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In this paper, we examined the elevation-dependent warming (EDW) patterns of MODIS LST across different seasons in the Qinling-Daba Mountains, further investigate the connections between the EDW patterns of Land surface temperature (LST) and land surface albedo (ALB) as well as aerosol optical depth (AOD). The key findings include: (1) Our study reveals a robust correlation between LST and air temperature in the Qinling-Daba Mountains, suggesting the feasibility of using MODIS LST to predict the temperature trends (2) During the period from 2001 to 2010, MODIS LST shows a significant EDW trend, primarily in the spring season. In contrast, a negative EDW is observed in the period during 2011–2021, which is contrary to the earlier decade, particularly during the autumn and winter seasons. (3) EDW of MODIS LST is affected by the combination of ALB and AOD. The former has a negative influence on the change of LST, particularly above 2500 m in elevation. However, the latter is negatively correlated with the trend of MODIS LST, primarily at lower and middle altitudes (0–2500 m). This study gives a comprehensive explanation for the EDW of the temporal variations of LST in the Qinling-Daba Mountains to improve our understanding of the complex interactions and potential future climate scenarios in the region. [ABSTRACT FROM AUTHOR]

Elevation‐dependent warming (EDW) has been a topic of intense debate due to limited observed data in global highland areas. This study aims to fill this gap by utilizing CRU and ERA5 datasets from 1981 to 2021 to explore the trends of climate change and its elevation dependency. The anomalies of temperature indicators (Tmean, Tmax, and Tmin) in both ERA5 and CRU showed significant warming trends over global highlands. Moreover, the response of temperature indicators to elevation across global highlands is not spatially uniform. The linear regression model based on the elevation showed significant warming signals for the temperature indicators at various elevations over the global highlands. On a regional scale, Tmean and Tmax predominantly showed linear EDW over EU highlands, while Tmean in Asian highlands exhibited EDW signals at 4–5 km. Tmin showed EDW at 2.5–5.5 km with ERA5 and 3–5 km with CRU. In the Andes, EDW was prominent at 2.5–4 km. Overall, EDW signals are evident in all studied regions but vary across them. While assessing the driving factors, the results of this study indicate that total column water vapour (TCWV), snow depth (SD), snow albedo, and normalized difference vegetation index (NDVI) correlated positively with the temperature indicators. These findings emphasize the significance of elevation‐specific interactions between environmental factors and temperature in forecasting temperature changes in mountainous areas. Additionally, temperature exhibited coherence with teleconnection indices from the Atlantic and Pacific Oceans. Asian and European (EU) highlands exhibited interzonal coherence with the Pacific and Atlantic Oceans, while North American (NA) highlands showed coherence, followed by South American (SA) highlands. These findings provide a comprehensive understanding of EDW and its implications for highland regions globally, including the potential for more severe depletion of snow/ice resources in a warmer future. [ABSTRACT FROM AUTHOR]

A scenario-based approach was used to test air and ground response to warming with and without changes to inverted surface lapse rates in four Yukon valleys. Generally, climate warming coupled with weakening of temperature inversions resulted in the greatest increase in air temperature at low elevations. However, ground temperatures at high elevations showed the greatest response to warming and variability between scenarios due to increased connectivity between air and ground. Low elevations showed less of a response to warming and permafrost was largely preserved in these locations. Local models also predicted higher permafrost occurrence compared to a regional permafrost probability model, due to the inclusion of differential surface and thermal offsets. Results show that the spatial warming patterns in these mountains may not follow those predicted in other mountain environments following elevation-dependent warming (EDW). As a result, the concept of EDW should be expanded to become more inclusive of a wider range of possible spatial warming distributions. The purpose of this paper is not to provide exact estimations of warming, but rather to provide hypothetical spatial warming patterns, based on logical predictions of changes to temperature inversion strength, which may not directly follow the distribution projected through EDW.

Abstract In this paper, we examined the elevation-dependent warming (EDW) patterns of MODIS LST across different seasons in the Qinling-Daba Mountains, further investigate the connections between the EDW patterns of Land surface temperature (LST) and land surface albedo (ALB) as well as aerosol optical depth (AOD). The key findings include: (1) Our study reveals a robust correlation between LST and air temperature in the Qinling-Daba Mountains, suggesting the feasibility of using MODIS LST to predict the temperature trends (2) During the period from 2001 to 2010, MODIS LST shows a significant EDW trend, primarily in the spring season. In contrast, a negative EDW is observed in the period during 2011–2021, which is contrary to the earlier decade, particularly during the autumn and winter seasons. (3) EDW of MODIS LST is affected by the combination of ALB and AOD. The former has a negative influence on the change of LST, particularly above 2500 m in elevation. However, the latter is negatively correlated with the trend of MODIS LST, primarily at lower and middle altitudes (0–2500 m). This study gives a comprehensive explanation for the EDW of the temporal variations of LST in the Qinling-Daba Mountains to improve our understanding of the complex interactions and potential future climate scenarios in the region.

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Understanding temperature variability especially elevation dependent warming (EDW) in high-elevation mountain regions is critical for assessing the impacts of climate change on water resources including glacier melt, degradation of soils, and active layer thickness. EDW means that temperature is warming faster with the increase of altitude. In this study, we used observed temperature data during 1979–2017 from 23 meteorological stations in the Qilian Mountains (QLM) to analyze temperature trend with Mann-Kendall (MK) test and Sen's slope approach. Results showed that the warming trends for the annual temperature followed the order of T_min > T_mean > T_max and with a shift both occurred in 1997. Spring and summer temperature have a higher increasing trend than that in autumn and winter. T_mean shifts occurred in 1996 for spring and summer, in 1997 for autumn and winter. T_max shifts occurred in 1997 for spring and 1996 for summer. T_min shifts occurred in 1997 for spring, summer and winter as well as in 1999 for autumn. Annual mean diurnal temperature range (DTR) shows a significant decreasing trend (−0.18°C/10a) from 1979 to 2017. Summer mean DTR shows a significant decreasing trend (−0.26°C/10a) from 1979 to 2017 with a shift occurred in 2010. After removing longitude and latitude factors, we can learn that the warming enhancement rate of average annual temperature is 0.0673°C/km/10a, indicating that the temperature warming trend is accelerating with the continuous increase of altitude. The increase rate of elevation temperature is 0.0371°C/km/10a in spring, 0.0457°C/km/10a in summer, 0.0707°C/km/10a in autumn, and 0.0606°C/km/10a in winter, which indicates that there is a clear EDW in the QLM. The main causes of warming in the Qilian Mountains are human activities, cloudiness, ice-snow feedback and El Nino phenomenon. [ABSTRACT FROM AUTHOR]

The identification of projected changes in temperature caused by global warming at a fine-scale spatial resolution is of great importance for the high-altitude glacier and snow covered Upper Indus Basin. This study used a multimodel ensemble mean bias-correction technique which uses the ensemble empirical mode decomposition method to correct the bias of ensemble mean of seven CMIP6 GCMs outputs with reference to the European Centre for Medium-Range Weather Forecasts Reanalysis 5 (ERA5). The bias-corrected data have a nonlinear trend of seven GCMs but interannual variance and mean climate of ERA5 dataset. The dataset spans from 1985 to 2100 for historical and future climate scenarios (SSP126, SSP245, SSP370, and SSP585) at daily time intervals with a 1 km grid resolution. The result of different scenarios indicates that the increase in maximum (Tmax) and minimum temperature (Tmin) ranging from 1.5 to 5.4 °C and 1.8 to 6.8 °C from 2015 to 2100, respectively. Similarly, elevation-dependent warming is identified in Tmin from 1.7 to 7.0 °C at elevations

Warming in mountainous regions has experienced obvious elevation dependence (the warming rate of air temperature is amplified with elevation), which accelerates the melting of ice and snow, affecting glacier size and mass, and water resources in mountainous regions. Here, we used ERA5-Land monthly averaged datasets from 1979 to 2019 to analyze the elevation-dependent warming (EDW) variability, driving factor, and its implications to water resources in the Qilian Mountains (QLM). Results showed that: (1) Annual mean temperature shows a significant increasing trend in the QLM from 1979 to 2019 (0.31 °C/10a; p < 0.01), and the warming rate of annual mean temperature increased with elevation in the QLM in general. For seasonal scales, the most obvious EDW was found in summer. In the past 41 years, snow cover and snow depth showed a slight decreasing trend. There was a significant negative correlation between temperature and snow cover, which can explain that enhanced regional warming has caused decreases in snow cover and snow depth, largely controlling the pattern of EDW on the QLM. EDW has significant implications for water resources over QLM, especially above 5,000 m. Our study can provide a reference in understanding the importance of EDW to water resources in mountainous areas. HIGHLIGHTS ERA5-Land reanalysis 2 m temperature data are reliable in Qilian Mountains.; There is an obvious elevation-dependent warming (EDW) of annual mean temperature, especially above 5,000 m.; Snow cover in Qilian Mountain showed a decreasing trend.; Snow cover is an important mechanism driving EDW.; EDW has an important implication for water resources (especially above 5,000 m).;

The present study estimates spatial and temporal (seasonal/annual) trends in daytime land surface temperature (LST) and its drivers (elevation, cloud fraction (CF), atmospheric water vapor (AWV), normalized difference vegetation index (NDVI), and snow cover area (SCA)) over the High Mountain Asia (HMA) during 2001–2019 using MODIS remote sensing data. The findings of the study showed mixed trends in LST in the region with intra-regional variations. Overall, the warming in the region is attributed to increasing AWV and NDVI and declining CF and SCA. The study also found evidence of elevation-dependent warming (EDW) (4500–5500 m AMSL) in some regions. However, the same conclusion cannot be drawn in all the sub-regions of HMA, suggesting the need to explore the effects of additional natural and anthropogenic factors on LST with fine resolution data to improve the understanding of its spatio-temporal dynamics.

Copyright of Canadian Water Resources Journal / Revue Canadienne des Ressources Hydriques is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Recent studies offer more evidence that the rate of warming is amplified with elevation, indicating thereby that high-elevation ecosystems tend to be exposed to more accelerated changes in temperature than ecosystems at lower elevations. The phenomenon of elevation-dependent warming (EDW), as one of the regional climate-change impacts, has been observed across the Tibetan Plateau. Studies have often found large-scale greening trends, but the drivers of vegetation dynamics are still not fully understood in this region, such that the local implications of vegetation change have been infrequently discussed. This study was designed to quantify and characterize the seasonal changes in vegetation across the Three Rivers Headwaters Region (TRHR), where the land cradles the headwaters of the Yangtze, the Yellow, and the Lancang (Mekong). By mapping the normalized difference vegetation index (NDVI) over the growing season from 1982 to 2015, we were able to evaluate seasonal changes in vegetation cover over time. The results show a slightly increased tendency in green vegetation cover, which could possibly be attributed to sustained warming in this region over the past three decades, whereas a decline in the green-up rate with elevation was found, indicating an inconsistent trend of vegetation greening with EDW. The cause of the green-up rate decline at high elevations could be linked to the reduced soil water availability induced by the fast increase in warming rates associated with EDW. The findings of this study have important implications for devising adaptation strategies for alpine ecosystems in a changing climate. [ABSTRACT FROM AUTHOR]

Climate change will impact western USA water supplies by shifting precipitation from snow to rain and driving snowmelt earlier in the season. However, changes at the regional-to-mountain scale is still a major topic of interest. This study addresses the impacts of climate change on mountain snowpack by assessing historical and projected variable-resolution (VR) climate simulations in the community earth system model (VR-CESM) forced by prescribed sea-surface temperatures along with widely used regional downscaling techniques, the coupled model intercomparison projects phase 5 bias corrected and statistically downscaled (CMIP5-BCSD) and the North American regional climate change assessment program (NARCCAP). The multi-model RCP8.5 scenario analysis of winter season SWE for western USA mountains indicates by 2040-2065 mean SWE could decrease −19% (NARCCAP) to −38% (VR-CESM), with an ensemble median change of −27%. Contrary to CMIP5-BCSD and NARCCAP, VR-CESM highlights a more pessimistic outcome for western USA mountain snowpack in latter-parts of the 21st century. This is related to temperature changes altering the snow-albedo feedback, snowpack storage, and precipitation phase, but may indicate that VR-CESM resolves more physically consistent elevational effects lacking in statistically downscaled datasets and teleconnections that are not captured in limited area models. Overall, VR-CESM projects by 2075–2100 that average western USA mountain snowfall decreases by −30%, snow cover by −44%, SWE by −69%, and average surface temperature increase of +5.0 ∘C. This places pressure on western USA states to preemptively invest in climate adaptation measures such as alternative water storage, water use efficiency, and reassess reservoir storage operations.

The present study estimates spatial and temporal (seasonal/annual) trends in daytime land surface temperature (LST) and its drivers (elevation, cloud fraction (CF), atmospheric water vapor (AWV), normalized difference vegetation index (NDVI), and snow cover area (SCA)) over the High Mountain Asia (HMA) during 2001–2019 using MODIS remote sensing data. The findings of the study showed mixed trends in LST in the region with intra-regional variations. Overall, the warming in the region is attributed to increasing AWV and NDVI and declining CF and SCA. The study also found evidence of elevation-dependent warming (EDW) (4500–5500 m AMSL) in some regions. However, the same conclusion cannot be drawn in all the sub-regions of HMA, suggesting the need to explore the effects of additional natural and anthropogenic factors on LST with fine resolution data to improve the understanding of its spatio-temporal dynamics. [ABSTRACT FROM AUTHOR]

Temperature extremes have been extensively observed on the Tibetan Plateau (TP), of which the dynamics were mostly monitored by traditional trend analysis based on linear regression. This method however, is often impacted by a quasi‐periodic heterogeneity disturbance in variance, leading to results susceptible to extreme outliers. In this study, we conducted the comprehensive detection of extreme temperature changes using quantile regression on the TP from 100 weather stations from 1979 to 2019. The use of quantile regression enabled us to characterize the entire density function of the extreme temperature time‐series (the daily minimum, mean and maximum temperature) at each location. Our results revealed that the daily minimum temperature was generally warming faster than the daily maximum and mean temperatures with the respective trend interval of [−0.45, 1.29], [−0.1, 0.98], [−0.01, 1.01] °C/decade among the conditional quantile levels. Furthermore, the warming rate of extremely cold (0.05 quantile level) and hot days (0.95 quantile level) was higher than that of the mean condition (0.5 quantile level) in each extreme temperature time‐series. We also found that there was a significant elevation‐dependent warming only in extremely cold days. In addition, results from the teleconnection analysis showed that the Arctic Oscillation had a strong influence on the extreme cold and hot extremes over the northern and southwestern TP region, while the El Niño‐Southern Oscillation mainly modulated temperatures over the southeastern TP area. This study can potentially offer improved understanding of the temperature extremes over TP in the face of global warming. Plain Language Summary: It is well known that the Tibetan Plateau (TP) is covered extensively with snow and ice and is the major birthplace of many Asian rivers and nurtures billions of people. In the context of global warming, extreme temperature events were found to be more frequent and intense, which has posed increasing threats to the hydrological ecosystem over TP. Although the changes in temperature extremes over the TP have been previously investigated, these studies mostly applied traditional linear regression, which is sensitive and vulnerable to extreme outliers and serial correlation. Therefore, this study aimed to obtain reliable trends in temperature extremes based on a quantile regression method, along with an in‐depth understanding of their elevation dependency. By investigating daily minimum, mean and maximum temperatures at 100 stations, our results showed that significant and universal warming occurred at most stations. Moreover, extreme minimum temperatures usually changed faster than extreme maximum temperatures, which was also true for extremely cold (low quantile group) and hot days (high quantile group) in the same variable. Additionally, it was evidenced that there was a significant elevation‐dependent warming only on extremely cold days. Key Points: Changes in temperature extremes are comprehensively investigated based on quantile regression over the Tibetan Plateau (TP)The entire density function of the daily temperature time‐series was built by quantile regressionThe mechanisms and altitude dependence of climate warming was explored based on the trend retrieved by quantile regression [ABSTRACT FROM AUTHOR]

Greater warming rates in the mountain areas (higher elevations) compared to other parts of the world have drawn the attention of the scientific community in recent years. In this study, we first analyzed elevation‐dependent warming (EDW) patterns based on maximum temperature trends along the south–north temperature gradients of Nepal and then focused on influencing factors of EDW. Nonparametric statistical test was used to identify the warming trend (1970–2016) in each meteorological station along the altitude gradients. Furthermore, aerosol optical depth data was used to observe aerosol concentrations in different seasons across Nepal. Overall, the EDW trend was found positive on the mean annual and seasonal cycle in the study area. It was observed that there was more significant positive correlation of warming rates with altitude below the middle parts of the Lower Hills while a less pronounced correlation above it. This different behavior is attributed to high aerosol concentration on the lower part of this region. [ABSTRACT FROM AUTHOR]

High-altitude areas are thought to be more sensitive to climate change, but long-term series of land surface temperature (LST) observations are still inadequate in low-latitude high-altitude mountainous areas. We investigated spatiotemporal variations in the LST and its dominant driving factors at different time scales based on the long-term series (2001 - 2020) of MODIS data over the Yunnan Province (YNP) in southwest China, with a special focus on elevation-dependent warming (EDW). The results indicated that annual LST generally increased at a rate of 0.18 °C decade -1 over the past 20 years, and the increase was stronger in summer (0.47 °C decade -1 ). Moreover, the nighttime warming rate (0.43 °C decade -1 ) was much faster than that during the daytime (- 0.08 °C decade -1 ), indicating that there was an asymmetric diurnal warming. We also confirmed the presence of EDW, which behaves more greatly above 3500 m. Spatially, the warming trend in high-cold mountains, hot-dry river valleys and the tropics was obvious, while the trend in the northeastern YNP and western side of the Ailao Mountains was opposite. On the timescales of annual, autumn and winter, more than 60% of the LST in the study area was mainly affected by temperature, and 20% ~ 30% was affected by precipitation. LST and warming trend largely differenced with respect to land cover types, with the highest values occurring in built-up lands. This research is expected to contribute to a better understanding of climate change processes in the YNP., Competing Interests: Declarations. Ethical Approval: We declare that there are no ethical issues addressed in this study., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Abstract Temperature extremes have been extensively observed on the Tibetan Plateau (TP), of which the dynamics were mostly monitored by traditional trend analysis based on linear regression. This method however, is often impacted by a quasi‐periodic heterogeneity disturbance in variance, leading to results susceptible to extreme outliers. In this study, we conducted the comprehensive detection of extreme temperature changes using quantile regression on the TP from 100 weather stations from 1979 to 2019. The use of quantile regression enabled us to characterize the entire density function of the extreme temperature time‐series (the daily minimum, mean and maximum temperature) at each location. Our results revealed that the daily minimum temperature was generally warming faster than the daily maximum and mean temperatures with the respective trend interval of [−0.45, 1.29], [−0.1, 0.98], [−0.01, 1.01] °C/decade among the conditional quantile levels. Furthermore, the warming rate of extremely cold (0.05 quantile level) and hot days (0.95 quantile level) was higher than that of the mean condition (0.5 quantile level) in each extreme temperature time‐series. We also found that there was a significant elevation‐dependent warming only in extremely cold days. In addition, results from the teleconnection analysis showed that the Arctic Oscillation had a strong influence on the extreme cold and hot extremes over the northern and southwestern TP region, while the El Niño‐Southern Oscillation mainly modulated temperatures over the southeastern TP area. This study can potentially offer improved understanding of the temperature extremes over TP in the face of global warming.

Abstract Greater warming rates in the mountain areas (higher elevations) compared to other parts of the world have drawn the attention of the scientific community in recent years. In this study, we first analyzed elevation‐dependent warming (EDW) patterns based on maximum temperature trends along the south–north temperature gradients of Nepal and then focused on influencing factors of EDW. Nonparametric statistical test was used to identify the warming trend (1970–2016) in each meteorological station along the altitude gradients. Furthermore, aerosol optical depth data was used to observe aerosol concentrations in different seasons across Nepal. Overall, the EDW trend was found positive on the mean annual and seasonal cycle in the study area. It was observed that there was more significant positive correlation of warming rates with altitude below the middle parts of the Lower Hills while a less pronounced correlation above it. This different behavior is attributed to high aerosol concentration on the lower part of this region.

The present study aims to estimate the trends in daytime land surface temperature (LST) and its relationship with other parameters such as elevation and land use/land cover (LULC) over the Ganga River Basin (GRB) during 2001–2019. The study examined monthly daytime clear-sky LST, elevation, LULC, snow cover area (SCA), clear-sky days, and aerosols data of the GRB. Annual mean clear-sky daytime LST has been declining at the rate −0.017 °C year−1 over the basin during the study period. At seasonal scale, LST has been rising during monsoon (average rate of 0.026 °C year−1), whereas other seasons show a decline with the highest magnitude during winter season (−0.078, oC year−1). The study observed pronounced warming trends (0.003 to 0.07 °C year−1) in post-monsoon above the elevation of 3000 m amsl indicating elevation-dependent warming (EDW) in the basin. The vagary in LST over the basin may be attributed to the changes in LULC, increasing aerosols loading, and rising hazy days. [ABSTRACT FROM AUTHOR]

The intensity and direction of elevation-dependent warming (EDW) could vary in different parts of the mountain, while less attention is paid to the local EDW effect. The Tibetan Plateau (TP) and the T'ai-hang & Lvliang Mountains in Shanxi Province of China (TLMsx) were taken as cases to examine the relationship between EDW and the long-term trend of surface air temperature (SAT) lapse rate (SATLR). For the observed data, the intensity of regional EDW (I EDW) was estimated with linear regression model, while the SATLR was estimated with geographically weighted regression (GWR) model. The long-term trend of SATLR was estimated applying the modified Theil-Sen method, and the regional average SATLR trend (k SATLR ¯) was calculated and analyzed. Both observed data and simulation experiment revealed that there was not significant difference between I EDW and − k SATLR ¯ , with a little difference caused by the noise in the SAT trends. As the SATLR trend measured the difference in the surface air warming rate within 1-km vertical distance, i.e. the intensity of EDW in a small spatial scale, in the context of climate warming, it could be used to estimate the intensity of local EDW. The SATLR trend thus provided a new perspective to study the EDW effect in the future, and facilitated the quantitative analysis on the mechanisms of EDW. • Two kinds of elevation-dependent warming (EDW) effect, positive EDW and negative EDW, are found. • The regional average surface air temperature lapse rate (SATLR) trend (k SATLR ¯) was broadly opposite to that of the intensity of EDW (I EDW). • There was not significant difference between I EDW and − k SATLR ¯. [ABSTRACT FROM AUTHOR]

Mountain regions have been recognized to be more sensitive to climate and environmental changes, and in particular to global warming. Several studies report on elevation-dependent warming (EDW), i.e., when warming rates are different in different altitude ranges, particularly focusing on the enhancement of warming rates with elevation. The Andean chain proved to be a relevant climate change hot-spot with positive temperature trends and a widespread glacier retreat over the recent decades. To assess and to better understand elevation dependent warming in this mountain region and to identify its possible dependence on latitude, the Andean Cordillera was split into five domains, three pertaining to the tropical zone and two pertaining to the Subtropics. Further, for each area the eastern and western faces of the mountain range were separately analyzed. An ensemble of regional climate model (RCM) simulations participating in the Coordinated Regional Climate Downscaling Experiment (CORDEX), consisting of one RCM nested into eight different global climate models from the CMIP5 ensemble was considered in this study. EDW was assessed by calculating the temperature difference between the end of the century (2071–2100) and the period 1976–2005 and relating it to the elevation. Future projections refer to the RCP 8.5 high-emission scenario. Possible differences in EDW mechanisms were identified using correlation analyses between temperature changes and all the variables identified as possible EDW drivers. For the maximum temperatures, a positive EDW signal (i.e. enhancement of warming rates with elevation) was identified in each side of both the tropical and subtropical Andes and in all seasons. For the minimum temperatures, on the contrary, while a positive EDW was identified in the Subtropics (particularly evident in the western side of the chain), the Tropics are characterized by a negative EDW throughout the year. Therefore, the tropical boundary marks a transition between discordant EDW behaviours in the minimum temperature. In the Tropics and particularly in the inner Tropics, different EDW drivers were identified for the minimum temperature, whose changes are mostly associated with changes in downward longwave radiation, and for the maximum temperature, whose changes are mainly driven by changes in downward shortwave radiation. This might explain the opposite EDW signal found in the tropical Andes during daytime and nighttime. Changes in albedo are an ubiquitous driver for positive EDW in the Subtropics, for both the minimum and the maximum temperature. Changes in longwave radiation and humidity are also EDW drivers in the Subtropics but with different relevance throughout the seasons and during daytime and nighttime. Also, the western and eastern sides of the Cordillera might be influenced by different EDW drivers. [ABSTRACT FROM AUTHOR]

Warming in mountainous areas has obvious elevation dependence (warming rate increases with elevation), which deeply impacts runoff change in mountainous areas. This study analysed the influence of elevation-dependent warming on runoff in the headwater region of the Urumqi River Basin (URB) based on meteorological data, remote sensing images, and runoff data. Results indicated a significant warming rate in the URB from 1960 to 2019 (0.362 °C/decade; p < 0.01). The temperature increased with an obvious elevation-dependent warming in the URB, especially during winter. Glaciers sharply retreated in the headwater region of the URB under regional warming, and remote-based results showed that glacier areas decreased by 29.45 km2 (−57.81%) from the 1960s to 2017. The response of glacier mass balance and meltwater runoff to temperature change has a lag of 3 years in the headwater region of the URB. The elevation-dependent warming of temperature changes significantly impacted glacial meltwater runoff in the URB (R2 = 0.49). Rising temperatures altered the glacial meltwater runoff, and the maximum annual runoff of the Urumqi Glacier No. 1 meltwater runoff increased 78.6% in 1990–2017 compared to 1960–1990. During the period of 1960–1996, the total glacial meltwater runoff amounted to 26.9 × 108 m3, accounting for 33.4% of the total runoff during this period, whereas the total glacial meltwater runoff accounted for 51.1% of the total runoff in 1996–2006. Therefore, these results provide a useful reference for exploring runoff changes in mountainous watersheds in the context of elevation-dependent warming. [ABSTRACT FROM AUTHOR]

High mountains are among the regions most affected by climate change. The complex network of interactions between climate, biological, and sociocultural structures in these regions is being altered by the changing climate. In this work, we try to explore the future challenges for these unique regions. We analyse why they are important and what problems they are facing in today’s climate and political scenario, with a special focus on the Pyrenees. [ABSTRACT FROM AUTHOR]

Recent studies offer more evidence that the rate of warming is amplified with elevation, indicating thereby that high-elevation ecosystems tend to be exposed to more accelerated changes in temperature than ecosystems at lower elevations. The phenomenon of elevation-dependent warming (EDW), as one of the regional climate-change impacts, has been observed across the Tibetan Plateau. Studies have often found large-scale greening trends, but the drivers of vegetation dynamics are still not fully understood in this region, such that the local implications of vegetation change have been infrequently discussed. This study was designed to quantify and characterize the seasonal changes in vegetation across the Three Rivers Headwaters Region (TRHR), where the land cradles the headwaters of the Yangtze, the Yellow, and the Lancang (Mekong). By mapping the normalized difference vegetation index (NDVI) over the growing season from 1982 to 2015, we were able to evaluate seasonal changes in vegetation cover over time. The results show a slightly increased tendency in green vegetation cover, which could possibly be attributed to sustained warming in this region over the past three decades, whereas a decline in the green-up rate with elevation was found, indicating an inconsistent trend of vegetation greening with EDW. The cause of the green-up rate decline at high elevations could be linked to the reduced soil water availability induced by the fast increase in warming rates associated with EDW. The findings of this study have important implications for devising adaptation strategies for alpine ecosystems in a changing climate.

Abstract Snow plays an essential role in regulating climate change, the hydrological cycle, and various biological processes. Passive microwave snow depth data and gridded data from the Climate Research Unit (CRU_TS4.04) are utilized in this study to investigate spatiotemporal variations of snow depth over the Tibetan Plateau (TP), with special focus on the vertical dimension. The response of snow to elevation‐dependent warming (EDW) is determined accordingly. High mountains experience more rapid warming than lower elevations. During 1980–2014, the total snow depth over the TP decreased; areas with the most significant decreasing trends are mainly concentrated in the northwestern and southwestern parts of the TP. The plateau‐wide decrease in snow depth (−0.24 cm/decade) is mainly affected by increasing temperature (0.30°C/decade). The reduction in snow depth trend intensifies as sub‐regional mean elevation increases from 3,332 m (IID2) to 5,074 m (ID1). A stronger snow depth decrease in high‐elevation sub‐regions generally corresponds to higher warming rates, which demonstrates EDW. The most pronounced correlation between snow depth decrease rate and elevation occurs in the southeastern TP, which covers the largest elevation range on the plateau (from 2,000 to 6,000 m).

Snow plays an essential role in regulating climate change, the hydrological cycle, and various biological processes. Passive microwave snow depth data and gridded data from the Climate Research Unit (CRU_TS4.04) are utilized in this study to investigate spatiotemporal variations of snow depth over the Tibetan Plateau (TP), with special focus on the vertical dimension. The response of snow to elevation‐dependent warming (EDW) is determined accordingly. High mountains experience more rapid warming than lower elevations. During 1980–2014, the total snow depth over the TP decreased; areas with the most significant decreasing trends are mainly concentrated in the northwestern and southwestern parts of the TP. The plateau‐wide decrease in snow depth (−0.24 cm/decade) is mainly affected by increasing temperature (0.30°C/decade). The reduction in snow depth trend intensifies as sub‐regional mean elevation increases from 3,332 m (IID2) to 5,074 m (ID1). A stronger snow depth decrease in high‐elevation sub‐regions generally corresponds to higher warming rates, which demonstrates EDW. The most pronounced correlation between snow depth decrease rate and elevation occurs in the southeastern TP, which covers the largest elevation range on the plateau (from 2,000 to 6,000 m). [ABSTRACT FROM AUTHOR]

To explore the driving mechanisms of elevation-dependent warming (EDW) over the Tibetan Plateau (TP), the output from a suite of numerical experiments with different cumulus parameterization schemes (CPs) under the Coordinated Regional Climate Downscaling Experiments-East Asia (CORDEX-EA-II) project is examined. Results show that all experiments can broadly capture the observed temperature distributions over the TP with consistent cold biases, and the spread in temperature simulations commonly increases with elevation with the maximum located around 4000–5000 m. Such disagreements among the temperature simulations could to a large extent be explained by their spreads in the surface albedo feedback (SAF). All the experiments reproduce the observed EDW below 5000 m in winter but fail to capture the observed EDW above 4500 m in spring. Further analysis suggests that the simulated EDW during winter is mainly caused by the SAF, and the clear-sky downward longwave radiation (LWclr) plays a secondary role in shaping EDW. The models' inability in simulating EDW during spring is closely related to the SAF and the surface cloud radiative forcing (CRFs). Furthermore, the magnitude and structure of the simulated EDW are sensitive to the choice of CPs. Different CPs generate diverse snow cover fractions, which can modulate the simulated SAF and its effect on EDW. Also, the CPs show great influence on the LWclr via altering the low-level air temperature. Additionally, the mechanism for different temperature changes among the experiments varies with altitudes during summer and autumn, as the diverse temperature changes appear to be caused by the LWclr for the low altitudes while by the SAF for the middle-high altitudes. [ABSTRACT FROM AUTHOR]

Climate change is having disproportionate impacts on the Tibetan plateau. Elevation-dependent- warming (EDW), faster warming in high mountains, poses an enhanced threat to life-supporting snow/ice reserves above 5000 m. Past studies debate how EDW is caused, and cannot predict how it will change in future. This study, for the first time, shows that the amplitude of regional warming determines the pattern of EDW, and that changing elevation gradients in snow depth over time have been responsible. Snow loss at increasingly higher elevations moves the zone of enhanced impact uphill, probably continuing in future. Our results explain the divergence in previous studies about causes of EDW, and also have critical implications for longer-term sustainability of water resources on the Tibetan Plateau. [Display omitted] Elevation-dependent warming (EDW), whereby warming rates are stratified by elevation, may increase the threat to the life-supporting solid water reservoir on the Tibetan Plateau. Previous studies have debated whether EDW exists and how it is driven. Using temperatures at 133 weather stations on the Tibetan Plateau during 17 different periods generated using a 30-year sliding window over 1973–2018, this study finds that the existence of EDW varies as the period moves forward, and critically it has become more severe over time. During the early part of the record with weaker regional warming, there were limited changes in snow depth and no EDW, but as time advances and regional warming intensifies, snow depth declines significantly at higher elevations, causing development of EDW. We conclude that enhanced regional warming has caused decreases in snow depth, largely controlling the pattern of EDW on the Tibetan Plateau. This may explain contrasting conclusions on EDW from previous studies which have used data for different periods, and our findings support enhanced EDW and more severe depletion of the Tibetan Plateau solid water reserves in a warmer future. [ABSTRACT FROM AUTHOR]

Under the Coordinated Regional Climate Downscaling Experiments‐East Asia (CORDEX‐EA‐II), the outputs from two regional climate models (RCMs) driven by four global climate models (GCMs) are used to investigate the characteristics and possible mechanisms of the projected elevation‐dependent warming (EDW) over the Tibetan Plateau (TP) under the Representative Concentration Pathway emission scenario 8.5 (RCP8.5). Results show that widespread warming over the TP is projected with considerable disagreements in warming intensity and the maximum warming center among RCMs. The largest spread in the surface air temperature (Tas) projections is found above 5,000 m, indicating that a large uncertainty exists over the higher elevations. A marked EDW signal over the TP is simulated under the RCP 8.5 by the multi‐RCM ensemble mean for all seasons, particularly in autumn. Based on the analysis of the surface energy budget, it is found that the surface albedo feedback (SAF) is the primary contributor to EDW and acts as the main source of uncertainty in EDW projections among RCMs. The downward longwave radiation (DLW) is found to be the dominant factor in regulating Tas change over the TP, and its contribution to EDW is model‐dependent. Furthermore, the structure and magnitude of projected EDW are sensitive to the RCM physics and driving GCM, as they can alter the projections of snow cover and albedo, which modulate the simulated SAF and its effect on EDW. Additionally, RegCM4 shows a higher sensitivity to the anthropogenic greenhouse forcing than WRF, evidenced by the larger temperature projections and stronger EDW signal in RegCM4. Key Points: Elevation‐dependent warming will happen in the future with its magnitude and structure varying with seasonsSurface albedo feedback is the primary contributor to elevation‐dependent warming and the dominant source of uncertainty in its projectionsThe projected elevation‐dependent warming depends not only on the driving global climate model but also on the internal model physics [ABSTRACT FROM AUTHOR]

Warming in mountainous areas has obvious elevation dependence (warming rate increases with elevation), which deeply impacts runoff change in mountainous areas. This study analysed the influence of elevation-dependent warming on runoff in the headwater region of the Urumqi River Basin (URB) based on meteorological data, remote sensing images, and runoff data. Results indicated a significant warming rate in the URB from 1960 to 2019 (0.362 °C/decade; p < 0.01). The temperature increased with an obvious elevation-dependent warming in the URB, especially during winter. Glaciers sharply retreated in the headwater region of the URB under regional warming, and remote-based results showed that glacier areas decreased by 29.45 km2 (−57.81%) from the 1960s to 2017. The response of glacier mass balance and meltwater runoff to temperature change has a lag of 3 years in the headwater region of the URB. The elevation-dependent warming of temperature changes significantly impacted glacial meltwater runoff in the URB (R2 = 0.49). Rising temperatures altered the glacial meltwater runoff, and the maximum annual runoff of the Urumqi Glacier No. 1 meltwater runoff increased 78.6% in 1990–2017 compared to 1960–1990. During the period of 1960–1996, the total glacial meltwater runoff amounted to 26.9 × 108 m3, accounting for 33.4% of the total runoff during this period, whereas the total glacial meltwater runoff accounted for 51.1% of the total runoff in 1996–2006. Therefore, these results provide a useful reference for exploring runoff changes in mountainous watersheds in the context of elevation-dependent warming.

This paper investigates the elevation‐warming relationships across the Carpathian Mountains, using the 0.1° × 0.1° gridded daily air temperature dataset developed within the CARPATCLIM project, in order to understand the spatial patterns of annual and seasonal temperature trends and test the hypothesis of enhanced warming with elevation. Temperature trend and elevation‐warming analyses were conducted over the 50 years of the dataset (1961–2010). The vertical variations of five key isotherms relevant for the development of cold‐climate weathering, presence of permafrost (−2°C, 0°C, +2°C, +3°C) and spread of forest vegetation (July +10°C) were also examined. The Carpathian Mountains are under visible annual and seasonal warming (stronger in the summer and winter), both daytime and nighttime. The warming process shows a great spatial inhomogeneity, but is more pronounced in the lowlands of the region, generally below 1,000–1,200 m. The correlations between elevation and warming rates across the Carpathians have been found both to be positive and negative, while mostly significant at the 5% level. Evidence of enhanced warming with elevation was found to be related to the minimum temperature increase mostly across the NW and SW Carpathians, at both annual and seasonal scales (winter, summer and spring). Less prominent EDW signals have been identified in the NE, E and S Carpathians (summer), as well as in the NE Carpathians (spring). Parts of the detected temperature trends and EDW signals have been considered to be an effect of the changing atmospheric circulation (i.e. westerly intensification especially in the winter), although other mechanisms and processes could be involved (e.g. snow‐albedo feedbacks in the spring). These results could serve as a reference for further investigations of climate warming effects across the Carpathian Mountains region (e.g. ecological and geomorphic), especially in relation to the augmented summer heat stress (e.g. more frequent heatwaves) and milder winters (e.g. less freezing days). [ABSTRACT FROM AUTHOR]

Mountains become warmer with elevation in response to greenhouse gas warming, an effect known as elevation-dependent warming. The Eocene is considered a replica of the future climate in an epoch with high atmospheric carbon dioxide concentration (CO _2 ). Therefore, the topographic features of the Eocene strata are of interest. However, obtaining proxy data for mountain regions during the Eocene hothouse is challenging. Paleoclimate model simulation is an effective tool for exploring past climate change. Therefore, we conducted sensitivity experiment simulations employing the Community Earth System Model version 1.2 forced by proxy-estimated CO _2 levels. This is the first Eocene study demonstrating the elevation-dependent temperature changes and illustrated using the surface energy budget decomposition. Here five major mountain ranges have been chosen based on their paleogeographic continental location. We found a nonlinear response of elevation-dependent temperature change to CO _2 concentrations regulated by seasonal variations. The radiative and non-radiative feedback compensation is responsible for the elevation-dependency temperature changes. Our results suggest temperature perturbations regulate elevation-dependent changes in skin temperature through a combination of feedback under greenhouse warming in the early Eocene. These findings also show future paradox response exhibiting elevation-dependent cooling overall mountain regions due to lower elevation warming.

Investigating the changes in the extreme temperature indices is crucial for the assessment of climate change and to recommend practical adaptation strategies particularly in countries like Nepal, which is highly prone to the impacts of extreme climatic events. This study analyses the mean temperatures and the changes of extreme temperature indices at 25 stations located in different physiographic regions in Nepal at monthly and annual time scales for 1986–2015. Ten extreme temperature indices recommended by ETCCDI are selected and examined. Quality control is first conducted for original daily maximum and minimum temperature data. In Nepal, it is warming in general with maximum temperature (0.04°C year−1) increasing faster than minimum temperature (0.02°C year−1) on countrywide average which is contrary to the changes in the Tibetan Plateau and its surroundings and the global average. The changes in extreme temperatures are spatiotemporally heterogeneous and unique. Annually, cold extremes increase but the percentage of days below 10th percentile becomes less frequent. Terai and Siwalik plain regions show negative annual trends in cold indices (TNn and TXn), but mixed changes in other extreme indices. There are strong correlations between the trends of maximum temperature‐related variables and elevation. This analysis also adds the evidence of pronounced warming in higher elevation only for day‐time extreme temperatures but not for temperature minima in Nepal which differs from the other studies around the world. This study also reveals that December and January tend to have colder days in the Terai. However, summer months are getting hotter in each region across the country. Kathmandu, the most urbanized city in Nepal shows a significant increase in minimum temperature (Tmin) and minimum Tmin (TNn) indicating the influence of urbanization in temperature change ‐ an urban heat island effect. [ABSTRACT FROM AUTHOR]

Many studies have focused on elevation-dependent warming (EDW) across high mountains, but few studies have examined both EDW and LDW (latitude-dependent warming) on Antarctic warming. This study analyzed the Antarctic amplification (AnA) with respect to EDW and LDW under SSP1–2.6, SSP2–4.5, SSP3–7.0 and SSP5–8.5 from Coupled Model Intercomparison Project Phase 6 (CMIP6) during the period 2015–2100. The results show that the AnA appears under all socioeconomic scenarios, and the greatest signal appears in austral autumn. In the future, Antarctic warming is not only elevation-dependent, but also latitude-dependent. Generally, positive EDW of mean temperature (T mean), maximum temperature (T max) and minimum temperature (T min) appear in the range of 1.0–4.5 km, and the corresponding altitudinal amplification trends are 0.012/0.012/0.011 (SSP1–2.6)—0.064/0.065/0.053 (SSP5–8.5) °C decade−1•km−1. Antarctic EDW demonstrates seasonal differences, and is strong in summer and autumn and weak in winter under SSP3–7.0 and SSP5–8.5. For T mean , T max and T min , the feature of LDW is varies in different latitude ranges, and also shows seasonal differences. The strongest LDW signal appears in autumn, and the warming rate increases with increasing latitude at 64–79°S under SSP1–2.6. The similar phenomenon can be observed at 68–87°S in the other cases. Moreover, the latitude component contributes more to the warming of T mean and T max relative to the corresponding altitude component, which may relates to the much larger range of latitude (∼2600 km) than altitude (∼4.5 km) over Antarctica, while the EDW contributes more warming than LDW in the changes in T min in austral summer. Moreover, surface downwelling longwave radiation, water vapor and latent heat flux are the potential factors influencing Antarctic EDW, and the variation in surface downwelling longwave radiation can also be considered as an important influencing factor for Antarctic LDW. Our results provide preliminary insights into EDW and LDW in Antarctica. • Antarctic amplification exists under SSP1–2.6, SSP2–4.5, SSP3–7.0 and SSP5–8.5 during 2015–2100. • Elevation-dependent warming (EDW) and latitude-dependent warming (LDW) exist in future warming over Antarctica. • EDW and LDW enhance with the strengthening of forcing. • The EDW and LDW in Antarctica shows seasonal differences, and LDW shows different features in different ranges. • Longwave radiation, water vapor and latent heat flux are the possible factors promoting EDW in Antarctica. [ABSTRACT FROM AUTHOR]

This study uses the CMA (China Meteorological Administration) global land-surface daily air temperature dataset V1.0 (GLSATD V1.0) to analyze long-term changes in extreme temperature events over the Hindu Kush Himalaya (HKH) during 1961–2015. Results show there was a significant decrease in the number of extreme cold events (cold nights, cold days, and frost days) but a significant increase in the number of extreme warm events (warm nights, warm days, and summer days) over the entire HKH during 1961–2015. For percentile-based indices, trends of extreme events related to minimum temperature (Tmin) were greater in magnitude than those related to maximum temperature (Tmax). For absolute-value based indices, maximum Tmax, minimum Tmin, and summer days all show increasing trends, while frost days and the diurnal temperature range (DTR) show significant decreasing trends. In addition, there was a decrease in extreme cold events in most parts of east HKH, particularly in Southwest China and the Tibetan Plateau, while there was a general increase in extreme warm events over the entire HKH. Finally, the change in extreme cold events in the HKH appears to be more sensitive to elevation (with cold nights and cold days decreasing with elevation), whereas the change in warm extremes (warm nights, warm days, and maximum Tmax) shows no detectable relationship with elevation. Frost days and minimum Tmin also have a good relationship with elevation, and the trend in frost days decreases with an increase in elevation while the trend in minimum Tmin increases with an increase in elevation.

Decadal trends of continuous seasonal maximum and minimum air temperature and air temperature range are analyzed by elevation within the southern Appalachian Mountains of the southeastern United States. Temperature data included spanned December 1969 to November 2018 and were obtained from the quality controlled Global Historical Climatology Network-monthly, version 4. Linear least squares regression indicates statistically-significant warming trends with minimum seasonal air temperature typically increasing more than maximum seasonal air temperature, reflecting a decrease of the air temperature range with time, particularly during the boreal meteorological winter, spring, and summer seasons. Regressions of station decadal trends versus station elevation illustrate the presence of elevation-dependent warming with the magnitude of decadal temperature trends decreasing as station elevation increases, at least up to 850 m above mean sea level. As a result, the regional vertical temperature lapse rate was also found to increase with time, suggesting the possibility for precipitation and convection lift implications. From a biogeography standpoint, the increasing vertical temperature gradient may imply an acceleration of species upslope migration with time. Las tendencias decenales de la temperatura del aire máxima y mínima continuas estacionales y el rango de temperatura del aire se analizan por elevación dentro de los Montes Apalaches del sur del sureste de los Estados Unidos. Los datos de temperatura incluyeron desde diciembre de 1969 hasta noviembre de 2018 y se obtuvieron de la red de Climatología Histórica Global con calidad controlada mensual, versión 4. La regresión lineal de mínimos cuadrados indica tendencias de calentamiento estadísticamente significativas con una temperatura del aire estacional mínima que generalmente aumenta más que la temperatura del aire estacional, lo que refleja una disminución del rango de la temperatura del aire con el tiempo, particularmente durante las estaciones meteorológicas boreales de invierno, primavera y verano. Las regresiones de las tendencias decenales de la estación frente a la elevación de la estación ilustran la presencia de un calentamiento dependiente de la elevación con la magnitud de las tendencias decadales de la temperatura disminuyendo a medida que aumenta la elevación de la estación, al menos hasta 850 m por encima del nivel medio del mar. Como resultado, también se encontró que la tasa de caída vertical de la temperatura aumentaba con el tiempo, lo que sugiere la posibilidad de implicaciones de elevación por convección y precipitación. Desde el punto de vista de la biogeografía, el aumento del gradiente vertical de temperatura puede implicar una aceleración de la migración en pendiente de las especies con el tiempo. [End Page 365] [ABSTRACT FROM AUTHOR]

Significant elevation-dependent warming (EDW) of maximum near-surface air temperature and diurnal temperature range (DTR) has been observed in Nepal (southern central Himalaya) until 2566 m a.s.l., over the last four decades (1976–2015). During this period, on the average and across the entire country, maximum air temperature increased (+0.045 °C y−1, p <.001) more than minimum temperature (+0.009 °C y−1, p <.05) and, as a consequence, DTR also increased significantly (+0.034 °C y−1, p <.001). Maximum temperature increases have been observed during all seasons of the year. This warming pattern differs from the symmetrical one observed at global level in the same period, and it is in contrast to more prominent minimum temperature increases observed in the north of Himalaya (Tibetan Plateau). Furthermore, the near-surface air temperature change observed in Nepal contrasts the global evidence of main increasing trends occurring during the winter months. We point out that this asymmetric warming pattern could have more serious impacts in Nepal than in other regions of the world, considering the consequences of associated warm maximum-temperature extremes (heatwaves, hot days) on human life, increased primary production, and modifications in the hydrological cycle. We conclude sustaining that the observed EDW of maximum temperature and the DTR could be attributed to the monsoon weakening, namely to the reduced number of rainy days observed in the region during the last decades. These phenomena could have been accompanied by decreasing cloudiness and consequent increasing of daytime shortwave and decreasing of nighttime longwave incoming solar radiation. Unlabelled Image • Air temperature from land stations has been analysed in Nepal (1976–2015) until 2566 m. • During all seasons, maximum temperature increased more than minimum temperature. • Elevation-dependence of maximum temperature and diurnal temperature range has been observed. • Elevation-dependence warming in Nepal could be explained by the monsoon weakening. [ABSTRACT FROM AUTHOR]

Over the Upper Colorado River basin (UCRB), temperatures in widely used gridded data products do not warm as much as mean temperatures from a stable set of U.S. Historical Climatology Network (USHCN) stations, located at generally lower elevations, in most months of the year. This is contrary to expectations of elevation‐dependent warming, which suggests that warming increases with elevation. These findings could reflect (a) a genuine absence of elevation‐dependent warming in the region, (b) systematic non‐climatic influences on either the USHCN stations or high‐elevation stations, including known inhomogeneities related to changes in the time of observation and instrumentation, or (c) suppression of an elevation‐dependent warming signal introduced by changes in the station network. While we cannot categorically dismiss the first two possibilities, we show here that over portions of the 20th century, gridded temperatures warm less than USHCN temperatures, and the difference cannot be explained by accounting for known inhomogeneities. These analyses suggest that changing station coverage in the UCRB has influenced trends in gridded temperature estimates that incorporate changing suites of stations over time. Specifically, increases in the number of high‐elevation stations in the UCRB may have led to an underestimation of elevation‐dependent warming, particularly during the spring. This phenomenon is unlikely limited to this specific basin and may be present in other high‐elevation watersheds across the western United States The effects of systematically changing station coverage are profound and significantly impact our ability to assess long‐term trends where instrumentation is sparse. Data sets disagree in ways that are consistent with choices made during product development, so that it is critical for users to understand and acknowledge each data set's specific characteristics, in much the same way that the community already addresses differences between the many hydrological models that are in use. Annual average differences between PRISM and U.S. Historical Climatology Network minimum (blue) and maximum (red) temperature estimates that have (solid) and have not (dashed) been adjusted for inhomogeneities across the UCRB relative to the average elevation of the available station network (purple). Cyan shading shows the period of time when the record might be influenced by the inclusion of data from SNOTEL sites. Marking the onset of potential inhomogeneities related to SNOTEL instrumentation. [ABSTRACT FROM AUTHOR]

This study uses the daily maximum and minimum temperature data sets of 48 meteorological stations to assess the observed changes in temperature extremes over China–Pakistan Economic Corridor (CPEC) during 1980–2016. The nonparametric Mann–Kendall, Sen's slope estimator, least squares method, and two‐tailed simple t‐test methods were used to assess the trend in nine temperature extreme indices. The results of the study indicated that the trends in annual mean anomalies of cold nights, cold days, and frost days significantly decreased at the rates of −1.09, −1.58, and −1.05 day/decade, respectively. The number of warm nights, warm days, and summer days exhibited significant positive trends at the rates of 1.49, 1.04, and 4.32 day/decade, respectively. In addition, the trends of the warmest day and coldest day also increased significantly at the rates of 0.45 and 0.51 °C/decade, respectively. The trend of diurnal temperature range decreased significantly with −0.35 °C/decade. The spatial distribution of temperature extreme indices indicated that the number of cold nights, cold days, and diurnal temperature range have been decreased, while the trends of warm nights, warm days, summer days, warmest day, and coldest day have been increased over the whole country. Large‐scale atmospheric circulation changes derived from ERA‐Interim reanalysis show that a weak (strong) wind pressure, increasing (decreasing) geopotential height, and rapid warming (cooling) over the northern (southern) region have contributed to the changes in temperature extremes in Pakistan to some extent. With respect to elevation‐dependent warming (EDW), the trends of cold nights, warm days, summer days, warmest day, and diurnal temperature range showed significant positive correlations with increasing elevation. However, the trends of cold days, warm nights, frost days, and coldest day showed significant negative relationships with increasing elevation. The findings of this study will be helpful in the adaptation of climate change and mitigation of climatological disasters in the region. The study recommends that future studies should investigate the natural and anthropogenic drivers of temperature extremes and the possible mechanism of EDW in the CPEC region. Topographic map of the study area with CPEC routes and selected meteorological stations. [ABSTRACT FROM AUTHOR]

The enhancement of warming rates with elevation, so-called elevation-dependent warming (EDW), is one of the regional, still not completely understood, expressions of global warming. Sentinels of climate and environmental changes, mountains have experienced more rapid and intense warming trends in the recent decades, leading to serious impacts on mountain ecosystems and downstream. In this paper we use a state-of-the-art Global Climate Model (EC-Earth) to investigate the impact of model spatial resolution on the representation of this phenomenon and to highlight possible differences in EDW and its causes in different mountain regions of the Northern Hemisphere. To this end we use EC-Earth climate simulations at five different spatial resolutions, from ∼ 125 to ∼ 16 km, to explore the existence and the driving mechanisms of EDW in the Colorado Rocky Mountains, the Greater Alpine Region and the Tibetan Plateau-Himalayas. Our results show that the more frequent EDW drivers in all regions and seasons are the changes in albedo and in downward thermal radiation and this is reflected in both daytime and nighttime warming. In the Tibetan Plateau-Himalayas and in the Greater Alpine Region, an additional driver is the change in specific humidity. We also find that, while generally the model shows no clear resolution dependence in its ability to simulate the existence of EDW in the different regions, specific EDW characteristics such as its intensity and the relative role of different driving mechanisms may be different in simulations performed at different spatial resolutions. Moreover, we find that the role of internal climate variability can be significant in modulating the EDW signal, as suggested by the spread found in the multi-member ensemble of the EC-Earth experiments which we use. [ABSTRACT FROM AUTHOR]

There is evidence for elevation-dependent warming (EDW) in many mountainous regions, including the Alps, Rockies, and Tibetan Plateau, all of which are in mid latitudes. Most studies finding evidence of EDW indicate that both recent decadal and future projected warming rates are greater at higher elevations. In this study, we examine the roles of Arctic amplification and elevation on future warming rates in winter and summer in eastern Siberia (50–70° N; 80–180° E). This region includes four major river basins that flow into the Arctic Ocean (the Yenisei, Lena, Indigirka, and Kolyma) and intersects with mountain ranges in northern Mongolia and eastern Siberia. We analyze projected 21st century temperature projections using a six-member ensemble of the National Center for Atmospheric Research (NCAR) Community Climate System Model (CCSM4) with a radiative forcing of 8.5 W m ^−2 . Projected warming rates in winter for the 21st century are dominated by Arctic amplification, which leads to significantly larger warming rates at higher latitudes, with latitudinal gradients of about 0.16 °C degree ^−1 latitude. In summer, the latitudinal gradient is near zero (0.02 °C degree ^−1 of latitude). Within specific latitude bands, we also find EDW. However, unlike most mid-latitude locations where warming rates are greater at higher elevations, we find that future warming rates are smaller at higher elevations for this high-latitude region, particularly during winter, with statistically significant rates varying between −0.70 °C km ^−1 and −2.46 °C km ^−1 for different 5° latitude bands. The decrease in warming rates with elevation in winter at the highest latitudes is primarily attributed to strong inversions and changes in the lapse rate as free-air temperatures warm at slower rates than surface temperatures. In summer, the elevation dependence is much weaker than in winter but still statistically significant and negative in all but the most northern latitude band with values ranging between −0.10 °C km ^−1 and −0.56 °C km ^−1 .

We assessed maximum (Tmax) and minimum (Tmin) temperatures over Pakistan’s Indus basin during the 21st century using statistical downscaling. A particular focus was given to spatiotemporal heterogeneity, reference and General Circulation Model (GCM) uncertainties, and statistical skills of regression models using an observational profile that could significantly be improved by recent high-altitude observatories. First, we characterized the basin into homogeneous climate regions using K-means clustering. Predictors from ERA-Interim reanalysis were then used to model observed temperatures skillfully and quantify reference and GCM uncertainties. Thermodynamical (dynamical) variables mainly governed reference (GCM) uncertainties. The GCM predictors under RCP4.5 and RCP8.5 scenarios were used as “new” predictors in statistical models to project ensemble temperature changes. Our analysis projected non-uniform warming but could not validate elevation-dependent warming (EDW) at the basin scale. We obtained more significant warming during the westerly-dominated seasons, with maximum heating during the winter season through Tmin changes. The most striking feature is a low-warming monsoon (with the possibility of no change to slight cooling) over the Upper Indus Basin (UIB). Therefore, the likelihood of continuing the anomalous UIB behavior during the primary melt season may not entirely be ruled out at the end of the 21st century under RCP8.5.

Mountain regions are experiencing more pronounced climate change than other global land areas. How have vegetation dynamics responded to these changes and what are the implications for hydrology? To answer these questions, we examine the impacts of changes in mean air temperature ( T _mean ), precipitation ( P ) and winter snow cover extent ( SCE ) in the headwaters of the Yellow River basin (HYRB) on two important vegetation dynamic metrics: (i) the maximum growing-season greenness (represented by the monthly maximum NDVI); and (ii) the beginning of growing season (BGS). Satellite-derived NDVI and SCE , along with observation-based gridded climate data, show that during the past 34 years (1982–2015) the HYRB experienced widespread vegetation greening, while no significant trend in BGS was observed. Spring greenness and phenology were significantly affected by SCE change, highlighting the importance of snow-related process to spring vegetation activity. We observed a clear signal of elevation-dependent warming below 4300 m elevation, which is absent at higher elevations. Changes in NDVI and BGS are elevation-dependent, and trends in T _mean , P, and SCE with elevation play different roles in this dependence. Both observed and estimated watershed annual evapotranspiration series show increasing trends, suggesting that vegetation greening imposes positive effects on evaporative fluxes. Given steady-state and non-stationary hydrological conditions, increasing evapotranspiration should result in runoff reduction, which agrees with catchment-scale runoff observations across the HYRB. These findings represent new knowledge regarding the vegetation response to climate change in alpine environments which has important implications for the hydrology of the region and for other high-water yielding mountainous regions worldwide.

In Part I of our study (Zazulie et al. Clim Dyn, 2017, hereafter Z17) we analyzed the ability of a subset of fifteen high-resolution global climate models (GCMs) from the Coupled Model Intercomparison Project phase 5 to reproduce the past climate of the Subtropical Central Andes (SCA) of Argentina and Chile. A subset of only five GCMs was shown to reproduce well the past climate (1980-2005), for austral summer and winter. In this study we analyze future climate projections for the twenty-first century over this complex orography region using those five GCMs. We evaluate the projections under two of the representative concentration pathways considered as future scenarios: RCP4.5 and RCP8.5. Future projections indicate warming during the twenty-first century over the SCA region, especially pronounced over the mountains. Projections of warming at high elevations in the SCA depend on altitude, and are larger than the projected global mean warming. This phenomenon is expected to strengthen by the end of the century under the high-emission scenario. Increases in winter temperatures of up to 2.5 °C, relative to 1980-2005, are projected by 2040-2065, while a 5 °C warming is expected at the highest elevations by 2075-2100. Such a large monthly-mean warming during winter would most likely result in snowpack melting by late winter-early spring, with serious implication for water availability during summer, when precipitation is a minimum over the mountains. We also explore changes in the albedo, as a contributing factor affecting the net flux of energy at the surface and found a reduction in albedo of 20-60% at high elevations, related to the elevation dependent warming. Furthermore, a decrease in winter precipitation is projected in central Chile by the end of the century, independent of the scenario considered. [ABSTRACT FROM AUTHOR]

Abstract: Under current global warming, high‐elevation regions are expected to experience faster warming than low‐elevation regions. However, due to the lack of studies based on long‐term large‐scale data, the relationship between tree spring phenology and the elevation‐dependent warming is unclear. Using 652k records of leaf unfolding of five temperate tree species monitored during 1951–2013 in situ in Europe, we discovered a nonlinear trend in the altitudinal sensitivity (SA, shifted days per 100 m in altitude) in spring phenology. A delayed leaf unfolding (2.7 ± 0.6 days per decade) was observed at high elevations possibly due to decreased spring forcing between 1951 and 1980. The delayed leaf unfolding at high‐elevation regions was companied by a simultaneous advancing of leaf unfolding at low elevations. These divergent trends contributed to a significant increase in the SA (0.36 ± 0.07 days 100/m per decade) during 1951–1980. Since 1980, the SA started to decline with a rate of −0.32 ± 0.07 days 100/m per decade, possibly due to reduced chilling at low elevations and improved efficiency of spring forcing in advancing the leaf unfolding at high elevations, the latter being caused by increased chilling. Our results suggest that due to both different temperature changes at the different altitudes, and the different tree responses to these changes, the tree phenology has shifted at different rates leading to a more uniform phenology at different altitudes during recent decades. [ABSTRACT FROM AUTHOR]