Difference between revisions of "Staff Priorities - Masha"
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=== Yesterday === | === Yesterday === | ||
+ | * CISM meeting at 9am | ||
+ | * CSEP meeting at noon | ||
* Trac ticket #372: Support Bayesian ensemble models for one-day forecasts: | * Trac ticket #372: Support Bayesian ensemble models for one-day forecasts: | ||
− | ** | + | ** Added another acceptance test to check for existing Bayesian forecasts before creating new ones |
− | + | ** Added support for GZIP compression for Bayesian forecasts if compression is enabled | |
+ | * | ||
=== Today === | === Today === | ||
− | * | + | * Post CSEP meeting minutes, send next meeting announcement |
− | |||
* Trac ticket #372: Support Bayesian ensemble models for one-day forecasts: | * Trac ticket #372: Support Bayesian ensemble models for one-day forecasts: | ||
− | ** | + | ** Commit code changes to SVN |
− | |||
** Set up forecast group on csep-cert to create Bayesian ensemble forecasts with BMA and SequencialBMA skill weighting | ** Set up forecast group on csep-cert to create Bayesian ensemble forecasts with BMA and SequencialBMA skill weighting | ||
Revision as of 20:24, 17 March 2016
Current Activities
Yesterday
- CISM meeting at 9am
- CSEP meeting at noon
- Trac ticket #372: Support Bayesian ensemble models for one-day forecasts:
- Added another acceptance test to check for existing Bayesian forecasts before creating new ones
- Added support for GZIP compression for Bayesian forecasts if compression is enabled
Today
- Post CSEP meeting minutes, send next meeting announcement
- Trac ticket #372: Support Bayesian ensemble models for one-day forecasts:
- Commit code changes to SVN
- Set up forecast group on csep-cert to create Bayesian ensemble forecasts with BMA and SequencialBMA skill weighting
Blocked: No
Followups: No
TODO
- csep-op failure: evaluation was issued on the very first day of new one-year Global forecasts - should not be the case
- Trac ticket #374: Remove temporary input catalog generated by CA ETASV12_10 model
- Trac ticket #353: Optimize RELM N-test by avoiding event to bin look up when masking bit is set for the whole forecast