Mean State

Temporally integrated period mean

BENCHMARK MEAN
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MODEL MEAN
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BIAS
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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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Site Plots

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All Models

Benchmark
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CLM40r243CRUNCEP
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CLM40r243GSWP3
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CLM40SPr253GSWP3
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CLM45r243CRUNCEP
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CLM45r243GSWP3
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CLM45SPr253GSWP3
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CLM50r243CRUNCEP
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CLM50r243GSWP3
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CLM50SPr243CRUNCEP
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CLM50SPr243GSWP3
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Data Information

  _NCProperties: version=1|netcdflibversion=4.4.1|hdf5libversion=1.8.17

  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