Sea surface temperature driven modulation of decadal co-variability in mean and extreme precipitation Article Swipe
Mustapha Adamu
,
Shayne McGregor
,
Ailie Gallant
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1088/1748-9326/ad2ab9
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1088/1748-9326/ad2ab9
This study investigates the role that sea surface temperature (SST) variability plays in modulating the relationship between decadal-scale mean precipitation and monthly-scale extreme precipitation using the Australian Community Climate and Earth System Simulator Earth System model (ACCESS ESM1.5) climate model. The model large ensemble successfully reproduces the observed strong co-variability between monthly mean rainfall and wet extreme rainfall, defined as monthly rainfall totals above the 95th percentile. Removing SST variability in the ACCESS ESM1.5 model significantly weakens the co-variability between mean and wet extremes over most of the globe, showing that SSTs play a key role in modulating this co-variability. The study identifies Pacific and Atlantic SST patterns as the main drivers of the decadal scale co-variability in mean and extreme wet precipitation. On the other hand, observations and model results show that co-variability between mean and dry extremes is generally weaker than for wet extremes, with highly regional signals. Model experiments also show that SST variability plays a weaker role in modulating the co-variability between the mean precipitation and dry extremes as compared to wet extremes. These results suggest that stochastic atmospheric variability plays a stronger role in generating dry precipitation extremes compared SST forcing.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1088/1748-9326/ad2ab9
- https://iopscience.iop.org/article/10.1088/1748-9326/ad2ab9/pdf
- OA Status
- gold
- Cited By
- 3
- References
- 44
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4391933372
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4391933372Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1088/1748-9326/ad2ab9Digital Object Identifier
- Title
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Sea surface temperature driven modulation of decadal co-variability in mean and extreme precipitationWork title
- Type
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articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-02-19Full publication date if available
- Authors
-
Mustapha Adamu, Shayne McGregor, Ailie GallantList of authors in order
- Landing page
-
https://doi.org/10.1088/1748-9326/ad2ab9Publisher landing page
- PDF URL
-
https://iopscience.iop.org/article/10.1088/1748-9326/ad2ab9/pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
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https://iopscience.iop.org/article/10.1088/1748-9326/ad2ab9/pdfDirect OA link when available
- Concepts
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Climatology, Environmental science, Precipitation, Sea surface temperature, Atmospheric sciences, Meteorology, Geology, GeographyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
3Total citation count in OpenAlex
- Citations by year (recent)
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2025: 3Per-year citation counts (last 5 years)
- References (count)
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44Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.Earth | 31, 34 |
| abstract_inverted_index.Model | 151 |
| abstract_inverted_index.These | 178 |
| abstract_inverted_index.above | 64 |
| abstract_inverted_index.hand, | 127 |
| abstract_inverted_index.large | 43 |
| abstract_inverted_index.model | 36, 42, 75, 130 |
| abstract_inverted_index.other | 126 |
| abstract_inverted_index.plays | 12, 158, 185 |
| abstract_inverted_index.scale | 116 |
| abstract_inverted_index.study | 2, 102 |
| abstract_inverted_index.using | 25 |
| abstract_inverted_index.ACCESS | 73 |
| abstract_inverted_index.ESM1.5 | 74 |
| abstract_inverted_index.System | 32, 35 |
| abstract_inverted_index.globe, | 89 |
| abstract_inverted_index.highly | 148 |
| abstract_inverted_index.model. | 40 |
| abstract_inverted_index.strong | 49 |
| abstract_inverted_index.totals | 63 |
| abstract_inverted_index.weaker | 142, 160 |
| abstract_inverted_index.(ACCESS | 37 |
| abstract_inverted_index.Climate | 29 |
| abstract_inverted_index.ESM1.5) | 38 |
| abstract_inverted_index.Pacific | 104 |
| abstract_inverted_index.between | 17, 51, 80, 135, 166 |
| abstract_inverted_index.climate | 39 |
| abstract_inverted_index.decadal | 115 |
| abstract_inverted_index.defined | 59 |
| abstract_inverted_index.drivers | 112 |
| abstract_inverted_index.extreme | 23, 57, 121 |
| abstract_inverted_index.monthly | 52, 61 |
| abstract_inverted_index.results | 131, 179 |
| abstract_inverted_index.showing | 90 |
| abstract_inverted_index.suggest | 180 |
| abstract_inverted_index.surface | 8 |
| abstract_inverted_index.weakens | 77 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.Atlantic | 106 |
| abstract_inverted_index.Removing | 68 |
| abstract_inverted_index.compared | 174, 194 |
| abstract_inverted_index.ensemble | 44 |
| abstract_inverted_index.extremes | 84, 139, 172, 193 |
| abstract_inverted_index.forcing. | 196 |
| abstract_inverted_index.observed | 48 |
| abstract_inverted_index.patterns | 108 |
| abstract_inverted_index.rainfall | 54, 62 |
| abstract_inverted_index.regional | 149 |
| abstract_inverted_index.signals. | 150 |
| abstract_inverted_index.stronger | 187 |
| abstract_inverted_index.Community | 28 |
| abstract_inverted_index.Simulator | 33 |
| abstract_inverted_index.extremes, | 146 |
| abstract_inverted_index.extremes. | 177 |
| abstract_inverted_index.generally | 141 |
| abstract_inverted_index.rainfall, | 58 |
| abstract_inverted_index.Australian | 27 |
| abstract_inverted_index.generating | 190 |
| abstract_inverted_index.identifies | 103 |
| abstract_inverted_index.modulating | 14, 98, 163 |
| abstract_inverted_index.reproduces | 46 |
| abstract_inverted_index.stochastic | 182 |
| abstract_inverted_index.atmospheric | 183 |
| abstract_inverted_index.experiments | 152 |
| abstract_inverted_index.percentile. | 67 |
| abstract_inverted_index.temperature | 9 |
| abstract_inverted_index.variability | 11, 70, 157, 184 |
| abstract_inverted_index.investigates | 3 |
| abstract_inverted_index.observations | 128 |
| abstract_inverted_index.relationship | 16 |
| abstract_inverted_index.successfully | 45 |
| abstract_inverted_index.decadal-scale | 18 |
| abstract_inverted_index.monthly-scale | 22 |
| abstract_inverted_index.precipitation | 20, 24, 169, 192 |
| abstract_inverted_index.significantly | 76 |
| abstract_inverted_index.co-variability | 50, 79, 117, 134, 165 |
| abstract_inverted_index.precipitation. | 123 |
| abstract_inverted_index.co-variability. | 100 |
| cited_by_percentile_year.max | 97 |
| cited_by_percentile_year.min | 96 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 3 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/14 |
| sustainable_development_goals[0].score | 0.5 |
| sustainable_development_goals[0].display_name | Life below water |
| citation_normalized_percentile.value | 0.77907093 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |