The University of Arizona’s Contribution to RASM Michael A. Brunke and Xubin Zeng

Vegetation dataset generation 2VEGETATION DYNAMICS  GIMMS 16 km NDVI for  Maximum GVC based on Zeng et al. (2000):  Varies from year to year.  De-greening of Taimyr Peninsula.

Vegetation dataset generation 3VEGETATION DYNAMICS  MODIS 1 km NDVI for 2002-present (Patrick Broxton)

Vegetation dataset generation 4VEGETATION DYNAMICS  LAI also provided by the MODIS team.  Can see progression of LAI from tropics poleward as leaves bud out in spring and back towards tropics with senescence in fall. (Thanks to Patrick Broxton)

Implementation of CN(DV) into VIC 5VEGETATION DYNAMICS UAUW Implement VIC4.1.2.d into RASM. Implement CN into offline VIC4.1.2.d. 1

Implementation of CN(DV) into VIC 6VEGETATION DYNAMICS VICCN Surface met Soil moisture/temp. LAI Canopy geometry Root distribution

Implementation of CN(DV) into VIC 7VEGETATION DYNAMICS UAUW Implement VIC4.1.2.d into RASM. Implement CN into offline VIC4.1.2.d. Implement VIC-CN into RASM. Test offline VIC-CN/comparison to flux tower data Test RASM simulation with VIC-CN. 4 VIC-CNDV development

Bias in r32RB1a 8TEMPERATURE BIAS MERRA r32RB1a r30RB1g  Warm biases replaced by cool biases in eastern Canada and northern Eurasia.

Bias in r32RB1a 9TEMPERATURE BIAS MERRAr32RB1ar30RB1g 0Z 3Z 6Z 9Z 12Z 15Z 18Z 21Z  Warm biases replaced by cool biases in eastern Canada and northern Eurasia.  Cool bias worse during the daytime.

Bias in r32RB1a 10TEMPERATURE BIAS ON KZ January

How does albedo affect r33? 11TEMPERATURE BIAS January KZ ON

How does albedo affect r33? 12TEMPERATURE BIAS September KZ ON

Using RASM 13HUMIDITY INVERSIONS  Ready to use RASM to analyze specific humidity inversion climatology in the Arctic.  Finer detail of humidity inversions in RASM.

Using RASM 14HUMIDITY INVERSIONS  Ready to use RASM to analyze specific humidity inversion climatology in the Arctic.  Finer detail of humidity inversions in RASM.  Can compare with IPCC models.