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
CLM4.5_CRUNCEPv7 [-] 0.581 -0.245 0.72 0.87 0.67 0.75
CLM4.5_GSWP3v1 [-] 0.811 -0.0140 0.80 0.97 0.66 0.81
CLM4_CRUNCEPv7 [-] 0.525 -0.300 0.68 0.68 0.69 0.68
CLM4_GSWP3v1 [-] 0.769 -0.0566 0.81 0.93 0.68 0.81
CLM5_CRUNCEPv7 [-] 0.579 -0.246 0.69 0.80 0.58 0.69
CLM5_GSWP3v1 [-] 0.910 0.0842 0.79 0.97 0.59 0.79

Temporally integrated period mean

BENCHMARK MEAN
Data not available
Data not available
MODEL MEAN
Data not available
Data not available
BIAS
Data not available
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SPATIAL TAYLOR DIAGRAM
Data not available
MODEL COLORS
Data not available

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
Data not available
orange
Data not available
ganges
Data not available
columbia
Data not available
huanghe
Data not available
indigirka
Data not available
orinoco
Data not available
tocantins
Data not available
mekong
Data not available
severnayadvina
Data not available
dnepr
Data not available
colorado
Data not available
pechora
Data not available
brahmaputra
Data not available
riogrande
Data not available
coruripe
Data not available
don
Data not available
olenek
Data not available
yana
Data not available
churchill
Data not available
xijiang
Data not available
senegal
Data not available
irrawaddy
Data not available
volta
Data not available
fraser
Data not available
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
CLM4.5_CRUNCEPv7
Data not available
Data not available
CLM4.5_GSWP3v1
Data not available
Data not available
CLM4_CRUNCEPv7
Data not available
Data not available
CLM4_GSWP3v1
Data not available
Data not available
CLM5_CRUNCEPv7
Data not available
Data not available
CLM5_GSWP3v1
Data not available
Data not available

Data Information

  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

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

  source_file: This product is generated from yearly GRDC_Aiguo observations

  title: derived GRDC Aiguo Runoff Dataset

  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