Hans Joachim Schellnhuber’s research while affiliated with International Institute for Applied Systems Analysis and other places

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Publications (100)


Climate network and complexity approach predict neutral ENSO event for 2025
  • Preprint

January 2025

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H. J. Schellnhuber

The El Ni\~no Southern Oscillation (ENSO) is the strongest driver of interannual global climate variability and can lead to extreme weather events like droughts and flooding. Additionally, ENSO influences the mean global temperature with strong El Ni\~no events often leading, in a warming climate, to new record highs. Recently, we have developed two approaches for the early forecasting of El Ni\~no. The climate network-based approach allows forecasting the onset of an El Ni\~no event about 1 year ahead. The complexity-based approach allows additionally to forecast the magnitude of an upcoming El Ni\~no event in the calendar year before. These methods successfully forecasted the onset of an Eastern Pacific El Ni\~no for 2023/24 and the subsequent record-breaking warming of 2024. Here, we apply these methods to forecast the ENSO state in 2025. Both methods forecast the absence of an El Ni\~no in 2025, with 91.2% and 91.7% probability, respectively. Combining these forecasts with a logistic regression based on the Oceanic Ni\~no Index (ONI) leads to a 69.6% probability that 2025/26 will be a neutral ENSO event. We estimate the probability of a La Ni\~na at 21.8%. This makes it likely that the mean global temperature in 2025 will decrease somewhat compared to the 2024 level.


Kornhuber_etal_2024PNAS_SI.pdf
  • Data
  • File available

December 2024

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10 Reads

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Global emergence of regional heatwave hotspots outpaces climate model simulations

November 2024

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268 Reads

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8 Citations

Proceedings of the National Academy of Sciences

Multiple recent record-shattering weather events raise questions about the adequacy of climate models to effectively predict and prepare for unprecedented climate impacts on human life, infrastructure, and ecosystems. Here, we show that extreme heat in several regions globally is increasing significantly and faster in magnitude than what state-of-the-art climate models have predicted under present warming even after accounting for their regional summer background warming. Across all global land area, models underestimate positive trends exceeding 0.5 °C per decade in widening of the upper tail of extreme surface temperature distributions by a factor of four compared to reanalysis data and exhibit a lower fraction of significantly increasing trends overall. To a lesser degree, models also underestimate observed strong trends of contraction of the upper tails in some areas, while moderate trends are well reproduced in a global perspective. Our results highlight the need to better understand and model the drivers of extreme heat and to rapidly mitigate greenhouse gas emissions to avoid further harm from unexpected weather events.


Fig. 1. Climate network analysis of interactions within the complex Earth system. (a) Temperature anomaly time series from 1979 to 2022 for nodes located in the Tibetan Plateau and Arctic region. (b) Time-delayed Pearson cross-correlation function between the TP and Arctic nodes shown in (a). (c, d) Similar analyses as in (a, b) but for nodes in the TP and East China region. (e) Spatial representation of node locations and directional links: red indicates a time lag of -2 days (as shown in b, Arctic to TP), blue indicates = 2 days (as shown in c, TP to East China). Top right of (e): Representation of complexity science methodologies utilized in constructing the climate network; Bottom right: AI icon symbolizing the integration of AI in future research paradigms. The original image for (e) was created using artificial intelligence, specifically ChatGPT.
Complexity Science Meets Earth System

October 2024

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404 Reads

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3 Citations

Science Bulletin


Global emergence of regional heatwave hotspots outpaces climate model projections

June 2024

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176 Reads

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1 Citation

Multiple recent record shattering weather events raise questions about the adequacy of climate models to effectively predict and prepare for unprecedented climate impacts on human life, infrastructure, and ecosystems. Here we show that extreme heat in several regions globally is increasing significantly and faster in magnitude than what state-of-the-art climate models have predicted under present warming even after accounting for their regional summer background warming. Across all global land area, models underestimate positive trends exceeding 0.5 °C per decade in widening of the upper tail width of extreme surface temperature distributions by a factor of 4.1 compared to reanalysis data, and exhibit a lower fraction of significantly-increasing trends overall. This highlights the need to better understand and model the drivers of extreme heat and to rapidly mitigate greenhouse gas emissions to avoid further harm from unexpected weather events.


Fig. 4 Difference in forest area in million hectares (Mha) between 2100 and 2020. Shades of green represent the increase in plantation area in 2100 compared to 2020 (Mishra et al., 2022)
Bauhaus Earth: Sustainable Use of Wood in the Construction Sector

June 2024

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115 Reads

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1 Citation

In an ever warming world the need for action on the mitigation of climate change and climate restoration is overdue. To stay within the Paris Agreement guardrail of 2 °C above pre-industrial level of atmospheric CO2, the global economy and transport system must be decarbonized by 2050 at the latest. With the climate system more and more out of balance the need for additional carbon removal from the atmosphere will be inevitable. But how can this be done? One scalable solution is a transition of the building sector towards a sustainable bio-based construction economy. Based on the transdisciplinary idea of the Bauhaus movement in the early 20ies of the last century, the Bauhaus Earth was founded to bring their vision and ideals to live today with the climate crisis at its core. Key are climate-friendly materials, integrated planning and nature-based design. Sustainable forestry provides an extraordinary building material, which combined with today’s technology and innovation will transform cities into wooden human-made carbon sinks in order to restore the global climate, tenth by tenth of a degree Celsius.


The structure of the climate network. Each of the 14 grid points in the “El Niño basin” (red circles) is linked to each of the 193 grid points outside this domain (blue circles). The green rectangle denotes the Niño3.4 region
The forecasting scheme. We compare the average link strength S(t) in the climate network (red curve) with the decision threshold Θ=2.82\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\Theta =2.82$$\end{document} (horizontal line) and the ONI (right scale), between January 1981 and December 2011. When the link strength crosses the threshold from below and the last available ONI is below 0.5°C, we give an alarm and predict that a new El Niño episode will start in the following calendar year. Periods with an ONI greater or equal to 0.5°C for less than 5 months, i.e., periods that do not satify the definition of an El Niño are shown in light blue. The El Niño episodes (when the ONI is greater or equal 0.5°C for at least 5 months) are displayed in dark blue. Correct predictions are marked by green arrows and false alarms by dashed arrows. The early false alarms in February 1994 and July 2004 are followed by at least one ONI value equal or above 0.5°C in the same year. We would like to note that in the shown hindcasting period of the algorithm, the temporal distance between two El Niño onsets is at least 2 calendar years. However, this does not hold in general since in the learning phase (1950-1980, here not shown, see, e.g., the table in CPC 2023), there were 3 instances where an El Niño onset was directly followed by a 2nd onset in the following calendar year
The real-time forecasts. Same as Fig. 2, but for the period between January 2011 and December 2023. As in Fig. 2, the false alarm (in 2019) is followed by at least one ONI value equal to or above 0.5°C (highlighted in light blue) in the same year. Only alarms until 2022, where the outcome is known, are marked by arrows
Forecasts based on ocean temperatures. Similar to Figs. 2 and 3, but here the mean link strength S(t) is calculated from the potential temparature at 5 meter ocean depth. The construction of the climate network has been adapted to match the GODAS dataset: the climate network grid resolution is now 5° and the temporal resolution of the input data is 5 days. The figure shows version 2 of the forecasting algorithm for the decision threshold Θ=2.12\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\Theta =2.12$$\end{document}. All major El Niños are also predicted with the GODAS data set. In contrast, 2 small El Niños are now not predicted (1994 and 2018), but the 2006 El Niño is predicted additionally
Evaluation of the real-time El Niño forecasts by the climate network approach between 2011 and present

May 2024

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39 Reads

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2 Citations

Theoretical and Applied Climatology

El Niño episodes are part of the El Niño-Southern Oscillation (ENSO), which is the strongest driver of interannual climate variability, and can trigger extreme weather events and disasters in various parts of the globe. Previously we have described a network approach that allows to forecast El Niño events about 1 year ahead. Here we evaluate the real-time forecasts of this approach between 2011 and 2022. We find that the approach correctly predicted (in 2013 and 2017) the onset of both El Niño periods (2014-2016 and 2018-2019) and generated only 1 false alarm in 2019. In June 2022, the approach correctly forecasted the onset of an El Niño event in 2023. For determining the p-value of the 12 real-time forecasts, we consider 2 null hypotheses: (a) random guessing where we assume that El Niño onsets occur randomly, and (b) correlated guessing where we assume that in the year an El Niño ends, no new El Niño will start. We find pa≅0.005pa0.005p_a\cong 0.005 and pb≅0.015pb0.015p_b\cong 0.015, this way rejecting both the null hypotheses that the same quality of the forecast can be obtained by chance. We also discuss how the network algorithm can be further improved by systematically reducing the number of false alarms. For 2024, the method indicates the absence of a new El Niño event.



Fig. 1 Classification of the type of El Niño events. The table summarizes the classification according to 11 approaches. The numbers in the first row indicate the last two digits of the El Niño onset years. Eastern Pacific El Niños are marked 'E' and shown in orange. Central Pacific El Niños are marked`Cmarked`C' and shown in blue. El Niño events marked by 'M' are not identified as pure EP or CP events, see Supplementary Note 1.
Fig. 4 SSHA based forecasting scheme for the type of an El Niño event. Same as Fig. 3 but for the anomaly of the monthly sea surface height (SSH) difference between west Pacific and central Pacific as predictor for the type of an El Niño. Forecasting based on SSHA leads to the same forecasts as that based on SSTA.
Fig. 5 Composite evolution of equatorial SSTAs for different subsets of El Niños. a all EP El Niños, (b) all CP El Niños, and (c) the CP El Niños that were correctly forecasted by ΔT WP-CP . The longitude-time diagrams show the SSTA in ∘ C averaged between 5N and 5S. The figure shows that in the second half of the year before an EP event, there is a warming in the western Pacific while the central Pacific is significantly colder. In the year before a CP El Niño, there is a mild warming in the central Pacific, which later expands eastward. Subfigure (b) includes the 3 El Niños that were incorrectly forecasted as EP events. When only correctly forecasted CP events are considered (c), the warm anomalies in the center Pacific are more pronounced and cold anomalies are present in the western Pacific in the year before the onset. The figures confirm that ΔT WP-CP , which aggregates these patterns, is predictive of the type of an El Niño in the calendar year before the onset.
Contingency table showing the skill of the forecasting methods in predicting the type of an El Niño event.
Forecasting the El Niño type well before the spring predictability barrier

November 2023

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155 Reads

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7 Citations

npj Climate and Atmospheric Science

El Niño events represent anomalous episodic warmings, which can peak in the equatorial Central Pacific (CP events) or Eastern Pacific (EP events). The type of an El Niño (CP or EP) has a major influence on its impact and can even lead to either dry or wet conditions in the same areas on the globe. Here we show that the difference of the sea surface temperature anomalies between the equatorial western and central Pacific in December enables an early forecast of the type of an upcoming El Niño ( p -value < 10 ⁻³ ). Combined with a previously introduced climate network-based approach that allows to forecast the onset of an El Niño event, both the onset and type of an upcoming El Niño can be efficiently forecasted. The lead time is about 1 year and should allow early mitigation measures. In December 2022, the combined approach forecasted the onset of an EP event in 2023.



Citations (55)


... The performance of temperature forecasts is illustrated by time series plots for regions with heat risk in recent years. For T2m forecasts over land, three grid cells are selected from Western Europe (Ballester et al., 2023), North America (Kornhuber et al., 2024), and East Asia (Hua et al., 2023). Hindcasts from 1983 to 2010 are showcased in the first column of Figure 7, whereas raw and post-processed forecasts from 2011 to 2024 are in the second to sixth columns. ...

Reference:

Global Temperature Forecasting Incrementally Improved by Model Output Statistics
Global emergence of regional heatwave hotspots outpaces climate model simulations

Proceedings of the National Academy of Sciences

... Complex networks facilitate effective characterizations of links between different variables (Boccaletti et al. 2014;Boers et al. 2021;Fan et al. 2024). For a single variable, pairwise nonlinear associations can be identified from time series across different locations and then be mapped to a single-layer network, such as EPEs (Boers et al. 2019;Mondal et al. 2020;) and droughts (Mondal et al. 2023;Chauhan et al. 2024;Zhao et al. 2024). ...

Complexity Science Meets Earth System

Science Bulletin

... Lhotka et al. (2018) found that most of the regional climate models participating in EURO-CORDEX struggle to correctly simulate the joint contribution of large-scale circulation and land-atmosphere interactions, which affects the magnitude of modelled heatwaves. Boe ' et al. (2020) suggest that current EURO-CORDEX models do not capture the upper part of the climate change uncertainty range, and Kornhuber et al. (2024) showed that extreme heat in several regions globally is increasing faster than what predicted by models. Depending on whether models underestimate the forced response or the internal variability, Vautard et al. (2023) claim that the pace of future summer extreme heat in Europe is unclear. ...

Global emergence of regional heatwave hotspots outpaces climate model projections

... Critical insights from current research are integrated throughout, particularly focusing on decision-making processes essential for enhancing agricultural resilience, as explored in (Bekee B 2023) [4] . Ultimately, the essay culminates in a synthesis of findings that not only advances academic discourse but also proposes actionable strategies for farmers, thereby bridging the gap between technology and sustainable agricultural practices, as underscored in (Schellnhuber HJ 2024) [11] . ...

Bauhaus Earth: Sustainable Use of Wood in the Construction Sector

... To resolve this problem, we have recently introduced two alternative forecasting approaches, which considerably extend the probabilistic prediction horizon. The first approach [1][2][3] is based on complex network analysis [48][49][50][51][52][53][54][55] and provides forecasts for the onset of an El Niño event, but not for its magnitude, in the year before the event starts. The second approach [4] relies on the System Sample Entropy (SysSampEn), an information entropy, which measures the complexity (disorder) in the Niño3.4 ...

Evaluation of the real-time El Niño forecasts by the climate network approach between 2011 and present

Theoretical and Applied Climatology

... The method provides forecasts for both the onset and magnitude of an El Niño event at the end of the previous year. By regarding additional predictors, the El Niño forecasts of these methods can be leveraged to obtain more specific forecasts, for instance, for the type (Eastern Pacific or Central Pacific) of an El Niño event [56,57]. ...

Forecasting the El Niño type well before the spring predictability barrier

npj Climate and Atmospheric Science

... All prior climate records were broken in 2023, and 2024 is expected to witness even higher temperatures (Mooney, 2023). Scientists have been taken aback by abrupt climate change, which has raised concerns about the dangers of extreme weather, dangerous climate chain reactions, and the possibility of destructive tipping points occurring sooner than anticipated (Mckay et al., 2022;Ripple et al., 2023). Natural disasters are wreaking havoc on planet earth, which ultimately leads to development of mental health issues among the masses. ...

Many risky feedback loops amplify the need for climate action
  • Citing Article
  • February 2023

One Earth

... Neglecting these regions in the SDG framework could precipitate an unforeseen "tragedy of the commons". More importantly, once polar regions are 'left behind', it might seriously impair the Earth's sustainable future through the cascading effects of interconnected tipping elements 21 , thereby jeopardizing efforts to maintain planetary boundaries within a safe operating space 22 . If the right actions are implemented through global partnerships (SDG17), they would not only strengthen the sustainable development in polar regions, but also further enable the achievement of global SDGs. ...

Teleconnections among tipping elements in the Earth system

Nature Climate Change

... Furthermore, research should not be a PR exercise aimed to sway the public, in open democracies we have a duty to do honest risk assessments combined with clear recommendations for what can be done. 19 Of course, these factors are only compounded by the consensus procedures of the IPCC, which seeks to synthesise scientific evidence for political purposes but is still often held up as a neutral arbiter of climate science. While useful, these procedures tend to produce lowest common-denominator outcome, which is precisely what is not needed when exploring extreme risks. ...

Reply to Bhowmik et al.: Democratic climate action and studying extreme climate risks are not in tension

Proceedings of the National Academy of Sciences

... There is no reason that considering extreme risks will slow decarbonisation or hinder adaptation. Instead, a lack of effective risk assessments can slow action and create faulty policies (Kemp et al., 2022a(Kemp et al., , 2022b(Kemp et al., , 2022c. Nor is there strong or convincing evidence that considering extreme risks will inevitably lead to apathy. ...

Reply to Burgess et al: Catastrophic climate risks are neglected, plausible, and safe to study

Proceedings of the National Academy of Sciences