Sea Surface Temperature Patterns Research Articles

Nonstationary Teleconnections Over North America Revealed in Paleoclimate Data Assimilation Reconstructions Spanning the Last Millennium

AbstractModes of climate variability, such as the El Niño Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), and Atlantic Multi‐decadal Oscillation (AMO), have been shown to have large impacts on North American hydroclimate through their atmospheric teleconnections. However, short instrumental records limit our ability to examine the long‐term stability (or stationarity) of hydroclimate teleconnections. Here, we use two last millennium (LM) paleoclimate data assimilation (DA) products to assess the stationarity of hydroclimate teleconnections over two key regions: the southwestern U.S. and Lower Mississippi River basin. Moving correlations between climate indices and regional hydroclimate expose highly nonstationary regional hydroclimate teleconnections with significant periodic variations on multi‐decadal and multi‐centennial timescales. Although limitations of the DA products prohibit a robust analysis of climate mode intensity, consistent sea surface temperature (SST) patterns between DA products during strong and weak teleconnection periods suggest that changing teleconnection strength is driven by the changing relationships between climate modes over the LM. Although our results are sensitive to proxy availability, the DA techniques provide novel insight into the nonstationarity and long‐term variability of North American hydroclimate teleconnections. This work provides a baseline for teleconnection behavior from DA products, which is potentially valuable for decadal prediction.

The relative importance of forced and unforced temperature patterns in driving the time variation of low-cloud feedback

Abstract Atmospheric models forced with observed sea-surface temperatures (SSTs) suggest a trend toward a more-stabilizing cloud feedback in recent decades, partly due to the surface cooling trend in the eastern Pacific (EP) and the warming trend in the western Pacific (WP). Here we show model evidence that the low-cloud feedback has contributions from both forced and unforced feedback components, and that its time variation arises in large part through changes in the relative importance of the two over time, rather than through variations in forced or unforced feedbacks themselves. Initial-condition large ensembles (LEs) suggest that the SST patterns are dominated by unforced variations for 30-year windows ending prior to the 1980s. In general, unforced SSTs are representative of an ENSO-like pattern, which corresponds to weak low-level stability in the tropics and less-stabilizing low-cloud feedback. Since the 1980s, the forced signals have become stronger, outweighing the unforced signals for the 30-year windows ending after the 2010s. Forced SSTs are characterized by relatively uniform warming with an enhancement in the WP, corresponding to a more-stabilizing low-cloud feedback in most cases. The time-evolving SST pattern due to this increasing importance of forced signals is the dominant contributor to the recent stabilizing shift of low-cloud feedback in the LEs. Using single-forcing LEs, we further find that if only greenhouse gases evolve with time, the transition to the domination of forced signals occurs 10-20 years earlier compared to the LEs with full forcings, which can be understood through the compensating effect between aerosols and greenhouse gases.

An Improved Bio-Physical Parameterization for Ocean Radiant Heating in Conditions of Near-Surface Stratification.

Solar heating of the upper ocean is a primary energy input to the ocean-atmosphere system, and the vertical heating profile is modified by the concentration of phytoplankton in the water, with consequences for sea surface temperature and upper ocean dynamics. Despite the development of increasingly complex modeling approaches for radiative transfer in the atmosphere and upper ocean, the simple parameterizations of radiant heating used in most ocean models can be significantly improved in cases of near-surface stratification. There remains a need for a parameterization that is accurate in the upper meters and contains an explicitly spectral dependence on the concentration of biogenic material, while maintaining the computational simplicity of the parameterizations currently in use. Here, we assemble observationally-validated physical modeling tools for the key controls on ocean radiant heating, and simplify them into a parameterization that fulfills this need. We then use observations from 64 spectroradiometer depth casts across 6 cruises in diverse water bodies, 13 surface hyperspectral radiometer deployments, and broadband albedo from 2 UAV flights to probe the accuracy and uncertainty associated with the new parameterization. A novel case study using the parameterization demonstrates the impact of chlorophyll concentration on the structure of diurnal warm layers. The parameterization presented in this work will allow for better modeling of global patterns of sea surface temperature, diurnal warming, and freshwater lenses, without a prohibitive increase in complexity.

Nonlinear Radiative Response to Patterned Global Warming due to Convection Aggregation and Nonlinear Tropical Dynamics

Abstract Climate responses to global warming exhibit large dependence on the spatial pattern of sea surface temperature (SST) changes. A Green’s function (GF) approach—predicting the global climate response to a complex SST pattern change as the linear superposition of the response to finite-area SST perturbations evaluated in isolation—has been used to systematically evaluate and understand the top of atmosphere (TOA) radiation response to patterned warming. However, in general, the linear GF approach fails for TOA radiation reconstruction under future global warming scenarios in coupled models. Here, we show that the linear superposition of global mean TOA radiation responses to large SST warming perturbations at multiple patches (the GF approach prediction) overestimates the actual response to simultaneous multipatch perturbation. This is because the linear superposition overestimates tropical large-scale convection aggregation strengthening upon localized heating that enhances longwave radiative cooling, which is further explained by the overestimation of circulation response and associated horizontal water vapor transport. The nonadditivity of TOA radiation response is caused by the nonadditivity of convection aggregation, ultimately rooted in nonlinear tropical dynamics. We also demonstrate that the prediction error of the GF approach grows with decreasing patch size (equivalently, increasing patch number). We conclude that using the GF approach to predict future climate change could overestimate longwave radiative cooling and underestimate (effective) climate sensitivity. Numerical experiments may be used to identify specific perturbation patterns where the errors are smaller than the signal. Our research also highlights that an increase in the degree of large-scale convection aggregation has a nonlinear and negative feedback for mean warming.

Climate drivers of phytoplankton production along the Chilean coast

The west coast of South America is known for its high primary productivity. The level of phytoplankton can be measured through satellite images that detect chlorophyll (Chl), which is dependent on several oceanographic and meteorological parameters. Climate drivers such as El Niño Southern Oscillation (ENSO) and the Southeast Pacific Subtropical Anticyclone (SPSA) affect these parameters and, consequently, the phytoplankton. The objective of this study was to identify the impact of ENSO on SPSA, climate variables, and phytoplankton patterns. Composites were created using the years selected with either strongly positive or negative ENSO to understand their influence on different parameters. To create the Chl composite, it was necessary to extend it using Canonical Correlation Analysis (CCA) based on the sea surface temperature (SST) pattern. The study concludes that ENSO has a noticeable impact on Chl, mainly in the Southern Zone during the warm season. This is driven by the expansion of SPSA to the South, which increases the sea level pressure (SLP) in that region. However, predicting the Chl concentration has a high degree of uncertainty due to its complexity.

Correction to: Analysis of sea surface temperature pattern, variability and their teleconnection with rainfall dynamics over the Gulf of Guinea

Correction to: Analysis of sea surface temperature pattern, variability and their teleconnection with rainfall dynamics over the Gulf of Guinea

Drying trend in land and sea in East Asia during the warm season over the past four decades

Abstract The East Asian region is typically characterized by warm and humid conditions from late spring to summer. However, in recent decades, this region has experienced an increase in severe drying conditions, deviating from historical climatological patterns. This study investigated the precipitation − evaporation (P − E) trends across land and sea regions in East Asia (EA) during the extended summer season (April–September) from 1980 to 2022, and the key physical processes driving these trends through moisture budget decomposition and numerical experiments. The results reveal pronounced drying trends in southeastern China and the Yellow Sea and parts of the Korea Strait and Korean Peninsula over the past 43 years. The underlying physical processes driving these drying conditions differ between land and sea in EA. In southeastern China, the drying is driven by dynamic processes, particularly moisture divergence related to wind changes. This is linked to anomalous strengthening of descending motion due to the Indo-Pacific warm pool warming induced by both anthropogenic global warming and natural Pacific Decadal Oscillation-like sea surface temperature (SST) patterns. Conversely, drying in the Yellow Sea and adjacent areas is influenced by thermodynamic moisture advection. The altered humidity distribution due to global warming-induced SST patterns, which are higher over the Northwest Pacific marginal sea and lower in inland China, drives dry air transport from inland China to the Yellow Sea via background southwesterly wind. These findings enhance our understanding of the drying trend and their distinct processes in EA’s land and sea areas during the extended summer.

Contrasting Rainfall Anomaly Patterns Over South America Related to Central and Eastern Atlantic Niño Modes

ABSTRACTThe present study examines the effects of the central Atlantic Niño (CAN) and eastern Atlantic Niño (EAN) events on the seasonal precipitation in South America (SA) during the 1951–2020 period. For the CAN during the summer and autumn, an interhemispheric sea surface temperature (SST) dipole mode induces an anomalous thermally direct circulation in the 10° N–10° S band and is the main factor causing precipitation anomaly patterns with a dipole structure between northern (negative) and northeastern (positive) SA. For winter and spring, the SST pattern featuring a South Atlantic dipole induces meridional and zonal anomalous circulations, which are the mechanisms causing positive precipitation anomalies in tropical SA to the north of 20° S. In contrast, for the EAN, the precipitation anomaly patterns show large areas with anomalous dryness, particularly during summer, autumn, and spring. For summer and autumn, the east–west SST anomaly gradient in the equatorial Atlantic and the associated sea level pressure (SLP) anomalies induce equatorial westerlies and a regional Walker cell with descending motions in most tropical SA, where large areas with anomalous dryness are noted. During spring, a northward SST gradient in the tropical Atlantic induces a meridional cell with descending motions in the 0°–10° S band; meanwhile, the westward SST gradient in the equatorial Atlantic and tropical South Atlantic induces a zonal circulation with descending motions over northeastern and eastern Brazil. These descending motions extend the anomalous dryness over a large area. For the EAN events, the east–west SST gradient and the associated east–west circulation in the South American/Atlantic region are crucial elements to modulate precipitation variability in SA. Therefore, the CAN and EAN events induce distinct precipitation anomaly patterns in SA due to distinct associated regional circulation patterns. The results presented here have not been discussed before and might have relevant implications for climate monitoring and modelling studies.

Synergistic effects of the winter North Atlantic Oscillation (NAO) and El Niño–Southern Oscillation (ENSO) on dust activities in North China during the following spring

Abstract. Dust significantly influences global weather and climate by impacting the Earth's radiative balance. Based on reanalysis datasets, this study explores how the North Atlantic Oscillation (NAO) and El Niño–Southern Oscillation (ENSO) during winter impact dust activities in North China in the following spring. It is found that both the NAO and the ENSO significantly affect dust activities in North China, especially during their negative phases. When both are in their negative phases, their combined impact on dust activities exceeds that of each factor individually. The previous winter's NAO notably affects sea surface temperatures (SSTs) in the North Atlantic, associated with an anomalous tripole SST pattern. These SST anomalies persist into the following spring due to their inherent persistence, inducing an anomalous atmospheric teleconnection wave train that influences dust activities in North China. The ENSO, on the one hand, directly impacts dust activities in North China by modulating circulation over the western North Pacific. Moreover, the ENSO enhances the NAO's effect on North Atlantic SST, which explains the synergistic effects of the ENSO and NAO on dust activities in North China. This study elucidates the combined role of the NAO and ENSO in influencing dust activities in North China, providing one-season-ahead signals for predicting spring dust activities in North China.

Dominant modes of interannual variability in spring compound dry and hot events over Northern Asia and the possible mechanisms

In this study, spatial and temporal variations of spring compound dry and hot events (CDHEs) over northern Asia (NA) during 1950–2020 and the related possible mechanisms are investigated on the interannual timescale. The standardized compound event indicator (SCEI) is used to represent compound dry and hot conditions over NA, which is validated by the observed summer case of CDHEs over western Russia in 2010. The first empirical orthogonal function (EOF1) mode of the SCEI over NA presents a monopole pattern, while the EOF2 mode shows an east-west dipole pattern. Possible mechanism analysis indicates that the CDHEs tend to be modulated by local high-pressure anomalies, accompanied by reduced cloud cover and more solar radiation. The high-pressure anomalies can lead to warm temperature and water vapor divergence, which synergistically contributes to the occurrence of CDHEs. Further analysis shows that the EOF1 mode is jointly affected by the Scandinavian (SCAND) pattern and the Arctic Oscillation (AO); while the EOF2 mode is influenced by the Atlantic-Eurasian (AEA) teleconnection. Moreover, the North Atlantic tripolar pattern of sea surface temperature (SST) can influence the EOF1 mode through changing the AO. And the diagonal tripolar SST pattern over the North Atlantic affects the EOF2 mode via altering the AEA pattern. The influence of the SST patterns is further confirmed by numerical experiments using the Community Atmospheric Model version CAM-5.3.

Environmental factors affecting the distribution of deep-water rose shrimp (Parapenaeus longirostris, Lucas, 1846) abundance in the Strait of Sicily (Mediterranean Sea)

The distribution of deep-water rose shrimp (Parapenaeus longirostris, FAO 3 alpha code DPS), the main target species of demersal fisheries in the Strait of Sicily, is investigated in relation to surface parameters and biogeochemical processes. Such processes are known to influence sea bottom habitats and may be particularly relevant to the Strait of Sicily because of its relative shallowness and high surface primary production. Shrimp abundances recorded during multi-annual and seasonal trawl surveys (2004–2008) are analyzed. A GAMM and GAM model analysis is performed comparing juvenile abundances to monthly mean spatial patterns of remotely-sensed sea surface temperature (SST) and surface chlorophyll (chl), as well as their frontal structures, with a time-lag of one month, given the pelagic behavior of DPS early life stages preceding settlement. Juvenile and total shrimp abundances are also compared to the flux of particulate organic carbon (POC) to the seabed. The POC flux is computed via 1-D and 3-D models simulating sinking, re-mineralization and horizontal advection and diffusion of surface POC. The latter is derived from surface primary production maps obtained from ocean color data. Results show that the abundance of the juvenile fraction of DPS is significantly correlated with depth, distance to SST fronts and the intensity of chl fronts (correlation R2 = 80%). Furthermore, results strongly suggest the significant role of bottom POC flux in conditioning the distribution of DPS abundance, indicating that ecological processes occurring in surface waters influence food availability near the seabed in the investigated area.

Analysis of sea surface temperature pattern, variability and their teleconnection with rainfall dynamics over the Gulf of Guinea

Spatial pattern and variability of sea surface temperature SST and their teleconnections with rainfall dynamics in the Gulf of Guinea (GOG) were examined in this study. SST and rainfall data of 50 years (1970–2022) were obtained from ERA5 and NOAA CPC at 0.25° x × 0.25° and 0.5° × 0.5° spatial resolution from longitudes 10°W and 8°W, 6oW, 4oW, and 2oW and latitudes 15°N, 5oN, 3oN, 15oS, 5oS, and 3oS, distributed along the Gulf of Guinea (GOG) respectively. Analysis was further carried out on twelve rainfall gridded stations distributed along the Gulf of Guinea (GoG) for the characterization of the Rainfall-SST teleconnection across the region while the relationship between the rainfall-SST anomalies, seasonal, inter-annual, and decadal scales was carried out using correlation analyses and composites. Interpolation of the meteorological variables was carried out using Inverse Distance Weight (IDW) from the ArcGIS Spatial Analyst Tool, Ferret, and CDO which were further employed to generate the seasonal and decadal rainfall and SST maps and statistical analysis of the study area. The result of the decadal and seasonal analysis of SST variability from 1970–1980,1980–1990, 1990–2000,2000–2010,2010–2020 and 2022 indicate that SST was highest from 2010 to 2020 at 28.91 °C and fluctuated between (28.49 °C) in the 1970–1980 and (28.08 °C) for the 1980–1990 decade While the seasonal pattern of SST showed marked variability with March–April and May(MAM) recording 29.34 °C with the lowest being in June-July–August(JJA) at 28.7 °C. In terms of decadal analysis of rainfall, the period 2010–2020 recorded the highest amount of rainfall along the coast (3,145.5 mm-3,928.3 mm while 1970–1980 recorded the lowest amount of rainfall (2,650–3.310 mm. To investigate the teleconnection between of SST and rainfall dynamics, statistical analysis was used where the SST values were plotted against seasonal rainfall in 11 stations namely Abidjan, Banjul, Accra, Guinea, Conakry, Cotonou, Dakar Doula, Freetown, Lagos, Lome, and Monrovia. The outcome of the statistical analysis and Standardized Anomaly Index used indicate that Banjul, Cotonou, Dakar, and Doula exhibited statistically insignificant correlation at 0.05 confidence level while Abidjan, Accra, Lagos, Lome, Freetown, and Monrovia showed positive and statistically significant correlation. The spatial pattern of seasonal rainfall climatology categorized into DJF, MAM, JJA, and SON reveals that JJA and SON produced 80% of rainfall in the Coastal GOG followed by MAM. The study affirmed that warm and cold tongues exist in the GOG alongside positive teleconnection and that the spatial variability of SST observed in this study corresponds positively with the decadal and seasonal variability of rainfall.

Tropical Pacific trends explain the discrepancy between observed and modelled rainfall change over the Americas

Understanding the causes for discrepancies between modelled and observed regional climate trends is important for improving present-day climate simulation and reducing uncertainties in future climate projections. Here, we analyse the performance of coupled climate models in reproducing regional precipitation trends during the satellite era. We find statistically significant observed drying in southwestern North America and wetting in the Amazon during the period 1979–2014. Historical climate model simulations do not capture these observed precipitation trends. We trace this discrepancy to the inability of coupled simulations to capture the observed Pacific trade wind intensification over this period. A linear adjustment of free running historical simulations, based on the observed strengthening of the Pacific trade winds and modeled ENSO teleconnections, explains the discrepancy in precipitation trends. Furthermore, both the Pacific trade wind trends and regional precipitation trends are reproduced in climate simulations with prescribed observed sea surface temperatures (SST), underscoring the role of the tropical Pacific SST patterns.

Enhanced interaction between ENSO and the South Atlantic subtropical dipole over the past four decades

AbstractThis study investigates the relationship between sea surface temperature (SST) anomalies in the subtropical Atlantic Ocean, as represented by the Southern Atlantic subtropical dipole (SASD), and SST anomalies in the tropical Pacific Ocean, identified by the El Niño‐Southern Oscillation (ENSO). Contrary to the previously held notion of a weak relationship between SASD and ENSO as suggested by earlier literature, our analysis reveals a substantial inverse correlation between the two. This correlation exhibits significant multi‐decadal variability, which has notably intensified over the most recent two decades compared with the preceding two decades. This intensification in the SASD–ENSO inverse correlation may be attributed to the shift in ENSO regime from predominance of eastern Pacific El Niño to central Pacific El Niño events around the turn of the century. This transition triggers wavetrains that propagate along different paths, consequently influencing the South Atlantic subtropical high and inducing alterations in anomalous SST patterns in the subtropical Atlantic Ocean. These findings advance our comprehension of the interactions between South Atlantic and Pacific SST variations, which strongly influence rainfall patterns, particularly in South America and southern Africa. Understanding such teleconnection holds promise for improving sub‐seasonal to seasonal precipitation predictions in these regions.

2023 temperatures reflect steady global warming and internal sea surface temperature variability

2023 was the warmest year on record, influenced by multiple warm ocean basins. This has prompted speculation of an acceleration in surface warming, or a stronger than expected influence from loss of aerosol induced cooling. Here we use a recent Green’s function-based method to quantify the influence of sea surface temperature patterns on the 2023 global temperature anomaly, and compare them to previous record warm years. We show that the strong deviation from recent warming trends is consistent with previously observed sea surface temperature influences, and regional forcing. This indicates that internal variability was a strong contributor to the exceptional 2023 temperature evolution, in combination with steady anthropogenic global warming.

RCEMIP-II: mock-Walker simulations as phase II of the radiative–convective equilibrium model intercomparison project

Abstract. The radiative–convective equilibrium (RCE) model intercomparison project (RCEMIP) leveraged the simplicity of RCE to focus attention on moist convective processes and their interactions with radiation and circulation across a wide range of model types including cloud-resolving models (CRMs), general circulation models (GCMs), single-column models, global cloud-resolving models, and large-eddy simulations. While several robust results emerged across the spectrum of models that participated in the first phase of RCEMIP (RCEMIP-I), two points that stand out are (1) the strikingly large diversity in simulated climate states and (2) the strong imprint of convective self-aggregation on the climate state. However, the lack of consensus in the structure of self-aggregation and its response to warming is a barrier to understanding. Gaining a deeper understanding of convective aggregation and tropical climate will require reducing the degrees of freedom with which convection can vary. Therefore, we propose phase II of RCEMIP (RCEMIP-II) that utilizes a prescribed sinusoidal sea surface temperature (SST) pattern to provide a constraint on the structure of convection and move one critical step up the model hierarchy. This so-called “mock-Walker” configuration generates features that resemble observed tropical circulations. The specification of the mock-Walker protocol for RCEMIP-II is described, along with example results from one CRM and one GCM. RCEMIP-II will consist of five required simulations: three simulations with the same three mean SSTs as in RCEMIP-I but with an SST gradient and two additional simulations at one of the mean SSTs with different values of the SST gradients. We also test the sensitivity to the imposed SST gradient and the domain size. Under weak SST gradients, unforced self-aggregation emerges across the entire domain, similar to what was found in RCEMIP. As the SST gradient increases, the convective region narrows and is more confined to the warmest SSTs. At warmer mean SSTs and stronger SST gradients, low-frequency variability in the convective aggregation emerges, suggesting that simulations of at least 200 d may be needed to achieve robust equilibrium statistics in this configuration. Simulations with different domain sizes generally have similar mean statistics and convective structures, depending on the value of the SST gradient. The prescribed SST boundary condition is the only difference in the set-up between RCEMIP-II and RCEMIP-I, which enables comparison between the two; however, we also welcome participation in RCEMIP-II from models that did not participate in RCEMIP-I.

Interdecadal change in the influence of the southern annular mode to the tropical cyclone frequency over the Bay of Bengal

AbstractThe current study investigates the modulation of the tropical cyclone (TC) frequency (TCF) over the Bay of Bengal (BoB) by the southern annular mode (SAM). The analysis reveals that the SAM–TCF relationship during October–November–December has undergone interdecadal changes from significant during 1971–1994 to insignificant during 1995–2021. This contrasting influence of the SAM on the TCF occurrence is also echoed in the large‐scale environmental variables conducive to forming tropical cyclones (TCs). Based on the possible mechanism, we found that the SAM can imprint tripole sea surface temperature (SST) patterns in the southern Indian Ocean via altering surface wind speed from 1971 to 1994. The SAM‐related tripole SST pattern induces the surface‐level anticyclone anomaly, which enhances the south easterlies towards the western equatorial Indian Ocean. Such intensified anomalous wind crosses the equator and diverts towards the east to form the cyclone anomaly in the BoB. Meanwhile, at 200 hPa, the anomalous anticyclone over western Australia induces divergent wind flows over the study region. Consequently, the ascending motion in BoB promotes the tropical cyclone generation. During 1995–2021, however, the SAM is associated with the dipole SST pattern in the southern Indian Ocean. Correspondingly, the SAM‐related dipole SST yields anomalous atmospheric circulations confined to the Southern Hemisphere and eventually fails to impact the formation of TCs in the northern Indian Ocean, where the study region is located. The findings of this research can be useful in advancing our knowledge of the interannual variability of TCs activity in the BoB based on the remote climate signal.

Network-based constraint to evaluate climate sensitivity

The 2015 Paris agreement was established to limit Greenhouse gas (GHG) global warming below 1.5°C above preindustrial era values. Knowledge of climate sensitivity to GHG levels is central for formulating effective climate policies, yet its exact value is shroud in uncertainty. Climate sensitivity is quantitatively expressed in terms of Equilibrium Climate Sensitivity (ECS) and Transient Climate Response (TCR), estimating global temperature responses after an abrupt or transient doubling of CO2. Here, we represent the complex and highly-dimensional behavior of modelled climate via low-dimensional emergent networks to evaluate Climate Sensitivity (netCS), by first reconstructing meaningful components describing regional subprocesses, and secondly inferring the causal links between these to construct causal networks. We apply this methodology to Sea Surface Temperature (SST) simulations and investigate two different metrics in order to derive weighted estimates that yield likely ranges of ECS (2.35–4.81°C) and TCR (1.53-2.60°C). These ranges are narrower than the unconstrained distributions and consistent with the ranges of the IPCC AR6 estimates. More importantly, netCS demonstrates that SST patterns (at “fast” timescales) are linked to climate sensitivity; SST patterns over the historical period exclude median sensitivity but not low-sensitivity (ECS < 3.0°C) or very high sensitivity (ECS ≥ 4.5°C) models.

Impact of late winter sea surface temperature seesaw between equatorial central Pacific and Philippine Sea on early spring vegetation over the low-latitude highlands of China

In this study, the impact of late winter (January–February) sea surface temperature (SST) seesaw between equatorial central Pacific and Philippine Sea on early spring (March–April) vegetation interannual variation over the low-latitude highlands of China (CLLH) is investigated. The positive phase of late winter seesaw SST pattern, characterized by warmer (colder)-than-normal SSTs in the equatorial central Pacific (Philippine Sea), favors early spring CLLH vegetation growth. From the local perspective, the positive phase of late winter SST seesaw results in stronger (higher)-than-normal precipitation (surface air temperature) in the west (east) of the CLLH, these abnormal signals may be recorded by land surface and may persist to early spring, and this wetter(warmer)-than-normal land surface condition in the west (east) of the CLLH favors local vegetation growth. For the atmospheric circulation anomalies, the positive phase of late winter seesaw SST pattern contributes to an anomalous anticyclone over Philippine Sea in lower troposphere. On one hand, anomalous northerly winds on the eastern flank of this anomalous cyclone advect off-equatorial dry and cold air to the Maritime Continent and cause precipitation reduction there, consequently an anomalous anticyclone over the tropical north Indian Ocean in lower troposphere is excited via a Gill-type Rossby wave atmospheric response. This anomalous anticyclone leads to enhanced upward motion and increased precipitation in the west of the CLLH resultantly. On the other hand, southerly wind anomalies being the western flank of the anomalous anticyclone advect warm air to the east of the CLLH, result in increased surface air temperature there.

Contribution of internal variability to the Mongolian Plateau summer precipitation trends in MPI-ESM large-ensemble model

Summer precipitation over the Mongolian Plateau (MP) has experienced a consistent decline in recent decades. While the influence of atmospheric wave train on this reduction in precipitation has been recognized in prior studies, this study delves deeper into the physical mechanisms and quantifies the contributions of the internal atmosphere and oceanic variations to the diminishing precipitation utilizing a comprehensive 100-member ensemble simulations from the Max Planck Institute Earth System Model (MPI-ESM). Results show that the ensemble-mean precipitation in MP exhibits a positive trend and cannot explain the observed results. The precipitation trends vary significantly among individual ensemble members, highlighting the pivotal role of internal variability. The leading EOF mode of precipitation trends among ensemble members exhibits uniform variations. Further investigations reveal that the internal summer precipitation in MP is affected by the internal atmospheric circulation, the remote influence of the North Atlantic Dipole sea surface temperature (SST) anomalies, and Pacific Decadal Oscillation-like SST patterns. An eastward-propagating Rossby wave originating from the North Atlantic dipole SST anomalies provides the anomalous large-scale circulation that influences summer precipitation. The PDO contributes to reinforcing the anticyclonic anomaly over the MP. Additionally, the uncertainty of precipitation trends in MPI-ESM can be reduced by 13% through removing the internal atmospheric wave train-related precipitation variation, while oceanic factors only contribute about 7% uncertainty of precipitation variations. Our insights enhance the understanding of the physical drivers behind summer precipitation variability in the MP and effectively quantify the uncertainties stemming from internal variability.