Downscaled Climate and Hydrology Projections Archive
Date 10-Jun-2020
Archive Collaborators:
Bureau of Reclamation
California-Nevada Climate Applications Program
Climate Analytics Group
Cooperative Institute for Research in Environmental Sciences
Lawrence Livermore National Laboratory
National Center for Atmospheric Research
Santa Clara University
Scripps Institution of Oceanography
Southwest Climate Adaptation Science Center
U.S. Army Corps of Engineers
U.S. Geological Survey
I. Terms of Use
These projections are being distributed to interested users for consideration
in research and planning applications. Such applications may include any
project carried out by an individual or organized by a university, a
scientific institute, public agency, or private sector entity for research or
planning purposes. Any decision to use these projections is at the interested
user's discretion and subject to the Disclaimer provided below.
II. Disclaimer
These projections are being made available to provide immediate access for
the convenience of interested persons. They are being made available by
Archive Collaborators (i.e. Bureau of Reclamation, California-Nevada Climate
Applications Program, Climate Analytics Group, Cooperative Institute for
Research in Environmental Sciences, Lawrence Livermore National Laboratory,
National Center for Atmospheric Research, Santa Clara University, Scripps
Institution of Oceanography, Southwest Climate Adaptation Science Center,
U.S. Army Corps of Engineers, and U.S. Geological Survey). Archive
Collaborators believe the information to be correct representations of
potential high-resolution climate/hydrologic variations and changes subject
to the limitations of the CMIP3 and CMIP5 global climate simulations, and the
downscaling methods and their limitations, as described elsewhere in this web
site. However, human and mechanical errors remain possibilities. Therefore,
Archive Collaborators do not guarantee the accuracy, completeness,
timeliness, or correct sequencing of the information. Also, neither Archive
Collaborators, nor any of the sources of the information shall be responsible
for any errors or omissions, or for the use or results obtained from the use
of this information.
III. Acknowledgements and Citation of these Projections
Whenever you publish research based on projections from this archive, please
include two acknowledgements:
1. First, acknowledge the superceding effort.
a. For CMIP3, the following is language suggested by the CMIP3 archive hosts
at PCMDI: "We acknowledge the modeling groups, the Program for Climate Model
Diagnosis and Intercomparison (PCMDI) and the WCRP's Working Group on Coupled
Modelling (WGCM) for their roles in making available the WCRP CMIP3
multi-model dataset. Support of this dataset is provided by the Office of
Science, U.S. Department of Energy." PCMDI also requests that in first making
reference to the projections from this archive, please first reference the
CMIP3 dataset by including the phrase "the World Climate Research Programme's
(WCRP's) Coupled Model Intercomparison Project phase 3 (CMIP3) multi-model
dataset". Subsequent references within the same publication might refer to
the CMIP3 data with terms such as "CMIP3 data", "the CMIP3 multi-model
dataset", "the CMIP3 archive", or the "CMIP3 dataset".
b. For CMIP5, , the model output should be referred to as "the CMIP5
multi-model ensemble [archive/output/results/of simulations/dataset/ ...]".
In publications, you should include a table (referred to below as Table XX)
listing the models and institutions that provided model output used in your
study. In this table and as appropriate in figure legends, you should use the
CMIP5 "official" model names found in "CMIP5 Modeling Groups and their Terms
if Use" (pdf document, also in Word doc format). In addition, an
acknowledgment similar to the following should be included in your publication:
"We acknowledge the World Climate Research Programme's Working Group on
Coupled Modelling, which is responsible for CMIP, and we thank the climate
modeling groups (listed in Table XX of this paper) 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."
where, "Table XX" in your paper should list the models and modeling groups
that provided the data you used. In addition it may be appropriate to cite
one or more of the CMIP5 experiment design articles listed on the CMIP5
reference page.
2. Second, generally acknowledge this archive as "Downscaled CMIP3 and CMIP5
Climate and Hydrology Projections" archive at
http://gdo-dcp.ucllnl.org/downscaled_cmip_projections/. To reference specific
information in the archive, you may also use the following references:
a. for BCSD CMIP3 climate: Maurer, E.P., L. Brekke, T. Pruitt, and P.B.
Duffy, 2007, � Eos Trans. AGU, 88(47), 504.
b. for BCSD CMIP3 hydrology: Reclamation, 2011, West-Wide Climate Risk
Assessments: Bias-Corrected and Spatially Downscaled Surface Water
Projections, Technical Memorandum No. 86-68210-2011-01, prepared by the U.S.
Department of the Interior, Bureau of Reclamation, Technical Services
Center, Denver, Colorado, 138 p.
c. for BCSD CMIP5 climate: Provide citation to: Reclamation, 2013.
Downscaled CMIP3 and CMIP5 Climate Projections: Release of Downscaled CMIP5
Climate Projections, Comparison with Preceding Information, and Summary of
User Needs. U.S. Department of the Interior, Bureau of Reclamation, 104 p.,
available at:
http://gdo-dcp.ucllnl.org/downscaled_cmip_projections/techmemo/downscaled_ climate.pdf.
d. for BCSD CMIP5 hydrology: Reclamation, 2014. Downscaled CMIP3 and
CMIP5 Hydrology Projections - Release of Hydrology Projections, Comparison
with Preceding Information, and Summary of User Needs. U.S. Department of
the Interior, Bureau of Reclamation,104 p., available at:
http://gdo-dcp.ucllnl.org/downscaled_cmip_projections/techmemo/downscaled_ climate.pdf.
e. for the locally constructed analogs method (LOCA) CMIP5 projections:
Pierce, D. W., D. R. Cayan, and B. L. Thrasher, Statistical Downscaling
Using Localized Constructed Analogs (LOCA)*, Journal of Hydrometeorology,
15(6), 2558-2585, 2014.; and Pierce, D. W., D. R. Cayan, E. P. Maurer, J. T.
Abatzoglou, and K. C. Hegewisch, 2015: Improved bias correction techniques
for hydrological simulations of climate change. J. Hydrometeorology, v. 16,
p. 2421-2442. DOI: http://dx.doi.org/10.1175/JHM-D-14-0236.1.
f. for LOCA CMIP5 hydrologic projections:
Vano, J., J. Hamman, E. Gutmann, A. Wood, N. Mizukami, M. Clark, D. W.
Pierce, D. R. Cayan, C. Wobus, K. Nowak, and J. Arnold. (June 2020).
Comparing Downscaled LOCA and BCSD CMIP5 Climate and Hydrology Projections -
Release of Downscaled LOCA CMIP5 Hydrology., available at:
http://gdo-dcp.ucllnl.org/downscaled_cmip_projections/techmemo/LOCA_BCSD_hydrology_tech_memo.pdf
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================================================================================
Requested products directory structure
================================================================================
rgrd3 - 2 degree regridded cmip3 GCM projections
bc3 - 2 degree Bias-Corrected cmip3 GCM projections
bcsd3 - 1/8 degree bias-corrected & downscaled cmip3 GCM projections (monthly)
bcca3 - 1/8 degree bias-corrected & downscaled cmip3 GCM projections (daily)
hydro3 - 1/8 degree VIC hydrology projections based on cmip3 BCSD projections
rgrd5 - 1 degree regridded cmip5 GCM projections
bc5 - 1 degree Bias-Corrected cmip5 GCM projections
bcsd5 - 1/8 degree bias-corrected & downscaled cmip5 GCM projections (monthly)
bcca5 - 1/8 degree bias-corrected & downscaled cmip5 GCM projections (daily)
hydro5 - 1/8 degree VIC hydrology projections based on cmip5 BCSD projections
loca5 - 1/16 degree bias-corrected & downscaled cmip5 GCM projections (daily)
loca_hydro5 - 1/16 degree VIC hydrology projections based on cmip5 LOCA projections
loca5_1x1 - 1 degree bias-corrected & downscaled cmip5 GCM projections (daily)
These are bias-corrected on the native GCM grid, then downscaled
with the LOCA method to 1 degree
1_8obs - 1/8 degree observed (Maurer 2002) data
1obs - 1 degree regridded observed (Maurer 2002) data
2obs - 2 degree regridded observed (Maurer 2002) data
1_16obs - 1/16 degree observed (Livneh 2015) data
hydro_obs5 - 1/8 VIC hydrology results based on Maurer, 2002 observed data
loca_hydro_obs5 - 1/16 VIC hydrology results based on Livneh, 2015 observed data
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For NetCDF data requests (*.nc)
================================================================================
The netcdf header contains infomation about data attributes.
Extracted Data Series files
---------------------------
Extraction_<variable(s)>.nc, where
variable(s) = Prcp, Tavg, or TavgPrcp
Statistics files
----------------
PeriodStats.nc
SpatialStats.nc
Projections Order key file (associated with run axis in the .nc file)
---------------------------------------------------------------------
Projections3.txt - cmip3 projections
Projections5.txt - cmip5 projections
================================================================================
For ASCII comma-delimited (csv) data requests (*.csv)
================================================================================
Extracted Data Series files
---------------------------
<scenario.model.run>.<variable>.csv
where,
Variables:
# BCSD archive - monthly data
Tavg - Average Surface Air Temperature (deg C)
Prcp - Average Precipitation Rate (mm/day)
# BCCA archive - daily data
pr - Precipitation Rate (mm/day)
tasmin - Minimum Surface Air Temperature (deg C)
tasmax - Maximum Surface Air Temperature (deg C)
# LOCA archive - daily data
pr - Precipitation Rate (mm/day) kg m-2 s-1 in archive files,
converted to mm/day in 'Subset Request' interface
tasmin - Minimum Surface Air Temperature (deg C) deg K in archive files,
converted to deg C in 'Subset Request' interface
tasmax - Maximum Surface Air Temperature (deg C) deg K in archive files,
converted to deg C in 'Subset Request' interface
# Hyrdology archive - monthly data
prcp - Total monthly precipitation (mm)
tmax - mean monthly maximum daily temperature (deg C)
tmin - mean monthly minimum daily temperature (deg C)
wind - mean monthly wind speed (m/s)
smc - soil moisture content, state 1st day of month (mm)
swe - snow water equivalent in snow pack, state 1st day of month (mm)
streamflow - surface runoff + baseflow (mm)
et - actual ET (mm)
petnatveg - natural vegetaion PET (mm)
petwater - open water surface PET (mm)
pettall - tall reference crop PET (mm)
petshort - short reference crop PET (mm)
# LOCA Hydrology archive - daily data
precip - Precipitation (mm/day)
rainfall - Rainfall Rate (mm/day)
Tair - Average Air Temperature (deg C)
windspeed - Wind Speed (m/s)
soilMoist1 - Soil Moisture (layer 1) (mm)
soilMoist2 - Soil Moisture (layer 2) (mm)
soilMoist3 - Soil Moisture (layer 3) (mm)
SWE - Snow Water Equivalent (mm)
del_SWE - Change in SWE (mm/day)
baseflow - Baseflow (mm/day)
runoff - Runoff (mm/day)
ET - Evapotranspiration - Actual (mm/day)
pet_natveg - Evapotranspiration - Potential, natural veg (mm/day)
Qair - Absolute Humidity (kg/kg)
relHumid - Relative Humidity (percent)
wdew - Dew Accumulation (mm/day)
albedo - Albedo (fraction)
latent - Latent Heat Flux (W/m**2)
longwave_net - Longwave Net Heat Flux (W/m**2)
sensible - Sensible Heat Flux (W/m**2)
shortwave_in - Shortwave Down Heat Flux (W/m**2)
net_shortwave - Shortwave Net Heat Flux (W/m**2)
snow_melt - Snow Melt Rate (mm/day)
snowfall - Snowfall Rate (mm/day)
sublimation_net - Sublimation (mm/day)
# Row/Column information
ASCII table rows and columns depend on data request:
-- time (rows) x run (columns)
-- time (rows) x latitude (columns)
-- time (rows) x longitude (columns)
-- run (rows) x latitude (columns)
-- run (rows) x longitude (columns)
-- latitude (rows) x longitude (columns)
ROWS_Tavg.txt - time, latitude, or longitude
COLS_Tavg.txt - run, latitude, or longitude
ROWS_Prcp.txt - time, latitude, or longitude
COLS_Prcp.txt - run, latitude, or longitude
Statistics files
----------------
<variable>_<statistic_type>_<statistic>.csv
where,
variable:
same as Variable list above
statistic type =
SpatialStat, or...
PeriodStat
statistic:
stdev - standard deviation
mean - grid-cell-area-weighted mean
File Metadata
-------------
Info_<statistic_type>.txt
where,
statistic_type = PeriodStat or SpatialStat
Row/Column information
----------------------
ROWS_PeriodStat.txt - projection or latitude
COLS_PeriodStat.txt - projection or longitude
ROWS_SpatialStat.txt - time, days from 1950-1-1
COLS_SpatialStat.txt - projection, <scenario.model.run>