Didier Monselesan

Didier Monselesan

orcid

Research Focus & Metrics

Academic Career Length

40Years (1987-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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2 February 2015 in Nature Climate Change
Verified
Journal Article
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DRDean Roemmich
Dean Roemmich
JCJohn Church
John Church
JGJohn Gilson
John Gilson
DMDidier Monselesan
Didier Monselesan
PSPhilip Sutton
Philip Sutton
SWSusan Wijffels
Susan Wijffels

26 June 2017 in Nature Climate Change
Verified
Journal Article
Closed access
XCXianyao Chen
Xianyao Chen
XZXuebin Zhang
Xuebin Zhang
JCJohn Church
John Church
CWChristopher S. Watson
Christopher S. Watson
MKMatt King
Matt King
CHChristopher Harig
Christopher Harig

7 September 2020 in Earth System Science Data
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Journal Article
Open access
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KSKarina von Schuckmann
Karina von Schuckmann
LCLijing Cheng
Lijing Cheng
MPMatthew D. Palmer
Matthew D. Palmer
JHJames Hansen
James Hansen
CTCaterina Tassone
Caterina Tassone
SWSusan E. Wijffels
Susan E. Wijffels
Human-induced atmospheric composition changes cause a radiative imbalance at the top of the atmosphere which is driving global warming. This Earth energy imbalance (EEI) is the most critical number defining the prospects for continued global warming and climate change. Understanding the heat gain of the Earth system – and particularly how much and where the heat is distributed – is fundamental to understanding how this affects warming ocean, atmosphere and land; rising surface temperature; sea level; and loss of grounded and floating ice, which are fundamental concerns for society. This study is a Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory and presents an updated assessment of ocean warming estimates as well as new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period 1960–2018. The study obtains a consistent long-term Earth system heat gain over the period 1971–2018, with a total heat gain of 358±37 ZJ, which is equivalent to a global heating rate of 0.47±0.1 W m −2 . Over the period 1971–2018 (2010–2018), the majority of heat gain is reported for the global ocean with 89 % (90 %), with 52 % for both periods in the upper 700 m depth, 28 % (30 %) for the 700–2000 m depth layer and 9 % (8 %) below 2000 m depth. Heat gain over land amounts to 6 % (5 %) over these periods, 4 % (3 %) is available for the melting of grounded and floating ice, and 1 % (2 %) is available for atmospheric warming. Our results also show that EEI is not only continuing, but also increasing: the EEI amounts to 0.87±0.12 W m −2 during 2010–2018. Stabilization of climate, the goal of the universally agreed United Nations Framework Convention on Climate Change (UNFCCC) in 1992 and the Paris Agreement in 2015, requires that EEI be reduced to approximately zero to achieve Earth's system quasi-equilibrium. The amount of CO 2 in the atmosphere would need to be reduced from 410 to 353 ppm to increase heat radiation to space by 0.87 W m −2 , bringing Earth back towards energy balance. This simple number, EEI, is the most fundamental metric that the scientific community and public must be aware of as the measure of how well the world is doing in the task of bringing climate change under control, and we call for an implementation of the EEI into the global stocktake based on best available science. Continued quantification and reduced uncertainties in the Earth heat inventory can be best achieved through the maintenance of the current global climate observing system, its extension into areas of gaps in the sampling, and the establishment of an international framework for concerted multidisciplinary research of the Earth heat inventory as presented in this study. This Earth heat inventory is published at the German Climate Computing Centre (DKRZ, https://www.dkrz.de/, last access: 7 August 2020) under the DOI https://doi.org/10.26050/WDCC/GCOS_EHI_EXP_v2 (von Schuckmann et al., 2020).

25 March 2022 in npj Climate and Atmospheric Science
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DRDoug Richardson
Doug Richardson
ABAmanda S. Black
Amanda S. Black
DIDamien Irving
Damien Irving
RMRichard J. Matear
Richard J. Matear
DMDidier Monselesan
Didier Monselesan
CTCarly R. Tozer
Carly R. Tozer
Wildfire can cause significant adverse impacts to society and the environment. Weather and climate play an important role in modulating wildfire activity. We explore the joint occurrence of global fire weather and meteorological drought using a compound events framework. We show that, for much of the globe, burned area increases when periods of heightened fire weather compound with dry antecedent conditions. Regions associated with wildfire disasters, such as southern Australia and the western USA, are prone to experiencing years of compound drought and fire weather. Such compound events have increased in frequency for much of the globe, driven primarily by increases in fire weather rather than changes in precipitation. El Ni $$\tilde{{{{\rm{n}}}}}$$ñ o Southern Oscillation is associated with widespread, spatially compounding drought and fire weather. In the Northern Hemisphere, a La Ni $$\tilde{{{{\rm{n}}}}}$$ñ a signature is evident, whereas El Ni $$\tilde{{{{\rm{n}}}}}$$ñ o is associated with such events in the tropics and, to a lesser degree, the Southern Hemisphere. Other climate modes and regional patterns of atmospheric circulation are also important, depending on the region. We show that the lengths of the fire weather seasons in eastern Australia and western North America have increased substantially since 2000, raising the likelihood of overlapping fire weather events in these regions. These cross-hemispheric events may be linked to the occurrence of El Ni $$\tilde{{{{\rm{n}}}}}$$ñ o, although the sea-surface temperature magnitudes are small. Instead, it is likely that anthropogenic climate change is the primary driver of these changes.

19 June 2025 in Earth System Science Data
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Journal Article
Open access
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PFPiers M. Forster
Piers M. Forster
CSChris Smith
Chris Smith
TWTristram Walsh
Tristram Walsh
WLWilliam F. Lamb
William F. Lamb
RLRobin Lamboll
Robin Lamboll
PZPanmao Zhai
Panmao Zhai
In a rapidly changing climate, evidence-based decision-making benefits from up-to-date and timely information. Here we compile monitoring datasets (published at https://doi.org/10.5281/zenodo.15639576; Smith et al., 2025a) to produce updated estimates for key indicators of the state of the climate system: net emissions of greenhouse gases and short-lived climate forcers, greenhouse gas concentrations, radiative forcing, the Earth's energy imbalance, surface temperature changes, warming attributed to human activities, the remaining carbon budget, and estimates of global temperature extremes. This year, we additionally include indicators for sea-level rise and land precipitation change. We follow methods as closely as possible to those used in the IPCC Sixth Assessment Report (AR6) Working Group One report. The indicators show that human activities are increasing the Earth's energy imbalance and driving faster sea-level rise compared to the AR6 assessment. For the 2015–2024 decade average, observed warming relative to 1850–1900 was 1.24 [1.11 to 1.35] °C, of which 1.22 [1.0 to 1.5] °C was human-induced. The 2024-observed best estimate of global surface temperature (1.52 °C) is well above the best estimate of human-caused warming (1.36 °C). However, the 2024 observed warming can still be regarded as a typical year, considering the human-induced warming level and the state of internal variability associated with the phase of El Niño and Atlantic variability. Human-induced warming has been increasing at a rate that is unprecedented in the instrumental record, reaching 0.27 [0.2–0.4] °C per decade over 2015–2024. This high rate of warming is caused by a combination of greenhouse gas emissions being at an all-time high of 53.6±5.2 Gt CO 2 e yr −1 over the last decade (2014–2023), as well as reductions in the strength of aerosol cooling. Despite this, there is evidence that the rate of increase in CO 2 emissions over the last decade has slowed compared to the 2000s, and depending on societal choices, a continued series of these annual updates over the critical 2020s decade could track decreases or increases in the rate of the climatic changes presented here.

16 October 2013 in Journal of Climate
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Journal Article
Open access
AGAlexander Sen Gupta
Alexander Sen Gupta
NJNicolas C. Jourdain
Nicolas C. Jourdain
JBJaclyn N. Brown
Jaclyn N. Brown
DMDidier Monselesan
Didier Monselesan
Climate models often exhibit spurious long-term changes independent of either internal variability or changes to external forcing. Such changes, referred to as model “drift,” may distort the estimate of forced change in transient climate simulations. The importance of drift is examined in comparison to historical trends over recent decades in the Coupled Model Intercomparison Project (CMIP). Comparison based on a selection of metrics suggests a significant overall reduction in the magnitude of drift from phase 3 of CMIP (CMIP3) to phase 5 of CMIP (CMIP5). The direction of both ocean and atmospheric drift is systematically biased in some models introducing statistically significant drift in globally averaged metrics. Nevertheless, for most models globally averaged drift remains weak compared to the associated forced trends and is often smaller than the difference between trends derived from different ensemble members or the error introduced by the aliasing of natural variability. An exception to this is metrics that include the deep ocean (e.g., steric sea level) where drift can dominate in forced simulations. In such circumstances drift must be corrected for using information from concurrent control experiments. Many CMIP5 models now include ocean biogeochemistry. Like physical models, biogeochemical models generally undergo long spinup integrations to minimize drift. Nevertheless, based on a limited subset of models, it is found that drift is an important consideration and must be accounted for. For properties or regions where drift is important, the drift correction method must be carefully considered. The use of a drift estimate based on the full control time series is recommended to minimize the contamination of the drift estimate by internal variability.