Mean State

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Period Mean (original grids) [mm d-1]
Model Period Mean (intersection) [mm d-1]
Benchmark Period Mean (intersection) [mm d-1]
Model Period Mean (complement) [mm d-1]
Benchmark Period Mean (complement) [mm d-1]
Bias [mm d-1]
RMSE [mm d-1]
Phase Shift [months]
Bias Score [1]
RMSE Score [1]
Seasonal Cycle Score [1]
Spatial Distribution Score [1]
Overall Score [1]
Benchmark [-] 0.835
v3.20tr.Emissions01 [-] 0.848 0.843 0.835 0.755 0.918 0.00820 0.930 1.38 0.564 0.459 0.832 0.875 0.638

Temporally integrated period mean

BENCHMARK MEAN
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MODEL MEAN
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BIAS
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BIAS SCORE
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RMSE
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RMSE SCORE
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BENCHMARK MAX MONTH
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MODEL MAX MONTH
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DIFFERENCE IN MAX MONTH
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SEASONAL CYCLE SCORE
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SPATIAL TAYLOR DIAGRAM
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MODEL COLORS
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Spatially integrated regional mean

MODEL COLORS
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REGIONAL MEAN
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ANNUAL CYCLE
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MONTHLY ANOMALY
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All Models

Benchmark
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v3.20tr.Emissions01
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Data Information

  Title:
Linear Optimal Runoff Aggregate v1.0

  Institution:
University of New South Wales

  Source:
total runoff outputs and seven streamflow outputs from tiers 1 and 2 of the eartH2Observe project (ftp://wci.earth2observe.eu/)

  History:
2018-07-12 13:38:28 v1.0

  References:
Hobeichi, Sanaa, 2018: Linear Optimal Runoff Aggregate v1.0 . NCI National Research Data Collection , doi:10.25914/5b612e993d8ea

  Conventions:
CF-1.6, ACDD-1.3

  Summary:
LORA monthly runoff estimates with associated uncertainties derived by optimally combining 11 state-of-the-art gridded runoff products from the eartH2Observe project

  License:
http://creativecommons.org/licenses/by-nc-sa/4.0/

  Id:
http://dx.doi.org/10.25914/5b612e993d8ea

  Product_version:
1.0

  Contact:
s.hobeichi@student.unsw.edu.au

  Organisation:
ARC Centre of Excellence for Climate System Science

  Keywords:
040608 Surfacewater Hydrology

  Date_created:
2018-07-01

  Creator_name:
Sanaa Hobeichi

  Creator_email:
s.hobeichi@student.unsw.edu.au

  Publisher_name:
ARCCSS data manager

  Publisher_email:
paola.petrelli@utas.edu.au

  Time_coverage_start:
1980-01-01

  Time_coverage_end:
1980-12-31

  Geospatial_lat_min:
-90.0

  Geospatial_lat_max:
90.0

  Geospatial_lon_min:
-180.0

  Geospatial_lon_max:
180.0