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RAPID WATCH and the RAPID Data Centre (RDC)
No full textThe RAPID Data Centre provides dedicated data management support for the NERC RAPID Directed Mode programme, and holds observational, model and synthesis data from the projects involved. This support will be continued in the follow-on programme, RAPID-WATCH
Mulit-year Predictability of Greenland Sea Spring Sea-ice Volume in a Coupled Climate Model
No full textPrediction of sea-ice is not only important for shipping but also for weather as it can have
a signicant climatic impact. Therefore sea-ice predictions are important for accurate
inter-annual to decadal prediction of climate in coupled climate models. However, to our
knowledge there has been little work on how predictable sea-ice is in a coupled
atmosphere-ocean-ice model. We have studied the predictability of sea-ice in HadCM3 using
case study ensemble experiments with external forcing from the late 20th century designed to emphasize
the predictability in the climate system due to initial conditions. Here, we will concentrate
on spring (maximum) ice-volume in a box in the Greenland Sea (30W to 10E, 68N to 80N). Model
climatology from a control-run shows that this region has high inter-annual variability in
sea-ice volume. We find that although ice may almost completely disappear from this area in
late autumn, the same anomalies re-appear in the following spring for at least the first four years
in three out of four case studies. The mechanism for this appears to be related to persistence of
ocean heat content in the initial conditions and the state of the meridional overturning circulation
and its associated heat transport. In this model, the atmosphere appears to less important than the
ocean in determining the predictability of sea-ice volume in the Greenland Sea
Monitoring current changes in precipitation and Earth’s radiative energy balance using satellite data, reanalyses and models
No full textUnderstanding and predicting African Easterly waves using moist singular vectors
No full textMoist singular vectors (MSV) have been applied successfully to predicting mid-latitude storms growing in association with latent heat of condensation. Tropical cyclone sensitivity has also been assessed. There is now considerable interest in its application for singular vector computation in the tropics and tropical perturbations for the ensemble system on a wider basis than targeting tropical cyclones. Extending this approach to more general tropical weather systems, MSVs are evaluated here for understanding and predicting African easterly waves (AEWs). These are arguably, the tropical systems that exhibit dynamical organization in a manner that is most similar to extra-tropical weather systems, and yet provide the context for convection that is of great importance both in their development and their subsequent behaviour, in their impact on society and in yielding ideas on the interaction between physics and dynamics in the tropical atmosphere that may have more general relevance.
The systematic errors that can plague the forecast skill in this region may be improved by process studies aimed at understanding the fundamental dynamics governing the WAM. Here we present first results from a study that aims to use MSVs to build on our recently gained theoretical insights from normal mode studies of the moist AEJ-AEW system, and to learn for practical purposes, whether MSVs targeted on W. Africa could be suitable as perturbations to the ECMWF ensemble system for improving AEW prediction and associated rainfall. First results, without initial moisture perturbations, suggest MSVs may be used advantageously. Perturbations bear similar structural and energy profiles to previous idealised non-linear studies and observations. Strong sensitivities prevail in the metrics and trajectories chosen. The benefits of including initial moisture perturbations are appraised in the light of these findings
