J. Sauber, S. Luthcke, S-Ch Han, D. Hall, (NASA GSFC)

Collaborators:R. Bruhn, R. Forster, M. Cotton, E. Burgess, J. Turrin (U of Utah)

B. Molnia, K. Angeli and ASC staff (USGS)N. Ruppert (UAF, AEIS), R. Muskett, C. Lingle (UAF)

R. King, T. Herring (MIT), S. McClusky (ANU)

Measurement and Modeling of Cryosphere Geosphere Interactions‐

AB35

GRACE

•Cryosphere-Geosphere signals in campaign and PBO GPS observations•Cryosphere change from GRACE•Post-1964 earthquake gravity change & ice mass change trends

Terra

Campaign GPS

GPSPBOGPS

AB35

ISLE

DON

ISLE

MacBook Air Dual Core

Mac Desktop 6 Cores

Mac Cluster~50 cores

DISCOVER (GSFC HEC) Use ~150 cores

PyLith & other numerical models GRACE processing of L1B data:

The GPS station positions for both sites are predicted to move to the north-northwest (NNW) and up due to (steady) tectonic forcing (PCFC relative NOAM)

1993-1995 surge interval versus post-surge time period, 1996-2001:

• A higher uplift rate for ISLE. Site is moving faster to the northwest. Ice unloading to the south of the site would cause uplift & north directed motion. • In contrast, the station DON is undergoing vertical subsidence during the surge but uplift subsequently (as predicted for tectonic loading). The rate of the northward motion is lower during the surge.Sauber and Molnia, 2004

1993-1995 Bering Glacier Surge: A Solid Earth Geophysicist ViewRepresent 10s of meters of drawdown (unloading) in surge reservoir and thickening & terminus advancement in receiving/terminus (loading) region as disc loadsAs a “local load”, use elastic half-space model or radially stratified, gravitating Earth model to predict vertical and horizontal displacements [Farrell, 1972].

reservoir

receiving

ISLE

DON

ISLE 38 mm uplift

DON -42 mm

Predicted Horizontal Displ.

Predicted Vertical Displ.

N: 12 mm E: -5.5

N: 7 mm E:4 mm

Surge Related

Assumptions & Limitations in predicted values:1.1993-1995 net transfer of ice mass from surge reservoir to receiving area over the duration of surge is equal (~14km3). GPS motions reflect magnitude of (un)loading & can be used to invert for process scaling factor. 2.Ignores seasonal snow/ice build-up & summer melting. Horizontal component is complex due to tectonic strain as well as possible push moraine toward DON due to surge .

Elliott et al.,2013 estimates of horizontal site velocities between 2005-2008: DON: ~43 mm/yr @N30oWISLE: ~20 mm/yr @N14oW

Sauber et al., 2000

reservoir receiving

Above: Repeated aircraft laser altimetry of elevation change (m/yr)

Surge dynamics on Bering Glacier, Alaska, in 2008–2011 E.W. Burgess , R. R. Forster , C. F. Larsen , and M. Braun, Cryosphere, 2012

Below: L-, C- and X-band SAR derived ice horizontal displacement rate (m/day) via offset/speckle tracking methods along a longitudinal profile of the Bering Glacier

2008-2011 was a smaller surge than 1993-1995, with less terminus advancement

GPS PBO observations in this areabegan ~ 2007

-4 to -1 -1 to 0 0 to 1 1 to 2 2 to 3 > 3 oC

March 2005

March 2012

MONTHLY Mean Land Surface Temperature (LST) from Terra MODIS (11.02 and 12.02 mm)

AB42

AB35AC09

Melt onset Sauber et al., AGU, 2013

North

East

Up

•Similar rates of horizontal deformation at the 3 coastal GoA sites .•Uplift rates are more variable. (SOPAC GPS Explorer combined solution)

AB42

AB32

AC09

Detrended North, East and Up for AB42, AB35, and AC09 (SOPAC, GPS Explorer)

Up annual term (mm): AB42: 12.9 + 0.1 AB35 = 10.5 + 0.1 AC09 = 7.9 + 0.1

GPS multipath for snow depth estimation (K. Larson & colleagues):

AC09

Up to almost a meter of snow near AC09. In this marine environment the snow has high water content and undergoes compaction as the season progresses.

Snow loading begins ~Mid-September to October and reaches a maximum in late Feb-March. 1 km (hydrologist) versus 10 km (geophysicist) versus regional estimates.

CIG Pylith finite element model:

--Single 10km load at (0,0) with time history given by AC09 snow profile & r = 1.

--20 km elastic layer over 80km Maxwell viscoelastic layer

meters

90 days

meters

No of days*10

Solid Earth responseto Snow Loading

Nov

embe

r Mar

ch

April

-4 to -1 -1 to 0 0 to 1 1 to 2 2 to 3 > 3

May 2005

May 2012

AC09AB35

AB42

May 2012-4 to -1 -1 to 0 0 to 1 1 to 2 2 to 3 > 3 oC

Snow mostly gone

GRACE estimates of mass change

GSFC Mascon solution, Luthcke et al., J. of Glaciology, 2013 12

• 41,168 equal area 1-arc-degree mascons are directly estimated from GRACE KBRR L1B data from the GRACE project [Tapley et al., 2004] with spatial and temporal exponential taper constraints applied.

• 10-day temporal resolution• Spatial constraint: 100 km correlation distance• Temporal constraint: 10-day correlation• Includes: LIA (Larsen et al., 2005)

and ICE5G(Peltier, 2004) corrections

Gt

Overall G of Alaska Trend = -69 ± 11 Gt a-1

but note variability from year to year such as the cold (2012) versus warm water (2005) years.

Gulf of Alaska mascons (61)

cmw.e.

Mascon 1484: North Central Smaller seasonal signal Moderate 10-year trend

Mascon 1457: Central Coastal (study area) Moderate seasonal, 50 -75 cm w.e.Largest 10-year trend

Year

*

*

Mascon 1425, South Eastern Alaska:Large seasonal, up to 100 cm w.e. (p to p) Small 10 year-trend in ice mass loss

SE

NC

Gulf of Alaska

*

1425

1484

1457

Regional Variability:

GRACE MASCONS near three cGPS sites

1449 (AB42)

1457 (AC09)

1456 AB35)

cmw.e.

Reminder: GRACE is sensitive to changes at spatial scales >300kmNEXT SLIDE: We use the estimate of the temporal history of mass changeto estimate surface load changes again assuming a 10km load near a site.

CIG Pylith finite element model:

--Single 10km load at (0,0) with time history ((cm w.e. profile) given by GRACE water year 2012

--20 km elastic layer over 80km Maxwell viscoelastic layer

Nov

embe

r

Febr

uary

Augu

st -

Sept

embe

r.Days x 30

Postseismic gravity change in EWH [cm/yr]

Epicenter of the 1964 Alaska earthquake

~1 cm/yr

Simulation of the present-day postseismic gravity change1964 Mw = 9.2 Prince William Sound (Alaska) earthquake

- Used Johnson et al. [1996] finite fault model: inversion of tsunami and geodetic data to estimate 1964 coseismic slip

- We used the viscoelastic Earth model that is consistent with other studies in this region [Suito and Freymueller, 2009; Sato et al., 2010]

- Global normal mode relaxation code was used to compute the gravity change over the period 2002 - 2014. (Courtesy of R. Riva and F. Pollitz)

=> ~1 cm/yr of gravity change (in w.e.) is predicted, primarily dependent on the asthenosphere viscosity (1019 Pa s)

Spherical harmonic coefficients from RL05 CSR L2 monthly data,degree up to 60; ~330 km resolution.

Schematic

Time-series at the epicenter (60N 212W)

GRACE secular trend ~ –8.3 cm/yr (observed RL05 CSR L2 )1964 EQ postseismic change ~ +1.0 cm/yr (model predicted)

The postseismic gravity change could be as large as 10% of the observed mass change, even 50 years after the 1964 earthquake.

How does cryosphere mass change on times scales of months to years in southern Alaska? 1. The individual GRACE mascons located in distinctly different regions capture important inter-

annual variations in the magnitude of the seasonal signal wastage trend. 2. These GRACE differences are important for estimating the timing and magnitude of broad-

scale differences between regional GPS sites; however, more local estimates of changes in snow/ice extent and magnitude are needed to model cryosphere signal in GPS time series.

As estimated from EarthScope GPS data and FEM modeling, how do the surface displacements due to inter-annual and seasonal cryosphere mass change compare to tectonic displacement rates?

3. In the study region the surface horizontal displacements due cryosphere changes are generally <10% of the tectonic displacements whereas the vertical displacements can be comparable in magnitude to predicted tectonic uplift rates in localized regions near glaciers.

4. With a longer history of continuous GPS, and careful management of the sites, we may be able to use GPS derived changes in vertical and horizontal displacements to constrain process oriented models of cryosphere changes.

Summary