Climate

Precipitation and Temperature Data

The precipitation climatology will allow you to investigate historical precipitation using a weekly, monthly or annual time step. Historical precipitation information by itself will not tell you if a drought is expected, but it will show the wet and dry periods and how long they typically last for your location of interest.

Standardized Precipitation Index (SPI)

The Standardized Precipitation Index (SPI) is an index based on the probability of precipitation for any time scale. The underlying assumption is that a deficit of precipitation has different impacts on groundwater, reservoir storage, soil moisture, snowpack, and streamflow. The SPI was designed to quantify the precipitation deficit for multiple time scales. These time scales reflect the impact of drought on the availability of the different water resources. Soil moisture conditions respond to precipitation anomalies on a relatively short scale. Groundwater, streamflow, and reservoir storage reflect the longer-term precipitation anomalies.

The SPI calculation for any location is based on the long-term precipitation record for a desired period. This long-term record is fitted to a probability distribution, which is then transformed into a normal distribution so that the mean SPI for the location and desired period is zero (Edwards and McKee, 1997). Positive SPI values indicate greater than median precipitation, and negative values indicate less than median precipitation. Because the SPI is normalized, wetter and drier climates can be represented in the same way, and wet periods can also be monitored using the SPI.

A drought event occurs any time the SPI is continuously negative and reaches an intensity of -1.0 or less. The event ends when the SPI becomes positive. Each drought event, therefore, has a duration defined by its beginning and end, and an intensity for each month that the event continues. The positive sum of the SPI for all the months within a drought event can be termed the drought's "magnitude".

Standardized Precipitation-Evapotranspiration Index (SPEI)

One of the more recently developed (in 2009) drought indices is the Standardized Precipitation Evapotranspiration Index (SPEI), which took the basic premise of the SPI and added a temperature component to capture a simplified water balance (Vicente-Serrano et al., 2010). The SPEI, like the PDSI, uses a simple water balance calculation that is based on the Thornthwaite (1948) model for calculating potential evapotranspiration (PET) and a climatic water balance in which both wet and dry periods can be identified. Several studies have shown that good estimates of PET can be obtained with various meteorological parameters, but for the purpose of a drought index these parameters are not needed because only a general estimation of the water balance is required. This also keeps the calculations simple and usable given the additional data requirements needed for determining actual evapotranspiration values. Like the SPI, the SPEI can be updated weekly using a moving window for each time step. The SPEI uses the difference between the basic calculations for PET and precipitation to determine a wet or dry period. Given the flexible nature of the SPEI, it has the capacity to be utilized in monitoring the various types of droughts because of the included water balance calculations. As such, it has the potential to better track agricultural drought

Palmer Drought Severity Index (PDSI)

The PDSI is a meteorological drought index, and it responds to weather conditions that have been abnormally dry or abnormally wet. When conditions change from dry to normal or wet, for example, the drought measured by the PDSI ends without taking into account streamflow, lake and reservoir levels, and other longer-term hydrologic impacts (Karl and Knight, 1985). PDSI calculations are based on precipitation and temperature data as well as the local available water content (AWC) of the soil. From the inputs, all the basic terms of the water balance equation can be determined, including evapotranspiration, soil recharge, runoff, and moisture loss from the surface layer. Human impacts on the water balance, such as irrigation, are not considered. Complete descriptions of the equations can be found in the original study by Palmer (1965) and the more recent analysis by Alley (1984).

The Palmer Index varies roughly between -6.0 and +6.0. Palmer arbitrarily selected the classification scale of moisture conditions based on his original study areas in central Iowa and western Kansas (Palmer, 1965). The Palmer Index is designed so that, ideally a -4.0 in South Carolina has the same meaning in terms of the moisture departure from a climatological normal as a -4.0 in Idaho (Alley, 1984).

Self-calibrated Palmer Drought Severity Index (SC-PDSI)

One of the inherent problems associated with the PDSI was that comparisons were being made using results from different regions, especially those with very different climate regimes, and in many cases this was not appropriate. The Self-Calibrated Palmer Drought Severity Index (scPDSI) is based upon the original PSDI work, but takes all the constants and replaces them with values that are calibrated based upon the data for each individual location (Wells et al., 2004). To make the process “self-calibrating”, several calculations from within the PDSI needed to be addressed, including the climatic characteristics and duration factors. With the calculations for the scPDSI accounting for each individual location, the index becomes more reflective of what is happening at each site and allows for comparisons between regions to be more accurate. With these new calculations, the data can be computed at different time steps (weekly, biweekly, and monthly), and the extreme events being calculated by the scPSDI are indeed rare because they are based on calculations at that location and are not a constant. The positive consequences of the new calculations associated with the sc-PDSI provided the following results: 1) The range of the PDSI values is close to an expected range of -5.0 to 5.0, where values below -4 and above 4 represent extreme conditions. 2) The sensitivity of the index is based upon the local climate. 3) The sc-PDSI has different sensitivities to moist periods and dry periods.

Drought Periods

In this section, users can compare indices to see how they were indicating drought at various times.

Compare Drought Indices

A comparison of drought indices will give users a better understanding of which indicators are best suited for tracking drought in their area. Choose the year of interest, the index of interest and the relevant timestep and then click this button to add the index to the comparison.

Station Trends

The trends displayed on the individual plots represent 1) magnitudes of linear trends in data, and 2) whether or not these trends are deemed to be statistically significant at different confidence intervals.