Ocean synthesis inter-comparison Ocean synthesis inter-comparison using OceanDIVAusing OceanDIVA

Alastair GemmellKeith HainesGreg SmithJon Blower

Environmental Systems Science Centre

University of Reading, UK

D

D

D

s

http://www.resc.rdg.ac.ukColor-coded model-obs T misfits

OutlineOutline

MethodsMethods – OceanDIVA – a – OceanDIVA – a Java web application to Java web application to visualize and compare visualize and compare gridded modelgridded model data, and data, and in-in-situ pointsitu point observationsobservations

GeospatialGeospatial representation representation of the data.of the data.

StatisticalStatistical representation representation of the dataof the data

ConclusionsConclusions

OceanDIVA – Ocean Data Inter-comparison and OceanDIVA – Ocean Data Inter-comparison and Visualization ApplicationVisualization Application

Input data can be local to the web service or read in remotely via OPeNDAP protocol

For this study:For this study:

• Used EN3 (ENACT/ENSEMBLES) observations dataset

• Compared a range of CLIVAR GSOP ocean syntheses accessible via OPeNDAP

• Analysed Sept ’04 (Sept ’01 for syntheses finishing before ‘04)

Geospatial representation of data in Geospatial representation of data in Google EarthGoogle Earth

Minimum bin content = 1Minimum bin content = 2Minimum bin content = 3

Probability Density Functions (PDFs)Probability Density Functions (PDFs)Covering the north Pacific.Covering the north Pacific. Model is Reading ¼ degreeModel is Reading ¼ degree

• Binned data into bins of 10m by 0.2oC• Blues = bins with lower data density• Reds = bins with higher data density• Data density normalised to depth level

Probability Density Functions (PDFs)Probability Density Functions (PDFs)Covering the north Pacific. Model is Reading ¼ degreeCovering the north Pacific. Model is Reading ¼ degree

DepthDepth

TemperatureTemperature

Observed DepthObserved Depth Salinity MisfitSalinity MisfitDepth MisfitDepth Misfit

Salinity MisfitSalinity MisfitTemperature MisfitTemperature Misfit

Regional VariabilityRegional VariabilityThis example: Reading ¼ degree model showing S(T)This example: Reading ¼ degree model showing S(T)

PacificPacificObs.Obs. MisfitMisfit

NorthNorth

SouthSouth

TropTrop..

AtlanticAtlanticObs.Obs. MisfitMisfit

North Pacific z(T) across synthesesNorth Pacific z(T) across synthesesObservationsObservations ECCO-JPLECCO-JPL GFDLGFDL ECMWFECMWF

CERFACS 2001CERFACS 2001 ECCO-SIO 2001ECCO-SIO 2001 SODASODA MERCATORMERCATOR

INGV 2001INGV 2001 GECCO 2001GECCO 2001 Reading 1Reading 1oo control control Reading 1Reading 1oo assim. assim.

WOA ‘05WOA ‘05 ECCO-GODAEECCO-GODAE Reading 1/4Reading 1/4oo control control Reading 1/4Reading 1/4oo assim. assim.

World Ocean Atlas ‘05

Bias v Standard DeviationBias v Standard DeviationNorth Pacific – z(T) – over T range 12-22 North Pacific – z(T) – over T range 12-22 ooCC

CERFACS ‘01 ECCO-GODAE ECCO-JPL ECCO-SIO ‘01 ECMWF

GECCO ‘01 GFDL INGV ‘01 MERCATOR Reading 1o control

Reading 1o assim. Reading ¼o control Reading ¼o assim. SODA WOA 2005

Misfit Mean (m) 500

25

Mis

fit

Std

. D

ev.

(m)

6

5

North Pacific S(T) across synthesesNorth Pacific S(T) across synthesesObservationsObservations ECCO-JPLECCO-JPL GFDLGFDL ECMWFECMWF

CERFACS 2001CERFACS 2001 ECCO-SIO 2001ECCO-SIO 2001 SODASODA MERCATORMERCATOR

INGV 2001INGV 2001 GECCO 2001GECCO 2001 Reading 1Reading 1oo control control Reading 1Reading 1oo assim. assim.

WOA ‘05WOA ‘05 ECCO-GODAEECCO-GODAE Reading 1/4Reading 1/4oo control control Reading 1/4Reading 1/4oo assim. assim.

ECCO-GODAE

Bias v Standard DeviationBias v Standard DeviationNorth Pacific – S(T) – over T range 5-17 North Pacific – S(T) – over T range 5-17 ooCC

CERFACS ‘01 ECCO-GODAE ECCO-JPL ECCO-SIO ‘01 ECMWF

GECCO ‘01 GFDL INGV ‘01 MERCATOR Reading 1o control

Reading 1o assim. Reading ¼o control Reading ¼o assim. SODA WOA 2005

Misfit Mean (PSU) 0.140.0

0.0

5

M

isfi

t Std

. D

ev.

(PSU

) 0

.13

Bias v Standard DeviationBias v Standard DeviationNorth Pacific – S(T) – over T range 17-30 North Pacific – S(T) – over T range 17-30 ooCC

CERFACS ‘01 ECCO-GODAE ECCO-JPL ECCO-SIO ‘01 ECMWF

GECCO ‘01 GFDL INGV ‘01 MERCATOR Reading 1o control

Reading 1o assim. Reading ¼o control Reading ¼o assim. SODA WOA 2005

Misfit Mean (PSU) 0.080.0

0.0

4

M

isfi

t Std

. D

ev.

(PSU

) 0

.11

ConclusionsConclusions OceanDIVA is a useful tool for visualizing data, and comparing OceanDIVA is a useful tool for visualizing data, and comparing

model data with observations.model data with observations.

Useful for validation in fields ofUseful for validation in fields of• Ocean reanalysesOcean reanalyses• Operational oceanographyOperational oceanography

Outputs shown which appear to reflect differences between Outputs shown which appear to reflect differences between synthesis techniques – e.g. methods of data assimilation.synthesis techniques – e.g. methods of data assimilation.• E.g. mode waters, S(T) relationshipsE.g. mode waters, S(T) relationships

Interesting Future work planned includingInteresting Future work planned including• different and longer time periods different and longer time periods • using isopycnalsusing isopycnals• more syntheses.more syntheses.

Provided correct metadata and standards are usedProvided correct metadata and standards are used, there is the , there is the exciting prospect of increasing amounts of data available on exciting prospect of increasing amounts of data available on OPeNDAP servers etc, leading to more collaborative work and OPeNDAP servers etc, leading to more collaborative work and comparisons being carried out.comparisons being carried out.