scholarly journals The influence of the forest on night-time snow surface temperature

2001 ◽  
Vol 32 ◽  
pp. 217-222 ◽  
Author(s):  
Peter Höller
Keyword(s):  
Surface Temperature ◽  
Open Field ◽  
Air Temperature ◽  
Forest Canopy ◽  
Small Range ◽  
Snow Surface ◽  
Net Radiation ◽  
Night Time ◽  
Near Surface ◽  
Snow Surface Temperature

AbstractSnow surface temperature (Ts) plays an important role in the formation of surface hoar or near-surface faceted crystals The goal of this study was to obtain detailed information on Ts in different forest stands nelr the timberline. The investigations were conducted during clear nights and showed that the snow surface temperature is influenced very strongly by the forest canopy. While the air temperature was very similar on the different experimental sites, Ts was higher in the forest than in the open field; on the south-facing slope the difference between the forest and the open field was 3–4.5°C, and on the north-facing slope approximately 3–7°C. Taking into account that εair is 0.7 and εtree is 0.94, the incoming radiation (I ↓) for the different experimental sites was calculated by the equation of Brunt (the canopy density was estimated using photographs taken with an 8 mm fish-eye). To calculate Ts, air temperature and averaged values of the net radiation (because the net radiation (I) has only a small range of variation during clear nights) were used. The results show that the calculated values were higher than the measured values (by approximately 2°C). However, a better correlation was found by using lower values of the emissivity (εair0.67 and εtree0.91).

scholarly journals Aerodynamic and Radiative Controls on the Snow Surface Temperature

2016 ◽  
Vol 17 (8) ◽  
pp. 2175-2189 ◽  
Author(s):  
J. W. Pomeroy ◽  
R. L. H. Essery ◽  
W. D. Helgason
Keyword(s):  
Surface Temperature ◽  
Air Temperature ◽  
Infrared Radiation ◽  
Near Infrared ◽  
Longwave Radiation ◽  
Snow Surface ◽  
State Variables ◽  
Near Infrared Radiation ◽  
Snow Surface Temperature ◽  
Aerodynamic Roughness

Abstract The snow surface temperature (SST) is essential for estimating longwave radiation fluxes from snow. SST can be diagnosed using finescale multilayer snow physics models that track changes in snow properties and internal energy; however, these models are heavily parameterized, have high predictive uncertainty, and require continuous simulation to estimate prognostic state variables. Here, a relatively simple model to estimate SST that is not reliant on prognostic state variables is proposed. The model assumes that the snow surface is poorly connected thermally to the underlying snowpack and largely transparent for most of the shortwave radiation spectrum, such that a snow surface energy balance among only sensible heat, latent heat, longwave radiation, and near-infrared radiation is possible and is called the radiative psychrometric model (RPM). The RPM SST is sensitive to air temperature, humidity, ventilation, and longwave irradiance and is secondarily affected by absorption of near-infrared radiation at the snow surface that was higher where atmospheric deposition of particulates was more likely to be higher. The model was implemented with neutral stability, an implicit windless exchange coefficient, and constant shortwave absorption factors and aerodynamic roughness lengths. It was evaluated against radiative SST measurements from the Canadian Prairies and Rocky Mountains, French Alps, and Bolivian Andes. With optimized and global shortwave absorption and aerodynamic roughness length parameters, the model is shown to accurately predict SST under a wide range of conditions, providing superior predictions when compared to air temperature, dewpoint, or ice bulb calculation approaches.

scholarly journals Near–surface air temperature and snow skin temperature comparison from CREST-SAFE station data with MODIS land surface temperature data

2015 ◽  
Vol 12 (8) ◽  
pp. 7665-7687 ◽  
Author(s):  
C. L. Pérez Díaz ◽  
T. Lakhankar ◽  
P. Romanov ◽  
J. Muñoz ◽  
R. Khanbilvardi ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Skin Temperature ◽  
Air Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Hydrological Cycle ◽  
Critical Role ◽  
Surface Air Temperature ◽  
Balance Model ◽  
Near Surface

Abstract. Land Surface Temperature (LST) is a key variable (commonly studied to understand the hydrological cycle) that helps drive the energy balance and water exchange between the Earth's surface and its atmosphere. One observable constituent of much importance in the land surface water balance model is snow. Snow cover plays a critical role in the regional to global scale hydrological cycle because rain-on-snow with warm air temperatures accelerates rapid snow-melt, which is responsible for the majority of the spring floods. Accurate information on near-surface air temperature (T-air) and snow skin temperature (T-skin) helps us comprehend the energy and water balances in the Earth's hydrological cycle. T-skin is critical in estimating latent and sensible heat fluxes over snow covered areas because incoming and outgoing radiation fluxes from the snow mass and the air temperature above make it different from the average snowpack temperature. This study investigates the correlation between MODerate resolution Imaging Spectroradiometer (MODIS) LST data and observed T-air and T-skin data from NOAA-CREST-Snow Analysis and Field Experiment (CREST-SAFE) for the winters of 2013 and 2014. LST satellite validation is imperative because high-latitude regions are significantly affected by climate warming and there is a need to aid existing meteorological station networks with the spatially continuous measurements provided by satellites. Results indicate that near-surface air temperature correlates better than snow skin temperature with MODIS LST data. Additional findings show that there is a negative trend demonstrating that the air minus snow skin temperature difference is inversely proportional to cloud cover. To a lesser extent, it will be examined whether the surface properties at the site are representative for the LST properties within the instrument field of view.

scholarly journals Evaluation of alternative formulae for calculation of surface temperature in snowmelt models using frequency analysis of temperature observations

2009 ◽  
Vol 6 (3) ◽  
pp. 3863-3890 ◽  
Author(s):  
C. H. Luce ◽  
D. G. Tarboton
Keyword(s):  
Time Series ◽  
Energy Balance ◽  
Surface Temperature ◽  
Energy Flux ◽  
Frequency Analysis ◽  
Energy Content ◽  
Balance Model ◽  
Snow Surface ◽  
Fourier Frequency ◽  
Snow Surface Temperature

Abstract. The snow surface temperature is an important quantity in the snow energy balance, since it modulates the exchange of energy between the surface and the atmosphere as well as the conduction of energy into the snowpack. It is therefore important to correctly model snow surface temperatures in energy balance snowmelt models. This paper focuses on the relationship between snow surface temperature and conductive energy fluxed that drive the energy balance of a snowpack. Time series of snow temperature at the surface and through the snowpack were measured to examine energy conduction in a snowpack. Based on these measurements we calculated the snowpack energy content and conductive energy flux at the snow surface. We then used these estimates of conductive energy flux to evaluate formulae for the calculation of the conductive flux at the snow surface based on surface temperature time series. We use a method based on Fourier frequency analysis to estimate snow thermal properties. Among the formulae evaluated, we found that a modified force-restore formula, based on the superimposition of the force-restore equation capturing diurnal fluctuations on a gradually changing temperature gradient, had the best agreement with observations of heat conduction. This formula is suggested for the parameterization of snow surface temperature in a full snowpack energy balance model.

scholarly journals Modeling the snow surface temperature with a one-layer energy balance snowmelt model

2013 ◽  
Vol 10 (12) ◽  
pp. 15071-15118 ◽  
Author(s):  
J. You ◽  
D. G. Tarboton ◽  
C. H. Luce
Keyword(s):  
Energy Balance ◽  
Surface Temperature ◽  
Snow Water Equivalent ◽  
Effective Conductivity ◽  
Energy Content ◽  
Single Layer ◽  
Conductive Heat ◽  
Snow Surface ◽  
Snow Surface Temperature ◽  
Snowmelt Model

Abstract. \\label{sec:abstract} Snow surface temperature is a key control on energy exchanges at the snow surface, particularly net longwave radiation and turbulent energy fluxes. The snow surface temperature is in turn controlled by the balance between various external fluxes and the conductive heat flux, internal to the snowpack. Because of the strong insulating properties of snow, thermal gradients in snow packs are large and nonlinear, a fact that has led many to advocate multiple layer snowmelt models over single layer models. In an effort to keep snowmelt modeling simple and parsimonious, the Utah Energy Balance (UEB) snowmelt model used only one layer but allowed the snow surface temperature to be different from the snow average temperature by using an equilibrium gradient parameterization based on the surface energy balance. Although this procedure was considered an improvement over the ordinary single layer snowmelt models, it still resulted in discrepancies between modeled and measured snowpack energy contents. In this paper we examine the parameterization of snow surface temperature in single layer snowmelt models from the perspective of heat conduction into a semi-infinite medium. We evaluate the equilibrium gradient approach, the force-restore approach, and a modified force-restore approach. In addition, we evaluate a scheme for representing the penetration of a refreezing front in cold periods following melt. We also introduce a method to adjust effective conductivity to account for the presence of ground near to a shallow snow surface. These parameterizations were tested against data from the Central Sierra Snow Laboratory, CA, Utah State University experimental farm, UT, and Subnivean snow laboratory at Niwot Ridge, CO. These tests compare modeled and measured snow surface temperature, snow energy content, snow water equivalent, and snowmelt outflow. We found that with these refinements the model is able to better represent the snowpack energy balance and internal energy content while still retaining a parsimonious one layer format.

Quantifying heating biases in marine air temperature observations, ~1790 - present

2021 ◽  
Author(s):  
Thomas Cropper ◽  
Elizabeth Kent ◽  
David Berry ◽  
Richard Cornes ◽  
Beatriz Recinos-Rivas
Keyword(s):  
Air Temperature ◽  
Diurnal Cycle ◽  
Surface Air Temperature ◽  
Night Time ◽  
Data Set ◽  
Near Surface ◽  
Marine Surface ◽  
Heating Model ◽  
Marine Air

<p>Accurate, long-term time series of near-surface air temperature (AT) are the fundamental datasets on which the magnitude of anthropogenic climate change is scientifically and societally addressed. Across the ocean, these (near-surface) climate records use Sea Surface Temperature (SST) instead of Marine Air Temperature (MAT) and blend the SST and AT over land to create datasets. MAT has often been overlooked as a data choice as daytime MAT observations from ships are known to contain warm biases due to the storage of accumulated solar energy. Two recent MAT datasets, CLASSnmat (1881 – 2019) and UAHNMAT (1900 – 2018), both use night-time MAT observations only. Daytime MAT observations in the International Comprehensive Ocean–Atmosphere Data Set (ICOADS) account for over half of the MAT observations in ICOADS, and this proportion increases further back in time (i.e. pre-1850s). If long-term MAT records over the ocean are to be extended, the use of daytime MAT is vital.</p><p> </p><p>To adjust for the daytime MAT heating bias, and apply it to ICOADS, we present the application of a physics-based model, which accounts for the accumulated energy storage throughout the day. As the ‘true’ diurnal cycle of MAT over the ocean has not been, to-date, adequately quantified, our approach also removes the diurnal cycle from ICOADS observations and generates a night-time equivalent MAT for all observations. We fit this model to MAT observations from groups of ships in ICOADS that share similar heating biases and metadata characteristics. This enables us to use the empirically derived coefficients (representing the physical energy transfer terms of the heating model) obtained from the fit for use in removal of the heating bias and diurnal cycle from ship-based MAT observations throughout ICOADS which share similar characteristics (i.e. we can remove the diurnal cycle from a ship which only reports once daily at noon). This adjustment will create an MAT record of night-time-equivalent temperatures that will enable an extension of the marine surface AT record back into the 18<sup>th</sup> century.</p>

scholarly journals Evaluation of alternative formulae for calculation of surface temperature in snowmelt models using frequency analysis of temperature observations

2010 ◽  
Vol 14 (3) ◽  
pp. 535-543 ◽  
Author(s):  
C. H. Luce ◽  
D. G. Tarboton
Keyword(s):  
Time Series ◽  
Energy Balance ◽  
Surface Temperature ◽  
Energy Flux ◽  
Frequency Analysis ◽  
Energy Content ◽  
Balance Model ◽  
Snow Surface ◽  
Fourier Frequency ◽  
Snow Surface Temperature

Abstract. The snow surface temperature is an important quantity in the snow energy balance, since it modulates the exchange of energy between the surface and the atmosphere as well as the conduction of energy into the snowpack. It is therefore important to correctly model snow surface temperatures in energy balance snowmelt models. This paper focuses on the relationship between snow surface temperature and conductive energy fluxes that drive the energy balance of a snowpack. Time series of snow temperature at the surface and through the snowpack were measured to examine energy conduction in a snowpack. Based on these measurements we calculated the snowpack energy content and conductive energy flux at the snow surface. We then used these estimates of conductive energy flux to evaluate formulae for the calculation of the conductive flux at the snow surface based on surface temperature time series. We use a method based on Fourier frequency analysis to estimate snow thermal properties. Among the formulae evaluated, we found that a modified force-restore formula, based on the superimposition of the force-restore equation capturing diurnal fluctuations on a gradually changing temperature gradient, had the best agreement with observations of heat conduction. This formula is suggested for the parameterization of snow surface temperature in a full snowpack energy balance model.

scholarly journals What controls the isotopic composition of Greenland surface snow?

2014 ◽  
Vol 10 (1) ◽  
pp. 377-392 ◽  
Author(s):  
H. C. Steen-Larsen ◽  
V. Masson-Delmotte ◽  
M. Hirabayashi ◽  
R. Winkler ◽  
K. Satow ◽  
...  
Keyword(s):  
Water Vapor ◽  
Isotopic Composition ◽  
Air Temperature ◽  
Ice Core ◽  
Snow Surface ◽  
Atmospheric Models ◽  
Near Surface ◽  
Core Data ◽  
Surface Snow ◽  
Precipitation Events

Abstract. Water stable isotopes in Greenland ice core data provide key paleoclimatic information, and have been compared with precipitation isotopic composition simulated by isotopically enabled atmospheric models. However, post-depositional processes linked with snow metamorphism remain poorly documented. For this purpose, monitoring of the isotopic composition (δ18O, δD) of near-surface water vapor, precipitation and samples of the top (0.5 cm) snow surface has been conducted during two summers (2011–2012) at NEEM, NW Greenland. The samples also include a subset of 17O-excess measurements over 4 days, and the measurements span the 2012 Greenland heat wave. Our observations are consistent with calculations assuming isotopic equilibrium between surface snow and water vapor. We observe a strong correlation between near-surface vapor δ18O and air temperature (0.85 ± 0.11‰ °C−1 (R = 0.76) for 2012). The correlation with air temperature is not observed in precipitation data or surface snow data. Deuterium excess (d-excess) is strongly anti-correlated with δ18O with a stronger slope for vapor than for precipitation and snow surface data. During nine 1–5-day periods between precipitation events, our data demonstrate parallel changes of δ18O and d-excess in surface snow and near-surface vapor. The changes in δ18O of the vapor are similar or larger than those of the snow δ18O. It is estimated using the CROCUS snow model that 6 to 20% of the surface snow mass is exchanged with the atmosphere. In our data, the sign of surface snow isotopic changes is not related to the sign or magnitude of sublimation or deposition. Comparisons with atmospheric models show that day-to-day variations in near-surface vapor isotopic composition are driven by synoptic variations and changes in air mass trajectories and distillation histories. We suggest that, in between precipitation events, changes in the surface snow isotopic composition are driven by these changes in near-surface vapor isotopic composition. This is consistent with an estimated 60% mass turnover of surface snow per day driven by snow recrystallization processes under NEEM summer surface snow temperature gradients. Our findings have implications for ice core data interpretation and model–data comparisons, and call for further process studies.

scholarly journals Daytime preservation of surface-hoar crystals

1998 ◽  
Vol 26 ◽  
pp. 22-26 ◽  
Author(s):  
Akihiro Hachikubo ◽  
Eizi Akitaya
Keyword(s):  
Shear Strength ◽  
Surface Layer ◽  
Relative Humidity ◽  
Solar Radiation ◽  
Surface Temperature ◽  
Snow Surface ◽  
Previous Night ◽  
Snow Surface Temperature ◽  
Transfer Method

Surface hoar growing for several clear and humid days were observed. During daytime, air and snow-surface temperature increased and relative humidity decreased, hence evaporation (sublimation) occurred at the snow surface. The amount of evaporation calculated using a bulk-transfer method suggests that the surface-hoar crystals which grew during the previous night should have disappeared but they were observed to survive on the snow surface even during the daytime. During the following night, new surface-hoar crystals formed on top of the older ones and grew even larger. This result indicates that, although the surface-hoar crystals evaporated into the air during the daytime, snow grains beneath the surface were warmed by solar radiation and evaporated to the air. They may partially condense into the surface-hoar crystals and make up for the reduction in size. Depth-hoar crystals formed beneath the snow surface for several days and the surface layer, composed of both types of hoar crystal, showed a very weak shear strength.

Recent Trends in Land Surface Temperature on the Tibetan Plateau

2006 ◽  
Vol 19 (12) ◽  
pp. 2995-3003 ◽  
Author(s):  
Yuichiro Oku ◽  
Hirohiko Ishikawa ◽  
Shigenori Haginoya ◽  
Yaoming Ma
Keyword(s):  
Tibetan Plateau ◽  
Surface Temperature ◽  
Air Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Precipitation Amount ◽  
Surface Air Temperature ◽  
The Tibetan Plateau ◽  
Near Surface ◽  
Diurnal Range

Abstract The diurnal, seasonal, and interannual variations in land surface temperature (LST) on the Tibetan Plateau from 1996 to 2002 are analyzed using the hourly LST dataset obtained by Japanese Geostationary Meteorological Satellite 5 (GMS-5) observations. Comparing LST retrieved from GMS-5 with independent precipitation amount data demonstrates the consistent and complementary relationship between them. The results indicate an increase in the LST over this period. The daily minimum has risen faster than the daily maximum, resulting in a narrowing of the diurnal range of LST. This is in agreement with the observed trends in both global and plateau near-surface air temperature. Since the near-surface air temperature is mainly controlled by LST, this result ensures a warming trend in near-surface air temperature.

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