# Presentation: 913192

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

**Mingyue Chen****1)**** , Pinging Xie****2)****, **
**John E. Janowiak****2)****,  &  Phillip A. Arkin****3)**

- 1) RS Information Systems, Inc.
- 2) Climate Prediction Center, NCEP/NWS/NOAA
- 3) Earth Systems Science Interdisciplinary Center, UMD

**The 29****th**** Annual Climate Diagnostics & Prediction Workshop, 2004**

**Notes:**
Uncertainties in gauge-based precipitation analysis when they are used to detect the spatial distribution of the long-term trend of global land precipitation.

The work has been done in the group of ....

## 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

**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);**

- (PREC/L, 1948-2003)

**Notes:**
Spatial distribution of long-term trend [mm/day/decade] calculated for each grid box through linear regression between the PREC/L annual mean precip and years[rain = a * year + b], from year 1948 to 2003.

Increasing trend over North America the US region, NW Australia, and Argentina;
A Decreasing trend over most of tropical regions and E Australia, like Africa, 

## 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;**

**Notes:**
However, uncertainties exist in the trend shown in the previous slide.

Here we show distribution of gauge networks for four selected years through the data period.

........

Number of gauges in a 2.5 deg lat/lon available for different months through the period from 1948 to 2003.

Substantial differences are observed in gauge networks throughout 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;**

**Notes:**
The total number available gauges changes through the period.
These changes may yield time-changing bias, or artificial trends, in the resulting analyses.
Therefore, we have to be cautions when using gridded data sets to analyze the long term trend. 

## We conducted comparative studies to examine how the magnitude of the gauge-based analyses vary with

- Gauge network configuration; and
- 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;

**Notes:**
The time series of the number of reporting stations from 1911 to 2003 over Sahel region.
As shown in red line, it is the total number of reporting stations.

Red Line:		number of all stations with reports

Green Line:		number of stations with reporting rates of 80% or higher

The subset of stations not only have relatively high reporting rates, but have reasonably well coverage over the Sahel region.

## 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;**

**Notes:**
To select a period in which the coverage of gauge stations over the Sahel region is reasonably well, and those stations have relatively high reporting rates during the period;
Then, define the long-term trend based on the analysis using the selected fixed gauge network;
Assume the obtained trend is true.
Then using different gauge networks for various years to construct analyses of monthly precipitation during the period;
To examine how the various gauge networks effect on the long-term trend;

## Number of gauge stations on 0.5olat/lon grid

- Number of gauge stations on 0.5olat/lon grid

- The gauge coverage is reasonably well, but
- Less stations at the northern dry regions;

**Notes:**
Upper Panel:	number of all stations with reports
Bottom:		number of stations with reporting rates of 80% or higher

The coverage is reasonably well, the most of gauges are at the southern party (large precipitation region), and the northern dry has less stations.

## 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;**

**Notes:**
Results over the ENTIRE Sahel region
Red Line:		total annual mean based on analysis with the select fixed subset of gauge stations
Blue shading:	The Root mean square error between the analyses with various gauge network and 				the fixed subset gauge network;
Points:
Similar trends in the analyses using all available gauges or gauges with stable reporting rates;
The RMSE is much less the long-term trend;
OI produce less RMSE due to the various gauge network;

Time series of mean precipitation over the Sahel region calculated by interpolating gauge observations with various assumed network configuration. 

Results based on the OI and the Shepard algorithms are plotted in top and bottom panels, respectively.

Gauge-based analyses are created using 9 sets of gauge networks, those of 1921, 1931 .... 1991, as well as with all available gauges.  Center of the line is for results with all gauges, while width of the line indicates standard deviation among the analyses based on 9 sets of gauge configurations. 

Points here are

The OI technique produces analyses with more stable magnitude (smaller standard deviation) for variable gauge networks compared to that based on the Shapard;

Over Sahel, the uncertainty, as indexed by the standard deviation, is much less than the magnitude of trend, for both algorithms. 

We are now extending this examination for other regions. 

## 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;

**Notes:**
1% 5% 10% 20% 50% 100%

## 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);**

**Notes:**
Probably due to the large scale nature of the trend distribution.

## 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)**_

**Notes:**
Here are Global distributions for period from 1948 to 2003.
The annual mean precipitation: large precipitation over tropical regions
The linear trend:
The root mean square error of trend caused by the various gauge networks from different years through the period:
The relative root mean square error of trend:

## 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.

**Notes:**
major trend described

2) Uncertainties explored 

Uncertainties related to algorithm;

Network related but overall trend alias is limited except some regions

 future work underway to further quantify.. Significance test...