Brandon J. Fisel

Geological & Atmospheric Sciences

Working Prospectus Outline

Program of Study Committee:

William Gutowski

John Cassano

Mike Chen

Gene Takle

Ray Arritt

I. Analysis of the energy and moisture budgets in a Regional Arctic System Model (RASM)

A. Comparisons of the energy and moisture budgets in RASM versus stand-alone WRF simulations

1. Background

a. Arctic energy budget – Porter et al. (2010), Semmler et al. (2005), Serreze et al. (2007), Walsh et al. (2008)

b. Arctic moisture budget – Cullather et al. (2011), Jakobson et al. (2010), Serreze et al. (1995), Serreze et al. (2006)

2. Calculation of budgets in RASM

a. Polar wall at 70° N. latitude - Porter et al. (2010), Serreze et al. (2007), Genthon and Krinner (1998), Nakamura and Oort (1988), Peixoto and Oort (Phys. Of Climate), among others

b. Polar cap at 70° N. to NP is made up of 72% ocean, 28% land

3. Methods

a. Regional Arctic System Model (RASM) with WRF/VIC using specified SST’s and sea ice

b. Stand-alone WRF with specified SST’s and sea ice

c. Forcing data – ERA-Interim

i. ERA-Interim is on a lat-lon grid

ii. WRF is on a curvilinear grid – rcm2rgrid_Wrap to regrid WRF to lat-lon grid

iii. Have to rotate winds on lat-lon grid making them “true” winds

d. Simulations –

i. Resolution – 50 km horizontal; 30 levels vertical

ii. Ensemble – ?

iii. Integration length – long (i.e., 25 yr. to length of ERA-Interim) or during period with observations (e.g.,CERES, ect.)

iv. model spin-up for land/ocean

v. How to handle Greenland elevation?

4. Results

a. Evaluation of RASM’s individual energy and moisture budgets and differences between RASM and stand-alone WRF energy moisture budgets.

i. TOA radiation fluxes, energy convergence, transport across polar cap and surface fluxes and energy storage, Greenland ice-sheets (?)

ii. Influence of feedbacks in RASM versus stand-alone WRF

A. ice-albedo feedback

B. snow-albedo feedback

II. Impact of increased model resolution on energy and moisture budgets in the fully-coupled RASM model

A. Sensitivity of RASM energy and moisture budgets to increased resolution

1. Background

a. Hack et al. (2005)

2. Calculation of moisture budget in RASM

a. Polar wall at 70° N latitude

b. Polar cap at 70° N to NP is made up of 72% ocean and 28% land

3. Methods

a. Fully coupled regional arctic system model (RASM)– WRF, VIC, POP, CICE and others; WRF parameterization schemes

b. Forcing data – ERA-Interim

i. ERA-Interim is on a lat-lon grid

ii. WRF is on a curvilinear grid – rcm2rgrid_Wrap to regrid WRF to lat-lon grid

iii. Have to rotate winds on lat-lon grid making them “true” winds

c. Simulations

i. Resolution – 50 km horizontal and 10 km; 30 levels vertical; POP/CICE at 1/12°

ii. Ensemble – ?

iii. Integration length – long (i.e., 25 yr. to length of ERA-Interim) or during period with observations (e.g.,CERES, ect.)

iv. model spin-up for land/ocean

v. How to handle Greenland elevation?

d. Observations

i. Arctic precipitation - Russian ice drifting stations available for 1950-1991 located at NSIDC (Colony et al., 1998; Yang, 1999), Tiksi Arctic observatory (1938-present), Barrow Observatory (2007-present), ArcticRIMS

e. Re-analysis

i. Mass balance corrections in ERA-Interim re-analysis data

A. Mass is not conserved on pressure levels in re-analysis (Boer and Sargent, 1985; Alexander and Schubert, 1990; Trenberth, 1991)

B. Velocity fields should be adjusted so p_s’ for monthly means are balanced

C. Direct/indirect methods and compute residual (Serreze et al., 2007) to estimate degree of mass balance at a grid point

D. Trenberth (1991; 1997; 2001), Meyer et al. (2011), Serreze et al. (2007), among others

4. Results

a. Evaluation of RASM’s individual energy and moisture budget components at increased resolution and comparisons with re-analysis energy and moisture budgets

i. TOA radiation fluxes, energy convergence, transport across polar cap and surface fluxes and energy storage, surface moisture flux including horizontal transport across polar cap, longitudinal variance (?), Greenland ice sheets (?)

ii. Effect of model resolution on energy and moisture budgets

A. Comparisons with mass-balanced ERA-Interim re-analysis energy and moisture budgets

III. Impact of cloud cover on ice-albedo feedback during recent years of changing sea ice and effect on arctic energy (moisture?) budget(s)

A. As the climate system continues to warm, the atmosphere may hold more water allowing for increases in cloud, especially between spring and fall seasons. Sea ice has also been experiencing more melt in the recent decade and is expected to continue to decline in area in the future as the Arctic warms, increasing the albedo of the oceans and allowing for more solar radiation to be absorbed into the ocean, allowing for additional melt: a process known as the ice-albedo feedback (positive feedback). It is still uncertain whether increases in cloud cover in the arctic (especially during summer when sea-ice melt is occurring and also in fall when sea ice begins to refreeze) could amplify or dampen the ice-albedo feedback. Studies have found that more cloud cover is occurring over sea ice during summer and increasing low-cloud cover over open ocean during fall. The increasing cloud cover during fall may allow a cloud-ice feedback (positive) that acts to insulate the arctic boundary layer allowing for additional melt or a delay in refreezing of sea ice. This delay in refreezing of sea ice during the fall will promote thinner sea ice; sea ice that is more likely to melt the next spring. Understanding the effects of cloud on the ice-albedo feedback (specifically the longwave component) may allow for implications to be made about a future sea-ice tipping point: a period (approximately 1 month or longer) when arctic sea ice disappears.

1. Background

a. Holland et al. (2010), Mahlstein et al. (2011), Porter et al. (2010), Screen et al. (2010), Tietsche et al. (2011)

b. Melting of sea ice leads to a decrease in surface albedo, allowing for additional ocean heating, which then allows for additional melting of sea ice

2. Methods

a. Fully coupled regional arctic system model (RASM)– WRF, VIC, POP, CICE and others; WRF parameterization schemes

b. Forcing data – ERA-Interim

i. ERA-Interim is on a lat-lon grid

ii. WRF is on a curvilinear grid – rcm2rgrid_Wrap to regrid WRF to lat-lon grid

iii. Have to rotate winds on lat-lon grid making them “true” winds

c. Simulations

i. Resolution – horizontal resolution determined in energy budget papers – 30 vertical levels (?)

ii. Ensemble – (?)

iii. Integration length – > 10 years, multi-decadal simulations(?)

iv. model spin-up for land/ocean

v. How to handle Greenland elevation?

d. Observations

i. Global Precipitation Climatology Project (GPCP), CERES/CERES-EBAF

ii. ERA-Interim

e. Re-analysis

i. Mass balance corrections in ERA-Interim re-analysis data

A. Mass is not conserved on pressure levels in re-analysis (Boer and Sargent, 1985; Alexander and Schubert, 1990; Trenberth, 1991)

B. Velocity fields should be adjusted so p_s’ for monthly means are balanced

C. Direct/indirect methods and compute residual (Serreze et al., 2007) to estimate degree of mass balance at a grid point

D. Trenberth (1991; 1997; 2001), Meyer et al. (2011), Serreze et al. (2007) among others

3. Results

a. Comparisons observations (?) and mass-balanced ERA-Interim re-analysis energy/moisture budgets

b. Implications: future changes in energy budgets due to further decline in sea ice and can sea ice reach a tipping point?

Additional notes/random thoughts:

Decadal RASM simulations (1970-1980; 1980-1990;1990-2000;2000-2010) will be used to examine the influence of anomalous energy flux convergence (F_wall) on preconditioning ice melt during early summer (JJA) and increased oceanic heat loss to sustain ice melt during fall (JAS)

As the climate system continues to warm the atmosphere may hold more water allowing for increases in cloud, which allows for further warming, a positive feedback. What are the effects that increased cloud cover during the fall/winter have on the arctic energy budget? Could this positive feedback during the fall/winter allow for additional sea-ice melt during the fall and act as a further precondition mechanism for earlier sea-ice melt the following spring? The ocean heat loss would be delayed during the fall due to heat gained during the summer and cloud cover radiation feedback (increased cloud -> increased downward longwave radiation). Is there an increase in horizontal heat transport then during late fall/winter due to radiation positive feedback? What is the interannual variability of the net radiation from the ocean and does this increase/decrease during the fall/winter?

Increasing heat during June/July in F_sfc leading to later refreeze of sea ice – near constant F_wall/F_rad with larger F_sfc during SON leading to more energy storage dE/dt in the arctic?

Boundary conditions coming from GCM

RASM simulations into future

Link between energy/moisture budgets and extremes – changes in energy/moisture budgets allowing for a more extreme, future arctic?

Can the RASM model duplicate the same regime behavior found in the Regimes manuscript? How does the delay of sea ice freezing in fall affect the variability of the fall atmospheric circulation (SON)? Do we see a shift in similar regime behavior occurring in summer to early/later fall (SON) due to more heat being released by the ocean caused by the delay of freezing sea ice? RASM should be run for at least 10 years. Effect on model regimes using modeled sea surface temperatures versus specified SST’s?