Long-term Trend of Global Land Precipitation: Uncertainties in Gauge-based Analyses

Long-term Trend of Global Land
Precipitation:
Uncertainties in Gauge-based
Analyses
Mingyue Chen1) , Pinging Xie2),
John E. Janowiak2), & Phillip A. Arkin3)
1) RS Information Systems, Inc.
2) Climate Prediction Center, NCEP/NWS/NOAA
3) Earth Systems Science Interdisciplinary Center, UMD
The 29th Annual Climate Diagnostics & Prediction Workshop, 2004
Background
• Long-term trends in temperature and
•
precipitation have been examined using
STATION OBSERVATIONS [e.g. Karl et al.
1993; Lamb and Peppler 1991];
SPATIAL DISTRIBUTION of the long-term
trend is needed for many applications
such as model verifications;
• Long-term trend in analysis field may be
biased due to changes in gauge network;
Objectives
• To describe the spatial
distribution of
long-term trend of precipitation using
gauge-based analyses over land, and
• To explore ways to quantify uncertainties
of the long-trend in the gauge based
analyses due to changes of gauge
networks;
Data
PREC/L:
 The global monthly precipitation analysis over land
from 1948-present;
 Optimal interpolation (OI) of gauge observation;
 2.5o lat/lon;
Gauge observations:
Monthly precipitation collected in GHCN v2 of
NCDC/NOAA;
Monthly precipitation collected in CAMS of CPC;
Over 17,000 stations;
From 1948 to the present;
Linear Trend of Annual Mean Precipitation
(PREC/L, 1948-2003)
• Increasing trend over the US, NW Australia, …;
• Decreasing trend over the equatorial Africa, E Australia, …;
• The similar patterns are observed in other published gauge
based analyses, e.g. Dai et al. (1997), and New et al. (2000);
Spatial Distribution of Available gauges
•The spatial distribution of gauge network changes;
•Good coverage in earlier years over most regions;
•The US region has good coverage through the period;
Time Series of the Total Number of Available Gauges
Used to Define the Gauge-Based Analysis
•The total number of available gauges changes;
•The maximum during 1960s;
•Decreased during later period;
We conducted comparative studies
to examine how the magnitude of
the gauge-based analyses vary with
1) Gauge network configuration; and
2) Interpolation algorithms;
Detailed Examinations
of the Gauge-Based Analyses
over the Sahel Region
Time series of reporting station number
•The number of gauge stations changes;
•Subset stations with relatively high reporting rates;
Experiment I:
Comparisons of gauge-based analyses using
various gauge networks (1931-1980)
• Select a period with the best gauge availability
over the region [1931 – 1980];
• Construct analyses using observations at
stations with 80% or higher reporting rates (the
fixed network) and those available at 1921, 1931,
…, 1991, 2001 (the changing networks);
• Compare the trends calculated from the analyses
based on different gauge networks;
• Analyses are created using the OI and Shepard
algorithms;
Number of gauge stations on 0.5olat/lon grid
•The gauge coverage is reasonably well, but
•Less stations at the northern dry regions;
Interpolation Algorithms
• OI (Optimal Interpolation of Gandin [1965])
Interpolate the monthly anomalies;
Weighting statistically;
Add the interpolated anomalies to climatology;
• Shepard (1965)
Interpolate the monthly total;
Inverse-distance weighting;
Using 4-10 nearest stations;
Areal mean of annual precipitation from
OI/Shepard over the Sahel region
(1931-1980, June-Sep.)
• Similar trends in the analyses with various gauge networks;
• The RMSD is much less the magnitude of long-term trend;
• OI interpolation is less affected by the gauge network
than Shepard;
Spatial distributions of annual mean, trend, RMSD of trend
(1931-1980, June-Sep.)
•Over most of the Sahel region the trend uncertainties due to
change of gauge network is very limited;
•The Shepard produce more small scale feature of trend pattern;
•OI is less affected by the change of gauge network;
Experiment II:
Comparisons of trends interpolated using
using various gauge networks for data
period [1948-2003]
• Assume the trend calculated from the
PREC/L gauge-based analysis for 1948 –
2003 is true;
• Interpolate the trend using gauge networks
for each year of the 56-year period;
• Compare the 56 sets of interpolated trend
distribution to get insight into the uncertainties
Spatial distribution of trend calculated with
gauge networks of different years
(1948-2003)
•Trend distribution is
smoothed;
•The overall patterns
of trend are similar
even when networks
are very sparse
(e.g.2000);
Trend calculated with gauge networks of
different years over the Sahel region
• Overall, trends calculated
using various gauge networks
do not show big difference with
that based on a dense
network;
•Differences in the calculated
trend are larger when networks
are sparser;
Summary of Results for the Sahel Region
•
•
•
•
The annual precipitation over the regions of
Sahel have been decreasing during the
periods of 1931-1980 & 1948-2003;
The uncertainties exist due to the change of
network through the period;
The magnitude of the uncertainties in trend
is much less than that of the trend itself;
The OI algorithm produces gauge-based
analysis with less alias in magnitude than
the Shepard;
Examinations over the
Global Land Areas for
1948 – 2003
Spatial distributions of annual mean, trend, RMSE of trend
(1948-2003)
Summary and Future Work
• The spatial distribution of major trend of annual
•
•
•
•
precipitation has been described from the long-term
gauge based analysis;
The uncertainties due to the change of gauge
network through the period has been explored;
The uncertainties are related to interpolation
algorithms, the OI interpolation is better than the
Shepard;
The trend are related to gauge network but the trend
alias over the major trend regions is limited;
Future work is underway to further quantify the
uncertainties, such as, significance test, etc.