Tressa L. Fowler

Beyond the Basics: Evaluating Model-Based Precipitation Forecasts Using Traditional, Spatial, and Object-Based Methods

AbstractWhile traditional verification methods are commonly used to assess numerical model quantitative precipitation forecasts (QPFs) using a grid-to-grid approach, they generally offer little diagnostic information or reasoning behind the computed statistic. On the other hand, advanced spatial verification techniques, such as neighborhood and object-based methods, can provide more meaningful insight into differences between forecast and observed features in terms of skill with spatial scale, coverage area, displacement, orientation, and intensity. To demonstrate the utility of applying advanced verification techniques to mid- and coarse-resolution models, the Developmental Testbed Center (DTC) applied several traditional metrics and spatial verification techniques to QPFs provided by the Global Forecast System (GFS) and operational North American Mesoscale Model (NAM). Along with frequency bias and Gilbert skill score (GSS) adjusted for bias, both the fractions skill score (FSS) and Method for Object-Ba...

THE DEVELOPMENTAL TESTBED CENTER AND ITS WINTER FORECASTING EXPERIMENT

Abstract The Weather Research and Forecasting (WRF) Developmental Testbed Center (DTC) was formed to promote exchanges between the development and operational communities in the field of Numerical Weather Prediction (NWP). The WRF DTC serves to accelerate the transfer of NWP technology from research to operations and to support a subset of the current WRF operational configurations to the general community. This article describes the mission and recent activities of the WRF DTC, including a detailed discussion about one of its recent projects, the WRF DTC Winter Forecasting Experiment (DWFE). DWFE was planned and executed by the WRF DTC in collaboration with forecasters and model developers. The real-time phase of the experiment took place in the winter of 2004/05, with two dynamic cores of the WRF model being run once per day out to 48 h. The models were configured with 5-km grid spacing over the entire continental United States to ascertain the value of high-resolution numerical guidance for winter weat...

Multiyear Droughts and Pluvials over the Upper Colorado River Basin and Associated Circulations

AbstractThis study analyzes spatial and temporal characteristics of multiyear droughts and pluvials over the southwestern United States with a focus on the upper Colorado River basin. The study uses two multiscalar moisture indices: standardized precipitation evapotranspiration index (SPEI) and standardized precipitation index (SPI) on a 36-month scale (SPEI36 and SPI36, respectively). The indices are calculated from monthly average precipitation and maximum and minimum temperatures from the Parameter-Elevation Regressions on Independent Slopes Model dataset for the period 1950–2012. The study examines the relationship between individual climate variables as well as large-scale atmospheric circulation features found in reanalysis output during drought and pluvial periods. The results indicate that SPEI36 and SPI36 show similar temporal and spatial patterns, but that the inclusion of temperatures in SPEI36 leads to more extreme magnitudes in SPEI36 than in SPI36. Analysis of large-scale atmospheric fields ...

Testing the Tests: What Are the Impacts of Incorrect Assumptions When Applying Confidence Intervals or Hypothesis Tests to Compare Competing Forecasts?

AbstractWhich of two competing continuous forecasts is better? This question is often asked in forecast verification, as well as climate model evaluation. Traditional statistical tests seem to be well suited to the task of providing an answer. However, most such tests do not account for some of the special underlying circumstances that are prevalent in this domain. For example, model output is seldom independent in time, and the models being compared are geared to predicting the same state of the atmosphere, and thus they could be contemporaneously correlated with each other. These types of violations of the assumptions of independence required for most statistical tests can greatly impact the accuracy and power of these tests. Here, this effect is examined on simulated series for many common testing procedures, including two-sample and paired t and normal approximation z tests, the z test with a first-order variance inflation factor applied, and the newer Hering–Genton (HG) test, as well as several boots...