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Improved blocking at 25km resolution? Reinhard Schiemann 1,2, Marie-Estelle Demory 1, Mio Matsueda 3, Matthew Mizielinski 2, Malcolm Roberts 2, Len Shaffrey.

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Presentation on theme: "Improved blocking at 25km resolution? Reinhard Schiemann 1,2, Marie-Estelle Demory 1, Mio Matsueda 3, Matthew Mizielinski 2, Malcolm Roberts 2, Len Shaffrey."— Presentation transcript:

1 Improved blocking at 25km resolution? Reinhard Schiemann 1,2, Marie-Estelle Demory 1, Mio Matsueda 3, Matthew Mizielinski 2, Malcolm Roberts 2, Len Shaffrey 1, Jane Strachan 1,2, Pier Luigi Vidale 1 1 NCAS Climate, Department of Meteorology, University of Reading, UK 2 Met Office Hadley Centre, Exeter, UK 3 Atmospheric Physics, University of Oxford A partnership in weather and climate research Joint Weather and Climate Research Programme

2 Motivation and Outline Representation of atmospheric blocking has been shown to improve with resolution. in controlled experiments (Matsueda et al. 2009, Berckmans et al. 2013, Anstey et al. 2013) in CMIP5 (Anstey et al. 2013) Here, analyse recent ensemble of HadGEM3-A high-resolution global simulations of present-day climate. 1.How well is blocking represented? location, frequency, persistence of blocking events 2.Sensitivity to (horizontal) resolution as we go to ~25 km? 3.Mean biases and blocking (following Scaife et al., 2010)

3 A-GCM experiments N216 (60 km) N96 (135 km) N512 (25 km) Resolution increase HadGEM3-A 85 levels top @ 85km GA3.0 OSTIA daily SSTs validate against ERA-Interim (T255, 80 km) 5001500orography (m) 4 x 26 years 3 x 26 years 5 x 26 years ➡ UPSCALE

4 UPSCALE Project UK on PRACE - weather resolving Simulations of Climate for globAL Environmental risk current “numerical mission” of the JWCRP High-resolution climate modelling team 144 million core hours (equivalent to roughly half the HECToR facility) awarded for 1 year by PRACE (Partnership for Advanced Computing in Europe) HadGEM3-A multi-decadal simulations at N96 (130 km) to N512 (25 km), shorter experimental simulations at N1024 (12 km) present climate simulations forced with OSTIA SSTs 1985-2011 (27 years) 5 ensemble members future climate simulations 3 ensemble members à 27 years following RCP8.5 SST: daily OSTIA + HadGEM2-AO RCP8.5 2100 ΔSST UPSCALE output available on JASMIN@CEDA

5 A-GCM experiments N216 (60 km) N96 (135 km) N512 (25 km) T95 (210 km) T319 (60 km) T959 (20 km) Resolution increase HadGEM3-A 85 levels top @ 85km GA3.0 MRI-AGCM 3.2 64 levels top @ 0.01 hPa AMIPII SSTs validate against ERA-Interim (T255, 80 km) 5001500orography (m) 4 x 25 years 1 x 25 years 4 x 26 years 3 x 26 years 5 x 26 years ➡ UPSCALE

6 Blocking index AGP (absolute geopotential height) index as in Scherrer (2006), Schwierz (2004) reversal of meridional geopotential height gradient (500 hPa) and westerlies to the north 5-day persistence criterion 2D generalisation of index by Tibaldi and Molteni (1990) latitude Z 500 hPa 15° (1) (2) (1)(2)

7 Blocking index AGP (absolute geopotential height) index as in Scherrer (2006), Schwierz (2004) reversal of meridional geopotential height gradient (500 hPa) and westerlies to the north 5-day persistence criterion 2D generalisation of index by Tibaldi and Molteni (1990) blocked-day composite (DJF, ERA-Interim): Z 500 hPa (m) SLP (hPa)

8 DJF, HadGEM3-A frequency of blocked days N96 (135 km) N216 (60 km) N512 (25 km) ERA-Interim

9 DJF, HadGEM3-A frequency of blocked days ERA-Interim (normalised by #all days) (norm. by #blocked days in each dataset)

10 DJF, MRI-AGCM 3.2 frequency of blocked days ERA-Interim T95 (210 km) T319 (60 km) T959 (20 km)

11 DJF, MRI-AGCM 3.2 frequency of blocked days ERA-Interim (norm. by #blocked days in each dataset)(normalised by #all days)

12 MAM, HadGEM3-A frequency of blocked days N216 (60 km) N512 (25 km) ERA-Interim N96 (135 km)

13 MAM, HadGEM3-A (norm. by #blocked days in each dataset) frequency of blocked days ERA-Interim (normalised by #all days)

14 MAM, MRI-AGCM 3.2 frequency of blocked days ERA-Interim T95 (210 km) T319 (60 km) T959 (20 km)

15 Mean biases and blocking frequency of blocked days N96 (135 km) ERA-Interim DJF, HadGEM3-A N512 (25 km) stormtrack too far south also seen in CMIP5 (Zappa et al., 2013, and poster 24)

16 Mean biases and blocking frequency of blocked days N96 (135 km) ERA-Interim DJF, HadGEM3-A N512 (25 km) prob. density (1) prob. density mean corrected to ERA-Interim

17 Mean biases and blocking frequency of blocked days N96 (135 km) ERA-Interim DJF, HadGEM3-A N512 (25 km) prob. density (2) mean corrected to ERA-Interim

18 Mean biases and blocking frequency of blocked days MAM, HadGEM3-A N96 (135 km) ERA-Interim N512 (25 km)

19 Mean biases and blocking frequency of blocked days MAM, HadGEM3-A prob. density (1) N512 (25 km) N96 (135 km) ERA-Interim mean corrected to ERA-Interim

20 Mean biases and blocking frequency of blocked days MAM, HadGEM3-A prob. density N512 (25 km) N96 (135 km) ERA-Interim (2) mean corrected to ERA-Interim see also Masato et al. (2013), and poster 22

21 Mean biases and blocking DJF, HadGEM3-A 9981004hPa1016 50605180m5420 ERA-Interim N96 (135 km) N216 (60 km) N512 (25 km) Z 500 hPa SLP

22 Pacific blocking frequency of blocked days ERA-Interim N96 (135 km) N216 (60 km) N512 (25 km) ERA-Interim T95 (210 km) T319 (60 km) T959 (20 km) DJF HadGEM3-AGCM MRI-AGCM 3.2 ERA-Interim N96 (135 km) N216 (60 km) N512 (25 km) ERA-Interim T95 (210 km) T319 (60 km) T959 (20 km) JJA HadGEM3-AGCM MRI-AGCM 3.2

23 Summary So, is blocking improved at 25 km? ➡ Atlantic: Yes. Pacific: No. ➡ But there are details (model / region / season). DJFMAMJJASON HadGEM3- AGCM =+= (+) MRI- AGCM 3.2 ++ (+) = Better with resolution? And how good is it anyway? DJFMAMJJASON HadGEM3- AGCM MRI- AGCM 3.2 Atlantic

24 Summary So, is blocking improved at 25 km? ➡ Atlantic: Yes. Pacific: No. ➡ But there are details (model / region / season). DJFMAMJJASON HadGEM3- AGCM = (-) = MRI- AGCM 3.2 = (-) = (+) Better with resolution? And how good is it anyway? DJFMAMJJASON HadGEM3- AGCM MRI- AGCM 3.2 Pacific

25 Summary So, is blocking improved at 25 km? ➡ Atlantic: Yes. Pacific: No. ➡ But there are details (model / region / season). And where blocking is sensitive to resolution, is the change in blocking consistent with a change in the mean state? ➡ Yes (HadGEM3-A). And how much of the resolution sensitivity can be associated with a change in the mean state? ➡ A lot. Not quantified yet. How is the persistence of events simulated? Where the blocking frequency is underestimated, there are ➡ too few occurrences of blocking and ➡ the events that do occur do not last long enough. Thank you

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