Large-scale Modes Of Climate Variability Research Articles

Two centuries of southwest Iceland annually-resolved marine temperature reconstructed from Arctica islandica shells

Iceland's exposure to major ocean current pathways of the central North Atlantic makes it a useful location for developing long-term proxy records of past marine climate. Such records provide more detailed understanding of the full range of past variability which is necessary to improve predictions of future changes. We constructed a 225-year (1791–2015 CE) master shell growth chronology from 29 shells of Arctica islandica collected at 100 m water depth in southwest Iceland (Faxaflói). The growth chronology provides a robust age model for shell oxygen isotope (δ18Oshell) data produced at annual resolution for 251 years (1765–2015 CE). The temperature reconstruction derived from δ18Oshell shows coherence with May–October local surface temperature records and sea surface temperatures in the North Atlantic region, suggesting it is a useful proxy indicator of water temperature variability at 100 m depth within Faxaflói. Field correlations between the shell-based records and gridded sea surface temperature data reveal strong positive correlations between the 1-year lagged shell growth and temperatures within the subpolar gyre post-1972, suggesting a delayed influence of subpolar gyre dynamics on ecological indicators in southwest Iceland in recent decades. However, the shell growth chronology and δ18Oshell record generally show relatively weak and insignificant correlations with larger region climate indices including the Atlantic Multidecadal Variability, North Atlantic Oscillation, and East Atlantic pattern. Therefore the interannual variations in the newly produced shell-based records appear to reflect more local to regional dynamics around southwest Iceland than large-scale modes of climate variability.

Drought- and heatwave-associated compound extremes: A review of hotspots, variables, parameters, drivers, impacts, and analysis frameworks

Droughts and heatwaves are rising concerns with regard to the frequent formation of the compound or concurrent extremes (CEs), which can cause greater havoc than an individual event of a higher magnitude. Recently, they have been frequently detected to form CEs together or with other events (e.g., floods, aridity, and humidity events) concurrently or with spatiotemporal lags. Therefore, this systematic review assesses these CEs by reviewing the following aspects: CE hotspots, events, and variable combinations that form CEs; frequently analyzed CE parameters (e.g., frequency and severity); large-scale modes of climate variability (CV) as drivers alongside the approaches to relate them to CEs; and CE impacts (e.g., yield loss and fire risk) alongside the impact integration approaches from 166 screened publications. Additionally, three varied analysis frameworks of CEs are summarized to highlight the different analysis components of drought- and heatwave-associated CEs, which is the novelty of this study. The analysis frameworks vary with regard to the three major assessment objectives: only CE parameters (event–event), driver association (event–driver), and impacts (event–impact). According to this review, the most frequently reported hotspots of these CEs in global studies are southern Africa, Australia, South America, and Southeast Asia. In regional studies, several vital hotspots (e.g., Iberian Peninsula, Balkans, and Mediterranean Basin) have been reported, some of which have not been mentioned in global studies because they usually report hotspots as broader regions. In addition, different event combinations (e.g., drought and heatwave; and heatwave and stagnation) are analyzed by varying the combination of variables, namely, temperature, precipitation, and their derived indices. Thus, this study presents three major analysis frameworks and components of drought- and heatwave-associated CE analysis for prospective researchers.

Linking maize yields in Veneto Italy, to large-scale atmospheric variability, circulation regimes and weather types

AbstractThis paper describes the relationships between large-scale modes of climate variability and its related weather types with the fluctuations in the yield of maize crops in Veneto, Italy. The teleconnections analysed in this work are the winter North Atlantic Oscillation (NAO) and the summer North Atlantic Oscillation (SNAO); the West African monsoon (WAM) and the Intertropical Front (ITF). Despite that these indices are not rigorously linked to one another, they result in being considerably related to atmospheric circulation regimes and associated weather types. They have an impact on temperature and precipitation patterns in Italy and on yields of maize crops in Veneto, a region located in northeast Italy. Yields are strongly affected by large-scale temperate and tropical variability directly through three main circulation regimes. Troughing weather regimes that produced below average temperatures depress yields over the entire Veneto region, as does the zonal regime that affects rainfall. Results confirm the relevance of large-scale modes and associated weather regimes and types on maize crop yields fluctuations in Veneto.

The Impact of Interacting Climate Modes on East Australian Precipitation Moisture Sources

Abstract Modes of climate variability can drive significant changes to regional climate affecting extremes such as droughts, floods, and bushfires. The need to forecast these extremes and expected future increases in their intensity and frequency motivates a need to better understand the physical processes that connect climate modes to regional precipitation. Focusing on east Australia, where precipitation is driven by multiple interacting climate modes, this study provides a new perspective into the links between large-scale modes of climate variability and precipitation. Using a Lagrangian back-trajectory approach, we examine how El Niño–Southern Oscillation (ENSO) modifies the supply of evaporative moisture for precipitation, and how this is modulated by the Indian Ocean dipole (IOD) and southern annular mode (SAM). We demonstrate that La Niña modifies large-scale moisture transport together with local thermodynamic changes to facilitate local precipitation generation, whereas below-average precipitation during El Niño stems predominantly from increased regional subsidence. These dynamic–thermodynamic processes were often more pronounced during co-occurring La Niña/negative IOD and El Niño/positive IOD periods. As the SAM is less strongly correlated with ENSO, the impact of co-occurring ENSO and SAM largely depended on the state of ENSO. La Niña–related processes were exacerbated when combined with +SAM and dampened when combined with −SAM, and vice versa during El Niño. This new perspective on how interacting climate modes physically influence regional precipitation can help elucidate how model biases affect the simulation of Australian climate, facilitating model improvement and understanding of regional impacts from long-term changes in these modes. Significance Statement How climate modes modulate the oceanic and terrestrial sources of moisture for rainfall in east Australia is investigated. East Australia is wetter during La Niña because more moisture is transported into the region and is more easily turned into rainfall when it arrives, whereas drier conditions during El Niño are because local conditions inhibit the conversion of moisture into rainfall. Distant atmospheric changes over the Indian and Southern Oceans can intensify these changes. Our results can be used to better understand and predict the regional impact of long-term changes in these modes of climate variability, which are potentially altered under climate change.

Tree-Ring Stable Carbon Isotope as a Proxy for Hydroclimate Variations in Semi-Arid Regions of North-Central China

Carbon and oxygen isotope ratios (δ13C and δ18O) were measured in annual tree-ring cellulose samples dated from 1756 to 2015 CE. These samples were extracted from Chinese pine (Pinus tabulaeformis Carr.) trees located in a semi-arid region of north-central China. We found that tree-ring δ13C and δ18O values both recorded similar climatic signals (e.g., temperature and moisture changes), but found that tree-ring δ13C exhibited a stronger relationship with mean temperature, precipitation, average relative humidity, self-calibrating Palmer drought severity index (scPDSI), and standard precipitation evaporation index (SPEI) than δ18O during the period 1951–2015 CE. The strongest correlation observed was between tree-ring δ13C and scPDSI (previous June to current May), which explains ~43% of the variance. The resulting 130-year reconstruction reveals severe drought events in the 1920s and a sustained drying trend since the 1980s. This hydroclimate record based on tree-ring δ13C data also reveals similar dry and wet events to other proxy data (i.e., tree-ring width and historical documentation) that have allowed reconstructions to be made across the northern fringe of the Asian summer monsoon region. Our results suggest that both large-scale modes of climate variability (e.g., El Niño-Southern Oscillation, Pacific Decadal Oscillation, and North Atlantic Oscillation) and external forcing (e.g., solar variability) may have modulated moisture variability in this region. Our results imply that the relationship between tree-ring δ18O and local climate is less well-characterized when compared to δ13C and may be affected more strongly by the influences of these different atmospheric circulation patterns. In this semi-arid region, tree-ring δ13C appears to represent a better tool with which to investigate historical moisture changes (scPDSI).

The effects of ENSO and the North American monsoon on mast seeding in two Rocky Mountain conifer species.

We aimed to disentangle the patterns of synchronous and variable cone production (i.e. masting) and its relationship to climate in two conifer species native to dry forests of western North America. We used cone abscission scars to reconstruct ca 15 years of recent cone production in Pinus edulis and Pinus ponderosa, and used redundancy analysis to relate time series of annual cone production to climate indices describing the North American monsoon and the El Niño Southern Oscillation (ENSO). We show that the sensitivity to climate and resulting synchrony in cone production varies substantially between species. Cone production among populations of P. edulis was much more spatially synchronous and more closely related to large-scale modes of climate variability than among populations of P. ponderosa. Large-scale synchrony in P. edulis cone production was associated with the North American monsoon and we identified a dipole pattern of regional cone production associated with ENSO phase. In P. ponderosa, these climate indices were not strongly associated with cone production, resulting in asynchronous masting patterns among populations. This study helps frame our understanding of mast seeding as a life-history strategy and has implications for our ability to forecast mast years in these species. This article is part of the theme issue 'The ecology and evolution of synchronized seed production in plants'.

Calibration of ECMWF Seasonal Ensemble Precipitation Reforecasts in Java (Indonesia) Using Bias-Corrected Precipitation and Climate Indices

AbstractThe seasonal precipitation forecast is one of the essential inputs for economic and agricultural activities and has significant impact on decision-making. Large-scale modes of climate variability have strong relationships with seasonal rainfall in Java and are natural candidates for use as potential predictors in a statistical postprocessing application. We explore whether using climate indices as additional predictors in the statistical postprocessing of ECMWF Seasonal Forecast System 5 (SEAS5) precipitation can improve skill. We use parametric statistical postprocessing by applying a logistic distribution-based ensemble model output statistics (EMOS) technique. We add a variety of potential predictors in the analysis, namely SEAS5 raw and empirical quantile mapping (EQM) bias-corrected precipitation, Niño-3.4 index, dipole mode index (DMI), Madden–Julian oscillation (MJO) indices, sea surface temperature (SST) around Java, and several other predictors. We analyze the period of 1981–2010, focusing on July, August, September, and October. We use the continuous ranked probability skill score (CRPSS) and Brier skill score (BSS) in a comparative verification of raw, EQM, and EMOS seasonal precipitation forecasts. We have found that it is essential to use EQM-corrected precipitation as a predictor instead of raw precipitation in the latter. Besides, Niño-3.4 and DMI forecasts are not needed as extra predictors to improve monthly precipitation forecasts for the first lead month, except for September. However, for somewhat longer lead months, in September and October when there is more skill than climatology, the model that includes only Niño-3.4 and DMI forecasts as potential predictors performs about the same compared to the model that uses only EQM-corrected precipitation as a predictor.

Influence of ENSO and tropical Atlantic climate variability on flood characteristics in the Amazon basin

Abstract. Flooding in the Amazon basin is frequently attributed to modes of large-scale climate variability, but little attention is paid to how these modes influence the timing and duration of floods despite their importance to early warning systems and the significant impacts that these flood characteristics can have on communities. In this study, river discharge data from the Global Flood Awareness System (GloFAS 2.1) and observed data at 58 gauging stations are used to examine whether positive or negative phases of several Pacific and Atlantic indices significantly alter the characteristics of river flows throughout the Amazon basin (1979–2015). Results show significant changes in both flood magnitude and duration, particularly in the north-eastern Amazon for negative El Niño–Southern Oscillation (ENSO) phases when the sea surface temperature (SST) anomaly is positioned in the central tropical Pacific. This response is not identified for the eastern Pacific index, highlighting how the response can differ between ENSO types. Although flood magnitude and duration were found to be highly correlated, the impacts of large-scale climate variability on these characteristics are non-linear; some increases in annual flood maxima coincide with decreases in flood duration. The impact of flood timing, however, does not follow any notable pattern for all indices analysed. Finally, observed and simulated changes are found to be much more highly correlated for negative ENSO phases compared to the positive phase, meaning that GloFAS struggles to accurately simulate the differences in flood characteristics between El Niño and neutral years. These results have important implications for both the social and physical sectors working towards the improvement of early warning action systems for floods.

Assessing the contribution of the ENSO and MJO to Australian dust activity based on satellite- and ground-based observations

Abstract. Despite Australian dust's critical role in the regional climate and surrounding marine ecosystems, the controlling factors of the spatiotemporal variations of Australian dust are not fully understood. Here we assess the connections between observed spatiotemporal variations of Australian dust with key modes of large-scale climate variability, namely the El Niño–Southern Oscillation (ENSO) and Madden–Julian Oscillation (MJO). Multiple dust observations from the Aerosol Robotic Network (AERONET), weather stations, and satellite instruments, namely the Moderate Resolution Imaging Spectroradiometer (MODIS) and Multi-angle Imaging SpectroRadiometer (MISR), are examined. The assessed multiple dust observations consistently identify the natural and agricultural dust hotspots in Australia, including the Lake Eyre basin, Lake Torrens basin, Lake Frome basin, Simpson Desert, Barwon–Darling basin, Riverina, Barkly Tableland, and the lee side of the Great Dividing Range, as well as a country-wide, austral spring-to-summer peak in dust activity. Our regression analysis of observed dust optical depth (DOD) upon an ocean Niño index confirms previous model-based findings on the enhanced dust activity in southern and eastern Australia during the subsequent austral spring and summer dust season following the strengthening of austral wintertime El Niño. Our analysis further indicates the modulation of the ENSO–dust relationship with the MJO phases. During sequential MJO phases, the dust-active center moves from west to east, associated with the eastward propagation of MJO, with the maximum enhancement in dust activity at about 120, 130, and 140∘ E, corresponding to MJO phases 1–2, 3–4, and 5–6, respectively. MJO phases 3–6 are favorable for enhanced ENSO modulation of dust activity, especially the occurrence of extreme dust events, in southeastern Australia, currently hypothesized to be attributed to the interaction between MJO-induced anomalies in convection and wind and ENSO-induced anomalies in soil moisture and vegetation.

The precipitation variability of the wet and dry season at the interannual and interdecadal scales over eastern China (1901–2016): the impacts of the Pacific Ocean

Abstract. The spatiotemporal variability of rainfall in the dry (October–March) and wet (April–September) seasons over eastern China is examined from 1901–2016 based on the gridded rainfall dataset from the University of East Anglia Climatic Research Unit. Principal component analysis is employed to identify the dominant variability modes, wavelet coherence is utilized to investigate the spectral features of the leading modes of precipitation and their coherences with the large-scale modes of climate variability, and the Bayesian dynamical linear model is adopted to quantify the time-varying correlations between climate variability modes and rainfall in the dry and wet seasons. Results show that first and second principal components (PCs) account for 34.2 % (16.1 %) and 13.4 % (13.9 %) of the variance in the dry (wet) season, and their variations are roughly coincident with phase shifts of the El Niño–Southern Oscillation (ENSO) in both seasons. The anomalous moisture fluxes responsible for the occurrence of precipitation events in eastern China exhibit an asymmetry between high and light rainfall years in the dry (wet) season. The ENSO has a 4- to 8-year signal of the statistically positive (negative) association with rainfall during the dry (wet) season over eastern China. The statistically significant positive (negative) associations between the Pacific Decadal Oscillation (PDO) and precipitation are found with a 9- to 15-year (4- to 7-year) signal. The impacts of the PDO on rainfall in eastern China exhibit multiple timescales as compared to the ENSO episodes, while the PDO triggers a stronger effect on precipitation in the wet season than the dry half year. The interannual and interdecadal variations in rainfall over eastern China are substantially modulated by drivers originated from the Pacific Ocean. During the wet season, the ENSO exerted a gradually weakening effect on eastern China rainfall from 1901 to 2016, while the effects of the PDO decreased before the 1980s, and then shifted into increases after the 2000s. The finding provides a metric for assessing the capability of climate models and guidance of seasonal prediction.

Links between Large-Scale Modes of Climate Variability and Synoptic Weather Patterns in the Southern Indian Ocean

AbstractWeather systems in the southern Indian Ocean (SIO) drive synoptic-scale precipitation variability in East Antarctica and southern Australia. Improved understanding of these dynamical linkages is beneficial to diagnose long-term climate changes from climate proxy records as well as informing regional weather and climate forecasts. Self-organizing maps (SOMs) are used to group daily 500-hPa geopotential height (z500; ERA-Interim) anomalies into nine regional synoptic types based on their dominant patterns over the SIO (30°–75°S, 40°–180°E) from January 1979 to October 2018. The pattern anomalies represented include four meridional, three mixed meridional–zonal, one zonal, and one transitional node. The frequency of the meridional nodes shows limited association with the phase of the southern annular mode (SAM), especially during September–November. The zonal and mixed patterns were nevertheless strongly and significantly correlated with SAM, although the regional synoptic representation of SAM+ conditions was not zonally symmetric and was represented by three separate nodes. We recommend consideration of how different synoptic conditions vary the atmospheric representation of SAM+ in any given season in the SIO. These different types of SAM+ mean a hemispheric index fails to capture the regional variability in surface weather conditions that is primarily driven by the synoptic variability rather than the absolute polarity of the SAM.

Linking crop yields in Tuscany, Italy, to large-scale atmospheric variability, circulation regimes and weather types

AbstractThe paper presents results from a study examining the relationship between large-scale modes of climate variability with the fluctuations in the yield of barley, durum wheat, olives and sunflower crops in Tuscany, Italy. In particular, the blocking circulation over the growing season, with associated hot and dry conditions, decreased yield for olive crops, barley and durum wheat. The teleconnections analysed in this study are the winter North Atlantic Oscillation (NAO) and the Summer North Atlantic Oscillation (SNAO); the West African Monsoon (WAM) and the Intertropical Front (ITF); and although NAO, SNAO, ITF and WAM are not strictly related to each other, the values of these indices are strongly related to the atmospheric circulation regimes and related weather types. Thus, they have an impact on precipitation and temperature patterns in Italy and on yields of important crops in Tuscany. Results show that the large-scale temperate and tropical variability directly influences the crop yield through three main circulation regimes. These patterns illustrate the importance of the large-scale modes, which, together with the associated weather types, have an impact directly on Tuscan crop yields; both barley and olive yields decline significantly when the ITF is further north with warmer and drier conditions in Italy.

Precipitation responses to ENSO and IOD in the Maldives: Implications of large-scale modes of climate variability in weather-related preparedness

This research seeks to address the extent to which indices of large-scale modes of climate variability (El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD)) can be linked to physical differences in the local mean and extreme rainfall conditions experienced in the Maldives in order to suggest implications for disaster risk reduction (DRR). While some significant differences in precipitation metrics do occur at the local level between different phases of the large-scale modes of climate variability studied, they do not occur for all sites studied. While the constrained availability of historical meteorological data in the region is a limiting factor in this analysis, these findings suggest that with respect to decision-making related to extreme precipitation, ENSO/IOD forecasting may be most helpful on local scales, when supplementing an approach of on-going readiness in which communities are prepared to effectively manage hazards in any phase of the large-scale modes of climate variability studied. These conclusions are based on only precipitation; results may vary for other impacts including changing sea levels and sea surface temperatures.

Stable water isotopes and accumulation rates in the Union Glacier region, Ellsworth Mountains, West Antarctica, over the last 35 years

Abstract. Antarctica is well known to be highly susceptible to atmospheric and oceanic warming. However, due to the lack of long-term and in situ meteorological observations, little is known about the magnitude of the warming and the meteorological conditions in the intersection region between the Antarctic Peninsula (AP), the West Antarctic Ice Sheet (WAIS) and the East Antarctic Ice Sheet (EAIS). Here we present new stable water isotope data (δ18O, δD, d excess) and accumulation rates from firn cores in the Union Glacier (UG) region, located in the Ellsworth Mountains at the northern edge of the WAIS. The firn core stable oxygen isotopes and the d excess exhibit no statistically significant trend for the period 1980–2014, suggesting that regional changes in near-surface air temperature and moisture source variability have been small during the last 35 years. Backward trajectory modelling revealed the Weddell Sea sector, Coats Land and Dronning Maud Land (DML) to be the main moisture source regions for the study site throughout the year. We found that mean annual δ18O (δD) values in the UG region are negatively correlated with sea ice concentrations (SICs) in the northern Weddell Sea but not influenced by large-scale modes of climate variability such as the Southern Annular Mode (SAM) and the El Niño–Southern Oscillation (ENSO). Only mean annual d-excess values show a weak positive correlation with the SAM. On average annual snow accumulation in the UG region amounts to 0.245 m w.e. a−1 in 1980–2014 and has slightly decreased during this period. It is only weakly related to sea ice conditions in the Weddell Sea sector and not correlated with SAM and ENSO. We conclude that neither the rapid warming nor the large increases in snow accumulation observed on the AP and in West Antarctica during the last decades have extended inland to the Ellsworth Mountains. Hence, the UG region, although located at the northern edge of the WAIS and relatively close to the AP, exhibits rather stable climate characteristics similar to those observed in East Antarctica.

Time-lagged response of vegetation dynamics to climatic and teleconnection factors

Understanding vegetation dynamics and its response to climate changes is important for revealing the mechanisms of terrestrial ecosystem behaviour, predicting future vegetation growth, and thus guiding environmental management. The Jing River Basin (JRB) and the Beiluo River Basin (BLRB), two typical ecoenvironmentally vulnerable regions on the Loess Plateau in China, were selected as case study regions. Based on long-term Normalized Difference Vegetation Index (NDVI) datasets, the time-lag relationships between NDVI and climatic factors (precipitation/temperature) as well as teleconnection factors (large-scale modes of climate variability and solar activity) were revealed. Additionally, ridge regression models were established to quantitatively explore the response of vegetation dynamics to climate change. Results indicate that: (1) NDVI in autumn showed significantly increasing trend (p < 0.01), whereas that in spring and summer was insignificant; (2) there was a time-lag of more than one month between spring/winter NDVI and precipitation/temperature behaviour, and summer NDVI exhibited no lag with temperature but a one month lag with precipitation; (3) regarding the time-lag effects, precipitation was the driving factor of NDVI variations in spring, whereas sunspots dominated NDVI variations in autumn; (4) when time-lagged teleconnection factors were considered, the explanation of the climate effect on the vegetation dynamics in three seasons all relatively increased by >95%, which indicates that the prediction accuracy of NDVI was significantly improved; (5) in summer, time-lagged climatic and teleconnection factors explained <20% of NDVI variations, whereas when soil moisture and base flow were considered, the explanation of NDVI changes in the JRB and BLRB relatively increased by 37.4% and 65.1%, respectively. These findings highlight that considering the time-lag effect of climatic and teleconnection factors has important significance for the accurate monitoring of underlying surface dynamics under changing environment.

The Cape Point wave record, extreme events and the role of large-scale modes of climate variability

Situated on the southwestern coast of South Africa, Cape Point is directly impacted by ocean surface waves generated by midlatitude cyclones in the westerly wind belt. Severe swell events have a huge impact on coastal communities, infrastructure and maritime operations. We use the long term Council for Industrial and Scientific Research (CSIR) Cape Point Waverider buoy data and WaveWatch III model data together with atmospheric reanalysis data to investigate the role of the El Niño Southern Oscillation (ENSO) and the Southern Annular Mode (SAM) and their associated adjustments of cyclone tracks and intensities on the variability and extreme events of the Cape Point wave record. During austral summer (DJF), when the waves are generally smaller and more southerly, SAM and ENSO tend to result in robust responses: a negative (positive) SAM tends to result in bigger (smaller) more westerly (southerly) waves, while a positive (negative) ENSO results in bigger (smaller) waves from a more westerly (southerly direction). The mean austral (JJA) winter waves do not respond coherently to either SAM or ENSO. A shift in the wave characteristics between periods 1980–1992 and 1994–2006 is clear. The waves become smaller and more southerly during the latter period. This shift is associated with the shift to a more coherently out of phase relationship between SAM and ENSO, dominated by a positive SAM and negative ENSO, that amplifies the wave response, giving rise to smaller waves from a more southerly direction. During summer months there is a significant reduction in not only the mean wave heights, but also the extreme wave heights between the two periods, while during winter months there is only a significant change in the mean wave direction that becomes more southerly during the latter period. During a positive ENSO and negative SAM combination, the summer extreme wave heights tend to be more westerly while the inverse combination does not produce a robust result. Finally, we show that during summer months a positive (negative) ENSO leads to more frequent extreme wave events. On the other hand, a positive (negative) SAM leads to less (more) frequent extreme wave events during winter months.

Do Gulf of Alaska fish and crustacean populations show synchronous non-stationary responses to climate?

Changes in the abundance and productivity of biological populations in the North Pacific have often been associated with large-scale modes of climate variability. The Pacific Decadal Oscillation (PDO), which describes spatio-temporal variability in North Pacific sea surface temperature (SST), correlates with much of this variability. However, since the late 1980s, the North Pacific Gyre Oscillation (NPGO) has explained an increasing proportion of variance in North Pacific climate properties. Ecological responses to this change in the proportion of variance ascribed to the two climate patterns remain poorly understood. Here, we test the hypothesis that relationships between biological time series and climate covariates (SST and the PDO) differ for nine Gulf of Alaska fish and crustacean populations before and after the late 1980s. Additionally, we evaluate whether non-stationary climate-biology relationships arose synchronously across populations as a community response. We used different formulations of Generalized Additive Models in a population and community context and compared results to the classical approach of aggregated population responses based on Principal Component Analysis (PCA). The results showed that climate-biology relationships weakened or reversed for most populations in the late 1980s, coinciding with the increase in variance of the NPGO. However, these non-stationary responses were highly species-specific and did not arise synchronously as a community response. We show that PCA does not represent community dynamics properly when only few species covary in time and exhibit long-term trends. Therefore, this approach might not be always useful to detect synchronous changes among biological time series as a community response. Novel associations among climate variables and novel climate-biology relationships are expected to become increasingly evident with future climate change, and the recognition of switches between different explanatory variable-response relationships may be critical for successful management of marine resources during transitions to these novel climate states.

Atmospheric rivers impacting Northern California and their modulation by a variable climate

Understanding the role of climate variability in modulating the behavior of land-falling atmospheric rivers (ARs) is important for seasonal and subseasonal predictability for water resource management and flood control. We examine daily activity of ARs targeting the Northern California coast over six decades using observations of synoptic-scale circulation, high-resolution precipitation, and a long-term AR detection catalog to quantify distinct types of land-falling ARs categorized by their circulation features. We demonstrate how dramatically different atmospheric states evolve into landfalling ARs along distinct pathways that are modulated by interannual (El Niño/Southern Oscillation (ENSO) and the Pacific Decadal Oscillation) and subseasonal (Arctic Oscillation, Pacific North American Pattern, Western Pacific Oscillation, and the Eastern Pacific Oscillation) modes of large-scale climate variability. Different configurations of climate variability modes are shown to favor ARs having different characteristics in terms of synoptic evolution, integrated vapor transport and landfall orientation resulting in different patterns of precipitation over the landscape. In particular, our results show that while ENSO plays an important role in modulating the synoptic evolution of ARs and their orientation at landfall, subseasonal regional climate modes, which also influence landfall orientation as well as the position of the storm track, appear to be more influential than ENSO in modulating precipitation variability in California. This could have implications for seasonal to subseasonal (S2S) forecasting. Finally, we examine AR activity over the most recent and highly anomalous winter 2016–2017 and show how the unprecedented wet conditions in Northern California were at least partly due to the persistence of ARs characterized by a southward storm track and southerly orientation, which represent the type of ARs associated with heavy rainfall in California, and which are associated with the negative phase of subseasonal regional teleconnection patterns.

Terrestrial evaporation response to modes of climate variability

Large-scale modes of climate variability (or teleconnection patterns), such as the El Niño Southern Oscillation and the North Atlantic Oscillation, affect local weather worldwide. However, the response of terrestrial water and energy fluxes to these modes of variability is still poorly understood. Here, we analyse the response of evaporation to 16 teleconnection patterns, using a simple supervised learning framework and global observation-based datasets of evaporation and its key climatic drivers. Our results show that the month-to-month variability in terrestrial evaporation is strongly affected by (coupled) oscillations in sea-surface temperature and air pressure: in specific hotspot regions, up to 40% of the evaporation dynamics can be explained by climate indices describing the fundamental modes of climate variability. While the El Niño Southern Oscillation affects the dynamics in land evaporation worldwide, other phenomena such as the East Pacific–North Pacific teleconnection pattern are more dominant at regional scales. Most modes of climate variability affect terrestrial evaporation by inducing changes in the atmospheric demand for water. However, anomalies in precipitation associated to particular teleconnections are crucial for the evaporation in water-limited regimes, as well as in forested regions where interception loss forms a substantial fraction of total evaporation. Our results highlight the need to consider the concurrent impact of these teleconnections to accurately predict the fate of the terrestrial branch of the hydrological cycle, and provide observational evidence to help improve the representation of surface fluxes in Earth system models.

Responses of tree-ring growth in Schinopsis brasiliensis to climate factors in the dry forests of northeastern Brazil

This paper aims to provide evidences of the influence of physical atmospheric parameters on the growth of the endemic tree Schinopsis brasiliensis, and their consequent teleconnection with large-scale modes of climate variability affecting rainfall in semi-arid region of the Brazilian Northeast. The Brazilian Northeast is a region of low rainfall and high temperatures and evaporation. The surface temperature of the Atlantic Ocean (STA) modulates the rains in the Northeast in association with El Nino and La Nina (ENSO) events. Tree species that grow in this region, forming the tropical Caatinga dry forests, are subjected to long periods of drought. This study investigated the influence of climatic events on the secondary growth of a typical Caatinga tree species. The analysis was based on 39 samples of Schinopsis brasiliensis, from which we derived a chronology of tree-ring growth between 1963 and 2015, with an inter-correlation of 0.56, mean sensitivity of 0.53, and mean growth rate of 3.33 mm per year. Our results indicate that growth ring chronology is related directly to the rainy season, in addition to peaks in humidity associated with isolated downpours occurring during the dry season. On the other hand, air temperature, insolation, and evaporation revealed an inverse relationship with the chronology. Inter-correlations with ENSO events, STA, and precipitation were negative, while those between ENSO events and temperature were positive. Growth in S. brasiliensis is associated with the climatic anomalies of the region. Leaf-fall and cambial shutdown occur during the dry season, while the plant is predisposed for potential growth spurts during the intermittent rains that may occur from December onwards.