Mean State

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Period Mean [mm d-1]
Bias [mm d-1]
Bias Score [1]
Spatial Distribution Score [1]
Interannual Variability Score [1]
Overall Score [1]
Benchmark [-] 0.825
CAM6CLM50SP [-] 1.12 0.290 0.760 0.914 0.564 0.746
CAM6CTSM51SP [-] 1.12 0.292 0.767 0.918 0.550 0.745

Temporally integrated period mean

BENCHMARK MEAN
Data not available
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MODEL MEAN
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BIAS
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SPATIAL TAYLOR DIAGRAM
Data not available
MODEL COLORS
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Spatially integrated regional mean

MODEL COLORS
Data not available
amazon
Data not available
ob
Data not available
lena
Data not available
yenisey
Data not available
mississippi
Data not available
congo
Data not available
mackenzie
Data not available
parana
Data not available
nile
Data not available
amur
Data not available
niger
Data not available
changjiang
Data not available
yukon
Data not available
nelson
Data not available
stlawrence
Data not available
kolyma
Data not available
murray
Data not available
danube
Data not available
indus
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orange
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ganges
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columbia
Data not available
huanghe
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indigirka
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orinoco
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tocantins
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mekong
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severnayadvina
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dnepr
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colorado
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pechora
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brahmaputra
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riogrande
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coruripe
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don
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olenek
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yana
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churchill
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xijiang
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senegal
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irrawaddy
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volta
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fraser
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taz
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rhine
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vistula
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parnaiba
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huai
Data not available
liao
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kuskokwim
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All Models

Benchmark
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CAM6CLM50SP
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CAM6CTSM51SP
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Data Information

  Title:
derived GRDC Aiguo Runoff Dataset

  Source_file:
This product is generated from yearly GRDC_Aiguo observations

  Conventions:
Please contact Prof. James Randerson (Email: jranders@uci.edu) or Dr. Mingquan Mu (mmu@uci.edu) for any question

  Altitude:

  Site_name:
Amazon,Ob,Lena,Yenisey,Mississippi,Congo,Mackenzie,Parana,Nile,Amur,Niger (Issa Ber,Changjiang,Yukon,Nelson,St Lawrence,Kolyma,Murray,Danube,Indus,Orange (Senqu),Ganges (Ganga),Columbia,Huanghe,Indigirka,Orinoco,Tocantins,Mekong,Severnaya Dvina,Dnepr,Colorado-AR,Pechora,Brahmaputra,Rio Grande (Bra,Coruripe,Don,Olenek,Yana,Churchill,Xijiang,Senegal,Irrawaddy (Ayey,Volta,Fraser,Taz,Rhine,Vistula (Wisla),Parnaiba,Huai,Liao,Kuskokwim

  Creation_date:
Thu Apr 14 00:21:01 PDT 2016

  Approach:
I read the variable (FLOW) from the original data file, then pick up top 50 global largest rivers based on TRIP riverbasins. I also converted river flow from river gauge stations to river mouthes by using ratio of volume between river mouth and station (ratio_m2s), then I converted the unit from m3/s to Kg/m2/s by using drainage area at river mouth (area_mou), finally I saveed the data in NetCDF format by each month and each year.

  Temporal resolution:
monthly

  General information:
This product was derived from global 925 rivers gauge observations from Dai and Trenberth (2002).

  Spatial resolution:
river gauge observation

  Derived data code:
http://redwood.ess.uci.edu/mingquan/www/ILAMB/Download/CODES/CODES/subroutines/convert/convert-riverbasin-TRIP+runoff.ncl