OSTIA water/land mask and new inland water bodies dataset

Laura Carrea and I have been looking at the OSTIA water/land mask in comparison with the new higher resolution dataset from the Landcover CCI project. The OSTIA mask is at 0.05 deg lat-lon resolution, and is used for the SST CCI Analysis product (gap filled daily SSTs); its precise heritage (since being created several years ago) hasn't been re-traceable, so it is useful to check its nature.

The plot below shows for a small area (Baltic Sea) the prevalence of water (according to the LC CCI product) within each 0.05 deg cell which is labelled in OSTIA as land. Red colours indicate the presence of a small fraction of water in an OSTIA "land" cell, and rivers and the many lakes on land are obvious. Dark blues indicate total or near-total water in an OSTIA "land" cell. Some of these are inland lakes no resolved in OSTIA, which is no surprise. There are a few cells around the Baltic coasts that are apparently water-filled (dark blue) yet are "land" cells in the OSTIA mask. Globally, however, such cases are exceptions. In general the coasts don't have a fringe, which suggests that the OSTIA mask is designed such that a cell tends to be labelled "water" if there is any significant fraction of sea within the cell. (If the design were such that a cell was labelled "water" if it contains >50% of sea, then there would be a fringe of intermediate values of %water-in-land-cell all coastlines.) So OSTIA must use a "fat" water mask, rather than a mask that is neutral with respect to land and water.

This next plot shows the prevalence of land in cells labelled water in OSTIA. Here, blue colours indicate a small amount of land, and red a lot of land in the cell. The fact that the whole coastline tends to be fringed with colour confirms that the OSTIA mask is "fat" with respect to water. (That is, truly mixed cells tend to be labelled as sea, so there is a fringe of land-in-water-cell cases along coasts.) However, it is also clear that there are many "water" cells that are in LC CCI completely land (dark red in this picture). These appear preferentially on northern coasts. This is consistent globally, and not just around the UK. This suggests that there is an offset in the N-S direction, roughly half an OSTIA cell in size, in the OSTIA mask relative to the Landcover CCI data set.

Where an OSTIA cell is flagged as sea and is in fact filled with land, there will be (or should be) no satellite SST retrievals ever available for that cell -- the data will always be provided by the gap-filling procedures associated with creating the L4 SST CCI analysis.

How to represent different SSTs in the products

As previously discussed we aim in future products to include not only the skin SST (the primary geophysical retrieval) and, as before, a 20 cm estimate at a fixed local time (to minimise aliasing of the diurnal cycle in the long term trends), but also a UTC-day mean estimate. This combination hits a good fraction of the diverse range of user requirements we collected for depths and time.

We also need to provide an adjustment to the most consistent possible retrieval (default in product is the best available type of retrieval, but one might also want to analyse one type of retrieval through the whole record).

To deliver this information in a GHRSST-compatible form requires some thought, since the retrieval and the various model-derived adjustments all have up to three components of uncertainty as well as their values.

Project team discussions have concluded on the following: to store the best available skin SST as the primary variable, and give a set of adjustments that can be added to this, each with N (1 <= N <= 3) uncertainty components. This is a much smaller data volume than adding all the different SSTs each with three uncertainty components. Data volume is a concern for a significant set of users.

For the convenience of users faced with the complexity of adding adjustments to the primary data, we will need to provide a reader programme that configures the calculation of a desired SST type and its uncertainty. Even nicer would be configuration of the desired fields on the fly on download -- that is a technological solution we aim to discuss with those who will do the CCI programme data portal (invitation to tender currently published).

Uncertainty information in Climate Data Records

We are well into our planning for a User Consultation workshop on representing uncertainty information in our SST CCI products in the most useful way. (Registration is still open.)

Venue: Met Office Hadley Centre, Exeter, UK
Date: 18-20th November 2014.

This workshop will be a two-way discussion between data providers and users. We aim to create a common understanding of: where uncertainty comes from (in this case, uncertainty in satellite sea surface temperature); how to talk about uncertainty unambiguously; how well the uncertainty information that is provided addresses users´ needs; and how to practically use such uncertainty information. It will achieve this through a mixture of oral and poster presentations, activities and group discussions.

We as data producers need to provide uncertainty information that users have confidence in, and have confidence in using. That is, they need to know it is realistic information, and what they can validly do with the information. Achieving this definitely involves increased mutual understanding, so it should be a very stimulating and lively meeting.