Atmospheric blocking in the Southern Hemisphere – from the seasonal cycle to

interannual and decadal variability

Caroline C. Ummenhofer1, Pia Freisen2, Michael J. Pook3, Peter C. McIntosh3, James S. Risbey3, Andrew G. Marshall4,

Gary A. Meyers3

1Woods Hole Oceanographic Institution, Physical Oceanography, Woods Hole, USA2Christian-Albrechts University, Kiel, Germany

3CSIRO Oceans and Atmosphere, Hobart, Australia4Bureau of Meteorology, Melbourne, Australia

SH Atmospheric blockingNNR Zonal winds – 500hPa

Risbey et al. (2009)

BlockingSAMIODENSO

Winter precipitation (due to cutoff lows) in Southeast Australia often associated with atmospheric blocking

Blocking in the AUS-NZ sector

Blocking index for AUS-NZ sector based on zonal wind U at the 500hPa level(Pook & Gibson 1999)

BI = 0.5 (U25+U30-U40-2*U45-U50+U55+U60)BI = 0.5 (U25+U30-U40-2*U45-U50+U55+U60)

Blocking indices

BoM BI500hPa GH at 45°S

daily measure of Tibaldi-Molteni index of blocked flow

Pook et al. (2013)

June – Sep 1989

- during winter months- at longitudes140E-140W

Blocking peaks:

SH annual cycle of blockingSeasonal cycle of blocked days (%) at 140E

Pook et al. (2013)

Change in April-July 1000-500hPa thickness

SH annual cycle of blockingSeasonal cycle of BI at 140°E and height

difference at 35° and 55°S

Change in meridional SAT gradient (°C per degree of latitude) from summer (DJF) to winter (JJA)

SH annual cycle of blocking

Change in 500hPa wind from summer (Jan) to winter (Jul) at 140°E

Pook et al. (2013)

Mean JJA SST (°C) Cross-section of SST (°C) along 55°S

BI at 160°E (Jun-Sep)

High-blocking year 1989

0.0

5.0

10.0

15.0

20.0

25.0

30.0

35.0

1948 1952 1956 1960 1964 1968 1972 1976 1980 1984 1988 1992 1996 2000 2004 2008 2012

m/s

Atmospheric model (CAM3)

Sensitivity to surface forcing in an AGCMPrevious studies on atmospheric blocking largely focus on NH; some factors of importance for blocking in AUS-NZ sector include

- (sub)tropical heating (e.g. Simpson & Downey 1975, Hinton et al. 2009)

- extratropical temperature gradients (e.g. Taljaard 1972, Coughlan 1983, Bals-Elsholz et al. 2001, Pook 1994, Pook et al. 2013)

AGCM experiments with NCAR’s Community Atmosphere Model v3 (CAM3) at 1.4°lat/lon horizontal resolution

Acronym SST forcing Length of simulation 

(yr)

CTRL Observed climatological SST 120 

SSTreal Interannually varying observed SST (1950‐2009)

60

1989 1989 SST 50

various SST anomalies in specificlocations

100

Sensitivity to surface forcing in an AGCMPrevious studies on atmospheric blocking largely focus on NH; some factors of importance for blocking in AUS-NZ sector include

- (sub)tropical heating (e.g. Simpson & Downey 1975, Hinton et al. 2009)

- extratropical temperature gradients (e.g. Taljaard 1972, Coughlan 1983, Bals-Elsholz et al. 2001, Pook 1994, Pook et al. 2013)

Configurations to maximize/minimize blocking in AUS-NZ sector

BLmax BLmin

Ummenhofer et al. (2013)

Model mean state (JJA) – zonal wind

NNR

CTRL

Model underestimates mid-latitude slow-down in Australia-New Zealand sector Ummenhofer et al. (2013)

Variability in the BI at 160°E (JJA)

BInorth

BImid

BIsouth

Ummenhofer et al. (2013)

Extratropical temperature gradients & land cooling

combining locations in favorable configuration results in a small shift towards higher BI values, through mediating slow-down in mid-latitudes

Lc + SWc + SEw

Warm SST north of AUS

Tropical heating

Cold SST north of AUS

Clear shift in the BI distribution towards higher/lower BI values associated with warm/cool SST to the north of Australia

Implications for model biases (cf. Hinton et al. 2009) Ummenhofer et al. (2013)

Tropical heating

Warm SST north of AUS

Cold SST north of AUS

500hPa height anomaly

Combined effects - BIBLmax

Clear shift in the BI distribution towards higher/lower BI values associated with BLmax/BLminconfiguration BLmax/BLmin act on mid-latitude component, BLmin also on subtropical jet

Select years with highest and lowest 10% BI in CESM Interannual

variability

Select sustained periods with high/low BI in CESM Decadal variability

Decadal blocking variability in CESM1300-yr pre-industrial control simulation BI time-series (JJA)

Decadal blocking variability in CESM

Freisen and Ummenhofer (in prep)

High blocking decadesLow blocking decades

Summary- Seasonal cycle of blocking in Australian region associated with

- major seasonal temperature changes over AUS and smaller changes over surrounding oceans- favorable background state for blocking due to geographical configuration and positive W-to-E SST gradient in Indo-Australian sector

- Investigated effect of surface forcing on BI in AUS-NZ sector, through changes in individual components:

- Extratropical temperature gradients induced small changes in BI- Tropical heating affected BI through changes in subtropical jet and as source for Rossby wave generation

- BLmax improves blocking, through changes in subtropical jet and in particular mid-latitude slowing down

- Decadal variability in SH blocking in a 1300-yr CESM control simulation associated with extratropical anomalous SST to South of AUS

References- Freisen P and Ummenhofer CC (2016) Decadal variability in atmosphericblocking in the Southern Hemisphere and its impact on Australian rainfall.Geophysical Research Letters, in prep.

- Pook M et al. (2013) The seasonal cycle of blocking and associatedphysical mechanisms in the Australian region and relationship with rainfall.Monthly Weather Review, 141, 4534-4553.

- Ummenhofer CC et al. (2013) Impact of surface forcing on SouthernHemisphere atmospheric blocking in the Australia-New Zealand sector.Journal of Climate, 26, 8476-8494

For further information: www.whoi.edu/ummenhofer