Arctic Research Collaboration for Radiosonde Observing System Experiment (ARCROSE) Jun Inoue (National Institute of Polar Research, Japan)

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Arctic Research Collaboration for Radiosonde Observing System Experiment (ARCROSE) Jun Inoue (National Institute of Polar Research, Japan) Collaborators: A. Yamazaki & J. Ono (JAMSTEC) H. Yamaguchi (The Univ. Tokyo) K. Dethloff, M. Maturilli & R. Neuber (AWI) P. Edwards(Env. Canada) Inoue.jun@nipr.ac.jp

Why is Arctic radiosonde data important? ü Improve sea-ice forecasts over Northern Sea Route Ø high waves, strong winds, icing caused by Arctic cyclones ü Understand the linkage between Arctic and mid-latitudes Ø extreme events over Eurasia (e.g. severe winter) Arctic Research Collaboration for Radiosonde Observing System Experiment Extra Observations Data sparse area Modeling Better predictions

Predictability studies for YOPP ü Frequent radiosonde obs. from ships & land stns. R/Vs Mirai & Polarstern, Ny- Alesund, etc. Improvements of NWPs and reanalyses ü Data assimilagon (DA) Observing System Experiment (OSE) EvaluaGng the effect of intensive obs., and proposing a future observing network

Pilot Studies for YOPP & MOSAiC Aug 2012 (RV Polarstern: a great cyclone case) Sep 2013 (RV Mirai, Ny-Ålesund, Alert & Eureka) Sep 2014 (RVs Polarstern, Mirai, & Oden; Ny-Ålesund, Alert & Eureka) Global observations Additional Obs. (radiosondes) JAMSTEC ALERA2 Observing system experiments Control Reanalysis Atmospheric forecast Sea-ice forecast Reanalysis w/o extra obs Atmospheric forecast Sea-ice forecast Data assimilation Predictability of extreme events Predictability of sea ice over NSR

Application to forecasting Arctic cyclones Special observagons from R/V Polarstern improves the predictability of the great ArcGc cyclone on Aug. 6, 2012. Central pressure did not develop w/o observagons R/V Polarstern Control reanalysis Central pressure was well predicted if observagon data was used Yamazaki et al. (2014 JGR- A, submi[ed)

Stationary observations by RV Mirai (21UTC 10 Sep. 00UTC 26 Sep. 2013) 3- hourly: Radiosondes 6- hourly: CTD/R, Plankton nets Twice daily: TurboMAP, Clean water sampling Daily: PRR CTD (daily) XCTD (daily) 72.75 o N 168.25 o W 9nm (1 hour) 9nm (1 hour) 50m

Arctic Ocean Research using R/V Mirai R/V Mirai: Japanese Ice-strengthen vessel The only ship for the Arctic cruise which has a Doppler radar and an auto balloon launcher

ARCROSE2013 & 2014 Ny- Alesund Alert Eureka Polarstern Mirai Oden GTS status in NCEP ADP Global Upper Air ObservaGons 22 launches per day during ARCROSE

Northern Sea Route was closed during ARCROSE2013 Ø A good case to invesggate the impact of ARCROSE data on the predictability of high pressure system Ny- Alesund Alert H Eureka 3 days H Mirai

Setting for Observing System Experiments (OSE) Ø Ø Ø Control reanalysis (63 members) was made by assimilagng all ARCROSE data Observing System Experiment (OSE) reanalyses were made Ensemble forecast runs were conducted by using each reanalysis Mirai Eureka Alert Ny- Alesund IOP IOP operagonal IOP operagonal IOP operagonal CTL 8 2 2 2 2 5 1 OSE MEAN 0 0 2 0 2 0 1 OSE M 0 2 2 2 2 5 1 OSE EA 8 0 2 0 2 5 1 OSE N 8 2 2 2 2 0 1

6 days forecast for SLP (color) and Z500 (cont.)

Difference in prediction skills among the OSEs Low skill cases: OSE M, OSE N & OSEN MEAN Ø Data from Mirai and Ny- Alesund is crigcal in this case ü ü ü

Difference in surface winds between CTL and OSE MEAN Difference in surface wind speed along the NSR exceeds 4 m s - 1

Impact of ARCROSE data at upper level Ø Ensemble spread originated from ARCROSE stagons traveled along the polar vortex (e.g. at 100hPa) Ø Impacts of addigonal observagons likely reach at midlagtudes Z100 CTL Ny- Alesund Alert Eureka Dots: trajectories of difference in ensemble spread between Z100 CTL and Z100 OSE_MEAN Mirai

Challenges towards YOPP/MOSAiC ü Understanding seasonality in pargcular winter (e.g. N- ICE2015) Ø predicgons of extreme cold winters ü CoordinaGon of land stagons (e.g. Alert & Eureka) Ø Russian stagons? ü CollaboraGon with operagonal agencies (ECMWF, NCEP, etc) Ø They must have opinions for addigonal observagons (e.g. Cost effecgve number of stagons or obs frequency) ü Impact of atmospheric forecasts on sea- ice forecasts Ø More applied challenging works

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