Pacific Sea Surface Temperature Pattern Research Articles

Recent global climate feedback controlled by Southern Ocean cooling

The magnitude of global warming is controlled by climate feedbacks associated with various aspects of the climate system, such as clouds. The global climate feedback is the net effect of these feedbacks, and its temporal evolution is thought to depend on the tropical Pacific sea surface temperature pattern. However, current coupled climate models fail to simulate the pattern observed in the Pacific between 1979 and 2013 and its associated anomalously negative feedback. Here we demonstrate a mechanism whereby the Southern Ocean controls the global climate feedback. Using climate model experiments in which Southern Ocean sea surface temperatures are restored to observations, we show that accounting for recent Southern Ocean cooling—which is absent in coupled climate models—halves the bias in the global climate feedback by removing the cloud component bias. This global impact is mediated by a teleconnection to the Southeast Pacific, where remote sea surface temperature anomalies cause a strong stratocumulus cloud feedback. We propose that this Southern Ocean-driven pattern effect is underestimated in most climate models, owing to an overly weak stratocumulus cloud feedback. Addressing this bias may shift climate sensitivities to higher values than currently simulated as the Southern Ocean undergoes accelerated warming in future projections.

Skillful U.S. Soy Yield Forecasts at Presowing Lead Times

Abstract Soy harvest failure events can severely impact farmers, insurance companies, and raise global prices. Reliable seasonal forecasts of misharvests would allow stakeholders to prepare and take appropriate early action. However, especially for farmers, the reliability and lead time of current prediction systems provide insufficient information to justify within-season adaptation measures. Recent innovations increased our ability to generate reliable statistical seasonal forecasts. Here, we combine these innovations to predict the 1–3 poor soy harvest years in the eastern United States. We first use a clustering algorithm to spatially aggregate crop producing regions within the eastern United States that are particularly sensitive to hot–dry weather conditions. Next, we use observational climate variables [sea surface temperature (SST) and soil moisture] to extract precursor time series at multiple lags. This allows the machine learning model to learn the low-frequency evolution, which carries important information for predictability. A selection based on causal inference allows for physically interpretable precursors. We show that the robust selected predictors are associated with the evolution of the horseshoe Pacific SST pattern, in line with previous research. We use the state of the horseshoe Pacific to identify years with enhanced predictability. We achieve high forecast skill of poor harvests events, even 3 months prior to sowing, using a strict one-step-ahead train-test splitting. Over the last 25 years, when the horseshoe Pacific SST pattern was anomalously strong, 67% of the poor harvests predicted in February were correct. When operational, this forecast would enable farmers to make informed decisions on adaption measures, for example, selecting more drought-resistant cultivars or change planting management. Significance Statement If soy farmers would know that the upcoming growing season will be hot and dry, they could decide to take anticipatory action to reduce losses, that is, buy more drought resistant soy cultivars or change planting management. To make such decisions, farmers would need information even prior to sowing. On these very long lead times, a predictable signal can emerge from low-frequency processes of the climate system that can affect surface weather via teleconnections. However, traditional forecast systems are unable to make reliable predictions at these lead times. In this work, we used machine learning techniques to train a forecast model based on these low-frequency components. This allowed us to make reliable predictions of poor harvest years even 3 months prior to sowing.

Joint Contribution of Preceding Pacific SST and Yunnan-Guizhou Plateau Soil Moisture to September Precipitation over the Middle Reaches of the Yellow River

The middle reaches of the Yellow River (MRYR) are an important base for agricultural and husbandry production and coal and coal-based power and chemical industries. Understanding the variability of autumn (especially September) precipitation over the MRYR region and the associated atmospheric circulation anomalies and precursory signals is of great importance for the prevention and mitigation of meteorological disasters during autumn rainy season. This study primarily explored precursory signals for September precipitation over the MRYR from the perspectives of sea surface temperature (SST) and soil moisture (SM) anomalies. The results reveal that the northward-shifted East Asian westerly jet (EAWJ) and the strengthened and westward-extended western Pacific subtropical high (WPSH) are responsible for more precipitation over the MRYR region. Further analyses show that the September MRYR precipitation is significantly related to the preceding July–August southern Pacific SST pattern (SPSP) and Yunnan-Guizhou Plateau (YGP) SM. The preceding SPSP anomaly, which reflects the La Niña/El Niño-like SST anomalies, can be maintained until September and plays an important role in modulating the September MRYR precipitation. Moreover, the above SST anomalies may adjust the SM anomalies in the YGP during July–August. The SM anomalies in The YGP persist from July–August to September and eventually affect the MRYR precipitation through exciting an anomalous vertical motion during September. The effect of the preceding SPSP anomaly on the September MRYR precipitation decreases when the SM effect is absent, which suggests that the YGP SM anomalies act as a bridge linking the preceding Pacific SST anomalies and the ensuing September MRYR precipitation. This study discloses the joint contribution of the preceding Pacific SST and YGP SM anomalies to the September MRYR precipitation and may shed new light on the short-term prediction of autumn precipitation over the MRYR.

Decadal prediction skill for spring and summer surface air-temperature over India and its association with SST patterns in CFSv2 and CNRM coupled models

In this study, we have assessed the skill of decadal prediction of boreal spring (March–May) and summer (June–September) Surface Air Temperature (SAT) over India and its relation with Sea Surface Temperature (SST) in the National Centers for Environmental Prediction (NCEP) Climate Forecast System Version 2 (CFSv2) coupled model. The skill of CFSv2 is compared with CNRM (Centre National de Recherches Meteorologiques) coupled model, which is the best among the selected CMIP5 (Coupled Model Intercomparison Project 5) models for long-lead forecasts (6–9 years) of global SSTs (with high skill). It is found that both models show significant skill in predicting 4-year mean SAT over central and southern peninsular India at 1–5 year leads in spring. During summer, significant skills for SAT over the northwest and southeast India are seen in CFSv2, whereas CNRM displayed significant skills over the north and central India at 1–5 years lead. The first Empirical Orthogonal Function (EOF) mode of SAT variability over India indicates a country-wide warming/cooling pattern in both observations and models for spring and summer. The analysis reveals that the decadal variability of SAT (EOF-1) over India is highly related to SST variations over the Indo-Pacific and North Atlantic regions. The strong convergence of low-level winds over the equatorial Indian Ocean and maritime continent accompanied by warm SST anomalies drive the northerly dry winds over India and favour warm SAT in both spring and summer. Further, changes in shortwave radiation also contributed to SAT variability over India. In general, the SAT relationship with SST in different parts of tropical and sub-tropical regions is underestimated in CFSv2 compared to the observations and CNRM in both boreal spring and summer. The models are able to represent the changes in the atmospheric circulation and related Indo-Western Pacific SST patterns reasonably well at the 1–5 years lead with some discrepancy. However, both models showed relatively low skills in capturing the relationship between SAT over India and equatorial Pacific SSTs. This might limit the skills of models in predicting decadal variations of SAT over India.

Decadal Modulation of Precipitation Patterns over Eastern China by Sea Surface Temperature Anomalies

Annual precipitation anomalies over eastern China are characterized by a north–south dipole pattern, referred to as the “southern flooding and northern drought” pattern (SF/ND), fluctuating on decadal time scales. Previous research has suggested possible links with oceanic forcing, but the underlying physical mechanisms by which sea surface temperature (SST) variability impacts the dipole pattern remains unclear. Idealized atmospheric general circulation model experiments conducted by the U.S. CLIVAR Drought Working Group are used to investigate the role of historical SST anomalies associated with Pacific El Niño–Southern Oscillation (ENSO)-like and the Atlantic multidecadal oscillation (AMO) patterns in this dipole pattern. The results show that the Pacific SST pattern plays a dominant role in driving the decadal variability of this dipole pattern and the associated atmospheric circulation anomalies, whereas the Atlantic SST pattern contributes to a much lesser degree. The direct atmospheric response to the Pacific SST pattern is a large-scale cyclonic or anticyclonic circulation anomaly in the lower troposphere occupying the entire northern North Pacific. During the warm phase of the Pacific SST pattern, it is cyclonic with northwesterly wind anomalies over northern China pushing the monsoon front to the south and consequently SF/ND. During the cold phase of the Pacific SST pattern, the circulation anomaly reverses with southeasterly winds over northern China allowing the monsoon front and the associated rainband to migrate northward, resulting in southern drought and northern flooding. The Atlantic SST pattern plays a supplementary role, enhancing the dipole pattern when the Pacific SST and Atlantic SST patterns are in opposite phases and weakening it when the phases are the same.

Natural variations of tropical width and recent trends

AbstractThe temporal evolution of the tropical width since 1979 is investigated in observations and models by using metrics based on outgoing radiation, 6.7 µm brightness temperature, and atmospheric reanalysis. The maximum 20 year widening as seen in radiation by satellites occurred during 1993–2012 and was associated with a global sea surface temperature (SST) change that resembles the El Niño–Southern Oscillation/Pacific Decadal Oscillation in the Pacific region. Idealized experiments with Community Atmospheric Model version 5 reveal that Tropical Pacific SST pattern largely accounts for the widening. A number of Coupled Model Intercomparison Project Phase 5 coupled models can simulate, without any type of forcing, this satellite‐inferred tropical widening and its associated Pacific SST pattern. While model‐simulated widenings are consistent for all metrics, the two reanalysis‐based widenings are inconsistent internally and with the satellite‐based and model widenings. Our results reinforce suggestions that observed widenings can be explained by internal variability as captured by climate models, though this depends on whether reanalysis trends are regarded as reliable.

La Niña diversity and Northwest Indian Ocean Rim teleconnections

The differences in tropical Pacific sea surface temperature (SST) expressions of El Nino-Southern Oscillation (ENSO) events of the same phase have been linked with different global atmospheric circulation patterns. This study examines the dynamical forcing of precipitation during October–December (OND) and March–May (MAM) over East Africa and during December–March (DJFM) over Central-Southwest Asia for 1950–2010 associated with four tropical Pacific SST patterns characteristic of La Nina events, the cold phase of ENSO. The self-organizing map method along with a statistical distinguishability test was used to isolate La Nina events, and seasonal precipitation forcing was investigated in terms of the tropical overturning circulation and thermodynamic and moisture budgets. Recent La Nina events with strong opposing SST anomalies between the central and western Pacific Ocean (phases 3 and 4), force the strongest global circulation modifications and drought over the Northwest Indian Ocean Rim. Over East Africa during MAM and OND, subsidence is forced by an enhanced tropical overturning circulation and precipitation reductions are exacerbated by increases in moisture flux divergence. Over Central-Southwest Asia during DJFM, the thermodynamic forcing of subsidence is primarily responsible for precipitation reductions, with moisture flux divergence acting as a secondary mechanism to reduce precipitation. Eastern Pacific La Nina events in the absence of west Pacific SST anomalies (phases 1 and 2), are associated with weaker global teleconnections, particularly over the Indian Ocean Rim. The weak regional teleconnections result in statistically insignificant precipitation modifications over East Africa and Central-Southwest Asia.

Variability of agro climatic regime over homogeneous monsoon regions of India — El Niño and La Niña events

The global short term climate signal from the Equatorial Pacific sea surface temperature pattern in conjunction with the Southern oscillation of sea level pressure plays a crucial role in governing the global weather systems by modulating and altering the yearly climate scenario across the globe. The analysis of Normalized Difference in Vegetation Index (NDVI) fields of the five homogeneous regions of India with the index of moisture adequacy and Multivariate ENSO Index yielded the phenological metrics such as senescence in terms of greenness up and down along with the lag between maximum NDVI and index of moisture adequacy for normal (1982–2000), El Niño (1997) and La Niña (1998) years respectively. A threshold value of 60% soil moisture adequacy is considered for sustainable crop or vegetation growth in obtaining the phenological metrics for the regions under consideration. The north east, peninsular India along with west central India experienced an increase in the number of humid days both in the El Niño and La Niña years compared to normal. The annual figures of All India rice yields are increasing linearly and the trend was significant but no trend is noticed in moisture adequacy. An agro climatic model is developed for the estimation of All India rice yield and is of help in designing the agro meteorological advisories.

Evaluation of the South Pacific Convergence Zone in IPCC AR4 Climate Model Simulations of the Twentieth Century

Abstract Understanding how the South Pacific convergence zone (SPCZ) may change in the future requires the use of global coupled atmosphere–ocean models. It is therefore important to evaluate the ability of such models to realistically simulate the SPCZ. The simulation of the SPCZ in 24 coupled model simulations of the twentieth century is examined. The models and simulations are those used for the Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC). The seasonal climatology and interannual variability of the SPCZ is evaluated using observed and model precipitation. Twenty models simulate a distinct SPCZ, while four models merge intertropical convergence zone and SPCZ precipitation. The majority of models simulate an SPCZ with an overly zonal orientation, rather than extending in a diagonal band into the southeast Pacific as observed. Two-thirds of models capture the observed meridional displacement of the SPCZ during El Niño and La Niña events. The four models that use ocean heat flux adjustments simulate a better tropical SPCZ pattern because of a better representation of the Pacific sea surface temperature pattern and absence of cold sea surface temperature biases on the equator. However, the flux-adjusted models do not show greater skill in simulating the interannual variability of the SPCZ. While a small subset of models does not adequately reproduce the climatology or variability of the SPCZ, the majority of models are able to capture the main features of SPCZ climatology and variability, and they can therefore be used with some confidence for future climate projections.

Paleoclimate reconstruction along the Pole–Equator–Pole transect of the Americas (PEP 1)

Examples are presented of inter-hemispheric comparison of instrumental climate and paleoclimate proxy records from the Americas for different temporal scales. Despite a certain symmetry of seasonal precipitation patterns along the PEP 1 transect, decadal variability of winter precipitation shows different characteristics in terms of amplitude and frequency in both the last 100 and last 1000 years. Such differences in variability are also seen in a comparison of time series of different El Niño/Southern Oscillation proxy records from North and South America, however, these differences do not appear to affect the spatial correlation with Pacific sea surface temperature patterns. Local and regional differences in response to climate change are even more pronounced for records with lower temporal resolution, and inter-hemispheric synchroneity may or may not be indicative of the same forcing. This aspect is illustrated in an inter-hemispheric comparison of the last 1000 years of glacier variability, and of the full- and lateglacial lake level history.

Premonitory Signs of the 1978 Break in the West Coast Drought

A diagnosis is made of the atmospheric-flow patterns and North Pacific sea surface temperature patterns leading up to the dramatic break in the western drought of the winters 1975–76 and 1976–77. Excessively wet weather occurred during the winter 1977–78. Antecedent signs of the break occurred as early as September 1977—both in atmospheric flow patterns over the Northern Hemisphere and in North Pacific sea surface temperatures. Quasi-objective methods of long-range prediction involving large-scale air-sea interactions were employed to successfully predict the change in precipitation regime.