scholarly journals On the Role of Snow Cover in Depressing Air Temperature

2008 ◽  
Vol 47 (7) ◽  
pp. 2008-2022 ◽  
Author(s):  
Thomas L. Mote
Keyword(s):  
Boundary Layer ◽  
North America ◽  
Snow Cover ◽  
Air Temperature ◽  
Snow Depth ◽  
Cloud Cover ◽  
Effect Of Temperature ◽  
Temperature Changes ◽  
Temperature Depression

Abstract This study empirically examines the role of snow depth on the depression of air temperature after controlling for effect of temperature changes above the boundary layer. In addition, this study examines the role of cloud cover, solar elevation angle, and maximum snow-covered albedo on the temperature depression due to snow cover. The work uses a new dataset of daily, gridded snow depth, snowfall, and maximum and minimum temperatures for North America from 1960 to 2000 in conjunction with 850-hPa temperature data for the same period from the NCEP–NCAR reanalysis, version 1. The 850-hPa temperatures are used as a control to remove the effect of temperature changes above the boundary layer on surface air temperatures. Findings from an analysis of variance demonstrate that snow cover can result in daily maximum (minimum) temperature depressions on average of 4.5°C (2.6°C) for snow depths greater than 10 cm over the grasslands of central North America, but temperature depressions average only 1.2°C (1.1°C) overall. The temperature depression of snow cover is shown to be reduced by increased cloud cover and decreased maximum albedo, which is indicative of denser forest cover. The role of snow melting on temperature depression is further explored by comparing days with maximum temperatures above or below freezing.

scholarly journals Spatio-Temporal Variation Characteristics of Snow Depth and Snow Cover Days over the Tibetan Plateau

Water ◽  
2021 ◽  
Vol 13 (3) ◽  
pp. 307
Author(s):  
Chi Zhang ◽  
Naixia Mou ◽  
Jiqiang Niu ◽  
Lingxian Zhang ◽  
Feng Liu
Keyword(s):  
Tibetan Plateau ◽  
Snow Cover ◽  
Snow Depth ◽  
Feedback Effect ◽  
Effect Of Temperature ◽  
The Tibetan Plateau ◽  
Reanalysis Dataset ◽  
Spatio Temporal ◽  
The Impact ◽  
Main Factor

Changes in snow cover over the Tibetan Plateau (TP) have a significant impact on agriculture, hydrology, and ecological environment of surrounding areas. This study investigates the spatio-temporal pattern of snow depth (SD) and snow cover days (SCD), as well as the impact of temperature and precipitation on snow cover over TP from 1979 to 2018 by using the ERA5 reanalysis dataset, and uses the Mann–Kendall test for significance. The results indicate that (1) the average annual SD and SCD in the southern and western edge areas of TP are relatively high, reaching 10 cm and 120 d or more, respectively. (2) In the past 40 years, SD (s = 0.04 cm decade−1, p = 0.81) and SCD (s = −2.3 d decade−1, p = 0.10) over TP did not change significantly. (3) The positive feedback effect of precipitation is the main factor affecting SD, while the negative feedback effect of temperature is the main factor affecting SCD. This study improves the understanding of snow cover change and is conducive to the further study of climate change on TP.

scholarly journals Effect of Temperature on Picloram Absorption and Translocation in Leafy Spurge (Euphorbia esula)

Weed Science ◽  
1990 ◽  
Vol 38 (6) ◽  
pp. 471-474 ◽  
Author(s):  
Rodney G. Lym ◽  
Calvin G. Messersmith
Keyword(s):  
Root System ◽  
Air Temperature ◽  
Leafy Spurge ◽  
Euphorbia Esula ◽  
Effect Of Temperature ◽  
Temperature Changes

Temperature changes prior to picloram application affects its activity in leafy spurge. Absorption of14C picloram was directly correlated with temperature changes; each 1 C increase in air temperature 24 h before treatment resulted in a 1% increase of14C-picloram absorption in leafy spurge and vice versa. The greatest14C-picloram absorption averaged 47% of applied14C when the temperature increased from 18 C to 24 or 30 C 24 h before treatment compared to 33% when temperatures were constant. Translocation of14C picloram was more sensitive than absorption to temperature changes with 4.3 and 1% of applied14C-picloram translocated to the roots when the plants were maintained at 12 and 30 C, respectively. Even though absorption increased directly with temperature,14C-picloram translocation to the root system declined as temperature increased.

scholarly journals Improvement of the Snow Depth in the Common Land Model by Coupling a Two-Dimensional Deterministic Ensemble Model with a Variational Hybrid Snow Cover Fraction Data Assimilation Scheme and a New Observation Operator

2017 ◽  
Vol 18 (1) ◽  
pp. 119-138 ◽  
Author(s):  
Jianhui Xu ◽  
Feifei Zhang ◽  
Hong Shu ◽  
Kaiwen Zhong
Keyword(s):  
Data Assimilation ◽  
Snow Cover ◽  
Snow Depth ◽  
Cloud Cover ◽  
Two Dimensional ◽  
Observation Operator ◽  
Snow Cover Fraction ◽  
Depletion Curve ◽  
Common Land Model ◽  
The Common

Abstract During snow cover fraction (SCF) data assimilation (DA), the simplified observation operator and presence of cloud cover cause large errors in the assimilation results. To reduce these errors, a new snow cover depletion curve (SDC), known as an observation operator in the DA system, is statistically fitted to in situ snow depth (SD) observations and Moderate Resolution Imaging Spectroradiometer (MODIS) SCF data from January 2004 to October 2008. Using this new SDC, a two-dimensional deterministic ensemble–variational hybrid DA (2DEnVar) method of integrating the deterministic ensemble Kalman filter (DEnKF) and a two-dimensional variational DA (2DVar) is proposed. The proposed 2DEnVar is then used to assimilate the MODIS SCF into the Common Land Model (CoLM) at five sites in the Altay region of China for data from November 2008 to March 2009. The analysis performance of the 2DEnVar is compared with that of the DEnKF. The results show that the 2DEnVar outperforms the DEnKF as it effectively reduces the bias and root-mean-square error during the snow accumulation and ablation periods at all sites except for the Qinghe site. In addition, the 2DEnVar, with more assimilated MODIS SCF observations, produces more innovations (observation minus forecast) than the DEnKF, with only one assimilated MODIS SCF observation. The problems of cloud cover and overestimation are addressed by the 2DEnVar.

scholarly journals The role of snow and ice thickness on river ice process in Songhua River basin, Northeast China

2019 ◽  
Author(s):  
Qian Yang ◽  
Kaishan Song ◽  
Xiaohua Hao ◽  
Zhidan Wen ◽  
Yue Tan ◽  
...  
Keyword(s):  
River Basin ◽  
Air Temperature ◽  
Snow Depth ◽  
Northeast China ◽  
River Ice ◽  
Ice Thickness ◽  
Songhua River ◽  
Songhua River Basin ◽  
Ice Phenology

Abstract. Songhua River basin is a sensitive area to global warming in Northeast China that could be indicated by changes in lake and river ice development. The regional role and trends of ice characteristics of this area have been scarcely investigated, which are critical for aquatic ecosystem, climate variability, and human activities. Based on the ice record of hydrological stations, we examined the spatial variations of the ice phenology and ice thickness in Songhua River basin in Northeast China from 2010 to 2015 and explored the role of ice thickness, snow during ice-on and ice-off process. All five river ice phenology including freeze-up start, freeze-up end, break-up start, break-up end and complete frozen duration showed latitudinal distribution and a changing direction from southeast to northwest, and five typically geographic zones were identified based on rotated empirical orthogonal function. Maximum ice thickness had a higher correlation with five parameters than that of average snow depth and air temperature on bank. A linear regression function was established between ice thickness and snow depth on ice and indicated ice thickness was closely associated with snow depth on ice. The air temperature had higher correlation with ice phenology and influenced the lake ice phenology significantly, and snow cover did not show significant correlation with the ice phenology. However, snow cover correlated with ice thickness significantly and positively during the periods when the freshwater is completely frozen.

Influence of December snow cover over North America on January surface air temperature over the midlatitude Asia

2019 ◽  
Vol 40 (1) ◽  
pp. 572-584
Author(s):  
Jingyi Li ◽  
Fei Li ◽  
Shengping He ◽  
Huijun Wang ◽  
Yvan J. Orsolini
Keyword(s):  
North America ◽  
Snow Cover ◽  
Air Temperature ◽  
Surface Air Temperature

scholarly journals CHERNOHIRSKYI TRAIL AS A BRAND OF UKRAINIAN HIKING TOURISM

2020 ◽  
pp. 17-25
Author(s):  
Viktor Vyshnevskyi
Keyword(s):  
Snow Cover ◽  
Air Temperature ◽  
Three Dimensional ◽  
Climatic Conditions ◽  
Practical Significance ◽  
Southeastern Part ◽  
Tourist Attractions ◽  
Temperature Changes ◽  
Dimensional Image ◽  
Second World

Aim: promotion of the walking route by the Chornohora Ridge of the Ukrainian Carpathians in the section from Hoverla to Pip Ivan mountain. Methods: observation, measurement, description, comparison, analysis, analogy, cartographic, statistical. Based on radar survey data SRTM and Global Mapper program it was created a three-dimensional image of the studied region. The SAS.Planet program was used to measure distances. Results: A three-dimensional image of the Ukrainian Carpathians was created using SRTM data. The main information about the highest Chornohirskyi Ridge in these mountains was presented. The route from Hoverla to Pip Ivan mountain is described. It is proposed to call it the Chernohirskyi Trail. Data on the height of the terrain at the beginning and end of the route are shown. A brief description of the tourist attractions on the trail is provided, including lakes Nesamovyte and Brebeneskul. Information on the meteorological and at the same time astronomical observatory "White Elephant", which was built on the eve of the Second World War was presented. Modern measures for its restoration are described, in particular as to installation of an automated meteorological station on its roof. Based on observations on nearby meteorological stations, the climatic conditions on the route were identified. Data about air temperature in January and in the warm period of the year are presented. The features of air temperature changes, depending on elevation, are established. Data on the amount of precipitation at existing meteorological stations in the mountains are provided. Information on the height of snow cover was presented. The features of snow formation and its disappearance in the southeastern part of the Ukrainian Carpathians are shown. Scientific novelty. The hiking route by the Chornohora Ridge of the Ukrainian Carpathians is substantiated as brand of Ukrainian hiking tourism. The expediency of traffic from Hoverla to Pip Ivan has been proved. It was found that at altitudes above 1000 m the decrease in air temperature in July is 0.40 C per 100 m altitude, in August – 0.30 C per 100 m. It is substantiated that the best time to travel along the Chornohirskyi Ridge is August. The significant distribution of snow cover on the Chornohirskyi Ridge, which is the highest within the Ukrainian Carpathians, is shown. Practical significance: popularization of tourism in the Ukrainian Carpathians, providing tourists with information to make travel more interesting and safe.

scholarly journals Snow Depth and Air Temperature Seasonality on Sea Ice Derived From Snow Buoy Measurements

2021 ◽  
Vol 8 ◽  
Author(s):  
Marcel Nicolaus ◽  
Mario Hoppmann ◽  
Stefanie Arndt ◽  
Stefan Hendricks ◽  
Christian Katlein ◽  
...  
Keyword(s):  
Sea Ice ◽  
Snow Cover ◽  
Air Temperature ◽  
Snow Depth ◽  
Snow Accumulation ◽  
Arctic Sea Ice ◽  
Weddell Sea ◽  
The Arctic ◽  
Validation Data ◽  
Antarctic Sea Ice

Snow depth on sea ice is an essential state variable of the polar climate system and yet one of the least known and most difficult to characterize parameters of the Arctic and Antarctic sea ice systems. Here, we present a new type of autonomous platform to measure snow depth, air temperature, and barometric pressure on drifting Arctic and Antarctic sea ice. “Snow Buoys” are designed to withstand the harshest environmental conditions and to deliver high and consistent data quality with minimal impact on the surface. Our current dataset consists of 79 time series (47 Arctic, 32 Antarctic) since 2013, many of which cover entire seasonal cycles and with individual observation periods of up to 3 years. In addition to a detailed introduction of the platform itself, we describe the processing of the publicly available (near real time) data and discuss limitations. First scientific results reveal characteristic regional differences in the annual cycle of snow depth: in the Weddell Sea, annual net snow accumulation ranged from 0.2 to 0.9 m (mean 0.34 m) with some regions accumulating snow in all months. On Arctic sea ice, the seasonal cycle was more pronounced, showing accumulation from synoptic events mostly between August and April and maxima in autumn. Strongest ablation was observed in June and July, and consistently the entire snow cover melted during summer. Arctic air temperature measurements revealed several above-freezing temperature events in winter that likely impacted snow stratigraphy and thus preconditioned the subsequent spring snow cover. The ongoing Snow Buoy program will be the basis of many future studies and is expected to significantly advance our understanding of snow on sea ice, also providing invaluable in situ validation data for numerical simulations and remote sensing techniques.

Detection of precipitation and snow cover trends in the the European Alps over the last century using model and observational data

2020 ◽  
Author(s):  
Julien Beaumet ◽  
Martin Menegoz ◽  
Hubert Gallée ◽  
Vincent Vionnet ◽  
Xavier Fettweis ◽  
...  
Keyword(s):  
Climate Change ◽  
Snow Cover ◽  
Observational Data ◽  
Snow Depth ◽  
European Alps ◽  
Temperature Changes ◽  
In Situ Observations ◽  
Precipitation Changes ◽  
High Elevations

<p><span>The European Alps are particularly sensitive to climate change. Compared to temperature, changes in precipitation are more challenging to detect and attribute to ongoing anthropic climate change </span><span>mainly </span><span>as a result of large inter-annual variability, </span><span>lack of reliable measurements at high elevations</span><span> and opposite signals depending on the season or the elevation considered. However, changes in precipitation and snow cover have significant socio-environmental impact mostly trough water resource availability. These changes are investigated within the framework of the Trajectories initiative (</span><span><span></span></span><span>). The variability and changes in precipitation and snow cover in the European Alps has been simulated with the MAR regional climate model at a 7 km horizontal resolution driven by ERA20C (1902-2010) and ERA5 (1979-2018) reanalyses. </span></p><p><span>For precipitation, MAR outputs were compared with EURO-4M, SAFRAN, SPAZM and E-OBS reanalyses as well as in-situ observations. The model was shown to reproduce correctly seasonal and inter-annual variability. The spatial biases of the model have the same order of magnitude as the differences between the three observational data sets. Model experiment has been used to detect precipitation changes over the last century. An increase in winter precipitation is simulated over the North-western part of the Alps at high altitudes (>1500m). Significant decreases in summer precipitation were found in many low elevation areas, especially the Po Plain while no significant trends where found at high elevations. Because of large internal variability, precipitation changes are significant (pvalue<0.05) only when considering their evolution over long period, typically 60-100 years in both model and observations.</span></p><p><span>Snow depth and water equivalent (SWE) in the French Alps simulated with MAR have been compared to the SAFRAN-Crocus reanalyses and to in-situ observations. MAR was found to simulate a realistic distribution of SWE as function of the elevation in the French Alpine massifs, although it underestimates SWE at low elevations in the Pre-Alps. Snow cover over the whole European Alps is evaluated using MODIS satellite data. Finally, trends in snow cover and snow depth are highlighted as well as their relationships with the precipitation and temperature changes over the last century. </span></p>

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