Diagnostic evaluation of extreme winter rainfall events over the Arabian Peninsula using high‐resolution weather research and forecasting simulations

Abstract

The sensitivity of different cumulus physical parameterization schemes for simulating extreme winter precipitation events over the Arabian Peninsula (AP) is investigated using a high-resolution weather research and forecasting (WRF) model. For winters in 2001-2016, the following three parameterization schemes are examined: (i) Kain-Fritsch (KF), (ii) Betts-Miller-Janji c (BMJ), and (iii) Grell-Freitas (GF). The simulation results suggest that the AP extreme winter rainfall events are best simulated using the KF, followed by the BMJ, in terms of spatial distribution and intensity.The spatial pattern correlation coefficient between the model-simulated and observed rainfall is highest with KF (0.94), followed by BMJ (0.91) and GF (0.76). These results are attributed to a better representation of the moisture transport associated with upper-tropospheric cyclonic circulation and potential vorticity intrusions. By contrast, the GF scheme fails to simulate moisture convergence and updrafts, leading to an unrealistic representation of cloud hydrometeors and an improper organization of convection and associated extreme rainfall intensities. Meanwhile, the KF and BMJ also successfully simulate the dynamics and thermodynamics of extreme rainfall events that are usually driven by synoptic forcing. The study results suggest that the choice of cumulus parameterization schemes in the WRF model is critical for reliable simulation of extreme rainfall in the hyperarid AP region.

Numerical Simulation of Winter Precipitation over the Western Himalayas Using a Weather Research and Forecasting Model during 2001–2016

“…Ref. [29] reported the underestimation of zonal winds by RCM over WH, which is in agreement with our findings. The wind speeds observed for D01 and D02 are comparable to those noted by [85].…”

“…Precise depiction of local-scale energy balance is critical for the accurate simulation of atmospheric flow, especially across dynamic terrains like WH, which necessitates higher grid resolution. Furthermore, a much higher model grid resolution may assist in reducing the uncertainties associated with predicting precipitation characteristics by providing a detailed representation of the interaction between synoptic weather systems and local topography [28,29]. Therefore, adequate model horizontal grid spacing in the RCM numerical model configuration is important for effectively depicting the topographical characteristics [30].…”

Underlying physical mechanisms of winter precipitation extremes over India's high mountain region

“…Positive PV in the upper level corresponds to cyclonic circulation, whereas negative values usually suggest anticyclonic circulation. Moreover, a prominent meridional gradient of upper level PV can strengthen the background flow, facilitating the expansion of cyclonic circulations to lower levels too (Attada et al ., 2022; Hoskins et al ., 2007). The upper tropospheric (300 hPa) PV composite anomalies, shown in Figure 3e,f, illustrate the presence of strong positive PV anomalies along the WHR, providing conditions that support moist convection.…”

“…The upper tropospheric (300 hPa) PV composite anomalies, shown in Figure 3e,f, illustrate the presence of strong positive PV anomalies along the WHR, providing conditions that support moist convection. The reduced atmospheric stability through higher PV flux has been linked to initiation of enhanced convection through Rossby wave‐breaking (Attada et al ., 2022). In particular, the interaction of WDs and stronger PV can help in the growth of WDs through moist baroclinic instability via orographic interactions during extremes.…”