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Accurate observational estimation of the ocean surface heat, momentum, and freshwater fluxes is crucial for studies of the global climate system. Estimating surface flux using satellite remote sensing techniques is one possible answer to this challenge. In this paper, we introduce J-OFURO3, a third-generation data set developed by the Japanese Ocean Flux Data Sets with Use of Remote-Sensing Observations (J-OFURO) research project, which represents a significant improvement from older data sets as the result of research and development conducted from several perspectives. J-OFURO3 offers data sets for surface heat, momentum, freshwater fluxes, and related parameters over the global oceans (except regions of sea ice) from 1988 to 2013. The surface flux data, based on a 0.25° grid system, have a higher spatial resolution and are more accurate than the previous efforts. This has been achieved through the adopting of the state-of-the-art algorithms that estimate the near-surface air specific humidity and the improvement of techniques using observations from multi-satellite sensors. Comparisons with in situ observations using a systematic system developed along with the J-OFURO3 data set confirmed these improvements in accuracy, as did comparisons with other data sets. J-OFURO3 data are of good quality, facilitating a clearer understanding of more fine-scale ocean–atmosphere features (such as ocean fronts, mesoscale eddies, and geographic features) and their effects on surface fluxes. The information contained in this long-term (26 year) data set is demonstrably beneficial to understanding climate change and its relationship to oceans and the atmosphere.

Sixteen monthly air–sea heat flux products from global ocean/coupled reanalyses are compared over 1993–2009 as part of the Ocean Reanalysis Intercomparison Project (ORA-IP). Objectives include assessing the global heat closure, the consistency of temporal variability, comparison with other flux products, and documenting errors against in situ flux measurements at a number of OceanSITES moorings. The ensemble of 16 ORA-IP flux estimates has a global positive bias over 1993–2009 of 4.2 ± 1.1 W m −2 . Residual heat gain (i.e., surface flux + assimilation increments) is reduced to a small positive imbalance (typically, +1–2 W m −2 ). This compensation between surface fluxes and assimilation increments is concentrated in the upper 100 m. Implied steady meridional heat transports also improve by including assimilation sources, except near the equator. The ensemble spread in surface heat fluxes is dominated by turbulent fluxes (>40 W m −2 over the western boundary currents). The mean seasonal cycle is highly consistent, with variability between products mostly <10 W m −2 . The interannual variability has consistent signal-to-noise ratio (~2) throughout the equatorial Pacific, reflecting ENSO variability. Comparisons at tropical buoy sites (10°S–15°N) over 2007–2009 showed too little ocean heat gain (i.e., flux into the ocean) in ORA-IP (up to 1/3 smaller than buoy measurements) primarily due to latent heat flux errors in ORA-IP. Comparisons with the Stratus buoy (20°S, 85°W) over a longer period, 2001–2009, also show the ORA-IP ensemble has 16 W m −2 smaller net heat gain, nearly all of which is due to too much latent cooling caused by differences in surface winds imposed in ORA-IP.

Inconsistent findings in soil moisture (SM)‐precipitation feedback literature motivate further research into the role of the boundary layer in these feedbacks. The present study explores mechanisms that can explain the spatial patterns found in a previous analysis employing satellite measured SM: positive feedback in the semi‐arid western U.S. (higher morning SM predicting greater likelihood of afternoon rainfall), and negative feedback in the humid east. Using a cloud–topped boundary layer model, we examine how evaporative fraction (EF, a proxy for SM) influences cloud mass flux (CMF). We then use logistic regression to relate CMF to precipitation. The results are consistent with the previous analysis: in semi‐arid areas, increased humidification with increased EF dominates CMF strength, yielding net positive feedbacks; in humid areas, reductions in convective velocity with increasing EF dominate the CMF, yielding net negative feedbacks. Such offsetting feedbacks may contribute to inconsistencies reported in the literature.

Lake surface fluxes provide important information about the lake's thermal environment. To capture their spatial variations, a ship serves as an excellent platform for applying the eddy correlation (EC) method. Although ship‐based EC measurements have been conducted over the ocean, this has not been the case over lake surfaces. Ship‐based measurements in a lake differ from those over the ocean in terms of the freedom to select the ship, route, and operation, as well as the wave regime, creating measurement conditions that have not been addressed in ocean studies. Thus, 10‐day EC flux measurements on the highly maneuverable yet stable research ship NIES'94 were conducted in Lake Kasumigaura (surface area of 172 km2), which facilitated extensive data analysis on the ship's motion and fluxes under various conditions. The results indicated that the ship's motion differs greatly depending on the ship's shape and dimensions, and that a larger fluctuation in roll and pitch angles propagates into a larger error of the vertical wind velocity measurements. The motion correction was found necessary for momentum fluxes, while it is preferable but may not be essential under favorable conditions for scalar fluxes. Comparisons between the fluxes obtained from the EC method and those from the bulk method showed that the ship's speed and direction and wave height have minimal impact on the agreement, reflecting the use of a stable ship and lower wave height in our study, leading to small ship motion in Lake Kasumigaura compared to the ocean.

In Earth system modeling, the land surface is coupled with the atmosphere through surface turbulent fluxes. These fluxes are computed using mean meteorological variables between the surface and a reference height in the atmosphere. However, the dependence of flux computation on the reference height, which is usually set as the lowest level in the atmosphere in Earth system models, has not received much attention. Based on high-resolution large-eddy simulation (LES) data under unstable conditions, we find the setting of reference height is not trivial within the framework of current surface layer theory. With a reasonable prescription of aerodynamic roughness length (following the setting in LESs), reference heights near the top of the surface layer tend to provide the best estimate of surface fluxes, especially for the momentum flux. Furthermore, this conclusion for the sensible heat flux is insensitive to the ratio of roughness length for momentum versus heat. These results are robust, whether using the classical or revised surface layer theory. They provide a potential guide for setting the proper reference heights for Earth system modeling and can be further tested in the near future using observational data from land–atmosphere feedback observatories.

Increased resolution has enabled kilometer‐scale weather and climate models to partially resolve secondary circulations, including horizontal convective rolls (HCRs) and cold pool gust fronts. Although these circulations are ubiquitous in convective boundary layers over land, their impacts on the surface energy balance are largely unknown. Doppler lidar and surface observations were combined with DOE E3SM land model experiments, revealing increased surface winds (5 m/s) and heat fluxes (50 W/m2) in convergent branches of HCRs. Larger wind‐driven flux responses (up to 150 W/m2) were found along gust fronts. Surface energy balance shifts to accommodate wind‐driven fluxes, reducing ground heat conduction and longwave cooling. Our findings from the US Southern Great Plains are broadly relevant to modeling convective boundary layers. In particular, widely used subgrid wind gust parameterizations were found to be physically inconsistent with resolved secondary circulations and could worsen climate prediction biases at kilometer‐scales. Plain Language Summary Earth's surface is heated by solar radiation, and this energy is transferred to the overlying air in the form of sensible and latent heat fluxes. Surface heat fluxes are generated by turbulent motions that are too small to be directly simulated in weather and climate models. Instead, models use mathematical functions, known as parameterizations, to predict surface fluxes from simulated winds and surface‐to‐air differences in moisture and temperature. Observed winds near Earth's surface are known to organize into patterns referred to as secondary circulations, creating frequently observed “cloud streets,” and influencing the soaring patterns of birds. With increasing computational power, weather, and climate models have begun to resolve these circulations in winds simulated at kilometer scales. Although they are widely observed, this study provides new evidence that secondary circulations significantly alter surface heat fluxes and the energy balance of the land surface. It is also shown that current parameterizations of wind‐driven heat fluxes can be made more realistic to improve predictions in weather and climate models that are run at kilometer‐scale spatial resolutions. Key Points Lidar and surface wind measurements provide evidence linking widely observed secondary circulations to surface wind gusts The circulations alter the land surface energy balance and increase surface heat fluxes in convergent branches of circulation updrafts Land model parameterizations are inconsistent with resolved circulations, pointing to needed improvements at kilometer‐scale resolutions

Large-eddy simulations (LES) are an important tool for investigating the longstanding energy-balance-closure problem, as they provide continuous, spatially-distributed information about turbulent flow at a high temporal resolution. Former LES studies reproduced an energy-balance gap similar to the observations in the field typically amounting to 10–30% for heights on the order of 100 m in convective boundary layers even above homogeneous surfaces. The underestimation is caused by dispersive fluxes associated with large-scale turbulent organized structures that are not captured by single-tower measurements. However, the gap typically vanishes near the surface, i.e. at typical eddy-covariance measurement heights below 20 m, contrary to the findings from field measurements. In this study, we aim to find a LES set-up that can represent the correct magnitude of the energy-balance gap close to the surface. Therefore, we use a nested two-way coupled LES, with a fine grid that allows us to resolve fluxes and atmospheric structures at typical eddy-covariance measurement heights of 20 m. Under different stability regimes we compare three different options for lower boundary conditions featuring grassland and forest surfaces, i.e. (1) prescribed surface fluxes, (2) a land-surface model, and (3) a land-surface model in combination with a resolved canopy. We show that the use of prescribed surface fluxes and a land-surface model yields similar dispersive heat fluxes that are very small near the vegetation top for both grassland and forest surfaces. However, with the resolved forest canopy, dispersive heat fluxes are clearly larger, which we explain by a clear impact of the resolved canopy on the relationship between variance and flux–variance similarity functions.

In this study, a systematic mathematical analysis has been presented for the extent of applicability of various non-linear similarity functions for momentum (φm) and heat (φh) under stable conditions to compute surface turbulent fluxes in numerical models. The investigation is carried out for equal and unequal momentum (z0) and heat (zh) roughness lengths. The study reveals that φm and φh utilized in the National Centre for Atmospheric Research Community Atmosphere Model version 5 (NCAR-CAM5) (Holtslag et al. in Mon Weather Rev 118:1561–1575, 1990) have several restrictions on their applicability in moderately to strongly stable cases. If the ratios of z0 and zh to the height (z) from the surface (i.e., z0z and zhz) lie in the range (0.2,1), the functions are valid for a limited range of ζ (stability parameter) in strong stable conditions ζ>1; however, when z0z≤0.2 and zhz≤0.2, the validity of functions is unrestricted. In terms of bulk Richardson number RiB, the functions are valid for a limited range of moderately to strongly stable conditions. These theoretically derived upper limits have also been validated using observations from the UK Meteorological Office’s Cardington and Cooperative Atmosphere-Surface Exchange Study-99 datasets. On the other hand, similarity functions based on Cheng and Brutsaert (Boundary-Layer Meteorol 114:519–538, 2005), Grachev et al. (Boundary-Layer Meteorol 124:315–333, 2007), Srivastava et al. (Meteorol Appl 27, 2020), and Gryanik et al. (J Atmos Sci 77:2687–2716, 2020) are found to be theoretically valid for all values of ζ and RiB. The efforts have also been made to implement these functions in the Weather Research and Forecasting as well as global scale models.

There is no consensus on the physical mechanisms controlling the scale at which convective activity organizes near the Equator, where the Coriolis parameter is small. High resolution cloud-permitting simulations of non-rotating convection show the emergence of a dominant length scale, which has been referred to as convective self-aggregation. Furthermore, simulations in an elongated domain of size 12228km x 192km with a 3km horizontal resolution equilibrate to a wave-like pattern in the elongated direction, where the cluster size becomes independent of the domain size. These recent findings suggest that the size of convective aggregation may be regulated by physical mechanisms, rather than artifacts of the model configuration, and thus within the reach of physical understanding. We introduce a diagnostic framework relating the evolution of the length scale of convective aggregation to the net radiative heating, the surface enthalpy flux, and horizontal energy transport. We evaluate these length scale tendencies of convective aggregation in twenty high-resolution cloud-permitting simulations of radiative-convective equilibrium. While both radiative fluxes contribute to convective aggregation, the net longwave radiative flux operates at large scales (1000-5000 km) and stretches the size of moist and dry regions, while the net shortwave flux operates at smaller scales (500-2000 km) and shrinks it. The surface flux length scale tendency is dominated by convective gustiness, which acts to aggregate convective activity at smaller scales (500-3000 km). We further investigate the scale-by-scale radiative tendencies in a suite of nine mechanism denial experiments, in which different aspects of cloud radiation are homogenized or removed across the horizontal domain, and find that liquid and ice cloud radiation can individually aggregate convection. However, only ice cloud radiation can drive the convective cluster to scales exceeding 5000 km, because of the high optical thickness of ice, and the increase in coherence between water vapor and deep convection with horizontal scale. The framework presented here focuses on the length scale tendencies rather than a static aggregated state, which is a step towards diagnosing clustering feedbacks in the real world. Overall, our work underscores the need to observe and simulate surface fluxes, radiative and advective fluxes across the 1km-1000km range of scales to better understand the characteristics of turbulent moist convection.

Processes at the air‐sea interface govern the climate mean state and variability by determining the exchange of momentum, heat, and water between the atmosphere and ocean. Traditional climate models compute those exchanges across the air‐sea interface by assuming an ocean surface with roughness determined by atmospheric wind and stability conditions, essentially assuming ocean surface waves are in equilibrium states. In reality, that is rarely the case. Such effects have been emphasized in numerical weather predictions for weather systems like tropical cyclones. An accurate representation of ocean surface waves requires a prognostic ocean surface wave model. The addition of WAVEWATCH III to the Community Earth System Model version 2 (CESM2) makes it possible to parameterize the impacts of ocean surface waves on the momentum and energy exchange. This study documents the implementation of a sea‐state‐dependent surface flux scheme in CESM2. It considers the effects of waves on ocean surface roughness and those of sea spray on sensible and latent heat. It is found that the new scheme significantly impacts mean atmospheric circulation and the upper ocean. The errors in mean atmospheric circulation and surface temperature patterns are reduced. The modified surface flux lowers the eddy‐driven jet speed and weakens the Hadley circulation. Global sea surface temperature (SST) warm bias is reduced due to the cooling of the Southern Ocean and eastern boundary currents. In particular, some parts of eastern and central Pacific exhibit a weak cooling trend in the simulation for recent decades, reducing the existing SST trend bias in CESM2. Plain Language Summary The ocean and the atmosphere are both essential components of the Earth system. They exchange momentum, heat, and water at the air‐sea interface. Traditionally, those exchanges are estimated based on atmospheric stability, wind, and the air‐sea difference in temperature and humidity, which are assumed to determine microscale turbulence. Ocean surface waves can potentially change the morphology of the air‐sea interface and, therefore, affect turbulence. Sea spray generated in waves can also enhance water vapor transport into the atmosphere via the evaporation of small droplets. However, those enhancements depend on sea states such as wave height and phase speed, which were traditionally not simulated in Earth system models. The WAVEWATCH III model has recently been added to the Community Earth System Model version 2 (CESM2) to compute sea states and improve ocean surface mixing. In this work, we developed a new scheme in CESM2 to include the effects of ocean surface waves on air‐sea momentum, heat, and water exchanges. We found that the new methods reduce lower‐level wind speed in the atmosphere and introduce meaningful improvements in temperature, precipitation, and ocean circulation. The improved sea‐state dependent air‐sea coupling in CESM2 can yield more realistic climate simulations regarding the mean states and trends. Key Points A sea‐state dependent surface flux parameterization is implemented in the Community Earth System Model version 2 The new scheme reduces biases in the mean climate state such as barotropic jet speed in the Southern Hemisphere and sea surface temperature The scheme also produces the weak cooling in some regions of the Pacific, similar to observed trends in recent decades