scholarly journals On the relationship between Vertical Profile of Radar Reflectivity and LightningFlash Rate observed by the TRMM/PR and LIS

2005 ◽  
Vol 25 (2) ◽  
pp. 47-53
Author(s):  
Tomoo Ushio ◽  
Sakurai Syunsuke ◽  
Tomoaki Mega ◽  
Ken'ichi Okamoto ◽  
Zen-Ichiro Kawasaki
2017 ◽  
Vol 7 (2) ◽  
pp. 58 ◽  
Author(s):  
Shailendra Kumar

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.


2010 ◽  
Vol 27 (7) ◽  
pp. 1247-1254 ◽  
Author(s):  
David A. Short ◽  
Kenji Nakamura

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.


2004 ◽  
Vol 37 (5) ◽  
pp. 836-840 ◽  
Author(s):  
R. W. Alkire ◽  
R. Schuessler ◽  
F. J. Rotella ◽  
J. D. Gonczy ◽  
G. Rosenbaum

A 1 mm vertical-profile X-ray beamstop has been designed to operate in the energy range 6–20 keV. The relationship between the beamstop-to-sample distance and air scatter is discussed with the intent of establishing criteria for optimal beamstop positioning during an experiment. Different choices for beamstop materials are described with respect to stopping power, fluorescence and scattering from the surface. Suggestions for improvements in beamstop design are presented which are applicable for future automation and equipment safety. All work was performed on the Structural Biology Center insertion-device beamline, 19ID, at the Advanced Photon Source.


2011 ◽  
Vol 28 (3) ◽  
pp. 301-319 ◽  
Author(s):  
Mathew R. Schwaller ◽  
K. Robert Morris

Abstract A prototype Validation Network (VN) is currently operating as part of the Ground Validation System for NASA’s Global Precipitation Measurement (GPM) mission. The VN supports precipitation retrieval algorithm development in the GPM prelaunch era. Postlaunch, the VN will be used to validate GPM spacecraft instrument measurements and retrieved precipitation data products. The period of record for the VN prototype starts on 8 August 2006 and runs to the present day. The VN database includes spacecraft data from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and coincident ground radar (GR) data from operational meteorological networks in the United States, Australia, Korea, and the Kwajalein Atoll in the Marshall Islands. Satellite and ground radar data products are collected whenever the PR satellite track crosses within 200 km of a VN ground radar, and these data are stored permanently in the VN database. VN products are generated from coincident PR and GR observations when a significant rain event occurs. The VN algorithm matches PR and GR radar data (including retrieved precipitation data in the case of the PR) by calculating averages of PR reflectivity (both raw and attenuation corrected) and rain rate, and GR reflectivity at the geometric intersection of the PR rays with the individual GR elevation sweeps. The algorithm thus averages the minimum PR and GR sample volumes needed to “matchup” the spatially coincident PR and GR data types. The result of this technique is a set of vertical profiles for a given rainfall event, with coincident PR and GR samples matched at specified heights throughout the profile. VN data can be used to validate satellite measurements and to track ground radar calibration over time. A comparison of matched TRMM PR and GR radar reflectivity factor data found a remarkably small difference between the PR and GR radar reflectivity factor averaged over this period of record in stratiform and convective rain cases when samples were taken from high in the atmosphere. A significant difference in PR and GR reflectivity was found in convective cases, particularly in convective samples from the lower part of the atmosphere. In this case, the mean difference between PR and corrected GR reflectivity was −1.88 dBZ. The PR–GR bias was found to increase with the amount of PR attenuation correction applied, with the PR–GR bias reaching −3.07 dBZ in cases where the attenuation correction applied is >6 dBZ. Additional analysis indicated that the version 6 TRMM PR retrieval algorithm underestimates rainfall in case of convective rain in the lower part of the atmosphere by 30%–40%.


2020 ◽  
Vol 33 (7) ◽  
pp. 2853-2870 ◽  
Author(s):  
Michela Biasutti ◽  
Aiko Voigt

AbstractThe Tropical Rain Belts with an Annual Cycle and Continent Model Intercomparison Project (TRACMIP) ensemble—a multimodel ensemble of slab-ocean simulations in idealized configurations—provides a test of the relationship between the zonal mean ITCZ and the cross-equatorial atmospheric energy transports (AHTeq). In a gross sense, the ITCZ position is linearly related to AHTeq, as expected from the energetic framework. Yet, in many aspects, the TRACMIP model simulations do not conform to the framework. Throughout the annual cycle there are large excursions in the ITCZ position unrelated to changes in the AHTeq and, conversely, substantial variations in the magnitude of the AHTeq while the ITCZ is stationary at its northernmost position. Variations both in the net vertical energy input at the ITCZ location and in the vertical profile of ascent play a role in setting the model behavior apart from the conceptual framework. Nevertheless, a linear fit to the ITCZ–AHTeq relationship captures a substantial fraction of the seasonal variations in these quantities as well as the intermodel or across-climate variations in their annual mean values. The slope of the ITCZ–AHTeq linear fit for annual mean changes across simulations with different forcings and configurations varies in magnitude and even sign from model to model and we identify variations in the vertical profile of ascent as a key factor. A simple sea surface temperature–based index avoids the complication of changes in the vertical structure of the atmospheric circulation and provides a more reliable diagnostic for the ITCZ position.


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