Water Vapor Vertical Profiles on Mars in Dust Storms Observed by TGO/NOMAD
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The Nimbus 5 satellite is provided with a passive microwave spectrometer (NEMS) incorporating channels at 22.235 and 31.4 GHz to measure atmospheric water vapor and liquid water over ocean. The discussion covers principles of atmospheric water determination, accuracy of measurements, observations of specific storms and fronts, and observations of water vapor and liquid water on a global scale. The NEMS experiment has demonstrated the ability of a two-channel microwave spectrometer to determine integrated abundances of water vapor and liquid water with estimated rms accuracies of 0.2 and 0.01 g per sq cm, respectively. The data can be used to plot global maps or accumulate global statistics.
The amount of water vapor in the atmosphere helps to determine the likelihood that severe storms may develop. The concentration of water vapor, though, is highly variable in space and time. And yet small changes in water vapor concentration over a short period of time or over a short spatial distance can determine whether a storm may or may not develop. Therefore, in order to improve the ability to forecast severe weather such as thunderstorms it is important to measure water vapor in the atmosphere with high spatial and temporal resolution. One of the most attractive research tools for measuring water vapor in the atmosphere with high spatial and temporal resolution is a Raman lidar. A Raman lidar consists of a laser transmitter, a telescope receiver and optics and electronics for processing opticand electronic signals. A laser pulse is emitted into the atmosphere and it interacts with molecules in the atmosphere causing them to become excited and to emit, through the Raman process, photons of different wavelength than emitted by the laser. The molecule that emitted these emitted. This is the way that a Raman lidar identifies water vapor molecules in the atmosphere. can be identified based on the wavelength of the photons One of the great challenges in Raman lidar measurements has been to make useful daytime measurements of the water vapor profile under bright daytime conditions. In this first of two papers, we describe the instrumentation and analysis of the first documented Raman lidar that is able to measure water vapor in the daytime with sufficient quality to permit the study of developing storm systems.
General problems faced by hydrologists when using historical records, real time data, statistical analysis, and system simulation in providing quantitative information on the temporal and spatial distribution of water are related to the limitations of these data. Major problem areas requiring multispectral imaging-based research to improve hydrology models involve: evapotranspiration rates and soil moisture dynamics for large areas; the three dimensional characteristics of bodies of water; flooding in wetlands; snow water equivalents; runoff and sediment yield from ungaged watersheds; storm rainfall; fluorescence and polarization of water and its contained substances; discriminating between sediment and chlorophyll in water; role of barrier island dynamics in coastal zone processes; the relationship between remotely measured surface roughness and hydraulic roughness of land surfaces and stream networks; and modeling the runoff process.
Radar research that is directed toward improving storm forecasts and hazard warnings and studying lightning is discussed. The two moderately sensitive Doppler weather radars in central Oklahoma, with their wide dynamic range, have demonstrated the feasibility of mapping wind fields in all weather conditions from the clear skies of quiescent air and disturbed prestorm air near the earth's surface to the optically opaque interior of severe and sometimes tornadic thunderstorms. Observations and analyses of Doppler weather radar data demonstrate that improved warning of severe storm phenomena and improved short-term forecast of storms may be available when Doppler techniques are well integrated into the national network of weather radars. When used in combination with other sensors, it provides an opportunity to learn more about the complex interrelations between the wind, water, and electricity in storms.
ERTS imagery of Lake Superior in the late summer of 1972 shows dirty water near the city of Duluth. Water samples and simultaneous photographs were taken on three separate days following a heavy storm which caused muddy runoff water. The water samples were analyzed for turbidity, color, and solids. Reflectance and transmittance characteristics of the water samples were determined with a spectrophotometer apparatus. This same apparatus attached to a microdensitometer was used to analyze the photographs for the approximate colors or wavelengths of reflected energy that caused the exposure. Although other parameters do correlate for any one particular day, it is only the water quality parameter of turbidity that correlates with the aerial imagery on all days, as the character of the dirty water changes due to settling and mixing.
A research study is described in which the application to rainfall prediction of cloud liquid water data obtained from the SCAMS experiment of Nimbus 6 is explored. The study area is the Pacific Northwest coast of the United States, where rainfall is produced by extratropical storms that approach from across the Pacific Ocean. SCAMS data related to cloud liquid water over the ocean, and coastal rainfall data, are analyzed for 20 different storm systems in the northeastern Pacific Ocean; these produced significant rainfall from Washington to central California during the period October 1975-March 1976. Results show that the distribution of storm-cloud water analyzed from the SCAMS data over the ocean foreshadows the distribution of coastal rainfall accumulated from the storm at a later time. It is concluded that passive microwave sensor measurements of cloud water over the ocean, when used in conjunction with numerical and other objective guidance, can be used to enhance the accuracy of predictions of coastal rainfall distribution. Limitations in the SCAMS measurements and in the data analysis and interpretation are noted.
Over the years, hurricane track and intensity forecasts and storm surge models and the digital terrain and bathymetry data they depend on have improved significantly. Strides have also been made in knowledge of the detailed variation of the surface wind field driving the surge. The area of least improvement has been in obtaining data on the details of the temporal/spatial variation of the storm surge dome of water as it evolves and inundates the land to evaluate the performance of the numerical models. Tide gages in the vicinity of the landfall are frequently destroyed by the surge. Survey crews dispatched after the event provide no temporal information and only indirect indications of the maximum surge envelope over land. The landfall of Hurricane Bonnie on 26 August 1998, with a surge less than 2 m, provided an excellent opportunity to demonstrate the potential benefits of direct airborne measurement of the temporal/spatial evolution of storm surge. Despite a 160 m variation in aircraft altitude, an 11.5 m variation in the elevation of the mean sea surface relative to the ellipsoid over the flight track, and the tidal variation over the 5 hour data acquisition interval, a survey-quality Global Positioning System (GPS) aircraft trajectory allowed the NASA Scanning Radar Altimeter carried by a NOAA hurricane research aircraft to produce storm surge measurements that generally fell between the predictions of the NOAA SLOSH model and the North Carolina State University storm surge model.
The application to rainfall prediction of cloud liquid water data obtained from the SCAMS experiment of Nimbus-6 is explored. The study area is the Pacific Northwest coast of the United States, where rainfall is produced by extratropical storms that approach from across the Pacific Ocean. The SCAMS data related to cloud liquid water over the ocean, and coastal rainfall data, are analyzed for 20 different storm systems in the northeastern Pacific Ocean; these produced significant rainfall from Washington to central California during the period October 1975 through March 1976. Results show that the distribution of storm cloud water analyzed from the SCAMS data over the ocean foreshadows the distribution of coastal rainfall accumulated from the storm at a later time. It is concluded that passive microwave sensor measurements of cloud water over the ocean, when used in conjunction with numerical and other objective guidance, can be used to enhance the accuracy of predictions of coastal rainfall distribution. Limitations in the SCAMS measurements and in the data analysis and interpretation are noted.
Cities and towns along the tidal Hudson River are highly vulnerable to flooding through the combination of storm tides and high streamflows, compounded by sea level rise. Here a three-dimensional hydrodynamic model, validated by comparing peak water levels for 76 historical storms, is applied in a probabilistic flood hazard assessment. In simulations, the model merges streamflows and storm tides from tropical cyclones (TCs), offshore extratropical cyclones (ETCs) and inland "wet extratropical" cyclones (WETCs). The climatology of possible ETC and WETC storm events is represented by historical events (1931-2013), and simulations include gauged streamflows and inferred ungauged streamflows (based on watershed area) for the Hudson River and its tributaries. The TC climatology is created using a stochastic statistical model to represent a wider range of storms than is contained in the historical record. TC streamflow hydrographs are simulated for tributaries spaced along the Hudson, modeled as a function of TC attributes (storm track, sea surface temperature, maximum wind speed) using a statistical Bayesian approach. Results show WETCs are important to flood risk in the upper tidal river (e.g., Albany, New York), ETCs are important in the estuary (e.g., New York City) and lower tidal river, and TCs are important at all locations due to their potential for both high surge and extreme rainfall. The raising of floods by sea level rise is shown to be reduced by approximately 30-60 percent at Albany due to the dominance of streamflow for flood risk. This can be explained with simple channel flow dynamics, in which increased depth throughout the river reduces frictional resistance, thereby reducing the water level slope and the upriver water level.
On August 14, 2021, a Mw 7.2 earthquake struck the Tiburon Peninsula of western Haiti triggering thousands of landslides. Three days after the earthquake on August 17, 2021, Tropical Storm Grace crossed shallow waters offshore of southern Haiti triggering more landslides worsening the situation. In the aftermath of these events, several organizations with disaster response capabilities or programs activated to provide information on the location of landslides to first responders on the ground. Utilizing remote sensing to support rapid response, one organization manually mapped initiation point of landslides and three automatically detected landslides. The 2021 Haiti event also provided a unique opportunity to test different automated landslide detection methods that utilized both SAR and optical data in a rapid response scenario where rapid situational awareness was critical. As the methods used are highly replicable, the main goal of this study is to summarize the landslide rapid response products released by the organizations, detection methods, quantify accuracy and provide guidelines on how some of the shortcomings encountered in this effort might be addressed in the future. To support this validation, a manually mapped polygon-based landslide inventory covering the entire affected area was created and is also released through this effort.
NASA's Soil Moisture Active Passive (SMAP) Project now has completed its prime-phase (three years) mission and has entered a new five-year extended phase. The global L-band radiometry from SMAP has enabled diverse scientific investigations in water, energy and carbon cycle research, terrestrial ecology and ocean science. These include eliciting the role of soil moisture control on the evaporation regime and vegetation gross primary productivity, observing soil-vegetation continuum water relations, analysis of flood and droughts, climate modeling and weather prediction, detecting ocean high-winds during tropical storms, and observing fresh-water outflow in coastal oceans. This paper highlights the recent enhancements to the SMAP suite of science products (from instrument level-1 to geophysical retrievals level-2 and level-3).
Data were obtained from ERTS images for western Lake Superior for 1972-74. Data examination showed that for easterly winds the turbidity originating along the Wisconsin shore and the resuspension areas are transported northward then out along a N.E. path where it disperses, and often, for large storms, contaminates the Duluth water intake. Contaminants such as dredging fines anywhere along these paths would likewise find their way to the intake areas in concentrations comparable to the relative red clay concentration.
The field of sun-climate is beset with an extraordinary number of numerical correlations attempting to relate various periodicities of solar activity with changes in the Earth's weather and climate. Signatures representing climatological variability have been sought for cycles as short as the solar 28-day rotational period up to Milankovich periods of thousands of years, although a majority of correlations have concentrated on the 11-year sunspot and 22-year Hale double sunspot cycles. For the shorter term, parameters including temperature, pressure, winds storm tracks, rainfall, and water levels in rivers and lakes, etc. have been correlated with solar variability. For longer periods, it has been necessary to seek more indirect evidence in ice cores, tree rings, and geologic deep sea cores. Other atmospheric parameters relating to atmospheric electricity and the global electric circuit have also been correlated in similar fashion. Unfortunately, few, if any, of this wide spectrum of numerical correlations have been associated with any viable physical explanation, making most studies in the field an exercise in numerical statistics. More recently, a few suggestions for plausible coupling processes have begun to appear. These, coupled with new and stronger correlations involving selective binning of climatological data sets have injected new life and hope to this field. An overview is given of the historical past and current perspectives, to evaluate possible avenues for defining physical linking processes in the future.
While there have been several studies suggesting the possibility of electrical activity on Mars, to date there have been no measurements to search for evidence of such activity. In the absence of widespread water clouds and convective storm systems similar to those on the Earth and Jupiter, the most likely candidate for the creation of electrostatic charges and fields is triboelectric charging of dust, i.e., the friction between blown dust and the ground, and of dust particles with each other. Terrestrial experience demonstrates that electric fields 5 to 15 kV-m(exp -1) are not uncommon in dust storms and dust devils in desert regions, where the polarity varies according to the chemical composition and grain size. Simple laboratory experiments have demonstrated that modest electrostatic fields of roughly 5,000 V-m(exp -1) may be produced, along with electrical spark discharges and glow discharges, in a simulation of a dusty, turbulent Martian surface environment. While the Viking landers operated for several years with no apparent deleterious effects from electrostatic charging, this may have been at least partly due to good engineering design utilizing pre-1976 electronic circuitry to minimize the possibility of differential charging among the various system components. However, free roaming rovers, astronauts, and airborne probes may conceivably encounter an environment where electrostatic charging is a frequent occurrence, either by way of induction from a static electric field or friction with the dusty surface and atmosphere. This raises the possibility of spark discharges or current surges when subsequent contact is made with other pieces of electrical equipment, and the possibility of damage to modern microelectronic circuitry. Measurements of electrostatic fields on the surface of Mars could therefore be valuable for assessing this danger. Electric field measurements could also be useful for detecting natural discharges that originate in dust storms. This detection could be performed at distances ranging from 10s of km in the case of J-charge-like discharge signatures, to planetary distances if there exists a global electrical circuit or Schumann resonance spectrum.
A GEO-based Synthetic Aperture Radar (SAR) could provide daily coverage of basically all of North and South America with very good temporal coverage within the mapped area. This affords a key capability to disaster management, tectonic mapping and modeling, and vegetation mapping. The fine temporal sampling makes this system particularly useful for disaster management of flooding, hurricanes, and earthquakes. By using a fairly long wavelength, changing water boundaries caused by storms or flooding could be monitored in near real-time. This coverage would also provide revolutionary capabilities in the field of radar interferometry, including the capability to study the interferometric signature immediately before and after an earthquake, thus allowing unprecedented studies of Earth-surface dynamics. Preeruptive volcano dynamics could be studied as well as pre-seismic deformation, one of the most controversial and elusive aspects of earthquakes. Interferometric correlation would similarly allow near real-time mapping of surface changes caused by volcanic eruptions, mud slides, or fires. Finally, a GEO SAR provides an optimum configuration for soil moisture measurement that requires a high temporal sampling rate (1-2 days) with a moderate spatial resolution (1 km or better). From a technological point of view, the largest challenges involved in developing a geosynchronous SAR capability relate to the very large slant range distance from the radar to the mapped area. This leads to requirements for large power or alternatively very large antenna, the ability to steer the mapping area to the left and right of the satellite, and control of the elevation and azimuth angles. The weight of this system is estimated to be 2750 kg and it would require 20 kW of DC-power. Such a system would provide up to a 600 km ground swath in a strip-mapping mode and 4000 km dual-sided mapping in a scan-SAR mode.
Among the most productive ecosystems on earth, salt marshes provide crucial ecosystem services including water filtration, shoreline protection, storm surge buffering, and flood mitigation. Marshes are largely dependent on their sediment budget which can significantly vary across a region and can be used to determine the life span of the marsh. Upstream land use change near Charleston, South Carolina, along with rising sea levels, are expected to alter sediment budgets and threaten marsh stability and long-term health. The unvegetated-vegetated ratio (UVVR), developed by researchers at USGS, is a scalable and efficient method to assess vulnerability. The NASA DEVELOP National Program collaborated with the South Carolina Department of Natural Resources, the South Carolina Department of Health and Environmental Control, and the United States Geological Survey Woods Hole Coastal and Marine Science Center to apply the UVVR method within Google Earth Engine. Marsh vulnerability was analyzed using UVVR derived from clustering and manual interpretation of National Agriculture Imagery Program (NAIP) high-resolution aerial imagery. NAIP derived UVVR was aggregated to Landsat 8 Operational Land Imager (OLI) and Landsat 7 Enhanced Thematic Mapper (ETM+) resolution and projection. A Random Forest Regression between Landsat derived data and UVVR was modeled to estimate a potential relationship. The estimation of this relationship was used to produce temporal change analysis maps of salt marsh vulnerability back to 1984. The NAIP imagery processed through Google Earth Engine allowed us to make detailed UVVR maps for 2009, 2015, 2017, and 2019 for decision making within South Carolina. Google Earth Engine scripting provided a novel approach to UVVR methodology that will allow decision makers to input new marsh regions and easily calculate marsh vulnerability without external data downloading. These results were used to understand what areas of the marsh need most resource allocation in the future.
Among the most productive ecosystems on earth, salt marshes provide crucial ecosystem services including water filtration, shoreline protection, storm surge buffering, and flood mitigation. Marshes are largely dependent on their sediment budget which can significantly vary across a region. Upstream land use change near Charleston, South Carolina, along with rising sea levels, are expected to alter sediment budgets and threaten marsh stability and long-term health. The unvegetated-vegetated ratio (UVVR) is a scalable and efficient method to assess vulnerability. This NASA DEVELOP project collaborated with the South Carolina Department of Natural Resources, the South Carolina Department of Health and Environmental Control, and the United States Geological Survey Woods Hole Coastal and Marine Science Center. Marsh vulnerability was analyzed using UVVR derived from Landsat 8 Operational Land Imager (OLI) and Landsat 7 Enhanced Thematic Mapper (ETM+) in conjunction with National Agriculture Imagery Program (NAIP) high-resolution aerial imagery. A Landsat random forest regression showed a low correlation (r2 = 0.247) between Landsat 7 ETM+ bands and NAIP aggregated UVVR suggesting the need for a more complex model and higher resolution sensors. Google Earth Engine scripting provided a novel approach to UVVR methodology that will allow decision makers to input new marsh areas and easily calculate UVVR without external data downloading.