European Space Agency, ESRIN/Contract No. 4000101570/10/I-AM ‘Phase 1 of the ESA Climate Change Initiative SST_cci’
Friday, 26 September 2014
Learning Python
After years of relying on IDL for interacting with data, I am taking the plunge and switching to Python. The tipping point was deciding that iPython notebooks are a good way of maintaining the links between results, figures and the code used to generate them. My first plot is based on SST CCI data, of course!
Wednesday, 17 September 2014
Geoscience Data Journal paper
An open-access journal article describing the SST CCI phase 1 datasets was published today.
It is published in Geoscience Data Journal. I think the advent of 'data journals' over the past few years is a good development. The traditional recourse of trying to shoe-horn a detailed data description into a paper with science results was not ideal, particularly for large complex datasets such as those created by reprocessing EO archives for climate.
The new paper is:
It is published in Geoscience Data Journal. I think the advent of 'data journals' over the past few years is a good development. The traditional recourse of trying to shoe-horn a detailed data description into a paper with science results was not ideal, particularly for large complex datasets such as those created by reprocessing EO archives for climate.
The new paper is:
Merchant, C. J., Embury, O., Roberts-Jones, J., Fiedler, E., Bulgin, C. E., Corlett, G. K., Good, S., McLaren, A., Rayner, N., Morak-Bozzo, S. and Donlon, C. (2014), Sea surface temperature datasets for climate applications from Phase 1 of the European Space Agency Climate Change Initiative (SST CCI). Geoscience Data Journal. doi: 10.1002/gdj3.20
Wednesday, 3 September 2014
What differences to use in validation?
Validation is the comparison of (in this case) our satellite SSTs with temperature measured in situ, from buoys, ships, etc. Validation gives assurance that the satellite SSTs are, in a general sense, accurate. However, the comparison is complicated by the fact that different SSTs are genuinely different (geophysical differences), so that the difference between any two data points is a mix of error contributions and true differences. In addition, the SST CCI products include a number of SST estimates, each of which requires validation.
We therefore need to be clear about which in-situ/satellite comparisons will be made, and why. This post records the results of a review of our options, following discussions between myself and Gary Corlett (Leicester).
"Raw differences"
Here, we will compare the skin SST from the satellite to the nearest-in-time depth SST of the in situ measurement. In this case we expect certain systematic differences. (1) There is a geophysical difference based on the ocean thermal skin effect, which is typically of order -0.2 K, but also has a wind-speed dependence which should be clear in night-time differences. (2) There should be a trend in the raw difference with respect to the time separation of in situ and satellite: for example, in mid morning the ocean is typically warming, so in situ measurements after the satellite time will tend to be warmer. However, with respect to things that might affect the satellite retrieval adversely (but not directly the skin-depth SST difference) the systematic dependencies should be small; for example, a systematic effect in the raw differences with latitude should be no larger than we might be able to account for by the fact that mean wind speed (and therefore skin effect) varies with latitude.
"Skin-skin differences"
The idea here is to estimate the skin and depth effects at the time of the satellite observation and add these to the in situ observation. The in situ history is first interpolated to the satellite observation time, so giving an estimate of SST-20cm at the location and time of a satellite SST. Any 20-cm-to-subskin stratification is estimated using a model (usually small, and only ever large for day-time cases) and the skin effect is also estimated using a skin-effect model. There should ideally be no systematic effects with respect to latitude, wind, satellite-buoy-time-difference, etc, because the models are meant to account correctly (on average) for all the geophysical differences (other than those from comparing a point to a pixel, which are assumed to add zero-mean noise). This measure therefore tests the combination of "retrieval + adjustment for skin effect + adjustment in depth".
"Depth-depth differences"
In the SST products there is an adjustment provided that can be added to the fundamental satellite SST retrieval (of skin SST at the time of the satellite) to give an estimate of SST at typical drifting buoy depth (~20 cm) at standard local times of day (10.30 h or 22.30 h). To explore this, the satellite SST-20cm estimate for a standard local time will be differenced with the spatially-matched in situ SST history interpolated in time to the same local time. There should ideally be no systematic effects with respect to latitude, wind, satellite-buoy-time-difference, etc, because the adjustment is meant to account correctly (on average) for all the geophysical effects (other than those from comparing a point to a pixel, which are assumed to be zero-mean noise). This measure therefore tests the combination of "retrieval + adjustment for skin effect + adjustment in depth + adjustment in time". Compared to the skin-skin difference, this tests in addition the time-adjustment of the SST for the diurnal cycle.
"Daily mean depth-depth differences"
Although not generated in existing datasets, there has been a requirement which we are considering to estimate an adjustment to be added to the skin SST from the satellite which would give an estimate of the daily-mean SST at the location of the satellite observation. The day over which the mean is to be estimated is the UTC (i.e., GMT, not local) day which includes the time of the satellite observation. The in situ data would therefore consist of the average of the history of the in situ measurements over a 24 hour period. This comparison therefore tests "retrieval + adjustment for skin effect + adjustment in depth + adjustment to daily mean", and the spread of the results will include the uncertainty effect of estimation of the daily mean SST from a single observation. Systematic effects in the differences should be small.
We therefore need to be clear about which in-situ/satellite comparisons will be made, and why. This post records the results of a review of our options, following discussions between myself and Gary Corlett (Leicester).
"Raw differences"
Here, we will compare the skin SST from the satellite to the nearest-in-time depth SST of the in situ measurement. In this case we expect certain systematic differences. (1) There is a geophysical difference based on the ocean thermal skin effect, which is typically of order -0.2 K, but also has a wind-speed dependence which should be clear in night-time differences. (2) There should be a trend in the raw difference with respect to the time separation of in situ and satellite: for example, in mid morning the ocean is typically warming, so in situ measurements after the satellite time will tend to be warmer. However, with respect to things that might affect the satellite retrieval adversely (but not directly the skin-depth SST difference) the systematic dependencies should be small; for example, a systematic effect in the raw differences with latitude should be no larger than we might be able to account for by the fact that mean wind speed (and therefore skin effect) varies with latitude.
"Skin-skin differences"
The idea here is to estimate the skin and depth effects at the time of the satellite observation and add these to the in situ observation. The in situ history is first interpolated to the satellite observation time, so giving an estimate of SST-20cm at the location and time of a satellite SST. Any 20-cm-to-subskin stratification is estimated using a model (usually small, and only ever large for day-time cases) and the skin effect is also estimated using a skin-effect model. There should ideally be no systematic effects with respect to latitude, wind, satellite-buoy-time-difference, etc, because the models are meant to account correctly (on average) for all the geophysical differences (other than those from comparing a point to a pixel, which are assumed to add zero-mean noise). This measure therefore tests the combination of "retrieval + adjustment for skin effect + adjustment in depth".
"Depth-depth differences"
In the SST products there is an adjustment provided that can be added to the fundamental satellite SST retrieval (of skin SST at the time of the satellite) to give an estimate of SST at typical drifting buoy depth (~20 cm) at standard local times of day (10.30 h or 22.30 h). To explore this, the satellite SST-20cm estimate for a standard local time will be differenced with the spatially-matched in situ SST history interpolated in time to the same local time. There should ideally be no systematic effects with respect to latitude, wind, satellite-buoy-time-difference, etc, because the adjustment is meant to account correctly (on average) for all the geophysical effects (other than those from comparing a point to a pixel, which are assumed to be zero-mean noise). This measure therefore tests the combination of "retrieval + adjustment for skin effect + adjustment in depth + adjustment in time". Compared to the skin-skin difference, this tests in addition the time-adjustment of the SST for the diurnal cycle.
"Daily mean depth-depth differences"
Although not generated in existing datasets, there has been a requirement which we are considering to estimate an adjustment to be added to the skin SST from the satellite which would give an estimate of the daily-mean SST at the location of the satellite observation. The day over which the mean is to be estimated is the UTC (i.e., GMT, not local) day which includes the time of the satellite observation. The in situ data would therefore consist of the average of the history of the in situ measurements over a 24 hour period. This comparison therefore tests "retrieval + adjustment for skin effect + adjustment in depth + adjustment to daily mean", and the spread of the results will include the uncertainty effect of estimation of the daily mean SST from a single observation. Systematic effects in the differences should be small.
Subscribe to:
Posts (Atom)