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At least 163 records · Page 9

Monsoon Convective During the South China Sea Monsoon Experiment: Observations from Ground-Based Radar and the TRMM Satellite

A main goal of the recent South China Sea Monsoon Experiment (SCSMEX) was to study convective processes associated with the onset of the Southeast Asian summer monsoon. The NASA TOGA C-band scanning radar was deployed on the Chinese research vessel Shi Yan #3 for two 20 day cruises, collecting dual-Doppler measurements in conjunction with the BMRC C-Pol dual-polarimetric radar on Dongsha Island. Soundings and surface meteorological data were also collected with an NCAR Integrated Sounding System (ISS). This experiment was the first major tropical field campaign following the launch of the Tropical Rainfall Measuring Mission (TRMM) satellite. These observations of tropical oceanic convection provided an opportunity to make comparisons between surface radar measurements and the Precipitation Radar (PR) aboard the TRMM satellite in an oceanic environment. Nearly continuous radar operations were conducted during two Intensive Observing Periods (IOPS) straddling the onset of the monsoon (5-25 May 1998 and 5-25 June 1998). Mesoscale lines of convection with widespread regions of both trailing and forward stratiform precipitation were observed following the onset of the active monsoon in the northern South China Sea region. The vertical structure of the convection during periods of strong westerly flow and relatively moist environmental conditions in the lower to mid-troposphere contrasted sharply with convection observed during periods of low level easterlies, weak shear, and relatively dry conditions in the mid to upper troposphere. Several examples of mesoscale convection will be shown from the ground (ship)-based and spaceborne radar data during times of TRMM satellite overpasses. Examples of pre-monsoon convection, characterized by isolated cumulonimbus and shallow, precipitating congestus clouds, will also be discussed.

Cifelli, Rob↗

Seasonal Characteristics of Non-Meteorological Radar Reflectivity Returns in Central Florida and Their Impact on TRMM Ground Validation

Radar data quality control is a major component to the Tropical Rainfall Measuring Mission (TRMM) Ground Validation (GV) effort. The quality control algorithm utilizes several adjustable height and reflectivity threshold parameters to remove non-precipitation echoes from ground-based radar data. Spurious radar reflectivity returns not removed during the quality control process may create biases in ground validation rainfall products used to evaluate rainfall measurements retrieved from aboard the TRMM satellite. To better evaluate the performance of the quality control algorithm, WSR-88D radar data from one primary GV site, Melbourne, Florida, are used to determine the seasonal characteristics of non-meteorological radar echoes in cast central Florida during the first year of the TRMM mission. It is demonstrated that unique spurious echo regimes develop throughout the year, leading to different levels of successful non-meteorological echo removal by the quality control algorithm. In addition to the type of non- precipitation echoes present, the success of the algorithm is also greatly dependent upon the amount of precipitation present. Less aggressive attempts to remove non-meteorological echoes must be employed when rain is observed so as not to remove these echoes as well. Therefore, precipitation statistics from ground validation monthly rainfall products will be utilized to further document the quality control algorithm performance. Moreover, these precipitation statistics will be used to demonstrate the relationship between dominant spurious echo regimes and rainfall amount. Finally, monthly statistics of contaminated ground validation radar data will be calculated and the effect on rainfall accumulation products will be discussed.

Robinson, Michael↗

Standard Reference Rainfall Products Used in the TRMM Ground Efforts

The Primary goal of the Tropical Rainfall Measuring Mission (TRMM) Ground Validation (GV) effort is to provide basic validation of satellite-derived precipitation measurements over monthly climatologies. To this end, the Joint Center for Earth Systems Technology (JCET) at the University of Maryland, Baltimore County produces monthly rainfall accumulation reference products for each of the four primary TRMM GV sites. These products, standard methodology for deriving monthly, gauge-adjusted rainfall products, are utilized for each primary site. The monthly rainfall GV reference products are developed in discrete, modular steps with distinct intermediate products. These developmental steps, which will be fully discussed, include: (1) extracting radar data over locations of rain gauges, (2) merging rain gauge and radar data in time and space with user-defined options, (3) quality control of radar and gauge merged data by tracking accumulations from each instrument, and (4) deriving Z_R relationship from quality-controlled merged data over monthly time scales. A summary of all gauge statistics and GV rainfall reference products available for TRMM science users will be presented. Basic reference product results and trends involving monthly accumulation, Z-R relationship, and gauge statistics for primary GV site will be discussed. Finally, the sample impact on monthly rainfall reference products, through varying the time interval between intermediate rainfall accumulations, will be analyzed and presented.

Marks, David A.↗

The Impact of TRMM on Mesoscale Model Simulation of Super Typhoon Paka

Tropical cyclone Paka formed during the first week of December 1997 and underwent three periods of rapid intensification over the following two weeks. During one of these periods, which initiated early on December 10, Paka's Dvorak-measured windspeed increased from 23 to 60 m/s over a 48-hr period. On December 18, during the last rapid deepening episode, Paka became a supertyphoon with a maximum wind speed of about 80 m/s. In this study, the Penn State/NCAR Mesoscale Model (MM5) with improved physics (i.e., cloud microphysics, radiation, land-soil-vegetation-surface processes, and TOGA COARE flux scheme) and a multiple level nesting technique (135, 45 and 15 km horizontal resolution) will be used to simulate supertyphoon Paka. We performed two runs initialized with Goddard Earth Observing System (GEOS) data sets. The first GEOS data set does not incorporate either TRMM (tropical rainfall measuring mission satellite) or SSM/I (sensor microwave imager) observed rainfall fields into the GEOS's assimilation system while the second one does. Preliminary results show that the MM5 simulated surface pressure deepened by more than 25 mb (45 km resolution domain) in the run initialized with the GEOS data set incorporating TRMM and SSM/I derived rainfall, compared to the one initialized without. However, the track and precipitation patterns are quite similar between the runs. In our presentation, we will show the impact of TRMM rainfall upon the MM5 simulation of Paka at various horizontal resolutions. We will also examine the physical processes associated with initial explosive development by comparing MM5 simulated rainfall and latent heat release. In addition, budget (vorticity, PV, momentum and heat) calculations and sensitivity tests will be performed to examine the upper-tropospheric and SST mechanisms responsible for the explosive development of Paka.

Tao, W.-K.↗

TRMM Observations of Lightning and Rainfall

A multi-sensor algorithm is proposed that uses total lightning observations in conjunction,with conventional weather satellite imagery to develop proportionality relationships that can be used to improve space-time estimates of rainfall in data sparse regions. Previous studies have examined the relationships between rainfall and cloud-to-ground lightning only. The proposed algorithm is developed from relationships developed between total lightning and rainfall data collected at the TRMM ground validation site at Kennedy Space Center, Florida and elsewhere. The algorithm is evaluated throughout the tropics with data collected by the TRMM Lightning Imaging Sensor (LIS) and the other TRMM instruments. Based on earlier studies of relationships among total lightning, passive microwave ice scattering signatures, and cloud top height, this algorithm is expected to improve rainfall estimates from geosynchronous orbit. A lightning sensor is currently being designed for a future flight on the GOES satellite.

Goodman, S. J.↗

TRMM Precipitation Radar Reflectivity Profiles Compared to High-Resolution Airborne and Ground-Based Radar Measurements

In this paper, TRMM (Tropical Rainfall Measuring Mission Satellite) Precipitation Radar (PR) products are evaluated by means of simultaneous comparisons with data from the high-altitude ER-2 Doppler Radar (EDOP), as well as ground-based radars. The comparison is aimed primarily at the vertical reflectivity structure, which is of key importance in TRMM rain type classification and latent heating estimation. The radars used in this study have considerably different viewing geometries and resolutions, demanding non-trivial mapping procedures in common earth-relative coordinates. Mapped vertical cross sections and mean profiles of reflectivity from the PR, EDOP, and ground-based radars are compared for six cases. These cases cover a stratiform frontal rainband, convective cells of various sizes and stages, and a hurricane. For precipitating systems that are large relative to the PR footprint size, PR reflectivity profiles compare very well to high-resolution measurements thresholded to the PR minimum reflectivity, and derived variables such as bright band height and rain types are accurate, even at high PR incidence angles. It was found that for, the PR reflectivity of convective cells small relative to the PR footprint is weaker than in reality. Some of these differences can be explained by non-uniform beam filling. For other cases where strong reflectivity gradients occur within a PR footprint, the reflectivity distribution is spread out due to filtering by the PR antenna illumination pattern. In these cases, rain type classification may err and be biased towards the stratiform type, and the average reflectivity tends to be underestimated. The limited sensitivity of the PR implies that the upper regions of precipitation systems remain undetected and that the PR storm top height estimate is unreliable, usually underestimating the actual storm top height. This applies to all cases but the discrepancy is larger for smaller cells where limited sensitivity is compounded by incomplete beam filling. Users of level three TRMM PR products should be aware of this scale dependency.

Heymsfield, G. M.↗

Hydrological Balance in Tropical Cyclones with Scatterometer and TRMM Data

Precipitation over oceans can be estimated from the radar and the microwave radiometer of the Tropical Rain Measuring Mission (TRMM). It can also be estimated from the divergence of the vertically integrated water vapor transport, through the conservation principle, assuming evaporation is relatively small. In tropical cyclones, the divergence of vertically integrated water vapor is highly dependent on the vertical transport and, therefore, on the wind divergence. Spaceborne scatterometers provide surface wind velocity and, therefore, surface wind divergence at spatial resolutions that are much higher than products of numerical weather prediction (NWP). In this study, ocean surface winds derived from the observations of space-based scatterometers and surface precipitation measured by TRMM were objectively interpolated to the same time and location during the passage of a tropical cyclone. Surface precipitation distribution was derived from wind and humidity profiles provided by NWP. When the surface level winds of NWP were replaced by the scatterometer winds, the surface precipitation patterns computed with the conservation method were found to be significantly changed and the new patterns are much closer in agreement with the patterns observed by TRMM.

Liu, W. Timothy↗

Improving Global Analysis and Short-Range Forecast Using Rainfall and Moisture Observations Derived from TRMM and SSM/I Passive Microwave Instruments

The Global Precipitation Mission, a satellite project under consideration as a follow-on to the Tropical Rainfall Measuring Mission (TRMM) by the National Aeronautics and Space Agency (NASA) in the United States, the National Space Development Agency (NASDA) in Japan, and other international partners, comprises an improved TRMM-like satellite and a constellation of 8 satellites carrying passive microwave radiometers to provide global rainfall measurements at 3-hour intervals. The success of this concept relies on the merits of rainfall estimates derived from passive microwave radiometers. This article offers a proof-of-concept demonstration of the benefits of using, rainfall and total precipitable water (TPW) information derived from such instruments in global data assimilation with observations from the TRMM Microwave Imager (TMI) and 2 Special Sensor Microwave/Imager (SSM/I) instruments. Global analyses that optimally combine observations from diverse sources with physical models of atmospheric and land processes can provide a comprehensive description of the climate systems. Currently, such data analyses contain significant errors in primary hydrological fields such as precipitation and evaporation, especially in the tropics. We show that assimilating the 6-h averaged TMI and SSM/I surface rainrate and TPW retrievals improves not only the hydrological cycle but also key climate parameters such as clouds, radiation, and the upper tropospheric moisture in the analysis produced by the Goddard Earth Observing System (GEOS) Data Assimilation System, as verified against radiation measurements by the Clouds and the Earth's Radiant Energy System (CERES) instrument and brightness temperature observations by the TIROS Operational Vertical Sounder (TOVS) instruments. Typically, rainfall assimilation improves clouds and radiation in areas of active convection, as well as the latent heating and large-scale motions in the tropics, while TPW assimilation leads to reduced moisture biases and improved radiative fluxes in clear-sky regions. Ensemble forecasts initialized with analyses that incorporate TMI and SSM/I rainfall and TPW data also yield better short-range predictions of geopotential heights, winds, and precipitation in the tropics. This study offers a compelling illustration of the potential of using rainfall and TPW information derived from passive microwave instruments to significantly improve the quality of 4-dimensional global datasets for climate analysis and weather forecasting applications.

Hou, Arthur Y.↗

A Study of TRMM Static Earth Sensor Performance Using On-Orbit Sensor Data

This paper presents the results of a study of the Barnes static Earth sensor assembly (ESA) using on-orbit data collected from the Tropical Rainfall Measuring Mission (TRMM) spacecraft. It is shown that there exist strong correlations between the large penetration angle residuals and the voltages produced by the Offset Radiation Source (ORS). It is conjectured that at certain times in the TRMM orbit the ORS is operating out of its calibrated range, and consequently corrupts the penetration angle information observed and processed by the ESA. The observed yaw drift between Digital Sun Sensor (DSS) observations is shown to be consistent with predictions by a simple roll-yaw coupling computation. This would explain the large drifts seen on TRMM, where the propagation of the yaw angle between DSS updates does not take into account the possibility of a non-zero roll angle error. Finally, the accuracy of the onboard algorithm used when only three of the four quadrants supply valid penetration angles is assessed. In terms of procedures used to perform this study, the analysis of ESA penetration angle residuals is discovered to be a very useful and insightful tool for assessing, the health and functionality of the ESA.

Natanson, Gregory↗

Effects of Nonuniform Beam Filling on Rainfall Retrieval for the TRMM Precipitation Radar

The Tropical Rainfall Measuring Mission (TRMM) will carry the first spaceborne radar for rainfall observation. Because the TRMM Precipitation Radar (PR) footprint size of 4.3 km is greater than the scale of some convective rainfall events, there is concern that nonuniform filling of the PR antenna beam may bias the retrieved rain-rate profile. The authors investigate this effect theoretically and then observationally using data from the NASA Jet Propulsion Laboratory Airborne Rain Mapping Radar (ARMAR), acquired during Tropical Oceans Global Atmosphere Coupled Ocean Atmosphere Response Experiment in early 1993. The authors' observational approach is to simulate TRMM PR data using the ARMAR data and compare the radar observables and retrieved rain rate from the simulated PR data with those corresponding to the high-resolution radar measurements. The authors find that the path-integrated attenuation and the resulting path-averaged rain rate are underestimated. The reflectivity and rain rate near the top of the rainfall column are overestimated. The near-surface reflectivity can be overestimated or underestimated, with a mean error very close to zero. The near-surface rain rate, however, is usually underestimated, sometimes severely.

Durden, Stephen L.↗

Latent Heating Retrievals Using the TRMM Precipitation Radar: A Multi-Seasonal Study

The Goddard Convective-Stratiform Heating (CSH) algorithm is used to retrieve profiles of latent heating over the global tropics for a period of several months using TRMM precipitation radar data. The seasonal variation of heating over the tropics is then examined. The period of interest also coincides with several TRMM field campaigns that recently occurred over the South China Sea in 1998 (SCSMEX), Brazil in 1999 (TRMM-LBA), and in the central Pacific in 1999 (KWAJEX). Sounding diagnosed Q1 budgets from these experiments could provide a means of validating the retrieved profiles of latent heating from the CSH algorithm.

Tao, W.-K.↗

Using TRMM Field Campaign Data for Assessing GEOS Forecast and Assimilation Products

The wealth of in-situ measurements gathered during Tropical Rain Measuring Mission (TRMM) field campaigns over a wide range of tropical conditions constitute an important data source for evaluating the quality of global model forecasts and assimilated datasets. In this study we use selected observations of cloud microphysics and atmospheric sounding from TEFLUN-1998, SCEMEX-1998, and TRMMLBA-1999 to examine the assimilation and forecast fields produced by the operational GEOS-3 (Goddard Earth Observing System - version 3) global data assimilation system (DAS) and a new finite-volume DAS under development at the Data Assimilation Office. Additionally, TRMM field campaign measurements are used to verify the impact of assimilating rainfall and moisture data derived from TRMM Microwave Imager and Special Sensor Microwave/Imager instruments on the GEOS analysis. We will also explore issues concerning the 'error of representativeness' in using in-situ observations of quantities with large spatial and temporal variability such as precipitation for validating gridded global data products.

Hou, Arthur Y.↗

Structure and Characteristics of Precipitation Systems Observed by TRMM

Multi-sensor measurements of total lightning (in-cloud plus cloud-to-ground) from the Lightning Imaging Sensor (LIS) aboard the TRMM satellite has been combined with passive microwave ice scattering and precipitation radar reflectivity profile information previously cataloged for precipitation features observed by TRMM. These precipitation features are defined by their surface rainfall or ice scattering signatures, with horizontal scales approx. 100 - 10000 sq km. Additionally, convective scale (approx. 100 sq km) storms are defined by the lightning data. Over the U.S. the national cloud-to-ground lightning observations are used to also determine the ratio of in-cloud to cloud-to-ground lightning, where it is hypothesized these ratios are related to the vertical profile of reflectivity and concentration of precipitation-sized ice. Combining the LIS, TRMM Microwave Imager (TMI), and Precipitation Radar (PR) for these storms allows investigation of the convective structures and convective regimes leading to observed lightning, scattering, and reflectivity signatures. Application of this approach to a global, multi-year data set (1998-2000) furthers our understanding of convective processes in different climatological regimes. The figure shows the distribution of high flash rate storms.

Goodman, Steve↗

Vertical Profiles of Latent Heating in TRMM: Validation and Assimilation in the GEOS Data Assimilation System

I have derived the vertical profiles of apparent heating Q and Q2 by using 3-hourly balloon sounding data from the ARM SGP sounding array for three IOPs in 2000. These IOPs cover the periods from 3/1 to 3/22, from 9/25 to 10/8, and from 11/27 to 12/22. These heating profiles will be collocated with the TRMM heating profiles for validation studies once the TRMM profiles become available to the investigators. I have also produced the objective analyses of Q1, Q2 and forcing fields for the international GCSS Case 3 Intercomparison project. The GSFC CRM participated in study, based on which TRMM heating profiles are derived. I have also studied to assimilate the vertical heating profile by constraining the cloud-base mass flux in the cumulus convection scheme using the CCM3. I first derive the vertical heating profile for each convective plume of unit cloud-base mass flux. The observed heating profile form ARM is then de-convoluted to derive the cloud base mass fluxes of all individual plumes. These fluxes are compared with those derived from the quasi-equilibrium hypothesis. They are shown to improve many other aspects of the model behavior.

Zhang, Ming-Hua↗

Monthly Oceanic Rainfall from TRMM Microwave Imager (TMI) Data

We evaluated the performance of the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) at-launch algorithm for monthly oceanic rain rate using two years (January 1998 - December 1999) of TMI data. The TMI at-launch algorithm is based on Wilheit et al.'s technique for estimating monthly oceanic rainfall that relies on histograms of multichannel microwave measurements. Comparisons with oceanic monthly rain rates derived from the Defense Meteorological Satellite Program (DMSP) F-13 and F-14 Special Sensor Microwave Imager (SSM/I) data show the average rain rates over the TRMM region (between 400S and 40N) are 3.0, 2.85 and 2.89 mm/day, respectively for F-13, F-14 and TMI. Based on the latest version of TB data (version 5), both rainrate and freezing height derived from TMI are similar to those from the F-13 and F-14 SSM/I data. However, regionally the differences are statistically significant at the 95% confidence. Three hourly monthly rainrates are also computed from 3-hourly TB histograms to examine the diurnal cycle of precipitation. Over most of the oceanic TRMM area, a distinct early morning rainfall peak is found. A harmonic analysis shows that the amplitude of the 12h harmonic is significant and comparable to that of the 24h harmonic.

Chang, Alfred T. C.↗

The Impact of TRMM Data on Mesoscale Numerical Simulation of Super Typhoon Paka

Accurate measurement of the spatial and temporal variations of tropical rainfall around the globe had remained as a critical problem in meteorology until the recent launch of the Tropical Rainfall Measuring Mission (TRMM). TRMM offers a unique opportunity to improve understanding of tropical meteorology and also offers a great opportunity to evaluate the impact of rainfall data on tropical weather forecasts. This study assesses the impact of TRMM Microwave Imager (TMI) derived surface rainfall data on the numerical simulation of Super Typhoon Paka (1997).

Pu, Zhao-Xia↗

A TRMM-Calibrated Infrared Technique for Convective and Stratiform Rainfall: Analysis and Validation

A satellite infrared technique with passive microwave calibration has been developed for estimating convective and stratiform. rainfall. The Convective-Stratiform Technique, calibrated by coincident, physically retrieved rain rates from the TRMM Microwave Imager (TMI), has been applied to 30 min interval GOES infrared data and aggregated over seasonal and yearly periods over northern South America. The diurnal cycle of rainfall, as well as the division between convective and stratiform rainfall is presented. For the period Jan-April 1999, analysis revealed significant effects of local circulations (river breeze, land/sea breeze, mountain/valley) on both the total rainfall and it's diurnal cycle. Results compared well (a one-hour lag) with the diurnal cycle derived from TOGA radar-estimated rainfall in Rondonia. The satellite estimates revealed that the convective rain constituted 24% of the rain area while accounting for 67% of the rain volume. Estimates of the diurnal cycle (both total rainfall and convective/stratiform) for an area encompassing the Amazon Basin (3 x 10(exp 6) square km) were in phase with those from the TRMM Precipitation Radar, despite the latter's limited sampling. Results will be presented comparing the yearly (2000) diurnal cycle for large regions (including the Amazon Basin), and an intercomparison of January-March estimates for three years, 1999-2001. We hope to demonstrate the utility of using the TRMM PR observations as verification for infrared estimates of the diurnal cycle, and as verification of the apportionment of rainfall into convective and stratiform components.

Negri, Andrew↗

Tropical Rainfall Measuring Mission (TRMM) and the Future of Rainfall Estimation from Space

Tropical rainfall is important in the hydrological cycle and to the lives and welfare of humans. Three-fourths of the energy that drives the atmospheric wind circulation comes from the latent heat released by tropical precipitation. Recognizing the importance of rain in the tropics, NASA for the U.S.A. and NASDA for Japan have partnered in the design, construction and flight of a satellite mission to measure tropical rainfall and calculate the associated latent heat release. The Tropical Rainfall Measuring Mission (TRMM) satellite was launched on November 27, 1997, and data from all the instruments first became available approximately 30 days after launch. Since then, much progress has been made in the calibration of the sensors, the improvement of the rainfall algorithms and applications of these results to areas such as Data Assimilation and model initialization. TRMM has reduced the uncertainty of climatological rainfall in tropics by over a factor of two, therefore establishing a standard for comparison with previous data sets and climatologies. It has documented the diurnal variation of precipitation over the oceans, showing a distinct early morning peak and this satellite mission has shown the utility of precipitation information for the improvement of numerical weather forecasts and climate modeling. This paper discusses some promising applications using TRMM data and introduces a measurement concept being discussed by NASA/NASDA and ESA for the future of rainfall estimation from space.

Kakar, Ramesh↗