Earth Simulator Research Articles

A Study of the Mixed Layer Warming Induced by the Barrier Layer in the Northern Bay of Bengal in 2013

Strong salinity stratification induced by large freshwater fluxes in the northern Bay of Bengal (BOB) results in the formation of a quasi-permanent barrier layer (BL) that covers almost the entire BOB and leads to a unique temperature inversion within the thick BL in winter. In the presence of temperature inversions, the entrainment process at the bottom of the mixed layer (ML) induces warming effects in the ML, but little is known about this. In this paper, we quantify the contribution of the entrainment process to the ML temperature (MLT) in the northern BOB during the winter of 2013 using monthly and daily data from the Ocean General Circulation Model for the Earth Simulator version 2 (OFES2). It is found that the warming effect of the daily entrainment heat flux (EHF), which resolved the high-frequency variations, is 4 orders of magnitude larger than the monthly EHF for most of the wintertime. This significantly enhanced warming effect in daily data offsets up to 87% of the surface cooling induced by net heat flux during wintertime. A further analysis reveals that the larger daily EHF warming effect compared to its monthly counterpart is closely related to the deepened ML, the larger temperature difference within the ML and vertical velocity at the bottom of the ML.

Feedback mechanisms controlling Antarctic glacial-cycle dynamics simulated with a coupled ice sheet–solid Earth model

Abstract. The dynamics of the ice sheets on glacial timescales are highly controlled by interactions with the solid Earth, i.e., the glacial isostatic adjustment (GIA). Particularly at marine ice sheets, competing feedback mechanisms govern the migration of the ice sheet's grounding line (GL) and hence the ice sheet stability. For this study, we developed a coupling scheme and performed a suite of coupled ice sheet–solid Earth simulations over the last two glacial cycles. To represent ice sheet dynamics we apply the Parallel Ice Sheet Model (PISM), and to represent the solid Earth response we apply the 3D VIscoelastic Lithosphere and MAntle model (VILMA), which, in addition to load deformation and rotation changes, considers the gravitationally consistent redistribution of water (the sea-level equation). We decided on an offline coupling between the two model components. By convergence of trajectories of the Antarctic Ice Sheet deglaciation we determine optimal coupling time step and spatial resolution of the GIA model and compare patterns of inferred relative sea-level change since the Last Glacial Maximum with the results from previous studies. With our coupling setup we evaluate the relevance of feedback mechanisms for the glaciation and deglaciation phases in Antarctica considering different 3D Earth structures resulting in a range of load-response timescales. For rather long timescales, in a glacial climate associated with the far-field sea-level low stand, we find GL advance up to the edge of the continental shelf mainly in West Antarctica, dominated by a self-amplifying GIA feedback, which we call the “forebulge feedback”. For the much shorter timescale of deglaciation, dominated by the marine ice sheet instability, our simulations suggest that the stabilizing sea-level feedback can significantly slow down GL retreat in the Ross sector, which is dominated by a very weak Earth structure (i.e., low mantle viscosity and thin lithosphere). This delaying effect prevents a Holocene GL retreat beyond its present-day position, which is discussed in the scientific community and supported by observational evidence at the Siple Coast and by previous model simulations. The applied coupled framework, PISM–VILMA, allows for defining restart states to run multiple sensitivity simulations from. It can be easily implemented in Earth system models (ESMs) and provides the tools to gain a better understanding of ice sheet stability on glacial timescales as well as in a warmer future climate.

Estimating the Ebro river discharge at 1 km/daily resolution using indirect satellite observations

Estimating river discharge Q at global scale from satellite observations is not yet fully satisfactory in part because of limited space/time resolution. Furthermore, on highly anthropized basins, it is essential to anchor the analysis to reliable Q measurements. Gauge networks are however very sparse and limited in time, and SWOT (Surface Water Ocean Topography) river discharge estimates at global scale are not yet available. The method proposed here is able to obtain continuous daily Q estimates at 1 km/daily resolution, using indirect satellite data and ground-based estimates. We focus here on the Ebro. Over such an anthropized basin (e.g. change of land use, irrigation), the exploitation of 205 available gauges at their nominal resolution (i.e., daily point measurements) is a necessity. The hydrological Continuum model is used to help interpolate spatially and temporally the observations into our optimal interpolation scheme. The proposed Q-mapping is similar to an assimilation scheme were Earth observations (precipitation, evapotranspiration and total water storage change) and model simulations are constrained by in situ gauge measurements. The Q estimates are evaluated using a rigorous leave-one-out experiment, showing a good agreement with the in situ data: a correlation of 0.72 (median), and a 75th percentile of Nash-Sutcliffe Efficiency up to 0.62. Our spatio-temporal continuous Q estimates at high spatial/temporal resolution can describe complex continental water dynamics, including extreme events. SWOT estimates will soon be available, at the global scale but with irregular space/time sampling: our method should help exploit them to obtain a regular space-temporal description of the water cycle at high resolution.

Using climate envelopes and earth system model simulations for assessing climate change induced forest vulnerability

Changing climatic conditions threaten forest ecosystems. Drought, disease and infestation, are leading to forest die-offs which cause substantial economic and ecological losses. In central Europe, this is especially relevant for commercially important coniferous tree species. This study uses climate envelope exceedance (CEE) to approximate species risk under different future climate scenarios. To achieve this, we used current species presence-absence and historical climate data, coupled with future climate scenarios from various Earth System Models. Climate scenarios tended towards drier and warmer conditions, causing strong CEEs especially for spruce. However, we show that annual averages of temperature and precipitation obscure climate extremes. Including climate extremes reveals a broader increase in CEEs across all tree species. Our study shows that the consideration of climate extremes, which cannot be adequately reflected in annual averages, leads to a different assessment of the risk of forests and thus the options for adapting to climate change.

Twenty-Year Climatology of Solar UV and PAR in Cyprus: Integrating Satellite Earth Observations with Radiative Transfer Modeling

In this study, we present comprehensive climatologies of effective ultraviolet (UV) quantities and photosynthetically active radiation (PAR) over Cyprus for the period 2004 to 2023, leveraging the synergy of earth observation (EO) data and radiative transfer model simulations. The EO dataset, encompassing satellite and reanalysis data for aerosols, total ozone column, and water vapor, alongside cloud modification factors, captures the nuanced dynamics of Cyprus’s atmospheric conditions. With a temporal resolution of 15 min and a spatial of 0.05° × 0.05°, these climatologies undergo rigorous validation against established satellite datasets and are further evaluated through comparisons with ground-based global horizontal irradiance measurements provided by the Meteorological Office of Cyprus. This dual-method validation approach not only underscores the models’ accuracy but also highlights its proficiency in capturing intra-daily cloud coverage variations. Our analysis extends to investigating the long-term trends of these solar radiation quantities, examining their interplay with changes in cloud attenuation, aerosol optical depth (AOD), and total ozone column (TOC). Significant decreasing trends in the noon ultraviolet index (UVI), ranging from −2 to −4% per decade, have been found in autumn, especially marked in the island’s northeastern part, mainly originating from the (significant) positive trends in TOC. The significant decreasing trends in TOC, of −2 to −3% per decade, which were found in spring, do not result in correspondingly significant positive trends in the noon UVI since variations in cloudiness and aerosols also have a strong impact on the UVI in this season. The seasonal trends in the day light integral (DLI) were generally not significant. These insights provide a valuable foundation for further studies aimed at developing public health strategies and enhancing agricultural productivity, highlighting the critical importance of accurate and high-resolution climatological data.

Finding reconnection lines and flux rope axes via local coordinates in global ion-kinetic magnetospheric simulations

Abstract. Magnetic reconnection is a crucially important process for energy conversion in plasma physics, with the substorm cycle of Earth's magnetosphere and solar flares being prime examples. While 2D models have been widely applied to study reconnection, investigating reconnection in 3D is still, in many aspects, an open problem. Finding sites of magnetic reconnection in a 3D setting is not a trivial task, with several approaches, from topological skeletons to Lorentz transformations, having been proposed to tackle the issue. This work presents a complementary method for quasi-2D structures in 3D settings by noting that the magnetic field structures near reconnection lines exhibit 2D features that can be identified in a suitably chosen local coordinate system. We present applications of this method to a hybrid-Vlasov Vlasiator simulation of Earth's magnetosphere, showing the complex magnetic topologies created by reconnection for simulations dominated by quasi-2D reconnection. We also quantify the dimensionalities of magnetic field structures in the simulation to justify the use of such coordinate systems.

Suppression of Mesoscale Eddy Mixing by Topographic PV Gradients

Abstract Oceanic mesoscale eddy mixing plays a crucial role in Earth’s climate system by redistributing heat, salt, and carbon. For many ocean and climate models, mesoscale eddies still need to be parameterized. This is often done via an eddy diffusivity , which sets the strength of turbulent downgradient tracer fluxes. A well-known effect is the modulation of in the presence of background potential vorticity (PV) gradients, which suppresses cross-PV gradient mixing. Topographic slopes can induce such suppression through topographic PV gradients. However, this effect has received little attention, and topographic effects are often not included in parameterizations for . In this study, we show that it is possible to describe the effect of topography on analytically in a barotropic framework, using a simple stochastic representation of eddy–eddy interactions. We obtain an analytical expression for the depth-averaged as a function of the bottom slope, which we validate against diagnosed eddy diffusivities from a numerical model. The obtained analytical expression can be generalized to any constant barotropic PV gradient. Moreover, the expression is consistent with empirical parameterizations for eddy diffusivity over topography from previous studies and provides a physical rationalization for these parameterizations. The new expression helps to understand how eddy diffusivities vary across the ocean, and thus how mesoscale eddies impact ocean mixing processes. Significance Statement Large oceanic “whirls,” called eddies, can mix and transport ocean properties such as heat, salt, carbon, and nutrients. Mixing plays an important role for oceanic ecosystems and the climate system. In numerical simulations of Earth’s climate, eddy mixing is typically represented using a simplified expression. However, an effect that is often not included is that eddy mixing is weaker over a sloping seafloor. In most areas of the ocean the bottom slope is steep enough for this effect to be significant. In this study we derive an expression for eddy mixing that accounts for oceanic bottom slopes. The present effort provides a physical basis for eddy mixing over oceanic bottom slopes, justifying their use in climate models.

Energetics of eddy-mean flow interactions in the western tropical Pacific Ocean

The eddy-mean flow interactions are critical processes in the ocean energy cycle. This study investigated the energetics of eddy-mean flow interactions in the western tropical Pacific Ocean using the multiscale window transform (MWT) and MWT-based canonical transfer theory, based on 16-year numerical outputs from the Ocean General Circulation Model for the Earth Simulator and two mooring measurements. Energy analysis revealed that prominent eddy kinetic energy (EKE) appears in the upper layer of the Sulawesi Sea and the source region of North Equatorial Countercurrent (NECC), and in the subsurface layer along the Philippine coast. The kinetic energy in the upper layer is mainly transferred from the mean flow to the eddy field through barotropic instability. Below the thermocline, the prominent subsurface EKE is not only caused by barotropic conversion, but also by baroclinic one. Subsurface mesoscale eddies east of the Mindanao Island extract energy from mean flow through barotropic instability, and those further north seem to release their kinetic energy to the mean flow of North Equatorial Undercurrent, indicating inverse energy cascades. Our results highlight that the advection effect plays a key role in the horizontal distribution of EKE, which generally shifts the high EKE area a few degrees downstream from the eddy formation region. Particularly, in the source region of NECC, the advection term shifts the EKE center 5° eastward from ∼132°E to ∼137°E.

Adjoint inversion of antipodal PKPab waveforms for P wave velocity anomaly at the base of the lower mantle

We perform an adjoint inversion by using antipodal PKPab phases to estimate the heterogeneous Vp structure at the base of the lowermost mantle. We have carefully examined antipodal stations with high S/N ratios during the past 30 years and selected 20 source-receiver pairs with the epicentral distances >179.0 degree and the Mw <7.0. We have used the spectral-element method on the Earth Simulator of JAMSTEC to calculate the synthetic seismograms for a heterogeneous mantle Vp model with the accuracy of period about 8 s (110 km wavelength at the CMB). We have set up the time window to retrieve the PKPab phase from the vertical component of both observed and computed seismograms to calculate the adjoint source to obtain the sensitivity kernels of Vp in the mantle. The computed Vp sensitivity kernel for each event shows the characteristic annulus pattern in the lowermost mantle, which covers a large area of the CMB. The twenty PKPab earthquake-station pairs in this antipodal study contribute the equivalent of about 3140 measurements at the CMB—compared with 1871 previously studied—and provide new data. Therefore, although the number of individual source-receiver pairs is not large, the summed sensitivity kernels of the PKPab phase for Vp structure at the base of the mantle may be sufficient to model heterogeneity of the Vp structure at the CMB. We summed each event kernel to set up a sensitivity kernel of Vp in the lowermost mantle and iterated the inversion to estimate a heterogeneous structure in D″. Although we have iterations that dominantly affect both South America and the South Pacific, the summary final model shows features within South of Africa, South Pacific, SE Australia, and Central & South America. Keeping the Vs model fixed, we map the CMB Vp heterogeneity measured by the parameter Rs,p = dlnVs/dlnVp and find qualitative, proximal correspondence with the degree-2 pattern of Large Low Velocity Shear Provinces observed in shear tomographic models: in the Pacific and Africa Rs,p > 2.0, whereas the surrounding edges of the edges of the Pacific show Rs,p < 2.0.

Global Magnetic Reconnection During Sustained Sub‐Alfvénic Solar Wind Driving

AbstractWhen the solar wind speed falls below the local Alfvén speed, the magnetotail transforms into an Alfvén wing configuration. A Grid Agnostic Magnetohydrodynamics for Extended Research Applications (GAMERA) simulation of Earth's magnetosphere using solar wind parameters from the 24 April 2023 sub‐Alfvénic interval is examined to reveal modifications of Dungey‐type magnetotail reconnection during sustained sub‐Alfvénic solar wind. The simulation shows new magnetospheric flux is generated via reconnection between polar cap field lines from the northern and southern hemisphere, similar to Dungey‐type magnetotail reconnection between lobe field lines mapping to opposite hemispheres. The key feature setting the Alfvén wing reconnection apart from the typical Dungey‐type is that the majority of new magnetospheric flux is added to the polar cap at local times 1–3 (21‐23) in the northern (southern) hemisphere. During most of the sub‐Alfvénic interval, reconnection mapping to midnight in the polar cap generates relatively little new magnetospheric flux.

Impact of marine carbon removal on atmospheric CO2

Abstract A computer simulation of Earth’s climate is used to study if marine carbon removal will lead to a reduced atmospheric carbon dioxide concentration, and if there are potential secondary impacts on marine life and chemistry. We find that for stationary carbon removal plants the ocean cannot supply sufficient carbon rich water to allow a meaningful reduction of atmospheric CO2. This also means that outside the location of carbon removal there is no noticeable impact on plankton concentrations. It can be speculated that putting carbon removal plants on ships would lead to a significant increase in removal efficiency, although the engineering and energy aspects of this approach would need to be investigated.

Perspectives on AI Architectures and Codesign for Earth System Predictability

Abstract Recently, the U.S. Department of Energy (DOE), Office of Science, Biological and Environmental Research (BER), and Advanced Scientific Computing Research (ASCR) programs organized and held the Artificial Intelligence for Earth System Predictability (AI4ESP) workshop series. From this workshop, a critical conclusion that the DOE BER and ASCR community came to is the requirement to develop a new paradigm for Earth system predictability focused on enabling artificial intelligence (AI) across the field, laboratory, modeling, and analysis activities, called model experimentation (ModEx). BER’s ModEx is an iterative approach that enables process models to generate hypotheses. The developed hypotheses inform field and laboratory efforts to collect measurement and observation data, which are subsequently used to parameterize, drive, and test model (e.g., process based) predictions. A total of 17 technical sessions were held in this AI4ESP workshop series. This paper discusses the topic of the AI Architectures and Codesign session and associated outcomes. The AI Architectures and Codesign session included two invited talks, two plenary discussion panels, and three breakout rooms that covered specific topics, including 1) DOE high-performance computing (HPC) systems, 2) cloud HPC systems, and 3) edge computing and Internet of Things (IoT). We also provide forward-looking ideas and perspectives on potential research in this codesign area that can be achieved by synergies with the other 16 session topics. These ideas include topics such as 1) reimagining codesign, 2) data acquisition to distribution, 3) heterogeneous HPC solutions for integration of AI/ML and other data analytics like uncertainty quantification with Earth system modeling and simulation, and 4) AI-enabled sensor integration into Earth system measurements and observations. Such perspectives are a distinguishing aspect of this paper. Significance Statement This study aims to provide perspectives on AI architectures and codesign approaches for Earth system predictability. Such visionary perspectives are essential because AI-enabled model-data integration has shown promise in improving predictions associated with climate change, perturbations, and extreme events. Our forward-looking ideas guide what is next in codesign to enhance Earth system models, observations, and theory using state-of-the-art and futuristic computational infrastructure.

Opinion: Tropical cirrus – from micro-scale processes to climate-scale impacts

Abstract. Tropical cirrus clouds, i.e., any type of ice cloud with tops above 400 hPa, play a critical role in the climate system and are a major source of uncertainty in our understanding of global warming. Tropical cirrus clouds involve processes spanning a wide range of spatial and temporal scales, from ice microphysics on cloud scales to mesoscale convective organization and planetary wave dynamics. This complexity makes tropical cirrus clouds notoriously difficult to model and has left many important questions stubbornly unanswered. At the same time, their multi-scale nature makes them well-positioned to benefit from the rise of global, high-resolution simulations of Earth's atmosphere and a growing abundance of remotely sensed and in situ observations. Rapid progress on our understanding of tropical cirrus requires coordinated efforts to take advantage of these modern computational and observational abilities. In this opinion paper, we review recent progress in cirrus studies, highlight important unanswered questions, and discuss promising paths forward. Significant progress has been made in understanding the life cycle of convectively generated “anvil” cirrus and the response of their macrophysical properties to large-scale controls. On the other hand, much work remains to be done to fully understand how small-scale anvil processes and the climatological anvil radiative effect will respond to global warming. Thin, in situ formed cirrus clouds are now known to be closely tied to the thermal structure and humidity of the tropical tropopause layer, but microphysical uncertainties prevent a full understanding of this link, as well as the precise amount of water vapor entering the stratosphere. Model representation of ice-nucleating particles, water vapor supersaturation, and ice depositional growth continue to pose great challenges to cirrus modeling. We believe that major advances in the understanding of tropical cirrus can be made through a combination of cross-tool synthesis and cross-scale studies conducted by cross-disciplinary research teams.

Projecting global fertilizer consumption under shared socioeconomic pathway (SSP) scenarios using an approach of ensemble machine learning

Comprehensively projecting global fertilizer consumption is essential for providing critical datasets in related fields such as earth system simulation, the fertilizer industry, and agricultural sciences. However, since previous studies have not fully considered the socioeconomic factors affecting fertilizer consumption, huge uncertainties may remain in fertilizer consumption projections. Here, an approach ensembled six machine learning algorithms was proposed in this study to predict global fertilizer consumption from 2020 to 2100 by considering the impact of socioeconomic factors under shared socioeconomic pathway (SSP) scenarios. It indicates that the proposed approach provides a rational and reliable framework for fertilizer consumption prediction that stably outperforms the single algorithms with relatively high accuracy (Nash-Sutcliffe efficiency of 0.93, Kling-Gupta efficiency of 0.89, and mean absolute percentage error of 10.97 %). We found that global N and P fertilizer consumption may decrease from 2020 to 2100, while K fertilizer may buck the trend. N fertilizer consumption showed a declining trend of −1 %, −17.13 %, and −3.43 % under the SSP1, SSP2, and SSP3 scenarios in 2100, respectively. For P fertilizer, those were −0.68 %, −9.68 %, and −2.03 %. In contrast, global K fertilizer consumption may increase by 18.03 %, 9.18 %, and 6.74 %, respectively. On average, N, P, and K fertilizer consumption is highest in China, and the lowest is in Kazakhstan. However, the hotspots of N fertilizer consumption may shift from China to Latin America and the Caribbean. This study highlighted the ensemble machine learning approach could potentially be a robust method for predicting future fertilizer consumption. Our prediction product will not only contribute to a better understanding of global fertilizer consumption trends and dynamics but also provide flexible and accurate key data/parameters for related research. The Projected Global Fertilizers Consumption Datasets are available at doi:https://doi.org/10.5281/zenodo.8195593 (Gao et al., 2023).

Parametrization of coefficients for sub-grid modeling of pitch-angle diffusion in global magnetospheric hybrid-Vlasov simulations

Sub-grid models are key tools to accurately describe the physical processes at play in a system when high-resolution simulations are not feasible. We previously developed a sub-grid model for pitch-angle diffusion in hybrid-Vlasov simulations of Earth's magnetosphere. However, a more precise description of the pitch-angle diffusion coefficient is required to apply this model to global simulations. In this study, we use an existing method to parametrize pitch-angle diffusion coefficients from monotonic distribution functions and adapt it to bi-Maxwellian distributions. We determine these coefficients for various values of the ion temperature anisotropy and plasma β∥. We use these newly parametrized coefficients in our sub-grid model and show that it accurately models reduction of temperature anisotropy in both local simulations and global simulations of the Earth's magnetosphere, while using minimal computational resources.

Surrogate model-based calibration of a flying Earth observation satellite

At the European Space Agency (ESA), Modeling and Simulation (M&S) plays a fundamental role during the lifetime of a spacecraft, being used from the design phase to the testing and during operations in space. M&S tools embed general physics-based models and disciplines characterized by configurable parameters which have to be calibrated in order to mimic the behavior of the actual flying spacecraft. However, their calibration requires a large number of simulations which are unfeasible to be obtained through computationally expensive high-fidelity simulation models. Thus, the inability to calibrate the high-fidelity simulation models poses limitations for the use of M&S tools during spacecraft operations.In this light, the present work proposes the use of a surrogate model-based approach for the calibration of simulation models of spacecraft. The approach integrates a computationally inexpensive deep-learning-based surrogate model, which mimics the high-fidelity simulation model without requiring the same computational burden, and a metaheuristic optimization algorithm, to identify the optimal values of the simulation model configurable parameters. This enhances the capabilities of M&S tools and allows their use in operations. The approach’s effectiveness is shown by its application to real flying Earth observation satellite data and simulation models.

A study of the simulated climatological January mean upwelling in the northwestern Gulf of Alaska

In this research, we studied the upwelling in the northwestern Gulf of Alaska using the climatological January mean and data from the output of the Ocean General Circulation Model for Earth Simulator (OFES2). Specifically, we analyzed the upwelling in the regions where the Alaska Coastal Current (ACC) flows out of the Shelikof Strait (especially the part to the west of Kodiak Island) and where the ACC and the Alaskan Stream (AS) are confluent. In both regions, strong geostrophic currents and downwelling-favorable wind predominate in winter. Furthermore, there are freshwater discharges along the Alaskan coast and an observed mean current vertical shear in the ACC. We revealed that when the internal water stress is larger than the wind stress inside the study regions, this could be decisive in terms of the local horizontal velocity divergence and further upwelling, even if the region is away from the coast and lacks upwelling-favorable wind conditions. Geostrophic stress is part of the internal water stress and is a product of the geostrophic current shear (due to the thermal wind relation) and the vertical viscosity coefficient. The analysis indicated that a front with a large geostrophic stress may act as a “virtual wall” and contribute to local upwelling within a depth of approximately 100 m in the study regions. This process could provide a heuristic for understanding the distribution of pollock in the areas during February and March, which corresponds to the simulated upwelling region.

Designing an Accurate Temperature Control System for Infrared Earth Simulators Using Semiconductor and Air Cooling Integration.

In a laboratory environment, in order to test the attitude recognition capability and accuracy of the satellite attitude sensor-the infrared Earth sensor-the infrared Earth simulator is fixed on a five-axis turntable to enable multi-angle testing. In the past, the temperature control system of the Earth simulator was water cooled, which not only affected the working accuracy of the Earth simulator but also affected its size and portability and made it more difficult to use on the turntable. Therefore, we designed a cooling method for the cold plate based on semiconductor cooling technology combined with air cooling, and we designed a fuzzy PID control algorithm to accurately control the temperature according to this cooling method. In this article, we use SOLIWORKS to build the system model for the system and use the ANAYS Workbench to perform temperature analysis of the Earth simulator. The results show that the cold plate temperature can be maintained at 20.089 °C when the hot plate temperature is 85 °C. The overall temperature uniformity of the hot plate is better than ±0.3 °C, which meets the index requirements of the Earth simulator. We found that this cooling method can replace water cooling, giving the simulator the advantage of being miniaturized, and it can be adaptable to the turntable, which can be widely used in various sizes of Earth simulators and in various complex environments and operating conditions.

The seasonal variation of shallow meridional overturning circulation in the South China Sea and the related dynamics

The shallow meridional overturning circulation (SMOC) in the South China Sea (SCS) contributes to the local heat redistribution. Most investigations focused on its annual mean structure but paid little attention to its seasonal variation. In this study, the products of Ocean General Circulation Model for the Earth Simulator (OFES) are used to study the seasonal variation of the SMOC in the SCS. Results indicate that the SMOC can be formed in both winter and summer, and its structure has a prominent seasonal variation. The SMOC is clockwise and appears between 9°N and 18°N in winter, while it is anticlockwise and confined to the southern SCS in summer. Related dynamics of the SMOC seasonal variation are further investigated. It is found that the winter monsoon is essential for the formation of the clockwise winter SMOC, and the buoyancy flux also contributes to the winter SMOC formation via influencing the mixed layer depth. Although the SCS conditions are dramatically changed in summer, the summer monsoon can still circulate the water around in the circuit of the anticlockwise summer SMOC. The monsoon is the primary driving factor that dominates the formation and seasonal variation of the SMOC in the SCS.

Estimation of AMSU-A Radiance Observation Impacts in an LETKF-Based Atmospheric Global Data Assimilation System: Comparison with EFSO and Observing System Experiments

Abstract This work assesses the contribution of assimilating AMSU-A satellite-based radiance measurements to a global data assimilation system based on an atmospheric general circulation model and the local ensemble transform Kalman filter (LETKF). The radiance measurements were from three channels that are sensitive to the upper troposphere and lower stratosphere. The contribution of these measurements, or AMSU-A observation impact, was estimated both through ensemble-based forecast sensitivity to observations (EFSO) and observing system experiments (OSEs). Two streams of data-denial experiments for the AMSU-A observations were performed for about one month during winter in each hemisphere. The OSEs quantified the accumulated observation impact by cycling (repeating) data denials: including AMSU-A observations reduced the total observation impact for all observations of each data assimilation cycle. In contrast, EFSO estimated AMSU-A to increase the total observation impact. The opposing effects were attributed to the accumulated observation impact in the OSEs; the accumulation could stabilize the data assimilation cycles. In both experiments, the accumulated observation impact of AMSU-A was strongest in the upper troposphere, particularly in the austral midlatitudes where westerly jets exist and observations of other types are sparse. EFSO also assessed AMSU-A to have the most beneficial observation impact in similar locations. The AMSU-A observation impact tended to accumulate just downstream of where EFSO estimated the beneficial observation impact signals. The accumulated AMSU-A observation impact was tied to dynamic processes in the upper-tropospheric and general stratospheric circulation. Therefore, EFSO helps estimate the beneficial distributions of AMSU-A accumulated observation impact by considering their dynamical propagation. Significance Statement The Advanced Microwave Sounding Unit-A (AMSU-A) satellite radiance assimilation technique was successfully integrated into the Atmospheric General Circulation Model for the Earth Simulator (AFES)–LETKF data assimilation system. We conducted OSEs and used EFSO to assess the AMSU-A observation impact. The two estimation methods identified opposite observation impacts due to the cycling (repeating) OSEs of the AMSU-A observations. We interpreted the causes of the opposite estimations. However, even for the cycling OSEs, EFSO appeared to help estimate distributions of the accumulated observation impact. It is important to consider the dynamical propagation of accumulated observation impact in general circulation.