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A fundamental goal of satellite weather and climate observations is profiling the atmosphere with in situ-like precision and resolution with absolute accuracy and unbiased, all-weather, global coverage. While GPS radio occultation (RO) has perhaps come closest in terms of profiling the gas state from orbit, it does not provide sufficient information to simultaneously profile water vapor and temperature. We have been developing the Active Temperature, Ozone and Moisture Microwave Spectrometer (ATOMMS) RO system that probes the 22 and 183 GHz water vapor absorption lines to simultaneously profile temperature and water vapor from the lower troposphere to the mesopause. Using an ATOMMS instrument prototype between two mountaintops, we have demonstrated its ability to penetrate through water vapor, clouds and rain up to optical depths of 17 (7 orders of magnitude reduction in signal power) and still isolate the vapor absorption line spectrum to retrieve water vapor with a random uncertainty of less than 1 %. This demonstration represents a key step toward an orbiting ATOMMS system for weather, climate and constraining processes. ATOMMS water vapor retrievals from orbit will not be biased by climatological or first-guess constraints and will be capable of capturing nearly the full range of variability through the atmosphere and around the globe, in both clear and cloudy conditions, and will therefore greatly improve our understanding and analysis of water vapor. This information can be used to improve weather and climate models through constraints on and refinement of processes affecting and affected by water vapor. [ABSTRACT FROM AUTHOR]

A fundamental goal of satellite weather and climate observations is profiling the atmosphere with in situ-like precision and resolution with absolute accuracy and unbiased, all-weather, global coverage. While GPS radio occultation (RO) has come perhaps closest in terms of profiling the gas state from orbit, it does not provide sufficient information to simultaneously profile water vapor and temperature. We have been developing the Active Temperature, Ozone and Moisture Microwave Spectrometer (ATOMMS) RO system that probes the 22 and 183 GHz water vapor absorption lines to simultaneously profile temperature and water vapor from the lower troposphere to the mesopause. Using an ATOMMS instrument prototype between two mountaintops, we have demonstrated its ability to penetrate through water vapor, clouds and rain up to optical depths of 17 (7 orders of magnitude reduction in signal power) and still isolate the vapor absorption line spectrum to retrieve water vapor with a precision better than 1%. This demonstration represents a key step toward an orbiting ATOMMS system for weather, climate and constraining processes. [ABSTRACT FROM AUTHOR]

Water vapor is an important constituent in the earth's atmosphere that must be understood to predict weather and climate. Water vapor is challenging to measure, and observations of water vapor must be as independent of weather and climate models as possible in order to assess and improve those models. When combined with independent atmospheric temperature estimates, GPS radio occultation (RO) refractivity profiles yield unique, all-weather, high-vertical-resolution, globally distributed profiles of tropospheric water vapor whose vertical extent is maximum at low latitudes. A method for retrieving water vapor, known as the direct method, combines GPS RO-derived refractivity with temperatures from global weather analyses. Unlike variational methods, the direct method does not use the water vapor estimates from analyses because of their potential systematic errors. While utilization of the direct method has been limited because it produces negative values, these unphysical negative values reveal unique information about errors. A deconvolution technique is presented here that uses the negative values to estimate and remove random errors in histograms of water vapor derived via the direct method. Results indicate direct method specific humidity errors at low latitudes range from 0.4 g kg−1 at 725 hPa to 0.14 g kg−1 near 350 hPa, which can be removed via deconvolution. The deconvolved histograms extend to about the 240-K level in the troposphere, corresponding to 10 km at low latitudes. Unlike the limited information of low-order statistical moments like means and variances, histograms capture the full range of variability, which opens a new window into water vapor behavior and increases understanding of processes at work in the hydrological cycle. [ABSTRACT FROM AUTHOR]

The article focuses on the field testing of the Active Temperature, Ozone and Moisture Microwave Spectrometer (ATOMMS) which is developed as a satellite-to-satellite occultation system for monitoring climate. It notes that the field test is centered on the remote sensing of water by assessing the attenuation caused by the 22 gigahertz (GHz) and 183 GHz water absorption lines. It reveals that the ATOMMS amplitude measurements attribute approximately 0.3 percent errors.

The article presents a study which tests the remote sensing system called the active temperature, ozone and moisture microwave spectrometer (ATOMMS). It focuses on the development of a prototype instrument to demonstrate an aircraft to aircraft occultation. The study uses the 183 gigahertz (GHz) line spectrum measured along a path. It shows that ATOMMS amplitude errors were at 0.3% level with hygrometer which showed its consistency at 1% absolute humidity.

The probability distribution of local relative humidity R in the free troposphere is explored by comparing a simple theoretical calculation with observations from the global positioning system (GPS) and the Microwave Limb Sounder (MLS). The calculation is based on a parcel of air that conserves its composition during diabatic subsidence, until it is resaturated by randomly entering a convective system. This simple “advection–condensation” model of relative humidity predicts a probability density for R proportional to Rr-1, where r is the ratio of time scales associated with subsidence drying and random moistening. The observations obey this distribution remarkably well from 600 to 200 hPa in the Tropics and midlatitudes; possible reasons for this are discussed. The lowest values of R are predicted, and observed, to be the most probable. The observed vertical variation of R is well explained by that of the subsidence time scale, which is set by large-scale dynamics and radiation. These results imply that cloud microphysics exerts little control on water vapor’s greenhouse effect, but that relatively subtle dynamical changes have the potential to alter the strength of its feedback on climate change. [ABSTRACT FROM AUTHOR]

This paper describes the details of a fast, linear, forward-inverse refractive index mapping operator that can be used for assimilation of occultation data of various kinds into NWP models. Basically, the mapping consists of the integration of the refractive index along finite straight lines, mimicking the observational geometry as well as the subsequent retrieval of a refractive index profile, assuming spherical symmetry. Line integrals are discretized such that the refractivity is evaluated along the horizontal at fixed levels that can be chosen to coincide with the pressure levels of an NWP model. Integration of the hydrostatic equation at a large number of locations is thereby avoided. The mapping operator is tested using an idealized model of a weather front with large horizontal gradients. Mapped refractivity profiles are compared with retrieved refractivity profiles obtained via accurate 3D ray tracing simulations of GPS radio occultation events with ray path tangent points near the weather front. The simulations indicate that the mapping is a good representation of occultation measurements, including the influence large horizontal gradients have on retrieved refractivity profiles. To further the results, a simple ad hoc modification is introduced to approximately account for the ray path bending near the tangent points. The forward-inverse mapping allows for the near cancellation of otherwise crude approximations—for example, straight-line propagation—and the general concept could perhaps be adapted for the development of fast and accurate observation operators for the assimilation of other types of remote sensing data. [ABSTRACT FROM AUTHOR]

A new remote sensing concept extrapolated from the GPS occultation concept is presented in which the signal frequencies are chosen to determine atmospheric water, temperature, and the geopotential of atmospheric pressure surfaces. Using frequencies near the 22- and 183-GHz water lines allows not only the speed of light to be derived as a GPS occultation but also derivation of profiles of absorption caused by atmospheric water. Given the additional water information, moisture and temperature as well as the geopotential of pressure surfaces can be separated and solved for. Error covariance results indicate that the accuracies of individual water profiles will be 0.5%-3% extending from roughly 1-75-km altitude. Temperature accuracies of individual profiles will be sub-Kelvin from ∼1- to 70-km altitude depending on latitude and season. Accuracies of geopotential heights of pressure will be 10-20 m from the surface to 60-km altitude. These errors are random such that climatological averages derived from this data will be significantly more accurate. Owing to the limb-viewing geometry, the along-track resolution is comparable to the 200-300 km of the GPS occultation observations, but the shorter 22- and 183-GHz wavelengths improve the diffraction-limited vertical resolution to 100-300 m. The technique can be also used to determine profiles of other atmospheric constituents such as upper-tropospheric and stratospheric ozone by using frequencies near strong lines of that constituent. The combined dynamic range, accuracy, vertical resolution, and ability to penetrate clouds far surpass that of any present or planned satellite sensors. A constellation of such sensors would provide an all-weather, global remote sensing capability including full sampling of the diurnal cycle for process studies related to water, climate research, and weather prediction in general. [ABSTRACT FROM AUTHOR]

We have performed an analysis of reprocessed GPS/MET data spanning 1995–1997 generated by the COSMIC Data Analysis and Archive Center (CDAAC) in 2007. CDAAC developed modified dual-frequency processing methods for the encrypted data (anti-spoofing (AS)-on) during 1995–1997. We compared the CDAAC data set to the Modern-Era Retrospective Analysis for Research and Applications-2 (MERRA-2) reanalysis, separately for AS-on and AS-off, focusing on the altitude range 10–30 km. MERRA-2 did not assimilate GPS/MET data in the period 1995–1997. To gain insight into the CDAAC data set, we developed a single-frequency data set for GPS/MET , which is unaffected by the presence of encryption. We find excellent agreement between the more limited single-frequency data set and the CDAAC data set: the bias between these two data sets is consistently less than 0.25 % in refractivity, whether or not AS is on. Given the different techniques applied between the CDAAC and the new data set presented here (designated JPL), agreement suggests that the CDAAC AS-on processing and the single-frequency processing are not biased in an aggregate sense greater than 0.25 % in refractivity, which corresponds approximately to a temperature bias less than 0.5 K. Since the profiles contained in the new single-frequency data set are not a subset of the CDAAC profiles, the combination of the CDAAC data set, consisting of 9579 profiles, and the new single-frequency data set, consisting of 4729 profiles, yields a total number of 11 531 unique profiles from combining the JPL and CDAAC data sets. All numbers are after quality control has been applied by the respective processing activities. [ABSTRACT FROM AUTHOR]

The global positioning system (GPS) radio occultation (RO) technique has demonstrated the ability to precisely probe earth’s atmosphere globally with high vertical resolution. However, the lowermost troposphere still presents some challenges for the technique. Over moist marine areas, especially in subtropical regions, a very large negative moisture gradient often exists across the thermal inversion capping the marine boundary layer (MBL), which frequently causes superrefraction (SR), or ducting. In the presence of SR, the reconstruction of refractivity from RO data becomes an ill-posed inverse problem. This study shows that one given RO bending angle profile is consistent with a continuum (an infinite number) of refractivity profiles. The standard Abel retrieval gives the minimum refractivity solution of the continuum and thus produces the largest negative bias, consistent with a negative bias often present in the retrieved refractivity profiles in the moist lower troposphere. By applying a simple linear parameterization of the refractivity structure within and just below the SR layer, an analytical relation between the Abel-retrieved refractivity and a continuum of solutions is derived. Combining the Abel retrieval and the analytical relation with some physical constraints, a novel approach is developed to reconstruct the vertical refractivity structure within and below the SR layer. Numerical simulation studies in this paper have demonstrated the great potential of the reconstruction method to provide a much-improved retrieval in the presence of SR, and the method should greatly enhance the ability to measure the MBL structure globally using the GPS RO technique. [ABSTRACT FROM AUTHOR]

Tracking of the radio signals broadcast by the Global Positioning System (GPS) satellites as they are occulted from a GPS receiver by the Earth's atmosphere can provide high resolution vertical profiles of atmospheric refractivity, temperature and water vapour. Most implementations of this radio occultation technique use two GPS frequencies to correct for ionospheric effects. However, during most soundings, one of the frequencies is degraded by the introduction of the so-called Anti-Spoofing (AS) encryption mode. A retrieval method is discussed in this work for periods when only one of the two frequency signals has good quality. This method uses only the frequency with higher signal-to-noise ratio. We illustrate the quality of the atmospheric profiles obtained from such single frequency retrievals using GPS/MET data from the periods where the AS was turned off and the two frequencies were available. The results enable us to ensure the quality of a climate record of thousands of radio occultations collected by GPS/MET during the period with AS encryption, and the data processing of future missions with similar constraints, like IOX, can be performed. [ABSTRACT FROM AUTHOR]

Radio occultation (RO) measurements have little direct sensitivity to clouds, but recent studies have shown that they may have an indirect sensitivity to thin, high clouds that are difficult to detect using conventional passive space-based cloud sensors. We implement two RO-based cloud detection (ROCD) algorithms for atmospheric layers in the middle and upper troposphere. The first algorithm is based on the methodology of a previous study, which explored signatures caused by upper-tropospheric clouds in RO profiles according to retrieved relative humidity, temperature lapse rate, and gradients in log-refractivity (ROCD-P), and the second is based on inferred relative humidity alone (ROCD-M). In both, atmospheric layers are independently predicted as cloudy or clear based on observational data, including high-performance RO retrievals. In a demonstration, we use data from 10 days spanning 7 months in 2020 of Formosa Satellite 7 (FORMOSAT-7)/COSMIC-2. We use the forecasts of NOAA GFS to aid in the retrieval of relative humidity. The prediction is validated with a cloud truth dataset created from the imagery of the GOES-16 Advanced Baseline Imager (ABI) satellite and the GFS three-dimensional analysis of cloud-state conditions. Given these two algorithms for the presence or absence of clouds, confusion matrices and receiver operating characteristic (ROC) curves are used to analyze how well these algorithms perform. The ROCD-M algorithm has a balanced accuracy, which defines the quality of the classification test that considers both the sensitivity and specificity, greater than 70% for all altitudes between 6 and 10.25 km. [ABSTRACT FROM AUTHOR]

Observing the Global Positioning System with a satellite in low earth orbit in an occulting geometry provides a powerful means of imaging the ionosphere. Tomographic imaging of the ionosphere from space and ground is examined using singular value decomposition analysis. The resolution and covariance matrices are examined, and simulations are performed that indicate that space data are significantly more effective than ground data in resolving both horizontal and vertical structures. It is shown that narrow vertical structures, such as the E layer, can be probed with occultation data. [ABSTRACT FROM AUTHOR]

We have performed an analysis of reprocessed GPS/MET data spanning 1995--1997 generated by CDAAC in 2007. CDAAC developed modified dual-frequency processing methods for the encrypted data (AS-on) during 1995--1997. We compared the CDAAC data set to the MERRA-2 reanalysis, separately for AS-on and AS-off, focusing on the altitude range 10--30km. MERRA-2 did not assimilate GPS/MET data in the period 1995--1997. To gain insight into the CDAAC data set, we developed a single-frequency data set for GPS/MET, which is unaffected by the presence of encryption. We find excellent agreement between the more limited single frequency data set and the CDAAC data set: the bias between these two data sets is consistently less than 0.25% in refractivity, whether or not AS is on. Given the different techniques applied between the CDAAC and JPL data sets, agreement suggests that the CDAAC AS-on processing and the single frequency processing are not biased in an aggregate sense greater than 0.25% in refractivity, which corresponds approximately to a temperature bias less than 0.5K. Since the profiles contained in the new single frequency data set are not a subset of the CDAAC profiles, the combination of the CDAAC data set, consisting of 9,579 profiles, and the new single-frequency data set, consisting of 4,729 profiles, yields a total number of 11,531 unique profiles from combining the JPL and CDAAC data sets. All numbers are after quality control has been applied by the respective processing activities. [ABSTRACT FROM AUTHOR]

In the upper troposphere (UT), Global Navigation Satellite System (GNSS) Radio Occultations (ROs) provide accurate air temperatures (<0.5 K) every ∼200 m vertically. We use RO observations from 01/2002 until 12/2018 at 300, 250, and 200 hPa to quantify the tropical upper tropospheric amplification (defined as the ratio of temperature trends in the UT relative to the surface). We compare the RO‐derived results against Atmospheric Infrared Sounder (AIRS), Coupled Model Intercomparison Project Phase 6 (CMIP6) Atmospheric Model Intercomparison Project (AMIP) models, Modern‐Era Retrospective Analysis for Research and Applications version 2 (MERRA‐2), and European Center for Medium‐range Weather Forecasts Re‐Analysis Interim (ERA‐Interim) data. We find that CMIP6 AMIP models show excellent agreement with independent AIRS and RO observations on the magnitude of the UT warming and show warming that is significantly faster than both reanalyses above 250 hPa. Additionally, AIRS and CMIP6 AMIP present excellent agreement with the RO‐measured tropical tropospheric amplification. Plain Language Summary: In the upper troposphere, Global Navigation Satellite System Radio Occultations (GNSS‐RO) measure the air's refractive index, which depends primarily on the air's temperature. We use these GNSS‐RO temperatures from 01/2002 until 12/2018 at 200, 250, and 300 hPa in the tropics (where the atmosphere experiences the largest amplification in response to surface warming). Routinely, climate models are used to simulate how much the upper atmosphere has warmed in response to surface warming. However, there appears to be a disagreement between observations and models, which today we try to understand. The GNSS‐RO observations have a unique feature of being able to measure the air temperature every 200 m, and show us that that climate models are in close agreement with the GNSS‐RO and other infrared observations. In other words, GNSS‐RO observations show that the upper atmosphere warms faster and the amplification due to surface warming is stronger than what current reanalysis estimate. Independent infrared observations of the Earth's upper troposphere also support the GNSS‐RO findings and are also in very close agreement with the climate models. Interestingly, the reanalysis indicates that at 200 hPa there is no warming observed, contrary to what GNSS‐RO, infrared, and climate models reveal. Key points: Coupled model intercomparison project phase 6 (cmip6) atmospheric model intercomparison project (AMIP) models agree with independent radio occultation and infrared data on the magnitude of the tropical upper tropospheric temperature trendsRadio occultations reveal faster tropical upper tropospheric warming than both modern‐era retrospective analysis for research and applications version 2 (MERRA‐2) and European Center for Medium‐Range Weather Forecasts Re‐Analysis Interim (ERA‐Interim) (above 250 hPa) reanalysesERA‐Interim presents decreasing tropical upper troposphere amplification with altitude, unlike the amplification shown by radio occultations [ABSTRACT FROM AUTHOR]

The Global Energy and Water cycle Exchanges (GEWEX) Data and Assessments Panel (GDAP) initiated the GEWEX Water Vapor Assessment (G-VAP), which has the main objectives to quantify the current state of art in water vapour products being constructed for climate applications and to support the selection process of suitable water vapour products by GDAP for its production of globally consistent water and energy cycle products. During the construction of the G-VAP data archive, freely available and mature satellite and reanalysis data records with a minimum temporal coverage of 10 years were considered. The archive contains total column water vapour (TCWV) as well as specific humidity and temperature at four pressure levels (1000, 700, 500, 300 hPa) from 22 different data records. All data records were remapped to a regular longitude/latitude grid of 2° × 2°. The archive consists of four different folders: 22 TCWV data records covering the period 2003-2008, 11 TCWV data records covering the period 1988-2008, as well as seven specific humidity and seven temperature data records covering the period 1988-2009. The G-VAP data archive is referenced under the following digital object identifier (doi): doi:10.5676/EUM_SAF_CM/GVAP/V001. Within G-VAP, the characterisation of water vapour products is, among other ways, achieved through intercomparisons of the considered data records, as a whole and grouped into three classes of predominant retrieval condition: clear-sky, cloudy-sky and all-sky. Associated results are shown using the 22 TCWV data records. The standard deviations among the 22 TCWV data records have been analysed and exhibit distinct maxima over central Africa and the tropical warm pool (in absolute terms) as well as over the poles and mountain regions (in relative terms). The variability in TCWV within each class can be large and prohibits conclusions on systematic differences in TCWV between the classes. [ABSTRACT FROM AUTHOR]

Several recent studies have observed systematic differences between measurements in the 183.31 GHz water vapor line by space-borne sounders and calculations using radiative transfer models, with inputs from either radiosondes (radiosonde observations, RAOBs) or short-range forecasts by numerical weather prediction (NWP) models. This paper discusses all the relevant categories of observation-based or model-based data, quantifies their uncertainties and separates biases that could be common to all causes from those attributable to a particular cause. Reference observations from radiosondes, Global Navigation Satellite System (GNSS) receivers, differential absorption lidar (DIAL) and Raman lidar are thus overviewed. Biases arising from their calibration procedures, NWP models and data assimilation, instrument biases and radiative transfer models (both the models themselves and the underlying spectroscopy) are presented and discussed. Although presently no single process in the comparisons seems capable of explaining the observed structure of bias, recommendations are made in order to better understand the causes. [ABSTRACT FROM AUTHOR]

Several recent studies have observed systematic differences between measurements in the 183.31 GHz water vapor line by space-borne sounders and calculations using radiative transfer models, with inputs from either radiosondes (radiosonde observations, RAOBs) or short-range forecasts by numerical weather prediction (NWP) models. This paper discusses all the relevant categories of observation-based or model-based data, quantifies their uncertainties and separates biases that could be common to all causes from those attributable to a particular cause. Reference observations from radiosondes, Global Navigation Satellite System (GNSS) receivers, differential absorption lidar (DIAL) and Raman lidar are thus overviewed. Biases arising from their calibration procedures, NWP models and data assimilation, instrument biases and radiative transfer models (both the models themselves and the underlying spectroscopy) are presented and discussed. Although presently no single process in the comparisons seems capable of explaining the observed structure of bias, recommendations are made in order to better understand the causes. [ABSTRACT FROM AUTHOR]

The complex interactions between water vapor fields and deep atmospheric convection remain one of the outstanding problems in tropical meteorology. The lack of high spatial-temporal resolution, all-weather observations in the tropics has hampered progress. Numerical models have difficulties, for example, in representing the shallow-to-deep convective transition and the diurnal cycle of precipitation. Global Navigation Satellite System (GNSS) meteorology, which provides all-weather, high-frequency (5 min), precipitable water vapor estimates, can help. The Amazon Dense GNSS Meteorological Network experiment, the first of its kind in the tropics, was created with the aim of examining water vapor and deep convection relationships at the mesoscale. This innovative, Brazilian-led international experiment consisted of two mesoscale (100 km x 100 km) networks: 1) a 1-yr (April 2011-April 2012) campaign (20 GNSS meteorological sites) in and around Manaus and 2) a 6-week (June 2011) intensive campaign (15 GNSS meteorological sites) in and around Belem, the latter in collaboration with the Cloud Processes of the Main Precipitation Systems in Brazil: A Contribution to Cloud-Resolving Modeling and to the Global Precipitation Measurement (CHUVA) Project in Brazil. Results presented here from both networks focus on the diurnal cycle of precipitable water vapor associated with sea-breeze convection in Belem and seasonal and topographic influences in and around Manaus. Ultimately, these unique observations may serve to initialize, constrain, or validate precipitable water vapor in high-resolution models. These experiments also demonstrate that GNSS meteorology can expand into logistically difficult regions such as the Amazon. Other GNSS meteorology networks presently being constructed in the tropics are summarized. [ABSTRACT FROM AUTHOR]

A Global Navigation Satellite System (GNSS) radio occultation (RO) experiment is being accommodated in the Spanish low Earth orbiter for Earth Observation PAZ. The RO payload will provide globally distributed vertical thermodynamic profiles of the atmosphere suitable to be assimilated into weather numerical prediction models. The Ground Segment services of the U.S. National Oceanographic and Atmospheric Administration and standard-RO processing services by University Corporation for Atmospheric Research (USA) will be available under best effort basis. Moreover, the mission will run, for the first time, a double-polarization GNSS RO experiment to assess the capabilities of polarimetric GNSS RO for sensing heavy rain events. This paper introduces the Radio-Occultation and Heavy Precipitation experiment aboard PAZ and performs a theoretical analysis of the concept. The L-band GNSS polarimetric observables to be used during the experiment are presented, and their sensitivity to moderate to heavy precipitation events is evaluated. This study shows that intense rain events will induce polarimetric features above the detectability level. [ABSTRACT FROM PUBLISHER]

To date, a large variety of water vapour data records from satellite and reanalysis are available. It is key to understand the quality and uncertainty of these data records in order to fully exploit these records and to avoid data being employed incorrectly or misinterpreted. Therefore, it is important to inform users on accuracy and limitations of these data records based on consistent inter-comparisons carried out in the framework of international assessments. Addressing this challenge is the major objective of the Global Water and Energy Exchanges (GEWEX) water vapor assessment (G-VAP) which was initiated by the GEWEX Data and Assessments Panel (GDAP). Here, an overview of G-VAP objectives and an introduction to the results from G-VAP's first phase are given. After this overview, a summary of available data records on water vapour and closely related variables and a short introduction to the utilized methods are presented. The results from inter-comparisons, homogeneity testing and inter-comparison of trend estimates, achieved within G-VAP's first phase are summarized. The conclusions on future research directions for the wider community and for G-VAP's next phase are outlined and recommendations have been formulated. For instance, a key recommendation is the need for recalibration and improved inter-calibration of radiance data records and subsequent reprocessing in order to increase stability and to provide uncertainty estimates. This need became evident from a general disagreement in trend estimates (e.g., trends in TCWV ranging from −1.51 ± 0.17 kg/m2/decade to 1.22 ± 0.16 kg/m2/decade) and the presence of break points on global and regional scale. It will be a future activity of G-VAP to reassess the stability of updated or new data records and to assess consistency, i.e., the closeness of data records given their uncertainty estimates. [ABSTRACT FROM AUTHOR]