North American Regional Climate Change Assessment Program · 2020-01-06 · North American Regional...
Transcript of North American Regional Climate Change Assessment Program · 2020-01-06 · North American Regional...
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North American Regional Climate Change Assessment Program
Toni Rosati IMAGe – NCAR [email protected]
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Outline
• Basic concepts of numerical climate modeling
• NetCDF data format overview • NARCCAP project • NARCCAP curation and citation
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The fundamental element of climate simulation is a big box of air 200 x 200 GCM 50 x 50 km in NARCCAP
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• hus: humidity • ps: pressure • ta: temperature
• ua: E-W wind • va: N-S wind • zg: height
Each box is represented by 6 numbers
Simulation: apply Partial Differential Equations for fluid flow to each box to update the 6 numbers and calculate flux between neighboring boxes. (“dynamical core”)
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Sub-gridscale processes are handled by parameterization (e.g., thunderstorms)
Sub-models for other processes (“physics”) • radiation transfer • land surface • planetary boundary layer • convection • microphysics (rain/clouds)
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-99 0.5 -99 -99 -99 -99 -99 -99
-99 0.8 1.7 -99 -99 -99 -99 -99
-99 -99 0.9 0.5 -99 -99 -99 -99
-99 0.7 1.1 0.9 0.3 -99 -99 -99
0.4 1.2 1.6 1.9 2.3 1.2 -99 -99
0.9 2.5 2.2 2.8 4.1 1.8 0.2 -99
-99 1.3 2.2 2.9 3.3 2.1 0.5 -99
-99 0.8 2.6 3.1 2.8 2.2 0.8 -99
-99 0.1 1.9 4.2 2.4 1.6 0.9 0.1
-99 -99 0.4 2.9 1.8 0.5 -99 -99
-99 -99 0.2 1.5 0.7 -99 -99 -99
-99 -99 -99 0.3 -99 -99 -99 -99
-99 -99 -99 -99 -99 -99 -99 -99
Climate models represent reality as big grids of numbers
(“Raster data” in GIS parlance)
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How do you store the data? • Binary: platform dependent, opaque • Plain text: huge files, format ambiguity
1 2 3 4 4 3 2 1 5 5 5 5
123443215555 541532523514
?
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NetCDF
Network Common Data Form
• self-describing • platform-independent • array-oriented • scientific data • file format
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units: km missing_value: -99
-99 0.5 -99 -99 -99 -99 -99 -99
-99 0.8 1.7 -99 -99 -99 -99 -99
-99 -99 0.9 0.5 -99 -99 -99 -99
-99 0.7 1.1 0.9 0.3 -99 -99 -99
0.4 1.2 1.6 1.9 2.3 1.2 -99 -99
0.9 2.5 2.2 2.8 4.1 1.8 0.2 -99
-99 1.3 2.2 2.9 3.3 2.1 0.5 -99
-99 0.8 2.6 3.1 2.8 2.2 0.8 -99
-99 0.1 1.9 4.2 2.4 1.6 0.9 0.1
-99 -99 0.4 2.9 1.8 0.5 -99 -99
-99 -99 0.2 1.5 0.7 -99 -99 -99
-99 -99 -99 0.3 -99 -99 -99 -99
-99 -99 -99 -99 -99 -99 -99 -99
71.4 71.6 71.8 72.0 72.2 72.4 72.6 72.8
0.4
0.3
0.2
0.1
0.0
-0.1
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-0.3
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orog
lat
lon
NetCDF Data Model
units: degrees_east units: degrees_north
//GLOBAL title: island topography creator: Seth McGinnis Conventions: CF-1.6
lat
lon
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units: km missing_value: -99
-99 0.5 -99 -99 -99 -99 -99 -99
-99 0.8 1.7 -99 -99 -99 -99 -99
-99 -99 0.9 0.5 -99 -99 -99 -99
-99 0.7 1.1 0.9 0.3 -99 -99 -99
0.4 1.2 1.6 1.9 2.3 1.2 -99 -99
0.9 2.5 2.2 2.8 4.1 1.8 0.2 -99
-99 1.3 2.2 2.9 3.3 2.1 0.5 -99
-99 0.8 2.6 3.1 2.8 2.2 0.8 -99
-99 0.1 1.9 4.2 2.4 1.6 0.9 0.1
-99 -99 0.4 2.9 1.8 0.5 -99 -99
-99 -99 0.2 1.5 0.7 -99 -99 -99
-99 -99 -99 0.3 -99 -99 -99 -99
-99 -99 -99 -99 -99 -99 -99 -99
71.4 71.6 71.8 72.0 72.2 72.4 72.6 72.8
0.4
0.3
0.2
0.1
0.0
-0.1
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orog
lat
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Variables
units: degrees_east units: degrees_north
//GLOBAL title: island topography creator: Seth McGinnis Conventions: CF-1.6
lat
lon
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units: km missing_value: -99
-99 0.5 -99 -99 -99 -99 -99 -99
-99 0.8 1.7 -99 -99 -99 -99 -99
-99 -99 0.9 0.5 -99 -99 -99 -99
-99 0.7 1.1 0.9 0.3 -99 -99 -99
0.4 1.2 1.6 1.9 2.3 1.2 -99 -99
0.9 2.5 2.2 2.8 4.1 1.8 0.2 -99
-99 1.3 2.2 2.9 3.3 2.1 0.5 -99
-99 0.8 2.6 3.1 2.8 2.2 0.8 -99
-99 0.1 1.9 4.2 2.4 1.6 0.9 0.1
-99 -99 0.4 2.9 1.8 0.5 -99 -99
-99 -99 0.2 1.5 0.7 -99 -99 -99
-99 -99 -99 0.3 -99 -99 -99 -99
-99 -99 -99 -99 -99 -99 -99 -99
71.4 71.6 71.8 72.0 72.2 72.4 72.6 72.8
0.4
0.3
0.2
0.1
0.0
-0.1
-0.2
-0.3
-0.4
-0.5
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-0.7
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orog
lat
lon
Dimensions
units: degrees_east units: degrees_north
//GLOBAL title: island topography creator: Seth McGinnis Conventions: CF-1.6
lat
lon
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units: km missing_value: -99
-99 0.5 -99 -99 -99 -99 -99 -99
-99 0.8 1.7 -99 -99 -99 -99 -99
-99 -99 0.9 0.5 -99 -99 -99 -99
-99 0.7 1.1 0.9 0.3 -99 -99 -99
0.4 1.2 1.6 1.9 2.3 1.2 -99 -99
0.9 2.5 2.2 2.8 4.1 1.8 0.2 -99
-99 1.3 2.2 2.9 3.3 2.1 0.5 -99
-99 0.8 2.6 3.1 2.8 2.2 0.8 -99
-99 0.1 1.9 4.2 2.4 1.6 0.9 0.1
-99 -99 0.4 2.9 1.8 0.5 -99 -99
-99 -99 0.2 1.5 0.7 -99 -99 -99
-99 -99 -99 0.3 -99 -99 -99 -99
-99 -99 -99 -99 -99 -99 -99 -99
71.4 71.6 71.8 72.0 72.2 72.4 72.6 72.8
0.4
0.3
0.2
0.1
0.0
-0.1
-0.2
-0.3
-0.4
-0.5
-0.6
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orog
lat
lon
Attributes
units: degrees_east units: degrees_north
//GLOBAL title: island topography creator: Seth McGinnis Conventions: CF-1.6
lat
lon
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File Structure
• Header defines contents, holds metadata; actual data comes after in body of file
• NetCDF: binary. Plain-text equivalent: CDL • ncdump converts netcdf to CDL • ncgen converts CDL to netcdf
ncdump –h file.nc
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CF Metadata Standard CF = Climate and Forecast
• Set of rules about file naming conventions and metadata contents
• Designed to promote the processing and sharing of files created with the NetCDF API.
• Allows smart tools, GIS compatibility • standard_name, units attributes • NARCCAP data follows v 1.0 • CF spec is extensive
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CF Metadata Standard CF = Climate and Forecast
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NARCCAP: North American Regional Climate Change Assessment Program
Nest high-res* regional models (RCMs) inside coarser global models (GCMs) over N. America *50 km gridcells
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Goals of NARCCAP
• Evaluate model performance and uncertainty
• Generate high-res climate change scenario data for impacts analysis
• Support further dynamical downscaling experiments
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6 RCM Modeling Teams
• CRCM - S. Biner, OURANOS • ECP2 - A. Nunes, Scripps • HRM3 - R. Jones, et al, Hadley Centre • MM5I - B. Gutowski, R. Arritt, ISU • RCM3 - M. Snyder, UC Santa Cruz • WRFG - R. Leung, PNNL • Details: narccap.ucar.edu/data/rcm-characteristics.html
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Advantages of higher resolution
North America at 50 km grid spacing
North America at typical global climate model resolution
Hadley Centre AOGCM (HadCM3), 2.5˚ (lat) x 3.75˚ (lon), ~ 280 km
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The Basic Idea
• Nest RCMs inside GCMs to obtain dynamically downscaled data
• Two 30-year runs, current (1971-2000) and future (2041-2070).
• SRES A2 emissions scenario for future run
• narccap.ucar.edu/about/aogcms.html
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AOGCM-RCM Matrix
GFDL CGCM3 HADCM3 CCSM3
MM5 X X**
RegCM X** X**
CRCM X** X**
HadRM X** X**
RSM X** X
WRF X** X**
*CAM3 X *GFDL X**
*= time slice experiments Red = run completed ** = data loaded
AOGCMS
RCMs
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Looking Into the Future
• No crystal balls • Scenarios, not forecasts • Look at current and future • No “best” model • Look at multiple models • Embrace uncertainty
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Data Archive
• Data distribution: earthsystemgrid.org • Organization: RCM → Driver → Table • 1 variable per file, 5 years per file* * (except at beginning of run)
• Filenames: Var_Model_Driver_Time.nc Time = yyyymmddhh of first timestep
• http://narccap.ucar.edu/data/output_archive.html
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Data Tables
• Table 1: daily values (e.g. Tmin & Tmax) • Table 2: “big 7” variables for impacts:
temp, prec, pressure, wind, sun, humidity • Table 3: all the other 2-D variables • Table 4: static (unchanging) variables
Not on ESG! narccap.ucar.edu/data/table4 • Table 5: all 3-D variables
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NARCCAP Users Three main types of NARCCAP users: • Those who want to perform analyses on the NARCCAP
output (e.g., for a particular subdomain). • Those who want to use the results as climate scenarios
for performing impacts studies (e.g. on agriculture, water resources).
• Those who want to use the results for performing further downscaling experiments, either via higher resolution RCM simulations or statistical downscaling.
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Analysis Users
• Comparisons – Between models – Change between current and future
• Bias • “We will use NARCCAP precipitation and temperature
data to check the outputs of different coupled combinations between global and regional models to try to answer the question: ‘Among all combinations, which coupled models are perform best throughout the southern U.S and northern Mexico?’"
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Impacts Users
• Ecology, biology, adaptation, water management
• Plug into other models • “Data from these climate change models or
scenarios will be used as inputs to the SWAT model to forecast the impacts on water quantity and quality as well as crop and timber yields. We also will examine the likely changes in the ecosystem services based on forecasts of land use change in the region.”
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Further Downscaling Users
• Statistical • Dynamical (WRF) • Uncertainty • “NARCCAP output serves as boundary
conditions with which to drive inner nests of the WRF modelled, centered over southern Ontario. This allows climate simulations to be dynamically downscaled over the region of interest”
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The “Other” Category • “I'm working on a regional downscaling effort at Oregon
State University using RegCM3. I am having trouble formatting our NetCDF output to be CF-1.0 compliant so that it properly imports into ArcGIS. I would like access to the NARCCAP output so I can have a working datasets to compare to. I think we'd benefit by being able to compare our 50km North America runs to those on NARCCAP.”
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Citation
• First NCAR dataset to receive a DOI • Why one DOI? • Challenge of finding NARCCAP papers –
register, but once gotten can’t track w/o citations.
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Curation
• Different types of users have different support needs
• Publishing data is different than publishing an article
• More than just versioning • How to make data citation standard
practice?
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Citation • Previously, we requested an “acknowledgement” • "We wish to thank the North American Regional Climate
Change Assessment Program (NARCCAP) for providing the data used in this paper. NARCCAP is funded by the National Science Foundation (NSF), the U.S. Department of Energy (DoE), the National Oceanic and Atmospheric Administration (NOAA), and the U.S. Environmental Protection Agency Office of Research and Development (EPA)."
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Citation
• Mearns, L.O., et al., 2007, updated 2012. The North American Regional Climate Change Assessment Program dataset, National Center for Atmospheric Research Earth System Grid data portal, Boulder, CO. Data downloaded 2012-06-04. [doi:10.5065/D6RN35ST]