Large Sea Surface Research Articles

Greenland summer blocking characteristics: an evaluation of a high-resolution multi-model ensemble

AbstractAtmospheric blocking is a phenomenon that can lead to extreme weather events over a large region, yet its causes are not fully understood. Global climate models show limitations in representing Northern Hemisphere blocking, especially its frequency, and decadal variability in Greenland blocking in summer in the recent decades. In this study we evaluate the ability of high-resolution (HighResMIP) Earth System Models (ESMs) to simulate summer blocking over the Greenland area, using different but complementary methods to describe the characteristics of blocking. We find that the HighResMIP ensemble can reproduce the spatial pattern of Greenland blocking events, albeit with systematic biases, and capture the relative frequencies of the main blocking patterns: namely the wave breaking structure, North Atlantic ridge, and omega-type blocking. However, the HighResMIP ensemble fails to simulate the observed temporal variations of Greenland blocking index (GB2) and the extremely high values of daily GB2 observed in recent decades. In addition, we do not find clearly superior representation of blocking features from higher-resolution in HighResMIP models compared with lower-resolution models. We also find large sea surface temperature (SST) biases over the North Atlantic and seas surrounding Greenland, and biases in moisture transport over the North Atlantic toward Greenland, especially over the western flank of blocking areas, which might together contribute to model biases in the representation of blocking magnitude.

Aggregation and transport of microplastics by a cold-core ring in the southern recirculation of the Kuroshio Extension: the role of mesoscale eddies on plastic debris distribution

Mesoscale eddies – ocean vortices with spatial scales of tens to hundreds of kilometers and time scales of months to years – are among the most energetic forms of flow in the ocean, and may act as significant transporters of floating microplastics. Yet, shipboard observation has thus far not clarified the abundance and transport of microplastics in mesoscale eddies. We conducted floating microplastic surveys in an intense cyclonic mesoscale eddy with a large sea surface height depression (approximately 0.8 m), a so-called cold-core ring, in the Kuroshio Extension recirculation gyre (KERG) southeast of Japan. The concentration of microplastics within the eddy (460 × 104 pieces/km2) was one or two orders of magnitude higher than in the adjacent oceanic waters, likely due to the acquisition of microplastics from the microplastic-rich Kuroshio Extension (KE) when detaching, as well as the horizontal entrainment of particles by the eddy. Our examination by using an assimilation product showed that most particles captured by the eddy remained within for several months while the eddy moved clockwise in the KERG. These results suggest that mesoscale eddies are of importance in the transportation and redistribution of microplastics on the ocean surface.

Spatial and Temporal Variability of Ocean Thermal Energy Resource of the Pacific Islands

A lack of natural resources drives the oil dependency in Pacific Island Countries and Territories (PICTs), hampering energy security and imposing high electricity tariffs in the region. Nevertheless, the Western Equatorial Pacific is known for its large Sea Surface Temperature (SST) and deep-sea water (DSW) temperature difference favorable for harvesting thermal energy. In this study, we selected 18 PICTs in the western Equatorial Pacific to estimate Annual Energy Production (AEP) for a 1 MW class Ocean Thermal Energy Conversion (OTEC) plant. We combined the DSW temperature from the mean in situ Argo profiles and 1 km resolution satellite SST data to estimate the thermal energy resource resolving the fine features of the island coastline. Furthermore, the twenty-year-long SST dataset was used to analyze the SST variability. The analysis showed that Equatorial islands and Southern islands have the highest inter-annual variability due to El Nino Southern Oscillation (ENSO). The power density varied from 0.26 to 0.32 W/m2 among the islands, with the lowest values found for the southernmost islands near the South Equatorial Countercurrent. Islands within the South Equatorial Current, Equatorial Undercurrent, and North Equatorial Countercurrent showed the highest values for both power density and gross power. Considering a 1 MW class OTEC plant, Annual Energy Production (AEP) in 2022 varied from 7 GWh to 8 GWh, with relatively low variability among islands near the Equator and in low latitudes. Considering the three variables, AEP, SST variability, and distance from the shore, Nauru is a potential candidate for OTEC, with a net power of 1.14 MW within 1 km from the shore.

Lagrangian characterization of the southwestern Atlantic from a dense surface drifter deployment

The Southwestern Atlantic (SWA) is characterized by its large Eddy Kinetic Energy as the result of the confluence of two major western boundary currents, the northward flowing Malvinas Current (MC) and the southward flowing Brazil Current. The SWA study was addressed in the literature based on altimetry data, in situ measurements, regional models and ocean reanalysis. The present study constitutes the first effort to sample a portion of the SWA, with a dense drifter array (N = 62) deployment. The drifters, drogued at 15 m depths, were deployed across the MC and the Argentine Continental Shelf along two zonal transects located at 47°S and 47.25°S, between the 8th and the September 9, 2021. Drifters were set to deliver their position every 10 and 60 min, providing accurate Lagrangian trajectories that provide information on a large range of space and time scales of the surface currents. Three regions are clearly identified based on the analysis of the speed of the drifters, of their trajectories and of the spectral density of their velocities: the continental shelf, the slope and the open ocean. The comparison of the trajectories of the drifters with satellite altimetry images shows that, in general, drifters follow mesoscale features that are detectable in satellite altimetry maps. The analysis of the drifter trajectories also allowed us the study of submesoscale features of the flow (1–10 km) that are not observable in satellite altimetry data. Comparison with cloud-free, high-resolution color images, shows that drifter trajectories organized by the mesoscale flow might also locally follow sub-mesoscale features. In frontal regions it was found that drifter velocities double satellite altimetry geostrophic velocities, which suggests that the dynamics at those regions is largely dominated by ageostrophic components. The ageostrophic Ekman component might explain the direction of the drifters when strong winds from a given direction prevail for several days and the drifters are not in a region with large sea surface height (SSH) gradients. The joint analysis of drifters’ trajectory and SSH clearly depicts that mesoscale features on the open ocean region control the cross-shelf exchanges between the MC and open ocean regions as well as the strength and width of the MC. Finally, the spatial density distribution of the drifters during the first hours after deployment and within a small eddy also allowed us to characterize the flow in terms of its divergence, vorticity and strain, indicating that the MC is geostrophic and has a jet-like behavior while the eddy is largely ageostrophic and has a dominant vorticity component over strain. We conclude observing that the analysis of a dense array of drifters provides valuable information of the flow that cannot be attained solely based on satellite data.

Trends and drivers of CO2 parameters, from 2006 to 2021, at a time-series station in the Eastern Tropical Atlantic (6°S, 10°W)

The seawater fugacity of CO2 (fCO2) has been monitored hourly at an instrumented mooring at 6°S, 10°W since 2006. The mooring is located in the South Equatorial Current and is affected by the equatorial Atlantic cold tongue. This site is characterized by large seasonal sea surface temperature variations (>4°C). The fCO2 is measured by a spectrophotometric sensor deployed at about 1.5 meters deep. Measurements of seawater fCO2, sea surface temperature (SST) and sea surface salinity (SSS) are used to calculate total dissolved inorganic carbon (TCO2) and pH. Total alkalinity (TA) is calculated using an empirical relationship with SSS determined for this region. Satellite chlorophyll-a concentrations at 6°S, 10°W are low (<0.2 mg m-3) but some peaks over 0.8 mg m-3 are sometimes detected in August. Nevertheless, the site is a permanent source of CO2 to the atmosphere, averaging 4.7 ± 2.4 mmol m-2d-1 over 2006-2021. Despite the weakening of the wind, the CO2 flux increases significantly by 0.20 ± 0.05 mmol m-2d-1 yr-1. This suggests that the source of CO2 is increasing in this region. This is explained by seawater fCO2 increasing faster than the atmospheric increase during 2006-2021. Most of the seawater fCO2 increase is driven by the increase of TCO2, followed by SST. The fCO2 increase leads to a pH decrease of -0.0030 ± 0.0004 yr-1. The SST anomalies (SSTA) at 6°S, 10°W are correlated to the Tropical Southern Atlantic (TSA) index and to the Atlantic 3 region (ATL3) index with a correlation coefficient higher than 0.75. The strong positive phase of both ATL3 and TSA, observed towards the end of the time-series, is likely contributing to the strong increase of seawater fCO2.

Revisiting the Impacts of Tropical Pacific SST Anomalies on the Pacific Meridional Mode during the Decay of Strong Eastern Pacific El Niño Events

Abstract The Pacific meridional mode (PMM) can modulate El Niño–Southern Oscillation (ENSO) and is also affected by ENSO-related tropical Pacific sea surface temperature anomalies (SSTAs). Two tropical feedbacks on the PMM have been proposed: a positive one of central tropical Pacific SSTAs and a negative one of eastern tropical Pacific (ETP) SSTAs, the latter of which is suggested to be active only during strong eastern Pacific (EP) El Niño events like those in 1982/83 and 1997/98. However, we find that no strong, negative PMM-like SSTAs appeared, although the PMM indices (PMMIs) were strongly negative in spring of 1983 and 1998. Observation and model experiments show that tropical warming in 1983 and 1998 not only occurred in the ETP but also extended to the date line, thus inducing wind anomalies unfavorable for establishing the wind–evaporation–SST feedback for a negative PMM in the subtropics. To understand the discrepancy between the large negative PMMIs and weak PMM-related subtropical cooling during strong EP El Niño events, we isolate the relative contributions of subtropical and tropical SSTAs to the PMMIs by calculating their spatial projections on the PMM. Analysis combined using observation and CMIP6 models shows that despite the large contribution from subtropical SSTAs, the large tropical SSTAs, especially the extreme ETP warming, could cause large negative PMMIs during strong EP El Niño events even without strong, negative subtropical SSTAs. Our study clarifies the impact of ETP warming in causing a negative PMM and indicates the overstatement of negative PMMIs by tropical SSTAs during strong EP El Niño events. Significance Statement This paper aims to reevaluate the previously proposed effect of strong eastern Pacific El Niño events, like those in 1982/83 and 1997/98, on exciting a negative Pacific meridional mode (PMM). We find that although the PMM indices were strongly negative during the decay of strong eastern Pacific El Niño events, the large negative PMM sea surface temperature anomalies (SSTAs) could not be observed in the subtropical Pacific. Further diagnosis indicates that the PMM index can be large if strong SSTAs occur in eastern tropical Pacific even without subtropical SSTAs, implying that one should be careful when using the PMM index.

Wintertime sea surface temperature variability modulated by Arctic Oscillation in the northwestern part of the East/Japan Sea and its relationship with marine heatwaves

The northwestern part of the East/Japan Sea (EJS) is a region with large sea surface temperature (SST) variability and is known as a hotspot of marine heatwaves (MHW) stress for marine environments that peaked in boreal winter (January-February-March). This could have profound impacts on the marine ecosystems over the EJS. Here, we used a set of high-resolution satellite and reanalysis products to systematically analyze the spatiotemporal SST variations and examine their linkage to a large-scale mode of climate variability, such as the Arctic Oscillation (AO). The results show that AO-related wind forcing modulates the SST variability over the EJS via the oceanic dynamic adjustment processes. In particular, the abnormally warm SSTs in the northwestern part of the EJS are driven by the anomalous anticyclonic eddy-like circulation and Ekman downwelling during a positive AO phase. This physical linkage between a positive AO and the abnormally warm SST could be conducive to MHW occurrences in the EJS as in the extremely positive AO event during the winter of 2020. These results have implications that the MHW occurrences in the EJS could be amplified by natural climate variability along with long-term SST warming.

Multi-Scale Ship Detection Algorithm Based on YOLOv7 for Complex Scene SAR Images

Recently, deep learning techniques have been extensively used to detect ships in synthetic aperture radar (SAR) images. The majority of modern algorithms can achieve successful ship detection outcomes when working with multiple-scale ships on a large sea surface. However, there are still issues, such as missed detection and incorrect identification when performing multi-scale ship object detection operations in SAR images of complex scenes. To solve these problems, this paper proposes a complex scenes multi-scale ship detection model, according to YOLOv7, called CSD-YOLO. First, this paper suggests an SAS-FPN module that combines atrous spatial pyramid pooling and shuffle attention, allowing the model to focus on important information and ignore irrelevant information, reduce the feature loss of small ships, and simultaneously fuse the feature maps of ship targets on various SAR image scales, thereby improving detection accuracy and the model’s capacity to detect objects at several scales. The model’s optimization is then improved with the aid of the SIoU loss function. Finally, thorough tests on the HRSID and SSDD datasets are presented to support our methodology. CSD-YOLO achieves better detection performance than the baseline YOLOv7, with a 98.01% detection accuracy, a 96.18% recall, and a mean average precision (mAP) of 98.60% on SSDD. In addition, in comparative experiments with other deep learning-based methods, in terms of overall performance, CSD-YOLO still performs better.

Ocean Waves in Large‐Scale Air‐Sea Weather and Climate Systems

AbstractIn spite of massive efforts directed to development of climate models over recent decades, accurate climate simulations and prediction remain a grand challenge. Large sea surface temperature model bias is one of the key indicators of the problem, among others. Qiao and his team suggested the concept of surface wave‐induced turbulence and elaborated the way for such coupling, through turbulent processes at both sides of the air‐ocean interface. These are the wave mixing in the ocean and wave modulation of air‐sea fluxes. This wave‐ocean coupled approach led to essential improvements of performance of ocean circulation and climate models, essentially introducing the next generation of large‐scale air‐sea interaction models. This Commentary reviews three recent JGR publications where the Qiao theory was implemented. The first paper (Huang & Qiao, 2021; https://doi.org/10.1029/2020JC016839) reported that the momentum gain by the ocean could be larger than the wind stress input, due to the ocean waves. The second paper (Chen et al., 2022; https://doi.org/10.1029/2021JC018360) demonstrated that, also due to waves, the drag coefficients in the atmospheric boundary layer have a spatial asymmetry during tropical cyclones. The third paper (Zhao et al., 2022; https://doi.org/10.1029/2022JC019015), based on combination of wave‐coupled effects on both sides of air‐sea interface, demonstrates their impact on simulation of tropical cyclone intensity. All papers are based on unique in situ measurements and their data analysis. The Commentary is further used as an opportunity to outline and review the current state of the small‐large scale coupling topic with respect to ocean, weather and climate modeling.

Back-and-forth nudging for the quasi-geostrophic ocean dynamics with altimetry: Theoretical convergence study and numerical experiments with the future SWOT observations

<p style='text-indent:20px;'>In data assimilation for geophysical problems, the increasing amount of satellite data to analyze makes it more and more challenging to guarantee near real time forecasting. Thus, low time and memory consuming data assimilation methods become very attractive. The back-and-forth nudging (BFN) method is a non-classical data assimilation method that can be seen as a deterministic and smoothing version of the Kalman filter. From a practical point of view, the BFN method is very valuable for its simplicity of implementation (no optimization, no differentiation, ...) and its rapidity of convergence. Under observability conditions, we prove the mathematical convergence of BFN at deep layers for a multi-layer quasi-geostrophic (MQG) ocean circulation model using an infinite dimensional variant of LaSalle's invariance principle. We also extend the BFN to the problem of joint state-parameter identification. The numerical experiments, performed on 120km large swath sea surface height (SSH) simulated data of the Surface Water Ocean Topography (SWOT) satellite, show the high robustness of the algorithm to uncertainties and the few iterations needed to reach convergence, whereas some problems remain due to non-reversibility properties in time. We also give a strategy to improve geophysical model accuracy, considering the large number of uncertain parameters inherent to models and their impacts on state estimation performance. We propose here a joint state-parameter estimation, tested on the baroclinic wavenumber as an unobserved parameter.</p>

Arctic Ocean annual high in {{boldsymbol{p}}}_{{{bf{CO}}}_{{bf{2}}}} could shift from winter to summer

Long-term stress on marine organisms from ocean acidification will differ between seasons. As atmospheric carbon dioxide (CO2) increases, so do seasonal variations of ocean CO2 partial pressure ({p}_{{{rm{CO}}}_{2}}), causing summer and winter long-term trends to diverge1–5. Trends may be further influenced by an unexplored factor—changes in the seasonal timing of {p}_{{{rm{CO}}}_{2}}. In Arctic Ocean surface waters, the observed timing is typified by a winter high and summer low6 because biological effects dominate thermal effects. Here we show that 27 Earth system models simulate similar timing under historical forcing but generally project that the summer low, relative to the annual mean, eventually becomes a high across much of the Arctic Ocean under mid-to-high-level CO2 emissions scenarios. Often the greater increase in summer {p}_{{{rm{CO}}}_{2}}, although gradual, abruptly inverses the chronological order of the annual high and low, a phenomenon not previously seen in climate-related variables. The main cause is the large summer sea surface warming7 from earlier retreat of seasonal sea ice8. Warming and changes in other drivers enhance this century’s increase in extreme summer {p}_{{{rm{CO}}}_{2}} by 29 ± 9 per cent compared with no change in driver seasonalities. Thus the timing change worsens summer ocean acidification, which in turn may lower the tolerance of endemic marine organisms to increasing summer temperatures.

Modelled impact of ocean warming on tropical cyclone size and destructiveness over the Bay of Bengal: A case study on FANI cyclone

Ocean warming influences tropical cyclone (TC) destructive parameters and hence their guidance certainly helps the disaster management agencies to reduce the damage. The present study modelled the sensitivity of TC size, intensity, rainfall, and destructive potential parameters under various ocean warming conditions. A recent extremely severe cyclonic storm FANI (2019) over the Bay of Bengal is chosen for this purpose. The 9-km grid-spacing Weather Research and Forecasting (WRF) model simulations are performed by altering the default sea surface temperature (SST) by −1 °C, +1 °C, +2 °C and, +3 °C respectively along with the control run. The model simulations revealed that ocean warming causes the FANI cyclone to turn northeastward direction. The observed changes of tangential wind speed due to large sea surface enthalpy fluxes associated with ocean warming result in TC size changes and then guide the cyclone to northeastward movement. The radius of 34-knot wind (R34) is more sensitive to the SST warming compared to the radius of maximum winds. The modelled R34 values ranged between ~180–600 km against observations (~100–400 km) during the TC life period. The increased tangential wind speeds (~50–60 m s−1) and convective updrafts (~1.3–1.5 m s−1) in the TC area are responsible for TC intensity and size changes. A linear and exponential growth is seen for the TC destructive potential indicators those estimated using TC intensity and R34 values. The SST increase could result in peak heavy rainfall (>65 mm day−1) in the TC inner-core region, especially the rear sector. The categorical rainfall distribution analysis also proved that heavy rainfall areas extend to greater distances (>300 km) around the TC center with SST warming. The study helps in assessing the hydro-meteorological destruction associated with the TCs in the future warming climate.

Numerical Study of Circulation and Seasonal Variability in the Southwestern Yellow Sea

A nested-grid ocean circulation modelling system (NGMS-swYS) is used for examining the impact of tides and winds on the three-dimensional (3D) circulation, hydrography and seasonal variability over the southwestern Yellow Sea (swYS). The modelling system is based on the Princeton Ocean Model (POM) and uses a nested-grid setup, with a fine-resolution (~2.7 km) inner model nested inside a coarse-resolution (~9.0 km) outer model. The domain of the outer model covers the China Seas and adjacent deep ocean waters. The domain of the fine-resolution inner model covers the swYS and adjacent waters. The NGMS-swYS is driven by a suite of external forcings, including the atmospheric forcing, tides, freshwater discharge and currents specified at the lateral open boundaries. A comparison of model results with observations and previous numerical studies demonstrates the satisfactory performance of the NGMS-swYS in simulating tides, seasonal mean circulation and distribution of temperature and salinity. Five additional numerical experiments were conducted using NGMS-swYS with different combinations of external forcing. Analysis of model results demonstrates that the monthly mean circulation over the swYS is affected significantly by tides and winds, with large seasonal variability. The northward Subei Shoal Current occurred in both winter and summer months in 2015, with persistent strong southeastward mean currents induced by tides along the 50 m isobath. Model results also demonstrated that strong wind-induced currents occurred with large sea surface cooling during Typhoon Chan-Hom.

Composite Electromagnetic Scattering and High-Resolution SAR Imaging of Multiple Targets above Rough Surface

Aiming at the high efficiency of composite electromagnetic scattering analysis and radar target detection and recognition utilizing high-range resolution profile (HRRP) characteristics and high-resolution synthetic aperture radar (SAR) images, a near-field modified iterative physical optics and facet-based two-scale model for analysis of composite electromagnetic scattering from multiple targets above rough surface have been presented. In this method, the coupling scattering of multiple targets is calculated by near-field iterative physical optics and the far-field scattering is calculated by the physical optics method. For the evaluation of the scattering of an electrically large sea surface, a slope cutoff probability distribution function is introduced in the two-scale model. Moreover, a fast imaging method is introduced based on the proposed hybrid electromagnetic scattering method. The numerical results show the effectiveness of the proposed method, which can generate backscattering data accurately and obtain high-resolution SAR images. It is concluded that the proposed method has the advantages of accurate computation and good recognition performance.

Numerical modelling of wind-influenced above sea gas dispersion and explosion risk analysis due to subsea gas release on multileveled offshore platform

Above-sea gas dispersion due to subsea release could lead to explosion on nearby offshore facility. Less congested single-deck offshore platform has been considered in past for numerical modelling of above-sea gas dispersion and deflagration. Offshore platforms are designed compactly and comprise of multiple decks due to space restrictions. The approaching flammable gas may disperse differently at each deck, and high overpressures could develop in event of explosion in confined decks causing severe damages. Therefore, investigating effect of above-sea gas release and dispersion and resulting vapour cloud explosion on equipment damage and human fatality in complex multi-deck platform is worth investigating. This paper presents above-sea gas dispersion and explosion modelling on realistic multileveled fixed offshore platform under varying wind speeds using FLACS. Simplified steps are provided to model gas release from large area sea surface gas pool along with atmospheric dispersion and subsequent explosion in FLACS. It was found that generally, lower decks had near-stoichiometry concentrations thus being most susceptible to explosion consequences. High wind speed increased flammable cloud accumulation, where 50-60% of decks were filled at 3m/s wind speed whereas 100% filled under 7m/s. It is suggested to have adequate ventilation on lower platform decks specially under high wind circumstances to avoid possible explosion hazard due to cloud accumulation. Congested and confined regions with low flammable concentration produced more overpressure than the areas with same concentration but no or low congestion and confinement. Stoichiometric concentration together with congestion produced incredibly high localised overpressure reaching 3.55-4 barg. The probability of equipment damage and human fatality was reaching 1 for explosions at base and deck 2 under 7 m/s wind speed. Since roof was open, the probability of equipment damage and human fatality was least.

Different Responses of Central Asian Precipitation to Strong and Weak El Niño Events

AbstractThe present study investigated impacts of strong and weak El Niño events on central Asian precipitation variability from El Niño developing years to decaying years. It is found that strong El Niño events persistently enhance central Asian precipitation from the mature winter to decaying summer. Large warm sea surface temperature (SST) anomalies in the tropical central-eastern Pacific induce anomalous upper-level divergence and updraft over central Asia through large-scale convergence and divergence in the mature winter and decaying spring. Meanwhile, the associated wind anomalies induce anomalous eastward and northeastward moisture flux from the North Atlantic and the Arabian Sea to central Asia. Both anomalous ascent and moisture flux convergence favor above-normal precipitation over central Asia in the mature winter and decaying spring. The El Niño events induced central Asian precipitation anomalies that are extended to the decaying summer due to the role of soil moisture. Increased rainfall in winter and spring enhances soil moisture in the following summer, which in turn contributes to more precipitation in summer through modulating regional evaporation. During weak El Niño events, significant wet anomalies are only seen in the developing autumn, which result from anomalous southeastward moisture flux from the Arctic Ocean, and the abnormal signals are weak in the other seasons. The different responses of central Asian precipitation to strong and weak El Niño events may be attributed to the difference in intensity of tropical SST anomalies between the two types of events.

Interdecadal Changes in the Relationship between Wintertime Surface Air Temperature over the Indo-China Peninsula and ENSO

Abstract Interdecadal variations of the relationship between El Niño–Southern Oscillation (ENSO) and the Indo-China Peninsula (ICP) surface air temperature (SAT) in winter are investigated in the study. Generally, there exists a positive correlation between them during 1958–2015 because the ENSO-induced anomalous western North Pacific anticyclone (WNPAC) is conducive to pronounced temperature advection anomalies over the ICP. However, such correlation is unstable in time, having experienced a high-to-low transition around the mid-1970s and a recovery since the early 1990s. This oscillating relationship is owing to the anomalous WNPAC intensity in different decades. During the epoch of high correlation, the anomalous WNPAC and associated southwesterly winds over the ICP are stronger, which brings amounts of warm temperature advection and markedly heats the ICP. In contrast, a weaker WNPAC anomaly and insignificant ICP SAT anomalies are the circumstances for the epoch of low correlation. It is also found that substantial southwesterly wind anomalies over the ICP related to the anomalous WNPAC occur only when large sea surface temperature (SST) anomalies over the northwest Indian Ocean (NWIO) coincide with ENSO (viz., when the ENSO–NWIO SST connection is strong). The NWIO SST anomalies are capable of driving favorable atmospheric circulation that effectively alters ICP SAT and efficiently modulates the ENSO–ICP SAT correlation, which is further supported by numerical simulations utilizing the Community Atmospheric Model, version 4 (CAM4). This paper emphasizes the non-stationarity of the ENSO–ICP SAT relationship and also uncovers the underlying modulation factors, which has important implications for the seasonal prediction of the ICP temperature.

Facet-Based Hybrid Method for Electromagnetic Scattering From Shallow Water Waves Modulated by Submarine Topography

This article presents a mechanism model of synthetic aperture radar (SAR) remote sensing imaging of submarine topography in shallow areas. According to the shallow water effect and complex geographical factors, a 3-D geometric model of multiscale wave is generated by combining sea spectrum separation and phase superposition methods. It has the advantage of reflecting the random fluctuation characteristics of waves and the refraction phenomenon influenced by submarine topography. In addition, the modulation relationship among submarine topography, tidal current, and sea surface microroughness is established. This constitutes hydrodynamic modulation. The facet-based hybrid method that combines the geometry optics (GO) and the integral equation method (IEM) is adopted to solve the electromagnetic (EM) scattering of super electrically large sea surface. This contains tilt modulation. The effectiveness of the proposed model is demonstrated through the comparisons with the measured results. The influence of the parameters of radar, sea state, water depth, and tidal current direction on the scattering intensity of sea surface is studied as well. It is revealed that the shallower the water depth, the more significant the hydrodynamic and tilt effect. In addition, the velocity bunching (VB) modulation is a special modulation method in SAR imaging. According to the simulated results, the contributions of tilt, hydrodynamic, and VB modulation in SAR imaging mechanism are compared. The VB is the main factor, hydrodynamic is second, and tilt is the least.

Climate Process Team: Improvement of Ocean Component of NOAA Climate Forecast System Relevant to Madden‐Julian Oscillation Simulations

AbstractGiven the increasing attention in forecasting weather and climate on the subseasonal time scale in recent years, National Oceanic and Atmospheric Administration (NOAA) announced to support Climate Process Teams (CPTs) which aim to improve the Madden‐Julian Oscillation (MJO) prediction by NOAA’s global forecasting models. Our team supported by this CPT program focuses primarily on the improvement of upper ocean mixing parameterization and air‐sea fluxes in the NOAA Climate Forecast System (CFS). Major improvement includes the increase of the vertical resolution in the upper ocean and the implementation of General Ocean Turbulence Model (GOTM) in CFS. In addition to existing mixing schemes in GOTM, a newly developed scheme based on observations in the tropical ocean, with further modifications, has been included. A better performance of ocean component is demonstrated through one‐dimensional ocean model and ocean general circulation model simulations validated by the comparison with in‐situ observations. These include a large sea surface temperature (SST) diurnal cycle during the MJO suppressed phase, intraseasonal SST variations associated with the MJO, ocean response to atmospheric cold pools, and deep cycle turbulence. Impact of the high‐vertical resolution of ocean component on CFS simulation of MJO‐associated ocean temperature variations is evident. Also, the magnitude of SST changes caused by high‐resolution ocean component is sufficient to influence the skill of MJO prediction by CFS.

Application of Z-numbers to teleconnection modeling between monthly precipitation and large scale sea surface temperature

Abstract The teleconnection modeling of hydro-climatic events is a complex problem with highly uncertain circumstances. In contrast to the classic fuzzy logic methods, by using the Z-number in addition to the constraint of information, and by evaluating the data reliability, it is possible to characterize the degree of ambiguity of data. In this regard, this study investigates the performance of the Z-number-based model (ZBM) in prediction of classified monthly precipitation (MP) events of two synoptic stations in Iran (up to five months in advance). To this end, the sea surface temperature (SST) of adjacent seas was used as a predictor. The suggested model, by using Z-number directly and applying fuzzy Hausdorff distance to determine weights of if-then rules, predicted MP events of both the stations with over 70% confidence. Analysis of the results in the test step showed that the ZBM compared to the traditional fuzzy approach improved the results by 69% for Kermanshah and 112% for Tabriz. Overall, the Z-number concept by assessing events reliability can be used in various sectors of water resources management such as decision-making and drought monitoring.