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At least 127 records · Page 7

SSM/I Rain Retrievals Within a Unified All-Weather Ocean Algorithm

A new method for the physical retrieval of rain rates from satellite microwave radiometers is presented and compared to two other rainfall climatologies derived from satellites. The method is part of a unified ocean parameter retrieval algorithm that is based on the fundamental principles of radiative transfer. The algorithm simultaneously finds near-surface wind speed W, columnar water vapor V, columnar cloud liquid water L, rain rate R, and effective radiating temperature T(sub U) for the upwelling radiation. The performance of the algorithm in the absence of rain is discussed in Wentz, and this paper focuses on the rain component of the algorithm. A particular strength of the unified algorithm is its ability to 'orthogonalize' the retrievals so that there is minimum cross-talk between the retrieved parameters. For example, comparisons of the retrieved water vapor with radiosonde observations show that there is very little correlation between the water vapor retrieval error and rain rate. For rain rates from 1 to 15 mm/h, the rms difference between the retrieved water vapor and the radiosonde value is 5 mm. A novel feature of the rain retrieval method is a beamfilling correction that is based upon the ratio of the retrieved liquid water absorption coefficients at 37 GHz and 19.35 GHz. This ratio decreases by about 40% when heavy and light rain co-exist within the SSM/I footprint as compared to the case of uniform rain. This correction has the effect of increasing the rain rate when the spectral ratio of the absorption coefficients is small. Even with this beamfilling correction, tropical rainfall is still unrealistically low when the freezing level in the tropics (approx. 5 km) is used to specify the rain layer thickness. We restore realism by reducing the assumed averaged tropical rain layer thickness to 3 km, thereby accounting for the existence of warm rain processes in which the rain layer does not extend to the freezing level. Global rain rates are produced for the 1991 through 1994 period from observations taken by microwave radiometers (SSM/I) that are aboard two polar-orbiting satellites. We find that approximately 6% of the SSM/I observations detect measurable rain rates (R greater than 0.2 mm/h). Zonal averages of the rain rates show the peak at the intertropical convergence zone (ITCZ) is quite narrow in meridional extent and varies from about 7 mm/day in the winter to a maximum 11 mm/day in the summer. Very low precipitation rates (less than 0.3 mm/day) are observed in those areas of subsidence influenced by the large semipermanent anticyclones. In general, these features are similar to those reported in previously published rain climatologies. However, significant differences do exists between our rain rates and those produced by Spencer. These differences seem to be related to non-precipitating cloud water.

Wentz, Frank J.↗

Estimation of Rainfall Sampling Uncertainty: A Comparison of Two Diverse Approaches

The spatial and temporal intermittence of rainfall causes the averages of satellite observations of rain rate to differ from the "true" average rain rate over any given area and time period, even if the satellite observations are perfectly accurate. The difference of satellite averages based on occasional observation by satellite systems and the continuous-time average of rain rate is referred to as sampling error. In this study, rms sampling error estimates are obtained for average rain rates over boxes 100 km, 200 km, and 500 km on a side, for averaging periods of 1 day, 5 days, and 30 days. The study uses a multi-year, merged radar data product provided by Weather Services International Corp. at a resolution of 2 km in space and 15 min in time, over an area of the central U.S. extending from 35N to 45N in latitude and 100W to 80W in longitude. The intervals between satellite observations are assumed to be equal, and similar In size to what present and future satellite systems are able to provide (from 1 h to 12 h). The sampling error estimates are obtained using a resampling method called "resampling by shifts," and are compared to sampling error estimates proposed by Bell based on earlier work by Laughlin. The resampling estimates are found to scale with areal size and time period as the theory predicts. The dependence on average rain rate and time interval between observations is also similar to what the simple theory suggests.

Steiner, Matthias↗

Current Scientific Progress and Future Scientific Prospects Enabled by Spaceborne Precipitation Radar Measurements

First, we examine current scientific progress and understanding that have been possible through use of spaceborne precipitation radar measurements being provided by the TRMM and CloudSat satellites. Second, we look across a future 20-year time frame to assess how and why anticipated improvements in space radar systems will further advance scientific progress into topic areas once considered beyond the realm of space-based remote sensing. JAXA's 13.8 GHz Ku-band cross-track scanning Precipitation Radar (PR) developed for flight on NASA's non-sun-synchronous, diurnally-precessing TRMM satellite, was the first Earth radar flown in space that was designed specifically for precipitation measurement. Its proven accuracy in measuring global rainfall in the tropics and sub-tropics and its unanticipated longevity in continuing these measurements beyond a full decade have established the standards against which all follow-up and future space radars will be evaluated. In regards to the current PR measurement time series, we will discuss a selection of major scientific discoveries and impacts which have set the stage for future radar measuring systems. In fact, the 2nd contemporary space radar applicable for terrestrial precipitation measurement, i.e., JPL-CSA's 94 GHz nadir-staring Cloud Profiling Radar (CPR) flown on NASA's sun-synchronous CloudSat satellite, although designed primarily for measurement of non-precipitating cloud hydrometeors and aerosols, has also unquestionably advanced precipitation measurement because CPR's higher frequency and greatly increased sensitivity (approximately 30 dBZ) has enabled global observations of light rain rate spectrum processes (i.e., rain rates below 0.05 mm per hourand of precipitation processes in the high troposphere (particularly ice phase processes). These processes are beyond reach of the TRMM radar because the PR sensitivity limit is approximately 17 dBZ which means its lower rain rate cutoff is around 0.3 mm per hour and its vertical profiling acuity is greatly limited above the melting layer. Thus, the newer CPR measurements have become important for a variety of scientific reasons that will be highlighted and assessed. In considering scientific progress likely to stem from future precipitation radar systems, we will specifically examine possible scientific impacts from three anticipated missions for which NASA and various of its space agency partners are expected to lead the way. These three missions are: (1) the nearterm Global Precipitation Measuring (GPM) Mission; (2) the decadal timeline Aerosol and Cloud Experiment (ACE) Mission; and the post-decadal timeline NEXRAD in Space (NIS) Mission. The observational capabilities of the planned radar systems for each of these three satellite missions are distinct from each other and each provides progressive improvements in precipitation measuring and scientific research capabilities relative to where we are now -- insofar as TRMM PR and the CloudSat CPR capabilities. The potential innovations in scientific research will be discussed in a framework of likely synergisms between next-generation radar capabilities and accessible dynamical and microphysical properties that have heretofore evaded detection.

Smith, Eric A.↗

A TRMM Rainfall Estimation Method Applicable to Land Areas

Methods developed to estimate rain rate on a footprint scale over land with the satellite-borne multispectral dual-polarization Special Sensor Microwave Imager (SSM/1) radiometer have met with limited success. Variability of surface emissivity on land and beam filling are commonly cited as the weaknesses of these methods. On the contrary, we contend a more significant reason for this lack of success is that the information content of spectral and polarization measurements of the SSM/I is limited. because of significant redundancy. As a result, the complex nature and vertical distribution C, of frozen and melting ice particles of different densities, sizes, and shapes cannot resolved satisfactorily. Extinction in the microwave region due to these complex particles can mask the extinction due to rain drops. Because of these reasons, theoretical models that attempt to retrieve rain rate do not succeed on a footprint scale. To illustrate the weakness of these models, as an example we can consider the brightness temperature measurement made by the radiometer in the 85 GHz channel (T85). Models indicate that T85 should be inversely related to the rain rate, because of scattering. However, rain rate derived from 15-minute rain gauges on land indicate that this is not true in a majority of footprints. This is also supported by the ship-borne radar observations of rain in the Tropical Oceans and Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA-COARE) region over the ocean. Based on these observations. we infer that theoretical models that attempt to retrieve rain rate do not succeed on a footprint scale. We do not follow the above path of rain retrieval on a footprint scale. Instead, we depend on the limited ability of the microwave radiometer to detect the presence of rain. This capability is useful to determine the rain area in a mesoscale region. We find in a given rain event that this rain area is closely related to the mesoscale-average rain rate. Based on this observation, in this study we have developed a method to estimate the mesoscale-average rain rate over land utilizing microwave radiometer data. Because of the high degree of geographic and seasonal variability in the nature and intensity of rain, this method requires some tuning with 15-minute rain gauge data on land. After tuning the method, it can be applied to an independent set of rain events that are close in time and space. We find that the mesoscale rain rates retrieved over the period of a month on land with this method shows a correlation of about 0.85 with respect to the surface rain-gauge observations. This mesoscale-average rain rate estimation method can be useful to extend the spatial and temporal coverage of the rainfall data provided by the Precipitation Radar on board the Tropical Rainfall Measuring Mission (TRMM) satellite.

Prabhakara, C.↗

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.↗

Impact of Uncertainty in the Drop Size Distribution on Oceanic Rainfall Retrievals From Passive Microwave Observations

The variability of the drop size distribution (DSD) is one of the factors that must be considered in understanding the uncertainties in the retrieval of oceanic precipitation from passive microwave observations. Here, we have used observations from the Precipitation Radar on the Tropical Rainfall Measuring Mission spacecraft to infer the relationship between the DSD and the rain rate and the variability in this relationship. The impact on passive microwave rain rate retrievals varies with the frequency and rain rate. The total uncertainty for a given pixel can be slightly larger than 10% at the low end (ca. 10 GHz) of frequencies commonly used for this purpose and smaller at higher frequencies (up to 37 GHz). Since the error is not totally random, averaging many pixels, as in a monthly rainfall total, should roughly halve this uncertainty. The uncertainty may be lower at rain rates less than about 30 mm/h, but the lack of sensitivity of the surface reference technique to low rain rates makes it impossible to tell from the present data set.

Wilheit, Thomas T.↗

Assessment of the quality of GATE area rainfall data from a Nimbus-5 radiometer

The quality of rainfall intensity estimates derived from passive microwave measurements by the Electrically Scanned Microwave Radiometer (ESMR-5) aboard the NIMBUS-5 satellite was evaluated. The microwave measurements used are those coincident with the GARP (Global Atmospheric Research Program) Atlantic Tropical Experiment (GATE). ESMR-5 derived rainfall intensity estimates are compared with hourly averaged GATE radar rainfall measurements. Using the radar measurements as ground truth it is determined that with the transfer curve derived herein the ratio (ESMR-5 derived rain rate)/radar measured rain rate has a mean of approximately 0.62.

Knox, N.↗

TRMM Gridded Text Products

NASA's Tropical Rainfall Measuring Mission (TRMM) has many products that contain instantaneous or gridded rain rates often among many other parameters. However, these products because of their completeness can often seem intimidating to users just desiring surface rain rates. For example one of the gridded monthly products contains well over 200 parameters. It is clear that if only rain rates are desired, this many parameters might prove intimidating. In addition, for many good reasons these products are archived and currently distributed in HDF format. This also can be an inhibiting factor in using TRMM rain rates. To provide a simple format and isolate just the rain rates from the many other parameters, the TRMM product created a series of gridded products in ASCII text format. This paper describes the various text rain rate products produced. It provides detailed information about parameters and how they are calculated. It also gives detailed format information. These products are used in a number of applications with the TRMM processing system. The products are produced from the swath instantaneous rain rates and contain information from the three major TRMM instruments: radar, radiometer, and combined. They are simple to use, human readable, and small for downloading.

Stocker, Erich Franz↗

A model for the beam-filling effect associated with the microwave retrieval of rain

Estimating rain rate from environmental microwave emissions is hampered by several difficulties. One of these difficulties is known as the beam-filling effect. Beam filling is the systematic error introduced when the microwave radiometer's field of view is not filled with uniform rain. Beam filling can have dramatic effects on rain-rate estimation, causing rain rates to be underestimated by as much as a factor of 2. The present study derives an approximate expression for beam filling that provides, in principle, a way to estimate this effect. In addition, this study deals only with single-channel microwave rain estimation over the ocean. The final results reveal that beam filling is essentially determined by the freezing level, the mean fraction of the footprint raining, and the footprint-averaged rain rate. Also, the numerical results appear to agree with other empirical studies. Furthermore, the analysis brings to light an interesting connection with rain threshold techniques for estimating area-averaged rain rates.

Graves, Charles E.↗

Goddard Latent Heating Retrieval Algorithm for TRMM and GPM

The Goddard Convective-Stratiform Heating (CSH) algorithm has been used to retrieve latent heating (LH) associated with clouds and cloud systems in support of the Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Measurement (GPM) mission. The CSH algorithm requires the use of a cloud-resolving model (CRM) to simulate LH profiles to build look-up tables (LUTs). In this paper we describe the current V6 CSH and its differences/similarities versus the previous V5 CSH. Long-term CRM simulations are conducted to identify the impact of CRM resolution and the convective-stratiform separation method on LH structure/profiles. The TRMM and GPM Combined algorithm derived surface rainfall rates and their associated precipitation properties are the input to the CSH algorithm. Since there is no direct measurement of LH structure, the performance of the CSH V6 algorithm is examined by comparing its vertically-integrated heating (or equivalent surface rainfall rate) against the surface rainfall rate derived from the TRMM/GPM Combined algorithm. The results suggest the CSH three-month and zonal mean equivalent surface rain rates are in good agreement with the Combined rates over the ITCZ region; the agreement is best over ocean. CSH three-month and zonal mean equivalent surface rain rates are larger than the Combined rates over land in both the tropics and sub-tropics. CSH three-month mean equivalent surface rainfall rates also have local differences with the Combined rates that can be smoothed by area averaging to larger horizontal resolutions (from the CSH standard grid of 0.25° × 0.25° to 0.5° × 0.5° or 1.0° × 1.0°). CSH equivalent surface rainfall rates have more light rain rates but less larger rain rates compared to the GPM Combined surface rain rates.

Latent heating retrieval↗

Rainfall estimation over oceans from scanning multichannel microwave radiometer and special sensor microwave/imager microwave data

The brightness temperature (T sub b) measured at 37 GHz shows fairly strong emission from rain, and only slight effects caused by scattering by ice above the rain clouds. At frequencies below 37 GHz, were the fov is larger and the volume extinction coefficient is weaker, it is found that the observations do not yield appreciable additional information about rain. At 85 GHz (fov = 15 km), where the volume extinction is considerably larger, direct information about rain below the clouds is usually masked. Based on the above ideas, 37 GHz observations with a 30 km fov from SMMR and SSM/I are selected to develop an empirical method for the estimation of rain rate. In this method, the statistics of the observed T sub b's at 37 GHz in a rain storm are related to the rain rate statistics in that storm. The underestimation of rain rate, arising from the inability of the radiometer to respond sensitively to rain rate above a given threshold, is rectified in this technique with the aid of two parameters that depend on the total water vapor content in the atmosphere. The retrieved rain rates compare favorably with radar observations and monthly mean global maps of rain derived from this technique over the oceans.

Prabhakara, C.↗

Rainfall estimation over oceans from SMMR and SSM/I microwave data

The brightness temperature (T sub b) measured at 37 GHz shows fairly strong emission from rain, and only slight effects caused by scattering by ice above the rain clouds. At frequencies below 37 GHz, where the FOV is larger and the volume extinction coefficient is weaker, it is found that the observations do not yield appreciable additional information about rain. At 85 GHz (FOV = 15 km), where the volume extinction is considerably larger, direct information about rain below the clouds is usually masked. Based on the above idea, 37 GHz observations with a 30 km FOV from SMMR and SSM/I are selected to develop an empirical method for the estimation of rain rate. In this method, the statistics of the observed T sub b's at 37 GHz in a rain storm are related to the rain rate statistics in that storm. The underestimation of rain rate, arising from the inability of the radiometer to respond sensitively to rain rate above a given threshold is rectified in this technique with the aid of two parameters that depend on the total water vapor content in the atmosphere. The retrieved rain rates compare favorably with radar observations and monthly mean global maps of rain derived from this technique over the oceans.

Prabhakara, C.↗

A global model for rain attenuation prediction

A model was developed for the prediction of rain attenuation statistics for 8 rain rate climate regions spanning all land regions from the equator to the poles. The model uses empirically determined rain rate distributions for each climate region and an empirical model to estimate path averaged rain rate for given values of point rain rate. Attenuation distribution observations were compared with model predictions. Good agreement was obtained for earth-space paths at 0.1 percent of the year. At the extremes, 0.01 and 1 percent of the year the observations were generally within the model estimate bounds but the agreement is not as good as at 0.1 percent of the year. The discrepancies are attributed to the limited duration of the attenuation observations and to the limited number of rain rate distribution observations.

Crane, R. K.↗

A comparison of optical rain gauge and radar data from TOGA/COARE

A comparison between rain gauge data and radar data from the Tropical Oceans Global Atmosphere/Coupled Ocean Atmosphere Response Experiment (TOGA/COARE) was studied. The rain gauge data from an echo that passed over the Xiangyanghong #5 on December 24, 1992 was compared to what the MIT radar saw at this location from the R/V Vickers, 103.4 km to the east. The precipitation measured by the rain gauge peaked at 108 mm/hr 92 seconds into the period before tapering off 11 1/2 minutes later. This sharp gradient was evident in a PPI plot of the radar reflectivities and the percentage area-rainfall for the radar data statistics. The percentage area curve was converted to rain rates using a GATE Z-R and compared to a percentage time curve of rain rates according to the rain gauge. A four minute running average applied to the rain gauge rates improved the comparison of peak rates between the rain gauge and radar. Differences in peaks between rain rates observed by the rain gauge and reflectivities observed by the radar could be due to variations in rainfall rates within a single radar data bin. For example, two measurements of reflectivity such as 37 and 47 dBZ within the same bin would result in a 44 dBZ average. This range in rates from 12 mm/hr to 74 mm/hr is observed in 30 seconds by the rain gauges within the first two minutes of the radar echo passage.

Galusha, Linda↗

Evaluation of TRMM Ground-Validation Radar-Rain Errors Using Rain Gauge Measurements

Ground-validation (GV) radar-rain products are often utilized for validation of the Tropical Rainfall Measuring Mission (TRMM) spaced-based rain estimates, and hence, quantitative evaluation of the GV radar-rain product error characteristics is vital. This study uses quality-controlled gauge data to compare with TRMM GV radar rain rates in an effort to provide such error characteristics. The results show that significant differences of concurrent radar-gauge rain rates exist at various time scales ranging from 5 min to 1 day, despite lower overall long-term bias. However, the differences between the radar area-averaged rain rates and gauge point rain rates cannot be explained as due to radar error only. The error variance separation method is adapted to partition the variance of radar-gauge differences into the gauge area-point error variance and radar rain estimation error variance. The results provide relatively reliable quantitative uncertainty evaluation of TRMM GV radar rain estimates at various times scales, and are helpful to better understand the differences between measured radar and gauge rain rates. It is envisaged that this study will contribute to better utilization of GV radar rain products to validate versatile spaced-based rain estimates from TRMM, as well as the proposed Global Precipitation Measurement, and other satellites.

Wang, Jianxin↗

Microwave Observations of Precipitation and the Atmosphere

This research effort had three elements devoted to improving satellite-derived passive microwave retrievals of precipitation rate: morphological rain-rate retrievals, warm rain retrievals, and extension of a study of geostationary satellite options. The morphological precipitation-rate retrieval method uses for the first time the morphological character of the observed storm microwave spectra. The basic concept involves: 1) retrieval of point rainfall rates using current algorithms, 2) using spatial feature vectors of the observations over segmented multi-pixel storms to estimate the integrated rainfall rate for that storm (cu m/s), and 3) normalization of the point rain-rate retrievals to ensure consistency with the storm-wide retrieval. This work is ongoing, but two key steps have been completed: development of a segmentation algorithm for defining spatial regions corresponding to single storms for purposes of estimation, and reduction of some of the data from NAST-M that will be used to support this research going forward. The warm rain retrieval method involved extension of Aquai/AIRS/AMSU/HSB algorithmic work on cloud water retrievals. The central concept involves the fact that passive microwave cloud water retrievals over approx. 0.4 mm are very likely associated with precipitation. Since glaciated precipitation is generally detected quite successfully using scattering signatures evident in the surface-blind 54- and 183-GHz bands, this new method complements the first by permitting precipitation retrievals of non-glaciated events. The method is most successful over ocean, but has detected non-glaciated convective cells over land, perhaps in their early formative stages. This work will require additional exploration and validation prior to publication. Passive microwave instrument configurations for use in geostationary orbit were studied. They employ parabolic reflectors between 2 and 4 meters in diameter, and frequencies up to approx.430 GHz; this corresponds to nadir spot diameters as small as 10 km.

Staelin, David H.↗

A passive microwave algorithm for tropical oceanic rainfall

This study discusses a rainfall algorithm utilizing six channels of microwave radiance data from the Nimbus-7 Scanning Multifrequency Microwave Radiometer. The algorithm is intended for short-term climate studies over the ocean at low latitudes. To find a set of functional relationships, rain rates are regressed on brightness temperatures for each channel. Next, these functions are integrated over a class of rain-rate distributions to find relations between mean brightness temperatures and mean rain rates. This step accounts for beam filling. Finally, weights are obtained for combining the rain rates from the individual channels. The weights vary with the rain rates, so that the optimum combination of channels is always used. Results are stored in a database grid 1 deg latitude x 1 deg longitude by one month. To test the algorithm, three years (1979-81) of data from the Indian Ocean are processed.

Hinton, Barry B.↗

First meeting of the Working Group on the Shuttle Microwave Precipitation Radiometer (SMPR)

The working group agreed that the first (primary) objective should be the determination of methods for the accurate measurement of total rain water and total cloud water with passive microwave methods. There was no argument on the points concerning nonlinear relationships between T sub B and rain rate (R) over the range of important rain rates (half of oceanic rainfall occurs at rates greater than 15 mm h-1), such that variations in rain rate within a footprint lead to an incorrect measurement of the average rate for that footprint, and one cannot determine the characteristics of the sensed rain area. This is especially true near 18 GHz, where the dynamic range above 15 mm h-1 is very small because this frequency does not clearly fall in either a scattering regime or emissive regime at these wavelengths. It is also not clear whether very low frequency (emissive) techniques will be the best at measuring rain processes, or high frequency (scattering) techniques, where precipitation-size ice plays a major role in the signal attenuation. It is still not known what signal of rain is at certain rates on an observational basis because of the many different conditions that can exist within a single satellite observed footprint.

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