Ct Plummer

Interdecadal Pacific variability and eastern Australian megadroughts over the last millennium

The Interdecadal Pacific Oscillation (IPO) influences multidecadal drought risk across the Pacific, but there are no millennial-length, high-resolution IPO reconstructions for quantifying long-term drought risk. In Australia, drought risk increases in positive phases of the IPO, yet few suitable rainfall proxies and short (∼100 years) instrumental records mean large uncertainties remain around drought frequency and duration. Likewise, it is unknown whether megadroughts have occurred in Australias past. In this study, an atmospheric teleconnection in the Indian Ocean midlatitudes linking East Antarctica and Australia is exploited to produce the first accurate, annually dated millennial-length IPO reconstruction from the Law Dome (East Antarctica) ice core. Combined with an eastern Australian rainfall proxy from Law Dome, the first millennial-length Australian megadrought (>5 year duration) reconstruction is presented. Eight megadroughts are identified including one 39 year drought (A.D. 1174–1212), which occurred during an unprecedented century of aridity (A.D. 1102–1212).

A Millennial Proxy Record of ENSO and Eastern Australian Rainfall from the Law Dome Ice Core, East Antarctica

ENSO causes climate extremes across and beyond the Pacific basin; however, evidence of ENSO at high southern latitudes is generally restricted to the South Pacific and West Antarctica. Here, the authors report astatisticallysignificantlinkbetweenENSOandseasaltdepositionduringsummerfromtheLawDome(LD) ice core in East Antarctica. ENSO-related atmospheric anomaliesfrom the central-western equatorialPacific (CWEP) propagate to the South Pacific and the circumpolar high latitudes. These anomalies modulate high- latitude zonal winds, with El Nino (La Nina) conditions causing reduced (enhanced) zonal wind speeds and subsequent reduced (enhanced) summer sea salt deposition at LD. Over the last 1010 yr, the LD summer sea salt(LDSSS)recordhasexhibitedtwobelow-average(ElNino-like)epochs,1000-1260 ADand1920-2009 AD, and a longer above-average (La Nina-like) epoch from 1260 to 1860 AD. Spectral analysis shows the below- average epochs are associated with enhanced ENSO-like variability around 2-5 yr, while the above-average epoch is associated more with variability around 6-7 yr. The LDSSS record is also significantly correlated with annual rainfall in eastern mainland Australia. While the correlation displays decadal-scale variability similar to changes in the interdecadal Pacific oscillation (IPO), the LDSSS record suggests rainfall in the modern instrumental era (1910-2009 AD) is below the long-term average. In addition, recent rainfall declines in some regions of eastern and southeastern Australia appear to be mirrored by a downward trend in the LDSSS record, suggesting current rainfall regimes are unusual though not unknown over the last millennium.

No coincident nitrate enhancement events in polar ice cores following the largest known solar storms

Knowledge on the occurrence rate of extreme solar storms is strongly limited by the relatively recent advent of satellite monitoring of the Sun. To extend our perspective of solar storms prior to the satellite era and because atmospheric ionization induced by solar energetic particles (SEPs) can lead to the production of odd nitrogen, nitrate spikes in ice cores have been tentatively used to document both the occurrence and intensity of past SEP events. However, the reliability of the use of nitrate in ice records as a proxy for SEP events is strongly debated. This is partly due to equivocal detection of nitrate spikes in single ice cores and possible alternative sources, such as biomass burning plumes. Here we present new continuous high-resolution measurements of nitrate and of the biomass burning species ammonium and black carbon, from several Antarctic and Greenland ice cores. We investigate periods covering the two largest known SEP events of 775 and 994 Common Era as well as the Carrington event and the hard SEP event of February 1956. We report no coincident nitrate spikes associated with any of these benchmark events. We also demonstrate the low reproducibility of the nitrate signal in multiple ice cores and confirm the significant relationship between biomass burning plumes and nitrate spikes in individual ice cores. In the light of these new data, there is no line of evidence that supports the hypothesis that ice cores preserve or document detectable amounts of nitrate produced by SEPs, even for the most extreme events known to date.

Atmospheric impacts of the strongest known solar particle storm of 775 AD

Sporadic solar energetic particle (SEP) events affect the Earth’s atmosphere and environment, in particular leading to depletion of the protective ozone layer in the Earth’s atmosphere, and pose potential technological and even life hazards. The greatest SEP storm known for the last 11 millennia (the Holocene) occurred in 774–775 AD, serving as a likely worst-case scenario being 40–50 times stronger than any directly observed one. Here we present a systematic analysis of the impact such an extreme event can have on the Earth’s atmosphere. Using state-of-the-art cosmic ray cascade and chemistry-climate models, we successfully reproduce the observed variability of cosmogenic isotope 10Be, around 775 AD, in four ice cores from Greenland and Antarctica, thereby validating the models in the assessment of this event. We add to prior conclusions that any nitrate deposition signal from SEP events remains too weak to be detected in ice cores by showing that, even for such an extreme solar storm and sub-annual data resolution, the nitrate deposition signal is indistinguishable from the seasonal cycle. We show that such a severe event is able to perturb the polar stratosphere for at least one year, leading to regional changes in the surface temperature during northern hemisphere winters.

Correlation confidence limits for unevenly sampled data

Estimation of correlation with appropriate uncertainty limits for scientific data that are potentially serially correlated is a common problem made seriously challenging especially when data are sampled unevenly in space and/or time. Here we present a new, robust method for estimating correlation with uncertainty limits between autocorrelated series that does not require either resampling or interpolation. The technique employs the Gaussian kernel method with a bootstrapping resampling approach to derive the probability density function and resulting uncertainties. The method is validated using an example from radar geophysics. Autocorrelation and error bounds are estimated for an airborne radio-echo profile of ice sheet thickness. The computed limits are robust when withholding 10%, 20%, and 50% of data. As a further example, the method is applied to two time-series of methanesulphonic acid in Antarctic ice cores from different sites. We show how the method allows evaluation of the significance of correlation where the signal-to-noise ratio is low and reveals that the two ice cores exhibit a significant common signal. HighlightsCorrelation confidence limits can be calculated for unevenly sampled data.Employs Gaussian kernel method used with bootstrapping resampling.Two different studies using highly autocorrelated data validates method.