Time-series of seagrass and land cover maps from 1972 to 2010, in South East Queensland, Australia, with links to GeoTIFFs

Long term global archives of high-moderate spatial resolution, multi-spectral satellite imagery are now readily accessible, but are not being fully utilised by management agencies due to the lack of appropriate methods to consistently produce accurate and timely management ready information. This work developed an object-based remote sensing approach to map land cover and seagrass distribution in an Australian coastal environment for a 38 year Landsat image time-series archive (1972-2010). Landsat Multi-Spectral Scanner (MSS), Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM+) imagery were used without in situ field data input (but still using field knowledge) to produce land and seagrass cover maps every year data were available, resulting in over 60 map products over the 38 year archive. Land cover was mapped annually using vegetation, bare ground, urban and agricultural classes. Seagrass distribution was also mapped annually, and in some years monthly, via horizontal projected foliage cover classes, sand and deep water. Land cover products were validated using aerial photography and seagrass maps were validated with field survey data, producing several measures of accuracy. An average overall accuracy of 65% and 80% was reported for seagrass and land cover products respectively, which is consistent with other studies in the area. This study is the first to show moderate spatial resolution, long term annual changes in land cover and seagrass in an Australian environment, created without the use of in situ data; and only one of a few similar studies globally. The land cover products identify several long term trends; such as significant increases in South East Queensland's urban density and extent, vegetation clearing in rural and rural-residential areas, and inter-annual variation in dry vegetation types in western South East Queensland. The seagrass cover products show that there has been a minimal overall change in seagrass extent, but that seagrass cover level distribution is extremely dynamic; evidenced by large scale migrations of higher seagrass cover levels and several sudden and significant changes in cover level. These mapping products will allow management agencies to build a baseline assessment of their resources, understand past changes and help inform implementation and planning of management policy to address potential future changes.

(Table 1) Seasonal sea ice concentration and the observed changes from 1972 to 2007 for the Southern Beaufort Sea

A reliable data set of Arctic sea ice concentration based on satellite observations exists since 1972. Over this time period of 36 years western arctic temperatures have increased; the temperature rise varies significantly from one season to another and over multi-year time scales. In contrast to most of Alaska, however, on the North Slope the warming continued after 1976, when a circulation change occurred, as expressed in the PDO index. The mean temperature increase for Barrow over the 36-year period was 2.9°C, a very substantial change. Wind speeds increased by 18% over this time period, however, the increase were non-linear and showed a peak in the early 1990s. The sea ice extent of the Arctic Ocean has decreased strongly in recent years, and in September 2007 a new record in the amount of open water was recorded in the Western Arctic. We observed for the Southern Beaufort Sea a fairly steady increase in the mean annual amount of open water from 14% in 1972 to 39% in 2007, as deduced from the best linear fit. In late summer the decrease is much larger, and September has, on average, the least ice concentration (22%), followed by August (35%) and October (54%). The correlation coefficient between mean annual values of temperature and sea ice concentration was 0.84. On a monthly basis, the best correlation coefficient was found in October with 0.88. However, the relationship between winter temperatures and the sea ice break-up in summer was weak. While the temperature correlated well with the CO2 concentration (r=0.86), the correlation coefficient between CO2 and sea ice was lower (r=-0.68). After comparing the ice concentration with 17 circulation indices, the best relation was found with the Pacific Circulation Index (r=-0.59).

ERA-CLIM Historical Upper-Air Data 1900-1972

Historical, i.e. pre-1957, upper-air data are a valuable source of information on the state of the atmosphere, in some parts of the World back to the early 20th century. However, to date reanalyses have only partially made use of these data, and only of observations made after 1948. Even for the period between 1948 (the starting year of the NCEP/NCAR reanalysis) and the International Geophysical Year in 1957 (the starting year of the ERA-40 reanalysis), when the global upper-air coverage reached more or less its current status, many observations have not been digitised until now. The Comprehensive Historical Upper-Air Network (CHUAN) already compiled a large collection of pre-1957 upper-air data. In the framework of the European project ERA-CLIM, significant amounts of additional upper-air data have been catalogued (> 1.3 mio station days), imaged (> 200,000 images) and digitised (> 700,000 station days) in order to prepare a new input dataset for upcoming reanalyses. The records cover large parts of the globe, focussing on so far less well covered regions such as the Tropics, the polar regions and the Oceans, and on very early upper-air data from Europe and the US. The total number of digitised/inventoried records is 61/101 for moving upper-air data, i.e. data from ships etc., and 735/1,783 for fixed upper-air stations. Here, we give a detailed description of the resulting dataset including the metadata and the quality checking procedures applied. The data will be included in the next version of CHUAN.