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Showing results for: [ Climatology (excl. Climate Change Processes) ]
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
This file contains the monthly Global Mean Sea Level (GMSL) time series as described in Church and White (2011).
3.3 ACCSP-SL change, storm surge - ACCSP - Published 13 Dec 2016
This file contains the monthly Global Mean Sea Level (GMSL) time series as shown on figure 2 of Church and White (2006). The sea level was reconstructed as described in Church et al (2004).
3.3 ACCSP-SL change, storm surge - details - Published 13 Dec 2016
This dataset contains global monthly 0.5 degree spatial resolution actual evapotranspiration and components (transpiration, soil evaporation, interception) from 1981 to 2012 inclusive. The estimates w... moreere computed through the observation-driven Penman-Monteith-Leuning (PML) model. For details refer to Zhang et al. (2016) http://dx.doi.org/10.1038%2Fsrep19124 The data is in netCDF4 format. less
CLSD Regional and global water modelling - Global Water Modelling - Published 02 May 2016
Ocean wave hindcast, using the WaveWatch III v4.18 wave model forced with NCEP CFSv2 hourly winds and daily sea ice, June 2013 - July 2014. The dataset contains spectral wave output at 3683 points, as... more well as gridded outputs on a global 0.4 degree (24 arcminute) grid, with nested Australian and western Pacific subgrids of 10 and 4 arcminutes resolution. For further information, see Durrant et al (2014)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. and http://dx.doi.org/10.4225/08/52817E2858340 for Jan 2011- May 2013 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact CSIRO enquiries@csiro.au or BoM climatedata@bom.gov.au for more information.less
CLSD 4.3 PACCSAP - High resolution wind- - Hindcast - Published 11 Aug 2015
The directory contains archived output from wave climate simulations carried out using a 1 degree global implementation of WaveWatch III (v3.14). The model is outlined in manuscripts: Hemer, Katzfey a... morend Trenham, 2013. Global dynamical projections of surface ocean wave climate for a future high greenhouse gas emission scenario. Ocean Modelling. DOI: 10.1016/j.ocemod.2012.09.008 Wave model forcing consisted of surface wind and sea-ice concentration fields. Archived variables, in monthly NetCDF files for all simulations, include significant wave height, mean wave period (Tm01), and mean wave direction. In total, this directory contains over 1050 model simulation years of data. Directory Structure: Global_wave_projections Historical (spans 1980-2005) - CFSR (This is a hindcast run, forced with NCEP CFSR, with same model configuration as GCM forced runs) - CMIP3 (ECHAM5, Mk3.5 both unadjusted and bias adjusted to CFSR), - CMIP5 (ACCESS1.0, CNRM-CM3, HadGEM2, INMCM4, BCC-CSM1.1, MIROC5, GFDL-CM3, MRI-CGCM3) Mid-Century (spans 2026-2045) - CMIP5 - RCP4.5 (ACCESS1.0, CNRM-CM3, HadGEM2, INMCM4, BCC-CSM1.1, MIROC5, GFDL-CM3, MRI-CGCM3) - RCP8.5 (ACCESS1.0, CNRM-CM3, HadGEM2, INMCM4, BCC-CSM1.1, MIROC5, GFDL-CM3, MRI-CGCM3) End-of-Century (spans 2080-2099) - CMIP3 - SRESA2 (ECHAM, Mk3.5 both unadjusted and bias adjusted to CFSR), - CMIP5 - RCP4.5 (ACCESS1.0, CNRM-CM3, HadGEM2, INMCM4, BCC-CSM1.1, MIROC5, GFDL-CM3, MRI-CGCM3) - RCP8.5 (ACCESS1.0, CNRM-CM3, HadGEM2, INMCM4, BCC-CSM1.1, MIROC5, GFDL-CM3, MRI-CGCM3)less
CLSD 4.3 PACCSAP - High resolution wind- - Wave simulations - Published 11 Aug 2015
Ocean wave hindcast, using the WaveWatch III v4.08 wave model forced with NCEP CFSv2 hourly winds and daily sea ice, January 2011 - May 2013. The dataset contains spectral wave output at 3683 points... more, as well as gridded outputs on a global 0.4 degree (24 arcminute) grid, with nested Australian and western Pacific subgrids of 10 and 4 arcminutes resolution. For further information, see Durrant et al (in prep)**. See DAP entry http://dx.doi.org/10.4225/08/523168703DCC5 for 1979-2010 data. Please note that the licensee/user is required to acknowledge the source of this data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information.less
CLSD 4.3 PACCSAP - High resolution wind- - Hindcast - Published 07 May 2015
Ocean wave hindcast, using the WaveWatch III v4.08 wave model forced with NCEP CFSR hourly winds and daily sea ice, 1979-2010. The dataset contains spectral wave output at 3683 points, as well as gri... moredded outputs on a global 0.4 degree (24 arcminute) grid, with nested Australian and western Pacific subgrids of 10 and 4 arcminutes resolution. For further information, see Durrant et al (in prep)**. N.B. January 1979 is a "model spin-up" month and data from this month should not be used for research purposes. Spectral wave parameters output: time; station; longitude; latitude; frequency; frequency1; frequency2 (centre, upper and lower bands); direction; Efth (sea surface wave directional variance spectral density); depth; u10m; udir (wind speed and direction 10m above surface); curr; currdir (sea water speed and direction). Gridded parameters output: longitude; latitude; time; MAPSTA (status map) ; U10; V10 (Eastward and Northward wind); CI (sea ice area fraction) ; hs (significant wave height); wl (mean wave length) ; t02 (mean wave period Tm02); t (mean period Tm01); tm0m1(mean period Tm0-1); CgE (wave energy flux); fp (peak wave frequency); dir (mean wave direction); spr (directional spread); dp (peak direction); hs0; hs1; hs2; hs3 (significant wave height partitions); tp0; tp1; tp2; tp3 (peak period partitions); lp0; lp1; lp2; lp3 (mean wave length partitions); th0; th1; th2; th3 (mean wave direction partitions); si0; si1; si2; si3 (directional spread partitions); ws0; ws1; ws2; ws3 (wind sea fraction partitions); wsf (wind sea fraction); pnr (number of wave partitions); dtd (dynamic time step); uust; vust (eastward, northward friction velocities); cha (Charnock coefficient); faw (wind to wave energy flux); utaw; vtaw (eastward, northward wave supported wind stress); utwa; vtwa (eastward, northward wave to wind stress); wcc (whitecap coverage); Sxx; Syy; Sxy (radiation stress components); utwo; vtwo (eastward, northward wave to ocean stress); uuss; vuss (eastward, northward surface stokes drift). Please note that the user is required to acknowledge the source of the data on the following terms: 'Source: Bureau of Meteorology and CSIRO © 2013'. Apart from dealings under the Copyright Act 1968, the licensee shall not reproduce (electronically or otherwise), modify or supply (by sale or otherwise) this data without written permission. Please contact us for more information.less
This product provides estimates of canopy conductance at a global scale (0.05⁰) based on MODIS reflectance from MCD43C4 product and three vegetation indices (NDVI, EVI and Kc). The data is produced ... moreglobally at 0.05⁰ and every 8 days. Monthly and anuual climatologies are also available. Base Period for Climatology: 2001-2011 Extra information about the pixel values: Units: mms-1 Multiply by scale factor: 0.001 Fill values: -9999 The full reference for the algorithm is: Yebra, M., Van Dijk, A., Leuning, R., Huete, A., Guerschman, J.P., 2013. Evaluation of optical remote sensing to estimate actual evapotranspiration and canopy conductance. Remote Sensing of Environment. 129, 250-261less
1212.0 OCE Post Doc Marta Yebra - Final mapping - Published 18 Dec 2012
These data provide rasterised layers of climatic variables hypothesised to explain spatial patterns in biological diversity at continental scales for use with statistical modelling tools. Specificall... morey, these data were derived for modelling the compositional pattern of multiple species with environmental factors such as climate, soil and topography using the statistical technique Generalised Dissimilarity Modelling applied to continental Australia. Climate variables are monthly mean values for minimum temperature, maximum temperature, relative humidity, vapour pressure, precipitation, aridity, solar radiation, evaporation, wind and others. Some of these monthly variables were used to generate growth indices (using the GROCLIM module of ANUCLIM). These data for Generalised Dissimilarity Modelling (GDM) analysis were masked to consistently define data/nodata values and supplied in DIVA-GIS floating-grid format in the WGS84 geographic reference system. NOTE: Full details of the data, with a list of data sources and bibliography, are provided in a PDF file included as part of the data collection.less
Closed DEWHA Harness Cntnnt-wide Bdvrsty - Spatial Environmental Data Preparation - Published 29 Jan 2015
Daily near-surface wind speeds (u) grids have been developed over all of Australia at a 0.01° spatial resolution by interpolating terrestrial anemometers measurements from an expanded network for 1975... more–2006. For these new grids, the Australian-averaged u trend for 1975–2006 was -0.009 m s-1 a-1 (agreeing with earlier site-based studies) with stilling over 88% of the land-surface. This new dataset can be used in numerous environmental applications, including benchmarking general circulation models to improve the representation of key parameters that govern u estimation. The methodology implemented here can be applied globally. Dataset Creation Date: 2008-07-15 Datsets updated on Jan 2013 to include years 2007 - 2014less
Legacy data - Near-Surface Wind Speed - Published 03 Feb 2017
