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DTSTAMP:20220812T074334Z
LOCATION:Foyer 2nd Floor
DTSTART;TZID=Europe/Stockholm:20220628T090000
DTEND;TZID=Europe/Stockholm:20220628T110000
UID:submissions.pasc-conference.org_PASC22_sess181_pos139@linklings.com
SUMMARY:P39 - Challenges of SINFONY - the Combination of Nowcasting and Nu
 merical Weather Prediction on the Convective Scale at DWD
DESCRIPTION:Poster\n\nP39 - Challenges of SINFONY - the Combination of Now
 casting and Numerical Weather Prediction on the Convective Scale at DWD\n\
 nBlahak, SINFONY\n\nThere are different "optimal" forecast methods for dif
 ferent lead-times and weather phenomena.<br />For precipitation and severe
  convection up to some hours ahead, radar extrapolation techniques (Nowcas
 ting)<br />show good skill up to 1-2h ahead, while numerical weather predi
 ction (NWP)<br />outperforms Nowcasting only at later hours. At DWD, both 
 systems are independently developed and operationally operated by differen
 t teams on completely different computer architectures. NWP runs as an ens
 emble, while Nowcasting is deterministic. There are no integrated ("combin
 ed") forecast products for warning meteorologists and hydrological authori
 ties, making simultaneous use of both methods difficult.<br /><br />To ove
 rcome this situation and provide meaningful seamless forecasts from minute
 s to 12h, DWD's new Seamless INtegrated FOrecastiNg sYstem (SINFONY) will 
 come to life in the next two years.<br />Nowcasting- and NWP-ensembles are
  developed, enhanced and integrated in one large interdisciplinary team. T
 opics:<br />a) Nowcasting ensembles for precipitation, radar reflectivity 
 and convective cell-objects,<br />b) hourly km-scale Rapid-Update-Cycle En
 semble-NWP, assimilating new high-resolution observations (3D-radar-volume
 s, Meteosat-VIS-channels, cell-objects),<br />c) lead-time-weighted optima
 l combinations of Nowcasting- and NWP ensembles in observation space.<br /
 ><br />The poster will discuss some big challenges, e.g., such arising fro
 m different inherent characteristics of Nowcasting- and NWP-forecasts, and
  real-time production of high-frequent forecast updates across different c
 omputing platforms.
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