Greenhouse Climate Modelling: What It Can Tell You Before You Build

Greenhouse climate modelling estimates how a specified structure and control strategy will behave under particular weather conditions. It can help compare sites, equipment choices and operating approaches before construction.

The value comes from answering a defined question. For example: would a proposed cooling system provide suitable conditions for the intended crop during the hottest part of the production season? What electricity and water would it require?

Agree the decision before running the model

A model needs a purpose and a comparison. Identify the baseline design, the alternatives and the measures that will determine the choice.

Those measures might include indoor temperature, humidity, hours outside a specified range or resource demand. The choice depends on the crop, project stage and capabilities of the model being used.

Keep the alternatives comparable. If one option changes the structure, crop, operating schedule and energy assumptions at once, it becomes difficult to explain what caused the result. A sequence of controlled comparisons is easier to assess.

Check the inputs

The simulation needs weather data and a description of the greenhouse. Depending on its scope, this may include the structure's dimensions, covering properties, ventilation openings, screens, equipment capacity and operating settings.

Crop assumptions also matter where plant processes are represented. A young crop and a mature canopy can interact differently with the growing environment. The model documentation should explain how those differences are treated.

For each important input, establish whether it comes from measurement, a supplier specification, published research or an assumption. A precise-looking result can still be highly dependent on a value that has not been checked.

Look at difficult periods as well as averages

An annual summary is useful for budgeting, but it can hide short periods of poor performance. Examine the conditions that put the design under pressure: extreme heat, high humidity, weak wind or limitations in the available equipment.

Ask whether the model assumes equipment can always meet its setpoint. In a real greenhouse, cooling, ventilation and power supply have limits. A study should explain what happens when those limits are reached.

Weather selection deserves the same attention. A typical year helps compare normal operating conditions. Testing additional years or defined extreme events can reveal different weaknesses. Those tests should be described clearly so readers understand what has actually been examined.

Understand calibration and validation

Calibration adjusts model parameters using observed data. Validation examines how well the resulting model performs against measurements, preferably including data that were not used to make those adjustments.

Performance is specific to the variables and conditions tested. Good temperature predictions at one facility do not automatically establish accurate water use, yield or performance in another climate.

For example, a Wageningen study of greenhouse management in subtropical China collected climate and crop measurements to evaluate the KASPRO model before exploring management alternatives. The study illustrates the role of measured evidence; it does not validate other models or locations.

Connect the results to the business case

Climate outputs can inform equipment selection, resource budgets and assessments of crop suitability. Further assumptions are needed to translate them into commercial production and revenue.

Keep those steps visible. Predicted indoor conditions, estimated crop output, saleable grades and realised prices are different parts of the assessment. Each needs its own evidence and explanation.

Test whether the recommended design changes when uncertain inputs move within plausible ranges. If a small change reverses the decision, the report should identify the information needed to improve confidence before capital is committed.

What a useful modelling report contains

Ask for the question tested, input sources, model version, design alternatives, results and important limitations. It should explain which findings hold across the conditions tested, which depend on uncertain assumptions and what the project team recommends doing next.

Drylands uses climate simulation within its project-development and advisory work. GROVE is part of that modelling work, considered alongside engineering, crop knowledge and the commercial assessment. The scope of a study should specify the outputs and conditions being evaluated.

If you are comparing sites or greenhouse designs, discuss the decisions your feasibility study needs to test.