National Marine Environmental Forecasting Center

Over the past decade it has become apparent that the atmosphere is a significant pathway for the transport of many natural and pollutant materials from the continents to the ocean. The atmospheric input of many of these species can have an impact (either positive or negative) on biological processes in the sea and on marine chemical cycling. For example, there is now evidence that the atmosphere may be an important transport path for such essential nutrients as iron and nitrogen in some regions. In this report we assess current data in this area, develop global scale estimates of the atmospheric fluxes of trace elements, mineral aerosol, nitrogen species, and synthetic organic compounds to the ocean; and compare the atmospheric input rates of these substances to their input via rivers. Trace elements considered were Pb, Cd, Zn, Cu, Ni, As, Hg, Sn, Al, Fe, Si, and P. Oxidized and reduced forms of nitrogen were considered, including nitrate and ammonium ions and the gaseous species NO, NO2, HNO3, and NH3. Synthetic organic compounds considered included polychlorinated biphenyls (PCBs), hexachlorocyclohexanes (HCHs), DDTs, chlordane, dieldrin, and hexachlorobenzenes (HCBs). Making this assessment was difficult because there are very few actual measurements of deposition rates of these substances to the ocean. However, there are considerably more data on the atmospheric concentrations of these species in aerosol and gaseous form. Mean concentration data for 10° × 10° ocean areas were determined from the available concentration data or from extrapolation of these data into other regions. These concentration distributions were then combined with appropriate exchange coefficients and precipitation fields to obtain the global wet and dry deposition fluxes. Careful consideration was given to atmospheric transport processes as well as to removal mechanisms and the physical and physicochemical properties of aerosols and gases. Only annual values were calculated. On a global scale atmospheric inputs are generally equal to or greater than riverine inputs, and for most species atmospheric input to the ocean is significantly greater in the northern hemisphere than in the southern hemisphere. For dissolved trace metals in seawater, global atmospheric input dominates riverine input for Pb, Cd, and Zn, and the two transport paths are roughly equal for Cu, Ni, As, and Fe. Fluxes and basin‐wide deposition of trace metals are generally a factor of 5‐10 higher in the North Atlantic and North Pacific regions than in the South Atlantic and South Pacific. Global input of oxidized and reduced nitrogen species are roughly equal to each other, although the major fraction of oxidized nitrogen enters the ocean in the northern hemisphere, primarily as a result of pollution sources. Reduced nitrogen species are much more uniformly distributed, suggesting that the ocean itself may be a significant source. The global atmospheric input of such synthetic organic species as HCH,PCBs, DDT, and HCB completely dominates their input via rivers.

Numerical model studies have suggested that the ongoing global climate change will likely affect tropical cyclone activity. Since the global warming has been underway, it is meaningful to ask: Are there evidences of observed changes in tropical cyclone activity? Using best‐track data from 1965 to 2003, we show for the first time that over the past four decades the two prevailing typhoon tracks in the western North Pacific (WNP) have shifted westward significantly; thus the subtropical East Asia has experienced increasing typhoon influence; but the typhoon influence over the South China Sea has considerably decreased. Our trajectory model simulation indicates that the long‐term shifts in the typhoon tracks result primarily from the changes in the mean translation velocity of typhoons or the large‐scale steering flow, which is associated with the westward expansion and strengthening of the WNP subtropical high.

Abstract The polar regions have been attracting more and more attention in recent years, fueled by the perceptible impacts of anthropogenic climate change. Polar climate change provides new opportunities, such as shorter shipping routes between Europe and East Asia, but also new risks such as the potential for industrial accidents or emergencies in ice-covered seas. Here, it is argued that environmental prediction systems for the polar regions are less developed than elsewhere. There are many reasons for this situation, including the polar regions being (historically) lower priority, with fewer in situ observations, and with numerous local physical processes that are less well represented by models. By contrasting the relative importance of different physical processes in polar and lower latitudes, the need for a dedicated polar prediction effort is illustrated. Research priorities are identified that will help to advance environmental polar prediction capabilities. Examples include an improvement of the polar observing system; the use of coupled atmosphere–sea ice–ocean models, even for short-term prediction; and insight into polar–lower-latitude linkages and their role for forecasting. Given the enormity of some of the challenges ahead, in a harsh and remote environment such as the polar regions, it is argued that rapid progress will only be possible with a coordinated international effort. More specifically, it is proposed to hold a Year of Polar Prediction (YOPP) from mid-2017 to mid-2019 in which the international research and operational forecasting communites will work together with stakeholders in a period of intensive observing, modeling, prediction, verification, user engagement, and educational activities.

Abstract Both the Arctic and Antarctic sea ice extents (SIEs) from 44 coupled models in the Coupled Model Intercomparison Project Phase 6 (CMIP6) are evaluated by comparing them with observations and CMIP5 results. The CMIP6 multimodel mean can adequately reproduce the seasonal cycles of both the Arctic and Antarctic SIE. The observed Arctic September SIE declining trend (−0.82 ± 0.18 million km 2 per decade) between 1979 and 2014 is slightly underestimated in CMIP6 models (−0.70 ± 0.06 million km 2 per decade). The observed weak but significant upward trend of the Antarctic SIE is not captured, which was an issue already in the CMIP5 phase. Compared with CMIP5 models, CMIP6 models have lower intermodel spreads in SIE mean values and trends, although their SIE biases are relatively larger. The CMIP6 models did not reproduce the new summer tendencies after 2000, including the faster decline of Arctic SIE and the larger interannual variability in Antarctic SIE.

The CWRF is developed as a climate extension of the Weather Research and Forecasting model (WRF) by incorporating numerous improvements in the representation of physical processes and integration of external (top, surface, lateral) forcings that are crucial to climate scales, including interactions between land, atmosphere, and ocean; convection and microphysics; and cloud, aerosol, and radiation; and system consistency throughout all process modules. This extension inherits all WRF functionalities for numerical weather prediction while enhancing the capability for climate modeling. As such, CWRF can be applied seamlessly to weather forecast and climate prediction. The CWRF is built with a comprehensive ensemble of alternative parameterization schemes for each of the key physical processes, including surface (land, ocean), planetary boundary layer, cumulus (deep, shallow), microphysics, cloud, aerosol, and radiation, and their interactions. This facilitates the use of an optimized physics ensemble approach to improve weather or climate prediction along with a reliable uncertainty estimate. The CWRF also emphasizes the societal service capability to provide impactrelevant information by coupling with detailed models of terrestrial hydrology, coastal ocean, crop growth, air quality, and a recently expanded interactive water quality and ecosystem model. This study provides a general CWRF description and basic skill evaluation based on a continuous integration for the period 1979– 2009 as compared with that of WRF, using a 30-km grid spacing over a domain that includes the contiguous United States plus southern Canada and northern Mexico. In addition to advantages of greater application capability, CWRF improves performance in radiation and terrestrial hydrology over WRF and other regional models. Precipitation simulation, however, remains a challenge for all of the tested models.

Abstract The global physical and biogeochemical environment has been substantially altered in response to increased atmospheric greenhouse gases from human activities. In 2023, the sea surface temperature (SST) and upper 2000 m ocean heat content (OHC) reached record highs. The 0–2000 m OHC in 2023 exceeded that of 2022 by 15 ± 10 ZJ (1 Zetta Joules = 1021Joules) (updated IAP/CAS data); 9 ± 5 ZJ (NCEI/NOAA data). The Tropical Atlantic Ocean, the Mediterranean Sea, and southern oceans recorded their highest OHC observed since the 1950s. Associated with the onset of a strong El Niño, the global SST reached its record high in 2023 with an annual mean of ∼0.23°C higher than 2022 and an astounding > 0.3°C above 2022 values for the second half of 2023. The density stratification and spatial temperature inhomogeneity indexes reached their highest values in 2023.

Abstract Typhoons Hato (2017) and Typhoon Mangkhut (2018) struck the Pearl River Delta, China, in two consecutive years, causing intense flooding and severe damage along the coast, especially in Macau. These two typhoons are extreme events because of their record‐breaking storm tides, and they are typical typhoons in terms of their track forward directions, which affect the coast of Guangdong Province, China. This paper analyzes and compares the physical processes of these two major typhoons. We first report the results of our posttyphoon surveys in Macau and the constructed inundation maps for both typhoon events. The inundation maps in conjunction with measured wind, atmospheric pressure, and wave data are used to validate a package of numerical models that simulate fully coupled tide‐surge‐wave fields during a typhoon. We quantify storm surges and wave heights in the Pearl River Delta. The surge around Macau was mainly affected by wind, while atmosphere pressure and ocean waves played a secondary role. In additional to inundation depth, we also investigate inundation durations and flow velocities. Typhoon Mangkhut made its landfall at much lower tidal level than that of Typhoon Hato. However, Typhoon Mangkhut generated much larger storm surge with larger affected areas and significantly longer inundation durations. We attribute the causes mainly to Typhoon Mangkhut's storm size, which was almost three times larger than that of Typhoon Hato.

Atmospheric concentrations of aluminium, an indicator of dust substances, have been determined in a set of high-volume aerosol particle samples collected at different locations over continental China and over the China Sea. High concentrations of dust were observed in northern continental China, and at certain locations such as Beijing dust may include an anthropogenic fraction. The mass particle-size distributions of dust varied depending on its distance from source regions, with the mass median diameter for Al of ~1.6-5.9 μm at Beijing in northern China and ~ 1.9 μm over off-shore areas of the East China Sea. Model-predicted mean dry deposition velocities of dust particles are from 1.4 to 4.8 cm s-1 over northern continental China and from 1.4 to 2.1 cm s-1 over the China Sea. Atmospheric deposition models have been applied to estimate the atmospheric fluxes and deposition of dust at different locations. The estimated atmospheric flux of dust at Xi’an of the Loess Plateau is 25 (4.9 to 44) g m-2 mo-1 which is the highest among the regions we studied. The estimated present-day dust flux is comparable to the late quaternary records of eolian dust accumulation at this site. The total atmospheric deposition of dust to the China Sea is 67 Tg yr-1, accounting for 14% of the total atmospheric deposition of dust to the entire North Pacific. With such a high deposition rate, Asian dust may play an important rôle in biogeochemical cycles of trace substances in the Asia/North Pacific region.

Operational evolution of global and regional ocean forecasting systems has been extremely significant in recent years. Global Ocean Data Assimilation Experiment (GODAE) Oceanview supports the national research groups providing them with coordination and sharing expertise among the partners. Several systems have been set up and developed pre-operationally, and the majority of these are now fully operational; at the present time, they provide medium- and long-term forecasts of the most relevant ocean physical variables. These systems are based on ocean general circulation models and data-assimilation techniques that are able to correct the model with the information inferred from different types of observations. A few systems also incorporate a biogeochemical component coupled with the physical system, while others are based on coupled ocean–wave–ice–atmosphere models. The products are routinely validated with observations in order to assess their quality. Data and product implementation and organization, as well as service, for users have been well tried and tested, and most of the products are now available to users. The interaction with different users is an important factor in the development process. This paper provides a synthetic overview of the GODAE OceanView prediction systems.

During the last 15 years, operational oceanography systems have emerged in several countries around the world. This emergence has been largely fostered by the GODAE experiment, during which each nation engaged in this activity have organised partnership and constructive competition. This trans-national coordination was very beneficial for the development of operational oceanography, leading to economies of scales and more targeted actions. Today, several systems provide routine real-time ocean analysis and forecast and/or reanalysis products. They are all based on (i) state-of-the-art primitive equation baroclinic Ocean General Circulation Model (OGCM) configurations, either global or regional (basin-scale), with resolutions that range from coarse to eddy resolving and (ii) data assimilation techniques whose complexity ranges from simple analysis correction to advanced 4D variational schemes. They assimilate altimeter sea level anomalies, remotely sensed SST such as GHRSST products and in situ profiles of T and S, including ARGO. Some systems have implemented downscaling capacities in specific regions of interest including shelf/coastal seas. Some also have implemented coupling

Abstract The impact of assimilating sea ice thickness data derived from ESA's Soil Moisture and Ocean Salinity (SMOS) satellite together with Special Sensor Microwave Imager/Sounder (SSMIS) sea ice concentration data of the National Snow and Ice Data Center (NSIDC) in a coupled sea ice‐ocean model is examined. A period of 3 months from 1 November 2011 to 31 January 2012 is selected to assess the forecast skill of the assimilation system. The 24 h forecasts and longer forecasts are based on the Massachusetts Institute of Technology general circulation model (MITgcm), and the assimilation is performed by a localized Singular Evolutive Interpolated Kalman (LSEIK) filter. For comparison, the assimilation is repeated only with the SSMIS sea ice concentrations. By running two different assimilation experiments, and comparing with the unassimilated model, independent satellite‐derived data, and in situ observation, it is shown that the SMOS ice thickness assimilation leads to improved thickness forecasts. With SMOS thickness data, the sea ice concentration forecasts also agree better with observations, although this improvement is smaller.

Abstract The 168 year trends of summer (July–September) sea ice area (SIA) variations in six Arctic regions during 1850–2017 are analyzed. SIA has been significantly decreasing in most Arctic regions since 1850. The rate of retreat for the period of 1948–2017 accelerated multi-fold. For the nearly four decades since 1979, most Arctic regions are experiencing the highest reduction rate. Besides the increasing surface air temperature, the key drivers to the accelerated summer Arctic sea ice decline are found to be the combined global warming and the regional Arctic warming exerted simultaneously by the Arctic Oscillation, North Atlantic Oscillation, Atlantic Multidecadal Oscillation and Pacific Decadal Oscillation during the last several decades. The dynamical and thermodynamical warming, driven by the internal variability of the teleconnection patterns, occurred in the last several decades, in particular on the multidecadal timescales. This leads to Arctic amplification that accelerates the positive ice/ocean albedo feedback loop, resulting in accelerating summer sea ice decline.

The deep structure of the continental collision between India and Asia and whether India's lower crust is underplated beneath Tibet or subducted into the mantle remain controversial. It is also unknown whether the active normal faults that facilitate orogen-parallel extension of Tibetan upper crust continue into the lower crust and upper mantle. Our receiver-function images collected parallel to the India-Tibet collision zone show the 20-km-thick Indian lower crust that underplates Tibet at 88.5-92°E beneath the Yarlung-Zangbo suture is essentially absent in the vicinity of the Cona-Sangri and Pumqu-Xainza grabens, demonstrating a clear link between upper-crustal and lower-crustal thinning. Satellite gravity data that covary with the thickness of Indian lower crust are consistent with the lower crust being only ∼30% eclogitized so gravitationally stable. Deep earthquakes coincide with Moho offsets and with lateral thinning of the Indian lower crust near the bottom of the partially eclogitized Indian lower crust, suggesting the Indian lower crust is locally foundering or stoping into the mantle. Loss of Indian lower crust by these means implies gravitational instability that can result from localized rapid eclogitization enabled by dehydration reactions in weakly hydrous mafic granulites or by volatile-rich asthenospheric upwelling directly beneath the two grabens. We propose that two competing processes, plateau formation by underplating and continental loss by foundering or stoping, are simultaneously operating beneath the collision zone.

Abstract Changes in ocean heat content (OHC), salinity, and stratification provide critical indicators for changes in Earth’s energy and water cycles. These cycles have been profoundly altered due to the emission of greenhouse gasses and other anthropogenic substances by human activities, driving pervasive changes in Earth’s climate system. In 2022, the world’s oceans, as given by OHC, were again the hottest in the historical record and exceeded the previous 2021 record maximum. According to IAP/CAS data, the 0–2000 m OHC in 2022 exceeded that of 2021 by 10.9 ± 8.3 ZJ (1 Zetta Joules = 10 21 Joules); and according to NCEI/NOAA data, by 9.1 ± 8.7 ZJ. Among seven regions, four basins (the North Pacific, North Atlantic, the Mediterranean Sea, and southern oceans) recorded their highest OHC since the 1950s. The salinity-contrast index, a quantification of the “salty gets saltier—fresh gets fresher” pattern, also reached its highest level on record in 2022, implying continued amplification of the global hydrological cycle. Regional OHC and salinity changes in 2022 were dominated by a strong La Niña event. Global upper-ocean stratification continued its increasing trend and was among the top seven in 2022.

The frequent occurrences of the second-year surface cooling condition in the eastern equatorial Pacific, as observed in late 2021, are attributed to decadal changes in the thermocline depth, which determine the relative dominances of local cooling effect in the east and subsurface warming effect remotely from the west. Coupled models need to adequately represent these processes in a balanced way, thus being able to successfully predict the observed sea surface temperature evolution in late 2021.

Abstract The increased concentration of greenhouse gases in the atmosphere from human activities traps heat within the climate system and increases ocean heat content (OHC). Here, we provide the first analysis of recent OHC changes through 2021 from two international groups. The world ocean, in 2021, was the hottest ever recorded by humans, and the 2021 annual OHC value is even higher than last year’s record value by 14 ± 11 ZJ (1 zetta J = 1021 J) using the IAP/CAS dataset and by 16 ± 10 ZJ using NCEI/NOAA dataset. The long-term ocean warming is larger in the Atlantic and Southern Oceans than in other regions and is mainly attributed, via climate model simulations, to an increase in anthropogenic greenhouse gas concentrations. The year-to-year variation of OHC is primarily tied to the El Niño-Southern Oscillation (ENSO). In the seven maritime domains of the Indian, Tropical Atlantic, North Atlantic, Northwest Pacific, North Pacific, Southern oceans, and the Mediterranean Sea, robust warming is observed but with distinct inter-annual to decadal variability. Four out of seven domains showed record-high heat content in 2021. The anomalous global and regional ocean warming established in this study should be incorporated into climate risk assessments, adaptation, and mitigation.

Abstract Storm surges are responsible for much of the damage and loss of life associated with landfalling tropical cyclones (TCs). Thus, understanding the characteristics of risk associated with TC storm surges for the coastal regions of China is of great interest. Based on a comprehensive assessment of hazard indices for TC storm surges and vulnerability indices for coastal counties, we obtained a risk assessment for coastal regions of China as a county‐level unit. The hazard index was calculated using a model based on the parameters of a TC landfall frequency index ( f ) and maximum storm surge elevation (MSSE). The MSSE was calculated from the TC maximum sustained wind and tide gauge records using a regression function. Vulnerability indices were obtained from indices on socioeconomics, land use, the ecological environment, and resilience. From this study, it can be concluded that the hazard level of TC storm surges increases from north to south along the Chinese coast, the vulnerabilities have significant spatial heterogeneity, and coastal regions of China can be divided into four zones of risk level. The results of this study can provide scientific support for marine disaster mitigation and decision making. Additionally, the risk assessment methodology used here for storm surges could be extended and applied to other coastal areas.

The impact of assimilating weekly CryoSat‐2 sea ice thickness data together with daily SMOS sea ice thickness and daily SSMIS sea ice concentration data on the sea ice fields of a coupled sea ice–ocean model of the Arctic Ocean is investigated. The sea‐ice model is based on the Massachusetts Institute of Technology general circulation model (MITgcm) and the assimilation is performed by a localized Singular Evolutive Interpolated Kalman (LSEIK) filter coded in the Parallel Data Assimilation Framework (PDAF). A period of three months from 1 November 2011 to 30 January 2012 is selected to assess the skill of the assimilation system in the cold season. Compared to the unassimilated solution and a solution where only sea ice concentration is assimilated, the model–data misfits are substantially reduced in areas of both thick and thin ice. The sea ice thickness estimates agree significantly better with in situ observations in the central Arctic Ocean than the sea ice thickness obtained from assimilating SMOS data alone, while the sea ice concentration shows very small improvements. The sea ice fields obtained by the joint assimilation of SMOS and CryoSat‐2 data also have lower errors in thickness and concentration than those obtained from directly assimilating a statistically merged SMOS and CryoSat‐2 sea ice thickness product. These lower errors suggest that model dynamics play a significant role in data blending.

Abstract Marine heatwaves (MHWs) in the South China Sea (SCS) have dramatic impacts on local ecosystems, fisheries, and aquacultures. Our results show that SCS MHWs were strongly regulated by El Niño–Southern Oscillation (ENSO) with a distinct life cycle during 1982–2018. Based on the ENSO-associated sea surface temperature anomaly (SSTA) warming peaks in the SCS, we can classify SCS MHWs into three categories: El Niño-P1 during the first warming peak of El Niño from September to the following February, El Niño-P2 during the second warming peak of El Niño from the following June to September, and La Niña-P1 during the single warming peak of La Niña from the following February to May. The three types of SCS MHWs are all affected by the lower-level enhanced anticyclone over the western North Pacific (WNP), but their physical mechanisms are quite different. In El Niño-P1, SCS MHWs are mostly induced by enhanced net downward shortwave radiation and reduced latent heat flux loss over the southwestern and northern SCS, respectively. In El Niño-P2, SCS MHWs are primarily attributed to weaker entrainment cooling caused by a local enhanced anticyclone and stronger Ekman downwelling in the central-northern SCS. However, in La Niña-P1, SCS MHWs are mainly contributed by the reduced latent heat loss due to the weaker WNP anticyclone centered east of the Philippines on the pentad time scale. The distinct spatial distributions of MHWs show phase locking with ENSO-associated SCS SSTA warming, which provides a potential seasonal forecast of SCS MHWs according to the ENSO phase.

Here sea ice concentration derived from the Special Sensor Microwave Imager/Sounder and thickness derived from the Soil Moisture and Ocean Salinity and CryoSat-2 satellites are assimilated in the National Centers for Environmental Prediction Climate Forecast System using a localized error subspace transform ensemble Kalman filter (LESTKF). Three ensemble-based hindcasts are conducted to examine impacts of the assimilation on Arctic sea ice prediction, including CTL (without any assimilation), LESTKF-1 (with initial sea ice assimilation only), and LESTKF-E5 (with every 5-day sea ice assimilation). Assessment with the assimilated satellite products and independent sea ice thickness datasets shows that assimilating sea ice concentration and thickness leads to improved Arctic sea ice prediction. LESTKF-1 improves sea ice forecast initially. The initial improvement gradually diminishes after ~3-week integration for sea ice extent but remains quite steady through the integration for sea ice thickness. Large biases in both the ice extent and thickness in CTL are remarkably reduced through the hindcast in LESTKF-E5. Additional numerical experiments suggest that the hindcast with sea ice thickness assimilation dramatically reduces systematic bias in the predicted ice thickness compared with sea ice concentration assimilation only or without any assimilation, which also benefits the prediction of sea ice extent and concentration due to their covariability. Hence, the corrected state of sea ice thickness would aid in the forecast procedure. Increasing the number of ensemble members or extending the integration period to generate estimates of initial model states and uncertainties seems to have small impacts on sea ice prediction relative to LESTKF-E5.