[1] Mesoscale eddy properties in the northwestern subtropical Pacific Ocean are investigated by analyzing 22,567 cyclonic eddies (CEs) and 26,365 anticyclonic eddies (AEs) detected from 19 year altimetric sea level records. Eddy occurrence frequency and kinetic energy are prevailingly high in the Subtropical Countercurrent zonal band between 19 N and 26 N and further elevated near the Luzon-Taiwan coast. A general superiority of AEs is observed at most latitudes except between 19 N and 22 N, where the CE number is larger. The modal radius and mean lifespan of the CEs (AEs) are 134 km and 11.2 weeks (121 km and 10.9 weeks), respectively. After generation, most eddies propagate westward with a mean speed of 7.2 cm s À1 and deflect northward following the Kuroshio along the Luzon-Taiwan coast. Three-dimensional eddy structures are further explored with composite eddy images in five subregions constructed by surfacing Argo temperature/salinity data into altimeter-detected eddy areas. Due to the existence of mode waters in the main thermocline, eddy-induced temperature anomaly exhibits a double-core vertical structure which is especially evident in CE images. Because of the vertical water mass distribution, salinity anomaly features a sandwich-like pattern which is more evident in AE images. Also revealed is the significant structure difference in these five subregions. Eddies are greatly intensified as they approach the western boundary, inducing larger temperature and salinity anomalies and influencing deeper ocean. Along the Luzon-Taiwan coast, AEs are preferentially strengthened by the northward background flow.

Abstract. We present a new framework for global ocean–sea-ice model simulations based on phase 2 of the Ocean Model Intercomparison Project (OMIP-2), making use of the surface dataset based on the Japanese 55-year atmospheric reanalysis for driving ocean–sea-ice models (JRA55-do). We motivate the use of OMIP-2 over the framework for the first phase of OMIP (OMIP-1), previously referred to as the Coordinated Ocean–ice Reference Experiments (COREs), via the evaluation of OMIP-1 and OMIP-2 simulations from 11 state-of-the-science global ocean–sea-ice models. In the present evaluation, multi-model ensemble means and spreads are calculated separately for the OMIP-1 and OMIP-2 simulations and overall performance is assessed considering metrics commonly used by ocean modelers. Both OMIP-1 and OMIP-2 multi-model ensemble ranges capture observations in more than 80 % of the time and region for most metrics, with the multi-model ensemble spread greatly exceeding the difference between the means of the two datasets. Many features, including some climatologically relevant ocean circulation indices, are very similar between OMIP-1 and OMIP-2 simulations, and yet we could also identify key qualitative improvements in transitioning from OMIP-1 to OMIP-2. For example, the sea surface temperatures of the OMIP-2 simulations reproduce the observed global warming during the 1980s and 1990s, as well as the warming slowdown in the 2000s and the more recent accelerated warming, which were absent in OMIP-1, noting that the last feature is part of the design of OMIP-2 because OMIP-1 forcing stopped in 2009. A negative bias in the sea-ice concentration in summer of both hemispheres in OMIP-1 is significantly reduced in OMIP-2. The overall reproducibility of both seasonal and interannual variations in sea surface temperature and sea surface height (dynamic sea level) is improved in OMIP-2. These improvements represent a new capability of the OMIP-2 framework for evaluating process-level responses using simulation results. Regarding the sensitivity of individual models to the change in forcing, the models show well-ordered responses for the metrics that are directly forced, while they show less organized responses for those that require complex model adjustments. Many of the remaining common model biases may be attributed either to errors in representing important processes in ocean–sea-ice models, some of which are expected to be reduced by using finer horizontal and/or vertical resolutions, or to shared biases and limitations in the atmospheric forcing. In particular, further efforts are warranted to resolve remaining issues in OMIP-2 such as the warm bias in the upper layer, the mismatch between the observed and simulated variability of heat content and thermosteric sea level before 1990s, and the erroneous representation of deep and bottom water formations and circulations. We suggest that such problems can be resolved through collaboration between those developing models (including parameterizations) and forcing datasets. Overall, the present assessment justifies our recommendation that future model development and analysis studies use the OMIP-2 framework.

Abstract. This paper presents global comparisons of fundamental global climate variables from a suite of four pairs of matched low- and high-resolution ocean and sea ice simulations that are obtained following the OMIP-2 protocol (Griffies et al., 2016) and integrated for one cycle (1958–2018) of the JRA55-do atmospheric state and runoff dataset (Tsujino et al., 2018). Our goal is to assess the robustness of climate-relevant improvements in ocean simulations (mean and variability) associated with moving from coarse (∼ 1∘) to eddy-resolving (∼ 0.1∘) horizontal resolutions. The models are diverse in their numerics and parameterizations, but each low-resolution and high-resolution pair of models is matched so as to isolate, to the extent possible, the effects of horizontal resolution. A variety of observational datasets are used to assess the fidelity of simulated temperature and salinity, sea surface height, kinetic energy, heat and volume transports, and sea ice distribution. This paper provides a crucial benchmark for future studies comparing and improving different schemes in any of the models used in this study or similar ones. The biases in the low-resolution simulations are familiar, and their gross features – position, strength, and variability of western boundary currents, equatorial currents, and the Antarctic Circumpolar Current – are significantly improved in the high-resolution models. However, despite the fact that the high-resolution models “resolve” most of these features, the improvements in temperature and salinity are inconsistent among the different model families, and some regions show increased bias over their low-resolution counterparts. Greatly enhanced horizontal resolution does not deliver unambiguous bias improvement in all regions for all models.

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This paper introduces the Flexible Global Ocean‐Atmosphere‐Land System Model: Grid‐Point Version 3 (FGOALS‐g3) and evaluates its basic performance based on some of its participation in the sixth phase of the Coupled Model Intercomparison Project (CMIP6) experiments. Our results show that many significant improvements have been achieved by FGOALS‐g3 in terms of climatological mean states, variabilities, and long‐term trends. For example, FGOALS‐g3 has a small (−0.015°C/100 yr) climate drift in 700‐yr preindustrial control (piControl) runs and smaller biases in climatological mean variables, such as the land/sea surface temperatures (SSTs) and seasonal soil moisture cycle, compared with its previous version FGOALS‐g2 during the historical period. The characteristics of climate variabilities, for example, Madden‐Julian oscillation (MJO) eastward/westward propagation ratios, spatial patterns of interannual variability of tropical SST anomalies, and relationship between the East Asian Summer Monsoon and El Niño–Southern Oscillation (ENSO), are well captured by FGOALS‐g3. In particular, the cooling trend of globally averaged surface temperature during 1940–1970, which is a challenge for most CMIP3 and CMIP5 models, is well reproduced by FGOALS‐g3 in historical runs. In addition to the external forcing factors recommended by CMIP6, anthropogenic groundwater forcing from 1965 to 2014 was incorporated into the FGOALS‐g3 historical runs.

.[1] Climatological seasonal variations of the thermocline in the China Seas and northwestern Pacific Ocean were studied using historical data from 1930 through 2001 (707,624 profiles). The quantitative roles of surface thermal buoyancy (B q ), haline buoyancy flux (B p ), and total buoyancy flux (B) against the wind-induced mixing (t) in different seasons and regions were also explored using the buoyancy ratio (R = |B q /B p |) and the Monin-Obukhov depth ratio (d), respectively. The thermocline has obvious seasonal variations in the study area north of 20°N. There is no thermocline along the west coast of the Bohai Sea (BS), Yellow Sea (YS), and northern East China Sea from December to March resulting from surface cooling and wind mixing. The significantly different variation of the thermocline strength on and off the Chinese shelf is mainly caused by the fact that the thermal stratification is enhanced by bottom tidal mixing on the shelf. The d indicates that the thermocline depth on the Chinese shelf is mainly dominated by B in summer, while it is dominated by t in winter. It reveals an opposite feature in the Kuroshio region; the dominating factor is B in winter, associated with the large heat buoyancy loss there. South of 20°N, the dominating factor is similar to that on the shelf, with the more obvious B dominant characteristic during the monsoon transition periods. The R demonstrates that B is mainly controlled by B q all year round, with some sporadically B p -dominated regions in the tropical area in winter and in the BS and eastern YS in September.

a b s t r a c tThe continuous ecological restoration of the Loess Plateau, which aims to reduce the sediment entering into the Yellow River, is known throughout the world for two strategies: the integrated soil conservation project that began in the 1970s, and the ''Grain for Green" project that began in the 1990s. However, the topic of whether the muddy water in the middle Yellow River run clearer remains debatable, and, in fact, response to the topic is reasonably well documented in regard to hydrological changes in the sediment source area. Six sub-catchments nested in the Beiluo River basin -one of the major sediment sources for the Yellow River -were selected, with data series ranging from 1957 to 2009. The Mann-Kendall and Pettitt tests were used for trend detection. A simple method was developed based on the distribution of suspended sediment concentration (SSC) versus water discharge. Using this method, we evaluated the quantities of sediment yield reduction attributed to streamflow and SSC changes due to the two strategies.The results showed that annual sediment yield in 5 out of 6 stations significantly decreased, with rates varying from À4 to À217 tÁkm À2 Áyr À1 . Significant decreases in daily and event streamflow and suspended sediment concentration were identified, especially at a high SSC (top 1-5%). During the integrated soil conservation period, the sediment yield was reduced mainly by decreases in high flow and high SSC conditions. In contrast, during the ''Grain for Green" period, sediment yield was reduced due to decreases in streamflow and SSC at all magnitudes. It was concluded that rainfall-sediment load dynamics have changed in the context of ecological restoration. Changes in both streamflow and the SSC-water discharge relationship induced the sediment yield reduction over time; in other words, the streamflow in the middle reaches of Yellow River became clearer during periods of ecological restoration. Moreover, the increased annual sediment yield at the Zhangcunyi station exposed a risk of increased erosion in areas where forests had been well preserved.

The eastern Pacific Ocean, ranging from the tropical region to mid-latitudes, is an exceedingly dynamic region that has been extensively investigated during the past century. The eastern boundary currents, e.g., the California Current and Humboldt Current, are highly productive, especially in the region off Peru (Ning et al., 1998). Although the area of the coastal zone near Peru represents less than 1% of the world's ocean, it contributes more than 8% of the global fish production (Hutchings et al., 2009). Productivity is highly impacted by the availability of nutrients, which determines the growth rate of phytoplankton, zooplankton and fishes at higher trophic levels (Belkin et al., 2009). Fronts, which are generated at the intersection of