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At least 235 records · Page 13

Passive microwave measurements of temperature and salinity in coastal zones

Experimental methods and results from the maritime remote sensing (MARSEN) experiments using dual frequency microwave radiometer detecting systems on board aircraft are described. The radiometers were operated at 1.43 and 2.65 GHz and flown above U.S. Atlantic coastal areas, Chesapeake Bay, around Puerto Rico, and over the German Bight. The advanced switched radiometers used were configured to be independent of gain variations and errors originating from front-end losses and determined the absolute brightness temperatures to within a few tenths Kelvin. Corrections to the observed brightness temperature of the ocean are analytically defined, including accounts made for roughness, the cosmic background radiation, and the solar radio source. The coastal flight data for salinity gradients and surface temperatures were compared with sea truth measured from ships and found to be accurate to within 1 C and 1 pph.

Blume, H.-J. C.↗

Ship-based Observations and Climate Model Simulations of Cloud Phase over the Southern Ocean

The Southern Ocean (SO) clouds exert a significant influence on the Earth’s radiation budget. Here we analyzed ship-based remote sensing observations of SO clouds over a five-month long DOE ARM Measurements of Aerosols, Radiation and Clouds over the Southern Oceans (MARCUS) field campaign to better understand cloud phase variability. We developed a method to classify eight categories of hydrometeors (ice, liquid, mixed phase, rain, drizzle, snow, aerosols, and clear sky) based on measurements of lidar, radar and radiosondes. Cloud thermodynamic phases (liquid, ice and mixed phase) at coarser scales were further derived to compare with the DOE Energy Exascale Earth System Model version 1 (E3SMv1) simulation and the Earth Model Column Collaboratory (EMC 2 ) instrument simulator. For a scale-aware comparison with climate model simulations, we found that spatially averaging the raw remote sensing data (e.g., backscatter, reflectivity) results in increased cloud cover and cloud liquid, whereas, directly averaging cloud phase from higher to lower resolution maintains clear air regions and is thus recommended for in-cloud frequency comparisons. For cloud thermodynamic phases in stratiform clouds, the E3SM underestimates cloud ice and overestimates cloud liquid at temperatures between -40 and 0°C. When latitudes increase, both observations and simulations show a transition of dominant phase from liquid to ice for cloud tops as well as for the entire cloud columns, but the model underestimation of ice phase is more severe at higher latitudes. Such model bias is unlikely caused by spatial scale differences or lack of heterogeneity in cloud vertical structure in the simulation.

54 ENVIRONMENTAL SCIENCES↗

Remote sensing of land-surface temperature from HIRS/MSU data

A relaxation algorithm which permits meteorological parameters to be obtained from satellite data, without a priori assumptions about the properties of the other unknowns in the field of view, was developed. Atmospheric temperature profiles, atmospheric humidity, cloud cover, cloud top height, cloud top temperature, sea-surface temperature, land-surface temperature, snow cover, and ice cover are derived. Simultaneous determination of atmospheric and surface thermal structure and the cloud distribution provides information on heat sources and sinks, storage rates, and transport phenomena in the atmosphere. Such information is critical in determining the driving mechanisms for motions in the atmosphere and oceans and in improving numerical weather prediction.

Chahine, M. T.↗

Coastal Research Imaging Spectrometer

The Coastal Research Imaging Spectrometer (CRIS) is an airborne remote-sensing system designed specifically for research on the physical, chemical, and biological characteristics of coastal waters. The CRIS includes a visible-light hyperspectral imaging subsystem for measuring the color of water, which contains information on the biota, sediment, and nutrient contents of the water. The CRIS also includes an infrared imaging subsystem, which provides information on the temperature of the water. The combination of measurements enables investigation of biological effects of both natural and artificial flows of water from land into the ocean, including diffuse and point-source flows that may contain biological and/or chemical pollutants. Temperature is an important element of such measurements because temperature contrasts can often be used to distinguish among flows from different sources: for example, a sewage outflow could manifest itself in spectral images as a local high-temperature anomaly.anomaly. Both the visible and infrared subsystems scan in "pushbroom" mode: that is, an aircraft carrying the system moves along a ground track, the system is aimed downward, and image data are acquired in acrosstrack linear arrays of pixels. Both subsystems operate at a frame rate of 30 Hz. The infrared and visible-light optics are adjusted so that both subsystems are aimed at the same moving swath, which has across-track angular width of 15. Data from the infrared and visible imaging subsystems are stored in the same file along with aircraft-position data acquired by a Global Positioning System receiver. The combination of the three sets of data is used to construct infrared and hyperspectral maps of scanned areas shown.

Source record↗

Coastal Research Imaging Spectrometer

The Coastal Research Imaging Spectrometer (CRIS) is an airborne remote-sensing system designed specifically for research on the physical, chemical, and biological characteristics of coastal waters. The CRIS includes a visible-light hyperspectral imaging subsystem for measuring the color of water, which contains information on the biota, sediment, and nutrient contents of the water. The CRIS also includes an infrared imaging subsystem, which provides information on the temperature of the water. The combination of measurements enables investigation of biological effects of both natural and artificial flows of water from land into the ocean, including diffuse and point-source flows that may contain biological and/or chemical pollutants. Temperature is an important element of such measurements because temperature contrasts can often be used to distinguish among flows from different sources: for example, a sewage outflow could manifest itself in spectral images as a local high-temperature anomaly.

Lucey, Paul G.↗

Coastal Research Imaging Spectrometer

The Coastal Research Imaging Spectrometer (CRIS) is an airborne remote sensing system designed specifically for research on the physical, chemical, and biological characteristics of coastal waters. The CRIS includes a visible-light hyperspectral imaging subsystem for measuring the color of water, which contains information on the biota, sediment, and nutrient contents of the water. The CRIS also includes an infrared imaging subsystem, which provides information on the temperature of the water. The combination of measurements enables investigation of biological effects of both natural and artificial flows of water from land into the ocean, including diffuse and point-source flows that may contain biological and/or chemical pollutants. Temperature is an important element of such measurements because temperature contrasts can often be used to distinguish among flows from different sources: for example, a sewage outflow could manifest itself in spectral images as a local high-temperature anomaly. Both the visible and infrared subsystems scan in pushbroom mode: that is, an aircraft carrying the system moves along a ground track, the system is aimed downward, and image data are acquired in across-track linear arrays of pixels. Both subsystems operate at a frame rate of 30 Hz. The infrared and visible-light optics are adjusted so that both subsystems are aimed at the same moving swath, which has across-track angular width of 15 . Data from the infrared and visible imaging subsystems are stored in the same file along with aircraft- position data acquired by a Global Positioning System receiver. The combination of the three sets of data is used to construct infrared and hyperspectral maps of scanned areas (see figure). The visible subsystem is based on a grating spectrograph and a rapid-readout charge-coupled-device camera. Images of the swatch are acquired in 256 spectral bands at wavelengths from 400 to 800 nm. The infrared subsystem, which is sensitive in a single wavelength band of 8 to 10 m, is based on a focal-plane array of HgCdTe photodetectors that are cooled to an operating temperature of 77 K by use of a closed-Stirling-cycle mechanical cooler. The nonuniformities of the HgCdTe photodetector array are small enough that the raw pixel data from the infrared subsystem can be used to recognize temperature differences on the order of 1 C. By use of a built-in blackbody calibration source that can be switched into the field of view, one can obtain bias and gain offset terms for individual pixels, making it possible to offset the effects of nonuniformities sufficiently to enable the measurement of temperature differences as small as 0.1 C.

Lucey, Paul G.↗

Low Noise Amplifier Receivers from Millimeter Wave Atmospheric Remote Sensing

We currently achieve 3.4 dB noise figure at 183GHz and 2.1 dB noise figure at 90 GHz with our MMIC low noise amplifiers (LNAs) in room temperature. These amplifiers and the receivers we have built using them made it possible to conduct highly accurate airborne measurement campaigns from the Global Hawk unmanned aerial vehicle, develop millimeter wave internally calibrated radiometers for altimeter radar path delay correction, and build prototypes of large arrays of millimeter receivers for a geostationary interferometric sounder. We use the developed millimeter wave receivers to measure temperature and humidity profiles in the atmosphere and in hurricanes as well as to characterize the path delay error in ocean topography altimetry.

millimeter wave radiometers↗

Remote sensing of the thermal forcing on the tropical Pacific

Monthly fields of shortwave radiation (SR) and latent heat flux (LE) over the central and eastern tropical Pacific between 1980 and 1983 have been computed using satellite data. They are the dominant variable components of surface thermal forcing on the ocean in this time scale. During the 1982-1983 ENSO episode, surface-wind convergence and cloudiness associated with the displacement of equatorial organized convection caused a reduction in both the SR into the ocean and the LE out of the ocean. The lag-correlation coefficients between the forcing (SR-LE) and the sea surface temperature are found to be significantly high outside the equatorial region, showing that surface thermal forcing is the dominant factor in sea surface temperature change. In the narrow equatorial wave guide, ocean dynamics play a more important role, and surface heat flux is a consequence rather than the cause of sea surface temperature change.

Liu, W. Timothy↗

Coastal typologies and surface and subsurface characteristics of the Alaskan Beaufort Sea Coast

This dataset was generated to classify the Alaskan Beaufort Sea Coast (ABSC) into a set of distinct coastal typologies, to understand the surface and subsurface characteristics and variability of the ABSC, and to quantify relationships between these characteristics and historical rates of shoreline change. This geospatial dataset contains two csv files of points along the ABSC at a 50 m spacing, one for points sheltered by a barrier island and one for points exposed to the open ocean. Each point has a lat/lon location, and we have attributed to each point average values for elevation, historical long-term shoreline change rates, shoreline orientation, landcover, mean annual ground temperature, geomorphic unit, lithology, geology, ecological landscape unit, maximum thaw settlement potential, massive ice content, and segregated ice content. Each point is also assigned to one of 16 coastal typologies, determined by a hierarchical clustering algorithm on the elevation, shoreline change, orientation, and ground temperature data. There are 9 sheltered typologies and 7 exposed typologies, identified by an integer label in the last column of each csv file. The other two csv files contain the integer IDs and classes for the landcover and geomorphology datasets.

54 ENVIRONMENTAL SCIENCES↗

Measurement of SST and SSS Using Frequencies in the Range 0.3–2.0 GHz

Wide bandwidth radiometer systems that make measurements at multiple frequencies in the range from 300 MHz to 2 GHz have been proposed to address parameters important for understanding issues in the cryosphere associated with climate change such as ice sheet thickness and temperature. It is also possible with such a system to retrieve sea surface salinity (SSS), which is important for understanding the impact of climate change on ocean circulation at high latitude. In contemporary sensors for retrieving SSS, such as on Soil Moisture and Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP), sea surface temperature (SST), another parameter important for understanding ocean circulation and necessary in the retrieval of salinity, is treated as an ancillary parameter obtained from an independent source. However, both SSS and SST have peaks in sensitivity below 1 GHz; and it has been shown that measurements at multiple frequencies in this portion of the spectrum can take advantage of this peak in sensitivity to improve the accuracy of the retrieval of SSS. In this manuscript, it will be shown that there is also the potential to retrieve SST and, in cold water, the possibility for improved accuracy over existing retrievals.

Microwave remote sensing↗

Intercomparison of independent estimates of cloud properties from simultaneous satellite observations

Preliminary results are reported from comparisons between two techniques for determining the cloud cover fraction within a satellite remote sensing scene. One method (PRM) quantifies cloud-free and cloud-filled areas on the bases of physical relationships between temperature, humidity, cloud optical properties and emitted radiation. The other approach (RSSM) derives the fractional cover from the spatial structure of radiances detected by the sensor. The HIRS (PRM) and the AVHRR (RSSM) instruments, tuned to IR wavelengths, on the TIROS-N polar-orbiting satellite furnished the trial data. Sample results are provided from scans at 15 and 11 microns over the Pacific Ocean.

Coakley, J. A., Jr.↗

Aircraft remote sensing of phytoplankton spatial patterns during the 1989 Joint Global Ocean Flux Study (JGOFS) North Atlantic bloom experiment

Mesoscale phytoplankton chlorophyll variability near the Joint Global Ocean Flux study sites along the 20 W meridian at 34 N, 47 N, and 59 N is discussed. The NASA P-3 aircraft and the Airborne Oceanographic Lidar (AOL) system provides remote sensing support for the North Atlantic Bloom Experiment. The principal instrument of the AOL system is the blue-green laser that stimulates fluorescence from photoplankton chlorophyll, the principal photosynthetic pigment. Other instruments on the NASA P-3 aircraft include up- and down-looking spectrometers, PRT-5 for infrared measurements to determine sea surface temperature, and a system to deploy and record AXBTs to measure subsurface temperature structure.

Yoder, James A.↗

Understanding Relationships Between Satellite, Model, and Ground-Based Surface Temperature Characterizations From Overcast to Clear Conditions in Support of Satellite Remote Sensing of Clouds and Radiation

Accurate and consistent global estimates of cloud coverage and their properties are fundamental to long-term Earth radiation budget (ERB) monitoring efforts like the Clouds and the Earth’s Radiant Energy System (CERES) project. Cloud detection algorithms often apply thresholding approaches to identify where clouds occur by comparing satellite-measured radiances with those that are expected under cloud-free conditions. In addition, once a cloud is detected, the derivation of cloud optical and microphysical properties also requires knowledge of the background radiances below the cloud. In the infrared, knowledge of the surface emissivity and the expected skin temperature under both cloudy and cloud-free conditions is needed. These traits are generally well known over the oceans. Over land, however, comparisons between satellite-derived land surface temperature (LST) with that characterized in numerical weather analyses reveal large differences in many parts of the world, often exceeding 5 K, which can lead to significant satellite cloud detection and cloud property retrieval errors. Furthermore, clouds have a dramatic influence on the LST, and therefore characterization of that model parameter also depends on the capability of the model to accurately resolve clouds. Thus, the LST characterized in models is, at times, a poor approximation for what would otherwise be observed, thereby impeding accurate satellite cloud retrievals. As a result, we seek to develop a more robust method for estimating the LST required for satellite cloud characterizations. This effort is accomplished through a combination of surface emission/air temperature relationship studies in all-sky conditions using ground measurement stations, along with deep neural network (DNN) estimates of expected LST under overcast and cloud-free conditions. We demonstrate that substituting DNN-predicted LST for that generated by numerical models can mitigate model-inherent diurnal dependencies and reduce overall bias and uncertainty relative to satellite/ground observations by 0.5–4 K and 0.5–2 K, respectively. It is expected that this work will lead to improved satellite cloud retrievals that enhance ERB monitoring efforts.

B Scarino↗

Remote sensing as a research tool

The application of aircraft and spacecraft remote sensing techniques to sea ice surveillance is evaluated. The effects of ice in the air-sea-ice system are examined. The measurement principles and characteristics of remote sensing methods for aircraft and spacecraft surveillance of sea ice are described. Consideration is given to ambient visible light, IR, passive microwave, active microwave, and laser altimeter and sonar systems. The applications of these systems to sea ice surveillance are discussed and examples are provided. Particular attention is placed on the use of microwave data and the relation between ice thickness and sea ice interactions. It is noted that spacecraft and aircraft sensing techniques can successfully measure snow cover; ice thickness; ice type; ice concentration; ice velocity field; ocean temperature; surface wind vector field; and air, snow, and ice surface temperatures.

Carsey, F. D.↗

Bias-Correcting Carbon Fluxes Derived From Land-Surface Satellite Data for Retrospective and Near Real-Time Assimilation Systems

The ability to monitor and understand natural and anthropogenic variability in atmospheric carbon dioxide(CO2) is a growing need of many stakeholders across the world. Systems that assimilate satellite observations, given their short latency and dense spatial coverage, into high resolution global models are valuable, if not essential, tools for addressing this need. A notable drawback of modern assimilation systems is the long latency of many vital in-put datasets, e.g., inventories, in situ measurements, and re-processed remote-sensing data can trail the current date by months to years. This paper describes techniques for bias-correcting surface fluxes derived from satellite observations of the Earth’s surface to be consistent with constraints from inventories and in situ CO2 datasets. The techniques are applicable in both short-term forecasts and retrospective simulations, thus taking advantage of the coverage and short latency of satellite data while reproducing the major features of long-term inventory and in situ records. Our approach begins with a standard collection of diagnostic fluxes which incorporate a variety of remote-sensing driver data, viz. vegetation indices, fire radiative power, and nighttime lights. We then apply an empirical sink so that global budgets of the diagnostic fluxes match given atmospheric and oceanic growth rates for each year. This step removes coherent, systematic flux errors that produce biases inCO2which mask the signals an assimilation system hopes to capture. Depending on the simulation mode, the empirical sink uses different choices of atmospheric growth rates: estimates based on observations in retrospective mode and projections based on seasonal fore-casts of sea surface temperature in forecasting mode. The retrospective fluxes, when used in simulations with NASA’s Goddard Earth Observing System (GEOS), reproduce marine boundary layer measurements with comparable skill to those using fluxes from a modern inversion system. The forecasted fluxes show promising accuracy in their application to the analysis of changes in the carbon cycle as they occur.

CO2↗

Making a Superbolt: Reconciling Observations of the Optically Brightest Lightning on Earth From Different Satellites

We previously documented geographic distributions of the optically brightest lightning on Earth—known as “superbolts”—using two space-based instruments: the photodiode detector (PDD) on the Fast On-orbit Recording of Transient Events (FORTE) satellite and the Geostationary Lightning Mapper (GLM) on NOAA's Geostationary Operational Environmental Satellites. In this study, we further examine the superbolts identified by the PDD and GLM to reconcile the differences between their geographic distributions. We find that both the physical extent of the parent flash and the development speed of its leaders are important for making a superbolt. The oceanic PDD superbolts tend to occur early in flashes that rapidly expand laterally into long horizontal “megaflashes.” The top GLM superbolts occur over land at later times in particularly large megaflashes. These land-based flashes grow more slowly until they extend over multiple hundreds of kilometers. The FORTE PDD missed these delayed superbolts due to limitations in its triggering. Coincident Tropical Rainfall Measuring Mission measurements show that the warm season megaflash superbolts detected by Lightning Imaging Sensor/GLM and wintertime oceanic superbolts observed by the PDD occur in otherwise similar thunderstorm environments. Both are marked by: low storm heights (<10 km), widespread precipitation near the surface, small infrared brightness temperature gradients, and low flash rates. We suggest that the vertically compact, stratiform nature of these clouds provides favorable conditions for superbolt production.

54 ENVIRONMENTAL SCIENCES↗

FOREWORD: Satellite Remote Sensing Beyond 2015

Satellite remote sensing has progressed tremendously since the first Landsat was launched on June 23, 1972. Since the 1970s, satellite remote sensing and associated airborne and in situ measurements have resulted in vital and indispensable observations for understanding our planet through time. These observations have also led to dramatic improvements in numerical simulation models of the coupled atmosphere-land-ocean systems at increasing accuracies and predictive capability. The same observations document the Earth's climate and are driving the consensus that Homo sapiens is changing our climate through greenhouse gas emissions. These accomplishments are the combined work of many scientists from many countries and a dedicated cadre of engineers who build the instruments and satellites that collect Earth observation data from satellites, all working toward the goal of improving our understanding of the Earth. This edition of the Remote Sensing Handbook (Vol. I, II, and III) is a compendium of information for many research areas of our Planet that have contributed to our substantial progress since the 1970s. Remote sensing community is now using multiple sources of satellite and in situ data to advance our studies, what ever they might be. In the following paragraphs, I will illustrate how valuable and pivotal role satellite remote sensing has played in climate system study over last five decades, The Chapters in the Remote Sensing Handbook (Vol. I, II, and III) provides many other specific studies on land, water, and other applications using EO data of last five decades, The Landsat system of Earth-observing satellites has led the way in pioneering sustained observations of our planet. From 1972 to the present, at least one and sometimes two Landsat satellites have been in operation. Starting with the launch of the first NOAA-NASA Polar Orbiting Environmental Satellites NOAA-6 in 1978, improved imaging of land, clouds, and oceans and atmospheric soundings of temperature were accomplished. The NOAA system of polar-orbiting meteorological satellites has continued uninterrupted since that time, providing vital observations for numerical weather prediction. These same satellites are also responsible for the remarkable records of sea surface temperature and land vegetation index from the Advanced Very High Resolution Radiometers (AVHRR) that now span more than 33 years, although no one anticipated these valuable climate records from this instrument before the launch of NOAA-7 in 1981. The success of data from the AVHRR led to the design of the MODIS instruments on NASA's Earth Observing System of satellite platforms that improved substantially upon the AVHRR. The first of the EOS platforms, Terra, was launched in 2000 and the second of these platforms, Aqua, was launched in 2002.

Tucker, Compton J.↗

Identifying Meteorologic and Oceanic Conditions Contributing to a Unique Phytoplankton Bloom Occurrence in Micronesia during October 2013

On the first several days of October 2013, daily chlorophyll a (chl a) data acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the National Aeronautics and Space Administration (NASA) Aqua satellite detected a marked increase in chlorophyll a concentrations (chl a) in the vicinity of Chuuk Lagoon and the Federated States of Micronesia. Such an increase, likely indicative of a phytoplankton bloom, has not been observed in this location at any other time during the MODIS-Aqua mission, which commenced in 2002 and continues to present. Examination of sea surface wind data from the Modern Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) reanalysis dataset indicated that the region experienced a sequence of alternating elevated and very low wind speed events prior to the observation of the bloom. The influence of the winds can be seen in MERRA-2 sea surface skin temperature data. Elevated windspeeds for several days likely induced a mixing of deeper waters with higher nutrient levels to the surface, which was followed by stratification and phytoplankton growth during low wind intervals and finally transport induced by a brief high windspeed event. Analysis of hourly MERRA-2 maximum windspeed data over a 40-year period indicated that this sequence was climatologically rare.

Remote Sensing↗