Turbulent Latent Heat Fluxes Research Articles

Effects of Arctic sea-ice concentration on turbulent surface fluxes in four atmospheric reanalyses

Abstract. A prerequisite for understanding the local, regional, and hemispherical impacts of Arctic sea-ice decline on the atmosphere is to quantify the effects of sea-ice concentration (SIC) on the turbulent surface fluxes of sensible and latent heat in the Arctic. We analyse these effects utilising four global atmospheric reanalyses, ERA5, JRA-55, MERRA-2, and NCEP/CFSR (including both the NCEP Climate Forecast System Reanalysis (CFSR) and the NCEP Climate Forecast System Version 2 (CFSv2)), and evaluate their uncertainties arising from inter-reanalysis differences in SIC and in the sensitivity of the turbulent surface fluxes to SIC. The magnitude of the differences in SIC is up to 0.15 but typically around 0.05 in most of the Arctic over all four seasons. Orthogonal-distance regression and ordinary-least-squares regression analyses indicate that the greatest sensitivity of both the latent and the sensible heat flux to SIC occurs in the cold season, November to April. For these months, using daily means of data, the average sensitivity is 400 W m−2 for the latent heat flux and over 800 W m−2 for the sensible heat flux per unit of SIC (change in SIC from 0 to 1), with differences between reanalyses that are as large as 300 W m−2 for the latent heat flux and 600 W m−2 for the sensible heat flux per unit of SIC. The sensitivity is highest for the NCEP/CFSR reanalysis. Comparing the periods 1980–2000 and 2001–2021, we find that the effect of SIC on turbulent surface fluxes has weakened owing to the increasing surface temperature of sea ice and sea-ice decline. The results also indicate signs of a decadal-scale improvement in the mutual agreement between reanalyses. The effect of SIC on turbulent surface fluxes arises mostly via the effect of SIC on atmosphere–surface differences in temperature and specific humidity, whereas the effect of SIC on wind speed (via surface roughness and atmospheric-boundary-layer stratification) partly cancels out in the turbulent surface fluxes, as the wind speed increases the magnitudes of both upward and downward fluxes.

Surface Turbulent Fluxes From the MOSAiC Campaign Predicted by Machine Learning

AbstractReliable boundary‐layer turbulence parametrizations for polar conditions are needed to reduce uncertainty in projections of Arctic sea ice melting rate and its potential global repercussions. Surface turbulent fluxes of sensible and latent heat are typically represented in weather/climate models using bulk formulae based on the Monin‐Obukhov Similarity Theory, sometimes finely tuned to high stability conditions and the potential presence of sea ice. In this study, we test the performance of new, machine‐learning (ML) flux parametrizations, using an advanced polar‐specific bulk algorithm as a baseline. Neural networks, trained on observations from previous Arctic campaigns, are used to predict surface turbulent fluxes measured over sea ice as part of the recent MOSAiC expedition. The ML parametrizations outperform the bulk at the MOSAiC sites, with RMSE reductions of up to 70 percent. We provide a plug‐in Fortran implementation of the neural networks for use in models.

Quality evaluation for measurements of wind field and turbulent fluxes from a UAV-based eddy covariance system

Abstract. Instrumentation packages for eddy covariance (EC) measurements have been developed for unoccupied aerial vehicles (UAVs) to measure the turbulent fluxes of latent heat (LE), sensible heat (H), and CO2 (Fc) in the atmospheric boundary layer. This study aims to evaluate the performance of this UAV-based EC system. First, the measurement precision (1σ) of georeferenced wind was estimated to be 0.07 m s−1. Then, the effect of the calibration parameter and aerodynamic characteristics of the UAV on wind measurement was examined by conducting a set of calibration flights. The results showed that the calibration improved the quality of the measured wind field, and the influence of upwash and the leverage effect can be ignored in wind measurement by the UAV. Third, for the measurements of turbulent fluxes, the error caused by instrumental noise was estimated to be 0.03 µmolm-2s-1 for Fc, 0.02 W m−2 for H, and 0.08 W m−2 for LE. Fourth, data from the standard operational flights were used to assess the influence of resonance on the measurements and to test the sensitivity of the measurement under the variation (±30 %) in the calibration parameters around their optimum value. The results showed that the effect of resonance mainly affected the measurement of CO2 (∼5 %). The pitch offset angle (εθ) significantly affected the measurement of vertical wind (∼30 %) and turbulent fluxes (∼15 %). The heading offset angle (εψ) mainly affected the measurement of horizontal wind (∼15 %), and other calibration parameters had no significant effect on the measurements. The results lend confidence to the use of the UAV-based EC system and suggest future improvements for the optimization of the next-generation system.

Surface energy balance fluxes in a suburban area of Beijing: energy partitioning variability

Abstract. Measurements of radiative and turbulent heat fluxes for 16 months in suburban Miyun with a mix of buildings and agriculture allows the changing role of these fluxes to be assessed. Daytime turbulent latent heat fluxes (QE) are largest in summer and smaller in winter, consistent with the net all-wave radiation (Q*), whereas the daytime sensible heat flux (QH) is greatest in spring but smallest in summer rather than in winter, as commonly observed in suburban areas. The results have larger seasonal variability in energy partitioning compared to previous suburban studies. Daytime energy partitioning is between 0.15–0.57 for QH/Q* (mean summer = 0.16; winter = 0.46), 0.06–0.56 for QE/Q* (mean summer = 0.52; winter = 0.10), and 0.26–7.40 for QH/QE (mean summer = 0.32; winter = 4.60). Compared to the literature for suburban areas, these are amongst the lowest and highest values. Results indicate that precipitation, irrigation, vegetation growth activity, and land use and land cover all play critical roles in the energy partitioning. These results will help to enhance our understanding of surface–atmosphere energy exchanges over cities and are critical to improving and evaluating urban canopy models needed to support integrated urban services that include urban planning to mitigate the adverse effects of urban climate change.

Continuous observations of the surface energy budget and meteorology over the Arctic sea ice during MOSAiC

The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) was a yearlong expedition supported by the icebreaker R/V Polarstern, following the Transpolar Drift from October 2019 to October 2020. The campaign documented an annual cycle of physical, biological, and chemical processes impacting the atmosphere-ice-ocean system. Of central importance were measurements of the thermodynamic and dynamic evolution of the sea ice. A multi-agency international team led by the University of Colorado/CIRES and NOAA-PSL observed meteorology and surface-atmosphere energy exchanges, including radiation; turbulent momentum flux; turbulent latent and sensible heat flux; and snow conductive flux. There were four stations on the ice, a 10 m micrometeorological tower paired with a 23/30 m mast and radiation station and three autonomous Atmospheric Surface Flux Stations. Collectively, the four stations acquired ~928 days of data. This manuscript documents the acquisition and post-processing of those measurements and provides a guide for researchers to access and use the data products.

Radiative controls by clouds and thermodynamics shape surface temperatures and turbulent fluxes over land

Land surface temperatures (LSTs) are strongly shaped by radiation but are modulated by turbulent fluxes and hydrologic cycling as the presence of water vapor in the atmosphere (clouds) and at the surface (evaporation) affects temperatures across regions. Here, we used a thermodynamic systems framework forced with independent observations to show that the climatological variations in LSTs across dry and humid regions are mainly mediated through radiative effects. We first show that the turbulent fluxes of sensible and latent heat are constrained by thermodynamics and the local radiative conditions. This constraint arises from the ability of radiative heating at the surface to perform work to maintain turbulent fluxes and sustain vertical mixing within the convective boundary layer. This implies that reduced evaporative cooling in dry regions is then compensated for by an increased sensible heat flux and buoyancy, which is consistent with observations. We show that the mean temperature variation across dry and humid regions is mainly controlled by clouds that reduce surface heating by solar radiation. Using satellite observations for cloudy and clear-sky conditions, we show that clouds cool the land surface over humid regions by up to 7 K, while in arid regions, this effect is absent due to the lack of clouds. We conclude that radiation and thermodynamic limits are the primary controls on LSTs and turbulent flux exchange which leads to an emergent simplicity in the observed climatological patterns within the complex climate system.

Surface energy balance on a polythermal glacier, Arctic, and the role of poleward atmospheric moisture transport

In recent years, increasing moisture over the Arctic and subarctic regions shows that the Arctic is experiencing wetting conditions, and poleward atmospheric moisture transport (PAMT) plays a vital role in the atmosphere-ice/snow interactions in the Arctic. To identify the effect of PAMT on the surface energy balance (SEB) for the Arctic glacier, meteorological data from an automatic weather station (AWS) at 377 m a.s.l. on the Austre Lovénbreen glacier, as well as the ERA5 reanalysis data from 30 April 2014 to 30 April 2015, were analyzed in this paper. Our results show that the net shortwave radiation (Snet) (18 W m−2, 55%), turbulent sensible (H) (14 W m−2, 43%) and subsurface heat flux (G) (1 W m−2, 2%) act as the energy sources, while the net longwave radiation (Lnet) (−19 W m−2, 56%), melt energy (Qm) (−12 W m−2, 35%) and turbulent latent heat flux (LE) (−3 W m−2, 9%) represent the heat sink. The development process of Atmospheric River (AR), primary form of PAMT, near the Svalbard in February 2015 was revealed according to the total column water vapor, 850 hPa winds and geopotential height fields. Compared to summer, the glacier SEB was more affected in winter by PAMT, leading to a frequent overcast and thus increasing air temperature, moisture, and wind speed, all of which are variables governing the SEB by decreasing H, LE and G less than increasing the Lnet. Our findings obtained here can help to better understand the diverse SEB change on the high Arctic glacier from the perspective of PAMT and large-scale atmospheric circulations anomalies.

Turbulent fluxes at kilometer scale determined by optical-microwave scintillometry in a heterogeneous oasis cropland of the Heihe River Basin

Observations of kilometer-scale turbulent fluxes of sensible (H) and latent heat (LE) are required for the validation of flux estimate algorithms from satellite remote-sensing data and the development of parameterization schemes in the hydro-meteorological models. Since 2019, two sets of Optical and Microwave scintillometer (OMS) systems have been operated in the Heihe River Basin of northwestern China, one on an alpine grassland of upper reaches, another on an oasis cropland of middle reaches, to measure both the areal H and LE. Combined with the observations of eddy-covariance (EC) and meteorological tower systems in both sites, an improved procedure for OMS data processing is proposed. The newly proposed procedure especially improves the preprocessing of raw scintillation data, properly uses the current probably better Lüdi et al. (2005) method in deriving meteorological structure parameters, and chooses the coefficients of similarity functions by Kooijmans and Hartogensis (2016) in calculating fluxes. Evaluated with the results of rather homogeneous grassland, the area-averaged H and LE over the heterogeneous oasis are then determined. Estimates of H and LE agree reasonably well with those obtained from EC in most cases. However, the most interesting is that LE over the oasis during the early crop growing stages is clearly larger than that of EC; while both agree well during the longer crop grown periods. Footprint analysis shows that, compared with EC, the OMS has clearly larger source area that contains a slight area of orchard and shelterbelts distributed near the light path, leading to larger LE during the early stages of crop growth. The area-averaged evapotranspiration (ET) over the oasis is then analyzed more acceptably, which varies from 3 to 5 mm day−1 depending on meteorological conditions during the 39 days of the crop growing period. These results are used to validate the Penman-Monteith-Leuning Version 2 (PML-V2) scheme.

Quantifying the Aerodynamic Roughness Length of Snow Surfaces With Time‐Lapse Structure‐From‐Motion

AbstractThe aerodynamic roughness length (z0m) of snow surfaces plays an essential role in estimating turbulent fluxes of latent and sensible heat (LE and H). Constant z0m has been widely used in previous studies due to the difficulty in monitoring dynamic z0m. This leads to large uncertainties in simulating LE and H fluxes. In the current study we used a time‐lapse structure‐from‐motion (SfM) photogrammetric method to study temporal variation in z0m of snow surfaces. The study site was located at the edge of the August‐one ice cap in the Qilian Mountains of China. The study ran from August 2019 to September 2020. We measured aerodynamic roughness length over time (z0m_t) using SfM‐based micro‐topographic methods and validated our results by comparing z0m_t with z0m_prof (profile‐based) and z0m_EC (EC‐based) data. The validated dynamic z0m_t was then used to estimate LE and H fluxes using a bulk aerodynamic method. These results were then compared with LE and H measured by eddy covariance (EC) and with manual sublimation/condensation measurements to indirectly validate z0m_t. We found that z0m_t overall agreed with profile‐based z0m_prof and EC‐based z0m_EC. Indeed, our estimates of bulk LE and H fluxes using dynamic z0m_t agreed slightly better with EC and manual sublimation/condensation measurements than did static EC‐based z0m_EC. Micro‐topographic z0m_t can be helpful in precisely estimating varying LE and H fluxes over the course of a year.

Inferring surface energy fluxes using drone data assimilation in large eddy simulations

Abstract. Spatially representative estimates of surface energy exchange from field measurements are required for improving and validating Earth system models and satellite remote sensing algorithms. The scarcity of flux measurements can limit understanding of ecohydrological responses to climate warming, especially in remote regions with limited infrastructure. Direct field measurements often apply the eddy covariance method on stationary towers, but recently, drone-based measurements of temperature, humidity, and wind speed have been suggested as a viable alternative to quantify the turbulent fluxes of sensible (H) and latent heat (LE). A data assimilation framework to infer uncertainty-aware surface flux estimates from sparse and noisy drone-based observations is developed and tested using a turbulence-resolving large eddy simulation (LES) as a forward model to connect surface fluxes to drone observations. The proposed framework explicitly represents the sequential collection of drone data, accounts for sensor noise, includes uncertainty in boundary and initial conditions, and jointly estimates the posterior distribution of a multivariate parameter space. Assuming typical flight times and observational errors of light-weight, multi-rotor drone systems, we first evaluate the information gain and performance of different ensemble-based data assimilation schemes in experiments with synthetically generated observations. It is shown that an iterative ensemble smoother outperforms both the non-iterative ensemble smoother and the particle batch smoother in the given problem, yielding well-calibrated posterior uncertainty with continuous ranked probability scores of 12 W m−2 for both H and LE, with standard deviations of 37 W m−2 (H) and 46 W m−2 (LE) for a 12 min vertical step profile by a single drone. Increasing flight times, using observations from multiple drones, and further narrowing the prior distributions of the initial conditions are viable for reducing the posterior spread. Sampling strategies prioritizing space–time exploration without temporal averaging, instead of hovering at fixed locations while averaging, enhance the non-linearities in the forward model and can lead to biased flux results with ensemble-based assimilation schemes. In a set of 18 real-world field experiments at two wetland sites in Norway, drone data assimilation estimates agree with independent eddy covariance estimates, with root mean square error values of 37 W m−2 (H), 52 W m−2 (LE), and 58 W m−2 (H+LE) and correlation coefficients of 0.90 (H), 0.40 (LE), and 0.83 (H+LE). While this comparison uses the simplifying assumptions of flux homogeneity, stationarity, and flat terrain, it is emphasized that the drone data assimilation framework is not confined to these assumptions and can thus readily be extended to more complex cases and other scalar fluxes, such as for trace gases in future studies.

Excitation of the Madden‐Julian Oscillation in Response to Transient Ocean Warming in SPCAM

AbstractRecent studies have suggested that the Madden‐Julian oscillation (MJO) could be generated as part of atmospheric adjustment to localized equatorial heating in models properly resolving moist convection. Here we use the Super‐parameterized Community Atmosphere Model (SPCAM) to study atmospheric response to transient sea surface warming in the equatorial Indian Ocean, which leads to the excitation of an MJO event, robust across different experiments, in addition to the expected equatorial Rossby and Kelvin waves. A moist static energy (MSE) budget analysis suggests that longwave and surface turbulent latent heat flux anomalies are predominantly responsible for the MJO excitation; however, these terms oppose its eastward propagation. In contrast, advection of MSE generally weakens the MJO amplitude, but contributes to its eastward propagation. These results highlight the role of the MJO in the moist atmospheric adjustment to localized tropical heating, with implications for the MJO mechanisms and prediction.

UDALES 1.0: a large-eddy simulation model for urban environments

Abstract. Urban environments are of increasing importance in climate and air quality research due to their central role in the population's health and well-being. Tools to model the local environmental conditions, urban morphology and interaction with the atmospheric boundary layer play an important role for sustainable urban planning and policy making. uDALES is a high-resolution, building-resolving, large-eddy simulation code for urban microclimate and air quality. uDALES solves a surface energy balance for each urban facet and models multi-reflection shortwave radiation, longwave radiation, heat storage and conductance, as well as turbulent latent and sensible heat fluxes. Vegetated surfaces and their effect on outdoor temperatures and energy demand can be studied. Furthermore, a scheme to simulate emissions and transport of passive and reactive gas species is present. The energy balance has been tested against idealised cases and the dispersion against wind tunnel experiments of the Dispersion of Air Pollution and its Penetration into the Local Environment (DAPPLE) field study, yielding satisfying results. uDALES can be used to study the effect of new buildings and other changes to the urban landscape on the local flow and microclimate and to gain fundamental insight into the effect of urban morphology on local climate, ventilation and dispersion. uDALES is available online under the GNU General Public License and remains under active maintenance and development.

GABLS4 intercomparison of snow models at Dome C in Antarctica

Abstract. The Antarctic plateau, characterized by cold and dry weather conditions with very little precipitation, is mostly covered by snow at the surface. This paper describes an intercomparison of snow models, of varying complexity, used for numerical weather prediction or academic research. The results of offline numerical simulations, carried out during 15 d in 2009, on a single site on the Antarctic plateau, show that the simplest models are able to reproduce the surface temperature as well as the most complex models provided that their surface parameters are well chosen. Furthermore, it is shown that the diversity of the surface parameters of the models strongly impacts the numerical simulations, in particular the temporal variability of the surface temperature and the components of the surface energy balance. The models tend to overestimate the surface temperature by 2–5 K at night and underestimate it by 2 K during the day. The observed and simulated turbulent latent heat fluxes are small, of the order of a few W m−2, with a tendency to underestimate, while the sensible heat fluxes are in general too intense at night as well as during the day. The surface temperature errors are consistent with too large a magnitude of sensible heat fluxes during the day and night. Finally, it is shown that the most complex multilayer models are able to reproduce well the propagation of the daily diurnal wave, and that the snow temperature profiles in the snowpack are very close to the measurements carried out on site.

Large-Eddy Simulations of Marine Boundary Layer Clouds Associated with Cold-Air Outbreaks during the ACTIVATE Campaign. Part I: Case Setup and Sensitivities to Large-Scale Forcings

Abstract Large-eddy simulation (LES) is able to capture key boundary layer (BL) turbulence and cloud processes. Yet, large-scale forcing and surface turbulent fluxes of sensible and latent heat are often poorly prescribed for LESs. We derive these quantities from measurements and reanalysis obtained for two cold-air outbreak (CAO) events during Phase I of the Aerosol Cloud Meteorology Interactions over the Western Atlantic Experiment (ACTIVATE) in February–March 2020. We study the two contrasting CAO cases by performing LES and test the sensitivity of BL structure and clouds to large-scale forcings and turbulent heat fluxes. Profiles of atmospheric state and large-scale divergence and surface turbulent heat fluxes obtained from ERA5 data agree reasonably well with those derived from ACTIVATE field measurements for both cases at the sampling time and location. Therefore, we adopt the time-evolving heat fluxes, wind, and advective tendencies profiles from ERA5 data to drive the LES. We find that large-scale thermodynamic advective tendencies and wind relaxations are important for the LES to capture the evolving observed BL meteorological states characterized by the hourly ERA5 data and validated by the observations. We show that the divergence (or vertical velocity) is important in regulating the BL growth driven by surface heat fluxes in LESs. The evolution of liquid water path is largely affected by the evolution of surface heat fluxes. The liquid water path simulated in LES agrees reasonably well with the ACTIVATE measurements. This study paves the path to investigate aerosol–cloud–meteorology interactions using LES informed and evaluated by ACTIVATE field measurements.

Evaluation of nature-based solutions implementation scenarios, using urban surface modelling

The present paper aims to study the impact of Nature Based Solutions (NBS) on the urban environment. The Surface Urban Energy and Water balance Scheme (SUEWS) is used to quantify the impact of NBS in the city of Heraklion, Crete, Greece, a densely built urban area. Local meteorological data and data from an Eddy Covariance flux tower installed in the city center are used for the model simulation and evaluation. Five different scenarios are tested by replacing the city’s roofs and pavements with green infrastructure, i.e., trees and grass, and water bodies. The NBS impact evaluation is based on the changes of air temperature above 2m from the ground, relative humidity and energy fluxes. A decrease of the air temperature is revealed with the highest reduction (2.3%) occurring when the pavements are replaced with grass for all scenarios. The reduction of the air temperature is followed by a decrease in turbulent sensible heat flux. For almost all cases, an increase of the relative humidity is noticed, accompanied by a considerable increase of the turbulent latent heat flux. Therefore, NBS in cities change the energy balance significantly and modify the urban environment for the citizens' benefit.

Enhanced Turbulent Heat Fluxes Improve Meiyu‐Baiu Simulation in High‐Resolution Atmospheric Models

AbstractBased on 10 pairs of atmospheric general circulation models from the Coupled Model Intercomparison Project Phase 6 High Resolution Model Intercomparison Project, we find that high‐resolution models (HRMs, ∼50 km) perform better than low‐resolution models (LRMs, ∼100 km) in simulating the East Asian summer monsoon (EASM) rain belt. We attribute the increased rainfall to enhanced vertical advection of water vapor in the HRMs which is mainly contributed by enhanced vertical motion. Based on moist static energy analyses, the stronger vertical motion in the HRMSs is mainly balanced by enhanced net energy flux into the atmosphere column in the “Meiyu‐Baiu” (MB) region due to the increase of air‐sea turbulent latent heat fluxes along the Kuroshio and sensible heat fluxes over land. The increased net energy flux in the HRMs drives stronger ascending motion, resulting in more realistic rainfall in the MB region. Higher saturated specific humidity determined by finer sea surface temperature, less near‐surface specific humidity along the Kuroshio, and stronger near‐surface winds on western side of the western North Pacific Subtropical High strengthened by the enhanced pressure gradient together contribute to higher ventilation efficiencies and enhanced ocean forcing along the Kuroshio, leading to more turbulent latent heat fluxes in the HRMs. Additionally, drier and less cloudy atmosphere in the HRMs result in more downward shortwave radiation heating over the land, which partly contributes to the increased sensible heat flux. This understanding of the sensitivity of simulated MB to model resolution has implications for precipitation simulation and prediction over East Asia.

Sensitivity of the Greenland surface mass and energy balance to uncertainties in key model parameters

Abstract. We investigate the sensitivity of a distributed glacier surface mass and energy balance model using a variance-based analysis, for two distinct periods of the last glacial cycle: the present day (PD) and the Last Glacial Maximum (LGM). The results can be summarized in three major findings: the sensitivity towards individual model parameters and parameterizations is as variable in space as it is in time. The model is most sensitive to uncertainty related to atmospheric emissivity and the down-welling longwave radiation. While the turbulent latent heat flux has a sizable contribution to the surface mass balance uncertainty in central Greenland today, it dominates over the entire ice sheet during the cold climate of the LGM, in spite of its low impact on the overall surface mass balance of the Greenland ice sheet in the modern climate. We conclude that quantifying the model sensitivity is very helpful for tuning free model parameters because it clarifies the relative importance of individual parameters and highlights interactions between them that need to be considered.

Monsoon Clouds Control the Summer Surface Energy Balance on East Rongbuk Glacier (6,523 m Above Sea Level), the Northern of Mt. Qomolangma (Everest)

AbstractTo identify the atmospheric controls of the summertime glacier surface energy balance in the Himalayas, in situ meteorological data collected at 6,523 m above sea level during May–July 2005 were obtained and analyzed. Our results showed that net shortwave radiation (103 W m−2) and turbulent sensible heat flux (12 W m−2) acted as energy sources, and net longwave radiation (−62 W m−2) and turbulent latent heat flux (−20 W m−2) represented heat sinks. Cloud cover controlled the summer surface energy balance. During the active period of the South Asian Summer Monsoon, the frequent cloud coverage increased the incoming longwave radiation more than it decreased the incident solar radiation. Intensification (weakening) of the South Asian Summer Monsoon strengthened (suppressed) surface melting. The melt energy measured during the nonmonsoon period was small due to the energy consumption associated with glacier volume warming, energy loss from sublimation, and large heat loss through net longwave radiation due to the low amount of incoming longwave radiation caused by the low cloudiness. The comparison of glacier surface energy balances on the Tibetan Plateau shows that on continental glaciers, net radiation is lower and accounts for a smaller contribution to energy sources, and the dominant energy sinks are sublimation and evaporation, rather than melting, which is the primary energy sink for maritime/subcontinental glaciers. This implies an important spatial variability in glacial sensitivity to different climatic conditions on the Tibetan Plateau.

Advection Fog over the Eastern Yellow Sea: WRF Simulation and Its Verification by Satellite and In Situ Observations

An observed sea fog event over the Eastern Yellow Sea on 15–16 April 2012 was reproduced in the Weather Research and Forecasting (WRF) simulation with high-resolution to investigate the roles of physical processes and synoptic-scale flows on advection fog with phase transition. First, it was verified by a satellite-based fog detection algorithm and in situ observation data. In the simulation, longwave (infrared) radiative cooling (LRC) with a downward turbulent sensible heat flux (SHF), due to the turbulence after sunset, triggered cloud formation over the surface when warm-moist air advection occurred. At night, warm air advection with continuous cooling due to longwave radiation and SHF near the surface modulated the change of the SHF from downward to upward, resulting in a drastic increase in the turbulent latent heat flux (LHF) that provided sufficient moisture at the lower atmosphere (self-moistening). This condition represents a transition from cold-sea fog to warm-sea fog. Enhanced turbulent mixing driven by a buoyancy force increased the depth of the sea fog and the marine atmospheric boundary layer (MABL) height, even at nighttime. In addition, cold air advection with a prevailing northerly wind at the top of the MABL led to a drastic increase in turbulent mixing and the MABL height and rapid growth of the height of sea fog. After sunrise, shortwave radiative warming in the fog layers offsetting the LRC near the surface weakened thermal instability, which contributed to the reduction in the MABL height, even during the daytime. In addition, dry advection of the northerly wind induced dissipation of the fog via evaporation. An additional sensitivity test of sea surface salinity showed weaker and shallower sea fog than the control due to the decrease in both the LHF and local self-moistening. Detailed findings from the simulated fog event can help to provide better guidance for fog detection using remote sensing.

The impact of sea waves on turbulent heat fluxes in the Barents Sea according to numerical modeling

Abstract. This paper investigates the impact of sea waves on turbulent heat fluxes in the Barents Sea. The Coupled Ocean–Atmosphere Response Experiment (COARE) algorithm, meteorological data from reanalysis and wave data from the WAVEWATCH III wave model results were used. The turbulent heat fluxes were calculated using the modified Charnock parameterization for the roughness length and several parameterizations that explicitly account for the sea wave parameters. A catalog of storm wave events and a catalog of extreme cold-air outbreaks over the Barents Sea were created and used to calculate heat fluxes during extreme events. The important role of cold-air outbreaks in the energy exchange between the Barents Sea and the atmosphere is demonstrated. A high correlation was found between the number of cold-air outbreak days and turbulent fluxes of sensible and latent heat, as well as with the net flux of longwave radiation averaged over the ice-free surface of the Barents Sea during a cold season. The differences in the long-term mean values of heat fluxes calculated using different parameterizations for the roughness length are small and are on average 1 %–3 % of the flux magnitude. The parameterizations of Taylor and Yelland (2001) and Oost et al. (2002) lead to an increase in the magnitude of the fluxes on average, and the parameterization of Drennan et al. (2003) leads to a decrease in the magnitude of the fluxes over the entire sea compared with the Charnock parameterization. The magnitude of heat fluxes and their differences during the storm wave events exceed the mean values by a factor of 2. However, the effect of explicitly accounting for the wave parameters is, on average, small and multidirectional, depending on the parameterization used for the roughness length. With respect to the climatic aspect, it can be argued that explicitly accounting for sea waves in the calculations of heat fluxes can be neglected. However, during the simultaneously observed storm wave events and cold-air outbreaks, the sensitivity of the calculated values of fluxes to the parameterizations used increases along with the turbulent heat transfer increase. In some extreme cases, during storms and cold-air outbreaks, the difference exceeds 700 W m−2.