Multiple Non-Uniform Resolution Grid Model 050 km San Pedro River Benson Tombstone USA MEXICO...
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Multiple Non-Uniform Resolution Grid Model 0 50 km Sa n Pe d r o Rive r Benson Tombstone USA MEXICO Cananea BLM – S PN RCA Sierra Vista Ft. Huachuca Uniform Resolution 500m 1 km 3 km 9 km .5 km Multiple Uniform Resolutions Multiple Non-Uniform Resolutions Luis A. Bastidas, Norman L. Miller Soni Yatheendradas, Ajay Kalra, Jiming Jin
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Transcript of Multiple Non-Uniform Resolution Grid Model 050 km San Pedro River Benson Tombstone USA MEXICO...
Multiple Non-Uniform Resolution Grid Model
0 50 km
San Pedro River
Benson
Tombstone
USA
MEXICO
Cananea
BL
M – SP
NR
CA
Sierra VistaFt. Huachuca
Uniform Resolution500m
1 km
3 km
9 km
.5 km
Multiple UniformResolutions
Multiple Non-UniformResolutions
Luis A. Bastidas, Norman L. MillerSoni Yatheendradas, Ajay Kalra, Jiming Jin
Multiple Non-Uniform Resolution Grid ModelSH flux
-100
0
100
200
300
400
500LE flux
-100
0
100
200
300
400
500
Grnd T
280
285
290
295
300
305
310
315
320
325Soil Mois
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
9 km
SH flux
-100
0
100
200
300
400
500LE flux
-100
0
100
200
300
400
500
Grnd T
280
285
290
295
300
305
310
315
320
325Soil Mois
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
0.5
1 kmPreliminary ResultsPreliminary ResultsLuis A. Bastidas, Norman L. Miller
Soni Yatheendradas, Ajay Kalra, Jiming Jin
Remote Sensing Influence on Errors
30 40 50 60 70 80 90 1000
1
2
3
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5
G
rou
nd
Tem
p R
MS
E [
K]
Sensible Heat RMSE [w/m²]
30 40 50 60 70 80 90 1000
1
2
3
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5
Gro
un
d T
emp
RM
SE
[K
]
Latent Heat RMSE [w/m²]
30 40 50 60 70 80 90 100
30
40
50
60
70
80
90
100
Sensible Heat RMSE [w/m²]
Lat
ent
Hea
t R
MS
E [
w/m
²]
Ground ObservationsP replacedS replacedP and S replaced
Ground ObservationsP replacedS replacedP and S replaced
L. Bastidas, H. Gupta, S. Sorooshian
Ongoing PILPS Semi Arid ExperimentLucky Hills
Kendall
Tucson
NEW MEXICO
L. Bastidas, H. Gupta, W. Emmerich, B. Nijseen, E. Small
SAHRA
Ongoing PILPS Science Questions
1. What is the ability of the models to reproduce the water, energy, and carbon exchanges in semi-arid environments?
2. Are the current (usually single) representations of semi-arid lands in the models enough to reproduce the different environments that exist in those areas?
3. Does model calibration reduce the among-model range in the model simulations?
4. How much influence does the model parameterization have on the parameter estimations of “physically meaningful” parameters?
5. Do current carbon representations, developed for forests, properly reproduce carbon exchanges over vegetated arid lands?
