scholarly journals Precipitating Cloud Characteristics during Changma as Seen in TRMM PR Observations

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Eun-Kyoung Seo ◽  
Kyu-Myong Kim
Keyword(s):  
Seasonal Variability ◽  
Tropical Rainfall Measuring Mission ◽  
Reanalysis Data ◽  
Rainy Period ◽  
Convective Clouds ◽  
Convective Rain ◽  
Cloud Properties ◽  
Cloud Characteristics ◽  
Trmm Pr ◽  
Precipitating Clouds

The climatological characteristics of precipitating clouds during Changma, the summer rainy period in the Korean Peninsula, were investigated using the Precipitation Radar (PR) on the Tropical Rainfall Measuring Mission (TRMM) satellite. This investigation was further augmented with reanalysis data. Specifically, Changma clouds are compared with post-Changma clouds. Similarities and differences in cloud properties between the two periods are discussed based on seasonal changes in thermodynamic environments. For convective clouds migrating along the Changma (stationary) front, rain intensity is much stronger and cloud height is relatively higher than during any other summer period, including post-Changma period. Convective rain clouds have a large seasonal variability, even during summer. The seasonal variability in rain parameters related to convective rain type appears to be due to the thermodynamic and dynamic environments.

Lightning Frequency and Microphysical Properties of Precipitating Clouds over the Western North Pacific during Winter as Derived from TRMM Multisensor Observations

2007 ◽  
Vol 135 (6) ◽  
pp. 2226-2241 ◽  
Author(s):  
Yasu-Masa Kodama ◽  
Haruna Okabe ◽  
Yukie Tomisaka ◽  
Katsuya Kotono ◽  
Yoshimi Kondo ◽  
...  
Keyword(s):  
North Pacific ◽  
Western North Pacific ◽  
Large Scale ◽  
Tropical Rainfall Measuring Mission ◽  
Radar Reflectivity ◽  
Phase Layer ◽  
Convective Clouds ◽  
Microphysical Properties ◽  
The Tropics ◽  
Precipitating Clouds

Abstract Tropical Rainfall Measuring Mission observations from multiple sensors including precipitation radar, microwave and infrared radiometers, and a lightning sensor were used to describe precipitation, lightning frequency, and microphysical properties of precipitating clouds over the midlatitude ocean. Precipitation over midlatitude oceans was intense during winter and was often accompanied by frequent lightning. Case studies over the western North Pacific from January and February 2000 showed that some lightning occurred in deep precipitating clouds that developed around cyclones and their attendant fronts. Lightning also occurred in convective clouds that developed in regions of large-scale subsidence behind extratropical cyclones where cold polar air masses were strongly heated and moistened from below by the ocean. The relationships between lightning frequency and the minimum polarization corrected temperature (PCT) at 37 and 85 GHz and the profile of the maximum radar reflectivity resembled relationships derived previously for cases in the Tropics. Smaller lapse rates in the maximum radar reflectivity above the melting level indicate vigorous convection that, although shallow and relatively rare, was as strong as convection over tropical oceans. Lightning was most frequent in systems for which the minimum PCT at 37 GHz was less than 260 K. Lightning and PCT at 85 GHz were not as well correlated as lightning and PCT at 37 GHz. Thus, lightning was frequent in convective clouds that contained many large hydrometeors in the mixed-phase layer, because PCT is more sensitive to large hydrometeors at 37 than at 85 GHz. The relationship between lightning occurrence and cloud-top heights derived from infrared observations was not straightforward. Microphysical conditions that support lightning over the midlatitude ocean in winter were similar to conditions in the Tropics and are consistent with Takahashi’s theory of riming electrification.

scholarly journals Climatological Behavior of Precipitating Clouds in the Northeast Region of Brazil

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Rayana Santos Araújo Palharini ◽  
Daniel Alejandro Vila
Keyword(s):  
Relative Frequency ◽  
Tropical Rainfall Measuring Mission ◽  
Precipitation Radar ◽  
Convective Clouds ◽  
Strong Signal ◽  
Deep Convective Clouds ◽  
Stratiform Clouds ◽  
Precipitating Clouds ◽  
Data Period

This study aims to analyze the climatological classification of precipitating clouds in the Northeast of Brazil using the radar on board the Tropical Rainfall Measuring Mission (TRMM) satellite. Thus, for this research a time series of 15 years of satellite data (period 1998–2012) was analyzed in order to identify what types of clouds produce precipitation estimated by Precipitation Radar (PR) and how often these clouds occur. From the results of this work it was possible to estimate the average relative frequency of each type of cloud present in weather systems that influence the Northeast of Brazil. In general, the stratiform clouds and shallow convective clouds are the most frequent in this region, but the associated rainfall is not as abundant as precipitation caused by deep convective clouds. It is also seen that a strong signal of shallow convective clouds modulates rainfall over the coastal areas of Northeast of Brazil and adjacent ocean. In this scenario, the main objective of this study is to contribute to a better understanding of the patterns of cloud types associated with precipitation and building a climatological analysis from the classification of clouds.

scholarly journals The invigoration of deep convective clouds over the Atlantic: aerosol effect, meteorology or retrieval artifact?

2010 ◽  
Vol 10 (18) ◽  
pp. 8855-8872 ◽  
Author(s):  
I. Koren ◽  
G. Feingold ◽  
L. A. Remer
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Transport Model ◽  
Chemical Transport ◽  
Reanalysis Data ◽  
Cloud Fraction ◽  
Chemical Transport Model ◽  
Convective Clouds ◽  
Cloud Parameters ◽  
Cloud Properties

Abstract. Associations between cloud properties and aerosol loading are frequently observed in products derived from satellite measurements. These observed trends between clouds and aerosol optical depth suggest aerosol modification of cloud dynamics, yet there are uncertainties involved in satellite retrievals that have the potential to lead to incorrect conclusions. Two of the most challenging problems are addressed here: the potential for retrieved aerosol optical depth to be cloud-contaminated, and as a result, artificially correlated with cloud parameters; and the potential for correlations between aerosol and cloud parameters to be erroneously considered to be causal. Here these issues are tackled directly by studying the effects of the aerosol on convective clouds in the tropical Atlantic Ocean using satellite remote sensing, a chemical transport model, and a reanalysis of meteorological fields. Results show that there is a robust positive correlation between cloud fraction or cloud top height and the aerosol optical depth, regardless of whether a stringent filtering of aerosol measurements in the vicinity of clouds is applied, or not. These same positive correlations emerge when replacing the observed aerosol field with that derived from a chemical transport model. Model-reanalysis data is used to address the causality question by providing meteorological context for the satellite observations. A correlation exercise between the full suite of meteorological fields derived from model reanalysis and satellite-derived cloud fields shows that observed cloud top height and cloud fraction correlate best with model pressure updraft velocity and relative humidity. Observed aerosol optical depth does correlate with meteorological parameters but usually different parameters from those that correlate with observed cloud fields. The result is a near-orthogonal influence of aerosol and meteorological fields on cloud top height and cloud fraction. The results strengthen the case that the aerosol does play a role in invigorating convective clouds.

scholarly journals Vertical Characteristics of Reflectivity in Intense Convective Clouds using TRMM PR Data

2017 ◽  
Vol 7 (2) ◽  
pp. 58 ◽  
Author(s):  
Shailendra Kumar
Keyword(s):  
Vertical Profile ◽  
Regional Differences ◽  
Vertical Structure ◽  
Convective Cloud ◽  
Convective Precipitation ◽  
Vertical Profiles ◽  
Gangetic Plain ◽  
Convective Clouds ◽  
Trmm Pr ◽  
Precipitation Area

Tropical Rainfall Measuring Mission Precipitation Radar (TRMM-PR) based vertical structure in intense convective precipitation is presented here for Indian and Austral summer monsoon seasons. TRMM 2A23 data is used to identify the convective echoes in PR data. Two types of cloud cells are constructed here, namely intense convective cloud (ICC) and most intense convective cloud (MICC). ICC consists of PR radar beams having Ze>=40 dBZ above 1.5 km in convective precipitation area, whereas MICC, consists of maximum reflectivity at each altitude in convective precipitation area, with at least one radar pixel must be higher than 40 dBZ or more above 1.5 km within the selected areas. We have selected 20 locations across the tropics to see the regional differences in the vertical structure of convective clouds. One of the important findings of the present study is identical behavior in the average vertical profiles in intense convective precipitation in lower troposphere across the different areas. MICCs show the higher regional differences compared to ICCs between 5-12 km altitude. Land dominated areas show higher regional differences and Southeast south America (SESA) has the strongest vertical profile (higher Ze at higher altitude) followed by Indo-Gangetic plain (IGP), Africa, north Latin America whereas weakest vertical profile occurs over Australia. Overall SESA (41%) and IGP (36%) consist higher fraction of deep convective clouds (>10 km), whereas, among the tropical oceanic areas, Western (Eastern) equatorial Indian ocean consists higher fraction of low (high) level of convective clouds. Nearly identical average vertical profiles over the tropical oceanic areas, indicate the similarity in the development of intense convective clouds and useful while considering them in model studies.

scholarly journals Possible Misidentification of Rain Type by TRMM PR over Tibetan Plateau

2007 ◽  
Vol 46 (5) ◽  
pp. 667-672 ◽  
Author(s):  
Yunfei Fu ◽  
Guosheng Liu
Keyword(s):  
Tibetan Plateau ◽  
Common Knowledge ◽  
Tropical Rainfall Measuring Mission ◽  
Stratiform Rain ◽  
Freezing Level ◽  
Central Tibetan Plateau ◽  
Standard Product ◽  
Trmm Pr ◽  
Trmm Precipitation ◽  
Rain Events

Abstract Rain-type statistics derived from Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) standard product show that some 70% of raining pixels in the central Tibetan Plateau summer are stratiform—a clear contradiction to the common knowledge that rain events during summer in this region are mostly convective, as a result of the strong atmospheric convective instability resulting from surface heating. In examining the vertical distribution of the stratiform rain-rate profiles, it is suspected that the TRMM PR algorithm misidentifies weak convective rain events as stratiform rain events. The possible cause for this misidentification is believed to be that the freezing level is close to the surface over the plateau, so that the ground echo may be mistakenly identified as the melting level in the PR rain classification algorithm.

Comparison of snow cover characteristics according to weather stations and ERA 5-Land reanalysis in the Perm region

2021 ◽  
Vol 2 ◽  
pp. 95-110
Author(s):  
A.D., Kryuchkov ◽  
◽  
N.A Kalinin ◽  
Keyword(s):  
Snow Cover ◽  
Interannual Variability ◽  
Seasonal Variability ◽  
Snow Depth ◽  
Reanalysis Data ◽  
Error Distribution ◽  
Current Version ◽  
Weather Stations ◽  
Perm Region

Comparison of snow cover characteristics according to weather stations and ERA 5-Land reanalysis in the Perm region / Kryuchkov A.D., Kalinin N.A. // Hydrometeorological Research and Forecasting, 2021, no. 2 (380), pp. 95-110. The consistency of information on the snow depth contained in the ERA 5-Land reanalysis with data of weather stations of the Perm region is analyzed. The study is performed for the period from October 1990 to May 2020. It is shown that the interannual variability of the snow cover is generally successfully reflected by the current version of the reanalysis. Data on the snow availability are more accurately reproduced during the period of formation of the snow cover than during its melt. The performed calculations demonstrate a systematic overestimation of the snow depth in the ERA 5-Land reanalysis relative to the actual observations and a predominantly meridional error distribution on the territory of the Perm region. The maximum values in the seasonal variability of the snow cover occur earlier in the reanalysis than in the actual observations. Keywords: snow cover, reanalysis, weather stations, seasonal variability, interannual variability

scholarly journals A comparison between the GNSS tomography technique and the WRF model in retrieving 3D wet refractivity field in Hong Kong

2018 ◽  
Author(s):  
Zhaohui Xiong ◽  
Bao Zhang ◽  
Yibin Yao
Keyword(s):  
Hong Kong ◽  
Water Vapor ◽  
Weather Prediction ◽  
Wrf Model ◽  
Vertical Direction ◽  
Lower Troposphere ◽  
Reanalysis Data ◽  
Radiosonde Data ◽  
Rainy Period ◽  
Lower Accuracy

Abstract. Water vapor plays an important role in various scales of weather processes. However, there are limited means to monitor its 3-dimensional (3D) dynamical changes. The Numerical Weather Prediction (NWP) model and the Global Navigation Satellite System (GNSS) tomography technique are two of the limited means. Here, we conduct an interesting comparison between the GNSS tomography technique and the Weather Research and Forecasting (WRF) model (a representative of the NWP models) in retrieving Wet Refractivity (WR) in Hong Kong area during a rainy period and a rainless period. The GNSS tomography technique is used to retrieve WR from the GNSS slant wet delay. The WRF Data Assimilation (WRFDA) model is used to assimilate GNSS Zenith Tropospheric Delay (ZTD) to improve the background data. The WRF model is used to generate reanalysis data using the WRFDA output as the initial values. The radiosonde data are used to validate the WR derived from the GNSS tomography and the reanalysis data. The Root Mean Square (RMS) of the tomographic WR, the reanalysis WR that assimilate GNSS ZTD, and the reanalysis WR that without assimilating GNSS ZTD are 6.50 mm/km, 4.31 mm/km and 4.15 mm/km in the rainy period. The RMS becomes 7.02 mm/km, 7.26 mm/km and 6.35 mm/km in the rainless period. The lower accuracy in the rainless period is mainy due to the sharp variation of WR in the vertical direction. The results also show that assimilating GNSS ZTD into the WRFDA model only slightly improves the accuracy of the reanalysis WR and that the reanalysis WR is better than the tomographic WR in most cases. However, in a special experimental period when the water vapor is highly concentrated in the lower troposphere, the tomographic WR outperforms the reanalysis WR in the lower troposphere. When we assimilate the tomographic WR in the lower troposphere into the WRFDA model, the reanalysis WR is improved.

scholarly journals Effect of TRMM Orbit Boost on Radar Reflectivity Distributions

2010 ◽  
Vol 27 (7) ◽  
pp. 1247-1254 ◽  
Author(s):  
David A. Short ◽  
Kenji Nakamura
Keyword(s):  
Probability Distributions ◽  
Gaussian Function ◽  
Tropical Rainfall Measuring Mission ◽  
Radar Reflectivity ◽  
Response Functions ◽  
Precipitation Radar ◽  
Mathematical Properties ◽  
Trmm Pr ◽  
Before And After ◽  
Basic Characteristics

Abstract Probability distributions of measured radar reflectivity from the precipitation radar (PR) on board the Tropical Rainfall Measuring Mission (TRMM) satellite show a small, counterintuitive increase in the midrange, 20–34 dBZ, when comparing data from periods before and after the orbit altitude was boosted in August 2001. Data from two 2-yr time periods, 1999–2000 (preboost) and 2002–03 (postboost), show statistically significant differences of 2%–3% at altitudes of 2, 4, and 10 km and for path-averaged reflectivity. The bivariate Gaussian function, used to model idealized radar response functions, has mathematical properties that indicate an increase in field-of-view (FOV) size associated with an increase in satellite altitude can be expected to result in a narrowing of observed dBZ distributions, with a resulting increase in midrange values. Numerical simulations with echo areas much smaller and larger than the TRMM PR FOV before (4.3 km) and after (5.0 km) boost are used to demonstrate basic characteristics of the observed and expected distribution changes.

scholarly journals Thermodynamic phase retrieval of convective clouds: impact of sensor viewing geometry and vertical distribution of cloud properties

2013 ◽  
Vol 6 (3) ◽  
pp. 539-547 ◽  
Author(s):  
E. Jäkel ◽  
J. Walter ◽  
M. Wendisch
Keyword(s):  
Phase Retrieval ◽  
Near Infrared ◽  
Three Dimensional ◽  
Ice Clouds ◽  
Convective Clouds ◽  
Microphysical Properties ◽  
Cloud Properties ◽  
Reflectivity Spectra ◽  
Vertical Distributions ◽  
Thermodynamic Phase

Abstract. The sensitivity of passive remote sensing measurements to retrieve microphysical parameters of convective clouds, in particular their thermodynamic phase, is investigated by three-dimensional (3-D) radiative transfer simulations. The effects of different viewing geometries and vertical distributions of the cloud microphysical properties are investigated. Measurement examples of spectral solar radiance reflected by cloud sides (passive) in the near-infrared (NIR) spectral range are performed together with collocated lidar observations (active). The retrieval method to distinguish the cloud thermodynamic phase (liquid water or ice) exploits different slopes of cloud side reflectivity spectra of water and ice clouds in the NIR. The concurrent depolarization backscattering lidar provides geometry information about the cloud distance and height as well as the depolarization.

Seasonal Variability of Storm Top Altitudes in the Tropics and Subtropics Observed by TRMM PR

2016 ◽  
Vol 169 ◽  
pp. 113-126 ◽  
Author(s):  
Fengjiao Chen ◽  
Yunfei Fu ◽  
Peng Liu ◽  
Yuanjian Yang
Keyword(s):  
Seasonal Variability ◽  
Trmm Pr ◽  
The Tropics
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