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Amplification of sea surface temperature (SST) seasonality in response to global warming is a robust feature in climate model projections but season‐dependent regional disparities in this amplification and the associated mechanisms are not well addressed. Here, by analyzing large ensemble simulations using Community Earth System Model version 2, we investigate detailed spatiotemporal characteristics of the amplification of SST seasonality focusing on the North Pacific and North Atlantic, where robust changes are projected to emerge around 2050 under SSP3‐7.0 scenario. Our results indicate that atmosphere‐ocean coupled processes shape regional changes in SST seasonality differently between warm (MAMJJAS) and cold seasons (ONDJF). During the warm season, the projected warming tendency is mainly due to increased net surface heat flux and weakening of vertical mixing. On the other hand, in the cold season, the projected cooling tendency is driven by strengthened vertical mixing over the North Pacific associated with the northward shift of storm tracks but weakened horizontal advection and mixing due to changes in ocean currents over the North Atlantic. Plain Language Summary: In addition to the increase in annual mean sea surface temperature (SST), the amplitude of SST seasonal cycle is projected to intensify in response to greenhouse warming over many parts of the global ocean due to more warming during local summer than winter. By analyzing large ensemble simulations, we show how different atmospheric and ocean processes influence spatiotemporal differences in SST seasonality changes in the North Pacific and North Atlantic. Our findings indicate that during local summer, the projected warming tendency intensifies with the increased heat input into the ocean and weakening of ocean mixing. Meanwhile, during local winter, the projected cooling tendency intensifies with the strengthening of vertical mixing associated with the enhanced storm track activities in the North Pacific, but the weakening of ocean horizontal advection and mixing attributable to the weakened ocean circulation over the North Atlantic. They together contribute to the amplification of SST seasonality, which could have implications for marine ecosystems, including the plankton phenology. Key Points: Using CESM2 large ensemble simulations, this study explores the robustness of future sea surface temperature (SST) seasonality changes and the associated atmospheric and surface ocean processesIn the warm season, the future SST warming is mainly driven by the reduced upper ocean mixing and the increased net surface heat influx into the oceanIn the cold season, the future SST cooling is attributable to strengthened vertical mixing over the North Pacific but weakened horizontal advection and mixing in the North Atlantic [ABSTRACT FROM AUTHOR]

Abstract Amplification of sea surface temperature (SST) seasonality in response to global warming is a robust feature in climate model projections but season‐dependent regional disparities in this amplification and the associated mechanisms are not well addressed. Here, by analyzing large ensemble simulations using Community Earth System Model version 2, we investigate detailed spatiotemporal characteristics of the amplification of SST seasonality focusing on the North Pacific and North Atlantic, where robust changes are projected to emerge around 2050 under SSP3‐7.0 scenario. Our results indicate that atmosphere‐ocean coupled processes shape regional changes in SST seasonality differently between warm (MAMJJAS) and cold seasons (ONDJF). During the warm season, the projected warming tendency is mainly due to increased net surface heat flux and weakening of vertical mixing. On the other hand, in the cold season, the projected cooling tendency is driven by strengthened vertical mixing over the North Pacific associated with the northward shift of storm tracks but weakened horizontal advection and mixing due to changes in ocean currents over the North Atlantic.

The study of heat and water fluxes is one of the most essential components for understanding the interactions and exchanges between the ocean and atmosphere. Heat transfer across the air–sea interface is an important process in ocean–atmosphere dynamics. In this study, a 40-year (1981–2020) high-resolution (0.25° × 0.25°) ERA-5 reanalysis dataset from the European Centre for Medium-Range Weather Forecasts (ECMWF) is used to estimate the variability and trends of heat and water flux components in the Red Sea. The results show that the surface net heat flux is negative (loss) in the Northern Red Sea (NRS) and positive (gain) in the Southern Red Sea (SRS). The highest seasonal surface net heat flux is observed in the spring and early summer, while the lowest is reported in the winter. A significant linear trend is found in the surface net heat flux over the NRS and SRS, with values of about −0.12 ± 0.052 (W/m2)/yr and +0.20 ± 0.021 (W/m2)/yr, respectively. The annual mean surface net water flux loss to the atmosphere over the entire Red Sea is +1.46 ± 0.23 m/yr. The seasonal surface net water flux peak occurs in winter as a result of the northeast monsoon wind, which increases evaporation rate over the whole length of the Red Sea. The highest surface net water flux (+2.1 m/yr) is detected during 2020, while the lowest value (+1.3 m/yr) is observed during 1985.

In the Indian Ocean regions under the influence of monsoons, two phytoplankton blooms characterize the seasonal cycle of surface chlorophyll, one during summer, and the other during winter. In the Northern Mozambique Channel, however, where the wind regime is an extension of the northern Indian Ocean monsoons, the annual cycle of chlorophyll concentrations is characterized by a single winter bloom. Wind stress and surface net heat flux modulate the seasonal cycle of the mixed layer depth with impacts on the surface chlorophyll. In order to evaluate the importance of these forcing fields on the seasonality of the mixed layer depth, and consequently, the surface chlorophyll variability, we used a suite of physical-biogeochemical model sensitivity experiments. Our results show that the seasonal cycle of surface chlorophyll is primarily modulated by the net heat flux while the wind field controls the amplitude. The winter bloom is triggered by negative surface heat fluxes, where cooling at the surface induces mixing and entrainment of nutrients at the base of the nutricline and light is not limiting. Winds enhance the winter bloom by uplifting additional nutrients and diluting subsurface chlorophyll into the surface layer. In the summertime, weaker wind stress and positive heat flux inhibit vertical mixing. As a consequence, the surface layer is depleted in nutrients and a deep chlorophyll maximum is formed. Analysis of top-down control on phytoplankton biomass reveals that zooplankton abundance increases in a near-linear proportion with phytoplankton biomass despite the deepening of the mixed layer depth. This suggests that the phytoplankton stock in the Northern Mozambique Channel is also controlled by grazing, given that zooplankton biomass is not directly affected by the deepening of the mixed layer during wintertime. [ABSTRACT FROM AUTHOR]

The near-surface layers in the Arabian Sea progressively warm up from February to early May resulting in the formation of pool of warm waters popularly known as the Arabian Sea Warm Pool (ASWP). The availability of high quality TMI sea surface temperature (SST) data for the years 1998-2010 is exploited to describe the evolution of the ASWP on seasonal and interannual time scales and to explain the associated mechanisms. The multi-year (1998-2010) averaged TMI SSTs during April-May show peak values of the ASWP in excess of 30 °C with its core >30.5 °C extending offshore as a well-marked southwestward tongue stretching from the southwest coast of India. The ASWP shows both seasonal and interannual variability in the evolution of spatio-temporal characteristics such as amplitude, phase and spatial extent. Among these 13 years, the ASWP was most (least) pronounced during 1998, 2003 and 2010 (1999, 2000, 2001 and 2008). The mechanisms that govern the observed interannual variability of the ASWP are examined addressing the most relevant issues such as-(1) dynamic pre-conditioning: background pycnocline topography influenced by the westward propagating Rossby waves during October-May, (2) thermal pre-conditioning: background SST/heat content signal during October-January influenced by the strength of the preceding year's summer monsoon and the post-monsoon cyclones during October-December, (3) haline pre-conditioning: near-surface vertical salinity stratification during November-February influenced by the advection of low saline waters from the Bay of Bengal, (4) influence of surface net heat flux forcing during February-May, and (5) influence of El Nino/La Nina. [ABSTRACT FROM AUTHOR]

The study of heat and water fluxes is one of the most essential components for understanding the interactions and exchanges between the ocean and atmosphere. Heat transfer across the air–sea interface is an important process in ocean–atmosphere dynamics. In this study, a 40-year (1981–2020) high-resolution (0.25° × 0.25°) ERA-5 reanalysis dataset from the European Centre for Medium-Range Weather Forecasts (ECMWF) is used to estimate the variability and trends of heat and water flux components in the Red Sea. The results show that the surface net heat flux is negative (loss) in the Northern Red Sea (NRS) and positive (gain) in the Southern Red Sea (SRS). The highest seasonal surface net heat flux is observed in the spring and early summer, while the lowest is reported in the winter. A significant linear trend is found in the surface net heat flux over the NRS and SRS, with values of about −0.12 ± 0.052 (W/m2)/yr and +0.20 ± 0.021 (W/m2)/yr, respectively. The annual mean surface net water flux loss to the atmosphere over the entire Red Sea is +1.46 ± 0.23 m/yr. The seasonal surface net water flux peak occurs in winter as a result of the northeast monsoon wind, which increases evaporation rate over the whole length of the Red Sea. The highest surface net water flux (+2.1 m/yr) is detected during 2020, while the lowest value (+1.3 m/yr) is observed during 1985. [ABSTRACT FROM AUTHOR]

We use the U.S. Navy’s Master Oceanographic Observation Data Set (MOODS) for the Yellow Sea/East China Sea (YES) to investigate the climatological water mass features and the seasonal and non-seasonal variabilities of the thermohaline structure, and use the Comprehensive Ocean-Atmosphere Data Set (COADS) from 1945 to 1989 to investigate the linkage between the fluxes (momentum, heat, and moisture) across the air-ocean interface and the formation of the water mass features. After examining the major current systems and considering the local bathymetry and water mass properties, we divide YES into five regions: East China Sea (ECS) shelf, Yellow Sea (YS) Basin, Cheju bifurcation (CB) zone, Taiwan Warm Current (TWC) region, Kuroshio Current (KC) region. The long term mean surface heat balance corresponds to a heat loss of 30 W m−2 in the ESC and CB regions, a heat loss of 65 W m−2 in the KC and TWC regions, and a heat gain of 15 W m−2 in the YS region. The surface freshwater balance is defined by precipitation minus evaporation. The annual water loss from the surface for the five subareas ranges from 1.8 to 4 cm month−1. The fresh water loss from the surface should be compensated for from the river run-off. The entire water column of the shelf region (ECS, YS, and CB) undergoes an evident seasonal thermal cycle with maximum values of temperature during summer and maximum mixed layer depths during winter. However, only the surface waters of the TWC and KC regions exhibit a seasonal thermal cycle. We also found two different relations between surface salinity and the Yangtze River run-off, namely, out-of-phase in the East China Sea shelf and in-phase in the Yellow Sea. This may confirm an earlier study that the summer fresh water discharge from the Yangtze River forms a relatively shallow, low salinity plume-like structure extending offshore on average towards the northeast. [ABSTRACT FROM AUTHOR]