Degree Of Warming Research Articles

The influence of climate change on the potential distribution of Ageratum conyzoides in China.

Ageratum conyzoides L., an invasive plant originating from South America, is characterized by rapid growth and strong ecological adaptability, posing a threat to China's ecosystems, agricultural industry, and biodiversity. In this study, we optimized the MaxEnt model using the ENMeval package and constructed an ensemble model using the Biomod2 package based on global geospatial distribution data of A. conyzoides and considering climate, soil, and topography factors. We simulated the potential suitable distribution of A. conyzoides in China at present and in the future (2041-2060, 2061-2080). Through multivariate environment similarity surface and most dissimilar variable analysis, we identified the main environmental variables influencing the distribution of A. conyzoides. Additionally, niche analysis elucidated temporal and spatial variations in A. conyzoides' climate niche. Our results demonstrate that the ensemble model, constructed from the top seven single models, outperforms the individual models in predicting the suitable habitat of A. conyzoides. The ensemble model achieved the true skill statistic (TSS) of 0.833 and the area under the subject curve (AUC) of 0.971, indicative of outstanding predictive performance. Presently, the suitable habitat of A. conyzoides in China primarily exists in the region between 18° and 28° N, covering approximately 1.47 million km2. The temperature annual range, precipitation of the wettest month, and mean temperature of the coldest quarter were identified as the primary environmental variables influencing its distribution, while soil and elevation variables had minor roles. Under future climate conditions, the suitable habitat of A. conyzoides is expected to expand northeastward, with the centroid of its habitat shifting northward as the climate warms. The migration speed of A. conyzoides is projected to increase with the degree of warming. Furthermore, the climate niche of A. conyzoides will undergo certain changes and may face both niche expansion and a decrease in niche overlap under different climate conditions.

Projected Changes in Mean and Extreme Precipitation over Northern Mexico

Abstract Northern Mexico is home to more than 32 million people and is of significant agricultural and economic importance for the country. The region includes three distinct hydroclimatic regions, all of which regularly experience severe dryness and flooding and are highly susceptible to future changes in precipitation. To date, little work has been done to characterize future trends in either mean or extreme precipitation over northern Mexico. To fill this gap, we investigate projected precipitation trends over the region in the NA-CORDEX ensemble of dynamically downscaled simulations. We first verify that these simulations accurately reproduce observed precipitation over northern Mexico, as derived from the Multi-Source Weighted-Ensemble Precipitation (MSWEP) product, demonstrating that the NA-CORDEX ensemble is appropriate for studying precipitation trends over the region. By the end of the century, simulations forced with a high-emissions scenario project that both mean and extreme precipitation will decrease to the west and increase to the east of the Sierra Madre highlands, decreasing the zonal gradient in precipitation. We also find that the North American monsoon, which is responsible for a substantial fraction of the precipitation over the region, is likely to start later and last approximately three weeks longer. The frequency of extreme precipitation events is expected to double throughout the region, exacerbating the flood risk for vulnerable communities in northern Mexico. Collectively, these results suggest that the extreme precipitation-related dangers that the region faces, such as flooding, will increase significantly by the end of the century, with implications for the agricultural sector, economy, and infrastructure. Significance Statement Northern Mexico regularly experiences severe flooding and its important agricultural sector can be heavily impacted by variations in precipitation. Using high-resolution climate model simulations that have been tested against observations, we find that these hydroclimate extremes are likely to be exacerbated in a warming climate; the dry (wet) season is projected to receive significantly less (more) precipitation (approximately ±10% by the end of the century). Simulations suggest that some of the changes in precipitation over the region can be related to the North American monsoon, with the monsoon starting later in the year and lasting several weeks longer. Our results also suggest that the frequency of extreme precipitation will increase, although this increase is smaller than that projected for other regions, with the strongest storms becoming 20% more frequent per degree of warming. These results suggest that this region may experience significant changes to its hydroclimate through the end of the century that will require significant resilience planning.

An emergent constraint on the thermal sensitivity of photosynthesis and greenness in the high latitude northern forests

Despite the general consensus that the warming over the high latitudes northern forests (HLNF) has led to enhanced photosynthetic activity and contributed to the greening trend, isolating the impact of temperature increase on photosynthesis and greenness has been difficult due to the concurring influence of the CO2 fertilization effect. Here, using an ensemble of simulations from biogeochemical models that have contributed to the Trends in Net Land Atmosphere Carbon Exchange project (TRENDY), we identify an emergent relationship between the simulation of the climate-driven temporal changes in both gross primary productivity (GPP) and greenness (Leaf Area Index, LAI) and the model’s spatial sensitivity of these quantities to growing-season (GS) temperature. Combined with spatially-resolved observations of LAI and GPP, we estimate that GS-LAI and GS-GPP increase by 17.0 ± 2.4% and 24.0 ± 3.0% per degree of warming, respectively. The observationally-derived sensitivities of LAI and GPP to temperature are about 40% and 71% higher, respectively, than the mean of the ensemble of simulations from TRENDY, primarily due to the model underestimation of the sensitivity of light use efficiency to temperature. We estimate that the regional mean GS-GPP increased 28.2 ± 5.1% between 1983–1986 and 2013–2016, much larger than the 5.8 ± 1.4% increase from the CO2 fertilization effect implied by Wenzel et al. This suggests that warming, not CO2 fertilization, is primarily responsible for the observed dramatic changes in the HLNF biosphere over the last century.

Why the lower stratosphere cools when the troposphere warms

Observational data have long suggested that in the tropics, when the troposphere locally warms, the lower stratosphere locally cools. Here, the observed anti-correlation between tropospheric and lower stratospheric temperature is confirmed-the lower stratosphere cools by approximately 2 degrees per degree of warming in the mid-troposphere. This anti-correlation is explained through a recently proposed theory holding that there is a quasi-balanced response of the stratosphere to tropospheric heating [J. Lin, K. Emanuel, Tropospheric thermal forcing of the stratosphere through quasi-balanced dynamics. J. Atmos. Sci. (2024).]. The local-scale anti-correlation between tropospheric and lower stratospheric temperature also holds when considering climate change-where the troposphere has been anomalously warming relative to the zonal mean, the lower stratosphere has been anomalously cooling, and vice versa. This suggests that zonally asymmetries in tropospheric temperature trends will be reflected in that of the lower stratospheric temperature trends. The zonally asymmetric trends are also found to be comparable in magnitude to the mean temperature trends in the lower stratosphere, highlighting the importance of the pattern of warming. The results and proposed theory suggest that in addition to forcing via wave-dissipation, the lower stratosphere can also be subject to direct forcing by the troposphere, through quasi-steady, quasi-balanced dynamics.

Proximity to freshwater and seagrass availability mediate the impacts of climate change on the distribution of the West Indian manatee

How climate change alters persistence and distribution of endangered species is an urgent question in current ecological research. However, many species distribution models do not consider consumers in the context of their resources. The distribution and survival of the West Indian manatee (Trichechus manatus), listed as a Vulnerable species on the IUCN Red List, critically depend on seagrass resources and freshwater sources for drinking. We parameterized Maxent models with Bio-ORACLE environmental layers, freshwater proximity data, and modelled seagrass distance layers, to determine manatee and seagrass distributions under future climate change scenarios. We used two plausible IPCC Representative Concentration Pathways (RCP45 and RCP26, respectively) for the year 2050. The model fits had high accuracies and predicted a marked decline in seagrass coverage (RCP26: -1.9%, RCP45: -6%), coinciding with declines in manatee ranges (RCP26: -9%, RCP45: -11.8%). We also found that over 94% of the projected manatee distribution for all scenarios fell within the seagrass distribution. The analysis showed a decline in seagrass coverage to significantly impact manatee distributions, since the distance to seagrass ecological layer contributed significantly to manatee distributions, along with distance to freshwater sources. Our findings suggest that manatees will lose substantial range due to future climate change, but the extent and direction of this change will be mediated by the degree of warming and its impact on the resources manatees depend on.

Constraining CMIP6 estimates of Arctic Ocean temperature and salinity in 2025-2055

Global climate models (CMIP6 models) are the basis for future predictions and projections, but these models typically have large biases in their mean state of the Arctic Ocean. Considering a transect across the Arctic Ocean, with a focus on the depths between 100-700m, we show that the model spread for temperature and salinity anomalies increases significantly during the period 2025-2045. The maximum model spread is reached in the period 2045-2055 with a standard deviation 10 times higher than in 1993-2010. The CMIP6 models agree that there will be warming, but do not agree on the degree of warming. This aspect is important for long-term management of societal and ecological perspectives in the Arctic region. We therefore test a new approach to find models with good performance. We assess how CMIP6 models represent the horizontal patterns of temperature and salinity in the period 1993-2010. Based on this, we find four models with relatively good performance (MPI-ESM1-2-HR, IPSL-CM6A-LR, CESM2-WACCM, MRI-ESM2-0). For a more robust model evaluation, we consider additional metrics (e.g., climate sensitivity, ocean heat transport) and also compare our results with other recent CMIP6 studies in the Arctic Ocean. Based on this, we find that two of the models have an overall better performance (MPI-ESM1-2-HR, IPSL-CM6A-LR). Considering projected changes for temperature for the period 2045-2055 in the high end ssp585 scenario, these two models show a similar warming in the Mid Layer (300-700m; 1.1-1.5°C). However, in the low end ssp126 scenario, IPSL-CM6A-LR shows a considerably higher warming than MPI-ESM1-2-HR. In contrast to the projected warming by both models, the projected salinity changes for the period 2045-2055 are very different; MPI-ESM1-2-HR shows a freshening in the Upper Layer (100-300m), whereas IPSL-CM6A-LR shows a salinification in this layer. This is the case for both scenarios. The source of the model spread appears to be in the Eurasian Basin, where warm waters enter the Arctic. Finally, we recommend being cautious when using the CMIP6 ensemble to assess the future Arctic Ocean, because of the large spread both in performance and the extent of future changes.

Quantifying thermal adaptation of soil microbial respiration

Quantifying the rate of thermal adaptation of soil microbial respiration is essential in determining potential for carbon cycle feedbacks under a warming climate. Uncertainty surrounding this topic stems in part from persistent methodological issues and difficulties isolating the interacting effects of changes in microbial community responses from changes in soil carbon availability. Here, we constructed a series of temperature response curves of microbial respiration (given unlimited substrate) using soils sampled from around New Zealand, including from a natural geothermal gradient, as a proxy for global warming. We estimated the temperature optima ({T}_{{opt}}) and inflection point ({T}_{inf }) of each curve and found that adaptation of microbial respiration occurred at a rate of 0.29 °C ± 0.04 1SE for {T}_{{opt}} and 0.27 °C ± 0.05 1SE for {T}_{inf } per degree of warming. Our results bolster previous findings indicating thermal adaptation is demonstrably offset from warming, and may help quantifying the potential for both limitation and acceleration of soil C losses depending on specific soil temperatures.

Intensive and extensive margins of the peak load: Measuring adaptation with mixed frequency panel data

In this work we investigate the response of daily electricity peak load to daily maximum temperatures across states in Europe and India. We propose a method that decomposes short- from medium/long-run effects, retains the high frequency nature of the load-weather covariation and treats economic growth as a modulating factor. By simultaneously exploiting variation in unexpected daily weather anomalies and decade-long climatic changes in each location we decompose transitory - intensive margin - adjustments from permanent - extensive margin - adjustments. We find that the shocks over the long-run differ substantially from the short-run dynamics. Furthermore, we find evidence that per capita income modulates the adjustments over the short- and long-run. We project that in response to climate change around 2050 the peak load may increase by up to 20%-30% in Southern Europe and in several states in India, depending on the degree of warming and the evolution of socio-economic conditions. Even with a limited scope to two world regions, we identify that the structure of the economy and differences in future income growth matter in shaping the adaptation to climate change. Our decomposition allows to identify how future weather anomalies can further amplify the relative increase associated to the shift in the climate norm. Assuming that the interannual variability of maximum temperatures follows the distribution observed in the past, we find a doubling of the impacts of climate change during the summer in Europe. Uncertainty around the distribution of future weather anomalies may lead to further unexpected peak load amplifications. Our results have important policy implications for power systems’ generation capacity, transmission and storage, as we show that the challenges to accommodate the peak load in days with extreme temperatures may substantially increase already around mid-century.

Predicting Changes in Population Exposure to Precipitation Extremes over Beijing–Tianjin–Hebei Urban Agglomeration with Regional Climate Model RegCM4 on a Convection-Permitting Scale

In this study, we have investigated changes in precipitation extremes and the population’s exposure to these extremes during 2091–2099 in China’s Beijing–Tianjin–Hebei (JJJ) region relative to the historical period of 1991–1999. First, the regional climate model RegCM4, with a hydrostatic dynamic core, was run for east Asia, including China, at a 12 km resolution for 1990–1999 and 2090–2099. This model is forced by global climate model (GCM) MPI-ESM1.2-HR under the middle shared socioeconomic pathways (SSP245). The first year was used as a model spinup. Then, the 12 km results were used to force RegCM4 with a non-hydrostatic dynamic core (RegcM4-NH) at a 3 km convection-permitting scale over the JJJ region during the historical and future periods. Future precipitation extremes were predicted to increase over the whole of China and its four subregions, while decreases were predicted over the JJJ region. This may partly be caused by lower increases in specific humidity over the JJJ region. The percentage contributions of the three components of total population exposure, i.e., changes in exposure due to changes in the population, precipitation extremes and the joint impact of the population and extremes, were then analyzed. Changes in the population and wet extremes were closely related to changes in the total exposure over the JJJ region. The population is the dominant factor that most impacts the total exposure to dry extremes. Finally, changes in future population exposure to precipitation extremes per degree of warming were quantified for the JJJ region.

Revisiting temperature sensitivity: how does Antarctic precipitation change with temperature?

Abstract. With progressing global warming, snowfall in Antarctica is expected to increase, which could counteract or even temporarily overcompensate increased ice-sheet mass losses caused by increased ice discharge and melting. For sea-level projections it is therefore vital to understand the processes determining snowfall changes in Antarctica. Here we revisit the relationship between Antarctic temperature changes and precipitation changes, identifying and explaining regional differences and deviations from the theoretical approach based on the Clausius–Clapeyron relationship. Analysing the latest estimates from global (CMIP6, Coupled Model Intercomparison Project Phase 6) and regional (RACMO2.3) model projections, we find an average increase of 5.5 % in annual precipitation over Antarctica per degree of warming, with a minimum sensitivity of 2 % K−1 near Siple Coast and a maximum sensitivity of > 10 % K−1 at the East Antarctic plateau region. This large range can be explained by the prevailing climatic conditions, with local temperatures determining the Clausius–Clapeyron sensitivity that is counteracted in some regions by the prevalence of the coastal wind regime. We compare different approaches of deriving the sensitivity factor, which in some cases can lead to sensitivity changes of up to 7 percentage points for the same model. Importantly, local sensitivity factors are found to be strongly dependent on the warming level, suggesting that some ice-sheet models which base their precipitation estimates on parameterisations derived from these sensitivity factors might overestimate warming-induced snowfall changes, particularly in high-emission scenarios. This would have consequences for Antarctic sea-level projections for this century and beyond.

Changes in mean and extreme homogeneous precipitation in China during 1960–2020

This study aims to explore the observed national and regional changes in the seasonal mean and extreme precipitation in mainland China between 1960 and 2020 using data from 678 stations. Tests of homogeneity (e.g. standard normal homogeneity test, Pettitt's test and Buishand range test) are applied to identify homogeneous stations for the trend analysis. The non-parametric Mann-Kendall test and a modified Theil-Sen slope estimator were then used to examine changes in the precipitation characteristics. Our results show that despite a decreasing trend in the frequency of wet days, the mean precipitation has actually increased. Extreme precipitation has also increased, and in many locations, at greater rates than those of the mean. This is principally due to a greater rate of increase per degree of warming, of 8% for extreme precipitation compared to 7% for the mean. However, considerably regional and seasonal variability has been seen in the trends. Mean and extreme precipitation trends are positive throughout in western China for all seasons, but they vary in eastern China. Mean precipitation increased slightly in the southeast but decreased in the northeast of the country. Extreme precipitation increased in both regions, but the increases were greater in the southeast. Trends, additionally, also differed within regions, especially over eastern China. In southeast China, precipitation increased in the east and decreased in the west. In northeast China, precipitation increased in the north and decreased in the south. Using a multiple regression model, we found that changes during summer precipitation clearly dominate the overall annual changes in most regions. Most long-term changes over eastern China appear to be linked to those of the East-Asian and South-Asian Summer Monsoons.

Global Increase of the Intensity of Tropical Cyclones under Global Warming Based on their Maximum Potential Intensity and CMIP6 Models

Future changes in the intensity of tropical cyclones (TCs) under global warming are uncertain, although several studies have projected an upward trend in TC intensity. In this study, we examined the changes in the strength of TCs in the twenty-first century based on the Hurricane Maximum Potential Intensity (HuMPI) model forced with the sea surface temperature (SST) from the bias-corrected CMIP6 dataset. We first investigated the relationship between the mean lifetime maximum intensity (LMI) of major hurricanes (MHs) and the maximum potential intensity (MPI) using the SST from the Daily Optimum Interpolation SST database. The LMI of MHs and the MPI in the last two decades was, on average, 2–3% higher than mean values in the sub-period 1982–2000, suggesting a relationship between changes in MPI and LMI. From our findings, the projected changes in TC intensity in the near-future period (2016–2040) will be almost similar for SSP2-4.5 and SSP5-8.5 climate scenarios. However, TCs will be 9.5% and 17% more intense by the end (2071–2100) of the twenty-first century under both climate scenarios, respectively, compared with the mean intensity over the historical period (1985–2014). In addition, the MPI response to a warmed sea surface temperature per degree of warming is a 5–7% increase in maximum potential wind speed. These results should be interpreted as a projection of changes in TC intensity under global warming since the HuMPI formulation does not include environmental factors (i.e., vertical wind shear, mid-level moisture content and environmental stratification) that influence TC long-term intensity variations.HighlightsThe maximum potential intensity (MPI) of tropical cyclones is a predictor of their climatological intensities.Tropical cyclones will be 17% more intense than today by the end of the 21st Century.The maximum potential wind speed will increase by 5–7%/ºC under global warming.

The Problem with the Anthropocene: Kainos, Not Anthropos

The Problem with the Anthropocene: <i>Kainos</i>, Not <i>Anthropos</i>

Effect of droughts and climate change on future soil weathering rates in Sweden

Abstract. In a future warmer climate, extremely dry, warm summers might become more common. Soil weathering is affected by temperature and precipitation, and climate change and droughts can therefore affect soil chemistry and plant nutrition. In this study, climate change and drought effects on soil weathering rates and release of Ca, Mg, K and Na were studied on seven forest sites across different climates in Sweden, using the dynamical model ForSAFE. Two climate scenarios were run, one medium severity climate change scenario from IPCC (A1B) and one scenario where a future drought period of 5 years was added, while everything else was equal to the first scenario. The model results show a large geographical variation of weathering rates for the sites, without any geographical gradient, despite the strong dependence of temperature on weathering and the strong gradient in temperature in Sweden. This is because soil texture and mineralogy have strong effects on weathering. The weathering rates have a pronounced seasonal dynamic. Weathering rates are low during winters and generally high, but variable, during summers, depending on soil moisture and temperature. According to the model runs, the future yearly average weathering rates will increase by 5 %–17 % per degree of warming. The relative increase is largest in the two southeastern sites, with low total weathering rates. At sites in southern Sweden, future weathering increase occurs throughout the year according to the modelling. In the north, the increase in weathering during winters is almost negligible, despite larger temperature increases than in other regions or seasons (5.9 ∘C increase in winter in Högbränna; the yearly average temperature increase for all sites is 3.7 ∘C), as the winter temperatures still will mostly be below zero. The drought scenario has the strongest effect in southern Sweden, where weathering during the later parts of the drought summers decreases to typical winter weathering rates. Soil texture and amount of gravel also influence how fast the weathering decreases during drought and how fast the soil rewets and reaches normal weathering rates after the drought. The coarsest of the modelled soils dries out and rewets quicker than the less coarse of the modelled soils. In the north, the soils do not dry out as much as in the south, despite the low precipitation, due to lower evapotranspiration, and in the northernmost site, weathering is not much affected. Yearly weathering during the drought years relative to the same years in the A1B scenario are between 78 % and 96 % for the sites. The study shows that it is crucial to take seasonal climate variations and soil texture into account when assessing the effects of a changed climate on weathering rates and plant nutrient availability.

Future Drying Subtropical East Asia in Winter: Mechanism and Observational Constraint

Abstract Coupled climate models project robust wintertime wetting trend over midlatitude East Asia under global warming scenarios, but the projected change in precipitation shows large intermodel uncertainty over subtropical East Asia from southern China to southwestern Japan. Based on an ensemble of climate models participating in CMIP6, this study shows that the weakened southern branch westerly jet (SWJ) on the southern side of Tibetan Plateau (TP) plays a key role in suppressing subtropical East Asian precipitation. The SWJ is deflected into southwesterly wind on the southeastern side of TP, bringing ascent and precipitation to subtropical East Asia primarily through isentropic gliding. As a result of the poleward and upward shift of the planetary-scale westerly jet under global warming, the SWJ becomes weaker and it acts to suppress subtropical East Asian precipitation by weakening the southwesterly wind and ascent. The SWJ–precipitation linkage also exists on interannual time scales, but the sensitivity of precipitation to interannual SWJ variability is systematically underestimated by the models compared with observation. The combined effects of the change in SWJ strength and the sensitivity of precipitation to SWJ explain about 40% of the intermodel spread of the projected precipitation changes. Observational constraint on the SWJ–precipitation relationship amplifies the projected drying trend and narrows the intermodel spread. It shows that the regional-averaged precipitation over subtropical East Asia decreases by 3.3% per degree of warming, and the amplitude of precipitation reduction over subtropical East Asia (southern China) is about 1.4 (3.4) times the raw projection.

Ground warming releases inorganic mercury and increases net methylmercury production in two boreal peatland types

Boreal peatlands are considered sinks for atmospheric mercury (Hg) and are important sources of methylmercury (MeHg) to downstream ecosystems. Climate change-driven increases in average annual temperature in coming decades will be amplified at higher latitudes and will modify many biogeochemical processes in high boreal and subarctic peatlands that are important landscape features in these regions. Changes in water quality are an important issue for Northern ecosystems and fish consumers, and the directionality of changes in mercury levels due to climate warming presents considerable uncertainty. Peatlands are key landscape hotspots for MeHg production, however, the impact of climate warming on Hg cycling in boreal peatlands is not well studied. We use a multi-year field-based warming experiment (2 years passive, 1 year active ground warming) across two boreal peatland types (moss and sedge dominated) to explore the effects of ground warming on inorganic Hg (IHg) release, net MeHg production, and biogeochemical controls on both of these processes including the availability of sulfate (SO42−) and dissolved organic matter (DOM) quality and concentration. There were higher porewater IHg and MeHg concentrations under active ground warming conditions in both peatlands, likely related to both increased microbial metabolism, and changes in biogeochemical conditions that favor Hg methylation. Both SO42− (electron acceptor) and bioaccessible DOM (electron donor) are nutrients for sulfate-reducing bacteria which are dominant Hg methylators in freshwater environments, and increases in SO42− and/or bioaccessible DOM concentrations under warming played an important role in the observed changes in net MeHg production. Warming increased SO42− concentrations in the sedge-dominated but not in the moss-dominated fen likely because of a larger pool of groundwater derived SO42− in the sedge-dominated site. Warming increased DOM concentration in both peatland sites through enhanced decomposition of peat and increased release of root exudates from vascular plants, and the balance of these processes varied by peatland type and degree of warming. Experimentally increased ground temperatures increased microbial metabolism, organic matter turnover, and the availability of IHg all of which resulted in increases in porewater MeHg, indicating that climate-driven ground warming will increase MeHg production in northern peatlands in the future.

A multi-disciplinary analysis of the exceptional flood event of July 2021 in central Europe – Part 2: Historical context and relation to climate change

Abstract. Heavy precipitation over western Germany and neighboring countries in July 2021 led to widespread floods, with the Ahr and Erft river catchments being particularly affected. Following the event characterization and process analysis in Part 1, here we put the 2021 event in the historical context regarding precipitation and discharge records and in terms of the temporal transformation of the valley morphology. Furthermore, we evaluated the role of ongoing and future climate change on the modification of rainfall totals and the associated flood hazard, as well as implications for flood management. The event was among the five heaviest precipitation events of the past 70 years in Germany. However, consideration of the large LAERTES-EU regional climate model (RCM) ensemble revealed a substantial underestimation of both return levels and periods based on extreme value statistics using only observations. An analysis of homogeneous hydrological data of the last 70 years demonstrated that the event discharges exceeded by far the statistical 100-year return levels. Nevertheless, the flood peaks at the Ahr river were comparable to the reconstructed major historical events of 1804 and 1910, which were not included in the flood risk assessment so far. A comparison between the 2021 and past events showed differences in terms of the observed hydro-morphodynamic processes which enhanced the flood risk due to changes in the landscape organization and occupation. The role of climate change and how the 2021 event would unfold under warmer or colder conditions (within a −2 to +3 K range) was considered based on both a pseudo global warming (PGW) model experiments and the analysis of an RCM ensemble. The PGW experiments showed that the spatial mean precipitation scales with the theoretical Clausius–Clapeyron (CC) relation, predicting a 7 % to 9 % increase per degree of warming. Using the PGW rainfall simulations as input to a hydrological model of the Ahr river basin revealed a strong and non-linear effect on flood peaks: for the +2 K scenario, the 18 % increase in areal rainfall led to a 39 % increase of the flood peak at gauge Altenahr. The analysis of the high-resolution convection-permitting KIT-KLIWA RCM ensemble confirmed the CC scaling for moderate spatial mean precipitation but showed a super CC scaling of up to 10 % for higher intensities. Moreover, the spatial extent of such precipitation events is also expected to increase.

Projected Changes in Future Extreme Precipitation over the Northeast United States in the NA-CORDEX Ensemble

Abstract The northeastern United States (NEUS) is a densely populated region with a number of major cities along the climatological storm track. Despite its economic and social importance, as well as the area’s vulnerability to flooding, there is significant uncertainty around future trends in extreme precipitation over the region. Here, we undertake a regional study of the projected changes in extreme precipitation over the NEUS through the end of the twenty-first century using an ensemble of high-resolution, dynamically downscaled simulations from the North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX) project. We find that extreme precipitation increases throughout the region, with the largest changes in coastal regions and smaller changes inland. These increases are seen throughout the year, although the smallest changes in extreme precipitation are seen in the summer, in contrast to earlier studies. The frequency of heavy precipitation also increases such that there are relatively fewer days with moderate precipitation and relatively more days with either no or strong precipitation. Averaged over the region, extreme precipitation increases by +3%–5% °C−1 of local warming, with the largest fractional increases in southern and inland regions and occurring during the winter and spring seasons. This is lower than the +7% °C−1 rate expected from thermodynamic considerations alone and suggests that dynamical changes damp the increases in extreme precipitation. These changes are qualitatively robust across ensemble members, although there is notable intermodel spread associated with models’ climate sensitivity and with changes in mean precipitation. Together, the NA-CORDEX simulations suggest that this densely populated region may require significant adaptation strategies to cope with the increase in extreme precipitation expected at the end of the next century. Significance Statement Observations show that the northeastern United States has already experienced increases in extreme precipitation, and prior modeling studies suggest that this trend is expected to continue through the end of the century. Using high-resolution climate model simulations, we find that coastal regions will experience large increases in extreme precipitation (+6.0–7.5 mm day−1), although there is significant intermodel spread in the trends’ spatial distribution and in their seasonality. Regionally averaged, extreme precipitation will increase at a rate of ∼2% decade−1. Our results also suggest that the frequency of extreme precipitation will increase, with the strongest storms doubling in frequency per degree of warming. These results, taken with earlier studies, provide guidance to aid in resiliency preparation and planning by regional stakeholders.

Evaluating Hydrologic Sensitivity in CMIP6 Models: Anthropogenic Forcing versus ENSO

Abstract Large uncertainty exists in hydrologic sensitivity (HS), the global-mean precipitation increase per degree of warming, across global climate model (GCM) ensembles. Meanwhile, the global circulation and hence global precipitation are sensitive to variations of surface temperature under internal variability. El Niño–Southern Oscillation (ENSO) is the most dominant mode of global temperature variability and hence of precipitation variability. Here we show in phase 6 of the Coupled Model Intercomparison Project (CMIP6) that the strength of HS under ENSO is predictive of HS in the climate change context (r = 0.56). This correlation increases to 0.62 when only central Pacific ENSO events are considered, suggesting that they are a better proxy for HS under future warming than east Pacific ENSO events. GCMs with greater HS are associated with greater weakening of the Walker circulation and expansion of the Hadley circulation under ENSO. Observations of HS under ENSO suggest that it is significantly underestimated by the GCMs, with the lower bound of observational uncertainty almost double even the highest-HS GCMs. The ENSO-related transformation of the tropical circulation holds clues into how the GCMs may be improved in order to more reliably simulate future hydrological cycle intensification.

Quantifying uncertainty about global and regional economic impacts of climate change

The economic impacts of climate change are highly uncertain. Two of the most important uncertainties are the sensitivity of the climate system and the so-called damage functions, which relate climate change to economic costs and benefits. Despite broad awareness of these uncertainties, it is unclear which of them is most important, especially at the regional level. Here we construct regional damage functions, based on two different global damage functions, and apply them to two climate models with vastly different climate sensitivities. We find that uncertainty in both climate sensitivity and aggregate economic damages per degree of warming are of similar importance for the global economic impact of climate change, with the decrease in global economic productivity ranging between 4% and 24% by the end of the century under a high-emission scenario. At the regional level, however, the effects of climate change can vary even more substantially, depending both on a region’s initial temperature and the amount of warming it experiences, with some regions gaining in productivity and others losing. The ranges of uncertainty are therefore potentially much larger at a regional level. For example, at the end of the century, under a high-emission scenario, we find that India’s productivity decreases between 13% and 57% and Russia’s increases between 24% and 74%, while Germany’s change in productivity ranges from an increase of 8% to a decrease of 4%. Our findings emphasise the importance of including these uncertainties in estimates of future economic impacts, as they are vital for the resulting impacts and thus policy implications.