Evaluation of monthly turbulent heat fluxes from WHOI analysis and NCEP reanalysis in the tropical Atlantic

The biases and their sources in monthly turbulent heat fluxes from the Woods Hole Oceanographic Institution （WHOI） analysis, and the National Centers for Environmental Prediction-National Center for Atmospheric Research reanalyses 1 and 2 （NCEPI and NCEP2） are checked in the climatically representative regions in the tropical Atlantic using the fluxes from the Southampton Oceanographic Centre （SOC） and the pilot research moored array in the tropical Atlantic （PIRATA） as references. For the WHOI analysis, the biases in turbulent heat fluxes mainly exist in equatorial regions which are due to the overestimated sea surface temperature and the underestimated 2 m air humidity. For the NCEP2 reanalysis, the maximum biases, about （40±5） W/m^2, exist in southeast and northeast trade wind regions, which are mainly caused by the flux algorithm used because the biases in wind speed and air-sea humidity difference are relatively small. In the equatorial regions, the flux biases in the NCEP2 derived from both flux-related basic variables and algorithm are equally large. Although the estimations of time series trends and air-sea humidity difference of the NCEPI are improved greatly in the NCEP2, the biases of latent heat flux in the NCEP2 are about 20 W/m^2 greater than those from the NCEP1 in the trade wind regions. The result shows that the climatologies and monthly variabilities of the turbulent heat fluxes from the WHOI are more accurate than those from the NCEP1 and NCEP2 in the tropical Atlantic, especially on outside of the equatorial regions.

Seasonal variability of turbulent heat fluxes in the tropical Atlantic Ocean based on WHOI flux product

The mean seasonal variability of turbulent heat fluxes in the tropical Atlantic Ocean is examined using the Woods Hole Oceanographic Institution （WHOI） flux product. The most turbulent heat fluxes occur during winter seasons in the two hemispheres, whose centers are located at 10° -20°N and 5° 15°S respectively. In climatological ITCZ, the turbulent heat fluxes are the greatest from June to August, and in equatorial cold tongue the turbulent heat fluxes are the greatest from March to May. Seasonal variability of sensible heat flux is smaller than that of latent heat flux and mainly is dominated by the variations of air-sea temperature difference. In the region with larger climatological mean wind speed （air-sea humidity difference）, the variations of air-sea humidity difference （wind speed） dominate the variability of latent heat flux. The characteristics of turbulent heat flux yielded from theory analysis and WHOI dataset is consistent in physics which turns out that WHOI＇ s flux data are pretty reliable in the tropical Atlantic Ocean.

Effect of Counter-Gradient in the Computation of Turbulent Fluxes of Heat and Moisture in a Regional Model

The counter-gradient terms in the computations of turbulent fluxes of heat and moisture have been included in the PBL parameterization of a regional model for monsoon prediction. Results show that inclusion of counter-gradient terms has a marginal impact in the prediction of large scale monsoon circulation and rainfall rates.

Estimations of Land Surface Characteristic Parameters and Turbulent Heat Fluxes over the Tibetan Plateau Based on FY-4A/AGRI Data

Accurate estimates of land surface characteristic parameters and turbulent heat fluxes play an important role in the understanding of land-atmosphere interaction. In this study, Fengyun-4A (FY-4A) Advanced Geostationary Radiation Imager (AGRI) satellite data and the China Land Data Assimilation System (CLDAS) meteorological forcing dataset CLDAS-V2.0 were applied for the retrieval of broadband albedo, land surface temperature (LST), radiation flux components, and turbulent heat fluxes over the Tibetan Plateau (TP). The FY-4A/AGRI and CLDAS-V2.0 data from 12 March 2018 to 30 April 2018 were first used to estimate the hourly turbulent heat fluxes over the TP. The time series data of in-situ measurements from the Tibetan Observation and Research Platform were divided into two halves-one for developing retrieval algorithms for broadband albedo and LST based on FY-4A, and the other for the cross validation. Results show the root-mean-square errors (RMSEs) of the FY-4A retrieved broadband albedo and LST were 0.0309 and 3.85 K, respectively, which verifies the applicability of the retrieval method. The RMSEs of the downwelling/upwelling shortwave radiation flux and downwelling/upwelling longwave radiation flux were 138.87/32.78 W m^(−2) and 51.55/17.92 W m^(−2), respectively, and the RMSEs of net radiation flux, sensible heat flux, and latent heat flux were 58.88 W m^(−2), 82.56 W m^(−2) and 72.46 W m^(−2), respectively. The spatial distributions and diurnal variations of LST and turbulent heat fluxes were further analyzed in detail.

A Sensitivity Study of Arctic Ice-Ocean Heat Exchange to the Three-Equation Boundary Condition Parametrization in CICE6

In this study,we perform a stand-alone sensitivity study using the Los Alamos Sea ice model version 6(CICE6)to investigate the model sensitivity to two Ice-Ocean(IO)boundary condition approaches.One is the two-equation approach that treats the freezing temperature as a function of the ocean mixed layer(ML)salinity,using two equations to parametrize the IO heat exchanges.Another approach uses the salinity of the IO interface to define the actual freezing temperature,so an equation describing the salt flux at the IO interface is added to the two-equation approach,forming the so-called three-equation approach.We focus on the impact of the three-equation boundary condition on the IO heat exchange and associated basal melt/growth of the sea ice in the Arctic Ocean.Compared with the two-equation simulation,our three-equation simulation shows a reduced oceanic turbulent heat flux,weakened basal melt,increased ice thickness,and reduced sea surface temperature(SST)in the Arctic.These impacts occur mainly at the ice edge regions and manifest themselves in summer.Furthermore,in August,we observed a downward turbulent heat flux from the ice to the ocean ML in two of our three-equation sensitivity runs with a constant heat transfer coefficient(0.006),which caused heat divergence and congelation at the ice bottom.Additionally,the influence of different combinations of heat/salt transfer coefficients and thermal conductivity in the three-equation approach on the model simulated results is assessed.The results presented in this study can provide insight into sea ice model sensitivity to the three-equation IO boundary condition for coupling the CICE6 to climate models.

Coastal buoy observation of air-sea net heat flux in the East China Sea in summer 2020

The full fluxes and associated air-sea variables based on three months of operational buoy observations in the East China Sea(ECS)in summer 2020 were analyzed for the first time.The surface net heat flux(Q_(net))was positive(139.7±77.7 W/m^(2))and was dominated by the combined eff ects of solar shortwave radiation(SW)and latent heat fluxes(LH).The mean heat flux components of 4 reanalysis datasets(NCEP2,MERRA-2,CFSR,and ERA5)and buoy data were compared to assess the mean ability of the modeling/reanalysis simulation.Among the four components of air-sea flux,SW was the best simulated,while LH was the worst simulated.The longwave radiation(LW)and LH values from reanalysis were higher than those from buoy data,especially LH.The high LH resulted in low Q_(net).Furthermore,the 4 reanalysis datasets were compared with the buoy dataset.Among all flux products,the difference in radiation flux was the smallest,while that in the turbulent flux was the greatest.The observed variables related to turbulent flux were analyzed to help determine the cause of the flux discrepancies.High wind speeds were the main cause of this difference.Using the variables provided by the reanalysis data and the same bulk formulas of the Coupled Ocean-Atmospheric Response Experiment(COARE 3.0),we found that the recalculated sensible heat flux(SH)and LH were closer to the observed heat fluxes than the direct model outputs.The signifi cant diff erences between these methods could account for the discrepancies among diff erent data.Among all air-sea flux products,the air-sea flux in ERA5 was closer to the in-situ observations than the other products.The comparison results of reanalysis data provide an important reference for more accurate studies of the summer heat flux in the ECS at the synoptic and climatic scales.

On the turbulent heat fluxes:A comparison among satellite-based estimates,atmospheric reanalyses,and in-situ observations during the winter climate over Arctic sea ice

The surface energy budget is crucial for Arctic sea ice mass balance calculation and climate systems,among which turbulent heat fluxes significantly affect the airesea exchanges of heat and moisture in the atmospheric boundary layer.Satellite observations(e.g.CERES and APPX)and atmospheric reanalyses(e.g.,ERA5)are often used to represent components of the energy budget at regional and pan-Arctic scales.However,the uncertainties of the satellite-based turbulent heat fluxes are largely unknown,and cross-comparisons with reanalysis data and insitu observations are limited.In this study,satellite-based turbulent heat fluxes were assessed against in-situ observations from the N-ICE2015 drifting ice station(north of Svalbard,JanuaryeJune 2015)and ERA5 reanalysis.The turbulent heat fluxes were calculated by two approaches using the satellite-based ice surface temperature and radiative fluxes,surface atmospheric parameters from ERA5,and snow/sea ice thickness from the pan-Arctic Ice Ocean Modeling and Assimilation System(PIOMAS).We found that the bulk-aerodynamic formula based results could better capture the variations of turbulent heat fluxes,while the maximum entropy production based estimates are comparable with ERA5 in terms of root-mean-square error(RMSE).CERES-based estimates outperform the APP-X-based ones but ERA5 performs the best in all seasons(RMSE of 18 and 7 W m^(-2)for sensible and latent heat flux,respectively).The aireice temperature/humidity differences and the surface radiation budget were found the primary driving factors in the bulk-formula method and maximum entropy production(MEP)method,respectively.Furthermore,errors in the surface and near-surface temperature and humidity explain almost 50%of the uncertainties in the estimates based on the bulk-formula,whereas errors in the net radiative fluxes explain more than 50%of the uncertainties in the MEP-based results.

Modeling turbulent heat fluxes over Arctic sea ice using a maximum-entropy-production approach

Recently,an algorithm of surface turbulent heat fluxes over snow/sea ice has been developed based on the theory of maximum entropy production(MEP),which is fundamentally different from the bulk flux algorithm(BF)that has been used in sea ice models for a few decades.In this study,we first assess how well the MEP algorithm captures the observed variations of turbulent heat fluxes over Arctic sea ice.It is found that the calculated heat fluxes by the MEP method are in good agreement with in-situ observations after considering the absorption of incoming radiation in a snow/ice surface layer with infinitesimal depth.We then investigate the effects of two different schemes(MEP vs.BF)in the sea ice model of CICE6 on simulated turbulent heat fluxes and sea ice processes in the Arctic Basin.Our results show that the two different schemes give quite different representations of seasonal variations of heat fluxes,particularly for sensible heat fluxes in summer.The heat fluxes simulated by the MEP produce weak cooling effect on the ice surface in summer,whereas the BF generates a warming effect.As a result,compared to the BF,the MEP leads to a reduced seasonal cycle of Arctic sea ice mass flux by modulating snow-to-ice conversion,basal ice growth,surface ice melt and basal ice melt.

Global Land Surface Climate Analysis Based on the Calculation of a Modified Bowen Ratio

A modified Bowen ratio(BRm),the sign of which is determined by the direction of the surface sensible heat flux,was used to represent the major divisions in climate across the globe,and the usefulness of this approach was evaluated. Five reanalysis datasets and the results of an offline land surface model were investigated. We divided the global continents into five major BRm zones using the climatological means of the sensible and latent heat fluxes during the period 1980–2010:extremely cold,extremely wet,semi-wet,semi-arid and extremely arid. These zones had BRm ranges of(-∞,0),(0,0.5),(0.5,2),(2,10) and(10,+∞),respectively. The climatological mean distribution of the Bowen ratio zones corresponded well with the K ¨oppen-like climate classification,and it reflected well the seasonal variation for each subdivision of climate classification. The features of climate change over the mean climatological BRm zones were also investigated. In addition to giving a map-like classification of climate,the BRm also reflects temporal variations in different climatic zones based on land surface processes. An investigation of the coverage of the BRm zones showed that the extremely wet and extremely arid regions expanded,whereas a reduction in area was seen for the semi-wet and semi-arid regions in boreal spring during the period 1980–2010. This indicates that the arid regions may have become drier and the wet regions wetter over this period of time.

Possible Links between Arctic Sea Ice Loss Events and Cold Eurasian Anomalies in Winter

Recently,there have been two competing perspectives on the links of rapid sea ice retreat over the Barents–Kara Seas(BKS)and in midlatitude severe cold winters over Eurasia.By using the daily ECMWF reanalysis(ERA)-Interim dataset during 1979–2016,we reconcile two contrasting viewpoints,namely,if an upward turbulent heat flux appears and maintains several days after the rapid sea ice loss over the BKS in winter,a dipole structure which consists of a primary positive center of action around the Barents Sea with the other opposite-sign center of action over Eurasian continent is easily amplified,and consequently a cold anomaly over Eurasia will occur,but not vice versa.Our work casts light on the links between the Arctic sea ice loss and Eurasian cold winter anomalies by revealing the different responses of the surface turbulent heat flux(STHF)after rapid sea ice retreat on a daily basis.