Growing season air temperature lapse rate in the Snowy Mountains

2014 ◽  
Vol 64 (4) ◽  
pp. 289-291 ◽  
Author(s):  
K Green
2018 ◽  
Vol 19 (7) ◽  
pp. 1215-1233 ◽  
Author(s):  
Guoqiang Tang ◽  
Ali Behrangi ◽  
Ziqiang Ma ◽  
Di Long ◽  
Yang Hong

Abstract Precipitation phase has an important influence on hydrological processes. The Integrated Multisatellite Retrievals for Global Precipitation Measurement (IMERG) uses temperature data from reanalysis products to implement rain–snow classification. However, the coarse resolution of reanalysis data may not reveal the spatiotemporal variabilities of temperature, necessitating appropriate downscaling methods. This study compares the performance of eight air temperature Ta downscaling methods in the contiguous United States and six mountain ranges using temperature from the Parameter-Elevation Regressions on Independent Slopes Model (PRISM) as the benchmark. ERA-Interim Ta is downscaled from the original 0.75° to 0.1°. The results suggest that the two purely statistical downscaling methods [nearest neighbor (NN) and bilinear interpolation (BI)] show similar performance with each other. The five downscaling methods based on the free-air temperature lapse rate (TLR), which is calculated using temperature and geopotential heights at different pressure levels, notably improves the accuracy of Ta. The improvement is particularly obvious in mountainous regions. We further calculated wet-bulb temperature Tw, for rain–snow classification, using Ta and dewpoint temperature from ERA-Interim and PRISM. TLR-based downscaling methods result in more accurate Tw compared to NN and BI in the western United States, whereas the improvement is limited in the eastern United States. Rain–snow partitioning is conducted using a critical threshold of Tw with Snow Data Assimilation System (SNODAS) snowfall data serving as the benchmark. ERA-Interim-based Tw using TLR downscaling methods is better than that using NN/BI and IMERG precipitation phase. In conclusion, TLR-based downscaling methods show promising prospects in acquiring high-quality Ta and Tw with high resolution and improving rain–snow partitioning, particularly in mountainous regions.


2013 ◽  
Vol 54 (63) ◽  
pp. 120-130 ◽  
Author(s):  
Lene Petersen ◽  
Francesca Pellicciotti ◽  
Inge Juszak ◽  
Marco Carenzo ◽  
Ben Brock

AbstractNear-surface air temperature, typically measured at a height of 2 m, is the most important control on the energy exchange and the melt rate at a snow or ice surface. It is distributed in a simplistic manner in most glacier melt models by using constant linear lapse rates, which poorly represent the actual spatial and temporal variability of air temperature. In this paper, we test a simple thermodynamic model proposed by Greuell and Böhm in 1998 as an alternative, using a new dataset of air temperature measurements from along the flowline of Haut Glacier d’Arolla, Switzerland. The unmodified model performs little better than assuming a constant linear lapse rate. When modified to allow the ratio of the boundary layer height to the bulk heat transfer coefficient to vary along the flowline, the model matches measured air temperatures better, and a further reduction of the root-mean-square error is obtained, although there is still considerable scope for improvement. The modified model is shown to perform best under conditions favourable to the development of katabatic winds – few clouds, positive ambient air temperature, limited influence of synoptic or valley winds and a long fetch – but its performance is poor under cloudy conditions.


Water ◽  
2019 ◽  
Vol 11 (8) ◽  
pp. 1561 ◽  
Author(s):  
Bhanu Pratap ◽  
Parmanand Sharma ◽  
Lavkush Patel ◽  
Ajit T. Singh ◽  
Vinay Kumar Gaddam ◽  
...  

In Himalaya, the temperature plays a key role in the process of snow and ice melting and, importantly, the precipitation phase changes (i.e., snow or rain). Consequently, in longer period, the melting and temperature gradient determine the state of the Himalayan glaciers. This necessitates the continuous monitoring of glacier surface melting and a well-established meteorological network in the Himalaya. An attempt has been made to study the seasonal and annual (October 2015 to September 2017) characteristics of air temperature, near-surface temperature lapse rate (tlr), in-situ glacier surface melting, and surface melt simulation by temperature-index (T-index) models for Sutri Dhaka Glacier catchment, Lahaul-Spiti region in Western Himalaya. The tlr of the catchment ranges from 0.3 to 6.5 °C km−1, varying on a monthly and seasonal timescale, which suggests the need for avoiding the use of standard environmental lapse rate (SELR ~6.5 °C km−1). The measured and extrapolated average air temperature (tavg) was found to be positive on glacier surface (4500 to 5500 m asl) between June and September (summer). Ablation data calculated for the balance years 2015–16 and 2016–17 shows an average melting of −4.20 ± 0.84 and −3.09 ± 0.62 m w.e., respectively. In compliance with positive air temperature in summer, ablation was also found to be maximum ~88% of total yearly ice melt. When comparing the observed and modelled ablation data with air temperature, we show that the high summer glacier melt was caused by warmer summer air temperature and minimum spells of summer precipitation in the catchment.


MAUSAM ◽  
2021 ◽  
Vol 68 (3) ◽  
pp. 417-428
Author(s):  
JANAK LAL NAYAVA ◽  
SUNIL ADHIKARY ◽  
OM RATNA BAJRACHARYA

This paper investigates long term (30 yrs) altitudinal variations of surface air temperatures based on air temperature data of countrywide scattered 22 stations (15 synoptic and 7 climate stations) in Nepal. Several researchers have reported that rate of air temperature rise (long term trend of atmospheric warming) in Nepal is highest in the Himalayan region (~ 3500 m asl or higher) compared to the Hills and Terai regions. Contrary to the results of previous researchers, however this study found that the increment of annual mean temperature is much higher in the Hills (1000 to 2000 m asl) than in the Terai and Mountain Regions. The temperature lapse rate in a wide altitudinal range of Nepal (70 to 5050 m asl) is -5.65 °C km-1. Warming rates in Terai and Trans-Himalayas (Jomsom) are 0.024 and 0.029 °C/year respectively.  


2018 ◽  
Vol 123 (8) ◽  
pp. 3943-3960 ◽  
Author(s):  
Hongbo Zhang ◽  
Fan Zhang ◽  
Guoqing Zhang ◽  
Tao Che ◽  
Wei Yan

2016 ◽  
Vol 121 (20) ◽  
pp. 12,005-12,030 ◽  
Author(s):  
Lei Wang ◽  
Litao Sun ◽  
Maheswor Shrestha ◽  
Xiuping Li ◽  
Wenbin Liu ◽  
...  

2021 ◽  
Author(s):  
Rajesh Joshi ◽  
Ninchhen Dolma Tamang ◽  
Surendra Pratap Singh

Abstract There are emergent evidences that the rise in temperature in high altitude regions in comparison to low altitude of the Himalaya is more rapid than other parts of the World. This Elevation-dependent warming (EDW) can accelerate the rate of change in mountain ecosystems, including cryosphere, hydrology, biodiversity and socio-economic systems. In this paper, we present Temperature Lapse Rates (TLRs) from 20 stations for three treeline transects representing different climate regimes along the Himalayan arc. TLRs were calculated based on high temporal resolution data collected for two year (2017-18) from complex mountain terrain of treeline environment. The annual mean TLR increased with decreasing moisture, being markedly high at dry WH transect (-0.66℃/100 m) and lowest (-0.50℃/100 m) for moist EH transect. The One-Way ANOVA confirms that the TLR varied spatially, declining from West to East across the Himalayan arc, and significantly differ among seasons (F=3.2175; P = 0.03). The lowest mean TLRs were found during the winter season (EH: -0.46℃/100m; CH: -0.40℃/100m; WH: -0.31℃/100m). The monthly TLR varied within a narrow range (-0.49℃/100m to -0.54℃/100m) at EH transect, -0.24℃/100m to -0.68℃/100m at CH transect and from -0.26℃ to -0.90℃ at WH transect with lowest monthly TLR in December (-0.24 to -0.32℃/ 100m) for all three sites. Study shows moisture, snow albedo and reflectance play a key role as controlling factors on TLR in treeline environments. Higher growing season temperatures observed for treelines in Himalaya (8.4±1.8℃, 10.3±1.4℃, and 7.5±2.7℃) shows warmer treeline in Himalaya. The EDW may impact the dynamics of treeline, snow and moisture regime, surface energy balance, increased water stress, species distribution, and growing season of alpine vegetation in the Himalaya. The findings of the study could provide useful insight (ground-based) to re-parameterize the climate models over the Himalayan region. This study can facilitate improving interpolation of air temperature for ecological modeling studies in ungauged and the data-sparse regions, especially for the higher Himalaya where ground based station data are extremely scarce.


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