The accurate estimation of precipitation is an important objective for the Dual-frequency Precipitation Radar (DPR), which is located on board the Global Precipitation Measurement (GPM) satellite core observatory. In this study, a Bayesian correction (BC) approach is proposed to improve the DPR's instantaneous rainfall rate product. Ground dual-polarization radar (GR) observations are used as references, and a log-transformed Gaussian distribution is assumed as the instantaneous rainfall process. Additionally, a generalized regression model is adopted in the BC algorithm. Rainfall intensities such as light, moderate, and heavy rain and their variable influences on the model's performance are considered. The BC approach quantifies the predictive uncertainties associated with the Bayesian-corrected DPR (DPR_BC) rainfall rate estimates. To demonstrate the concepts developed in this study, data from the GPM overpasses of the Weather Service Surveillance Radar (WSR-88D), KHGX, in Houston, Texas, between April 2014 and June 2018 are used. Observation errors in the DPR instantaneous rainfall rate estimates are analyzed as a function of rainfall intensity. Moreover, the best-performing BC model is implemented in three GPM-overpass cases with heavy rainfall records across the southeastern United States. The results show that the DPR_BC rainfall rate estimates have superior skill scores and are in better agreement with the GR references than with the DPR estimates. This study demonstrates the potential of the proposed BC algorithm for enhancing the instantaneous rainfall rate product from spaceborne radar equipment.
Data from the continuous observations of four shallow snow events (echo top < 8 km) and two deep events (> 10 km) were obtained using the C-band vertically pointing radar with frequency-modulation continuous-wave technology with extremely high resolution during the winter of 2015–2016 in middle latitudes of China. Snow-generating cells (GCs) were found near the cloud top in each event. Reflectivity (Z), radial velocity (Vr), and the vertical gradients of Z (dZ/dh, where h is the vertical distance) and Vr (dVr/dh) showed different vertical distribution characteristics between the upper GC and lower stratiform regions (St regions). Fall streaks (FSs) associated with GCs were embedded in the St regions. In the deep events, the proportions of GC regions were slightly larger, but the average contributions to the growth of Z (33 %) were lower than those in the shallow events (42 %). The average d Z /dh values were usually two to three times larger inside GCs and FSs compared to outside. Bimodal Doppler spectra were used to establish the relationships between Z and the reflectivity-weighted particle fall speed (Vz) for the two regions. The vertical air velocity (Wa) and Vz were then retrieved, and the results showed that both the updraft and the downdraft were alternately observed in GC regions. GC locations were usually accompanied by strong upward air motion, with average speeds mostly distributed around 1.2 m s−1, whereas downward air motion often appeared between GCs. In the St regions, the speeds of Wa were mainly within 0.5 m s−1. The upper areas of the St regions consisted primarily of weak upward motion, whereas weak downward motion dominated the lower areas. There was no apparent difference in Wa inside and outside the FSs. The average Vz was slightly larger inside GCs and FSs compared to outside, with a difference of 0.1–0.3 m s−1 and 0.2–0.4 m s−1, respectively.
Global simulations with 1.45 km grid spacing are presented that were performed using the Integrated Forecasting System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF). Simulations are uncoupled (without ocean, sea ice, or wave model), using 62 or 137 vertical levels and the full complexity of weather forecast simulations is presented, including recent date initial conditions, real-world topography, and state-of-the-art physical parametrizations, as well as diabatic forcing including shallow convection, turbulent diffusion, radiation and five categories for the water substance (vapor, liquid, ice, rain, and snow). Simulations are evaluated with regard to computational efficiency and model fidelity. Scaling results are presented, which were performed on the fastest supercomputer in Europe, Piz Daint (Top 500, November 2018). Important choices for the model configuration at this unprecedented resolution for the IFS are discussed such as the use of hydrostatic and non-hydrostatic equations or the time resolution of physical phenomena which is defined by the length of the time step.
Our simulations indicate that the IFS model—based on spectral transforms with a semi-implicit, semi-Lagrangian time stepping scheme in contrast to more local discretization techniques—can provide a meaningful baseline reference for O(1) km global simulations.
Variations in raindrop size distribution (DSD) during the southwest monsoon (SWM) season over different climatic regions in the Indian subcontinent and adjoining seas are studied in this paper using five years (2014–2018) of global precipitation measurement dual-frequency precipitation radar derived DSDs. The rain rate (R) stratified DSD measurements show clearly that land, sea, and orography differ in their mass-weighted mean diameter (Dm) values. Irrespective of R, Dm values of deep rain were found to be larger in continental rain than in maritime and orographic rain. However, for shallow storms, the Dm values were smaller for continental rain than for orographic and maritime rain. Based on the Dm values and their variations with R of the deep systems, the regions could be categorized into four groups, within which the Dm values were nearly equal: (1) the northwest India (NWI) and the southeast peninsular India (SEPI); (2) the foothills of the Himalayas (FHH) and the central India (CI); (3) the northeast India (NEI) and the Bay of Bengal (BOB); and (4) the Arabian Sea (AS), the Western Ghats (WG), and the Myanmar coast (MC). Compared to other geographical regions of the Indian subcontinent, the Dm values of the deep systems were the largest over NWI and SEPI and the smallest over the WG, MC, and AS; while for shallow systems, the Dm values were the largest over the BOB and AS and the smallest over the SEPI and NWI regions. Though the cloud drops were smaller over the continental regions, the raindrops were larger than in the maritime and orographic rain regions. The microphysical and dynamical processes that occur during precipitation play a vital role in altering the DSDs of continental rain.