Visible and infrared imagery from meteorological satellites
Visible and IR imagery by meteorological satellites measuring surface temperature, atmospheric circulation and state parameters, storm development and tracking, cloud motions, etc
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Visible and IR imagery by meteorological satellites measuring surface temperature, atmospheric circulation and state parameters, storm development and tracking, cloud motions, etc
The five-minute rapid-scan imagery from the Synchronous Meteorological Satellite is employed to study cloud motions associated with the Omaha tornado of May 6, 1975. Cloud-motion vectors derived from automated and man-machine interactive systems provide an account of the mesoscale phenomena. In addition to the geostationary satellite data, aerial photography obtained during a cloud-truth mission is used in the severe storm investigation. For tracking overland cumuli with short half-lives, a three-minute scan interval appears necessary for the satellite imagery.
Lightning measurements acquired principally by a ground-based network of magnetic direction finders are used to diagnose and predict the existence, temporal evolution, and decay of thunderstorms over a wide range of space and time scales extending over four orders of magnitude. The non-linear growth and decay of thunderstorms and their accompanying cloud-to-ground lightning activity is described by the three parameter logistic growth model. The growth rate is shown to be a function of the storm size and duration, and the limiting value of the total lightning activity is related to the available energy in the environment. A new technique is described for removing systematic bearing errors from direction finder data where radar echoes are used to constrain site error correction and optimization (best point estimate) algorithms. A nearest neighbor pattern recognition algorithm is employed to cluster the discrete lightning discharges into storm cells and the advantages and limitations of different clustering strategies for storm identification and tracking are examined.
Microwave remote sensing observations of hurricanes, from NOAA and USAF hurricane surveillance aircraft, provide vital data for hurricane research and operations, for forecasting the intensity and track of tropical storms. The current operational standard for hurricane wind speed and rain rate measurements is the Stepped Frequency Microwave Radiometer (SFMR), which is a nadir viewing passive microwave airborne remote sensor. The Hurricane Imaging Radiometer, HIRAD, will extend the nadir viewing SFMR capability to provide wide swath images of wind speed and rain rate, while flying on a high altitude aircraft. HIRAD was first flown in the Genesis and Rapid Intensification Processes, GRIP, NASA hurricane field experiment in 2010. This paper reports on geophysical retrieval results and provides hurricane images from GRIP flights. An overview of the HIRAD instrument and the radiative transfer theory based, wind speed/rain rate retrieval algorithm is included. Results are presented for hurricane wind speed and rain rate for Earl and Karl, with comparison to collocated SFMR retrievals and WP3D Fuselage Radar images for validation purposes.
Global mean sea level (GMSL) has risen by about 7-8 inches (about 16-21 cm) since 1900, with about 3 of those inches (about 7 cm) occurring since 1993. Human-caused climate change has made a substantial contribution to GMSL rise since 1900, contributing to a rate of rise that is greater than during any preceding century in at least 2,800 years. Relative to the year 2000, GMSL is very likely to rise by 0.3-0.6 feet (9-18 cm) by 2030, 0.5-1.2 feet (15-38 cm) by 2050, and 1.0-4.3 feet (30-130 cm) by 2100. Future pathways have little effect on projected GMSL rise in the first half of the century, but significantly affect projections for the second half of the century. Emerging science regarding Antarctic ice sheet stability suggests that, for high emission scenarios, a GMSL rise exceeding 8 feet (2.4 m) by 2100 is physically possible, although the probability of such an extreme outcome cannot currently be assessed. Regardless of pathway, it is extremely likely that GMSL rise will continue beyond 2100. Relative sea level (RSL) rise in this century will vary along U.S. coastlines due, in part, to changes in Earth's gravitational field and rotation from melting of land ice, changes in ocean circulation, and vertical land motion (very high confidence). For almost all future GMSL rise scenarios, RSL rise is likely to be greater than the global average in the U.S. Northeast and the western Gulf of Mexico. In intermediate and low GMSL rise scenarios, RSL rise is likely to be less than the global average in much of the Pacific Northwest and Alaska. For high GMSL rise scenarios, RSL rise is likely to be higher than the global average along all U.S. coastlines outside Alaska. Almost all U.S. coastlines experience more than global mean sea level rise in response to Antarctic ice loss, and thus would be particularly affected under extreme GMSL rise scenarios involving substantial Antarctic mass loss. As sea levels have risen, the number of tidal floods each year that cause minor impacts (also called "nuisance floods") have increased 5- to 10-fold since the 1960s in several U.S. coastal cities. Rates of increase are accelerating in over 25 Atlantic and Gulf Coast cities. Tidal flooding will continue increasing in depth, frequency, and extent this century. Assuming storm characteristics do not change, sea level rise will increase the frequency and extent of extreme flooding associated with coastal storms, such as hurricanes and nor'easters. A projected increase in the intensity of hurricanes in the North Atlantic could increase the probability of extreme flooding along most of the U.S. Atlantic and Gulf Coast states beyond what would be projected based solely on RSL rise. However, there is low confidence in the projected increase in frequency of intense Atlantic hurricanes, and the associated flood risk amplification and flood effects could be offset or amplified by such factors as changes in overall storm frequency or tracks.
Tropopause-overshooting cloud locations, their volume, and the percentage of anvil cloud occupied by overshooting were quantified from state-of-the-art merged NEXRAD radar and GOES-16/17 satellite products during the 2021 and 2022 Dynamics and Chemistry of the Summer Stratosphere (DCOTSS) study periods. A novel method for defining and tracking large individual storms or storm outbreak objects in space and time was presented, which enabled improved understanding of the complex feature-specific biases among GOES- and GridRad-derived overshooting metrics. GOES overshooting cloud top height was estimated using a stratospheric lapse rate approach informed by GOES visible and IR measurements of shadows from OTs and calibrated based on previously observed maximum GridRad overshooting distribution. Total overshooting volumes derived over CONUS are higher for GOES than GridRad for both years, especially during 2021. Over all storm outbreak objects with observed overshooting, GOES observed higher overshooting percentages while GridRad observed relatively higher overshooting magnitudes. The greater spatial coverage of GOES overshooting, especially noticeable during the mature and dissipation stages of outbreaks due to inherent limitations of infrared satellite data which make it difficult to differentiate cold, high-altitude outflow from true updraft cores, outweighed differences in magnitude to yield higher GOES volume. Individual events, however, revealed that the higher overshooting magnitudes observed by GridRad produce higher overshooting volumes at times. Four-dimensional trajectories of tropopause-overshooting air parcels were compared 5 days after overshooting occurred to depict the envelope of convectively impacted air in the stratosphere. The generally good agreement in parcel plume area initiated from GOES and GridRad overshooting detections suggests that geostationary satellite data can be used to estimate where and how often overshooting impacts stratospheric composition in regions without a ground-based weather radar network to estimate climate impacts of overshooting convection.
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 cold-season Tornado outbreak that occurred over the Southeast on 5-6 February 2008 was significant for the following reasons: about 84 tornadoes were documented over a 15 h period between late afternoon on 5 February and early morning on 6 February 2008; a wide variety of parent storms were associated with the tornadoes; a total of five EF-4 tornadoes occurred, with two forming over Alabama during the early morning hours prior to sunrise; there was a significant lull period between the initial convective and the early morning activity over Alabama 10 hours later; and, a wide spectrum of storm types, ranging from isolated supercell storms to QLCS bow echoes, accompanied the tornadoes. The goal of this paper is to provide a general description of the outbreak including the distribution of tornadoes and supercell storms over the region, a detailed map of the tornado tracks, time series of tornadoes and parent storms, and general characteristics of all parent tornado storms. The total number of major storms (duration greater than 3 h, at least three tornadoes produced) was seven. Several noteworthy storms are described: a long track (198 km long) tornado and its parent storm over Arkansas; a prolific supercell storm persisted for 7-8 hours and produced 16 tornadoes from north-central Mississippi to southern KY; and, bow echo storms (QLCS's) were simultaneous over KY and produced 16 tornadoes.
The Geostationary Lightning Mapper (GLM) is a single channel, near-IR optical detector, used to detect, locate and measure total lightning activity over the full-disk as part of a 3-axis stabilized, geostationary weather satellite system. The next generation NOAA Geostationary Operational Environmental Satellite (GOES-R) series with a planned launch in 2014 will carry a GLM that will provide continuous day and night observations of lightning from the west coast of Africa (GOES-E) to New Zealand (GOES-W) when the constellation is fully operational. The mission objectives for the GLM are to 1) provide continuous, full-disk lightning measurements for storm warning and Nowcasting, 2) provide early warning of tornadic activity, and 3) accumulate a long-term database to track decadal changes of lightning. The GLM owes its heritage to the NASA Lightning Imaging Sensor (1997-Present) and the Optical Transient Detector (1995-2000), which were developed for the Earth Observing System and have produced a combined 11 year data record of global lightning activity. Instrument formulation studies begun in January 2006 will be completed in March 2007, with implementation expected to begin in September 2007. Proxy total lightning data from the NASA Lightning Imaging Sensor on the Tropical Rainfall Measuring Mission (TRMM) satellite, airborne science missions (e.g., African Monsoon Multi-disciplinary Analysis, AMMA), and regional test beds (e.g, Lightning Mapping Arrays) are being used to develop the pre-launch algorithms and applications, and also improve our knowledge of thunderstorm initiation and evolution. Real time lightning mapping data now being provided to selected forecast offices will lead to improved understanding of the application of these data in the severe storm warning process and accelerate the development of the pre-launch algorithms and Nowcasting applications. Proxy data combined with MODIS and Meteosat Second Generation SEVERI observations will also lead to new applications (e.g., multi-sensor precipitation algorithms blending the GLM with the Advanced Baseline Imager, convective cloud initiation and identification, early warnings of lightning threat, storm tracking, and data assimilation).
Storms of interplanetary type III radio bursts (IP storms) are commonly observed in the interplanetry medium by the ISEE-3 radio instrument. This instrument has the capability of accurately determining the arrival direction of the radio emission. At each observing frequency, the storm radio sources are tracked as they cross the line-of-sight to the Sun. Usng a simple model, the emission levels are determined at a number of radio frequencies for four separate storms. The IP storm radiation is found to occur in regions of enhanced density at levels of 0.05 to 0.8 AU. The density in these enhancements falls off faster than R(-2). The solar wind speed in the storm region is also measured. The analysis is consistent with steady conditions in the storm region during a few days around the central meridian passage of the storm. The comparison with average in situ density measurements compiled from the HELIOS 1-2 observations favors type III storm burst radio emission at the harmonic of the local plasma frequency.
Storms of interplanetary type III radio bursts (IP storms) are commonly observed in the interplanetary medium by the ISEE-3 radio instrument. This instrument has the capability of accurately determining the arrival direction of the radio emission. At each observing frequency, the storm radio sources are tracked as they cross the line-of-sight to the sun. Using a simple model, the emission levels are determined at a number of radio frequencies for four separate storms. The IP storm radiation is found to occur in regions of enhanced density at levels of 0.05 to 0.8 AU. The density in these enhancements falls off faster than R(-2). The solar wind speed in the storm region is also measured. The analysis is consistent with steady conditions in the storm region during a few days around the III storm burst radio emission at the harmonic of the local plasma frequency.
The Midwest is home to one of the world's largest agricultural growing regions. Between the time period of late May through early September, and with irrigation and seasonal rainfall these crops are able to reach their full maturity. Using moderate to high resolution remote sensors, the monitoring of the vegetation can be achieved using the red and near-infrared wavelengths. These wavelengths allow for the calculation of vegetation indices, such as Normalized Difference Vegetation Index (NDVI). The vegetation growth and greenness, in this region, grows and evolves uniformly as the growing season progresses. However one of the biggest threats to Midwest vegetation during the time period is thunderstorms that bring large hail and damaging winds. Hail and wind damage to crops can be very expensive to crop growers and, damage can be spread over long swaths associated with the tracks of the damaging storms. Damage to the vegetation can be apparent in remotely sensed imagery and is visible from space after storms slightly damage the crops, allowing for changes to occur slowly over time as the crops wilt or more readily apparent if the storms strip material from the crops or destroy them completely. Previous work on identifying these hail damage swaths used manual interpretation by the way of moderate and higher resolution satellite imagery. With the development of an automated and near-real time hail swath damage identification algorithm, detection can be improved, and more damage indicators be created in a faster and more efficient way. The automated detection of hail damage swaths will examine short-term, large changes in the vegetation by differencing near-real time eight day NDVI composites and comparing them to post storm imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Terra and Aqua and Visible Infrared Imaging Radiometer Suite (VIIRS) aboard Suomi NPP. In addition land surface temperatures from these instruments will be examined as for hail damage swath identification. Initial validation of the automated algorithm is based upon Storm Prediction Center storm reports but also the National Severe Storm Laboratory (NSSL) Maximum Estimated Size Hail (MESH) product. Opportunities for future work are also shown, with focus on expansion of this algorithm with pixel-based image classification techniques for tracking surface changes as a result of severe weather.
Accurate determination of thermospheric neutral density holds crucial importance for satellited rag calculations. The problem is twofold and involves the correct estimation of the quiet time climatology and storm time variations. In this work, neutral density estimations from two empirical and threephysics based models of the ionosphere thermosphere are compared with the neutral densities along the Challenging MicroSatellite Payload satellite track for six geomagnetic storms. Storm time variations are extracted from neutral density by (1) subtracting the mean difference between model and observation (bias),(2) setting climatological variations to zero, and (3) multiplying model data with the quiet time ratio between the model and observation. Several metrics are employed to evaluate the model performances. We find that the removal of bias or climatology reveals actual performance of the model in simulating the storm time variations. When bias is removed, depending on event and model, storm time errors in neutral density can decrease by an amount of 113% or can increase by an amount of 12% with respect to error in models with quiet time bias. It is shown that using only average and maximum values of neutral density to determine the model performances can be misleading since a model can estimate the averages fairly well but may not capture the maximum value or vice versa. Since each of the metrics used for determining model performances provides different aspects of the error, among these, we suggest employing mean absolute error, prediction efficiency, and normalized root mean square error together as a standard set ofmetrics for the neutral density.
The first comprehensive assessment of geospace model skill to specify magnetic perturbations (delta-B) on the ground and their time derivative (dB/dt) was performed at the Community Coordinated Modeling Center starting in 2010. This study resulted in the addition of the Space Weather Modling Framework to the suite of operational models run by the NOAA Space Weather Prediction Center (SWPC). Since then, magnetic pertubations have been made available on a larger scale for Run-on-Request simulations in geospace at the CCMC. We will demonstrate recent additions to the suite of analysis tools and model results including magnetic perturbations at more stations and on a grid of positions from both, original model outputs (SWMF using preset run configurations) and post-processed calculations using CalcDeltaB and their analysis and visualization using the open-source Kamodo data access and analysis suite and the Comprehensive Assessment of Models and Events using Library tools (CAMEL) application.
Emergency response to natural disasters requires coordination between multiple local, state, and federal agencies. Single, relatively weak tornado events may require comparatively simple response efforts; but larger "outbreak" events with multiple strong, long-track tornadoes can benefit from additional tools to help expedite these efforts. Meteorologists from NOAA's National Weather Service conduct field surveys to map tornado tracks, assess damage, and determine the tornado intensity following each event. Moderate and high resolution satellite imagery can support these surveys by providing a high-level view of the affected areas. Satellite imagery could then be used to target areas for immediate survey or to corroborate the results of the survey after it is completed. In this study, the feasibility of using satellite imagery to identify tornado damage tracks was determined by comparing the characteristics of tracks observed from low-earth orbit to tracks assessed during the official NWS storm survey process. Of the 68 NWS confirmed centerlines, 24 tracks (35.3%) could be distinguished from other surface features using satellite imagery. Within each EF category, 0% of EF-0, 3% of EF-1, 50% of EF-2, 77.7% of EF-3, 87.5% of EF-4 and 100% of EF-5 tornadoes were detected. It was shown that satellite data can be used to identify tornado damage tracks in MODIS and ASTER NDVI imagery, where damage to vegetation creates a sharp drop in values though the minimum EF-category which can be detected is dependent upon the type of sensor used and underlying vegetation. Near-real time data from moderate resolution sensors compare favorably to field surveys after the event and suggest that the data can provide some value in the assessment process.
Emergency response to natural disasters requires coordination between multiple local, state, and federal agencies. Single, relatively weak tornado events may require comparatively simple response efforts; but larger "outbreak" events with multiple strong, long-track tornadoes can benefit from additional tools to help expedite these efforts. Meteorologists from NOAA's National Weather Service conduct field surveys to map tornado tracks, assess damage, and determine the tornado intensity following each event. Moderate and high resolution satellite imagery can support these surveys by providing a high-level view of the affected areas. Satellite imagery could then be used to target areas for immediate survey or to corroborate the results of the survey after it is completed. In this study, the feasibility of using satellite imagery to identify tornado damage tracks was determined by comparing the characteristics of tracks observed from low-earth orbit to tracks assessed during the official NWS storm survey process. Of the 68 NWS confirmed centerlines, 24 tracks (35.3%) could be distinguished from other surface features using satellite imagery. Within each EF category, 0% of EF-0, 3% of EF-1, 50% of EF-2, 77.7% of EF-3, 87.5% of EF-4 and 100% of EF-5 tornadoes were detected. It was shown that satellite data can be used to identify tornado damage tracks in MODIS and ASTER NDVI imagery, where damage to vegetation creates a sharp drop in values though the minimum EF-category which can be detected is dependent upon the type of sensor used and underlying vegetation. Near-real time data from moderate resolution sensors compare favorably to field surveys after the event and suggest that the data can provide some value in the assessment process.
Anthropogenic climate change leads to increased precipitation intensity and exacerbated droughts in California, challenging the reliability and drought resiliency of water supply. Storing floodwater underground via managed aquifer recharge can mitigate these effects through direct infiltration or streambed infiltration. Seasonally dry streams (arroyos) already play an important part in managing groundwater recharge to the Livermore basin (CA). Understanding how, when and where stormwater and arroyo water infiltrate is critical to effectively utilise this strategy. To track water from recent storms (water year 2022–2023, WY23) into the Livermore Valley Groundwater Basin, we analysed stable water isotopes (δ 18 O and δ 2 H) in combination with naturally occurring radioactive isotopic tracers, sulphur-35 ( 35 S, t ½ = 87 days) and tritium ( 3 H, t ½ = 12.3 years). By comparing measurements of δ 18 O, 35 S and 3 H in arroyos to precipitation and groundwater, we classified the relative age and identified source of recharge to 16 wells near two arroyos. Two wells contained water with recent recharge (from WY23) from local precipitation. One well had recent recharge from variable (precipitation and imported water) sources. One well contained imported water recharge. Three wells contained water from mixed recent and older (pre-WY23) waters, from local precipitation sources. Two wells contained recent recharge from local mine settling ponds. Seven wells had older recharge from local precipitation sources. This combination of isotopes allows us to delineate where local and imported water recharges in this highly managed basin and identify locations where managed aquifer recharge is contributing to rapid groundwater infiltration. Our combined interpretation of isotopic water ages and sources in the context of land use shows that local infiltration of precipitation in open spaces is an important recharge mechanism, in addition to the managed arroyo recharge. Finally, a broader familiarity with 35 S will enable more extensive research on the infiltration of urban floodwaters.
Research was conducted to use the KSC Lightning Detection and Ranging (LDAR) system, together with companion data, in four subprojects: weather forecasting and advisory applications of LDAR, LDAR in relation to field mill readings, lightning flash and stroke detection using LDAR, and LDAR in relation to radar reflectivity patterns and KSC wind profiler vertical velocities. The research is aimed at developing rules, algorithms, and training materials that can be used by the operational weather forecasters who issue weather advisories for daily ground operations and launches by NASA and the United States Air Force. During the summer of 1993, LDAR data was examined on an hourly basis from 14 thunderstorm days and compared to ground strike data measured by the Lightning Location and Protection (LLP) system. These data were re-examined during 1994 to identify, number, and track LDAR-detected storms continually throughout the day and avoid certain interpretation problems arising from the use of hourly files. An areal storm growth factor was incorporated into a scheme to use current mappings of LDAR-defined thunderstorms to predict future ground strikes. During the summer of 1994, extensive sets of LDAR and companion data have been collected for 16 thunderstorm days, including a variety of meteorological situations. Detailed case studies are being conducted to relate the occurence of LDAR to the radar structure and evolution of thunderstorms. Field mill (LPWS) data are being examined to evaluate the complementary nature of LDAR and LPLWS data in determining the time of beginning and ending of the ground strike threat at critical sites. A computerized lightning flash and stroke discrimination algorithm has been written that can be used to help locate the points of origin of the electrical discharges, help distinguish in-cloud, cloud-ground, and upward flashes, and perhaps determine when the threat of ground strikes has ceased. Surface wind tower (mesonet), radar, sounding, and KSC wind profiler data will be used to develop schemes to help anticipate the timing and location of new thunderstorm development. Analysis of this data will continue in graduate student research projects.