NERC Data Catalogue Service
NERC Data Catalogue Service (Natural Environment Research Council)
Continents, countries, sea regions of the world.
https://catalogue.ceda.ac.uk/uuid/f3d6b37e91304c4a89f4014d6f9e1f47 f3d6b37e91304c4a89f4014d6f9e1f47 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.3hr.clt.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.pr.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.3hr.hfls.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.3hr.hfss.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.3hr.huss.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.3hr.pr.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.3hr.ps.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.3hr.rlds.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.3hr.rldscs.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.3hr.rlus.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.3hr.rsds.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.3hr.rsdscs.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.3hr.rsus.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.3hr.rsuscs.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.3hr.tas.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.3hr.tos.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.6hrLev.hus.gn.v20190128.v20190128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.6hrLev.ps.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.6hrLev.ta.gn.v20181204.v20181204 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.6hrLev.ua.gn.v20181204.v20181204 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.6hrLev.va.gn.v20181204.v20181204 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.6hrPlevPt.psl.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.6hrPlevPt.ta.gn.v20181129.v20181129 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.6hrPlevPt.ua.gn.v20181129.v20181129 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.6hrPlevPt.va.gn.v20181129.v20181129 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.ccb.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.cct.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.ch4.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.ci.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.cl.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.cli.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.clivi.gn.v20190311.v20190311 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.clt.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.clw.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.clwvi.gn.v20190311.v20190311 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.co2.gn.v20181221.v20181221 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.evspsbl.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.fco2antt.gn.v20181213.v20181213 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.fco2fos.gn.v20181213.v20181213 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.fco2nat.gn.v20181213.v20181213 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.hfls.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.hfss.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.hur.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.hurs.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.hus.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.huss.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.mc.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.n2o.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.o3.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.pr.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.prc.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.prsn.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.prw.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.ps.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.psl.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.rlds.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.rldscs.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.rlus.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.rlut.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.rlutcs.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.rsds.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.rsdscs.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.rsdt.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.rsus.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.rsuscs.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.rsut.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.rsutcs.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.rtmt.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.sci.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.sfcWind.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.ta.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.tas.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.tasmax.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.tasmin.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.tauu.gn.v20190403.v20190403 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.tauv.gn.v20190403.v20190403 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.ts.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.ua.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.uas.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.va.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.vas.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.wap.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Amon.zg.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.E3hr.gpp.gn.v20181220.v20181220 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.E3hr.ra.gn.v20181220.v20181220 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.E3hr.rh.gn.v20181220.v20181220 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Emon.cSoil.gn.v20181115.v20181115 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.LImon.snc.gn.v20181114.v20181114 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.LImon.snw.gn.v20181114.v20181114 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Lmon.cLeaf.gn.v20181114.v20181114 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Lmon.cLitterAbove.gn.v20181114.v20181114 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Lmon.cLitterBelow.gn.v20181114.v20181114 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Lmon.cRoot.gn.v20181114.v20181114 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Lmon.cSoilFast.gn.v20181114.v20181114 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Lmon.cSoilMedium.gn.v20181114.v20181114 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Lmon.cSoilSlow.gn.v20181114.v20181114 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Lmon.cVeg.gn.v20181114.v20181114 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Lmon.gpp.gn.v20181114.v20181114 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.day.snc.gn.v20181114.v20181114 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Lmon.lai.gn.v20181114.v20181114 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Lmon.mrro.gn.v20181114.v20181114 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Lmon.mrso.gn.v20181114.v20181114 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Lmon.mrsos.gn.v20181114.v20181114 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Lmon.ra.gn.v20181114.v20181114 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Lmon.rh.gn.v20181114.v20181114 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Lmon.tsl.gn.v20181114.v20181114 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Oday.tos.gn.v20181211.v20181211 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Omon.fgco2.gn.v20181211.v20181211 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Omon.masscello.gn.v20181211.v20181211 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Omon.masso.gn.v20181211.v20181211 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Omon.mlotst.gn.v20181211.v20181211 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Omon.so.gn.v20181211.v20181211 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Omon.sos.gn.v20181211.v20181211 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Omon.thetao.gn.v20181211.v20181211 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Omon.thkcello.gn.v20181211.v20181211 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Omon.tos.gn.v20181211.v20181211 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Omon.uo.gn.v20181211.v20181211 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Omon.vo.gn.v20181211.v20181211 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Omon.volo.gn.v20181211.v20181211 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Omon.zos.gn.v20181211.v20181211 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.Omon.zostoga.gn.v20181211.v20181211 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.SIday.siconc.gn.v20181211.v20181211 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.SImon.simass.gn.v20181211.v20181211 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.day.clt.gn.v20181129.v20181129 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.day.hfls.gn.v20181129.v20181129 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.day.hfss.gn.v20181129.v20181129 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.day.hus.gn.v20181129.v20181129 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.day.huss.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.day.mrro.gn.v20190222.v20190222 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.day.mrso.gn.v20181226.v20181226 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.day.mrsos.gn.v20181226.v20181226 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.day.pr.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.day.psl.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.day.rlds.gn.v20181129.v20181129 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.day.rlus.gn.v20181129.v20181129 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.day.rlut.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.day.rsds.gn.v20181129.v20181129 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.day.rsus.gn.v20181129.v20181129 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.day.sfcWind.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.day.snw.gn.v20181114.v20181114 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.day.ta.gn.v20181129.v20181129 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.day.tas.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.day.tasmax.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.day.tasmin.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.day.ua.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.day.va.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r1i1p1f1.day.zg.gn.v20181129.v20181129 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.ccb.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.cct.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.ch4.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.ci.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.cl.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.cli.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.clivi.gn.v20190311.v20190311 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.clt.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.clw.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.clwvi.gn.v20190311.v20190311 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.co2.gn.v20181221.v20181221 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.evspsbl.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.fco2antt.gn.v20181213.v20181213 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.fco2fos.gn.v20181213.v20181213 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.fco2nat.gn.v20181213.v20181213 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.hfls.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.hfss.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.hur.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.hurs.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.hus.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.huss.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.mc.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.n2o.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.o3.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.pr.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.prc.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.prsn.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.prw.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.ps.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.psl.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.rlds.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.rldscs.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.rlus.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.rlut.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.rlutcs.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.rsds.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.rsdscs.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.rsdt.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.rsus.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.rsuscs.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.rsut.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.rsutcs.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.rtmt.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.sci.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.sfcWind.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.ta.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.tas.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.tasmax.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.tasmin.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.tauu.gn.v20190403.v20190403 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.tauv.gn.v20190403.v20190403 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.ts.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.ua.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.uas.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.va.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.vas.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.wap.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Amon.zg.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Emon.cSoil.gn.v20181116.v20181116 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.LImon.snc.gn.v20181116.v20181116 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.LImon.snw.gn.v20181116.v20181116 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Lmon.cLeaf.gn.v20190201.v20190201 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Lmon.cLitterAbove.gn.v20190201.v20190201 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Lmon.cLitterBelow.gn.v20190201.v20190201 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Lmon.cRoot.gn.v20190201.v20190201 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Lmon.cSoilFast.gn.v20190201.v20190201 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Lmon.cSoilMedium.gn.v20190201.v20190201 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Lmon.cSoilSlow.gn.v20190201.v20190201 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Lmon.cVeg.gn.v20190201.v20190201 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Lmon.gpp.gn.v20190201.v20190201 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Lmon.lai.gn.v20190201.v20190201 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Lmon.mrro.gn.v20190201.v20190201 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Lmon.mrso.gn.v20190201.v20190201 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Lmon.mrsos.gn.v20190201.v20190201 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Lmon.ra.gn.v20190201.v20190201 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Lmon.rh.gn.v20190201.v20190201 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Lmon.tsl.gn.v20181116.v20181116 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Oday.tos.gn.v20181211.v20181211 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Omon.fgco2.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Omon.masscello.gn.v20181217.v20181217 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Omon.masso.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Omon.mlotst.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Omon.so.gn.v20181217.v20181217 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Omon.sos.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Omon.thetao.gn.v20181217.v20181217 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Omon.thkcello.gn.v20181217.v20181217 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Omon.tos.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Omon.uo.gn.v20181217.v20181217 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Omon.vo.gn.v20181217.v20181217 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Omon.volo.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Omon.zos.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.Omon.zostoga.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.SIday.siconc.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.SImon.simass.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.day.huss.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.day.mrro.gn.v20190222.v20190222 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.day.mrso.gn.v20181226.v20181226 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.day.mrsos.gn.v20181226.v20181226 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.day.pr.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.day.psl.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.day.rlut.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.day.snc.gn.v20190222.v20190222 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.day.snw.gn.v20190222.v20190222 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.day.tas.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.day.tasmax.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.day.tasmin.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.day.ua.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r2i1p1f1.day.va.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.ccb.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.cct.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.ch4.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.ci.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.cl.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.cli.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.clivi.gn.v20190311.v20190311 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.clt.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.clw.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.clwvi.gn.v20190311.v20190311 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.co2.gn.v20181221.v20181221 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.evspsbl.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.fco2antt.gn.v20181213.v20181213 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.fco2fos.gn.v20181213.v20181213 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.fco2nat.gn.v20181213.v20181213 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.hfls.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.hfss.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.hur.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.hurs.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.hus.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.huss.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.mc.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.n2o.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.o3.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.prc.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.prsn.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.prw.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.ps.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.psl.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.rlds.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.rldscs.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.rlus.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.rlut.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.rlutcs.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.rsds.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.rsdscs.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.rsdt.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.rsus.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.rsuscs.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.rsut.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.rsutcs.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.rtmt.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.sci.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.sfcWind.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.ta.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.tas.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.tasmax.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.tasmin.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.tauu.gn.v20190403.v20190403 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.tauv.gn.v20190403.v20190403 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.ts.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.ua.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.uas.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.va.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.vas.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.wap.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Amon.zg.gn.v20181122.v20181122 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Emon.cSoil.gn.v20181116.v20181116 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.LImon.snc.gn.v20181116.v20181116 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.LImon.snw.gn.v20181116.v20181116 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Lmon.cLeaf.gn.v20190201.v20190201 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Lmon.cLitterAbove.gn.v20190201.v20190201 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Lmon.cLitterBelow.gn.v20190201.v20190201 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Lmon.cRoot.gn.v20190201.v20190201 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Lmon.cSoilFast.gn.v20190201.v20190201 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Lmon.cSoilMedium.gn.v20190201.v20190201 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Lmon.cSoilSlow.gn.v20190201.v20190201 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Lmon.cVeg.gn.v20190201.v20190201 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Lmon.gpp.gn.v20190201.v20190201 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Lmon.lai.gn.v20190201.v20190201 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Lmon.mrro.gn.v20190201.v20190201 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Lmon.mrso.gn.v20190201.v20190201 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Lmon.mrsos.gn.v20190201.v20190201 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Lmon.ra.gn.v20190201.v20190201 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Lmon.rh.gn.v20190201.v20190201 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Lmon.tsl.gn.v20181116.v20181116 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Oday.tos.gn.v20181217.v20181217 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Omon.fgco2.gn.v20181217.v20181217 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Omon.masscello.gn.v20181217.v20181217 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Omon.masso.gn.v20181217.v20181217 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Omon.mlotst.gn.v20181217.v20181217 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Omon.so.gn.v20181217.v20181217 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Omon.sos.gn.v20181217.v20181217 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Omon.thetao.gn.v20181217.v20181217 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Omon.thkcello.gn.v20181217.v20181217 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Omon.tos.gn.v20181217.v20181217 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Omon.uo.gn.v20181217.v20181217 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Omon.vo.gn.v20181217.v20181217 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Omon.volo.gn.v20181217.v20181217 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Omon.zos.gn.v20181217.v20181217 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.Omon.zostoga.gn.v20181217.v20181217 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.SIday.siconc.gn.v20181129.v20181129 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.SImon.simass.gn.v20181129.v20181129 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.day.huss.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.day.mrro.gn.v20190222.v20190222 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.day.mrso.gn.v20181226.v20181226 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.day.mrsos.gn.v20181226.v20181226 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.day.pr.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.day.psl.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.day.rlut.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.day.snc.gn.v20190222.v20190222 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.day.snw.gn.v20190222.v20190222 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.day.tas.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.day.tasmax.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.day.tasmin.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.day.ua.gn.v20181128.v20181128 CMIP6.CMIP.BCC.BCC-CSM2-MR.esm-hist.r3i1p1f1.day.va.gn.v20181128.v20181128
WCRP CMIP6: Beijing Climate Center (BCC) BCC-CSM2-MR model output for the "esm-hist" experiment
The World Climate Research Program (WCRP) Coupled Model Intercomparison Project, Phase 6 (CMIP6) data from the Beijing Climate Center (BCC) BCC-CSM2-MR model output for the "all-forcing simulation of the recent past with atmospheric CO2 concentration calculated" (esm-hist) experiment. These are available at the following frequencies: 3hr, 6hrLev, 6hrPlevPt, Amon, E3hr, Emon, LImon, Lmon, Oday, Omon, SIday, SImon and day. The runs included the ensemble members: r1i1p1f1, r2i1p1f1 and r3i1p1f1. CMIP6 was a global climate model intercomparison project, coordinated by PCMDI (Program For Climate Model Diagnosis and Intercomparison) on behalf of the WCRP and provided input for the Intergovernmental Panel on Climate Change (IPCC) 6th Assessment Report (AR6). The official CMIP6 Citation, and its associated DOI, is provided as an online resource linked to this record.
Public data: access to these data is available to both registered and non-registered users.
Under the following licence https://artefacts.ceda.ac.uk/licences/specific_licences/CMIP6_Terms_of_Use.pdf, appropriate use of these data may fall under unclassified use. This message is intended as guidance, always read the full licence. When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record.
Data were produced and verified by Beijing Climate Center (BCC) scientists before publication via the Earth Systems Grid Federation (ESGF) and a copy obtained by the Centre for Environmental Data Analysis (CEDA).
https://catalogue.ceda.ac.uk/uuid/73bdbc2013b80c66062a57ca1ec4e5c7 73bdbc2013b80c66062a57ca1ec4e5c7
Total Ozone Mapping Spectrometer (TOMS) measurements from Earth Probe (1996-2005)
The Total Ozone Mapping Spectrometer (TOMS) is an instrument built and operated by the National Aeronautics and Space Administration (NASA). The instrument uses backscattered ultraviolet radiance to infer total column ozone measurements. The dataset consists of daily gridded averages of total ozone covering the entire globe, in the form of images, from NASA NIMBUS 7, Meteor-3, Earth Probe and ADEOS satellites. Data is from 1978 to 2006. The Ozone Monitoring Instrument (OMI) on the AURA spacecraft, OMI data of ozone are now available for the entire OMI mission. In addition to ozone data, OMI data for aerosol and reflectivity are available. These datasets are public.
Under the following licence http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/, appropriate use of these data may fall under any use. This message is intended as guidance, always read the full licence. When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record.
Total Ozone Mapping Spectrometer (TOMS) data were mirrored from GSFC NASA until saturday December 2, 2006, when contact with Earth Probe was lost. Ozone Monitoring Instrument (OMI) data are continuously being mirrored at the BADC from NASA (since 2004).
https://catalogue.ceda.ac.uk/uuid/835e1ee64daf5c1496d21dde141964ce 835e1ee64daf5c1496d21dde141964ce
Data from the Photographic Camera, CASI and ATM AZ-16 Instruments on-board the Piper PA31 Navajo Chieftain G-NERC Aircraft during Flight 00/22 over the New Forest Area
The Airborne Research & Survey Facility (ARSF, formerly Airborne Remote Sensing Facility) is managed by NERC Scientific Services and Programme Management. It provides the UK environmental science community, and other potential users, with the means to obtain remotely-sensed data in support of research, survey and monitoring programmes. The ARSF is a unique service providing environmental researchers, engineers and surveyors with synoptic analogue and digital imagery of high spatial and spectral resolution.The NEODC holds the entire archive of Airborne Thematic Mapper (ATM) and Compact Airborne Spectrographic Imager (CASI) data acquired by the NERC ARSF. High-resolution scanned digital versions of the entire collection of analogue photographs are now also available as well as selected LiDAR-derived elevation and terrain models for selected sites flown using the sensor.
Access to these data is available to any registered CEDA user. Please Login or Register for a CEDA account to gain access.
Data have been provided to NEODC via a number of routes: Most data up to 2005 was provided directly from ARSF flight team (ARSF-Ops) or Andrew Wilson at CEH, on various media. Data since 2008 was mostly transferred to NEODC from ARSF-Data Analysis Node (DAN) in Plymouth via rsync. Data for 2006 - 2008 were provided partly from ARSF-DAN, partly from ARSF-Ops, and some from Andrew Wilson. Data from the ULM LiDAR instrument was provided, via FTP or on media, from ULM Cambridge. Scanned aerial photographs were provided by Bluesky Ltd, who carried out the digitisation, on LaCiE disks. Some data ("user_provided") was sent to NEODC by ARSF data users.
Chapter 3 of the Working Group I Contribution to the IPCC Sixth Assessment Report - data for Figure 3.34 (v20220104)
Data for Figure 3.34 from Chapter 3 of the Working Group I (WGI) Contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Figure 3.34 shows attribution of observed seasonal trends in the annular modes to forcings. --------------------------------------------------- How to cite this dataset --------------------------------------------------- When citing this dataset, please include both the data citation below (under 'Citable as') and the following citation for the report component from which the figure originates: Eyring, V., N.P. Gillett, K.M. Achuta Rao, R. Barimalala, M. Barreiro Parrillo, N. Bellouin, C. Cassou, P.J. Durack, Y. Kosaka, S. McGregor, S. Min, O. Morgenstern, and Y. Sun, 2021: Human Influence on the Climate System. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Masson-Delmotte, V., P. Zhai, A. Pirani, S.L. Connors, C. Péan, S. Berger, N. Caud, Y. Chen, L. Goldfarb, M.I. Gomis, M. Huang, K. Leitzell, E. Lonnoy, J.B.R. Matthews, T.K. Maycock, T. Waterfield, O. Yelekçi, R. Yu, and B. Zhou (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 423–552, doi:10.1017/9781009157896.005. --------------------------------------------------- Figure subpanels --------------------------------------------------- The figure has 3 panels, and all the data are provided in a single file named NAM_SAM_detection_attribution.nc. --------------------------------------------------- List of data provided --------------------------------------------------- This dataset contains - Observed and simulated DJF NAM trends for 1958-2019 - Observed and simulated JJA NAM trends for 1958-2019 - Observed and simulated DJF SAM trends for 1979-2019 - Observed and simulated JJA SAM trends for 1979-2019 - Observed and simulated DJF SAM trends for 2000-2019 - Observed and simulated JJA SAM trends for 2000-2019 Simulations are from CMIP6 historical, hist-GHG, hist-aer, hist-nat, and hist-stratO3 simulations, and from equivalent time segments from CMIP6 piControl simulations (one segment from one model). NAM: Northern Annular Mode ​​​ SAM: Southern Annular Mode GHG: greenhouse gas JJA: June, July, August DJF: December, January, February --------------------------------------------------- Data provided in relation to figure --------------------------------------------------- Panel a: - NAM_obs_DJF_1958_2019: grey horizontal lines in the left -->ERA5: obs_dataset = 0\n -->JRA-55: obs_dataset = 1\n - NAM_piControl_DJF_62yrs: multimodel ensemble mean and percentiles for blue open box-whisker in the left - NAM_hist_DJF_1958_2019: multimodel ensemble mean and percentiles for red open box-whisker in the left, and multimodel ensemble mean and confidence interval for red filled box, with ensemble means of individual models for black dots, in the left - NAM_GHG_DJF_1958_2019: multimodel ensemble mean and confidence interval for brown filled box, with ensemble means of individual models for black dots, in the left - NAM_aer_DJF_1958_2019: multimodel ensemble mean and confidence interval for light blue filled box, with ensemble means of individual models for black dots, in the left - NAM_stratO3_DJF_1958_2019: multimodel ensemble mean and confidence interval for purple filled box, with ensemble means of individual models for black dots, in the left - NAM_nat_DJF_1958_2019: multimodel ensemble mean and confidence interval for green filled box, with ensemble means of individual models for black dots, in the left - NAM_obs_JJA_1958_2019: grey horizontal lines in the right -->ERA5: obs_dataset = 0\n -->JRA-55: obs_dataset = 1\n - NAM_piControl_JJA_62yrs: multimodel ensemble mean and percentiles for blue open box-whisker in the right - NAM_hist_JJA_1958_2019: multimodel ensemble mean and percentiles for red open box-whisker in the right, and multimodel ensemble mean and confidence interval for red filled box, with ensemble means of individual models for black dots, in the right - NAM_GHG_JJA_1958_2019: multimodel ensemble mean and confidence interval for brown filled box, with ensemble means of individual models for black dots, in the right - NAM_aer_JJA_1958_2019: multimodel ensemble mean and confidence interval for light blue filled box, with ensemble means of individual models for black dots, in the right - NAM_stratO3_JJA_1958_2019: multimodel ensemble mean and confidence interval for purple filled box, with ensemble means of individual models for black dots, in the right - NAM_nat_JJA_1958_2019: multimodel ensemble mean and confidence interval for green filled box, with ensemble means of individual models for black dots, in the right Panel b: - SAM_obs_DJF_1979_2019: grey horizontal lines in the left -->ERA5: obs_dataset = 0\n -->JRA-55: obs_dataset = 1\n - SAM_piControl_DJF_41yrs: multimodel ensemble mean and percentiles for blue open box-whisker in the left - SAM_hist_DJF_1979_2019: multimodel ensemble mean and percentiles for red open box-whisker in the left, and multimodel ensemble mean and confidence interval for red filled box, with ensemble means of individual models for black dots, in the left - SAM_GHG_DJF_1979_2019: multimodel ensemble mean and confidence interval for brown filled box, with ensemble means of individual models for black dots, in the left - SAM_aer_DJF_1979_2019: multimodel ensemble mean and confidence interval for light blue filled box, with ensemble means of individual models for black dots, in the left - SAM_stratO3_DJF_1979_2019: multimodel ensemble mean and confidence interval for purple filled box, with ensemble means of individual models for black dots, in the left - SAM_nat_DJF_1979_2019: multimodel ensemble mean and confidence interval for green filled box, with ensemble means of individual models for black dots, in the left - SAM_obs_JJA_1979_2019: grey horizontal lines in the right -->ERA5: obs_dataset = 0\n -->JRA-55: obs_dataset = 1\n - SAM_piControl_JJA_41yrs: multimodel ensemble mean and percentiles for blue open box-whisker in the right - SAM_hist_JJA_1979_2019: multimodel ensemble mean and percentiles for red open box-whisker in the right, and multimodel ensemble mean and confidence interval for red filled box, with ensemble means of individual models for black dots, in the right - SAM_GHG_JJA_1979_2019: multimodel ensemble mean and confidence interval for brown filled box, with ensemble means of individual models for black dots, in the right - SAM_aer_JJA_1979_2019: multimodel ensemble mean and confidence interval for light blue filled box, with ensemble means of individual models for black dots, in the right - SAM_stratO3_JJA_1979_2019: multimodel ensemble mean and confidence interval for purple filled box, with ensemble means of individual models for black dots, in the right - SAM_nat_JJA_1979_2019: multimodel ensemble mean and confidence interval for green filled box, with ensemble means of individual models for black dots, in the right Panel c: - SAM_obs_DJF_2000_2019: grey horizontal lines in the left -->ERA5: obs_dataset = 0\n -->JRA-55: obs_dataset = 1\n - SAM_piControl_DJF_20yrs: multimodel ensemble mean and percentiles for blue open box-whisker in the left - SAM_hist_DJF_2000_2019: multimodel ensemble mean and percentiles for red open box-whisker in the left, and multimodel ensemble mean and confidence interval for red filled box, with ensemble means of individual models for black dots, in the left - SAM_GHG_DJF_2000_2019: multimodel ensemble mean and confidence interval for brown filled box, with ensemble means of individual models for black dots, in the left - SAM_aer_DJF_2000_2019: multimodel ensemble mean and confidence interval for light blue filled box, with ensemble means of individual models for black dots, in the left - SAM_stratO3_DJF_2000_2019: multimodel ensemble mean and confidence interval for purple filled box, with ensemble means of individual models for black dots, in the left - SAM_nat_DJF_2000_2019: multimodel ensemble mean and confidence interval for green filled box, with ensemble means of individual models for black dots, in the left - SAM_obs_JJA_2000_2019: grey horizontal lines in the right -->ERA5: obs_dataset = 0\n -->JRA-55: obs_dataset = 1\n - SAM_piControl_JJA_20yrs: multimodel ensemble mean and percentiles for blue open box-whisker in the right - SAM_hist_JJA_2000_2019: multimodel ensemble mean and percentiles for red open box-whisker in the right, and multimodel ensemble mean and confidence interval for red filled box, with ensemble means of individual models for black dots, in the right - SAM_GHG_JJA_2000_2019: multimodel ensemble mean and confidence interval for brown filled box, with ensemble means of individual models for black dots, in the right - SAM_aer_JJA_2000_2019: multimodel ensemble mean and confidence interval for light blue filled box, with ensemble means of individual models for black dots, in the right - SAM_stratO3_JJA_2000_2019: multimodel ensemble mean and confidence interval for purple filled box, with ensemble means of individual models for black dots, in the right - SAM_nat_JJA_2000_2019: multimodel ensemble mean and confidence interval for green filled box, with ensemble means of individual models for black dots, in the right --------------------------------------------------- Notes on reproducing the figure from the provided data --------------------------------------------------- Multimodel ensemble means, interquartile ranges and 5th and 95th percentiles of historical and hist-* simulations are calculated after weighting individual members with the inverse of the ensemble size of the same model. The weight is given as the weight attribute of each variable. The weighting is not applied to piControl simulations. Filled boxes and black dots are evaluated based on the models with minimum 3 ensemble members. ensemble_assign attribute in each variable provides the model number to which each ensemble member belongs. For the confidence interval, first the ensemble average of individual models (with minimum 3 ensemble members) are calculated and then the confidence interval is evaluated based on t statistic. --------------------------------------------------- Sources of additional information --------------------------------------------------- The following weblinks are provided in the Related Documents section of this catalogue record: - Link to the report component containing the figure (Chapter 3) - Link to the Supplementary Material for Chapter 3, which contains supporting information on the figure in Section and details on the input data used in Table 3.SM.1 - Link to the code for the figure, archived on Zenodo - Link to the figure on the IPCC AR6 website
Northern Hemisphere summer monsoon circulation index
Under the following licence http://creativecommons.org/licenses/by/4.0/, appropriate use of these data may fall under any use. This message is intended as guidance, always read the full licence. When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record.
Data produced by Intergovernmental Panel on Climate Change (IPCC) authors and supplied for archiving at the Centre for Environmental Data Analysis (CEDA) by the Technical Support Unit (TSU) for IPCC Working Group I (WGI). Data curated on behalf of the IPCC Data Distribution Centre (IPCC-DDC).
NCAVEO: NERC Field Spectroscopy Facility (FSF) Fabric Calibration Site Reflectance data collected at Chilbolton using an ASD FieldSpec Pro
This dataset consists of the reflectance spectra which was collected on the 16th-17th June 2006 from three artificial targets deployed at the Chilbolton Facility for Atmospheric and Radio Research (CFARR), as part of the Network for Calibration and Validation of Earth Observation data (NCAVEO) 2006 Field Experiment. The reflectance data were acquired using an ASD FieldSpec Pro fitted with a contact probe. For further details on each of the data files please see the dataset's metadata document in linked documentation.
These data were provided to NEODC by university of Southampton, who carried out work to convert formats to NASA-Ames, and write metadata documents. The metadata documents describing the processing are archived alongside the data as PDF files.
https://catalogue.ceda.ac.uk/uuid/e8cda2b998a447518b2f76231b8bda97 e8cda2b998a447518b2f76231b8bda97 cmip5.output1.MPI-M.MPI-ESM-MR.decadal1980.6hr.atmos.6hrPlev.r1i1p1.v20120608.v20120608 cmip5.output1.MPI-M.MPI-ESM-MR.decadal1980.6hr.atmos.6hrPlev.r2i1p1.v20120608.v20120608 cmip5.output1.MPI-M.MPI-ESM-MR.decadal1980.6hr.atmos.6hrPlev.r3i1p1.v20120608.v20120608 cmip5.output1.MPI-M.MPI-ESM-MR.decadal1980.day.atmos.day.r1i1p1.v20120608.v20120608 cmip5.output1.MPI-M.MPI-ESM-MR.decadal1980.day.atmos.day.r2i1p1.v20120608.v20120608 cmip5.output1.MPI-M.MPI-ESM-MR.decadal1980.day.atmos.day.r3i1p1.v20120608.v20120608 cmip5.output1.MPI-M.MPI-ESM-MR.decadal1980.day.ocean.day.r1i1p1.v20120608.v20120608 cmip5.output1.MPI-M.MPI-ESM-MR.decadal1980.day.ocean.day.r2i1p1.v20120608.v20120608 cmip5.output1.MPI-M.MPI-ESM-MR.decadal1980.day.ocean.day.r3i1p1.v20120608.v20120608 cmip5.output1.MPI-M.MPI-ESM-MR.decadal1980.fx.atmos.fx.r0i0p0.v20120608.v20120608 cmip5.output1.MPI-M.MPI-ESM-MR.decadal1980.fx.land.fx.r0i0p0.v20120608.v20120608 cmip5.output1.MPI-M.MPI-ESM-MR.decadal1980.fx.ocean.fx.r0i0p0.v20120608.v20120608 cmip5.output1.MPI-M.MPI-ESM-MR.decadal1980.mon.atmos.Amon.r1i1p1.v20120608.v20120608 cmip5.output1.MPI-M.MPI-ESM-MR.decadal1980.mon.atmos.Amon.r2i1p1.v20120608.v20120608 cmip5.output1.MPI-M.MPI-ESM-MR.decadal1980.mon.atmos.Amon.r3i1p1.v20120608.v20120608 cmip5.output1.MPI-M.MPI-ESM-MR.decadal1980.mon.land.Lmon.r1i1p1.v20120608.v20120608 cmip5.output1.MPI-M.MPI-ESM-MR.decadal1980.mon.land.Lmon.r2i1p1.v20120608.v20120608 cmip5.output1.MPI-M.MPI-ESM-MR.decadal1980.mon.land.Lmon.r3i1p1.v20120608.v20120608 cmip5.output1.MPI-M.MPI-ESM-MR.decadal1980.mon.landIce.LImon.r1i1p1.v20120608.v20120608 cmip5.output1.MPI-M.MPI-ESM-MR.decadal1980.mon.landIce.LImon.r2i1p1.v20120608.v20120608 cmip5.output1.MPI-M.MPI-ESM-MR.decadal1980.mon.landIce.LImon.r3i1p1.v20120608.v20120608 cmip5.output1.MPI-M.MPI-ESM-MR.decadal1980.mon.ocean.Omon.r1i1p1.v20120608.v20120608 cmip5.output1.MPI-M.MPI-ESM-MR.decadal1980.mon.ocean.Omon.r2i1p1.v20120608.v20120608 cmip5.output1.MPI-M.MPI-ESM-MR.decadal1980.mon.ocean.Omon.r3i1p1.v20120608.v20120608 cmip5.output1.MPI-M.MPI-ESM-MR.decadal1980.mon.seaIce.OImon.r1i1p1.v20120608.v20120608 cmip5.output1.MPI-M.MPI-ESM-MR.decadal1980.mon.seaIce.OImon.r2i1p1.v20120608.v20120608 cmip5.output1.MPI-M.MPI-ESM-MR.decadal1980.mon.seaIce.OImon.r3i1p1.v20120608.v20120608
WCRP CMIP5: Max Planck Institute for Meteorology (MPI-M) MPI-ESM-MR model output for the decadal1980 experiment
WCRP CMIP5: Max Planck Institute for Meteorology (MPI-M) MPI-ESM-MR model output for the 10-year hindcast/prediction initialized in year 1980 (decadal1980) experiment. These data cover the following realms: atmos, land, landIce, ocean and seaIce; at the following frequencies: 6hr, day, fx and mon. The runs included the ensemble members: r0i0p0, r1i1p1, r2i1p1 and r3i1p1. The WCRP Coupled Model Intercomparison Project, Phase 5 (CMIP5), was a global climate model intercomparison project, coordinated by PCMDI (Program For Climate Model Diagnosis and Intercomparison) on behalf of the World Climate Research Program (WCRP) and provided input for the Intergovernmental Panel on Climate Change (IPCC) 5th Assessment Report (AR5).
Under the following licence https://artefacts.ceda.ac.uk/licences/specific_licences/cmip5_open.pdf, appropriate use of these data may fall under any use. This message is intended as guidance, always read the full licence. When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record.
Data were produced and verified by Max Planck Institute for Meteorology (MPI-M) scientists before publication via the Earth Systems Grid Federation (ESGF) and a copy obtained by the Centre for Environmental Data Analysis (CEDA).
https://catalogue.ceda.ac.uk/uuid/61a3d74d7eade3c91a98328ce72388d9 61a3d74d7eade3c91a98328ce72388d9
ACSOE MAGE EAE-96: Ground-based Atmospheric Oxidant Observations from the Mace Head Atmospheric Research Centre
The Atmospheric Chemistry Studies in the Oceanic Environment (ACSOE) was a 5-year Natural Environment Research Council (NERC) programme on tropospheric chemistry coordinated by the University of East Anglia and involving research groups from a number of UK universities and research institutes. The project had three consortia of UK institutes and universities, each of which focused on a different scientific topic. The aims of the Marine Aerosol and Gas Exchange (MAGE) Eastern Atlantic Experiment were to quantify input of Dimethyl sulphide (DMS) into a parcel of air, examine the oxidation of DMS and its reaction with nitrogen species with time, investigate the formation of new particles as a results of these transformations, and to discriminate between natural and anthropogenic fractions of sulphur and nitrogen using isotopic measurements. Data contains profiles of aerosol size and distribution and trace gases throughout the marine boundary layer, taken using the British Aerospace Jetstream aircraft.
Data collected by instruments on Mace Head Atmospheric Research Facility, Ireland. Data acquired by BADC for archiving as programme was underway.
ECMWF ERA-40: daily monthly average reduced N80 Gaussian gridded pressure level analysis data (ggap)
This dataset contains daily monthly average, N80 Gaussian gridded, pressure level, analysis timestep parameters from the European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA) 40 program from September 1957 to August 2002. ERA-40 followed on from the ERA-15 re-analysis project. Access limited to UK based academic researchers only. These data are GRIB formatted.
Under the following licence https://artefacts.ceda.ac.uk/licences/specific_licences/ecmwf-era-products.pdf, appropriate use of these data may fall under any use. This message is intended as guidance, always read the full licence. When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record.
Data were generated by the ERA-40 project at European Centre for Medium-Range Weather Forecasts (ECMWF) and stored within ECMWF's archives. The BADC then obtained a copy from the ECMWF archived and ingested into the BADC archives to aid wider academic use of these data.
https://catalogue.ceda.ac.uk/uuid/7f6362108ef44ab3b6d471e890e3ecd9 7f6362108ef44ab3b6d471e890e3ecd9
FAAM B009 Calibration flight, number 8: Airborne atmospheric measurements from core instrument suite on board the BAE-146 aircraft
Airborne atmospheric measurements from core instrument suite data on board the FAAM BAE-146 aircraft during flight 8 for FAAM Test, Calibration, Training and Non-science Flights and other non-specified flight projects.
Data were collected by instrument scientists during the flight before preparation and delivery for archiving at the NCAS British Atmospheric Data Centre.
NEXTMap British Digital Terrain 50m resolution (DTM10) Model Data by Intermap
This dataset consists of the Digital Terrain Model 50m resolution data (DTM10) from the NEXTMap British Digital Terrain Model project produced by Intermap. These data have a spatial resolution of 50m and cover the British Isles.
Restricted data: please submit an application using the REQUEST ACCESS link for access.
Under the following licence https://artefacts.ceda.ac.uk/licences/specific_licences/nextmap_eula.pdf, appropriate use of these data may fall under academic and specific use. This message is intended as guidance, always read the full licence. When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record.
Data were purchased by the Natural Environmental Research Council from Intermap who produced the data. These data were then delivered to the NEODC for curation and to permit NERC funded researchers to access these data centrally.
CMIP6 ES-Doc ensemble member r1i1p1f1 entry for the esm-hist run with BCC-CSM2-MR model.
CMIP6 ES-Doc ensemble member r2i1p1f1 entry for the esm-hist run with BCC-CSM2-MR model.
CMIP6 ES-Doc ensemble member r3i1p1f1 entry for the esm-hist run with BCC-CSM2-MR model.
Detailed experiment description for: "all-forcing simulation of the recent past with atmospheric CO2 concentration calculated" (esm-hist)
Official CMIP6 DOI Citation: Wu, Tongwen; Chu, Min; Dong, Min; Fang, Yongjie; Jie, Weihua; Li, Jianglong; Li, Weiping; Liu, Qianxia; Shi, Xueli; Xin, Xiaoge; Yan, Jinghui; Zhang, Fang; Zhang, Jie; Zhang, Li; Zhang, Yanwu (2018). BCC BCC-CSM2MR model output prepared for CMIP6 CMIP esm-hist. Version YYYYMMDD*.Earth System Grid Federation. https://doi.org/10.22033/ESGF/CMIP6.2901
Earth probe total ozone mapping spectrometer (TOMS): data products user's guide
ORIGIN OF FIGURE (IPCC REPORT CHAPTER): Eyring, V., N.P. Gillett, K.M. Achuta Rao, R. Barimalala, M. Barreiro Parrillo, N. Bellouin, C. Cassou, P.J. Durack, Y. Kosaka, S. McGregor, S. Min, O. Morgenstern, and Y. Sun, 2021: Human Influence on the Climate System. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change
SUPPLEMENTARY MATERIAL FOR REPORT CHAPTER: Eyring, V., N.P. Gillett, K.M. Achuta Rao, R. Barimalala, M. Barreiro Parrillo, N. Bellouin, C. Cassou, P.J. Durack, Y. Kosaka, S. McGregor, S. Min, O. Morgenstern, and Y. Sun: 2021, Human Influence on the Climate System Supplementary Material. In Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change
Complex Citation Object: CMIP6 input data usage information for IPCC WGI AR6 figure 3.34, Zenodo. https://doi.org/10.5281/zenodo.14986385
CMIP5 Metadata Simulation Quality Control Report
CMIP5 File Metadata Quality Control procedure
BADC Doc: ACSOE NASA Ames file format explained
Encoding and decoding GRIB data (GRIBEX)
GDAL - Geospatial Data Abstraction Library website
Centre for Environmental Data Analysis (CEDA)
NCAS British Atmospheric Data Centre (NCAS BADC)
NERC Earth Observation Data Centre (NEODC)
Airborne Research and Survey Facility (ARSF)
NERC EDS Centre for Environmental Data Analysis
Network for Calibration and Validation of EO data (NCAVEO)
Max Planck Institute for Meteorology (MPI-M)
Natural Environment Research Council (NERC)
European Centre for Medium-Range Weather Forecasts (ECMWF)
Facility for Airborne Atmospheric Measurements (FAAM)
MSG: Visible imagery at 1.6 micron over the UKV domain area
The Meteosat Second Generation (MSG) satellites, operated by EUMETSAT (The European Organisation for the Exploitation of Meteorological Satellites), provide almost continuous imagery to meteorologists and researchers in Europe and around the world. These include visible, infra-red, water vapour, High Resolution Visible (HRV) images and derived cloud top height, cloud top temperature, fog, snow detection and volcanic ash products. These images are available for a range of geographical areas. This dataset contains visible images from MSG satellites over the UKV domain area. Imagery available from March 2005 onwards at a frequency of 15 minutes (some are hourly) and are at least 24 hours old. The geographic extent for images within this datasets is available via the linked documentation 'MSG satellite imagery product geographic area details'. Each MSG imagery product area can be referenced from the third and fourth character of the image product name giving in the filename. E.g. for EEAO11 the corresponding geographic details can be found under the entry for area code 'AO' (i.e West Africa).
Under the following licence https://artefacts.ceda.ac.uk/licences/specific_licences/msg.pdf, appropriate use of these data may fall under academic use. This message is intended as guidance, always read the full licence. When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record.
Data obtained by satellite from March 2005, prepared by the Met Office and stored in the BADC archive.
https://catalogue.ceda.ac.uk/uuid/4fee3f23f1ace59f839333a6f7280bf5 4fee3f23f1ace59f839333a6f7280bf5
SOLAS: University of East Anglia LongPath DOAS at Cape Verde Observatory (2009)
The overall aim of the UK Surface Ocean / Lower Atmosphere Study (UK SOLAS) is to advance understanding of environmentally significant interactions between the atmosphere and ocean, focusing on material exchanges that involve ocean productivity, atmospheric composition and climate. The knowledge obtained will improve the predictability of climate change and give insights into the distribution and fate of persistent pollutants. Data from observations made at the The Cape Verde Atmospheric Observatory (16.848N, 24.871W) which exists to advance understanding of climatically significant interactions between the atmosphere and ocean and to provide a regional focal point and long-term data. The observatory is based on Calhau Island of São Vicente, Cape Verde in the tropical Eastern North Atlantic Ocean, a region which is data poor but plays a key role in atmosphere-ocean interactions of climate-related and biogeochemical parameters including greenhouse gases. It is an open-ocean site that is representative of a region likely to be sensitive to future climate change, and is minimally influenced by local effects and intermittent continental pollution. The dataset contains LongPath DOAS measurements.
Data collected at Cape Verde Atmospheric Observatory before being transmitted back to UK where NCAS staff prepare data for archiving at BADC.
https://catalogue.ceda.ac.uk/uuid/fdb0f57040d04ecfa9715ea85c8aba49 fdb0f57040d04ecfa9715ea85c8aba49
FAAM B865 GAUGE flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft
Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for The GAUGE (Greenhouse gAs UK and Global Emissions Project project.
MSG satellite imagery geographic area codes and bounding box information.
Flight summary file for FAAM BAE-146 flight B865
Flight track for FAAM BAE-146 flight B865