Online Geography Resources


Droughts - An Overview

IB DP Geography
Next page
Geography Starter


Geographical Visualisation

GIS > Geographical Visualisation - Spatial Extent

Global Drought Occurence
Google Earth Placemark   Global Drought Monitor | Source
Geography Activities



Produce notes on the definition of drought, it's spatial extent, it's predictability, it's frequency and magnitude.

Think - location, prediction, frequency and magnitude?

Geography Activities


Geography Activities

Location / Spatial Extent

Regional distribution of disasters by type 1991 - 2005
Regional distribution of disasters by type [1991 - 2005]
Geography Activities


Predicting Droughts With Greater Certainty

ScienceDaily (June 3, 2009)

 ScienceDaily: Your source for the latest research news and science breakthroughs -- updated daily Science News Share   Blog   Cite Print   Email   Bookmark Predicting Droughts With Greater Certainty

Using new data and reconstructions of the “Dust Bowl” drought in America during the 1930s, climatologists have shown for the first time a three-dimensional picture of the atmospheric circulation that led to the drought. This will enable climate models to be evaluated and further improved. The scientists hope this work will make it possible to predict future periods of drought more accurately.

In the 1930s, a drought that lasted almost ten years wrought havoc on the Midwest region of North America. The enormous dust storms accompanying it gave the “Dust Bowl” drought its name. This drought had devastating socio-economic consequences for America. The legendary “Route 66”, along which the farmers fled towards California, was made famous in part by the Dust Bowl.

Scientists have been studying the Dust Bowl phenomenon for decades, and until now the mechanisms that caused this exceptionally long period of drought have not been fully understood, as little information has been available on the atmospheric circulation. At the time of the drought, wind and temperature readings were already being taken using balloons and aircraft, initially at altitudes of three to eight kilometres, and later at much higher altitudes. These data have now been digitalised as part of a US project and a project undertaken by the Swiss National Science Foundation. Based on these data, statistical methods were used to reconstruct the upper air circulation at an altitude of up to 15 kilometres.

Based on computer models, researchers have up to now conjectured that unusual sea surface temperatures in the Pacific and Atlantic Oceans would have altered the wind systems, thereby triggering the drought. At the same time, the dying vegetation, the parched soil and the dust created by these conditions could have further intensified the drought.

In their study, the scientists focused on three known circulation patterns which characterise the basic wind conditions of the region and the wider area. Using the new data, they were able to show that a specific wind flow, the Great Plains Low-Level Jet, was shallower at the time of the Dust Bowl. This air current usually carries moist air from the tropical Atlantic far into the region, which covers approximately two million square kilometres. In addition, the Jet did not penetrate as far north as usual, as it was deflected too early towards the east.

The researchers believe this was caused by a high-pressure system that built up over the Plains and was associated with an abnormal upper air flow extending from the Pacific across North America to the Atlantic. “Overall, these features are clearly consistent with the flow conditions that climate models predict as the effect of a cold Pacific coinciding with a warm Atlantic”. Because the temperatures of the tropical oceans can to a certain degree be predicted, the scientists see here the possibility of predicting periods of drought as well. However, the study also shows up some remaining shortcomings in the models: for the most part, they would not correctly depict the spatial shift of the Low-Level Jet, and in many models the drought is located too far to the south.

Adapted from source


'Nature caused Sahel drought'

BBC: Thursday, 18 November, 1999: Toby Murcott

Nature caused Sahel drought

A massive drought that struck parts of Northern Africa in the 1970s and 80s may have been the result of a natural climate cycle.

Up to now, many scientists thought the drought in the Sahel zone was caused by humans over-using natural resources in the region. But a new study in the journal Science shows how a combination of ocean temperature and loss of natural vegetation could have been the sole reasons for the drought. The drought pushed the Sahara desert south, destroying farmland. It had a major impact on many countries including Nigeria, Niger and Mali.

Now, scientists from the Nasa Goddard Space Flight Centre and the University of California in Los Angeles believe it could all be explained by natural phenomena. The researchers produced a computer model that included ocean surface temperature, the amount of moisture in the soil, and loss of vegetation. With all those conditions, the computer model behaved just like the Sahel drought - producing a long period of dry, cool weather. It appears that human activity might not have been to blame for the drought, and the study suggests the Sahel region may be naturally prone to such large climate changes.

The challenge now is whether that information will help scientists predict when the next drought is likely to occur.


Geography Activities


Number of natural disasters by type: regional distribution 1991-2005
Number of natural disasters by type: regional distribution [1991-2005]
Number of natural disasters by type 1991-2005
Number of natural disasters by type [1991-2005]

Magnitude - Drought Indices | Adapted from source

Percent of Normal

Overview: The percent of normal is a simple calculation well suited to the needs of TV weathercasters and general audiences.
Pros: Quite effective for comparing a single region or season.
Cons: Easily misunderstood.

The percent of normal precipitation is one of the simplest measurements of rainfall for a location. Analyses using the percent of normal are very effective when used for a single region or a single season. Percent of normal is also easily misunderstood and gives different indications of conditions, depending on the location and season. It is calculated by dividing actual precipitation by normal precipitation—typically considered to be a 30-year mean—and multiplying by 100%. This can be calculated for a variety of time scales. Usually these time scales range from a single month to a group of months representing a particular season, to an annual or water year. Normal precipitation for a specific location is considered to be 100%.

One of the disadvantages of using the percent of normal precipitation is that the mean, or average, precipitation is often not the same as the median precipitation, which is the value exceeded by 50% of the precipitation occurrences in a long-term climate record. The reason for this is that precipitation on monthly or seasonal scales does not have a normal distribution. Use of the percent of normal comparison implies a normal distribution where the mean and median are considered to be the same.

Palmer Drought Severity Index

Overview: The Palmer is a soil moisture algorithm calibrated for relatively homogeneous regions.
Who uses it: Many U.S. government agencies and states rely on the Palmer to trigger drought relief programs.
Pros: The first comprehensive drought index developed in the United States.
Cons: Palmer values may lag emerging droughts by several months.

Palmer Classifications
4.0 or more extremely wet
3.0 to 3.99 very wet
2.0 to 2.99 moderately wet
1.0 to 1.99 slightly wet
0.5 to 0.99 incipient wet spell
0.49 to -0.49 near normal
-0.5 to -0.99 incipient dry spell
-1.0 to -1.99 mild drought
-2.0 to -2.99 moderate drought
-3.0 to -3.99 severe drought
-4.0 or less extreme drought

Palmer based his index on the supply-and-demand concept of the water balance equation, taking into account more than just the precipitation deficit at specific locations. The objective of the Palmer Drought Severity Index (PDSI), as this index is now called, was to provide measurements of moisture conditions that were standardized so that comparisons using the index could be made between locations and between months.

The PDSI is a meteorological drought index, and it responds to weather conditions that have been abnormally dry or abnormally wet. The PDSI is calculated based on precipitation and temperature data, as well as the local Available Water Content (AWC) of the soil.

The Palmer Index is popular and has been widely used for a variety of applications across the United States. It is most effective measuring impacts sensitive to soil moisture conditions, such as agriculture. It has also been useful as a drought monitoring tool and has been used to trigger actions associated with drought contingency plans

Geography Review

Review and Homework Task


Research a recent news story focused upon the link between climate change and drought [BBC News Search would be a good starting point]. Produce a one side of A4 summary of the news story. on facebook
Follow @gatwUpdates on twitter
© 2006-2021 - All Rights Reserved - Author: Richard Allaway | Logout