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Task 1

Objectives

1. To better understand atmospheric impact of SST, sea ice, and snow cover

2. To assess the relative contributions of SST, sea ice, snow cover, and internal atmospheric dynamics in recent NH climate change

Models:

• Six models: CAM4(0.9x1.25deg.L26)/WACCM(L66), IFS(T255L91), ECHAM5(T106L31), IAP(1.4x1.4deg.L26), LMDZ (2.5x1.25deg.L39)

• Low and high top, low and high-horizontal resolution

Experiments

Tier1

• AGCM with full sea ice and SST variations

• AGCM with full sea ice and climatological SST variations

• Period 1982 to 2013 2014 (revised in May2015)

• Number of ensemble: 20 member for each experiments to be determined by each group (e.g., different days in January 1981)

• Daily SST and sea ice variations will be used

Tier 2

• Case studies based on analysis of tier 1 experiments to better diagnose mechanisms

• Experiments to assess impact of snow cover variations

Boundary conditions (BCs) and external forcing

Description

• Under maintainance on missing data periods (Asking NOAA to fix that. 26th March 2015 by Fumiaki Ogawa). Now revised version is available.

• NOAA Optimum Interpolation 1/4 Degree Daily Sea Surface Temperature Analysis – version2, AVHRR-only product. This extends from September 2001 till present. The sea ice for 1981-2004 is from Cavalieri et al. [1997,2005]. The sea ice from 2005 to present is from Grumbine et al. [1998].

• Reference for the data Reynolds et al. [2007].

• Transient forcing following CMIP5 protocol. Specifically, "historical" until the end of 2005 while RCP8.5 from 2006 onward.

• Boundary conditions for the experiments with observed varying SIC and climatological SST follows Screen et al. [2013]: In any grid box north of 40N, if the daily mean SIC deviated from daily climatology by > 10%, the grid box was set to observed SIC and SST. All the grid boxes south of 40N and at grid boxes north of 40N where the daily mean sea ice concentration was within 10% of the climatological daily mean, observed SIC and climatological SST were used.

• NOAA data are provided from http://www.ncdc.noaa.gov/sst/index.php; 1982~2013 2014 was used to prepare the BCs.

• NOAA original BC data has error, therefore year-to-year daily anomaly was linearly interpolated 29Nov1987-18Jan1988 (SIC) and 27Apr2009-19May2009 (SST&SIC) for the GREENICE experiments.

• BC data can be downloaded from the links below.

Download BCs

• Hexagon

hexagon.bccs.uib.no:/work/shared/nn9039k/GREENICE/OISST/OISST.GREENICE-AGCM.sstice.nc (SST clim)

hexagon.bccs.uib.no:/work/shared/nn9039k/GREENICE/OISST/OISST.sstice.nc

• NorStore

norstore.uio.no:/projects/NS9039K/shared/GREENICE/OISST/OISST.GREENICE-AGCM.sstice.nc

norstore.uio.no:/projects/NS9039K/shared/GREENICE/OISST/OISST.sstice.nc

• Online

http://ns9039k.web.sigma2.no/GREENICE-OISST/OISST.GREENICE-AGCM.sstice.nc

http://ns9039k.web.sigma2.no/GREENICE-OISST/OISST.sstice.nc

http://ns9039k.web.sigma2.no/GREENICE-OISST/README (currently a place holder)

Some specific issues to be addressed by groups

• Role of stratosphere-troposphere interaction at medium horizontal resolution ~1deg by comparing low versus high top simulations with daily SST and SIC data (UiB/NERSC)
• Anti-phase correlation of the Siberia High between November and December-January (NERSC, L Suo, Y Gao)

Task 2 (added on 27 March 2017)

Objectives

1. To assess the uncertainties of Northern Hemisphere climate change contributed by the change of sea ice cover and sea surface temperature (SST)

2. To provide better constrained predictions of near-term (10-30 year) changes in Northern Hemisphere climate and associated weather extremes

Experiments

Design

• The uncertainties are quantified by the inter-model spread of the forced response between the RCP8.5 run (2069-2098) and the historical run (1971-2000) in 11 models participating in the fifth phase of the Coupled Model Intercomparison Project (CMIP5). These 11 models have at least three ensemble members in both runs, which can suppress the signals due to internal climate variability.

• The uncertainties of Northern Hemisphere climate change are represented by the sea level pressure (SLP).

• A singular value decomposition (SVD) analysis is applied to the annual-mean forced response of Northern Hemisphere SLP (left vector) and the annual-mean forced response of Arctic sea ice concentrations (SIC) merged with SST (right vector) across 11 models. The first SVD (SVD1) pattern infers the largest amount of uncertainties and spatial inhomogeneity of the Northern Hemisphere climate change coupled with SIC and SST.

• To get the monthly varying inter-model spread of the boundary conditions, the monthly forced response of SIC and SST is projected to the heterogeneous SVD1 pattern of SIC merged SST.

Tier 1

Run	Period	SIC	SST
0	1971-2000	Monthly varying MME climatology	Monthly varying MME climatology
1	2069-2098	Monthly varying MME climatology	Monthly varying MME climatology
2	2069-2098	Monthly varying MME climatology adds the inter-model spread	Monthly varying MME climatology adds the inter-model spread
3	2069-2098	Monthly varying MME climatology subtracts the inter-model spread	Monthly varying MME climatology subtracts the inter-model spread
4	2069-2098	Monthly varying MME climatology	Monthly varying MME climatology adds the inter-model spread
5	2069-2098	Monthly varying MME climatology	Monthly varying MME climatology subtracts the inter-model spread
6	2069-2098	Monthly varying MME climatology adds the inter-model spread	Monthly varying MME climatology
7	2069-2098	Monthly varying MME climatology subtracts the inter-model spread	Monthly varying MME climatology

• MME refers to the multiple model ensemble of the 11 CMIP5 models

Tier 2

Additional experiments will be performed to identify the key SST and sea ice regions responsible for the uncertainties of Northern Hemisphere climate change

Download boundary conditions (BCs)

• SST

http://ns9064k.norstore.uio.no/GREENICE_WG2/sst.svd1.GREENICE.WG2.V20170227.nc

• SIC

http://ns9064k.norstore.uio.no/GREENICE_WG2/sst.svd1.GREENICE.WG2.V20170227.nc

Downloading monthly outputs (only the outputs of task 1 are available; last update: 27 March 2017)

Use web browser:

https://webserver1.norstore.uio.no:8443/GREENICE

Note that you need ID and password.

Downloading through a linux terminal is like:

wget --http-user="the ID" --http-password="the password" https://webserver1.norstore.uio.no:8443/GREENICE/WP1/${EXP}/${MODEL}/${FILE}.nc

Note wget may not work if its version is 1.13 or older (see wget -h).

Output variables

To be made available by each modeling group.

Summary chart for uploading monthly & constant data to Norstore

3D variable- Summary for uploading monthly data

description	variable name	unit	note
temperature	ta	K
u wind	ua	m/s	positive for eastward
v wind	va	m/s	positive for northward
Specific humidity Humidity	hus hur	1 %
vertical velocity	wap	Pa/s	negative for upward motion
GPH	zg	m

2D variable- Summary for uploading monthly data

description	variable name	unit	note
SLP	psl	Pa	not hPa
Surface pressure	ps	Pa	not hPa
Radiation, Longwave, Downward, Surface	rlds	W/m2	positive for downward
Radiation, Longwave, Upward, Surface	rlus	W/m2	positive for upward
Radiation, Shortwave, Downward, Surface	rsds	W/m2	positive for downward
Radiation, Shortwave, Upward, Surface	rsus	W/m2	positive for upward
Radiation, Longwave, Upward, TOA	rlut	W/m2	positive for upward
Radiation, Shortwave, Downward, TOA	rsdt	W/m2	positive for downward
Radiation, Shortwave, Upward, TOA	rsut	W/m2	positive for upward
Evaporation	evspsbl	kg/m2/s
Surface temperature	ts	K	not Celcius
10m u wind	uas	m/s	positive for eastward
10m v wind	vas	m/s	positive for northward
Cloud cover, Total	clt	%
Cloud cover, Low-level	cll	%
Cloud cover, Mid-level	clm	%
Cloud cover, High-level	clh	%
Snow cover	snc	%
Snow liquid water equivalent	lwsnl	kg/m2
Precipitation, Total	pr	kg/m2/s
Precipitation, Large Scale	prl prlprof	kg/m2/s
Precipitation, Convective	prc prcprof	kg/m2/s
Precipitation, Snow	prsn	kg/m2/s
2m tempareture	tas	K	not Celcius
Upward Heat Flux, Latent, Surface	hfls	W/m2	positive for upward
Upward Heat Flux, Sensible, Surface	hfss	W/m2	positive for upward
Surface downward U wind stress	tauu	Pa	positive for eastward
Surface downward V wind stress	tauv	Pa	positive for northward
Prescribed SST	tos	K	not Celcius. Name is not SST
Prescribed SIC	sic	%

2D Constant- Summary for uploading

description	variable name	unit	note
Surface Altitude	orog	m
Land Area Fraction	sftlf	%

3D-fields (daily)

• temperature

• wind u, v

• humidity

• vertical velocity

• GPH

Levels (hPa): 1000 925 850 700 600 500 400 300 250 200 150 100 70 50 30 20 10 7 5

2D-fields (daily)

• SLP

• surface pressure

• all radiation components (both clear and all sky fluxes)

• evaporation

• daily max/min temperature

• surface temperature

• 10m wind

• cloud cover (total, low, medium, high)

• Cloud liquid water content

• cloud ice water content

• total column water

• total column water vapor

• soil temperature (several layers)

• soil wetness (several layers)

• runoff (surface and deep)

• snow cover

• snow depth and density or liquid water equivalent.

• Total precipitation

• T2m

• Surface fluxes (latent, sensible, momentum)

• Precipitation (large scale, convective, snow)

2D fields at 3hrly frequency

• T2m

• Surface fluxes (latent, sensible, momentum)

• Precipitation (large scale, convective, snow)

• SLP

• 10m wind

Experiments to start by mid-November to be completed by the first year annual meeting <= delayed a little...

Technical setup of AGCM

WACCM/CAM4(low-top)

• by Fumiaki Ogawa (WACCM, UiB) and Lingling Suo (CAM4, NERSC)

• Output levels of WACCM are same as CAM4 below 100hPa, while split above there into 30 levels in total (originally 66).

GREENICE output

WACCM/CAM4(low-top)

• See the instruction to download the data : http://ns9064k.norstore.uio.no/README.shared

References

• Cavalieri D., C. Parkinson, P. Gloerson, and H.J. Zwally. 1997, updated 2005. Sea ice concentrations from Nimbus-7 SMMR and DMSP SSM/I passive microwave data, June to September 2001. Boulder, CO, USA (from http://nsidc.org/data/nsidc-0051.html)

• Grumbine, R. W., 1996: Automated passive microwave sea ice concentration analysis at NCEP, 13pp. Unpublished manuscript available from NCEP/NWS/NOAA, 5200 Auth Road, Camp Springs, MD, 20746, USA. (from http://polar.ncep.noaa.gov/seaice/)

• Reynolds, R. W., T. M. Smith, C. Liu, D. B. Chelton, K. S. Casey, and M. G. Schlax (2007), Daily high-resolution-blended analyses for sea surface temperature, J Climate, 20(22), 5473-5496

• Screen, J. A., I. Simmonds, C. Deser, and R. Tomas (2013), The Atmospheric Response to Three Decades of Observed Arctic Sea Ice Loss, J Climate, 26(4), 1230-1248, 10.1175/jcli-d-12-00063.1.

• Ogawa, F., N., Keenlyside, Y., Gao, T., Koenigk, S.Yang, L.,Suo, T., Wang, G., Gastineau, T., Nakamura, H. Cheung, N.-E., Omrani, J. Ukita, V., Semenov (2018): Evaluating impacts of the Arctic sea-ice loss on the northern hemisphere climate changes, Geophysical Research. Letters, 45, doi:10.1002/2017GL076502.

• Ogawa, F., Koenigk, T., Yang, S., Gastineau, G., Wang, T., Nakamura, T., Suo, L. (2018). The outputs from GREENICE coordinated AGCM hindcast experiments driven by NOAA OI SST and sea ice data, Norstore research data archive. https://doi.org/10.11582/2018.00007

• Koenigk. T., Y. Gao, G. Gastineau, N. Keenlyside, T. Nakamura, F. Ogawa, Y. Orsolini, V. Semenov, L. Suo, T. Tian, T. Wang, J. Wettstein, S. Yang (2018): Impact of Arctic sea ice variations on winter temperature anomalies in northern hemispheric land areas, Climate Dynamics, 51, doi: 10.1007/s00382-018-4305-1.

Contact informations

Fumiaki.Ogawa@gfi.uib.no (about Task 1), Ho.Cheung@uib.no (about Task 2), Noel.Keenlyside@gfi.uib.no (Other related questions)