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NASA NTRS2001

Environmental Characteristics of Convective Systems During TRMM-LBA

In this paper, data collected from 51 days of continual upper atmospheric soundings and TOGA radar at ABRACOS Hill during the TRMM-LBA experiment are used to describe the mean thermodynamic and kinematic airmass properties of wet season convection over Rondonia, Brazil. Distinct multi-day easterly and westerly lower tropospheric wind regimes occurred during the campaign with contrasting airmass characteristics. Westerly wind periods featured modest CAPE (1000 J/kg), moist conditions (>90% RH) extending through 700 mb and shallow (900 mb) speed shear on the order of 10(exp -4)/s. This combination of characteristics promoted convective systems that featured a relatively large fraction of stratiform rainfall and weak convection nearly devoid of lightning. The environment is very similar to the general airmass conditions experienced during the Darwin, Australia monsoon convective regime. In contrast, easterly regime convective systems were more strongly electrified and featured larger convective rain rates and reduced stratiform rainfall fraction. These systems formed in an environment with significantly larger CAPE (1500 J/kg), drier lower and middle level humidities (< 80% RH) and a wind shear layer that was both stronger (10(exp -3)/s) and deeper (700 mb). The larger CAPE resulted from strong insolation under relatively cloud-free skies (owing to reduced column humidity) and was also weakly capped in the lowest 1-2 km, thus contributing to a more explosive growth of convection. The time series of low- and mid-level averaged humidity exhibited marked variability between westerly and easterly regimes and was characterized by low frequency (i.e., multi-day to weekly) oscillations. The synoptic scale origins of these moisture fluctuations are examined, which include the effects of variable low-level airmass trajectories and upper-level, westward migrating cyclonic vortices. The results reported herein provide an environmental context for ongoing dual Doppler analyses and numerical modeling case studies of individual TRMM-LBA convective systems.

Halverson, Jeffrey B.↗
NASA NTRS2001

A TRMM-Calibrated Infrared Rainfall Algorithm Applied Over Brazil

A satellite infrared (IR) technique for estimating rainfall over northern South America is presented. The objectives are to examine the diurnal variability of rainfall and to investigate the relative contributions from the convective and stratiform components. In this study, we apply the Convective-Stratiform Technique (CST) of Adler and Negri (1988). The parameters of the original technique were re-calibrated using coincident rainfall estimates (Olson et W., 2000) derived from the Tropical Rain Measuring Mission (TRMM) Microwave Imager (TMI) and GOES IR (11 micrometer) observations. Local circulations were found to play a major role in modulating the rainfall and its diurnal cycle. These included land/sea circulations (notably along the northeast Brazilian coast and in the Gulf of Panama), mountain/valley circulations (along the Andes Mountains), and circulations associated with the presence of rivers. This last category was examined in detail along the Amazon R. east of Manaus. There we found an early morning rainfall maximum along the river (5 LT at 58W, 3 LT at 56W). Rainfall avoids the river in the afternoon (12 LT and later), notably at 56 W. The width of the river seems to be generating a land/river circulation which enhances early morning rainfall but inhibits afternoon rainfall. Results are compared to ground-based radar data collected during the Large-Scale Biosphere-Atmosphere (LBA) experiment in southwest Brazil, to monthly raingages in northeastern Brazil, and to data from the TRMM Precipitation Radar.

Negri, Andrew J.↗
NASA NTRS2001

Convective Systems Observed and Simulated During TRMM Field Campaigns

Recently completed TRMM field campaigns (TEFLUN1998, SCSMEX-1998, TRMM.LBA-1999, and KWAJEX 1999) have obtained direct measurements of microphysical data associated with convective systems from various geographical locations. These TRMM field experiments were designed to contribute to fundamental understanding of cloud dynamics and microphysics, as well as for validation,, testing assumptions and error estimates of cloud-resolving models, forward radiative transfer models, algorithms used to estimate rainfall statistics and vertical structure of precipitation and latent heating from both surface-based radar and satellites.

Tao, Wei-Kuo↗
NASA NTRS2001

Precipitation-Lightning Relationships on a Global Basis and a Study of Tropical Continental Convection in TRMM Brazil

This report is concerned with a summary of work completed under NASA Grant NAG5-4778 entitled: "Precipitation-Lightning Relationships on a Global Basis", with a supplement entitled: "A Study of Tropical Continental Convection in TRMM/Brazil". Several areas of endeavor are summarized, some of them concerned directly with the observations from the TRMM satellite, and others focussing on ground based measurements in the NASA TRMM LBA field program in Brazil.

Williams, Earle R.↗
NASA NTRS2000

TRMM Microwave Radiometer Rain Rate Estimation Method with Convective and Stratiform Discrimination

Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) radiometer brightness temperature data in the 85 GHz channel (T85) reveal distinct local minima (T85min) in a regional map containing a Mesoscale Convective System (MCS). A map of surface rain rate for that region, deduced from simultaneous measurements made by the Precipitation Radar (PR) on board the TRMM satellite, reveals that these T85min, produced by scattering, correspond to local PR rain maxima. Utilizing the PR rain rate map as a guide, we have developed a TMI algorithm to retrieve convective and stratiform rain. In this algorithm, two parameters are used to classify three kinds of thunderstorms (Cbs) based on the T85 data: a) the magnitude of scattering depression deduced from local T85mi, and b) the mean horizontal gradient of T85 around such minima. Initially, the algorithm is optimized or tuned utilizing the PR and TMI data of a few MCS events. The areal distribution of light (1-10 mm/hr), moderate (10-20 mm/hr), and intense (greater than or equal to 20 mm/hr) rain rates are retrieved on the average with an accuracy of about 15%. Taking advantage of this ability of our retrieval method, one could derive the latent heat input into the atmosphere over the 760 km wide swath of the TMI radiometer in the tropics.

Prabhakara, Cuddapah↗
NASA NTRS2001

Estimation of Mesoscale Atmospheric Latent Heating Profiles from TRMM Rain Statistics Utilizing a Simple One-Dimensional Model

In this study, a model is developed to estimate mesoscale-resolution atmospheric latent heating (ALH) profiles. It utilizes rain statistics deduced from Tropical Rainfall Measuring Mission (TRMM) data, and cloud vertical velocity profiles and regional surface thermodynamic climatologies derived from other available data sources. From several rain events observed over tropical ocean and land, ALH profiles retrieved by this model in convective rain regions reveal strong warming throughout most of the troposphere, while in stratiform rain regions they usually show slight cooling below the freezing level and significant warming above. The mesoscale-average, or total, ALH profiles reveal a dominant stratiform character, because stratiform rain areas are usually much larger than convective rain areas. Sensitivity tests of the model show that total ALH at a given tropospheric level varies by less than +/- 10 % when convective and stratiform rain rates and mesoscale fractional rain areas are perturbed individually by 1 15 %. This is also found when the non-uniform convective vertical velocity profiles are replaced by one that is uniform. Larger variability of the total ALH profiles arises when climatological ocean- and land-surface temperatures (water vapor mixing ratios) are independently perturbed by +/- 1.0 K (+/- 5 %) and +/- 5.0 K (+/- 15 %), respectively. At a given tropospheric level, such perturbations can cause a +/- 25 % variation of total ALH over ocean, and a factor-of-two sensitivity over land. This sensitivity is reduced substantially if perturbations of surface thermodynamic variables do not change surface relative humidity, or are not extended throughout the entire model evaporation layer. The ALH profiles retrieved in this study agree qualitatively with tropical total diabatic heating profiles deduced in earlier studies. Also, from January and July 1999 ALH-profile climatologies generated separately with TRMM Microwave Imager and Precipitation Radar rain statistics, it is shown that ALH profiles can be retrieved utilizing diverse satellite-derived rain products that offer convective and stratiform discrimination. Therefore, the ALH retrieval model developed in this study can be used to make regional estimates of total diabatic heating profiles in the future Global Precipitation Measurement mission, and to assimilate these profiles into numerical weather forecast and climate models.

Iacovazzi, Robert A., Jr.↗
NASA NTRS2001

TRMM Precipitation Radar and Microwave Imager Observations of Convective and Stratiform Rain and Their Theoretical Implications

Theoretical models of radiative transfer are developed to simulate the 85 GHz brightness temperature, T85, observed by the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) radiometer as a function of rain rate. These simulations are performed separately over regions of convective and stratiform rain. For the purpose of constructing vertical profiles of hydrometeors in these regions, guidance is taken from TRMM Precipitation Radar (PR) observations, and from recent investigations of LDR and Z(sub DR) measurements made by land-based polarimetric radars. We find that for a given rain rate, the extinction in 85 GHz due to hydrometeors above the freezing level is relatively weak in convective regions compared to that in stratiform regions. The hydrometeor profile above the freezing level responsible for this weak extinction in convective regions is inferred, from LDR and Z(sub DR) observations and theoretical considerations, to contain two layers: 1) a layer of two km thickness with mixed phase particles, liquid drops and graupel, directly above the freezing level, and 2) a layer of graupel extending from the top of the mixed-phase layer to the cloud top. Strong extinction in the stratiform regions is inferred to result from slowly-falling, low-density ice aggregates (snow) above the freezing level. These theoretical results are consistent with T85 measured by TMI and the rain rate deduced from PR for convective and stratiform rain regions. On the basis of this study we infer that the accuracy of the rain rate sensed by TMI depends critically on the specification of the convective or stratiform nature of the rain.

Prabhakara, C.↗
NASA NTRS2001

Validation of TRMM Satellite Rainfall Products Over Oklahoma for a Three Year Period (1998-2000)

This study evaluates the level 2 and level 3 rainfall products from the Tropical Rainfall Measuring Mission gridded distribution of 118 high resolution tipping buckets from the Oklahoma Mesonet. The Tropical Rainfall Measuring Mission, a joint satellite mission between NASA and the National Space Development Agency (NASDA) of Japan, was designed to estimate global precipitation between 40 S and 40 N latitude. The TRMM satellite, consisting of two main precipitation sensors, a passive microwave (TMI) and precipitation radar (PR) sensors, was launched in 1997. Although the great advantage of TRMM has been its ability to sample precipitation globally over the tropical oceans in places where ground sensors do not exist, regional points over land still offer the best opportunity for validating these rain estimates. For this study, the gauge data was gridded at I x I degree resolution between 34 and 36 N and -95 and -100 W. The location of Oklahoma is somewhat unique, in that, it is located near the turning point for the satellite. This study investigates effects of temporal sampling on the satellite measurements and the resulting rainfall bias observed between space and ground based sensors. The first part of the study analyzes the monthly rainfall statistics of the 3AI2 (TMI), the 3A25 (PR) and the 31142 (combined sensors) with the rain gauges. It uses regression techniques and a computation of the probability density function (PDF) and cumulative probability density function (CDF) for each sensor to evaluate the effects of temporal sampling on the satellite products and the sufficiency of using two overpasses a day to estimate rainfall on a monthly scale. In further probing this issue, the study also looked at the direct coincidence of ground and satellite measurements by comparing instantaneous comparisons obtained from the level 2 orbital track data, e.g. 2A12, 2A25. Lastly, the effects of temporal sampling were further studied by sub-sampling the gauge data only at overpass times. This methodology provides a quantitative way of separately inferring the fraction of bias due to temporal sampling and the rainfall algorithm. In addition to showing the salient effects of temporal sampling, the study also revisits the historical problem of correlating point gauge estimates with area estimates, though, the problem is ameliorated by averaging and gridding the data to the area resolution scale of the satellite.

Fisher, Brad↗
NASA NTRS2001

TRMM Precipitation Radar and Microwave Imager Observations of Convective and Stratiform Rain Over Land and Their Theoretical Implications

Observations of brightness temperature, Tb made over land regions by the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) radiometer have been analyzed along with the nearly simultaneous measurements of the vertical profiles of reflectivity factor, Z, made by the Precipitation Radar (PR) onboard the TRMM satellite. This analysis is performed to explore the interrelationship between the TMI and PR data in areas that are covered predominantly by convective or stratiform rain. In particular, we have compared on a scale of 20 km, average vertical profiles of Z with the averages of Tbs in the 19, 37 and 85 GHz channels. Generally, we find from these data that as Z increases, Tbs in the three channels decrease due to extinction. In order to explain physically the relationship between the Tb and Z observations, we have performed radiative transfer simulations utilizing vertical profiles of hydrometeors applicable to convective and stratiform rain regions. These profiles are constructed taking guidance from the Z observations of PR and recent LDR and ZDR measurements made by land-based polarimetric radars.

Prabhakara, C.↗
NASA NTRS2001

Sampling of the Diurnal Cycle of Precipitation using TRMM

We examine the temporal sampling of tropical regions using observations from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and Precipitation Radar (PR). We conclude that PR estimates at any one hour, even using three years of data, are inadequate to describe the diurnal cycle of precipitation over regions smaller than 12 degrees, due to high spatial variability in sampling. We show that the optimum period of accumulation is four hours. Diurnal signatures display half as much sampling error when averaged over four hours of local time. A similar pattern of sampling variability is found in the TMI data, despite the TMI's wider swath and increased sampling. These results are verified using an orbital model. The sensitivity of the sampling to satellite altitude is presented, as well as sampling patterns at the new TRMM altitude of 402.5 km.

Negri, Andrew J.↗
NASA NTRS2002

Use of TRMM Data to Test an Improved Parameterization of Stratiform Precipitation

We successfully implemented our EAUcup parameterization of convection in our most recent geodesic-grid version of the Colorado State University General Circulation Model (CSU GCM). Tendencies due to convection and large-scale cloud microphysics are computed using the same time-step, allowing smoother interactions between convective and large-scale moist processes. Figures illustrate our most recent progress on the simulation of convective and stratiform precipitations for January. Comparisons against TRMM precipitation radar (PR) data would reveal a systematic overestimation of the simulated monthly-mean convective rainfall over well-known areas of deep convection. One major deficiency in the global distribution of stratiform precipitation simulated in the CSU GCM is the lack of stratiform precipitation over land in the tropics. This result strongly disagree with Fowler and Randall who show that convective and stratiform precipitations always coexist and that their ratio to the total precipitation is about 0.5. We believe that stratiform precipitation over land evaporates before reaching the ground because the lower troposphere remains too dry in response to the lack of convective detrainment occurring immediately above the Planetary Boundary Layer (PBL). This issue is further investigated at present. We made significant progress in the development of our parameterization of fractional cloudiness. As an example of our ongoing research effort, a figure shows the global distribution of the cloud ice mixing ratio and corresponding fractional area of ice clouds at 250 hPa. These results were obtained using our latitude-longitude grid version of the CSU GCM. There is a nice correspondence between areas of high (low) values of the cloud ice mixing ratio and the cloud fraction. A nice correspondence between the global distribution of the cloud water mixing ratio and fraction of water clouds in the lower troposphere can also be found. We are pursuing this effort, but in the geodesic version of the GCM. We hope to be able to make comparison of the simulated precipitation against TRMM precipitation data in the near future.

Randall, David A.↗
NASA NTRS2002

Understanding the Global Water and Energy Cycle Through Assimilation of Precipitation-Related Observations: Lessons from TRMM and Prospects for GPM

Understanding the Earth's climate and how it responds to climate perturbations relies on what we know about how atmospheric moisture, clouds, latent heating, and the large-scale circulation vary with changing climatic conditions. The physical process that links these key climate elements is precipitation. Improving the fidelity of precipitation-related fields in global analyses is essential for gaining a better understanding of the global water and energy cycle. In recent years, research and operational use of precipitation observations derived from microwave sensors such as the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager and Special Sensor Microwave/Imager (SSM/I) have shown the tremendous potential of using these data to improve global modeling, data assimilation, and numerical weather prediction. We will give an overview of the benefits of assimilating TRMM and SSM/I rain rates and discuss developmental strategies for using space-based rainfall and rainfall-related observations to improve forecast models and climate datasets in preparation for the proposed multi-national Global Precipitation Mission (GPM).

Hou, Arthur↗
NASA NTRS2002

A Method to Retrieve Rainfall Rate Over Land from TRMM Microwave Imager Observations

Over tropical land regions, rain rate maxima in mesoscale convective systems revealed by the Precipitation Radar (PR) flown on the Tropical Rainfall Measuring Mission (TRMM) satellite are found to correspond to thunderstorms, i.e., Cbs. These Cbs are reflected as minima in the 85 GHz brightness temperature, T85, observed by the TRMM Microwave Imager (TMI) radiometer. Because the magnitude of TMI observations do not discriminate satisfactorily convective and stratiform rain, we developed here a different TMI discrimination method. In this method, two types of Cbs, strong and weak, are inferred from the Laplacian of T85 at minima. Then, to retrieve rain rate, where T85 is less than 270 K, a weak (background) rain rate is deduced using T85 observations. Furthermore, over a circular area of 10 km radius centered at the location of each T85 minimum, an additional Cb component of rain rate is added to the background rain rate. This Cb component of rain rate is estimated with the help of (T19-T37) and T85 observations. Initially, our algorithm is calibrated with the PR rain rate measurements from 20 MCS rain events. After calibration, this method is applied to TMI data taken from several tropical land regions. With the help of the PR observations, we show that the spatial distribution and intensity of rain rate over land estimated from our algorithm are better than those given by the current TMI-Version-5 Algorithm. For this reason, our algorithm may be used to improve the current state of rain retrievals on land.

Prabhakara, C.↗
NASA NTRS2002

Effects of Uncertainty in TRMM Precipitation Radar Path Integrated Attenuation on Interannual Variations of Tropical Oceanic Rainfall

Considerable uncertainty surrounds the issue of whether precipitation over the tropical oceans (30 deg N/S) systematically changes with interannual sea-surface temperature (SST) anomalies that accompany El Nino (warm) and La Nina (cold) events. Time series of rainfall estimates from the Tropical Rainfall Measuring Mission (TRMM Precipitation Radar (PR) over the tropical oceans show marked differences with estimates from two TRMM Microwave Imager (TMI) passive microwave algorithms. We show that path-integrated attenuation derived from the effects of precipitation on the radar return from the ocean surface exhibits interannual variability that agrees closely with the TMI time series. Further analysis of the frequency distribution of PR (2A25 product) rain rates suggests that the algorithm incorporates the attenuation measurement in a very conservative fashion so as to optimize the instantaneous rain rates. Such an optimization appears to come at the expense of monitoring interannual climate variability.

Robertson, Franklin R.↗
NASA NTRS2002

Estimation of Mesoscale Atmospheric Latent Heating Profiles from TRMM Rain Statistics Utilizing a Simple One-Dimensional Model

In this study, a model is developed to estimate mesoscale-resolution atmospheric latent heating (ALH) profiles. It utilizes rain statistics deduced from Tropical Rainfall Measuring Mission (TRMM) data, and cloud vertical velocity profiles and regional surface thermodynamic climatologies derived from other available data sources. From several rain events observed over tropical ocean and land, ALH profiles retrieved by this model in convective rain regions reveal strong warming throughout most of the troposphere, while in stratiform rain regions they usually show slight cooling below the freezing level and significant warming above. The mesoscale-average, or total, ALH profiles reveal a dominant stratiform character, because stratiform rain areas are usually much larger than convective rain areas. Sensitivity tests of the model show that total ALH at a given tropospheric level varies by less than +/- 10 % when convective and stratiform rain rates and mesoscale fractional rain areas are perturbed individually by +/- 15 %. This is also found when the non-uniform convective vertical velocity profiles are replaced by one that is uniform. Larger variability of the total ALH profiles arises when climatological ocean- and land-surface temperatures (water vapor mixing ratios) are independently perturbed by +/- 1.0 K (+/- 5%) and +/- 5.0 K (+/- 15%), respectively. At a given tropospheric level, such perturbations can cause a +/- 25% variation of total ALH over ocean, and a factor-of-two sensitivity over land. This sensitivity is reduced substantially if perturbations of surface thermodynamic variables do not change surface relative humidity, or are not extended throughout the entire model evaporation layer. The ALH profiles retrieved in this study agree qualitatively with tropical total diabatic heating profiles deduced in earlier studies. Also, from January and July 1999 ALH-profile climatologies generated separately with TRMM Microwave Imager and Precipitation Radar rain statistics, it is shown that ALH profiles can be retrieved utilizing diverse satellite-derived rain products that offer convective and stratiform discrimination. Therefore, the ALH retrieval model developed in this study can be used to make regional estimates of total diabatic heating profiles in the future Global Precipitation Measurement mission, and to assimilate these profiles into numerical weather forecast and climate models.

Iacovazzi, Robert A., Jr.↗
NASA NTRS2003

Estimating Uncertainty in GPCP and TRMM Multi-Satellite Precipitation Estimates

One of the high-priority problems in satellite precipitation estimation is developing algorithms for estimating the errors in precipitation retrievals by individual sensors and subsequent multi-satellite combinations. Classically, we distinguish between "random" and "bias" errors, which do and do not, respectively average to zero over a "big enough" time/space sample. The current operational GPCP and TRMM multi-satellite algorithms are nearly unique in estimating random error for the monthly precipitation estimates from individual sensor systems (including gauge), following Huffman, and then making multi-sensor combinations. No routinely operational global precipitation produces estimates of bias error. Subsequently, a similar scheme has been followed to provide random error estimates for the Multi-satellite Precipitation Analysis (MPA) being computed in real time and after real time for TRMM. The Huffman algorithm for random error is briefly reviewed, including a discussion of the limitations imposed on the algorithm by standard monthly precipitation data sets. Starting from a very simple theoretical treatment of the histogram of precipitation samples in a month, an equation is developed that depends on the estimated average precipitation rate for the month, the number of samples in the month, and two constants. The constants are set separately for each source of precipitation estimate (such as "raingauge") by calibration at selected ground sites. We discuss recent work validating the random error estimates to highlight the successes and limitations of this first-generation approach. We then consider what information is needed from the individual sensor algorithms to facilitate additional accuracy in the estimation of random errors across the time/space span of climate regimes which a global estimation system must handle. In addition, the thorny issue of estimating bias is raised. Finally, the role of error estimates (and the qualitative errors!) in creating combinations of precipitation estimates from different individual sensors is discussed. This issue is particularly important when fine scales in space and time are being considered, say the 0.25 x 0.25-deg 3-hourly estimates in the MPA.

Huffman, G. J.↗
NASA NTRS2002

High-Resolution Simulation of Hurricane Bonnie (1998): Microphysics Validation using TRMM Data

A simulation of Hurricane Bonnie (1998) has been performed using multiple grid nesting to 2 km grid spacing. The simulation is initialized with large-scale analysis fields from the European Center for Medium Range Forecasts and with a bogus vortex inserted via four-dimensional variational data assimilation. The simulation reproduces well the storm intensity, the wavenumber 1 asymmetry of the precipitation field, the occurrence of deep convective towers within the eyewall, and the presence of broad stratiform precipitation regions. Radar and microwave observations from TRMM are used to validate the simulation. Result show excessive graupel production and, to some extent, excessive precipitation production in general by the model. Additional simulations are conducted (and validated by TRMM data) to test parameters and assumptions within the microphysics parameterizations including particle size distributions, particle densities, and assumptions that impact the partitioning of precipitation mass between graupel and snow.

Starr, David OC.↗
NASA NTRS2002

Passive and Active Microwave Remote Sensing of Precipitation and Latent Heating Distributions in the Tropics from TRMM

Passive and active microwave remote sensing data are analyzed to identify signatures of precipitation and vertical motion in tropical convection. A database of cloud/radiative model simulations is used to quantify surface rain rates and latent heating profiles that are consistent with these signatures. At satellite footprint-scale (approximately 10 km), rain rate and latent heating estimates are subject to significant random errors, but by averaging the estimates in space and time, random errors are substantially reduced, Bias errors have been minimized by improving the microphysics in the supporting cloud/radiative model simulations, and by imposing a consistent definition of remotely-sensed and model-simulated convective/stratiform rain coverage. Remotely-sensed precipitation and latent heating distributions in the tropics are derived from Tropical Rainfall Measuring Mission (TRMM) and Special Sensor Microwave/ Imager (SSM/ I) sensor data. The prototype Version 6 TRMM passive microwave algorithm typically yields average heating profiles with maxima between 6 and 7 km altitude for organized mesoscale convective systems. Retrieved heating profiles for individual convective systems are compared to coincident estimates based upon a combination of dual-Doppler radar and rawinsonde data. Also, large-scale latent heating distributions are compared to estimates derived from a simpler technique that utilizes observations of surface rain rate and stratiform rain proportion to infer vertical heating structure. Results of these tests will be presented at the conference.

Olson, William S.↗