MACA References and License

MACA Method

Abatzoglou J.T. and Brown T.J. "A comparison of statistical downscaling methods suited for wildfire applications " International Journal of Climatology (2012),doi: 10.1002/joc.2312. Full Article

Hegewisch,K.C., Abatzoglou J.T. " An improved Multivariate Adaptive Constructed Analogs(MACA) Statistical Downscaling Method. In preparation.

Observation Dataset: METDATA

Abatzoglou J. T. " Development of gridded surface meteorological data for ecological applications and modelling " International Journal of Climatology. (2011), doi: 10.1002/joc.3413.
Full Article. More information.

Observation Dataset: LIVNEH

Livneh B, E.A. Rosenberg, C. Lin, V. Mishra, K. Andreadis, E.P. Maurer, and D.P. Lettenmaier. " A Long-Term Hydrologically Based Dataset of Land Surface Fluxes and States for the Conterminous United States: Update and Extensions. J. Climate, 26, 9384–9392.(2013).
Abstract

GCM Dataset: CMIP5 Project

Taylor, K.E., R.J. Stouffer, G.A. Meehl: An Overview of CMIP5 and the experiment design. MS-D-11-00094.1, 2012.

How to Reference Data from a MACA dataset:


MACAv1-METDATA

Climate forcings in the MACAv1-METDATA were drawn from a statistical downscaling of global climate model (GCM) data from the Coupled Model Intercomparison Project 5 (CMIP5, Taylor et al. 2010) utilizing the Multivariate Adaptive Constructed Analogs (MACA, Abatzoglou and Brown, 2012) method with the METDATA(Abatzoglou, 2011) observational dataset as training data.

MACAv2-LIVNEH

Climate forcings in the MACAv2-LIVNEH were drawn from a statistical downscaling of global climate model (GCM) data from the Coupled Model Intercomparison Project 5 (CMIP5, Taylor et al. 2010) utilizing a modification(Hegewisch, Abatzoglou, in prep.) of the Multivariate Adaptive Constructed Analogs (MACA, Abatzoglou and Brown, 2012) method with the Livneh(Livneh et.al.,2013) observational dataset as training data.

MACAv2-METDATA

Climate forcings in the MACAv2-METDATA were drawn from a statistical downscaling of global climate model (GCM) data from the Coupled Model Intercomparison Project 5 (CMIP5, Taylor et al. 2010) utilizing a modification(Hegewisch, Abatzoglou, in prep.) of the Multivariate Adaptive Constructed Analogs (MACA, Abatzoglou and Brown, 2012) method with the METDATA(Abatzoglou, 2011) observational dataset as training data.

The MACA datasets were created with funding from the US government and are in the public domain in the United States. For further clarity, unless otherwise noted, the MACA datasets are made available with a Creative Commons CC0 1.0 Universal dedication. In short, John Abatzoglou waives all rights to the work worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law. You can copy, modify, distribute, and perform the work, even for commercial purposes, all without asking permission. John Abatzoglou makes no warranties about the work, and disclaims liability for all uses of the work, to the fullest extent permitted by applicable law.

While not required, when using The MACA datasets in your own work, we ask that proper credit be given. An example citation is provided below: Abatzoglou J.T. and Brown T.J. "A comparison of statistical downscaling methods suited for wildfire applications " International Journal of Climatology (2012) doi: 10.1002/joc.2312.

Please acknowledge the funding agencies: Regional Approaches to Climate Change (REACCH), the Climate Impacts Research Consortium(CIRC) and the Northwest/SouthEast Climate Science Centers(NWCSC,SECSC).


CC0
To the extent possible under law, John Abatzoglou has waived all copyright and related or neighboring rights to MACA Datasets. This work is published from: United States.

How to Acknowledge a MACA dataset:


MACAv1-METDATA

The dataset MACAv1-METDATA was produced with funding from the Regional Approaches to Climate Change (REACCH) project. We acknowledge the World Climate Research Programme's Working Group on Coupled Modeling, which is responsible for CMIP, and we thank the climate modeling groups for producing and making available their model output. For CMIP, the U.S. Department of Energy's Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals.

MACAv2-LIVNEH

The dataset MACAv2-LIVNEH was produced under the Northwest Climate Science Center (NW CSC) US Geological Survey Grant Number G12AC20495. We acknowledge the World Climate Research Programme's Working Group on Coupled Modeling, which is responsible for CMIP, and we thank the climate modeling groups for producing and making available their model output. For CMIP, the U.S. Department of Energy's Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals.

MACAv2-METDATA

The dataset MACAv2-METDATA was produced with funding from the Regional Approaches to Climate Change (REACCH) project and the SouthEast Climate Science Center(SECSC). We acknowledge the World Climate Research Programme's Working Group on Coupled Modeling, which is responsible for CMIP, and we thank the climate modeling groups for producing and making available their model output. For CMIP, the U.S. Department of Energy's Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals.

Publications of Interest to MACA Users

Abatzoglou, J.T., D.E. Rupp and P.W. Mote, 2014, Understanding seasonal climate variability and change in the Pacific Northwest of the United States, Journal of Climate, 27, 21252142 doi: 10.1175/JCLI-D-13-00218.1
Abstract

Abatzoglou J.T., R. Barbero, J.W. Wolf, Z. Holden, 2014, Tracking interannual streamflow variability with drought indices in the Pacific Northwest, US, Journal of Hydrometeorology, 15, 1900-1912
Abstract

Rupp, D.E., J.T. Abatzoglou, K.C. Hegewisch and P.W. Mote, 2013, Evaluation of CMIP5 20th century climate simulations for the Pacific Northwest USA, J. Geophysical Research Atmospheres, doi:10.1002/jgrd.50843
Abstract

SouthEast Climate Science Center
Rupp, D.E., 2016, An evaluation of 20th century climate for the Southeastern United States as simulated by Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models: U.S. Geological Survey Open-File Report 2016–1047, 32 p., http://dx.doi.org/10.3133/ofr20161047.
USGS Open-File Report(PDF, 6.1 MB).

Reports of Interest to MACA Users

Northwest Climate Science Center: Integrated Scenarios of the Future Northwest Environment Project
Phil Mote, John Abatzoglou, Dennis Lettenmaier,Dave Turner,David Rupp, Dominique Bachelet, David Conklin. 'Final Report for Integrated Scenarios of climate, hydrology, and vegetation for the Northwest'.

Southern Nevada Water Authority
Abatzoglou, J. T., Hegewisch, K., Carroll, R. W., Lutz, A., Leising, J. F., Rajagopal, S., Brooks, K., Thomas, J. M. (2014). Impacts of a Changing Climate on Water Resources in the Eastern Great Basin, DRI, Submitted

Seattle Public Utilities
Dalton, M.M. and K. Hegewisch. 2014. Technical Memorandum #3 for Seattle Public Utilities PUMA Project: "Evaluation of Historic MACA-Downscaled Station Data." Climate Impacts Research Consortium. June 2.

Hegewisch, K. and J. Abatzoglou. 2013. Technical Memorandum #2 for Seattle Public Utilities PUMA Project: "Climate Downscaling." Climate Impacts Research Consortium.

Portland Water Bureau
Abatzoglou, J. and K. Hegewisch. 2013a. Climate Downscaling. University of Idaho. December 20.

Abatzoglou, J. and K. Hegewisch. 2013b. Climate Model Evaluation and Projections Synopsis. University of Idaho. December 20.