Air temperature thresholds to evaluate snow melting at the surface of Alpine glaciers by T-index models: the case study of Forni Glacier (Italy)

Abstract. The glacier melt conditions (i.e.: null surface temperature and positive energy budget) can be assessed by analyzing meteorological and energy data acquired by a supraglacial Automatic Weather Station (AWS). In the case this latter is not present the assessment of actual melting conditions and the evaluation of the melt amount is difficult and simple methods based on T-index (or degree days) models are generally applied. These models require the choice of a correct temperature threshold. In fact, melt does not necessarily occur at daily air temperatures higher than 273.15 K. In this paper, to detect the most indicative threshold witnessing melt conditions in the April–June period, we have analyzed air temperature data recorded from 2006 to 2012 by a supraglacial AWS set up at 2631 m a.s.l. on the ablation tongue of the Forni Glacier (Italian Alps), and by a weather station located outside the studied glacier (at Bormio, a village at 1225 m a.s.l.). Moreover we have evaluated the glacier energy budget and the Snow Water Equivalent (SWE) values during this time-frame. Then the snow ablation amount was estimated both from the surface energy balance (from supraglacial AWS data) and from T-index method (from Bormio data, applying the mean tropospheric lapse rate and varying the air temperature threshold) and the results were compared. We found that the mean tropospheric lapse rate permits a good and reliable reconstruction of glacier air temperatures and the major uncertainty in the computation of snow melt is driven by the choice of an appropriate temperature threshold. From our study using a 5.0 K lower threshold value (with respect to the largely applied 273.15 K) permits the most reliable reconstruction of glacier melt.

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Using daily air temperature thresholds to evaluate snow melting occurrence and amount on Alpine glaciers by <i>T</i>-index models: the case study of the Forni Glacier (Italy)

The Cryosphere ◽

10.5194/tc-8-1921-2014 ◽

2014 ◽

Vol 8 (5) ◽

pp. 1921-1933 ◽

Cited By ~ 22

Author(s):

A. Senese ◽

M. Maugeri ◽

E. Vuillermoz ◽

C. Smiraglia ◽

G. Diolaiuti

Keyword(s):

Air Temperature ◽

Energy Budget ◽

Snow Depth ◽

Lapse Rate ◽

Positive Energy ◽

Temperature Threshold ◽

Snow Melting ◽

Air Temperatures ◽

Temperature Thresholds ◽

The Mean

Abstract. Glacier melt conditions (i.e., null surface temperature and positive energy budget) can be assessed by analyzing data acquired by a supraglacial automatic weather station (AWS), such as the station installed on the surface of Forni Glacier (Italian Alps). When an AWS is not present, the assessment of actual melt conditions and the evaluation of the melt amount is more difficult and simple methods based on T-index (or degree days) models are generally applied. These models require the choice of a correct temperature threshold. In fact, melt does not necessarily occur at daily air temperatures higher than 0 °C. In this paper, we applied both energy budget and T-index approaches with the aim of solving this issue. We start by distinguishing between the occurrence of snowmelt and the reduction in snow depth due to actual ablation (from snow depth data recorded by a sonic ranger). Then we find the daily average temperature thresholds (by analyzing temperature data acquired by an AWS on Forni Glacier) which, on the one hand, best capture the occurrence of significant snowmelt conditions and, on the other, make it possible, using the T-index, to quantify the actual snow ablation amount. Finally we investigated the applicability of the mean tropospheric lapse rate to reproduce air temperature conditions at the glacier surface starting from data acquired by weather stations located outside the glacier area. We found that the mean tropospheric lapse rate allows for a good and reliable reconstruction of glacier air temperatures and that the choice of an appropriate temperature threshold in T-index models is a very important issue. From our study, the application of the +0.5 °C temperature threshold allows for a consistent quantification of snow ablation while, instead, for detecting the beginning of the snow melting processes a suitable threshold has proven to be at least −4.6 °C.

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Direct Calculation of Thermodynamic Wet-Bulb Temperature as a Function of Pressure and Elevation

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-12-00191.1 ◽

2013 ◽

Vol 30 (8) ◽

pp. 1757-1765 ◽

Cited By ~ 10

Author(s):

Sayed-Hossein Sadeghi ◽

Troy R. Peters ◽

Douglas R. Cobos ◽

Henry W. Loescher ◽

Colin S. Campbell

Keyword(s):

Air Temperature ◽

Mean Absolute Error ◽

Direct Calculation ◽

Ambient Air ◽

Absolute Error ◽

Mean Square ◽

Air Temperatures ◽

Order Polynomial ◽

The Mean ◽

Very High

Abstract A simple analytical method was developed for directly calculating the thermodynamic wet-bulb temperature from air temperature and the vapor pressure (or relative humidity) at elevations up to 4500 m above MSL was developed. This methodology was based on the fact that the wet-bulb temperature can be closely approximated by a second-order polynomial in both the positive and negative ranges in ambient air temperature. The method in this study builds upon this understanding and provides results for the negative range of air temperatures (−17° to 0°C), so that the maximum observed error in this area is equal to or smaller than −0.17°C. For temperatures ≥0°C, wet-bulb temperature accuracy was ±0.65°C, and larger errors corresponded to very high temperatures (Ta ≥ 39°C) and/or very high or low relative humidities (5% < RH < 10% or RH > 98%). The mean absolute error and the root-mean-square error were 0.15° and 0.2°C, respectively.

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Rail Temperature Approximation and Heat Slow Order Best Practices

2015 Joint Rail Conference ◽

10.1115/jrc2015-5720 ◽

2015 ◽

Cited By ~ 1

Author(s):

Radim Bruzek ◽

Michael Trosino ◽

Leopold Kreisel ◽

Leith Al-Nazer

Keyword(s):

Air Temperature ◽

Geographical Location ◽

Ambient Air ◽

Temperature Threshold ◽

Eastern United States ◽

Ambient Air Temperature ◽

Air Temperatures ◽

The Difference ◽

Temperature Offset ◽

Environmental Prediction

The railroad industry uses slow orders, sometimes referred to as speed restrictions, in areas where an elevated rail temperature is expected in order to minimize the risk and consequence of derailment caused by track buckling due to excessive rail temperature. Traditionally, rail temperature has been approximated by adding a constant offset, most often 30°F, to a peak ambient air temperature. When this approximated maximum rail temperature exceeds a given risk threshold, slow orders are usually issued for a predefined period of the day. This “one size fits all” approach, however, is not effective and suitable in all situations. On very warm days, the difference between rail temperature and ambient air temperature can exceed railroad-employed offsets and remain elevated for extended periods of time. A given temperature offset may be well suited for certain regions and track buckling risk-related rail temperature thresholds but less accurate for others. Almost 160,000 hours of rail temperature measurements collected in 2012 across the eastern United States by two Class I railroads and predicted ambient air temperatures based on the National Weather Service’s National Centers for Environmental Prediction (NCEP) data were analyzed using detection theory in order to establish optimal values of offsets between air and rail temperatures as well as times when slow orders should be in place based on geographical location and the track buckling risk rail temperature threshold. This paper presents the results of the analysis and describes an improved procedure to manage heat-related slow orders based on ambient air temperatures.

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Suitability of a constant air temperature lapse rate over an Alpine glacier: testing the Greuell and Böhm model as an alternative

Annals of Glaciology ◽

10.3189/2013aog63a477 ◽

2013 ◽

Vol 54 (63) ◽

pp. 120-130 ◽

Cited By ~ 31

Author(s):

Lene Petersen ◽

Francesca Pellicciotti ◽

Inge Juszak ◽

Marco Carenzo ◽

Ben Brock

Keyword(s):

Air Temperature ◽

Surface Air Temperature ◽

Ambient Air ◽

Lapse Rate ◽

Spatial And Temporal Variability ◽

Near Surface ◽

Alpine Glacier ◽

Temperature Lapse Rate ◽

Boundary Layer Height ◽

Air Temperatures

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.

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Study of laws of spatial variation of the mean air temperature for the growing season on the territory of the Crimean Peninsula

Magarach. Vinogradstvo i Vinodelie ◽

10.35547/im.2020.29.71.007 ◽

2020 ◽

pp. 120-124

Author(s):

Евгений Александрович Рыбалко ◽

Наталья Валентиновна Баранова ◽

Виктория Юрьевна Борисова ◽

Валерий Семенович Петров

Keyword(s):

Spatial Distribution ◽

Spatial Variation ◽

Air Temperature ◽

Growing Season ◽

Reference Points ◽

Weather Station ◽

Crimean Peninsula ◽

The Mean ◽

The Crimean Peninsula

В статье приведен анализ метеорологической информации по средней температуре воздуха за вегетационный период на территории Крымского полуострова. Рассчитано среднее многолетнее значение в точках расположения метеостанций с длинным рядом метеонаблюдений на территории Крымского полуострова. При расчетах использовали многолетние данные за 30 лет по 17 метеостанциям Крымского полуострова. Для моделирования пространственного распределения величины средней температуры воздуха на первом этапе также была выбрана глобальная климатическая модель WorldClim 2.0. На её основе рассчитаны величины исследуемого показателя для опорных точек. Произведена корректировка данных модели WorldClim 2.0 путём прибавления к результатам расчёта поправки 0,99, что несколько повысило точность моделирования. Составлена также линейная многофакторная модель, учитывающая географическую широту местности и абсолютную высоту над уровнем моря. Установлено, что в зависимости от географического положения метеостанции значения средних многолетних температур воздуха составляют от 17,9 °С (Белогорск) до 20,0 °С (Феодосия, Ялта). Проанализированы при помощи технологий геоинформационного моделирования закономерности пространственного варьирования величины средней температуры. В результате проведенного анализа были получены модели, описывающие данные закономерности. С помощью полученных моделей, разработана цифровая крупномасштабная картографическая модель пространственного распределения величины средней температуры воздуха, на основе которой на территории Крымского полуострова выделено 4 зоны. Разработанная модель, в сочетании с современными геоинформационными технологиями дает возможность автоматизировать анализ степени пригодности территории для возделывания винограда. The article provides the analysis of meteorological information of the mean air temperature for the growing season on the territory of the Crimean Peninsula. The long-term mean value in the points of weather station locations with a long series of weather observations on the territory of the Crimean Peninsula was calculated. For calculations we used the long-term data for 30 years on 17 weather stations of the Crimean Peninsula. To simulate the spatial distribution of the mean air temperature value at the first stage, the WorldClim 2.0 global climate model was also selected. The values of the studied parameter for reference points were calculated on its basis. The data of the WorldClim 2.0 model was adjusted by adding an error correction of 0.99 to the results of calculation, which slightly increased the modeling accuracy. A linear multivariate model was also compiled, taking into account the geographical latitude of the terrain and the absolute height above sea level. It was established that, depending on the geographical location of the weather station, the values of long-term mean air temperatures range from 17.9 ° C (Belogorsk) to 20.0 ° C (Feodosia, Yalta). The patterns of spatial variation of the mean temperature were analyzed using the technologies of geoinformation modeling. Models describing these patterns were obtained as a result of the analysis. Using the models received, a digital large-scale cartographic model of the spatial distribution of the mean air temperature was developed. On its basis 4 zones on the territory of the Crimean Peninsula were allocated. The developed model, in combination with modern geoinformation technologies, makes it possible to automate the analysis of fitness degree of the territory for grapes cultivating.

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Spatial and temporal variation of surface air temperature at different altitude zone in recent 30 years over Nepal

MAUSAM ◽

10.54302/mausam.v68i3.649 ◽

2021 ◽

Vol 68 (3) ◽

pp. 417-428

Author(s):

JANAK LAL NAYAVA ◽

SUNIL ADHIKARY ◽

OM RATNA BAJRACHARYA

Keyword(s):

Air Temperature ◽

Surface Air Temperature ◽

Temperature Data ◽

Lapse Rate ◽

Spatial And Temporal Variation ◽

Mountain Regions ◽

Temperature Lapse Rate ◽

Air Temperatures ◽

Long Term Trend

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.

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Using Leaf Temperature to Improve Simulation of Heat and Drought Stresses in a Biophysical Model

Plants ◽

10.3390/plants9010008 ◽

2019 ◽

Vol 9 (1) ◽

pp. 8 ◽

Cited By ~ 1

Author(s):

Ruchika S. Perera ◽

Brendan R. Cullen ◽

Richard J. Eckard

Keyword(s):

Heat Stress ◽

Air Temperature ◽

Energy Budget ◽

Perennial Ryegrass ◽

Measured Data ◽

Leaf Temperature ◽

Biophysical Model ◽

Controlled Environment ◽

Air Temperatures ◽

Environment Experiment

Despite evidence that leaf temperatures can differ by several degrees from the air, crop simulation models are generally parameterised with air temperatures. Leaf energy budget is a process-based approach that can be used to link climate and physiological processes of plants, but this approach has rarely been used in crop modelling studies. In this study, a controlled environment experiment was used to validate the use of the leaf energy budget approach to calculate leaf temperature for perennial pasture species, and a modelling approach was developed utilising leaf temperature instead of air temperature to achieve a better representation of heat stress impacts on pasture growth in a biophysical model. The controlled environment experiment assessed the impact of two combined seven-day heat (control = 25/15 °C, day/night, moderate = 30/20 °C, day/night, and severe = 35/25 °C, day/night) and drought stresses (with seven-day recovery period between stress periods) on perennial ryegrass (Lolium perenne L.), cocksfoot (Dactylis glomerata L.), tall fescue (Festuca arundinacea Schreb.) and chicory (Cichorium intybus L.). The leaf temperature of each species was modelled by using leaf energy budget equation and validated with measured data. All species showed limited homeothermy with the slope of 0.88 (P < 0.05) suggesting that pasture plants can buffer temperature variations in their growing environment. The DairyMod biophysical model was used to simulate photosynthesis during each treatment, using both air and leaf temperatures, and the patterns were compared with measured data using a response ratio (effect size compared to the well-watered control). The effect size of moderate heat and well-watered treatment was very similar to the measured values (~0.65) when simulated using T leaf, while T air overestimated the consecutive heat stress impacts (0.4 and 0). These results were used to test the heat stress recovery function (Tsum) of perennial ryegrass in DairyMod, finding that recovery after heat stress was well reproduced when parameterized with T sum = 20, while T sum = 50 simulated a long lag phase. Long term pasture growth rate simulations under irrigated conditions in south eastern Australia using leaf temperatures predicted 6–34% and 14–126% higher pasture growth rates, respectively at Ellinbank and Dookie, during late spring and summer months compared to the simulations using air temperatures. This study demonstrated that the simulation of consecutive heat and/or drought stress impacts on pasture production, using DairyMod, can be improved by using leaf temperatures instead of air temperature.

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Influence of air temperature on a glacier’s active-layer temperature

Annals of Glaciology ◽

10.3189/172756406781812203 ◽

2006 ◽

Vol 43 ◽

pp. 285-291 ◽

Cited By ~ 16

Author(s):

V. Zagorodnov ◽

O. Nagornov ◽

L.G. Thompson

Keyword(s):

Active Layer ◽

Air Temperature ◽

Seasonal Temperature ◽

Temperature Variations ◽

Surface Conditions ◽

Tropical Glaciers ◽

Air Temperatures ◽

Screen Level ◽

The Mean

AbstractSeasonal temperature variations occur in the glacier layer about 15–20 m below the surface, while at greater depths the glacier temperature depends on the long-term surface conditions. It is generally accepted that for glaciers without surface melting the temperature at 10 m depth (T10) is close to the mean annual air temperature at standard screen level (Ta), i.e. T10 =Ta. We found that this relationship is not valid for Ta above –17˚C and below –55˚C. The goal of our investigation is to find a better temperature transfer function (TTF) between Ta and temperature at the boundary of the active layer in accumulation areas of polar and tropical glaciers. Low-precision T10 temperatures from boreholes, obtained at 41 sites, are compared with air temperatures (Ta) measured in the vicinity of these sites for at least a 1 year period. We determine that when Ta falls into the temperature range –60 to –7˚C, empirical values can be approximated as T10 = 1:2Ta + 6:7. Analysis of these data suggests that high T10 occurs in the areas of the glacier that collect meltwater.

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Daily air temperature estimation on glacier surfaces in the Tibetan Plateau using MODIS LST data

Journal of Glaciology ◽

10.1017/jog.2018.6 ◽

2018 ◽

Vol 64 (243) ◽

pp. 132-147 ◽

Cited By ~ 10

Author(s):

HONGBO ZHANG ◽

FAN ZHANG ◽

GUOQING ZHANG ◽

YAOMING MA ◽

KUN YANG ◽

...

Keyword(s):

Tibetan Plateau ◽

Air Temperature ◽

Lapse Rate ◽

The Tibetan Plateau ◽

Mean Square ◽

Night Time ◽

Glacier Surface ◽

Temperature Estimation ◽

Air Temperatures ◽

Air Temperature Estimation

ABSTRACTThe MODerate resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) data have been widely used for air temperature estimation in mountainous regions where station observations are sparse. However, the performance of MODIS LST in high-elevation glacierized areas remains unclear. This study investigates air temperature estimation in glacierized areas based on ground observations at four glaciers across the Tibetan Plateau. Before being used to estimate the air temperature, MODIS LST data are evaluated at two of the glaciers, which indicates that MODIS night-time LST is more reliable than MODIS daytime LST data. Then, linear models based on each of the individual MODIS LST products from two platforms (Terra and Aqua) and two overpasses (night-time and daytime) are built to estimate daily mean, minimum and maximum air temperatures in glacierized areas. Regional glacier surface (RGS) models (mean /-mean-square differences: 3.3, 3.0 and 4.8°C for daily mean, minimum and maximum air temperatures, respectively) show higher accuracy than local non-glacier surface models (mean root-mean-square differences: 4.2, 4.7 and 5.7°C). In addition, the RGS models based on MODIS night-time LST perform better to estimate daily mean, minimum and maximum air temperatures than using temperature lapse rate derived from local stations.

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Analysis of Microclimate and Cucumber Fruit Yield in a Screenhouse and an Evaporatively Cooled Greenhouse in a Semi-Arid Location

Transactions of the ASABE ◽

10.13031/trans.12144 ◽

2018 ◽

Vol 61 (2) ◽

pp. 619-629 ◽

Cited By ~ 4

Author(s):

Yaseen A. Al-Mulla ◽

Mohammed I. Al-Balushi ◽

Hamad A. Al-Busaidi ◽

Adil A. Al-Mahdouri ◽

Constantinos Kittas ◽

...

Keyword(s):

Water Use Efficiency ◽

Water Use ◽

Air Temperature ◽

Fruit Quality ◽

Evaporative Cooling ◽

Quality Characteristics ◽

Summer Period ◽

Air Temperatures ◽

Use Efficiency ◽

The Mean

Abstract. The microclimate and cucumber crop response in a screenhouse and in an evaporatively cooled greenhouse were studied in Oman during winter/spring and spring/summer cultivation periods. Measurements were carried out in two similarly shaped structures: (1) a greenhouse equipped with a pad-and-fan system for evaporative cooling of the greenhouse environment and (2) a screenhouse with no cooling system. Analysis of the spring/summer period climate data showed that the evaporative cooling in the greenhouse reduced the mean air temperature by about 4.5°C compared to outside and maintained the leaf temperature close to the greenhouse air temperature. The 24 h mean leaf and air temperatures in the greenhouse reached 25.8°C ±1.3°C and 25.9°C ±0.8°C, respectively. On the other hand, the 24 h mean leaf and air temperatures in the screenhouse were higher by 1.0°C and 1.3°C, respectively, compared to outside. The 24 h mean leaf and air temperatures in the screenhouse reached 32.8°C ±1.2°C and 31.8°C ±1.5°C, respectively. Furthermore, the evaporative cooling in the greenhouse maintained the 24 h mean air vapor pressure deficit (VPD) values at levels lower than 1.1 kPa, while the 24 h mean air VPD in the screenhouse reached values up to 4.5 kPa. These differences resulted in a 50% decrease in crop fruit yield during the spring/summer period. The radiation and water use efficiency (WUE) values observed in the two structures were similar during the winter/spring period but were higher in the greenhouse during the spring/summer period. However, for the greenhouse, when the water evaporated in the wet pad was also considered, the overall WUE was at the same level in both structures during summer. Furthermore, the evaporative cooling applied in the greenhouse enhanced the mean values of fruit quality characteristics measured during the spring/summer, such as fruit dry matter content (5.6%), fruit firmness (5.0 kg cm-2), and chroma (18.6), compared to that of the screenhouse (5.0%, 4.9 kg cm-2 and 16.3, respectively), but did not significantly affect other fruit quality characteristics, such as mean fruit weight (128 g for greenhouse and 123 g for screenhouse), total soluble solids content (3.9 °Brix for both structures), and juice pH (5.7 for greenhouse and 5.6 for screenhouse). Overall, it can be concluded that under the weather conditions of Oman, although greenhouses are still needed during spring/summer, screenhouses can be used during winter without jeopardizing crop production quantity and quality. Keywords: Evaporative cooling, Evapotranspiration, Radiation use efficiency, Water user efficiency. Total water use efficiency, Climate.

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