CW3E Atmospheric River Landfall MET/MODE Verification Tool
The products are provided “as is” and are intended for research purposes only (disclaimer).
MODE, the Method for Object-Based Diagnostic Evaluation, provides an object-based verification for comparing gridded forecasts to gridded observations. It has most commonly been applied to precipitation fields and radar reflectivity, but here it is applied to integrated water vapor transport (IVT). The objects identified by this tool serve as a simplified Atmospheric River (AR) detection tool. While the majority of the identified objects will be ARs, and the majority of ARs will be identified objects, there may be some exceptions.
The maps show AR objects that have a length greater than approximately 1500 km and a centroid latitude north of 20oN at a given threshold (250, 500, or 750 kg m-1 s-1). If there is more than one such AR object, the statistics will be performed on the larger one. For more information on MODE click here.
Landfall Position Error (left): For ARs that come within 1 degree of the coast, the figure shows the core (where IVT > 80% of the max IVT) as a box, the location of the max IVT as a line in the box, and the northern and southern extent of the AR as whiskers. When an AR is 2-pronged or there are 2 ARs at the coast at the same time, a lighter color is used and the latitudes that are not experiencing an AR have the color removed from the bar & whiskers. Additionally, when there is a forecasted AR at the coast, but not in the analysis, a lighter color is used to indicate the false alarm. For an annotated description click here.
Measure of Effectiveness (middle): Points at the top right corner of the figure indicate that the forecast object and analysis object are the same size and in exactly the same location. Points along the diagonal line indicate that the 2 objects are the same size, but not in exactly the same location. When the forecast object is smaller than the analysis object, the corresponding point is above the diagonal, and points for a larger forecast object are below the diagonal.
The measure of effectiveness is computed as follows: the ratio between the intersection area to the analysis area is on the x-axis. This is a measure of false negative. The ratio between the intersection area and forecasted area is on the y-axis; a measure of false-positive.
Wind rose (right): The length of the lines indicates the 90th percentile intensity within the AR object. The angle is the average angle of the entire object.
MODE, the Method for Object-Based Diagnostic Evaluation, provides an object-based verification for comparing gridded forecasts to gridded observations. MODE may be used in a generalized way to compare data from which objects may be well defined. It has most commonly been applied to precipitation fields and radar reflectivity. The steps performed in MODE consist of:
- Define objects in the forecast and observation fields based on user-defined parameters.
- Compute attributes for each of those objects: such as area, centroid, axis angle, and intensity.
- For each forecast/observation object pair, compute differences between their attributes: such as area ratio, centroid distance, angle difference, and intensity ratio.
- Use fuzzy logic to compute a total interest value for each forecast/observation object pair based on user-defined weights.
- Based on the computed interest values, match objects across fields and merge objects within the same field.
- Write output statistics summarizing the characteristics of the single objects, the pairs of objects, and the matched/merged objects.
- MODE may be configured to use a few different sets of logic with which to perform matching and merging.
It is not uncommon for the domain of the model to cut short what would have been an AR object, making it less likely that objects near the domain boundary will be identified. A curved AR object is also less likely to be identified, since the computation of the aspect ratio includes the area in the middle of the curve.