Xiaohua Yang wrote:I am uncertain if the ALADIN component in GLAMEPS also suffer similar problem in climate generation. If so, it indeed could explain part of the odd features as reported in the recent discussion about coastal SST issue. I'll report in separate recent findings and remedy in GLAMEPS about the latter.
Greetings, Xiaohua
The above was written quite some days ago, I update now part of the findings about SST and ice in the GLAMEPS.
In both HIRLAM and ALARO members as used in GLAMEPS, ECMWF SST and ice cover are used either as pseudo observation or background in surface analysis. In the deterministic HIRLAM, it had been reaslised that the SST and ice information in the ECMWF data at ANALYSIS time does not assign value on land point, i.e., UNDEFINED. For some reason, from the forecast data stream, land points are given a somewhat artificial value. In view of these difference, HIRLAM since 7.2 release specified in the scripts to acquire ECMWF SST and ice data from ANALYSIS, instead of FORECAST data stream. The interpolation and surface analysis scheme will then take it into account when encountering undefined SST value over land points. The HARMONIE GL interpolation procedure, which ALARO model component in GLAMEPS uses, have also taken this into account.
However, in GLAMEPS, the implementation so far failed to take the subtle difference in ECMWF sst and ice data stream between analysis and forecast into account. When interpolation procedure see the 'continuous' data from forecast file of ECMWF/ENFO, a normal interpolation is done, which results in often an unrealistic gradient at coastal area. The erroroneous sst gradient at European coastal area appears to have caused severe consequence on resulting T2m forecast, with the negative impact sprending over not only coastal area but whole model domain. The SST problem here is assumed to be one of the main cause for the abnormally larger T2m bias in GLAMEPS members.
Last week, a solution has been implemented in the daily GLAMEPS suite in which data stream for ECMWF SST and Sea Ice was changed from ENFO data stream to that of the deterministic ANALYSIS data. The positive impact of such change is immediately visible from the monitoring of the T2m behavior in the GLAMEPS controle run. see e.g. the wiki interface
hirlam.org/portal/glameps/WebgraF/ObsVer...l?choice_ind=Surface
The attached plot shows the time series of the T2mstd and bias for GLAMEPS domain, comparing control suites of HIRLAM-KF (blue), HIRLAM-ST (magenda) , ALARO (green) and ECEPS (red) models, as well as the ensemble mean (cyan) for the current month.