Transcript Augmenting_Hydro-MET_Data_Demands

Augmenting Hydro-MET Data Demands of
Impact Assessment Models
Team:
IWMI (Charlotte, Solomon)
Cornell (Tamo, Dan, Zach)
BDU (Seifu, Esayas)
Background
• Modeling landscape processes requires detailed climatic and
geographic datasets
• Meteorological stations in most parts of Africa are very sparse
and most watersheds are un-gauged
• Climate records are incomplete; high percentage of missing
data and relevant variables
• Poor data accessibility due to lack of data sharing agreement
among trans-boundary riparian countries

High-resolution global reanalysis data for SWAT
modeling applications in Africa
Global Climate Data Sources
Product
Spatial
Resolution
Temporal
Resolution
Time
Horizon
Variables
CMAP
2.5 degree
Monthly
1979 – 2009
Precipitation
GPCP
2.5 degree
Monthly
1979 – 2010
Precipitation
GPCC
0.5 degree
Monthly
1951 – 2010
Precipitation
WorldClim
30 sec
Monthly
Climatology
Precipitation
Min, mean and max temp
TRMM
0.25 degree
3-hr, Daily
1997 – 2012
Precipitation
R1, R2
2.5 degree
6-hr, Daily
1948 – 2012
Climate variables
ERA40
2.5 degree
6-hr, Daily
1979 – 2001
Climate variables
CFSR
0.312 degree
(~38km)
Hourly, Daily
1979 – 2012
Climate variables, and
Hydrological quantities
Climate Forecast and Reanalysis System (CFSR)
•
A coupled atmosphere-ocean-land-sea ice system
•
Assimilates satellite radiances instead of the retrieved
temperature and humidity values
•
Accounts for changing CO2 and other trace gases, and solar
variations
•
Finer spatial (~38km) and temporal (hourly and daily) resolution
•
Assimilates hydrological quantities from a parallel LSM forced by
CMAP and CPC unified daily gauge analysis
Applications of CFSR Data
• Weather generator files for areas with missing and
incomplete climate datasets
– Solar radiation, relative humidity, wind speed
– Maximum half-hour rainfall
• SWAT weather input files for un-gauged watersheds
• Climate downscaling and bias correction
• Study of large-scale water and energy fluxes
CFSR Data for SWAT Modeling
CFSR Variable
CFSR
Unit
Conversion Factor
SWAT Unit
Precipitation Rate
Kgm-2s-1
x 86,400
mm/day
Min Temperature at 2m
K
- 273.16
OC
Min Temperature at 2m
K
- 273.16
OC
Directional wind at 10m
(Zonal and Meridional)
ms-1
Magnitude and
x 0.748
Wind speed at
2m, ms-1
Downward Solar Radiation
flux
Wm-2
x 0.0864
MJ/m2/day
Specific Humidity at 2m
KgKg-1
Relative
humidity, %
Pressure at ground surface
Pa
Universal gas law
and saturation vapor
pressure equations
Hourly Precipitation rate
Kgm-2s-1
Scaling theory and
factor with duration
Max half-hour
rainfall, mm
Gumera: CFSR vs. Gauge Data 1
Gumera: CFSR vs. Gauge Data 2
Monthly mean
Rainfall
Maximum Half-hour Rainfall
• Strict sense simple scaling property: the probability
distribution of maximum rainfall depth is invariant of time
scale (Burlando and Rosso, 1996)
d
H lD  l H D

• Wide sense simple scaling property: extends the scaleinvariant property to quantiles and moments
ht (lD)  l ht ( D)
• If the reference duration is 1hr, then l = D
ht ( D)  D ht (1)

Maximum Half-hour Rainfall - 2
Maximum Half-hour Rainfall - 3
Scaling Exponent
Scaling exp. ()
0.9
0.8
y = 0.8691e-0.023x
R² = 0.9505
0.7
0.6
0.5
0.4
0
3
6
9
12
15
Duration (D), hr
18
21
24
CFSR for SWAT Modeling - 1
CFSR for SWAT Modeling - 2
CFSR for Spatial Downscaling
CFSR for Water Fluxes Study
(percentage of water fluxes relative to rainfall in wet season)
Conclusions
• High resolution reanalysis data had great potential to improve
modeling of landscape processes
• CFSR data has comparable performance as gauged climate data
for SWAT modeling in Ethiopian highlands
• The spatial pattern of CFSR data is useful for spatial downscaling
and bias correction of GCM data
• The water fluxes of the CFSR data could be to study large-scale
fluxes without doing cumbersome data assimilation
CFSR Data Description
CFSR_Grids_Data
CFSR_SWAT_Inputs
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•
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Grids’ Center Location File:
CFSR_Eth_Grids.xls
CFSR Data File Names:
GP1<xx>2<yy>_Eth.csv
<xx>: the grid number in westeast direction
<yy>: the grid number in northsouth direction
CFSR_WGEN: monthly statistics
and grids’ center location
•
Grids’ Center Location Files:
*.DBF’ and *.txt
SWAT Input File Names:
<cc>1<xx>2<yy>.txt
<cc>: climate variables code (PC,
TM, HM, SL and WN
respectively for rainfall,
temperature, relative
humidity, solar radiation and
wind speed)