Geostationary Observational Environmental Satellite Research Articles

Infrasound signals of fireballs detected by the Geostationary Lightning Mapper

Context. Fireballs are particularly bright meteors produced by large meteoroids or small asteroids that enter the Earth’s atmosphere. These objects, of sizes from some tens of centimetres to a few metres, are difficult to record with typical meteor detection methods. Therefore, their characteristics and fluxes are still not well known. Infrasound signals can travel particularly well through the atmosphere over large distances. Impacting meteoroids and asteroids can produce those signals, as well as space-detectable optical signatures. Aims. This paper aims to study and compare fireball data from the Geostationary Lightning Mappers (GLMs) on board the two Geostationary Observational Environmental Satellites (GOES-16 and GOES-17) and the data from the infrasound stations of the International Monitoring System of the Comprehensive Nuclear-Test-Ban Treaty Organisation (Vienna, Austria). The overall goal is a more accurate energy estimation of meteoroids and asteroids as well as a better understanding of both methods. Methods. The data consist of the brightest 50 events in the GLM database, as identified by recorded peak energy. For 24 of those fireballs, a significant signature could be identified in infrasound data. The data are supplemented by, if available, optical fireball data based on US government sensors on satellites provided by NASA’s Center for Near-Earth Object Studies (CNEOS). Results. The energies as computed from the GLM data range from 3.17 × 107 J up to 1.32 × 1012 J with a mean of 1.65 × 1011 J. The smallest meteoroid recorded by infrasound had an energy of about 1.8 × 109 J, the largest one of about 9.6 × 1013 J, and the mean energy is 5.2 × 1012 J. For 19 events, data were simultaneously available from all three data sources. A comparison between the energy values for the same event as determined from the different data sources indicates that CNEOS tends to give the lowest energy estimations. Analysis of infrasound data results in the largest derived energies. Conclusions. The energies derived using the three methods often deviate from one another by as much as an order of magnitude. This indicates a potential observational bias and highlights uncertainties in fireball energy estimation. By determining the fireball energy with another independent method, this study can help to better quantify and address this range of uncertainty.

Retrieval of Aerosol Optical Depth From INSAT‐3D Imager Over Asian Landmass and Adjoining Ocean: Retrieval Uncertainty and Validation

AbstractAn algorithm for aerosol optical depth (τ) retrieval from imager data onboard geostationary Indian National Satellite (INSAT‐3D) is described. The basic principles of the algorithm are adopted from Geostationary Observational Environmental Satellite Aerosol and Smoke Algorithm, where darkest observations over a time period and constant background aerosol optical depth (τb) value are used to derive surface reflectance. However, in INSAT‐3D algorithm spatially and temporally dynamic τb derived from Moderate Resolution Imaging Spectroradiometer (MODIS)‐aqua is used. The theoretical simulations suggest retrieval uncertainty of around ±30–45% depending on the certainty of aerosol optical properties and other parameters used in radiative transfer calculations. Retrieval uncertainty is less over dark regions and lower scattering angles. INSAT‐3D τ at 0.55 μm is derived operationally for the first time over Asia and adjoining ocean at 30‐min temporal resolution. The retrieval algorithm is validated against in situ Sun‐sky radiometer measurements at 26 Aerosol Robotic Network sites and Sun‐photometer measurements during Sagar‐Sampada cruise in the northern Arabian Sea. The validation study encompassing 3,803 and 844 data points over land and ocean stations show correlations ranging from 0.70 to 0.91 and 0.79 to 0.91, respectively. The uncertainty of retrievals is within 45% over land and within 30% over ocean. The diurnal variability of INSAT‐3D and Aerosol Robotic Network τ in India and southeast Asia is also presented. The comparison of INSAT‐3D and MODIS‐aqua monthly average τ shows correlation ranging from 0.74 to 0.89 and 0.65 to 0.97 over Indian landmass and adjoining ocean, respectively. The validation suggests that INSAT‐3D can be used for aerosol monitoring and can be merged with MODIS‐aqua/terra aerosol product to generate combined aerosol product at high temporal resolution.

Identification of Potential Sites for Astronomical Observations in Northern South America

In this study, we describe an innovative method to determine potential sites for optical and infrared astronomical observations in the Andes region of northern South America. The method computes the clear-sky fraction (CSF) from Geostationary Observational Environmental Satellite (GOES) data for the years 2008–2012 through a comparison with temperatures obtained from long-term records of weather stations and atmospheric temperature profiles from radiosonde. Criteria for sky clearance were established for two infrared GOES channels in order to determine potential sites in the Andes region of northern South America. The method was validated using the reported observed hours at the Observatorio Nacional de Llano del Hato in Venezuela. Separate CSF percentages were computed for dry and rainy seasons for both photometric and spectroscopic night qualities. Twelve sites with 5-year averages of CSF for spectroscopic nights larger than 30% during the dry seasons were found to be suitable for astronomical observations. The best site with (220 ± 42) spectroscopic clear nights per year is located in the Andes of Venezuela (70°28′48″W, 9°5′60″N) at an altitude of 3480 m. Lower quality regions were found in Sierra Nevada de Santamarta and Serranía del Perijá with (126 ± 34) and (111 ± 27) clear nights per year, respectively. Sites over the Andes are identified in Norte de Santander with (107 ± 23) and in the north-east part of Boyacá with a mean of (94 ± 13) clear nights per year. Two sites at low latitude located in Ecuador with more than 100 clear nights per year and with similar seasonal CSF percentages were also identified. Five-year evolution suggests a possible correlation between the lowest percentages observed during the rainy seasons of 2010 and 2011 with positive values of the Southern Oscillation Index.

Estimating and forecasting the precipitable water vapor from GOES satellite data at high altitude sites

In this work, we describe a method to estimate the precipitable water vapor (PWV) from Geostationary Observational Environmental Satellite (GOES) data at high altitude sites. The method was applied at Atacama Pathfinder Experiment (APEX) and Cerro Toco sites, located above 5000 m altitude in the Chajnantor plateau, in the north of Chile. It was validated using GOES-12 satellite data over the range 0–1.2 mm since submillimeter/millimeter astronomical observations are only useful within this PWV range. The PWV estimated from GOES and the Final Analyses (FNL) at APEX for 2007 and 2009 show root mean square error values of 0.23 mm and 0.36 mm over the ranges 0–0.4 mm and 0.4–1.2 mm, respectively. However, absolute relative errors of 51% and 33% were shown over these PWV ranges, respectively. We recommend using high-resolution thermodynamic profiles from the Global Forecast System (GFS) model to estimate the PWV from GOES data since they are available every three hours and at an earlier time than the FNL data. The estimated PWV from GOES/GFS agrees better with the observed PWV at both sites during night time. The largest errors are shown during daytime. Short-term PWV forecasts were implemented at both sites, applying a simple persistence method to the PWV estimated from GOES/GFS. The 12 h and 24 h PWV forecasts evaluated from August to October 2009 indicates that 25% of them show a very good agreement with observations whereas 50% of them show reasonably good agreement with observations. Transmission uncertainties calculated for PWV estimations and forecasts over the studied sites are larger over the range 0–0.4 mm than over the range 0.4–1.2 mm. Thus, the method can be used over the latter interval with more confidence.

EVIDENCE FOR DEPARTURE FROM A POWER-LAW FLARE SIZE DISTRIBUTION FOR A SMALL SOLAR ACTIVE REGION

Active region 11029 was a small, highly flare-productive solar active region observed at a time of extremely low solar activity. The region produced only small flares: the largest of the $>70$ Geostationary Observational Environmental Satellite (GOES) events for the region has a peak 1--$8{\AA}$ flux of $2.2\times 10^{-6} {\rm W} {\rm m}^{-2}$ (GOES C2.2). The background-subtracted GOES peak-flux distribution suggests departure from power-law behavior above $10^{-6} {\rm W} {\rm m}^{-2}$, and a Bayesian model comparison strongly favors a power-law plus rollover model for the distribution over a simple power-law model. The departure from the power law is attributed to this small active region having a finite amount of energy. The rate of flaring in the region varies with time, becoming very high for two days coinciding with the onset of an increase in complexity of the photospheric magnetic field. The observed waiting-time distribution for events is consistent with a piecewise-constant Poisson model. These results present challenges for models of flare statistics and of energy balance in solar active regions.

Cycle 23 flare temperatures and emission measures as derived from GOES X-ray data

Solar X-ray observations recorded by the series of geostationary observational environmental satellites ( GOES) are analyzed over a time interval of the 23rd solar cycle. Statistical analysis of a large database of GOES events is performed. Temperature and emission measures derived based on GOES fluxes for all events are compared and analyzed. A specific application of GOES X-ray measurements to space weather forecasting is discussed. Namely, using an information about maximum temperature and maximum emission measure of a given flare one can assign a probability to this flare of being “non-SEP associated”.

Initial Test of a Bayesian Approach to Solar Flare Prediction

AbstractA test of a new Bayesian approach to solar flare prediction is presented. The approach uses the past history of flaring together with phenomenological rules of flare statistics to make a prediction for the probability of occurrence of a large flare within an interval of time, or to refine an initial prediction (which may incorporate other information). The test of the method is based on data from the Geostationary Observational Environmental Satellites, and involves whole-Sun prediction of soft X-ray flares for 1976–2003. The results show that the method somewhat over-predicts the probability of all events above a moderate size, but performs well in predicting large events.

Validation of TRMM and Other Rainfall Estimates with a High-Density Gauge Dataset for West Africa. Part II: Validation of TRMM Rainfall Products

Gauge data from a West African network of 920 stations are used to assess Tropical Rainfall Measuring Mission (TRMM) satellite and blended rainfall products for 1998. In this study, mean fields, scattergrams, and latitudinal transects for the months of May‐September and for the 5-month season are presented. Error statistics are also calculated. This study demonstrates that both the TRMM-adjusted Geostationary Observational Environmental Satellite precipitation index (AGPI) and TRMM-merged rainfall products show excellent agreement with gauge data over West Africa on monthly-to-seasonal timescales and 2.5 83 2.58 latitude/longitude space scales. The root-mean-square error of both is on the order of 0.6 mm day 21 at seasonal resolution and 1 mm day21 at monthly resolution. The bias of the AGPI is only 0.2 mm day21, whereas the TRMM-merged product shows no bias over West Africa. Performance at 1.0 83 1.08 latitude/longitude resolution is also excellent at the seasonal scale and good for the monthly scale. A comparison with standard rainfall products that predate TRMM shows that AGPI and the TRMM-merged product perform as well as, or better than, those products. The AGPI shows marked improvement when compared with the GPI, in reducing the bias and in the scatter of the estimates. The TRMM satellite-only products from the precipitation radar and the TRMM Microwave Imager do not perform well over West Africa. Both tend to overestimate gauge measurements.

Aerosol optical depth retrieval from GOES‐8: Uncertainty study and retrieval validation over South America

An algorithm for aerosol optical depth τ retrieval from the Geostationary Observational Environmental Satellite (GOES) series is described, where the darkest pixels are used to create a spatial composite of surface reflectance. The data are calibrated and corrected for atmospheric extinction to retrieve the surface reflectance which is then used to retrieved τ. Analysis suggests that τ retrieval uncertainty is ±18–34% depending on the certainty of the assumed radiative transfer model parameters. Retrieval uncertainty is less over low surface reflectances and at large scattering angles. The retrieval algorithm is validated against Sun‐sky radiometer τ measurements for aerosols emitted by biomass burning in South America during 1995 and 1998. The relative differences between observed and retrieved τ are within the estimated uncertainty, having correlations ranging from 0.78 to 0.97. Further, the GOES retrievals are compared to τ retrieved using the Moderate‐Resolution Imaging Spectroradiometer (MODIS) airborne simulator (MAS). The average relative difference in this comparison is 11%, thus retrieval validations are again within the estimated algorithm uncertainty. These results suggest that the GOES satellite can be used to monitor aerosols over land, while the agreement between MAS and GOES retrievals suggests the ability to combine the spectral abilities of MODIS with the temporal observations of GOES.

Dynamics of volcanic and meteorological clouds produced on 26 December (Boxing Day) 1997 at Soufrière Hills Volcano, Montserrat

Abstract The 26 December 1997 explosive activity of Soufrière Hills Volcano, Montserrat, provided an opportunity to study the evolution of a volcanic cloud by merging data from various satellites with wind-trajectory data. The activity involved a debris avalanche that descended SSW from the lava dome, to the coast, and a pyroclastic density current that traversed the coast and entered the sea. The slope failure and subsequent dome collapse occurred at c . 07:01 universal time (UT; 03:01 local time), lasted 15.2 minutes, and produced an upwardly convecting volcanic ash cloud that cloud temperatures suggest rose to c . 15 km. The volcanic ash cloud was unusual because the pyroclastic density current transported hot fine ash to the sea, where it rapidly transferred its heat to the sea water. The evaporation of large volumes of water produced a volcanogenic meteorological (VM) cloud that convected along with the volcanic ash cloud. The evolution of the volcanic and VM clouds was studied using an isentropic wind trajectory model and data from three satellite sensors: Geostationary Observational Environmental Satellite 8 (GOES 8), Advanced Very High Resolution Radiometer (AVHRR), and Total Ozone Mapping Spectrometer (TOMS). The high temporal resolution of the GOES 8 images filled many of the time gaps the other satellites left, and allowed quantitative retrievals to be performed using a two-band infrared retrieval method. The three-dimensional morphology of the volcanic cloud was reconstructed using GOES 8 data and by determining the heights of air parcels from wind-trajectory data. The volcanic cloud was estimated to contain up to 4.5 x 10 7 kg of silicate ash. Between c . 07:39 UT and 13:39 UT the ash signal of the volcanic cloud was masked by the VM cloud, which had a mass of up to 1.5 x 10 8 kg of ice. Ice forms when moist air is convected upwards to temperatures of less than -40°C and becomes saturated. Ice formation in volcanic clouds is especially likely when hot volcanic material is cooled by seawater rather than the atmosphere. The efficiency of evaporation of the seawater was calculated to be c . 5%, based on physical and GOES 8 data. TOMS data showed the SO 2 in the volcanic cloud rose higher than the ash in the volcanic cloud, as has occurred in several other eruptions. A comparison between GOES 8 and AVHRR data showed that AVHRR data retrieved higher fine-ash silicate masses and higher cloud areas than GOES 8 due to the finer spatial resolution of AVHRR images. The effect on retrieval data of the high water vapour content in the lower troposphere of the tropical atmosphere was quantified; the high humidity in the Montserrat region caused the characteristic ash signal to the infrared sensors to be depressed by up to 80%. This signal depression caused a corresponding underestimation of the mass and area of the volcanic cloud when the infrared brightness temperature difference retrieval technique was used.

Ford gets $11.8 million for GOES ground control

Ford Aerospace Corporation in College Park, Md., has been awarded an $11.8‐million contract to develop, build, and maintain a command and telemetry system for the new class of Geostationary Observational Environmental Satellite (GOES) weather satellites that Ford is building for the National Oceanic and Atmospheric Administration (NOAA).

Satellite Studies Of Fresh-Water Ice Movement On Lake Erie

AbstractSince the winter of 1972–73, NOAA visible and thermal images of North America have been available for the study of ice on the Great Lakes. The shallowest of the Great Lakes is Lake Erie, on which ice occurs from December usually through April. The NOAA series of polar-orbiting satellites collect two thermal and one visible image per day; the Geostationary Observational Environmental Satellites (GOES) collect visible and infrared images every 30 min. NASA’s Landsat satellite has an 18 d revisit cycle (a 9 d cycle when two are operating), with superb ground resolution (79 m). Satellite images from all three satellites were used in this study.Ice formation, movement, and break-up in Lake Erie are different in each sub-basin, Western, Central, and Eastern, owing to the variation in depth of water, geomorphology, and meteorologic factors.Ice movement after initial break-up in 1974–77 resulted in the accumulation of ice at the entrance of the Niagara River at the eastern end of the lake. In 1973, satellite images show the unusual development of an ice dam across the entire width of Lake Erie and the “ice plug” at the mouth of the Niagara did not form.The effect of wind direction on break-up patterns is seen to be critical to any attempt at forecasting date of complete ice melt as well as day-to-day distribution of ice. Satellite observation of ice in Lake Erie—and in all large lakes—provides information regularly, routinely, and synoptically from a point in space. These data are useful for the study of ice formation, movement, and break-up, and they provide an unrivaled and unprecedented data set of historical records.

Satellite Studies Of Fresh-Water Ice Movement On Lake Erie

Abstract Since the winter of 1972–73, NOAA visible and thermal images of North America have been available for the study of ice on the Great Lakes. The shallowest of the Great Lakes is Lake Erie, on which ice occurs from December usually through April. The NOAA series of polar-orbiting satellites collect two thermal and one visible image per day; the Geostationary Observational Environmental Satellites (GOES) collect visible and infrared images every 30 min. NASA’s Landsat satellite has an 18 d revisit cycle (a 9 d cycle when two are operating), with superb ground resolution (79 m). Satellite images from all three satellites were used in this study. Ice formation, movement, and break-up in Lake Erie are different in each sub-basin, Western, Central, and Eastern, owing to the variation in depth of water, geomorphology, and meteorologic factors. Ice movement after initial break-up in 1974–77 resulted in the accumulation of ice at the entrance of the Niagara River at the eastern end of the lake. In 1973, satellite images show the unusual development of an ice dam across the entire width of Lake Erie and the “ice plug” at the mouth of the Niagara did not form. The effect of wind direction on break-up patterns is seen to be critical to any attempt at forecasting date of complete ice melt as well as day-to-day distribution of ice. Satellite observation of ice in Lake Erie—and in all large lakes—provides information regularly, routinely, and synoptically from a point in space. These data are useful for the study of ice formation, movement, and break-up, and they provide an unrivaled and unprecedented data set of historical records.