This thesis investigates long-term climate trends in the Netherlands using historical weather data from the De Bilt station, maintained by the Royal Netherlands Meteorological Institute (KNMI). It examines changes in temperature, precipitation, and extreme weather events, including tropical days, ice days, and days with heavy or minimal rainfall.

To identify trends, both continuous variables (e.g., annual average temperature) and count-based indicators (e.g., number of tropical days) are analyzed. Methods include linear and isotonic regression for continuous data, and Poisson and negative binomial regression for count data, which often show overdispersion or excess zeros. Hypothesis tests, including slope tests and permutation tests, are used to assess statistical significance.

Results show strong evidence of warming: yearly, winter, and summer temperatures have all increased, with a clear rise in tropical days and a decline in ice days. Precipitation trends are less pronounced but suggest increases in winter and annual totals. The frequency of dry, wet, and extremely wet days also shows modest upward trends.

Overall, the findings confirm that regional climate change is observable in Dutch weather records. The results are consistent across multiple statistical models and align with global observations reported by the IPCC. This study contributes to the understanding of how global climate shifts manifest at a local level.