Climate and climate change are critical factors influencing global ecosystems, agriculture and forestry. Climate refers to the long-term patterns of temperature, precipitation and atmospheric conditions, while climate change refers to significant alterations in these patterns over time. This review examines the impacts of climate change on natural systems, with particular focus on variations in temperature, precipitation and related climatic variables. The review integrates advanced statistical methodologies, including homogeneity tests, trend analysis and change-point detection, to analyze climate data and identify patterns of variability and shifts over time. Homogeneity tests are used to detect sudden changes or inhomogeneities caused by non-climatic variables (from station relocations or instrumental changes). Trend analysis is employed to detect long-term changes in climate variables such as temperature and precipitation, providing information on existing climate changes. Change-point detection tests help identify specific points at which significant shifts in climatic patterns occur, which may influence sudden transitions in ecosystems. Collectively, these tools enhance our ability to detect, interpret and respond to the evolving nature of climate change, thereby supporting timely and informed adaptation strategies in the fields of agriculture and forestry.