Spatial and temporal agreement in climate model simulations of the Interdecadal Pacific Oscillation

Accelerated warming and hiatus periods in the long-term rise of Global Mean Surface Temperature (GMST) have, in recent decades, been associated with the Interdecadal Pacific Oscillation (IPO). Critically, decadal climate prediction relies on the skill of state-of-the-art climate models to reliably represent these low-frequency climate variations. We undertake a systematic evaluation of the simulation of the IPO in the suite of Coupled Model Intercomparison Project 5 (CMIP5) models. We track the IPO in pre-industrial (control) and all-forcings (historical) experiments using the IPO tripole index (TPI). The TPI is explicitly aligned with the observed spatial pattern of the IPO, and circumvents assumptions about the nature of global warming. We find that many models underestimate the ratio of decadal-to-total variance in sea surface temperatures (SSTs). However, the basin-wide spatial pattern of positive and negative phases of the IPO are simulated reasonably well, with spatial pattern correlation coefficients between observations and models spanning the range 0.4–0.8. Deficiencies are mainly in the extratropical Pacific. Models that better capture the spatial pattern of the IPO also tend to more realistically simulate the ratio of decadal to total variance. Of the 13% of model centuries that have a fractional bias in the decadal-to-total TPI variance of 0.2 or less, 84% also have a spatial pattern correlation coefficient with the observed pattern exceeding 0.5. This result is highly consistent across both IPO positive and negative phases. This is evidence that the IPO is related to one or more inherent dynamical mechanisms of the climate system

The shared socio-economic pathway (SSP) greenhouse gas concentrations and their extensions to 2500

Anthropogenic increases in atmospheric greenhouse gas concentrations are the main driver of current and future climate change. The integrated assessment community has quantified anthropogenic emissions for the shared socio-economic pathway (SSP) scenarios, each of which represents a different future socio-economic projection and political environment. Here, we provide the greenhouse gas concentrations for these SSP scenarios – using the reduced-complexity climate–carbon-cycle model MAGICC7.0. We extend historical, observationally based concentration data with SSP concentration projections from 2015 to 2500 for 43 greenhouse gases with monthly and latitudinal resolution. CO2 concentrations by 2100 range from 393 to 1135 ppm for the lowest (SSP1-1.9) and highest (SSP5-8.5) emission scenarios, respectively. We also provide the concentration extensions beyond 2100 based on assumptions regarding the trajectories of fossil fuels and land use change emissions, net negative emissions, and the fraction of non-CO2 emissions. By 2150, CO2 concentrations in the lowest emission scenario are approximately 350 ppm and approximately plateau at that level until 2500, whereas the highest fossil-fuel-driven scenario projects CO2 concentrations of 1737 ppm and reaches concentrations beyond 2000 ppm by 2250. We estimate that the share of CO2 in the total radiative forcing contribution of all considered 43 long-lived greenhouse gases increases from 66 % for the present day to roughly 68 % to 85 % by the time of maximum forcing in the 21st century. For this estimation, we updated simple radiative forcing parameterizations that reflect the Oslo Line-By-Line model results. In comparison to the representative concentration pathways (RCPs), the five main SSPs (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) are more evenly spaced and extend to lower 2100 radiative forcing and temperatures. Performing two pairs of six-member historical ensembles with CESM1.2.2, we estimate the effect on surface air temperatures of applying latitudinally and seasonally resolved GHG concentrations. We find that the ensemble differences in the March–April–May (MAM) season provide a regional warming in higher northern latitudes of up to 0.4 K over the historical period, latitudinally averaged of about 0.1 K, which we estimate to be comparable to the upper bound (∼5 % level) of natural variability. In comparison to the comparatively straight line of the last 2000 years, the greenhouse gas concentrations since the onset of the industrial period and this studies' projections over the next 100 to 500 years unequivocally depict a “hockey-stick” upwards shape. The SSP concentration time series derived in this study provide a harmonized set of input assumptions for long-term climate science analysis; they also provide an indication of the wide set of futures that societal developments and policy implementations can lead to – ranging from multiple degrees of future warming on the one side to approximately 1.5 ∘C warming on the other

The shared socio-economic pathway (SSP) greenhouse gas concentrations and their extensions to 2500

Anthropogenic increases in atmospheric greenhouse gas concentrations are the main driver of current and future climate change. The integrated assessment community has quantified anthropogenic emissions for the shared socio-economic pathway (SSP) scenarios, each of which represents a different future socio-economic projection and political environment. Here, we provide the greenhouse gas concentrations for these SSP scenarios – using the reduced-complexity climate–carbon-cycle model MAGICC7.0. We extend historical, observationally based concentration data with SSP concentration projections from 2015 to 2500 for 43 greenhouse gases with monthly and latitudinal resolution. CO2 concentrations by 2100 range from 393 to 1135 ppm for the lowest (SSP1-1.9) and highest (SSP5-8.5) emission scenarios, respectively. We also provide the concentration extensions beyond 2100 based on assumptions regarding the trajectories of fossil fuels and land use change emissions, net negative emissions, and the fraction of non-CO2 emissions. By 2150, CO2 concentrations in the lowest emission scenario are approximately 350 ppm and approximately plateau at that level until 2500, whereas the highest fossil-fuel-driven scenario projects CO2 concentrations of 1737 ppm and reaches concentrations beyond 2000 ppm by 2250. We estimate that the share of CO2 in the total radiative forcing contribution of all considered 43 long-lived greenhouse gases increases from 66 % for the present day to roughly 68 % to 85 % by the time of maximum forcing in the 21st century. For this estimation, we updated simple radiative forcing parameterizations that reflect the Oslo Line-By-Line model results. In comparison to the representative concentration pathways (RCPs), the five main SSPs (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) are more evenly spaced and extend to lower 2100 radiative forcing and temperatures. Performing two pairs of six-member historical ensembles with CESM1.2.2, we estimate the effect on surface air temperatures of applying latitudinally and seasonally resolved GHG concentrations. We find that the ensemble differences in the March–April–May (MAM) season provide a regional warming in higher northern latitudes of up to 0.4 K over the historical period, latitudinally averaged of about 0.1 K, which we estimate to be comparable to the upper bound (∼5 % level) of natural variability. In comparison to the comparatively straight line of the last 2000 years, the greenhouse gas concentrations since the onset of the industrial period and this studies' projections over the next 100 to 500 years unequivocally depict a “hockey-stick” upwards shape. The SSP concentration time series derived in this study provide a harmonized set of input assumptions for long-term climate science analysis; they also provide an indication of the wide set of futures that societal developments and policy implementations can lead to – ranging from multiple degrees of future warming on the one side to approximately 1.5 ∘C warming on the other

Australian rainfall and El Niño diversity: past variability and context for recent changes

© 2018 Dr. Mandy Barbara FreundThe climate system integrates internally and externally induced variability at various time scales as a result of interactions between the ocean and atmosphere. The influence of external forcing on the climate system and with it the structural changes of climate variability, in particular on seasonal and longer time-scales, is difficult to examine due to high natural variability and short observational records. The interplay between high and low-frequency variability restricts our understanding of the full range of climate variability and our ability to contextualise changes. This thesis explores and evaluates the potential to use seasonal paleoclimate information to advance our knowledge of natural climate variability and the multi-century context of recent changes in the Australasian and tropical Pacific region. Climate modes of variability including the El Niño -Southern Oscillation influence Australian rainfall and make Australian rainfall highly variable at interannual timescales. Multi-century reconstructions of past climate variability are developed for Australian rainfall at bi-seasonal resolution. The rainfall reconstruction is based on local paleoclimate proxies and teleconnected links between remote paleoclimate proxies, climate modes of variability and Australian rainfall. In a multi-century context, the recent drying trends in parts of southern Australia, as well as the tendency towards wetter conditions in northern Australia, are found to be unusual. The cool and warm season rainfall reconstructions allow the documentation of distinct characteristics of past major droughts in terms of their spatial extent, duration, intensity, and seasonality. Using coral data at seasonal resolution, two El Niño index reconstructions illustrate the sequence of diversity of past eastern and central Pacific El Niño events for the last 400 years. The distinct spatio-temporal signatures of both types of El Niño are exploited, and together with a novel machine learning approach, the diversity of past El Niño events is reconstructed and compared to recent changes. The recent increase in the frequency of central Pacific El Niño events relative to eastern Pacific El Niño events during the late 20th century appears unusual. The most recent 30-year period includes more intense eastern Pacific events compared to the past four centuries. To further investigate the changes and interactions between Australian rainfall and El Niño diversity, observations and climate model simulations are compared to the multi-century reconstructions. A number of climate models taking part in the Coupled Model Intercomparison Project Phase 5 (CMIP5) are identified that simulate spatially distinct El Niño behaviour. Identification of El Niño events reveals a lack of model agreement about projected changes of El Niño diversity. The probability of infrequent El Niño characteristics is evaluated and point towards an under-representation of central Pacific events that are followed by eastern Pacific events in the observational records. Future simulations in climate models indicate that this El Niño transition as observed most recently in 2014-2016, could become less common. Based on the rainfall and El Niño reconstructions, the general drying impacts of El Niño is consistent for both types. Despite the strength asymmetry between eastern and central Pacific El Niño events, the impact on Australian rainfall is of a similar order of magnitude but also highlights a strong variable nature of the different types of El Niño and Australian hydroclimate. The context of recent changes provided by the reconstructions in this thesis advances our knowledge of natural climate variability in the Australasian and tropical Pacific region and offers new insights into the future climate of the region

Multi-century cool and warm season rainfall reconstructions forAustralia’s major climatic regions: Data and additional information on a seasonal rainfall reconstruction of major the eight natural resource management regions (NRM) based on paleoclimate data

<u><b>Additional information and datasets</b> </u><div>used in Freund et al. 2017, Multi-century cool and warm season rainfall reconstructions of Australia's major climatic regions.<div>-------------------------------------------------------------------------------</div><div><br> <div><div></div></div><div>Files includes all primary input and output files. </div><div><b>Input files</b>: The bi-seasonal NRM regional averages based in AWAP</div><div><b>Output files</b>: Bi-seasonal reconstructions for cool and warm season for all NRM regions </div><div><br></div><div><b>Warm</b> and <b>Cool</b> season* rainfall for the eight Natural Resource Management (NRM)** regions</div><div><br> <div>---------------------------------------------------------------------------<br><div>File format provided: netcdf (.nc) and text format (.txt)<br><div><div><div></div></div><div>---------------------------------------------------------------------------</div><div><br></div><div><b>1)</b> Instrumental regional averages for each NRM region (1900-2015) based on the gridded Australian Water Availability Project (AWAP)</div><div><br></div><div><b>2)</b> Reconstructed regional averages for each NRM region (1200-2015) based on a network of palaeoclimate records from the Southern Hemisphere</div><div><br></div><div>---------------------------------------------------------------------------<br></div><div>* Warm season (average precipitation in: Oct, Nov, Dec, Jan, Feb, Mar)</div></div></div></div><div>* Cool season (average precipitation in: Apr, May, Jun, Jul, Aug, Sep)<br></div><div><br></div><div>** NRM regions are defined by the CSIRO and Bureau of Meteorology (https://www.climatechangeinaustralia.gov.au/en/climate-projections/about/modelling-choices-and-methodology/regionalisation-schemes/) and should cited as followed: CSIRO and Bureau of Meteorology 2015, Climate Change in Australia Information for Australia's Natural Resource Management Regions: Technical Report, CSIRO and Bureau of Meteorology, Australia,2015.</div><div><br></div><div><u>Regions: </u></div><div><b>CS</b>-Central Slopes</div><div><b>EC</b>-East Coast</div><div><b>MB</b>-Murray Basin</div><div><b>MN</b>-Monsoonal North</div><div><b>R</b>-Rangelands</div><div><b>SS</b>-Southern Slopes</div><div><b>SSWF</b>-Southern and South-Western Flatlands</div><div><b>WT</b>-Wet Tropics<br></div><div><br></div><div><br></div><div><b><u>Please cite and find further details in:</u></b></div><div>Freund, M., Henley, B. J., Karoly, D. J., Allen, K. J. and Baker, P. J.: Multi-century cool- and warm-season rainfall reconstructions for Australia's major climatic regions, Clim. Past, 13(12), 1751–1770, doi:10.5194/cp-13-1751-2017, 2017.</div></div><div>https://www.clim-past.net/13/1751/2017/cp-13-1751-2017.html<br></div></div></div

Warm seasonal rainfall

<b>Warm</b> season* rainfall for the eight Natural Resource Management (NRM)** regions <div>---------------------------------------------------------------------------<br><div>File format provided: netcdf and csv format<br><div><div><div><div> </div> </div> </div><div>---------------------------------------------------------------------------</div><div><br></div><div><b>1)</b> Instrumental regional averages for each NRM region (1900-2015) based on the gridded Australian Water Availability Project (AWAP)</div><div><br></div><div><b>2)</b> Reconstructed regional averages for each NRM region (1200-2015) based on a network of palaeoclimate records from the Southern Hemisphere</div><div><br></div><div>---------------------------------------------------------------------------<br></div><div>* Warm season (average precipitation in: Oct, Nov, Dec, Jan, Feb, Mar)</div></div></div></div><div><br></div><div>** NRM regions are defined by the CSIRO and Bureau of Meteorology (https://www.climatechangeinaustralia.gov.au/en/climate-projections/about/modelling-choices-and-methodology/regionalisation-schemes/) and should cited as followed: CSIRO and Bureau of Meteorology 2015, Climate Change in Australia Information for Australia's Natural Resource Management Regions: Technical Report, CSIRO and Bureau of Meteorology, Australia,2015.</div><div><br></div><div><u>Regions: </u></div><div><b>CS</b>-Central Slopes</div><div><b>EC</b>-East Coast</div><div><b>MB</b>-Murray Basin</div><div><b>MN</b>-Monsoonal North</div><div><b>R</b>-Rangelands</div><div><b>SS</b>-Southern Slopes</div><div><b>SSWF</b>-Southern and South-Western Flatlands</div><div><b>WT</b>-Wet Tropics<br></div><div><br></div><div><br></div><div><u>Reference and details in: </u></div><div>Freund, M., Henley, B. J., Karoly, D. J., Allen, K. J. and Baker, P. J.: Multi-century cool- and warm-season rainfall reconstructions for Australia's major climatic regions, Clim. Past, 13(12), 1751–1770, doi:10.5194/cp-13-1751-2017, 2017.<br></div

Variability and long-term change in Australian monsoon rainfall: A review

The Australian monsoon delivers seasonal rain across a vast area of the continent stretching from the far northern tropics to the semi-arid regions. This article provides a review of advances in Australian monsoon rainfall (AUMR) research and a supporting analysis of AUMR variability, observed trends, and future projections. AUMR displays a high degree of interannual variability with a standard deviation of approximately 34% of the mean. AUMR variability is mostly driven by the El Niño-Southern Oscillation (ENSO), although sea surface temperature anomalies in the tropical Indian Ocean and north of Australia also play a role. Decadal AUMR variability is strongly linked to the Interdecadal Pacific Oscillation (IPO), partially through the IPO\u27s impact on the strength and position of the Pacific Walker Circulation and the South Pacific Convergence Zone. AUMR exhibits a century-long positive trend, which is large (approximately 20 mm per decade) and statistically significant over northwest Australia. The cause of the observed trend is still debated. Future changes in AUMR over the next century remain uncertain due to low climate model agreement on the sign of change. Recommendations to improve the understanding of AUMR and confidence in AUMR projections are provided. This includes improving the representation of atmospheric convective processes in models, further explaining the mechanisms responsible for AUMR variability and change. Clarifying the mechanisms of AUMR variability and change would aid with creating more sustainable future agricultural systems by increasing the reliability of predictions and projections. This article is categorized under: Paleoclimates and Current Trends \u3e Modern Climate Change

European tree-ring isotopes indicate unusual recent hydroclimate

In recent decades, Europe has experienced more frequent flood and drought events. However, little is known about the long-term, spatiotemporal hydroclimatic changes across Europe. Here we present a climate field reconstruction spanning the entire European continent based on tree-ring stable isotopes. A pronounced seasonal consistency in climate response across Europe leads to a unique, well-verified spatial field reconstruction of European summer hydroclimate back to AD 1600. We find three distinct phases of European hydroclimate variability as possible fingerprints of solar activity (coinciding with the Maunder Minimum and the end of the Little Ice Age) and pronounced decadal variability superimposed by a long-term drying trend from the mid-20th century. We show that the recent European summer drought (2015–2018) is highly unusual in a multi-century context and unprecedented for large parts of central and western Europe. The reconstruction provides further evidence of European summer droughts potentially being influenced by anthropogenic warming and draws attention to regional differences

Higher frequency of Central Pacific El Niño events in recent decades relative to past centuries

El Niño events differ substantially in their spatial pattern and intensity. Canonical Eastern Pacific El Niño events have sea surface temperature anomalies that are strongest in the far eastern equatorial Pacific, whereas peak ocean warming occurs further west during Central Pacific El Niño events. The event types differ in their impacts on the location and intensity of temperature and precipitation anomalies globally. Evidence is emerging that Central Pacific El Niño events have become more common, a trend that is projected by some studies to continue with ongoing climate change. Here we identify spatial and temporal patterns in observed sea surface temperatures that distinguish the evolution of Eastern and Central Pacific El Niño events in the tropical Pacific. We show that these patterns are recorded by a network of 27 seasonally resolved coral records, which we then use to reconstruct Central and Eastern Pacific El Niño activity for the past four centuries. We find a simultaneous increase in Central Pacific events and a decrease in Eastern Pacific events since the late twentieth century that leads to a ratio of Central to Eastern Pacific events that is unusual in a multicentury context. Compared to the past four centuries, the most recent 30 year period includes fewer, but more intense, Eastern Pacific El Niño events