Seasonal and Synoptic Variations in Near-Surface Air Temperature Lapse Rates in a Mountainous Basin

2008 ◽  
Vol 47 (1) ◽  
pp. 249-261 ◽  
Author(s):  
Troy R. Blandford ◽  
Karen S. Humes ◽  
Brian J. Harshburger ◽  
Brandon C. Moore ◽  
Von P. Walden ◽  
...  

Abstract To accurately estimate near-surface (2 m) air temperatures in a mountainous region for hydrologic prediction models and other investigations of environmental processes, the authors evaluated daily and seasonal variations (with the consideration of different weather types) of surface air temperature lapse rates at a spatial scale of 10 000 km2 in south-central Idaho. Near-surface air temperature data (Tmax, Tmin, and Tavg) from 14 meteorological stations were used to compute daily lapse rates from January 1989 to December 2004 for a medium-elevation study area in south-central Idaho. Daily lapse rates were grouped by month, synoptic weather type, and a combination of both (seasonal–synoptic). Daily air temperature lapse rates show high variability at both daily and seasonal time scales. Daily Tmax lapse rates show a distinct seasonal trend, with steeper lapse rates (greater decrease in temperature with height) occurring in summer and shallower rates (lesser decrease in temperature with height) occurring in winter. Daily Tmin and Tavg lapse rates are more variable and tend to be steepest in spring and shallowest in midsummer. Different synoptic weather types also influence lapse rates, although differences are tenuous. In general, warmer air masses tend to be associated with steeper lapse rates for maximum temperature, and drier air masses have shallower lapse rates for minimum temperature. The largest diurnal range is produced by dry tropical conditions (clear skies, high solar input). Cross-validation results indicate that the commonly used environmental lapse rate [typically assumed to be −0.65°C (100 m)−1] is solely applicable to maximum temperature and often grossly overestimates Tmin and Tavg lapse rates. Regional lapse rates perform better than the environmental lapse rate for Tmin and Tavg, although for some months rates can be predicted more accurately by using monthly lapse rates. Lapse rates computed for different months, synoptic types, and seasonal–synoptic categories all perform similarly. Therefore, the use of monthly lapse rates is recommended as a practical combination of effective performance and ease of implementation.

2017 ◽  
Vol 131 (3-4) ◽  
pp. 1221-1234 ◽  
Author(s):  
Mingxia Du ◽  
Mingjun Zhang ◽  
Shengjie Wang ◽  
Xiaofan Zhu ◽  
Yanjun Che

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.


2020 ◽  
Vol 66 (257) ◽  
pp. 386-400
Author(s):  
Patrick Troxler ◽  
Álvaro Ayala ◽  
Thomas E. Shaw ◽  
Matt Nolan ◽  
Ben W. Brock ◽  
...  

AbstractWe examine the spatial patterns of near-surface air temperature (Ta) over a melting glacier using a multi-annual dataset from McCall Glacier, Alaska. The dataset consists of a 10-year (2005–2014) meteorological record along the glacier centreline up to an upper glacier cirque, spanning an elevation difference of 900 m. We test the validity of on-glacier linear lapse rates, and a model that calculates Ta based on the influence of katabatic winds and other heat sources along the glacier flow line. During the coldest hours of each summer (10% of time), average lapse rates across the entire glacier range from −4.7 to −6.7°C km−1, with a strong relationship between Ta and elevation (R2 > 0.7). During warm conditions, Ta shows more complex, non-linear patterns that are better explained by the flow line-dependent model, reducing errors by up to 0.5°C compared with linear lapse rates, although more uncertainty might be associated with these observations due to occasionally poor sensor ventilation. We conclude that Ta spatial distribution can vary significantly from year to year, and from one glacier section to another. Importantly, extrapolations using linear lapse rates from the ablation zone might lead to large underestimations of Ta on the upper glacier areas.


2013 ◽  
Vol 14 (3) ◽  
pp. 929-945 ◽  
Author(s):  
Brian Henn ◽  
Mark S. Raleigh ◽  
Alex Fisher ◽  
Jessica D. Lundquist

Abstract Near-surface air temperature observations often have periods of missing data, and many applications using these datasets require filling in all missing periods. Multiple methods are available to fill missing data, but the comparative accuracy of these approaches has not been assessed. In this comparative study, five techniques were used to fill in missing temperature data: spatiotemporal correlations in the form of empirical orthogonal functions (EOFs), time series diurnal interpolation, and three variations of lapse rate–based filling. The method validation used sets of hourly surface temperature observations in complex terrain from five regions. The most accurate method for filling missing data depended on the number of available stations and the number of hours of missing data. Spatiotemporal correlations using EOF reconstruction were most accurate provided that at least 16 stations were available. Temporal interpolation was the most accurate method when only one or two stations were available or for 1-h gaps. Lapse rate–based filling was most accurate for intermediate numbers of stations. The accuracy of the lapse rate and EOF methods was found to be sensitive to the vertical separation of stations and the degree of correlation between them, which also explained some of the regional differences in performance. Horizontal distance was less significantly correlated with method performance. From these findings, guidelines are presented for choosing a filling method based on the duration of the missing data and the number of stations.


2017 ◽  
Vol 38 (1) ◽  
pp. 41-60 ◽  
Author(s):  
Klára Ambrožová ◽  
Kamil Láska

AbstractA two-year-long data set of air temperature from four different altitudes above Petuniabukta, central Spitsbergen, was analysed in order to assess the near-surface temperature lapse rates and the relative frequency of air temperature inversion occurrence. From August 2013 to July 2015, air temperatures at adjacent altitudes in Petuniabukta were strongly correlated. The near-surface lapse rates in all three layers differed significantly both from the average lapse rate in the international standard atmosphere (0.65°C 100 m−1) and the lapse rate calculated by linear regression. A pronounced annual cycle was detected in the lowermost air layer (from 23 to 136 m a.s.l.) with a variable near-surface lapse rate in the winter months, while an annual cycle was not apparent in the air layers above 136 m a.s.l. The lowermost layer was also characterized by a notable daily cycle in near-surface lapse rate in spring and autumn. Air temperature inversions occurred in up to 80% of the study period in the air layer below 136 m a.s.l., with the relative frequency being much lower in the other two air layers. The air temperature inversions lasted as long as 139 hours. A case study revealed that one of the strongest air temperature inversions was connected to an area of lower pressure gradients at the 850-hPa pressure level.


2016 ◽  
Vol 62 (231) ◽  
pp. 185-198 ◽  
Author(s):  
THOMAS E. SHAW ◽  
BEN W. BROCK ◽  
CATRIONA L. FYFFE ◽  
FRANCESCA PELLICCIOTTI ◽  
NICK RUTTER ◽  
...  

ABSTRACTNear-surface air temperature is an important determinant of the surface energy balance of glaciers and is often represented by a constant linear temperature gradients (TGs) in models. Spatio-temporal variability in 2 m air temperature was measured across the debris-covered Miage Glacier, Italy, over an 89 d period during the 2014 ablation season using a network of 19 stations. Air temperature was found to be strongly dependent upon elevation for most stations, even under varying meteorological conditions and at different times of day, and its spatial variability was well explained by a locally derived mean linear TG (MG–TG) of −0.0088°C m−1. However, local temperature depressions occurred over areas of very thin or patchy debris cover. The MG–TG, together with other air TGs, extrapolated from both on- and off-glacier sites, were applied in a distributed energy-balance model. Compared with piecewise air temperature extrapolation from all on-glacier stations, modelled ablation, using the MG–TG, increased by <1%, increasing to >4% using the environmental ‘lapse rate’. Ice melt under thick debris was relatively insensitive to air temperature, while the effects of different temperature extrapolation methods were strongest at high elevation sites of thin and patchy debris cover.


1996 ◽  
Vol 6 (2) ◽  
pp. 71 ◽  
Author(s):  
BE Potter

Lower atmosphere moistures, temperatures, winds, and lapse rates are examined for the days of 339 fires over 400 ha in the United States from 1971 through 1984. These quantities are compared with a climatology dataset from the same 14-year period using 2-way unbalanced analysis of variance. The results show that the fire-day surface-air temperature and moisture differ from the climatology at the 0.001 significance level. Near-surface wind shear does not appear to differ significantly between fire and climatology days. Results are inconclusive for wind speed and surface lapse rate.


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