How is the weather changing where you live? Use aWhere’s tools to find out

How is the weather changing where you live? Use aWhere’s tools to find out

How is the weather changing where you live? Is the climate becoming wetter, drier, hotter or colder? When do you see these changes?  How will this impact you?  With aWhere weather data and tools you can answer these key questions quickly on our adaptER Platform Weather Apps. This blog will demonstrate how to leverage the Climate Trend application to analyze weather variability in a location since 2006. 

Understanding key rainfall patterns and seasons

In the example locations below, a climate chart was created prior to the climate trend chart in order to understand the key months for rainfall. The climate chart shows the weekly rainfall totals compared to the long-term normal. This chart is most useful when looking at a 6-month to 1-year period of time. For example, the chart below for the location in Odisha, India tells us that the main rainy season occurs from June through about September/October. The orange line is the 15-year weekly precipitation average and we  can see that rainfall totals for some weeks during the monsoon season in 2020 were less than this location typically receives while other weeks far exceeded the normal rains, particularly at the onset. 

Is the rainfall in Odisha, India trending lower? Use the Climate Trend Chart to analyze the season from 2006-2020

The climate trend app produces four trend charts based on a location and time period set by the user. You will be able to download trend charts for precipitation, minimum temperature, maximum temperature, and precipitation over potential evapotranspiration (P/PET). These charts reveal weather variability in several ways such as the deviation from the trend line to statistical analysis such as the coefficient of variation (CV) reported in the chart header. Weather variability makes it difficult for farmers to plan their activities as they can no longer reliably rely on historical records for rainfall and temperature as climate change has made the onset of a rainy season variable and difficult to time planting in rainfed agriculture. 

For the example in Odisha, India, the most critical time period for rain is June-September, which was shown in the weekly climate chart. Using the same location and time period, the climate trend chart for precipitation was created below. The pattern shows that this location is trending wetter as seen by the regression line (dashed line). 2019 and 2020 were the wettest years on record since 2006. 2021 will be an important year to alert farmers to these trends.  

Each of these charts includes the following key data points and options: 

  • Coefficient of variation (CV): is a measure of variability over time. For biological systems, anything greater than 20% is considered highly variable.
  • Mean: average for each variable (precipitation, temperature, P/PET) for the specified time period
  • P-value: is a measure of statistical significance. If the P-value is lower than 0.05, the trend is significant and is unlikely to be a random occurrence.
  • Standard deviation (SD): is dispersion of the dataset relative to the mean.
  • Regression line: this is an optional addition to add to each chart but can be helpful in seeing the statistical trend more clearly.

Additional examples:

The following examples show how we used the weekly climate chart to highlight a specific seasonal trend in the climate trend chart.


This location is where the 2019 fires burned at an alarming rate. We chose to analyze the rainfall pattern for the month of January as it is typically a wet month and dryness during the rainy season usually points to a higher risk of forest fires months in advance. The climate trend chart (right) shows that this location is becoming drier and 2021 was one of the driest years on record.


This location in Madagascar, Africa is a very wet location but 2019 and 2020 were much drier during the key rains. This will impact wildlife and the growth of key commodities grown in this region such as vanilla and cocoa. 


This location in Kitui, Kenya is also becoming drier and the 2020 October-January rainy season was far less than normal as shown by the lower blue bars indicating weekly rainfall compared to the orange line representing the long-term average. The climate trend chart shows how precipitation over potential evapotranspiration (P/PET) during the key month of December is now falling below 1.0 which points water stress for rainfed crops. If this location continues to dry out during this critical time, farmers will need to plan for augmentative irrigation or begin planting more drought-tolerant crops.

United States

The location selected in California was the site of one of the largest and deadliest fires on record in California. In early 2020, the rains were well below normal which likely led to the extreme fire conditions later in the year. Late 2020 and early 2021 have also been drier than normal but it does appear more rain has fallen in the last few weeks than in 2020. These conditions are still likely conducive to a high fire risk. The climate trend chart to the right shows the pattern of dryness occurring in this location. January-February in 2020 and 2021 have been some of the driest years since 2006. The fire risk for later in 2021 could be at the same level as 2020. These charts can help policy makers plan ahead for these risks and take precautions in advance of catastrophic losses.

aWhere is launching a YouTube Challenge to users to find the most extreme changes in local weather patterns. The above steps will help guide you on how to leverage the aWhere apps found on the adaptER Platform. Are you ready to join the challenge? Follow this guide to access key resources from aWhere and start understanding how weather is changing in your community.