RETRIEVAL OF ICE CLOUD PARAMETERS USING DMSP SPECIAL SENSOR MICROWAVE IMAGER/SOUNDER

Clouds exert a profound influence on both the water balance of the atmosphere and the earth's radiation budget (Stephens 2005; Stephens and Kummerow 2007). Among the global distribution, 30% of them are ice clouds (Riedi et al. 2000). It is important to improve our knowledge of the ice cloud properties in order to determine their influence to the global ecosystem. For ice clouds with millimeter-size ice particles, which are generally found in anvil cirrus and deep convections, microwave and millimeter wave length satellite measurements are suitable for the ice cloud microphysical property retrieval because of its strong ability to penetrate deeper into dense ice clouds. For these types of ice clouds, brightness temperatures at the top of the atmosphere are analytically derived as a function of vertically integrated ice water content (i.e. ice water path), effective particle diameter, and bulk volume density. In general, three brightness temperature measurements are needed to retrieve the three ice cloud microphysical parameters. A two-stream radiative transfer theory was applied to data from the Advanced Microwave Sounding Unit (AMSU) and the Moisture Humidity Sensor (MHS) in order to generate global ice water paths operationally. This research further applied the model and theory to derive ice water path (IWP) from the Special Sensor Microwave Imager/Sounder (SSMIS) onboard the Defense Meteorological Satellite Program (DMSP) F-16 satellite. Compared to AMSU/MHS, which have field of views (FOV) varying with scan position, SSMIS scans the Earth's atmosphere at a constant viewing angle of 53o and therefore offers a uniform FOV within each scan. This unique feature allows for improved global mapping and monitoring of ice clouds so that a more accurate and realistic IWP and ice particle effective diameter distribution is expected. A direct application of SSMIS-derived ice water path is its relationship with surface rain rate as derived previously for AMSU and MHS instruments. Here, SSMIS-derived rain rate was compared to the AMSU and MHS rainfall products and hourly synthetic precipitation observations from rain gauges and surface radar. Results show that SSMIS surface precipitation distribution is spatially consistent and does not have apparent artificial boundary near coastal zones as previously seen in other algorithms. Also, the ice water path associated with a severe storm reasonably delineates the strong convective precipitation areas and has a spatial variation consistent with surface precipitation. From retrieved instantaneous surface precipitation, a tropical and subtropical oceanic precipitation anomaly time series is constructed from 5 year's worth (2005-2009) of SSMIS data. This data record is also linked to the previous constructed SSM/I 15-year (1992-2006) data record to provide a longer term climate study by satellite observations. In future studies, refined algorithms for the estimate of ice cloud base temperature and ice particle bulk volume density are going to be developed to improve the accuracy of IWP retrieval under various cloud vertical distributions. Meanwhile, a better inter-sensor cross calibration scheme is the key to make satellite measurements more useful in climate change study

Aqua: AIRS, AMSU, HSB, AMSR-E, CERES, MODIS

This brochure provides an overview of the Aqua spacecraft, instruments, science, and data products Aqua, Latin for water, is a NASA Earth Science satellite mission named for the large amount of information that the mission is collecting about the Earth's water cycle, including evaporation from the oceans, water vapor in the atmosphere, clouds, precipitation, soil moisture, sea ice, land ice, and snow cover on the land and ice. Additional variables also measured by Aqua include radiative energy fluxes, aerosols, vegetation cover on the land, phytoplankton and dissolved organic matter in the oceans, and air, land, and water temperatures. Note: this guide was produced before Aqua was launched; for the most recent information on Aqua, go to http://aqua.nasa.gov. Educational levels: Undergraduate lower division, Undergraduate upper division, Graduate or professional, Informal education

Radiometric Correction of Observations from Microwave Humidity Sounders

The Advanced Microwave Sounding Unit-B (AMSU-B) and Microwave Humidity Sounder (MHS) are total power microwave radiometers operating at frequencies near the water vapor absorption line at 183 GHz. The measurements of these instruments are crucial for deriving a variety of climate and hydrological products such as water vapor, precipitation, and ice cloud parameters. However, these measurements are subject to several errors that can be classified into radiometric and geometric errors. The aim of this study is to quantify and correct the radiometric errors in these observations through intercalibration. Since the bias in the calibration of microwave instruments changes with scene temperature, a two-point intercalibration correction scheme was developed based on averages of measurements over the tropical oceans and nighttime polar regions. The intercalibration coefficients were calculated on a monthly basis using measurements averaged over each specified region and each orbit, then interpolated to estimate the daily coefficients. Since AMSU-B and MHS channels operate at different frequencies and polarizations, the measurements from the two instruments were not intercalibrated. Because of the negligible diurnal cycle of both temperature and humidity fields over the tropical oceans, the satellites with the most stable time series of brightness temperatures over the tropical oceans (NOAA-17 for AMSU-B and NOAA-18 for MHS) were selected as the reference satellites and other similar instruments were intercalibrated with respect to the reference instrument. The results show that channels 1, 3, 4, and 5 of AMSU-B on board NOAA-16 and channels 1 and 4 of AMSU-B on board NOAA-15 show a large drift over the period of operation. The MHS measurements from instruments on board NOAA-18, NOAA-19, and MetOp-A are generally consistent with each other. Because of the lack of reference measurements, radiometric correction of microwave instruments remain a challenge, as the intercalibration of these instruments largely depends on the stability of the reference instrument

New algorithm for retrieval of tropospheric wet path delay over inland water bodies and coastal zones using brightness temperature deflection ratios, A

2013 Spring.Includes bibliographical references.As part of former and current sea-surface altimetry missions, brightness temperatures measured by nadir-viewing 18-34 GHz microwave radiometers are used to determine apparent path delay due to variations in index of refraction caused by changes in the humidity of the troposphere. This tropospheric wet-path delay can be retrieved from these measurements with sufficient accuracy over open oceans. However, in coastal zones and over inland water the highly variable radiometric emission from land surfaces at microwave frequencies has prevented accurate retrieval of wet-path delay using conventional algorithms. To extend wet path delay corrections into the coastal zone (within 25 km of land) and to inland water bodies, a new method is proposed to correct for tropospheric wet-path delay by using higher-frequency radiometer channels from approximately 50-170 GHz to provide sufficiently small fields of view on the surface. A new approach is introduced based on the variability of observations in several millimeter-wave radiometer channels on small spatial scales due to surface emissivity in contrast to the larger-scale variability in atmospheric absorption. The new technique is based on the measurement of deflection ratios among several radiometric bands to estimate the transmissivity of the atmosphere due to water vapor. To this end, the Brightness Temperature Deflection Ratio (BTDR) method is developed starting from a radiative transfer model for a downward-looking microwave radiometer, and is extended to pairs of frequency channels to retrieve the wet path delay. Then a mapping between the wet transmissivity and wet-path delay is performed using atmospheric absorption models. A frequency selection study is presented to determine the suitability of frequency sets for accurate retrieval of tropospheric wet-path delay, and comparisons are made to frequency sets based on currently-available microwave radiometers. Statistical noise analysis results are presented for a number of frequency sets. Additionally, this thesis demonstrates a method of identifying contrasting surface pixels using edge detection algorithms to identify contrasting scenes in brightness temperature images for retrieval with the BTDR method. Finally, retrievals are demonstrated from brightness temperatures measured by Special Sensor Microwave Imager/Sounder (SSMIS) instruments on three satellites for coastal and inland water scenes. For validation, these retrievals are qualitatively compared to independently-derived total precipitable water products from SSMIS, the Tropical Rainfall Measurement Mission (TRMM) Microwave Imager (TMI) and the Advanced Microwave Sounding Radiometer for Earth Observing System (EOS) (AMSR-E). Finally, a quantitative method for analyzing the data consistency of the retrieval is presented as an estimate of the error in the retrieved wet path delay. From these comparisons, one can see that the BTDR method shows promise for retrieving wet path delays over inland water and coastal regions. Finally, several additional future uses for the algorithm are described

Evaluation of Precipitation Detection over Various Surfaces from Passive Microwave Imagers and Sounders

During the middle part of this decade a wide variety of passive microwave imagers and sounders will be unified in the Global Precipitation Measurement (GPM) mission to provide a common basis for frequent (3 hr), global precipitation monitoring. The ability of these sensors to detect precipitation by discerning it from non-precipitating background depends upon the channels available and characteristics of the surface and atmosphere. This study quantifies the minimum detectable precipitation rate and fraction of precipitation detected for four representative instruments (TMI, GMI, AMSU-A, and AMSU-B) that will be part of the GPM constellation. Observations for these instruments were constructed from equivalent channels on the SSMIS instrument on DMSP satellites F16 and F17 and matched to precipitation data from NOAA's National Mosaic and QPE (NMQ) during 2009 over the continuous United States. A variational optimal estimation retrieval of non-precipitation surface and atmosphere parameters was used to determine the consistency between the observed brightness temperatures and these parameters, with high cost function values shown to be related to precipitation. The minimum detectable precipitation rate, defined as the lowest rate for which probability of detection exceeds 50%, and the detected fraction of precipitation, are reported for each sensor, surface type (ocean, coast, bare land, snow cover) and precipitation type (rain, mix, snow). The best sensors over ocean and bare land were GMI (0.22 mm/hr minimum threshold and 90% of precipitation detected) and AMSU (0.26 mm/hr minimum threshold and 81% of precipitation detected), respectively. Over coasts (0.74 mm/hr threshold and 12% detected) and snow-covered surfaces (0.44 mm/hr threshold and 23% detected), AMSU again performed best but with much lower detection skill, whereas TMI had no skill over these surfaces. The sounders (particularly over water) benefited from the use of re-analysis data (vs. climatology) to set the a-priori atmospheric state and all instruments benefit from the use of a conditional snow cover emissivity database over land. It is recommended that real-time sources of these data be used in the operational GPM precipitation algorithms

On-orbit Inter-satellite Radiometric Calibration of Cross-track Scanning Microwave Radiometers

This dissertation concerns the development of an improved algorithm for the inter-satellite radiometric calibration (XCAL) for cross track scanning microwave radiometers in support of NASA\u27s Global Precipitation Mission (GPM). This research extends previous XCAL work to assess the robustness of the CFRSL double difference technique for sounder X-CAL. In this work, using a two-year of observations, we present a statistical analysis of radiometric biases performed over time and viewing geometry. In theory, it is possible to apply the same X-CAL procedure developed for conical-scanning radiometers to cross-track scanners; however the implementation is generally more tedious. For example, with the cross-track scan angle, there is a strong response in the observed Tb due to changes in the atmosphere slant path and surface emissivity with the Earth incidence angle. For ocean scenes this is trivial; however for land scenes there is imperfect knowledge of polarized emissivity. However, for the sounder channels the surface emissivity is not the dominant component of top-of-the-atmosphere Tb, which is a mitigating factor. Also, cross-track scanners introduce changes in the radiometer antenna observed polarization with scan angle. The resulting observation is a mixture of un-polarized atmospheric emissions and vertical and horizontal polarized surface emissions. The degree of polarization mixing is known from geometry; however, reasonable estimates of the surface emissivity are required, which complicate over land comparisons. Finally, the IFOV size monotonically increases over the cross-track scan. Thus, when inter-comparing cross-track scanning radiometers, it will be necessary to carefully consider these effects when performing the double difference procedure

Combined MW-IR Precipitation Evolving Technique (PET) of convective rain fields

This paper describes a new multi-sensor approach for convective rain cell continuous monitoring based on rainfall derived from Passive Microwave (PM) remote sensing from the Low Earth Orbit (LEO) satellite coupled with Infrared (IR) remote sensing Brightness Temperature (TB) from the Geosynchronous (GEO) orbit satellite. The proposed technique, which we call Precipitation Evolving Technique (PET), propagates forward in time and space the last available rain-rate (RR) maps derived from Advanced Microwave Sounding Units (AMSU) and Microwave Humidity Sounder (MHS) observations by using IR TB maps of water vapor (6.2 μm) and thermal-IR (10.8 μm) channels from a Spinning Enhanced Visible and Infrared Imager (SEVIRI) radiometer. PET is based on two different modules, the first for morphing and tracking rain cells and the second for dynamic calibration IR-RR. The Morphing module uses two consecutive IR data to identify the motion vector to be applied to the rain field so as to propagate it in time and space, whilst the Calibration module computes the dynamic relationship between IR and RR in order to take into account genesis, extinction or size variation of rain cells. Finally, a combination of the Morphing and Calibration output provides a rainfall map at IR space and time scale, and the whole procedure is reiterated by using the last RR map output until a new MW-based rainfall is available. The PET results have been analyzed with respect to two different PM-RR retrieval algorithms for seven case studies referring to different rainfall convective events. The qualitative, dichotomous and continuous assessments show an overall ability of this technique to propagate rain field at least for 2–3 h propagation time

Diurnal Cycle of Passive Microwave Brightness Temperatures over Land at a Global Scale

Satellite-borne passive microwave radiometers provide brightness temperature (TB) measurements in a large spectral range which includes a number of frequency channels and generally two polarizations: horizontal and vertical. These TBs are widely used to retrieve several atmospheric and surface variables and parameters such as precipitation, soil moisture, water vapor, air temperature profile, and land surface emissivity. Since TBs are measured at different microwave frequencies with various instruments and at various incidence angles, spatial resolutions, and radiometric characteristics, a mere direct integration of them from different microwave sensors would not necessarily provide consistency. However, when appropriately harmonized, they can provide a complete dataset to estimate the diurnal cycle. This study first constructs the diurnal cycle of land TBs using the non-sun-synchronous Global Precipitation Measurement (GPM) Microwave Imager (GMI) observations by utilizing a cubic spline fit. The acquisition times of GMI vary from day to day and, therefore, the shape (amplitude and phase) of the diurnal cycle for each month is obtained by merging several days of measurements. This diurnal pattern is used as a point of reference when intercalibrated TBs from other passive microwave sensors with daily fixed acquisition times (e.g., Special Sensor Microwave Imager/Sounder, and Advanced Microwave Scanning Radiometer 2) are used to modify and tune the monthly diurnal cycle to daily diurnal cycle at a global scale. Since the GMI does not cover polar regions, the proposed method estimates a consistent diurnal cycle of land TBs at global scale. Results show that the shape and peak of the constructed TB diurnal cycle is approximately similar to the diurnal cycle of land surface temperature. The diurnal brightness temperature range for different land cover types has also been explored using the derived diurnal cycle of TBs. In general, a large diurnal TB range of more than 15 K has been observed for the grassland, shrubland, and tundra land cover types, whereas it is less than 5K over forests. Furthermore, seasonal variations in the diurnal TB range for different land cover types show a more consistent result over the Southern Hemisphere than over the Northern Hemisphere. The calibrated TB diurnal cycle may then be used to consistently estimate the diurnal cycle of land surface emissivity. Moreover, since changes in land surface emissivity are related to moisture change and freeze–thaw (FT) transitions in high-latitude regions, the results of this study enhance temporal detection of FT state, particularly during the transition times when multiple FT changes may occur within a day

Precipitation products from the hydrology SAF

Abstract. The EUMETSAT Satellite Application Facility on Support to Operational Hydrology and Water Management (H-SAF) was established by the EUMETSAT Council on 3 July 2005, starting activity on 1 September 2005. The Italian Meteorological Service serves as Leading Entity on behalf of twelve European member countries. H-SAF products include precipitation, soil moisture and snow parameters. Some products are based only on satellite observations, while other products are based on the assimilation of satellite measurements/products into numerical models. In addition to product development and generation, H-SAF includes a product validation program and a hydrological validation program that are coordinated, respectively, by the Italian Department of Civil Protection and by the Polish Institute of Meteorology and Water Management. The National Center of Aeronautical Meteorology and Climatology (CNMCA) of the Italian Air Force is responsible for operational product generation and dissemination. In this paper we describe the H-SAF precipitation algorithms and products, which have been developed by the Italian Institute of Atmospheric Sciences and Climate (in collaboration with the international community) and by CNMCA during the Development Phase (DP, 2005–2010) and the first Continuous Development and Operations Phase (CDOP-1, 2010–2012). The precipitation products are based on passive microwave measurements obtained from radiometers onboard different sun-synchronous low-Earth-orbiting satellites (especially, the SSM/I and SSMIS radiometers onboard DMSP satellites and the AMSU-A + AMSU-B/MHS radiometer suites onboard EPS-MetOp and NOAA-POES satellites), as well as on combined infrared/passive microwave measurements in which the passive microwave precipitation estimates are used in conjunction with SEVIRI images from the geostationary MSG satellite. Moreover, the H-SAF product generation and dissemination chain and independent product validation activities are described. Also, the H-SAF program and its associated activities that currently are being carried out or are planned to be performed within the second CDOP phase (CDOP-2, 2012–2017) are presented in some detail. Insofar as CDOP-2 is concerned, it is emphasized that all algorithms and processing schemes will be improved and enhanced so as to extend them to satellites that will be operational within this decade – particularly the geostationary Meteosat Third Generation satellites and the low-Earth-orbiting Core Observatory of the international Global Precipitation Measurement mission. Finally, the role of H-SAF within the international science and operations community is explained.</p