Simulated Sea Surface Temperature Research Articles

Influence of the solar penetration depth and heat-fluxes on the sea surface temperature using an ocean mixed layer model

Solar penetration depth is a major factor in modulating the Sea Surface Temperature (SST) and hence influences the air-sea interface processes. This study investigates the influence of solar penetration depth and heat-fluxes on the SST at three RAMA (Research Moored Array for African-Asian-Australian Monsoon Analysis and Prediction) buoy locations (along 90°E at 15°N, 12°N, and 8°N) in the Bay of Bengal (BoB) using the One-Dimensional Price-Weller-Pinkel (1D-PWP) model. The results show that SST has strong dependence on the solar penetration depths with the shortwave component of solar insolation outweighing its longwave component. We found that spatio-temporally varying penetration depths refine the simulated SST, when compared against constant penetration depths. These spatio-temporally varying penetration depths (ranging from 10 to 75 m for the shortwave component; with higher values during monsoon) can be attributed to spatio-temporally changing biological parameters, wind, precipitation, and suspended particulate matter. Upon examination, an antiphase relationship between the penetration depths and total chlorophyll, total primary production, & total phytoplankton was found. Upon including the effect of horizontal advection and vertical entrainment in the 1D-PWP model results, the SST predictions improved albeit by a small amount. Furthermore, the effects of increased heat-fluxes, under the different Representative Concentration Pathway (RCP) equivalent scenarios, coupled with varying penetration depths were estimated. It was found that for the spatio-temporally varying penetration depths, the mean (maximum) increment was 0.52 °C (0.92 °C) under the highest emission scenario, i.e., RCP8.5, across all the locations. The results of the study can potentially be used further for 3D ocean modeling studies, and the characterization of air-sea interaction during monsoon and cyclones in the BoB.

Correcting Climate Model Sea Surface Temperature Simulations with Generative Adversarial Networks: Climatology, Interannual Variability, and Extremes

Correcting Climate Model Sea Surface Temperature Simulations with Generative Adversarial Networks: Climatology, Interannual Variability, and Extremes

Ocean Satellite Data Fusion for High-Resolution Surface Current Maps

Real-time reconstruction of ocean surface currents is a challenge due to the complex, non-linear dynamics of the ocean, the small number of in situ measurements, and the spatio-temporal heterogeneity of satellite altimetry observations. To address this challenge, we introduce HIRES-CURRENTS-Net, an operational real-time convolutional neural network (CNN) model for daily ocean current reconstruction. This study focuses on the Mediterranean Sea, a region where operational models have great difficulty predicting surface currents. Notably, our model showcases higher accuracy compared to commonly used alternative methods. HIRES-CURRENTS-Net integrates high-resolution measurements from the infrared or visible spectrum—high resolution Sea Surface Temperature (SST) or chlorophyll (CHL) images—in addition to the low-resolution Sea Surface Height (SSH) maps derived from satellite altimeters. In the first stage, we apply a transfer learning method which uses a high-resolution numerical model to pre-train our CNN model on simulated SSH and SST data with synthetic clouds. The observation of System Simulation Experiments (OSSEs) offers us a sufficient training dataset with reference surface currents at very high resolution, and a model trained on this data can then be applied to real data. In the second stage, to enhance the real-time operational performance of our model over previous methods, we fine-tune the CNN model on real satellite data using a novel pseudo-labeling strategy. We validate HIRES-CURRENTS-Net on real data from drifters and demonstrate that our data-driven approach proves effective for real-time sea surface current reconstruction with potential operational applications such as ship routing.

Tropical Cyclogenesis Bias over the Central North Pacific in CMIP6 Simulations

Abstract Current coupled climate models contain large biases in simulating tropical cyclogenesis, reducing the confidence in tropical cyclone (TC) projection. In this study, we investigated the influence of sea surface temperature (SST) biases on TC genesis in the Coupled Model Intercomparison Project phase 6 simulations from 1979 to 2014. Positive TC genesis biases were found over the tropical central North Pacific (CNP) in most of climate models, including the high-resolution models. Compared to coupled models, TC genesis density (TCGD) simulations over CNP in uncoupled models forced by observational SST improved obviously. A warm SST bias over the tropical CNP in the coupled models is the main cause of TC genesis biases. The SST bias–induced diabatic heating leads to an anomalous Gill-type atmospheric circulation response, which contributes to a series of favorable environmental conditions for TC formation over the CNP. Numerical experiments were also performed with HiRAM to demonstrate the influence of SST biases on the TCGD simulation, further confirming our conclusion. The current results highlight the importance of improving TC simulation in state-of-the-art climate models by reducing SST simulation bias.

Evaluation of Bias-Corrected GCM CMIP6 Simulation of Sea Surface Temperature over the Gulf of Guinea

This study used an ERA5 reanalysis SST dataset re-gridded to a common grid with a 0.25° × 0.25° spatial resolution (latitude × longitude) for the historical (1940–2014) and projected (2015–2100) periods. The SST simulation under the SSP5-8.5 scenario was carried out with outputs from eight General Circulation Models (GCMs). The bias-corrected dataset was developed using Empirical Quantile Mapping (EQM) for the historical (1940–2015) and future (2030–2100) periods while the CMIP6 model simulation was evaluated against the ERA5 monthly observed reanalysis data for temperatures over the Gulf of Guinea. Overall, the CMIP6 models’ future simulations in 2030–20100 based on the SSP5-8.5 scenario indicate that SSTs are projected, for the Gulf of Guinea, to increase by 4.61 °C, from 31 °C in the coast in 2030 to 35 °C in 2100, and 2.6 °C in the Western GOG (Sahel). The Linux-based Ncview, Ferret, and the CDO (Climate Data Operator) software packages were used to perform further data re-gridding and assess statistical functions concerning the data. In addition, ArcGIS was used to develop output maps for visualizing the spatial trends of the historical and future outputs of the GCM. The correlation coefficient (r) was used to evaluate the performance of the CMIP6 models, and the analysis showed ACCESS 0.1, CAMS CSM 0.2, CAN ESM 0.3, CMCC 0.3, and MCM 0.4, indicating that all models performed well in capturing the climatological patterns of the SSTs. The CMIP6 bias-corrected model simulations showed that increased SST warming over the GOG will be higher in the far period than the near-term climate scenario. This study affirms that the CMIP6 projections can be used for multiple assessments related to climate and hydrological impact studies and for the development of mitigation measures under a warming climate.

Impacts of Nudged Sea Surface Temperature on Tropical Precipitation, Moisture, and Vertical Velocity in an Earth System Model

Abstract Understanding the effect of the nudged sea surface temperature (SST) on precipitation simulation is important in Earth system models. In this study, we analyzed the role of nudged SST and air–sea interaction in precipitation simulation by using the Chinese Academy of Sciences Earth System Model version 2 (CAS-ESM2). CAS-ESM2 fully coupled runs with and without nudged tropical SST to observations, and the atmosphere-only runs (AMIP) are comprehensively evaluated against observations and reanalysis over the tropical ocean from 1982 to 2015. The precipitation is affected by the nudged SST and air–sea interaction by means of changes in both thermodynamic and dynamic processes. Simulation with the nudged SST dramatically improves the climatological precipitation fields over the tropics and four regional areas. As the simulated SSTs are nudged toward the observations, CAS-ESM2 well reproduces the mean annual values in column water vapor (CWV), vertical structure of specific humidity, and large-scale circulation. The nudged SST run also captures a wide range of the complex interactions between SST, precipitation, moisture, and large-scale circulations, as measured by the monthly relationships and bivariate probability distribution function. The biases in heavy precipitation associated with the CWV induced under moist conditions are decreased by applying the nudging technique. In particular, the nudging run performs better in reproducing the SST–precipitation covariability than the control and AMIP runs. However, CAS-ESM2 with nudged tropical SST simulates the degradation of strong ascending motions, which is similar to the AMIP runs and reflects the deviation of the atmospheric model. Our results confirm that the fully coupled run using the nudged SST is a method for improving the precipitation simulation across the tropical oceans. Significance Statement Understanding the sources of precipitation errors in Earth system models is challenging because of the complex error compensation and air–sea interaction. When the simulated SST is nudged toward observations, few studies have focused on the changes in both thermodynamic and dynamic processes via atmospheric large-scale circulation, moisture, and changes in the SST–precipitation relationship at the same time. Here, we carry out two CMIP6 historical experiments (a fully coupled control run and an SST-nudged run) and the atmosphere-only runs by using CAS-ESM2 from 1982 to 2015. Then, we validate and analyze the climatology of SST, precipitation, moisture, large-scale circulation, and their complex interactions over the tropical oceans and different regional areas. The fully coupled nudged-SST run outperforms the fully free coupled run in reproducing the climatology and complex interactions between SST, precipitation, moisture, and large-scale circulations across the tropics. Moreover, the biases in the SST–precipitation covariability are significantly alleviated in the nudging experiments. We confirmed that the SST nudging method is a potential way to improve precipitation simulation in CAS-ESM2.

Local and Remote Causes of the Equatorial Pacific Cold Sea Surface Temperature Bias in the Kiel Climate Model

Abstract We investigate the origin of the equatorial Pacific cold sea surface temperature (SST) bias and its link to wind biases, local and remote, in the Kiel Climate Model (KCM). The cold bias is common in climate models participating in phases 5 and 6 of the Coupled Model Intercomparison Project. In the coupled experiments with the KCM, the interannually varying NCEP/CFSR wind stress is prescribed over four spatial domains: globally, over the equatorial Pacific (EP), the northern Pacific (NP), and the southern Pacific (SP). The corresponding EP SST bias is reduced by 100%, 52%, 12%, and 23%, respectively. Thus, the EP SST bias is mainly attributed to the local wind bias, with small but not negligible contributions from the extratropical regions. Erroneous ocean circulation driven by overly strong winds causes the cold SST bias, while the surface heat flux counteracts it. Extratropical Pacific SST biases contribute to the EP cold bias via the oceanic subtropical gyres, which is further enhanced by dynamical coupling in the equatorial region. The origin of the wind biases is examined by forcing the atmospheric component of the KCM in a stand-alone mode with observed SSTs and simulated SSTs from the coupled experiments. Wind biases over the EP, NP, and SP regions originate in the atmosphere model. The cold EP SST bias substantially enhances the wind biases over all three regions, while the NP and SP SST biases support local amplification of the wind bias. This study suggests that improving surface wind stress, at and off the equator, is a key to improve mean-state equatorial Pacific SST in climate models.

The Influence of Typhoon-Induced Wave on the Mesoscale Eddy

The strong wind-induced current and sea level have influences on the wave distribution in a tropical cyclone (TC). In particular, the wave–current interaction is significant in the period in which the TC passed the mesoscale eddy. In this study, the wave fields of Typhoon Chan-hom (2015) are hindcastly simulated using a coupled oceanic model that utilizes a nested triangle grid, i.e., the finite-volume community ocean model-simulating waves nearshore (FVCOM-SWAVE) model. The forcing wind field is composited from the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis data and the simulation using a parametric Holland model, denoted as H-E. The open boundary fields include tide data from TPOX.5 and the hybrid coordinate ocean model (HYCOM) global datasets, including sea surface temperature (SST), sea surface salinity, sea surface current, and sea level data. The simulated oceanic parameters (e.g., the significant wave height, SWH) are validated against the measurements from the Jason-2 altimeter, yielding a root mean square error (RMSE) of 0.58 m for the SWH, a correlation (COR) coefficient of 0.94, and a scatter index (SI) of 0.23. Similarly, the simulated SSTs are compared with the remote sensing products of the remote sensing system (REMSS) and the measurements from Argos, yielding an RMSE of <0.8 °C, a COR of >0.95, and an SI of <0.04. The significant zonal asymmetry of the wave distribution along the typhoon track is observed. The Stokes drift is calculated from the FVCOM-SWAVE simulation results, and then the contribution of the Stokes transport is estimated using the Ekman–Stokes numbers. It is found that the ratio of the Stokes transport to the total net transport can reach >80% near the typhoon center, and the ratio is reduced to approximately <20% away from the typhoon center, indicating that Stokes transport is an essential aspect in the water mixing during a TC. The mesoscale eddies are detected by the sea level anomalies (SLA) fusion data from AVISO. It is found that the significant wave heights, Stokes drift, and Stokes transport inside the eddy area were higher than those outside the eddy area. These parameters inside the cold mesoscale eddies were higher than t inside the warm mesoscale eddies. Otherwise, the SST mainly increased within the cold mesoscale eddies area, while decreased within the warm mesoscale eddies area. The influence of mesoscale eddies on the SST was in proportion to the eddy radius and eddy EKE.

Assessing the cloud radiative bias at Macquarie Island in the ACCESS-AM2 model

Abstract. As a long-standing problem in climate models, large positive shortwave radiation biases exist at the surface over the Southern Ocean, impacting the accurate simulation of sea surface temperature, atmospheric circulation, and precipitation. Underestimations of low-level cloud fraction and liquid water content are suggested to predominantly contribute to these radiation biases. Most model evaluations for radiation focus on summer and rely on satellite products, which have their own limitations. In this work, we use surface-based observations at Macquarie Island to provide the first long-term, seasonal evaluation of both downwelling surface shortwave and longwave radiation in the Australian Community Climate and Earth System Simulator Atmosphere-only Model version 2 (ACCESS-AM2) over the Southern Ocean. The capacity of the Clouds and the Earth’s Radiant Energy System (CERES) product to simulate radiation is also investigated. We utilize the novel lidar simulator, the Automatic Lidar and Ceilometer Framework (ALCF), and all-sky cloud camera observations of cloud fraction to investigate how radiation biases are influenced by cloud properties. Overall, we find an overestimation of +9.5±33.5 W m−2 for downwelling surface shortwave radiation fluxes and an underestimation of -2.3±13.5 W m−2 for downwelling surface longwave radiation in ACCESS-AM2 in all-sky conditions, with more pronounced shortwave biases of +25.0±48.0 W m−2 occurring in summer. CERES presents an overestimation of +8.0±18.0 W m−2 for the shortwave and an underestimation of -12.1±12.2 W m−2 for the longwave in all-sky conditions. For the cloud radiative effect (CRE) biases, there is an overestimation of +4.8±28.0 W m−2 in ACCESS-AM2 and an underestimation of -7.9±20.9 W m−2 in CERES. An overestimation of downwelling surface shortwave radiation is associated with an underestimated cloud fraction and low-level cloud occurrence. We suggest that modeled cloud phase is also having an impact on the radiation biases. Our results show that the ACCESS-AM2 model and CERES product require further development to reduce these radiation biases not just in shortwave and in all-sky conditions, but also in longwave and in clear-sky conditions.

A Regime View of ENSO Flavors Through Clustering in CMIP6 Models

AbstractEl Niño‐Southern Oscillation (ENSO) flavors in the tropical Pacific are studied from a regime perspective. Five recurring spatial patterns or regimes characterizing the diversity of ENSO are established using a clustering approach applied to the HadISST sea surface temperature (SST) anomalies. Compared to previous studies, our approach gives a monthly characterization of the diversity of the warm and cold phases of ENSO established from observations but commonly applied to models and observations. Two warm (eastern and central El Niño), two cold (basin wide and central La Niña) and a neutral reference regimes are found. Simulated SST anomalies by the models from the latest Coupled Model Intercomparison Project Phase 6 are then matched to these reference regimes. This allows for a consistent assessment of the skill of the models in reproducing the reference regimes over the historical period and the change in these regimes under the high‐warming Shared Socio‐economic Pathway (SSP5.8.5) scenario. Results over the historical period show that models simulate well the reference regimes with some discrepancies. Models simulate more intense and spatially extended ENSO patterns and have issues in capturing the correct regime seasonality, persistence, and transition between regimes. Some models also have difficulty simulating the frequency of regimes, the eastern El Niño regime in particular. In the future, both El Niño and central La Niña regimes are expected to be more frequent accompanied with a less frequent neutral regime. The central Pacific El Niño and La Niña regimes are projected to increase in amplitude and variability.

A Refined Understanding of the Ice Cloud Longwave Scattering Effects in Climate Model

AbstractBecause longwave (LW) absorption by greenhouse gases and clouds is more significant than the LW scattering effect by clouds, most climate models neglect cloud LW scattering to save computational costs. Ignoring cloud LW scattering directly overestimates outgoing longwave radiation (OLR). This study included ice‐cloud LW scattering treatment in the Exascale Energy Earth System Model (E3SM) version 2 and ran fully‐coupled simulations, prescribed sea surface temperature simulations, and offline radiative transfer calculations to comprehensively assess the impact of ice‐cloud LW scattering on global climate simulation. The instantaneous effect due to ice‐cloud LW scattering reduces the OLR by ∼1 W/m2 on the global average and 2 W/m2 on the tropical average. Tropospheric warming and high cloud amount reduction act to partially compensate for such instantaneous OLR reduction caused by the inclusion of LW scattering. When the simulation reaches the equilibrium, the surface warms by 0.66 K on average with respect to the simulation without LW scattering, with the Arctic surface temperature differences more than twice as large as that of the global mean. The impact of including LW scattering on the simulated climate change in response to 4 × CO2 is also assessed. While including the cloud LW scattering does not significantly modify radiative forcing and total radiative feedback under such a scenario, it results in a 10% more positive cloud feedback.

The Effects of Wave-Induced Stokes Drift and Mixing Induced by Nonbreaking Surface Waves on the Ocean in a Climate System Ocean Model

Oceanic general circulation models (OGCMs) are important tools used to investigate mechanisms for ocean climate variability and predict the ocean change in the future. However, in most current ocean models, the impact of sea surface waves as one of the most significant dynamic processes in the upper ocean is absent. In this study, the Stokes drift and the vertical mixing induced by nonbreaking surface waves derived from the wave model (WAVEWATCH III) are incorporated into a Climate System Ocean Model, and their effects on an ocean climate simulation are analyzed. Numerical experiments show that both physical processes can improve the simulation of sea surface temperature (SST) and mixed layer depth (MLD) in the Southern Hemisphere. The introduction of Stokes drift effectively reduces the subsurface warm bias in the equatorial tropics, which is caused by the weakening of vertical mixing in the equatorial region. The nonbreaking surface wave mainly reduces the temperature bias in the Southern Ocean by enhancing mixing in the upper ocean. For the MLD, the Stokes drift mainly improves the simulation of the winter MLD, and the nonbreaking surface wave improves the summer MLD. For MLD south of 40° S in summer, the introduction of nonbreaking surface waves resulted in a reduction of 11.86 m in MLD bias and 7.8 m in root mean square errors (RMSEs), respectively. For winter subtropical MLD in the Southern Hemisphere, considering the Stokes drift, the MLD bias and RMSEs were reduced by 2.49 and 5.39 m, respectively. Adding these two physical processes simultaneously provides the best simulation performance for the structure of the upper layer. The introduction of sea surface waves effectively modulates the vertical mixing of the upper ocean and then improves the simulation of the MLD. Thus, sea surface waves are very important for ocean simulation, so we will further couple a sea waves model in the Chinese Academy of Sciences Earth System Model (CAS-ESM) as part of their default model component.

Impacts of Oceanic Mesoscale Structures on Sea Surface Temperature in the Arabian Sea and Indian Summer Monsoon Revealed by Climate Model Simulations

Abstract Climate models typically have a cold sea surface temperature (SST) bias for the Arabian Sea, which regulates the Indian monsoon system as a water vapor source. Since the SST for the Arabian Sea is critical for the Indian monsoon, a better understanding of the processes that affect the SST is required. In this study, the effects of mesoscale oceanic variability on simulations of the Arabian Sea SST and Indian summer monsoon precipitation were investigated based on a comparison of climate model experiments in which non-eddying and eddy-permitting ocean components are coupled. In the eddy-permitting model, warm water advection driven by mesoscale variability near the Gulf of Aden and the Gulf of Oman increases the SST in the western Arabian Sea. Lateral eddy heat transport enhances warm water outflows to the Arabian Sea and suppresses surface water cooling by coastal upwelling during the southwestern monsoon season. Furthermore, a sensitivity experiment shows the primary importance of resolving oceanic mesoscale eddies and the secondary importance of resolving the Persian Gulf and Red Sea for the Arabian Sea SST. Also, the summer monsoonal precipitation decreases (increases) over the southeastern Arabian Sea (western and northern India) in the eddy-permitting model due to enhancement of wind convergence in the lower troposphere. Atmospheric general circulation model experiments indicate that the precipitation difference is partly caused by SST changes over the western Arabian Sea. The findings imply that the ocean resolution of climate models is a key factor in efficiently simulating the Indian monsoon.

Simulated and projected SST of Asian marginal seas based on CMIP6 models

Sea surface temperature (SST) is an important element in studying the global ocean-atmospheric system, as well as its simulation and projection in climate models. In this study, we evaluate the simulation skill of the Coupled Model Intercomparison Project Phase 6 (CMIP6) models in simulating the climatological SST in the Asian Marginal Seas (AMS), known as the most rapidly warming region over the global ocean. The results show that the spatial patterns and seasonal variability of Asian Marginal Seas (AMS) climatological SST simulated by the CMIP6 models are generally in good agreement with the observations, but there are simulation biases in the values. In boreal winter, the simulated climatological SST tends to be overestimated in the Japan/East Sea and the East China Seas (ECSs) by up to 2°C, while being underestimated in the Sea of Okhotsk by up to 2°C. In boreal summer, the simulated climatological SSTs are overestimated in the Indonesian seas and western Arabian Sea, while being underestimated in the Sea of Okhotsk and the northern ECSs by 1.2–1.5 and 2°C, respectively. Furthermore, we calculate the projected sea surface warming trends in the AMS under different future scenarios in the CMIP6 models. The results show warming trends of 0.8–1.8, 1.7–3.4, and 3.8–6.5°C/century for the Shared Socio-Economic Pathway (SSP) of low- (global radiative forcing of 2.6 W/m² by the year 2100), medium- (global radiative forcing of 4.5 W/m² by 2100) and high-end (8.5 W/m² by 2100) pathways, respectively. In addition, the middle and high latitudes of the AMS are found to have faster warming trends than the low latitudes, with the most rapidly warming occurring in the Sea of Okhotsk, which is around 2 times larger than the global mean SST warming trend. The SST warming trends are relatively slow in the South China Sea and the Indonesian seas, roughly equal to the global mean SST warming trend.

Sea level pressure response to the specification of eddy-resolving sea surface temperature in simulations of Australian east coast lows

Four east coast lows (ECLs) were simulated with the Weather Research and Forecast model to investigate the influence of the sea surface temperature (SST) distribution on the sea level pressure (SLP). Each ECL was simulated with two different SST datasets: the Bluelink SST field and NCEP skin temperature field. The former resolved eddies in the East Australian Current while the latter did not. The simulated SLP fields in the eddy-resolving SST runs were compared with those in the non-eddy-resolving SST runs. On time-scales of about 48 hours, higher SSTs were asso-ciated with lower SLPs. The spatial scale of the SLP response was similar to that of the ocean eddies, indicative of the rapidity and robustness of the response given the rapidly evolving conditions within the storms. On shorter time-scales, the SLP response to SST change can become substantially larger. The largest reductions in SLP in the eddy-resolving SST runs were associated with regions of deep atmospheric convection that warm the tropospheric column. These areas were shown to be related to the SST distribution with the greatest SLP reductions associated with convection over strong SST gradient regions. The landfall of a damaging convective mesoscale low pressure system on 8 June 2007 was also investigated. It was found that a region of strong SST gradients on the southern flank of a large warm ocean eddy was associated with lower pressures at the time of formation of this meso-low. In addition, the only case that simulated the low pressure at the correct time (albeit at not quite the correct location) was the eddy-resolved SST run. It was hy-pothesized that the development of this meso-low that impacted the coast around Newcastle, was enhanced because of the eddy-scale SST distribution at the time.

4D-Var data assimilation and observation impact on surface transport of HF-Radar derived surface currents in the North-Western Mediterranean Sea

We investigated the effect of the assimilation of surface velocities from two HF-Radars (HFRs) and satellite sea surface temperature (SST) into an ocean circulation model, implemented on the North-Western Mediterranean Sea, using the ROMS 4D-Var Data Assimilation (DA) System. A three months period from September to November 2020 is analysed. A model free run is used as reference simulation to quantify the impact of the data assimilation procedure on the surface circulation. The DA framework consists of a sequence of 3-day windows during which the observations are assimilated into the model, followed by forecast simulations, starting from the last time step of the analysis run. The comparison of simulated velocities and SST against the assimilated observations shows that both forecast and analysis runs improve the solution as compared to the freerun, with error reduction up to the 47% and doubling of correlation values. If SST is not assimilated, the simulated sea surface temperature slightly degrades as a result of the DA procedure. Furthermore, we used surface velocities from Lagrangian drifters to test the model against independent observations. The results show that both the forecast and the analysis simulate surface circulation better than the free run within the areas covered by HFR observations, with error reduction ranging from 10% to 50%, and increase in correlation from 5% to more than doubled. Nevertheless, farther afield, outside the area covered by HFRs, improvements and degradations of the solution due to the DA procedure balance each other. The impact of assimilated observation on the alongshore transport of the upper 50 m is analysed along three transects adjacent to the two HFR areas and along a section in between. The transport increment is significant where the surface velocities are assimilated whereas it is negligible elsewhere. The effect of SST is to modify the velocity distribution along the transects, while keeping the transport increment unchanged. Modifications to the initial conditions have the most significant effect on the alongshore transport, whereas the corrections to boundary conditions and atmospheric forcing have different importance according to the analysed transects. The assimilation of surface velocities and SST affects more the ageostrophic component of the surface velocity field, rather than the geostrophic one.

The improvements of sea surface temperature simulation over China Offshore Sea in present climate from CMIP5 to CMIP6 models

The improvements of sea surface temperature simulation over China Offshore Sea in present climate from CMIP5 to CMIP6 models

Rectifying low-frequency variability in future climate sea surface temperature simulations: are corrections for extreme change scenarios realistic?

Most procedures for redressing systematic bias in climate modeling are calibrated using current climate observations, and perform well. However, their performance in the future climate remains uncertain as no observations exist to compare against. In this context, we use the current and future climate outputs of an ultra-high resolution of Community Earth System Model (UHR-CESM) as the representative truth and bias correct monthly sea surface temperature (SST) simulations of eight Coupled Model Intercomparison Project 6 models over the Niño 3.4 region. A time-frequency bias correction approach is used to correct for bias in distributional, trend, and spectral attributes present in the models. This results in a near perfect power spectrum of the bias corrected current climate model simulations. Considering all correction procedures remain unchanged into the future, the overall representation of the corrected SST simulations shows improvement with consistency across models for the doubled CO2 scenario, but higher variability and lower consistency in the quadrupled CO2 concentration scenario.

Stratification Breakdown by Fall Cold Front Winds over the Louisiana Shelf in the Northern Gulf of Mexico: A Numerical Experiment

Cold fronts are meteorological phenomena that impact the northern Gulf of Mexico, mostly between the fall and spring seasons. On average, they pass the region every 3–7 days, with a duration ranging between 24 and 74 h. In the present study, a high-resolution FVCOM model with an unstructured mesh was used to simulate the effect of the fall cold front winds on water column mixing over the Louisiana shelf, which is often stratified in the summer, leading to hypoxia. Numerical experiments were conducted for October 2009, a period with five consecutive cold front events. Winds from an offshore station forced the model, while climatological temperature/salinity profiles prepared by NOAA for September were used for model initialization. The model performance was evaluated by comparing it with the surface current measurements at two offshore stations, and the results showed a good agreement between the model results and observations. Shelf mixing and stratification were investigated through examining the simulated sea surface temperature as well as the longitudinal and cross-shelf vertical sections. Simulation results showed a significant effect on shelf mixing, with the mixed layer depth increasing from the initial values of 5 m to 25 m at the end of simulation at different parts of the shelf, with maximum mixed layer depths corresponding to the peak of cold fronts. The buoyancy frequency, Richardson number, and the average potential energy demand (APED) for mixing the water column were used to quantify the stratification at two selected locations over the shelf. Results showed that all these parameters almost continuously decreased due to mixing induced by cold front wind events during this time. At the station off the Terrebonne Bay with a water depth of 20 m, the water column became fully mixed after three of the cold front events, with Richardson numbers smaller than 0.25 and approaching zero. This continued mixing trend was also proven by obtaining a decreasing trend of APED from 100 to 5 kg/m.s2 with several close to zero energy demand values.

Embedding a one-column ocean model in the Community Atmosphere Model 5.3 to improve Madden–Julian Oscillation simulation in boreal winter

Abstract. The effect of the air–sea interaction on the Madden–Julian Oscillation (MJO) was investigated using the one-column ocean model Snow–Ice–Thermocline (SIT 1.06) embedded in the Community Atmosphere Model 5.3 (CAM5.3; hereafter CAM5–SIT v1.0). The SIT model with 41 vertical layers was developed to simulate sea surface temperature (SST) and upper-ocean temperature variations with a high vertical resolution that resolves the cool skin and diurnal warm layer and the upper oceanic temperature gradient. A series of 30-year sensitivity experiments were conducted in which various model configurations (e.g., coupled versus uncoupled, vertical resolution and depth of the SIT model, coupling domains, and absence of the diurnal cycle) were considered to evaluate the effect of air–sea coupling on MJO simulation. Most of the CAM5–SIT experiments exhibit higher fidelity than the CAM5-alone experiment in characterizing the basic features of the MJO such as spatiotemporal variability and the eastward propagation in boreal winter. The overall MJO simulation performance of CAM5–SIT benefits from (1) better resolving the fine vertical structure of upper-ocean temperature and therefore the air–sea interaction that results in more realistic intraseasonal variability in both SST and atmospheric circulation and (2) the adequate thickness of a vertically gridded ocean layer. The sensitivity experiments demonstrate the necessity of coupling the tropical eastern Pacific in addition to the tropical Indian Ocean and the tropical western Pacific. Coupling is more essential in the south than north of the Equator in the tropical western Pacific. Enhanced MJO could be obtained without considering the diurnal cycle in coupling.