Assessing the potential of the Atmospheric Infrared Sounder (AIRS) surface temperature and specific humidity in turbulent heat flux estimates in the Southern Ocean

2010 ◽  
Vol 115 (C5) ◽  
Author(s):  
Shenfu Dong ◽  
Sarah T. Gille ◽  
Janet Sprintall ◽  
Eric J. Fetzer
Keyword(s):  
Heat Flux ◽  
Southern Ocean ◽  
Surface Temperature ◽  
Turbulent Heat Flux ◽  
Specific Humidity ◽  
Turbulent Heat ◽  
Atmospheric Infrared Sounder

scholarly journals Estimating subpixel turbulent heat flux over leads from MODIS thermal infrared imagery with deep learning

2021 ◽  
Author(s):  
Zhixiang Yin ◽  
Xiaodong Li ◽  
Yong Ge ◽  
Cheng Shang ◽  
Xinyan Li ◽  
...  
Keyword(s):  
Heat Flux ◽  
Surface Temperature ◽  
Spatial Resolution ◽  
Important Variable ◽  
Turbulent Heat Flux ◽  
The Arctic ◽  
Turbulent Heat ◽  
Modis Imagery ◽  
Mixed Pixels ◽  
Thermal Infrared Imagery

Abstract. Turbulent heat flux (THF) over leads is an important variable used for monitoring climate change in the Arctic. Presently, THF over leads is often calculated from satellite imagery. The accuracy of the estimated THF is low for mixed pixels that consist of ice and leads, because the mixed pixels along lead boundaries will lower the accuracy of the surface temperature measured over leads and the corresponding lead map. To address this problem, a deep residual convolutional neural network (CNN)-based framework is proposed to estimate THF over leads at the subpixel scale (DeepSTHF) with remotely sensed imagery. The DeepSTHF allows the production of a sea surface temperature (SST) image and a corresponding lead map with a finer spatial resolution than the input SST image using two CNNs, so that the subpixel scale THF can be estimated from them. The proposed approach is assessed using simulated and real MODIS imagery and compared against the conventional bicubic interpolation and pixel-based methods. The results demonstrate that the proposed CNN-based method can effectively estimate subpixel-scale information from the coarse data and performs well in producing fine spatial resolution SST images and lead maps, thereby allowing researchers to obtain more accurate and reliable THF over leads.

Augmentations to the Noah Model Physics for Application to the Yellow River Source Area. Part II: Turbulent Heat Fluxes and Soil Heat Transport

2015 ◽  
Vol 16 (6) ◽  
pp. 2677-2694 ◽  
Author(s):  
Donghai Zheng ◽  
Rogier van der Velde ◽  
Zhongbo Su ◽  
Xin Wang ◽  
Jun Wen ◽  
...  
Keyword(s):  
Heat Flux ◽  
Organic Matter ◽  
Surface Temperature ◽  
Heat Transport ◽  
Yellow River ◽  
Turbulent Heat Flux ◽  
Heat Fluxes ◽  
The Yellow River ◽  
Turbulent Heat ◽  
Turbulent Heat Fluxes

Abstract This is the second part of a study on the assessment of the Noah land surface model (LSM) in simulating surface water and energy budgets in the high-elevation source region of the Yellow River. Here, there is a focus on turbulent heat fluxes and heat transport through the soil column during the monsoon season, whereas the first part of this study deals with the soil water flow. Four augmentations are studied for mitigating the overestimation of turbulent heat flux and underestimation of soil temperature measurements: 1) the muting effect of vegetation on the thermal heat conductivity is removed from the transport of heat from the first to the second soil layer, 2) the exponential decay factor imposed on is calculated using the ratio of the leaf area index (LAI) over the green vegetation fraction (GVF), 3) Zilitinkevich’s empirical coefficient for turbulent heat transport is computed as a function of the momentum roughness length , and 4) the impact of organic matter is considered in the parameterization of the thermal heat properties. Although usage of organic matter for calculating improves the correspondence between the estimates and laboratory measurements of heat conductivities, it is shown to have a relatively small impact on the Noah LSM performance even for large organic matter contents. In contrast, the removal of the muting effect of vegetation on and the parameterization of greatly enhances the soil temperature profile simulations, whereas turbulent heat flux and surface temperature computations mostly benefit from the modified formulation. Further, the nighttime surface temperature overestimation is resolved from a coupled land–atmosphere perspective.

scholarly journals The bulk parameterizations of turbulent air-sea fluxes in NEMO4: the origin of Sea Surface Temperature differences in a global model study

2022 ◽  
Author(s):  
Giulia Bonino ◽  
Doroteaciro Iovino ◽  
Laurent Brodeau ◽  
Simona Masina
Keyword(s):  
Heat Flux ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Skin Temperature ◽  
Wind Stress ◽  
Ocean Model ◽  
Turbulent Heat Flux ◽  
Global Model ◽  
Sea Surface ◽  
Turbulent Heat

Abstract. Wind stress and turbulent heat fluxes are the major driving forces which modify the ocean dynamics and thermodynamics. In the NEMO ocean general circulation model, these turbulent air-sea fluxes (TASFs), which are components of the ocean model boundary conditions, can critically impact the simulated ocean characteristics. This paper investigates how the different bulk parametrizations to calculated turbulent air-sea fluxes in the NEMO4 (revision 12957) drives substantial differences in sea surface temperature (SST). Specifically, we study the contribution of different aspects and assumptions of the bulk parametrizations in driving the SST differences in NEMO global model configuration at ¼ degree of horizontal resolution. These include the use of the skin temperature instead of the bulk SST in the computation of turbulent heat flux components, the estimation of wind stress and the estimation of turbulent heat flux components which vary in each parametrization due to the different computation of the bulk transfer coefficients. The analysis of a set of short-term sensitivity experiments, where the only experimental change is related to one of the aspects of the bulk parametrizations, shows that parametrization-related SST differences are primarily sensitive to the wind stress differences across parametrizations and to the implementation of skin temperature in the computation of turbulent heat flux components. Moreover, in order to highlight the role of SST-turbulent heat flux negative feedback at play in ocean simulations, we compare the TASFs differences obtained using NEMO ocean model with the estimations from Brodeau et al. (2017), who compared the different bulk parametrizations using prescribed SST. Our estimations of turbulent heat flux differences between bulk parametrizations is weaker with respect to Brodeau et al. (2017) differences estimations.

scholarly journals Characteristics of Satellite-Based Ocean Turbulent Heat Flux around the Korean Peninsula and Relationship with Changes in Typhoon Intensity

2020 ◽  
Vol 13 (1) ◽  
pp. 42
Author(s):  
Jaemin Kim ◽  
Yun Gon Lee
Keyword(s):  
Heat Flux ◽  
Korean Peninsula ◽  
Energy Exchange ◽  
Turbulent Heat Flux ◽  
Heat Fluxes ◽  
Sea Surface ◽  
Specific Humidity ◽  
Turbulent Heat ◽  
Ocean Atmosphere ◽  
Buoy Data

Ocean-atmosphere energy exchange is an important factor in the maintenance of oceanic and atmospheric circulation and the regulation of meteorological and climate systems. Oceanic sensible and latent heat fluxes around the Korean Peninsula were determined using satellite-based air-sea variables (wind speed, sea surface temperature, and atmospheric specific humidity and temperature) and the coupled ocean-atmosphere response experiment (COARE) 3.5 bulk algorithm for six years between 2014 and 2019. Seasonal characteristics of the marine heat flux and its short-term fluctuations during summer typhoons were also investigated. air-sea variables were produced through empirical relationships and verified with observational data from marine buoys around the Korean Peninsula. Satellite-derived wind speed, sea surface temperature, atmospheric specific humidity, and air temperature were strongly correlated with buoy data, with R2 values of 0.80, 0.97, 0.90, and 0.91, respectively. Satellite-based sensible and latent heat fluxes around the peninsula were also validated against fluxes calculated from marine buoy data, and displayed low values in summer and higher values in autumn and winter as the difference between air-sea temperature and specific humidity increased. Through analyses of spatio-temporal fluctuations in the oceanic turbulent heat flux and variations in intensities of typhoons, this study assessed the possibility of monitoring air-sea energy exchange using satellite-based ocean turbulent heat fluxes during high-impact weather.

scholarly journals Estimation of turbulent heat flux over leads using satellite thermal images

2019 ◽  
Vol 13 (6) ◽  
pp. 1565-1582 ◽  
Author(s):  
Meng Qu ◽  
Xiaoping Pang ◽  
Xi Zhao ◽  
Jinlun Zhang ◽  
Qing Ji ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Heat Flux ◽  
Surface Temperature ◽  
Turbulent Heat Flux ◽  
The Arctic ◽  
Landsat 8 ◽  
Turbulent Heat ◽  
Thermal Images ◽  
Modis Data ◽  
Ice Leads

Abstract. Sea ice leads are an important feature in pack ice in the Arctic. Even covered by thin ice, leads can still serve as prime windows for heat exchange between the atmosphere and the ocean, especially in the winter. Lead geometry and distribution in the Arctic have been studied using optical and microwave remote sensing data, but turbulent heat flux over leads has only been measured on-site during a few special expeditions. In this study, we derive turbulent heat flux through leads at different scales using a combination of surface temperature and lead distribution from remote sensing images and meteorological parameters from a reanalysis dataset. First, ice surface temperature (IST) was calculated from Landsat-8 Thermal Infrared Sensor (TIRS) and Moderate Resolution Imaging Spectroradiometer (MODIS) thermal images using a split-window algorithm; then, lead pixels were segmented from colder ice. Heat flux over leads was estimated using two empirical models: bulk aerodynamic formulae and a fetch-limited model with lead width from Landsat-8. Results show that even though the lead area from MODIS is a little larger, the length of leads is underestimated by 72.9 % in MODIS data compared to TIRS data due to the inability to resolve small leads. Heat flux estimated from Landsat-8 TIRS data using bulk formulae is 56.70 % larger than that from MODIS data. When the fetch-limited model was applied, turbulent heat flux calculated from TIRS data is 32.34 % higher than that from bulk formulae. In both cases, small leads accounted for more than a quarter of total heat flux over leads, mainly due to the large area, though the heat flux estimated using the fetch-limited model is 41.39 % larger. A greater contribution from small leads can be expected with larger air–ocean temperature differences and stronger winds.

scholarly journals Estimates of Air–Sea Feedbacks on Sea Surface Temperature Anomalies in the Southern Ocean

2016 ◽  
Vol 29 (2) ◽  
pp. 439-454 ◽  
Author(s):  
Ute Hausmann ◽  
Arnaud Czaja ◽  
John Marshall
Keyword(s):  
Heat Flux ◽  
Southern Ocean ◽  
Surface Temperature ◽  
Radiative Heat ◽  
Spatial Scales ◽  
Heat Fluxes ◽  
Sea Surface ◽  
Turbulent Heat ◽  
Damping Effect ◽  
Heat Flux Feedback

Abstract Sea surface temperature (SST) air–sea feedback strengths and associated decay time scales in the Southern Ocean (SO) are estimated from observations and reanalysis datasets of SST, air–sea heat fluxes, and ocean mixed layer depths. The spatial, seasonal, and scale dependence of the air–sea heat flux feedbacks is mapped in circumpolar bands and implications for SST persistence times are explored. It is found that the damping effect of turbulent heat fluxes dominates over that due to radiative heat fluxes. The turbulent heat flux feedback acts to damp SSTs in all bands and spatial scales and in all seasons, at rates varying between 5 and 25 W m−2 K−1, while the radiative heat flux feedback has a more uniform spatial distribution with a magnitude rarely exceeding 5 W m−2 K−1. In particular, the implied net air–sea feedback (turbulent + radiative) on SST south of the polar front, and in the region of seasonal sea ice, is as weak as 5–10 W m−2 K−1 in the summertime on large spatial scales. Air–sea interaction alone thus allows SST signals induced around Antarctica in the summertime to persist for several seasons. The damping effect of mixed layer entrainment on SST anomalies averages to approximately 20 W m−2 K−1 across the ACC bands in the summer-to-winter entraining season and thereby reduces summertime SST persistence to less than half of that predicted by air–sea interaction alone (i.e., 3–6 months).

Linking submesoscale fronts and air-sea heat fluxes in the Southern Ocean: Results from the first Saildrone circumnavigation of Antarctica

2021 ◽  
Author(s):  
Hanna S. Rosenthal ◽  
Louise C. Biddle ◽  
Sebastiaan Swart ◽  
Sarah T. Gille ◽  
Matthew R. Mazloff
Keyword(s):  
Heat Flux ◽  
Southern Ocean ◽  
Global Climate ◽  
Global Scale ◽  
Turbulent Heat Flux ◽  
Heat Fluxes ◽  
Turbulent Heat ◽  
Fine Scale ◽  
Atmospheric Conditions ◽  
The Impact

<p>The role of the Southern Ocean in the global heat and carbon cycle is fundamental towards our climate, but observational data to quantify air-sea fluxes, such as surface  heat  fluxes, are  still  scarce. In  order  to  investigate  the  effects  of  fine- scale oceanic fronts (0.1 km–10 km) on air-sea fluxes in the Southern Ocean, high-resolution  hydrographic  and  meteorological  data  collected  by  three  un-crewed surface vehicles (Saildrones) during their first Circumnavigation of Antarctica in 2019 was assessed. Comparisons of key variables from the in situ Saildrones datasets with those from ERA5 and a stationary mooring show good  agreement.  Temperature-driven density fronts were detected in the Saildrone data and their impact on the turbulent heat flux was quantified during steady atmospheric conditions.  Over 2000 surface ocean temperature dominated density fronts were detected at length-scales (i.e.  front width) ranging from sub-kilometer to mesoscale (order of 0.1 km–100 km). <br>Temperature-driven density fronts with a length scale (as seen from the Saildrones perspective ) smaller than 1 km contributed 75% and 51% of the sensible and latent heat flux changes, respectively. The direct link between the fronts and the impact on the heat fluxes decreases sharply  when the front length increases. This suggests that smaller (submesoscale) fronts have a larger impact on heat flux variability than larger (balanced) fronts . The parametrization of  these  fine-scale ocean-atmospheric processes  in  global climate  models  could  lead to more accurate  representations  of  the  heat  flux  variability both at local and global scale.</p>

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