Sea Surface Temperature Distribution Research Articles

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.

Imaging performance prediction of a hypersonic target in a geosynchronous orbit based on multi-dimensional information correlation of radiation, multi-spectral, and polarization

Hypersonic target detection based on infrared intensity characteristics is easily disturbed by sea surface and cloud flares when detected by space-based optical systems, which results in a low detection rate, high false alarm, and difficulty in stable detection. This paper explores a method to improve target detection performance based on the correlation of infrared radiation, multi-spectral and polarization. Firstly, the comprehensive factors that influence complex ambient illumination, atmospheric transmission, and clutter background on spectral-polarization characteristics of hypersonic targets are analyzed. Based on the global radiation scattering theory, the temperature distribution model of the hypersonic target is established by using FLUENT. The polarization emission and pBRDF model of the target is established, and the radiation polarization transfer model is generated. Secondly, the sea surface temperature distribution is obtained by inversion of Landsat8 remote sensing data. The radiation polarization transfer model of the sea surface is established based on the Cox-Munk model combined with pBRDF and the polarization emission model. Thirdly, the polarization scattering effect of atmospheric particles on the upward radiation of the interaction of the target with the sunlight is considered comprehensively, and the 6SV radiative transfer model is used to calculate the polarization effect of atmospheric particles on the upward radiation transmission of the target and the background. Then, combined with the point diffusion of the optical system and the photoelectric conversion of the detector, the multi-dimensional full-chain imaging prediction model of the hypersonic target-sea background-ambient atmosphere-optical system-detector is established. The imaging characteristics and detection performance of the target in different imaging dimensions are simulated and analyzed with the signal-to-clutter ratio (SCR). The research shows that in the direction of reflected sunlight from the sea surface, the sea surface glare is suppressed and the target is highlighted through a target detection method of multi-dimensional information. This method has better detection results than the infrared multi-spectral detection method.

Seasonal variations in chlorophyll–a and sea surface temperature in the exclusive economic zone of Sri Lanka

Oceanic phytoplankton plays a crucial role in regulating the biogeochemical cycle in marine ecosystems. Light harvesting pigments such as chlorophyll–a (chl–a) can be used to understand marine primary productivity, especially phytoplankton abundance. Sea surface temperature is closely linked with phytoplankton abundance and climatic changes. The objective of the current study is to determine spatial and temporal variations of chl–a and sea surface temperature and their co-variation, over 12 years using statistical methodologies and Remote Sensing, Geographic Information System (GIS) and Cloud Computing Approach. In this study, the available sea surface temperature and chl–a data acquired from a Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensor were proceeded through Google Earth Engine and Earth Science Data System. Data visualization was carried out using ArcMap™ software. Results show a weak negative linear relationship (−0.40, P < 0.05) between sea surface temperature and chl–a. Therefore, additional favorable environmental factors such as coastal upwelling, and nutrient discharge through river run-off can control the primary productivity of phytoplankton. We also illustrated spatial and temporal maps for chl–a and sea surface temperature distribution in the exclusive economic zone of Sri Lanka. Chlorophyll–a concentration is enhanced during the southwest monsoon, and the lowest concentration is observed during the first inter-monsoon period. Next, the highest sea surface temperature is recorded during the first inter-monsoon period, and the lowest sea surface temperature is observed during the northeast monsoon. Seasonal behavior of chl–a concentration and sea surface temperature are changed as chl–a (SWM) > chl–a (NEM) > chl–a (SIM) > chl–a (FIM) and SST (FIM) > SST (SIM) > SST (SWM) > SST (NEM), respectively. In addition, both trend lines for each variable show a positive gradient, which may be attributed to global warming. Finally, we observed the alteration of chl–a and sea surface temperature that linked to changes in ocean chemistry during the global COVID–19 pandemic.

Investigating extreme marine summers in the Mediterranean Sea

Abstract. The Mediterranean Sea (MS) has undergone significant surface warming, particularly pronounced during summers and associated with devastating impacts on marine life. Alongside the ongoing research on warming trends and marine heatwaves (MHWs), here we address the importance of understanding anomalously warm conditions also on the seasonal timescale. We propose the concept of extreme marine summers (EMSs) and investigate their characteristics in the MS, using sea surface temperature (SST) reanalysis data spanning 1950–2020. We define EMSs at a particular location, as the summers with a mean summer SST exceeding the 95th percentile. A marine summer may become extreme, under various SST substructures. Results show that, in most of the basin, EMSs are formed primarily due to the warmer summer days being warmer than normal. Areas where the warmest (coldest) part of the SST distribution is more variable experience EMSs primarily due to the warmest (coldest) part of the distribution being anomalously warm. MHWs occurring within EMSs are more intense, longer lasting, and more frequent than usual mainly in the northern MS regions. These enhanced MHW conditions occur mainly within the warmest part of the SST distribution. By means of temporal coverage of MHW conditions, a more pronounced occurrence of MHWs in EMSs is found for the central and eastern basin where up to 55 % of MHW days over 1950–2020 fall within EMSs. The role of air–sea heat fluxes in driving EMSs is quantified through a newly proposed metric. Results suggest that surface fluxes primarily drive EMSs in the northern half of the MS, while oceanic processes play a major role in southern regions. Upper-ocean preconditioning also contributes to the formation of EMSs. Finally, a detrended dataset was produced to examine how the SST multi-decadal variability affects the studied EMS features. Despite leading to warmer EMSs basin-wide, the multi-decadal signal does not significantly affect the dominant SST substructures during EMSs. Results also highlight the fundamental role of latent heat flux in modulating the surface heat budget during EMSs, regardless of the long-term trends.

Emergent Constraint on Projection of the North Pacific Monsoon Trough and Its Implications for Typhoon Activity Using CMIP6 Models

AbstractThe North Pacific monsoon trough (NPMT) is an imperative large‐scale circulation pattern influencing tropical cyclone (TC) activity in the western North Pacific (WNP), thus its future change has great implications for the WNP TC activity. Here future change in the NPMT and its uncertainty are examined by using 35 climate models from Phase six of Coupled Model Intercomparison Project (CMIP6). Due to the El Niño‐like sea surface temperature (SST) pattern, the multi‐model ensemble (MME) mean projects an eastward extension of the NPMT in the latter half of the 21st century. However, considerable inter‐model uncertainty exists in the projection, which is associated with the diversity in the zonal SST gradient across the tropical Pacific. This diversity in the projected SST is largely rooted in the simulated precipitation biases in the tropical Pacific in the historical experiments of CMIP6 models, which can modulate future Pacific SST distribution through the shortwave‐SST feedback. This linkage between biases in historical climate and future climate allows us to constrain the projection by using observational data sets. Emergent constraint using observational precipitation data set reduces the projection uncertainty by 48% and projects an eastward extension of the north Pacific NPMT by 6.2°. This eastward extension of the NPMT indicates an eastward migration of TC genesis location, and elongated TC track and thus strengthened TC intensity, suggesting an increased TC‐related disaster for residents near the WNP.

Regional Comparison of Performance between EnKF and EnOI in the North Pacific

Abstract The North Pacific is divided into different regions based on ocean currents and sea surface temperature (SST) distribution. Data assimilation is a useful tool for generating accurate ocean estimates because of the limited availability of observational data. This study compared the performances of two data assimilation methods, ensemble optimal interpolation (EnOI) and ensemble Kalman filter (EnKF), in various North Pacific subregions using an ocean model configured with the Regional Ocean Modeling System (ROMS). Both methods assimilated spaceborne SST observations, and the simulation results varied by subregion. The study found that EnKF and EnOI methods performed better than the control model in all regions when compared against satellite SST. EnOI reproduced SST as well as EnKF and required fewer computational resources. However, EnOI performed worse than the control model at sea surface height (SSH) in the equatorial region, while EnKF’s performance improved. This was due to the crushed mean state in the EnOI, which used long-term historical data as an ensemble member. El Niño–Southern Oscillation at the equator drove substantial interannual variability that crushed the ensemble mean of SSH in the EnOI. It is crucial to use a suitable assimilation method for the target area, considering the regional properties of ocean variables. Otherwise, the performance of the assimilated model may be even worse than that of the control model. While EnKF is better suited for regions with high variability in ocean variables, EnOI requires fewer computational resources. Thus, it is crucial to use a suitable assimilation method for accurately predicting and understanding the dynamics of the North Pacific.

Aquaplanet simulations with winter and summer hemispheres: model setup and circulation response to warming

Abstract. To support further understanding of circulation changes in a warming climate, an idealised aquaplanet model setup containing summer and winter hemispheres is presented, and the results of circulation changes under warming are discussed. First, a setup is introduced that enables aquaplanet simulations with a warmer and a colder hemisphere, including realistic-looking summer and winter jet streams, storm tracks, and precipitation patterns that are fairly similar to observations, as well as a more intense and equatorward storm track in the winter compared to the summer hemisphere. The sea surface temperature (SST) distribution used here is inspired by the June–July–August zonal mean SST found in reanalysis data and is flexible to allow control of the occurrence of a single or double intertropical convergence zone (ITCZ). The setup is then used to investigate circulation changes under uniform warming, as motivated by recent research. For example, the stronger poleward shift of the storm tracks during summer compared to winter is reproduced. Furthermore, the jet waviness decreases under warming when compared on isentropes with maximum wind speed or isentropes at similar heights in pressure space. Jet stream waviness increases under warming when compared at similar-valued isentropes but primarily because the corresponding isentrope is closer to the surface in the warmer climate and waviness climatologically increases downwards in the atmosphere. A detailed analysis of the changes in wave amplitude for different wavenumbers confirms that the amplitude of large waves increases with warming, while that of short waves decreases with warming. The reduction in wave amplitude of short synoptic waves is found to dominate in the jet core region, where jet waviness also decreases and is more pronounced on the equatorward side of the jet. Long waves increase in amplitude on the poleward side of the jet and at upper stratospheric levels, which is consistent with increased jet waviness at these levels. The projected increased amplitude of planetary waves and the reduced amplitude of synoptic waves are thus clear in our aquaplanet simulations and do not require zonal asymmetries or regional warming patterns. During so-called high-amplitude wave events, there is no evidence for a preferential phase of Rossby waves of wavenumbers 5 or 7, indicating the crucial role of stationary waves forced by orography or land–sea contrast in establishing previously reported preferential phases. We confirm that feature-based block detection requires significant tuning to the warmer climate to avoid the occurrence of spurious trends. After adjustment for changes in tropopause height, the block detection used here shows no trend in the summer hemisphere and an increase in blocking in the colder hemisphere. We also confirm previous findings that the number of surface cyclones tends to decrease globally under warming and that the cyclone lifetimes become shorter, except for very long-lived cyclones.

On the Role of Wind–Evaporation–SST Feedbacks in the Subseasonal Variability of the East Pacific ITCZ

Abstract The intertropical convergence zone (ITCZ) is a zonally elongated band of near-surface convergence and precipitation near the equator. During boreal spring, the eastern Pacific ITCZ migrates latitudinally on daily to subseasonal time scales, and climate models exhibit the greatest ITCZ biases during this time of the year. In this work, we investigate the air–sea interactions associated with the variability in the eastern Pacific ITCZ’s latitudinal location for consecutive days when the ITCZ is only located north of the equator (nITCZ events) compared to when the ITCZ is on both sides of the equator or south of the equator (dsITCZ events) during February–April. The distribution of sea surface temperature (SST) anomalies and surface latent heat flux (SLHF) anomalies during the nITCZ and dsITCZ events follow the classic wind–evaporation–SST (WES) positive feedback mechanism. However, an alternative mechanism, embracing the effect of SST anomalies on vertical stratification and momentum mixing, gives rise to a negative WES feedback. Our results show that in the surface layer, there is a general progression of positive WES feedbacks happening in the weeks leading to the events followed by negative WES feedbacks occurring after the ITCZ events, with an alternate mechanism involving air–sea humidity differences limiting evaporation occurring in between. Additionally, the spatial structures of the components of the feedbacks are nearly mirror images for these opposite ITCZ events over the east Pacific during boreal spring. In closing, we find that understanding the air–sea interactions during daily to weekly varying ITCZ events (nITCZ and dsITCZ) helps to pinpoint how fundamental processes differ for ITCZs in different hemispheres.

Geospatial analysis for prediction of potential fishing zones in the Banggai Waters using hydroacoustic data and satellite remote sensing

Banggai waters are a strategic area rich in fish resources and a source of livelihood for most of the local population. Mapping fish stocks is important to ensure the sustainability of fishing in the area. One of them uses hydroacoustic data and satellite imagery to provide more comprehensive results on fish stocks and more accurate predictions of potential fishing zones. This study will spatially estimate fish density in Banggai waters using hydroacoustic data and investigate the distribution of chlorophyll-a and sea surface temperature using Himawari-8 imagery. Hydroacoustic data processing will produce target strength (TS) and volume backscatter strength (Sv) values to determine the value and distribution of fish density. Meanwhile, ZPPI results are obtained from the overlay of chlorophyll-a and sea surface temperature. From the results of mapping the potential fishing zone, the high category has the highest percentage of 43%, low 28% and medium 29%. The ZPPI point distribution map then shows the concentration of ZPPI points in the southern Banggai waters. The fish density distribution map shows that the spatial distribution tends to be around the coast of Banggai Peninsula, dominated by small and very small fish categories. Correlation of fish density point distribution with ZPPI results and oceanographic parameters has a positive influence on fish density from GAM modelling.

Analysis of Chlorophyll-A Distribution And Sea Surface Temperature for Estimation of Skipjack Fishing Grounds (Katsuwonus Pelamis) Based on Different Seasons in South Buton Waters

The success of fishing activities is certainly greatly influenced by the conditions of the Fishing Ground (FG). Therefore, information about potential fishing areas is needed by fishermen in fishing activities. Chlorophyll-a is the primary productivity in water. The development of aquatic chlorophyll is influenced by Sea Surface Temperature (SST). The purpose of this study was to analyze the distribution of chlorophyll-a and sea surface temperature (SST) for estimating fish fishing areas based on different seasons in South Buton Waters. This type of research is exploratory research. This study used remote sensing method. The direct interview method with respondents aims to validate data (fishermen) from remote sensing processing. The study used Aqua Modis satellite imagery data to derive parameter values of chlorophyll-a and sea surface temperature. The results of the analysis of the distribution of chlorophyll-a in South Buton waters are the highest with chlorophyll-a concentrations ranging from 0.3-3.0 mg / m³ spread in the waters of Sampolawa and Batauga Districts with surface temperatures ranging from 26 °C and 33 °C. Eastern and Transitional Season II have high levels of chlorophyll-a concentration. This season will be a potential skipjack fishing area in South Buton Waters.

Potential for Development of Seaweed Cultivation Business Post Covid-19 Post in the Marine Area, Serangan City, Denpasar - Bali

The aim of this research was to outline the possibilities for seaweed farming in Serangan Denpasar, Bali's maritime waters. study based on Aqua Modis satellite photography findings. The results of satellite photography for water depth are used, together with SST (Sea Surface Temperature) distribution photos taken between January and June 2019 and January and June 2023. Based on observations, the attack sea's waters contain an area of 70.61 Ha that could be used for seaweed production in 2019. 71.82 Ha could be used for seaweed farming in 2023

Analysis of Sea Surface Temperature and Chlorophyll-A and Its Relationship with Catch Results Flying Fish Eggs in the Waters of the Kei Islands

The Kei Islands water area is quite productive in fisheries management. Environmental characteristics and oceanographic factors in a body of water will determine the potential of fisheries resources in a water body, and influence fish movement patterns and the formation of fishing areas for flying fish eggs. This research aims to examine the distribution of sea surface temperature and chlorophyll-a concentrations and analyze the relationship between sea surface temperature and chlorophyll-a concentrations with catches of flying fish eggs. The research focused on the waters of the Kei Islands, Southeast Maluku, which is an area for catching flying fish eggs. The research data was studied in the period December 2014 – November 2017. SPL and Chlorophyll-a data were downloaded from Citra MODIS-Aqua, while data on flying fish egg production was obtained from PPN Tual. The research results show that the monthly average SST distribution is between 25.03-30.42ºC, and the monthly average of chlorophyll-a varies quite widely with a range of 0.05-3.09 mg/m3. The number of flying fish egg production fluctuates every year with a production range of 36.28-81.905 kg. The peak of catching flying fish eggs occurs in June-September (eastern season and transition season II). The results of the analysis show that the correlation between SST and chlorophyll-a variables has a very dominant influence on the abundance of flying fish eggs.

Revisiting the Global Energy Budget Dynamics with a Multivariate Earth Energy Balance Model to Account for the Warming Pattern Effect

Abstract Climate feedbacks are sensitive to the geographical distribution of sea surface temperature (SST). This sensitivity, called the pattern effect, affects the amplitude of the Earth radiative response to anomalies in global mean surface temperature (GMST) and thus is essential in shaping the global energy budget dynamics. Zero-dimensional energy balance models (EBMs) are the simplest representation of the global energy budget dynamics. Many only depend on GMST anomalies and cannot account for the pattern effect explicitly. In EBMs, the pattern effect leads to apparent variations of the global climate feedback parameter λ. Assuming a variable λ in EBMs enables them to more accurately reproduce AOGCM simulations of the GMST anomalies but it leads to variations in λ of &gt;+15%. These large variations mean λ is not a constant and the Taylor expansion underpinning EBMs’ formulation does not hold, casting doubts on the physical grounding of such EBMs. Here we propose a new EBM based on a multivariate linear Earth radiative response, which depends on both the GMST and the surface warming pattern. The resulting multilinear EBM accurately reproduces AOGCM simulations of anomalies in Earth radiative response and GMST under abrupt 4xCO2 forcing. When interpreted in terms of variable λ, the multivariate EBM leads to small variations in λ that are physically consistent with the underpinning Taylor expansion. We analyze with the multivariate framework the variations of the planetary heat uptake N as a function of the GMST and the pattern of warming through a 3D generalization of the Gregory plot. We show that the apparent nonlinear behavior of the radiative response of the Earth against GMST seen in classical monovariate EBMs (and in classical Gregory plots) can actually be explained by a bilinear dependance of the radiative response of the Earth on the GMST and the pattern of warming. The multivariate EBM further provides an explicit dependence of the global energy budget on the pattern of warming and on the climate state. It has important consequences on the expression of the climate sensitivity.

Projections of central Arctic summer sea surface temperatures in CMIP6

One of the most dramatic climate responses to future global warming is the near-disappearance of the perennial sea ice cover in the central Arctic Ocean, a phenomenon known as the ice-free summer Arctic. The immediate consequence of an ice-free Arctic would be the surface warming of the central Arctic Ocean, where sea surface temperatures (SSTs) used to be at freezing levels. Through an analysis of climate models participating in the climate model intercomparison project phase-6, this study demonstrates a wide range of responses in the central Arctic SSTs in August–September as a result of the projected ice-free summer Arctic. These responses vary from 0.7 to 8 °C in the shared socioeconomic pathway 2 (SSP2-4.5), referred to as the ‘middle of the road’ scenario, in which socioeconomic and technological trends do not significantly deviate from historical patterns. The extent of the central Arctic sea surface warming in August–September is found to have a loose correlation with the September sea ice extent (SIE), but a stronger connection to the SIE during spring to early summer (May–July), when incoming shortwave radiation is most intense. In certain climate models, the perennial sea ice cover disappears completely in September, causing central Arctic SSTs to rise by 5 °C–8 °C by the end of the 21st century. This leads to a bimodal distribution of annual SSTs. Further analysis reveals a close relationship between mid-summer SSTs in the central Arctic Ocean and preceding winter sea ice thickness (SIT). This underscores the significance of winter SIT in predicting future Arctic surface warming and marine heatwaves.

KAJIAN KUALITAS AIR DI PERAIRAN DESA SUMBERKIMA DAN DESA PEMUTERAN, KECAMATAN GEROKGAK, KABUPATEN BULELENG, PROVINSI BALI

Water quality has a significant impact on aquaculture productivity. Water quality characteristics influence fishing production. This study employs numerous prior research techniques to assess air quality factors such as Total Suspend Solid (TSS), salinity, Sea Surface Temperature (SST), and dissolved oxygen. However, physical elements such as rainfall, which are separated into wet and dry months in this study, have an impact on water quality. The approach was developed using Landsat-8 OLI satellite images. The algorithm's output is validated for data accuracy using Pearson correlation, root mean square error (RMSE), and R-square. The findings suggest that the distribution of water quality in dry and rainy months is low in coastal areas and high in locations adjacent to open waters. Furthermore, it was discovered that the average value of the distribution of TSS in dry months was lower than in wet months, the mean value of the distribution of salinity in dry months was higher than in wet months, the average value of the SST distribution in dry months was higher than in wet months, and the mean value of the dissolved oxygen distribution in dry months was lower than in wet months.&#x0D; Keywords: Water suitability; Landsat-8; Water Quality; Remote Sensing

Analysis of Fringescale Sardine Fishing Grounds (Sardinella fimbriata) Based on Sea Surface Temperature and Chlorophyll-A in Tegal Waters, Indonesia

An alternative that can be done in determining the fishing area is to use remote sensing technology through the approach of sea surface temperature distribution and chlorophyll-a. The purpose of this study was to determine the value of the distribution of sea surface temperature and chlorophyll-a, as well as analyze the relationship between sea surface temperature and chlorophyll-a on Fringescale sardine (Sardinella fimbriata). The research method used is the descriptive method. The research data taken are in-situ data and SNPP Viirs satellite imagery data, as well as capture data from 2018 – 2022. Data analysis used multiple linear regression methods and Pearson correlation analysis. The results showed that the sea surface temperature distribution value ranged from 29.5°C – 29.9°C and chlorophyll-a ranged from 0.0545 mg m-3 – 0.4022 mg m-3. The value of sea surface temperature and chlorophyll-a in Tegal waters on land tends to have a higher value compared to high seas waters. Analysis conducted between sea surface temperature and chlorophyll-a on catches found a coefficient of determination of 0.74 or 74% affecting the total catch. The partial correlation between sea surface temperature and catch is 0.81 or 81%. The correlation between chlorophyll-a and catch is 0.86 or 86% where this value is included in the very strong category in influencing the catch of Sardinella fimbriata. Fishermen no longer rely on instinct to predict potential fishing zone each season, but it has taken advantage of variables that affect the presence of S. fimbriata using potential fishing zone map.

Northward shift of the Kuroshio Extension during 1993–2021

The Kuroshio Extension (KE) flows eastward at the northern boundary of the North Pacific subtropical gyre. By transporting large amounts of seawater with heat, the KE contributes significantly to the formation of sea surface temperature (SST) fields. Recently, poleward shifts of major ocean gyres in the world ocean, including the North Pacific subtropical gyre, have been highlighted based on basin-scale changes in SST and sea surface height (SSH) distributions. However, a detailed investigation of the long-term meridional KE movement has not been presented. Investigation of KE path changes helps provide insights into long-term changes in the physical fields in the western North Pacific. In this study, we identified the KE path from satellite-derived SSH and surface current velocity data using a front identification method and showed that the KE migrated northward by approximately 210 km during 1993–2021. We further explored the cause of the northward KE shift based on atmospheric reanalysis data and numerical experiments using a high-resolution ocean general circulation model. It was revealed that the northward KE shift is mostly caused by the trend of wind stress curl in the North Pacific during 1993–2021.

The Long-Term Trends of Global Land Precipitation in GFDL’s CM4 and ESM4 Climate Models

Abstract Historical precipitation and temperature trends and variations over global land regions are compared with simulations of two climate models focusing on grid points with substantial observational coverage from the early twentieth century. Potential mechanisms for the differences between modeled and observed trends are investigated using subsets of historical forcings, including ones using only anthropogenic greenhouse gases or aerosols, and simulations forced with the observed sea surface temperature and sea ice distribution. For century-scale (1915–2014) precipitation trends, underestimated increasing or unrealistic decreasing trends are found in the models over the extratropical Northern Hemisphere. The temporal evolution of key discrepancies between the observations and simulations indicates that 1) for averages over 15°–45°N, while there is not a significant trend in observations, both models simulate reduced precipitation from 1940 to 2014, and 2) for 45°–80°N observations suggest sizable precipitation increases while models do not show a significant increase, particularly during ∼1950–80. The timing of differences between models and observations suggests a key role for aerosols in these dry trend biases over the extratropical Northern Hemisphere. Additionally, 3) for 15°S–15°N the observed multidecadal decrease over tropical west Africa (1950–80) is only roughly captured by simulations forced with observed sea surface temperature; additionally, 4) in the all-forcing runs, the model with higher global climate sensitivity simulates increasing trends of temperature and precipitation over lands north of 45°N that are significantly stronger than the lower-sensitivity model and more consistent with the observed increases. Thus, underestimated greenhouse gas–induced warming—particularly in the lower sensitivity model—may be another important factor, besides aerosols, contributing to the modeled biases in precipitation trends.

Effects of paleogeographic changes and CO2 variability on northern mid-latitudinal temperature gradients in the Cretaceous

The Cretaceous ‘greenhouse’ period (~145 to ~66 million years ago, Ma) in Earth’s history is relatively well documented by multiple paleoproxy records, which indicate that the meridional sea surface temperature (SST) gradient increased (non-monotonically) from the Valanginian (~135 Ma) to the Maastrichtian (~68 Ma). Changes in atmospheric CO2 concentration, solar constant, and paleogeography are the primary drivers of variations in the spatiotemporal distribution of SST. However, the particular contribution of each of these drivers (and their underlying mechanisms) to changes in the SST distribution remains poorly understood. Here we use data from a suite of paleoclimate simulations to compare the relative effects of atmospheric CO2 variability and paleogeographic changes on mid-latitudinal SST gradient through the Cretaceous. Further, we use a fundamental model of wind-driven ocean gyres to quantify how changes in the Northern Hemisphere paleogeography weaken the circulation in subtropical ocean gyres, leading to an increase in extratropical SSTs.

Intermodel Biases of the Western North Pacific Monsoon Trough in CMIP6 Models

Abstract The impact of climate change on tropical cyclone (TC) activity is often assessed by various downscaling approaches, statistical–dynamical frameworks, and high-resolution global climate models using the projected changes of environmental factors. Uncertainty in simulating and projecting TC-relevant, large-scale circulation is closely linked to the projection of TC activity in a warming climate. Based on the model output in phase 6 of the Coupled Model Intercomparison Project (CMIP6), this study examines the intermodel biases in simulating the western North Pacific monsoon trough (MT), which is one of the most important large-scale circulation systems for TC activity, especially TC formation. It is found that most CMIP6 models can successfully simulate the climatological mean structure of the MT, although considerable biases remain in its exact location and its simulated historical changes. The mean latitude of the simulated MT spreads between 10° and 20°N, with noticeable differences in its orientation. The multimodel ensemble mean indicates that the MT exhibits no significant long-term zonal and poleward shifts in the future scenarios, consistent with the projection in the selected models in which the simulated MT resembles the observed spatiotemporal characteristics of the counterpart. Further analysis suggests that the intermodel bias in the simulated MT location is closely related to the east–west contrast of sea surface temperature (SST) anomalies in the tropical Pacific. More attention is required on improving the simulation of the basinwide SST distribution and its associated MT to reduce the uncertainty in predicting the future location of TC formation.