Advanced Microwave Radiometer Research Articles

Utilization of Jason-3 Satellite Altimetry Data for Observation of TC Seroja

The Jason-3 Satellite Altimetry has two main instruments: the Poseidon-3B Altimeter and the Advanced Microwave Radiometer. The two sensors produce many output data. Satellite altimetry data commonly used to observe TC are Sea Level Anomaly (SLA) and Significant Wave Height (SWH). This research tries something new by adding three other data, namely Precipitable Water Vapor (PWV), Liquid Water Content (LWC), and Wind Speed (WS). The object of this research is TC Seroja which occurred from 2 to 12 April 2021. This research was conducted to obtain all variable’s spatial and temporal profiles. The results of this study indicate that TC Seroja causes an increase in SLA, PWV, SWH, LWC, and WS. The highest SLA was 0.495 m, SWH was 4.649 m, PWV was 0.10760 m, LWC was 2.08 kg/m2, and WS was 18.42 m/s. In addition, the spatial model for the five variables in April 2021 obtained using IDW (Inverse Distance Weighting) can also provide information on the influence of TC in various places.

Brightness Temperature and Wet Tropospheric Correction of HY-2C Calibration Microwave Radiometer Using Model-Derived Wet Troposphere Path Delay from ECMWF

The Calibration Microwave Radiometer (CMR) is a three-band radiometer deployed on the HY-2C satellite in a near-Earth orbit, and since it launched, there are few studies presented on the performance of CMR to date. Therefore, this paper focuses on providing an assessment of HY-2C CMR brightness temperature and wet troposphere correction (WTC). CMR works at 18.7 GHz, 23.8 GHz and 37 GHz in a nadir-viewing direction, aligned with the HY-2C radar altimeter. The wet troposphere path delay of the radar altimeter signal caused by water vapour and cloud liquid water content can be monitored and corrected by CMR. In this paper, guided by the concept of antenna pattern correction algorithm and a purely statistical method, we directly establish the function between the CMR antenna temperature and the model-derived WTC calculated by the European Centre from Medium-Range Weather Forecasting (ECMWF) Reanalysis data, which can obtain the brightness temperature and the WTC of CMR simultaneously. Firstly, the algorithm principle of CMR to establish the function between the antenna temperature and the model-derived WTC is introduced, and then the brightness temperature of CMR is evaluated using reference brightness temperatures of the Advanced Microwave Radiometer 2 (AMR-2) on Jason-3 satellite at crossover points. Furthermore, the performance of the CMR WTC is validated in three ways: (1) directly comparing with the colocated WTC measured by Jason-3 AMR-2, (2) directly comparing with model-derived WTC from ECMWF, which allows a rapid check at a global scale, (3) comparing the standard deviation of the Sea Surface Height (SSH) difference at crossover points using different WTC retrieval methods. The linear fit with Jason-3 brightness temperature and WTC in all non-precipitation conditions demonstrated a good agreement with Jason-3. In addition, the WTC of CMR has an obvious decrease in the standard deviation of the SSH difference compared with model-derived WTC, indicating the CMR can significantly improve the accuracy of the HY-2C SSH measurements. All the assessments indicate that the CMR performances are satisfying the expectations and fulfilling the mission requirements.

The Copernicus Sentinel-6 mission: Enhanced continuity of satellite sea level measurements from space

Given the considerable range of applications within the European Union Copernicus system, sustained satellite altimetry missions are required to address operational, science and societal needs. This article describes the Copernicus Sentinel-6 mission that is designed to provide precision sea level, sea surface height, significant wave height, inland water heights and other products tailored to operational services in the ocean, climate, atmospheric and land Copernicus Services. Sentinel-6 provides enhanced continuity to the very stable time series of mean sea level measurements and ocean sea state started in 1992 by the TOPEX/Poseidon mission and follow-on Jason-1, Jason-2 and Jason-3 satellite missions. The mission is implemented through a unique international partnership with contributions from NASA, NOAA, ESA, EUMETSAT, and the European Union (EU). It includes two satellites that will fly sequentially (separated in time by 5 years). The first satellite, named Sentinel-6 Michael Freilich, launched from Vandenburg Air Force Base, USA on 21st November 2020. The satellite and payload elements are explained including required performance and their operation. The main payload is the Poseidon-4 dual frequency (C/Ku-band) nadir-pointing radar altimeter that uses an innovative interleaved mode. This enables radar data processing on two parallel chains the first provides synthetic aperture radar (SAR) processing in Ku-band to improve the received altimeter echoes through better along-track sampling and reduced measurement noise; the second provides a Low Resolution Mode that is fully backward-compatible with the historical reference altimetry measurements, allowing a complete inter-calibration between the state-of-the-art data and the historical record. A three-channel Advanced Microwave Radiometer for Climate (AMRC) provides measurements of atmospheric water vapour to mitigate degradation of the radar altimeter measurements. The main data products are explained and preliminary in-orbit Poseidon-4 altimeter data performance data are presented that demonstrate the altimeter to be performing within expectations.

RF and Electronics Design of the Compact Ocean Wind Vector Radiometer

The Compact Ocean Wind Vector Radiometer (COWVR) was developed at the Jet Propulsion Laboratory as a proof of concept technology demonstration mission for the Air Force. COWVR is a fully polarimetric imaging radiometer system operating at 18.7, 23.8, and 33.9 GHz . Its receiver subsystem is based on the Jason-3 advanced microwave radiometer, which was launched in early 2016 and is currently in operation. Its enabling components are presented in this article, including the phase-matched waveguide components, noise injection, receivers, and polarimetric backend units.

Reliable and Stable Radiometers for Jason-3

The Jason-3 mission employs the Advanced Microwave Radiometer (AMR) to provide a tropospheric path delay measurement in support of ocean altimetry. NOAA and EUMETSAT are Jason-3 lead agencies with CNES and NASA/JPL providing implementation support. Jason-3 continues the measurements of TOPEX/Poseidon [1] , [2] , Jason-1, and Ocean Surface Topography Mission (OSTM)/Jason-2 supporting a multidecadal ocean topography studies, including ocean circulation, climate change, hurricane intensity forecasts, and sea level change. The objective of the Jason-3 AMR is to measure the columnar water vapor in the path of the Poseidon radar altimeter (CNES instrument) to correct for water in the atmospheric path delay in the altimeter range measurement. In this paper, the design and performance of AMR are described along with the changes made compared to the predecessor Jason-2 instrument to reduce development risks and improve the stability of the AMR instrument.

Assessing the Measurement Consistency Between the Jason-2/AMR and SARAL/AltiKa/DFMR Microwave Radiometers Using Simultaneous Nadir Observations

SARAL/AltiKa has a Dual Frequency Microwave Radiometer (DFMR), and Jason-2 has an Advanced Microwave Radiometer (AMR). Both microwave radiometer sensors include a 23.8 GHz primary water sensing channel. The measurement consistencies between DFMR and AMR are important for establishing a consistent altimetry data set between SARAL/AltiKa and Jason-2 in order to accurately assess sea level rise in a long-term time series. This study investigates the measurement consistency in the 23.8 GHz channel between DFMR and AMR at the Simultaneous Nadir Overpasses (SNO's) between the two satellites and also at coldest ocean brightness temperature locations. Preliminary results show that while both instruments show no significant trends over the one year since the launch of SARAL, a consistent relative bias of 2.88 K (DFMR higher than AMR) with a standard deviation of 0.98 K is observed. The relative bias at the lowest brightness temperature from the SNO method (-3.82 K) is consistent with that calculated from coldest ocean method (-3.74 K). The relative bias exhibits strong latitude (and scene temperature) dependency, changing from -3.82 K at high latitudes to -0.92 K near the equator. There also exists an asymmetry between the northern and southern hemisphere. The relative bias increases toward the lower end of brightness temperature.

SARAL/AltiKa Wet Tropospheric Correction: In-Flight Calibration, Retrieval Strategies and Performances

The SARAL/AltiKa mission is a complement of the Jason altimeter series. A two-channels (23.8 GHz and 37 GHz) microwave radiometer (MWR) is combined to the altimeter in order to correct the altimeter range for the excess path delay (referred as WTC for wet tropospheric correction. First, the in-flight calibration of AltiKa MWR is assessed from a systematic comparison to other radiometers using a complete set of metrics (comparison to simulations and over geophysical targets). Then the “mixed” empirical approach successfully used for Envisat shows nonoptimal performances for the WTC retrieval. In order to find the potential sources of issues, this method is compared to a purely empirical relationship established between measured brightness temperatures (TB) and altimeter backscattering coefficient () on one hand and modeled WTC on the other hand. Various retrieval configurations for both AltiKa MWR and advanced microwave radiometer (AMR) on Jason-2, are for the first time systematically compared with respect to their performances against the variance of sea surface height differences at crossovers. Finally, the issues on the “mixed” approach are attributed to the differences between simulated and measured at Ka-band. Now, a configuration of the empirical approach proved to have performances closed to what is initially expected with the “mixed” approach.

Improved wet path delays for all ESA and reference altimetric missions

The wet tropospheric correction (WTC) is still a significant error source in most altimetric products. For studies such as sea level change, as those performed in the scope of the ESA Sea Level Climate Change Initiative (SL_cci) project, the use of uniform and consistent WTC datasets are of major importance. For this purpose, a set of improved WTC, using the Global Navigation Satellite System (GNSS) derived Path Delay (GPD) algorithm, was envisaged for the main six altimetric missions: the so-called reference missions (TOPEX/Poseidon, Jason-1 and Jason-2) and the three ESA missions (ERS-1, ERS-2 and Envisat). The GPD methodology is based on the combination of wet path delays derived from zenith total delays calculated at a network of coastal GNSS stations and valid microwave radiometer (MWR) measurements at altimeter nearby points. At each altimeter point with an invalid MWR value, the WTC is estimated from the set of observations, along with the associated mapping error, using a linear space-time objective analysis technique that takes into account the spatial and temporal variability of the WTC field and the accuracy of each data set used. In the absence of observations, tropospheric delays from the European Centre for Medium-range Weather Forecasts (ECMWF) ReAnalysis (ERA) Interim model are adopted. Originally designed to improve the WTC in the coastal zone, the GPD evolved to include the global ocean, correcting for land and ice contamination in the MWR footprint, or spurious measurements due to e.g. instrument malfunction. This paper presents an overview of the GPD implementation for the afore-mentioned six altimetric missions. The GPD products have been validated by comparison with the WTC adopted as the reference correction by the Archiving, Validation, and Interpretation of Satellite Data in Oceanography (AVISO): the so-called composite correction (Comp) for all missions except Jason-2, for which the version D of the Geophysical Data Records (GDR-D) Advanced Microwave Radiometer (AMR) WTC is adopted. Various sea level anomaly (SLA) statistical analyses have been performed and are summarised in this paper: differences in SLA variance calculated along satellite tracks and at crossovers; SLA variance difference function of distance from the coast or function of latitude. Results show that the GPD WTC evidence a very significant improvement with respect to the Comp correction, particularly at polar and coastal regions, for all ESA and TOPEX/Poseidon missions. For the last, the impact is particularly significant in the second part of the mission, since detected anomalies present in the TOPEX Microwave Radiometer products are corrected by the algorithm. For Jason-1 and Jason-2, some improvements are observed in the coastal regions, although globally not very significant, particularly for Jason-2. This is attributed to the good performance of the WTC present in the most recent Jason-1 and Jason-2 products. The GPD WTC constitutes a coherent dataset of global and continuous corrections, for most missions a major improvement with respect to the baseline MWR and the Comp wet tropospheric corrections.

Retrieval Models of Water Vapor and Wet Tropospheric Path Delay for the HY-2A Calibration Microwave Radiometer

Abstract This paper focuses on the development and validation of retrieval models of water vapor (WV) and wet tropospheric path delay (PD) for the calibration microwave radiometer (CMR) on board the first ocean dynamic environment satellite of China—Haiyang-2A (HY-2A). The reference data are those of Jason-1 microwave radiometer (JMR) and Jason-2 advanced microwave radiometer (AMR). The crossover points of the HY-2A and Jason-1/2 satellite tracks are extracted, and the data pairs at these points are divided into fitting and validation datasets. The retrieval models of WV and PD are built for the CMR using the fitting dataset and genetic algorithm, and validated using the validation dataset. The validation shows that the results of the retrieval models are consistent with the JMR and AMR data, and the root-mean-square differences of WV and PD are 1.86 kg m−2 and 11.4 mm, respectively. Finally, the retrieved results from the CMR brightness temperature along-track data using the retrieval models and the AMR along-track data are gridded by the inverse distance weighted method. Their monthly-mean spatial distributions are compared in order to investigate the applicability of the retrieval models globally, namely, beyond locations of the data pairs in the validation dataset. The comparison shows that the retrieval models are applicable in most open ocean areas, and that the latitude and temporal inhomogeneity of the crossover point distribution in the fitting dataset does not lead to obvious latitude and temporal inhomogeneity in the gridded data.

The preliminary cross-calibration of the HY-2A calibration microwave radiometer with the Jason-1/2 microwave radiometers

This article focuses on the cross-calibration of the Haiyang-2A (HY-2A) calibration microwave radiometer (CMR) with the Jason-1 microwave radiometer (JMR) and the Jason-2 advanced microwave radiometer (AMR). The temporal trends in the CMR brightness temperatures (BTs) are compared with those of the JMR and the AMR in terms of period-averaged BT (averaged over each satellite cycle). The differences between them are observed and then corrected. The data pairs at the crossover points of HY-2A and Jason-1/2 are collected. The differences between the BTs of the CMR and those of the JMR and the AMR are further reduced by a latitude correction. The validation results show that after the time and latitude corrections, the root mean square values of the BT differences are clearly reduced by about 0.8, 0.8, and 0.6 K in the three channels, respectively. Based on the time and latitude corrected data, seven kinds of retrieval model (of vapour-induced wet tropospheric path delay, water vapour, cloud liquid, and sea surface wind speed) are built for the CMR. The results of the retrieval models based on the artificial neural networks show smaller differences from the JMR and AMR data than those of the other models.

Prelaunch calibration and primary results from in-orbit calibration of the atmospheric correction microwave radiometer (ACMR) on the HY-2A satellite of China

The atmospheric correction microwave radiometer (ACMR) is one of the main payloads for correcting atmospheric path delay in the radar altimeter on the Haiyang-2A (HY-2A) satellite. The ACMR is a three-band microwave radiometer operating at 18.7, 23.8, and 37.0 GHz. Calibration of the ACMR is important for applying its measurements to correct for atmospheric effects on the HY-2A altimeter signal transmission in the air. Therefore, a detailed introduction to the principles and specifications of the ACMR system is given first. The thermal vacuum calibration method of the ACMR is discussed and analysed, and the microwave transfer functions and related coefficients are given, especially the nonlinear coefficients derived from a test for correcting nonlinear responses between the input of antenna temperature and the output of voltage at each channel of the ACMR. Furthermore, antenna pattern correction algorithms for removing the effects of side lobe and cross-polarization are derived and their coefficients are used for in-orbit data processing. Primary calibration results are given by comparing with the similar spaceborne Jason microwave radiometer (JMR) on the Jason-1 satellite and with the advanced microwave radiometer (AMR) on Jason-2. The results of this comparison show that the data from the ACMR match well to those from the JMR and AMR.

Maintaining the Long-Term Calibration of the Jason-2/OSTM Advanced Microwave Radiometer Through Intersatellite Calibration

A method is applied to maintain the long-term calibration of a microwave radiometer through intersatellite calibration and is used to mitigate an observed calibration drift of the Advanced Microwave Radiometer (AMR) on Jason-2/Ocean Surface Topography Mission. The AMR provides a correction for the wet tropospheric path delay (PD) of the radar altimeter signal, and it is critical that any drift in the radiometer be estimated and removed to enable studies of global mean sea-level variability. The intersatellite calibration method transfers the long-term calibration from other satellite microwave radiometers using a transfer function to map the other sensor's brightness temperature (TB) observations to those of the AMR. Intersensor mapping functions are derived separately for ocean observations and observations over the Amazon rainforest. This provides a warm and cold TB calibration reference to enable the distinction between long-term gain and offset drifts. A database of co-incident observations is generated between the AMR and conically scanning microwave sensors, namely, AMSR-E, TMI, and SSMIS. Monthly averaged differences are found between the AMR and the AMR equivalent TBs computed from the reference sensors. The apparent change in the AMR calibration determined from the three reference sensors is intercompared between the sensors and compared to that determined using natural on-Earth references. It is found that apparent trends in the AMR TBs between the reference sensors and the natural on-Earth references agree within a month to better than 0.4 K. The AMR 18.7- and 23.8-GHz channels are found to be stable to 0.5 K over the first three years of the mission, and the calibration 34.0-GHz channel is found to drift downward by approximately 6 K. In all channels, the calibration change is determined to be a series of offset jumps (independent of TB). These calibration changes in each AMR channel are estimated and removed using the comparisons to the reference sensors. The uncertainty in the PD long-term stability after recalibration is estimated to be less than 0.5 mm/year from July 2008 to August 2011.

Partitioning of cloud water and rainwater content by ground‐based observations with the Advanced Microwave Radiometer for Rain Identification (ADMIRARI) in synergy with a micro rain radar

Cloud and rain liquid water path and total water vapor are retrieved simultaneously from passive microwave observations with the multifrequency dual‐polarized Advanced Microwave Radiometer for Rain Identification (ADMIRARI). A data set of linearly polarized brightness temperatures has been collected at 30° elevation angle together with slant radar reflectivity profiles at 24.1 GHz from a micro rain radar (MRR) pointing into the same viewing direction. The slant path integrated values are retrieved via a Bayesian inversion approach, the quality of which is evaluated by a simulation‐based retrieval sensitivity study. The algorithm includes a physical constraint by taking into account the rain column structural information from the MRR observations. Measurements and derived path‐integrated water component estimates from 23 August to 12 November 2008, obtained in Cabauw, Netherlands, are analyzed. During raining cloud conditions the zenith‐normalized root‐mean‐square error for water vapor, cloud liquid water path, and rain liquid water path are, on average, estimated to 1.54 kg m−2, 144 g m−2, and 52 g m−2, respectively. On the basis of these results, long‐term estimated distributions of cloud water–rainwater partitioning for midlatitude precipitating clouds are presented for the first time as obtained by a ground‐based radiometer.

Monitoring the Jason-2/AMR Stability Using SNO Observations from AMSU on MetOp-A

The microwave radiometers aboard the Jason satellites for altimetry missions are a key component of the Jason system, providing important measurements for water vapor correction, which is the most variable path delay correction in the altimeter measurement system. Unfortunately, these radiometers have exhibited on-orbit calibration drifts, step jumps, and other types of irregularities that can result in height rate errors comparable to 1 mm/yr, the stability requirement for measuring global mean sea level rise. Therefore, the calibration accuracy and short- and long-term stability of these radiometers are critical for the Jason mission to meet the stringent requirements. This study investigates the stability of the Jason-2 Advanced Microwave Radiometer (AMR) relative to the Advanced Microwave Sounding Unit (AMSU) on the MetOp-A satellite using the Simultaneous Nadir Overpass (SNO) time series method. Preliminary results show that using the AMSU as a stable reference, which has a demonstrated stability of better than 0.5 K per decade in previous studies, the Jason radiometer stability can be reliably monitored at 0.1 K per year level. The method has successfully detected a downward trend in the 23.8 GHz AMR channel (the primary one for detecting atmospheric water vapor) relative to the same AMSU channel for about −0.48 K per year since its launch on June 20, 2008, until February 2010, which is likely caused by AMR calibration problems during the period.

Calibration and Validation of the Jason-2/OSTM Advanced Microwave Radiometer Using Terrestrial GPS Stations

We use estimates of zenith tropospheric delay from terrestrial Global Positioning System (GPS) stations to validate the wet path-delay measurements from the Jason-2/Ocean Surface Topography Mission (OSTM) Advanced Microwave Radiometer (AMR). We validate the AMR wet path-delay measurements provided in the version “T” Geophysical Data Records (GDRs) and those generated using a recently developed coastal algorithm that will be applied to the version “C” GDRs. The new coastal algorithm reduces the variance of the GPS-AMR differences by as much as 28% within 25 km of land. This algorithm also facilitates open-ocean measurement accuracies as close to land as 15 km (as opposed to 25 km). We perform AMR/GPS comparisons with three different troposphere-mapping functions for the GPS-based estimates: Niell, Global, and Vienna. The choice of mapping function has minimal impact on our results, although the Vienna mapping function provided the smallest variance in the AMR–GPS differences.

Understanding three-dimensional effects in polarized observations with the ground-based ADMIRARI radiometer during the CHUVA campaign

[1] Measurements of down‐welling microwave radiation from raining clouds performed with the Advanced Microwave Radiometer for Rain Identification (ADMIRARI) radiometer at 10.7–21–36.5 GHz during the Global Precipitation Measurement Ground Validation “Cloud processes of the main precipitation systems in Brazil: A contribution to cloud resolving modeling and to the Global Precipitation Measurement” (CHUVA) campaign held in Brazil in March 2010 represent a unique test bed for understanding three‐dimensional (3D) effects in microwave radiative transfer processes. While the necessity of accounting for geometric effects is trivial given the slant observation geometry (ADMIRARI was pointing at a fixed 30° elevation angle), the polarization signal (i.e., the difference between the vertical and horizontal brightness temperatures) shows ubiquitousness of positive values both at 21.0 and 36.5 GHz in coincidence with high brightness temperatures. This signature is a genuine and unique microwave signature of radiation side leakage which cannot be explained in a 1D radiative transfer frame but necessitates the inclusion of three‐dimensional scattering effects. We demonstrate these effects and interdependencies by analyzing two campaign case studies and by exploiting a sophisticated 3D radiative transfer suited for dichroic media like precipitating clouds.

A Novel Near-Land Radiometer Wet Path-Delay Retrieval Algorithm: Application to the Jason-2/OSTM Advanced Microwave Radiometer

An algorithm is developed to retrieve wet tropospheric path delay (PD) near land from a satellite microwave radiometer to improve coastal altimetry studies. Microwave radiometers are included on ocean altimetry missions to retrieve the wet PD, but their performance has been optimized for retrievals in the open ocean. Near land, the radiometer footprint contains a mixture of radiometrically warm land and radiometrically cold ocean. Currently, the radiometer retrievals in the coastal region are flagged as invalid since large errors result when the open-ocean retrieval algorithm is applied to mixed land/ocean scenes. The PD retrieval algorithm developed in this paper is applicable to both open-ocean and mixed land-ocean scenes, thus enabling retrievals in the coastal zone. The performance of the algorithm is demonstrated with detailed simulations and application to measurements from the Advanced Microwave Radiometer on the Jason-2/Ocean Surface Topography Mission. The algorithm error is estimated to be less than 0.8 cm up to 15 km from land, less than 1.0 cm within 10 km from land, less than 1.2 cm within 5 km from land, and less than 1.5 cm up to the coastline.

Characterization of Precipitating Clouds by Ground-Based Measurements with the Triple-Frequency Polarized Microwave Radiometer ADMIRARI

AbstractA groundbreaking new-concept multiwavelength dual-polarized Advanced Microwave Radiometer for Rain Identification (ADMIRARI) has been built and continuously operated in two field campaigns: the Convective and Orographically Induced Precipitation Study (COPS) and the European Integrated Project on Aerosol Cloud Climate Air Quality Interactions (EUCAARI). The radiometer has 6 channels working in horizontal and vertical polarization at 10.65, 21.0, and 36.5 GHz, and it is completely steerable both in azimuth and in elevation. The instrument is suited to be operated in rainy conditions and is intended for retrieving simultaneously water vapor, rain, and cloud liquid water paths. To this goal the authors implemented a Bayesian retrieval scheme based on many state realizations simulated by the Goddard Cumulus Ensemble model that build up a prior probability density function of rainfall profiles. Detailed three-dimensional radiative transfer calculations, which account for the presence of nonspherical particles in preferential orientation, simulate the downwelling brightness temperatures and establish the similarity of radiative signatures and thus the probability that a given profile is actually observed. Particular attention is devoted to the sensitivity of the ADMIRARI signal to 3D effects, raindrop size distribution, and axial ratio parameterizations. The polarization and multifrequency signals represent key information to separate the effects introduced by non-Rayleigh scatterers and to separate rainwater (r-LWP) from the cloud water component (c-LWP). Long-term observations demonstrate that observed brightness temperatures and polarization differences can be well interpreted and reproduced by the simulated ones for all three channels simultaneously. Rough estimates of r-LWP derived from collocated observations with a micro rain radar confirm the rain/no rain separation and the variability trend of r-LWP provided by the radiometer-based retrieval algorithm. With this work the authors demonstrate the potential of ADMIRARI to retrieve information about the rain/cloud partitioning for midlatitude precipitation systems; future studies with this instrument will provide crucial information on rain efficiency of clouds for cloud modelers that might lead toward a better characterization of rain processes.

Rain Observations by a Multifrequency Dual-Polarized Radiometer

During the Convective and Orographically Induced Precipitation Study, advanced microwave radiometer for rain identification has continuously acquired measurements at the Atmospheric Radiation Measurement Mobile Facility in the Black Forest from the beginning of August until December 2007. The radiometer has six channels measuring in horizontal and vertical polarizations at 10.65, 21.0, and 36.5 GHz. Rainy events have been selected out of the entire database according to collocated gauges and, subsequently, analyzed. Measured brightness temperatures and (vertical-horizontal) polarization differences are interpreted by comparing with radiative transfer simulations, which account for the presence of nonspherical particles in preferential orientation. Measurements confirm the importance of the polarization signal for separating the effect introduced by non-Rayleigh scatterers and, therefore, the rain from the cloud component. More quantitative interpretation of the signal requires a better understanding of the role played by melting particles and an identification of the 3-D structure of the precipitating system under observation. Both aspects will be tackled in the near future by exploiting the synergy with a coinstalled micro rain radar.

Validation of western and eastern Pacific rainfall estimates from the TRMM PR using a radiative transfer model

Rainfall estimates from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) facility algorithm over the eastern Pacific are lower than those from the TRMM Microwave Imager (TMI) facility algorithm and a PR‐consistent advanced microwave radiometer algorithm, while they are in good agreement over the western Pacific. We investigate the consistency between TMI‐observed brightness temperatures (TBs) for the 19 GHz channel and those simulated from the PR rainfall estimates using a radiative transfer model. Discrepancies between observed TBs and simulated TBs from the PR are larger for the eastern Pacific than for the western Pacific, indicating that PR underestimates rainfall over the eastern Pacific. It is hypothesized that drop size distributions (DSDs) in the eastern Pacific have stronger maritimity (i.e., more small to medium sized raindrops) than the initial DSD model of the PR algorithm, representative of the “data‐rich” western Pacific, leading to underestimation of rain by the PR. Differences in the adjustable parameter of the PR algorithm, implying changes in the DSD, and the vertical structure of PR‐observed reflectivity over the western and eastern Pacific support the hypothesis.