Swaroop Sahoo

Atmospheric water vapor effects on spaceborne interferometric SAR imaging: Comparison with ground-based measurements and meteorological model simulations at different scales

Spaceborne Interferometric Synthetic Aperture Radar (InSAR) is a well established technique useful in many land applications, such as monitoring tectonic movements and landslides or extracting digital elevation models. One of its major limitations is the atmospheric variability, and in particular the high water vapor spatial and temporal variability, which introduces an unknown delay in the signal propagation. On the other hand, these effects might be exploited, so as InSAR could become a tool for highresolution water vapor mapping. This paper describes the approach and some preliminary results achieved in the framework of an ESA funded project devoted to the mitigation of the water vapor effects in InSAR applications. Although very preliminary, the acquired experimental data and their comparison give a first idea of what can be done to gather valuable information on water vapor, which play a fundamental role in weather prediction and radio propagation studies.

Three-Dimensional Humidity Retrieval Using a Network of Compact Microwave Radiometers to Correct for Variations in Wet Tropospheric Path Delay in Spaceborne Interferometric SAR Imagery

Spaceborne interferometric synthetic aperture radar (SAR) (InSAR) imaging has been used for over a decade to monitor tectonic movements and landslides, as well as to improve digital elevation models. However, InSAR is affected by variations in round-trip propagation delay due to changes in ionospheric total electron content and in tropospheric humidity and temperature along the signal path. One of the largest sources of uncertainty in estimates of tropospheric path delay is the spatial and temporal variability of water vapor density, which currently limits the quality of InSAR products. This problem can be partially addressed by using a number of SAR interferograms from subsequent satellite overpasses to reduce the degradation in the images or by analyzing a long time series of interferometric phases from permanent scatterers. However, if there is a sudden deformation of the Earths surface, the detection of which is one of the principal objectives of InSAR measurements over land, the effect of water vapor variations cannot be removed, reducing the quality of the interferometric products. In those cases, high-resolution information on the atmospheric water vapor content and its variation with time can be crucial to mitigate the effect of wet-tropospheric path delay variations. This paper describes the use of a ground-based microwave radiometer network to retrieve 3-D water vapor density with fine spatial and temporal resolution, which can be used to reduce InSAR ambiguities due to changes in wet-tropospheric path delay. Retrieval results and comparisons between the integrated water vapor measured by the radiometer network and satellite data are presented.

Radiometric Information Content for Water Vapor and Temperature Profiling in Clear Skies Between 10 and 200 GHz

Atmospheric profiles of water vapor and temperature can be estimated using appropriate retrieval algorithms based on radiometric measurements and atmospheric statistics. Radiometric measurements at multiple frequencies contribute information to profile retrieval, although at some frequencies the information they provide can be highly correlated with that at other frequencies due to similar sensitivities to changes in atmospheric pressure, temperature, and water vapor mixing ratio as a function of altitude. The goal for profile retrieval is to obtain as many independent measurements as possible, both to maximize the vertical resolution and to minimize the retrieval error of the profile. The goal of this study is to determine sets of frequencies in the range from 10 to 200 GHz that provide the largest amount of mutually independent information on water vapor and temperature profiles from ground and airborne instruments for clear sky measurements. Results of such a study are important and useful for frequency selection and design of microwave and millimeter-wave radiometers for humidity and temperature profiling. A branch and bound feature selection algorithm has been used to determine sets of frequencies between 10 and 200 GHz that have the greatest number of degrees of freedom (DOF) for water vapor and temperature retrieval. In general, it has been found that the frequency ranges of 20-23, 85-90, and 165-200 GHz are useful for water vapor profile retrieval, whereas the frequency ranges of 55-65 and 116-120 GHz are useful for temperature profile retrieval. Finally, an analysis has been performed to determine the impact of measurement uncertainty on the number of DOF of measurement and also on the vertical resolution. It was also found that vertical resolution is directly related to the number of DOF.

Optimization of Background Information and Layer Thickness for Improved Accuracy of Water-Vapor Profile Retrieval from Ground-Based Microwave Radiometer Measurements at K-Band

Ground-based microwave radiometers operating at frequencies near the 22.235 GHz (K-band) water vapor absorption line have been used extensively for remote sensing of water vapor in the troposphere, both the integrated amount and its profile. This paper explores the potential to use ground-based, zenith-pointing K-band radiometer measurements along with optimized background data sets consisting of radiosonde profiles to detect dynamic changes and gradients in water vapor profiles. To explore this capability, the HUMidity EXperiment 2011 (HUMEX11) was conducted at the U.S. Department of Energys (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) Site near Lamont, OK, USA. This enables the choice of appropriate retrieval parameters to monitor temporal changes in atmospheric water vapor profiles. The results of this study illustrate that in a retrieval algorithm both the choice of the size of the background data set measured near the radiometer measurement time and the choice of atmospheric layer thickness affect the ability to remotely sense dynamic changes in water vapor. In general, it is found that background data sets of larger size provide better accuracy in a statistical sense but inhibit the ability to detect gradients.

Retrieval of Slant Water Vapor Path and Slant Liquid Water from Microwave Radiometer Measurements during the DYNAMO Experiment

Observations during the Dynamics of the Madden-Julian Oscillation (DYNAMO) experiment focused on sensing atmospheric parameters, including vertical moisture profiles, cloud structure, precipitation processes, and planetary boundary layer properties, all of which are important for understanding and modeling the Madden-Julian Oscillation (MJO). These observations were performed using a variety of in-situ and remote sensors, including the S-band polarimetric and Ka-band (S-PolKa) radar, deployed by the National Center for Atmospheric Research (NCAR), and a colocated University of Miami microwave radiometer (UM-radiometer) operating at 23.8 and 30.0 GHz. These instruments sampled approximately the same volumes of the atmosphere at a variety of azimuth and elevation angles. The principal goal of this study is to develop a new retrieval strategy to estimate slant water vapor path (SWP) and slant liquid water (SLW) using UM-radiometer measurements from zenith to low elevation angles at a variety of azimuth angles. Retrievals of SWP along the radar signal path help to determine the error in radar reflectivity due to water vapor absorption. The retrieval algorithm has been developed using the vapor-liquid water ratio (VLWR) as well as both modeled and measured brightness temperatures for zenith to low elevation angles. Observation system simulation experiment (OSSE) results and measured radiosonde data have been used to determine that the retrieval uncertainty is less than 5% for integrated water vapor (IWV) and less than 12% for integrated liquid water (ILW). OSSE results for SWP show that the retrieval uncertainty is less than 8% at 5° elevation angle and less than 5% at 7° and 9°, while the mean difference between SWP retrieved from radiometer measurements and those retrieved from the S-PolKa radar during the DYNAMO campaign is less than 10% at 5° elevation angle and less than 7.5% at 7° and 9°. OSSE results for SLW show that the mean error is less than 24% for 5° elevation angle and less than 18% for 7° and 9°. Such retrievals of SWP and SLW help to characterize the distribution of water vapor and liquid water in the lower troposphere, which in turn may contribute to improvements in forecasting of convective initiation and precipitation.

Retrieval of slant water path, liquid water and rain events using the cloudy sky ratio from K-band brightness temperature measurements

The Dynamics of the Madden-Julian Oscillation (DYNAMO) field campaign was conducted to improve understanding and modeling of the Madden-Julian oscillation (MJO). Observations during DYNAMO focused on atmospheric parameters important for understanding MJO initiation, including vertical moisture profiles, cloud structure, precipitation processes and the planetary boundary layer. These observations were performed using a variety of in-situ and remote sensing instruments, including the S-PolKa radar deployed by the National Center for Atmospheric Research (NCAR) and the collocated University of Miami (UM) microwave radiometer operating at 23.8 and 30.0 GHz. These instruments sampled approximately the same volumes of the atmosphere. A second microwave radiometer was deployed by the Atmospheric Radiation Measurement (ARM) Program approximately 8.5 km from the UM radiometer. These observations provided an opportunity to retrieve slant water path (SWP) and slant liquid water (SLW) from ground-based microwave radiometer measurements over a range of azimuth and elevation angles during both clear sky and cloudy conditions. The retrieved SWP and SLW will be compared to those from S-PolKa radar measurements. The goal of this study is to develop an algorithm to retrieve water vapor and liquid water from ground-based radiometer measurements.

Resolution and performance of the cloudy sky ratio using measured brightness temperatures from ground-based microwave radiometers

The field campaign of DYNAMO/CINDY2011 took place in the central equatorial Indian Ocean between September 1, 2011 and January 5, 2012. The experiment was primarily designed to improve understanding of the Madden-Julian oscillation (MJO) in the region. Observations of vertical moisture profiles, cloud structure, precipitation processes and the planetary boundary layer are necessary to improve understanding of MJO initiation. A number of remote sensing instruments, including NCARs S-PolKa (dual-wavelength Sand Ka-band) radar and the University of Miamis microwave radiometer, were deployed to estimate water vapor and cloud structure. These instruments were collocated and scanned a common volume of the troposphere at various azimuth and elevation angles. The University of Miamis microwave radiometer performed brightness temperature measurements at 23.8 GHz, affected mostly by water vapor, and at 30.0 GHz, primarily sensitive to cloud liquid water. These measurements were performed continuously to estimate slant water path and liquid water path during various weather conditions, including clear and cloudy skies, as well as precipitation of various intensities. This work focuses on classifying clear and cloudy skies as well as precipitating conditions using ground-based brightness temperature measurements during DYNAMO. To perform this classification, the cloudy sky ratio (CSR) was defined as the ratio of the brightness temperature at 23.8 GHz to that at 30.0 GHz. This technique uses the principle that during clear sky conditions brightness temperatures at 23.8 GHz are larger than those at 30.0 GHz, and the ratio varies slightly depending on the atmospheric water vapor density. However, this relationship changes when there is liquid water in the atmosphere. As the amount of liquid water in the atmosphere increases, the brightness temperatures at 23.8 GHz and 30 GHz converge to a similar value, yielding a CSR near unity. Furthermore, the presence and intensity of rainfall significantly affect the CSR value due to the amount of liquid water in the atmosphere as well as effects of scattering from hydrometeors. The performance and resolution of the CSR will be evaluated based on a quantitative comparison with simultaneous reflectivity measurements from the collocated S-PolKa radar.

Spatial resolution and accuracy of retrievals of 2D and 3D water vapor fields from ground-based microwave radiometer networks

Atmospheric water vapor is known to affect many processes, including cloud formation and precipitation. Water vapor can be measured using both in situ instruments, including radiosondes, and remote sensing instruments, including Raman lidar. Radiosondes provide measurements of atmospheric water vapor and temperature that are some of the most widely used in numerical weather prediction models. They have high vertical resolution but poor temporal and horizontal sampling since they are launched every 12 hours and radiosondes are launched regularly in the U.S. from sites at an average separation of approximately 100 km. Therefore, there is a paucity of information on the horizontal, vertical and temporal variability of water vapor and temperature. Sensitivity studies indicate that severe storm forecasting is limited by a lack of accurate observations of water vapor aloft in the lower troposphere. Therefore, the availability of fine-resolution and accurate 2D and 3D water vapor field measurements would substantially improve numerical weather prediction model initialization. Microwave radiometers have the capability to measure atmospheric water vapor and temperature at sufficiently high spatial and temporal resolution to aid in advance forecasting of the onset, timing and location of severe weather.

Trade-off between vertical resolution and accuracy in water vapor retrievals from ground-based microwave brightness temperature measurements

Thermodynamic properties of the troposphere, particularly water vapor content and temperature, change in response to physical mechanisms, including frictional drag, evaporation, transpiration, heat transfer, pollutant emission and flow modification due to terrain. The planetary boundary layer (PBL) is characterized by a greater rate of change in its thermodynamic state than higher tropospheric altitudes. Such changes in the PBL typically occur on time scales of less than one hour; whereas the upper troposphere exhibits much longer time constants. Large horizontal gradients in vertical wind speed and steep vertical gradients in water vapor and temperature in the PBL result in high-impact weather, including severe thunderstorms. Observation of these gradients in the PBL with improved vertical resolution is important for improvement of weather prediction. Additionally high vertical resolution and accuracy of measured thermodynamic profiles, especially water vapor and temperature, are important for initialization of numerical weather prediction models. Satellite remote sensing in the visible, infrared and microwave bands provides qualitative and quantitative measurements of many atmospheric properties, including cloud cover, precipitation, liquid water content and precipitable water vapor in the atmosphere above the PBL. However, its ability to characterize thermodynamic properties of the PBL is limited by the confounding factors of ground emission in microwave channels and of cloud cover in visible and IR channels, as well as limitations in the vertical resolution of the remote sensing instruments onboard the satellite. Ground-based microwave radiometers are routinely used to estimate thermodynamic profiles, but the accuracy and resolution of vertical profiles may be improperly estimated. Here a new technique has been used to improve the vertical resolution of retrieved water vapor density profiles, based on the design of the Compact Microwave Radiometer for Humidity Profiling (CMR-H) [1]. The CMR-H operates at four frequencies near the weak water vapor absorption line, namely 22.12, 22.67, 23.25, and 24.5 GHz.

A radiometer concept to retrieve the 3-D radiometric emission from atmospheric temperature and water vapor density

In recent decades, atmospheric scientists have been interested in measuring thermodynamic variables such as tropospheric water vapor and temperature with increasing temporal and spatial resolution due to their importance on the climate modeling. For this purpose, microwave radiometers have been used to measure columnar integrated water vapor. The radiative transfer equation (RTE) has been used to retrieve the contributions of individual atmospheric layers, assuming a stratified atmosphere. In recent years, significant advances have been made toward retrieval of these parameters in 2-D, 3-D and 4-D (3-D + time) distributions. This work presents a new radiometric concept to directly measure the contribution of each pixel (avoiding the use of the RTE inversion) by using pencil-beam antennas and interferometric techniques. This new approach has the potential to improve the quality of the retrieved thermodynamic variables to meet the research goals of atmospheric science.