Pacific Ocean Sea Surface Temperature Research Articles

Investigating the relative contribution from tropical Indo-Pacific SST to Asian monsoon precipitation variability using LIM

Abstract A critical issue is determining the factors that control the year-to-year variability in precipitation over Southern Asia. In this study, we employ a cyclo-stationary linear inverse model (CS-LIM) to quantify the relative contribution of tropical Pacific and Indian Ocean sea surface temperature anomalies (SSTA) to the interannual variability of the Asian monsoon, especially Indian summer monsoon rainfall (ISMR). Through a series of CS-LIM experiments, we isolate the impacts of the direct forcing from Pacific SSTAs, Indian Ocean SSTAs, and their interaction on Asian monsoon rainfall variability. Our results reveal distinct patterns of influence with the direct forcing from the Pacific (Indian) Ocean tending to enhance (reduce) the magnitude of precipitation variability, while the Indo-Pacific interaction acts to strongly damp the variability of Asian monsoon precipitation, especially over India. We further investigate these specific impacts on ISMR by analyzing the relationship between tropical Indo-Pacific SSTAs and the leading three empirical orthogonal functions (EOFs) of ISMR. The results from our CS-LIM experiments indicate that the direct forcing from ENSO enhances variability of the first and third EOFs, while the Indian Ocean SSTA opposes ENSO’s effects, which is consistent with previous studies. Our new results show that the tropical Indo-Pacific interaction strongly damps ISMR variability, which is due to the ENSO-induced Indian Ocean Dipole (IOD) opposing the direct impacts from ENSO on ISMR. Additionally, reduced ENSO amplitude and duration associated with the Indo-Pacific interaction may also contribute to the damping effect on ISMR, but this requires further study to understand the relevant mechanisms.

Relict soil evidence for post-Miocene aridification in the Atacama Desert of South America

Deep exposures of soil profiles on Miocene or Mio-Pliocene alluvial deposits were studied along a 500 km N-S transect in the Atacama Desert. These ancient deposits, with excellent surface preservation, now stand many meters above a broad incised Plio-Pleistocene alluvial terrain. Total geochemical analyses and mass balance calculations allowed the establishment of elemental gains, losses, and redistribution in the soils. From north to south (presently hyperarid to arid), the ancient soils reveal an increase in losses of rock-forming elements (Si, Al, Fe, K, Mg). Additionally, rare earth elements (REE) show losses with increasing southerly latitude and systematic patterns with soil depth. Some REEs appear to be unique chemical tracers of exogenous dust and aerosol additions to the soils. The removal of major elements and REEs is impossible in the present climate (one of salt and dust accumulation), revealing that for a significant period following the deposition of the alluvium, soils were exposed to rainfall, chemical weathering, and mass loss—with a geographical pattern that mirrors the present rainfall gradient in the region. Following the cessation of weathering, the pre-weathered soils have undergone enormous dust and salt accumulations, with the rates and types of salt accumulation consistent with latitude: (1) carbonate in the south and (2) sulfate, chlorides, and nitrates to the north. The quantity, and apparent rates, of salt accumulation have a strong latitudinal trend. Isotopes of sulfate have predictable depth patterns based on isotope fractionation via vertical reaction and transport. The relict hyperarid soils are geochemically similar to buried Miocene soils (ca. 10−9 Ma) in the region, but they differ from older Miocene soils, which formed in more humid conditions. The overall soil record for the Atacama Desert appears to be the product of changes in Pacific Ocean sea surface temperatures over time, and resulting changes in rainfall. The mid-Miocene was relatively humid based on buried soil chemistry and evidence of fluvial activity. The mid to late Miocene cooling (ca. 10−5.5 Ma) appears to have aridified the region based on paleosol soil chemistry. Pliocene to earliest Pleistocene conditions caused weathering of the relict soils examined here, and regional fluvial activity. Since the earliest Pleistocene, the region has largely experienced the accumulation of salts and, except for smaller scale oscillations (glacial-interglacial), has experienced protracted hyperaridity.

The impact of El Niño–Southern Oscillation on the total column ozone over the Tibetan Plateau

Abstract. The Tibetan Plateau (TP; approximately 27.5–37.5° N, 75.5–105.5° E) is the highest and largest plateau on Earth with a mean elevation of over 4 km. This special geography causes strong surface solar ultraviolet radiation (UV), with potential risks to human and ecosystem health, which is mainly controlled by the local stratospheric ozone concentration. The El Niño–Southern Oscillation (ENSO), the dominant mode of interannual variability on Earth, is characterised by the tropical Pacific Ocean sea surface temperature anomalies (SSTAs) and sea level pressure change for the warm-phase El Niño and cold-phase La Niña events. Although some studies have suggested the existence of positive correlation between ENSO and the total column ozone (TCO) over the TP, the mechanism underlying this effect is not fully understood. Here we use the Copernicus Climate Change Service (C3S) merged satellite dataset, the Stratospheric Water and OzOne Satellite Homogenized (SWOOSH) dataset and the TOMCAT three-dimensional (3D) offline chemical transport model forced by ERA5 meteorological reanalyses from the European Centre for Medium-Range Weather Forecasts (ECMWF) over the period 1979–2021 to investigate the influence of ENSO on the TCO over the TP. We find that the El Niño (La Niña) events favour positive (negative) TCO anomalies over the TP from wintertime of its mature phase to springtime of its decaying phase. Through studying the ozone profile, we attribute the positive (negative) TCO anomalies mainly to the increased (decreased) ozone at the 200–70 hPa levels, i.e. in the upper troposphere and lower stratosphere (UTLS) regions. Our results suggest that the El Niño events impact the TP TCO via the following potential processes: (1) a negative upper-level geopotential height anomaly associated with El Niño is responsible for a decrease in air column thickness; (2) the thickness decrease modulates reduced tropospheric temperature and thus favours a decrease in the tropopause height (TH); and (3) such a TH decrease tends to induce a change in the relative amounts of ozone-poor tropospheric and ozone-rich stratospheric air in the profile, which increases the partial column ozone in the UTLS and hence corresponds to the TP TCO increase. The La Niña events affect TP TCO in a manner resembling the El Niño events, except with anomalies of opposite sign. This work provides a systematic understanding of the influence of ENSO on ozone over the TP, which has implications for the interannual variability of ozone.

Winter precipitation predictability in Central Southwest Asia and its representation in seasonal forecast systems

In Central Southwest Asia (CSWA; 22°N to 40°N and 30°E to 70°E), winter (November to February) precipitation contributes up to 70% of the annual mean, but substantial interannual variations exist. Dynamical models exhibit subpar predictability in this region, but the limits of their skills are not well established. Here, we identify the tropical and extratropical forcings that explain ~75% of area-averaged seasonal variability in CSWA winter precipitation. Tropical forcing comes from the indirect El Niño-Southern Oscillation (ENSO) pathway, the leading mode of tropical Indian Ocean precipitation variability. This mode is coupled with ENSO-related Pacific Ocean sea surface temperature variability. A direct ENSO influence on CSWA does not extend beyond its Indian Ocean connection. Extratropical forcing comes from a large-scale mode of internal atmospheric variability. The spatial structure, variability of tropical forcing, and teleconnection with CSWA winter precipitation are skillfully depicted in two seasonal forecasting systems: the fifth-generation seasonal forecasting system (SEAS5) and Seamless System for Prediction and Earth System Research (SPEAR). Extratropical forcing’s spatial structure is also produced skillfully in the two modelling systems; however, the representation of its interannual variability and teleconnection requires improvement. While SEAS5 displays skill in representing extratropical forcing influence on CSWA winter precipitation and marginal skill in reproducing interannual variability, SPEAR has negligible ability in both areas. Consequently, these models have limited predictive skills over CSWA in winter. While improvements in representing extratropical forcing may be inherently limited as it arises from internal atmospheric variability, further research is needed to establish its predictability limits fully.

Precursory signals of summer precipitation over southern Central Asia: Combined effect of April soil moisture and sea surface temperature

AbstractThis study investigates the interannual variability of summer precipitation over Central Asia and explores its precursory signals through soil moisture (SM) and sea surface temperature (SST) anomalies. The results reveal that southern Central Asia (SCA) is a crucial SM‐precipitation coupling region where summer precipitation is significantly linked to the preceding April SM in the Turan Plain, between the Caspian Sea and the Tibetan Plateau. The preceding Turan Plain SM (TPSM) anomaly can reflect the ensuing summer SM anomalies in the SCA region due to the persistence of SM. The higher TPSM can stimulate anomalous convective ascent and associated negative geopotential height anomalies over the SCA region, which is favourable for more SCA precipitation (SCAP) during summer. Additionally, Indian and Pacific Ocean SST (IPOS) anomalies can regulate the summer SCAP through ocean and land relay effects. The preceding April can reflect the subsequent summer SST anomalies across the northern Indian Ocean and South China Sea, which trigger a Matsuno‐Gill response and induce anomalous water vapour transport into the SCA region, providing favourable moisture conditions for more SCAP during summer. Apart from such an ocean relay effect, the preceding IPOS can modulate the April TPSM first and then affect the summer SCAP through the land relay effect caused by persistent SM anomalies from April to summer. The combined effect of the preceding TPSM and IPOS on the summer SCAP is more pronounced than the respective effect of either TPSM or IPOS. Incorporating the TPSM signal as a supplementary precursor can enhance the predictive skill of summer SCAP. These findings may provide valuable insights into the reasons and prediction of the variability of summer SCAP.

Assessing Tropical Pacific–Induced Predictability of Southern California Precipitation Using a Novel Multi-Input Multioutput Autoencoder

Abstract We construct a novel multi-input multioutput autoencoder (MIMO-AE) to capture the nonlinear relationship of Southern California precipitation and tropical Pacific Ocean sea surface temperature. The MIMO-AE is trained on both monthly tropical Pacific sea surface temperature (TP-SST) and Southern California precipitation (SC-PRECIP) anomalies simultaneously. The covariability of the two fields in the MIMO-AE shared nonlinear latent space can be condensed into an index, termed the MIMO-AE index. We use a transfer learning approach to train a MIMO-AE on the combined dataset of 100 yr of output from a historical simulation with the Energy Exascale Earth Systems Model, version 1, and a segment of observational data. We further use long short-term memory networks to assess subseasonal predictability of SC-PRECIP using the MIMO-AE index. We find that the MIMO-AE index provides enhanced predictability of SC-PRECIP for a lead time of up to 4 months as compared with the Niño-3.4 index and the El Niño–Southern Oscillation longitudinal index. Significance Statement Traditional El Niño–Southern Oscillation indices, like the Niño-3.4 index, although well predicted themselves, fail to offer reliable subseasonal-to-seasonal predictions of western U.S. precipitation. Here, we use a machine learning approach called a multi-input, multioutput autoencoder to capture the relationship between tropical Pacific Ocean and Southern California precipitation and project it onto a new index, which we call the MIMO-AE index. Using machine learning–based time series predictions, we find that the MIMO-AE index offers enhanced predictability of Southern California precipitation up to a lead time of 4 months as compared with other ENSO indices.

Predicting the interannual variability of the subtropical high over the western Pacific Ocean based on the improved information diffusion model

Because of its special location and structure, the Western Pacific Subtropical High (WPSH) influences greatly the climate and weather in East Asia, especially the summer precipitation. To clarify how the interannual variability (IAV) of the WPSH is related to anomalies in the tropical sea surface temperature (SST) and atmospheric circulation, time series of the intensity index of the WPSH are subjected to wavelet analysis, showing IAV in the index. Characteristic indexes are defined for three key sea areas and the equatorial-latitude westerly region. After a continuous wavelet transform, the oscillation period of them is similar to that of the WPSH. The cross-wavelet transform of the four regional and two WPSH indexes is used to obtain the corresponding time-delay correlation. Regarding the potential correlation, WPSH weakening leads to strengthening of the westerly wind and then affects the rise of SST in the eastern equatorial Pacific Ocean. At the same time, warm water moves eastward. This gradually increases the SST in the equatorial central Pacific and warm pool area and then strengthens the WPSH under the action of the Hadley circulation. From the above analysis, a model for predicting the IAV of the WPSH intensity index is established based on the information diffusion model improved by a genetic algorithm. An experiment is conducted to predict the IAV of the WPSH intensity index, and the results show that the prediction model is accurate in predicting the IAV trend, with good prediction for 84 months. The mean absolute percentage error is 14.44% and the correlation coefficient is 0.8507. Also, the normal and abnormal years of the WPSH are used as different starting points for different prediction experiments. However, the different starting points have little influence on the predictions, showing the stability of the model. Studying the IAV of the WPSH provides a strong theoretical and scientific basis for predicting its abnormal interannual behavior and offers the prospect of socially important disaster prevention and mitigation.

A Zonal See‐Saw Variation of Tropical Cyclogenesis Over the Arabian Sea and Bay of Bengal‐South China Sea

AbstractThe variation of tropical cyclone (TC) genesis over the North Indian Ocean (NIO) and South China Sea (SCS) during the post‐monsoon season is explored during 1979–2020. A zonal see‐saw variation of TC genesis is detected between the Arabian Sea (AS) and Bay of Bengal (BOB) –SCS (BOBSCS for brevity). More (less) TCs over the AS tend to concur with fewer (more) TCs over the BOBSCS. Analyses of both the observations and the Coupled Model Intercomparison Project Phase 6 outputs show that tripole sea surface temperature (SST) anomalies in the tropical Indian and Pacific Oceans play a crucial role in the zonal see‐saw variation of TC genesis. Positive western Indian (WI) Ocean and tropical central and eastern Pacific (CEP) Ocean SST anomalies and negative western Pacific (WP) SST anomalies induce anomalous ascending and descending motions and high and low humidity transportation to the middle troposphere over the AS and BOBSCS, respectively. Meantime, anticyclonic vorticity anomalies appear in the BOBSCS region and negative anomalies of vertical wind shear are induced over the NIO and SCS. The combined positive contributions of upward motion, mid‐level humidity increase, and low vertical wind shear favor higher TC genesis over the AS, whereas the joint negative effects of downward motion, mid‐level water vapor decrease, and lower‐level anticyclonic vorticity anomalies result in less TC genesis over the BOBSCS. Numerical experiments show a critical role of the WI SST anomalies in the dipole pattern of vertical motion, which is crucial for the zonal dipole variation of TC genesis.

Dampak La Nina 2021-2022 terhadap Peningkatan Curah Hujan

La Nina is a climate anomaly that can cause extreme weather. La Nina is marked by a decrease in the sea surface temperature of the Pacific Ocean at the equator. La Nina can cause a prolonged rainy season for Asia including Indonesia. From mid-2020 to the end of 2022, Indonesia has experienced La Nina events. This study aims to determine changes in rainfall patterns and the number of rainy days during La Nina events. This research was conducted descriptively, using Pacific Ocean sea surface temperature (SST) data and rain data originating from the BMKG Climatology Station of Sultan Syarif Kasim II Pekanbaru from data for the last 10 years 2013-2022. The results of the study show that La Nina occurred from October 2020 to December 2022 with a weak to moderate level of La Nina strength. La Nina has increased the amount of rainfall 54-90% from normal conditions and increased the number of rainy days 11-70% compared to climate with normal conditions. Monthly rainfall is in the low to high category, while daily rainfall is included in the heavy rain category. The La Nina event has caused a prolonged rainy season for almost 3 years and has increased the amount of rainfall and rainy days.

Correcting Subseasonal Forecast Errors with an Explainable ANN to Understand Misrepresented Sources of Predictability of European Summer Temperatures

Abstract Subseasonal forecasts are challenging for numerical weather prediction (NWP) and machine learning models alike. Forecasting 2-m temperature (t2m) with a lead time of 2 or more weeks requires a forward model to integrate multiple complex interactions, like oceanic and land surface conditions leading to predictable weather patterns. NWP models represent these interactions imperfectly, meaning that in certain conditions, errors accumulate and model predictability deviates from real predictability, often for poorly understood reasons. To advance that understanding, this paper corrects conditional errors in NWP forecasts with an artificial neural network (ANN). The ANN postprocesses ECMWF extended-range summer temperature forecasts by learning to correct the ECMWF-predicted probability that monthly t2m in western and central Europe exceeds the climatological median. Predictors are objectively selected from ECMWF forecasts themselves, and from states at initialization, i.e., the ERA5 reanalysis. The latter allows the ANN to account for sources of predictability that are biased in the NWP model itself. We attribute ANN corrections with two explainable artificial intelligence (AI) tools. This reveals that certain erroneous forecasts relate to tropical western Pacific Ocean sea surface temperatures at initialization. We conjecture that the atmospheric teleconnection following this source of predictability is imperfectly represented by the ECMWF model. Correcting the associated conditional errors with the ANN improves forecast skill. Significance Statement We want to understand occasions in which a numerical weather prediction (NWP) model fails to forecast a predictable event existing in the real world. For forecasts of European summer weather more than 2 weeks in advance, real predictable events are rare. When misrepresented by the model, predicted future states become needlessly biased. We diagnose these missed opportunities with an explainable neural network. The neural network is aware of the initial state and learns to correct the NWP forecast on occasions when it misrepresents a teleconnection from the western tropical Pacific Ocean to Europe. The explainable architecture can be useful for other applications in which conditional model errors need to be understood and corrected.

Can Tibetan Plateau Snow Depth Influence the Interannual Association between Tropical Indian Ocean Sea Surface Temperatures and Rapidly Intensifying Typhoons?

Abstract This study finds that the observed decrease in winter–spring Tibetan Plateau snow depth since 2000 has played an important role in weakening the correlation between rapidly intensifying tropical cyclones over the western North Pacific and tropical Indian Ocean sea surface temperatures (SSTs). Tibetan Plateau snow depth modulates convective activity through changes in the South Asian high. Increased Tibetan Plateau snow depth promotes basinwide tropical Indian Ocean cooling in spring through a Gill-type response. In the following seasons, downward latent heat flux anomalies associated with a weaker monsoon circulation contributes to warm SST anomalies over the western tropical Indian Ocean, thus favoring a positive phase of the Indian Ocean dipole. This evolution of tropical Indian Ocean SSTs associated with anomalously high Tibetan Plateau snow depth potentially weakens the relationship between rapidly intensifying tropical cyclone frequency and spring tropical Indian Ocean SSTs. When the effect of Tibetan Plateau snow depth is removed via partial correlation analysis, we find a significant relationship between spring tropical Indian Ocean SSTs and rapidly intensifying tropical cyclones as well as corresponding large-scale environmental factors. The results of this study enhance understanding of changes in tropical cyclone intensity and have implications for seasonal forecasting of tropical cyclone intensity over the western North Pacific basin. This study also emphasizes the importance of Tibetan Plateau thermal forcing in atmosphere–ocean coupling.

Contribution of PDO to Decadal Variations of Glaze Dipole Pattern in China

Abstract Based on the in situ observations, reanalysis, and model simulation, the variations in glaze dipole pattern in China and its underlying physical mechanism have been explored. The glaze dipole pattern features an out-of-phase relationship between winter glaze in the south of the Yangtze River valley (YRV) and northern China, accompanied by pronounced interdecadal variation around the late 1970s. The results from synoptic analyses suggest that cold air brought by the northerly winds and warm moist air by the southwesterly winds, as well as the occurrence of inversion layer are vital to the glaze weather in the south of YRV. Further analyses indicate that the interdecadal shift of the Pacific decadal oscillation (PDO) contributes largely to variations in glaze dipole pattern. Specifically, the warm PDO provides a beneficial environment for the occurrence of glaze dipole pattern by stimulating the tropical–extratropical circulation configuration with the deepened East Asian trough, strengthened East Asian westerly jet, anomalous anticyclone over the tropical western Pacific Ocean, and cyclone over the southern Tibetan Plateau at the decadal time scale. Consequently, the enhanced moisture transport brought by southwesterly and cold air intrusion induced by the deepened East Asian trough benefit the glaze weather in the south of YRV, while the decreased precipitation and a much lower temperature in northern China depress the generation of glaze. Moreover, the results from the CAM4 model simulation indicate the atmospheric circulation anomalies forced by PDO-like SST can roughly reproduce the extratropical configuration related to the glaze, but it has difficulties in capturing the tropical circulation anomalies. Significance Statement The purpose of this study is to better understand how the glaze dipole pattern in China responds to climate anomalies, which focuses on the spatial–temporal evolution of glaze days and its underlying physical mechanism. This study highlights the important role of Pacific Ocean sea surface temperature anomalies in the interdecadal variations in glaze dipole pattern, and it gives a clear clarification to demonstrate the impacts of Pacific decadal oscillation on the climatological background for the occurrence of glaze. Our results provide a guide on what drives the interdecadal variation in the glaze dipole pattern and help to understand the climate dynamic mechanism of variations in freezing events in China.

Regional tree-ring oxygen isotope deduced summer monsoon drought variability for Kumaun-Gharwal Himalaya

The precipitation in the Kumaun-Gharwal (Uttarakhand) Himalaya (KGH) is predominantly regulated by the Indian summer monsoon (ISM) and has been declining over the last century. However, because of limited historical data, it is difficult to place this recent decreasing trend in the context of pre-anthropogenic influences and understand a fuller range of hydroclimate scenarios for the region. Thus, we developed a 508-year regional tree-ring stable oxygen isotope (δ18OTR) record for multiple coniferous taxa (Abies spectabilis, Cedrus deodara and Picea smithiana) for the KGH, which spanned 1508–2015 CE. The δ18OTR record explained 35.8% of instrumental June–August Palmer Drought Severity Index (JJAPDSI) variance modelled from a nearby meteorological station. The JJAPDSI reconstruction shows regional coherency with both instrumental and proxy-based independent hydroclimatic records providing confidence that it is a reliable proxy to assess the long term hydroclimatic variability of the region. We identified decreasing strength of JJAPDSI reconstruction in KGH during recent decades indicating intensified drought. This is in the context of pre-anthropogenic influences and understand a fuller range of hydroclimate scenarios for the region. The δ18OTR also has coherency with Pacific and Indian Ocean sea surface temperature variability illustrating the broader teleconnections that influence the regional hydroclimate.

More profound impact of CP ENSO on Australian spring rainfall in recent decades

Most of Australia was in severe drought from 2018 to early 2020. Here we link this drought to the Pacific and Indian Ocean sea surface temperature (SST) modes associated with Central Pacific (CP) El Niño–Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD). Over the last 20 years, the occurrence frequency of CP El Niño has increased. This study extends the previous understanding of eastern Pacific (EP) El Niño-Australian rainfall teleconnections, exhibiting that CP El Niño can bring much broader and stronger rainfall deficiencies than EP El Niño during austral spring (September–November) over the northern Australia (NAU), central inland Australia and eastern Australia (EAU). The correlations between SST fields and rainfall in three Cluster regions divided by clustering analysis also confirm this, with rainfall variability in most of Australia except southern Australia (SAU) most significantly driven by CP ENSO. Also, we demonstrate that the CP El Niño affects rainfall in extratropical EAU via the Pacific-South American (PSA) pattern. While the influence of EP El Niño is only confined in tropical NAU because its PSA pattern sits far too east to convey its variability. With the development of ENSO diversity since 2000, the footprint of El Niño on Australian rainfall has become more complex.

Diagnosis of the Extreme Climate Events of Temperature and Precipitation in Metropolitan Lima during 1965–2013

The most extreme precipitation event in Metropolitan Lima (ML) occurred on 15 January 1970 (16 mm), this event caused serious damage, and the real vulnerability of this city was evidenced; the population is still not prepared to resist events of this nature. This research describes the local climate variability and extreme climate indices of temperature and precipitation. In addition, the most extreme precipitation event in ML is analyzed. Extreme climate indices were identified based on the methodology proposed by the Expert Team on Climate Change Detection and Indices (ETCCDI). Some extreme temperature indices highlight an initial trend toward warm conditions (1965–1998); this trend has changed towards cold conditions since 1999, consistent with the thermal cooling during the last two decades in ML (−0.5 °C/decade) and other coastal areas of Peru. The variations of extreme temperature indices are mainly modulated by sea-surface temperature (SST) alterations in the Niño 1 + 2 region (moderate to strong correlations were found). Extreme precipitation indices show trends toward wet conditions after the 1980s, the influence of the Pacific Ocean SST on the extreme precipitation indices in ML is weak and variable in sign. The most extreme precipitation event in ML is associated with a convergence process between moisture fluxes from the east (Amazon region) at high and mid levels and moisture fluxes from the west (Pacific Ocean) at low levels, and near the surface.

Dynamical Seasonal Prediction of the Asian Summer Monsoon in the China Meteorological Administration Climate Prediction System Version 3

Based on the 20 years of ensemble hindcast data, we evaluated the performance of the new version climate prediction system developed by the China Meteorological Administration (CMA CPSv3) on the Asian summer monsoon (ASM) seasonal prediction in this study. Many major features of the ASM are well predicted by CPSv3, including the intensity and location of the heavy precipitation centers, large-scale monsoon circulations, monsoon onset, and the interannual variation of dynamical monsoon indices. The model captures realistically interannual variability of the summer western North Pacific subtropical high (WNPSH) and is highly skillful for the WNPSH index. Compared with its predecessor, the prediction skill of summer precipitation over Asia in CPSv3 is obviously improved, especially over eastern China. The improvement mainly benefits from skillful predictions of the tropical Pacific Ocean and tropical Indian Ocean sea surface temperatures and ocean–atmosphere coupling associated with them.

Grasshoppers exhibit asynchrony and spatial non-stationarity in response to the El Niño/Southern and Pacific Decadal Oscillations

Grasshoppers are preeminent herbivores and perhaps the most significant rangeland pests in the United States (US). Despite the important ecosystem functions they provide, grasshopper populations often obtain densities that cause significant economic harm to grazing operations and agricultural production. Although numerous studies conducted at the level of individual field sites have examined potential mechanisms contributing to grasshopper population “boom and bust” cycles, there has yet to be a large, regional scaled analysis that quantified grasshopper variation across the Western US as a whole. While taking steps to account for data collection biases, mediating effects, and variable confounding, we assessed the influence of Pacific Ocean sea surface temperature oscillations on a 40-year record of grasshopper density in the Western US. Central to our analysis was employing spatially varying coefficients to model time and location-specific variation in grasshopper response to climate. Our results quantitatively demonstrated interannual changes in grasshopper density to be indirectly effected by seasonal El Niño/Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) variability and to exhibit spatial asynchrony and non-stationarity such that the relative influence of climate on grasshopper density varied through time and across geographic space. Our model is the first to incorporate climate indices as spatially varying coefficients for assessment of a terrestrial species and represents a critical step towards understanding causal drivers of regional grasshopper density.

Recent interdecadal changes in the Tropospheric Biennial Oscillation of the East Asian summer monsoon

This paper focuses on the interdecadal changes in the biennial East Asian summer monsoon (EASM) transition related to the Tropospheric Biennial Oscillation (TBO), which has major impacts on East Asian climate. During 1958–2020, the TBO signal in the EASM exhibits noticeable interdecadal changes around the late 1970s and late 1990s. Among the three periods [1958–1979 (P1), 1980–2000 (P2), 2001–2020 (P3)], the TBO signal is the strongest in P2 and the weakest in P1. Such changes are closely associated with changes in the amplitude and position of wind anomalies over the western North Pacific (WNP). Further analysis indicates that the regime shifts in ENSO properties, including intensity, period, and location of ENSO-related sea surface temperature (SST) anomalies, play a crucial role. Compared with P1, the warm SST anomalies in the central Pacific and North Indian Ocean SST associated with the slowly decaying ENSO together induce the stronger WNP wind anomalies in both P2 and P3. However, such SST warming is relatively weaker in P3 compared with those in P2, which is consistent with the weak intensity and short period of ENSO in P3. In comparison, the anomalous circulation over the WNP is thus relatively weaker in P3 than in P2. Therefore, these anomalous SSTs associated with the shift in the ENSO regime are suggested to induce circulation anomalies over the WNP that subsequently contributed to the changes in the EASM TBO around the late 1970s and late 1990s.

Evolving Sahel Rainfall Response to Anthropogenic Aerosols Driven by Shifting Regional Oceanic and Emission Influences

Abstract Sahel summertime precipitation declined from the 1950s to 1970s and recovered from the 1970s to 2000s. Anthropogenic aerosol contributions to this evolution are typically attributed to interhemispheric gradient changes of Atlantic Ocean sea surface temperature (SST). However recent work by Hirasawa et al. indicates a more complex picture, with the response being a combination of “fast” direct atmospheric (DA) processes and “slow” ocean-mediated (OM) processes. Here, we extend this understanding using the Community Atmosphere Model 5 to determine the role of regional ocean-basin perturbations and regional aerosol emission changes in the overall aerosol-driven OM and DA responses, respectively. From the 1950s to 1970s, there was an OM Sahel wetting response due to Pacific Ocean cooling that was offset by drying due to Atlantic cooling. By contrast, from the 1970s to 2000s, Atlantic trends reversed and amplified the Pacific cooling-induced wetting. This wetting was partially offset by drying driven by Indian Ocean cooling. Thus, the OM Sahel precipitation response to aerosol crucially depends on the balance of responses to Atlantic, Pacific, and Indian Ocean SST anomalies. From the 1950s to 1970s, there is DA Sahel drying that was principally due to North American aerosol emissions, with negligible effect from European emissions. DA drying from the 1970s to 2000s was mainly due to African aerosol emissions. Thus, the shifting roles of regional OM and DA effects reveal a complex interplay of direct driving and remote teleconnections in determining the time evolution of Sahel precipitation due to aerosol forcing in the late twentieth century. Significance Statement Studies of global climate models consistently indicate that anthropogenic aerosol emissions were a significant contributor to a severe drought that occurred in the Sahel region of Africa in the late twentieth century. The drying influence of aerosol forcing is the combined result of rapid atmospheric responses directly due to the forcing and slower responses due to forced ocean temperature changes. Using a set of simulations targeted at determining the influences from different ocean basins and different emission regions for two periods in the late twentieth century, we find there is a surprising range of mechanisms through which aerosol emissions affect the Sahel. This results in a complex interplay of at times competing and at times complementary regional influences.

Evaluation of East Asian Meiyu from CMIP6/AMIP simulations

East Asian Meiyu simulated by 35 global atmospheric models from the 6th Coupled Model Intercomparison Project (CMIP6)/Atmospheric Model Intercomparison Project (AMIP) were systematically evaluated for 1998–2014. The results show that most of the CMIP6/AMIP models can hardly reproduce the observed spatial pattern and interannual variability of East Asian Meiyu. The spatial pattern is relatively better simulated over Southern Korea and Japan where 14 out of 35 models have realistically simulated precipitation, as compared with the lower reaches of the Yangtze River where only 7 out of 35 models can well reproduce the Meiyu precipitation. For the Meiyu interannual variations, GFDL-CM4 and GFDL-ESM4 have the closest variance among the models versus the TRMM observations, while 12 out of 35 models show smaller variances. We explored the relationships of Meiyu precipitation with large-scale circulation and tropical sea surface temperature (SST), and showed that these relationships from CESM2-WACCM-FV2, EC-Earth3-CC, and MPI-ESM1-2-HAM agree well with those based on TRMM precipitation, MERRA2 reanalysis-derived large-scale atmospheric fields, and observed SST. It is found that the models with a better simulation of Meiyu precipitation can capture the relationship between Meiyu precipitation and the SST in the eastern equatorial Pacific and Indian Ocean more realistically. A performance ranking of the 35 individual CMIP6/AMIP models is further provided. It is shown that the top 20% of models based on interannual variability score tend to simulate a more realistic western Pacific subtropical high than the bottom 20% of models. And the top 20% of models based on comprehensive ranking measure simulate a more realistic EAP pattern than the bottom 20% of models.