Regional variability of anthropogenic heat flux in Iran and evaluation of a cluster-based deep learning framework

Air‐sea flux variability has contributions from both ocean and atmosphere at different spatio‐temporal scales. Atmospheric synoptic scales and the air‐sea turbulent heat flux that they drive are well represented in climate models, but ocean mesoscales and their associated variability are often not well resolved due to non‐eddy‐resolving spatial resolutions of current climate models. We deploy a physics‐based stochastic subgrid‐scale parameterization for ocean density, that reinforces the lateral density variations due to oceanic eddies, and examine its effect on air‐sea heat flux variability in a comprehensive coupled climate model. The stochastic parameterization substantially modifies sea surface temperature (SST) and latent heat flux (LHF) variability and their co‐variability, primarily at scales near the resolution of the ocean model grid. Enhancement in the SST‐LHF anomaly covariance, and correlations, indicate that the ocean‐intrinsic component of the air‐sea heat flux variability is more consistent with high‐resolution satellite observations, especially in Gulf Stream region.

Eddy covariance (EC) studies typically involve the use of one or maximum two measuring towers, which leads to a low level of spatial replication, compromising the statistical representativity of EC measurements, especially above highly heterogeneous ecosystems, such as agroforestry systems. Lower-cost eddy covariance setups (LC-EC) represent a potential solution to this problem, since their affordability allows for the installation of multiple EC towers to study heterogeneity at the landscape scale. In the last years, several LC-EC setups have been successfully validated against conventional EC setups (CON-EC), with the main difference being the use of slower gas analyzers. These introduce a higher uncertainty due to the enhanced high-frequency spectral attenuation in the turbulent energy spectrum.In this study, we analyzed turbulent fluxes of CO2 and H2O and turbulence characteristics measured by three flux towers equipped with LC-EC setups above one agroforestry system located in Wendhausen, Germany. The agroforestry system was a Short Rotation Alley Cropping (SRAC) system, consisting of alternating rows of trees and crops. The three flux towers were installed at different North-South aligned tree stripes. Additionally, we compared the results of the three LC-EC setups above the SRAC with another LC-EC setup installed at an adjacent monocropping (MC) field.The objectives of the study were: (i) to evaluate the spatial variability of EC fluxes from the three flux towers above the SRAC system; (ii) to compare the variability of fluxes within the SRAC to the variability of fluxes between SRAC and MC; (iii) to quantify whether the use of several LC-EC setups counteracts the higher uncertainty associated to LC-EC, due to the increased statistical robustness of the measurement network compared to the hypothetical use of just one EC station.The highest spatial variability across the SRAC was measured for CO2 fluxes, followed by latent heat (LE) flux, with coefficients of variation, calculated following Oren et al. (2006) (https://doi.org/10.1111/j.1365-2486.2006.01131.x), of 2.3 and 1.4 (dimensionless), respectively. The spatial variability in CO2 and LE fluxes within the SRAC was similar to the variability between MC and SRAC, and was attributed to the different land cover types around the towers. On the other hand, the spatial variability in sensible heat flux (H), momentum flux and turbulence characteristics (such as friction velocity and variance of vertical wind speed), within the SRAC, was smaller than the variability between SRAC and MC, likely explained by the development of an internal boundary layer (IBL) above the SRAC.Our results show that the heterogeneity of the SRAC, despite not affecting significantly the turbulence characteristics across the site, leads to a large spatial variation in CO2 and LE fluxes. Therefore, a distributed network of several EC systems is necessary to properly quantify patterns and drivers of CO2 and latent heat fluxes above such heterogeneous land-use systems.

Spatial variability in soil heat flux at three Inner Mongolia steppe ecosystems

The paper considers the spatial and temporal variability of sensible and latent heat fluxes over the Barents and Kara seas during 1979-2018 based on the ERA-Interim reanalysis data with a 6-hour resolution. It is shown that the localization of extreme turbulent fluxes over the past decades has not changed as compared to the middle and second half of the 20th century. It is revealed that the greatest spatial and temporal variability of the fluxes is observed in the southern and southwestern sectors of the Barents Sea. It is demonstrated that the winter values of the spatial variability of heat fluxes exceed the summer ones by 2-5 times, and annual total heat flux values in the Barents Sea are 3-5 times higher than in the Kara Sea. The study of the influence of the pressure field anomalies during different phases of the North Atlantic, Arctic, and Scandinavian oscillations on the intensity of turbulent fluxes showed that the area of warm currents of the Barents Sea is most sensitive to changes in the atmospheric circulation.

The variability and trend of volume and advective heat flux, in addition to the net inflow and outflow of advective heat flux in the Java Sea for 64 years (1950–2013), along with its relationship with the monsoon, ENSO (El Niño Southern Oscillation), and IOD (Indian Ocean Dipole), have all been studied. A simulation of the 3D hydrodynamic HYCOM (HYbrid Coordinate Ocean Model) with a 1/8° grid resolution was performed in this study. Judging from the simulated results, the seasonal variability, which has a period of 12 months, has a very significant impact on contributing to the variability and trend of volume and advective heat flux, as well as the net inflow and outflow of advective heat flux in the Java Sea for 64 years. This is followed by interannual variability, which has a time range of 1.5–6.5 years, and interdecadal variability, with a period of 21.3–32 years. The interannual variability in the Java Sea is strongly caused by ENSO and IOD. El Niño and a positive IOD caused a weakening of southward transport through Karimata and the Bangka Strait. On the contrary, southward transport strengthened during La Niña and the negative IOD. Furthermore, La Niña and a positive IOD both strengthen (weaken) the transport westward (eastward) in the Sunda Strait (Eastern Java). On the other hand, El Niño and a negative IOD weaken (strengthen) the westward (eastward) transport in the Sunda Strait (Eastern Java). According to the findings, the IOD effect is stronger than the ENSO effect in the Java Sea. The inflow and outflow of volume transport in the Java Sea are in balance, but not the advective heat flux. The advective heat transported through Karimata and Bangka Strait to the Java Sea is up to 0.216 PW, while the total advective heat flux through the outflow straits (Sunda Strait and Eastern Java) is 0.220 PW. Thus, the net advective heat flux out of the Java Sea is 0.004 PW, allegedly obtained from an atmosphere–sea interaction in which the sea received heat from the atmosphere.

Seasonal and regional variability of upper ocean diapycnal heat flux in the Atlantic cold tongue

The variability of surface heat flux over the Indian Ocean is investigated using in situ observational data. First, the Indian Ocean is divided into eight regions and the power spectra of surface heat fluxes are calculated for each region. Consequently it is shown that the surface heat flux over the Indian Ocean has three characteristic timescales: (1) the high frequency timescale (periods shorter than 20 months), (2) the middle frequency timescale (periods between 20 and 60 months), and (3) the low frequency timescale (periods longer than 60 months). Seasonal variation is dominant for the high frequency timescale, with shortwave radiation and the latent heat flux being the principal components of the variability at this timescale. Furthermore, the seasonal variation can be divided into three patterns depending on the region. The variation of shortwave radiation and the latent heat flux are also dominant in the middle‐frequency timescale. In some regions, heat flux variation for this timescale appears to be associated with El Niño. For the low‐frequency timescale, the latent heat flux is dominant. It should be noted that the heat flux from the ocean to the atmosphere has clearly increased since the late 1970s as a result of increases in wind speeds and the specific humidity difference.

Based on hydrographic data obtained at an ice camp deployed in the Makarov Basin by the 4th Chinese Arctic Research Expedition in August of 2010, temporal variability of vertical heat flux in the upper ocean of the Makarov Basin is investigated together with its impacts on sea ice melt and evolution of heat content in the remnant of winter mixed layer (rWML). The upper ocean of the Makarov Basin under sea ice is vertically stratified. Oceanic heat flux from mixed layer (ML) to ice evolves in three stages as a response to air temperature changes, fluctuating from 12.4 W/m2 to the maximum 43.6 W/m2. The heat transferred upward from ML can support (0.7±0.3) cm/d ice melt rate on average, and daily variability of melt rate agrees well with the observed results. Downward heat flux from ML across the base of ML is much less, only 0.87 W/m2, due to enhanced stratification in the seasonal halocline under ML caused by sea ice melt, indicating that increasing solar heat entering summer ML is mainly used to melt sea ice, with a small proportion transferred downward and stored in the rWML. Heat flux from ML into rWML changes in two phases caused by abrupt air cooling with a day lag. Meanwhile, upward heat flux from Atlantic water (AW) across the base of rWML, even though obstructed by the cold halocline layer (CHL), reaches 0.18 W/m2 on average with no obvious changing pattern and is also trapped by the rWML. Upward heat flux from deep AW is higher than generally supposed value near 0, as the existence of rWML enlarges the temperature gradient between surface water and CHL. Acting as a reservoir of heat transferred from both ML and AW, the increasing heat content of rWML can delay the onset of sea ice freezing.

This study analyzes the effects of interannual variation in surface heat flux on the variability of the upper layer circulation in the East Sea (Sea of Japan) via a series of numerical experiments. Comparing the intrinsic variability of the upper layer circulation, the interannual variation in the surface heat flux amplifies the variability in the Yamato Basin, but not in the Ulleung Basin. The variability in the water temperature in the northern region is highly correlated with the variability in the surface heat flux with a 1-month time lag. Under strong cooling conditions, the cyclonic gyre and convection in the northern region are intensified, and the expansion of the cold water area facilitates a more pronounced southward intrusion compared to weak cooling conditions. However, the interannual variation in surface heat flux does not significantly impact the northernmost latitude of the western boundary current (i.e., the East Korea Warm Current). Instead, the northernmost latitude of the East Korea Warm Current is influenced primarily by the magnitude of the strong positive winter wind stress curl in the northern region, which greatly affects the southward flow of cold water along the Korean coast. An increased (decreased) volume transport or lateral heat flux through Korea/Tsushima Strait promotes the eastward (westward) propagation of eddies distributed in the Yamato Basin, thereby affecting the meandering pattern of the Tsushima Warm Current. This study is expected to enhance understanding of the respective contributions of interannual variation in individual external forcing factors to the variability of the upper layer circulation in the East Sea.

Eustasy, supercontinental insulation, and the temporal variability of terrestrial heat flux

The seasonal and spatial variability of surface heat fluxes is crucial to the understanding of urban heat island phenomenon and dynamics. To estimate energy fluxes, remote sensing derived biophysical variables need to be integrated with surface atmospheric parameters measured in meteorological stations or in situ field measurements. In this study, based on the two-source energy balance algorithm, we applied a method to estimate surface energy fluxes by combined use of multispectral ASTER images and routine meteorological data, and applied it to the City of Indianapolis, United States, aiming at in-depth understanding of the spatial patterns of energy fluxes. By computing the fluxes by land use and land cover (LULC) type, we further investigated the spatial variability of heat fluxes. Results show that the energy fluxes possessed a strong seasonality, with the highest net radiation in summer, followed by spring, fall and winter. Sensible heat flux tended to change largely with surface temperature, while latent heat was largely modulated by the change in vegetation abundance and vigor and the accompanying moisture condition. The fluctuation in all heat fluxes tended to be high in the summer months and low in the winter months. Sensible and latent heat fluxes showed a stronger spatial variability than net radiation and ground heat flux. The variations of net radiation among the land use/cover types were mainly attributable to surface albedo and temperature, while the within-class variability in the turbulent heat fluxes was more associated with the changes in vegetation, water bodies, and other surface factors.

Variable viscosity effects on free and mixed convection boundary-layer flow from a horizontal surface in a saturated porous medium - variable heat flux

Evaluation of empirical heat transfer models using TFG heat flux sensors

Accurate heat flux estimation in continuous casting Molds via MH-MCMC Bayesian Inverse Method

The features of the spatial distribution of climate values and the coefficients of linear trends of total tur-bulent heat fluxes are revealed, based on NCEP/NCAR reanalysis data for 1950–2020 for the Atlantic Ocean. Variability of total turbulent heat fluxes is investigated on scales of more than 10 and more than 30 years. It is shown that the trends of average annual total heat fluxes significant at 95% level in most part of the Atlantic Ocean area are negative (except for the western parts of anticyclonic gyres and area of arctic sea ice edge). It is confirmed that the maxima of the low-frequency variability of the total heat fluxes correspond to important energy-active zones of the Atlantic, they are North Atlantic deep-water mass formation region, ice edge zone in the north of the North Atlantic and the Atlantic sector of the Arc-tic Ocean.