New research article: Improving soil moisture prediction of a high-resolution land surface model by parameterising pedotransfer functions through assimilation of SMAP satellite data https://t.co/oLJGCzNVdG
Brilliant to see our workshop participants using software written by @vlboult to produce their own TAMSAT-ALERT drought forecasts, based on @NCEOscience data produced by @EwanPinn@TristanQuaife and @ross_maidment. Plots by Ahmad Bello from @nimetnigeria. Great team effort!
Sharing TAMSAT soil moisture forecasts with the Kenya National Drought Management Authority (NDMA). Here - the NDMA staff are demonstrating their interpretation of our August forecast by annotating the scale at the bottom @NDMA_Kenya@TAMSAT_Reading@UniRdg_Research
New JULES Data Assimilation paper in discussion in @EGU_HESS. Led by @EwanPinn as part of @HydroJules. Applies Ewan's 4DEnVar system over part of the UK at 1 km resolution to tune pedotransfer coefficients. Assimilating 9 km @NASASMAP data. @NCEOscience
https://t.co/ghMXJlR2FV
Our 4DEnVar paper is out today. Led by @EwanPinn with @karinaewilliams , @amoslawless ,Tim Arkebauer and Dave Scoby. Also, much thanks to constructive reviewers.
The Land Variational Ensemble Data Assimilation Framework: LAVENDAR v1.0.0 https://t.co/maWHJ4ULS5
Our new paper on JULES data assimilation, led by
@EwanPinn, is in discussion in GMD: https://t.co/ccHqCa2j2u We've implemented a 4DEnVar, replacing the model adjoint used by 4DVar with an ensemble of model runs @amoslawless@karinaewilliams@NCEOscience