scholarly journals Diurnal Variation of Tropical Ice Cloud Microphysics: Evidence from Global Precipitation Measurement Microwave Imager Polarimetric Measurements

2018 ◽  
Vol 45 (2) ◽  
pp. 1185-1193 ◽  
Author(s):  
Jie Gong ◽  
Xiping Zeng ◽  
Dong L. Wu ◽  
Xiaowen Li
Author(s):  
Yasutaka Ikuta ◽  
Masaki Satoh ◽  
Masahiro Sawada ◽  
Hiroshi Kusabiraki ◽  
Takuji Kubota

AbstractIn this study, the single-moment 6-class bulk cloud microphysics scheme used in the operational numerical weather prediction system at the Japan Meteorological Agency was improved using the observations of the Global Precipitation Measurement (GPM) core satellite as reference values. The original cloud microphysics scheme has the following biases: underestimation of cloud ice compared to the brightness temperature of the GPM Microwave Imager (GMI) and underestimation of the lower troposphere rain compared to the reflectivity of GPM Dual-frequency Precipitation Radar (DPR). Furthermore, validation of the dual-frequency rate of reflectivity revealed that the dominant particles in the solid phase of simulation were graupel and deviated from DPR observation. The causes of these issues were investigated using a single-column kinematic model. The underestimation of cloud ice was caused by a high ice-to-snow conversion rate, and the underestimation of precipitation in the lower layers was caused by an excessive number of small-diameter rain particles. The parameterization of microphysics scheme is improved to eliminate the biases in the single-column model. In the forecast obtained using the improved scheme, the underestimation of cloud ice and rain is reduced. Consequently, the prediction errors of hydrometeors were reduced against the GPM satellite observations, and the atmospheric profiles and precipitation forecasts were improved.


2017 ◽  
Vol 17 (4) ◽  
pp. 2741-2757 ◽  
Author(s):  
Jie Gong ◽  
Dong L. Wu

Abstract. Scattering differences induced by frozen particle microphysical properties are investigated, using the vertically (V) and horizontally (H) polarized radiances from the Global Precipitation Measurement (GPM) Microwave Imager (GMI) 89 and 166 GHz channels. It is the first study on frozen particle microphysical properties on a global scale that uses the dual-frequency microwave polarimetric signals.From the ice cloud scenes identified by the 183.3 ± 3 GHz channel brightness temperature (Tb), we find that the scattering by frozen particles is highly polarized, with V–H polarimetric differences (PDs) being positive throughout the tropics and the winter hemisphere mid-latitude jet regions, including PDs from the GMI 89 and 166 GHz TBs, as well as the PD at 640 GHz from the ER-2 Compact Scanning Submillimeter-wave Imaging Radiometer (CoSSIR) during the TC4 campaign. Large polarization dominantly occurs mostly near convective outflow regions (i.e., anvils or stratiform precipitation), while the polarization signal is small inside deep convective cores as well as at the remote cirrus region. Neglecting the polarimetric signal would easily result in as large as 30 % error in ice water path retrievals. There is a universal bell curve in the PD–TBV relationship, where the PD amplitude peaks at  ∼  10 K for all three channels in the tropics and increases slightly with latitude (2–4 K). Moreover, the 166 GHz PD tends to increase in the case where a melting layer is beneath the frozen particles aloft in the atmosphere, while 89 GHz PD is less sensitive than 166 GHz to the melting layer. This property creates a unique PD feature for the identification of the melting layer and stratiform rain with passive sensors.Horizontally oriented non-spherical frozen particles are thought to produce the observed PD because of different ice scattering properties in the V and H polarizations. On the other hand, turbulent mixing within deep convective cores inevitably promotes the random orientation of these particles, a mechanism that works effectively in reducing the PD. The current GMI polarimetric measurements themselves cannot fully disentangle the possible mechanisms.


2017 ◽  
Vol 34 (8) ◽  
pp. 1693-1711 ◽  
Author(s):  
H. Dong ◽  
X. Zou

AbstractThe Global Precipitation Measurement (GPM) Microwave Imager (GMI) plays an important role in monitoring global precipitation. In this study, an along-track striping noise is found in GMI observations of brightness temperatures for the two highest-frequency channels—12 and 13—with their central frequencies centered at 183.31 GHz. These two channels are designed for sounding the water vapor in the middle and upper troposphere. The pitch maneuver data of deep space confirmed an existence of striping noise in channels 12 and 13. A striping noise mitigation method is used for extracting the striping noise from the earth scene or deep space measurements of brightness temperatures by combining the principle component analysis (PCA) with the ensemble empirical mode decomposition (EEMD) method. A power spectrum density analysis indicated that the frequency of striping noise ranges between 0.06 and 0.533 s−1, where the right bound of 0.533 s−1 of frequency is exactly the inverse of the time (i.e., 1.875 s) it takes for the GMI to complete one conical scan line. The magnitude of striping noise in the brightness temperature observations of GMI channels 12 and 13 is about ±0.3 K. It is shown that after striping noise mitigation, the observation minus model simulation (O − B) distributions of both the earth scene and deep space brightness temperatures show no visible striping features.


2018 ◽  
Vol 10 (8) ◽  
pp. 1278 ◽  
Author(s):  
Jean-François Rysman ◽  
Giulia Panegrossi ◽  
Paolo Sanò ◽  
Anna Marra ◽  
Stefano Dietrich ◽  
...  

This paper describes a new algorithm that is able to detect snowfall and retrieve the associated snow water path (SWP), for any surface type, using the Global Precipitation Measurement (GPM) Microwave Imager (GMI). The algorithm is tuned and evaluated against coincident observations of the Cloud Profiling Radar (CPR) onboard CloudSat. It is composed of three modules for (i) snowfall detection, (ii) supercooled droplet detection and (iii) SWP retrieval. This algorithm takes into account environmental conditions to retrieve SWP and does not rely on any surface classification scheme. The snowfall detection module is able to detect 83% of snowfall events including light SWP (down to 1 × 10−3 kg·m−2) with a false alarm ratio of 0.12. The supercooled detection module detects 97% of events, with a false alarm ratio of 0.05. The SWP estimates show a relative bias of −11%, a correlation of 0.84 and a root mean square error of 0.04 kg·m−2. Several applications of the algorithm are highlighted: Three case studies of snowfall events are investigated, and a 2-year high resolution 70°S–70°N snowfall occurrence distribution is presented. These results illustrate the high potential of this algorithm for snowfall detection and SWP retrieval using GMI.


2014 ◽  
Vol 31 (9) ◽  
pp. 1902-1921 ◽  
Author(s):  
Ji-Hye Kim ◽  
Mi-Lim Ou ◽  
Jun-Dong Park ◽  
Kenneth R. Morris ◽  
Mathew R. Schwaller ◽  
...  

Abstract Since 2009, the Korea Meteorological Administration (KMA) has participated in ground validation (GV) projects through international partnerships within the framework of the Global Precipitation Measurement (GPM) Mission. The goal of this work is to assess the reliability of ground-based measurements in the Korean Peninsula as a means for validating precipitation products retrieved from satellite microwave sensors, with an emphasis on East Asian precipitation. KMA has a well-developed operational weather service infrastructure composed of meteorological radars, a dense rain gauge network, and automated weather stations. Measurements from these systems, including data from four ground-based radars (GRs), were combined with satellite data from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and used as a proxy for GPM GV over the Korean Peninsula. A time series of mean reflectivity differences (GR − PR) for stratiform-only and above-brightband-only data showed that the time-averaged difference fell between −2.0 and +1.0 dBZ for the four GRs used in this study. Site-specific adjustments for these relative mean biases were applied to GR reflectivities, and detailed statistical comparisons of reflectivity and rain rate between PR and bias-adjusted GR were carried out. In rain-rate comparisons, surface rain from the TRMM Microwave Imager (TMI) and the rain gauges were added and the results varied according to rain type. Bias correction has had a positive effect on GR rain rate comparing with PR and gauge rain rates. This study confirmed advance preparation for GPM GV system was optimized on the Korean Peninsula using the official framework.


Atmosphere ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 9 ◽  
Author(s):  
Guolu Gao ◽  
Quanliang Chen ◽  
Hongke Cai ◽  
Yang Li ◽  
Zhenglin Wang

Observational data from the Global Precipitation Measurement (GPM) Core Observatory during four summers (2014–2017) has been used to investigate deep convection systems (DCSs) over the Tibetan Plateau (TP) and its south slope (SS). The frequency, geographical distribution diurnal variation, and vertical structure of DCSs over the TP and SS are compared among these two regions. The frequency of DCSs over the SS (0.98%) was far higher than over the TP (0.15%), suggesting that stronger DCSs occur to the east and south of the TP. The maximum number of DCS occurred in July and August. A clear diurnal variation in DCS was found over the whole region, DCSs over the TP and SS both have a greatest amplitude in the afternoon. The probability of DCSs from 1200 to 1800 local time (LT) was 76.3% and 44.1% over TP and SS respectively, whereas the probability of DCSs being generated from 2200 (LT) to 0600 on the next day LT was 0.03% and 33.1% over the TP and SS respectively. There was a very low frequency of DCSs over the TP during the night. Five special echo top heights were used to investigate the vertical structure of DCSs. DCSs over the TP were both weaker and smaller than those over the SS.


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