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Equatorial Pacific Ocean Sea Surface Temperature Anomaly ENSO Forecasts from the LDEO Climate Data Library

Listed in NASA Earthdata CMR

"Forecast sea surface temperature fields are produced on a monthly basis using the Zebiak and Cane (1987) coupled atmosphere-ocean model.

Description

At present, two forecast products are available: The standard, or LDEO, forecasts (consistent with those issued in the NOAA Diagnostic Bulletin over the past several years), and a newer product, referred to as LDEO2, that utilizes a different forecast initialization scheme. In the standard initialization, FSU pseudo-stress anomalies (with some filtering and smoothing as described in Cane et al, 1986, Nature) are used to "spin up" the ocean model from 1964 until the beginning of the forecast period; the atmosphere model is similarly spun up using the simulated SSTA from the forced ocean run.

Thus initialized, the coupled model runs ahead in time with no data insertion, producing a forecast for the evolution of the coupled atmosphere-ocean system. For the standard product, SSTA fields from individual forecasts are composited by lag-averaging the results from six consecutive monthly initial conditions. The composited forecasts for lead times of 3,6,9, and 12 months are then post-processed using a singular value decomposition analysis, to remove systematic spatial pattern errors and to map the idealized model domain onto the real one.

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The LDEO forecast results are archived from January 1972 (verification time) to the most recent month available. Also archived are forecasts of NINO3 (the average SSTA in the region 90W-150W, 5N-5S), a commonly used index of El Nino and the Southern Oscillation (ENSO). LDEO NINO3 forecast results are available at selected lead times as are the SSTA fields.

For the LDEO2 product, a nudging algorithm as described in Chen et al, 1995, Science, is used to initialize forecasts. In effect, the ocean is spun up with a weighted average of FSU and model-derived winds. This scheme results in much reduced "initialization shock", considerably improved forecast skill (.1 - .2 increase in correlation at all lead times from 0 to 18 months) and reduced seasonality of skill.

For the LDEO2 product, no lag-averaging is used, although small corrections for systematic errors are made using a singular value decomposition analysis. LDEO2 forecast results are available at selected lead times as are the LDEO2 NINO3 forecasts as are the SSTA fields." [from: "ingrid.ldeo.columbia.edu/SOURCES/.ENSOFORECAST/"]

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Stated by source
Enso · Not provided · Sst
Inferred from text
Climate change science 71%
Provenance · 1 source records, 10 field assertions
SourceKeyLast seenRaw
NASA Earthdata CMRC1214608537-SCIOPS15 d agoJSON v1
FieldAssertionExtractorEvidence
access_levelsource · NASA CMRconnector:nasa_cmr@1.0.0
concepts[field].anzsrc:group:3702enrichment · NASA CMRtaxonomy-embedding@1.1.0title+keywords+description (71%)
concepts[measured_variable].gcmd:earth-science/climate-indicators/atmospheric-ocean-indicators/teleconnections/el-nino-southern-oscillation-enso/ensosource · NASA CMRconnector:nasa_cmr@1.0.0
concepts[measured_variable].gcmd:earth-science/oceans/ocean-temperature/sea-surface-temperature/sstsource · NASA CMRconnector:nasa_cmr@1.0.0
concepts[platform].gcmd_platform:not-providedsource · NASA CMRconnector:nasa_cmr@1.0.0
descriptionsource · NASA CMRconnector:nasa_cmr@1.0.0/umm/Abstract
spatialsource · NASA CMRconnector:nasa_cmr@1.0.0/umm/SpatialExtent
temporalsource · NASA CMRconnector:nasa_cmr@1.0.0/umm/TemporalExtents
titlesource · NASA CMRconnector:nasa_cmr@1.0.0/umm/EntryTitle
version_labelsource · NASA CMRconnector:nasa_cmr@1.0.0