ALBEDO OPTIMIZATION

Select region:

STEP 1 : LEAF ALBEDO OPTIMIZATION

Data points selection (month-pixels from climatology 2009-2018) :

Optimization method: global L-BFGS-B with analytical gradient calculation (14 optimized parameters)

ndata - total number of used month-pixels, npts - total number of used grid pixels

LEAF_ALB_NIRPFT2PFT3PFT4PFT5PFT6PFT7PFT8PFT9PFT10PFT11PFT12PFT13PFT14PFT15
prior0.230.180.180.20.240.150.260.20.240.270.280.260.240.24
min0.170.170.10.10.160.10.10.160.10.170.10.150.10.2
max0.250.240.230.240.240.190.330.230.360.360.460.360.290.35
post0.2040.1890.150.1760.2280.1290.2630.1780.2960.2580.2590.2920.2220.323
LEAF_ALB_VISPFT2PFT3PFT4PFT5PFT6PFT7PFT8PFT9PFT10PFT11PFT12PFT13PFT14PFT15
prior0.040.040.040.040.030.030.030.030.060.060.060.060.060.06
min0.020.020.010.010.020.010.020.020.020.040.020.050.020.04
max0.060.080.090.080.070.050.040.040.180.180.230.150.160.1
post0.02250.020.02310.02310.020.02340.020.020.04640.04850.05130.06060.020.04


STEP 2 : SNOW ALBEDO OPTIMIZATION

Data points selection (day-pixels from 2018) :

Optimization method: global L-BFGS-B with analytical gradient calculation (8 optimized parameters)

ndata - total number of used month-pixels, total npts - number of used grid pixels

SNOW_ALB_NIRPFT1PFT4/5/7PFT6/8/9PFT10-15
snowa_aged_prior0.50.30.30.5
snowa_aged_min0.30.10.10.3
snowa_aged_max0.70.50.50.7
snowa_aged_post0.4920.1650.2790.525
snowa_dec_prior0.150.150.150.15
snowa_dec_min0.050.010.010.05
snowa_dec_max0.30.30.30.3
snowa_dec_post0.1220.01640.04350.054
SNOW_ALB_VISPFT1PFT4/5/7PFT6/8/9PFT10-15
snowa_aged_prior0.50.30.30.5
snowa_aged_min0.30.10.10.3
snowa_aged_max0.70.50.50.7
snowa_aged_post0.70.1370.3650.7
snowa_dec_prior0.150.150.150.15
snowa_dec_min0.050.010.010.05
snowa_dec_max0.30.30.30.3
snowa_dec_post0.2290.010.010.125


STEP 3 : BACKGROUND ALBEDO OPTIMIZATION

Data points selection (month-pixels from climatology 2009-2018) :

Optimization method: pixel-level L-BFGS-B with analytical gradient calculation (1 optimized parameter at each pixel, varying albedo by ±0.1 from the prior)

Post-processing: filling non-optimized pixels (having small bare soil fraction and not covered with snow throughout the year) with the average value from 10 closest pixels (where contfrac > 0.99 and inlandwater < 0.1)

ndata - total number of used month-pixels (or day-pixels on the right graph), npts - total number of used grid pixels, zpts - total number of not used grid pixels


RESULTS (seasonal cycle across different regional masks)