Estimation of contributions from different-scale components of the wind vector and air temperature to turbulent heat fluxes in the atmospheric surface layer

2020 ◽  
Author(s):  
Vladimir Gladkikh ◽  
Vladimir Mamyshev ◽  
Irina Nevzorova ◽  
Sergey Odintsov
Keyword(s):  
Surface Layer ◽  
Air Temperature ◽  
Atmospheric Surface Layer ◽  
Heat Fluxes ◽  
Turbulent Heat ◽  
Wind Vector ◽  
Turbulent Heat Fluxes

scholarly journals Feasibility of Estimating Turbulent Heat Fluxes via Variational Assimilation of Reference-Level Air Temperature and Specific Humidity Observations

2020 ◽  
Vol 12 (7) ◽  
pp. 1065
Author(s):  
Elahe Tajfar ◽  
Sayed M. Bateni ◽  
Essam Heggy ◽  
Tongren Xu
Keyword(s):  
Air Temperature ◽  
Heat Fluxes ◽  
Specific Humidity ◽  
Reference Level ◽  
Turbulent Heat ◽  
Area Index ◽  
Variational Assimilation ◽  
Available Energy ◽  
Turbulent Heat Fluxes ◽  
Mean Square Errors

This study investigated the feasibility of partitioning the available energy between sensible (H) and latent (LE) heat fluxes via variational assimilation of reference-level air temperature and specific humidity. For this purpose, sequences of reference-level air temperature and specific humidity were assimilated into an atmospheric boundary layer model (ABL) within a variational data assimilation (VDA) framework to estimate H and LE. The VDA approach was tested at six sites (namely, Arou, Audubon, Bondville, Brookings, Desert, and Willow Creek) with contrasting climatic and vegetative conditions. The unknowns of the VDA system were the neutral bulk heat transfer coefficient (CHN) and evaporative fraction (EF). EF estimates were found to agree well with observations in terms of magnitude and day-to-day fluctuations in wet/densely vegetated sites but degraded in dry/sparsely vegetated sites. Similarly, in wet/densely vegetated sites, the variations in the CHN estimates were found to be consistent with those of the leaf area index (LAI) while this consistency deteriorated in dry/sparely vegetated sites. The root mean square errors (RMSEs) of daily H and LE estimates at the Arou site (wet) were 25.43 (Wm−2) and 55.81 (Wm−2), which are respectively 57.6% and 45.4% smaller than those of 60.00 (Wm−2) and 102.21 (Wm−2) at the Desert site (dry). Overall, the results show that the VDA system performs well at wet/densely vegetated sites (e.g., Arou and Willow Creek), but its performance degrades at dry/slightly vegetated sites (e.g., Desert and Audubon). These outcomes show that the sequences of reference-level air temperature and specific humidity have more information on the partitioning of available energy between the sensible and latent heat fluxes in wet/densely vegetated sites than dry/slightly vegetated sites.

scholarly journals Estimation of Turbulent Heat Fluxes via Assimilation of Air Temperature and Specific Humidity into an Atmospheric Boundary Layer Model

2020 ◽  
Vol 21 (2) ◽  
pp. 205-225 ◽  
Author(s):  
E. Tajfar ◽  
S. M. Bateni ◽  
S. A. Margulis ◽  
P. Gentine ◽  
T. Auligne
Keyword(s):  
Boundary Layer ◽  
Atmospheric Boundary Layer ◽  
Air Temperature ◽  
Potential Temperature ◽  
Heat Fluxes ◽  
Specific Humidity ◽  
Turbulent Heat ◽  
Layer Model ◽  
Ground Heat Flux ◽  
Turbulent Heat Fluxes

AbstractA number of studies have used time series of air temperature and specific humidity observations to estimate turbulent heat fluxes. These studies require the specification of surface roughness lengths for heat and momentum (that are directly related to the neutral bulk heat transfer coefficient CHN) and/or ground heat flux, which are often unavailable. In this study, sequences of air temperature and specific humidity are assimilated into an atmospheric boundary layer model within a variational data assimilation (VDA) framework to estimate CHN, evaporative fraction (EF), turbulent heat fluxes, and atmospheric boundary layer (ABL) height, potential temperature, and humidity. The developed VDA approach needs neither the surface roughness parameterization (as it is optimized by the VDA approach) nor ground heat flux measurements. The VDA approach is tested over the First International Satellite Land Surface Climatology Project Field Experiment (FIFE) site in the summers of 1987 and 1988. The results indicate that the estimated sensible and latent heat fluxes agree fairly well with the corresponding measurements. For FIFE 1987 (1988), the daily sensible and latent heat fluxes estimates have a root-mean-square error of 25.72 W m−2 (27.77 W m−2) and 53.63 W m−2 (48.22 W m−2), respectively. In addition, the ABL height, specific humidity, and potential temperature estimates from the VDA system are in good agreement with those inferred from the radiosondes both in terms of magnitude and diurnal trend.

Spatial Variation in Turbulent Heat Fluxes in Drake Passage

2012 ◽  
Vol 25 (5) ◽  
pp. 1470-1488 ◽  
Author(s):  
ChuanLi Jiang ◽  
Sarah T. Gille ◽  
Janet Sprintall ◽  
Kei Yoshimura ◽  
Masao Kanamitsu
Keyword(s):  
Heat Flux ◽  
High Resolution ◽  
Air Temperature ◽  
Drake Passage ◽  
Polar Front ◽  
Heat Fluxes ◽  
Turbulent Heat ◽  
Length Scales ◽  
Sea Temperature ◽  
Turbulent Heat Fluxes

High-resolution underway shipboard atmospheric and oceanic observations collected in Drake Passage from 2000 to 2009 are used to examine the spatial scales of turbulent heat fluxes and flux-related state variables. The magnitude of the seasonal cycle of sea surface temperature (SST) south of the Polar Front is found to be twice that north of the front, but the seasonal cycles of the turbulent heat fluxes show no differences on either side of the Polar Front. Frequency spectra of the turbulent heat fluxes and related variables are red, with no identifiable spectral peaks. SST and air temperature are coherent over a range of frequencies corresponding to periods between ~10 h and 2 days, with SST leading air temperature. The spatial decorrelation length scales of the sensible and latent heat fluxes calculated from two-day transects are 65 ± 6 km and 80 ± 6 km, respectively. The scale of the sensible heat flux is consistent with the decorrelation scale for air–sea temperature differences (70 ± 6 km) rather than either SST (153 ± 2 km) or air temperature (138 ± 4 km) alone. These scales are dominated by the Polar Front. When the Polar Front region is excluded, the decorrelation scales are 10–20 km, consistent with the first baroclinic Rossby radius. These eddy scales are often unrepresented in the available gridded heat flux products. The Drake Passage ship measurements are compared with four recently available gridded turbulent heat flux products: the European Centre for Medium-Range Weather Forecasts high-resolution operational product in support of the Year of Coordinated Observing Modeling and Forcasting Tropical Convection (ECMWF-YOTC), ECMWF interim reanalysis (ERA-Interim), the Drake Passage reanalysis downscaling (DPRD10) regional product, and the objectively analyzed air–sea fluxes (OAFlux). The decorrelation length scales of the air–sea temperature difference, wind speed, and turbulent heat fluxes from these four products are significantly larger than those determined from shipboard measurements.

Estimation of turbulent heat fluxes and exchange coefficients for heat at Dumont d'Urville, East Antarctica

1999 ◽  
Vol 11 (1) ◽  
pp. 93-99 ◽  
Author(s):  
S. Argentini ◽  
G. Mastrantonio ◽  
A. Viola
Keyword(s):  
Boundary Layer ◽  
Heat Fluxes ◽  
East Antarctica ◽  
Turbulent Heat ◽  
Convective Boundary ◽  
Doppler Sodar ◽  
Turbulent Heat Fluxes ◽  
Unstable Boundary Layer ◽  
Sodar Measurements ◽  
The Antarctic

Simultaneous acoustic Doppler sodar and tethersonde measurements were used to study some of the characteristics of the unstable boundary layer at Dumont d'Urville, Adélie Land, East Antarctica during the summer 1993–94. A description of the convective boundary layer and its behaviour in connection with the wind regime is given along with the frequency distribution of free convection episodes. The surface heat flux has been evaluated using the vertical velocity variance derived from sodar measurements. The turbulent exchange coefficients, estimated by coupling sodar and tethered balloon measurements, are in strong agreement with those present in literature for the Antarctic regions.

Searching for new physics: Using explainable AI to understand deep learned parameterizations of turbulent heat fluxes

2021 ◽  
Author(s):  
Andrew Bennett ◽  
Bart Nijssen
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Deep Learning ◽  
Coupled System ◽  
Hydrologic Model ◽  
Heat Fluxes ◽  
Turbulent Heat ◽  
Phase Lag ◽  
Geophysical Research ◽  
Turbulent Heat Fluxes

<p>Machine learning (ML), and particularly deep learning (DL), for geophysical research has shown dramatic successes in recent years. However, these models are primarily geared towards better predictive capabilities, and are generally treated as black box models, limiting researchers’ ability to interpret and understand how these predictions are made. As these models are incorporated into larger models and pushed to be used in more areas it will be important to build methods that allow us to reason about how these models operate. This will have implications for scientific discovery that will ensure that these models are robust and reliable for their respective applications. Recent work in explainable artificial intelligence (XAI) has been used to interpret and explain the behavior of machine learned models.</p><p>Here, we apply new tools from the field of XAI to provide physical interpretations of a system that couples a deep-learning based parameterization for turbulent heat fluxes to a process based hydrologic model. To develop this coupling we have trained a neural network to predict turbulent heat fluxes using FluxNet data from a large number of hydroclimatically diverse sites. This neural network is coupled to the SUMMA hydrologic model, taking imodel derived states as additional inputs to improve predictions. We have shown that this coupled system provides highly accurate simulations of turbulent heat fluxes at 30 minute timesteps, accurately predicts the long-term observed water balance, and reproduces other signatures such as the phase lag with shortwave radiation. Because of these features, it seems this coupled system is learning physically accurate relationships between inputs and outputs. </p><p>We probe the relative importance of which input features are used to make predictions during wet and dry conditions to better understand what the neural network has learned. Further, we conduct controlled experiments to understand how the neural networks are able to learn to regionalize between different hydroclimates. By understanding how these neural networks make their predictions as well as how they learn to make predictions we can gain scientific insights and use them to further improve our models of the Earth system.</p>

The Effect of Soil on the Summertime Surface Energy Budget of a Humid Subarctic Tundra in Northern Quebec, Canada

2021 ◽  
Vol 22 (10) ◽  
pp. 2547-2564
Author(s):  
Georg Lackner ◽  
Daniel F. Nadeau ◽  
Florent Domine ◽  
Annie-Claude Parent ◽  
Gonzalo Leonardini ◽  
...  
Keyword(s):  
Heat Flux ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Land Surface ◽  
Sensible Heat Flux ◽  
Arctic Region ◽  
Heat Fluxes ◽  
Surface Energy Budget ◽  
Turbulent Heat ◽  
Turbulent Heat Fluxes

AbstractRising temperatures in the southern Arctic region are leading to shrub expansion and permafrost degradation. The objective of this study is to analyze the surface energy budget (SEB) of a subarctic shrub tundra site that is subject to these changes, on the east coast of Hudson Bay in eastern Canada. We focus on the turbulent heat fluxes, as they have been poorly quantified in this region. This study is based on data collected by a flux tower using the eddy covariance approach and focused on snow-free periods. Furthermore, we compare our results with those from six Fluxnet sites in the Arctic region and analyze the performance of two land surface models, SVS and ISBA, in simulating soil moisture and turbulent heat fluxes. We found that 23% of the net radiation was converted into latent heat flux at our site, 35% was used for sensible heat flux, and about 15% for ground heat flux. These results were surprising considering our site was by far the wettest site among those studied, and most of the net radiation at the other Arctic sites was consumed by the latent heat flux. We attribute this behavior to the high hydraulic conductivity of the soil (littoral and intertidal sediments), typical of what is found in the coastal regions of the eastern Canadian Arctic. Land surface models overestimated the surface water content of those soils but were able to accurately simulate the turbulent heat flux, particularly the sensible heat flux and, to a lesser extent, the latent heat flux.

The signature of mesoscale eddies on the air‐sea turbulent heat fluxes in the South Atlantic Ocean

2015 ◽  
Vol 42 (6) ◽  
pp. 1856-1862 ◽  
Author(s):  
A. B. Villas Bôas ◽  
O. T. Sato ◽  
A. Chaigneau ◽  
G. P. Castelão
Keyword(s):  
Atlantic Ocean ◽  
Mesoscale Eddies ◽  
South Atlantic ◽  
Heat Fluxes ◽  
South Atlantic Ocean ◽  
Turbulent Heat ◽  
The South ◽  
Turbulent Heat Fluxes
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