Equatorial Pacific Region Research Articles

Richness, Endemism and Seasonality of Horseflies (Diptera: Tabanidae) in Forests of the Equatorial Pacific Region of Ecuador.

The Equatorial Pacific Region (EPR) in Ecuador is characterized by high rates of vegetation diversity, and rapid loss of vegetation cover due to anthropogenic pressures. In this study, general ecological aspects of the Tabanidae family, including richness, endemism, and seasonality, were evaluated. Analyses reveal that approximately 42% of the species recorded for Ecuador are present in the EPR, and out of the 84 species cataloged in the EPR, 6 are endemic, representing an endemism of 7.14%. Furthermore, it was established that tabanid populations in a coastal dry forest significantly increased their population density during the dry season, while decreasing during the wet season.

Estimating Uncertainty in Simulated ENSO Statistics

AbstractLarge ensembles of model simulations are frequently used to reduce the impact of internal variability when evaluating climate models and assessing climate change induced trends. However, the optimal number of ensemble members required to distinguish model biases and climate change signals from internal variability varies across models and metrics. Here we analyze the mean, variance and skewness of precipitation and sea surface temperature in the eastern equatorial Pacific region often used to describe the El Niño–Southern Oscillation (ENSO), obtained from large ensembles of Coupled model intercomparison project phase 6 climate simulations. Leveraging established statistical theory, we develop and assess equations to estimate, a priori, the ensemble size or simulation length required to limit sampling‐based uncertainties in ENSO statistics to within a desired tolerance. Our results confirm that the uncertainty of these statistics decreases with the square root of the time series length and/or ensemble size. Moreover, we demonstrate that uncertainties of these statistics are generally comparable when computed using either pre‐industrial control or historical runs. This suggests that pre‐industrial runs can sometimes be used to estimate the expected uncertainty of statistics computed from an existing historical member or ensemble, and the number of simulation years (run duration and/or ensemble size) required to adequately characterize the statistic. This advance allows us to use existing simulations (e.g., control runs that are performed during model development) to design ensembles that can sufficiently limit diagnostic uncertainties arising from simulated internal variability. These results may well be applicable to variables and regions beyond ENSO.

Analysis of the spatiotemporal changes in global tropospheric ozone concentrations from 1980 to 2020

Tropospheric ozone affects human health, ecosystems, and climate change. Previous studies on Tropospheric Column Ozone (TCO) have primarily concentrated on specific regions or global geographic divisions. This has led to insufficient exploration of the spatiotemporal characteristics and influencing factors of TCO in global and rational subregions. In this study, TCO is calculated using the Modern Era Retrospective analysis for Research and Applications version 2 (MERRA-2) reanalysis data and corrected using satellite data. Cluster analysis is conducted to explore the temporal characteristics of TCO variations in different regions. The results show that the global TCO is basically distributed latitudinally, with higher TCO in the northern hemisphere, which is related to atmospheric circulation, radiation, stratospheric transport, and the distribution of ozone precursors. Between 1980 and 2020, the global average annual TCO showed an increasing trend at 0.09 DU yr−1 due to rising anthropogenic emissions of ozone precursors (NOx at 589547.86 t yr−1 and NMVOC at 1070818.24 t yr−1), increasing tropopause height (−0.10 hPa yr−1), and the enhanced ozone flux at the tropopause (0.22 ppbv m s−2 yr−1). Cluster analysis reveals different trends in TCO changes across regions. The ocean south of 60°S and parts of West Antarctica (Region 2), the region from 30°N to 60°N and the western oceanic region of 30°S (Region 3), and the region from the equator to 60°S and the region north of 60°N (Region 5) exhibit increasing trends (with rates of 0.08 DU yr−1, 0.07 DU yr−1, and 0.11 DU yr−1, respectively), linked to the enhanced ozone flux at the tropopause, the rising tropopause height and increasing ozone p precursors. Conversely, the decreasing TCO trends in the equatorial Pacific (Region 1) and East Antarctica (Region 4) (with rates of −0.01 DU yr−1 and -0.02 DU yr−1) may be related to increased cloudiness and weakened photochemical reactions.

Significant Increase in Global Steric Sea Level Variations over the Past 40 Years

Understanding global sea level variations and exploring their causes hold significant importance for future climate change predictions and the sustainable development of mankind, with the steric sea level (SSL) variations being one of the primary contributors to these changes. Here, we utilize four types of temperature and salinity products (i.e., EN4, IAP, SODA, and GDCSM) to investigate the spatiotemporal characteristics of global SSL changes from 1980 to 2020. We also explore the relationship between SSL changes and the El Niño-Southern Oscillation (ENSO) phenomenon. The findings reveal a rising trend of 0.64–0.97 mm/a in global SSL over the past 40 years, and the annual amplitudes of SSL time series are within the range of 0–50 mm. The SSL trend at a depth of 0–100 m exerts the greatest influence on the overall trend. The ENSO phenomenon has an obvious influence on sea level changes both in the equatorial Pacific region and global scale. The changes in the global sea level (GSL) associated with ENSO are primarily caused by changes in SSL. This study benefits the understanding of SSL changes and their connection to climate change, serves as a reference for comprehensively assessing sea level change mechanisms using diverse datasets and remote sensing technology, and further provides a scientific basis for the sustainable development of mankind in coastal areas.

Variability of East Asian Summer Monsoon precipitation during the Early Pleistocene based on pollen analysis from the western Loess Plateau, China

Understanding Early Pleistocene variability in precipitation associated with the East Asian Summer Monsoon (EASM) may help improve understanding of the effects of future global warming on this system. In this study, a quantitative EASM precipitation record with ∼2.7 kyr resolution was reconstructed for the Early Pleistocene (∼2.2–1.7 Ma) based on a pollen record from a loess-paleosol sequence in Lanzhou Basin, on the western Chinese Loess Plateau (CLP). The results show that the average annual precipitation (Pann) value was ∼505 mm, almost ∼1.6 times as much as today (∼310 mm), implying much stronger EASM intensity from ∼2.2–1.7 Ma. The EASM experienced a period of stronger intensity from ∼2.2 to 2.07 Ma, with Pann up to ∼525 mm and vegetation dominated by forest-steppe, as well as a period of weaker intensity between ∼2.07 and 1.99 Ma with lower average Pann (∼481 mm) and steppe dominated vegetation. A gradual intensification followed from ∼1.99 to 1.7 Ma, with increasing Pann (∼503 mm) accompanied by a significant increase in arboreal abundance. Our analysis suggests that the west to east temperature gradients across the Equatorial Pacific region influenced the Early Pleistocene EASM evolution over geological timescales. This finding differs from the traditional view that high-latitude ice sheet fluctuations were the primary driving force of Quaternary EASM. On orbital timescales, the Pann exhibits a dominant ∼41 kyr obliquity periodicity between ∼2.2–1.99 Ma and a ∼18 kyr precession periodicity between ∼1.99–1.7 Ma, indicating that Northern Hemisphere ice sheet and low-latitude solar insolation were the dominant drivers of EASM precipitation cycles in these two periods.

Local and Remote Causes of the Equatorial Pacific Cold Sea Surface Temperature Bias in the Kiel Climate Model

Abstract We investigate the origin of the equatorial Pacific cold sea surface temperature (SST) bias and its link to wind biases, local and remote, in the Kiel Climate Model (KCM). The cold bias is common in climate models participating in phases 5 and 6 of the Coupled Model Intercomparison Project. In the coupled experiments with the KCM, the interannually varying NCEP/CFSR wind stress is prescribed over four spatial domains: globally, over the equatorial Pacific (EP), the northern Pacific (NP), and the southern Pacific (SP). The corresponding EP SST bias is reduced by 100%, 52%, 12%, and 23%, respectively. Thus, the EP SST bias is mainly attributed to the local wind bias, with small but not negligible contributions from the extratropical regions. Erroneous ocean circulation driven by overly strong winds causes the cold SST bias, while the surface heat flux counteracts it. Extratropical Pacific SST biases contribute to the EP cold bias via the oceanic subtropical gyres, which is further enhanced by dynamical coupling in the equatorial region. The origin of the wind biases is examined by forcing the atmospheric component of the KCM in a stand-alone mode with observed SSTs and simulated SSTs from the coupled experiments. Wind biases over the EP, NP, and SP regions originate in the atmosphere model. The cold EP SST bias substantially enhances the wind biases over all three regions, while the NP and SP SST biases support local amplification of the wind bias. This study suggests that improving surface wind stress, at and off the equator, is a key to improve mean-state equatorial Pacific SST in climate models.

Advancing ocean subsurface thermal structure estimation in the Pacific Ocean: A multi-model ensemble machine learning approach

Estimation of the ocean subsurface thermal structure (OSTS) is important for understanding thermodynamic processes and climate variability. In the present study, a novel multi-model ensemble machine learning (Ensemble-ML) model is developed to retrieve subsurface thermal structure in the Pacific Ocean by integrating sea surface data with Argo observations. The Ensemble-ML model integrates four individual machine learning models to enhance estimation accuracy and reliability. Our results exhibit good agreement between the satellite sea surface temperature (SST) and sea surface salinity (SSS) data and Argo observations, providing validation for the utilization of these datasets in the Ensemble-ML model. The Ensemble-ML model exhibits better performance compared to individual machine learning models, with an average root mean square error (RMSE) of 0.3273 °C and an average coefficient of determination (R²) of 0.9905. Notably, incorporating geographical information as input variables enhance model performance, emphasizing the importance of considering spatial context in OSTS estimation. The Ensemble-ML model accurately captures the spatial distribution of OSTS across depths and seasons in the Pacific Ocean, effectively reproducing critical temperature features while maintaining strong agreement with Argo observations. Nevertheless, its performance shows relative weakness within the thermocline layer and the equatorial Pacific region (spanning from 10°S to 10°N latitude), which are characterized by complex circulation systems. Despite these challenges, the Ensemble-ML model effectively reproduces the spatial distribution of OSTS of the Pacific Ocean. This indicates the potential of machine learning models, particularly ensemble models, for enhancing OSTS estimation in the Pacific Ocean and other regions, offering valuable insights for future research and applications in physical oceanography.

The impact of ICE‐6G ice sheet topography in the oceanic carbonate system

AbstractDuring the Last Glacial Maximum (approximately 21 ka BP) the presence of large ice sheets over the Northern Hemisphere (NH) caused significant changes in the ocean–atmosphere interaction. Remarkable changes are noticed in NH both topography and atmospheric CO2 levels. This paper investigates the impact of the most recent paleotopography (ICE6G) in the Earth's climate and the oceanic carbonate system, based on a series of experiments conducted with the oceanic‐atmosphere‐vegetation‐ice‐carbon model, UVic ESCM. Results indicate enhanced cooling in northern North America in the ICE6G compared to the ICE4G simulation due to the lapse rate effect. The decrease of −24°C in the surface temperature in the ICE6G relative to the present day (PD) led to a modification of the atmospheric circulation in the Atlantic and North Pacific regions. Positive and negative anomalies vary widely for the E–P (evaporation–precipitation) flux pattern, but colder and drier atmosphere leads to a reduction in precipitation in the ICE6G experiment. Changes in wind stress between ICE6G and PD induce low temperatures in the Northern Hemisphere. These features are related changes of Ekman's transport and evaporative cooling resulting in positive anomalies of SST. Thus, changes in sea surface temperature and salinity (SST, SSS), and E–P flux led to modifications in the oceanic carbonate system, resulting in an overall increase of total alkalinity and a reduction in the concentrations of total carbon dioxide (TCO2) in the ICE6G with respect to the PD values. This is a consequence of the low concentration of glacial CO2 and increment in concentrations. The total alkalinity (TA) and TCO2 do not show a similar response to the SST and SSS, in the sense that larger departures from the PD are found in the Pacific equatorial region, which are affected by changes in water dilution as a result of precipitation and evaporation processes.

The mechanism of boreal summer SSTA phase-locking in the far eastern Pacific

In observations, the boreal winter El Niño—Southern Oscillation (ENSO) phase-locking phenomenon is evident in the central-eastern Pacific. In the far eastern equatorial Pacific (FEP) and South American coastal regions, however, the peak of sea surface temperature anomalies (SSTA) tends to occur in the boreal summer, with fewer winter peak events. By separating the direct ENSO forcing from the FEP SSTA, we found that the summer peak preference is contributed by the residual SSTA component, while the ENSO forcing provides only a small probability of winter peak. The dynamics of FEP SSTA phase-locking in observations and its biases in the climate models are investigated by adopting a linear stochastic-dynamical model. In observations, the summer phase-locking of FEP SSTA is controlled by the seasonal modulation of the SSTA damping process. In contrast, in the climate models the strength of FEP SSTA phase-locking is much smaller than observed due to the overly negative SSTA damping rate.

Pleistocene Sunda Shelf submersion-exposure cycles initiate vegetation Walker Circulation feedback

Abstract Recent research has found that the subsiding Sunda Shelf (Southeast Asia) was permanently exposed prior to ca. 400 ka with initial submersion-exposure cyclicity, associated with interglacial-glacial sea-level cycles, beginning between 400 and 240 ka. We analyzed the impact submersion-exposure cycles on regional environment and climate through a 640 k.y. leaf-wax carbon isotope (δ13Cwax) reconstruction at Andaman Sea Site U1448, representing relative changes in C3/C4 plant abundances. Prior to ca. 250 ka, the Sunda region was inhabited by a stable C3 (forest) biome, after which submersion-exposure cycles initiated with the deglacial sea-level rise at ca. 250 ka. During subsequent glacial-age sea-level drops, the newly exposed shelf was rapidly colonized by C4 grasses, followed by slow transitions back to C3 forests, representing a tenfold increase in the variability of C3/C4 vegetation in the Sunda region. The C3/C4 regime shift since 250 ka is coherent across the Southeast (SE) Asia peninsula and Sunda Shelf and is coincident with a shift in the east-west sea-surface temperature gradient in the equatorial Pacific Ocean. We hypothesize that the expansion of C4 grasslands promoted and sustained drier glacial-age climates over SE Asia via a feedback mechanism that contributed to weakening the ascending branch of the east-west atmospheric circulation in the equatorial Pacific region known as the Walker Circulation. Our results indicate that the Sunda Shelf region has a larger influence on Walker Circulation than is seen in current paleoclimate simulations.

Understanding rainfall prediction skill over the Sahel in NMME seasonal forecast

Sahelian rainfall presents large interannual variability which is partly controlled by the sea surface temperature anomalies (SSTa) over the eastern Mediterranean, equatorial Pacific and Atlantic oceans, making seasonal prediction of rainfall changes in Sahel potentially possible. However, it is not clear whether seasonal forecast models present skill to predict the Sahelian rainfall anomalies. Here, we consider the set of models from the North American Multi-model ensemble (NMME) and analyze their skill in predicting the Sahelian precipitation and address the sources of this skill. Results show that though the skill in predicting the Sahelian rainfall is generally low, it can be mostly explained by a combination of how well models predict the SSTa in the Mediterranean and in the equatorial Pacific regions, and how well they simulate the teleconnections of these SSTa with Sahelian rainfall. Our results suggest that Sahelian rainfall skill is improved for those models in which the Pacific SST—Sahel rainfall teleconnection is correctly simulated. On the other hand, models present a good ability to reproduce the sign of the Mediterranean SSTa—Sahel teleconnection, albeit with underestimated amplitude due to an underestimation of the variance of the SSTa over this oceanic region. However, they fail to correctly predict the SSTa over this basin, which is the main reason for the poor Sahel rainfall skill in models. Therefore, results suggest models need to improve their ability to reproduce the variability of the SSTa over the Mediterranean as well as the teleconnections of Sahelian rainfall with Pacific and Mediterranean SSTa.

Passive tracer advection in the equatorial Pacific region: statistics, correlations and a model of fractional Brownian motion

Abstract. Evaluating passive tracer advection is a common tool to study flow structures, particularly Lagrangian trajectories ranging from molecular scales up to the atmosphere and oceans. Here we report on numerical experiments in the region of the tropical Pacific (20∘ S–20∘ N), where 6600 tracer parcels are advected from a regular initial configuration (along a meridional line at 110∘ W between 15∘ S and 15∘ N) during periods of 1 year for 25 years altogether. We exploit AVISO surface flow fields and solve the kinematic equation for passive tracer movement in the 2D advection tests. We demonstrate that the strength of the advection defined by mean monthly westward displacements of the tracer clouds exhibit surprisingly large inter- and intra-annular variabilities. Furthermore, an analysis of cross-correlations between advection strength and the El-Niño and Southern Oscillation (SOI) indices reveal a significant anticorrelation between advection intensity and ONI (the Oceanic Niño Index) and a weaker positive correlation with SOI, both with a time lag of about 3 months (the two indices are strongly anticorrelated near real time). The statistical properties of advection (time-dependent mean squared displacement and first passage time distribution) suggest that the westward-moving tracers can be mapped into a simple 1D stochastic process, namely fractional Brownian motion. We fit the model parameters and show by numerical simulations of the fractional Brownian motion model that it is able to reproduce the observed statistical properties of the tracers' trajectories well. We argue that a traditional explanation based on the superposition of ballistic drift and a diffusion term yields different statistics and is incompatible with our observations.

Radiolarian assemblages controlled by ocean production in the western equatorial Pacific

The Western Pacific Warm Pool, covering much of the western Pacific equatorial region, contains the warmest surface waters exceeding 28.5 °C. A thorough investigation is necessary to assess radiolarian composition in such unique oceanographic conditions. In this study, we analyzed 80 surface sediment samples collected from the western equatorial Pacific. On the basis of principal coordinates analysis, three major radiolarian assemblages in sediment samples are identified: assemblages from northern and southern sediments, and an Ethmodiscus-rich fauna. Co-occurring highly abundant radiolarians and Ethmodiscus diatom fragments are reported for the Ethmodiscus-rich fauna. To explain this phenomenon we propose two hypotheses: that radiolarian assemblages co-existed in the upper column, or that assemblages indicate co-preservation in a sediment thanatocoenose. Net primary production, sea surface temperature, and phosphate, best explain the species composition of the northern and southern faunas in the oligotrophic warm western equatorial Pacific waters. Dominant species with higher proportions in the southern fauna, including Dictyocoryne muelleri and D. profundum groups, Spongaster tetras, and Stylodictya multispina, may sensitively respond to net primary production, or rather food availability. The higher abundances of the Tetrapyle and Phorticium groups in the northern fauna indicate their preference for cooler and inorganic nutrient-rich waters, and decreased dependence on food source associated with net primary production, possibly due to their obligate photosynthetic associations.

Evaluation of environmental degradation on Biomes in Brazilian Northeastern

In recent years, due to irregular rainfall, several regions across the globe have suffered from some environmental degradation. Depending on the degree of intensity, they can lead to a series of socioeconomic problems, both regional and national. One of the most emblematic types of degradation today is the desertification development process, resulting in a combination of anthropic, climatic, and/or environmental factors. In an attempt to understand the behavior of these impacts, this work evaluated the degradation process based on the Aridity Index (AI) on biomes located in the Brazilian Northeast (Caatinga, Atlantic Forest, Amazon, and Cerrado). The AI consists of the relationship between evapotranspiration (in this case, the Thornthwaite estimation method) and precipitation. The data used correspond to the product Climatologies at high resolution for the earth's land surface areas (CHELSA), which have a spatial resolution of 1km x 1km and temporal resolution on a monthly scale, from 1979 to 2013. In addition, it was found that the AI behavior during years of the El Niño-Southern Oscillation (ENSO) warm phase, the El Niños. The identification of El Niño episodes was based on the Oceanic Niño Index (ONI) climate proxy, characterized by the Equatorial Pacific region known as the Niño 3.4 region. The years 1983, 1993, 1998, and 2012 were selected. AI results point out different behaviors between the biomes, mainly over the south of the northeastern Cerrado and the Caatinga, motivated by the strong variability of rainfall in the respective regions. The Caatinga stands out, which exhibited a large part of its area was classified as arid (AI between 0.05 – 0.20) and hyper-arid (AI < 0.05), mainly in 2012. The Amazon and biomes, on the other hand. Atlantic Forest has areas classified as semi-arid (AI < 0.5). El Niño had a reduction in the AI values, motivated by the long periods of drought and irregular rainfall that negatively impacted the semi-arid of the Northeast region.

Role of moisture transport from Western Pacific region on water vapor isotopes over the Bay of Bengal

Bay of Bengal (BoB) region is a major moisture source to both Indian Summer Monsoon (ISM) and North East Monsoon (NEM) rainfall over the surrounding region. Oxygen isotopic ratios (δ18O) in the rainfall over the peripheral region show a decreasing trend towards the later months of ISM and shows minimum during NEM. This was previously explained with local factors of BoB such as isotopically depleted river discharge to BoB, increased cyclonic activity etc., however, the exact reasons remain unclear. δ18O of vapor collected from BoB when there was no cyclonic activity also shows ~2 ‰ depletion in NEM season compared to that during ISM. Here we show, easterly winds passing through a convectively active narrow zonal band (central to western equatorial Pacific and Indonesian region) bring significant amounts (median 64%: interquartile range 30%) of isotopically depleted moisture to BoB region, and results in anomalous depletion of vapor over BoB during NEM. Vapor source-tagged simulations from isotope enabled Community Atmospheric Model show easterly moisture flux from western Pacific region dominates over the BoB surface evaporation flux.

Synchronous Characteristics of Precipitation Extremes in the Yangtze and Murray-Darling River Basins and the Role of ENSO

The floods caused by the extreme precipitation in the Yangtze River basin (YRB) and Murray–Darling River basin (MDRB), the largest basins in China and Australia, have significant impacts on the society and regional economies. Based on the spatial–temporal analysis of the daily precipitation extremes (DPEs) during 1982–2016, we found that for both basins, the whole-basin-type DPEs have the highest proportion and a synchronous DPE interannual variation characteristic exists in the two basins, with the 3-yr running correlation coefficient of the annual DPE days (DPEDs) reaching almost 0.7 (significant at the 0.01 level). The El Nino–Southern Oscillation (ENSO), which is one of the most significant climate disturbance factors in the world, plays an important role in modulating the variability of the DPEs in the two basins. Singular value decomposition (SVD) analysis revealed that both the YRB and the MDRB’s whole-basin-type DPEs are closely coupled with the procedure that the preceding winter eastern Pacific (EP)-type El Nino faded to a central Pacific (CP)-type La Nina. This means that the DPEs in the YRB and MDRB may synchronously occur more frequently when the above process occurs. Owing to the atmosphere–ocean interaction from the east–west dipole sea surface temperature (SST) anomaly pattern, the atmospheric circulation disturbance exhibits a pattern in which the equatorial eastern Pacific region is a mass source anomaly with a higher pressure, drier air, and weaker convection, while the equatorial western Pacific region is a mass sink anomaly with a lower pressure, wetter air, and stronger convection. Moreover, two wave trains that originated from the tropical western Pacific were found to extend to the YRB and MDRB. The interaction between the wave train’s interphase dynamics and water vapor transport disturbance results in the ascent conditions and enhanced water vapor transport, which leads to the synchronous occurrence of DPEs in the YRB and MDRB on an interannual scale.

A historical record of the impact of nuclear activities based on 129I in coral cores in Baler, Philippines: An update

In a previous study in 2016, we presented how 129I in coral cores from the east (Baler) and west (Parola) sides of the Philippines recorded the impacts of human nuclear activities, including nuclear weapons testing, nuclear fuel reprocessing, and nuclear accidents. However, the 2016 Baler dataset only had a two-year time resolution and a crude age model based on growth band counting. Here we present a new 2020 Baler 129I/127I atomic ratio dataset that features at least annual time resolution and a more accurate age model constructed using 3D X-ray Computed Tomography. Results show that the bomb peaks in Baler primarily came from the Pacific Proving Grounds or PPG with a time lag of about 1.8 years (or more specifically, between 1.3 and 2.4 years). Moreover, a review of the Parola dataset shows that PPG signals may have been transported to Parola in the West Philippine Sea via two pathways: the northward and southward bifurcations of the North Equatorial Current, reaching Parola about 4.5 and 8.5 years after detonation, respectively. Moreover, a prominent peak in the year 2014.7 in Baler possibly came from the 2011 Fukushima Accident, transported by the Kuroshio Recirculation Gyre and the North Pacific Mode Waters with a 3.5-year time lag. This study contributes to the understanding of the impact and transport of human-made radionuclides to the Philippines and the relevant oceanographic processes in the Western Equatorial Pacific region.

Inter-annual variability and skill of tropical rainfall and SST in APCC seasonal forecast models

The present study explored the performance of the current coupled models obtained from the Asia Pacific Economic Cooperation (APEC) Climate Centre (APCC) in representing the tropical Indo-Pacific sea surface temperature (SST) and rainfall during boreal summer season (June through September; JJAS). We have used the retrospective/hindcast runs for 28 years from 1983 to 2010 initialized in May. The mean SST bias in the tropical Indo-Pacific Oceans showed large diversity among the models in JJAS. In the case of the rainfall, most of the models displayed a strong dry bias over the major continental regions and wet biases over the tropical oceans. The majority of the models simulated the Inter-annual variability (IAV) of JJAS rainfall and SST reasonably well over the equatorial Pacific region, where the models are close to observed IAV and maximum signal to noise ratio (SNR). It is found that the models display, low IAV of rainfall and SST over the Indian Ocean with low SNR values, resulting in less predictive skill as compared to the tropical Pacific region. Similarly, all models showed a higher skill in summer rainfall prediction over the oceanic regions compared to the Asian land region, where SNR is very low. Further analysis suggested that the models have greater skill in predicting El Nino-Southern Oscillation (ENSO). The category wise analysis showed that models could predict 60–70% of the extreme ENSO events, but the normal events are represented only by 50%. It is noted that the models predict many false alarms for El Nino resulting in a higher frequency of El Nino occurrence. This is mainly responsible for stronger ENSO and the Asian Monsoon teleconnections in the models than in the observations. Meanwhile, the category wise rainfall skill for extended Indian monsoon region (EMR) displayed 50–60% accuracy for the extreme monsoon years and is around 50% for normal years. However, models such as CCSM3, CFSV2, and CANCM3 have displayed higher rainfall skills over EMR as compared to the other models possibly due to better representation of teleconnections spatial patterns between EMR rainfall and SST anomalies over Indo-Pacific Oceans.

ENSO Precipitation Anomalies along the Equatorial Pacific: Moist Static Energy Framework Diagnostics

AbstractWith the recognition that equatorial Pacific precipitation anomalies are fundamental to global teleconnections during ENSO winters, the present research applies vertically integrated moist static energy (MSE) budget analysis to historical simulations of CMIP5 models. Process-based assessment is carried out to understand if the models capture the differing processes that account for regional precipitation anomalies along the equatorial Pacific and to isolate a few leading processes that account for the diversified precipitation response to similar SST forcing and vice versa. To assess SST biases in CMIP5, analysis is also carried out in AMIP5 solutions. Diagnostics reveal that models have limitations in representing the “sign” of MSE sources and sinks and, even if they do, compensating errors dominate the budget. The diverse response in precipitation depends on model parameterizations that determine anomalous net radiative flux divergence in the column, free troposphere moisture, and MSE export out of the column, although these processes are not independent. Diagnostics derived from AMIP5 solutions support the findings from CMIP5. The implication is that biases in representing any one of these processes are expected to imprint on others, acknowledging the tight connections among moisture, convection, and radiation. CMIP5 models have limitations in representing the basic states in SST and precipitation over the Niño-3.4 region, and the different convective regimes over the equatorial central and eastern Pacific regions with implications for ENSO. Study limitations are that MSE sources/sinks depend on parameterizations and their interactions, making it difficult to isolate one particular process for attribution. Budgets estimated from monthly anomalies do not capture contributions from high-frequency variability that are vital in closing the budgets.

ENSO Dynamics, Trends, and Prediction Using Machine Learning

AbstractEl Niño–Southern Oscillation (ENSO) has global effects on the hydrological cycle, agriculture, ecosystems, health, and society. We present a novel nonhomogeneous hidden Markov model (NHMM) for studying the underlying dynamics of sea surface temperature anomalies (SSTA) over the region 15°N–15°S, 150°E–80°W from January 1856 to December 2019, using the monthly SSTA data from the Kaplan extended SST v2 product. This nonparametric machine learning scheme dynamically simulates and predicts the spatiotemporal evolution of ENSO patterns, including their asymmetry, long-term trends, persistence, and seasonal evolution. The model identifies five hidden states whose spatial SSTA patterns are similar to the so-called ENSO flavors in the literature. From the fitted NHMM, the model shows that there are systematic trends in the frequency and persistence of the regimes over the last 160 years that may be related to changes in the mean state of basin temperature and/or global warming. We evaluated the ability of NHMM to make out-of-sample probabilistic predictions of the spatial structure of temperature anomalies for the period 1995–2016 using a training period from January 1856 to December 1994. The results show that NHMMs can simulate the behavior of the Niño-3.4 and Niño-1.2 regions quite well. The NHMM results over this period are comparable or superior to the commonly available ENSO prediction models, with the additional advantage of directly providing insights as to the space patterns, seasonal, and longer-term trends of the SSTA in the equatorial Pacific region.