TECHNIQUE POUR ECHANTILLONNER LES RACINES DE PLANTES DANS LE SOL GELE ET ENNEIGE

1976 ◽  
Vol 56 (3) ◽  
pp. 633-638 ◽  
Author(s):  
R. BOLDUC

A tubular drill has been designed to extract a frozen soil core 12–15 cm in diameter and 15–40 cm in length with the roots and collars of intact plants. A snow cylinder is used to clear the sampling spot, causing minimum disturbance to the snow cover. This equipment makes possible a large scale study of vegetation during the cold season.

2010 ◽  
Vol 24 (13) ◽  
pp. 1755-1765 ◽  
Author(s):  
Yukiyoshi Iwata ◽  
Tomoyoshi Hirota ◽  
Masaki Hayashi ◽  
Shinji Suzuki ◽  
Shuichi Hasegawa

2019 ◽  
Vol 32 (18) ◽  
pp. 6015-6033 ◽  
Author(s):  
Lars Gerlitz ◽  
Eva Steirou ◽  
Christoph Schneider ◽  
Vincent Moron ◽  
Sergiy Vorogushyn ◽  
...  

Abstract Central Asia (CA) is subjected to a large variability of precipitation. This study presents a statistical model, relating precipitation anomalies in three subregions of CA in the cold season (November–March) with various predictors in the preceding October. Promising forecast skill is achieved for two subregions covering 1) Uzbekistan, Turkmenistan, Kyrgyzstan, Tajikistan, and southern Kazakhstan and 2) Iran, Afghanistan, and Pakistan. ENSO in October is identified as the major predictor. Eurasian snow cover and the quasi-biennial oscillation further improve the forecast performance. To understand the physical mechanisms, an analysis of teleconnections between these predictors and the wintertime circulation over CA is conducted. The correlation analysis of predictors and large-scale circulation indices suggests a seasonal persistence of tropical circulation modes and a dynamical forcing of the westerly circulation by snow cover variations over Eurasia. An EOF analysis of pressure and humidity patterns allows separating the circulation variability over CA into westerly and tropical modes and confirms that the identified predictors affect the respective circulation characteristics. Based on the previously established weather type classification for CA, the predictors are investigated with regard to their effect on the regional circulation. The results suggest a modification of the Hadley cell due to ENSO variations, with enhanced moisture supply from the Arabian Gulf during El Niño. They further indicate an influence of Eurasian snow cover on the wintertime Arctic Oscillation (AO) and Northern Hemispheric Rossby wave tracks. Positive anomalies favor weather types associated with dry conditions, while negative anomalies promote the formation of a quasi-stationary trough over CA, which typically occurs during positive AO conditions.


2021 ◽  
Vol 18 (20) ◽  
pp. 5767-5787
Author(s):  
Alexandra Pongracz ◽  
David Wårlind ◽  
Paul A. Miller ◽  
Frans-Jan W. Parmentier

Abstract. The Arctic is warming rapidly, especially in winter, which is causing large-scale reductions in snow cover. Snow is one of the main controls on soil thermodynamics, and changes in its thickness and extent affect both permafrost thaw and soil biogeochemistry. Since soil respiration during the cold season potentially offsets carbon uptake during the growing season, it is essential to achieve a realistic simulation of the effect of snow cover on soil conditions to more accurately project the direction of arctic carbon–climate feedbacks under continued winter warming. The Lund–Potsdam–Jena General Ecosystem Simulator (LPJ-GUESS) dynamic vegetation model has used – up until now – a single layer snow scheme, which underestimated the insulation effect of snow, leading to a cold bias in soil temperature. To address this shortcoming, we developed and integrated a dynamic, multi-layer snow scheme in LPJ-GUESS. The new snow scheme performs well in simulating the insulation of snow at hundreds of locations across Russia compared to observations. We show that improving this single physical factor enhanced simulations of permafrost extent compared to an advanced permafrost product, where the overestimation of permafrost cover decreased from 10 % to 5 % using the new snow scheme. Besides soil thermodynamics, the new snow scheme resulted in a doubled winter respiration and an overall higher vegetation carbon content. This study highlights the importance of a correct representation of snow in ecosystem models to project biogeochemical processes that govern climate feedbacks. The new dynamic snow scheme is an essential improvement in the simulation of cold season processes, which reduces the uncertainty of model projections. These developments contribute to a more realistic simulation of arctic carbon–climate feedbacks.


1985 ◽  
Vol 6 ◽  
pp. 123-125
Author(s):  
Daiji Kobayashi ◽  
Hideaki Motoyama

A large scale study on the dependence of time lag of runoff on snow depth and stratigraphy was carried out in a watershed. The time lag in peak runoff was found to be increased by 1.5 - 4 h per I m increment in snow depth. Although the data were widely scattered, it was found that the time lag series converged in a line every year and that discrete layers in the snow cover composed in a warm winter, accelerated meltwater flow.Subtracting the time of propagation through a snowcover from the total time lag, the effect of size of a watershed on a delay in runoff was rearranged, as follows: where Tf is the time lag in min after discharge from a snow cover, A the area of a watershed in km2, Re the effective snowmelt in mm/hr. The time lag Tf increases only by 1.5 times when an area of a watershed is increased by a factor of ten.


2021 ◽  
Author(s):  
Alexandra Pongracz ◽  
David Wårlind ◽  
Paul A. Miller ◽  
Frans-Jan W. Parmentier

Abstract. The Arctic is warming rapidly, especially in winter, which is causing large-scale reductions in snow cover. Snow is one of the main controls on soil thermodynamics, and changes in its thickness and extent affect both permafrost thaw and soil biogeochemistry. Since soil respiration during the cold season potentially offsets carbon uptake during the growing season, it is essential to achieve a realistic simulation of the effect of snow cover on soil conditions to more accurately project the direction of arctic carbon-climate feedbacks under continued winter warming. The Lund-Potsdam-Jena General Ecosystem Simulator (LPJ-GUESS) dynamic vegetation model has used – up until now – a single layer snow scheme, which underestimated the insulation effect of snow, leading to a cold bias in soil temperature. To address this shortcoming, we developed and integrated a dynamic, multi-layer snow scheme in LPJ-GUESS. The new snow scheme performs well in simulating the insulation of snow at hundreds of locations across Russia compared to observations. We show that improving this single physical factor enhanced simulations of permafrost extent compared to an advanced permafrost product. Besides soil thermodynamics, the new snow scheme resulted in increased winter respiration and an overall lower soil carbon content due to warmer soil conditions. The Dynamic scheme also influenced vegetation dynamics, resulting in an improved vegetation distribution and tundra-taiga boundary simulation. This study highlights the importance of a correct representation of snow in ecosystem models to project biogeochemical processes that govern climate feedbacks. The new dynamic snow scheme is an essential improvement in the simulation of cold season processes, which reduces the uncertainty of model projections. These developments contribute to a better understanding of the Arctic's role in the global climate system.


1985 ◽  
Vol 6 ◽  
pp. 123-125 ◽  
Author(s):  
Daiji Kobayashi ◽  
Hideaki Motoyama

A large scale study on the dependence of time lag of runoff on snow depth and stratigraphy was carried out in a watershed. The time lag in peak runoff was found to be increased by 1.5 - 4 h per I m increment in snow depth. Although the data were widely scattered, it was found that the time lag series converged in a line every year and that discrete layers in the snow cover composed in a warm winter, accelerated meltwater flow. Subtracting the time of propagation through a snowcover from the total time lag, the effect of size of a watershed on a delay in runoff was rearranged, as follows: where Tf is the time lag in min after discharge from a snow cover, A the area of a watershed in km2, Re the effective snowmelt in mm/hr. The time lag Tf increases only by 1.5 times when an area of a watershed is increased by a factor of ten.


2019 ◽  
Vol 79 ◽  
pp. 152-158 ◽  
Author(s):  
Kristoffer Sølvsten Burgdorf ◽  
Betina B. Trabjerg ◽  
Marianne Giørtz Pedersen ◽  
Janna Nissen ◽  
Karina Banasik ◽  
...  

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