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Rainfall over oceans inferred from Nimbus 7 SMMR - Application to 1982-83 El Nino

Nimbus 7 Scanning Multichannel Microwave Radiometer (SMMR) measurements at five frequencies in the region 6.6 to 37 GHz, at a resolution of 155 km, are analyzed to infer precipitation over the global oceans. The microwave data show, on this spatial scale, that the combined liquid water in the clouds and rain increases the brightness temperature almost linearly with frequency in the 6.6-18-GHz region, while at 37 GHz such a simple relationship is not noticed. Further, as the atmospheric water-vapor absorption and the effects of scattering by precipitation particles are relatively weak at 6.6 and 10.7 GHz, a technique to remotely sense the liquid water content in the atmosphere is developed based on the brightness measurements at these two frequencies. Seasonal mean patterns of liquid water content in the atmosphere derived from SMMR over global oceans relate closely to climatological patterns of precipitation. Based on this, an empirical relationship is derived to estimate precipitation over the global oceans, with an accuracy of about + or - 30 percent, on a seasonal basis from satellite measurements made during the three years (1979-81) before the recent El Nino event. The deviations from these three-year means, in the precipitation, produced by the 1982-83 el Nino event are then deduced from the SMMR measurements. In the Pacific, the precipitation over the ITCZ in the north, the South Pacific Convergence Zone, and the oceans around Indonesia is drastically reduced. At the same time a substantial increase in precipitation is observed over the normally dry central and eastern equatorial Pacific Ocean.

Prabhakara, C.↗

Basic properties of developed wind waves and their influence on microwave remote sensing signatures

Error trends in wind speed measurements by satellite scatterometer altimeter and microwave radiometer are shown to be correlated with the degree of wave development. These errors are analyzed theoretically by studying the rms wave slope which, directly or indirectly, affects all microwave signatures. For equilibrium sea state, the influence of spectrum parameters on the wave slope is reviewed. In well-developed seas, the dominant wavelength is shown to have no effect on the slope. Temporal-spatial rates of steep and breaking waves are derived and compared with field observations. The inner scale that determines a rapid falloff of spectral density function at high frequencies is estimated. The dependence of the spectral parameters on wind speed and sea maturity is studied using NOAA buoy observations. It is concluded that the removal of environmental error trends from satellite measurements can be best accomplished by a joint processing of microwave returns from several independent instruments.

Glazman, Roman E.↗

Microwave Brightness Temperatures of Tilted Convective Systems

Aircraft and ground-based radar data from the Tropical Ocean and Global Atmosphere Coupled-Ocean Atmosphere Response Experiment (TOGA COARE) show that convective systems are not always vertical. Instead, many are tilted from vertical. Satellite passive microwave radiometers observe the atmosphere at a viewing angle. For example, the Special Sensor Microwave/Imager (SSM/I) on Defense Meteorological Satellite Program (DMSP) satellites and the Tropical Rainfall Measurement Mission (TRMM) Microwave Imager (TMI) on the TRMM satellite have an incident angle of about 50deg. Thus, the brightness temperature measured from one direction of tilt may be different than that viewed from the opposite direction due to the different optical depth. This paper presents the investigation of passive microwave brightness temperatures of tilted convective systems. To account for the effect of tilt, a 3-D backward Monte Carlo radiative transfer model has been applied to a simple tilted cloud model and a dynamically evolving cloud model to derive the brightness temperature. The radiative transfer results indicate that brightness temperature varies when the viewing angle changes because of the different optical depth. The tilt increases the displacements between high 19 GHz brightness temperature (Tb(sub 19)) due to liquid emission from lower level of cloud and the low 85 GHz brightness temperature (Tb(sub 85)) due to ice scattering from upper level of cloud. As the resolution degrades, the difference of brightness temperature due to the change of viewing angle decreases dramatically. The dislocation between Tb(sub 19) and Tb(sub 85), however, remains prominent.

Hong, Ye↗

WMAP - A Portrait of the Early Universe

A host of astrophysical observations suggest that early Universe was incredibly hot, dense, and homogeneous. A powerful probe of this time is provided by the relic radiation which we refer to today as the Cosmic Microwave Background (CMB). Images produced from this light contain the earliest glimpse of the Universe after the 'Big Bang' and the signature of the evolution of its contents. By exploiting these clues, constraints on the age, mass density, and geometry of the early Universe can be derived. A brief history of the evolution of the microwave radiometer systems and map making approaches used in advancing these aspects our understanding of cosmological will be reviewed. In addition, an overview of the results from NASA's Wilkinson Microwave Anisotropy (WMAP) will be presented.

Wollack, Edward J.↗

Microwave remote sensing of hydrologic parameters

A perspective on the implementation of microwave sensors in future airborne and spaceborne observations of hydrologic parameters is presented. The rationale is based on a review of the status and future trends of active (radar) and passive (radiometer) microwave research as applied to the remote sensing of soil moisture content, snowpack water equivalent, freeze/thaw boundaries, lake ice thickness, surface water area, and the specification of watershed runoff coefficients. Analyses and observations based on data acquired from ground based, airborne and spaceborne platforms, and an evaluation of advantages and limitations of microwave sensors are included.

Ulaby, F. T.↗

Application of the Man-computer Interactive Data Access System (McIDAS) to aerospace meteorology

The Man-computer Interactive Data Access System (McIDAS) considered in this paper has been in use at Marshall Space Flight Center (MSFC) since 1981. The MSFC McIDAS system is primarily employed as a research tool, taking into account rainfall estimates as deduced from Scanning Multichannel Microwave Radiometer (SMMR) data, remote sensing sensor development (MAMS), Doppler-lidar derived winds, cloud tracked winds, and analysis of lightning ground strike data. With respect to the SMMR data analysis, passive microwave satellite data are displayed on McIDAS as images. Two major research efforts are concerned with the determination of mesoscale winds. These efforts are based on a utilization of a Doppler-lidar system, and GOES multispectral imagery. It is pointed out that future plans include increased usage of the McIDAS system.

Meyer, P. J.↗

Precipitation and Latent Heating Distributions from Satellite Passive Microwave Radiometry. Part II: Evaluation of Estimates Using Independent Data

Rainfall rate estimates from spaceborne microwave radiometers are generally accepted as reliable by a majority of the atmospheric science community. One of the Tropical Rainfall Measuring Mission (TRMM) facility rain-rate algorithms is based upon passive microwave observations from the TRMM Microwave Imager (TMI). In Part I of this series, improvements of the TMI algorithm that are required to introduce latent heating as an additional algorithm product are described. Here, estimates of surface rain rate, convective proportion, and latent heating are evaluated using independent ground-based estimates and satellite products. Instantaneous, 0.5 deg. -resolution estimates of surface rain rate over ocean from the improved TMI algorithm are well correlated with independent radar estimates (r approx. 0.88 over the Tropics), but bias reduction is the most significant improvement over earlier algorithms. The bias reduction is attributed to the greater breadth of cloud-resolving model simulations that support the improved algorithm and the more consistent and specific convective/stratiform rain separation method utilized. The bias of monthly 2.5 -resolution estimates is similarly reduced, with comparable correlations to radar estimates. Although the amount of independent latent heating data is limited, TMI-estimated latent heating profiles compare favorably with instantaneous estimates based upon dual-Doppler radar observations, and time series of surface rain-rate and heating profiles are generally consistent with those derived from rawinsonde analyses. Still, some biases in profile shape are evident, and these may be resolved with (a) additional contextual information brought to the estimation problem and/or (b) physically consistent and representative databases supporting the algorithm. A model of the random error in instantaneous 0.5 deg. -resolution rain-rate estimates appears to be consistent with the levels of error determined from TMI comparisons with collocated radar. Error model modifications for nonraining situations will be required, however. Sampling error represents only a portion of the total error in monthly 2.5 -resolution TMI estimates; the remaining error is attributed to random and systematic algorithm errors arising from the physical inconsistency and/or nonrepresentativeness of cloud-resolving-model-simulated profiles that support the algorithm.

Yang, Song↗

University of Miami G-band Vapor Radiometer Calibration (UMGVR_CAL) Field Campaign Report

Cold-air outbreak (CAO) clouds in the Arctic are commonly mixed-phase (MP); however, the partitioning of the amount of ice and water in CAO clouds and precipitation is not always well observed. Understanding how cloud phases partition as a function of cloud life cycle is important for predicting snowfall rates, convective life cycle, and intensity at weather timescales. The partitioning into liquid versus ice also has radiative impacts that are consequential for climate. These concerns motivated the incorporation of an airborne G-band vapor radiometer (GVR) into an National Science Foundation-supported aircraft campaign named the Cold Air outbreak Experiment in the Sub-Arctic Region (CAESAR). The GVR is an upward-pointing passive microwave radiometer using four frequencies centered around the 183.31 GHz water vapor absorption line, displaced by +- 1, 3, 7, and 14 GHz. For context, The U.S. Department of Energy (DOE)’s Atmospheric Radiation Measurement (ARM) user facility operates a surface-based GVR at its North Slope of Alaska (NSA) site. The same GVR has been used previously for a field campaign in the southeast Pacific, where an offset was noticed between brightness temperatures (Tbs) measured under clear skies compared to those calculated from a radiative transfer model. To account for any calibration offsets to the Tbs, a request was made to DOE to allow the GVR to operate at ARM’s Southern Great Plains (SGP) observatory and enable comparisons between its measurements and those available at SGP. This request was granted, titled ‘UMGVR_CAL’, short for ‘UMGVR_Calibration’. From October 30 to November 10, 2023, the GVR was deployed to the ARM SGP site to take advantage of their regular, nearby radiosonde launches under clear-sky conditions. The latter were determined using the SGP total sky imagery data. The GVR brightness temperatures in these clear-sky conditions were compared to those calculated by a radiative transfer code (PAMTRA) based on the SGP radiosondes. During the campaign, four suitable clear-sky episodes could be used for the GVR calibration. While few in number, these proved to be enough to satisfy our goal.

54 ENVIRONMENTAL SCIENCES↗

Rain on snow (ROS) understudied in sea ice remote sensing: a multi-sensor analysis of ROS during MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate)

Abstract. Arctic rain on snow (ROS) deposits liquid water onto existing snowpacks. Upon refreezing, this can form icy crusts at the surface or within the snowpack. By altering radar backscatter and microwave emissivity, ROS over sea ice can influence the accuracy of sea ice variables retrieved from satellite radar altimetry, scatterometers, and passive microwave radiometers. During the Arctic Ocean MOSAiC (Multidisciplinary drifting Observatory for the Study of Arctic Climate) expedition, there was an unprecedented opportunity to observe a ROS event using in situ active and passive microwave instruments similar to those deployed on satellite platforms. During liquid water accumulation in the snowpack from rain and increased melt, there was a 4-fold decrease in radar energy returned at Ku- and Ka-bands. After the snowpack refroze and ice layers formed, this decrease was followed by a 6-fold increase in returned energy. Besides altering the radar backscatter, analysis of the returned waveforms shows the waveform shape changed in response to rain and refreezing. Microwave emissivity at 19 and 89 GHz increased with increasing liquid water content and decreased as the snowpack refroze, yet subsequent ice layers altered the polarization difference. Corresponding analysis of the CryoSat-2 waveform shape and backscatter as well as AMSR2 brightness temperatures further shows that the rain and refreeze were significant enough to impact satellite returns. Our analysis provides the first detailed in situ analysis of the impacts of ROS and subsequent refreezing on both active and passive microwave observations, providing important baseline knowledge for detecting ROS over sea ice and assessing their impacts on satellite-derived sea ice variables.

54 ENVIRONMENTAL SCIENCES↗

A satellite technique for quantitatively mapping rainfall rates over the oceans

A theoretical model for calculating microwave radiative transfer in raining atmospheres is developed. These calculations are compared with microwave brightness temperatures at a wavelength of 1.55 cm measured by the Electrically Scanning Microwave Radiometer (ESMR) on the Nimbus-5 satellite and rain rates derived from WSR-57 meteorological radar measurements. A specially designed ground-based verification experiment was also performed, wherein upward-viewing microwave brightness temperature measurements at wavelengths of 1.55 and 0.81 cm were compared with directly measured rain rates. It is shown that, over ocean areas, brightness temperature measurements from ESMR may be interpreted in terms of rain rate with about an accuracy of a factor of 2 over the range 1 to 25 mm/hr rain rate.

Wilheit, T. T.↗

Passive measurement and interpretation of polarized microwave brightness temperatures

The goal of this project is to develop satellite-based observational techniques for measuring both oceanic and atmospheric variables using passive polarimetric radiometry. Polarimetric radiometry offers a potential alternative to radar scatterometry in observing global ocean surface wind direction from satellites. Polarimetric radiometry might also provide a means of detecting cell-top ice in convective storms by virtue of the polarizing properties of oriented ice particles, and thus facilitate estimation of the phase of the storm. The project focuses on the development of polarimetric microwave radiometers using digital cross-correlators for obtaining precise measurements of all four Stokes' parameters. As part of the project a unique four-band polarimetric imaging radiometer, the Polar Scanning Radiometer (PSR), is being designed for use on the NASA DC-8 aircraft. In addition to providing an aircraft-based demonstration of digital correlation technology the PSR will significantly enhance the microwave imaging capability of the existing suite of DC-8 instruments. During the first grant year excellent progress has been made in the following areas: (1) demonstrating digital correlation radiometry, (2) fabricating aircraft-qualified correlators for use in the PSR, and (3) modeling observed SSM/I brightness signatures of ocean wind direction.

Gasiewski, A. J.↗

SSM/I and ECMWF Wind Vector Comparison

Wentz was the first to convincingly show that satellite microwave radiometers have the potential to measure the oceanic wind vector. The most compelling evidence for this conclusion was the monthly wind vector maps derived solely from a statistical analysis of Special Sensor Microwave Imager (SSM/I) observations. In a qualitative sense, these maps clearly showed the general circulation over the world's oceans. In this report we take a closer look at the SSM/I monthly wind vector maps and compare them to European Center for Medium-Range Weather Forecasts (ECMWF) wind fields. This investigation leads both to an empirical comparison of SSM/I calculated wind vectors with ECMWF wind vectors, and to an examination of possible reasons that the SSM/I calculated wind vector direction would be inherently more reliable at some locations than others.

Wentz, Frank J.↗

Precipitation and Latent Heating Distributions from Satellite Passive Microwave Radiometry: Method and Uncertainties - Part 1

A revised Bayesian algorithm for estimating surface rain rate, convective rain proportion, and latent heating/drying profiles from satellite-borne passive microwave radiometer observations over ocean backgrounds is described. The algorithm searches a large database of cloud-radiative model simulations to find cloud profiles that are radiatively consistent with a given set of microwave radiance measurements. The properties of these radiatively consistent profiles are then composited to obtain best estimates of the observed properties. The revised algorithm is supported by an expanded and more physically consistent database of cloud-radiative model simulations. The algorithm also features a better quantification of the convective and non-convective contributions to total rainfall, a new geographic database, and an improved representation of background radiances in rain-free regions. Bias and random error estimates are derived from applications of the algorithm to synthetic radiance data, based upon a subset of cloud resolving model simulations, and from the Bayesian formulation itself. Synthetic rain rate and latent heating estimates exhibit a trend of high (low) bias for low (high) retrieved values. The Bayesian estimates of random error are propagated to represent errors at coarser time and space resolutions, based upon applications of the algorithm to TRMM Microwave Imager (TMI) data. Errors in instantaneous rain rate estimates at 0.5 deg resolution range from approximately 50% at 1 mm/h to 20% at 14 mm/h. These errors represent about 70-90% of the mean random deviation between collocated passive microwave and spaceborne radar rain rate estimates. The cumulative algorithm error in TMI estimates at monthly, 2.5 deg resolution is relatively small (less than 6% at 5 mm/day) compared to the random error due to infrequent satellite temporal sampling (8-35% at the same rain rate).

Olson, William S.↗

Precipitation and Latent Heating Distributions from Satellite Passive Microwave Radiometry: Improved Method and Uncertainties - Part 1

A revised Bayesian algorithm for estimating surface rain rate, convective rain proportion, and latent heating profiles from satellite-borne passive microwave radiometer observations over ocean backgrounds is described. The algorithm searches a large database of cloud-radiative model simulations to find cloud profiles that are radiatively consistent with a given set of microwave radiance measurements. The properties of these radiatively consistent profiles are then composited to obtain best estimates of the observed properties. The revised algorithm is supported by an expanded and more physically consistent database of cloud-radiative model simulations. The algorithm also features a better quantification of the convective and nonconvective contributions to total rainfall, a new geographic database, and an improved representation of background radiances in rain-free regions. Bias and random error estimates are derived from applications of the algorithm to synthetic radiance data, based upon a subset of cloud-resolving model simulations, and from the Bayesian formulation itself. Synthetic rain-rate and latent heating estimates exhibit a trend of high (low) bias for low (high) retrieved values. The Bayesian estimates of random error are propagated to represent errors at coarser time and space resolutions, based upon applications of the algorithm to TRMM Microwave Imager (TMI) data. Errors in TMI instantaneous rain-rate estimates at 0.5 -resolution range from approximately 50% at 1 mm/h to 20% at 14 mm/h. Errors in collocated spaceborne radar rain-rate estimates are roughly 50%-80% of the TMI errors at this resolution. The estimated algorithm random error in TMI rain rates at monthly, 2.5deg resolution is relatively small (less than 6% at 5 mm day.1) in comparison with the random error resulting from infrequent satellite temporal sampling (8%-35% at the same rain rate). Percentage errors resulting from sampling decrease with increasing rain rate, and sampling errors in latent heating rates follow the same trend. Averaging over 3 months reduces sampling errors in rain rates to 6%-15% at 5 mm day.1, with proportionate reductions in latent heating sampling errors.

Olson, William S.↗

Radiant Temperature Nulling Radiometer

A nulling, self-calibrating infrared radiometer is being developed for use in noncontact measurement of temperature in any of a variety of industrial and scientific applications. This instrument is expected to be especially well-suited to measurement of ambient or near-ambient temperature and, even more specifically, for measuring the surface temperature of a natural body of water. Although this radiometer would utilize the long-wavelength infrared (LWIR) portion of the spectrum (wavelengths of 8 to 12 m), its basic principle of operation could also be applied to other spectral bands (corresponding to other temperature ranges) in which the atmosphere is transparent and in which design requirements for sensitivity and temperature-measurement accuracy could be satisfied. The underlying principle of nulling and self-calibration is the same as that of a typical microwave radiometer, but because of differences between the characteristics of signals in the infrared and microwave spectral regions, the principle must be implemented in a different way. A detailed description of the instrument including an infrared photodetector equipped with focusing input optics [e.g., lens(es) and/or mirrors] and an input LWIR band-pass filter is presented.

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Passive Microwave Observation of Diurnal Surface Soil Moisture

Microwave radiometers operating at low frequencies are sensitive to surface soil moisture changes. Few studies have been conducted that have involved multifrequency observations at frequencies low enough to measure a significant soil depth and not be attenuated by the vegetation cover. Another unexplored aspect of microwave observations at low frequencies has been the impact of diurnal variations of the soil moisture and temperature on brightness temperature. In this investigation, observations were made using a dual frequency radiometer (1.4 and 2.65 GHz) over bare soil and corn for extended periods in 1994. Comparisons of emissivity and volumetric soil moisture at four depths for bare soils showed that there was a clear correspondence between the 1 cm soil moisture and the 2.65-GHz emissivity and between the 3-5 cm soil moisture and the 1.4-GHZ emissivity, which confirms previous studies. Observations during drying and rainfall demonstrate that new and unique information for hydrologic and energy balance studies can be extracted from these data.

Jackson, Thomas J.↗

Unbiased estimation of oceanic mean rainfall from satellite borne radiometer measurements

The statistical properties of the radar derived rainfall obtained during the GARP Atlantic Tropical Experiment (GATE) are used to derive quantitative estimates of the spatial and temporal sampling errors associated with estimating rainfall from brightness temperature measurements such as would be obtained from a satelliteborne microwave radiometer employing a practical size antenna aperture. A basis for a method of correcting the so called beam filling problem, i.e., for the effect of nonuniformity of rainfall over the radiometer beamwidth is provided. The method presented employs the statistical properties of the observations themselves without need for physical assumptions beyond those associated with the radiative transfer model. The simulation results presented offer a validation of the estimated accuracy that can be achieved and the graphs included permit evaluation of the effect of the antenna resolution on both the temporal and spatial sampling errors.

Mittal, M. C.↗

International Geoscience and Remote Sensing Symposium, Washington, DC, June 8-10, 1981, Digest. Volumes 1 & 2

Sensors used for the geophysical and remote sensing studies are reviewed; in particular, NIMBUS-7 Scanning Multichannel Microwave Radiometer results are given. Remote sensing analyses consider such areas as hydrology, soil moisture, and planetary surfaces. In addition, Shuttle remote sensing experiments and SAR systems, remote sensing in the thermal infrared, and microwave remote sensing of the earth are considered. Finally, attention is given to lithologic and geobotanical studies, and geophysical sensing techniques and inversion theory.

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