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At least 127 records · Page 7

Deforestation and Secondary Growth in Rondonia, Brazil from SIR-C SAR and Landsat.SPOT data

Covers problems with existing data collected with high-resolution optical sensors. They say active microwave sensors could complement other sensors in getting through things like cloud cover. They analyzed SIR-C data in combination with Landsat TM data, a 9-year time series of SPOT XS data, and a preliminary field survey. They report findings and draw conclusions, including that SARs operating at long radar wavelengths, with both like and cross-polarizations, are needed for tropical deforestation studies.

high-resolution optical sensors SIR-C SAR SPOT↗

Superconducting Sensors for Microwave and Optical Photon-Starved Communications (Plenary)

NASA mission modeling indicates a desire for approximately a tenfold data improvement per decade from the Deep Space Network through the year 2040. Some of this improvement will come from aperture enhancement and antenna arraying, increased use of Ka-band over X-band, and high performance optical terminals (e.g. 12 m ground telescope). The remainder will depend on "disruptive" technologies. Deep-space communications differs from near earth communications. One way light travel times are measured in minutes rather than seconds and distances involved are large enough such that optical signals are photon limited and microwave signals have extremely low flux density. High frequency SQIF receivers and single photon detectors for optical communications will be described. Specifically, progress towards a "noiseless" receiver based on arrays of incommensurate area SQUIDs, and single photon counting detectors based on superconducting nanowires and kinetic inductance effects, will be discussed. Finally, the design of an optimal array of optical telescopes to emulate performance of a monolithic 12 m telescope will be outlined. In this case, optimal means minimizing the initial capital investment and operational cost while maintaining performance requirements of the deep-space link.

Romanofsky, Bob↗

Detecting Hail from Space: Using a Multi-Frequency Passive-Microwave Retrieval to Analyze the Global Climatology and Diurnal Cycle of Severe Hail

Severe hail poses myriad threats to society, causing extensive damage to infrastructure and agriculture. As hail is severe, relatively infrequent, and highly localized, it is difficult to measure in-situ and if left unresolved in models and precipitation retrievals, hail can cause large errors and uncertainties. The difficulty in measuring hail in situ and the inconsistency of surface-based hail reporting drive the motivation to use spaceborne remote-sensing platforms to retrieve hail and construct climatologies in a globally uniform way. We leverage the scattering signatures of severe hail in spaceborne passive-microwave datasets paired with surface hail reports to construct a multi-frequency hail retrieval using Tropical Rainfall Measuring Mission (TRMM) microwave imager (TMI) data. Using coincident Global Precipitation Measurement (GPM) Ku-band precipitation radar, we assessed this retrieval and several others in the literature for their effectiveness and regional variability. We use this retrieval to construct global passive-microwave climatologies of severe hail using the TRMM, GPM, Advanced Microwave Scanning Radiometer for EOS (AMSR-E), and Advanced Microwave Scanning Radiometer 2 (AMSR2) sensors and extend into the pre-TRMM era to the Special Sensor Microwave Imager/Sounder (SSMI/(S)) data. We also leverage the sensors in inclined orbits to assess the diurnal variability of severe hail globally and the effect the diurnal cycle has on the detection of hail by sensors in sun-synchronous orbit. The goal is to construct a robust, multi-decade multi-satellite climatology of hail. As part of the NASA Disasters Applied Sciences program, we assess these climatologies against other satellite severe weather datasets and use these climatologies in collaboration with stakeholders and end-users to help them assess risk, and improve the prediction, preparation, and response to severe storms around the world.

Sarah D Bang↗

Quantifying Uncertainties in Land-Surface Microwave Emissivity Retrievals

Uncertainties in the retrievals of microwaveland-surface emissivities are quantified over two types of land surfaces: desert and tropical rainforest. Retrievals from satellite-based microwave imagers, including the Special Sensor Microwave Imager, the Tropical Rainfall Measuring Mission Microwave Imager, and the Advanced Microwave Scanning Radiometer for Earth Observing System, are studied. Our results show that there are considerable differences between the retrievals from different sensors and from different groups over these two land-surface types. In addition, the mean emissivity values show different spectral behavior across the frequencies. With the true emissivity assumed largely constant over both of the two sites throughout the study period, the differences are largely attributed to the systematic and random errors inthe retrievals. Generally, these retrievals tend to agree better at lower frequencies than at higher ones, with systematic differences ranging 1%-4% (3-12 K) over desert and 1%-7% (3-20 K) over rainforest. The random errors within each retrieval dataset are in the range of 0.5%-2% (2-6 K). In particular, at 85.5/89.0 GHz, there are very large differences between the different retrieval datasets, and within each retrieval dataset itself. Further investigation reveals that these differences are most likely caused by rain/cloud contamination, which can lead to random errors up to 10-17 K under the most severe conditions.

Land-Surface↗

Multifrequency remote sensing of soil moisture

Multifrequency sensor data collected at Guymon, Oklahoma and Dalhart, Texas using NASA's C-130 aircraft were used to determine which of the all-weather microwave sensors demonstrated the highest correlation to surface soil moisture over optimal bare soil conditions, and to develop and test techniques which use visible/infrared sensors to compensate for the vegetation effect in this sensor's response to soil moisture. The L-band passive microwave radiometer was found to be the most suitable single sensor system to estimate soil moisture over bare fields. In comparison to other active and passive microwave sensors the L-band radiometer (1) was influenced least by ranges in surface roughness; (2) demonstrated the most sensitivity to soil moisture differences in terms of the range of return from the full range of soil moisture; and (3) was less sensitive to errors in measurement in relation to the range of sensor response. L-band emissivity related more strongly to soil moisture when moisture was expressed as percent of field capacity. The perpendicular vegetation index as determined from the visible/infrared sensors was useful as a measure of the vegetation effect on the L-band radiometer response to soil moisture.

Theis, S. W.↗

Microwave reflectometer ionization sensor

The development of the Microwave Reflectometer Ionization Sensor (MRIS) Instrument for use on the Aeroassist Flight Experiment (AFE) spacecraft is described. The instrument contract was terminated, due to cancellation of the AFE program, subsequent to testing of an engineering development model. The MRIS, a four-frequency reflectometer, was designed for the detection and location of critical electron density levels in spacecraft reentry plasmas. The instrument would sample the relative magnitude and phase of reflected signals at discrete frequency steps across 4 GHz bandwidths centered at four frequencies: 20, 44, 95, and 140 GHz. The sampled data would be stored for later processing to calculate the distance from the spacecraft surface to the critical electron densities versus time. Four stepped PM CW transmitter receivers were located behind the thermal protection system of the spacecraft with horn antennas radiating and receiving through an insulating tile. Techniques were developed to deal with interference, including multiple reflections and resonance effects, resulting from the antenna configuration and operating environment.

Seals, Joseph↗

Variations in Upper-Tropospheric Humidity and Convective Processes as Seen from SSM/T-2

Water vapor feedback, particularly involving water vapor in the upper troposphere (UTH), is widely regarded as the process with the most potential to amplify anthropogenic greenhouse forcing. Yet, our ability to quantify observationally water vapor variations in the current climate and the relationships to convective processes remains rather crude. Remote sensing from polar orbiting instruments has played a major role in documenting UTH variability, supplementing highly undersampled and poorly calibrated rawinsonde measurements. Most of our observational understanding of UTH has come from the 6.7 micrometer channel measurements which are subject to cloud contamination uncertainties. In this work we examine UTH variations present in the Special Sensor Microwave Temperature Sounder 2 (SSM/T-2) sensors flying aboard Defense Military Satellite Program (DMSP) polar orbiting satellites during the period 1993 through 2001. We employ data from the the 183.3 +/- 1 GHz channel which is far less sensitive to cirrus than IR methods. Our primary focus is on obtaining more reliable statistics of interannual behavior; i.e. How close to constant RH are interannual variations in T2 UTH over the tropics? How do temperature and moisture variations contribute regionally? The 1997/1998 strong ENS0 warming event and adjacent cool periods provide a strong signal to study, albeit a perturbation of natural climate variability. Modeling the 183.3 GHz channel using reanalysis temperature data, but with climatological water vapor, allows us to infer the separate contribution by water vapor in the observations. In addition, frozen hydrometeors produced by deep convection are also captured in the 150 GHz oxygen channel, providing an opportUnity to relate the incidence of deep convection to water vapor variability. Our results indicate a much larger variation of 183.3 GHz brightness temperatures would be observed were it not for water vapor variations positively correlated with tropical SSTs. Comparisons are made with previous studies using both IR and microwave observations to characterize UTH response to tropical SSTs.

Robertson, Franklin R.↗

Frequency band justifications for passive sensors, 1 to 10 GHz

Remote sensor systems operating in the microwave region of the frequency spectrum provide information unobtainable with basic imaging techniques such as photography, television, or multispectral imaging. The frequency allocation requirements for passive microwave sensors used in the earth exploration satellite and space research services are presented for: (1) agriculture, forestry, and range resources; (2) land use survey and mapping: (3) water resources; (4) weather and climate; (5) environmental quality; and (6) marine resources, estuarine and oceans. Because measurements are required simultaneously in multiple frequency bands to adequately determine values of some phenomena, the relationships between frequency bands are discussed. The various measurement accuracies, dynamic range, resolutions and frequency needs are examined. A band-by-band summary of requirements, unique aspects, and sharing analyses of the required frequency bands is included.

Source record↗

Sensing the earth's environment from space - User needs and technology opportunities

Results of a number of studies involving industry, universities and government agencies working in concert to identify specific measurement and data needs in the field of satellite remote sensing are discussed. Comparisons are made with existing sensor capabilities and with the trends in the supporting technology. A series of tables is presented describing, among other things, user subcommittees using remote sensing data, atmosphere, ocean, land and cryosphere measurement needs and funded capabilities, and the capability status of such sensors as passive and active microwave sensors, visible and IR radiometers and laser sensors.

Nagler, R. G.↗

Satellite observations of sea ice

Attention is given to techniques developed by NASA for the satellite acquisition of polar ice cover data, as well as for the spotlighting of selected ice cover areas in order to reveal detailed ice pack features. Of the visible, IR and microwave sensors available aboard satellites, only microwave units operate day and night and in all weather conditions to provide global synoptic coverage. Microwave may be either passive or active; the former include the Electrically Scanning Microwave Radiometer aboard Nimbus-5 and the Scanning Multichannel Microwave Radiometer of Seasat and Nimbus-7, while the latter are represented by synthetic aperture radars and radar altimeters aboard Seasat.

Thomas, R. H.↗

In-situ measurements for validation of microwave data - Problems, accuracies

This review covers the relationship between remotely sensed microwave data and data obtained in situ or from earth-based remote-sensing systems, both for validation of algorithms and as supplemental information for deriving a geophysical quantity. Parameters obtained from satellite microwave radiometers, the Scanning Multichannel Microwave Radiometer, and the Special Sensor Microwave Imager are emphasized. These include sea-surface temperature and wind speed, integrated atmospheric water vapor, cloud liquid water, and rain rate.

Katsaros, Kristina B.↗

Synergistic use of multispectral satellite data for monitoring land surface change

Observations by the Advanced Very High Resolution Radiometer (AVHRR) onboard the NOAA satellites were used to compute visible and near infrared reflectances and surface temperature, while passive microwave observations at 37 GHz frequency by the Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave Imager (SSM/I) on board, respectively, the Nimbus-7 and DMSP-F8 satellites were used to compute polarization difference. These observations were analyzed along transects from rainforest to desert over northern Africa for the period 1979-1987, which included an unprecedented drought during 1984 over the Sahel zone. Model simulations were made to understand the interrelationship among multispectral data.

Choudhury, Bhaskar J.↗

The effect of severe storms on the ice cover of the northern Tatarskiy Strait

Passive microwave images from the Special Sensor Microwave Imager are used to study the volume of ice and sea-bottom water in the Japan Sea as affected by winds and severe storms. The data set comprises brightness temperatures gridded on a polar stereographic projection, and the processing is accomplished with a linear algorithm by Cavalieri et al. (1983) based on the vertically polarized 37-GHz channel. The expressions for calculating heat fluxes and downwelling radiation are given, and ice-cover fluctuations are correlated with severe storm events. The storms generate large transient polynya that occur simultaneously with the strongest heat fluxes, and severe storms are found to contribute about 25 percent of the annual introduction of 25 cu km of ice in the region. The ice production could lead to the renewal of enough sea-bottom water to account for the C-14 data provided, and the generation of Japan Sea bottom water is found to vary directly with storm activity.

Martin, Seelye↗

Convective climatology over the southwest U.S. and Mexico from passive microwave and infrared data

Passive microwave data from the Special Sensor Microwave Imager (SSM/I) were used to estimate the amount of rainfall in the June-August season for the regions of the southwest U.S. and Mexico, and the results are compared to rain-gauge observations and to IR climatologies of Maddox et al. (1992), using both the hourly IR data and IR data sampled at the time of the overpass of the SSM/I. A comparison of the microwave climatology with monthly rainfall measured by the climatological gage network over several states of western Mexico resulted in a 0.63 correlation and a large (482 mm) bias, due to sampling and the incongruity of rain gages and satellite estimates. A comparison between the IR and microwave data showed that the IR tended toward higher percentages along the coast compared to the microwave.

Negri, Andrew J.↗

Climate Sensitivity Studies of the Greenland Ice Sheet Using Satellite AVHRR, SMMR, SSM/I and in Situ Data

The feasibility of using satellite data for climate research over the Greenland ice sheet is discussed. In particular, we demonstrate the usefulness of Advanced Very High Resolution Radiometer (AVHRR) Local Area Coverage (LAC) and Global Area Coverage (GAC) data for narrow-band albedo retrieval. Our study supports the use of lower resolution AVHRR (GAC) data for process studies over most of the Greenland ice sheet. Based on LAC data time series analysis, we can resolve relative albedo changes on the order of 2-5%. In addition, we examine Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave Imager (SSM/I) passive microwave data for snow typing and other signals of climatological significance. Based on relationships between in situ measurements and horizontally polarized 19 and 37 GHz observations, wet snow regions are identified. The wet snow regions increase in aerial percentage from 9% of the total ice surface in June to a maximum of 26% in August 1990. Furthermore, the relationship between brightness temperatures and accumulation rates in the northeastern part of Greenland is described. We found a consistent increase in accumulation rate for the northeastern part of the ice sheet from 1981 to 1986.

Steffen, K.↗

A Prototype MODI- SSM/I Snow Mapping Algorithm

Data in the wavelength range 0.545 - 1.652 microns from the Moderate Resolution Imaging Spectroradiometer (MODIS), to be launched aboard the Earth Observing System (EOS) Terra in the fall of 1999, will be used to map daily global snow cover at 500m resolution. However, during darkness, or when the satellite's view of the surface is obscured by cloud, snow cover cannot be mapped using MODIS data. We show that during these conditions, it is possible to supplement the MODIS product by mapping the snow cover using passive microwave data from the Special Sensor Microwave Imager (SSM/I), albeit with much poorer resolution. For a 7-day time period in March 1999, a prototype MODIS snow-cover product was compared with a prototype MODIS-SSM/I product for the same area in the mid-western United States. The combined MODIS-SSM/I product mapped 9% more snow cover than the MODIS-only product.

Tait, Andrew B.↗

Combined Microwave and Sferics Measurements as a Continuous Proxy for Latent Heating in Mesoscale Model Predictions

Planar rainfall distributions were retrieved from data provided by the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and Special Sensor Microwave Imager (SSM/I) radiometers. Lightning generates Very Low Frequency (VLF) radio noise pulses called sferics. Those pulses propagate over large distances so that they can be continuously monitored with a network of ground based radio receivers. An empirical relationship between the sferics rate and the convective rainfall permitted maps of convective latent heating profiles to be derived continuously from the sferics distributions. Those inferred latent heating rates were assimilated into the Penn State/NCAR Mesoscale Model (MM5) that depicted an intense winter cyclone that passed over Florida on 2 February 1998. When compared to a 14 hour MM5 rainfall forecast using conventional data, the use of lightning data improved the forecast.

Chang, D. -E.↗

Remotely Sensed Precipitation from the January 2000 East Coast Blizzard

Initial precipitation forecasts of the January 2000 blizzard were unable to adequately alert emergency response along the eastern seaboard. Cyclogenesis, over the Gulf of Mexico was a contributing cause of that problem. We present distributions of precipitation derived from spaceborne microwave measurements from the Special Sensor Microwave/ Imager (SSM/I) and the TRMM Microwave Imager (TMI) supplemented by NWS operational radar and the National lightning Detection Network (NLDN) Long-Range (LR) product. The combined NWS radar and NLDN-LR data revealed the location of precipitation between 1/23 and 1/27/2000 over the US, the Gulf and the Atlantic Ocean. The remotely sensed precipitation distributions are compared to the precipitation inferred from coincident TMI observations.

Chang, D.-E.↗