Measurements, models and drivers of incoming longwave radiation in the Himalaya

Kok, Remco de; Steiner, Jakob; Litt, Maxime; Wagnon, Patrick; Koch, Inka; Azam, Mohd Farooq; Immerzeel, Walter W.

doi:10.1002/joc.6249

Cited by 14 publications

(8 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The increasing LST night trend can be related to the enhanced LRi associated with the build‐up of greenhouse gases in the atmosphere. LRi emission is the dominant process at night owing to the absence of shortwave radiation and consequent decline of surface biophysical processes (latent and sensible heat flux) (de Kok et al, 2020; Oke & Cleugh, 1987). On the other hand, the global warming effect is more pronounced at night than daytime due to higher sensitivity of nighttime air temperature to perturbations of radiation balance associated with shallow boundary layer formation (Alexander et al, 2006; Davy et al, 2017; Vose et al, 2005).…”

Section: Discussionmentioning

confidence: 99%

Land Surface Temperature Trend and Its Drivers in East Africa

et al. 2020

View full text Add to dashboard Cite

Land surface temperature (LST) is affected by surface-atmosphere interaction. Yet, the degree to which surface and atmospheric factors impact the magnitude of LST trend is not well established. Here, we used surface energy balance, boosted regression tree model, and satellite observation and reanalysis data to unravel the effects of surface factors (albedo, sensible heat, latent heat, and ground heat) as well as incoming radiation (shortwave and longwave) on LST trends in East Africa (EA). Our result showed that 11% of EA was affected by significant (p < 0.05) daytime annual LST trends, which exhibited both cooling of −0.19 K year −1 (mainly in South Sudan and Sudan) and warming of 0.22 K year −1 (mainly in Somalia and Kenya). The nighttime LST trends affected a large part of EA (31%) and were dominated by significant warming trend (0.06 K year −1). Influenced by contrasting daytime and nighttime LST trends, the diurnal LST range reduced in 15% of EA. The modeling result showed that latent heat flux (32%), incoming longwave radiation (30%), and shortwave radiation (23%) were stronger in explaining daytime LST trend. The effects of surface factors were stronger in both cooling and warming trends, whereas atmospheric factors had stronger control only on surface cooling trends. These results indicate the differential control of surface and atmospheric factors on warming and cooling trends, highlighting the importance of considering both factors for accurate evaluation of the LST trends in the future.

show abstract

Section: Discussionmentioning

confidence: 99%

Land Surface Temperature Trend and Its Drivers in East Africa

et al. 2020

View full text Add to dashboard Cite

show abstract

“…Outgoing shortwave radiation SW↑ is computed using a constant albedo α d determined from on-glacier measurements. Incoming longwave radiation LW↓ is taken from measurements wherever available and otherwise computed using a model developed for the Himalaya (Kok et al, 2019). Contrary to the original model, which used stability corrections based on the Richardson number, we calculate sensible and latent heat flux only using a bulk transfer coefficient (Nicholson and Benn 2006;Cuffey and Paterson 2010), which was found to be more appropriate compared to direct measurements of turbulent fluxes (Steiner et al, 2018).…”

Section: Energy Balance Modelmentioning

confidence: 99%

Distributed Melt on a Debris-Covered Glacier: Field Observations and Melt Modeling on the Lirung Glacier in the Himalaya

2021

Self Cite

View full text Add to dashboard Cite

Debris-covered glaciers, especially in high-mountain Asia, have received increased attention in recent years. So far, few field-based observations of distributed mass loss exist and both the properties of the debris layer as well as the atmospheric drivers of melt below debris remain poorly understood. Using multi-year observations of on-glacier atmospheric data, debris properties and spatial surface elevation changes from repeat flights with an unmanned aerial vehicle (UAV), we quantify the necessary variables to compute melt for the Lirung Glacier in the Himalaya. By applying an energy balance model we reproduce observed mass loss during one monsoon season in 2013. We show that melt is especially sensitive to thermal conductivity and thickness of debris. Our observations show that previously used values in literature for the thermal conductivity through debris are valid but variability in space on a single glacier remains high. We also present a simple melt model, which is calibrated based on the results of energy balance model, that is only dependent on air temperature and debris thickness and is therefore applicable for larger scale studies. This simple melt model reproduces melt under thin debris (<0.5 m) well at an hourly resolution, but fails to represent melt under thicker debris accurately at this high temporal resolution. On the glacier scale and using only off-glacier forcing data we however are able to reproduce the total melt volume of a debris-covered tongue. This is a promising result for catchment scale studies, where quantifying melt from debris covered glaciers remains a challenge.

show abstract

“…Atmospheric transmittance is highly wavelength dependent and controlled by spatio-temporal variations in various atmospheric constituents including aerosols, and water vapor [72,73]. Cloud conditions may also have an impact on the magnitude of direct beam irradiance [74]. The diffuse skylight irradiance E d is governed by both meso-scale and local topographic properties, and is found to have a non-negligible effect on ice-cliff melting [44].…”

Section: Surface Energy Balancementioning

confidence: 99%

“…Surface ablation dynamics: (1) The ablation dynamics of ice-cliffs and supraglacial ponds/lakes are oversimplified or neglected in many existing simulations [5,38,44]. 2The influence of clouds on the longwave radiation has not been fully addressed [74]. 3The nonlinear profile of thermal properties within the debris layer has not been accounted for.…”

Section: Issues and Research Directionsmentioning

confidence: 99%

Modeling Surface Processes on Debris-Covered Glaciers: A Review with Reference to the High Mountain Asia

Huo

Chi

2021

Water

View full text Add to dashboard Cite

Surface processes on debris-covered glaciers are governed by a variety of controlling factors including climate, debris load, water bodies, and topography. Currently, we have not achieved a general consensus on the role of supraglacial processes in regulating climate–glacier sensitivity in High Mountain Asia, which is mainly due to a lack of an integrated understanding of glacier surface dynamics as a function of debris properties, mass movement, and ponding. Therefore, further investigations on supraglacial processes is needed in order to provide more accurate assessments of the hydrological cycle, water resources, and natural hazards in the region. Given the scarcity of long-term in situ data and the difficulty of conducting fieldwork on these glaciers, many numerical models have been developed by recent studies. This review summarizes our current knowledge of surface processes on debris-covered glaciers with an emphasis on the related modeling efforts. We present an integrated view on how numerical modeling provide insights into glacier surface ablation, supraglacial debris transport, morphological variation, pond dynamics, and ice-cliff evolution. We also highlight the remote sensing approaches that facilitate modeling, and discuss the limitations of existing models regarding their capabilities to address coupled processes on debris-covered glaciers and suggest research directions.

show abstract

Measurements, models and drivers of incoming longwave radiation in the Himalaya

Cited by 14 publications

References 30 publications

Land Surface Temperature Trend and Its Drivers in East Africa

Land Surface Temperature Trend and Its Drivers in East Africa

Distributed Melt on a Debris-Covered Glacier: Field Observations and Melt Modeling on the Lirung Glacier in the Himalaya

Modeling Surface Processes on Debris-Covered Glaciers: A Review with Reference to the High Mountain Asia

Contact Info

Product

Resources

About