Estimating Bias of SatelliteBased Precipitation Estimates
Relative to In Situ Measurements
Thomas Smith1
Phillip A. Arkin2
George J. Huffman3
John J. Bates1
1. NOAA/National Climatic Data Center/NESDIS
2. ESSIC, Univ. of Maryland, College Park
3. Science Systems and Applications, Inc. and NASA Goddard Space Flight Center
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Precipitation Bias
• Bias adjustments are needed for satellitebased precipitation.
• Bias Evaluations: estimates of satellite bias
relative to gauge data.
• Bias Uncertainty: how good are the bias
estimates given the available gauges.
• Oceanic Precipitation Bias: can satellite
estimates be adjusted over oceans to minimize
the bias.
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Bias Evaluations
• Bias = Satellite – Gauge difference.
• Analysis of monthly differences using a
large-scale optimum interpolation (OI).
• Bias spatial scales are needed for
analysis.
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Bias Correlation Scales
• Zonal Averages at each
latitude.
• Red: satellite bias w.r.t.
gauges (land only).
• Black: satellite to satellite
difference scales (land
and sea).
• Scales are similar, mostly
1000 km +.
• Use constant scales of
750 km in both directions,
to minimize excessive
spreading of bias.
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Examples: Zonal Averages
• 1996-2003 Bias
typically a few
mm/day.
• OPI bias smallest.
• SSMI combined and
GPI biases have
opposite signs, some
annual cycle.
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Examples: 1996-2003
Averages
• Positive bias over
central Africa.
• Negative over east
Asia and Hawaii.
• Different sign biases
may cancel when
data are combined.
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Differences that Bias
Corrections Make
• 1996-2003 Average
uncorrected and
corrected SSMIc.
• Most regions show
little difference.
• Large differences
over central Africa,
N.W. North America.
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Bias Uncertainty
• How well can the OI analysis reflect the
bias? (Input data 2.5o and monthly; OI uses
data from 12.5o centered region.)
• How does bias uncertainty change with
the number of raw biases analyzed?
• What is the bias uncertainty when there
are no gauges in a region?
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OI Relative Error
Error
• Set all raw biases = 1 and analyze, compute error change
with n = number of raw biases.
• An exponential function estimates the error as a function of n.
n
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RMS Bias
• RMS Bias (RMSB) is the typical bias magnitude (no
correction), from only near gauges, global.
• RMS difference between each satellite and all other
satellites (RMSDs, land + sea) is mostly comparable to
RMSB. OPI and TOVS have lower bias than the others,
which have similar magnitudes.
RMSB (mm/day) computed using n ≥ 20 for each satellite,1996-2003
and globally. SMMI RMSB is the same for all. The RMSD between
each satellite and all other satellites is also shown.
Satellite
OPI
AGPI
GPI
SSMI
SSMI/TOVS
TOVS
RMSB
0.9
1.5
2.0
1.8
1.5
1.2
RMSDs
2.0
1.7
2.1
2.0
1.8
2.0
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Bias Error from a Merged Analysis
• Merged error depends on how correlated the
biases are.
• All uncorrelated: E B2  E B2 ,k / N .
• All correlated:
E B2  E B2 ,k
N
• Part correlated:
E  w E
2
B
k 1

2
k
EB2 ,k
N
N
2
B ,k
j 1
 2 wi w j EB ,i EB , j ri , j
j  2 i 1
N 1 2

EB ,k r
N
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Bias Correlations
• Measured spatial correlations from wellsampled regions (n ≥ 20).
• Negative correlations reduce bias error by
canceling positive and negative errors.
• Most have weak positive correlations (r
usually < 0.5, some bias error reduction from use of
multiple satellites).
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Test: January 2000, all Satellites
• Observed correlations, equal weighting for all 8
satellite estimates.
• No bias analysis → no corrections (oceans).
• More satellite
coverage → less
error (tropics).
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High-Latitude Gauge Biases: Work in
Progress
• Bias errors from evaporation and blowing snow.
They may offset each other, but they can also be
as large as 30% of the mean (Groisman et al.).
• Gauge adjustments are recommended for high
latitudes. Uncertainty should be factored into
bias uncertainty.
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Oceanic Bias Adjustments: Work in Progress
• No oceanic gauges except scattered islands, near
coasts, and on some buoys. An oceanic low-bias
estimate needed for adjustments.
• TMI satellite estimates were found to have little bias
compared to tropical Pacific buoys (Bowman et al.
2003).
• Over oceans, Bias adjustment relative to TMI (or a
satellite with least bias relative to TMI). Uncertainty from
uncertainty estimate of TMI or of the satellite.
• TMI limited in time (beginning 1998) and to between
about 40ºS and 40ºN.
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Summary and Conclusions
• Using available data, satellite precipitation bias is
evaluated near gauges.
• Bias spatial scales are usually large (> 1000 km), but
may be smaller near coasts.
• Bias may be reduced by direct adjustment and by
combining analyses with uncorrelated biases.
• Oceanic estimates may be adjusted to a low-bias
satellite estimate, such as TMI.
• Because of uncertainties in the base analyses (gauges,
TMI) the absolute bias is difficult to define. Adjustment is
relative to a best estimate to minimize bias.
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