![Page 1: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/1.jpg)
LUSciD-LLNL UCSD/SIO Scientific Data Project:
SIO LLNL SDSCTim Barnett Doug Rotman Reagan MooreDavid Pierce Dave Bader Leesa BriegerDan Cayan Ben Santer Amit ChourasiaHugo Hidalgo Peter GlecklerMary Tyree Krishna AcutaRao
Climate Studies
![Page 2: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/2.jpg)
Objective
Can we detect a global warming signal in main hydrological features of the western United States?
![Page 3: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/3.jpg)
Program Elements
Control run: Natural variability CCSM3 from NCAR on Thunder. (approx 4.5 TB)
Downscaling: 12 km grid over west for spatial resolution (control+anthro; another 5 TB)
Hydrological modeling: The downscaled data on rainfall, temperature, terrain, etc. force a hydrological model for time histories of steam flows and snow pack evolution in the western US (control+anthro: another 5 TB).
Detection and attribution (D&A) analysis.
![Page 4: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/4.jpg)
Deliverables
Year 1
Complete a long GCM control run and begin statistical downscaling for selected geographic regions.…..DONE
Begin VIC simulations with both downscaled data and PCM forced realizations.……………………….....…..DONE
Implement a data grid linking resources between LLNL and SDSC. The data grid will be used to manage the simulation output that is generated.………………….…..DONE (1st order)
![Page 5: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/5.jpg)
Deliverables (con’t)
Year 2 Complete downscaling of Control. Complete VIC run on downscaled Control run. Prepare paper on downscaling intercomparisons Begin preliminary D&A analysis. Develop a digital library for publishing results, and integrating
with PCMDI
Year 3 Complete D&A analysis. Write a paper describing the results.
![Page 6: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/6.jpg)
Change in California Snowfall
![Page 7: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/7.jpg)
Change in Snow Water Equivalent
Observed, 1950-2003
Courtesy P. Mote
![Page 8: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/8.jpg)
River flow earlier in the year
![Page 9: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/9.jpg)
Runoff already coming earlier
![Page 10: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/10.jpg)
Projected change by 2050
![Page 11: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/11.jpg)
Key Question
Do the signals we see happen naturally or are they human-induced?
To answer, we need to know the levels and scales of natural variability in the western hydrological cycle.
![Page 12: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/12.jpg)
ACCOMPLISHMENTS:
Year 1
![Page 13: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/13.jpg)
Long GCM control run
CCSM3 with finite volume dynamical core (“-FV”)
Atmospheric resolution is 1.25ox1o with 26 vertical levels
Ocean resolution is 320x384 stretched grid with 40 levels (so-called “gx1v3” grid; averages 1 1/8ox0.5o)
760 years of a long pre-industrial control run transferred to SDSC
![Page 14: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/14.jpg)
CCSM3-FV: Temperature, DJF
![Page 15: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/15.jpg)
CCSM3-FV: Temperature, JJA
![Page 16: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/16.jpg)
CCSM3-FV: Precipitation, DJF
![Page 17: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/17.jpg)
CCSM3-FV: Precipitation, JJA
![Page 18: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/18.jpg)
CCSM3-FV: Precip Variablity, DJF
![Page 19: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/19.jpg)
CCSM3-FV: Precip Variablity, JJA
![Page 20: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/20.jpg)
CCSM3-FV and El Nino
![Page 21: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/21.jpg)
CCSM3-FV and La Nina
![Page 22: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/22.jpg)
Next steps with CCSM3-FV
Dynamical downscaling Provisional plan is to use COAMPS model
First tests underway with 20-yr segment of CCSM3-FV
![Page 23: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/23.jpg)
Statistical downscaling
Uses “analogue” technique: Start with daily CCSM3-FV data on coarse grid, and daily obs.
data on fine grid (Mauer et al. 2002; PRISM data disaggregated to daily level using daily obs)
Coarsen obs to model grid
Compare model field to coarsened obs
30 closest matches (least RMSE) and optimal weights found
Weights applied to obs on original fine grid
Hidalgo et. al 2006, J. Climate, submitted
![Page 24: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/24.jpg)
CCSM3-FV downscaling: Examples
![Page 25: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/25.jpg)
CCSM3-FV downscaling: Precipitation monthly EOFs
![Page 26: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/26.jpg)
CCSM3-FV downscaled: T-max EOFs vs. Obs
![Page 27: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/27.jpg)
Runoff applied to river flow model
![Page 28: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/28.jpg)
Sacramento River at Sacramento
Columbia River at the Dalles
Colorado River at Lees Ferry
![Page 29: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/29.jpg)
Next steps with statistical downscaling
Have processed ~100 yrs of the 760 yrs available
Process rest of CCSM3-FV control run
Evaluate observed changes in hydrology against this estimate of unforced variability
![Page 30: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/30.jpg)
PCM/VIC runs (Andy Wood, UW)
Historical simulations with estimated GHG and sulfate aerosols
4 ensemble members covering 1880-1999
![Page 31: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/31.jpg)
PCM/VIC:Trend in Snow Water Equivalent
![Page 32: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/32.jpg)
PCM/VIC: Trend in T-air
![Page 33: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/33.jpg)
PCM/VIC:River flow
![Page 34: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/34.jpg)
Amit Chourasia, SDSC, for the LUSciD project
![Page 35: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/35.jpg)
PCM/VIC:River flow
Amplitude shows strong decadal variability
Phase shows flow earlier in the year for some, but not all, rivers
![Page 36: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/36.jpg)
Next steps for PCM/VIC
Process other ensemble members to reduce natural internal decadal variability
Is the forced change statistically significant?
How does it compare to observations?
![Page 37: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/37.jpg)
Cooperative project #1:
SIO LLNL
Tim Barnett Krishna AchutaRao
David Pierce Peter Gleckler
Ben Santer
Karl Taylor
Ocean Heat Content
![Page 38: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/38.jpg)
Motivation
Can GHG and sulfate aerosol forcingexplain the warming signal in the world’s
oceans?
YES!
(surprisingly well)
![Page 39: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/39.jpg)
PCM Signal Strength & Noise
![Page 40: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/40.jpg)
Inter-Model Comparison: N. HemPCM signal + HadCM3 noise
![Page 41: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/41.jpg)
What about other models?
38 realizations of 20th century climate from 15 coupled models in the IPCC AR4 archive are being analyzed.
Work in progress
Krishna AchutaRao; David Pierce; Peter Gleckler; Tim Barnett
![Page 42: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/42.jpg)
NCAR CCSM 3.0
MRI CGCM 2.3a
![Page 43: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/43.jpg)
Preliminary findings
Most models show a detectable warming signal in all the ocean basins with some exceptions
NCAR CCSM 3.0 shows large natural variability in the North Atlantic
Details of signal penetration in some ocean basins vary
More complex picture than the previous study (Barnett et al. 2005) that considered two models
Does the fidelity of model heat uptake relate to climate sensitivity?
![Page 44: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/44.jpg)
Note: Plot shows only a subset of the 15 models analyzed.
Heat uptake vs. climate sensitivity
![Page 45: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/45.jpg)
Volcanic Eruptions and Heat Content
P. Gleckler1, K. AchutaRao1, T. Barnett2, D. Pierce2, B.D. Santer1 , K. Taylor1, J. Gregory3, and T. Wigley4
(1PCMDI 2UCSD/SIO, 3U.Reading, 4NCAR)
How do volcanic eruptions affect ocean heat content?
Can this give insight into how ocean heat content anomalies are formed and propagate?
![Page 46: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/46.jpg)
BackgroundH
eat
Conte
nt
(10
22
J) • Volcanic eruptions substantially reduced 20th Century ocean warming and thermal expansion.
• Recovery from Krakatoa (1883) takes decades.
• Effect of Pinatubo is much weaker than Krakatoa because it occurs against backdrop of substantial ocean warming.
• Models including V forcing agree more closely with late 20th Century observations than those without V
• Gleckler et al., Nature, 2006
Krakatoa Pinatubo
Depth
(m
)
Heat Content
Temperature
![Page 47: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/47.jpg)
Cooperative project #2:
SIO LLNL JPL
Tim Barnett Peter Gleckler Eric Fetzer
David Pierce Ben Santer
Atmospheric water vapor
![Page 48: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/48.jpg)
Water vapor a key greenhouse gas
How well do models simulate it?
New 3-D satellite data set available
Compare to AR-4 model fields in PCMDI database
![Page 49: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/49.jpg)
Annual mean: models too moist
![Page 50: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/50.jpg)
Fractional errors greater with height
![Page 51: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/51.jpg)
Summary
Goal: can we detect a global warming signal in main hydrological features of the western United States?
Long CCSM3-FV control run for estimate of natural internal variability is done CCSM3-FV simulation comparable to other NCAR-series models
Statistical downscaling to give river flow is progressing
PCM runs give another estimate of natural varaibility, and also in this case of the forced signal
Other cooperative projects (ocean heat content, atmospheric water vapor) progressing well
![Page 52: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/52.jpg)
![Page 53: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/53.jpg)
Sierra snow pack
Now and ………………….………….future?
![Page 54: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/54.jpg)
Global model (orange dots) vs. Regional model grid
(green dots)
Downscaling: the motivation
![Page 55: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/55.jpg)
CCSM3-FV: Temperature, MAM
![Page 56: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/56.jpg)
CCSM3-FV: Temperature, SON
![Page 57: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/57.jpg)
CCSM3-FV: Precipitation, MAM
![Page 58: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/58.jpg)
CCSM3-FV: Precipitation, SON
![Page 59: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/59.jpg)
CCSM3-FV: Precip Variablity, MAM
![Page 60: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/60.jpg)
CCSM3-FV: Precip Variablity, SON
![Page 61: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/61.jpg)
CCSM3-FV downscaling: T-max monthly EOFs
![Page 62: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/62.jpg)
CCSM3-FV downscaling: T-min monthly EOFs
![Page 63: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/63.jpg)
CCSM3-FV downscaled: Precipitation EOFs vs. Obs
![Page 64: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/64.jpg)
CCSM3-FV downscaled: T-min EOFs vs. Obs
![Page 65: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/65.jpg)
Spectrum of T-max PC#1
Observed M.Y. 240-289 M.Y. 290-339
(x axis is cycles per month)
![Page 66: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/66.jpg)
Spectrum of T-min PC#1
Observed M.Y. 240-289 M.Y. 290-339
(x axis is cycles per month)
![Page 67: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/67.jpg)
HadCM3 Signal Strength & Noise
![Page 68: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/68.jpg)
Seasonal cycle in North Pacific
Blue = 10 yrs of model
Red = 3 yrs of AIRS
![Page 69: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/69.jpg)
Work in progress:Evolution of the Krakatoa anomaly GISS-HYCOM NCAR CCSM3
•6 realizations of CCSM3, GISS-HYCOM (and GFDL2.1)
•Large inter-model differences
• Uncertainties associated with external forcings, model physics and initial conditions
•S/N analysis (in-progress) should help isolate model responses to eruptions - necessary to evaluate realism
Decadal average ocean heat content anomalies: zonally integrated cross-sections
Heat content (1016 Joules/m)
![Page 70: LUSciD-LLNL UCSD/SIO Scientific Data Project:](https://reader036.vdocument.in/reader036/viewer/2022062519/56815321550346895dc14950/html5/thumbnails/70.jpg)
Spectrum of Precipitation PC#1
Observed M.Y. 240-289 M.Y. 290-339
(x axis is cycles per month)