1. Collaborative Research: Towards Advanced Understanding and Predictive Capability of Climate Change in the Arctic using a High- Resolution Regional Arctic Climate System Model Iowa State University Role

2. Two New Graduate Students Justin Glisan (Ph.D.) M.S. Thesis (U. Missouri) - Two Extreme Cases of Atmospheric Blocking Over Europe and North America -2004 JJA “Baked Alaska” event Propose: Evaluation of model by analyzing persistent extremes in model (atmosphere alone and/or coupled model) and observations Brandon Fisel (M.S.) Background/interest in surface-atmosphere coupling Propose: Evaluation of model by focusing on episodes of strong air-sea interaction when gaps in ice appear

3. Work done Fall 07 with Ben Schwedler (hourly undergraduate) No data assimilation on interior

4. Work done Fall 07 with Ben Schwedler (hourly undergraduate) With data assimilation on interior

5. Work done Fall 07 with Ben Schwedler (hourly undergraduate) * Seem to be centered on model domain, not on the pole. Implies a geometric factor? But why high bias to sides and low toward center? * What is rms time variability of the field? How does that compare to the rms difference between the two runs on a day-by- day basis? (Wondering how much is due to phase difference as opposed to actual bias) * Appears that model's lows are deeper and (maybe) propagate more readily to the east. Perhaps highs are higher, too. * Storms seem to get much deeper and times and propagate more readily into the Arctic. Storm tracks shifted poleward? Is there a difference in sea ice or SST vs. reanalysis? * How do winds compare with actual rawinsondes?

6. Work done Fall 07 with Ben Schwedler (hourly undergraduate) PLAN: 1. Compute the temporal RMS variability about the time average, for each grid point (for MSLP). Then, also compute the domain average, by taking the average of the variance and then the square root. This should all be done on a monthly basis. 2. Compute the difference between the "reanalysis" and the simulation, where the "reanalysis" is the boundary conditions data that has been interpolated to the MM5 grid. Then get * monthly average bias * monthly standard deviation of differences at each grid point * domain averages of both of these. 3. Do these for the first 13-month simulation. Might then look at additional years. 4. Look at other fields? Might want to look at vertical profiles of bias.

7. MSLP - SEPTEMBER

8. MSLP - SDEV

12. Other items Effect of Permafrost Changes: Model of annual soil moisture fraction (b) Fixed annual precip. ET varies with b

13. Other items Wave fetch, strong storms -- coastal erosion