Polarimetric radar observations above the melting layer in winter storms reveal enhanced differential reflectivity ZDR and specific differential phase shift KDP, collocated with reduced copolar correlation coefficient ρhv; these signatures often appear as isolated “pockets.” High-resolution RHIs and vertical profiles of polarimetric variables were analyzed for a winter storm that occurred in Oklahoma on 27 January 2009, observed with the polarimetric Weather Surveillance Radar-1988 Doppler (WSR-88D) in Norman. The ZDR maximum and ρhv minimum are located within the temperature range between −10° and −15°C, whereas the KDP maximum is located just below the ZDR maximum. These signatures are coincident with reflectivity factor ZH that increases toward the ground. A simple kinematical, one-dimensional, two-moment bulk microphysical model is developed and coupled with electromagnetic scattering calculations to explain the nature of the observed polarimetric signature. The microphysics model includes nucleation, deposition, and aggregation and considers only ice-phase hydrometeors. Vertical profiles of the polarimetric radar variables (ZH, ZDR, KDP, and ρhv) were calculated using the output from the microphysical model. The base model run reproduces the general profile and magnitude of the observed ZH and ρhv and the correct shape (but not magnitude) of ZDR and KDP. Several sensitivity experiments were conducted to determine if the modeled signatures of all variables can match the observed ones. The model was incapable of matching both the observed magnitude and shape of all polarimetric variables, however. This implies that some processes not included in the model (such as secondary ice generation) are important in producing the signature.
Abstract.A dust storm of fearful proportions hit Phoenix in the early evening hours of 5 July 2011. This storm, an American haboob, was predicted hours in advance because numerical, land-atmosphere modeling, computing power and remote sensing of dust events have improved greatly over the past decade. High-resolution numerical models are required for accurate simulation of the small scales of the haboob process, with high velocity surface winds produced by strong convection and severe downbursts. Dust productive areas in this region consist mainly of agricultural fields, with soil surfaces disturbed by plowing and tracks of land in the high Sonoran Desert laid barren by ongoing draught.Model simulation of the 5 July 2011 dust storm uses the coupled atmospheric-dust model NMME-DREAM (Nonhydrostatic Mesoscale Model on E grid, Janjic et al., 2001; Dust REgional Atmospheric Model, Nickovic et al., 2001;Pérez et al., 2006) with 4 km horizontal resolution. A mask of the potentially dust productive regions is obtained from the land cover and the normalized difference vegetation index (NDVI) data from the Moderate Resolution Imaging Spectroradiometer (MODIS). The scope of this paper is validation of the dust model performance, and not use of the model as a tool to investigate mechanisms related to the storm. Results demonstrate the potential technical capacity and availability of the relevant data to build an operational system for dust storm forecasting as a part of a warning system. Model results are compared with radar and other satellitebased images and surface meteorological and PM 10 observations. The atmospheric model successfully hindcasted the position of the front in space and time, with about 1 h late arrival in Phoenix. The dust model predicted the rapid uptake of dust and high values of dust concentration in the ensuing storm. South of Phoenix, over the closest source regions (∼25 km), the model PM 10 surface dust concentration reached ∼2500 µg m −3 , but underestimated the values measured by the PM 10 stations within the city. Model results are also validated by the MODIS aerosol optical depth (AOD), employing deep blue (DB) algorithms for aerosol loadings. Model validation included Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), equipped with the lidar instrument, to disclose the vertical structure of dust aerosols as well as aerosol subtypes. Promising results encourage further research and application of high-resolution modeling and satellite-based remote sensing to warn of approaching severe dust events and reduce risks for safety and health.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.