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Development of Bias-Corrected
Precipitation Database and
Climatology for the Arctic Regions
Daqing Yang, Principal Investigator
Douglas L. Kane, Co-Investigator
Institute of Northern Engineering
University of Alaska Fairbanks
David R. Legates, Co-Investigator
Center for Climatic Research
Department of Geography
University of Delaware
Outline
• Background /Goals
• Methods
- Results and applications of WMO
gauge intercomparison project
• Data Sources
• Major Tasks
• Results/Products/Impacts
Uncertainties of Precipitation Records and
Climatology in the Arctic regions
• Sparseness of the precipitation observation networks;
• Uneven distribution of measurement sites, i.e. biased
toward coastal and the low-elevation areas;
• Spatial and temporal discontinuities of precipitation
measurements induced by changes in observation
methods and by different observation techniques used
across national borders; and
• Biases of gauge measurements, such as wind-induced
undercatch, wetting and evaporation losses, and
underestimate of trace amount of precipitation.
Research Goals
• Evaluate and define the accuracy of precipitation
measurements in the Arctic regions.
• Implement the consistent bias-correction methods
over the pan-Arctic, i.e. Alaska, northern Canada,
Siberia, northern Europe, Greenland, and the
Arctic Ocean.
• Develop biased-corrected and compatible
precipitation database (including grid products)
and climatology for the Arctic regions as a whole.
US Wyoming snow system in Barrow, AK WMO double fence intercomparison reference (DFIR)
in Barrow, AK
Canadian Nipher NWS 8" Alter
120
NWS 8" unsh Hellmann unsh
Ratio of gauge catch to the DFIR
Tretyakov
100
80
(%)
60
40
20
0
0 1 2 3 4 5 6 7 8 9
Wind speed at gauge height (m/s)
Annual precipitation (mm)
Ca
Annual precipitation (mm) p
100
200
300
400
500
600
700
800
900
0
Cl e P
in
to arry
n
Co Po
p in
19 Fo pe t
100
150
200
250
300
350
400
450
500
0
50
rt rni
48 n
Fo Rel e
19 rt ian
Si c e
50 m
19 Fo ps
rt on
52 S
19 Na mit
54 y h
Ri
ve
19 No r
56 rm In
an vik
19
58 Ee Y W e
llo ello lls
19 wk w
ni kni
60 fe fe
19 Ba Hy
62 Co r ke dro
19 ra La
64 l H ke
ar
19 Pe bou
66 lly r
Br Ba
19 ou y
68 gh A
archived
to ler
19 n t
70 Ca Isla
19 Ca pe nd
72 pe Dy
Ho er
19 op
74 e
De C r
19 wa lyd
76 rL e
ak
19 e
78 Eu s
Ha re
19 ll k e
80 Be
Whitehorse, Yukon, 1948-1994
ac
19 Lo h
82 ng Iqa
st lui
corrected
19 M af t
84 ao f Bl
ka uff
19 rI
86 Re nle
so t
19 B
Summary of bias correction in NWT, Canada, 1961-1990
88 Ca yro lute
m n
19 br Ba
id
90 g y
19 M eB
Sa ou ay
corrected
measured
92 c h ld
19 s Ba
Ha y
94 rb
ou
r
35
trace
30 wind-loss
measured
Overall mean
25 for the NP
Precipitation (mm)
20 drifting stations,
15 1957-90 (Yang,
10 1999)
5
0
1 2 3 4 5 6 7 8 9 10 11 12
Months
80
70
trace amount
Overall mean
wind correction
for 61 climate
Precipitation (mm)
60
measured
50
40
stations in
30 Siberia, 1986-
20
92 (Yang and
10
0
Ohata, 2001)
1 2 3 4 5 6 7 8 9 10 11 12
Month
Comparison of Bias Corrections in the High Latitudes
3.00
Range of yearly correction factor
2.50
2.00
1.50
1.00
0.50
Siberia Alaska NWT Greenland Arctic basin
Regions
a) DIKSON, 73.30N, 80.24E trace amount
120
Monthly precipitation (mm)
wind loss
100
measured
80
60
40
20
0
1 2 3 4 5 6 7 8 9 10 11 12
a) Dikson (73.30N, 80.24E)
Daily snow fall precipitation
35
30
25
20
(mm)
15
10
5
0
0 2 4 6 8 10 12 14 16 18 20
Daily mean w ind speed at 2m (m/s)
Data Sources
Daily precipitation, temperature and wind speed are needed
for this research.
• National Climatic Data Center (NCDC), global daily
surface data archive (1994-present) for over 8,000
stations around the world,
http://www.ncdc.noaa.gov/cgi-bin/res40.pl
• WMO GTS, the Global Climate Observing System
(GCOS) Surface Network (GSN),
http://www.wmo.ch/web/gcos/gcoshome.htlm
• Arctic Precipitation Data Archive (APDA) at the Global
Precipitation Data Center (GPDC),
http://www.dwd.de/research/gpcc/acsys
• Arctic Ocean (6 hourly and daily) met data
collected at the Russian NP drifting station,
National Snow and Ice Data Center (NSIDC)
http://www-nsidc.colorado.edu/index.html
Station and gauge info:
– type of precipitation gauge
– height of gauge and wind sensor
– wind shield
WMO and national weather services:
– USA, Canada
– Russia, Finland, Denmark, ...
Synoptic/climate stations on land above 45N and the Arctic
Ocean drifting stations will be used for this research
Canada
Mongolia
China
Russia
Greenland
Kazakhstan
Major Task 1:
Evaluation and Implementation of the WMO
Bias Correction Methods - threshold wind 6.5m/s
• Analysis of wind regimes over the arctic regions
• Focus on winter season and on snowfall days
• Define regions where the WMO bias correction
methods may not be appropriate and therefore
alternative approaches or further experimental
studies should be considered
Major Task 2:
Development of Bias-Corrected Arctic
Precipitation Database and Climatology
• Implement the WMO methods to all the stations in the
Arctic regions for last 30 years, 1970-2000???
• Create bias-corrected daily precipitation dataset- an
important basis for analyses of Arctic regional
precipitation, i.e. long-term mean, seasonal cycle, year-
to-year variation, and trend
• Develop improved precipitation climatology for the Arctic
regions
–Consider terrain and the orographic effect on precipitation
distribution, use high-resolution digital elevation models (DEM)
to determine elevation, slope, and aspect of the topography
–Apply PRISM (Daly et al., 1994) and the High-Resolution
Weather Data System (HRWxDS) (Legates et al,. 1999) to
generate regional maps of monthly/yearly bias-corrected
precipitation
–Develop gridded precipitation data, use equal-area EASE grid
system, compatible with ACSYS/Arctic Precipitation Data
Archive (APDA), hydrological model intercomparison project,
and RS snowcover (SCE/SWE) products
Major Task 3:
Comparison and Validation of the Results
• Compare our results with other precipitation
datasets/products, such as Legates and Willmott (1990),
Jaeger (1983), UNESCO (1978), Adam and Lettenmaier
(2003), and others?
• Compare gauge measurements/corrections with snowcover
accumulation in selected regions/basins
• Assess the impact of precipitation bias corrections to regional
hydrologic model analyses (Zhang et al., 2000)
• Compare GCM/RCM precipitation simulation with the
observed and bias-corrected precipitation fields in selected
regions, i.e. Alaska and central Siberia
– model simulation agrees better to bias-corrected precipitation
fields particularly in winter months and over windy areas !?
Results/Products/Impacts
• Practical procedures for correcting gauge-measured
precipitation data in the high latitude regions
• Bias-corrected daily/monthly/yearly (station)
precipitation records/correction factors (CF, %) for arctic
regions across national boundaries
• Bias-corrected, gridded monthly/yearly regional
precipitation data/climatology for the arctic regions
• Impacts:
– water balance calculations of both the Arctic Ocean and
terrestrial systems
– climate change analysis and hydrologic modeling
– validation of GCM/RCM simulations
– calibration of remote sensing data/products
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