Interdecadal Pacific variability and eastern Australian megadroughts over the last millennium

Vance, Tessa R.; Roberts, Jason L.; Plummer, CT; Kiem, Anthony S.; Ommen, T. D. van

doi:10.1002/2014gl062447

Cited by 127 publications

(196 citation statements)

References 45 publications

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“…Barring post-depositional processes, the recorded snow accumulation is the net result of solid precipitation, sublimation, wind erosion or deposition, and meltwater runoff. Integrated over the AIS the contributions made by sublimation or deposition, wind redistribution, rainfall, and meltwater runoff are relatively small (van Wessem et al, 2014) and therefore the dominant component of Antarctic SMB is solid precipitation. Locally, however, drifting snow erosion or deposition and sublimation may play an important role, especially in regions of strong katabatic flow .…”

Section: Snow Accumulation From Ice Coresmentioning

confidence: 99%

“…A recent evaluation of 3265 multiyear averaged in situ observations concluded that ERA-Interim exhibits the highest performance in capturing interannual variability in observed Antarctic precipitation of the available reanalysis products (Wang et al, 2016). In addition, we use the latest version of RACMO version 2.3p2 (RACMO2.3p2), which succeeds RACMO2.3 (Van Wessem et al, 2014) and combines the hydrostatic dynamics of the High Resolution Limited Area Model (HIRLAM) with the physics package of the ECMWF Integrated Forecast System. RACMO2.3p2 has been specifically adapted for use over glaciated regions, as it is coupled to a multilayer snow model (Ettema et al, 2010) that calculates processes in the firn, such as grain size growth, firn compaction, meltwater percolation or retention, and meltwater runoff.…”

Section: Modelled Surface Mass Balancementioning

confidence: 99%

“…Multiple in situ SMB observations can be combined to produce an SMB map for selected ice sheet regions (Rotschky et al, 2007) or for the entire AIS (Favier et al, 2013). Alternatively, SMB can be simulated by (regional) atmospheric climate models, such as the Regional Atmospheric Climate Model (RACMO) version 2.3 (Van Wessem et al, 2014), and various reanalysis products such as ERA-Interim (Dee et al, 2001) or JRA55 (Kobayashi et al, 2015). Estimates of SMB can be improved by combining methods following, for example, the approach of Arthern et al (2006) by interpolating field measurements with remotely sensed data as a background field or Van de Berg et al (2006), who fitted output from a regional model to in situ observations.…”

Section: Introductionmentioning

confidence: 99%

“…Alternatively, SMB can be simulated by (regional) atmospheric climate models, such as the Regional Atmospheric Climate Model (RACMO) version 2.3 (Van Wessem et al, 2014), and various reanalysis products such as ERA-Interim (Dee et al, 2001) or JRA55 (Kobayashi et al, 2015). Estimates of SMB can be improved by combining methods following, for example, the approach of Arthern et al (2006) by interpolating field measurements with remotely sensed data as a background field or Van de Berg et al (2006), who fitted output from a regional model to in situ observations. The resulting values of SMB averaged over the grounded AIS range from 143 kg m −2 yr −1 (Arthern et al, 2006) to 168 kg m −2 yr −1 (van de Berg et al, 2006).…”

Section: Introductionmentioning

confidence: 99%

“…Estimates of SMB can be improved by combining methods following, for example, the approach of Arthern et al (2006) by interpolating field measurements with remotely sensed data as a background field or Van de Berg et al (2006), who fitted output from a regional model to in situ observations. The resulting values of SMB averaged over the grounded AIS range from 143 kg m −2 yr −1 (Arthern et al, 2006) to 168 kg m −2 yr −1 (van de Berg et al, 2006). Several studies have evaluated modelled SMB with in situ observations across Antarctica (Thomas andBracegirdle, 2009, 2015;Agosta et al, 2012;Sinisalo et al, 2013;Medley et al, 2013 andWang et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

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Regional Antarctic snow accumulation over the past 1000 years

et al. 2017

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Abstract. Here we present Antarctic snow accumulation variability at the regional scale over the past 1000 years. A total of 79 ice core snow accumulation records were gathered and assigned to seven geographical regions, separating the high-accumulation coastal zones below 2000 m of elevation from the dry central Antarctic Plateau. The regional composites of annual snow accumulation were evaluated against modelled surface mass balance (SMB) from RACMO2.3p2 and precipitation from ERA-Interim reanalysis. With the exception of the Weddell Sea coast, the low-elevation composites capture the regional precipitation and SMB variability as defined by the models. The central Antarctic sites lack coherency and either do not represent regional precipitation or indicate the model inability to capture relevant precipitation processes in the cold, dry central plateau. Our results show that SMB for the total Antarctic Ice Sheet (including ice shelves) has increased at a rate of 7 ± 0.13 Gt decade −1 since 1800 AD, representing a net reduction in sea level of ∼ 0.02 mm decade −1 since 1800 and ∼ 0.04 mm decade −1 since 1900 AD. The largest contribution is from the Antarctic Peninsula (∼ 75 %) where the annual average SMB during the most recent decade (2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)) is 123 ± 44 Gt yr −1 higher than the annual average during the first decade of the 19th century. Only four ice core records cover the full 1000 years, and they suggest a decrease in snow accumulation during this period. However, our study emphasizes the importance of low-elevation coastal zones, which have been under-represented in previous investigations of temporal snow accumulation.

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Section: Snow Accumulation From Ice Coresmentioning

confidence: 99%

Section: Modelled Surface Mass Balancementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Regional Antarctic snow accumulation over the past 1000 years

et al. 2017

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A paleoclimate rainfall reconstruction in the Murray‐Darling Basin (MDB), Australia: 1. Evaluation of different paleoclimate archives, rainfall networks, and reconstruction techniques

Kiem

Verdon‐Kidd

2015

Water Resources Research

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From ∼1997 to 2009 the Murray‐Darling Basin (MDB), Australia's largest water catchment and reputed “food bowl,” experienced a severe drought termed the “Millennium Drought” or “Big Dry” followed by devastating floods in the austral summers of 2010/2011, 2011/2012, and 2012/2013. The magnitude and severity of these extreme events highlight the limitations associated with assessing hydroclimatic risk based on relatively short instrumental records (∼100 years). An option for extending hydroclimatic records is through the use of paleoclimate records. However, there are few in situ proxies of rainfall or streamflow suitable for assessing hydroclimatic risk in Australia and none are available in the MDB. In this paper, available paleoclimate records are reviewed and those of suitable quality for hydroclimatic risk assessments are used to develop preinstrumental information for the MDB. Three different paleoclimate reconstruction techniques are assessed using two instrumental rainfall networks: (1) corresponding to rainfall at locations where rainfall‐sensitive Australian paleoclimate archives currently exist and (2) corresponding to rainfall at locations identified as being optimal for explaining MDB rainfall variability. It is shown that the optimized rainfall network results in a more accurate model of MDB rainfall compared to reconstructions based on rainfall at locations where paleoclimate rainfall proxies currently exist. This highlights the importance of first identifying key locations where existing and as yet unrealized paleoclimate records will be most useful in characterizing variability. These results give crucial insight as to where future investment and research into developing paleoclimate proxies for Australia could be most beneficial, with respect to better understanding instrumental, preinstrumental and potential future variability in the MDB.

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A paleoclimate rainfall reconstruction in the Murray‐Darling Basin (MDB), Australia: 2. Assessing hydroclimatic risk using paleoclimate records of wet and dry epochs

Kiem

Verdon‐Kidd

2015

Water Resources Research

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Estimates of hydrological risk are crucial to enable adequate planning and preparation for extreme events. However, the accurate estimation of hydrological risk is hampered by relatively short instrumental records in many parts of the world. Information derived from climate‐sensitive paleoclimate proxies provide an opportunity to resolve hydroclimatic variability, but many regions, such as Australia's Murray‐Darling Basin (MDB), currently lack the suitable in situ proxies necessary to do this. Here new MDB rainfall reconstructions are presented based on a novel method using paleoclimate rainfall proxies in the Australasian region spanning from 749 B.C.E. to 1980 C.E. Our results emphasize the need to develop additional reconstructions and, with the companion paper, demonstrate how this information can be used to benefit water resource management. This study shows that prior to the twentieth century, both dry and wet epochs have persisted for longer periods than observed in the instrumental record—with the probability of both dry and wet periods exceeding a decade at least 10 times more likely prior to 1883 than suggested by the instrumental records. Some reconstructed rainfalls exceeded the instrumental range (i.e., drier dry epochs and wetter wet spells) despite a systematic underestimation of extremes due to a combination of proxy quality and model bias. Importantly, the results demonstrate that the instrumental record does not cover the full range of hydroclimatic variability possible in the MDB. Therefore, hydroclimatic risk assessments based on the instrumental record likely underestimate, or at least misinterpret, the frequency, duration, and magnitude of wet and dry epochs.

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Interdecadal Pacific variability and eastern Australian megadroughts over the last millennium

Abstract: 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.

Cited by 127 publications

References 45 publications

Regional Antarctic snow accumulation over the past 1000 years

Regional Antarctic snow accumulation over the past 1000 years

A paleoclimate rainfall reconstruction in the Murray‐Darling Basin (MDB), Australia: 1. Evaluation of different paleoclimate archives, rainfall networks, and reconstruction techniques

A paleoclimate rainfall reconstruction in the Murray‐Darling Basin (MDB), Australia: 2. Assessing hydroclimatic risk using paleoclimate records of wet and dry epochs

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