Scale-Selective Verification of Rainfall Accumulations from High-Resolution Forecasts of Convective Events

Abstract

The development of NWP models with grid spacing down to ∼1 km should produce more realistic forecasts of convective storms. However, greater realism does not necessarily mean more accurate precipitation forecasts. The rapid growth of errors on small scales in conjunction with preexisting errors on larger scales may limit the usefulness of such models. The purpose of this paper is to examine whether improved model resolution alone is able to produce more skillful precipitation forecasts on useful scales, and how the skill varies with spatial scale. A verification method will be described in which skill is determined from a comparison of rainfall forecasts with radar using fractional coverage over different sized areas. The Met Office Unified Model was run with grid spacings of 12, 4, and 1 km for 10 days in which convection occurred during the summers of 2003 and 2004. All forecasts were run from 12-km initial states for a clean comparison. The results show that the 1-km model was the most skillful over all but the smallest scales (approximately <10–15 km). A measure of acceptable skill was defined; this was attained by the 1-km model at scales around 40–70 km, some 10–20 km less than that of the 12-km model. The biggest improvement occurred for heavier, more localized rain, despite it being more difficult to predict. The 4-km model did not improve much on the 12-km model because of the difficulties of representing convection at that resolution, which was accentuated by the spinup from 12-km fields.

Mean and extreme precipitation over European river basins better simulated in a 25 km AGCM

“…We also conduct scale-dependent evaluation and calculate the fractions skill score (FSS) for different horizontal scales following Roberts and Lean (2008). The FSS is obtained by comparing binary fields, defined in terms of exceedance of a threshold, between model and observation for different sizes of an averaging neighbourhood, i.e.…”

“…The FSS takes values between 0 and 1, and typically increases with horizontal scale as shown in Fig. 3 of Roberts and Lean (2008). Here, we use different quantiles of each of the precipitation fields as the exceedance threshold in the FSS calculation so that the FSS approaches unity for large scales and the domain-mean bias (Table 1) is disregarded in this evaluation.…”

30-second-Update 100-m-Mesh Data Assimilation Experiments: A Sudden Local Rain Case in Kobe on 11 September 2014

“…Among others, much attention has been paid to skillful NWP for severe weather (e.g., Kain et al 2006, Hohenegger and Schär 2007a, b;Kawabata et al 2007;Roberts and Lean 2008). Recently, the ensemble Kalman filter (EnKF;Evensen 1994Evensen , 2003 has become a major method in data assimilation (DA), and has contributed to investigate convection-permitting regional NWP (e.g., Zhang et al 2007;Stensrud et al 2009Stensrud et al , 2013Clark et al 2010;Schwartz et al 2010; Baldauf et al 2011;Melhauser and Zhang 2012; Yussolf et al 2013, Kunii 2014a, Weng and Zhang 2016.…”

The use of potential vorticity inversion to evaluate the effect of precipitation on downstream mesoscale processes

“…Explaining why the WRF produces these values of precipitation and PV using this particular configuration for these two cases is beyond the scope of this article. It is well established that the development of convection (or lack thereof) has a nonlinear impact on the evolution of a simulation from that point onward (Zhang et al, , 2007, and the forecasting of convection remains challenging for current operational models (Fowle and Roebber, 2003;Roberts and Lean, 2008). Thus, our focus is on the effect that one area of precipitation has on another area of precipitation farther downstream.…”