Indicators and components of assessing variations and changes in climate change

In the present study, concepts related to climate change and climate study scales have been studied and various indicators related to climate change have been presented and then important and practical indicators in evaluating climate change components have been evaluated.

Monitoring the changes in extreme climatic events requires data in short-term time scales. The 32 indicators used in the present study were evaluated and classified into two categories related to rainfall and temperature. Rainfall indices included maximum rainfall and heavy rainfall, maximum number of consecutive dry and wet days, total wet day rainfall, seasonal rainfall index (SI). In addition, regarding temperature, the glacial day (FD) indices, tropical days and nights, hot and cold, minimum and maximum temperature in daily and monthly time scales, range of circadian temperature changes (DTR) and length of growing season (GSL) were assessed.

In selecting the appropriate index for assessing climate change, the length of the existing statistical period, existing of missing data, time scale of the data (hourly, daily, monthly, annual) and the purpose of the research should be considered. In the assessing drought and water balance, the mean values ​​and timing indices would be a good option. While, in studying the flow regime and hydrologic modeling, the daily data flow produce satisfying results. In assessing vegetation change due to climatic factors, as well as groundwater fluctuations, seasonal indicators of rainfall distribution and timing will be better. Average or minimum and maximum and daily or annual indicators will be used to predict changes in climatic variable.

The introduced indicators can be used in selection of suitable climatic variables and adaptive management approaches to climate change challenges. In general, the selection of the appropriate index depends on the available data and the purpose of the research, and the statistical methods used in interpreting the variables will affect the choice of the index.