IISD REPORT MAY 2015 ACCESSING AND USING CLIMATE DATA AND INFORMATION IN FRAGILE, DATA-POOR STATES
5
An example is shown in Figure 2, which indicates how rainfall in the Sahel region of Africa has changed over the last 100
years. From this igure, it is possible to gauge the following three components of climate variability:
1. Inter-annual red line: how climate can shift from year to year. Just as the weather today can difer considerably
from that of yesterday, so the climate this year can be very diferent from last year. In fact, in nearly all places,
the diference in rainfall from one year to the next is much larger than any changes that might be expected from
climate change. The largest part of climate variability that will need to be managed by practitioners occurs at
timescales of approximately 1 to 10 years—particularly when considering rainfall.
2. Decadal blue line: how climate can shift over periods of about 10 to 30 years. In some parts of the globe there
may be clusters of wet or dry years, possibly resulting in prolonged periods of drought or looding. For example,
the drought that the Sahel experienced during the 1970s and 1980s is clearly noted by the dip in the blue line,
while a recovery to more normal levels of rainfall is visible from the mid-1980s to around 2010. This component of
climate variability can be very important in adaptation planning: it is possible that short-term climate trends
perhaps over the coming 5 to 10 years could be inconsistent with the long-term trend. For example, it is
possible for an area to experience a period of a few years of steady or slowly cooling temperatures even if a strong
warming trend is anticipated over the next century. Similarly, strong recent warming trends may be much
faster than trends that can be expected for the coming decades.
3. Long-term trend black line: how climate can shift over the long term beyond 30 years. The most important
contributor at this timescale is the impact from climate change. Here, the long-term trend shows a decrease of
rainfall over 100 years. However long-term trends are much more evident in temperatures than in rainfall, and
are likely to be less relevant to those working in fragile contexts.
3.2 CURRENT INFORMATION
Current climate information involves assessments of current and recent conditions and the comparison of these conditions
to the historical climate. While current data are most accurate when attained from weather stations, access to such data
can be challenging even in countries with fully functioning meteorological services. Satellite data are an alternative, and
can be accessed online in near real-time from most locations, including from most fragile states.
2
Monitoring products can be presented in a wide variety of formats, usually difering in timescale and in how the recent
observations are compared with the historical background. Commonly used timescales include information for the
previous 10 days, the previous month, or the previous three- month period. The value of current climate information is
found in its ability to inform on what is happening now, but it should be noted that this could be done in diferent ways; the
best way will depend on the decision that is being made. In addition to using the absolute value of the climate variable in
question for example, today’s rainfall amount, it is often the case that the deviation of the current value from the historical
record referred to as the climatology, is equally if not more important.
200 250
300 350
400 450
500 550
600 650
700
1900 1910
1920 1930
1940 1950
1960 1970
1980 1990
2000 2010
OBS Linear
Decadal
FIGURE 2. OBSERVED ANNUAL RAINFALL IN THE SAHEL OVER 1900–2006
Source: Giannini, Saravanan, Chang 2003.
2
Some climate and environmental information could be derived from satellite data provided free of charge by NOAA and NASA See Annex 1 for links on how to access this data.
IISD REPORT MAY 2015 ACCESSING AND USING CLIMATE DATA AND INFORMATION IN FRAGILE, DATA-POOR STATES
6
One of the most commonly used methods for assessing how the current climate deviates from “normal” is to
create an anomaly by subtracting the historical average from the value in question. For example, the average
rainfall for 21–31 January from 1980 to 2010 say 135 mm can be subtracted from the total for 21–31 January
2015 say 200 mm to create a positive “anomaly” of 65 mm see Figure 3. It could then be determined
that rainfall for 21–31 January 2015 was 65 mm above average. However climate anomalies are presented,
monitoring is an important step in the identiication of the early onset of severe conditions, especially of slow-
onset hazards such as droughts. In combination with forecasting, monitoring can provide advanced warning of
imminent hazardous conditions.
Figure 3 depicts rainfall anomalies over Africa. On the map, brown colouring indicates areas with below-average
rainfall negative anomalies for the period January 21 to 31, 2015; and blue colouring indicates above-average
rainfall positive anomalies for the same period. The darker the colour, the greater the anomaly. For more
information on climate anomalies, please see Box 2.
3.3 PROSPECTIVE INFORMATION