderson
, and
Hideo Shiogama

Abstract

Precipitation events cause disruption around the world and will be altered by climate change. However, different climate modeling approaches can result in different future precipitation projections. The corresponding “method uncertainty” is rarely explicitly calculated in climate impact studies and major reports but can substantially change estimated precipitation changes. A comparison across five commonly used modeling activities shows that, for changes in mean precipitation, less than half of the regions analyzed had significant changes between the present climate and 1.5°C global warming for the majority of modeling activities. This increases to just over half of the regions for changes between present climate and 2°C global warming. There is much higher confidence in changes in maximum 1-day precipitation than in mean precipitation, indicating the robust influence of thermodynamics in the climate change effect on extremes. We also find that none of the modeling activities captures the full range of estimates from the other methods in all regions. Our results serve as an uncertainty map to help interpret which regions require a multimethod approach. Our analysis highlights the risk of overreliance on any single modeling activity and the need for confidence statements in major synthesis reports to reflect this method uncertainty. Considering multiple sources of climate projections should reduce the risks of policymakers being unprepared for impacts of warmer climates relative to using single-method projections to make decisions.

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Galina Wind
,
Steven Platnick
,
Michael D. King
,
Paul A. Hubanks
,
Michael J. Pavolonis
,
Andrew K. Heidinger
,
Ping Yang
, and
Bryan A. Baum

Abstract

Data Collection 5 processing for the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the NASA Earth Observing System (EOS) Terra and Aqua spacecraft includes an algorithm for detecting multilayered clouds in daytime. The main objective of this algorithm is to detect multilayered cloud scenes, specifically optically thin ice cloud overlying a lower-level water cloud, that present difficulties for retrieving cloud effective radius using single-layer plane-parallel cloud models. The algorithm uses the MODIS 0.94-μm water vapor band along with CO2 bands to obtain two above-cloud precipitable water retrievals, the difference of which, in conjunction with additional tests, provides a map of where multilayered clouds might potentially exist. The presence of a multilayered cloud results in a large difference in retrievals of above-cloud properties between the CO2 and the 0.94-μm methods. In this paper the MODIS multilayered cloud algorithm is described, results of using the algorithm over example scenes are shown, and global statistics for multilayered clouds as observed by MODIS are discussed. A theoretical study of the algorithm behavior for simulated multilayered clouds is also given. Results are compared to two other comparable passive imager methods. A set of standard cloudy atmospheric profiles developed during the course of this investigation is also presented. The results lead to the conclusion that the MODIS multilayer cloud detection algorithm has some skill in identifying multilayered clouds with different thermodynamic phases.

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