Cross-track Scanning Research Articles

Assessment of Ground-Reference Data and Validation of the H-SAF Precipitation Products in Brazil

The uncertainties associated with rainfall estimates comprise various measurement scales: from rain gauges and ground-based radars to the satellite rainfall retrievals. The quality of satellite rainfall products has improved significantly in recent decades; however, such algorithms require validation studies using observational rainfall data. For this reason, this study aims to apply the H-SAF consolidated radar data processing to the X-band radar used in the CHUVA campaigns and apply the well established H-SAF validation procedure to these data and verify the quality of EUMETSAT H-SAF operational passive microwave precipitation products in two regions of Brazil (Vale do Paraíba and Manaus). These products are based on two rainfall retrieval algorithms: the physically based Bayesian Cloud Dynamics and Radiation Database (CDRD algorithm) for SSMI/S sensors and the Passive microwave Neural network Precipitation Retrieval algorithm (PNPR) for cross-track scanning radiometers (AMSU-A/AMSU-B/MHS sensors) and for the ATMS sensor. These algorithms, optimized for Europe, Africa and the Southern Atlantic region, provide estimates for the MSG full disk area. Firstly, the radar data was treated with an overall quality index which includes corrections for different error sources like ground clutter, range distance, rain-induced attenuation, among others. Different polarimetric and non-polarimetric QPE algorithms have been tested and the Vulpiani algorithm (hereafter, R q 2 V u 15 ) presents the best precipitation retrievals when compared with independent rain gauges. Regarding the results from satellite-based algorithms, generally, all rainfall retrievals tend to detect a larger precipitation area than the ground-based radar and overestimate intense rain rates for the Manaus region. Such behavior is related to the fact that the environmental and meteorological conditions of the Amazon region are not well represented in the algorithms. Differently, for the Vale do Paraíba region, the precipitation patterns were well detected and the estimates are in accordance with the reference as indicated by the low mean bias values.

On off-nadir wind retrieval over the sea surface using APR-2 or similar radar geometry

ABSTRACTIn some cases, nadiral wind retrieval algorithms are not applicable for wind measurements due to the specificity of a radar instrument measuring geometry or its mounting on aircraft, and so off-nadir backscattering measurements can only be performed. In this paper, a method for off-nadir wind retrieval over the sea based on the sea-surface backscattering measurements with the Airborne Precipitation Radar-2 or similar radar measuring geometry has been proposed. The study is based on a theory of the quasi-specular microwave backscattering from the sea surface. An anisotropic water surface approach is considered. The wind vector is retrieved from the system of equations for measured normalized radar cross sections (NRCS) by using the relationships between the speed of the sea-surface wind and the standard deviations of the sea-surface slopes along the up- and cross-wind directions. A wind vector recovery with the cross-track scanning measurement geometry has been simulated. The maximum errors of the wind speed and direction estimations are within typical errors of wind measurements by a scatterometer. A maximum altitude of the method applicability for this geometry has been defined. Recommendations to perform the measurements have been described in detail.

In-orbit verification of microwave humidity sounder spectral channels coregistration using the moon

In-orbit verification of the coregistration of channels in a scanning microwave or infrared radiometer can in principle be done during normal in-orbit operation, using the regular events of lunar intrusion in the instrument cold space calibration view. A technique of data analysis based on best fit of data across lunar intrusions has been used to check the mutual alignment of the spectral channels of the microwave humidity sounder (MHS) instrument. MHS is a cross-track scanning radiometer in the millimeter-wave range flying on EUMETSAT and NOAA polar satellites, used operationally for the retrieval of atmospheric parameters in numerical weather prediction and nowcasting. This technique does not require any special operation or maneuver and only relies on the analysis of data from the nominal scanning operation. The coalignment of sounding channels and window channels can be evaluated by this technique, which would not be possible using Earth landmarks, due to the absorption effect of the atmosphere. The analysis reported shows an achievable accuracy below 0.5 mrad against a beam width at 3 dB and spatial sampling interval of about 20 mrad. In-orbit results for the MHS instrument on Metop-B are also compared with the prelaunch instrument characterization, showing a good correlation.

Daily precipitation estimation through different microwave sensors: Verification study over Italy

The accurate estimation of rainfall from remote sensing is of paramount importance for many applications as, for instance, the mitigation of natural hazards like floods, droughts, and landslides. Traditionally, microwave observations in the frequency between 10 and 183GHz are used for estimating rainfall based on the direct interaction of radiation with the hydrometeors within precipitating clouds in a so-called top-down approach. Recently, a bottom-up approach was proposed that uses satellite soil moisture products derived from microwave observations (<10GHz) for the estimation of accumulated rainfall amounts. The integration of the bottom-up and top-down approaches has large potential for providing high accurate rainfall estimates exploiting their different and complementary nature.In this study, we perform a long-term (3years) assessment of different satellite rainfall products exploiting the full range of microwave frequencies over Italy. Specifically, the integration of two top-down algorithms (CDRD, Cloud Dynamics and Radiation Database, and PNPR, Passive microwave Neural network Precipitation Retrieval) for estimating rainfall from conically and cross-track scanning radiometers, and one bottom-up algorithm (SM2RAIN) applied to the Advanced SCATterometer soil moisture product is carried out. The performances of the products, individually and merged together, are assessed at daily time scale. The integration of top-down and bottom-up approaches provides the highest performance both in terms of continuous and categorical scores (i.e., median correlation coefficient and root mean square error values equal to 0.71 and 6.62mm, respectively). In such a combination, the limitations of the two approaches are compensated allowing a better estimation of ground accumulated rainfall through SM2RAIN while, overcoming the limitations of rainfall estimation for intense events during wet conditions through CDRD-PNPR product. The accuracy and the reliability of the merged product open new possibilities for their testing in hydrological applications, such as the monitoring and prediction of floods and droughts over large areas, including regions where ground-based measurements are sparse or not available.

The new Passive microwave Neural network Precipitation Retrieval (PNPR) algorithm for the cross-track scanning ATMS radiometer: description and verification study over Europe and Africa using GPM and TRMM spaceborne radars

Abstract. The objective of this paper is to describe the development and evaluate the performance of a completely new version of the Passive microwave Neural network Precipitation Retrieval (PNPR v2), an algorithm based on a neural network approach, designed to retrieve the instantaneous surface precipitation rate using the cross-track Advanced Technology Microwave Sounder (ATMS) radiometer measurements. This algorithm, developed within the EUMETSAT H-SAF program, represents an evolution of the previous version (PNPR v1), developed for AMSU/MHS radiometers (and used and distributed operationally within H-SAF), with improvements aimed at exploiting the new precipitation-sensing capabilities of ATMS with respect to AMSU/MHS. In the design of the neural network the new ATMS channels compared to AMSU/MHS, and their combinations, including the brightness temperature differences in the water vapor absorption band, around 183 GHz, are considered. The algorithm is based on a single neural network, for all types of surface background, trained using a large database based on 94 cloud-resolving model simulations over the European and the African areas. The performance of PNPR v2 has been evaluated through an intercomparison of the instantaneous precipitation estimates with co-located estimates from the TRMM Precipitation Radar (TRMM-PR) and from the GPM Core Observatory Ku-band Precipitation Radar (GPM-KuPR). In the comparison with TRMM-PR, over the African area the statistical analysis was carried out for a 2-year (2013–2014) dataset of coincident observations over a regular grid at 0.5° × 0.5° resolution. The results have shown a good agreement between PNPR v2 and TRMM-PR for the different surface types. The correlation coefficient (CC) was equal to 0.69 over ocean and 0.71 over vegetated land (lower values were obtained over arid land and coast), and the root mean squared error (RMSE) was equal to 1.30 mm h−1 over ocean and 1.11 mm h−1 over vegetated land. The results showed a slight tendency to underestimate moderate to high precipitation, mostly over land, and overestimate moderate to light precipitation over ocean. Similar results were obtained for the comparison with GPM-KuPR over the European area (15 months, from March 2014 to May 2015 of coincident overpasses) with slightly lower CC (0.59 over vegetated land and 0.57 over ocean) and RMSE (0.82 mm h−1 over vegetated land and 0.71 mm h−1 over ocean), confirming a good agreement also between PNPR v2 and GPM-KuPR. The performance of PNPR v2 over the African area was also compared to that of PNPR v1. PNPR v2 has higher R over the different surfaces, with generally better estimation of low precipitation, mostly over ocean, thanks to improvements in the design of the neural network and also to the improved capabilities of ATMS compared to AMSU/MHS. Both versions of PNPR algorithm have shown a general consistency with the TRMM-PR.

Development of a Low-Cost Hyperspectral Whiskbroom Imager Using an Optical Fiber Bundle, a Swing Mirror, and Compact Spectrometers

Both inductive and deductive approaches based on hyperspectral remote sensing data require abundant observation opportunities under various conditions due to the high dimensionality of the hyperspectral data. With the recent advent of low-cost lightweight unmanned aerial vehicles (UAVs), UAVs for low-altitude aerial observation are becoming commodities rather than special equipment. Therefore, the appearance of low-cost hyperspectral imagers is anticipated for aerial hyperspectral sensing via UAVs. In this paper, we describe the development of a low-cost hyperspectral imager based on a whiskbroom scanning mechanism. The main components of the developed system include an optical fiber bundle, a swing mirror, and compact spectrometers. An image formed by an objective lens is quantized into a set of pixels by a two-dimensional array of quartz fiber-optic cables at one end of an optical fiber bundle. The quantized image travels to the other end of the bundle, inside of which a swing mirror is used for cross-track scanning. The light in each pixel of the quantized image is then measured using a compact spectrometer. Calculated reflectances in close-range measurements of color checkered patterns were spatially and spectrally accurate. In an aerial measurement of a coastal area from a 20-m altitude via a lightweight UAV, a hyperspectral image with a 0.5-m spatial resolution and an 8-m swath was acquired. Based on pattern matching using cross correlation, classification of three classes of marine macrophyte beds, agar, coralline, and sand realized overall accuracies of 0.755 (diffuse dominant illumination) and 0.719 (direct sunlight dominant illumination).

JPSS-1 VIIRS Radiometric Characterization and Calibration Based on Pre-Launch Testing

The Visible Infrared Imaging Radiometer Suite (VIIRS) on-board the first Joint Polar Satellite System (JPSS) completed its sensor level testing on December 2014. The JPSS-1 (J1) mission is scheduled to launch in December 2016, and will be very similar to the Suomi-National Polar-orbiting Partnership (SNPP) mission. VIIRS instrument has 22 spectral bands covering the spectrum between 0.4 and 12.6 μm. It is a cross-track scanning radiometer capable of providing global measurements twice daily, through observations at two spatial resolutions, 375 m and 750 m at nadir for the imaging and moderate bands, respectively. This paper will briefly describe J1 VIIRS characterization and calibration performance and methodologies executed during the pre-launch testing phases by the government independent team to generate the at-launch baseline radiometric performance and the metrics needed to populate the sensor data record (SDR) Look-Up-Tables (LUTs). This paper will also provide an assessment of the sensor pre-launch radiometric performance, such as the sensor signal to noise ratios (SNRs), radiance dynamic range, reflective and emissive bands calibration performance, polarization sensitivity, spectral performance, response-vs-scan (RVS), and scattered light response. A set of performance metrics generated during the pre-launch testing program will be compared to both the VIIRS sensor specification and the SNPP VIIRS pre-launch performance.

Error Analysis of a Conceptual Cloud Doppler Stereoradar with Polarization Diversity for Better Understanding Space Applications

AbstractAn error budget analysis is performed for retrieval of along-track winds based on the design of a spaceborne Doppler radar using polarization diversity. The analysis is conducted within the framework of a case study of an Atlantic hurricane. The proposed concept consists of either a Ka-band or W-band stereoradar mounted on an LEO satellite equipped with both nadir- and forward-viewing beams and with an optional cross-scanning capability. Such a radar design is intended for observing the microphysical and dynamical structures of cloud systems, including disturbed mesoscale convective systems. Because of the high winds involved in such weather phenomena and because of the Doppler fading introduced by platform motion, polarization diversity is adopted. The simulation framework enables a breakdown of the Doppler velocity measurement error budget into its most important components, that is, nonuniform beamfilling, multiple scattering, and inherent signal noise. The impact of each of these error terms on the total error depends on the adopted integration length, the number of scanned tracks, and the specifics of the radar. This allows for optimally selecting an integration length suitable for minimizing the total rms velocity error. The analysis shows that the use of a large antenna could achieve impressive measurement accuracy of the along-line-of-sight wind velocities. Notably, this would be the case for integration lengths longer than 3 km, even when carrying out cross-track scanning for up to 17 separate tracks. Examples of retrieved along-track wind fields also reveal that the large antenna configurations are capable of identifying and quantifying the foremost dynamic features (e.g., vertical wind shear and convergence/divergence regions).

Prelaunch Radiometric Characterization and Calibration of the S-NPP VIIRS Sensor

The Visible Infrared Imaging Radiometer Suite (VIIRS) is a key instrument onboard the Suomi National Polar-orbiting Partnership (S-NPP) spacecraft that was launched on October 28, 2011. VIIRS is designed to provide top of the atmosphere radiometric measurements and imaging of the entire planet Earth twice daily. It is a wide-swath (3040 km) cross-track scanning radiometer with spatial resolutions of 375 and 750 m at nadir for imaging and moderate bands, respectively. It has 22 spectral bands covering the spectrum between 0.4 and 12.5 μm, including 15 reflective solar bands and 7 thermal emissive bands. VIIRS observations are used to generate 22 environmental data records used by various operational applications and for climate research. This paper describes the prelaunch radiometric calibration and characterization methodologies used by the NASA VIIRS Characterization Support Team, including performance assessments for the reflective and emissive band radiometric calibration, the signal-to-noise ratios, dual gain transition, and dynamic range. Other aspects of the sensor performance such as scattered light response, response versus scan angle, polarization sensitivity, relative spectral response, and crosstalk will also be briefly described. A comprehensive set of performance metrics generated during the prelaunch testing program will be compared to the sensor requirements, and a list of lessons learned will be presented to enhance testing and performance assessment for future Joint Polar-Orbiting Satellite System VIIRS sensors.

The Passive microwave Neural network Precipitation Retrieval (PNPR) algorithm for AMSU/MHS observations: description and application to European case studies

Abstract. The purpose of this study is to describe a new algorithm based on a neural network approach (Passive microwave Neural network Precipitation Retrieval – PNPR) for precipitation rate estimation from AMSU/MHS observations, and to provide examples of its performance for specific case studies over the European/Mediterranean area. The algorithm optimally exploits the different characteristics of Advanced Microwave Sounding Unit-A (AMSU-A) and the Microwave Humidity Sounder (MHS) channels, and their combinations, including the brightness temperature (TB) differences of the 183.31 channels, with the goal of having a single neural network for different types of background surfaces (vegetated land, snow-covered surface, coast and ocean). The training of the neural network is based on the use of a cloud-radiation database, built from cloud-resolving model simulations coupled to a radiative transfer model, representative of the European and Mediterranean Basin precipitation climatology. The algorithm provides also the phase of the precipitation and a pixel-based confidence index for the evaluation of the reliability of the retrieval. Applied to different weather conditions in Europe, the algorithm shows good performance both in the identification of precipitation areas and in the retrieval of precipitation, which is particularly valuable over the extremely variable environmental and meteorological conditions of the region. The PNPR is particularly efficient in (1) screening and retrieval of precipitation over different background surfaces; (2) identification and retrieval of heavy rain for convective events; and (3) identification of precipitation over a cold/iced background, with increased uncertainties affecting light precipitation. In this paper, examples of good agreement of precipitation pattern and intensity with ground-based data (radar and rain gauges) are provided for four different case studies. The algorithm has been developed in order to be easily tailored to new radiometers as they become available (such as the cross-track scanning Suomi National Polar-orbiting Partnership (NPP) Advanced Technology Microwave Sounder (ATMS)), and it is suitable for operational use as it is computationally very efficient. PNPR has been recently extended for applications to the regions of Africa and the South Atlantic, and an extended validation over these regions (using 2 yr of data acquired by the Tropical Rainfall Measuring Mission precipitation radar for comparison) is the subject of a paper in preparation. The PNPR is currently used operationally within the EUMETSAT Hydrology Satellite Application Facility (H-SAF) to provide instantaneous precipitation from passive microwave cross-track scanning radiometers. It undergoes routinely thorough extensive validation over Europe carried out by the H-SAF Precipitation Products Validation Team.

Polarization signature from the FengYun-3 Microwave Humidity Sounder

Microwave Humidity Sounders (MHS) onboard NOAA-15, -16, -17, -18, -19, and EUMETSAT MetOp-A/B satellites provide radiance measurements at a single polarization state at any of five observed frequencies. The Microwave Humidity Sounder (MWHS) onboard the FengYun-3 (FY-3) satellite has a unique instrument design that provides dual polarization measurements at 150 GHz. In this study, the MWHS polarization signal was investigated using observed and modeled data. It is shown that the quasi-polarization brightness temperatures at 150 GHz display a scan angle dependent bias. Under calm ocean conditions, the polarization difference at 150 GHz becomes non-negligible when the scan angle varies from 10° to 45° and reaches a maximum when the scan angle is about 30°. Also, the polarization state is sensitive to surface parameters such as surface wind speed. Under clear-sky conditions, the differences between horizontal and vertical polarization states at 150 GHz increase with decreasing surface wind speed. Therefore, the polarization signals from the cross-track scanning microwave measurements at window channels contain useful information about surface parameters. In addition, the availability of dual polarization measurements allows a one-to-one conversion from antenna brightness temperature to sensor brightness temperature if a cross-polarization spill-over exists.

Radiometer Calibration Using Colocated GPS Radio Occultation Measurements

We present a new high-fidelity method of calibrating a cross-track scanning microwave radiometer using Global Positioning System (GPS) radio occultation (GPSRO) measurements. The radiometer and GPSRO receiver periodically observe the same volume of atmosphere near the Earth's limb, and these overlapping measurements are used to calibrate the radiometer. Performance analyses show that absolute calibration accuracy better than 0.25 K is achievable for temperature sounding channels in the 50-60-GHz band for a total-power radiometer using a weakly coupled noise diode for frequent calibration and proximal GPSRO measurements for infrequent (approximately daily) calibration. The method requires GPSRO penetration depth only down to the stratosphere, thus permitting the use of a relatively small GPS antenna. Furthermore, only coarse spacecraft angular knowledge (approximately one degree rms) is required for the technique, as more precise angular knowledge can be retrieved directly from the combined radiometer and GPSRO data, assuming that the radiometer angular sampling is uniform. These features make the technique particularly well suited for implementation on a low-cost CubeSat hosting both radiometer and GPSRO receiver systems on the same spacecraft. We describe a validation platform for this calibration method, the Microwave Radiometer Technology Acceleration (MiRaTA) CubeSat, currently in development for the National Aeronautics and Space Administration (NASA) Earth Science Technology Office. MiRaTA will fly a multiband radiometer and the Compact TEC/Atmosphere GPS Sensor in 2015.

A Study of Sea Surface Wind Vector Estimation From Near-Nadiral Cross-Track-Scanned Backscatter Data

The possibility of recovering sea surface wind vectors from near-nadiral cross-track Ku- or Ka-band backscatter measurements using a measuring geometry similar to that of the Airborne Precipitation Radar 2 is discussed. The cross-track scanning geometry includes diversity in both elevation and azimuth angles, allowing the possibility of both wind speed and direction retrieval to within a 180 ° direction ambiguity. A simulation study of wind vector retrieval accuracy is performed based on the use of the “cutoff-invariant two-scale model” of sea surface backscatter returns. The results show that a maximum likelihood retrieval approach utilizing data from the cross-track scan can provide reasonable wind vector retrieval accuracy.

CDRD and PNPR satellite passive microwave precipitation retrieval algorithms: EuroTRMM/EURAINSAT origins and H-SAF operations

Abstract. Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF) is a EUMETSAT (European Organisation for the Exploitation of Meteorological Satellites) program, designed to deliver satellite products of hydrological interest (precipitation, soil moisture and snow parameters) over the European and Mediterranean region to research and operations users worldwide. Six satellite precipitation algorithms and concomitant precipitation products are the responsibility of various agencies in Italy. Two of these algorithms have been designed for maximum accuracy by restricting their inputs to measurements from conical and cross-track scanning passive microwave (PMW) radiometers mounted on various low Earth orbiting satellites. They have been developed at the Italian National Research Council/Institute of Atmospheric Sciences and Climate in Rome (CNR/ISAC-Rome), and are providing operational retrievals of surface rain rate and its phase properties. Each of these algorithms is physically based, however, the first of these, referred to as the Cloud Dynamics and Radiation Database (CDRD) algorithm, uses a Bayesian-based solution solver, while the second, referred to as the PMW Neural-net Precipitation Retrieval (PNPR) algorithm, uses a neural network-based solution solver. Herein we first provide an overview of the two initial EU research and applications programs that motivated their initial development, EuroTRMM and EURAINSAT (European Satellite Rainfall Analysis and Monitoring at the Geostationary Scale), and the current H-SAF program that provides the framework for their operational use and continued development. We stress the relevance of the CDRD and PNPR algorithms and their precipitation products in helping secure the goals of H-SAF's scientific and operations agenda, the former helpful as a secondary calibration reference to other algorithms in H-SAF's complete mix of algorithms. Descriptions of the algorithms' designs are provided including a few examples of their performance. This aspect of the development of the two algorithms is placed in the context of what we refer to as the TRMM era, which is the era denoting the active and ongoing period of the Tropical Rainfall Measuring Mission (TRMM) that helped inspire their original development. In 2015, the ISAC-Rome precipitation algorithms will undergo a transformation beginning with the upcoming Global Precipitation Measurement (GPM) mission, particularly the GPM Core Satellite technologies. A few years afterward, the first pair of imaging and sounding Meteosat Third Generation (MTG) satellites will be launched, providing additional technological advances. Various of the opportunities presented by the GPM Core and MTG satellites for improving the current CDRD and PNPR precipitation retrieval algorithms, as well as extending their product capability, are discussed.

The Megha‐Tropiques mission: day 1 algorithms

The Megha-Tropiques mission is a mission jointly built by the Centre National d'Études Spatiales and the Indian Space Research Organisation launched in October 2011. ‘Megha’ means cloud in Sanskrit and ‘Tropiques’ is the French word for tropics. The major innovation of Megha-Tropiques is to bring together a suite of complementary instruments on a dedicated orbit that strongly improves the sampling of the water cycle elements. Indeed, the low inclination on the equator (20°) combined with the elevated height of the orbit (867 km) provides unique observing capabilities with up to 6 over-passes per day for the best case. The following payloads are embarked on board: SCARAB, a wide band instrument for inferring longwave and shortwave outgoing fluxes at the top of the atmosphere (cross track scanning, ∼ 40 km resolution at nadir); SAPHIR, a microwave sounder for water vapour sounding: six channels in the WV absorption band at 183.31 GHz (cross track, resolution ∼ 10 km); MADRAS, a microwave imager for precipitation: channels at 18, 23, 37, 89 and 157 GHz, H and V polarisations (conical swath, resolution <10 km to 40 km). A fourth instrument, a GPS-ROSA receiver, completes the mission. The scientific objectives of the mission deal with the water and energy cycle in the intertropical region. To achieve these objectives, a suite of algorithms has been developed based on the mission payloads and the available ancillary observations. This Special Issue presents the day 1 Megha-Tropiques retrievals and approaches with the emphasis on the quantification of the uncertainties associated with the products. The first series of papers by Brogniez et al., Aires et al. and Bernado et al. showcase the importance of the microwave payloads combination of SAPHIR and MADRAS for the estimation of the humidity profile. The instantaneous retrieval of surface rainfall is shown to be improved by using a renewed rainfall detection scheme (Kacimi et al.) and the uncertainty associated with the Bayesian approach to the estimation of the surface rain flux has been quantified over West Africa by Kirstetter et al. The integrated products that are envisioned for the scientific exploitation of the mission concern the accumulated daily rain amount and the composite life cycle of mesoscale convective systems. In both cases, the MT data are combined with the infrared geostationary imagery. Fiolleau and Roca, using the TRMM data as a surrogate, propose a first tropical wide composite of the rainfall evolution during the life cycle of convective systems and underline the improvement in sampling brought by the Megha-Tropiques mission. Chambon et al. show that the main source of uncertainty for the daily rain amount lies in the intermediate estimates of the instantaneous rain rates and promote a fully developed error model that includes the calibration, sampling and algorithm terms. Specific methodological developments for the validation of such products are summarized by Gosset et al., who emphasize the need for integrated hydrological validation in complement of the rainfall evaluation. While the Special Issue is mainly directed towards presenting the French team developments, a final paper by Gohil et al., highlights the Indian algorithms scenario. This Special Issue of Quarterly Journal of the Royal Meteorological Society brings to the future users of the MT data and products a suite of reference papers that should be useful for their further scientific investigations.

Long-Term Calibration and Accuracy Assessment of the FengYun-3 Microwave Temperature Sounder Radiance Measurements

The Chinese FengYun-3 (FY-3)A satellite was successfully launched on May 27, 2008, with a Microwave Temperature Sounder (MWTS) onboard. MWTS has four channels with frequencies of 50.3, 53.596, 54.94, and 57.29 GHz, respectively. The MWTS measurements are primarily used for profiling atmospheric temperatures from surface to lower stratosphere. MWTS is a cross-track scanning instrument, and its Earth-view measurements are calibrated through the warm target and cold space measurements during every scan cycle. In this paper, the FY-3A MWTS and its channel characteristics are first introduced. The calibration process and the postlaunch instrument performance are then presented, including the long-term trends of noise equivalent differential temperature (NEDT), calibration counts from cold space and warm targets, instrument telemetry, and channel gains. The observed and simulated brightness temperature (BT) differences of MWTS and Advanced Microwave Sounding Unit-A (AMSU-A) are compared. It is shown that the MWTS NEDT values at all channels are much better than its specification. The BT biases of MWTS channels 1 and 3 with respect to the simulations are similar in magnitude to those from National Oceanic and Atmospheric Administration-18 AMSU-A. The MWTS biases at channels 2 and 4 are larger than AMSU-A.

The High-Altitude MMIC Sounding Radiometer for the Global Hawk Unmanned Aerial Vehicle: Instrument Description and Performance

The Jet Propulsion Laboratory's High-Altitude Monolithic Microwave Integrated Circuit (MMIC) Sounding Radiometer (HAMSR) is a 25-channel cross-track scanning microwave sounder with channels near the 60- and 118-GHz oxygen lines and the 183-GHz water-vapor line. It has previously participated in three hurricane field campaigns, namely, CAMEX-4 (2001), Tropical Cloud Systems and Processes (2005), and NASA African Monsoon Multidisciplinary Analyses (2006). The HAMSR instrument was recently extensively upgraded for the deployment on the Global Hawk (GH) unmanned aerial vehicle platform. One of the major upgrades is the addition of a front-end low-noise amplifier, developed by JPL, to the 183-GHz channel which reduces the noise in this channel to less than 0.1 K at the sensor resolution (~2 km). This will enable HAMSR to observe much smaller scale water-vapor features. Another major upgrade is an enhanced data system that provides onboard science processing capability and real-time data access. HAMSR has been well characterized, including passband characterization, along-scan bias characterization, and calibrated noise-performance characterization. The absolute calibration is determined in-flight and has been estimated to be better than 1.5 K from previous campaigns. In 2010, HAMSR participated in the NASA Genesis and Rapid Intensification Processes campaign on the GH to study tropical cyclone genesis and rapid intensification. HAMSR-derived products include observations of the atmospheric state through retrievals of temperature, water-vapor, and cloud-liquid-water profiles. Other products include convective intensity, precipitation content, and 3-D storm structure.

Evaluation of Coincident Passive Microwave Rainfall Estimates Using TRMM PR and Ground Measurements as References

Abstract This study compares instantaneous rainfall estimates provided by the current generation of retrieval algorithms for passive microwave sensors using retrievals from the Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) and merged surface radar and gauge measurements over the continental United States as references. The goal is to quantitatively assess surface rain retrievals from cross-track scanning microwave humidity sounders relative to those from conically scanning microwave imagers. The passive microwave sensors included in the study are three operational sounders—the Advanced Microwave Sounding Unit-B (AMSU-B) instruments on the NOAA-15, -16, and -17 satellites—and five imagers: the TRMM Microwave Imager (TMI), the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) instrument on the Aqua satellite, and the Special Sensor Microwave Imager (SSM/I) instruments on the Defense Meteorological Satellite Program (DMSP) F-13, -14, and -15 satellites. The comparisons with PR data are based on “coincident” observations, defined as instantaneous retrievals (spatially averaged to 0.25° latitude and 0.25° longitude) within a 10-min interval collected over a 20-month period from January 2005 to August 2006. Statistics of departures of these coincident retrievals from reference measurements as given by the TRMM PR or ground radar and gauges are computed as a function of rain intensity over land and oceans. Results show that over land AMSU-B sounder rain retrievals are comparable in quality to those from conically scanning radiometers for instantaneous rain rates between 1.0 and 10.0 mm h−1. This result holds true for comparisons using either TRMM PR estimates over tropical land areas or merged ground radar/gauge measurements over the continental United States as the reference. Over tropical oceans, the standard deviation errors are comparable between imager and sounder retrievals for rain intensities above 5 mm h−1, below which the imagers are noticeably better than the sounders; systematic biases are small for both imagers and sounders. The results of this study suggest that in planning future satellite missions for global precipitation measurement, cross-track scanning microwave humidity sounders on operational satellites may be used to augment conically scanning microwave radiometers to provide improved temporal sampling over land without degradation in the quality of precipitation estimates.

Intense Tropical Thunderstorms Detected by the Special Sensor Microwave Imager/Sounder

The 150-GHz microwave window channel and the three water vapor channels, 183.3 plusmn 7, 183.3 plusmn 3, and 183.3 plusmn 1 GHz of the Defense Meteorological Satellite Programpsilas (DMSP) Special Sensor Microwave Imager/Sounder (SSMIS) are used to detect intense thunderstorms over the tropics (30deg S-30 deg N). This application utilizes the advantages of conical scanning and high surface horizontal resolution of the SSMIS compared to the same measurements made with cross-track scanning radiometers. The criteria to detect intense tropical thunderstorms are derived by the combination of the brightness temperature differences between the three water vapor channels and brightness temperatures at the four frequencies. One year of SSMIS data (December 2005-November 2006) is surveyed for intense tropical thunderstorms. The most intense tropical thunderstorms are predominant over land and are mainly concentrated over Central and South America, tropical west Africa, and northern Australia. Over most regions these very intense tropical thunderstorms have a strong regional dependence and a pronounced seasonal migration.

Multiyear On-Orbit Calibration and Performance of Terra MODIS Reflective Solar Bands

Terra Moderate Resolution Imaging Spectroradiometer (MODIS) has made continuous global observations for more than six years since its launch in December 1999. MODIS has 36 spectral bands: 20 reflective solar bands (RSBs) with wavelengths from 0.41-2.2 mum and 16 thermal emissive bands with wavelengths from 3.7-14.4 mum. It is a cross-track scanning radiometer that collects data at three nadir spatial resolutions: 0.25 km (2 bands), 0.5 km (5 bands), and 1 km (29 bands). An onboard solar diffuser (SD) and an SD stability monitor (SDSM) are used biweekly for RSB on-orbit radiometric calibration. Another onboard calibrator (OBC), a spectroradiometric calibration assembly, is used periodically to evaluate and monitor RSB spatial and spectral performance. In addition to measurements made using OBCs, lunar observations at nearly identical phase angles are used to track RSB calibration stability. This paper provides an overview of MODIS RSB on-orbit calibration algorithms and operational activities. It discusses sensor characteristics that could impact RSB calibration accuracy and data product quality, including degradation of the SD bidirectional reflectance factor (BRF), degradation of the scan mirror reflectance in the visible spectral region, and changes in operational configuration. The Terra MODIS OBCs have performed well in monitoring SD degradation and tracking changes in RSB response. Band 8 (0.41 mum) has experienced the largest response decrease with an approximate annual rate of 4.5% (mirror side 1). Band 9 (0.44 mum) has an annual response decrease of about 2.3% (mirror side 1). For most RSB bands with wavelengths greater than 0.5 mum, the annual response changes are generally less than 1.0%. Results from the SDSM on-orbit observations show that the SD BRF also has a similar wavelength-dependent degradation, with the largest degradation appearing at the shortest wavelengths. Among the 330 RSB detectors, there are no inoperable detectors, and only a few noisy detectors have appeared postlaunch