Air Temperature Lapse Rates Research Articles

Temperature and thermal growing season variations along elevational gradients on a sub-alpine, temperate China

Fully and accurately studying temperature variations in montane areas are conducive to a better understanding of climate modeling and climate-growth relationships on regional scales. To explore the spatio-temporal changes in air and soil temperatures and their relationship in montane areas, on-site monitoring over 2 years (2015 and 2016) was conducted at nine different elevations from 2040 to 2740 m a.s.l. on Luya Mountain in the semiarid region of China. The results showed that the annual mean of air temperature lapse rate (ATLR) was 0.67 °C/100 m. ATLR varied obviously in different months within a range of 0.57~0.79 °C/100 m. The annual mean of the soil temperature lapse rate (STLR) was 0.48 °C/100 m. Seasonally, monthly mean soil temperature did not show a consistent pattern with regard to elevation. The relationships between air and soil temperatures showed piecewise changes. Soil was decoupled from the air temperature in cold winter and early spring. The parameters of the growing season based on the two temperature types had no corresponding relations, and seasonal mean of soil temperature showed the smallest value at mid-elevation rather than in the treeline ecotone. Based on these changes, our results emphasized that altitudinal and seasonal variability caused by local factors (such as snow cover and soil moisture) should be taken into full consideration in microclimate extrapolation and treeline prediction in montane areas, especially in relation to soil temperature.

Near surface air temperature lapse rates over complex terrain: a WRF based analysis of controlling factors and processes for the central Himalayas

Various environmental processes are strongly controlled by spatio-temporal variations of surface air temperature (hereafter temperature) in complex terrain. However, the usually scarce network of observations in high mountain regions does not allow for an investigation of the relevant micro-meteorological processes that result in complex temperature fields. Climate impact studies often utilize a constant lapse rate of temperature (LRT hereafter) in order to generate spatially distributed temperature data, although it is well acknowledged that LRTs feature a pronounced variability at spatial, seasonal, and diurnal scales. In this study, the Weather Research and Forecasting (WRF) model is used to understand the factors and processes influencing temperature and LRT in the Khumbu and Rolwaling regions of the central Himalayas. A high resolution simulation is performed for one complete year (June 2014–May 2015) in order to capture the entire seasonal cycle. To test the model response to land cover and terrain characteristics, additional simulations with adjusted surface conditions are conducted. Our results demonstrate the capability of WRF to reproduce the processes controlling LRT, although an LRT bias is detected during non-monsoon seasons. The simulated temperature fields feature two LRT minima (i.e. low temperature decrease with elevation) during Nov–Dec and monsoon season, and two LRT maxima (strong temperature decrease with elevation) during the early post-monsoon and pre-monsoon seasons. A steeper LRT (i.e. a rapid decrease of temperature with elevation) is found at high elevations (> 4500 m) while shallower LRT values (i.e. a slower decrease or even increase of temperature with elevation) are apparent at lower elevations. During the pre-monsoon season, high net insolation rates and a reduced latent heat loss from snow free surfaces cause strong sensible heating at low elevations, while the presence of snow at high elevations leads to reduced sensible heating. This strong contrast results in steeper LRT values. Early post-monsoon shows similar characteristics but with a reduced magnitude. The shallow LRT during monsoon season is shown to be caused by the large-scale moisture supply and the associated latent heat release at the Himalayan slopes. This effect is further intensified due to strong up-valley winds which contribute to a well-mixed troposphere. Temperature inversions associated with cold air pooling cause shallow LRT values in lower river valleys during Nov–Dec. The results suggest that the identified processes should be considered for downscaling applications, particularly if distributed temperature fields are required for climate impact investigations.

Identification of homogeneous regions of near surface air temperature lapse rates across India

Spatial variation of near surface temperature lapse rate is usually analysed by subjectively dividing the study area in to different sub‐regions based on political or physiographic boundaries. This can often lead to unreliable results as near surface temperature lapse rate largely depends on regional conditions. In this study, homogeneous regions of near surface air temperature lapse rate across India have been identified for monthly mean minimum, mean, and mean maximum temperature using a probabilistic Gaussian mixture model clustering approach. For the delineated regions, lapse rates are estimated using weighted linear regression model. The weights corresponding to each station were obtained from the clustering approach. Results indicate that regions with uniform lapse rate vary across different months and a minimum of three regions is obtained for maximum temperature in April month. Further, temperature lapse rate estimates exhibit spatial and temporal variability, and are less steep than the Environmental lapse rate (−6.5°C/km). The maximum spatial variability in lapse rate is observed in May for both maximum and minimum temperature. The delineation of entire India into homogeneous regions improves temperature interpolation when compared to results obtained by considering entire India as one region. A maximum improvement of 34% in root mean square error is observed in prediction of monthly mean temperature in March. The identified regions and the associated lapse rates are expected to improve the prediction of near surface temperature at ungauged locations across India.

Trends of Southern Appalachian Seasonal Air Temperature and Regional Lapse Rate Spanning 1969–2018

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.

Toward modeling the spatial pressure field of tropical cyclones: Insights from Typhoon Hato (1713)

Information about the pressure field of tropical cyclones (TCs) is of crucial importance for determining a TC's wind structure. However, despite the fact that TC pressure deficit (ΔP) decreases with increasing height below a TC's outflow layer, most existing models focus only on the radial distribution of TC pressure. Quantitative studies on the spatial pressure field of TCs are considerably limited. This study presents a field study on the vertical pressure profiles of Typhoon Hato which is one of the few strongest sampled TCs in Hong Kong. Meteorological observations from eight radiosonde balloons released at different storm-relative positions during Hato's passage are investigated. Results show that the vertical profiles of ΔP below the outflow layer are distributed linearly with respect to altitude, with the slope increasing almost linearly with the increase of surface pressure deficit. Based on the above observation, an empirical model of the typhoon's spatial pressure field is established. Budget analysis of ΔP is then conducted. Both the dry-air component and water-vapor component are found to be evident. This study further presents an analytical model of TC pressure deficit. Comparison of results with various values of key input model parameters show that the model prediction is highly sensitive to the lapse rate of atmospheric temperature and surface air temperature. It is believed that both the empirical model and the analytical model have the potential to facilitate the development of TC spatial wind-field models.

Insect-flower interaction networks vary among endemic pollinator taxa over an elevation gradient.

Interaction networks are sensitive to elevation gradients through changes in local distribution of interacting partners. Here, we use plant-pollinator interaction network metrics to assess the effect of elevation on flowers and flower-visiting insect assemblages on a sentinel mountain used for monitoring climate change in the flower- and insect-rich Cape Floristic Region. We also use these interaction metrics to explain the effect of environmental factors on the interaction networks. We did this over four vegetation zones <1640m asl, as determined by former botanical studies. Overall, bees were the dominant flower visitors, followed by monkey beetles, and far behind were wasps and flies. The middle elevation zone (650–744 m a.s.l), which is also an ecotone between two distinct botanical zones, had the highest species richness and abundance of interacting plants and insects. Interaction frequency and size of network were also greatest in the middle zone, as were network diversity, generality, and linkage density, while lowest in the peak zone. In sum, there was distinct elevation zoning of flower-visiting insects. The greatest zonal change was between species at the middle compared with peak zone. Large-sized monkey beetles, bees and flies characterized the unique assemblage in the peak zone (1576–1640 m a.s.l.). The insect zonation tracked that of plant assemblages, with air temperature (lapse rate) being the primary driver of bee distribution, with lowest levels in the peak zone. In contrast, beetle distribution was driven mostly by flower assemblages as well as air temperature. In turn, wasp and fly interaction networks were not affected by any of the measured environmental variables. We conclude that increased elevation stress from reduced temperatures, changing abiotic weather conditions (e.g. strong winds at high elevations),and decline in flowering plant composition causes breakdown of interaction networks involving bees and beetles but not that of flies and wasps.

Temperature change along elevation and its effect on the alpine timberline tree growth in the southeast of the Tibetan Plateau

Smith fir (Abies georgei var. smithii), which is the timberline constructive tree species in the cool slope of Mt. Sygera in the southeast of Tibet, plays a very important role in maintaining the timberline completeness and indicating global climate change. This study uses the instrumental recorded meteorological data along the altitude from 3600 to 4400 m at every 200 m in the growing season, investigates the smith fir growth biomass from 2006 to 2010 in the same timberline ecotone, and makes a non-linear regression analysis to determine the relationship between the alpine tree growth biomass and its in-situ environment condition. The results showed that the cool and warm slope share different air temperature lapse rates, which were −0.48 °C (100 m)−1 in the warm slope and −0.54 °C (100 m)−1 in the cool slope, respectively. However, the dominant timberline tree species in the warm slope was Sabina saltuaria, and it can reach as high as 4570 m, which is approximately 170 m higher than that in the cool slope. Moreover, the smith fir in the cool slope was only distributed in the range of elevation from approximately 3600 to 4400 m. The altitude of approximately 3800 m was the appropriate altitude for the growing smith fir, where the mean air temperature in the growing season was about 9.0 °C, and the young smith fir tree can form more biomass. The results suggested that alpine forest chose a suitable environment where trees can grow more in the prolonged succession, but not in the warmer or cooler condition, it could be seen as a biological evidence for climate change.

How Accurately Can the Air Temperature Lapse Rate Over the Tibetan Plateau Be Estimated From MODIS LSTs?

AbstractThe air temperature lapse rate (TLR) is a key parameter for interpolating air temperature data in high mountainous regions such as the Tibetan Plateau (TP). The Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) has been frequently used for estimating air temperature during the past decade, but its performance in estimating the TLR in the TP has seldom been investigated. This study employed two methods in estimating the TLR based on MODIS LSTs compared with the “observed” TLR derived from 86 stations across the TP. The two methods include a method for directly computing the lapse rate from MODIS LST (DFM) and a second method for calculating the lapse rate of estimated air temperatures based on air temperature estimation from MODIS LST (TEM). The results show that the MODIS LST‐estimated TLR for daily mean air temperature (Tmean) using both DFM and TEM is more accurate than that for daily minimum and maximum air temperatures. When using MODIS nighttime LSTs, both DFM and TEM show acceptable accuracies for estimating the TLR of Tmean with averaged root‐mean‐square deviations of 0.21 and 0.19 °C/100 m, respectively. The spatial and seasonal patterns of MODIS LST‐estimated TLRs of Tmean from both DFM and TEM are found to be highly consistent with the observed TLRs. This study can help alleviate the data‐sparse problem in downscaling air temperature or hydrological modeling studies in ungauged areas, especially for the western TP where station data are extremely scarce.

Estimation of near‐surface air temperature lapse rates over continental Spain and its mountain areas

Although the mean environmental lapse rate (MELR) value (a linear decrease of −6.5 °C/km) is the most widely used, near‐surface (i.e., non‐free atmosphere) air temperature lapse rates (NSLRs; measured at ~1.5 m height) are variable in space and time because of their dependence on topography and meteorological conditions. In this study we conducted the first analysis of the spatial and temporal variability of NSLRs for continental Spain and their relationship to synoptic atmospheric circulation (circulation weather types [CWTs]), focusing on major mountain areas including the Pyrenees, Cantabrian, Central, Baetic, and Iberian ranges.The results showed that the NSLR varied markedly at spatial and seasonal scales and depended on the dominant atmospheric conditions. The median NSLR values were weaker (less negative) than the MELR for the mountain areas (Pyrenees −5.17 °C/km; Cantabrian range −5.22 °C/km; Central range −5.78 °C/km; Baetic range −4.83 °C/km; Iberian range −5.79 °C/km) and for the entire continental Spain (−5.28 °C/km). For the entire continental Spain the steepest NSLR values were found in April (−5.80 °C/km), May (−5.58 °C/km), and October (−5.54 °C/km) because of the dominance of northerly and westerly advections of cold air. The weakest NSLR values were found in July (−4.67 °C/km) and August (−4.78 °C/km) because of the inland heating, and in winter because of the occurrence of thermal inversions. As the use of the MELR involves the assumption of large errors, we propose 1 zonal, 12 monthly, 11 CWTs, and 132 hybrid monthly–CWTs NSLRs for each of the mountain ranges and for the entire continental Spain. More regional studies are urgently needed to accurately assess the NSLR as a function of atmospheric circulation conditions.

Temporal and spatial changes in estimated near‐surface air temperature lapse rates on Tibetan Plateau

Lapse rate (LR) of near‐surface (2 m) air temperature is essential for determining spatially distributed and gridded air temperature interpolated from in situ observational sites. However, due to the limitation of sparse observational networks, high‐resolution LRs are not usually available on regional scales, especially in mountainous regions. The purpose of this study is to estimate LRs for the entire Tibetan Plateau (TP) using observed air temperature and moderate‐resolution imaging spectroradiometer (MODIS) night‐time land surface temperatures (LSTs) and to analyse the spatio‐temporal changes of the estimated LRs. First, diurnal cycles of LRs derived from in situ observations in three subregions of the TP were analysed, which shows that the LRs in the western and northeastern regions were shallow in the cold season and steep in the warm season, whereas the southeastern region exhibited a different pattern. Further comparisons revealed that the LRs for night‐time air temperatures better represented the LRs for daily mean air temperatures than the daytime ones, and the night‐time MODIS LSTs correlated well with the night‐time air temperatures, especially for the MODIS Terra data sets. Therefore, the night‐time MODIS LSTs from the Terra data sets were used to estimate high‐resolution (10 km) LRs for the daily mean temperatures over the entire TP. Estimated LRs over most areas of the TP were shallower than the commonly used environmental LR (−6.5 K/km). The LRs in the southeastern region were steeper than those in the northeastern region, while steeper LR values occurred in the northwestern region with lower temperatures and less humidity.

Air and wet bulb temperature lapse rates and their impact on snowmaking in a Pyrenean ski resort

A set of 17 air temperature and relative humidity sensors were used to analyze the temporal variability of surface air temperature (Tair), wet bulb temperature (Twb), and daily snowmaking hours (SM, number of hours per day with Twb < − 2 °C), lapse rates, and the occurrence of thermal inversions at the Formigal ski resort (Spanish Pyrenees) from December to March during three consecutive ski seasons (2012–2013, 2013–2014, and 2014–2015). The Tair and Twb lapse rates showed strong hourly and daily variability, with both exhibiting almost identical temporal fluctuations. The Twb exhibited average lapse rates that were slightly steeper (− 5.2 °C/km) than those observed for Tair (− 4.9 °C/km). The less steep lapse rates and most thermal inversions were observed in December. Days having less (more) steep Tair and Twb lapse rates were observed under low (high) wind speeds and high (low) relative humidity and air pressure. The temporal dynamics of the SM lapse rates was more complex, as this involved consideration of the average Tair in the ski resort, in addition to the driving factors of the spatio-temporal variability of Twb. Thus, on a number of cold (warm) days, snowmaking was feasible at all elevations at the ski resort, independently of the slopes of the lapse rates. The SM exhibited an average daily lapse rate of 8.2 h/km, with a progressive trend of increase from December to March. Weather types over the Iberian Peninsula tightly control the driving factors of the Tair, Twb, and SM lapse rates (wind speed, relative humidity, and Tair), so the slopes of the lapse rates and the frequency of inversions in relation to elevation for the three variables are very dependent on the occurrence of specific weather types. The less steep lapse rates occurred associated with advections from the southeast, although low lapse rates also occurred during advections from the east and south, and under anticyclonic conditions. The steepest Tair and Twb lapse rates were observed during north and northwest advections, while the steepest rates for SM were observed during days of cyclonic circulation and advections from the northeast.

Impact of summer monsoon on the elevation‐dependence of meteorological variables in the south of central Himalaya

ABSTRACTThe South Asian summer monsoon brings abundant precipitation and associated latent heat release to the south of central Himalaya, and alters hydrothermal conditions of this region. This study explored the impact of South Asian summer monsoon on the elevation‐dependence of meteorological variables along the south slope of Mt. Everest in the central Himalaya, which is crucial to modelling the glacio‐hydrological processes in this elevated region. The data were collected at five stations deployed at 2660–5600 m above sea level (asl) along the slope during 2007–2011. Major findings are the following: (1) The amount of precipitation during the monsoon season usually decreases with elevation but it is relatively uniform between 3600 and 5000 m asl. This uniform profile may be attributed to the monsoon–terrain–land interactions, particularly to the retard effect of glacier cooling on daytime upvalley wind; (2) Cloud shielding effects cause lower solar radiation and higher downward longwave radiation in the monsoon than in the other seasons. In particular, higher elevations have more clouds in the afternoon, resulting in an abnormal elevation‐dependence of solar radiation (i.e. higher elevations receive less solar radiation); (3) Strong daytime upvalley wind and moist convection homogenizes the vertical distributions of air mass along the slope, causing a constant lapse rate of both surface air temperature and dew‐point temperature (representing humidity) during typical monsoon months, but this phenomenon is not found in the other seasons. These findings provide critical guidance for extrapolating the meteorological variables from lower to higher elevations in this region.

A strategy to represent impacts of subgrid-scale topography on snow evolution in the Canadian Land Surface Scheme

ABSTRACTThis sensitivity study applies the offline Canadian Land Surface Scheme (CLASS) version 3.6 to simulate snowpack evolution in idealized topography using observations at Likely, British Columbia, Canada over 1 July 2008 to 30 June 2009. A strategy for a subgrid-scale snow (SSS) parameterization is developed to incorporate two key features: ten elevation bands at 100 m intervals to capture air temperature lapse rates, and five slope angles on four aspects to resolve solar radiation impacts on the evolution of snow depth and SWE. Simulations reveal strong elevational dependencies of snow depth and SWE when adjusting temperatures using a moist adiabatic lapse rate with elevation, with 26% peak SWE differences between that at the average elevation versus the mean of the remainder of the elevation bands. Differences in peak SWE on north- and south-facing slopes increase from 3.0 mm at 10° slope to 17.9 mm at 50° slope. When applied to elevation, slope and aspect combinations derived from a high-resolution digital elevation model, elevation dominates the control of peak SWE values. Inclusion of the range of SSS effects into a regional climate model will improve snowpack and hydrological simulations of western North America's snow-dominated, mountainous watersheds.

Near-surface air temperature lapse rate in a humid mountainous terrain on the southern slopes of the eastern Himalayas

Based on climatic data from 18 stations on the southern slopes of the eastern Himalayas in Bhutan for the period from 1996 to 2009, this paper investigates monthly characteristics of the near-surface air temperature lapse rate (TLR). The station elevations used in this study range from 300 to 2760 m a. s. l. TLRs were evaluated using a linear regression model. The monthly values of maximum TLRs were always smaller than those of the minimum TLRs, which is in contrast to results from the surrounding mountainous regions. In this study, annual patterns of TLRs were somewhat consistent, particularly in the summer; during the other seasons, patterns contrasted to results from the southeastern Tibetan Plateau (China) and were almost comparable to results from Nepal. The shallowest observed values for TLRs in summer are due to intense latent heating at the higher elevation, associated with water vapor condensation from moist convection and evapotranspiration, and decreasing sensible heating at lower elevation, due to heavier rainfall, cloud, and forest cover. When compared to summer, the steeper TLRs in the non-monsoon season are due to sensible heating at the lower elevations, corresponding to dry and clear weather seasons, as well as increasing cooling at higher elevations, particularly in winter due to snow and cloud cover. Owing to lower albedo and higher aerodynamic roughness of forested areas, the TLRs were considerably reduced in daytime because of the dissipation of sensible heat to the atmospheric boundary layer. The distinct variation in diurnal TLR range is due to the diurnal variation in net radiation associated with reduced turbulent heating in the day and increased turbulent heating in the night, in addition to the effect of moisture and cloud cover. The shallower values of TLRs in this study when compared with the surrounding mountainous regions are due to high humidity, as well as the differing elevations and local climates.

Near-surface air temperature lapse rates in Xinjiang, northwestern China

Lapse rates of near-surface (2 m) air temperature are important parameters in hydrologic and climate simulations, especially for the mountainous areas without enough in-situ observations. In Xinjiang, northwestern China, the elevations range from higher than 7000 m to lower than sea level, but the existing long-term meteorological measurements are limited and distributed unevenly. To calculate lapse rates in Xinjiang, the daily data of near-surface air temperature (T min, T ave, and T max) were measured by automatic weather stations from 2012 to 2014. All the in situ observation stations were gridded into a network of 1.5° (latitude) by 1.5° (longitude), and the spatial distribution and the daily, monthly, seasonal variations of lapse rates for T min, T ave, and T max in Xinjiang are analyzed. The Urumqi River Basin has been considered as a case to study the influence of elevation, aspect, and the wet and dry air conditions to the T min, T ave, and T max lapse rates. Results show that (1) the lapse rates for T min, T ave, and T max vary spatially during the observation period. The spatial diversity of T min lapse rates is larger than that of T ave, and that of T max is the smallest. For each season, T max lapse rates have more negative values than T ave lapse rates which are steeper than T min lapse rates. The weakest spatial diversity usually appears in July throughout a year. (2) The comparison for the three subregions (North, Middle, and South region) exhibits that lapse rates have similar day-to-day and month-to-month characteristics which present shallower values in winter months and steeper values in summer months. The T ave lapse rates in North region are shallower than those in Middle and South region, and the steepest T ave lapse rates of the three regions all appear in April. T min lapse rates are shallower than T max lapse rates. The maximum medians of T min and T max lapse rates for each grid in the three regions all appear in January, whereas the minimum medians all concentrate in July. (3) The seasonality of T min, T ave, and T max in Xinjiang is also observed. An increasing trend from summer to winter and a decreasing trend from winter to next summer can be seen clearly. (4) The inversion phenomenon is obvious in the Urumqi River Basin and appears in March, November, December, January, and February. The great inversion phenomenon days (24 days) and persistent inversion phenomenon days (12 days) present in January. The influences of elevation and aspect are complex. Lapse rates for T ave, T min, and T max are steeper under humid air conditions, while dry air conditions lead to shallower lapse rates.

Surface Air Temperature Fluctuations and Lapse Rates on Olivares Gamma Glacier, Rio Olivares Basin, Central Chile, from a Novel Meteorological Sensor Network

Empirically based studies of glacier meteorology, especially for the Southern Hemisphere, are relatively sparse in the literature. Here, we use an innovative network of highly portable, low-cost thermometers to report on high-frequency (1-min time resolution) surface air temperature fluctuations and lapse rates (LR) in a ~800-m elevational range (from 3,675 to 4,492 m a.s.l.) across the glacier Olivares Gamma in the central Andes, Chile. Temperatures were measured during an intense field campaign in late Southern summer, 19–27 March 2015, under varying weather conditions. We found a complex dependence of high-frequency LR on time of day, topography, and wider meteorological conditions, with hourly temperature variations during this week that were probably mainly associated with short- and long-wave radiation changes and not with wind speed/direction changes. Using various pairs of sites within our station network, we also analyze spatial variations in LR. Uniquely in this study, we compare temperatures measured at heights of 1-m and 2-m above the glacier surface for the network of five sites and found that temperatures at these two heights occasionally differed by more than ±4°C during the early afternoons, although the mean temperature difference is much smaller (~0.3°C). An implication of our results is that daily, hourly, or even monthly averaged LR may be insufficient for feeding into accurate melt models of glacier change, with the adoption of subhourly (ideally 1–10-min) resolution LR likely to prove fruitful in developing new innovative high-time-resolution melt modelling. Our results are potentially useful as input LR for local glacier melt models and for improving the understanding of lapse rate fluctuations and glacier response to climate change.

Evaluation of branched GDGTs and leaf wax n-alkane δ2H as (paleo) environmental proxies in East Africa

The role of mountain evolution on local climate is poorly understood and potentially underestimated in climate models. One prominent example is East Africa, which underwent major geodynamic changes with the onset of the East African Rift System (EARS) more than 250Myr ago. This study explores, at the regional East African scale, a molecular approach for terrestrially-based paleo-climatic reconstructions that takes into account both changes in temperature and in altitude, potentially leading to an improved concept in paleo-climatic reconstructions. Using surface soils collected along pronounced altitudinal gradients in Mt. Rungwe (n=40; Southwest Tanzania) and Mt. Kenya (n=20; Central Kenya), we investigate the combination of 2 terrestrial proxies, leaf wax n-alkane δ2H (δ2Hwax) and branched glycerol dialkyl glycerol tetraether (br GDGT) membrane lipids, as (paleo) elevation and (paleo) temperature proxies, respectively. At the mountain scale, a weak link between δ2Hwax and altitude (R2=0.33) is observed at Mt. Kenya, but no relationship is observed at Mt. Rungwe. It is likely that additional parameters, such as decreasing relative humidity (RH) or vegetation changes with altitude, are outcompeting the expected 2H-depletion trend along Mt. Rungwe. In contrast, br GDGT-derived absolute mean annual air temperature (MAAT) and temperature lapse rate (0.65°C/100m) for both mountains are in good agreement with direct field measurements, further supporting the robustness of this molecular proxy for (paleo) temperature reconstructions. At the regional scale, estimated and observed δ2H data in precipitation along 3 mountains in East Africa (Mts. Rungwe, Kenya and Kilimanjaro) highlight a strong spatial heterogeneity, preventing the establishment of a regional based calibration of δ2Hwax for paeloaltitudinal reconstructions. Different from that, an improved regional soil calibration is developed between br GDGT distribution and MAAT by combining the data from this study (Mts. Rungwe and Kenya) with previous results from East African surface soils along Mts. Kilimanjaro (Tanzania) and Rwenzori (Uganda). This new regional calibration, based on 105 samples, improves both the R2 (0.77) and RMSE (root mean square error; 2.4°C) of br GDGT-derived MAAT over the global soil calibrations previously established (R2=0.56; RMSE=4.2°C) and leads to more accurate (paleo) temperature reconstructions in the region.

Assessing seasonal variation of near surface air temperature lapse rate across India

ABSTRACTPrecise characterization of surface air temperature at different spatial scales remains a challenge as it often requires a dense network of temperature sensors. The most common approach for estimating surface air temperature at a desired location in hydrological and terrestrial models is to interpolate surface air temperature observations obtained from a sparse set‐up of temperature sensors using the global standard uniform lapse rate. This interpolation technique, though easy to use, can lead to unreliable results, as the global standard uniform lapse rate may not be representative of seasonal and local variations in lapse rate. In this study, linear and nonlinear regression relationships are derived to estimate mean minimum, mean and mean maximum near surface air temperatures (at monthly and annual time scales) across India. The normal daily air temperature data from 439 stations and their corresponding latitude, longitude and elevation are used in the analysis. The computed temperature gradients exhibit seasonal variation. The effects of elevation and longitude are more pronounced in pre‐monsoon (March–May) and post‐monsoon (October–November) months, whereas the effects of latitude are more in winter months (December–February). Results indicate that the global standard uniform lapse rate (− 0.65 ° C 100 m− 1) is only applicable for monthly mean maximum temperature for April and May. The highest interpolation reliability is obtained for monthly mean minimum temperature. The regression equations though simple, hold promise for describing surface air temperature across India.

Near-Surface Air Temperature Lapse Rate Over Complex Terrain in the Southern Ecuadorian Andes: Implications for Temperature Mapping

ABSTRACTNear-surface air temperature variation with altitude (Tlr) is important for several applications including hydrology, ecology, climate, and biodiversity. To calculate Tlr accurately, a dense monitoring network over an altitudinal gradient is needed. Typically, meteorological monitoring in mountain regions is scarce and not adequate to calculate Tlr correctly. To overcome this problem in our region, we monitored temperature over a gradient ranging 2600–4200 m a.s.l. during an 18 month period. Using these data, we calculated Tlr for the first time at this altitude in the Andes and tested the impact of using the standard Tlr values instead of the observed ones to map temperature by means of the MTCLIM model. We found that annual lapse rate values (6.9 °C km-1 for Tmean, 5.5 °C km-1 for Tmin, and 8.8 °C km-1 for Tmax) differ significantly from the MTCLIM default values and that temperature maps improved vastly when measured Tlr was entered, especially for Tmax and Tmin. Our results may be representative of the broader area, as Tlr in our study period is not affected by microclimatic conditions generated by differences in topography and land cover between our monitoring sites; moreover, observed temperature during our study period was found to be representative of the longer-term annual climatology of the region.

Warm season bias of branched GDGT temperature estimates causes underestimation of altitudinal lapse rate

The temperature trend estimated from the distribution of bacterial branched glycerol dialkyl glycerol tetraethers (brGDGTs) in soil (i.e. the MBT–CBT or MBT′–CBT index) was studied along an altitude transect from 1850m to 5139m in the southeast Tibetan Plateau. Measured temperature values from weather stations in the area showed increasing seasonality with increasing elevation. The measured lapse rate of mean annual air temperature (MAAT) in the region was −7.2°C/km, whereas that estimated from the MBT- or MBT′–CBT index was lower, with only −3.2°C/km for the MBT′–CBT estimate. At elevation >4km, MBT′–CBT temperature values were increasingly higher than measured MAAT values. We hypothesized that the systematic changes in the length of the warm season, as well as the seasonal period of brGDGT production, with elevation are likely the cause of overestimation of the MBT′–CBT temperature at high elevation sites, and hence the underestimation of lapse rate. The hypothesis was supported by a similar lapse rate of −3.1°C/km calculated from the measured mean warm season temperature (MWST) that only included monthly temperature values >0°C. This suggests that care should be taken in interpreting brGDGT derived temperature values in environments with large seasonal contrasts.