Engineering topics

Iacovazzi, R., Jr.

Publications and source records attributed to Iacovazzi, R., Jr..

16 records

NASA NTRS2004

Feasibility of Sensing Tropospheric Ozone with MODIS 9.6 Micron Observations

With the infrared observations made by the Moderate Resolution Imaging Spectrometer (MODIS) on board the EOS-Aqua satellite, which include the 9.73 micron channel, a method is developed to deduce horizontal patterns of tropospheric ozone in cloud free conditions on a scale of about 100 km. It is assumed that on such small scale, at a given instant, horizontal changes in stratospheric ozone are small compared to that in the troposphere. From theoretical simulations it is found that uncertainties in the land surface emissivity and the vertical thermal stratification in the troposphere can lead to significant errors in the inferred tropospheric ozone. Because of this reason in order to derive horizontal patterns of tropospheric ozone in a given geographic area a tuning of this method is necessary with the help of a few dependent cases. After tuning, this method is applied to independent cases of MODIS data taken over Los Angeles basin in cloud free conditions to derive horizontal distribution of ozone in the troposphere. Preliminary results indicate that the derived patterns of ozone resemble crudely the patterns of surface ozone reported by EPA.

Prabhakara, C.↗

NASA NTRS2004

A Model for Estimation of Rain Rate on Tropical Land from TRMM Microwave Imager Radiometer Observations

Over the tropical land regions observations of the 85 GHz brightness temperature (T(sub 85v)) made by the TRMM Microwave Imager (TMI) radiometer when analyzed with the help of rain rate (R(sub pR)) deduced from the TRMM Precipitation Radar (PR) indicate that there are two maxima in rain rate. One strong maximum occurs when T(sub 85) has a value of about 220 K and the other weaker one when T(sub 85v) is much colder approx. 150 K. Together with the help of earlier studies based on airborne Doppler Radar observations and radiative transfer theoretical simulations, we infer the maximum near 220 K is a result of relatively weak scattering due to super cooled rain drops and water coated ice hydrometeors associated with a developing thunderstorm (Cb) that has a strong updraft. The other maximum is associated with strong scattering due to ice particles that are formed when the updraft collapses and the rain from the Cb is transit2oning from convective type to stratiform type. Incorporating these ideas and with a view to improve the estimation of rain rate from existing operational method applicable to the tropical land areas, we have developed a rain retrieval model. This model utilizes two parameters, that have a horizontal scale of approx. 20km, deduced from the TMI measurements at 19, 21 and 37 GHz (T(sub 19v), T(sub 21v), T(sub 37v). The third parameter in the model, namely the horizontal gradient of brightness temperature within the 20 km scale, is deduced from TMI measurements at 85 GHz. Utilizing these parameters our retrieval model is formulated to yield instantaneous rain rate on a scale of 20 km and seasonal average on a mesoscale that agree well with that of the PR.

Prabhakara, C.↗

NASA NTRS2003

Regional Variability in Convection and Rain Retrievals from the TRMM Microwave Imager (TMI)

Precipitation Radar (PR) on board the TRMM satellite shows that the average height of 30 dBz in convective rain areas of the tropics varies significantly from one region to the other. When the convection is weak this height is shallow and when convection is strong this height extends deeper into the troposphere. The brightness temperature (Tb) measured by the microwave radiometer by itself does not reflect this nature of convection satisfactorily. Radiative transfer simulations of Tbs reveal that this could be due to the variations in the vertical distribution of optically active water and ice hydrometeors and their density, shape, and size. These variations are not coupled uniquely to the strength of the convective updrafts, and as a result the Tbs do not reflect properly the convective strength indicated by PR. Because of this deficiency in the Tbs the rain rate deduced from them differs from that of PR. For this reason, to improve the estimation of rain rate we have developed an empirical method. In this method a parameter based on the areal extent of the Tbs that exceed a certain magnitude is included along with the Tbs. Rain rate deduced with this approach is better correlated with that of PR when compared to the current Version 5 operational algorithm. The percentage of rain volume as a function of rain rate, for a given region of 5deg lat. X 5deg long. over a period of three months, deduced from this method, is also in better agreement with that of the PR.

Prabhakara, C.↗

NASA NTRS2002

Simulation of TRMM Microwave Imager Brightness Temperature using Precipitation Radar Reflectivity for Convective and Stratiform Rain Areas over Land

Rain is highly variable in space and time. In order to measure rainfall over global land with satellites, we need observations with very high spatial resolution and frequency in time. On board the Tropical Rainfall Measuring Mission (TRMM) satellite, the Precipitation Radar (PR) and Microwave Imager (TMI) are flown together for the purpose of estimating rain rate. The basic method to estimate rain from PR has been developed over the past several decades. On the other hand, the TMI method of rain estimation is still in the state development, particularly over land. The objective of this technical memorandum is to develop a theoretical framework that helps relate the observations made by these two instruments. The principle result of this study is that in order to match the PR observations with the TMI observations in convective rain areas, a mixed layer of graupel and supercooled water drops above the freezing level is needed. On the other hand, to match these observations in the stratiform region, a layer of snowflakes with appropriate densities above the freezing level, and a melting layer below the freezing level, are needed. This understanding can lead to a robust rainfall estimation technique from the microwave radiometer observations.

Prabhakara, C.↗

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

A Method to Retrieve Rainfall Rate over Land from TRMM Observations

Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) observations over mesoscale convective systems (MCSs) reveal that there are localized maxima in the rain rate with a scale of about 10 to 20 km that represent thunderstorms (Cbs). Some of these Cbs are developing or intense, while others are decaying or weak. These Cbs constitute only about 20 % of the rain area of a given MCS. Outside of Cbs, the average rain rate is much weaker than that within Cbs. From an analysis of the PR data, we find that the spatial distribution of rain and its character, convective or stratiform, is highly inhomogeneous. This complex nature of rain exists on a scale comparable to that of a Cb. The 85 GHz brightness temperature, T85, observations of the TRMM Microwave Imager (TMI) radiometer taken over an MCS reflect closely the PR rain rate pattern over land. Local maxima in rain rate shown by PR are observed as local minima in T85. Where there are no minima in T85, PR observations indicate there is light rain. However, the TMI brightness temperature measurements (Tbs) have poor ability to discriminate convective rain from stratiform rain. For this reason, a TMI rain retrieval procedure that depends primarily on the magnitude of Tbs performs poorly. In order to retrieve rain rate from TMI data on land one has to include the spatial distribution information deduced from the T85 data in the retrieval method. Then, quantitative estimation of rain rate can be accomplished. A TMI rain retrieval method developed along these lines can yield estimates of rain rate and its frequency distribution which agree closely with that given by PR. We find the current TRMM project TMI (Version 5) rain retrieval algorithm on land could be improved with the retrieval scheme developed here. To support the conceptual frame work of the rain retrieval method developed here, a theoretical analysis of the TMI brightness temperatures in convective and stratiform regions is presented.

Prabhakara, C.↗

NASA NTRS2001

Global Warming: Evidence from Satellite Observations

Observations made in Channel 2 (53.74 GHz) of the Microwave Sounding Unit (MSU) radiometer, flown on-board sequential, sun-synchronous, polar orbiting NOAA operational satellites, indicate that the mean temperature of the atmosphere over the globe increased during the period 1980 to 1999. In this study we have minimized systematic errors in the time series introduced by the satellite orbital drift in an objective manner. This is done with the help the onboard warm black body temperature, which is used in the calibration of the MSU radiometer. The corrected MSU Channel 2 observations of the NOAA satellite series reveal that the vertically weighted global mean temperature of the atmosphere, with a peak weight near the mid-troposphere, warmed at the rate of 0.13 K per decade (with an uncertainty of 0.05 K per decade) during 1980 to 1999. The global warming deduced from conventional meteorological data that have been corrected for urbanization effects agrees reasonably with this satellite deuced result.

Prabhakara, C.↗

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

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 NTRS2000

Global Warming Estimation from MSU: Correction for Drift and Calibration Errors

Microwave Sounding Unit (MSU) radiometer observations in Ch 2 (53.74 GHz), made in the nadir direction from sequential, sun-synchronous, polar-orbiting NOAA morning satellites (NOAA 6, 10 and 12 that have approximately 7am/7pm orbital geometry) and. afternoon satellites (NOAA 7, 9, 11 and 14 that have approximately 2am/2pm orbital geometry) are analyzed in this study to derive global temperature trend from 1980 to 1998. In order to remove the discontinuities between the data of the successive satellites and to get a continuous time series, first we have used shortest possible time record of each satellite. In this way we get a preliminary estimate of the global temperature trend of 0.21 K/decade. However, this estimate is affected by systematic time-dependent errors. One such error is the instrument calibration error eo. This error can be inferred whenever there are overlapping measurements made by two satellites over an extended period of time. From the available successive satellite data we have taken the longest possible time record of each satellite to form the time series during the period 1980 to 1998 to this error eo. We find eo can decrease the global temperature trend by approximately 0.07 K/decade. In addition there are systematic time dependent errors ed and ec present in the data that are introduced by the drift in the satellite orbital geometry. ed arises from the diurnal cycle in temperature and ec is the drift related change in the calibration of the MSU. In order to analyze the nature of these drift related errors the multi-satellite Ch 2 data set is partitioned into am and pm subsets to create two independent time series. The error ed can be assessed in the am and pm data of Ch 2 on land and can be eliminated. Observation made in the MSU Ch 1 (50.3 GHz) support this approach. The error ec is obvious only in the difference between the pm and am observations of Ch 2 over the ocean. We have followed two different paths to assess the impact of the error ec on the global temperature trend. In one path the entire error ec is placed in the am data while in the other it is placed in the pm data. Global temperature trend is increased or decreased by approximately 0.03 K/decade depending upon this placement. Taking into account all random errors and systematic errors our analysis of MSU observations leads us to conclude that a conservative estimate of the global warming is 0. 11 (+/-) 0.04 K/decade during 1980 to 1998.

Prabhakara, C.↗

NASA NTRS2000

Global Warming Estimation from MSU: Correction for Drift and Calibration Errors

Microwave Sounding Unit (MSU) radiometer observations in Ch 2 (53.74 GHz), made in the nadir direction from sequential, sun-synchronous, polar-orbiting NOAA morning satellites (NOAA 6, 10 and 12 that have about 7am/7pm orbital geometry) and afternoon satellites (NOAA 7, 9, 11 and 14 that have about 2am/2pm orbital geometry) are analyzed in this study to derive global temperature trend from 1980 to 1998. In order to remove the discontinuities between the data of the successive satellites and to get a continuous time series, first we have used shortest possible time record of each satellite. In this way we get a preliminary estimate of the global temperature trend of 0.21 K/decade. However, this estimate is affected by systematic time-dependent errors. One such error is the instrument calibration error. This error can be inferred whenever there are overlapping measurements made by two satellites over an extended period of time. From the available successive satellite data we have taken the longest possible time record of each satellite to form the time series during the period 1980 to 1998 to this error. We find we can decrease the global temperature trend by about 0.07 K/decade. In addition there are systematic time dependent errors present in the data that are introduced by the drift in the satellite orbital geometry arises from the diurnal cycle in temperature which is the drift related change in the calibration of the MSU. In order to analyze the nature of these drift related errors the multi-satellite Ch 2 data set is partitioned into am and pm subsets to create two independent time series. The error can be assessed in the am and pm data of Ch 2 on land and can be eliminated. Observations made in the MSU Ch 1 (50.3 GHz) support this approach. The error is obvious only in the difference between the pm and am observations of Ch 2 over the ocean. We have followed two different paths to assess the impact of the errors on the global temperature trend. In one path the entire error is placed in the am data while in the other it is placed in the pm data. Global temperature trend is increased or decreased by about 0.03 K/decade depending upon this placement. Taking into account all random errors and systematic errors our analysis of MSU observations leads us to conclude that a conservative estimate of the global warming is 0. 11 (+-) 0.04 K/decade during 1980 to 1998.

Prabhakara, C.↗

NASA NTRS2000

TRMM Observations of Polarization Difference in 85 GHz: Information About Hydrometeors and Rain Rate

Observations made by the Precipitation Radar (PR) and the Microwave Imager (TMI) radiometer on board the Tropical Rainfall Measuring Mission (TRMM) satellite help us to show the significance of the 85 GHz polarization difference, PD85, measured by TMI. Rain type, convective or stratiform, deduced from the PR allows us to infer that PD85 is generally positive in stratiform rain clouds, while PD85 can be markedly negative in deep convective rain clouds. Furthermore, PD85 increases in a gross manner as stratiform rain rate increases. On the contrary, in a crude fashion PD85 decreases as convective rain rate increases. From the observations of TMI and PR, we find that PD85 is a weak indicator of rain rate. Utilizing information from existing polarimetric radar studies, we infer that negative values of PD85 are likely associated with vertically-oriented small oblate or wet hail that are found in deep convective updrafts.

Prabhakara, C.↗

NASA NTRS1999

TMI Rain Rate Estimation Over Land and Ocean Utilizing 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 in a regional map containing a Mesoscale Convective System (MCS). This is because of relatively small footprint size (approximately 5.5 km) and strong extinction properties in this channel of the TMI. A map of rain rate for that region, deduced from simultaneous measurements made by the Precipitation Radar (PR) on board the TRMM satellite, reveals that these T85 minima, produced by scattering, correspond to local PR rain maxima. Utilizing the PR rain rate map as a guide, we infer from TMI data the presence of three different kinds of thunderstorms or Cbs. They are young, mature, and decaying Cbs that have a scale of about 20 km on the average. Two parameters enable us to infer these three kinds of Cbs objectively: a) the magnitude of scattering depression deduced from local T85 minima and b) the mean horizontal gradient of T85 around such minima. Knowing the category of a given Cb, we can estimate the rain rate associated with it. Such estimation is done with the help of relationships linking T85 minimum to rain rate in each Cb type. Similarly, a weak background rain rate in all the areas where T85 is less than 260 K is deduced with another relationship linking T85 to rain rate. In our rain retrieval model, this background rain constitutes the stratiform rain where the Cbs are absent. Initially, these relationships are optimized or tuned utilizing the PR and TMI data of a few MCS events. After such tuning, the model is applied to independent MCS cases. The areal distribution of light (1-10 mm/hr), moderate (10-20 mm/hr), and intense (> 20 mm/hr) rain rates are retrieved satisfactorally. Accuracy in the estimates of the light, moderate and intense rain areas and the mean rain rates associated with such areas in these independent MCS cases is on the average 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, C.↗

NASA NTRS1999

A 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). This is because of relatively small footprint size (approximately 5.5 km) and strong extinction properties in this channel of the TMI. 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 T85(sub min), produced by scattering, correspond to local PR rain maxima. Utilizing the PR rain rate map as a guide, we infer empirically from TMI data the presence of three different kinds of thunderstorms or Cbs. These Cbs are classified as young, mature, and decaying types, and are assumed to have a scale of about 20 km on the average. Two parameters are used to classify these three kinds of Cbs based on the T85 data: a) the magnitude of scattering depression deduced from local T85(sub min) and b) the mean horizontal gradient of T85 around such minima. Knowing the category of a given Cb, we can estimate the rain rate associated with it. Such estimation is done with the help of relationships linking T85min to rain rate in each Cb type. Similarly, a weak background rain rate in all the areas where T85 is less than 260 K is deduced with another relationship linking T85 to rain rate. In our rain retrieval model, this background rain constitutes stratiform rain where the Cbs are absent. Initially, these relationships are optimized or tuned utilizing the PR and TMI data of a few MCS events. After such tuning, the model is applied to independent MCS cases. The areal distribution of light (1-10 mm/hr), moderate (10-20 mm/hr), and intense (>= 20 mm/hr) rain rates are retrieved satisfactorily. Accuracy in the estimates of the light, moderate, and intense rain areas and the mean rain rates associated with such areas in these independent MCS cases is on the average 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, C.↗

NASA NTRS1998

Global Warming Estimation From Microwave Sounding Unit

Microwave Sounding Unit (MSU) Ch 2 data sets, collected from sequential, polar-orbiting, Sun-synchronous National Oceanic and Atmospheric Administration operational satellites, contain systematic calibration errors that are coupled to the diurnal temperature cycle over the globe. Since these coupled errors in MSU data differ between successive satellites, it is necessary to make compensatory adjustments to these multisatellite data sets in order to determine long-term global temperature change. With the aid of the observations during overlapping periods of successive satellites, we can determine such adjustments and use them to account for the coupled errors in the long-term time series of MSU Ch 2 global temperature. In turn, these adjusted MSU Ch 2 data sets can be used to yield global temperature trend. In a pioneering study, Spencer and Christy (SC) (1990) developed a procedure to derive the global temperature trend from MSU Ch 2 data. Such a procedure can leave unaccounted residual errors in the time series of the temperature anomalies deduced by SC, which could lead to a spurious long-term temperature trend derived from their analysis. In the present study, we have developed a method that avoids the shortcomings of the SC procedure, the magnitude of the coupled errors is not determined explicitly. Furthermore, based on some assumptions, these coupled errors are eliminated in three separate steps. Such a procedure can leave unaccounted residual errors in the time series of the temperature anomalies deduced by SC, which could lead to a spurious long-term temperature trend derived from their analysis. In the present study, we have developed a method that avoids the shortcomings of the SC procedures. Based on our analysis, we find there is a global warming of 0.23+/-0.12 K between 1980 and 1991. Also, in this study, the time series of global temperature anomalies constructed by removing the global mean annual temperature cycle compares favorably with a similar time series obtained from conventional observations of temperature.

Prabhakara, C.↗

NASA NTRS1998

A TRMM Rainfall Estimation Method Applicable to Land Areas

Utilizing multi-spectral, dual-polarization Special Sensor Microwave Imager (SSM/I) radiometer measurements, we have developed in this study a method to retrieve average rain rate, R(sub f(sub R)), in a mesoscale grid box of 2deg x 3deg over land. The key parameter of this method is the fractional rain area, f(sub R), in that grid box, which is determined with the help of a threshold on the 85 GHz scattering depression 0 deduced from the SSM/I data. In order to demonstrate the usefulness of this method, nine-months of R(sub f(sub R))are retrieved from SSM/I data over three grid boxes in the Northeastern United States. These retrievals are then compared with the corresponding ground-truth-average rain rate, R(sub g), deduced from 15-minute rain gauges. Based on nine months of rain rate retrievals over three grid boxes, we find that R(sub f(sub R)can explain about 64 % of the variance contained in R(sub g). A similar evaluation of the grid-box-average rain rates R(sub GSCAT) and R(sub SRL), given by the NASA/GSCAT and NOAA/SRL rain retrieval algorithms, is performed. This evaluation reveals that R(sub GSCAT) and R(sub SRL) can explain only about 42 % of the variance contained in R(sub g). In our method, a threshold on the 85 GHz scattering depression is used primarily to determine the fractional rain area in a mesoscale grid box. Quantitative information pertaining to the 85 GHz scattering depression in the grid box is disregarded. In the NASA/GSCAT and NOAA/SRL methods on the other hand, this quantitative information is included. Based on the performance of all three methods, we infer that the magnitude of the scattering depression is a poor indicator of rain rate. Furthermore, from maps based on the observations made by SSM/I on land and ocean we find that there is a significant redundancy in the information content of the SSM/I multi-spectral observations. This leads us to infer that observations of SSM/I at 19 and 37 GHz add only marginal information to that given by 85 GHz scattering depression. As with other methods, the area-average rain retrieval method developed in this study needs tuning with radar and/or rain gauge observations. In the TRMM mission, the microwave radiometer rain retrieval algorithm can be tuned with TRMM radar observations. Since the radiometer has about 3.5 times wider spatial coverage compared to the radar in the TRMM mission, such an algorithm can be useful to extend geographically the rain information provided by the TRMM Precipitation Radar.

Prabhakara, C.↗