What common numerical weather prediction error arises from local boundary conditions?

In numerical weather prediction, local boundary conditions play a crucial role in determining the accuracy of forecasts. Model errors due to local effects occur when the physical processes and characteristics of specific areas, such as terrain variations, vegetation, bodies of water, and urban environments, are not accurately represented within the weather models.

These local effects can significantly influence weather phenomena, such as precipitation patterns, temperature variations, and wind flows. If the model fails to account for these localized influences, it can lead to substantial inaccuracies in the predicted weather conditions. For example, mountainous areas can create rain shadows, while urban heat islands can amplify local temperatures, both of which may not be captured accurately without high-resolution models that incorporate detailed boundary conditions.

The other options do not directly address the influence of local boundary conditions on numerical weather prediction. Incorrect temperature readings can arise from various factors that are not solely linked to local effects. Lack of sufficient data generally pertains to broader issues of data collection rather than specific local errors. A failure to detect severe weather could result from multiple factors, including the limitations of the model or network, but is not specifically tied to local boundary conditions.