Contribution of turbulent heat fluxes to surface ablation on the Greenland ice sheet.

Over ice sheets and glaciers, the turbulent heat fluxes are, next to the radiative fluxes, the second largest source of energy driving the ablation. In general, most (climate) models use a bulk turbulence parametrization for the estimation of these energy fluxes. Recent work suggest that the turbulent heat fluxes might be greatly underestimated by such models. Unfortunately, only a few direct and long-term observations of turbulent fluxes are available over ice sheets to evaluate their inclusion in models.&#160;In this study, we developed a vertical propeller eddy-covariance method to continuously monitor the sensible heat fluxes over the Greenland ice sheet (GrIS). We quantify its contribution to surface ablation using three years of data from the K-transect, located in the western ablation area of the GrIS. The direct flux measurements are also compared to those from several bulk turbulence models, and to a high-resolution regional climate model (RACMO2), in order to quantify modelling uncertainty.The differences between observations and models highlight the need for upgrading the bulk turbulence parameterizations and especially the model parameters, such as the surface roughness lengths. We also find that during short but extreme warm events, the turbulent heat fluxes become the largest source for surface ablation. Typical for such intense events on the K-transect are fast changes in wind direction, which cause changes in the surface roughness parameters due to the anisotropic feature of the ice hummocks. These parameters are critical for modelling the turbulent fluxes in bulk parameterizations, but are often variable and unknown. We conclude with drone topography measurements to better constrain the surface roughness locally, and discuss methods to improve the modelling of turbulent surface fluxes on the whole GrIS.

Download Full-text

Strong Summer Atmospheric Rivers Trigger Greenland Ice Sheet Melt through Spatially Varying Surface Energy Balance and Cloud Regimes

Journal of Climate ◽

10.1175/jcli-d-19-0835.1 ◽

2020 ◽

Vol 33 (16) ◽

pp. 6809-6832 ◽

Cited By ~ 2

Author(s):

Kyle S. Mattingly ◽

Thomas L. Mote ◽

Xavier Fettweis ◽

Dirk van As ◽

Kristof Van Tricht ◽

...

Keyword(s):

Energy Balance ◽

Surface Energy ◽

Surface Energy Balance ◽

Ice Sheet ◽

Greenland Ice Sheet ◽

Heat Fluxes ◽

Water Vapor Transport ◽

Turbulent Heat ◽

Atmospheric Rivers ◽

Turbulent Heat Fluxes

ABSTRACTMass loss from the Greenland Ice Sheet (GrIS) has accelerated over the past two decades, coincident with rapid Arctic warming and increasing moisture transport over Greenland by atmospheric rivers (ARs). Summer ARs affecting western Greenland trigger GrIS melt events, but the physical mechanisms through which ARs induce melt are not well understood. This study elucidates the coupled surface–atmosphere processes by which ARs force GrIS melt through analysis of the surface energy balance (SEB), cloud properties, and local- to synoptic-scale atmospheric conditions during strong summer AR events affecting western Greenland. ARs are identified in MERRA-2 reanalysis (1980–2017) and classified by integrated water vapor transport (IVT) intensity. SEB, cloud, and atmospheric data from regional climate model, observational, reanalysis, and satellite-based datasets are used to analyze melt-inducing physical processes during strong, >90th percentile “AR90+” events. Near AR “landfall,” AR90+ days feature increased cloud cover that reduces net shortwave radiation and increases net longwave radiation. As these oppositely signed radiative anomalies partly cancel during AR90+ events, increased melt energy in the ablation zone is primarily provided by turbulent heat fluxes, particularly sensible heat flux. These turbulent heat fluxes are driven by enhanced barrier winds generated by a stronger synoptic pressure gradient combined with an enhanced local temperature contrast between cool over-ice air and the anomalously warm surrounding atmosphere. During AR90+ events in northwest Greenland, anomalous melt is forced remotely through a clear-sky foehn regime produced by downslope flow in eastern Greenland.

Download Full-text

Measurements and modelling of snowmelt and turbulent heat fluxes over shrub tundra

Hydrology and Earth System Sciences ◽

10.5194/hess-14-1331-2010 ◽

2010 ◽

Vol 14 (7) ◽

pp. 1331-1340 ◽

Cited By ~ 31

Author(s):

D. Bewley ◽

R. Essery ◽

J. Pomeroy ◽

C. Ménard

Keyword(s):

Meteorological Data ◽

Sensible Heat Flux ◽

Heat Fluxes ◽

Model Parameters ◽

Turbulent Heat ◽

Turbulent Heat Fluxes ◽

Shrub Tundra ◽

Valley Site ◽

Heat Transfers ◽

Energy Balances

Abstract. Measurements of snowmelt and turbulent heat fluxes were made during the snowmelt periods of two years at two neighbouring tundra sites in the Yukon, one in a sheltered location with tall shrubs exposed above deep snow and the other in an exposed location with dwarf shrubs covered by shallow snow. The snow was about twice as deep in the valley as on the plateau at the end of each winter and melted out about 10 days later. The site with buried vegetation showed a transition from air-to-surface heat transfers to surface-to-air heat transfers as bare ground became exposed during snowmelt, but there were daytime transfers of heat from the surface to the air at the site with exposed vegetation even while snow remained on the ground. A model calculating separate energy balances for snow and exposed vegetation, driven with meteorological data from the sites, is found to be able to reproduce these behaviours. Averaged over 30-day periods the model gives about 8 Wm−2 more sensible heat flux to the atmosphere for the valley site than for the plateau site. Sensitivity of simulated fluxes to model parameters describing vegetation cover and density is investigated.

Download Full-text

Scintillometry Observations of Sensible and Latent Heat Fluxes over a Boreal Reservoir, Quebec, Canada

10.5194/egusphere-egu21-6213 ◽

2021 ◽

Author(s):

Adrien Pierre ◽

Daniel Nadeau ◽

Pierre-Érik Isabelle ◽

Antoine Thiboult ◽

Alain Rousseau ◽

...

Keyword(s):

Latent Heat ◽

Regional Scale ◽

Turbulent Fluxes ◽

Heat Fluxes ◽

Water Bodies ◽

Turbulent Heat ◽

Sensible Heat ◽

Near Surface ◽

Comparison Results ◽

Turbulent Heat Fluxes

Observations of sensible and latent heat fluxes over inland water bodies are unfortunately scarce and, yet, critical to the development of adequate lake parameterization for numerical weather forecast and climate models. When available, they usually consist of eddy covariance (EC) or lysimeter measurements, both representative of a relatively small footprint area, typically of a few hectares in the case of the EC approach. Over the past decades, we have seen the emergence of bichromatic scintillometry (SC), which allows for a &#8216;regional&#8217; (~km2) estimation of turbulent heat fluxes. In brief, two beams travelling from a set of transmitters to a set of receivers scintillate in the turbulent air above the surface of interest and enable, using the Monin-Obukhov Similarity Theory, the computation of sensible and latent heat fluxes at the land-atmosphere interface. While a handful of studies have looked at the performance of this approach over land surfaces, very few have assessed it over water bodies. This study presents an evaluation of scintillometry-derived turbulent heat fluxes over an 85-km2 boreal hydropower reservoir of eastern Canada (50.69&#176;N, 63.24&#176;W) with respect to those obtained with EC measurements collected on a nearby floating platform. The scintillometer beam path travelled for 1.7 km over a surface of the reservoir that reached depths of ~100m, from 14 August to 9 October 2019. Results indicate positive, day-and-night, latent heat fluxes throughout the whole period; highlighting that the reservoir steadily released heat over the second half of the open water period, from mid-august until freeze-up. Sensible heat fluxes peaked at night due to the near-surface air temperature vertical gradient reaching its daily maximum. For sensible heat fluxes, the SC approach corroborates well with the EC approach, while for latent heat fluxes, the agreement between EC and SC decreases. This suggests that the larger footprint of the SC system might be affected by heterogeneous surface flux characteristics in the reservoir, which encapsulates the need for large-scale measurements. Grouping results by atmospheric stability regimes does not improve comparison results. These results provide an opportunity to validate an innovative approach for measuring turbulent fluxes at a regional scale and, hence, improving our understanding of turbulent fluxes over large reservoirs and lakes.

Download Full-text

Measurements and modelling of snowmelt and turbulent heat fluxes over shrub tundra

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-7-1005-2010 ◽

2010 ◽

Vol 7 (1) ◽

pp. 1005-1032 ◽

Cited By ~ 2

Author(s):

D. Bewley ◽

R. Essery ◽

J. Pomeroy ◽

C. Ménard

Keyword(s):

Meteorological Data ◽

Heat Fluxes ◽

Model Parameters ◽

Turbulent Heat ◽

Bare Ground ◽

Turbulent Heat Fluxes ◽

Shrub Tundra ◽

Heat Transfers ◽

Energy Balances ◽

Exposed Location

Abstract. Measurements of snowmelt and turbulent heat fluxes were made during the snowmelt periods of two years at two neighbouring tundra sites in the Yukon, one in a sheltered location with tall shrubs exposed above deep snow and the other in an exposed location with dwarf shrubs covered by shallow snow. The site with buried vegetation showed a transition from air-to-surface heat transfers to surface-to-air heat transfers as bare ground became exposed during snowmelt, but there were daytime transfers of heat from the surface to the air at the site with exposed vegetation even while snow remained on the ground. A model calculating separate energy balances for snow and exposed vegetation, driven with meteorological data from the sites, is found to be able to reproduce these behaviours. Sensitivity of simulated fluxes to model parameters describing vegetation cover and density is investigated.

Download Full-text

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

Antarctic Science ◽

10.1017/s0954102099000127 ◽

1999 ◽

Vol 11 (1) ◽

pp. 93-99 ◽

Cited By ~ 3

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.

Download Full-text

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

10.5194/egusphere-egu21-3516 ◽

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

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&#8217; 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.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.&#160;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.

Download Full-text

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

Journal of Hydrometeorology ◽

10.1175/jhm-d-20-0243.1 ◽

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.

Download Full-text

Last Interglacial climate and sea-level evolution from a coupled ice sheet–climate model

Climate of the Past ◽

10.5194/cp-12-2195-2016 ◽

2016 ◽

Vol 12 (12) ◽

pp. 2195-2213 ◽

Cited By ~ 22

Author(s):

Heiko Goelzer ◽

Philippe Huybrechts ◽

Marie-France Loutre ◽

Thierry Fichefet

Keyword(s):

Surface Temperature ◽

Sea Level ◽

Ice Sheets ◽

Ice Sheet ◽

Greenland Ice Sheet ◽

Last Interglacial ◽

A Minor ◽

The Antarctic ◽

The Impact ◽

And Sea Level

Abstract. As the most recent warm period in Earth's history with a sea-level stand higher than present, the Last Interglacial (LIG, ∼  130 to 115 kyr BP) is often considered a prime example to study the impact of a warmer climate on the two polar ice sheets remaining today. Here we simulate the Last Interglacial climate, ice sheet, and sea-level evolution with the Earth system model of intermediate complexity LOVECLIM v.1.3, which includes dynamic and fully coupled components representing the atmosphere, the ocean and sea ice, the terrestrial biosphere, and the Greenland and Antarctic ice sheets. In this setup, sea-level evolution and climate–ice sheet interactions are modelled in a consistent framework.Surface mass balance change governed by changes in surface meltwater runoff is the dominant forcing for the Greenland ice sheet, which shows a peak sea-level contribution of 1.4 m at 123 kyr BP in the reference experiment. Our results indicate that ice sheet–climate feedbacks play an important role to amplify climate and sea-level changes in the Northern Hemisphere. The sensitivity of the Greenland ice sheet to surface temperature changes considerably increases when interactive albedo changes are considered. Southern Hemisphere polar and sub-polar ocean warming is limited throughout the Last Interglacial, and surface and sub-shelf melting exerts only a minor control on the Antarctic sea-level contribution with a peak of 4.4 m at 125 kyr BP. Retreat of the Antarctic ice sheet at the onset of the LIG is mainly forced by rising sea level and to a lesser extent by reduced ice shelf viscosity as the surface temperature increases. Global sea level shows a peak of 5.3 m at 124.5 kyr BP, which includes a minor contribution of 0.35 m from oceanic thermal expansion. Neither the individual contributions nor the total modelled sea-level stand show fast multi-millennial timescale variations as indicated by some reconstructions.

Download Full-text

Challenges in Modeling Turbulent Heat Fluxes to Snowpacks in Forest Clearings

Journal of Hydrometeorology ◽

10.1175/jhm-d-18-0050.1 ◽

2018 ◽

Vol 19 (10) ◽

pp. 1599-1616 ◽

Cited By ~ 5

Author(s):

Jonathan P. Conway ◽

John W. Pomeroy ◽

Warren D. Helgason ◽

Nicholas J. Kinar

Keyword(s):

Heat Exchange ◽

Surface Temperature ◽

Latent Heat ◽

Turbulent Fluxes ◽

Heat Fluxes ◽

Turbulent Heat ◽

Snow Surface ◽

Turbulent Heat Exchange ◽

Uncertainty Estimates ◽

Model Tuning

Abstract Forest clearings are common features of evergreen forests and produce snowpack accumulation and melt differing from that in adjacent forests and open terrain. This study has investigated the challenges in specifying the turbulent fluxes of sensible and latent heat to snowpacks in forest clearings. The snowpack in two forest clearings in the Canadian Rockies was simulated using a one-dimensional (1D) snowpack model. A trade-off was found between optimizing against measured snow surface temperature or snowmelt when choosing how to specify the turbulent fluxes. Schemes using the Monin–Obukhov similarity theory tended to produce negatively biased surface temperature, while schemes that enhanced turbulent fluxes, to reduce the surface temperature bias, resulted in too much melt. Uncertainty estimates from Monte Carlo experiments showed that no realistic parameter set could successfully remove biases in both surface temperature and melt. A simple scheme that excludes atmospheric stability correction was required to successfully simulate surface temperature under low wind speed conditions. Nonturbulent advective fluxes and/or nonlocal sources of turbulence are thought to account for the maintenance of heat exchange in low-wind conditions. The simulation of snowmelt was improved by allowing enhanced latent heat fluxes during low-wind conditions. Caution is warranted when snowpack models are optimized on surface temperature, as model tuning may compensate for deficiencies in conceptual and numerical models of radiative, conductive, and turbulent heat exchange at the snow surface and within the snowpack. Such model tuning could have large impacts on the melt rate and timing of the snow-free transition in simulations of forest clearings within hydrological and meteorological models.

Download Full-text