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

1. Mingyue Chen1) , Pinging Xie2), John E. Janowiak2), & Phillip A. Arkin3) Long-term Trend of Global Land Precipitation: Uncertainties in Gauge-based Analyses 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

2. 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;

3. 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;

4. 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;

5. 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);

6. 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;

7. 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;

8. We conducted comparative studies to examine how the magnitude of the gauge-based analyses vary with • Gauge network configuration; and • Interpolation algorithms;

9. Detailed Examinations of the Gauge-Based Analyses over the Sahel Region

10. Time series of reporting station number • The number of gauge stations changes; • Subset stations with relatively high reporting rates;

11. 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;

12. Number of gauge stations on 0.5olat/lon grid • The gauge coverage is reasonably well, but • Less stations at the northern dry regions;

13. 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;

14. 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;

15. 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;

16. 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

17. 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);

18. 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;

19. 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;

20. Examinations over the Global Land Areas for 1948 – 2003

21. Spatial distributions of annual mean, trend, RMSE of trend (1948-2003)

22. 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.