Abstract. From both practical and theoretical perspectives, it is essential to be able to express observed salinity distributions in terms of simplified theoretical models, which enable qualitative assessments to be made in many problems concerning water resource utilization (such as intake of fresh water) in estuaries. In this study, we propose a general and analytical salt intrusion model inspired by Guo's general unit hydrograph theory for flood hydrograph prediction in a watershed. To derive a simple, general and analytical model of salinity distribution, we first make four hypotheses on the longitudinal salinity gradient based on empirical observations; we then derive a general unit hydrograph for the salinity distribution along a partially mixed or well-mixed estuary. The newly developed model can be well calibrated using a minimum of three salinity measurements along the estuary axis and does converge towards zero when the along-estuary distance approaches infinity asymptotically. The theory has been successfully applied to reproduce the salt intrusion in 21 estuaries worldwide, which suggests that the proposed method can be a useful tool for quickly assessing the spread of salinity under a wide range of riverine and tidal conditions and for quantifying the potential impacts of human-induced and natural changes.
{"title":"Extension of the general unit hydrograph theory for the spread of salinity in estuaries","authors":"H. Cai, Bo Li, Junhao Gu, T. Zhao, E. Garel","doi":"10.5194/os-19-603-2023","DOIUrl":"https://doi.org/10.5194/os-19-603-2023","url":null,"abstract":"Abstract. From both practical and theoretical perspectives, it is\u0000essential to be able to express observed salinity distributions in terms of\u0000simplified theoretical models, which enable qualitative assessments to be\u0000made in many problems concerning water resource utilization (such as intake\u0000of fresh water) in estuaries. In this study, we propose a general and\u0000analytical salt intrusion model inspired by Guo's general unit hydrograph\u0000theory for flood hydrograph prediction in a watershed. To derive a simple,\u0000general and analytical model of salinity distribution, we first make four\u0000hypotheses on the longitudinal salinity gradient based on empirical\u0000observations; we then derive a general unit hydrograph for the salinity\u0000distribution along a partially mixed or well-mixed estuary. The newly\u0000developed model can be well calibrated using a minimum of three salinity\u0000measurements along the estuary axis and does converge towards zero when the\u0000along-estuary distance approaches infinity asymptotically. The theory has\u0000been successfully applied to reproduce the salt intrusion in 21 estuaries\u0000worldwide, which suggests that the proposed method can be a useful tool for\u0000quickly assessing the spread of salinity under a wide range of riverine and\u0000tidal conditions and for quantifying the potential impacts of\u0000human-induced and natural changes.\u0000","PeriodicalId":19535,"journal":{"name":"Ocean Science","volume":"74 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2023-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80674058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract. Mixed-layer depth (MLD) exhibits significant variability, which is important for atmosphere–ocean exchanges of heat and atmospheric gases. The origins of the mesoscale MLD variability in the Southern Ocean are studied here in an idealised regional ocean–atmosphere model (ROAM). The main conclusion from the analysis of the upper-ocean buoyancy budget is that, while the atmospheric forcing and oceanic vertical mixing, on average, induce the mesoscale variability of MLD, the three-dimensional oceanic advection of buoyancy counteracts and partially balances these atmosphere-induced vertical processes. The relative importance of advection changes with both season and average MLD. From January to May, when the mixed layer is shallow, the atmospheric forcing and oceanic mixing are the most important processes, with the advection playing a secondary role. From June to December, when the mixed layer is deep, both atmospheric forcing and oceanic advection are equally important in driving the MLD variability. Importantly, buoyancy advection by mesoscale ocean current anomalies can lead to both local shoaling and deepening of the mixed layer. The role of the atmospheric forcing is then directly addressed by two sensitivity experiments in which the mesoscale variability is removed from the atmosphere–ocean heat and momentum fluxes. The findings confirm that mesoscale atmospheric forcing predominantly controls MLD variability in summer and that intrinsic oceanic variability and surface forcing are equally important in winter. As a result, MLD variance increases when mesoscale anomalies in atmospheric fluxes are removed in winter, and oceanic advection becomes a dominant player in the buoyancy budget. This study highlights the importance of oceanic advection and intrinsic ocean dynamics in driving mesoscale MLD variability and underscores the importance of MLD in modulating the effects of advection on upper-ocean dynamics.
{"title":"Origins of mesoscale mixed-layer depth variability in the Southern Ocean","authors":"Yu Gao, I. Kamenkovich, Natalie Perlin","doi":"10.5194/os-19-615-2023","DOIUrl":"https://doi.org/10.5194/os-19-615-2023","url":null,"abstract":"Abstract. Mixed-layer depth (MLD) exhibits significant variability, which is important for atmosphere–ocean exchanges of heat and atmospheric gases. The origins of the mesoscale MLD variability in the Southern Ocean are studied here in an idealised regional ocean–atmosphere model (ROAM). The main conclusion from the analysis of the upper-ocean buoyancy budget is that, while the atmospheric forcing and oceanic vertical mixing, on average, induce the mesoscale variability of MLD, the three-dimensional oceanic advection of buoyancy counteracts and partially balances these atmosphere-induced vertical processes. The relative importance of advection changes with both season and average MLD. From January to May, when the mixed layer is shallow, the atmospheric forcing and oceanic mixing are the most important processes, with the advection playing a secondary role. From June to December, when the mixed layer is deep, both atmospheric forcing and oceanic advection are equally important in driving the MLD variability. Importantly, buoyancy advection by mesoscale ocean current anomalies can lead to both local shoaling and deepening of the mixed layer. The role of the atmospheric forcing is then directly addressed by two sensitivity experiments in which the mesoscale variability is removed from the atmosphere–ocean heat and momentum fluxes. The findings confirm that mesoscale atmospheric forcing predominantly controls MLD variability in summer and that intrinsic oceanic variability and surface forcing are equally important in winter. As a result, MLD variance increases when mesoscale anomalies in atmospheric fluxes are removed in winter, and oceanic advection becomes a dominant player in the buoyancy budget. This study highlights the importance of oceanic advection and intrinsic ocean dynamics in driving mesoscale MLD variability and underscores the importance of MLD in modulating the effects of advection on upper-ocean dynamics.\u0000","PeriodicalId":19535,"journal":{"name":"Ocean Science","volume":"49 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2023-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79655514","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
P Brandt, G. Alory, F. M. Awo, M. Dengler, S. Djakouré, Rodrigue Anicet Imbol Koungue, J. Jouanno, Mareike Körner, Marisa Roch, M. Rouault
Abstract. In this paper, we review observational and modelling results on the upwelling in the tropical Atlantic between 10∘ N and 20∘ S. We focus on the physical processes that drive the seasonal variability of surface cooling and the upward nutrient flux required to explain the seasonality of biological productivity. We separately consider the equatorial upwelling system, the coastal upwelling system of the Gulf of Guinea and the tropical Angolan upwelling system. All three tropical Atlantic upwelling systems have in common a strong seasonal cycle, with peak biological productivity during boreal summer. However, the physical processes driving the upwelling vary between the three systems. For the equatorial regime, we discuss the wind forcing of upwelling velocity and turbulent mixing, as well as the underlying dynamics responsible for thermocline movements and current structure. The coastal upwelling system in the Gulf of Guinea is located along its northern boundary and is driven by both local and remote forcing. Particular emphasis is placed on the Guinea Current, its separation from the coast and the shape of the coastline. For the tropical Angolan upwelling, we show that this system is not driven by local winds but instead results from the combined effect of coastally trapped waves, surface heat and freshwater fluxes, and turbulent mixing. Finally, we review recent changes in the upwelling systems associated with climate variability and global warming and address possible responses of upwelling systems in future scenarios.
{"title":"Physical processes and biological productivity in the upwelling regions of the tropical Atlantic","authors":"P Brandt, G. Alory, F. M. Awo, M. Dengler, S. Djakouré, Rodrigue Anicet Imbol Koungue, J. Jouanno, Mareike Körner, Marisa Roch, M. Rouault","doi":"10.5194/os-19-581-2023","DOIUrl":"https://doi.org/10.5194/os-19-581-2023","url":null,"abstract":"Abstract. In this paper, we review observational and modelling results on the\u0000upwelling in the tropical Atlantic between 10∘ N and 20∘ S. We focus on the physical processes that drive the seasonal variability of\u0000surface cooling and the upward nutrient flux required to explain the seasonality\u0000of biological productivity. We separately consider the equatorial upwelling\u0000system, the coastal upwelling system of the Gulf of Guinea and the tropical\u0000Angolan upwelling system. All three tropical Atlantic upwelling systems have\u0000in common a strong seasonal cycle, with peak biological productivity during\u0000boreal summer. However, the physical processes driving the upwelling vary\u0000between the three systems. For the equatorial regime, we discuss the wind\u0000forcing of upwelling velocity and turbulent mixing, as well as the underlying\u0000dynamics responsible for thermocline movements and current structure. The\u0000coastal upwelling system in the Gulf of Guinea is located along its northern\u0000boundary and is driven by both local and remote forcing. Particular emphasis\u0000is placed on the Guinea Current, its separation from the coast and the shape\u0000of the coastline. For the tropical Angolan upwelling, we show that this\u0000system is not driven by local winds but instead results from the combined\u0000effect of coastally trapped waves, surface heat and freshwater fluxes, and\u0000turbulent mixing. Finally, we review recent changes in the upwelling systems\u0000associated with climate variability and global warming and address possible\u0000responses of upwelling systems in future scenarios.\u0000","PeriodicalId":19535,"journal":{"name":"Ocean Science","volume":"3 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2023-05-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79595636","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Bajo, C. Ferrarin, G. Umgiesser, A. Bonometto, E. Coraci
Abstract. This paper analyses the variability of the sea level barotropic components in the Mediterranean Sea and their reproduction using a hydrodynamic model with and without data assimilation. The impact of data assimilation is considered both in reanalysis and short-forecast simulations. We used a two-dimensional finite element model paired with an ensemble Kalman filter, which assimilated hourly sea level data from 50 stations in the Mediterranean basin. The results brought about a significant improvement given by data assimilation in the reanalysis of the astronomical tide, the surge, and the barotropic total sea level, even in coastal areas and far from the assimilated stations (e.g. the southeastern Mediterranean Sea). As with the reanalysis simulations, the forecast simulations, which start from analysis states, improve, especially on the first day (37 % average error reduction) and when seiche oscillations are triggered. Since seiches are free barotropic oscillations that depend only on the initial state, their reproduction improves very effectively with data assimilation. Finally, we estimate the periods and the energy of these oscillations by means of spectral analysis, both in the Adriatic Sea, where they have been extensively studied, and in the Mediterranean Sea, where the present documentation is scarce. While the periods are well reproduced by the model even without data assimilation, their energy shows a good improvement when using it.
{"title":"Modelling the barotropic sea level in the Mediterranean Sea using data assimilation","authors":"M. Bajo, C. Ferrarin, G. Umgiesser, A. Bonometto, E. Coraci","doi":"10.5194/os-19-559-2023","DOIUrl":"https://doi.org/10.5194/os-19-559-2023","url":null,"abstract":"Abstract. This paper analyses the variability of the sea level barotropic components in the Mediterranean Sea and their\u0000reproduction using a hydrodynamic model with and without data assimilation.\u0000The impact of data assimilation is considered both in reanalysis and short-forecast simulations.\u0000We used a two-dimensional finite element model paired with an ensemble Kalman\u0000filter, which assimilated hourly sea level data from 50 stations in the Mediterranean basin. The\u0000results brought about a significant improvement given by data assimilation in the reanalysis of\u0000the astronomical tide, the surge, and the barotropic total sea level, even in coastal areas\u0000and far from the assimilated stations (e.g. the southeastern Mediterranean Sea).\u0000As with the reanalysis simulations, the forecast simulations, which start from analysis states,\u0000improve, especially on the first day (37 % average error reduction) and when\u0000seiche oscillations are triggered.\u0000Since seiches are free barotropic oscillations that depend only on the initial state, their\u0000reproduction improves very effectively with data assimilation. Finally, we estimate the\u0000periods and the energy of these oscillations by means of spectral analysis, both in the Adriatic Sea,\u0000where they have been extensively studied, and in the Mediterranean Sea, where the present\u0000documentation is scarce. While the periods are well reproduced by the model even without\u0000data assimilation, their energy shows a good improvement when using it.\u0000","PeriodicalId":19535,"journal":{"name":"Ocean Science","volume":"22 3 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2023-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77822810","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
R. D. Ngakala, G. Alory, C. Da-Allada, Olivia Estelle Kom, Julien, Jouanno, W. Rath, E. Baloïtcha
Abstract. In this study, we use a joint observation–model approach to investigate the mixed-layer heat and salt annual mean as well as seasonal budgets in the eastern tropical Atlantic. The regional PREFCLIM (PREFACE Climatology) observational climatology provides the budget terms with a relatively low spatial and temporal resolution compared to the online NEMO (Nucleus for European Modeling of the Ocean; Madec, G., 2014) model, and this is later resampled as in PREFCLIM climatology. In addition, advection terms are recomputed offline from the model as PREFCLIM gridded advection computation. In the Senegal, Angola, and Benguela regions, the seasonal cycle of mixed-layer temperature is mainly governed by surface heat fluxes; however, it is essentially driven by vertical heat diffusion in the equatorial region. The seasonal cycle of mixed-layer salinity is largely controlled by freshwater flux in the Senegal and Benguela regions; however, it follows the variability of zonal and meridional salt advection in the equatorial and Angola regions, respectively. Our results show that the time-averaged spatial distribution of NEMO offline heat and salt advection terms compares much better to PREFCLIM horizontal advection terms than the online heat and salt advection terms. However, the seasonal cycle of horizontal advection in selected regions shows that NEMO offline terms do not always compare well with PREFCLIM, sometimes less than online terms. Despite this difference, these results suggest the important role of small-scale variability in mixed-layer heat and salt budgets.
摘要在这项研究中，我们使用联合观测模型方法研究了热带大西洋东部混合层的年平均和季节收支。与在线的NEMO (Nucleus for European Modelingof Ocean)相比，区域性的PREFCLIM(前言气候学)观测气候学提供的预算项具有相对较低的空间和时间分辨率。Madec, G.， 2014)模型，然后像在PREFCLIM气候学中那样重新采样。此外，从模型中离线重新计算平流项作为PREFCLIM网格平流计算。在塞内加尔、安哥拉和本格拉地区，混合层温度的季节周期主要受地表热通量的支配;然而，它本质上是由赤道地区的垂直热扩散驱动的。塞内加尔和本格拉地区混合层盐度的季节循环主要受淡水通量控制;然而，它遵循赤道和安哥拉地区纬向和经向盐平流的变率。结果表明，NEMO离线热盐平流项的时间平均空间分布优于PREFCLIM水平平流项，而不是在线热盐平流项。然而，选定地区水平平流的季节周期表明，NEMO离线项并不总是与prefclim相比较，有时不如在线项。尽管存在这种差异，但这些结果表明，小尺度变化在混合层热盐收支中发挥了重要作用。
{"title":"Joint observation–model mixed-layer heat and salt budgets in the eastern tropical Atlantic","authors":"R. D. Ngakala, G. Alory, C. Da-Allada, Olivia Estelle Kom, Julien, Jouanno, W. Rath, E. Baloïtcha","doi":"10.5194/os-19-535-2023","DOIUrl":"https://doi.org/10.5194/os-19-535-2023","url":null,"abstract":"Abstract. In this study, we use a joint observation–model approach\u0000to investigate the mixed-layer heat and salt annual mean as well as seasonal\u0000budgets in the eastern tropical Atlantic. The regional PREFCLIM (PREFACE Climatology)\u0000observational climatology provides the budget terms with a relatively low\u0000spatial and temporal resolution compared to the online NEMO (Nucleus for European Modeling\u0000of the Ocean; Madec, G., 2014) model, and this\u0000is later resampled as in PREFCLIM climatology. In addition, advection\u0000terms are recomputed offline from the model as PREFCLIM gridded advection\u0000computation. In the Senegal, Angola, and Benguela regions, the seasonal cycle of\u0000mixed-layer temperature is mainly governed by surface heat fluxes; however,\u0000it is essentially driven by vertical heat diffusion in the equatorial region.\u0000The seasonal cycle of mixed-layer salinity is largely controlled by\u0000freshwater flux in the Senegal and Benguela regions; however, it follows the\u0000variability of zonal and meridional salt advection in the equatorial and Angola\u0000regions, respectively. Our results show that the time-averaged spatial\u0000distribution of NEMO offline heat and salt advection terms compares much better\u0000to PREFCLIM horizontal advection terms than the online heat and salt advection\u0000terms. However, the seasonal cycle of horizontal advection in selected\u0000regions shows that NEMO offline terms do not always compare well with\u0000PREFCLIM, sometimes less than online terms. Despite this difference, these\u0000results suggest the important role of small-scale variability in mixed-layer\u0000heat and salt budgets.\u0000","PeriodicalId":19535,"journal":{"name":"Ocean Science","volume":"79 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90465785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract. The eruption of the Hunga Tonga-Hunga Ha'apai volcano on 15 January 2022 provided a rare opportunity to understand global tsunami impacts of explosive volcanism and to evaluate future hazards, including dangers from “volcanic meteotsunamis” (VMTs) induced by the atmospheric shock waves that followed the eruption. The propagation of the volcanic and marine tsunamis was analyzed using globally distributed 1 min measurements of air pressure and water level (WL) (from both tide gauges and deep-water buoys). The marine tsunami propagated primarily throughout the Pacific, reaching nearly 2 m at some locations, though most Pacific locations recorded maximums lower than 1 m. However, the VMT resulting from the atmospheric shock wave arrived before the marine tsunami and propagated globally, producing water level perturbations in the Indian Ocean, the Mediterranean, and the Caribbean. The resulting water level response of many Pacific Rim gauges was amplified, likely related to wave interaction with bathymetry. The meteotsunami repeatedly boosted tsunami wave energy as it circled the planet several times. In some locations, the VMT was amplified by as much as 35-fold relative to the inverse barometer due to near-Proudman resonance and topographic effects. Thus, a meteotsunami from a larger eruption (such as the Krakatoa eruption of 1883) could yield atmospheric pressure changes of 10 to 30 mb, yielding a 3–10 m near-field tsunami that would occur in advance of (usually) larger marine tsunami waves, posing additional hazards to local populations. Present tsunami warning systems do not consider this threat.
{"title":"Global water level variability observed after the Hunga Tonga-Hunga Ha'apai volcanic tsunami of 2022","authors":"A. Devlin, D. Jay, S. Talke, Jiayi Pan","doi":"10.5194/os-19-517-2023","DOIUrl":"https://doi.org/10.5194/os-19-517-2023","url":null,"abstract":"Abstract. The eruption of the Hunga Tonga-Hunga Ha'apai volcano on 15 January 2022 provided a rare opportunity to understand global tsunami\u0000impacts of explosive volcanism and to evaluate future hazards, including\u0000dangers from “volcanic meteotsunamis” (VMTs) induced by the atmospheric\u0000shock waves that followed the eruption. The propagation of the volcanic and\u0000marine tsunamis was analyzed using globally distributed 1 min measurements\u0000of air pressure and water level (WL) (from both tide gauges and deep-water\u0000buoys). The marine tsunami propagated primarily throughout the Pacific,\u0000reaching nearly 2 m at some locations, though most Pacific locations\u0000recorded maximums lower than 1 m. However, the VMT resulting from the\u0000atmospheric shock wave arrived before the marine tsunami and propagated\u0000globally, producing water level perturbations in the Indian Ocean, the\u0000Mediterranean, and the Caribbean. The resulting water level response of many\u0000Pacific Rim gauges was amplified, likely related to wave interaction with\u0000bathymetry. The meteotsunami repeatedly boosted tsunami wave energy as it\u0000circled the planet several times. In some locations, the VMT was amplified\u0000by as much as 35-fold relative to the inverse barometer due to near-Proudman\u0000resonance and topographic effects. Thus, a meteotsunami from a larger\u0000eruption (such as the Krakatoa eruption of 1883) could yield atmospheric\u0000pressure changes of 10 to 30 mb, yielding a 3–10 m near-field tsunami that\u0000would occur in advance of (usually) larger marine tsunami waves, posing\u0000additional hazards to local populations. Present tsunami warning systems do\u0000not consider this threat.\u0000","PeriodicalId":19535,"journal":{"name":"Ocean Science","volume":"1 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2023-04-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82032049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract. In this work, we explore the performance of a statistical forecasting system for marine-litter concentration in the Mediterranean Sea. In particular, we assess the potential skills of a system based on the analogues method. The system uses a historical database of marine-litter concentration simulated by a high-resolution realistic model and is trained to identify meteorological situations in the past that are similar to the forecasted ones. Then, the corresponding marine-litter concentrations of the past analogue days are used to construct the marine-litter concentration forecast. Due to the scarcity of observations, the forecasting system has been validated against a synthetic reality (i.e., the outputs from a marine-litter-modeling system). Different approaches have been tested to refine the system, and the results show that using integral definitions for the similarity function, based on the history of the meteorological situation, improves the system performance. We also find that the system accuracy depends on the domain of application being better for larger regions. Also, the method performs well in capturing the spatial patterns but performs worse in capturing the temporal variability, especially the extreme values. Despite the inherent limitations of using a synthetic reality to validate the system, the results are promising, and the approach has potential to become a suitable cost-effective forecasting method for marine-litter concentration.
{"title":"An analogues-based forecasting system for Mediterranean marine-litter concentration","authors":"G. Jordà, J. Soto‐Navarro","doi":"10.5194/os-19-485-2023","DOIUrl":"https://doi.org/10.5194/os-19-485-2023","url":null,"abstract":"Abstract. In this work, we explore the performance of a statistical forecasting system\u0000for marine-litter concentration in the Mediterranean Sea. In particular, we\u0000assess the potential skills of a system based on the analogues method. The\u0000system uses a historical database of marine-litter concentration simulated\u0000by a high-resolution realistic model and is trained to identify\u0000meteorological situations in the past that are similar to the forecasted\u0000ones. Then, the corresponding marine-litter concentrations of the past\u0000analogue days are used to construct the marine-litter concentration\u0000forecast. Due to the scarcity of observations, the forecasting system has\u0000been validated against a synthetic reality (i.e., the outputs from a marine-litter-modeling system). Different approaches have been tested to refine\u0000the system, and the results show that using integral definitions for the\u0000similarity function, based on the history of the meteorological situation,\u0000improves the system performance. We also find that the system accuracy\u0000depends on the domain of application being better for larger regions. Also,\u0000the method performs well in capturing the spatial patterns but performs worse\u0000in capturing the temporal variability, especially the extreme values. Despite\u0000the inherent limitations of using a synthetic reality to validate the\u0000system, the results are promising, and the approach has potential to become a\u0000suitable cost-effective forecasting method for marine-litter concentration.\u0000","PeriodicalId":19535,"journal":{"name":"Ocean Science","volume":"1 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85579146","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Víctor Malagón-Santos, A. Slangen, T. Hermans, Sönke Dangendorf, M. Marcos, N. Maher
Abstract. Regional emulation tools based on statistical relationships, such as pattern scaling, provide a computationally inexpensive way of projecting ocean dynamic sea-level change for a broad range of climate change scenarios. Such approaches usually require a careful selection of one or more predictor variables of climate change so that the statistical model is properly optimized. Even when appropriate predictors have been selected, spatiotemporal oscillations driven by internal climate variability can be a large source of statistical model error. Using pattern recognition techniques that exploit spatial covariance information can effectively reduce internal variability in simulations of ocean dynamic sea level, significantly reducing random errors in regional emulation tools. Here, we test two pattern recognition methods based on empirical orthogonal functions (EOFs), namely signal-to-noise maximizing EOF pattern filtering and low-frequency component analysis, for their ability to reduce errors in pattern scaling of ocean dynamic sea-level change. We use the Max Planck Institute Grand Ensemble (MPI-GE) as a test bed for both methods, as it is a type of initial-condition large ensemble designed for an optimal characterization of the externally forced response. We show that the two methods tested here more efficiently reduce errors than conventional approaches such as a simple ensemble average. For instance, filtering only two realizations by characterizing their common response to external forcing reduces the random error by almost 60 %, a reduction that is only achieved by averaging at least 12 realizations. We further investigate the applicability of both methods to single-realization modeling experiments, including four CMIP5 simulations for comparison with previous regional emulation analyses. Pattern filtering leads to a varying degree of error reduction depending on the model and scenario, ranging from more than 20 % to about 70 % reduction in global-mean root mean squared error compared with unfiltered simulations. Our results highlight the relevance of pattern recognition methods as a tool to reduce errors in regional emulation tools of ocean dynamic sea-level change, especially when one or only a few realizations are available. Removing internal variability prior to tuning regional emulation tools can optimize the performance of the statistical model, leading to substantial differences in emulated dynamic sea level compared to unfiltered simulations.
{"title":"Improving statistical projections of ocean dynamic sea-level change using pattern recognition techniques","authors":"Víctor Malagón-Santos, A. Slangen, T. Hermans, Sönke Dangendorf, M. Marcos, N. Maher","doi":"10.5194/os-19-499-2023","DOIUrl":"https://doi.org/10.5194/os-19-499-2023","url":null,"abstract":"Abstract. Regional emulation tools based on statistical relationships, such as pattern scaling, provide a computationally inexpensive way of projecting ocean\u0000dynamic sea-level change for a broad range of climate change scenarios. Such approaches usually require a careful selection of one or more predictor\u0000variables of climate change so that the statistical model is properly optimized. Even when appropriate predictors have been selected, spatiotemporal\u0000oscillations driven by internal climate variability can be a large source of statistical model error. Using pattern recognition techniques that\u0000exploit spatial covariance information can effectively reduce internal variability in simulations of ocean dynamic sea level, significantly reducing\u0000random errors in regional emulation tools. Here, we test two pattern recognition methods based on empirical orthogonal functions (EOFs), namely\u0000signal-to-noise maximizing EOF pattern filtering and low-frequency component analysis, for their ability to reduce errors in pattern scaling of\u0000ocean dynamic sea-level change. We use the Max Planck Institute Grand Ensemble (MPI-GE) as a test bed for both methods, as it is a type of\u0000initial-condition large ensemble designed for an optimal characterization of the externally forced response. We show that the two methods tested\u0000here more efficiently reduce errors than conventional approaches such as a simple ensemble average. For instance, filtering only two realizations by\u0000characterizing their common response to external forcing reduces the random error by almost 60 %, a reduction that is only achieved by averaging\u0000at least 12 realizations. We further investigate the applicability of both methods to single-realization modeling experiments, including four CMIP5\u0000simulations for comparison with previous regional emulation analyses. Pattern filtering leads to a varying degree of error reduction depending on\u0000the model and scenario, ranging from more than 20 % to about 70 % reduction in global-mean root mean squared error compared with unfiltered\u0000simulations. Our results highlight the relevance of pattern recognition methods as a tool to reduce errors in regional emulation tools of ocean\u0000dynamic sea-level change, especially when one or only a few realizations are available. Removing internal variability prior to tuning regional\u0000emulation tools can optimize the performance of the statistical model, leading to substantial differences in emulated dynamic sea level compared to\u0000unfiltered simulations.\u0000","PeriodicalId":19535,"journal":{"name":"Ocean Science","volume":"15 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84277999","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Junyi Li, Min Li, Chao Wang, Q. Zheng, Ying Xu, Tianyu Zhang, L. Xie
Abstract. Using satellite observations from 2003 to 2020 and cruise observations from 2019 and 2021, this study reveals an unexpected minor role of upwelling in seasonal and interannual variations in chlorophyll a (Chl a) concentrations in the coastal upwelling region east of Hainan Island (UEH) in the northwestern South China Sea (NWSCS). The results show strong seasonal and interannual variability in the Chl a concentration in the core upwelling area of the UEH. Different from the strongest upwelling in summer, the Chl a concentration in the UEH area reaches a maximum of 1.18 mg m−3 in autumn and winter, with a minimum value of 0.74 mg m−3 in summer. The Chl a concentration in summer increases to as high as 1.0 mg m−3 with weak upwelling, whereas the maximum Chl a concentration in October increases to 2.5 mg m−3. The analysis of environmental factors shows that, compared to the limited effects of upwelling, the along-shelf coastal current from the northern shelf and the increased precipitation are crucially important to the Chl a concentration variation in the study area. These results provide new insights for predicting marine productivity in upwelling areas, i.e., multiple mechanisms, especially horizontal advection, should be considered in addition to the upwelling process.
{"title":"Multiple mechanisms for chlorophyll a concentration variations in coastal upwelling regions: a case study east of Hainan Island in the South China Sea","authors":"Junyi Li, Min Li, Chao Wang, Q. Zheng, Ying Xu, Tianyu Zhang, L. Xie","doi":"10.5194/os-19-469-2023","DOIUrl":"https://doi.org/10.5194/os-19-469-2023","url":null,"abstract":"Abstract. Using satellite observations from 2003 to 2020 and cruise\u0000observations from 2019 and 2021, this study reveals an unexpected minor role\u0000of upwelling in seasonal and interannual variations in chlorophyll a (Chl a)\u0000concentrations in the coastal upwelling region east of Hainan Island (UEH)\u0000in the northwestern South China Sea (NWSCS). The results show strong\u0000seasonal and interannual variability in the Chl a concentration in the core\u0000upwelling area of the UEH. Different from the strongest upwelling in summer,\u0000the Chl a concentration in the UEH area reaches a maximum of 1.18 mg m−3\u0000in autumn and winter, with a minimum value of 0.74 mg m−3 in summer.\u0000The Chl a concentration in summer increases to as high as 1.0 mg m−3 with\u0000weak upwelling, whereas the maximum Chl a concentration in October increases\u0000to 2.5 mg m−3. The analysis of environmental factors shows that,\u0000compared to the limited effects of upwelling, the along-shelf coastal\u0000current from the northern shelf and the increased precipitation are\u0000crucially important to the Chl a concentration variation in the study area.\u0000These results provide new insights for predicting marine productivity in\u0000upwelling areas, i.e., multiple mechanisms, especially horizontal advection,\u0000should be considered in addition to the upwelling process.\u0000","PeriodicalId":19535,"journal":{"name":"Ocean Science","volume":"24 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81678959","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A. Guerou, B. Meyssignac, P. Prandi, M. Ablain, A. Ribes, F. Bignalet-Cazalet
Abstract. We present the latest release of the global mean sea level (GMSL) record produced by the French space agency Centre National d’Etudes Spatiales (CNES) and distributed on the AVISO+ website. This dataset is based on reprocessed along-track data, so-called L2P 21, of the reference missions TOPEX/Poseidon (TP) and Jason-1, Jason-2 and Jason-3. The L2P 21 CNES/AVISO+ GMSL record covers the period January 1993 to December 2021 and is now delivered with an estimate of its measurement uncertainties following the method presented in Ablain et al. (2019). Based on the latest calibration (Cal) and validation (Val) knowledge, we updated the uncertainty budget of the reference altimetry mission measurements and demonstrate that the CNES/AVISO+ GMSL record now achieves stability of performances of ± 0.3 mm yr−1 at the 90 % confidence level (C.L.) for its trend and ±0.05 mm yr−2 (90 % C.L.) for its acceleration over the 29 years of the altimetry record. Thanks to an analysis of the relative contribution of each measurement uncertainty budget contributor, i.e. the altimeter, the radiometer, the orbit determination and the geophysical corrections, we identified the current limiting factors to the GMSL monitoring stability and accuracy. We find that the radiometer wet troposphere correction (WTC) and the high-frequency errors with timescales shorter than 1 year are the major contributors to the GMSL measurement uncertainty over periods of 10 years (30 %–70 %), for both the trend and acceleration estimations. For longer periods of 20 years, the TP data quality is still a limitation, but more interestingly, the International Terrestrial Reference Frame (ITRF) realization uncertainties becomes dominant over all the other sources of uncertainty. Such a finding challenges the altimetry observing system as it is designed today and highlights clear topics of research to be explored in the future to help the altimetry community to improve the GMSL measurement accuracy and stability.
摘要我们介绍由法国国家空间研究中心(CNES)制作的全球平均海平面(GMSL)记录的最新版本，并在AVISO+网站上发布。这个数据集是基于参考任务TOPEX/Poseidon (TP)和Jason-1、Jason-2和Jason-3的所谓L2P 21的重新处理的沿轨道数据。L2P 21 CNES/AVISO+ GMSL记录涵盖了1993年1月至2021年12月，现在根据Ablain等人(2019)提出的方法提供了其测量不确定度的估计。基于最新的校准(Cal)和验证(Val)知识，我们更新了参考测高任务测量的不确定度预算，并证明CNES/AVISO+ GMSL记录在其趋势的90%置信水平(C.L.)和加速度的±0.05 mm yr−2 (90% C.L.)下的稳定性达到了±0.3 mm yr−2。通过对高度计、辐射计、定轨和地球物理校正等测量不确定度预算贡献者的相对贡献分析，确定了当前限制GMSL监测稳定性和精度的因素。我们发现，在10年的时间尺度上，无论是趋势估计还是加速度估计，辐射计对流层湿校正(WTC)和短于1年的高频误差是造成GMSL测量不确定性的主要因素(30% - 70%)。在较长的20年期间，TP数据质量仍然是一个限制，但更有趣的是，国际地面参考框架(ITRF)实现的不确定性在所有其他不确定性来源中占主导地位。这一发现对当今设计的高度计观测系统提出了挑战，并突出了未来需要探索的明确研究课题，以帮助高度计界提高GMSL测量精度和稳定性。
{"title":"Current observed global mean sea level rise and acceleration estimated from satellite altimetry and the associated measurement uncertainty","authors":"A. Guerou, B. Meyssignac, P. Prandi, M. Ablain, A. Ribes, F. Bignalet-Cazalet","doi":"10.5194/os-19-431-2023","DOIUrl":"https://doi.org/10.5194/os-19-431-2023","url":null,"abstract":"Abstract. We present the latest release of the global mean sea level (GMSL) record produced by the French space agency Centre National d’Etudes Spatiales (CNES) and distributed on the AVISO+ website. This dataset is based on reprocessed along-track data, so-called L2P 21, of the reference missions TOPEX/Poseidon (TP) and Jason-1, Jason-2 and Jason-3. The L2P 21 CNES/AVISO+ GMSL record covers the period January 1993 to December 2021 and is now delivered with an estimate of its measurement uncertainties following the method presented in Ablain et al. (2019). Based on the latest calibration (Cal) and validation (Val) knowledge, we updated the uncertainty budget of the reference altimetry mission measurements and demonstrate that the CNES/AVISO+ GMSL record now achieves stability of performances of ± 0.3 mm yr−1 at the 90 % confidence level (C.L.) for its trend and ±0.05 mm yr−2 (90 % C.L.) for its acceleration over the 29 years of the altimetry record. Thanks to an analysis of the relative contribution of each measurement uncertainty budget contributor, i.e. the altimeter, the radiometer, the orbit determination and the geophysical corrections, we identified the current limiting factors to the GMSL monitoring stability and accuracy. We find that the radiometer wet troposphere correction (WTC) and the high-frequency errors with timescales shorter than 1 year are the major contributors to the GMSL measurement uncertainty over periods of 10 years (30 %–70 %), for both the trend and acceleration estimations. For longer periods of 20 years, the TP data quality is still a limitation, but more interestingly, the International Terrestrial Reference Frame (ITRF) realization uncertainties becomes dominant over all the other sources of uncertainty. Such a finding challenges the altimetry observing system as it is designed today and highlights clear topics of research to be explored in the future to help the altimetry community to improve the GMSL measurement accuracy and stability.\u0000","PeriodicalId":19535,"journal":{"name":"Ocean Science","volume":"11 1","pages":""},"PeriodicalIF":3.2,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84843022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：