Max Planck Institute for Meteorology
Recent publications
Climate change has heightened the need to understand physical climate risks, such as the increasing frequency and severity of heat waves, for informed financial decision-making. This study investigates the financial implications of extreme heat waves on stock returns in Europe and the United States. Accordingly, the study combines meteorological and stock market data by integrating methodologies from both climate science and finance. The authors use meteorological data to ascertain the five strongest heat waves since 1979 in Europe and the United States, respectively, and event study analyses to capture their effects on stock prices across firms with varying levels of environmental performance. The findings reveal a marked increase in the frequency of heat waves in the 21st century, reflecting global warming trends, and that European heat waves generally have a higher intensity and longer duration than those in the United States. This study provides evidence that extreme heat waves reduce stock values in both regions, with portfolio declines of up to 3.1%. However, there are marked transnational differences in investor reactions. Stocks listed in the United States appear more affected by the most recent heat waves compared to those further in the past, whereas the effect on European stock prices is more closely tied to event intensity and duration. For the United States sample only, the analysis reveals a mitigating effect of high corporate environmental performance against heat risk. This study introduces an innovative interdisciplinary methodology, merging meteorological precision with financial analytics to provide deeper insights into climate-related risks.
Plain Language Summary Enhancing understanding of the predictability of the El Niño‐Southern Oscillation (ENSO) is crucial for improving seasonal forecasting and managing extreme climate impacts. This study examines the seasonal Predictability Barrier (PRB) and Persistence Barrier (PEB) of ENSO using observational and dynamic prediction model data to analyze their intensity, timing, long‐term trends, and spatial distribution. Our analysis reveals a notable decrease in the intensity of the seasonal PRB of ENSO in dynamic models compared to the PEB. A marked increase in the strength of ENSO seasonal PRB and PEB was noted around the 2000s, potentially impacting ENSO predictability in the twenty‐first century. The central and eastern tropical Pacific regions are key areas for seasonal PRB and PEB occurrences. Decadal fluctuations in the chaotic nature of ENSO systems align with those of the seasonal PRB and PEB, implying that these barriers are predominantly influenced by the chaotic dynamics of ENSO systems.
To achieve the 1.5°C target of the Paris agreement, rapid, sustained, and deep emission reductions are required, which often includes negative emissions through land‐based mitigation. However, the effects of future land‐use change on climate are often not considered when quantifying the climate‐induced impacts on human heat stress and labor capacity. By conducting simulations with three fully coupled Earth System Models, we project the effects of land‐use change on heat stress and outdoor labor capacity for two contrasting future land‐use scenarios under high‐ambition mitigation. Achieving a sustainable land‐use scenario with increasing global forest cover instead of an inequality scenario with decreasing forest cover in the Global South causes a global cooling ranging between 0.09°C and 0.35°C across the Earth System Models. However, the effects on human heat stress are less strong, especially over the regions of intense land‐use change such as the tropics, where biogeophysical effects on near‐surface specific humidity and wind speed counteract the cooling effect under warm extremes. The corresponding influence on outdoor labor capacity is small and inconsistent across the three Earth System Models. These results clearly highlight the importance of land‐use change scenarios for achieving global temperature targets while questioning the adaptation potential for reduction in heat stress.
Permafrost thaw poses diverse risks to Arctic environments and livelihoods. Understanding the effects of permafrost thaw is vital for informed policymaking and adaptation efforts. Here, we present the consolidated findings of a risk analysis spanning four study regions: Longyearbyen (Svalbard, Norway), the Avannaata municipality (Greenland), the Beaufort Sea region and the Mackenzie River Delta (Canada) and the Bulunskiy District of the Sakha Republic (Russia). Local stakeholders’ and scientists’ perceptions shaped our understanding of the risks as dynamic, socionatural phenomena involving physical processes, key hazards, and societal consequences. Through an inter- and transdisciplinary risk analysis based on multidirectional knowledge exchanges and thematic network analysis, we identified five key hazards of permafrost thaw. These include infrastructure failure, disruption of mobility and supplies, decreased water quality, challenges for food security, and exposure to diseases and contaminants. The study’s novelty resides in the comparative approach spanning different disciplines, environmental and societal contexts, and the transdisciplinary synthesis considering various risk perceptions.
Space-borne remote sensing of atmospheric chemical constituents is crucial for monitoring and better understanding global and regional air quality. Since the 1990s, the continuous development of instruments onboard low-Earth orbit (LEO) satellites has led to major advances in air quality research by providing daily global measurements of atmospheric chemical species. The next generation of atmospheric composition satellites measures from the geostationary Earth orbit (GEO) with hourly temporal resolution, allowing the observation of diurnal variations of air pollutants. The first two instruments of the GEO constellation coordinated by the Committee on Earth Observation Satellites (CEOS), the Geostationary Environment Monitoring Spectrometer (GEMS) for Asia and the Tropospheric Emissions: Monitoring of Pollution (TEMPO) for North America, were successfully launched in 2020 and 2023, respectively. The European component, Sentinel-4, is planned for launch in 2025. This work provides an overview of satellite missions for atmospheric composition monitoring and the state of the science in air quality research. We cover recent advances in retrieval algorithms, the modeling of emissions and atmospheric chemistry, data assimilation, and the application of machine learning based on satellite data. We discuss the challenges and opportunities in air quality research in the era of GEO satellites, and provide recommendations on research priorities for the near future.
Climate-driven changes in high-elevation forest distribution and reductions in snow and ice cover have major implications for ecosystems and global water security. In the Greater Yellowstone Ecosystem of the Rocky Mountains (United States), recent melting of a high-elevation (3,091 m asl) ice patch exposed a mature stand of whitebark pine ( Pinus albicaulis ) trees, located ~180 m in elevation above modern treeline, that date to the mid-Holocene (c. 5,950 to 5,440 cal y BP). Here, we used this subfossil wood record to develop tree-ring-based temperature estimates for the upper-elevation climate conditions that resulted in ancient forest establishment and growth and the subsequent regional ice-patch growth and downslope shift of treeline. Results suggest that mid-Holocene forest establishment and growth occurred under warm-season (May-Oct) mean temperatures of 6.2 °C (±0.2 °C), until a multicentury cooling anomaly suppressed temperatures below 5.8 °C, resulting in stand mortality by c. 5,440 y BP. Transient climate model simulations indicate that regional cooling was driven by changes in summer insolation and Northern Hemisphere volcanism. The initial cooling event was followed centuries later (c. 5,100 y BP) by sustained Icelandic volcanic eruptions that forced a centennial-scale 1.0 °C summer cooling anomaly and led to rapid ice-patch growth and preservation of the trees. With recent warming (c. 2000–2020 CE), warm-season temperatures now equal and will soon exceed those of the mid-Holocene period of high treeline. It is likely that perennial ice cover will again disappear from the region, and treeline may expand upslope so long as plant-available moisture and disturbance are not limiting.
Societal Impact Statement The global carbon budget provides annual updates to society on the main cause of climate change—CO2 emissions—and quantifies carbon‐uptake ecosystem services provisioned by the biosphere. We show that more consistent assumptions in the estimates of land‐atmosphere carbon exchange results in a global carbon budget that is imbalanced (gains do not equal losses). This imbalance implies that key processes causing land carbon fluxes, especially processes associated with human land management and recovery following abandonment in anthropogenic biomes (anthromes), have been misquantified. This impacts policy for land carbon management across scales and calls for better understanding of carbon cycling in anthromes. Summary Inconsistencies in the calculation of the two anthropogenic land flux terms of the global carbon cycle are investigated. The two terms—the direct anthropogenic flux (caused by direct human disturbance in anthromes, currently a carbon source to the atmosphere) and the indirect anthropogenic flux (caused indirectly by human activities that lead to global change and affecting all biomes, currently an atmospheric carbon sink)—are typically calculated independently, resulting in inconsistent underlying assumptions. We harmonize the estimation of the two anthropogenic land flux terms by incorporating previous estimates of these inconsistencies. We recalculate the global carbon budget (GCB) and apply change‐point analysis to the cumulative budget imbalance. Cumulative over 1850–2018 (1959–2018), harmonization results in a 13% lesser (4% greater) land use source from anthromes and a 20% (23%) lesser land sink. This recalculation yields a greater non‐closure of the GCB, indicating a missing carbon sink averaging 0.65 Pg C year⁻¹ since the early 20th century. The imbalance likely results from a combination of method discontinuity and structural errors in the assessment of the direct anthropogenic land use flux, greater ocean carbon uptake, structural errors in land models, and in how these land terms are quantified for the budget. We caution against overconfidence in considering the GCB a solved problem and recommend further study of methodological discontinuities in budget terms. We strongly recommend studies that quantify the direct and indirect anthropogenic land fluxes simultaneously to ensure consistency, with a deeper understanding of human disturbance and legacy effects in anthromes.
The impact of ocean model resolution on sea level projections in the Southern Ocean is investigated using eddy-rich (ER) and eddy-parameterized configurations of the Max Planck Institute Earth System Model under the Shared Socioeconomic Pathway (SSP) 5-8.5 scenario. We employ the Flux-Anomaly Forced Model Intercomparison Project (FAFMIP) experiment—heat, stress, and freshwater perturbations—at both resolutions to pinpoint the sources of these differences. South of 55°S, we found that the changes in thermosteric and halosteric sea levels vary substantially between resolutions due to different responses to freshwater perturbations. In the eddy-parameterized model, the resulting increase in stratification suppresses the mixing of salt and heat from the Circumpolar Deep Water with surface layers. These cause differences in the response of surface fluxes and meridional transports yielding an increase in thermosteric sea levels and a decrease in halosteric sea levels. In the eddy-rich configuration, the main driver of eddy-induced warming and salinification between 40° and 44°S is wind stress perturbations. The efficiency of direct eddy effects in ER is restricted to small areas such as the Agulhas Retroflection, the Brazil–Malvinas confluence zone, the Tasman Sea, and, to some extent, the Antarctic Circumpolar Current (ACC). Contrary to expectations, ACC transport increases in the eddy-rich model while decreasing in the eddy-parameterized model under the SSP5-8.5 scenario. FAFMIP results reveal that this decrease is a result of the overcompensation of wind-induced changes by freshwater flux forcing. These results underscore the critical importance of high-resolution models for capturing the processes in sea level projections in the Southern Ocean and beyond. Significance Statement We studied how ocean model resolution affects sea level projections in the Southern Ocean using Max Planck Institute Earth System Model simulations. Higher-resolution models provide a more accurate representation of ocean circulation and its response to changing forcings. We examined how surface heat, momentum, and water fluxes, both separately and combined, shape ocean dynamics. In a strong global warming scenario, significant differences in steric sea level change were observed south of 55°S between the model that simulates eddies and the one that has their effects parameterized. The response to surface freshwater forcing is the primary cause of these differences. Our findings emphasize the critical role of ocean model resolution in accurately understanding and predicting future sea level changes, which is essential for effectively addressing our needs for adaptation.
Plain Language Summary The ocean contains about 60 times as much carbon as the atmosphere. The exchange of carbon between the ocean and the atmosphere is a major driver of global climate change. During the last ice age, atmospheric CO2 CO2{\text{CO}}_{2} concentrations were much lower, and the climate was much colder than today. Much evidence suggests that the ocean sequestered more carbon at the last ice age. Understanding this behavior of the ocean is vital to gaining knowledge about how the natural processes change atmospheric CO2 CO2{\text{CO}}_{2} and to better predict future atmospheric CO2 CO2{\text{CO}}_{2} and climate. Here, we use an Earth System Model to examine how the physical and biogeochemical processes in the ocean affected deep ocean carbon storage during the last ice age. We showcase that simulating a shallower Atlantic Meridional Overturning Circulation at the last ice age than it is today is crucial to reproducing proxy data observed from marine sediment cores. A more comprehensive representation of marine snow, a shower of biological debris from the upper ocean to the depth, and its sinking speeds also have a significant impact on the deep ocean carbon storage at the last ice age.
Changes in ocean salinity are essential for the stratification of the upper ocean and the regional marine ecosystem. In this study, 10 sets of large ensemble experiments and multi‐model ensembles from the Coupled Model Intercomparison Project Phase 6 (CMIP6) are used to investigate the effect of anthropogenic forcing on upper ocean salinity in the South China Sea (SCS). In most models, surface salinity increases during the historical period due to external forcing. Using the salinity budget, we find that a decrease in freshwater flux, particularly precipitation, is responsible for the increase in salinity, although horizontal advection also contributes to the change. Single forcing experiments reveal that the change in salinity in the SCS is mainly attributed to anthropogenic forcing, while the influence of natural forcing is relatively small. Anthropogenic aerosols (AAs) can decrease the dynamic and thermal components of precipitation, resulting in a considerable increase in salinity. In contrast, anthropogenic greenhouse gases (GHGs) have less effect on long‐term trend in SCS salinity because the GHG forcing leads to an increased thermal response of precipitation but a decreased dynamic response. Additionally, we use the Community Earth System Model version 1 (CESM1) to evaluate the role of different aerosol emission sources in modulating the salinity change in the SCS. The experimental results show that aerosol emissions from Asia dominate the salinity change in the SCS by changing the local Hadley circulation. In contrast, the contribution of aerosol emissions from North America and Europe (NAEU) is much smaller.
Arctic shorelines are vulnerable to climate change impacts as sea level rises, permafrost thaws, storms intensify, and sea ice thins. Seventy-five years of aerial and satellite observations have established coastal erosion as an increasing Arctic hazard. However, other hazards at play—for instance, the cumulative impact that sea-level rise and permafrost thaw subsidence will have on permafrost shorelines—have received less attention, preventing assessments of these processes’ impacts compared to and combined with coastal erosion. Alaska’s Arctic Coastal Plain (ACP) is ideal for such assessments because of the high-density observations of topography, coastal retreat rates, and permafrost characteristics, and importance to Indigenous communities and oilfield infrastructure. Here, we produce 21st-century projections of Arctic shoreline position that include erosion, permafrost subsidence, and sea-level rise. Focusing on the ACP, we merge 5 m topography, satellite-derived coastal lake depth estimates, and empirical assessments of land subsidence due to permafrost thaw with projections of coastal erosion and sea-level rise for medium and high emissions scenarios from the Intergovernmental Panel on Climate Change’s AR6 Report. We find that by 2100, erosion and inundation will together transform the ACP, leading to 6-8x more land loss than coastal erosion alone and disturbing 8-11x more organic carbon. Without mitigating measures, by 2100, coastal change could damage 40 to 65% of infrastructure in present-day ACP coastal villages and 10 to 20% of oilfield infrastructure. Our findings highlight the risks that compounding climate hazards pose to coastal communities and underscore the need for adaptive planning for Arctic coastlines in the 21st century.
Observational evidence has shown that precipitation extremes are expected to increase over Southeast Asia (SEA) under climate change. The physical mechanism of the future changes in precipitation extremes has remained largely unclear, which is a great challenge to project the future hydrologic cycle. In this study, the changes in precipitation extremes over SEA by the end of the 21st century (2071–2100) were estimated based on simulations from CMIP6 (Phase 6 of the Coupled Model Intercomparison Project) models. Results showed that the spatiotemporal intensity of precipitation extremes is expected to increase significantly over SEA, as compared to the historical period of 1985–2014. The frequency and intensity of precipitation extremes in Kalimantan is projected to increase markedly in 2071–2100. Moreover, the wet and dry periods will be intensified in SEA, which is consistent with the “wet-get-wetter, dry-get-drier” mechanism. We further investigated the thermodynamic and dynamic contributions to the enhanced precipitation extremes using a physical scaling diagnostic method, and results showed thermodynamic factors accounting for approximately 77% (75%) of the total scaling change under the SSP2-4.5 (SSP5-8.5) scenario, but dynamic components constituting around 18% (15%). Alterations in thermodynamic scaling prevail as the primary contributor to amplified precipitation extremes. Furthermore, it was verified that the change in saturation specific humidity of thermodynamic scaling is intensified, and the model simulation consistency of thermodynamic scaling is better than that of dynamic scaling, revealing the effects of atmospheric thermodynamics and dynamics in the change of precipitation extremes over SEA.
The radiation parameterization is one of the computationally most expensive components of Earth system models (ESMs). To reduce computational cost, radiation is often calculated on coarser spatial or temporal scales, or both, than other physical processes in ESMs, leading to uncertainties in cloud-radiation interactions and thereby in radiative temperature tendencies. One way around this issue is the emulation of the radiation parameterization using machine learning which is usually faster and has good accuracy in a high dimensional parameter space. This study investigates the development and interpretation of a machine learning based radiation emulator using the ICOsahedral Non-hydrostatic (ICON) model with the RTE-RRTMGP radiation code which calculates radiative fluxes based on the atmospheric state and its optical properties. With a Bidirectional Long Short-Term Memory (Bi-LSTM) architecture, which can account for vertical bidirectional auto-correlation, we can accurately emulate shortwave and longwave heating rates with a mean absolute error of 0.049 K/d(2.50%)0.049~K/d\,(2.50\%) and 0.069 K/d(5.14%)0.069~K/d\,(5.14\%) respectively. Further, we analyse the trained neural networks using Shapley Additive exPlanations (SHAP) and confirm that the networks have learned physical meaningful relationships among the inputs and outputs. Notably, we observe that the local temperature is used as a predictive source for the longwave heating, consistent with physical models of radiation. For shortwave heating, we find that clouds reflect radiation, leading to reduced heating below the cloud.
Northern forests are an important carbon sink, but our understanding of the driving factors is limited due to discrepancies between dynamic global vegetation models (DGVMs) and atmospheric inversions. We show that DGVMs simulate a 50% lower sink (1.1 ± 0.5 PgC yr⁻¹ over 2001–2021) across North America, Europe, Russia, and China compared to atmospheric inversions (2.2 ± 0.6 PgC yr⁻¹). We explain why DGVMs underestimate the carbon sink by considering how they represent disturbance processes, specifically the overestimation of fire emissions, and the lack of robust forest demography resulting in lower forest regrowth rates than observed. We reconcile net sink estimates by using alternative disturbance-related fluxes. We estimate carbon uptake through forest regrowth by combining satellite-derived forest age and biomass maps. We calculate a regrowth flux of 1.1 ± 0.1 PgC yr⁻¹, and combine this with satellite-derived estimates of fire emissions (0.4 ± 0.1 PgC yr⁻¹), land-use change emissions from bookkeeping models (0.9 ± 0.2 PgC yr⁻¹), and the DGVM-estimated sink from CO2 fertilisation, nitrogen deposition, and climate change (2.2 ± 0.9 PgC yr⁻¹). The resulting ‘bottom-up’ net flux of 2.1 ± 0.9 PgC yr⁻¹ agrees with atmospheric inversions. The reconciliation holds at regional scales, increasing confidence in our results.
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113 members
Suvarna Tikle
  • Environmental Modeling Division
Claudia Timmreck
  • Department Climate Physics
Klaus Arpe
  • Max Planck Institute for Meteorology
Stefan Kinne
  • Unit of Observations & Process Studies
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