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Showing results for: [ climate change ]
A selection of 9sec gridded National climate change variables for biodiversity modelling. This collection represents 30-year averages centred on each of 1990, 2050, 2070, 2090. Projected future climat... morees were generated by applying within-model changes for two circulation model outputs: GFDL and ACCESS1.0; and for two representative concentration pathways (RCP 4.5, 8.5), calculated at the native general circulation model grid resolution to these current surfaces, using ANUCLIM 6.1 prior to radiative adjustment. That the maximum temperature variables have been adjusted for topographic slope/aspect and shading effects. A short methods summary is provided in the file 9sClimateMethodsSummary.pdf for further information, including a nomenclature for files. The selected climate variables provided in this collection are: TNM - mean annual minimum temperature TXM - mean annual maximum temperature TXX - mean maximum monthly maximum temperature TXI - mean minimum monthly maximum temperature TNI - mean minimum monthly minimum temperature TNX - mean maximum monthly minimum temperature PTA - Average total annual rainfall PTX - mean maximum monthly rainfall PTI - mean minimum monthly rainfall Other variables (evaporation and water balance, temperature range, and seasonality, etc) are available upon application. The data are provided in ESRI binary float grid format (*.hdr, *.flt), Projection is geographic GDA94. less
1173.3 WPC Global Protected Area Assessm - climate change scenarios - Published 12 Sep 2018
Bio-physical, ecological and social information have been used to parameterise two computer models able to simulate (ALCES and Ecopath with Ecosim [EwE]) land, coastal and marine processes. A careful ... moreexamination of a large volume of publications from the academic, private and public sector has also allowed us to identify a number of climate and social economic development scenarios the Kimberly region may experience in the decades to comeless
WAMSI-Kim 2.2.8 MSE Modelling Knowledge - MSE modelling and ecosystem modelling - Published 09 Mar 2018
Projections of sea level rise (SLR) will lead to increasing coastal impacts during extreme sea level events globally, however, there is significant uncertainty around short-term coastal sea level vari... moreability and the attendant frequency and severity of extreme sea level events. In this study, we investigate drivers of coastal sea level variability (including extremes) around Australia by means of historical conditions as well as future changes under a high greenhouse gas emissions scenario (RCP 8.5). To do this, a multi-decade hindcast simulation is validated against tide gauge data. The role of tide-surge interaction is assessed and found to have negligible effects on storm surge characteristic heights over most of the coastline. For future projections, a couple of twenty-year long simulations are carried out over the time periods 1981-1999 and 2081-2099 using atmospheric forcing from four CMIP5 climate models. Results provide insights into how future atmospheric circulation changes may impact Australia’s coastal zone and highlight regions of potential sensitivity to atmospheric circulation changes. Areas of note are the Gulf of Carpentaria in the north where changes to the northwest monsoon could lead to relatively large increases in extreme sea levels during Austral summer. For the southern mainland coast the simulated scenarios suggest that a southward movement of the subtropical ridge leads to a small reduction in sea level extremes. less
NESP ESSC Coastal Hazards in a Variable and Changing Climate - - Published 01 Feb 2018
This collection provides additional analyses, figures and tables for an integrated risk assessment of natural, cultural and economic assets in the Kakadu Region of northern Australia, from the combine... mored threats of invasive species (feral animals & aquatic weeds) and climate change induced sea level rise saltwater inundation. It addresses cumulative multiple risks to multiple values over different time frames (Present-day, 2070 & 2100).less
Legacy data - Modelling - Published 25 Sep 2017
In this project (Kimberley Marine Research Project 2.2.7), historical data and numerical models have been used to identify the climate sensitivity of the Kimberley coast (Western Australia) to interan... morenual and decadal climate variability in the Pacific and Indian Ocean over the past several decades, especially on the variability of ocean temperature, precipitation and salinity, sea level, and shelf current associated with El Niño–Southern Oscillation (ENSO), Indian Ocean Dipole, and Pacific Decadal Oscillation. These analyses have provided the background understanding of the marine environment off the whole northwest shelf including the Kimberley coast and Scott Reef, to improve the predictability of climate-driven environmental variability, especially extreme events such as marine heatwaves. We have also utilised ocean downscaling models to project future climate change impacts on the marine environment such as the ocean temperature and internal wave characteristics. Data for model year 2069 onlyless
1177.1 WAMSI-Kim 2.2.7 Climate Modelling - Hydrodynamic modelling - Published 04 Sep 2017
In this project (Kimberley Marine Research Project 2.2.7), historical data and numerical models have been used to identify the climate sensitivity of the Kimberley coast (Western Australia) to interan... morenual and decadal climate variability in the Pacific and Indian Ocean over the past several decades, especially on the variability of ocean temperature, precipitation and salinity, sea level, and shelf current associated with El Niño–Southern Oscillation (ENSO), Indian Ocean Dipole, and Pacific Decadal Oscillation. These analyses have provided the background understanding of the marine environment off the whole northwest shelf including the Kimberley coast and Scott Reef, to improve the predictability of climate-driven environmental variability, especially extreme events such as marine heatwaves. We have also utilised ocean downscaling models to project future climate change impacts on the marine environment such as the ocean temperature and internal wave characteristics. Data for model year 2068 onlyless
In this project (Kimberley Marine Research Project 2.2.7), historical data and numerical models have been used to identify the climate sensitivity of the Kimberley coast (Western Australia) to interan... morenual and decadal climate variability in the Pacific and Indian Ocean over the past several decades, especially on the variability of ocean temperature, precipitation and salinity, sea level, and shelf current associated with El Niño–Southern Oscillation (ENSO), Indian Ocean Dipole, and Pacific Decadal Oscillation. These analyses have provided the background understanding of the marine environment off the whole northwest shelf including the Kimberley coast and Scott Reef, to improve the predictability of climate-driven environmental variability, especially extreme events such as marine heatwaves. We have also utilised ocean downscaling models to project future climate change impacts on the marine environment such as the ocean temperature and internal wave characteristics. Data for model year 2067 onlyless
In this project (Kimberley Marine Research Project 2.2.7), historical data and numerical models have been used to identify the climate sensitivity of the Kimberley coast (Western Australia) to interan... morenual and decadal climate variability in the Pacific and Indian Ocean over the past several decades, especially on the variability of ocean temperature, precipitation and salinity, sea level, and shelf current associated with El Niño–Southern Oscillation (ENSO), Indian Ocean Dipole, and Pacific Decadal Oscillation. These analyses have provided the background understanding of the marine environment off the whole northwest shelf including the Kimberley coast and Scott Reef, to improve the predictability of climate-driven environmental variability, especially extreme events such as marine heatwaves. We have also utilised ocean downscaling models to project future climate change impacts on the marine environment such as the ocean temperature and internal wave characteristics. Data for model year 2066 onlyless
In this project (Kimberley Marine Research Project 2.2.7), historical data and numerical models have been used to identify the climate sensitivity of the Kimberley coast (Western Australia) to interan... morenual and decadal climate variability in the Pacific and Indian Ocean over the past several decades, especially on the variability of ocean temperature, precipitation and salinity, sea level, and shelf current associated with El Niño–Southern Oscillation (ENSO), Indian Ocean Dipole, and Pacific Decadal Oscillation. These analyses have provided the background understanding of the marine environment off the whole northwest shelf including the Kimberley coast and Scott Reef, to improve the predictability of climate-driven environmental variability, especially extreme events such as marine heatwaves. We have also utilised ocean downscaling models to project future climate change impacts on the marine environment such as the ocean temperature and internal wave characteristics. Data for model year 2012 onlyless
In this project (Kimberley Marine Research Project 2.2.7), historical data and numerical models have been used to identify the climate sensitivity of the Kimberley coast (Western Australia) to interan... morenual and decadal climate variability in the Pacific and Indian Ocean over the past several decades, especially on the variability of ocean temperature, precipitation and salinity, sea level, and shelf current associated with El Niño–Southern Oscillation (ENSO), Indian Ocean Dipole, and Pacific Decadal Oscillation. These analyses have provided the background understanding of the marine environment off the whole northwest shelf including the Kimberley coast and Scott Reef, to improve the predictability of climate-driven environmental variability, especially extreme events such as marine heatwaves. We have also utilised ocean downscaling models to project future climate change impacts on the marine environment such as the ocean temperature and internal wave characteristics. Data for model year 2011 onlyless
In this project (Kimberley Marine Research Project 2.2.7), historical data and numerical models have been used to identify the climate sensitivity of the Kimberley coast (Western Australia) to interan... morenual and decadal climate variability in the Pacific and Indian Ocean over the past several decades, especially on the variability of ocean temperature, precipitation and salinity, sea level, and shelf current associated with El Niño–Southern Oscillation (ENSO), Indian Ocean Dipole, and Pacific Decadal Oscillation. These analyses have provided the background understanding of the marine environment off the whole northwest shelf including the Kimberley coast and Scott Reef, to improve the predictability of climate-driven environmental variability, especially extreme events such as marine heatwaves. We have also utilised ocean downscaling models to project future climate change impacts on the marine environment such as the ocean temperature and internal wave characteristics. Data for model year 2010 onlyless
In this project (Kimberley Marine Research Project 2.2.7), historical data and numerical models have been used to identify the climate sensitivity of the Kimberley coast (Western Australia) to interan... morenual and decadal climate variability in the Pacific and Indian Ocean over the past several decades, especially on the variability of ocean temperature, precipitation and salinity, sea level, and shelf current associated with El Niño–Southern Oscillation (ENSO), Indian Ocean Dipole, and Pacific Decadal Oscillation. These analyses have provided the background understanding of the marine environment off the whole northwest shelf including the Kimberley coast and Scott Reef, to improve the predictability of climate-driven environmental variability, especially extreme events such as marine heatwaves. We have also utilised ocean downscaling models to project future climate change impacts on the marine environment such as the ocean temperature and internal wave characteristics. Data for model year 2009 onlyless
IOCI3, a climate research collaboration between CSIRO, BoM and the Government of Western Australia produced statistically downscaled projections for daily rainfall and maximum and minimum temperature ... morefor south-west WA (29 sites) and north-west WA (9 Kimberley sites and 10 Pilbara sites). These fine-scale projections for mid-century and end-of-century time periods are useful for climate change adaptation management and planning (but see caveats & limitations under "Lineage" and "Read me" files). These results are provided as CSV (comma-separated-values) files.less
CLSD IOCI3 Theme 3 - C2006/4983 - Indian Ocean Climate Initiative Stage 3 (IOCI3) - Published 14 Mar 2017
The empirical scaling factors can be used to guide the plausible range of changes in the climate variables within impact-adaption-vulnerability assessment under climate change. The gridded dataset of ... moreall the scaling factors are produced at the spatial resolution of 0.5o×0.5o with the name ScalingFactor_0.5. In the dataset, there are 6 subfolders named as prcp, pexm, pet, tas, tasmax and tasmin representing scaling factors of precipitation, extreme high daily rainfall, potential evapotranspiration, mean temperature, maximum temperature and minimum temperature. In the subfolder, each text file represents the scaling factors of each GCM model and each run. less
SDIP1 wrap-up - climate change scaling factors - Published 19 Jan 2017
Using the Land-Use Trade-Offs (LUTO) model, this data collection was produced via a comprehensive, detailed, integrated, and quantitative scenario analysis of land-use and sustainability for Australia... more’s intensive-use agricultural land to 2050, under intersecting global change and domestic policies, and considering key uncertainties. We assessed land use competition between multiple land uses and assessed sustainability of economic returns and multiple ecosystem services at high spatial (1.1 km grid cell) and temporal (annual) resolution. Results available are for 648 scenarios covering combinations of four global outlooks, three general circulation climate models, three domestic land-use policies, three productivity growth rates, three land-use change adoption hurdle rates, and two capacity constraint settings. Outputs included for each scenario are: - annual land-use layers - summary data table - graphical dashboard summary - animation of potential land-use change, drivers, and impacts This analysis was conducted in conjunction with CSIRO’s Australian National Outlook initiative to assess future potential land-use change and the impacts for the sustainability of ecosystem services. A full description of the methods and synthesis of the results can be found in the papers listed in the Related Information below and freely available via email from the author. The data is provided to support a national conversation on the future for Australian land systems, public decision-making and policy design, and further scientific research. less
SIP 59 LUTO land use modelling science p - Modelling - Published 07 Jun 2016
This dataset contains rasters of the change in runoff and recharge under future climates
1157.1 NRM Murray Basin - Water activity - Published 02 May 2016
Projections of rainfall, potential evapotranspiration (PET) and runoff for 1 degree and 2 degrees of global warming.
Legacy data - Modelling - Published 07 Apr 2016
Three empirically-derived indices of tropical cyclone genesis - Genesis Potential Index (labelled in files as "gpi"), Murakami-GPI ("GPIM") and Tippett Index ("TCGI") - have been applied to monthly ou... moretputs of a suite of CMIP5 models. The indices each use combinations of monthly mean meteorological and sea surface temperature fields in order to indicate regions with favourable conditions for the generation of tropical cyclones (known as cyclogenesis). The resulting outputs have been calculated over three time periods. Data are in the form of netCDF files containing time series of either seasonal or annual averages for each index. The files are arranged inside folders named after the CMIP5 model from which these products have been derived (note: these are not the official CMIP5 model names). Index outputs are stored over each of the following periods: - 1980 to 1999 (historical), - 2046 to 2065 (rcp85), and - 2081 to 2100 (rcp85) where the bracketed text indicates the CMIP5 Representative Concentration Pathway (RCP) used to provide the climate forcings for the simulation. The seasonal time series files are labelled with the above year ranges, with a file name structure of: [index]_[year1]_[year2]_seasmean.nc The files containing annual average time series have file names of the form: [index]_ANN_mergetime_[model_label]_[year].nc The [year] label in the annual average file names corresponds to the first year of one of the respective periods above, respectively: - 1980, - 2046, and - 2081. less
CLSD PCCSAP TC Downscaling & Coincident - CMIP 5 model analysis of tropical cyclone behaviour - Published 02 Jul 2015
This data collection consists of: 1. ASCII text files listing each tropical cyclone detected within output of a suite of CMIP5 models for the Pacific region contained by latitudes 20N to 40S, and long... moreitudes 135E to 150W; and 2. Global images of tropical cyclone densities derived from these detections, presented as either days per year or storms per year for a 5 x 5 degree longitude/latitude grid. All tropical cyclones detected using the CSIRO Direct Detection and tracking algorithm within the above domain are presented in space-delimited ASCII text files for each model. Three time periods are available to select: - from 1981 to 2000 ("baseline" period used for projections); - from 2081 to 2100 ("future" period used for projections); and - from 1950 to 2100 (all data). There are two image types for each coupled model data source, both based on densities of storms within a 5 x 5 lon/lat degree box for the respective 20 year period (either 1981-2000 or 2081-2100): - images containing "days" in the file name show the number of days per year in which a tropical cyclone was detected within that box - images with "number" in the file name display the number of separate storms per year detected within that box.less
Codes used in the generation of Goyder Institute for Water Research downscaled climate projections for South Australia
1212.1 Goyder Climate - Task 3 - Statistically downscaled simulations - Published 14 Apr 2015
This is the high resolution version of the AdaptNRM Guide “Implications of Climate Change for Biodiversity: a community-level modelling approach” accompanies the digital datasets and maps. This versio... moren is the same as the web-version (lower resolution) available online at www.AdaptNRM.org. This AdaptNRM Module introduces a series of new measures based on ecological similarity to assess the potential for change in biodiversity under climate change at scales relevant to planning. It is intended to support assessment and lead into strategic planning in NRM. In addition to this Guide, the Module includes a series of maps in poster format and data layers. Links to the datasets and maps are given in “related materials”, below. This Guide explains how to interpret and use this information, rather than focusing on outcomes for any specific biological group, a likely future climate, or on how global human behaviour may be expressed though a particular emission scenario. In this Guide, we: 1. introduce a new approach to modelling/mapping change in biodiversity under climate change developed by CSIRO, 2. demonstrate the types of data, show how these can be viewed at national, regional and local scales, and explain their interpretation, 3. provide examples of how this information can be used in planning, with a particular focus on assessment and the core adaptation challenges outlined in The NRM Adaptation Checklist. CITATION: Williams KJ, Prober SM, Harwood TD, Doerr VAJ, Jeanneret T, Manion G, and Ferrier S (2014) Implications of climate change for biodiversity: a community-level modelling approach, CSIRO Land and Water Flagship, Canberra. Available at: www.AdaptNRM.org. ISBN 978-1-4863-0479-0 less
NRM National Project - AdaptNRM Biodiversity Module - Published 12 Dec 2014
This is a technical guide for 'AdaptNRM module 2: Invasive plant species and climate change', and a summary table of CLIMEX parameters for invasive plant species. The distribution maps for each of the... more species can be found in other collections in this portal.less
Module 2: Weed projections and invasion - Technical Guide and Parameter Sets for Invasive plant species distribution model using CLIMEX - Published 17 Nov 2014
Statistically downscaled simulations of daily weather variables for station networks within South Australian Natural Resource Management regions for present and future (projected) climate conditions.
1212.1 Goyder Climate - Task 3 - Statistically downscaled simulations - Published 13 Nov 2014
Global and Australian maps of Species Distribution Models (SDM) for current and 2070 climates for invasive plant species for which there are published CLIMEX models. The parameters for the model are l... moreisted in a cxp file. A GIS suitable file is provided.less
Module 2: Weed projections and invasion - Invasive plant species distribution model using CLIMEX - Published 28 Aug 2014
Module 2: Weed projections and invasion - Invasive plant species distribution model using CLIMEX - Published 19 Aug 2014
