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waweru-ke/Temperature-SARIMA

Domain:

climate

Record type:

project
Creator:
waw
Host:
Nyeri temprature modeling using a SARIMA model. # Nyeri 2m Temperature Modeling & Forecasting Using SARIMA An end-to-end time series analysis and forecasting project utilizing European Centre for Medium-Range Weather Forecasts (ECMWF) **ERA5 Reanalysis hourly data** for 2-meter temperatures in Nyeri, Kenya. This repository contains the workflow for data preprocessing, stationarity testing, seasonal decomposition, and the optimization of a **Seasonal Autoregressive Integrated Moving Average (SARIMA)** model to forecast climate trends. --- ## 🚀 Project Overview & Workflow This project models historical 2-meter air temperature data from Jan 2000 through late 2024 to generate robust, seasonality-aware climate forecasts extending into 2027. ### Key Features * **Data Processing & Conversion:** Efficient handling of large meteorological timeseries data, downsampling from hourly records to monthly averages, and converting values from Kelvin to Celsius (°C). * **Statistical Verification:** Verification of stationarity using the Augmented Dickey-Fuller (ADF) test to validate modeling assumptions. * **Time Series Decomposition:** Isolation of underlying **Trend**, **Seasonal (12-month period)**, and **Residual** components using additive decomposition models. * **Automated Hyperparameter Tuning:** Utilizing a stepwise execution search (`pmdarima`) to discover optimal $(p, d, q) \times (P, D, Q)_m$ configurations minimizing Akaike Information Criterion (AIC). * **Validation & Forecasting:** Validation against out-of-sample data (2025-2026) along with confidence interval mapping for an 18-month look-ahead forecast window. --- ## 🛠️ Installation & Prerequisites To set up the environment and run this notebook, install the following required packages: ```bash pip install xarray dask h5netcdf cfgrib pmdarima pandas numpy matplotlib seaborn statsmodels

Visit

github.com

Languages

Gikuyu

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