What you can see in this figure
This map illustrates historical patterns of key temperature and precipitation variables, along with derived climate indicators, across both land and ocean regions. Users can interact with the tool by selecting different variables, time periods, seasons, as well as choosing specific countries or subnational administrative units. These selections dynamically update the visual plots below.

Understanding the Data: Implications and Utility
Understanding how temperature and precipitation interact in each region is essential for planning in sectors such as agriculture, water resource management, and flood risk mitigation. For instance, high temperatures combined with low rainfall can exacerbate drought, while intense rainfall following dry periods can increase flood risk due to reduced soil absorption.

Temperature patterns are primarily influenced by elevation and latitude—higher elevations and latitudes generally experience cooler temperatures. However, regional temperature variations are also shaped by other factors such as land cover, proximity to water bodies, urbanization, and atmospheric circulation patterns.

• Maximum temperatures (day temperatures) are particularly important for assessing heat stress, wildfire risk, and drought conditions. Heat stress is particularly relevant in urban areas where the heat island effect can intensify impacts.
• Minimum temperatures (night temperatures) are critical for human health (e.g., sleep quality), animal health, agricultural productivity (e.g., frost risk), and ecosystem stability.

We provide a set of complementary climate indicators that go beyond basic temperature and precipitation data. These include metrics such as the number of days exceeding critical heat and humidity thresholds, which are particularly relevant for sectors like agriculture, public health, and urban planning.

Recognizing that different regions have different sensitivities, we offer multiple threshold levels to reflect local priorities and vulnerabilities. For example:

• Number of hot days (e.g., days above 35°C) can indicate heat stress risks for outdoor labor.
• Number of tropical nights (e.g., nights above 26°C) is important for sleep quality and agricultural crops.
• Number of hot and humid days (e.g., high temperature combined with high humidity) highlights conditions that pose serious risks for heat-related illnesses.

Precipitation patterns are broadly organized by climatic zones and rain fronts, but at finer scales, they are influenced by topography, distance from the coast, prevailing winds, and local convection processes. We also provide complementary indices to characterize extreme precipitation or extreme drought. 

What you can see in this figure
Temperature and precipitation change throughout a 12 month period. Understanding these patterns can help to identify local climate behavior and the potential for changing seasons over time. This chart presents essential climate variables to provide a snapshot into the seasonality of selected area. This chart is dynamic and elements can be turned on/off by selecting variables in legend. 

Understanding the Data: Implications and Utility
Users should use this chart to understand:

• When is the wet season? Are there multiple rainy seasons?
• How intense is the dry season and does it overlap with times of the year with highest temperatures? What might this mean for risk and need for adaptation/ resilience efforts?
• Are there significant temperature swings - throughout the year and/or between minimum and maximum temperatures?

What you can see in this figure
This graph presents the annually averaged time series from 1951 to the present, offering insights into long-term climate behavior. 

Understanding the Data: Implications and Utility
Users are encouraged to examine two key aspects:

1. Interannual variability – How much do values fluctuate from one year to the next? This helps define what constitutes a "normal" range of year-to-year variation.
2. Long-term trends – Are there clear patterns of warming, drying, or other shifts over time?

Year-to-year fluctuations are influenced by many factors, but one of the most prominent global drivers is the El Niño–Southern Oscillation (ENSO), which can significantly affect both temperature and precipitation patterns.

Temperature trends show a clear warming signal in most regions, particularly from the late 20th century onward, which also drives increases in related indicators—such as the number of extremely hot days, tropical nights, and hot and humid days. Tmin (nighttime temperatures) often increases faster than Tmax (daytime temperatures), due to nighttime heat retention. However, maximum temperatures tend to increase faster in dry regions. 

Precipitation trends are inherently more complex and vary significantly by region. Unlike temperature, these trends are often difficult to distinguish from natural interannual variability. While climate projections consistently indicate an increase in the frequency and intensity of extreme rainfall events, detecting these changes in historical records remains challenging.

What you can see in this figure
A Warming Stripes graph provides a visual representation of the change in selected temperature or precipitation variable. Each bar represents the the annual average for a year. 
Hover over the graph to view the exact annual values for each year, allowing for more detailed exploration of the data.

Understanding the Data: Implications and Utility
This visualization makes it easy to spot both gradual trends and abrupt shifts in climate.