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
BCC-CSM2-MR [-] 1.03 0.202 0.707 0.812 0.485 0.668
BGCv2LND.GSW [-] 0.822 -0.00373 0.787 0.963 0.634 0.794
BGCv2LNDATM [-] 1.08 0.250 0.732 0.931 0.550 0.738
CanESM5 [-] 0.859 0.0338 0.678 0.803 0.521 0.667
GFDL-ESM4 [-] 0.641 -0.185 0.656 0.701 0.590 0.649
MeanCMIP6 [-] 0.879 0.0532 0.782 0.843 0.546 0.724
MIROC-ES2L [-] 0.836 0.0108 0.681 0.763 0.550 0.664

Temporally integrated period mean

BENCHMARK MEAN
Data not available
Data not available
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
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lena
Data not available
yenisey
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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
Data not available
ganges
Data not available
columbia
Data not available
huanghe
Data not available
indigirka
Data not available
orinoco
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tocantins
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mekong
Data not available
severnayadvina
Data not available
dnepr
Data not available
colorado
Data not available
pechora
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brahmaputra
Data not available
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
Data not available
rhine
Data not available
vistula
Data not available
parnaiba
Data not available
huai
Data not available
liao
Data not available
kuskokwim
Data not available

All Models

Benchmark
Data not available
Data not available
BCC-CSM2-MR
Data not available
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BGCv2LND.GSW
Data not available
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BGCv2LNDATM
Data not available
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CanESM5
Data not available
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GFDL-ESM4
Data not available
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MeanCMIP6
Data not available
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MIROC-ES2L
Data not available
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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