Climate Sensitivity Research Articles

Efficacy of Automating the Analysis of TripAdvisor Data in Tourism and Climate Studies

ABSTRACT The viability and competitiveness of tourism locations depends, in part, on climate. Netnographic research utilising TripAdvisor reviews can objectively evaluate tourists’ climatic sensitivity and the meteorological factors most important to them. Manually reading and coding hundreds of reviews is time-consuming. Web-scraping can automate this process and analyse hundreds of thousands of reviews nationwide to evaluate climatic influence more comprehensively. This paper compares the outputs of manually collected and web-scraped TripAdvisor reviews, evaluating the efficacy of a web-scraping approach. The total number of climatic mentions captured varied by a statistically insignificant 3.56%, demonstrating a reasonable efficacy of web-scraping. Out of 26,687 TripAdvisor reviews, 1,163 mentioned climate. This 4.4% mean sensitivity to climatic variables is statistically significantly different to the 7.9% yielded from manual data collection. The two methodologies had minor statistically insignificant differences in climatic references at 19 destinations, ranging from 0.42% to 8.26%. A webscraping approach is thus possible but should be used with caution.

The carbon crater: Comparing anthropogenic greenhouse gas emissions to historical planetary events

Equilibrium climate sensitivity modeling relies heavily on paleoclimate records that were affected by meteorite impacts and volcanic explosions. This paper conducts a thought experiment by re-assembling known data and theories to shed new light on anthropogenic carbon waste. Anthropogenic activity, meteorite impacts and volcanic explosions all extract material from the Earth’s crust and deposit it in the atmosphere. This thought experiment tests if the mass of anthropogenic greenhouse gas emissions from 1851 to 2021 is comparable to the mass of atmospheric emissions from historical planetary events. Approximately 3.60 trillion tons of anthropogenic carbon dioxide equivalents are converted into volume and then transformed into the shape of a meteorite impact structure named the “Carbon Crater.” The 35 km crater (bounded by 34%–68% confidence intervals of 25–45 km) would rank 23rd on the list of known impact structures. The 2.6 km projectile required to create the Crater would be a 10 on the 1–10 Torino hazard scale described as “. . .capable of causing global climatic catastrophe. . .” The estimated re-occurrence interval for a projectile of this size is 5.3 million years. An interval of this time in Earth’s recent history predates homo sapiens. The Crater’s volume is exponentially larger than the 1883 eruption of Krakatoa and ranks as an 8 (“mega-colossal”) on the 0–8 Volcanic Explosivity Index. The thought experiment indicates that the Carbon Crater’s scale is comparable with large historical biospheric events. These results likely confer few direct implications for the study of the paleoclimate in climate modeling but might change conceptual understandings of atmospheric human waste. Additional empirical research is required to understand the potential impact of the Carbon Crater on conceptual change.

Arctic amplification causes earlier onset of seasonal tree growth in northeastern Siberia

Abstract Although recent warming affects the high-northern latitudes at an unprecedented rate, little is known about its impact on boreal forests because in situ observations from remote ecosystems in Siberia are sparse. Here, we analyze the radial growth and climate sensitivity of 54 Cajander larches (Larix cajanderi Mayr.) from three sites across the northern treeline ecotone within the Omoloy river basin in northeastern Siberia. Three independent tree-ring width chronologies span 279–499 years and exhibit distinct summer temperature signals. These records further reveal evidence for sufficiently earlier onsets of growing seasons since the middle of the 20th century. This phenological shift coincides with rapidly increasing May temperatures and associated earlier snowmelt. Our findings reinforce the importance of high-precision ground measurements from remote regions in Siberia to better understand how warming-induced changes in the functioning and productivity of the boreal forest influence carbon, nutrient, and water cycle dynamics.

Surface Warming Constraint Projects Less Permafrost Thawing in High Mountain Asia

AbstractReliable projections of permafrost change are crucial for estimating permafrost carbon loss. However, potential model biases in surface air temperature may yield unrealistic projections of future permafrost area. Here, by leveraging the emergent relationship between equilibrium climate sensitivity and projected changes in mean annual air temperature over High Mountain Asia (HMA), we mitigate the overestimated local warming rates and excessive thawing of permafrost associated with the “hot model” problem in models participating in the Coupled Model Intercomparison Project phase 6. After constraint, permafrost area over HMA will reduce by 37%, 64% and 99% in 2081–2100 relative to present‐day under the SSP1‐2.6, SSP2‐4.5 and SSP5‐8.5 scenarios, respectively. In contrast, the unconstrained projections tend to overestimate the loss of permafrost area by nearly 10% under the low and mid‐emission scenarios due to the overestimation of local warming rates. These findings are crucial for policymaking and provide valuable insights into global permafrost projection.

Combining tree-ring growth and carbon isotope data enhances the understanding of climate sensitivity and physiological responses for Chinese fir in a common garden

Chinese fir (Cunninghamia lanceolata (Lamb.) Hook) is one of China's most important tree species, and possible adverse factors affecting its growth and physiology is of particular concern for climate change adaptation. In this context, growth performance (BAI: basal area increment and MAXD: maximum density), climate sensitivity, and the relative contributions of climatic and physiological determinants to growth were evaluated across the 30 Chinese fir provenances using a combination of dendroclimatology and carbon isotope analysis (δ13C). Over the past 27 years, intrinsic water-use efficiency (iWUE) increased significantly by 12.71–33.56 %, while radial growth decreased (−63.38 % to −88.93 %). Strong growth decreases reflected increasing water stress due to climate warming, which was not offset by greater iWUE. A similar trend was observed in the theoretical gas exchange scenario as a response to increasing Ca as stomata opened and Ci increased proportionally to Ca. This study identified temperature and relative humidity as determinants of growth and physiology. However, meteorological factors (temperature, relative humidity, and sunshine hours) contributed much less to growth than physiological factors (iWUE). Variation in performance and climate sensitivity among populations significantly correlated with the mean annual temperature of the seed source origin. In general, seed sources from warmer and more humid climates in the center region grew faster and had higher iWUE. Provenances from drier climates had slower growth, higher wood density, and higher carbon isotope discrimination (Δ13C) compared to those from wetter climate conditions. Compared to provenances from cooler regions, the seed sources from warmer climates were less sensitive to temperature but more sensitive to sunshine hours for BAI and MAXD. These results contribute to a better understanding of the climate sensitivity and physiological responses of the Chinese fir provenances to long-term changing climate.

Coping with climate change: A livelihood vulnerability and adaptation analysis in Gaibandha, Rangpur, Bangladesh

AbstractThis study aimed to assess the impact of climate change using the Livelihood Vulnerability Index (LVI) and the adaptation strategies of communities, as measured by the Adaptation Strategy Index (ASI), among 120 households across six villages in Fulchari and Shaghata Upazilas of Gaibandha district in northern Bangladesh. The findings highlight changing climatic patterns and show that while respondents are generally aware of the impacts of climate change, there are notable knowledge gaps. Galna Adarshapara was identified as the most vulnerable village according to the LVI, indicating its high susceptibility in areas such as socio‐demographic profile, food security, health, natural hazards, and climate sensitivity. Factors contributing to this vulnerability include geographical isolation, limited education, underdeveloped infrastructure, inadequate health facilities, and a lack of alternative income sources during extreme events. However, coping mechanisms such as irrigation, crop diversification, and the use of double‐platform tube wells are commonly employed to address these climatic impacts. To enhance resilience, it is crucial to implement policy initiatives and institutional arrangements that support local communities in improving their living conditions and adapting to climate change challenges.

How Does Organized Convection Impact Explicitly Resolved Cloud Feedbacks in the Radiative‐Convective Equilibrium Model Intercomparison Project?

AbstractIn simulations of radiative‐convective equilibrium (RCE), and with sufficiently large domains, organized convection enhances top of atmosphere outgoing longwave radiation due to the reduced cloud coverage and drying of the mean climate state. As a consequence, estimates of climate sensitivity and cloud feedbacks may be affected. Here, we use a multi‐model ensemble configured in RCE to study the dependence of explicitly calculated cloud feedbacks on the existence of organized convection, the degree to which convection within a domain organizes, and the change in organized convection with warming sea surface temperature. We find that, when RCE simulations with organized convection are compared to RCE simulations without organized convection, the propensity for convection to organize in RCE causes cloud feedbacks to have larger magnitudes due to the inclusion of low clouds, accompanied by a much larger inter‐model spread. While we find no dependence of the cloud feedback on changes in organization with warming, models that are, on average, more organized have less positive, or even negative, cloud feedbacks. This is primarily due to changes in cloud optical depth in the shortwave, specifically high clouds thickening with warming in strongly organized domains. The shortwave cloud optical depth feedback also plays an important role in causing the tropical anvil cloud area feedback to be positive which is directly opposed to the expected negative or near zero cloud feedback found in prior work.

Bayesian Errors‐in‐Variables Estimation of Specific Climate Sensitivity

AbstractEstimation of climate sensitivity is fundamental to assessing how global climate will warm as atmospheric concentration increases. Geological archives of environmental change provide insights into Earth's past climate, but the incomplete nature of paleoclimate reconstructions and their inherent uncertainties make estimation of climate sensitivity challenging. Thus, quantifying climate sensitivity and assessing how it changed through geological time requires statistical frameworks that can handle data uncertainties in a principled fashion. Here we demonstrate some of the hurdles to estimating climate sensitivity, with a focus on current statistical techniques that may underestimate both climate sensitivity and its associated uncertainty. To solve these issues, we present a Bayesian error‐in‐variables regression model, which can yield estimates of climate sensitivity without bias. The regression model is flexible and can account for data point uncertainties with a known parametric form. The utility of this approach is demonstrated by estimating specific climate sensitivity with uncertainty for the Eocene.

Increased projected changes in quasi-resonant amplification and persistent summer weather extremes in the latest multimodel climate projections

High-amplitude quasi-stationary atmospheric Rossby waves with zonal wave numbers 6–8 associated with the phenomenon of quasi-resonant amplification (QRA) have been linked to persistent summer extreme weather events in the Northern Hemisphere. QRA is not well-resolved in current generation climate models, therefore, necessitating an alternative approach to assessing their behavior. Using a previously-developed fingerprint-based semi-empirical approach, we project future occurrence of QRA events based on a QRA index derived from the zonally averaged surface temperature field, comparing results from CMIP 5 and 6 (Coupled Model Intercomparison Project). There is a general agreement among models, with most simulations projecting substantial increase in QRA index. Larger increases are found among CMIP6-SSP5-8.5 (42 models, 46 realizations), with 85% of models displaying a positive trend, as compared with 60% of CMIP5-RCP8.5 (33 models, 75 realizations), with a reduced spread among CMIP6-SSP5-8.5 models. CMIP6-SSP3-7.0 (23 models, 26 realizations) simulations display qualitatively similar behavior to CMIP6-SSP5-8.5, indicating a substantial increase in QRA events under business-as-usual emissions scenarios, and the results hold regardless of the increase in climate sensitivity in CMIP6. Projected aerosol reductions in CMIP6-SSP3-7.0-lowNTCF (5 models, 16 realizations) lead to halting effect in QRA index and Arctic Amplification during the 1st half of the twenty-first century. Our analysis suggests that anthropogenic warming will likely lead to an even more substantial increase in QRA events (and associated summer weather extremes) than indicated by past analyses.

Shallow Convective Heating in Weak Temperature Gradient Balance Explains Mesoscale Vertical Motions in the Trades

AbstractEarth's climate sensitivity depends on how shallow clouds in the trades respond to changes in the large‐scale tropical circulation with warming. In canonical theory for this cloud‐circulation coupling, it is assumed that the clouds are controlled by the field of vertical motion on horizontal scales larger than the convection's depth ( 1 km). This assumption has been challenged both by recent in situ observations, and idealized large‐eddy simulations (LESs). Here, we therefore bring together the recent observations, new analysis from satellite data, and a 40‐day, large‐domain ( km2) LES of the North Atlantic from the 2020 EUREC4A field campaign, to study the interaction between shallow convection and vertical motions on scales between 10 and 1,000 km (mesoscales), in settings that are as realistic as possible. Across all data sets, the shallow mesoscale vertical motions are consistently represented, ubiquitous, frequently organized into circulations, and formed without imprinting themselves on the mesoscale buoyancy field. Therefore, we use the weak‐temperature gradient approximation to show that between at least 12.5–400 km scales, the vertical motion balances heating fluctuations in groups of precipitating shallow cumuli. That is, across the mesoscales, shallow convection controls the vertical motion in the trades, and does not simply adjust to it. In turn, the mesoscale convective heating patterns appear to consistently grow through moisture‐convection feedback. Therefore, to represent and understand the cloud‐circulation coupling of trade cumuli, the full range of scales between the synoptics and the hectometer must be included in our conceptual and numerical models.

Surface warming in Svalbard may have led to increases in highly active ice-nucleating particles

The roles of Arctic aerosols as ice-nucleating particles remain poorly understood, even though their effects on cloud microphysics are crucial for assessing the climate sensitivity of Arctic mixed-phase clouds and predicting their response to Arctic warming. Here we present a full-year record of ice-nucleating particle concentrations over Svalbard, where surface warming has been anomalously faster than the Arctic average. While the variation of ice-nucleating particles active at around −30 °C was relatively small, those active at higher temperatures (i.e., highly active ice-nucleating particles) tended to increase exponentially with rising surface air temperatures when the surface air temperatures rose above 0 °C and snow/ice-free barren and vegetated areas appeared in Svalbard. The aerosol population relevant to their increase was largely characterized by dust and biological organic materials that likely originated from local/regional terrestrial sources. Our results suggest that highly active ice-nucleating particles could be actively released from Arctic natural sources in response to surface warming.

Environmental Drivers of Palsa and Peat Plateau Occurrences: A Regional Comparison Across the Northern Hemisphere

ABSTRACTPalsas and peat plateaus occur in various environmental conditions, but their driving environmental factors have not been examined across the Northern Hemisphere with harmonized datasets. Such comparisons can deepen our understanding of these landforms and their response to climate change. We conducted a comparative study between four regions: Hudson Bay, Iceland, Northern Fennoscandia, and Western Siberia by integrating landform observations and geospatial data into a MaxEnt model. Climate and hydrological conditions were identified as primary, yet regionally divergent, factors affecting palsa and peat plateau occurrence. Suitable conditions for these landforms entail specific temperature ranges (500–1500 thawing degree days, 500–4000 freezing degree days), around 300 mm of rainfall, and high soil moisture accumulation potential. Iceland's conditions, in particular, differ due to higher precipitation, a narrower temperature range, and the significance of soil organic carbon content. The annual thermal balance is a critical factor in understanding the occurrence of permafrost peatlands and should be considered when comparing different regions. We conclude that palsas and peat plateaus share similar topographic conditions but occupy varying soil conditions and climatic niches across the Northern Hemisphere. These findings have implications for understanding the climatic sensitivity of permafrost peatlands and identifying potential greenhouse gas emitters.

An Evaluation of Cloud‐Precipitation Structures in Mixed‐Phase Stratocumuli Over the Southern Ocean in Kilometer‐Scale ICON Simulations During CAPRICORN

AbstractA persistent shortwave radiative bias of Southern Ocean (SO) clouds in climate models is strongly associated with incorrect cloud phase representation, which impacts precipitation. Measurements characterizing precipitation in low‐level mixed‐phase clouds, which frequently form over the SO, are rare, and our understanding of precipitation efficacy within these clouds remains limited. The simulated surface precipitation bias has an indirect effect on determining global climate sensitivity and a direct impact on the hydrological cycle. This study investigates the representation of low clouds, cloud variability, and precipitation statistics over the SO in real‐case Icosahedral Nonhydrostatic (ICON) simulations at the kilometer scale. The simulations are contrasted with 48 hr of continuous shipborne observations of open and closed‐cell stratocumuli, south of Tasmania. Our simulations show the significance of heavily rimed particle formation, their in‐cloud growth, and subcloud melting to capture the observed cloud‐precipitation vertical structure. In addition, supercooled drizzle formation impacts the vertical structure and precipitation statistics. ICON captures the observed intermittency of precipitation even at a standard vertical resolution of 200 m in the boundary layer but only captures the observed sparse distribution of intense precipitation (>1 mm hr−1) when the maximum vertical resolution is reduced to 100 m. However, the simulations of the 2‐day accumulated precipitation and the radiative effect are largely insensitive to the vertical resolution. The cloud reflectivity of the broken cloud deck is underestimated due to negative biases in cloud optical depth.

Dependence of tropical cyclone seeds and climate sensitivity on tropical cloud response.

Projections of future tropical cyclone frequency are uncertain, ranging from a slight increase to a considerable decrease according to climate models. Estimation of how much the Earth's surface temperature warms in response to greenhouse gas increase, quantified by effective climate sensitivity, is also uncertain. These two uncertainties have historically been studied independently as they concern different scales: One quantifies the extreme weather and the other the mean climate. Here, we show that these two uncertainties are not independent and are both influenced by the response of tropical clouds to warming. Across climate models, we show an anticorrelation between shortwave cloud radiative feedback and changes in the frequency of seed vortices, a prevalent type of tropical cyclone precursors. We further show an anticorrelation between effective climate sensitivity and tropical cyclone frequency changes, suggesting that global tropical cyclone frequency tends to decrease more substantially in models with larger temperature increase.

Geospatial assessment of climate sensitivity in Ibarapa North, Oyo State, Nigeria

Geospatial assessment of climate sensitivity in Ibarapa North, Oyo State, Nigeria

Effect of bedrock, tree size and time on growth and climate sensitivity of Norway spruce in the High Tatras

AbstractTree growth is a multifaceted process influenced by various factors at different spatial and temporal scales, including intrinsic tree traits and environmental conditions. Climate factors have a significant impact on tree growth dynamics, while geological controls can also play a crucial role. However, our understanding of the interplay between these factors concerning tree growth is currently limited. This study focuses on Norway spruce (Picea abies [L.] Karst.), one of the economically most important coniferous tree species in Europe, to investigate the interplay of growth, climate, and environment at the forest and corresponding treeline sites in the High Tatra Mountains of Slovakia. Specifically, we developed chronologies of tree-ring width (TRW) and late-wood density (MXD) for different tree size classes across two limestone and granitic sites. Growth rates of Norway spruce trees have been increasing in forests since the 1930s and from the 1950s at treelines. Growth rates were consistently higher on limestone bedrock compared to granitic bedrock conditions. Variability of radial growth is primarily driven by climate at both geological settings with trees on granitic bedrock displaying more pronounced responses to climatic variables. We observed weakening (non-stationarity) in climate signals over time and across all size classes in both geological settings. The magnitude of these effects is small, but varies across size classes, with larger trees generally displaying stronger climate sensitivities compared to smaller ones. Therefore, our findings accentuate the potential implications of geological settings, climate, and environmental factors on the absolute growth and growth dynamics of Norway spruce, highlighting the need for further research to fully understand and manage forest ecosystems in mountainous regions.

Season-dependent climate sensitivity of the surface runoff of major rivers in Changbai Mountain

Due to the sensitivity of runoff to changes in seasonal snowpack, the changes in surface runoff within high-latitude and high-elevation areas are more complex than in other areas. However, this sensitivity is often overlooked when correlating changes in runoff with meteorological variables. Here, we analyze changes in surface runoff during snowmelt and snowless periods and their sensitivity to climate change from 1960 to 2019 in the upstream watersheds of the Songhua, Yalu, and Tumen Rivers in Changbai Mountain. Most runoff indices, except for low flow in the Yalu River, exhibited decreasing trends during snowmelt and snowless periods. Precipitation was the primary variable responsible for surface runoff during snowless and snowmelt periods. Notably, rainfall replenished all runoff indices during snowless periods, particularly under high flow conditions. The average and high flows were also primarily supplemented by rainfall during snowmelt periods. However, low flow was positively correlated with snowmelt in the Songhua and Tumen Rivers and with temperature in the Songhua, Yalu and Tumen Rivers during snowmelt periods. Additionally, extreme runoff events were closely associated with extreme precipitation. These findings demonstrate the seasonal and index-dependent climate sensitivity of surface runoff within Changbai Mountain, offering insights into the surface runoff response mechanism to climate change in high-altitude mountainous areas. Under future climate change conditions, frequent and intense extreme precipitation events may increase the risk of flooding, owing to the high sensitivity of high flows to precipitation, posing a serious threat to regional ecological security.

Climatic and disturbances influence on tree-rings of Larix gmelinii in the southeast coastal area

The vast region of North East Asia is covered by primary mixed conifer-broadleaved forests which include a range of different tree species. A key factor in the dynamics of these ecosystems is wind disturbance. According to reports, this factor will be increasingly important as a result of the poleward migration of tropical cyclones, a characteristic of which is strong wind. At the same time, global climate change may reduce the recovery potency of some species and lead to new combinations of species. Gmelin Larch is one of the key early succession species in the north of the region. In the southeastern part of its range (Russian Far East), this species has not been widely studied by dendroclimatologists and there are no dendroecological studies available. This study shows how the seasonal growth of Larix gmelinii responds to changes in climate, specifically to variations in precipitation and temperature. The study has established that these trees are more affected by rising temperatures than by consistent precipitation levels, provided there is no shortage of water. Interestingly, after the 1970s there was a change in the climate sensitivity of Larix gmelinii in June (the month with the strongest correlation). It went from a negative correlation with temperature to a positive correlation with precipitation. By using tree ring data, we were able to reconstruct the past history of forest disturbance. The peaks in this chronology coincide with those in earlier published dendroecological reconstructions for other species. They indicate that the radial growth of larch is sensitive to canopy changes. We recorded two decade peaks in disturbance history in the 1960s and 2000s, during the period of meteorological observations. We attributed the first peak to the most powerful tropical cyclone Emma (1956). We assume also that the second peak reflects the recent intensification of tropical cyclones in the region. In our opinion, the change in microclimate as a result of disturbance has altered the relationship to climate in such a way that disturbance may cause tree growth to be dependent on precipitation. At the same time, such low correlations do not support a conclusion about the strong negative influence of the current climate on the trees.

Long- and short-term coupling of sea surface temperature and atmospheric CO2 during the late Paleocene and early Eocene

The late Paleocene and early Eocene (LPEE) are characterized by long-term (million years, Myr) global warming and by transient, abrupt (kiloyears, kyr) warming events, termed hyperthermals. Although both have been attributed to greenhouse (CO2) forcing, the longer-term trend in climate was likely influenced by additional forcing factors (i.e., tectonics) and the extent to which warming was driven by atmospheric CO2 remains unclear. Here, we use a suite of new and existing observations from planktic foraminifera collected at Pacific Ocean Drilling Program Sites 1209 and 1210 and inversion of a multiproxy Bayesian hierarchical model to quantify sea surface temperature (SST) and atmospheric CO2 over a 6-Myr interval. Our reconstructions span the initiation of long-term LPEE warming (~58 Ma), and the two largest Paleogene hyperthermals, the Paleocene-Eocene Thermal Maximum (PETM, ~56 Ma) and Eocene Thermal Maximum 2 (ETM-2, ~54 Ma). Our results show strong coupling between CO2 and temperature over the long- (LPEE) and short-term (PETM and ETM-2) but differing Pacific climate sensitivities over the two timescales. Combined CO2 and carbon isotope trends imply the carbon source driving CO2 increase was likely methanogenic, organic, or mixed for the PETM and organic for ETM-2, whereas a source with higher δ13C values (e.g., volcanic degassing) is associated with the long-term LPEE. Reconstructed emissions for the PETM (5,800 Gt C) and ETM-2 (3,800 Gt C) are comparable in mass to future emission scenarios, reinforcing the value of these events as analogs of anthropogenic change.

A Generalizable Prioritization Protocol for Climate-Sensitive Zoonotic Diseases.

Emerging and re-emerging zoonotic diseases pose a significant threat to global health and economic security. This threat is further aggravated by amplifying drivers of change, including climate hazards and landscape alterations induced by climate change. Given the complex relationships between climate change and zoonotic disease health outcomes, a structured decision-making process is required to effectively identify pathogens of greatest concern to prioritize prevention and surveillance efforts. Here, we describe a workshop-based expert elicitation process in six steps to prioritize climate-sensitive zoonoses based on a structured approach to defining criteria for climate sensitivity. Fuzzy analytical hierarchy process methodology is used to analyze data provided by experts across human, animal, and environmental health sectors accounting for uncertainties at different stages of the prioritization process. We also present a new interactive expert elicitation interface that facilitates data collection and real-time visualization of prioritization results. The novel approach presented in this paper offers a generalized platform for prioritizing climate-sensitive zoonoses at a national or regional level. This allows for a structured decision-making support process when allocating limited financial and personnel resources to enhance preparedness and response to zoonotic diseases amplified by climate change.