Sea Surface Temperature Difference Research Articles

Future amazon basin wetland hydrology under projected climate change

Climate change over the Amazon basin has the potential to cause major hydrological and ecological impacts over the region’s extensive wetlands. To investigate this the Joint UK Land Environment Simulator (JULES) land surface model is first extended to include riverine inundation. Potential impacts of future climate change on Amazon basin wetlands are then evaluated by driving this updated JULES model with modelled meteorology projections from six different climate simulations reaching approximately 4°C global warming at the end of the 21st Century. The projected changes in inundation extent and seasonality are assessed over four major wetland regions. The simulations project, on average, a significant decrease in total Amazon basin inundated area of 11% (range: -36% to +9%) by the 2090s. This considerable spread is primarily driven by disparity in simulated precipitation changes, ultimately driven by sea surface temperature differences. The wetter contemporary climate simulations simulate the greatest drying by the end of this Century, resulting in the largest wetland area reductions. The largest qualitative disagreement is over the western Iquitos wetland, with inundated area changes ranging from a very large reduction of -53% to an increase of 12%. A new wetland classification scheme is developed to summarise the projected changes in wetland seasonality. The largest drops in simulated wetland season length occur over the Central/East Manaus and West Iquitos wetland regions, with reductions of up to 10 and 8 months respectively. Such significant changes in future inundation are likely to have a major impact on regional wetland hydrology and their ecosystems.

Present Climate and Future Changes in the Annual Cycle of TC Activity in the WNP Investigated by HighResMIP GCMs

Abstract Atmospheric general circulation models (AGCMs) and coupled general circulation models (CGCMs) in the High Resolution Model Intercomparison Project (HighResMIP) were evaluated on their ability to simulate tropical cyclone (TC) activity in the western North Pacific (WNP) over its annual cycle. Specifically, we examined these models’ ability to simulate the south–north migration of the mean TC genesis location. The results revealed that both types of models realistically captured TC numbers and the south–north migration of TC genesis locations associated with the meridional migration of the WNP subtropical high ridge in response to the annual cycle. However, TC numbers decreased less rapidly in the AGCMs than in both the CGCMs and observed data during the monsoon retreat period (after September). This bias was probably attributed to a low-tropospheric cyclonic anomaly over the Philippine Sea in response to La Niña–like sea surface temperature (SST) differences between the AGCMs and the CGCMs. Because of these differences, the TC genesis frequency in the AGCMs over the Philippine Sea was overestimated. The cyclonic anomaly occurred when the northeasterly trade wind arose and was maintained through wind–evaporation–SST feedback. In future climate (2021–50), the main changes occurred during the monsoon retreat period. A more rapid decrease in TC numbers shown in AGCMs was likely attributed to the decrease (increase) of low-level vorticity (vertical wind shear) modulated by enhanced WNP subtropical high and subsidence anomalies. Conversely, a cyclonic circulation and ascending anomalies projected by CGCMs were identified off-equator, which favored TC genesis location shifting northward. Significance Statement Model performance and future changes in the annual cycle of tropical cyclone (TC) activity in the western North Pacific are investigated. We found that high-resolution uncoupled and coupled models realistically captured the TC numbers and meridional migration of TC genesis locations associated with the meridional migration of subtropical high ridge. However, TC numbers decreased more gradually in the uncoupled models than in the coupled models after September. This lower skill may stem from differences between the uncoupled and coupled models in simulating a cyclonic anomaly over the Philippine Sea in response to the La Niña–like sea surface temperature difference. In future climate (2021–50), TC numbers are significantly projected to decrease more rapidly during the monsoon retreat period in uncoupled models.

Sea surface temperature differences between in situ and GHRSST (L4) records in a socio-ecological critical area of the northeastern Pacific Ocean May 2015 to July 2016

Using satellite sensor data for studying sea surface temperature (SST) provides advantages over in situ information, such as obtaining data from large areas and remote access regions in short periods. However, differences between the SST values recorded in situ and those by satellite sensors are due to the intrinsic nature of both methods and meteorological factors. The present study aims to search the difference between SST values from in situ and satellite sensor data of 1×1 km resolution (type L4) from the Group of High-Resolution Sea Surface Temperature (GHRSST) for an annual cycle in a socio-ecological critical area known as the Gulf of Ulloa (GU). The linear regression, linear spline regression, and logic models showed an overestimated SST by satellites compared to in situ data, particularly at temperatures below 20°C. The overestimation can be attributed to the oceanic-atmospheric variations, which are consequences of upwelling and the time lag between the data record morning by in situ and night by satellite sensors. This finding may be relevant in decision-making for marine resource management and conservation in the GU. The information may help to seek the sustainability of this social-environmental system.

Sensitivity of Australian Rainfall to Driving SST Data Sets in a Variable‐Resolution Global Atmospheric Model

AbstractIn this study, we employ the Conformal Cubic Atmospheric Model (CCAM), a variable‐resolution global atmospheric model, driven by two distinct sea surface temperature (SST) data sets: the 0.25° Optimum Interpolation Sea Surface Temperature (CCAM_OISST) version 2.1 and the 2° Extended Reconstruction SSTs Version 5 (CCAM_ERSST5). Model performance is assessed using a benchmarking framework, revealing good agreement between both simulations and the climatological rainfall spatial pattern, seasonality, and annual trends obtained from the Australian Gridded Climate Data (AGCD). Notably, wet biases are identified in both simulations, with CCAM_OISST displaying a more pronounced bias. Furthermore, we have examined CCAM’s ability to capture El Niño‐Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) correlations with rainfall during Austral spring (SON) utilizing a novel hit rate metric. Results indicate that only CCAM_OISST successfully replicates observed SON ENSO‐ and IOD‐rainfall correlations, achieving hit rates of 86.6% and 87.5%, respectively, compared to 52.7% and 41.8% for CCAM_ERSST5. Large SST differences are found surrounding the Australian coastline between OISST and ERSST5 (termed the “Coastal Effect”). Differences can be induced by the spatial interpolation error due to the discrepancy between model and driving SST. An additional CCAM experiment, employing OISST with SST masked by ERSST5 in 5° proximity to the Australian continent, underscores the “Coastal Effect” has a significant impact on IOD‐Australian rainfall simulations. In contrast, its influence on ENSO‐Australian rainfall is limited. Therefore, simulations of IOD‐Australian rainfall teleconnection are sensitive to local SST representation along coastlines, probably dependent on the spatial resolution of driving SST.

Global warming and coastal protected areas: A study on phytoplankton abundance and sea surface temperature in different regions of the Brazilian South Atlantic Coastal Ocean.

In this study, we examined the relationship between sea surface temperature (SST) and phytoplankton abundance in coastal regions of the Brazilian South Atlantic: São Paulo, Paraná, and Santa Catarina, and the Protection Area of Southern right whales (Eubalaena australis) in Santa Catarina (APA), a conservation zone established along 130 km of coastline. Using SST and chlorophyll-a (Chl-a) data from 2002 to 2023, we found significant differences in SST between the regions, with São Paulo having the highest SST, followed by Paraná and Santa Catarina. All locations showed a consistent increase in SST over the years, with North Santa Catarina, APA and São Paulo experiencing the lowest rate of increase. Correlation analyses between SST and Chl-a revealed a stronger inverse relationship in North Santa Catarina and APA, indicating an increased response of Chl-a to SST variations in this region. The presence of protected area appears to play an essential role in reducing the negative impacts of increasing SST. Specifically, while there is a wealth of research on the consequences of global warming on diverse coastal and oceanic areas, heterogeneity among different settings persists and the causes for this necessitating attention. Our findings have implications for both localized scientific approaches and broader climate policies, emphasizing the importance of considering coastal ecosystem resilience to climate change in future conservation and adaptation strategies.

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

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

Intrinsic and extrinsic factors associated with the spatio-temporal distribution of infectious agents in early marine Chinook and coho salmon

Understanding the factors driving the spatial distribution of infectious agents in populations is key to predicting infectious agent distributions under future ecological and anthropogenic scenarios. We applied a geostatistical analysis to a data set of 59 infectious agents assayed in thousands of Chinook and coho salmon in their first marine year to identify intrinsic and extrinsic factors associated with the probability and density (infectious agent load) of infection. Meta-analysis of the pathogen-specific geostatistical models indicated that sea surface salinity was the extrinsic factor most frequently associated with infection probability and density for a majority of infectious agents. In addition, agents that were categorized as having a moderate risk of transmission from aquaculture to wild salmon were more likely to occur, and at higher infection densities, in fish collected closer to active aquaculture facilities. Although hypotheses pertaining to other intrinsic and extrinsic factors, including age at ocean entry, known hatchery origin, and sea surface temperature deviation, were not supported by the meta-analysis results, some individual agents demonstrated strong associations with these factors. Our results suggest that climate-change-driven shifts in coastal seawater salinity (and to a lesser extent, temperature) may result in changes to the infection dynamics of several infectious agents. In addition, our results contribute to existing evidence characterizing the risk of infectious agent transmission from netpen aquaculture to free-ranging salmon.

Asian winter monsoon controls marine primary productivity in north Arabian Sea during the Holocene

The Arabian Sea (AS), which is strongly impacted by monsoon winds, is one of the most biologically productive regions. The forcing of Asian monsoons on Holocene productivity remains debated in north AS, an area influenced by summer and winter monsoon. A sediment core from Makran margin was utilized to analyze organic biomarkers and high-resolution bromine intensities, unveiling the forces of biological productivity through the past 8000 years. Alkenone sea surface temperature (SST) records show significant cooling in north AS and augmented SST difference between north and west AS toward the late Holocene, suggesting Asian winter monsoon (AWM) strengthening during the period. The Holocene productivity signals in north AS, indicated by the bromine to rubidium ratio and multiple biomarkers, are responsive to SST changes and thus mainly controlled by the AWM variation, not modulated by Asian summer monsoon (ASM). Millennial-to-centennial-scale variability of marine productivity during the Holocene is closely related to North Atlantic climate oscillations, mainly through atmospheric circulations in winter.

Revealing Spatial–Temporal Patterns of Sea Surface Temperature in the South China Sea Based on Spatial–Temporal Co-Clustering

To discover the spatial–temporal patterns of sea surface temperature (SST) in the South China Sea (SCS), this paper proposes a spatial–temporal co-clustering algorithm optimized by information divergence. This method allows for the clustering of SST data simultaneously across temporal and spatial dimensions and is adaptable to large volumes of data and anomalous data situations. First, the SST data are initially clustered using the co-clustering algorithm. Second, we use information divergence as the loss function to refine the clustering results iteratively. During the iterative optimization of spatial clustering results, we treat the temporal dimension as a constraint; similarly, during the iterative optimization of temporal clustering, we treat the spatial dimension as a constraint. This is to ensure better robustness of the algorithm. Finally, this paper conducts experiments in the SCS to verify our algorithm. According to the analysis of the experimental results, we have drawn the following conclusions. First, the use of the spatial–temporal co-clustering algorithm reveals that the SST in the SCS exhibits strong seasonal patterns in the temporal clustering results. The spatial distribution of SST varies significantly in different seasons. There is a slight difference in SST between the northern and southern regions of the SCS in winter, but the largest difference is in summer. Second, during ocean anomalies, our proposed algorithm can identify the corresponding abnormal patterns. When ENSO occurs, the seasonal distribution pattern of SST in the SCS is destroyed and replaced by an abnormal temporal pattern. The results indicate that during ENSO events, the SST in specific months in the SCS exhibits a correlation with the SST observed 4–5 months afterward.

Changes in blue whale survival and abundance in the Gulf of California

AbstractUnderstanding the drivers of population abundance and distribution is fundamental to ecology and key to informing conservation actions, particularly in endangered species like blue whales (Balaenoptera musculus). Historically, some Eastern North Pacific blue whales have aggregated in the Gulf of California (GoC) each winter. Using photo‐identification data collected around Loreto Bay from 1984 to 2020, we analyzed 453 sightings histories using mark‐recapture models. Estimated apparent survival (including permanent emigration) decreased from 0.991, 95% CI [0.977, 0.997] in 1985 to 0.889, 95% CI [0.807, 0.939] in 2019. The estimated number of whales using the study area declined from 96 whales, 95% CI [50, 254] in 2012 to 13 whales, 95% CIs [12, 23 and 12, 28] in 2018 and 2019. Abundance of the whole Eastern North Pacific population is slowly increasing, so our results likely reflect declining usage of the GoC. Linear models found a relationship between the number of whales in the GoC and the difference in sea surface temperature between the study area and the Costa Rica Dome wintering area, suggesting that environmental variation could explain variation in blue whale numbers in the GoC. These results highlight the importance of tracking population dynamics as changing environmental conditions affect the range and distribution of populations.

Environmental control of interannual and seasonal variability in dinoflagellate cyst export flux over 18 years in the Cape Blanc upwelling region (Mauritania)

The increasing threat of anthropogenic environment and climate change amplifies the urgency to investigate the effect of these changes on marine ecosystems. We provide information about the export flux of organic-walled dinoflagellate cysts between 2003 and 2020 in the upwelling ecosystem off Cape Blanc (Mauritania), one of the world’s most productive regions. We compared the cyst export flux with variability in environmental parameters, such as wind speed, wind direction, dust emission, sea surface temperature (SST), SST difference between trap location and open ocean (SSTa), and chlorophyll-a concentration. This information is valuable to determine the ecological signal of dinoflagellate cysts that could be applied in recent and paleo records. The total export production of dinoflagellate cysts fluctuated between 0 - 1.18 x 105 cysts m-2 d-1 for the heterotrophs and 0 - 1.06 x 104 cysts m-2 d-1 for the photo-/mixotrophs. The export productions of both groups were in line with changes in upwelling intensity, which in most years, intensified in spring - summer. Dinoflagellate cyst association was dominated by heterotrophic taxa that formed an average of 94% of the association throughout the sediment trap record. A strong interannual variation in the cyst export fluxes, as well as the association composition was observed in the record. We identified five groups that showed comparable variability in export production with changes in environmental conditions: (1) maximal upwelling; Echinidinium delicatum/granulatum, E. transparantum/zonneveldiae, Echinidinium spp., Trinovantedinium spp., and Protoperidinium latidorsale, (2) combined maximal upwelling and dust input; Archaeperidinium spp., P. americanum, P. stellatum, and P. subinerme, (3) upwelling relaxation; Gymnodinium spp. and L. polyedra, (4) warm surface waters; Bitectatodinium spongium and Protoceratium reticulatum, (5) species with no specific relationship to the studied environmental variables; Brigantedinium spp., E. aculeatum, Impagidinium aculeatum, P. conicum, P. monospinum, Pentapharsodinium dalei, and Spiniferites spp. The sediment trap record documented a gradual shift in the cyst taxa association that co-occurred with the gradual increase of Saharan dust input to the region, notably after 2008. The cyst association contained five photo-/mixotrophic taxa that were formed by potentially toxic dinoflagellates. The latter could cause threats to the socio-economy of coastal communities.

Large spread in marine heatwave assessments for Asia and the Indo-Pacific between sea-surface-temperature products

Prolonged extremely warm ocean temperatures have great impacts on both natural ecosystems and human communities. These phenomena (i.e., marine heatwaves) could be easily monitored globally by satellite-based sea surface temperatures; however, the choice of datasets may lead to potential uncertainties in the marine heatwave assessment. Here we compared the marine heatwaves using three commonly used satellite products to illustrate the uncertainties over Asia and the Indo-Pacific. Distinct differences were found in the occurrence, duration, and long-term trend of marine heatwaves over both coastal and open oceans, while some discrepancies could become comparable with the obtained metrics themselves. Although differences in mean sea surface temperatures or their variances among datasets could not explain the abovementioned discrepancies, different sensors, procedures, and sea ice treatments in each dataset may contribute partially. Overall, our study suggests that the use of multiple datasets is crucial for evaluations of extreme events.

The relationship between December haze pollution in the Sichuan Basin and preceding climate factors

AbstractHaze pollution (HP) is one of the most serious disasters in the Sichuan Basin (SCB), adversely affecting human health, transportation, tourism and agriculture. HP in December is severe and differs from the haze days in January and February in terms of their temporal variations. To improve the understanding of December haze days in the SCB (DHDSCB), this study not only shows the atmospheric circulations and local meteorological circumstances related with the haze variation, but also analyses its relationship with the prior atmospheric apparent heat source over the Tibetan Plateau (TP) and the sea surface temperature (SST). The key circulation system associated with the interannual variation of the DHDSCB is that the SCB is controlled by the positive geopotential height anomalies and anomalous anticyclonic circulations with weak southwestward water vapour transport. Moreover, unfavourable local meteorological circumstances limit the vertical (horizontal) dispersion of pollutants. In addition, the DHDSCB during 1981–2022 is also found to have significant relationships with two preceding climate factors, which are the atmospheric apparent heat source (Q1) over the western TP in preceding November and the SST difference between the western Maritime Continent and western Australia in preceding autumn. The enhancement of Q1 over the western TP in preceding November is closely related to the midlatitude North Atlantic–southern Mediterranean Middle East–Arabian Sea–TP and its downstream region teleconnection pattern. Consequently, the anticyclonic circulation prevails over the SCB, and SCB is with less precipitation and more haze days in December. The western Maritime Continent and western Australia SST pattern in preceding Autumn is correlated with the Bay of Bengal–eastern TP and its downstream–Japan–Bering Sea teleconnection pattern, providing unfavourable moisture condition for the precipitation over the SCB and leading to the onset, development and maintenance of static weather in December. Therefore, the Q1 over the western TP and the SST pattern over the western Maritime Continent and western Australia may be potential indicators for the subseasonal prediction of HP in the SCB in December.

Numerical Simulation of the Northwest Pacific Based on the MaCOM

Based on the GLORY reanalysis data, the simulation results of the two versions of MaCOM volume conservation and mass conservation in the Northwest Pacific Ocean for 8 years (1993-2000) are tested. In this paper, the sea surface height, sea surface flow field, sea surface temperature, salinity, vertical profile structures of sea temperature, sea salinity are evaluated respectively. The results show that the average absolute deviation of sea surface temperature is about 0.3 °C, the average absolute deviation of sea surface salinity is about 0.5 psu, the average absolute deviation of sea surface height is about 0.06 m, and the average absolute deviation of see surface current velocity is about 0.08 m/s. Among them, the difference between volume conservation and mass conservation is not large, about from percentile to thousandth percentile. In the vertical direction, the temperature profiles of the two versions are generally consistent, and The maximum deviation from GLORY data is about 0.5°C at depths of 100-400m. In terms of salinity profile, the deviation between the two versions and GLORY mainly exists in the depth range of 200-800 meters, and the deviation is 0.1-0.3 psu. On the whole, MaCOM runs stably and the results are good. It can well reproduce the temperature and salinity characteristics, ocean current field and dynamic environment of the ocean, and is consistent with the internationally recognized high-precision reanalysis data. It is suitable as another powerful tool for studying the ocean.

Observed Relationships between Sea Surface Temperature, Vertical Wind Shear, Tropical Organized Deep Convection, and Radiative Effects

Abstract Organized deep convective activity has been routinely monitored by satellite precipitation radar from the Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Mission (GPM). Organized deep convective activity is found to increase not only with sea surface temperature (SST) above 27°C, but also with low-level wind shear. Precipitation shows a similar increasing relationship with both SST and low-level wind shear, except for the highest low-level wind shear. These observations suggest that the threshold for organized deep convection and precipitation in the tropics should consider not only SST, but also vertical wind shear. The longwave cloud radiative feedback, measured as the tropospheric longwave cloud radiative heating per amount of precipitation, is found to generally increase with stronger organized deep convective activity as SST and low-level wind shear increase. Organized deep convective activity, the longwave cloud radiative feedback, and cirrus ice cloud cover per amount of precipitation also appear to be controlled more strongly by SST than by the deviation of SST from its tropical mean. This study hints at the importance of non-thermodynamic factors such as vertical wind shear for impacting tropical convective structure, cloud properties, and associated radiative energy budget of the tropics. Significance Statement This study uses tropical satellite observations to demonstrate that vertical wind shear affects the relationship between sea surface temperature and tropical organized deep convection and precipitation. Shear also affects associated cloud properties and how clouds affect the flow of radiation in the atmosphere. Although how vertical wind shear affects convective organization has long been studied in the mesoscale community, the study attempts to apply mesoscale theory to explain the large-scale mean organization of tropical deep convection, cloud properties, and radiative feedbacks. The study also provides a quantitative observational baseline of how vertical wind shear modifies cloud radiative effects and convective organization, which can be compared to numerical simulations.

Assessment of thermocline depth bias in the Seychelles-Chagos Thermocline Ridge of the Southwestern Indian Ocean simulated by the CMIP6 models

The Seychelles-Chagos Thermocline Ridge (SCTR, 5°S-10°S, 50°E-80°E) is a unique open-ocean upwelling region in the southwestern Indian Ocean. Due to the negative wind stress curl between the equatorial westerlies and southeasterly trade winds, SCTR is known as a strong upwelling region with high biological productivity, providing a primary fishing zone for the surrounding countries. Given its importance in shaping the variability of the Indian Ocean climate by understanding the sea-air interaction and its dynamics, the simulation of SCTR is evaluated using outputs from the Coupled Model Intercomparison Project Phase Sixth (CMIP6). Compared to observations, 23 out of 27 CMIP6 models tend to simulate considerably deeper SCTR thermocline depth (defined as the 20°C isotherm depth (D20))– a common bias in climate models. The deep bias is related to the easterly wind bias in the equatorial to southern Indian Ocean, which is prominent in boreal summer and fall. This easterly wind bias produces a weak annual mean Ekman pumping, especially in the boreal fall. Throughout the year, the observed Ekman pumping is positive and is driven by two components: the curl term, is associated with the wind stress curl, leads to upwelling during boreal summer to fall; the beta term, is linked to planetary beta and zonal wind stress, contributes to downwelling during boreal spring to fall. However, the easterly wind bias in the CMIP6 increases both the positive curl and negative beta terms. The beta term bias offsets the curl term bias and reduces the upwelling velocity. Furthermore, the easterly wind bias is likely caused by the reduced east-west sea surface temperature (SST) difference associated with a pronounced warm bias in the western equatorial Indian Ocean, accompanied by the east-west mean sea level pressure gradient over the Indian Ocean. Furthermore, this study finds local wind-induced Ekman pumping to be a more dominant factor in thermocline depth bias than Rossby waves, despite CMIP6 models replicating Rossby wave propagation. This study highlights the importance of the beta term in the Ekman pumping simulation. Thus, reducing the boreal summer-to-fall easterly wind bias over the Indian Ocean region may improve the thermocline depth simulation over the SCTR region.

The role of in situ ocean data assimilation in ECMWF subseasonal forecasts of sea‐surface temperature and mixed‐layer depth over the tropical Pacific ocean

AbstractThe tropical Pacific plays an important role in modulating the global climate through its prevailing sea‐surface temperature spatial structure and dominant climate modes like El Niño–Southern Oscillation (ENSO), the Madden–Julian Oscillation (MJO), and their teleconnections. These modes of variability, including their oceanic anomalies, are considered to provide sources of prediction skill on subseasonal timescales in the Tropics. Therefore, this study aims to examine how assimilating in situ ocean observations influences the initial ocean sea‐surface temperature (SST) and mixed‐layer depth (MLD) and their subseasonal forecasts. We analyze two subseasonal forecast systems generated with the European Centre for Medium‐Range Weather Forecasts (ECMWF) Integrated Forecast System (IFS), where the ocean states were initialized using two Observing‐System Experiment (OSE) reanalyses. We find that the SST differences between forecasts with and without ocean data assimilation grow with time, resulting in a reduced cold‐tongue bias when assimilating ocean observations. Two mechanisms related to air–sea coupling are considered to contribute to this growth of SST differences. One is a positive feedback between the zonal SST gradient, pressure gradient, and surface wind. The other is the difference in Ekman suction and mixing at the Equator due to surface wind‐speed differences. While the initial mixed‐layer depth (MLD) can be improved through ocean data assimilation, this improvement is not maintained in the forecasts. Instead, the MLD in both experiments shoals rapidly at the beginning of the forecast. These results emphasize how initialization and model biases influence air–sea interaction and the accuracy of subseasonal forecasts in the tropical Pacific.

Weakening of the Indian Ocean Dipole in the Mid-Holocene due to the Mean Oceanic Climatology Change

Abstract The Indian Ocean dipole (IOD) is one of the leading modes of interannual climate variability in the tropical Indian Ocean (IO). The paleoclimate provides real climate scenarios to examine IOD behaviors and the linkage to basic states. Based on 18 models from phases 5 and 6 of the Coupled Model Intercomparison Project (CMIP5/6), the IOD change from the preindustrial period to the mid-Holocene is investigated. The multimodel mean reveals that the IOD variability weakens by 14%, as measured by the standard deviation of the dipole mode index, which is defined using the zonal sea surface temperature (SST) difference. Such attenuation is dominated by the spatially consistent suppression in the western-pole SST variability, while the eastern pole contributes little due to the opposite-signed changes in its northwestern and southeastern portions. The primary reason for the aforementioned changes comes from the altered climatic background, which displays a positive IOD-like pattern during IOD growing seasons, with intensified westward currents along the equator and northwestward currents in the southeastern equatorial IO. Such changes in the mean-state currents modulate the strength of the IOD-related anomalous advection and subsequently cause alterations in the IOD variability. Further analyses show that the IOD attenuation in the mid-Holocene is unlikely to be caused by the concurrently subdued El Niño–Southern Oscillation in the tropical Pacific, partially because of the diminished connections between the two oscillations themselves. The above simulated changes in both the IO mean climatology and IOD variability agree well with the available paleo records in literature. Significance Statement Understanding variations in the Indian Ocean dipole (IOD) and its relationship to the altered background mean state can advance our knowledge of tropical climate dynamics. The paleoclimate provides the opportunity to address this issue under real climate scenarios in the past. Based on multiple models from CMIP5/6, we investigate IOD changes during the mid-Holocene compared to the preindustrial period. The result shows a weakening of the IOD, and the main mechanism lies in the altered anomalous advection modulated by changes in the mean-state currents. The simulated changes in both the mean state and IOD variability are consistent with available paleo data. The present study extends the research scale of IOD dynamics beyond instrumental periods and provides scientific bases for deciphering geological records.

Millennial-scale paleotemperature change in the Japan Sea during Marine Isotope Stage 3: Impact of meridional oscillation of the subpolar front

The Japan Sea is a semi-closed marginal sea that has been significantly affected by fluctuations of the East Asian monsoon. Due to its geographic setting, the influence of the monsoon is significant especially during the last glacial period, when the low sea level stand restricted surface water exchange with adjacent seas. Millennial-scale change in the summer monsoon controlled the input of freshwater and nutrients into the Japan Sea during Marine Isotope Stage (MIS) 3, resulting in the deposition of alternating dark- and light-colored sedimentary layers. However, the relationships between the sediment color alternations and winter sea surface conditions, such as temperature and salinity, are not understood. Here, we provide high-resolution Mg/Ca-based winter sea surface temperature (SST) records during MIS3 from two sediment cores from the southern Japan Sea. The SSTs at both sites showed millennial-scale fluctuations with significantly different amplitudes. The southern site had a larger SST amplitude with warmer in dark- and cooler in light-colored intervals. The SST difference between the two cores was greater in dark-colored intervals. The millennial-scale changes in SST difference are probably attributable to meridional migration of the subpolar front, induced by winter monsoons and inflow of the Tsushima Warm Current, which had a northerly (southerly) position during interstadials (stadials). The results suggest that the millennial-scale winter monsoon variability contributed to sediment color alternation via greater cooling during stadials, which enhanced ventilation, in conjunction with the summer monsoon-induced productivity change. Therefore, both the winter and summer monsoons are key drivers of the oceanographic condition in the Japan Sea.

Interdecadal Variation of Spring Extreme High-Temperature Events in the Western Tianshan Mountains and Its Relationship with the Tropical SST

This study performed an observational analysis to examine the interdecadal variation in the frequency of extreme high-temperature events (EHEs) during spring over the western Tianshan mountain, China, which were characterized by relatively fewer (more) EHEs during 1983–1996 (2000–2015). A composite analysis indicated that the interdecadal increase in EHEs is closely related to a deep dynamic anomalous Iranian high. Under the control of this high system, the water vapor content decreased over the western Tianshan mountains, and atmospheric circulation was dominated by a descending motion. Both were attributed to the decreased cloud cover, inducing a cloud-forced net solar radiation increase. The short-wave radiation flux and sensible heat flux reaching the surface increased, and the net surface heat flux increased cumulatively, which was conducive to the surface temperature increase and EHE occurrence. The anomalous Iranian high responsible for ECEs occurrence was related to the air-sea interaction over the Atlantic and Indo-Pacific. The latitudinal sea surface temperature (SST) difference between the tropical western Pacific and the western Indian Ocean directly strengthens the Walker circulation and thus enhances the Iranian high. In addition, the anomalous Iranian high was affected by the atmospheric wave trains at middle latitude, which was triggered by the warm anomaly of the Atlantic SST.