Benjamin J. Henley

A Tripole Index for the Interdecadal Pacific Oscillation

Abstract A new index is developed for the Interdecadal Pacific Oscillation, termed the IPO Tripole Index (TPI). The IPO is associated with a distinct ‘tripole’ pattern of sea surface temperature anomalies (SSTA), with three large centres of action and variations on decadal timescales, evident in the second principal component (PC) of low-pass filtered global SST. The new index is based on the difference between the SSTA averaged over the central equatorial Pacific and the average of the SSTA in the Northwest and Southwest Pacific. The TPI is an easily calculated, non-PC-based index for tracking decadal SST variability associated with the IPO. The TPI time series bears a close resemblance to previously published PC-based indices and has the advantages of being simpler to compute and more consistent with indices used to track the El Niño–Southern Oscillation (ENSO), such as Niño 3.4. The TPI also provides a simple metric in physical units of °C for evaluating decadal and interdecadal variability of SST fields in a straightforward manner, and can be used to evaluate the skill of dynamical decadal prediction systems. Composites of SST and mean sea level pressure anomalies reveal that the IPO has maintained a broadly stable structure across the seven most recent positive and negative epochs that occurred during 1870–2013. The TPI is shown to be a robust and stable representation of the IPO phenomenon in instrumental records, with relatively more variance in decadal than shorter timescales compared to Niño 3.4, due to the explicit inclusion of off-equatorial SST variability associated with the IPO.

Climate-informed stochastic hydrological modeling: Incorporating decadal-scale variability using paleo data

A hierarchical framework for incorporating modes of climate variability into stochastic simulations of hydrological data is developed, termed the climate-informed multi-time scale stochastic (CIMSS) framework. A case study on two catchments in eastern Australia illustrates this framework. To develop an identifiable model characterizing long-term variability for the first level of the hierarchy, paleoclimate proxies, and instrumental indices describing the Interdecadal Pacific Oscillation (IPO) and the Pacific Decadal Oscillation (PDO) are analyzed. A new paleo IPO-PDO time series dating back 440 yr is produced, combining seven IPO-PDO paleo sources using an objective smoothing procedure to fit low-pass filters to individual records. The paleo data analysis indicates that wet/dry IPO-PDO states have a broad range of run lengths, with 90% between 3 and 33 yr and a mean of 15 yr. The Markov chain model, previously used to simulate oscillating wet/dry climate states, is found to underestimate the probability of wet/dry periods >5 yr, and is rejected in favor of a gamma distribution for simulating the run lengths of the wet/dry IPO-PDO states. For the second level of the hierarchy, a seasonal rainfall model is conditioned on the simulated IPO-PDO state. The model is able to replicate observed statistics such as seasonal and multiyear accumulated rainfall distributions and interannual autocorrelations. Mean seasonal rainfall in the IPO-PDO dry states is found to be 15%–28% lower than the wet state at the case study sites. In comparison, an annual lag-one autoregressive model is unable to adequately capture the observed rainfall distribution within separate IPO-PDO states.

A global multiproxy database for temperature reconstructions of the Common Era

Reproducible climate reconstructions of the Common Era (1 CE to present) are key to placing industrial-era warming into the context of natural climatic variability. Here we present a community-sourced database of temperature-sensitive proxy records from the PAGES2k initiative. The database gathers 692 records from 648 locations, including all continental regions and major ocean basins. The records are from trees, ice, sediment, corals, speleothems, documentary evidence, and other archives. They range in length from 50 to 2000 years, with a median of 547 years, while temporal resolution ranges from biweekly to centennial. Nearly half of the proxy time series are significantly correlated with HadCRUT4.2 surface temperature over the period 1850–2014. Global temperature composites show a remarkable degree of coherence between high- and low-resolution archives, with broadly similar patterns across archive types, terrestrial versus marine locations, and screening criteria. The database is suited to investigations of global and regional temperature variability over the Common Era, and is shared in the Linked Paleo Data (LiPD) format, including serializations in Matlab, R and Python.

Southern Hemisphere rainfall variability over the past 200 years

This study presents an analysis of three palaeoclimate rainfall reconstructions from the Southern Hemisphere regions of south-eastern Australia (SEA), southern South Africa (SAF) and southern South America (SSA). We provide a first comparison of rainfall variations in these three regions over the past two centuries, with a focus on identifying synchronous wet and dry periods. Despite the uncertainties associated with the spatial and temporal limitations of the rainfall reconstructions, we find evidence of dynamically-forced climate influences. An investigation of the twentieth century relationship between regional rainfall and the large-scale climate circulation features of the Pacific, Indian and Southern Ocean regions revealed that Indo-Pacific variations of the El Niño–Southern Oscillation (ENSO) and the Indian Ocean dipole dominate rainfall variability in SEA and SAF, while the higher latitude Southern Annular Mode (SAM) exerts a greater influence in SSA. An assessment of the stability of the regional rainfall–climate circulation modes over the past two centuries revealed a number of non-stationarities, the most notable of which occurs during the early nineteenth century around 1820. This corresponds to a time when the influence of ENSO on SEA, SAF and SSA rainfall weakens and there is a strengthening of the influence of SAM. We conclude by advocating the use of long-term palaeoclimate data to estimate decadal rainfall variability for future water resource management.

ENSO teleconnections with Australian rainfall in coupled model simulations of the last millennium

El Niño-Southern Oscillation is the major source of interannual rainfall variability in the Australian region, with the strongest influence over eastern Australia. The strength of this regional ENSO–rainfall teleconnection varies in the observational record. Climate model simulations of the “last millennium” (850–1850 C.E.) can be used to quantify the natural variability of the relationship between ENSO and Australian rainfall on decadal and longer time scales, providing a baseline for evaluating future projections. In this study, historical and last millennium (LM) simulations from six models were obtained from the Coupled Model Intercomparison Project Phase 5 and Palaeoclimate Modelling Intercomparison Project Phase 3. All models reproduce the observed negative correlation between September to February (SONDJF) eastern Australian rainfall and the NINO3.4 index, with varying skill. In the LM simulations, all models produce decadal-scale cooling over eastern Australia in response to volcanic forcing, as well as a long-term cooling trend. Rainfall variability over the same region is not strongly driven by external forcing, with each model simulating rainfall anomalies of different phase and magnitude. SONDJF eastern Australian rainfall is strongly correlated with ENSO in the LM simulations for all models, although some models simulate periods when the teleconnection weakens substantially for several decades. Changes in ENSO variance play a role in modulating the teleconnection strength, but are not the only factor. The long-term average spatial pattern of the ENSO–Australian rainfall teleconnection is similar in the LM and historical simulations, although the spatial pattern varies over time in the LM simulations.

Impact of hydroclimate parameter uncertainty on system yield

Abstract Water resource system behaviour is commonly evaluated using Monte Carlo simulation of synthetic streamflow and rainfall data. Fundamental to this process is the estimation of stochastic model parameters by calibration to short observed records. The uncertainty in key hydroclimate parameters, such as the mean, variance and serial autocorrelation, flows through to the simulated hydroclimate data. This study considers the subsequent influence of model parameter uncertainty on the calculated yield of a case study water supply system. A procedure is developed to estimate the system yield for individual samples of model parameters, providing a probability distribution of plausible system yields. The uncertainty in hydroclimate parameters is found to have an appreciable impact on the uncertainty in system yield – of the order of +/−10%. This uncertainty is likely to surpass, potentially by an order of magnitude or more, the influence of many choices made by water managers in both the modelling and operation of water resource systems.

Reduced heat exposure by limiting global warming to 1.5 °C

The benefits of limiting global warming to the lower Paris Agreement target of 1.5 °C are substantial with respect to population exposure to heat, and should impel countries to strive towards greater emissions reductions.

Data Descriptor: A global multiproxy database for temperature reconstructions of the Common Era

PAGES, a core project of Future Earth, is supported by the U.S. and Swiss National Science Foundations. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government. Some of this work was conducted as part of the North America 2k Working Group supported by the John Wesley Powell Center for Analysis and Synthesis, funded by the U.S. Geological Survey. B. Bauer, W. Gross, and E. Gille (NOAA National Centers for Environmental Information) are gratefully acknowledged for helping assemble the data citations and creating the NCEI versions of the PAGES 2k data records. We thank all the investigators whose commitment to data sharing enables the open science ethos embodied by this project.

Towards the prediction of multi-year to decadal climate variability in the Southern Hemisphere

Multi-year (2-7 years) and decadal climate variability (MDCV) can have a profound influence on lives, livelihoods and economies. Consequently, learning more about the causes of this variability, the extent to which it can be predicted, and the greater the clarity that we can provide on the climatic conditions that will unfold over coming years and decades is a high priority for the research community. This importance is reflected in new initiatives by WCRP, CLIVAR, and in the Decadal Climate Prediction Project (Boer et al., 2016) that target this area of research. Here we briefly examine some of the things we know, and have recently learnt, about the causes and predictability of Southern Hemisphere MDCV (SH MDCV), and current skill in its prediction.