Training Course Period: 12-23 October 2026

Online Phase: 12-17 October 2026
Face to Face Phase: 19-23 October 2026

This course strengthens participants’ technical and analytical capacity to work effectively with climate data for informed decision-making. It combines theoretical foundations of climate science with hands-on training in climate data collection, management, analysis, and visualization. Participants gain practical skills in using climate datasets, models, and tools to assess trends, extremes, and future scenarios. Emphasis is placed on applying climate data insights to climate change mitigation and adaptation, disaster risk reduction, and environmental planning and management across sectors.

This course aims to enhance participants’ technical and analytical capacity to effectively work with climate data for informed decision-making. Participants will develop a comprehensive understanding of different climate data types, sources, formats, and the critical importance of data quality. The course strengthens skills in climate data collection, management, and storage to ensure data integrity, accessibility, and usability. Participants will gain practical exposure to statistical methods, trend analysis, and climate modeling techniques, enabling them to interpret analytical results accurately. Emphasis is placed on applying climate data insights to climate change mitigation and adaptation, disaster risk reduction, and broader environmental planning and management contexts.

THEORY

Unit 1: What is Climate?

1.1 Climate and Weather
1.2 Why Climate Matters
1.3 Energy: Warming and Cooling Earth and the Atmosphere
1.4 Energy, Temperature, and Heat
1.5 Hydrological Cycle
1.6 Climate Statistics
1.7 Utilization of Weather Satellites

Unit 2: Basic General Circulation of Atmosphere and Ocean

2.1 General Circulation of the Atmosphere
2.2 The General Circulation and Precipitation Patterns
2.3 Global Wind Patterns and Surface Ocean Currents
2.4 El Nino, La Nina, and the Southern Oscillation
2.5 Other Significant Oscillation and Annual Mode

Unit 3: Air-Sea-Land-Climate Interactions

3.1 Air–Sea Interaction
3.2 Tropical Cyclones
3.3 Important Factors Affecting Land-Climate
3.4 Climate Classification
3.5 Climate Zones
3.6 Koppen-Geiger Climate Subdivisions

Unit 4: Climate Change

4.1 Past Climate Observations
4.2 Mechanisms of Climate Change
4.3 Current Climate Change
4.4 Understanding Recent Climate Change
4.5 Predicting Future Climate

Unit 5: Brief Introduction Mathematical Modelling of the Ocean and Atmosphere

5.1 Laboratory Models
5.2 Mathematical Model
5.3 Basic Concepts of Atmospheric and Climate General Circulation Models
5.4 Data Assimilation
5.5 Global Ocean Models
5.6 Regional Climate Models and Downscaling

Unit 6 What are Climate Model Phases and Scenarios?

6.1 The Models
6.2 Scenario Process for AR5
6.3 What are RCPs?
6.4 From Narratives to Scenarios

HAND-ON

Unit 1 Data Used in Climate and Weather Studies

1.1 Historical and Current Data
1.2 Forecasts and Projections
1.3 Reanalysis Data
1.4 Sectoral Information Needs
1.5 Some Important Climate Indices
1.6 Online Climate Data & Data Exploration Tools

Unit 2 Copernicus Climate Data Store (CDS)

2.1 Where to get Climate Data?
2.2 Copernicus Climate Change Service (C3S)
2.3 The Climate Data Store (CDS)
2.4 Data Format
2.5 ncdump & ncview

Unit 3 Introduction to Basic Linux

3.1 Windows Subsystem for Linux (WSL)
3.2 How to enable WSL on Windows 10
3.3 Basic Linux Structure & Command
3.4 Download Forecast Data
3.5 Tutorial 1

Unit 4 Introduction to Climate Data Operator (CDO)

4.1 Attributes of the Data
4.2 Data Analysis and Visualization
4.3 Basic Commands
4.4 Create Sub-Set of an Area
4.5 Arithmetic with a Constant

Unit 5 GrADS – Grid Analysis and Display System

5.1 What is GrADS?
5.2 The Data and Descriptor (.CTL) Files
5.3 Running 2.3 GrADS (initiation session)
5.4 Examples and Basic Exercises
5.5 More Examples for Practice
5.6 Inserting Titles, Texts, Forms and Symbols
5.7 Basic Controlling Graphical Options

Unit 6 Calculate Climate Indicators - Using Climpact

6.1 The ‘value’ of climate indices
6.2 Background to ETCCDI, Indices and Software
6.3 Background to Development of ET-SCI Indices
6.4 How to Run Climpact
6.5 Sector Data Correlation

The course adopts a blended and hands-on methodology combining theoretical instruction with practical computer-based exercises. Expert-led lectures introduce core climate science concepts, followed by guided tutorials using real climate datasets and analytical tools. Participants engage in step-by-step exercises on data retrieval, processing, visualization, and modeling. Interactive sessions, practice assignments, and facilitated discussions reinforce learning and enable participants to apply climate data analysis skills to real-world climate change, disaster risk reduction, and environmental planning contexts.

• Climate researchers and modelers who need advanced data analysis skills.
• Government officials and policymakers formulate environmental policies.
• Meteorologists analyze atmospheric data and forecast trends.
• Urban planners incorporate climate data into development plans.
• Industry stakeholders who are involved in emission reduction and sustainability.
• IT and technical support managing climate data systems.

$1,550 (without accommodation)
$2,036 [with accommodation (6 nights)]

Fees are inclusive of course materials (soft copy), cost of instructions, and course certificate. For face-to-face training, fee is inclusive of morning and afternoon snacks and lunch during the course.

Interested individuals and organizations can register online at www.adpc.net/apply.

For more information about the course, you may also contact Apibarl Bunchongraksa at apibarl@adpc.net and telephone numbers +66 22980681 to 92 ext. 132.