Lapse Rate Research Articles

Relationships among Arctic warming, sea-ice loss, stability, lapse rate feedback, and Arctic amplification

Relationships among Arctic warming, sea-ice loss, stability, lapse rate feedback, and Arctic amplification

Large anomalies in future extreme precipitation sensitivity driven by atmospheric dynamics

Increasing atmospheric moisture content is expected to intensify precipitation extremes under climate warming. However, extreme precipitation sensitivity (EPS) to temperature is complicated by the presence of reduced or hook-shaped scaling, and the underlying physical mechanisms remain unclear. Here, by using atmospheric reanalysis and climate model projections, we propose a physical decomposition of EPS into thermodynamic and dynamic components (i.e., the effects of atmospheric moisture and vertical ascent velocity) at a global scale in both historical and future climates. Unlike previous expectations, we find that thermodynamics do not always contribute to precipitation intensification, with the lapse rate effect and the pressure component partly offsetting positive EPS. Large anomalies in future EPS projections (with lower and upper quartiles of −1.9%/°C and 8.0%/°C) are caused by changes in updraft strength (i.e., the dynamic component), with a contrast of positive anomalies over oceans and negative anomalies over land areas. These findings reveal counteracting effects of atmospheric thermodynamics and dynamics on EPS, and underscore the importance of understanding precipitation extremes by decomposing thermodynamic effects into more detailed terms.

Surface Water Isoscape Modeling in the Himalayan Region: An Alternative for Moisture Source Investigation, Hydrograph Separation, and Paleolatitude Estimation

AbstractThe spatial distribution of water isotopes provides essential scientific data for understanding many hydrological, paleoclimate, and ecological processes. The limited isotopic data across the Himalayan River Basins (HRB) obstructs the study of basin‐scale hydrological processes. New data of stable isotopes of oxygen and hydrogen from Indus, in combination with a comprehensive compiled data set from HRB, was used for the first time to create isoscapes (δ18O and d‐excess) for specifically representing surface water. The δ18O and d‐excess isoscape define a clear isotopic distinction along a topographic gradient from south to north and west to east that could be reproduced (predicted) by using a Geographically weighted Regression Model (GWRM) based on surface heterogeneity by considering a combination of predictors (precipitation, temperature, evapotranspiration, runoff, elevation, slope, aspect, and land use landcover). The d‐excess isoscape demonstrates more complicated spatial variability, owing to differential moisture inputs from westerlies and the Indian Summer Monsoon, as well as secondary evaporation processes in the region. GWRM isoscapes have been able to compute the fractional contributions from different water sources across HRB. The model‐derived predicted δ18O and elevation values suggest a second‐order polynomial relationship that represents the Isotopic Lapse Rate more accurately than a linear one. The GWRM predictive isoscapes are sufficiently accurate to serve as a good proxy for the influence of moisture source and runoff estimation, palaeoecological studies, climate reconstruction, and changes in hydrological processes because of climate change. Therefore, GWRM can be applied to other regions where data is lacking.

The Contribution of Microrefugia to Landscape Thermal Inertia for Climate‐Adaptive Conservation Strategies

AbstractCurrent temperatures in microrefugia may persist longer than in nearby areas as temperatures warm. However, locating and measuring the contribution of microrefugia to thermal inertia in a landscape is challenging. We measured the thermal buffering capacity of microrefugia across a 40,000 km2 region of complex mountain topography by quantifying environmental lapse rate and solar radiation effects on air temperature in 0.1 km2 hexagons, a resource management‐relevant scale for climate adaptation. The greatest buffering capacity is −1.62°C, and only 2.8% of the region can buffer 1°C or greater. Historical loss of local cooling capacity is low, but by 2069 only 6.9%–11% of the region retains baseline temperature conditions. This thermal buffer index can find the most climate change‐buffered areas in lands identified as high priority for habitat conservation, wildlife corridors, and forest preservation. Other processes such as cold air pooling can complement our approach but depend on additional factors.

Solar Geoengineering in the Polar Regions: A Review

AbstractSolar geoengineering refers to proposals, including stratospheric aerosol injection (SAI), to slow or reverse climate change by reflecting away incoming sunlight. The rapid changes ongoing in the Arctic and Antarctic, and the risk of exceeding tipping points in the cryosphere within decades, make limiting such changes a plausible objective of solar geoengineering. Here, we review the impacts of SAI on polar climate and cryosphere, including the dependence of these impacts on the latitude(s) of injection, and make recommendations for future research directions. SAI would cool the polar regions and reduce many changes in polar climate under future warming scenarios. Some under‐cooling of the polar regions relative to the global mean is expected under SAI without high latitude injection, due to latitudinal variation in insolation and CO2 forcing, the forcing dependence of the polar lapse rate feedback, and altered atmospheric dynamics. There are also potential limitations in the effectiveness of SAI to arrest changes in winter‐time polar climate and to prevent sea‐level rise from the Antarctic ice sheet. Finally, we also review the prospects for three other solar geoengineering proposals targeting the poles: marine cloud brightening, cirrus cloud thinning, and sea‐ice albedo modification. Sea‐ice albedo modification appears unlikely to be viable on pan‐Arctic or Antarctic scales. Whether marine cloud brightening or cirrus cloud thinning would be effective in the polar regions remains uncertain. Solar geoengineering is an increasingly prominent proposal and a robust understanding of its consequences in the polar regions is needed to inform climate policy in the coming decades.

How Moisture Shapes Low‐Level Radiative Cooling in Subsidence Regimes

AbstractRadiative cooling of the lowest atmospheric levels is of strong importance for modulating atmospheric circulations and organizing convection, but detailed observations and a robust theoretical understanding are lacking. Here we use unprecedented observational constraints from subsidence regimes in the tropical Atlantic to develop a theory for the shape and magnitude of low‐level longwave radiative cooling in clear‐sky, showing peaks larger than 5–10 K/day at the top of the boundary layer. A suite of novel scaling approximations is first developed from simplified spectral theory, in close agreement with the measurements. The radiative cooling peak height is set by the maximum lapse rate in water vapor path, and its magnitude is mainly controlled by the ratio of column relative humidity above and below the peak. We emphasize how elevated intrusions of moist air can reduce low‐level cooling, by sporadically shading the spectral range which effectively cools to space. The efficiency of this spectral shading depends both on water content and altitude of moist intrusions; its height dependence cannot be explained by the temperature difference between the emitting and absorbing layers, but by the decrease of water vapor extinction with altitude. This analytical work can help to narrow the search for low‐level cloud patterns sensitive to radiative‐convective feedbacks: the most organized patterns with largest cloud fractions occur in atmospheres below 10% relative humidity and feel the strongest low‐level cooling. This motivates further assessment of favorable conditions for radiative‐convective feedbacks and a robust quantification of corresponding shallow cloud dynamics in current and warmer climates.

Altitudinal variations and seasonal dynamics of near-surface and soil temperatures in subtropical forests of Mt. Guanshan, Jiangxi Province, China.

Temperature lapse rate (TLR), measured as the degree of temperature change along an altitudinal gradient, is a key indicator of multiple ecological processes of mountain systems. Although many studies have examined temperature changes of open air or near-surface along altitudes, we know little about altitudinal variations of soil temperature, which play an important role in regulating growth and reproduction of organisms, as well as ecosystem nutrient cycling. Based on temperature data of near-surface (15 cm above ground) and soil layers (8 cm below ground) from 12 sampling sites of subtropical forest along an altitudinal gradient (300-1300 m) in Jiangxi Guan-shan National Nature Reserve from September 2018 to August 2021, we calculated the lapse rates of mean, maximum, and minimum temperatures, as well as accumulated temperatures by using simple linear regression for both near-surface and soil temperature. The seasonal dynamics of aforementioned variables were also evaluated. The results showed that there were large differences among mean, maximum, and minimum lapse rates for annual near-surface temperature, which were 0.38, 0.31 and 0.51 ℃·(100 m)-1, respectively. But little variation was documented for soil temperature which were 0.40, 0.38 and 0.42 ℃·(100 m)-1, respectively. The seasonal variations of temperature lapse rates for near-surface and soil layers were minor except for minimum temperature. The lapse rates of minimum temperature were deeper in spring and winter for near-surface and in spring and autumn for soil layers. For growing degree days (GDD), the accumulated temperature under both layers were negatively correlated with altitude, and the lapse rates of ≥5 ℃ were 163 ℃·d·(100 m)-1 for near-surface and 179 ℃·d·(100 m)-1 for soil. The ≥5 ℃ GDD in soil were about 15 days longer than that in near-surface at the same altitude. The results showed inconsistent patterns of altitudinal variations between near-surface and soil temperature. Soil temperature and its lapse rates had minor seasonal variations compared with the near-surface counterparts, which was related to the strong buffering capacity of soil.

Psychometric curves reveal changes in bias, lapse rate, and guess rate in an online vigilance task.

When human monitors are required to detect infrequent signals among noise, they typically exhibit a decline in correct detections over time. Researchers have attributed this vigilance decrement to three alternative mechanisms: shifts in response bias, losses of sensitivity, and attentional lapses. The current study examined the extent to which changes in these mechanisms contributed to the vigilance decrement in an online monitoring task. Participants in two experiments (N = 102, N = 192) completed an online signal detection task, judging whether the separation between two probes each trial exceeded a criterion value. Separation was varied across trials and data were fit with logistic psychometric curves using Bayesian hierarchical parameter estimation. Parameters representing sensitivity, response bias, attentional lapse rate, and guess rate were compared across the first and last 4 minutes of the vigil. Data gave decisive evidence of conservative bias shifts, an increased attentional lapse rate, and a decreased positive guess rate over time on task, but no strong evidence for or against an effect of sensitivity. Sensitivity decrements appear less robust than criterion shifts or attention lapses as causes of the vigilance loss.

Aerosol impacts on the entrainment efficiency of Arctic mixed-phase convection in a simulated air mass over open water

Abstract. Springtime Arctic mixed-phase convection over open water in the Fram Strait as observed during the recent ACLOUD (Arctic CLoud Observations Using airborne measurements during polar Day) field campaign is simulated at turbulence-resolving resolutions. The first objective is to assess the skill of large-eddy simulation (LES) in reproducing the observed mixed-phase convection. The second goal is to then use the model to investigate how aerosol modulates the way in which turbulent mixing and clouds transform the low-level air mass. The focus lies on the low-level thermal structure and lapse rate, the heating efficiency of turbulent entrainment, and the low-level energy budget. A composite case is constructed based on data collected by two research aircraft on 18 June 2017. Simulations are evaluated against independent datasets, showing that the observed thermodynamic, cloudy, and turbulent states are well reproduced. Sensitivity tests on cloud condensation nuclei (CCN) concentration are then performed, covering a broad range between pristine polar and polluted continental values. We find a significant response in the resolved mixed-phase convection, which is in line with previous LES studies. An increased CCN substantially enhances the depth of convection and liquid cloud amount, accompanied by reduced surface precipitation. Initializing with the in situ CCN data yields the best agreement with the cloud and turbulence observations, a result that prioritizes its measurement during field campaigns for supporting high-resolution modeling efforts. A deeper analysis reveals that CCN significantly increases the efficiency of radiatively driven entrainment in warming the boundary layer. The marked strengthening of the thermal inversion plays a key role in this effect. The low-level heat budget shifts from surface driven to radiatively driven. This response is accompanied by a substantial reduction in the surface energy budget, featuring a weakened flow of solar radiation into the ocean. Results are interpreted in the context of air–sea interactions, air mass transformations, and climate feedbacks at high latitudes.

Determination of Cirrus Occurrence and Distribution Characteristics Over the Tibetan Plateau Based on the SWOP Campaign

AbstractBalloon sounding with the Compact Optical Backscatter Aerosol Detector (COBALD) and Frost Point hygrometers (FPs) provides in situ data for a better understanding of the vertical distribution of cirrus clouds. In this study, eight summer balloon‐borne measurements in Kunming (2012, 2014, 2015, and 2017) and Lhasa (2013, 2016, 2018, and 2020) over the Tibetan Plateau were used to show the distribution characteristics of cirrus clouds. Differences of cirrus occurrence were compared by different indices: the backscatter ratio (BSR) at a 455 nm/940 nm wavelength (BSR455 > 1.2/BSR940 > 2), the color index (CI > 7), and the relative humidity with respect to ice (RHice > 70%). Analysis of the profiles indicated that BSR455 > 1.2 was the optimal criterion to identify the cirrus layer and depict the distribution of the CI and RHice within cirrus clouds. The results showed that the median CI (RHice) within the cirrus clouds at both sites was mostly in the 18–20 (90%–110%) range at pressures below 120 hPa. Furthermore, the balloon‐borne measurements combined with Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) measurements indicated a high frequency of cirrus occurrence near the tropopause in Kunming and Lhasa. The top height of cirrus occurrence at both sites was above the cold point tropopause and the lapse rate tropopause. Both Kunming and Lhasa had the highest frequency of thin cirrus clouds in the 0–0.4 km vertical cirrus thickness range.

Development of high-resolution annual climate surfaces for Turkey using ANUSPLIN and comparison with other methods

Many climate models have been developed due to the importance of the effects of climatic factors on the physical and biological environment, e.g., rock weathering, species distribution, and growth patterns of plants. Accurate, reliable climate surfaces are necessary, especially for countries such as Turkey, which has a complex terrain and limited monitoring stations. The accuracy of these models mainly depends on the spatial modeling methods used. In this study, the Australian National University Spline (ANUSPLIN) model was used to develop climate surfaces and was compared with other methods such as inverse distance weighting, co-kriging, lapse rate, and multilinear regression. The results from the developed climate surfaces were validated using three methods: (1) diagnostic statistics from the surface fitting model, such as signal, mean, root mean square predictive error, root mean square error estimate, root mean square residual of the spline, and estimate of the standard deviation of the noise in the spline; (2) a comparison of error statistics between interpolated surfaces and the withheld climate data from 81 stations; and (3) a comparison with other interpolation methods using model performance metrics, such as mean absolute error, mean error, root mean square error, and R2adj. The most accurate results were obtained by the ANUSPLIN model. It explained 95, 88, 92, and 71% of the variance in annual mean, minimum and maximum temperature, and total precipitation, respectively. The mean absolute error of these models was 0.63, 1.16, and 0.72 ºC, as well as 54.82 mm. The generated climate surfaces, having a spatial resolution of 0.005º × 0.005º could contribute to the fields of forestry, agriculture, and hydrology.

Machine-Learning-Based Downscaling of Hourly ERA5-Land Air Temperature over Mountainous Regions

In mountainous regions, the scarcity of air temperature (Ta) measurements is a major limitation for hydrological and crop monitoring. An alternative to in situ measurements could be to downscale the reanalysis Ta data provided at high-temporal resolution. However, the relatively coarse spatial resolution of these products (i.e., 9 km for ERA5-Land) is unlikely to be directly representative of actual local Ta patterns. To address this issue, this study presents a new spatial downscaling strategy of hourly ERA5-Land Ta data with a three-step procedure. First, the 9 km resolution ERA5 Ta is corrected at its original resolution by using a reference Ta derived from the elevation of the 9 km resolution grid and an in situ estimate over the area of the hourly Environmental Lapse Rate (ELR). Such a correction of 9 km resolution ERA5 Ta is trained using several machine learning techniques, including Multiple Linear Regression (MLR), Support Vector Regression (SVR), and Extreme Gradient Boosting (Xgboost), as well as ancillary ERA5 data (daily mean, standard deviation, hourly ELR, and grid elevation). Next, the trained correction algorithms are run to correct 9 km resolution ERA5 Ta, and the corrected ERA5 Ta data are used to derive an updated ELR over the area (without using in situ Ta measurements). Third, the updated hourly ELR is used to disaggregate 9 km resolution corrected ERA5 Ta data at the 30-meter resolution of SRTM’s Digital Elevation Model (DEM). The effectiveness of this method is assessed across the northern part of the High Atlas Mountains in central Morocco through (1) k-fold cross-validation against five years (2016 to 2020) of in situ hourly temperature readings and (2) comparison with classical downscaling methods based on a constant ELR. Our results indicate a significant enhancement in the spatial distribution of hourly local Ta. By comparing our model, which included Xgboost, SVR, and MLR, with the constant ELR-based downscaling approach, we were able to decrease the regional root mean square error from approximately 3 ∘C to 1.61 ∘C, 1.75 ∘C, and 1.8 ∘C, reduce the mean bias error from −0.5 ∘C to null, and increase the coefficient of determination from 0.88 to 0.97, 0.96, and 0.96 for Xgboost, SVR, and MLR, respectively.

Insights from the first winter weather observations near Mount Everest's summit

Insights from the first winter weather observations near Mount Everest's summit

Midday Boundary-Layer Collapse in the Altiplano Desert: The Combined Effect of Advection and Subsidence

Observations in the Altiplano region of the Atacama Desert show that the atmospheric boundary layer (ABL) suddenly collapses at noon. This rapid decrease occurs simultaneously to the entrance of a thermally driven, regional flow that causes a rise in wind speed and a marked temperature decrease. We identify the main drivers that cause the observed ABL collapse by using a land–atmosphere model. The free atmosphere lapse rate and regional forcings, such as advection of mass and cold air as well as subsidence, are first estimated by combining observations from a comprehensive field campaign and a regional model. Then, to disentangle the ABL collapse, we perform a suite of numerical experiments with increasing level of complexity: from only considering local land–atmosphere interactions, to systematically including the regional contributions of mass advection, cold air advection, and subsidence. Our results show that non-local processes related to the arrival of the regional flow are the main factors explaining the boundary-layer collapse. The advection of a shallower boundary layer (approx -250 m h^{-1} at noon) causes an immediate decrease in the ABL height (h) at midday. This occurs simultaneously with the arrival of a cold air mass, which reaches a strength of approx -4 K h^{-1} at 1400 LT. These two external forcings become dominant over entrainment and surface processes that warm the atmosphere and increase h. As a consequence, the ABL growth is capped during the afternoon. Finally, a wind divergence of approx 8 times 10^{-5} s^{-1} contributes to the collapse by causing subsidence motions over the ABL from 1200 LT onward. Our findings show the relevance of treating large and small-scale processes as a continuum to be able to understand the ABL dynamics.

Study of Some Stability Parameters in the Atmosphere of Oil Al-Dura Refinery, Southeast Baghdad

Wind and temperature measurements at an oil refinery site located southeast of Baghdad city at two levels, 15 and 30 m, are presented. Three schemes are used to determine different stability classifications: Monin-Obukhov length, gradient, and bulk Richardson numbers. Meanwhile, vertical changes in air temperature and wind shear are also computed. There were lapse rate and inversion cases during the nights and days while favorable wind shear was dominant. The variation of stability in each scheme is large, covering the entire range of stability for a given class. The results of stability schemes are compared to each other. The results show that the schemes based on gradient and bulk Richardson numbers reasonably compare them.

Predicting Convective Downdrafts From Updrafts and Environmental Conditions in a Global Storm Resolving Simulation

AbstractOne important component of precipitating convection is the formation of convective downdrafts. They can terminate the initial updraft, affect the mean properties of the boundary layer, and cause strong winds at the surface. While the basic forcing mechanisms for downdrafts are well understood, it is difficult to formulate general relationships between updrafts, environmental conditions, and downdrafts. To better understand what controls different downdraft properties, we analyze downdrafts over tropical oceans in a global storm resolving simulation. Using a global model allows us to examine a large number of downdrafts under naturally varying environmental conditions. We analyze the various factors affecting downdrafts using three alternative methods. First, hierarchical clustering is used to examine the correlation between different downdraft, updraft, and environmental variables. Then, either random forests or multiple linear regression are used to estimate the relationships between downdraft properties and the updraft and environmental predictors. We find that these approaches yield similar results. Around 75% of the variability in downdraft mass flux and 37% of the variability in downdraft velocity are predictable. Analyzing the relative importance of our various predictors, we find that downdrafts are coupled to updrafts via the precipitation generation argument. In particular, updraft properties determine rain amount and rate, which then largely control the downdraft mass flux and, albeit to a lesser extent, the downdraft velocity. Among the environmental variables considered, only lapse rate is a valuable predictor: a more unstable environment favors a higher downdraft mass flux and a higher downdraft velocity.

Limits of oxygen isotope palaeoaltimetry in Tibet

Measurements of stable water isotopes (oxygen and hydrogen) are commonly used to estimate palaeoelevation and quantify past changes in surface height across Tibet. Isotope palaeoaltimetry is often based on simple Rayleigh fractionation of a “parcel of air”, but must make a considerable number of approximations and assumptions. In this paper, we elaborate on the practicability of oxygen water isotopes in palaeoaltimetry, and evaluate a recent challenge to the palaeoaltimetry community. First, we examine the isotopic composition of oxygen (δ18O) versus altitude relationship in a set of five topographic realisations of Tibet using an isotope-enabled palaeoclimate model for the mid-Eocene, a period where a variety of topographic ‘uplift’ models have been proposed, and compare it to modern relationships. Second, we investigate whether isotopic composition is a good predictor of more modest changes in topography, such as the introduction of a valley system or uplift of only part of the Tibetan region. The aim of the paper is not to perform a direct comparison to data, but to use the model to further refine knowledge of the strengths and limitations of using oxygen isotopes in palaeoaltimetry. We find that oxygen isotope palaeoaltimetry works surprisingly well, with the exception that it could not identify low elevation valley systems bounded by high elevations because the isotopic composition of the water in the air becomes depleted at the first high elevation that an air parcel passes over and does not recover when it descends into the valley. Hence, isotope-based elevations are biased towards mountain range peaks. Overall, the application of oxygen isotope palaeoaltimetry does have value, but would be further strengthened when employed together with isotope-enabled models. In conjunction with other techniques such as terrestrial thermal lapse rates and energy conservation approaches, over a wide spatial region, a more accurate and fully three-dimension view of complex palaeo-topography is increasingly possible, which will in turn improve the precision of these palaeoaltimeters.

Rethinking spatiotemporal variations in air temperature over the Qilian Mountains, Western China, from 1979 to 2018

The Qilian Mountains region, located on the northeastern Tibetan Plateau, is a region in western China that is sensitive to climate change and serves as an important ecological security barrier. Previous studies mostly used meteorological stations to study climate change in the Qilian Mountains; however, due to the known distribution limitations (scarcity and inhomogeneity) of meteorological stations in mountainous areas, relevant results remain inconclusive. To address this issue, we used 30 meteorological stations in and around the Qilian Mountains and the China meteorological forcing dataset (CMFD) with a spatial resolution of 0.1° × 0.1° to comprehensively analyse the spatiotemporal distribution of and variation in the air temperature over the Qilian Mountains, with a particular focus on elevation-dependent warming (EDW); then, land surface albedo data from the ERA5-Land and MODIS products were employed to interpret the EDW. The results showed that the annual mean lapse rate in the Qilian Mountains is −0.56 °C/100 m. From 1979 to 2018, the air temperature over the Qilian Mountains experienced a significant upwards trend with an annual mean rate of 0.39 °C/decade, the maximum rate occurring in December–February (DJF, 0.56 °C/decade) and the minimum rate occurring in June–August (JJA, 0.28 °C/decade). Spatially, significant warming was found in most areas of the Qilian Mountains, and a slight cooling trend was found in the north and southeast. Unlike other typical areas, the Qilian Mountains showed reversed EDW during 1979–2018, i.e., the increasing trends in air temperature decreased with elevation, which was mainly caused by the reversal in EDW over the 1999–2008 period and could be largely explained by the change in land surface albedo.

A Meteorological Analysis from the Southern Slope of Mt. Everest, Nepal

Mt. Everest is the highest mountain in the world, with an elevation ending at 8848.86 m above sea level, providing unique opportunity for direct observation of the upper troposphere. Utilizing the data from recently established five automatic weather stations (AWSs) network along the Everest climbing route, as part of the National Geographic and Rolex Perpetual Planet Expedition to Mount Everest 2019, from June 2019 to May 2020, this study investigates the meteorological environment over the southern slope of the Mt. Everest. Precipitation, temperature, radiations (income and outgoing short wave and long wave radiation), wind speed and direction along with derived variables like Lapse Rate, Precipitation Gradient, 6.11 hPa Isoline, and zero-degree Isotherm are analyzed with the aim of understanding altitudinal variation. Precipitation is mainly concentrated in monsoon with highest in Phortse (530 mm). Analysis of temperature lapse rate shows the highest lapse rate (-5.6 ℃ km-1) in monsoon and lowest in post-monsoon (-7℃ km-1). The precipitation analysis reveals that the vertical and horizontal precipitation gradient for monsoon is -63 mm km-1 and is -8.6 mm km-1 however, during the post-monsoon, precipitation increased by 0.75mm km-1 and 4.6 mm km-1, respectively. Similarly, westerly winds dominate during winter in upper station while it’s nearly uniform for lower stations. Radiation, likewise, are highly correlated between the stations, with incoming shortwave being the highest in the upper station, South-Col. Both isoline and isotherm lines are observed at around 6000 m above sea level. The one-year data has revealed some of the interesting pictures of high-altitude meteorology, but long-term data with fewer data gaps should be required to confirm these patterns.

Response of glacier modelling parameters to time, space, and model complexity: Examples from eastern slopes of Canadian Rocky Mountains

Mountain glaciers are at risk of rapid retreat and require an accurate prediction of their melt and evolution. However, there is a great deal of hassle with mountain glacier melt modelling at a regional scale. Most advanced physical process-based models require an ample amount of high-resolution measurements, while widely-used empirical models suffer from parameter transferability. We developed a glacier melt, mass balance, and evolution modelling framework using three temperature index melt modelling approaches. We performed 24 model scenarios to examine the response of 19 empirical parameters to the effects of: (1) two time periods, for understanding how parameter response can vary with time period considered for the simulation; (2) two glaciers located at the eastern slopes of the Canadian Rocky Mountains, for understanding the effects of glaciers hydro-climate and geographic setting; and (3) two levels of complexity in the model structure including melt and mass balance models coupled with (complex) and without (simple) glacier evolution modules. The results showed that the best optimal melt parameter sets vary temporally and spatially for both simple and complex models, indicating that they are not transferable from one period to another and across glaciers. The variations of ice melt parameters are greater than the snowmelt parameters. The spatiotemporal variations of parameters are resulted from the geographical and local climatic settings and energy balance components, including albedo parameterization on the glacier surface, the altitudinal variations of the glaciers, and the slope and aspects to which glaciers are exposed. For all models, the most sensitive parameter is temperature Lapse rate (LR), but with increasing model complexity, the parameter responses vary depending on the melt model structure and input data. Our study provides important information for modelling glacier melt and evolution at a regional scale.