Post on 13-Jan-2016
description
Coordinated Enhanced Observing Period (CEOP)
CEOP HP : http://www.ceop.net
EOP-1EOP-2
EOP-3EOP-4
CAMP Reference Site
Data checking
CDC Server
Reference Site
Database
Data Plotting
CDA
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Point out Error & Noise
Updated DatabaseUpdated Data
CAMP Data Center(CDC)CAMP Data Center(CDC)
Document
Unified Format
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Open Category 1 after 6 months Category 2 after 15 months
composite
CAMP Reference Site
Considering the launching Schedule of the New Satellites
1997 1998 1999 2000 2001 2002 2003 2004 2005
TRMM Terra
ENVISAT Aqua
ADEOS-II
Considering the launching Schedule of the New Satellites
1997 1998 1999 2000 2001 2002 2003 2004 2005
TRMM Terra
ENVISAT Aqua
UNFORTUNATELY
Three types model outputs are offered by NWPCs
Model Output Location Time Series (MOLTS) at the reference sites: high temporal resolution time-series output
Gridded Output from operational global and regional prediction models
Output from global and regional reanalysis
Eight Numerical Weather Prediction Centers (NWPCs), NCEP, UKMO, ECMWF, JMA, CPTEC, BoM, ICMWF, ECPC, and two Data Assimilation Center, NASA/GMAO, NASA/GSFC provide model outputs to CEOP, and CEOP offers a globally consistent data sets for model validation and calibration.
The First Global Integrated Data Sets of the Water Cycle
CEOP EOP-1 Dataset tableCEOP EOP-1 Dataset table
Rn H Rn H
0
20
40
60
80
100
120
140
160
180
200
7/ 10 7/ 20 7/ 31 8/ 10 8/ 20 8/ 31 9/ 10 9/ 20 9/ 30
ARM(NPA)
0
20
40
60
80
100
120
140
160
180
200
7/ 10 7/ 20 7/ 31 8/ 10 8/ 20 8/ 31 9/ 10 9/ 20 9/ 30
0
20
40
60
80
100
120
140
160
180
200
7/ 10 7/ 20 7/ 31 8/ 10 8/ 20 8/ 31 9/ 10 9/ 20 9/ 30
Ft. Peck
0
20
40
60
80
100
120
140
160
180
200
7/ 10 7/ 20 7/ 31 8/ 10 8/ 20 8/ 31 9/ 10 9/ 20 9/ 30
0
20
40
60
80
100
120
140
160
180
200
7/ 10 7/ 20 7/ 31 8/ 10 8/ 20 8/ 31 9/ 10 9/ 20 9/ 30
ARM(TWP)
0
20
40
60
80
100
120
140
160
180
200
7/ 10 7/ 20 7/ 31 8/ 10 8/ 20 8/ 31 9/ 10 9/ 20 9/ 30
0
20
40
60
80
100
120
140
160
180
200
7/ 10 7/ 20 7/ 31 8/ 10 8/ 20 8/ 31 9/ 10 9/ 20 9/ 30
Caxiuana
0
20
40
60
80
100
120
140
160
180
200
7/ 10 7/ 20 7/ 31 8/ 10 8/ 20 8/ 31 9/ 10 9/ 20 9/ 30
0
20
40
60
80
100
120
140
160
180
200
7/ 10 7/ 20 7/ 31 8/ 10 8/ 20 8/ 31 9/ 10 9/ 20 9/ 30
Manaus
0
20
40
60
80
100
120
140
160
180
200
7/ 10 7/ 20 7/ 31 8/ 10 8/ 20 8/ 31 9/ 10 9/ 20 9/ 300
20
40
60
80
100
120
140
160
180
200
7/ 10 7/ 20 7/ 31 8/ 10 8/ 20 8/ 31 9/ 10 9/ 20 9/ 30
0
20
40
60
80
100
120
140
160
180
200
7/ 10 7/ 20 7/ 31 8/ 10 8/ 20 8/ 31 9/ 10 9/ 20 9/ 30
Bondville
0
20
40
60
80
100
120
140
160
180
200
7/ 10 7/ 20 7/ 31 8/ 10 8/ 20 8/ 31 9/ 10 9/ 20 9/ 30
0
20
40
60
80
100
120
140
160
180
200
7/ 10 7/ 20 7/ 31 8/ 10 8/ 20 8/ 31 9/ 10 9/ 20 9/ 30
SGP
0
20
40
60
80
100
120
140
160
180
200
7/ 10 7/ 20 7/ 31 8/ 10 8/ 20 8/ 31 9/ 10 9/ 20 9/ 30
0
20
40
60
80
100
120
140
160
180
200
7/ 10 7/ 20 7/ 31 8/ 10 8/ 20 8/ 31 9/ 10 9/ 20 9/ 30
Pantanal
0
20
40
60
80
100
120
140
160
180
200
7/ 10 7/ 20 7/ 31 8/ 10 8/ 20 8/ 31 9/ 10 9/ 20 9/ 30
Northern South China Sea - Southern Japan
Ta RH
Santarem
Ta RH
Ta RH
Lindenberg
Ta RH
0
20
40
60
80
100
120
140
160
180
200
7/ 10 7/ 20 7/ 31 8/ 10 8/ 20 8/ 31 9/ 10 9/ 20 9/ 30
Rondonia
0
20
40
60
80
100
120
140
160
180
200
7/ 10 7/ 20 7/ 31 8/ 10 8/ 20 8/ 31 9/ 10 9/ 20 9/ 30
Mongolia
0
20
40
60
80
100
120
140
160
180
200
7/ 10 7/ 20 7/ 31 8/ 10 8/ 20 8/ 31 9/ 10 9/ 20 9/ 30
0
20
40
60
80
100
120
140
160
180
200
7/ 10 7/ 20 7/ 31 8/ 10 8/ 20 8/ 31 9/ 10 9/ 20 9/ 30
Lindenberg
0
20
40
60
80
100
120
140
160
180
200
7/ 10 7/ 20 7/ 31 8/ 10 8/ 20 8/ 31 9/ 10 9/ 20 9/ 30
0
20
40
60
80
100
120
140
160
180
200
7/ 10 7/ 20 7/ 31 8/ 10 8/ 20 8/ 31 9/ 10 9/ 20 9/ 30
Cabauw
0
20
40
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80
100
120
140
160
180
200
7/ 10 7/ 20 7/ 31 8/ 10 8/ 20 8/ 31 9/ 10 9/ 20 9/ 30
O UB
O M G
O C YM O N G O LIA SA
C H IN A
RUSSIA
0
1
2
3
4
5
6
7
8
A B C D E F G H I J
AMSR-E Soil Moisture Validationat the Reference Site in Mongolia
0.0
5.0
10.0
15.0
20.0
25.0
30.0
35.0
0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0
Obs
Est
07_a07_d08_a
08_d09_a
09_d
Comparesion with Estimated(Mv) and Observed(Mv)
0
5
10
15
20
25
30
35
40
0 5 10 15 20 25 30 35 40
Obs Mv(%) at 3 cm
Est
Mv(
%)
Ascending 07Ascending 08Ascending 09Descending 07Descending 08Descending 09
Solar I nsolation f rom Solar I nsolation f rom CEOP ObservationsCEOP Observations, , GFS OPER runsGFS OPER runs, , and and GFS TEST runsGFS TEST runs at SGP, Pantanal, and Lindenbergat SGP, Pantanal, and Lindenberg
Assessment of land models in coupled models is hindered bysurface forcing errors in parent atmospheric model, such as biasesin precipitation and solar insolation.
Figures at right show high bias inthe global model’s monthly mean diurnal cycle of surface solarinsolation during J ul 2001compared to observations at 3 CEOP sites:
SGP: Lamont, OklahomaPantanal: BrazilLindenberg: Germany
Surface fluxes of Surface fluxes of GLOBAL MODELGLOBAL MODEL vsvs CEOP ObservationsCEOP Observationsat SGP (top), at SGP (top), PantanalPantanal (middle), and Lindenberg (bottom)(middle), and Lindenberg (bottom)
COLOR KEY:Red – observationsBlue – using OSU LSMGreen – using Noah LSM
Global model run withnewer Noah LSMshows a larger high biasin daytime latent heat flux, though bettersensible heat flux.
Forcing biases in parentatmospheric model spurus to consider uncoupledresults of Noah LSM inuncoupled NLDAS in slides to follow.
Surface Sensible Heat Flux (W/m2) Monthly Mean Diurnal Cycle
July 2001
Surface Latent Heat Flux (W/m2)
72 hours Prediction by JMA in the East Siberia in July
放射
0
100
200
300
400
500
600
700
800
900
1 13 25 37 49 61 73
RSDB obs
RSDB mdl
RSUB obs
RSUB mdl
RLDB obs
RLDB mdl
RLUB obs
RLUB mdl
予報時間
radiation
lead-time
• Small Diurnal Amplitude of Surface Temperature and Air Temperature
• Weak Atmospheric Heating in Daytime
0
10
20
30
40
1 13 25 37 49 61 73
24m 観測 0m 観測 モデル最下層気温 予報値 地表温度 予報値
予報時間
0
20
40
60
80
1 13 25 37 49 61 73
10cm 土壌水分 観測 40cm 土壌水分 観測1 土壌 層土壌水分 予報 2 土壌水分 層 予報
予報時間
%
Large Predicted Soil Moisture
72 hours Prediction by JMA in the East Siberia in July
CEOP ORGANIZATION STRUCTUREScience Steering Committee
•guide/oversee the science implementation•maximize the scientific and technical benefits
WCRP H.Grassl GEWEX: S.Sorooshian CLIVAR: C.R. MechosoCLiC: B. GoodisonWGNE: K. PuriGHP Chair J. RoadsGAME T. YasunariIGOS-P: R. Lawford (Water Theme Rep)Leading Scientist: T.Koike
Advisory/Oversight Committee•receivers of scientific ideas for funding and support•providers of reality checks on funding, infrastructure•membership criteria (provides data or funds efforts)
Co-chair: J.Kaye (NASA) & A.Sumi (NASDA)Delegates from WCRP, Space Agencies, and other Sponsoring Organizations.
Coordination Bodykeep communication flowing: newsletter, web, teleconference, meeting, etc.International Coordinator: S.BenedictImplementation Coordination Group: CSE Representatives and S.WilliamsNews Letter Editorial Board: P.Try, C.R.Mechoso, R.SchifferInternational Coordination Office(Japan): J.Matsumoto/T.Oki/D.Yang/K.Tamagawa/A.Goda (UT) , T.Matsumura (JMA), C.Ishida /N.Matsuura/S.Ochiai (NASDA), B.Burford/K.Misawa(RESTEC)
Working Groupsresponsible for carrying out the individual components and reporting to Scientific Steering Committee
Water and Energy Simulation & Prediction Monsoon SystemsCo-chair: J. Roads & J. Marengo Co-chair: W.Lau & J.MatsumotoR.Stewart, Carl Fortelius, T.Lebel, T.Oki , H.Berbery, W.Higgins, T.Lebel, R.Mechoso,
T.Ambrizzi, M.Bollasina
Satellite Data Integration Data ManagementChair:T.Koike & P.Houser Co-chair: S.Williams & H.IsemerG.Stephens(GEWEX), A.Walker(CliC), J.Fischer, B.Crawford, T.Lebel, K.Takahashi, L.Horta, U.Schneider, M. Chahine(Aqua/AIRS) T.Maurer, EColtounCEOS WGISS: S.SobueCEOS WGCV:V.Desnos Model Data Management (TBD)Validation scientists of TRMM, Terra, Aqua, ADEOS-II, ENVISAT NCEP, ECMWF,JMA,CPTEC,CMA, DAO, MPI, ECPC, UKMet
Scientific idea
Advise &opportunity
Scientific guidance
Implementation report
GEOS3 GAPP GEOS3 GAPP BondvilleBondville Energy Energy and Radiation Comparisonand Radiation Comparison
Monthly mean diurnal cycle of energy and Monthly mean diurnal cycle of energy and radiation components at closest grid pointradiation components at closest grid point
GEOS3 GAPP SGP Lamont Energy GEOS3 GAPP SGP Lamont Energy and Radiation Comparisonand Radiation Comparison
Too much latent heat in the analysis Too much latent heat in the analysis leads to cold surface temperaturesleads to cold surface temperatures
GEOS3 LBA ComparisonsGEOS3 LBA Comparisons
Even within the LBA, the variations in model and Even within the LBA, the variations in model and observed differences can be significantobserved differences can be significant