Surface Turbulent Heat Fluxes Research Articles

The rate of information transfer as a measure of ocean–atmosphere interactions

Abstract. Exchanges of mass, momentum and energy between the ocean and atmosphere are of large importance in regulating the climate system. Here, we apply for the first time a relatively novel approach, the rate of information transfer, to quantify interactions between the ocean surface and the lower atmosphere over the period 1988–2017 at a monthly timescale. More specifically, we investigate dynamical dependencies between sea surface temperature (SST), SST tendency and turbulent heat flux in satellite observations. We find a strong two-way influence between SST and/or SST tendency and turbulent heat flux in many regions of the world, with the largest values in the eastern tropical Pacific and Atlantic oceans, as well as in western boundary currents. The total number of regions with a significant influence by turbulent heat flux on SST and on SST tendency is reduced when considering the three variables (this case should be privileged, as it provides additional sources of information), while it remains large for the information transfer from SST and SST tendency to turbulent heat flux, suggesting an overall stronger ocean influence compared to the atmosphere. We also find a relatively strong influence by turbulent heat flux taken 1 month before on SST. Additionally, an increase in the magnitude of the rate of information transfer and in the number of regions with significant influence is observed when looking at interannual and decadal timescales compared to monthly timescales.

Why does the upward surface turbulent heat flux resulting from sea ice loss over the Barents and Kara Seas last only for a few days?

AbstractThis study explores the reason why strong upward anomalous surface turbulent heat fluxes (STHFs) over the Barents and Kara Seas (BKS) occur for a period of only a few days after wind‐driven sea ice loss, even though anomalously low sea ice persists for more than one month. Composite analysis with ERA5 reanalysis data reveals that the sea ice decline coincides with the poleward advection of warm, moist air on the eastern flank of a synoptic‐scale surface low. This results in the anomalous surface air temperature (SAT) exceeding the anomalous skin temperature (SKT) and a downward anomalous STHF. As the surface low propagates eastward, the wind direction changes, resulting in the advection of cold, dry air, the anomalous SKT exceeding the anomalous SAT and a brief period with a strong upward anomalous STHF. This period of strong upward anomalous STHF is cut short, as the surface low propagates southeastward out of the BKS. The eastward propagation of the surface low is crucial, as it allows for northward driving of sea ice to be followed by cold advection and a strong upward anomalous STHF. These results indicate that when wind‐driven sea ice motion exposes the ocean to the atmosphere, except for a brief episode, the reduction of sea ice does not coincide with an increase in a strong upward anomalous STHF.

Accounting for Turbulence-Induced Canopy Heat Transfer in the Simulation of Sensible Heat Flux in SEBS Model

Surface turbulent heat fluxes are crucial for monitoring drought, heat waves, urban heat islands, agricultural water management, and other hydrological applications. Energy Balance Models (EBMs) are widely used to simulate surface heat fluxes from a combination of remote sensing-derived variables and meteorological data. Single-source EBMs, in particular, are preferred in mapping surface turbulent heat fluxes due to their relative simplicity. However, most single-source EBMs suffer from uncertainties inherent to the parameter kB−1, which is used to account for differences in the source of heat and the sink of momentum when representing aerodynamic resistance in single-source EBMs. For instance, the parameterization of kB−1 in the commonly used single-source Surface Energy Balance System (SEBS) model uses a constant value of the foliage heat transfer coefficient (Ct), in the parameterization of the vegetation component of kB−1 (kBv−1). Thus, SEBS ignores the effect of turbulence on canopy heat transfer. As a result, SEBS has been found to greatly underestimate sensible heat flux in tall forest canopies, where turbulence is a key contributor to canopy heat transfer. This study presents a revised parameterization of kBv−1 for the SEBS model. A physically based formulation of Ct, which considers the effect of turbulence on Ct, is used in deriving the revised parameterization. Simulation results across 15 eddy covariance (EC) flux tower sites show that the revised parameterization significantly reduces the underestimation of sensible heat flux compared to the original parameterization under tall forest canopies. The revised parameterization is relatively simple and does not require additional information on canopy structure compared to some more complex parameterizations proposed in the literature. As such, the revised parameterization is suitable for mapping surface turbulent heat fluxes, especially under tall forest canopies.

Understanding two key processes associated with alpine lake ice phenology using a coupled atmosphere-lake model

Study regionLake Nam-Co, a typical deep alpine lake in the central of Tibetan Plateau. Study focusThis study investigates the role of surface turbulent fluxes in simulating lake freeze-up and the role of solar radiation transfer (when lake ice exists) in simulating the lake ice break-up. New hydrological insightsIn the coupled model, the realistic representation of surface turbulent heat fluxes is crucial to simulate the lake freeze-up. This is because turbulent heat fluxes, especially the latent heat, directly controlling the lake water temperature through energy exchange between water and atmosphere. Additionally, the partitioning of solar radiation transfers when lake ice exist is crucial in simulating lake ice break-up. The proportion absorbed by the ice surface will be released associated with upward longwave radiation and turbulent heat fluxes, and only a fraction is used for surface ice-water phase change. The proportion absorbed by the subsurface layer ice is directly used for ice-water phase changes. The proportion absorbed by the water, through ice penetration, is temporarily stored and used for ice melting through heat exchange between the ice and water. The offline FLake model is much less sensitive to the above two processes, implying the importance and necessity in improving the model physics in coupled model.

Modeling the effects of present-day irrigation on temperature extremes over China

Irrigation activities have been recognized as one of the most potentially sustainable land management practices to tackle climate change. In this study, we investigated the impacts of present-day irrigation activities on regional temperature extremes changes in China using the state-of-the-art regional climate model RegCM-4.8.2, through two sets of long-term numerical experiments (i.e., with and without irrigation). The key findings are as follows. Firstly, by comparing the observations, RegCM4 has a good ability to reproduce both the spatial distribution and the volume of irrigation for provincial irrigation activities in China. In this context, by comparing the results of numerical experiments, we found that irrigation led to significant reductions (slightly changes) in the extreme indices associated with the warm (cold) tails of the maximum and minimum temperatures distributions, e.g., hot days, tropical nights (cold nights, frost days), particularly in the regions with intense irrigation (e.g., the North China Plain). Furthermore, these extreme indices were dominated by irrigation-induced shifts in mean temperatures, but the impacts of changes in temperature variability on extreme hot events were also non-negligible for the strongly irrigated regions. In addition, through attributing irrigation-induced changes in mean state temperatures, we revealed that the irrigation-induced repartitioning of the surface turbulent heat fluxes (i.e., sensible and latent heat) dominated the variations of temperatures and the associated extremes. However, region-specific land-atmosphere coupling features also led to differences in the irrigation-induced responses of surface energy components. We highlight the possible effects and mechanisms of irrigation on multiple types of extreme temperature indices, particularly the extreme hot events, which provide scientific clues for mitigating and adapting regional climate change.

Observed and Parameterized Roughness Lengths for Momentum and Heat Over Rough Ice Surfaces

AbstractTurbulent heat fluxes, that is, the sensible heat flux and latent heat flux, are important sources/sinks of energy for surface melt over glaciers and ice sheets. Therefore, credible simulations of for example, future Greenland Ice Sheet mass loss need an accurate description of these fluxes. However, the parameterization of surface turbulent heat fluxes in climate models requires knowledge about the surface roughness lengths for momentum, heat and moisture, which are currently either unknown or tuned to indirect observations. In this study we take advantage of a large data set of eddy covariance observations acquired during multiple years and at multiple sites over the Greenland Ice Sheet. These in‐situ observations are used to develop an improved parameterization for the roughness length for momentum, and update the parameterization for the roughness lengths for heat and moisture over rough ice surfaces. The newly derived parameterizations are implemented in a surface energy balance model that is used to compute surface melt. Sensitivity experiments confirm the high sensitivity of surface melt to the chosen roughness length models. The new parameterization models the sensible heat flux to within 10 W m−2, and the cumulative ice ablation within 10% at three out of four sites. Two case studies demonstrate the important contribution of the turbulent heat fluxes to surface ablation. The presented roughness parameterizations can be implemented in climate models to improve the physical representation of surface roughness over rough snow and ice surfaces, which is expected to improve the modeled turbulent heat fluxes and thus surface melt.

Exploiting SMILEs and the CMIP5 Archive to Understand Arctic Climate Change Seasonality and Uncertainty

AbstractArctic Amplification (AA) exhibits a distinct seasonal dependence; it is weakest in boreal summer and strongest in winter. Here, we analyze simulations from single‐model initial‐condition large ensembles and Coupled Model Intercomparison Project Phase 5 to decipher the seasonal evolution of Arctic climate change. Models agree that the annual maximum AA shifts from autumn into winter over the 21st century, accompanied by similar shifts in sea‐ice loss and surface turbulent heat fluxes, whereas the maximum precipitation shifts only into late autumn. However, the exact seasonal timing and magnitude of these shifts are highly uncertain. Decomposing the uncertainty into model structural differences, emission scenarios, and internal variability reveals that model differences dominate the total uncertainty, which also undergo autumn‐to‐winter shifts. We also find that the scenario uncertainty is unimportant for projections of AA. These results highlight that understanding model differences is critical to reducing uncertainty in projected Arctic climate change.

Simple Hybrid Sea Ice Nudging Method for Improving Control Over Partitioning of Sea Ice Concentration and Thickness

AbstractTo assess the effect of ocean‐atmosphere coupling in the climate response to forced sea ice loss, the Polar Amplification Model Intercomparison Project protocol includes centennial coupled atmosphere‐ocean general circulation model simulations with imposed sea ice loss. The protocol, which specifies sea ice concentration and thickness distribution targets, does not prescribe a method for achieving them. Although different methods for imposing sea ice loss (or growth) in models have been documented, testing of the method‐dependence of the resulting climate responses has been limited. Achieving the targeted sea ice state has proven to be challenging using the so‐called ghost‐flux nudging method, which induces ice melt from below, as this method does not constrain the partitioning between thickness and concentration. We propose, describe and test a simple method that combines the advantages of direct sea ice nudging and ghost‐flux nudging. The hybrid nudging method better captures the partitioning between thickness and concentration while conserving total water content. We document how this novel sea ice constraining method reaches specific targets, enhances surface turbulent heat flux responses to sea ice loss, and induces tropospheric warming for both polar regions.

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.

Spatio-temporal variability of surface turbulent heat flux feedback for mesoscale sea surface temperature anomaly in the global ocean

The surface turbulent heat flux feedback αT plays an important role in the atmosphere–ocean coupling. However, spatio-temporal variability of αT for sea surface temperature anomaly (SSTA) at oceanic mesoscales in the global ocean remains poorly assessed. In this study, we tackle this issue using an advanced statistical model, i.e., the geographically and temporally weighted regression model. The estimated time-mean αT for mesoscale SSTA generally ranges from 10 to 50 W/(m2 K) within 70°S–70°N, except in the Antarctic coastal region where its value drops to zero. The αT is larger in the tropics than in off-tropical regions and locally enhanced in the equatorial cold tongues, western boundary currents, and their extensions. The spatial structure αT is primarily attributed to the non-linearity in the Clausius–Clapeyron relation and inhomogeneity in the background wind speed, whereas adjustment of surface wind speed, air temperature, or moisture to mesoscale SSTA plays an important role in the regional variability. There is an evident seasonal cycle of αT in the tropics and under the northern hemisphere’s storm tracks. The former is due to the seasonally varying response of surface wind speed to mesoscale SSTA, and the latter results from the seasonality of atmospheric and oceanic background states. Our analysis reveals prominent spatio-temporal variability of αT for mesoscale SSTA governed by complicated dynamics.

Connection between the North Atlantic sea surface temperature and the late autumn snow cover anomalies over the central Tibetan Plateau

Many studies have investigated the effects of the snow anomalies over the Tibetan Plateau (TP), yet the original causes of these anomalies are not fully understood. In this study, we explore the possible connection between the late autumn (November) central TP snow cover anomalies and the monthly sea surface temperature (SST) over the North Atlantic (NA) in autumn and find significant correlations over the mid-latitude NA during October and November. By analyzing the air-sea interaction over the NA, we show that a well-organized horseshoe-like SST anomaly pattern coupled with a surface anomalous anticyclone centered over the mid-latitude NA in October and its persistence in November may play a key role in the November central TP snow cover anomalies. Such an October surface anomalous anticyclone could effectively result in the surface turbulent heat flux anomalies via the surface wind-induced horizontal temperature advection, which is conducive to the formation of the horseshoe-like SST anomalies over the mid-latitude NA. The resultant anomalous SST pattern could further contribute to a North Atlantic Oscillation (NAO)-like pattern in November and stimulate the wave trains eastward to the TP. The anomalous anticyclone (cyclone) associated with the wave trains to the southwest (north) of the TP suppresses the precipitation over the central TP and thus reduces the local snow cover. The atmospheric circulation responses to the persistent NA-SST anomalies are well validated by the numerical experiments. The above result might help to predict the condition of the central TP snow cover anomalies in November, one month ahead.

Glacier parameterization in SLAV numerical weather prediction model

Abstract In the present paper, we describe a one-dimensional glacier parameterization for use in the numerical weather prediction models. The proposed scheme is implemented into the global atmospheric model SLAV. To avoid inconsistency of surface temperature and turbulent heat fluxes in the lower troposphere, glacier parameterization has been iteratively coupled with both planetary boundary layer and land surface schemes. First results from numerical experiments with the SLAV model show that the introduction of a simplified description of the glacier heat capacity can significantly improve the 2-meter temperature long-range weather forecast skill.

Role of Ocean and Atmosphere Variability in Scale‐Dependent Thermodynamic Air‐Sea Interactions

AbstractThis study investigates the influence of oceanic and atmospheric processes in extratropical thermodynamic air‐sea interactions resolved by satellite observations (OBS) and by two climate model simulations run with eddy‐resolving high‐resolution (HR) and eddy‐parameterized low‐resolution (LR) ocean components. Here, spectral methods are used to characterize the sea surface temperature (SST) and turbulent heat flux (THF) variability and co‐variability over scales between 50 and 10,000 km and 60 days to 80 years in the Pacific Ocean. The relative roles of the ocean and atmosphere are interpreted using a stochastic upper‐ocean temperature evolution model forced by noise terms representing intrinsic variability in each medium, defined using climate model data to produce realistic rather than white spectral power density distributions. The analysis of all datasets shows that the atmosphere dominates the SST and THF variability over zonal wavelengths larger than ∼2,000–2,500 km. In HR and OBS, ocean processes dominate the variability of both quantities at scales smaller than the atmospheric first internal Rossby radius of deformation (R1, ∼600–2,000 km) due to a substantial ocean forcing coinciding with a weaker atmospheric modulation of THF (and consequently of SST) than at larger scales. The ocean forcing also induces oscillations in SST and THF with periods ranging from intraseasonal to multidecadal, reflecting a red spectrum response to ocean forcing similar to that driven by atmospheric forcing. Such features are virtually absent in LR due to a weaker ocean forcing relative to HR.

Modulation of North Atlantic Polar Low Activity and Associated Flow Patterns by Sudden Stratospheric Warmings

Abstract Polar lows (PLs) are intense maritime mesoscale cyclones that can pose hazards to coastal communities and marine operation in the Arctic. This study examines the impacts of sudden stratospheric warmings (SSWs) on PL activity in the subarctic North Atlantic. The 20 days following SSWs are characterized by tropospheric circulation anomalies resembling the negative phase of the North Atlantic Oscillation. PL activity decreases significantly over the Labrador Sea, which can be attributed to the infrequent occurrence of low static stability and strong environmental baroclinicity, as well as reduced surface turbulent heat fluxes. These results suggest that a skillful prediction of SSWs can improve the extended-range forecast of PL activity over the Labrador Sea. For the Nordic seas, the results imply that the spatial structure of an SSW event is important for the PL modulation through different tropospheric circulation patterns. Situations with increased PL frequency in the Nordic seas are characterized by SSWs centered close to northern Greenland occurring over a smaller area, and a tropospheric response featuring enhanced cold-air outbreaks over the Norwegian Sea. Conversely, PL activity is suppressed over the Nordic seas when the SSW favors the formation of a tropospheric anticyclone above Greenland and Scandinavia. Significance Statement This study investigates the relationships between polar lows (PLs) and sudden stratospheric warmings (SSWs) over the subarctic North Atlantic. A better understanding of the effect of SSWs on PL development has the potential to improve extended-range forecasts of PLs. It is shown that SSWs are responsible for the significantly suppressed regional PL activity over the Labrador Sea, suggesting that SSWs can serve as a predictor for the extended-range forecast of PLs over this region. Following SSW events, the thermodynamic state of atmosphere becomes more stable over the Labrador Sea and hinders the convective development of PLs. For the northern Nordic seas, the impacts of SSWs on PL activity are sensitive to the spatial structure of stratospheric warming.

From a Shapiro–Keyser extratropical cyclone to the subtropical cyclone Raoni: An unusual winter synoptic situation over the South Atlantic Ocean

AbstractThe eastern coast of South America is a cyclogenetic region in terms of extratropical cyclones and, in lower number, of subtropical cyclones that are more frequent in austral summer and autumn. However, in June 2021, an unusual cyclone developed near the boundary of Uruguay and southern Brazil, initially having extratropical features and later undergoing a subtropical transition. At 1200 UTC 29 June, the Brazilian Navy named it as subtropical cyclone Raoni. This study aims to describe the synoptic evolution of the cyclone and address physical drivers for the subtropical transition based on the ECMWF‐ERA5 reanalysis and numerical experiments with the WRF model. The cyclone precursor of Raoni had its genesis at 1800 UTC 26 June 2021 forced by a trough at mid–upper levels that crossed the Andes Mountains and caused a rapid surface pressure drop. Less than 24 hr later, the cyclone presented a frontal T‐bone pattern and warm seclusion, following the Shapiro–Keyser development model. Strong surface heat fluxes, a deep moist troposphere, and the vertical alignment of the warm seclusion with an upper‐level cut‐off pattern provided the adequate environment for organising convection and, consequently, for subtropical transition at 0600 UTC 28 June. The fundamental role of the surface turbulent heat fluxes for the transition is confirmed through numerical experiments. This study is unprecedented in the sense that no subtropical cyclone originating from a warm seclusion has been documented over the South Atlantic before. These findings emphasise the need of monitoring cold‐season extratropical Shapiro–Keyser cyclones in the region since they can evolve to a subtropical or tropical cyclone and can cause damage to the maritime activities and coastal region due to the strong winds.

An Intercomparison of Antarctic NWP during the Austral Summer Special Observing Period for the Year of Polar Prediction

Abstract The special observing periods (SOPs) of the Year of Polar Prediction present an opportunity to assess the skill of numerical weather prediction (NWP) models operating over the Antarctic, many of which assimilated additional observations during an SOP to produce some of the most observationally informed model output to date for the Antarctic region and permitting closer examination of model performance under various configurations and parameterizations. This intercomparison evaluates six NWP models spanning global and limited domains, coupled and uncoupled, operating in the Antarctic during the austral summer SOP between 16 November 2018 and 15 February 2019. Model performance varies regionally between each model and parameter; however, the majority of models were found to be warm biased over the continent with respect to ERA5 at analysis, some with biases growing to 3.5 K over land after 48 h. Temperature biases over sea ice were found to be strongly correlated between analysis and 48 h in uncoupled models, but that this correlation can be reduced through coupling to a sea ice model. Surface pressure and 500-hPa geopotential height forecasts and biases were found to be strongly correlated over open ocean in all models, and wind speed forecasts were found to be generally more skillful at higher resolutions with the exception of fast modeled winds over sloping terrain in PolarWRF. Surface sensible and latent heat flux forecasts and biases produced diverse correlations, varying by model, parameter, and gridcell classification. Of the models evaluated, those which couple atmosphere, sea ice, and ocean typically exhibited stronger skill. Significance Statement We evaluated the performance of six numerical weather prediction models operating over the Antarctic during the Year of Polar Prediction austral summer special observing period (16 November 2018–15 February 2019). Our analysis found that several models were as much as 3.5 K warmer than the reference analysis (ERA5) at 48 h over land and were strongly correlated over sea ice in uncoupled models; however, this correlation is reduced through coupling to a sea ice model. Surface pressure biases are communicated to the midtroposphere over the ocean at larger spatial scales, while higher resolution showed an increase in positive wind biases at longer forecasts. Surface turbulent heat fluxes produced complex correlations with other forecast parameters, which should be quantified in future studies. Coupled models that included an ocean/sea ice component typically performed better; providing evidence that the inclusion of such components leads to improved model performance, even at short time scales such as these.

Reduced Sea Ice Enhances Intensification of Winter Storms over the Arctic Ocean

AbstractThe ideal environment for extratropical cyclone development includes strong vertical shear of horizontal wind and low static stability in the atmosphere. Arctic sea ice loss enhances the upward flux of energy to the lower atmosphere, reducing static stability. This suggests that Arctic sea ice loss may facilitate more intense storms over the Arctic Ocean. However, prior research into this possibility has yielded mixed results with uncertain cause and effect. This work has been limited either in scope (focusing on a few case studies) or resolution (focusing on seasonal averages). In this study, we extend this body of research by comparing the intensification rate and maximum intensity of individual cyclones to local sea ice anomalies. We find robust evidence that reduced sea ice in winter (December–March) strengthens Arctic cyclones by enhancing the surface turbulent heat fluxes and lessening static stability while also strengthening vertical shear of horizontal wind. We find weaker evidence for this connection in spring (April–June). In both seasons, lower sea ice concentration also enhances cyclone-associated precipitation. Although reduced sea ice also weakens static stability in September/October (when sea ice loss has been especially acute), this does not translate to stronger storms because of coincident weakening of wind shear. Sea ice anomalies also have little or no connection to cyclone-associated precipitation in these months. Therefore, future sea ice reductions (e.g., related to delayed autumn freeze-up) will likely enhance Arctic cyclone intensification in winter and spring, but this relationship is sensitive to simultaneous connections between sea ice and wind shear.Significance StatementSea ice is a barrier between the ocean and atmosphere, limiting the exchange of energy between them. As the amount of sea ice in the Arctic Ocean declines, the ocean can transfer more heat to the atmosphere above in fall and winter. It is theorized that this extra energy may help intensify storms that pass through the Arctic. We examine individual storms over the Arctic Ocean and what sea ice conditions they experience as they develop. We find that storms intensify more when sea ice is lower than normal in the winter season only. This relationship may contribute to stronger Arctic winter storms in the future, including heavier precipitation and stronger winds (which can enhance wave heights and coastal erosion).

Observational Characteristics of Wintertime Extreme Surface Turbulent Heat Flux Events in the North Pacific Subtropical Region

Surface turbulent heat flux is the most direct variable denoting air-sea interactions. In wintertime North Pacific, in addition to the Kuroshio-Oyashio extension (KOE) region, high-resolution observations show that the North Pacific subtropical region (NPSR) is also characterized with high surface heat flux, whose characteristics need systematic investigation. In this study, the extreme surface turbulent heat flux events in the NPSR are investigated using daily observational data. Our results show that the extreme events exhibit dipolar changes of surface flux over NPSR and KOE regions, lasting for several days. Though with a spatially correlated pattern, the occurrence of extreme events in NPSR and KOE is found greatly independent. In the extreme events, both surface sensible and latent heat fluxes display evident changes in north NPSR, while in south NPSR the change in surface latent heat flux dominates. The formation of extreme events in the NPSR is mainly determined by anomalous atmospheric circulation. Changes in the intensity of subtropical high influence the surface air wind speed, humidity, and temperature, contributing to the formation of extreme events in the NPSR. Our results further suggest that the processes through which the extreme events affect the atmospheric precipitation may be different in south and north NPSR. In south NPSR, the change of precipitation in extreme events is very likely attributed to the change of surface latent heat flux. In north NPSR, the change of water vapor transport by atmospheric circulations is found to play a major role.

Erratum to: Seasonality and time scale dependence of the relationship between turbulent surface heat flux and SST

Erratum to: Seasonality and time scale dependence of the relationship between turbulent surface heat flux and SST

Causes of the Arctic’s Lower-Tropospheric Warming Structure

AbstractArctic amplification has been attributed predominantly to a positive lapse rate feedback in winter, when boundary layer temperature inversions focus warming near the surface. Predicting high-latitude climate change effectively thus requires identifying the local and remote physical processes that set the Arctic’s vertical warming structure. In this study, we analyze output from the CESM Large Ensemble’s twenty-first-century climate change projection to diagnose the relative influence of two Arctic heating sources, local sea ice loss and remote changes in atmospheric heat transport. Causal effects are quantified with a statistical inference method, allowing us to assess the energetic pathways mediating the Arctic temperature response and the role of internal variability across the ensemble. We find that a step-increase in latent heat flux convergence causes Arctic lower-tropospheric warming in all seasons, while additionally reducing net longwave cooling at the surface. However, these effects only lead to small and short-lived changes in boundary layer inversion strength. By contrast, a step-decrease in sea ice extent in the melt season causes, in fall and winter, surface-amplified warming and weakened boundary layer temperature inversions. Sea ice loss also enhances surface turbulent heat fluxes and cloud-driven condensational heating, which mediate the atmospheric temperature response. While the aggregate effect of many moist transport events and seasons of sea ice loss will be different than the response to hypothetical perturbations, our results nonetheless highlight the mechanisms that alter the Arctic temperature inversion in response to CO2forcing. As sea ice declines, the atmosphere’s boundary layer temperature structure is weakened, static stability decreases, and a thermodynamic coupling emerges between the Arctic surface and the overlying troposphere.