scholarly journals Pacific climate reflected in Waipuna Cave drip water hydrochemistry

2020 ◽  
Vol 24 (6) ◽  
pp. 3361-3380 ◽  
Author(s):  
Cinthya Nava-Fernandez ◽  
Adam Hartland ◽  
Fernando Gázquez ◽  
Ola Kwiecien ◽  
Norbert Marwan ◽  
...  
Keyword(s):  
Air Temperature ◽  
Southern Oscillation ◽  
Austral Summer ◽  
Surface Air Temperature ◽  
Severe Drought ◽  
Response Dynamics ◽  
Calcite Precipitation ◽  
Drip Water ◽  
Diffuse Flow ◽  
Cave Drip Water

Abstract. Cave microclimate and geochemical monitoring is vitally important for correct interpretations of proxy time series from speleothems with regard to past climatic and environmental dynamics. We present results of a comprehensive cave-monitoring programme in Waipuna Cave in the North Island of New Zealand, a region that is strongly influenced by the Southern Westerlies and the El Niño–Southern Oscillation (ENSO). This study aims to characterise the response of the Waipuna Cave hydrological system to atmospheric circulation dynamics in the southwestern Pacific region in order to assure the quality of ongoing palaeo-environmental reconstructions from this cave. Drip water from 10 drip sites was collected at roughly monthly intervals for a period of ca. 3 years for isotopic (δ18O, δD, d-excess parameter, δ17O, and 17Oexcess) and elemental (Mg∕Ca and Sr∕Ca) analysis. The monitoring included spot measurements of drip rates and cave air CO2 concentration. Cave air temperature and drip rates were also continuously recorded by automatic loggers. These datasets were compared to surface air temperature, rainfall, and potential evaporation from nearby meteorological stations to test the degree of signal transfer and expression of surface environmental conditions in Waipuna Cave hydrochemistry. Based on the drip response dynamics to rainfall and other characteristics, we identified three types of discharge associated with hydrological routing in Waipuna Cave: (i) type 1 – diffuse flow, (ii) type 2 – fracture flow, and (iii) type 3 – combined flow. Drip water isotopes do not reflect seasonal variability but show higher values during severe drought. Drip water δ18O values are characterised by small variability and reflect the mean isotopic signature of precipitation, testifying to rapid and thorough homogenisation in the epikarst. Mg∕Ca and Sr∕Ca ratios in drip waters are predominantly controlled by prior calcite precipitation (PCP). Prior calcite precipitation is strongest during austral summer (December–February), reflecting drier conditions and a lack of effective infiltration, and is weakest during the wet austral winter (July–September). The Sr∕Ca ratio is particularly sensitive to ENSO conditions due to the interplay of congruent or incongruent host rock dissolution, which manifests itself in lower Sr∕Ca in above-average warmer and wetter (La Niña-like) conditions. Our microclimatic observations at Waipuna Cave provide a valuable baseline for the rigorous interpretation of speleothem proxy records aiming at reconstructing the past expression of Pacific climate modes.

scholarly journals Pacific climate reflected in Waipuna Cave dripwater hydrochemistry

2020 ◽  
Author(s):  
Cinthya Nava-Fernandez ◽  
Adam Hartland ◽  
Fernando Gázquez ◽  
Ola Kwiecien ◽  
Norbert Marwan ◽  
...  
Keyword(s):  
Southern Oscillation ◽  
Austral Summer ◽  
Surface Air Temperature ◽  
Co2 Concentration ◽  
Isotopic Signature ◽  
Severe Drought ◽  
Response Dynamics ◽  
Calcite Precipitation ◽  
Diffuse Flow ◽  
The North

Abstract. Cave microclimatic and geochemical monitoring is vitally important for correct interpretations of proxy time series from speleothems with regard to past climatic and environmental dynamics. We present results of a comprehensive cave monitoring programme in Waipuna Cave in the North Island of New Zealand, a region that is strongly influenced by the southern Westerlies and the El Niño–Southern Oscillation (ENSO). This study aims to characterise the response of the Waipuna Cave hydrological system to atmospheric circulation dynamics in the southwestern Pacific region in order to secure the quality of ongoing palaeo-environmental reconstructions from this cave. Cave air and water temperatures, drip rates, and CO2, concentration were measured, and samples for water isotopes (δ18O, δD, d-excess, 17Oexcess) and elemental ratios (Mg / Ca, Sr / Ca), were collected continuously and/or at monthly intervals from 10 drip sites inside Waipuna Cave for a period of ca. 3 years. These datasets were compared to surface air temperature, rainfall, and potential evaporation from nearby meteorological stations to test the degree of signal transfer and expression of surface environmental conditions in Waipuna Cave hydrochemistry. Based on the drip response dynamics to rainfall and other characteristics we identify three hydrological pathways in Waipuna Cave: diffuse flow, combined flow, and fracture flow. Dripwater isotopes do not reflect seasonal variability, but show higher values during severe drought. Dripwater δ18O values display limited variability and reflect the mean isotopic signature of precipitation, testifying to rapid and thorough buffering in the epikarst. Mg / Ca and Sr / Ca ratios in dripwaters are predominantly controlled by prior calcite precipitation (PCP). Prior calcite precipitation is strongest during austral summer (December–February), reflecting drier conditions and lack of effective infiltration, and is weakest during the wet austral winter (July–September). The Sr / Ca ratio is particularly sensitive to ENSO conditions due to the interplay of congruent/incongruent host rock dissolution, which manifests itself in lower Sr / Ca in above-average warmer and wetter (La Niña-like) conditions. Our microclimatic observations at Waipuna Cave provide valuable baseline for perceptive interpretation of speleothem proxy records aiming at reconstructing the past expression of Pacific climate modes.

Diagnosing Sources of U.S. Seasonal Forecast Skill

2006 ◽  
Vol 19 (13) ◽  
pp. 3279-3293 ◽  
Author(s):  
X. Quan ◽  
M. Hoerling ◽  
J. Whitaker ◽  
G. Bates ◽  
T. Xu
Keyword(s):  
Air Temperature ◽  
Southern Oscillation ◽  
Surface Air Temperature ◽  
Seasonal Forecast ◽  
Forecast Skill ◽  
Diagnostic Methods ◽  
Sea Surface ◽  
Empirical Methods ◽  
Spatial Coverage ◽  
Sst Anomalies

Abstract In this study the authors diagnose the sources for the contiguous U.S. seasonal forecast skill that are related to sea surface temperature (SST) variations using a combination of dynamical and empirical methods. The dynamical methods include ensemble simulations with four atmospheric general circulation models (AGCMs) forced by observed monthly global SSTs from 1950 to 1999, and ensemble AGCM experiments forced by idealized SST anomalies. The empirical methods involve a suite of reductions of the AGCM simulations. These include uni- and multivariate regression models that encapsulate the simultaneous and one-season lag linear connections between seasonal mean tropical SST anomalies and U.S. precipitation and surface air temperature. Nearly all of the AGCM skill in U.S. precipitation and surface air temperature, arising from global SST influences, can be explained by a single degree of freedom in the tropical SST field—that associated with the linear atmospheric signal of El Niño–Southern Oscillation (ENSO). The results support previous findings regarding the preeminence of ENSO as a U.S. skill source. The diagnostic methods used here exposed another skill source that appeared to be of non-ENSO origins. In late autumn, when the AGCM simulation skill of U.S. temperatures peaked in absolute value and in spatial coverage, the majority of that originated from SST variability in the subtropical west Pacific Ocean and the South China Sea. Hindcast experiments were performed for 1950–99 that revealed most of the simulation skill of the U.S. seasonal climate to be recoverable at one-season lag. The skill attributable to the AGCMs was shown to achieve parity with that attributable to empirical models derived purely from observational data. The diagnostics promote the interpretation that only limited advances in U.S. seasonal prediction skill should be expected from methods seeking to capitalize on sea surface predictors alone, and that advances that may occur in future decades could be readily masked by inherent multidecadal fluctuations in skill of coupled ocean–atmosphere systems.

scholarly journals Seasonal Variation and Spatial Patterns of the Atmospheric Component of the Pacific Decadal Oscillation

2013 ◽  
Vol 26 (5) ◽  
pp. 1575-1594 ◽  
Author(s):  
Catrin M. Mills ◽  
John E. Walsh
Keyword(s):  
United States ◽  
North America ◽  
Air Temperature ◽  
Pacific Decadal Oscillation ◽  
Southern Oscillation ◽  
Grid Point ◽  
Southeastern United States ◽  
Surface Air Temperature ◽  
The Pacific ◽  
Difference Fields

Abstract The Pacific decadal oscillation (PDO) is an El Niño–Southern Oscillation (ENSO)-like climate oscillation that varies on multidecadal and higher-frequency scales, with a sea surface temperature (SST) dipole in the Pacific. This study addresses the seasonality, vertical structure, and across-variable relationships of the local North Pacific and downstream North American atmospheric signal of the PDO. The PDO-based composite difference fields of 500-mb geopotential height, surface air temperature, sea level pressure, and precipitation vary not only across seasons, but also from one calendar month to another within a season, although month-to-month continuity is apparent. The most significant signals occur in western North America and in the southeastern United States, where a positive PDO is associated with negative heights, consistent with underlying temperatures in the winter. In summer, a negative precipitation signal in the southeastern United States associated with a positive PDO phase is consistent with a ridge over the region. When an annual harmonic is fit to the 12 monthly surface air temperature differences at each grid point, the PDO temperature signal peaks in winter in most of North America, while a peak in summer occurs in the southeastern United States. Approximately 25% of the variance of the PDO index is accounted for by ENSO. Atmospheric composite differences based on a residual (ENSO linearly removed) PDO index have many similarities to those of the full PDO signal.

scholarly journals A global empirical system for probabilistic seasonal climate prediction

2015 ◽  
Vol 8 (12) ◽  
pp. 3947-3973 ◽  
Author(s):  
J. M. Eden ◽  
G. J. van Oldenborgh ◽  
E. Hawkins ◽  
E. B. Suckling
Keyword(s):  
Air Temperature ◽  
Large Scale ◽  
Southern Oscillation ◽  
Surface Air Temperature ◽  
Climate Change Signal ◽  
Seasonal Forecasts ◽  
Physical Relationship ◽  
Skill Scores ◽  
Probabilistic Forecasts ◽  
Empirical System

Abstract. Preparing for episodes with risks of anomalous weather a month to a year ahead is an important challenge for governments, non-governmental organisations, and private companies and is dependent on the availability of reliable forecasts. The majority of operational seasonal forecasts are made using process-based dynamical models, which are complex, computationally challenging and prone to biases. Empirical forecast approaches built on statistical models to represent physical processes offer an alternative to dynamical systems and can provide either a benchmark for comparison or independent supplementary forecasts. Here, we present a simple empirical system based on multiple linear regression for producing probabilistic forecasts of seasonal surface air temperature and precipitation across the globe. The global CO2-equivalent concentration is taken as the primary predictor; subsequent predictors, including large-scale modes of variability in the climate system and local-scale information, are selected on the basis of their physical relationship with the predictand. The focus given to the climate change signal as a source of skill and the probabilistic nature of the forecasts produced constitute a novel approach to global empirical prediction. Hindcasts for the period 1961–2013 are validated against observations using deterministic (correlation of seasonal means) and probabilistic (continuous rank probability skill scores) metrics. Good skill is found in many regions, particularly for surface air temperature and most notably in much of Europe during the spring and summer seasons. For precipitation, skill is generally limited to regions with known El Niño–Southern Oscillation (ENSO) teleconnections. The system is used in a quasi-operational framework to generate empirical seasonal forecasts on a monthly basis.

scholarly journals Decadal-scale teleconnection between South Atlantic SST and southeast Australia surface air temperature in austral summer

2017 ◽  
Vol 50 (7-8) ◽  
pp. 2687-2703 ◽  
Author(s):  
Jiaqing Xue ◽  
Jianping Li ◽  
Cheng Sun ◽  
Sen Zhao ◽  
Jiangyu Mao ◽  
...  
Keyword(s):  
Air Temperature ◽  
Austral Summer ◽  
Surface Air Temperature ◽  
South Atlantic ◽  
Southeast Australia ◽  
Decadal Scale

scholarly journals Potential Predictability of North American Surface Temperature. Part I: Information-Based versus Signal-To-Noise-Based Metrics

2014 ◽  
Vol 27 (4) ◽  
pp. 1578-1599 ◽  
Author(s):  
Y. Tang ◽  
D. Chen ◽  
X. Yan
Keyword(s):  
Surface Temperature ◽  
Interannual Variability ◽  
Air Temperature ◽  
North American ◽  
Southern Oscillation ◽  
Surface Air Temperature ◽  
Multiple Model ◽  
Signal To Noise ◽  
Potential Predictability ◽  
Geographical Variations

Abstract In this study, the potential predictability of the North American (NA) surface air temperature was explored using information-based predictability framework and Ensemble-Based Predictions of Climate Changes and their Impacts (ENSEMBLES) multiple model ensembles. Emphasis was put on the comparison of predictability measured by information-based metrics and by the conventional signal-to-noise ratio (SNR)-based metrics. Furthermore, the potential predictability was optimally decomposed into different modes by maximizing the predictable information (equivalent to the maximum of SNR), from which the most predictable structure was extracted and analyzed. It was found that the conventional SNR-based metrics underestimate the potential predictability, in particular in these areas where the predictable signals are relatively weak. The most predictable components of the NA surface air temperature can be characterized by the interannual variability mode and the long-term trend mode. The former is inherent to tropical Pacific sea surface temperature (SST) forcing such as El Niño–Southern Oscillation (ENSO), whereas the latter is closely associated with the global warming. The amplitude of the two modes has geographical variations in different seasons. On this basis, the possible physical mechanisms responsible for the predictable mode of interannual variability and its potential benefits to the improvement of seasonal climate prediction were discussed.

scholarly journals Seasonal-to-Interannual Prediction Skills of Near-Surface Air Temperature in the CMIP5 Decadal Hindcast Experiments

2016 ◽  
Vol 29 (4) ◽  
pp. 1511-1527 ◽  
Author(s):  
Jung Choi ◽  
Seok-Woo Son ◽  
Yoo-Geun Ham ◽  
June-Yi Lee ◽  
Hye-Mi Kim
Keyword(s):  
Air Temperature ◽  
Climate Models ◽  
Southern Oscillation ◽  
Surface Air Temperature ◽  
Equatorial Pacific ◽  
Prediction Skill ◽  
Good Opportunity ◽  
Near Surface ◽  
Global Mean

Abstract This study explores the seasonal-to-interannual near-surface air temperature (TAS) prediction skills of state-of-the-art climate models that were involved in phase 5 of the Coupled Model Intercomparison Project (CMIP5) decadal hindcast/forecast experiments. The experiments are initialized in either November or January of each year and integrated for up to 10 years, providing a good opportunity for filling the gap between seasonal and decadal climate predictions. The long-lead multimodel ensemble (MME) prediction is evaluated for 1981–2007 in terms of the anomaly correlation coefficient (ACC) and mean-squared skill score (MSSS), which combines ACC and conditional bias, with respect to observations and reanalysis data, paying particular attention to the seasonal dependency of the global-mean and equatorial Pacific TAS predictions. The MME shows statistically significant ACCs and MSSSs for the annual global-mean TAS for up to two years, mainly because of long-term global warming trends. When the long-term trends are removed, the prediction skill is reduced. The prediction skills are generally lower in boreal winters than in other seasons regardless of lead times. This lack of winter prediction skill is attributed to the failure of capturing the long-term trend and interannual variability of TAS over high-latitude continents in the Northern Hemisphere. In contrast to global-mean TAS, regional TAS over the equatorial Pacific is predicted well in winter. This is mainly due to a successful prediction of the El Niño–Southern Oscillation (ENSO). In most models, the wintertime ENSO index is reasonably well predicted for at least one year in advance. The sensitivity of the prediction skill to the initialized month and method is also discussed.

scholarly journals Prediction of Arctic temperature and sea ice using a high-resolution coupled model

2021 ◽  
pp. 1-62
Author(s):  
Le Chang ◽  
Jing-Jia Luo ◽  
Jiaqing Xue ◽  
Haiming Xu ◽  
Nick Dunstone
Keyword(s):  
High Resolution ◽  
Sea Ice ◽  
Air Temperature ◽  
Southern Oscillation ◽  
Coupled Model ◽  
Surface Air Temperature ◽  
Arctic Region ◽  
Warming Trend ◽  
Lower Atmosphere ◽  
The Arctic

AbstractUnder global warming, surface air temperature has risen rapidly and sea ice decreased markedly in the Arctic. These drastic climate changes have brought about various severe impacts on the vulnerable environment and ecosystem there. Thus, accurate prediction of Arctic climate becomes more important than before. Here we examine the seasonal to interannual predictive skills of 2-meter air temperature (2-m T) and sea ice cover (SIC) over the Arctic region (70°∼90°N) during 1980–2014 with a high-resolution global coupled model called the Met Office Decadal Prediction System version 3 (DePreSys3). The model captures well both the climatology and interannual variability of the Arctic 2-m T and SIC. Moreover, the anomaly correlation coefficient (ACC) of Arctic-averaged 2-m T and SIC shows statistically significant skills at lead times up to 16 months. This is mainly due to the contribution of strong decadal trends. In addition, it is found that the peak warming trend of Arctic 2-m T lags the maximum decrease trend of SIC by one month, in association with the heat flux forcing from the ocean surface to lower atmosphere. While the predictive skill is generally much lower for the detrended variations, we find a close relationship between the tropical Pacific El Niño–Southern Oscillation and the Arctic detrended 2-m T anomalies. This indicates potential seasonal to interannual predictability of the Arctic natural variations.

Comparisons of different definitions of the western Pacific pattern and associated winter climate anomalies in Eurasia and North America

2020 ◽  
Author(s):  
Hasi Aru
Keyword(s):  
North America ◽  
Air Temperature ◽  
Southern Oscillation ◽  
Surface Air Temperature ◽  
Western Pacific ◽  
The Arctic ◽  
Temperature Anomalies ◽  
The Western Pacific ◽  
Air Temperature Anomalies ◽  
Western Pacific Pattern

<p>The western Pacific pattern (WP) is one of the most prominent teleconnection patterns over the Northern Hemisphere (NH) in boreal winter. There exist several methods employed to identify the WP in the literature. This study compares eight WPs defined by different methods. Correlation coefficients among the eight WP indices (WPIs) show considerable spreads, though most of them are statistically significant. The meridional dipole structure of WP can be captured by all of the WPIs, but it shows large spreads in the locations of the centers. Several WPIs produce a significant correlation with the winter Arctic Oscillation, with marked signals of atmospheric anomalies over the Arctic region. Connections of the WPs with the simultaneous winter El Niño-Southern Oscillation (ENSO) depend largely upon their definitions. Impacts of the WPs on the surface air temperature over many parts of Eurasia and North America are also sensitive to their definitions. Differences in the surface air temperature anomalies are closely related to differences in the spatial structure of the WPs. Finally, we define a new WP index as differences in the area-average 500-hPa geopotential height anomalies between subtropics and mid-latitude of northwestern Pacific. This newly defined WP index has a close relation with the above eight WPIs, the tropical Pacific sea surface temperature and surface air temperature anomalies over Eurasia and North America.</p>

Sign in / Sign up

Export Citation Format

Share Document