Intercomparison of Spatial Forecast Verification Methods

By Eric Gilleland, D. Ahijevych, B. Brown, Barbara Casati, Elizabeth E. Ebert. 2009

462 citations recorded by the source corpus.

Subfields: Atmospheric Science, Environmental Engineering, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/a6166c985e398d84fa047e17ee4bdc804561d93f

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Citations in the corpus

Can deep learning beat numerical weather prediction? (2021, background): “Evaluating spatiotemporal patterns, for example, precipitation forecasts, with the help of radar data is particularly challenging due to the double penalty problem (cf. [116,120]).”
Verification and Calibration of Neighborhood and Object-Based Probabilistic Precipitation Forecasts from a Multimodel Convection-Allowing Ensemble (2012, background): “Grid point–based forecast and verification methods have limited applicability at convection-allowing resolution [e.g., see review by Gilleland et al. (2009)].”
Probabilistic Forecast Guidance for Severe Thunderstorms Based on the Identification of Extreme Phenomena in Convection-Allowing Model Forecasts (2011, unknown): “Given the demonstration of skill of high-resolution forecasts provided by subjective assessments (e.g., Kain et al. 2006), there is a need for measures based on neighborhood veriﬁcation techniques (e.g., Ebert 2008; Gilleland et al. 2009).”
Toward Better Understanding of the Contiguous Rain Area (CRA) Method for Spatial Forecast Verification (2009, background): “The idealized and WRF forecast samples tested in the ICP so far fit this description quite well (AGBE; Gilleland et al. 2009).”
The Integrated Nowcasting through Comprehensive Analysis (INCA) System and Its Validation over the Eastern Alpine Region (2011, background): “Classical verification measures and scores are scrutinized with regard to statistical properties such as propriety and equitability (Mason 2008), and new spatial verification methods are being developed and compared (Gilleland et al. 2009).”
Use of NWP for Nowcasting Convective Precipitation: Recent Progress and Challenges (2014, methodology): “New methods and metrics have been developed in recent years (Gilleland et al. 2009) and they should be more widely implemented by the nowcasting community in the future.”
Spatial-temporal fractions verification for high-resolution ensemble forecasts (2013, methodology): “By focusing on the spatial uncertainty these methods are usually known as the spatial verification methods and were well reviewed in Gilleland et al. (2009).”
Neural general circulation models for weather and climate (2023, methodology): “This filtering approach tackles the ‘double penalty problem’ 47 as it prevents the model from being penalized for predicting high-wavenumber features in incorrect locations at later times, especially beyond the predictability horizon.”
New Developments of the Intensity-Scale Technique within the Spatial Verification Methods Intercomparison Project (2010, methodology): “The IS technique belongs to the group of scaleseparation verification methods (Casati et al. 2008; Gilleland et al. 2009).”