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NASA NTRS1998

Comparison of Radar Rainfall Retrieval Algorithms in Convective Rain During TOGA COARE

The authors compare deterministic and stochastic rain-rate retrieval algorithms by applying them to 14-GHz nadir-looking airborne radar reflectivity profiles acquired in tropical convective rain during the Tropical Ocean Global Atmosphere Coupled Ocean-Atmosphere Response Experiment, The deterministic algorithms both use the path-integrated attenuation (PIA), measured by the surface reference technique, as a constraint. One deterministic algorithm corrects the k-R relation, while the second corrects the Z-R relation. The stochastic algorithms are based on applying an extended Kalman filter to the reflectivity profile. One employs radar reflectivity only; the other additionally uses the PIA. The authors find that the stochastic algorithm, which uses the PIA, is the most robust algorithm with regard to incorrect assumptions about the drop size distribution (DSD). The deterministic algorithm that uses the PIA to adjust the Z-R relation is also fairly robust and produces rain rates similar to the stochastic algorithm that uses the PIA, The deterministic algorithm that adjusts only the k-R relation and the stochastic radar-only algorithm are more sensitive to assumptions about the DSD. It is likely that they underestimate convective rainfall, especially if the DSD is erroneously assumed to be appropriate for stratiform rain conditions.

Durden, Stephen L.↗
NASA NTRS2000

BOREAS HYD-9 Hourly and Daily Rainfall Maps for the Southern Study Area

The Boreal Ecosystem-Atmosphere Study (BOREAS) Hydrology (HYD)-9 team collected data on precipitation and streamflow over portions of the Northern Study Area (NSA) and Southern Study Area (SSA). This data set contains Cartesian maps of rain accumulation for one-hour and daily periods during the summer of 1994 over the SSA only (not the full view of the radar). A parallel set of one-hour maps for the whole radar view has been prepared and is available upon request from the HYD-09 personnel. An incidental benefit of the areal selection was the elimination of some of the less accurate data, because for various reasons the radar rain estimates degrade considerably outside a range of about 100 km. The data are available in tabular ASCII files. The HYD-09 hourly and daily radar rainfall maps for the SSA are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files are available on a CD-ROM (see document number 20010000884).

Eley, F. Joe↗
NASA NTRS2001

The Magnitude and Variability of Global and Regional Precipitation Based on the 22-Year GPCP (Global Precipitation Climatology Project) and Three-Year TRMM (Tropical Rainfall Measuring Mission) Data Sets

This paper gives an overview of the analysis of global precipitation over the last few decades and the impact of the new TRMM precipitation observations. The 20+ year, monthly, globally complete precipitation analysis of the World Climate Research Program's (WCRP/GEWEX) Global Precipitation Climatology Project (GPCP) is used to study global and regional variations and trends and is compared to the much shorter TRMM (Tropical Rainfall Measuring Mission) tropical data set. The GPCP data set shows no significant trend in precipitation over the twenty years, unlike the positive trend in global surface temperatures over the past century. The global trend analysis must be interpreted carefully, however, because the inhomogeneity of the data set makes detecting a small signal very difficult, especially over this relatively short period. Identifying regional trends in precipitation may be more practical. From 1979 to 1999 the northern mid-latitudes appear to be drying, the southern mid-latitudes have gotten wetter, and there is a mixed signal in the tropics. The relation between this field of trends and the relation to the frequency of El Nino events during this time period is explored. Monthly anomalies of precipitation are related to ENSO variations with clear signals extending into middle and high latitudes of both hemispheres. The El Nino and La Nina mean anomalies are near mirror images of each other and when combined produce an ENSO signal with significant spatial continuity over large distances. These El Nino minus La Nina composites of normalized precipitation show the usual positive, or wet, anomaly over the central and eastern Pacific Ocean with the negative, or dry, anomaly over the maritime continent along with an additional negative anomaly over Brazil and the Atlantic Ocean extending into Africa and a positive anomaly over the Horn of Africa and the western Indian Ocean. A number of the features are shown to extend into high latitudes. Positive anomalies extend in the Southern Hemisphere (S.H.) from the Pacific southeastward across Chile and Argentina into the south Atlantic Ocean. In the Northern Hemisphere (N.H.) the counterpart feature extends across the southern US and Atlantic Ocean into Europe. Further to the west a negative anomaly extends southeastward again from the Maritime Continent across the South Pacific and through the Drake Passage. The N.H. counterpart crosses the North Pacific and southern Canada. In the Southern Hemisphere an anomaly feature is shown to spiral into the Antarctica land mass. The extremes of ENSO-related anomalies are also examined and indicate that globally, during both El Nino and La Nina, more extremes of precipitation ( both wet and dry) occur than during the "neutral" regime, with the El Nino regime showing larger magnitudes. The distribution is different for the globe as a whole and when the area is restricted to just land. The recent (1998-present) TRMM observations are compared with the similar period of GPCP analyses with very good agreement in terms of pattern and generally good agreement with regard to magnitude. However, there still are differences among the individual TRMM products using passive and active microwave techniques and these need to be resolved before longer-term products such as the GPCP analyses can be validated.

Adler, Robert F.↗
NASA NTRS2000

Tropical Rainfall Measuring Mission (TRMM) Satellite: Assessment and Lessons Learned After Three Flight Years

Tropical Rain Measuring Mission (TRMM) is an experiment in measuring rainfall and the associated latent heat release from space. A primary goal is to help in initializing the large-scale weather and climate models for crucial improvement in location and profile of atmospheric heat release. For this, precipitation and latent heating profiles are needed. This goal requires cloud-resolving models. The basic approach was to use passive microwave and rain radar in combination to issue a limited number of products, improving the retrieval algorithms by testing during flight, so the products are updated annually. Despite a tight budget, the TRMM observatory and data system worked excellently from launch for the past three years. A basic philosophy has been to do physical validation as much as possible, in preference to empirical adjustments for algorithm improvement. Additional information is contained in the original extended abstract.

Simpson, Joanne↗
NASA NTRS2000

Sampling Errors in Monthly Rainfall Totals for TRMM and SSM/I, Based on Statistics of Retrieved Rain Rates and Simple Models

Estimates from TRMM satellite data of monthly total rainfall over an area are subject to substantial sampling errors due to the limited number of visits to the area by the satellite during the month. Quantitative comparisons of TRMM averages with data collected by other satellites and by ground-based systems require some estimate of the size of this sampling error. A method of estimating this sampling error based on the actual statistics of the TRMM observations and on some modeling work has been developed. "Sampling error" in TRMM monthly averages is defined here relative to the monthly total a hypothetical satellite permanently stationed above the area would have reported. "Sampling error" therefore includes contributions from the random and systematic errors introduced by the satellite remote sensing system. As part of our long-term goal of providing error estimates for each grid point accessible to the TRMM instruments, sampling error estimates for TRMM based on rain retrievals from TRMM microwave (TMI) data are compared for different times of the year and different oceanic areas (to minimize changes in the statistics due to algorithmic differences over land and ocean). Changes in sampling error estimates due to changes in rain statistics due 1) to evolution of the official algorithms used to process the data, and 2) differences from other remote sensing systems such as the Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave/Imager (SSM/I), are analyzed.

Bell, Thomas L.↗
NASA NTRS2000

Spaceborne Radar Measurements of Rainfall Vertical Velocity

This paper studies the performance of a spaceborne precipitation radar in measuring vertical Doppler velocity of rainfall. As far as a downward pointing precipitation radar is concerned, one of the major problems affecting Doppler measurement at the nadir direction arises from the Non-Uniform Beam-Filling effect (NUBF). That is, when significant variation in rain rate is present within the radar IFOV (Instrument Field of View) in the along track direction. the Doppler shift caused by the radial component of the horizontal speed of the satellite is weighted differently among the portions of IFOV. The effects of this non-uniform weighting may dominate any other contribution. Under this condition, shape, average value and width of the Doppler spectrum may not be directly correlated with the vertical velocity of the precipitating particles. However, by using an inversion technique which over-samples the radar measurements in the along track direction, we show that the shift due to NUBF can be evaluated, and that the NUBF induced errors on average fall speed can be reduced.

Im, Eastwood↗
NASA NTRS2000

Rainfall Algorithm Improvements and Validation for the TRMM Microwave Imager

The Texas A&M monthly total oceanic rainfall retrieval algorithm is based on radiative transfer models and can only be modified on a physically sound basis. Within this constraint we have examined some improvements to the algorithm and it appears that it can be made significantly better. In particular, it appears that by proper use of the range of frequencies available on TMI (TRMM Microwave Imager) and AMSR that the need for the log-normal fit can be eliminated.

Wilheit, Thomas T.↗
NASA NTRS2002

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↗
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

Calibration Methodology for the Lightweight Rainfall Radiometer STAR Aircraft Sensor

A proposed methodology for the in-flight calibration of a Synthetic Thinned Aperture Radiometer (STAR) airborne sensor with the potential application to a space flight version. The application of the spaceflight version of this instrument will address several pressing issues related to the Global Precipitation Measurement Mission (GPM). The X-Band Lightweight Rainfall Radiometer using STAR technology (LRR-X) is an aircraft sensor that is jointly developed by the NASA Goddard Space Flight Center and the University of Michigan. This paper will describe the theory of calibration as well as the hardware design specifications used by the method. The on-board hardware uses individual uncorrelated warm loads on each receiver as well as to a single noise diode providing a correlated noise source to each receiver. A procedure for maintaining onboard calibration with an optimum running average using correlated bursts of thermal noise interleaved with scene data will be exercised during the maiden flight of the LRR-X instrument during the spring of 2003. The final component of calibration of a synthetic aperture radiometer is the image reconstruction algorithm that uses the measured correlations to produce the temperature brightness (TB) images. An overview of system-level testing, both on the ground and in-flight, will be presented to validate the absolute accuracy of the image reconstruction algorithm.

Principe, Caleb↗
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 NTRS2002

Use of TRMM Rainfall Information in Improving Long-Term, Satellite-Based Global Precipitation Analyses

The TRMM rainfall products are inter-compared among themselves and to the 23 year, monthly, globally complete precipitation analysis of the World Climate Research Program's (WCRP/ GEWEX) Global Precipitation Climatology Project (GPCP). Ways in which the TRMM-based estimates can be used to improve the long-term data set are described. These include improvement of the passive microwave algorithm that is applied to the 15 year SSM/I record and calibration or adjustment of the current GPCP fields utilizing the 4-5 year overlap of TRMM and GPCP. A comparison of the GPCP monthly surface precipitation fields and the TRMM-based multi-satellite analyses indicates that the two are similar, but have significant differences that relate to the different input data sets. Although on a zonal average basis over the ocean the two analyses are similar in the deep Tropics, there are subtle differences between the eastern and western Pacific Ocean in the relative magnitudes. In mid-latitudes the GPCP has somewhat larger mean precipitation than TRMM. Statistical comparisons of TRMM and GPCP monthly fields are carried out in terms of histogram matching for both ocean and land regions and for small areas to diagnose differences. These comparisons form the basis for a TRMM calibration of the GPCP fields using matched histograms over regional areas as a function of season. Although final application of this procedure will likely await the Version 6 of the TRMM products, tests using Version 5 are shown that provide a TRMM-calibrated GPCP version that will produce an improved climatology and a more accurate month-to-month precipitation analysis for the last 20 years.

Starr, David OC.↗
NASA NTRS2003

Estimates of Random Error in Satellite Rainfall Averages

Satellite rain estimates are most accurate when obtained with microwave instruments on low earth-orbiting satellites. Estimation of daily or monthly total areal rainfall, typically of interest to hydrologists and climate researchers, is made difficult, however, by the relatively poor coverage generally available from such satellites. Intermittent coverage by the satellites leads to random "sampling error" in the satellite products. The inexact information about hydrometeors inferred from microwave data also leads to random "retrieval errors" in the rain estimates. In this talk we will review approaches to quantitative estimation of the sampling error in area/time averages of satellite rain retrievals using ground-based observations, and methods of estimating rms random error, both sampling and retrieval, in averages using satellite measurements themselves.

Bell, Thomas L.↗
NASA NTRS2004

Status of Validation Program for Tropical Rainfall Measuring Mission (TRMM)

The Tropical Rainfall Measuring Mission (TRMM) is in its sixth year of operation. This successful research mission, a joint U.S./Japan effort, has become-a key element in the routine monitoring of global precipitation. The package of rain measuring instrumentation, including the first meteorological radar in space, continues to function perfectly, and with the increase in orbital altitude (from 350 km to 400 km) the mission will hopefully continue for a number of years. The validation effort has been a combination of routine use of 1) ground-based radar and raingauge measurements for comparison with the satellite-based estimates, 2) the use of field experiment data for evaluation of the satellite data products and investigation of some of the assumptions in the satellite retrievals, and 3) use of other comparison data sets, including atoll and buoy gauges over ocean and research and operational gauge data sets over land. The status of the program will be described along with "lessons learned". Near term plans for improved validation products and new thrusts related to validation of TRMM-based multi-satellite products that extend into middle latitudes will be outlined.

Adler, Robert↗
NASA NTRS2003

A Stochastic Model of Space-Time Variability of Mesoscale Rainfall: Statistics of Spatial Averages

A characteristic feature of rainfall statistics is that they depend on the space and time scales over which rain data are averaged. A previously developed spectral model of rain statistics that is designed to capture this property, predicts power law scaling behavior for the second moment statistics of area-averaged rain rate on the averaging length scale L as L right arrow 0. In the present work a more efficient method of estimating the model parameters is presented, and used to fit the model to the statistics of area-averaged rain rate derived from gridded radar precipitation data from TOGA COARE. Statistical properties of the data and the model predictions are compared over a wide range of averaging scales. An extension of the spectral model scaling relations to describe the dependence of the average fraction of grid boxes within an area containing nonzero rain (the "rainy area fraction") on the grid scale L is also explored.

Kundu, Prasun K.↗
NASA NTRS2003

Angular Distribution Models for Top-of-Atmosphere Radiative Flux Estimation from the Clouds and the Earth's Radiant Energy System Instrument on the Tropical Rainfall Measuring Mission Satellite: Validation - Part II

Top-of-atmosphere (TOA) radiative fluxes from the Clouds and the Earth s Radiant Energy System (CERES) are estimated from empirical angular distribution models (ADMs) that convert instantaneous radiance measurements to TOA fluxes. This paper evaluates the accuracy of CERES TOA fluxes obtained from a new set of ADMs developed for the CERES instrument onboard the Tropical Rainfall Measuring Mission (TRMM). The uncertainty in regional monthly mean reflected shortwave (SW) and emitted longwave (LW) TOA fluxes is less than 0.5 W/sq m, based on comparisons with TOA fluxes evaluated by direct integration of the measured radiances. When stratified by viewing geometry, TOA fluxes from different angles are consistent to within 2% in the SW and 0.7% (or 2 W/sq m) in the LW. In contrast, TOA fluxes based on ADMs from the Earth Radiation Budget Experiment (ERBE) applied to the same CERES radiance measurements show a 10% relative increase with viewing zenith angle in the SW and a 3.5% (9 W/sq m) decrease with viewing zenith angle in the LW. Based on multiangle CERES radiance measurements, 18 regional instantaneous TOA flux errors from the new CERES ADMs are estimated to be 10 W/sq m in the SW and, 3.5 W/sq m in the LW. The errors show little or no dependence on cloud phase, cloud optical depth, and cloud infrared emissivity. An analysis of cloud radiative forcing (CRF) sensitivity to differences between ERBE and CERES TRMM ADMs, scene identification, and directional models of albedo as a function of solar zenith angle shows that ADM and clear-sky scene identification differences can lead to an 8 W/sq m root-mean-square (rms) difference in 18 daily mean SW CRF and a 4 W/sq m rms difference in LW CRF. In contrast, monthly mean SW and LW CRF differences reach 3 W/sq m. CRF is found to be relatively insensitive to differences between the ERBE and CERES TRMM directional models.

Loeb, N. G.↗
NASA NTRS2003

Angular Distribution Models for Top-of-Atmosphere Radiative Flux Estimation from the Clouds and the Earth's Radiant Energy System Instrument on the Tropical Rainfall Measuring Mission Satellite: Methodology - Part 1

Clouds and the Earth s Radiant Energy System (CERES) investigates the critical role that clouds and aerosols play in modulating the radiative energy flow within the Earth-atmosphere system. CERES builds upon the foundation laid by previous missions, such as the Earth Radiation Budget Experiment, to provide highly accurate top-of-atmosphere (TOA) radiative fluxes together with coincident cloud and aerosol properties inferred from high-resolution imager measurements. This paper describes the method used to construct empirical angular distribution models (ADMs) for estimating shortwave, longwave, and window TOA radiative fluxes from CERES radiance measurements on board the Tropical Rainfall Measuring Mission satellite. To construct the ADMs, multiangle CERES measurements are combined with coincident high-resolution Visible Infrared Scanner measurements and meteorological parameters from the European Centre for Medium-Range Weather Forecasts data assimilation product. The ADMs are stratified by scene types defined by parameters that have a strong influence on the angular dependence of Earth's radiation field at the TOA. Examples of how the new CERES ADMs depend upon the imager-based parameters are provided together with comparisons with existing models.

Loeb, N. G.↗
NASA NTRS2004

A Review of Current Investigations of Urban-Induced Rainfall and Recommendations for the Future

Precipitation is a key link in the global water cycle and a proxy for changing climate; therefore proper assessment of the urban environment s impact on precipitation (land use, aerosols, thermal properties) will be increasingly important in ongoing climate diagnostics and prediction, Global Water and Energy Cycle (GWEC) analysis and modeling, weather forecasting, freshwater resource management, urban planning-design and land-atmosphere-ocean interface processes. These facts are particularly critical if current projections for global urban growth are accurate. The goal of this paper is to provide a concise review of recent (1990-present) studies related to how the urban environment affects precipitation. In addition to providing a synopsis of current work, recent findings are placed in context with historical investigations such as METROMEX studies. Both observational and modeling studies of urban-induced rainfall are discussed. Additionally, a discussion of the relative roles of urban dynamic and microphysical (e.g. aerosol) processes is presented. The paper closes with a set of recommendations for what observations and capabilities are needed in the future to advance our understanding of the processes.

Shepherd, J. Marshall↗