Air Temperature Lapse Rates Research Articles

The relationship between elevation-dependent warming and long-term trend of surface air temperature lapse rate

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 (IEDW) 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 (kSATLR¯) was calculated and analyzed. Both observed data and simulation experiment revealed that there was not significant difference between IEDW and −kSATLR¯, 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.

Temporal variability in air temperature lapse rates across the glacierised terrain of the Chandra basin, western Himalaya

Temporal variability in air temperature lapse rates across the glacierised terrain of the Chandra basin, western Himalaya

Long-term trend of near-surface air temperature lapse rate over the Chinese mainland during 1961-2018

The near-surface air temperature lapse rate (SATLR) is a result of surface energy balance, and the long-term trend of SATLR is linked to elevation-dependent warming (EDW). The long-term trend of SATLR in China’s mainland was examined in the present study. It was found that the regional average values of annual, autumn, and winter SATLR anomalies in Tmean, Tmax, and Tmin decreased significantly during the period of 1961-2018. In terms of spatial distribution, most of the annual SATLR trends in Tmean across China’s mainland are negative. In spring, positive SATLR trends in Tmean are widespread in the northern mountainous areas of China, while in winter, strong negative trends are found in some areas of the central and eastern parts of the Tibetan Plateau and the Yunnan-Guizhou Plateau. Most of the negative annual SATLR trends in Tmax occur in the central part of China, but in the southwestern part of China for Tmin. Widespread negative SATLR trends in Tmin are usually found in winter, especially in the Hengduan Mountains of Southwestern China and the eastern part of the Tibetan Plateau. The significant positive SATLR trends in Tmax are observed in spring, mostly distributed in northern mountainous areas. In the context of global and regional warming, the long-term trend of SATLR has the potential to detect differences in altitude responses to climate change on a small spatial scale, and to explore the local effect of EDW.

Investigating the Effect of Fuel Moisture and Atmospheric Instability on PyroCb Occurrence over Southeast Australia

The incidence of pyro-cumulonimbus (pyroCb) caused by extreme wildfires has increased markedly in Australia over the last several decades. This increase can be associated with a dangerous escalation of wildfire risk and severe stratospheric pollution events. Atmospheric and fuel conditions are important influences on pyroCb occurrence, but the exact causal relationships are still not well understood. We used the Continuous Haines Index (C-Haines) to represent atmospheric instability and the Fuel Moisture Index (FMI) to represent fuel moisture to provide better insight into the effects of atmospheric and fuel conditions on pyroCb occurrence over southeast Australia. C-Haines and FMI were related to the probability of pyroCb occurrence by employing a logistic regression on data gathered between 1980 and 2020. Emphasis is placed on investigating the independent effects and combined effects of FMI and C-Haines, as well as assessing their potential to predict whether a pyroCb develops over a fire. The main findings of this study are: (1) high C-Haines and low FMI values are representative of favorable conditions for pyroCb occurrence, but C-Haines can offset the effect of FMI—the addition of C-Haines to the logistic model muted the significance of FMI; (2) among the components of C-Haines, air temperature lapse rate (CA) is a better predictor of pyroCb occurrence than the dryness component (CB); (3) there are important regional differences in the effect of C-Haines and FMI on pyroCb occurrence, as they have better predictive potential in New South Wales than in Victoria.

Estimation of Near-Surface Air Temperature Lapse Rate Based on MODIS Data Over the Tibetan Plateau

Near-surface air temperature lapse rate (NSATLR) is one of the key criteria for judging atmospheric stability. It is an important model parameter in glacier, hydrology, ecology, climate and meteorology in high mountains such as the Tibetan Plateau (TP). However, due to the complex interaction between the atmosphere and land surface, retrieving NSATLR from remotely sensed data is challenging. In this study, we develop a novel model based on the MODIS data to estimate the daily 5-km NSATLR over the TP. The input parameters of the model include DEM and the near-surface air temperature (NSAT) estimated from the MODIS data. By combining moving window and specified criteria, the pixel-based NASTLR with a 5-km spatial resolution over the TP is estimated. In addition, we also estimate the NSATLR based on the meteorological data over the TP (NSATLR <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in-situ</sub> ) to evaluate the accuracy of NSATLR estimation model. Results demonstrate that the NSATLR estimate agrees well with NSATLR <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in-situ</sub> in the eastern TP, with an overall root mean square error (RMSE) of 1.51°C/km and a mean bias error (MBE) of -0.78°C/km. Larger deviation exists in the southern TP. Thanks to the evident advantages of simplicity, the availability of input parameters and the independence from the meteorological data, the developed model can be applied to larger areas.

Altitudinal and Temporal Variations of Near-Surface Air Temperature Lapse Rate on the Northern Slope of the Tianshan Mountains

Abstract Near-surface air temperature lapse rate (NSATLR) is vital for hydrological simulation and mountain climate research in snowmelt-dominated regions. In this study, NSATLRs of two vertical zones (i.e., mountain grassland–coniferous forest belt and alpine meadow belt) of the Manasi River basin on the northern slope of the Tianshan Mountains were calculated using the near-surface air temperature data from 18 observation stations. Furthermore, temporal variations of NSATLRs of these two vertical zones at seasonal, monthly, and daily scales were analyzed, combined with altitudinal differences of local environments. The results show that the temporal variations of NSATLRs are different between these two vertical zones. The steepest monthly NSATLR occurs in July in the mountain grassland–coniferous forest belt and in April in the alpine meadow belt. In spring, summer, and autumn, the hourly NSATLRs in the mountain grassland–coniferous forest belt generally steepen with increasing solar radiation and vice versa, contrary to those in the alpine meadow belt. During winter, the hourly NSATLRs on sunny days are overall positive at night but negative during the day in the mountain grassland–coniferous forest belt. The findings of this study indicate that it is necessary to divide mountains with similar local environments to the study area into different vertical zones to accurately estimate NSATLR, and the use of a fixed NSATLR for different months and vertical zones is not suitable for snowmelt runoff modeling in snow-dominated regions such as the northern slope of the Tianshan Mountains. Significance Statement This study aims to investigate the altitudinal and temporal variations of near-surface air temperature lapse rate (NSATLR) on the northern slope of the Tianshan Mountains and how mountain environments affect NSATLR. This is important because altitudinal differences of mountain environments lead to different NSATLRs, and these altitudinal variations on the northern slope of the Tianshan Mountains are different from those on the Alps at the same latitude. Our results explain how altitudinal differences of mountain environments affect NSATLRs; hence, using a fixed NSATLR for different months and vertical zones is inappropriate, and estimating NSATLRs for different vertical zones is necessary.

Temperature lapse rate estimation and snowmelt runoff simulation in a high-altitude basin

As a key parameter of hydrological process modeling, the near-surface air temperature lapse rate reflects the vertical changes in air temperature characteristics in alpine basins but often lacks the support of sufficient ground observation data. This study estimated the lapse rate of the Lhasa River Basin (LRB) from the monthly air temperature dataset (2001–2015), which was derived based on good relationships between the observed air temperature at eight gauged stations and the corresponding gridded land surface temperature of MODIS. The estimated annual average air temperature lapse rate was approximately 0.62 °C/100 m. The monthly lapse rate in different years varied seasonally in the range of 0.45–0.8 °C/100 m; the maximum was in May, and the relatively low value occurred from September to January. The snow cover in the zones with relatively low altitudes showed seasonal variation, which was consistent with the air temperature variation. Permanent snow cover appeared in the area above 5000 m and expanded with increasing elevation.

Diurnal Variation in Cloud and Precipitation Characteristics in Summer over the Tibetan Plateau and Sichuan Basin

The diurnal variation in precipitation and cloud parameters and their influencing factors during summer over the Tibetan Plateau (TP) and Sichuan Basin (SB) were investigated using the Hydro-Estimator satellite rainfall estimates, ground observations, and ERA5 dataset. The precipitation and cloud parameters show diurnal propagation over the SB during the mei-yu period in contrast to such parameters over the TP. The diurnal maximum precipitation from the Hydro-Estimator satellite and cloud ice and liquid water content (cloud LWC and IWC) from the ERA5 dataset are concentrated in the early evening, while their diurnal minimums manifest in the morning. Cloud LWC accounts for more than 60% of the total water during almost the entire diurnal cycle over the inner TP and SB during the mei-yu period. The IWC accounts for more than 60% of the total water in the late afternoon over the edge of the SB and TP. The cloud base height (CBH) above ground level (AGL), the lifting condensation level (LCL) AGL, and the zero degree level AGL are almost equal over the TP during the summer period. The zero degree level AGL over the SB is higher than that over the TP because the air temperature lapse rate over the TP is larger. The thickness of liquid water cloud over the SB is larger than that over the TP. The correlation analysis shows that the CBH AGL and LCL AGL over the TP are related to the dewpoint spread, but less so over the SB because of the stronger turbulence and lower air density over the TP than the SB. Convective available potential energy has a larger impact on precipitation over the TP than the SB. The cloud LWC makes a larger contribution to the precipitation over the SB than over the TP, which is related to the mean zonal wind and diurnal cycle of low-level winds. The precipitation at the edge of the TP and SB (i.e., the steep downstream slope) is largely influenced by the ice water contained within clouds owing to the convergence rising motion over the slopes.

Modelling surface temperature and radiation budget of snow-covered complex terrain

Abstract. The surface temperature controls the temporal evolution of the snowpack, playing a key role in metamorphism and snowmelt. It shows large spatial variations in mountainous areas because the surface energy budget is affected by the topography, for instance because of the modulation of the short-wave irradiance by the local slope and the shadows and the short-wave and long-wave re-illumination of the surface from surrounding slopes. These topographic effects are often neglected in large-scale models considering the surface to be flat and smooth. Here we aim at estimating the surface temperature of snow-covered mountainous terrain in clear-sky conditions in order to evaluate the relative importance of the different processes that control the spatial variations. For this, a modelling chain is implemented to compute the surface temperature in a kilometre-wide area from local radiometric and meteorological measurements at a single station. The first component of this chain is the Rough Surface Ray-Tracing (RSRT) model. Based on a photon transport Monte Carlo algorithm, this model quantifies the incident and reflected short-wave radiation on every facet of the mesh describing the snow-covered terrain. The second component is a surface scheme that estimates the terms of the surface energy budget from which the surface temperature is eventually estimated. To assess the modelling chain performance, we use in situ measurements of surface temperature and satellite thermal observations (Landsat 8) in the Col du Lautaret area, in the French Alps. The results of the simulations show (i) an agreement between the simulated and measured surface temperature at the station for a diurnal cycle in winter within 0.2 ∘C; (ii) that the spatial variations in surface temperature are on the order of 5 to 10 ∘C in the domain and are well represented by the model; and (iii) that the topographic effects ranked by importance are the modulation of solar irradiance by the local slope, followed by the altitudinal variations in air temperature (lapse rate), the re-illumination by long-wave thermal emission from surrounding terrain, and the spectral dependence of snow albedo. The changes in the downward long-wave flux because of variations in altitude and the absorption enhancement due to multiple bounces of photons in steep terrain play a less significant role. These results show the necessity of considering the topography to correctly assess the energy budget and the surface temperature of snow-covered complex terrain.

Mapping Threats of Spring Frost Damage to Tea Plants Using Satellite-Based Minimum Temperature Estimation in China

Spring frost damage (SFD), defined as the disaster during the period of newly formed tea buds in spring caused by lower temperature and frost damage, is a particular challenge for tea plants (Camellia sinensis), whose capacity to adapt to extreme weather and climate impacts is limited. In this paper, the region of the Middle and Lower Reaches of the Yangtze River (MLRYR) in China was selected as the major tea plantation study area, and the study period was focused on the concentrated occurrence of SFD, i.e., from March to April. By employing the standard lapse rate of air temperature with elevation, a minimum temperature (Tmin) estimation model that had been previously established was used based on reconstructed MYD11A1 nighttime LST values for 3 × 3 pixel windows and digital elevation model data. Combined with satellite-based Tmin estimates and ground-based Tmin observations, the spatiotemporal characteristics of SFD for tea plants were systematically analyzed from 2003 to 2020 in the MLRYR. The SFD risks at three scales (temporal, spatial, and terrain) were then evaluated for tea plants over the MLRYR. The results show that both SFD days at the annual scale and SFD areas at the daily scale exhibited a decreasing trend at a rate of 2.7 days/decade and 2.45 × 104 ha/day, respectively (significant rates at the 0.05 and 0.01 levels, respectively). The period with the highest SFD risk appeared mainly in the first twenty days of March. However, more attention should be given to the mid-to-late April time period due to the occurrence of late SFD from time to time. Spatially, areas with relatively higher SFD days and SFD risks were predominantly concentrated in the higher altitude areas of northwestern parts of MLRYR for both multi-year averages and individual years. Fortunately, in regions with a higher risk of SFD, the distribution of tea plants was relatively scattered and the area was small. These findings will provide helpful guidance for all kinds of people, including government agencies, agricultural insurance agencies, and tea farmers, in order that reasonable and effective strategies to reduce losses caused by spring frost damage to tea plants may be recommended and implemented.

Combining sparse observations and reanalysis data for refining spatiotemporal variability in near‐surface air temperature lapse rates over China

AbstractUneven and sparse surface air temperature (Ta) observations challenge the understanding of the atmosphere‐land interactions and global environmental changes. Lapse rate () is thought of with great potential to obtain accurate long‐term and high‐resolution Ta dataset. However, previous studies on over China were solely based on observed data, which limited our understanding since few stations are distributed in western China. In this study, an improved procedure for estimating by combining sparse observations and newly released ERA5 reanalysis data was proposed. The spatial heterogeneity in over China and its influencing factors (e.g., topography, climate, and vegetation) were then explored. A re‐examination of long‐term spatiotemporal variations in and its potential driving forces over China was also performed at grid scales. The results demonstrated that our estimations reproduced similar patterns to those derived from observations. The subsequent analyses revealed that the annual and seasonal variability in varied substantially among different altitude gradients, land cover types, and climate zones. The vital role played by vegetation covers in regulating local was emphasized in this study, which was poorly assessed previously. Moreover, in low altitude zones showed lower values but strong temporal fluctuations and contributed more to the interannual variability in over China, which could be mainly attributed to human activities. The present findings can provide an alternative method for estimating and be further used to assess regional or global temperature changes.

Spring Frost Damage to Tea Plants Can Be Identified with Daily Minimum Air Temperatures Estimated by MODIS Land Surface Temperature Products

Tea (Camellia sinensis) is one of the most dominant economic plants in China and plays an important role in agricultural economic benefits. Spring tea is the most popular drink due to Chinese drinking habits. Although the global temperature is generally warming, spring frost damage (SFD) to tea plants still occurs from time to time, and severely restricts the production and quality of spring tea. Therefore, monitoring and evaluating the impact of SFD to tea plants in a timely and precise manner is a significant and urgent task for scientists and tea producers in China. The region designated as the Middle and Lower Reaches of the Yangtze River (MLRYR) in China is a major tea plantation area producing small tea leaves and low shrubs. This region was selected to study SFD to tea plants using meteorological observations and remotely sensed products. Comparative analysis between minimum air temperature (Tmin) and two MODIS nighttime land surface temperature (LST) products at six pixel-window scales was used to determine the best suitable product and spatial scale. Results showed that the LST nighttime product derived from MYD11A1 data at the 3 × 3 pixel window resolution was the best proxy for daily minimum air temperature. A Tmin estimation model was established using this dataset and digital elevation model (DEM) data, employing the standard lapse rate of air temperature with elevation. Model validation with 145,210 ground-based Tmin observations showed that the accuracy of estimated Tmin was acceptable with a relatively high coefficient of determination (R2 = 0.841), low root mean square error (RMSE = 2.15 °C) and mean absolute error (MAE = 1.66 °C), and reasonable normalized RMSE (NRMSE = 25.4%) and Nash–Sutcliffe model efficiency (EF = 0.12), with significantly improved consistency of LST and Tmin estimation. Based on the Tmin estimation model, three major cooling episodes recorded in the "Yearbook of Meteorological Disasters in China" in spring 2006 were accurately identified, and several highlighted regions in the first two cooling episodes were also precisely captured. This study confirmed that estimating Tmin based on MYD11A1 nighttime products and DEM is a useful method for monitoring and evaluating SFD to tea plants in the MLRYR. Furthermore, this method precisely identified the spatial characteristics and distribution of SFD and will therefore be helpful for taking effective preventative measures to mitigate the economic losses resulting from frost damage.

Application of geographically weighted regression model in the estimation of surface air temperature lapse rate

The surface air temperature lapse rate (SATLR) plays a key role in the hydrological, glacial and ecological modeling, the regional downscaling, and the reconstruction of high-resolution surface air temperature. However, how to accurately estimate the SATLR in the regions with complex terrain and climatic condition has been a great challenge for researchers. The geographically weighted regression (GWR) model was applied in this paper to estimate the SATLR in China’s mainland, and then the assessment and validation for the GWR model were made. The spatial pattern of regression residuals which was identified by Moran’s Index indicated that the GWR model was broadly reasonable for the estimation of SATLR. The small mean absolute error (MAE) in all months indicated that the GWR model had a strong predictive ability for the surface air temperature. The comparison with previous studies for the seasonal mean SATLR further evidenced the accuracy of the estimation. Therefore, the GWR method has potential application for estimating the SATLR in a large region with complex terrain and climatic condition.

Best practices for estimating near‐surface air temperature lapse rates

AbstractThe near‐surface air temperature lapse rate is the predominant source of spatial temperature variability in mountains and controls snowfall and snowmelt regimes, glacier mass balance, and species distributions. Lapse rates are often estimated from observational data, however there is little guidance on best practices for estimating lapse rates. We use observational and synthetic datasets to evaluate the error and uncertainty in lapse rate estimates stemming from sample size, dataset noise, covariate collinearity, domain selection, and estimation methods. We find that lapse rates estimated from small sample sizes (&lt;5) or datasets with high noise or collinearity can have errors of several °C km−1. Uncertainty in lapse rates due to non‐elevation related large‐scale temperature variability was reduced by correcting for spatial temperature gradients and restricting domains based on spatial clusters of stations. We generally found simple linear regression to be more robust than multiple linear regression for lapse rate estimation. Finally, lapse rates had lower error and uncertainty when estimated from a sample of topoclimatically self‐similar stations. Motivated by these results, we outline a set of best practices for lapse rate estimation that include using quality controlled temperature observations from as many locations as possible within the study domain, accounting for and minimizing non‐elevational sources of climatic gradients, and calculating lapse rates using simple linear regression across topoclimatically self‐similar samples of stations which are roughly 80% of the station population size.

Air temperature lapse rates and cloud cover in a hyper-oceanic climate

AbstractAir temperature lapse rates vary geographically and temporally. Sub-Antarctic Macquarie Island provides an opportunity to compare lapse rates between windward and leeward slopes in a hyper-oceanic climate. Lapse rates were steep by global standards, typically close to the dry adiabatic lapse rate despite the near-constant high humidity. Limited diurnal and seasonal variation occurs in lapse rates on Macquarie Island. High variability of lapse rates on the eastern (lee) slope in summer months and in the midday hours appears to be driven by solar radiation. No diurnal or seasonal pattern was evident on the western slope. Development of orographic cloud is expected to modify lapse rates, given the theoretical shift between dry and saturated adiabatic lapse rates that occurs with condensation of water vapour. Cloud cover was frequent, with higher elevations being under cloud 50% of the time, with no seasonal variation. However, cloud base level did not explain variation in lapse rates. Low cloud is likely to be of ecological importance because it influences fog precipitation, solar radiation and evapotranspiration. Year-round dominance of westerly airflows and limited seasonal variation in air temperature and humidity explain the limited seasonal variation in cloud cover and lapse rates on Macquarie Island.

Maximum and minimum air temperature lapse rates in the Andean region of Ecuador and Peru

AbstractTo know the vertical distribution of air temperature is complex, and this is necessary for different applications. The main explanatory variable of air temperature is elevation above sea level, whose relationship with air temperature is measured by air temperature lapse rates (LRs). LRs can vary considerably spatiotemporally due to a wide spectrum of geographical, environmental, and other atmospheric factors. Our study presents the first comprehensive assessment of spatiotemporal changes of LRs over the Tropical Andes. Our study is focused on the Peruvian and Ecuadorian Andes, divided in two subregions by the parallel 9.5° (i.e., north and south). Maximum and minimum air temperatures were employed from 115 quality checked weather stations, for the period 1994–2011. Maximum (LRmax) and minimum (LRmin) air temperature lapse rates have been calculated for the whole study period. The effects of seasonality, humidity content and ENSO on the variability of LRs have been analysed. Results show that LRs have large spatiotemporal variability, since references values of LRmax range from −3.57 (South, dry season) to −4.77 (North, wet season), and LRmin range from −3.78 (North, dry season) to −4.93°C·km−1 (South, dry season), in function of season and subregion. Results indicate that the ENSO phases contribute significantly to the variability of southern subregion LRs. This study also presents that minimum air temperatures were more unpredictable than maximum air temperatures in terms of error and uncertainty, as a consequence of the larger spatial variability of nocturnal air temperatures, mainly influenced by local topography. In conclusion, this work goes deeper into the need to obtain precise LRs adapted to the study region, and shows that the use of standard LR values can cause significant failures in modelling air temperature in regions of complex terrain, such as the Andes.

Impacts of Hydrological Processes on Stream Temperature in a Cold Region Watershed Based on the SWAT Equilibrium Temperature Model

Variance in stream temperature from historical norms, which reflects the impacts from both hydrological and meteorological factors, is a significant indicator of the stream ecosystem health. Therefore, it is imperative to study the hydrological processes controlling stream temperature in the watershed. The impacts of hydrological processes on stream temperature in the cold region of Western Canada were investigated based on the previously developed Soil and Water Assessment Tool (SWAT) equilibrium temperature model. The model was calibrated and validated for streamflow and stream temperature based on the observations and a global parameter sensitivity analysis conducted to identify the most important hydrological process governing the stream temperature dynamics. The precipitation and air temperature lapse rates were found to be the most sensitive parameters controlling the stream temperature, followed by the parameters regulating the processes of soil water dynamics, surface runoff, and channel routing. Our analysis showed an inverse relationship between streamflow volume and stream temperature, and different runoff components have different impacts on temporal regimes of stream temperatures. This study elaborates on the response of the stream temperature to changes in hydrological processes at the watershed scale and indicates that hydrological processes should be taken into account for prediction of stream temperatures.

Topographic and climatic influence on seasonal snow cover: Implications for the hydrology of ungauged Himalayan basins, India

Himalayan glaciers exert considerable influence on basin hydrology and its response to climate change. Melt-runoff generated from ungauged Himalayan basins (UHB) requires an understanding of snow and ice cover extent along with prevailing meteorological conditions. Therefore, an estimation of seasonal snow cover distribution, topographic (elevation, aspect, and slope) and climatic variability was carried out using satellite data and meteorological observations from three automatic weather stations (AWSs) located at different elevations in an UHB (Chorabari Glacier). Results suggest that the topography and the meteorological conditions of the basin influence the dynamics of snow cover and the corresponding processes responsible for the melt-runoff generation. The snow cover area (SCA) has high variability in the elevation range of 3799–5000 m, indicating that as glacier ablation begins, SCA below this elevation primarily contributes to the melt-runoff. Likewise, the eastern aspect and the slopes (0–10° and 70–80°) show higher variability. Further, the annual distribution of air temperature gradients (dT/dZ) or temperature lapse rates (TLRs) exhibits a bimodal pattern. The mean annual TLR for the basin is 6.0 °C km−1, which is lower than the traditionally used adiabatic or environmental lapse rate (6.5 °C km−1). We also established the role of TLRs in the dynamics of SCA, which is an important parameter used for the computation of melt-runoff. The 0 °C isotherm established indicates that the elevation zone above 5000–5500 m has persistent snow cover throughout the year and snow cover below this zone contributes to the melt-runoff during the ablation season. Therefore, validating the equilibrium line altitude (ELA) of Chorabari Glacier lies within this zone. Since the TLR and SCA vary with space and time, our study in an ungauged glacierized basin of river Ganga could be useful for policymakers as well as other researchers working on the regional hydrology.

Elevational patterns of temperature and humidity in the middle Tianshan Mountain area in Central Asia

The vertical distribution of vegetation types along an elevational gradient in mountain areas largely depends on the elevational changes in air temperature and humidity. In this study, we presented the seasonal and diurnal variations in the elevational gradients of air temperature and humidity on the southern and northern slopes in the middle Tianshan Mountain Range using data collected throughout the year via HOBO data loggers. The measurements were conducted at 12 different elevations from 1548 to 3277 m from September 2004 to August 2005. The results showed that the annual mean air temperature decreased along the elevational gradients with temperature lapse rates of (0.71±0.20)°C/100 m and (0.59±0.05)°C/100 m on the northern and southern slopes, respectively. The annual mean absolute humidity significantly decreased with increasing elevation on the northern slope but showed no significant trend on the southern slope. The annual mean relative humidity did not show a significant trend on the northern slope but increased with increasing elevation on the southern slope. The mean air temperature lapse rate exhibited significant seasonal variation, which is steeper in summer and shallower in winter, and this value varied between 0.37°C/100 m and 0.75°C/100 m on the southern slope and between 0.30°C/100 m and 1.02°C/100 m on the northern slope. The mean absolute and relative humidity also exhibited significant seasonal variations on both slopes, with the maximum occurring in summer and the minimum occurring in winter or spring. The monthly diurnal range of air temperature on both slopes was higher in spring than in winter. The annual range of air temperature on the southern slope was higher than that on the northern slope. Our results suggest that significant spatiotemporal variations in humidity and temperature lapse rate are useful when analyzing the relationships between species range sizes and climate in mountain areas.

Spatial Patterns and Trends in Surface Air Temperatures and Implied Changes in Atmospheric Moisture Across the Hawaiian Islands, 1905–2017

AbstractWhile the Hawaiian Islands are experiencing long‐term warming, spatial and temporal patterns are poorly characterized. Drawing on daily temperature records from 309 stations (1905–2017), we explored relationships of surface air temperatures (Tmax, Tmin, Tavg, and diurnal temperature range) to atmospheric, oceanic, and land surface variables. Statistical modeling of spatial patterns (2006–2017) highlighted the strong negative influence of elevation and moisture on air temperature and the effects of distance inland, cloud frequency, wind speed, and the local trade wind inversion on the elevation dependence of surface air temperature. We developed time series of sea level air temperature and surface lapse rate by modeling surface air temperature as a simple function of elevation and found a strong long‐term (1905–2017) warming trend in sea level Tmin, twice that of Tmax (+0.17 vs +0.07°C/decade), suggesting regional warming, possibly enhanced by urbanization and cloud cover effects. Removing this trend, sea level Tmax and Tmin tracked SST and rainfall at decadal time scales, while Tmax increased with periods of weakened trade winds. Sea level air temperatures correlated with North Pacific climate indices, reflecting the influence of regional circulation via SST, rain, clouds, and trade winds that modulate environmental warming across the Hawaiian Islands. Increasing (steeper) Tmax surface lapse rates for the 0‐ to 1,600‐m elevation range (into the cloud zone) over 1978–2017 coincide with observations of marine boundary layer drying and rising cloud base heights, suggesting a need to better understand elevation‐dependent warming in this tropical/subtropical maritime environment and associated changes to cloud formation and persistence.