A known weakness of the Ensemble Kalman filter approach is that its ability to provide state estimates that closely match densely distributed observations is very limited. This paper describes a computationally inexpensive innovative variation on the technique that greatly ameliorates this difficulty.
Gabriela Pilo and colleagues find that the Tasman Front is not so much a constant current, as is widely accepted, but switches between being an extension of the East Australian Current and an eddy field.
Climate scientists testing a new mathematical and statistical method that converts projections of future climate outcomes in a warming world into reliable probabilities have found there is a significant chance the Arctic could be ice-free even if world leaders meet the Paris targets of 1.5°C and 2°C.
The 21st Century has seen an increase in northwest cloudbands across Australia, according to a new dataset developed by CLEX researchers.
Using novel ocean glider technology, a team of researchers from France, Norway, and Australia observed small eddy-like lenses of cold water in July 2017 along the western Svalbard shelf in the Arctic.
New research confirms the long-term cooling over Antarctica during the last millennium and the delayed onset of anthropogenic warming are found in simulations that assimilate palaeoclimate data. This is not evident in simulations without data assimilation.
New students, an OA for Andy Pitman and some key work on evaporation, the impacts of mesophyll conductance on plant growth, a new algorithm for photosynthesis and future projections of drought made for a strong start to 2019.
Two workshops, the Sea Ice Modelling Workshop and Centre of Excellence for Climate Extremes “Southern Annular Mode (SAM) Cluster” workshop were held together at the Institute for Marine and Antarctic Studies in Hobart from February 19-21.
New data assimilation method leads to large improvements in forecast accuracy when satellite observations of electromagnetic radiation emanating from the Earth were used to inform the data assimilation scheme.
Calibration errors in the widely used Global Inventory Monitoring and Modeling System Version 3 NDVI (GIMMSv3.0g) dataset caused significant errors in the trends over some of Australia’s dryland regions. Though identified over Australia, the problematic calibration in the GIMMSv3.0g dataset may have effected dryland NDVI values globally. These errors have been addressed in the updated GIMMSv3.1g which is strongly recommended for use in future studies.