IR Satellite Imagery Research Articles

Assessment of Vegetation Cover of Bengaluru City, India, Using Geospatial Techniques

Bengaluru has a unique place due to its pleasant weather and green cover. Off late, the city has witnessed phenomenal urban growth, especially during last few decades. This study was envisaged to assess the decadal changes in vegetation cover of Bengaluru using multispectral IRS satellite imagery of 2006 and 2019 within Bruhat Bengaluru Mahanagara Palike (BBMP) area. Satellite datasets were analysed to assess changes in vegetation cover during the last decade. Vegetation (tree cover) within BBMP area was estimated to be 26.1% (18,572.2 ha) in 2019 as compared to 30.1% (21,414.9 ha) in 2006, indicating an overall reduction of 4%. Overall classification accuracy was estimated to be 92.1% for 2006 and 95.9% for 2019. Based on the analysis, a vegetation change map highlighting positive change areas, negative change areas and no change areas within vegetation categories were prepared for 198 BBMP wards. A total of 730 GT sample points were also collected along with geo-tagged field photographs, which covered diverse niche areas with different vegetation components and density classes, as well as non-vegetated urban and other areas. Recommendations have been given to sustain and improve existing vegetation cover.

Tropicalization process of the 7 November 2014 Mediterranean cyclone: Numerical sensitivity study

Tropical-like Mediterranean cyclones (medicanes) have been documented and investigated in the literature, revealing that their physical mechanisms are still poorly understood and likely not unique across cases. During late hours of 7 November 2014 a small-scale cyclone was detected over the Sicilian channel, affecting the Islands of Lampedusa, Pantelleria and Malta. Gust wind values exceeding 42.7ms−1 and a pressure drop above 20hPa in 6h were registered in Malta. Clear signatures of a well-defined cloud-free eye surrounded with convective activity of axisymmetric character were identifiable through IR satellite imagery during the late stages of the cyclone, resembling the properties of a hurricane. We investigate the cyclogenesis and posterior development of this small-scale cyclone as well as its physical nature; to this aim, a set of high-resolution sensitivity numerical experiments were performed. Hart's phase diagrams adapted to the Mediterranean region clearly reveal the tropical characteristics of the simulated storm. A numerical sensitivity analysis by means of a factor separation technique is used to gain quantitative insight on the roles latent heat release, surface heat fluxes and upper-level PV signatures (dynamically isolated through a PV-Inversion technique) have on the unfold of this singular event. Results show the importance of the upper-level dynamics to generate a baroclinic environment prone to surface cyclogenesis and in supporting the posterior tropicalization of the system. On the contrary, latent heat release and surface heat fluxes factors do not seem to contribute, as individual processes, to the genesis of the cyclone as much as it could be suspected, considering it behaves as a tropical-like cyclone. However, the asynchronous synergism between latent heat release and PV factors plays a crucial role for the intensification of the cyclone towards reaching the pure diabatic phase.

Electrical discharges in the overshooting tops of thunderstorms

AbstractPrevious studies have found that the vertical distribution of sources of very high frequency (VHF) signals from discharges mapped by Lightning Mapping Arrays typically have a secondary maximum in a storm's overshooting top. Low rates of these sources tend to occur continually throughout the lifetime of the overshooting top (OT), rather than sources occurring in the episodic distinct flashes observed at lower altitudes. This study examines the evolution of the VHF OT signature (VHF OT, defined here as a sustained period of ≥4 VHF sources per minute per 200 m layer above a storm's level of neutral buoyancy (LNB)) relative to the evolution of radar reflectivity and IR imagery of overshooting tops in three supercell and two multicell storms. The VHF OT began before OTs were detected in IR satellite imagery of the supercell storms. No OT was observed in IR imagery for either multicell storm, but this lack may have been due to the spatial and temporal resolution of the current IR imager. The VHF OT began near the time the 18 or 30 dBZ echo top rose above the LNB and ended near the time it fell below the LNB. There were too few radar volume scans of OTs in the multicell storms for a correlation analysis. In the supercell storms, however, the maximum altitude of VHF sources typically was less than or equal to the altitude of 18 dBZ echo tops and was correlated with these echo tops (linear correlation coefficient ≥0.86) during the period of the VHF OT.

Cyclone Center: Can Citizen Scientists Improve Tropical Cyclone Intensity Records?

Abstract The global tropical cyclone (TC) intensity record, even in modern times, is uncertain because the vast majority of storms are only observed remotely. Forecasters determine the maximum wind speed using a patchwork of sporadic observations and remotely sensed data. A popular tool that aids forecasters is the Dvorak technique—a procedural system that estimates the maximum wind based on cloud features in IR and/or visible satellite imagery. Inherently, the application of the Dvorak procedure is open to subjectivity. Heterogeneities are also introduced into the historical record with the evolution of operational procedures, personnel, and observing platforms. These uncertainties impede our ability to identify the relationship between tropical cyclone intensities and, for example, recent climate change. A global reanalysis of TC intensity using experts is difficult because of the large number of storms. We will show that it is possible to effectively reanalyze the global record using crowdsourcing. Through modifying the Dvorak technique into a series of simple questions that amateurs (“citizen scientists”) can answer on a website, we are working toward developing a new TC dataset that resolves intensity discrepancies in several recent TCs. Preliminary results suggest that the performance of human classifiers in some cases exceeds that of an automated Dvorak technique applied to the same data for times when the storm is transitioning into a hurricane.

The use of Numerical Weather Prediction and a Lagrangian transport (NAME-III) and dispersion (ASHFALL) models to explain patterns of observed ash deposition and dispersion following the August 2012 Te Maari, New Zealand eruption

The August 6, 2012 Te Maari, New Zealand eruption produced a very small ash-dominated plume (~230,000m3, 8–10km high) that was rapidly and widely dispersed, covering 1600km2 within an hour. This paper documents for the August 6, 2012 Te Maari eruption the upper level (troposphere) plume movement based on ash-detection algorithms applied to IR satellite imagery. It also presents the distribution of airborne ash and wind-influenced ashfall as determined by NAME-III aerial dispersion modelling using observed particle characteristics and grain size distribution measurements (that are also presented) and compares the ashfall with observations.The upper level (troposphere) ash movement was also evaluated from ash-detection algorithms, applied to infra-red satellite imagery and the resulting distributions were compared to those forecast by the numerical dispersion models. Forecasts of upper level ash-dispersion patterns explained the satellite imagery observations well, predicting the correct altitudes when using plausible ash size distributions and release levels. Patterns in proximal ashfall could only be partly explained by aerial dispersal of large particles released at low altitudes in the eruption column. The extreme distal (100–150km away) observed ashfall distributions also cannot be fully explained by NAME-III when using: reasonably prescribed initial particle size distributions, eruption column height, eruption timing, well forecast winds, and dry sedimentation processes. Aggregation and ice nucleation effects (observed in deposits) were not included in the ash dispersion model, but appear as a plausible mechanism to account for the observed fraction of wind dispersed ash particles <30μm deposited but not captured by the models.

Land Use Change Detection and Impact Assessment on an Agricultural Area

This study focuses on detecting, mapping and analyzing the conversion of forests into agricultural uses and agricultural uses into urban/peri-urban uses in Nzega district, Tabora Region - Tanzania over a period of 28 years since 1978. Land use classes were from multitemporal and multi-sensor satellite images and aerial photographs. Topographical maps at a scale of 1:50000 and onsite information gathered in the field were used for interpretation and ground truthing purposes. Land use changes were detected using land use change matrices and land use change maps. Four land use maps were compiled from Aerial photographs dated 1978, Landsat TM satellite imagery dated 1986, Landsat ETM+ satellite imagery dated 2000 and IRS satellite imagery dated 2006. The maps show agricultural areas are concentrated along road networks generally expanding towards neighboring grasslands and unprotected forested areas. Land use changes were detected from land use maps for three change periods: 1978 - 1986, 1986 - 2000 and 2000 - 2006, with emphasis on agricultural and forest land uses. The change maps and change matrices show that despite abandoned farms agricultural land increases with time. Change in the opposite direction was also common where abandoned agricultural land gradually regenerated back to grasslands and forests. An average of 16% of agricultural land has been maintained during the 1978 - 2006 period compared to 67% of forests that have been maintained in the same period of time.

Lake bathymetry from Indian Remote Sensing (P6‐LISS III) satellite imagery using artificial neural network model

AbstractThe remote sensing technique provides a rapid and relatively inexpensive means of identifying silted areas in large water bodies, in order that desilting activities can be effectively conducted. This study developed lake bathymetry for a selected lake system (Akkulam–Veli Lake, Kerala, India) from the Indian Remote Sensing (IRS P6‐LISS III) satellite imagery, using an artificial neural network (ANN) model. The water depth was measured for 17 months at different points in the lake on the same date of overpass of the IRS satellite. The satellite imageries obtained for 12 December 2007 and 16 February 2009 were identified as cloud‐free images. ANN models were developed with the four input series of radiance values from green, red, NIR and MIR bands observed for the satellite imagery obtained on 12 December 2007 at the sampling sites, with actual water depth measurements also being taken on the same date. A three‐layered feed forward neural network with back propagation training algorithm was developed for this study. To train the model, it was run several times by changing the number of neurons, learning rate and the momentum constants until the mean square error was minimum. When the number of neurons is increased to 35, and the logsig function is used as ANN transfer function, the error becomes minimum. To test the model, the developed ANN was run for a new set of input from the satellite imagery taken on 16 February 2009. Comparing the predicted and measured values for the same sites for the same day, it was found that the model is best suited for predicting water depth using ANN and the radiance values for four bands of IRS satellite imagery. The results of this study indicated that, for the shallow lake with lower depth, the difference between the actual and predicted value was considerable. In contrast, this was not the case where the lake water depth was greater, indicating an increased prediction accuracy with ANN with increasing depths for shallow lakes. A bathymetry map prepared with ANN indicated only the lake shoreline, as well as the shallow littoral zones. The approach used in this study requires further refinement, including further of the model based on using more field measurements to obtain a better bathymetry map.

Genesis of twin tropical cyclones as revealed by a global mesoscale model: The role of mixed Rossby gravity waves

In this study, it is proposed that twin tropical cyclones (TCs), Kesiny and 01A, in May 2002 formed in association with the scale interactions of three gyres that appeared as a convectively coupled mixed Rossby gravity (ccMRG) wave during an active phase of the Madden‐Julian Oscillation (MJO). This is shown by analyzing observational data, including NCEP reanalysis data and METEOSAT 7 IR satellite imagery, and performing numerical simulations using a global mesoscale model. A 10‐day control run is initialized at 0000 UTC 1 May 2002 with grid‐scale condensation but no sub‐grid cumulus parameterizations. The ccMRG wave was identified as encompassing two developing and one non‐developing gyres, the first two of which intensified and evolved into the twin TCs. The control run is able to reproduce the evolution of the ccMRG wave and thus the formation of the twin TCs about two and five days in advance as well as their subsequent intensity evolution and movement within an 8–10 day period. Five additional 10‐day sensitivity experiments with different model configurations are conducted to help understand the interaction of the three gyres, leading to the formation of the TCs. These experiments suggest the improved lead time in the control run may be attributed to the realistic simulation of the ccMRG wave with the following processes: (1) wave deepening (intensification) associated with a reduction in wavelength and/or the intensification of individual gyres, (2) poleward movement of gyres that may be associated with boundary layer processes, (3) realistic simulation of moist processes at regional scales in association with each of the gyres, and (4) the vertical phasing of low‐ and mid‐level cyclonic circulations associated with a specific gyre.

A Climatology of Hurricane Eye Formation

This paper presents a climatology of the initial eye formations of a broad set of Atlantic tropical cyclones (TCs) during 1989–2008. A new dataset of structure and intensity parameters is synthesized from the vortex data messages transmitted by routine aircraft reconnaissance. Using these data together with satellite imagery and other established datasets, the times when each TC achieved various stages of eye development are tabulated to form the basis of the climatology. About 60% of Atlantic TCs form eyes. Most often, aircraft observe the eye structure before it appears in IR satellite imagery. Eyes tend to form in high potential intensity environments characterized by high sea surface temperatures and low-to-moderate environmental vertical wind shear. A notable discovery is that most (67%) TCs that form eyes tend to do so within 48 h of the cyclone’s reaching tropical storm strength. This suggests the existence of an opportune time window during which a TC can readily form an eye. From the lengths of time taken to reach various stages of eye development, the characteristic time scale for eye formation is estimated to be about 36 h.

The genesis of Typhoon Nuri as observed during the Tropical Cyclone Structure 2008 (TCS-08) field experiment – Part 1: The role of the easterly wave critical layer

Abstract. An observational and real-time model forecast study of the genesis of Typhoon Nuri during the Tropical Cyclone Structure 2008 (TCS-08) field campaign in the western North Pacific sector is presented. Analysis and observational data show that the surrounding base state is an easterly trade wind flow and the precursor disturbance to Typhoon Nuri is an easterly wave that originates in the ITCZ in the Central Pacific. This disturbance can be tracked more than 10 days prior to tropical storm formation. An overview of the field data is presented here using a newly proposed dynamical framework for tropical cyclone formation within the critical layer of an easterly wave. Despite propagating through a hostile environment ripe with strong vertical wind shear and relatively dry air, the easterly wave critical layer protects the proto-vortex and allows it to gestate until it reaches a more favorable environment. Within this protective "Kelvin cat's eye flow" located within the wave's critical layer existed a sweet spot, defined as the intersection between the wave trough and critical latitude, which is the preferred location for tropical cyclogenesis. Global Forecast System Final Analyses and IR satellite imagery, which shows convective bands wrapping around the sweet spot as genesis nears, confirm that this sweet spot is the location where Typhoon Nuri's dominant low-level circulation emerges. United States Air Force C130 and Naval Research Laboratory P3 research flights on 16 and 17 August collected flight-level, dropwindsonde, and Doppler radar data that allowed an evaluation of the dynamic and thermodynamic processes within the cat's eye circulation. The dropwindsonde analyses identifies the precursor easterly wave disturbance on 16 August and identifies an area of weak low-level cyclonic circulation on 17 August. Real-time forecasts were produced using operational global prediction model data to support scientific missions during TCS-08. These forecasts were found to be useful in flight planning discussions and predicted Typhoon Nuri's eventual genesis latitude within 1.5 degrees 72 h in advance.

A Technique to Determine the Radius of Maximum Wind of a Tropical Cyclone

Abstract A simple technique is developed that enables the radius of maximum wind of a tropical cyclone to be estimated from satellite cloud data. It is based on the characteristic cloud and wind structure of the eyewall of a tropical cyclone, after the method developed by Jorgensen more than two decades ago. The radius of maximum wind is shown to be partly dependent on the radius of the eye and partly on the distance from the center to the top of the most developed cumulonimbus nearest to the cyclone center. The technique proposed here involves the analysis of high-resolution IR and microwave satellite imagery to determine these two parameters. To test the technique, the derived radius of maximum wind was compared with high-resolution wind analyses compiled by the U.S. National Hurricane Center and the Atlantic Oceanographic and Meteorological Laboratory. The mean difference between the calculated radius of maximum wind and that determined from observations is 2.8 km. Of the 45 cases considered, the difference in 50% of the cases was ≤2 km, for 33% it was between 3 and 4 km, and for 17% it was ≥5 km, with only two large differences of 8.7 and 10 km.

Landslide susceptibility mapping using GIS and the weight-of-evidence model

The weights-of-evidence model (a Bayesian probability model) was applied to the task of evaluating landslide susceptibility using GIS. Using landslide location and a spatial database containing information such as topography, soil, forest, geology, land cover and lineament, the weights-of-evidence model was applied to calculate each relevant factor's rating for the Boun area in Korea, which had suffered substantial landslide damage following heavy rain in 1998. In the topographic database, the factors were slope, aspect and curvature; in the soil database, they were soil texture, soil material, soil drainage, soil effective thickness and topographic type; in the forest map, they were forest type, timber diameter, timber age and forest density; lithology was derived from the geological database; land-use information came from Landsat TM satellite imagery; and lineament data from IRS satellite imagery. Tests of conditional independence were performed for the selection of factors, allowing 43 combinations of factors to be analysed. For the analysis of mapping landslide susceptibility, the contrast values, W + and W -, of each factor's rating were overlaid spatially. The results of the analysis were validated using the previous landslide locations. The combination of slope, curvature, topography, timber diameter, geology and lineament showed the best results. The results can be used for hazard prevention and land-use planning.

Application of Likelihood Ratio and Logistic Regression Models to Landslide Susceptibility Mapping Using GIS

For landslide susceptibility mapping, this study applied and verified a Bayesian probability model, a likelihood ratio and statistical model, and logistic regression to Janghung, Korea, using a Geographic Information System (GIS). Landslide locations were identified in the study area from interpretation of IRS satellite imagery and field surveys; and a spatial database was constructed from topographic maps, soil type, forest cover, geology and land cover. The factors that influence landslide occurrence, such as slope gradient, slope aspect, and curvature of topography, were calculated from the topographic database. Soil texture, material, drainage, and effective depth were extracted from the soil database, while forest type, diameter, and density were extracted from the forest database. Land cover was classified from Landsat TM satellite imagery using unsupervised classification. The likelihood ratio and logistic regression coefficient were overlaid to determine each factor's rating for landslide susceptibility mapping. Then the landslide susceptibility map was verified and compared with known landslide locations. The logistic regression model had higher prediction accuracy than the likelihood ratio model. The method can be used to reduce hazards associated with landslides and to land cover planning.

CMORPH: A Method that Produces Global Precipitation Estimates from Passive Microwave and Infrared Data at High Spatial and Temporal Resolution

A new technique is presented in which half-hourly global precipitation estimates derived from passive microwave satellite scans are propagated by motion vectors derived from geostationary satellite infrared data. The Climate Prediction Center morphing method (CMORPH) uses motion vectors derived from half-hourly interval geostationary satellite IR imagery to propagate the relatively high quality precipitation estimates derived from passive microwave data. In addition, the shape and intensity of the precipitation features are modified (morphed) during the time between microwave sensor scans by performing a time-weighted linear interpolation. This process yields spatially and temporally complete microwave-derived precipitation analyses, independent of the infrared temperature field. CMORPH showed substantial improvements over both simple averaging of the microwave estimates and over techniques that blend microwave and infrared information but that derive estimates of precipitation from infrared data when passive microwave information is unavailable. In particular, CMORPH outperforms these blended techniques in terms of daily spatial correlation with a validating rain gauge analysis over Australia by an average of 0.14, 0.27, 0.26, 0.22, and 0.20 for April, May, June–August, September, and October 2003, respectively. CMORPH also yields higher equitable threat scores over Australia for the same periods by an average of 0.11, 0.14, 0.13, 0.14, and 0.13. Over the United States for June–August, September, and October 2003, spatial correlation was higher for CMORPH relative to the average of the same techniques by an average of 0.10, 0.13, and 0.13, respectively, and equitable threat scores were higher by an average of 0.06, 0.09, and 0.10, respectively.

Spatial Variability in Fertility in Menoufia, Egypt, Assessed through the Application of Remote-Sensing and GIS Technologies

Fertility in rural areas such as the Governorate of Menoufia in Egypt may be influenced both by spatial factors (including the diffusion of innovations) and by essentially nonspatial factors (such as the availability of education for women and the percentage of adult women who are currently married). The nonspatial variables are available directly from censuses but the spatial component requires an accurate location of the villages to which the census data refer and then appropriate decomposition of the data into spatial and nonspatial components. We use IRS satellite imagery to classify the built area in a rural governorate in Egypt and then assign village-level census data to the centroids of those polygons and incorporate the data into a GIS. We then employ measures of global and local spatial statistics to conclude that in 1976 the combination of female illiteracy, proportion married, and spatial clustering accounted for 39% of the variation in fertility in Menoufia. In 1986 those same factors explained 51% of the variation in fertility. In 1976 about one third and in 1986 about half of the explained variability was due to the spatial component (‘diffusion’) and the other half due to a combination of demographic characteristics. Furthermore, between 1976 and 1986 there was a clear north-to-south drift of fertility, with lower fertility being clustered in the north and higher fertility clustered in the south.

Analysis of frontogenesis and frontolysis by means of Q-vector diagnostics combined with satellite images

The correlation between the normal component of theQ-vector(Q n ) and the pixel values in IR satellite images has been investigated on a six-months data set. The average linear correlation coefficients are negative in all three selected isobaric levels, but not of significant magnitude (the correlation is best for the 850 hPa level, with a correlation coefficient of about 0.3), indicating an only slight tendency for negative values ofQ n to be associated with high IR grey shade values or, in other words, with cold cloud tops. It is explained why a better correlation should be expected for frontal cases, followed by an evaluation of 14 IR images containing cloudiness of cold fronts that occurred in February 1995. The correspondence betweenQ n at the 850 hPa level and IR pixel values in those cases is compared to the statistics for the whole month of February 1995, including also nonfrontal cases. The more pronounced connection is found for frontal cases, as expected. Finally, examples of frontogenesis and frontolysis demonstrate the possibility of using the prognostic quantityQ n in combination with IR satellite imagery as a tool for operational nowcasting and/or forecasting of the development or decay of frontal cloudiness.

Initiation of an Elevated Mesoscale Convective System Associated with Heavy Rainfall

A mesoscale convective system (MCS) developed during the morning hours of 6 June 1993 and moved across northern and central Missouri, resulting in a narrow swath of excessive rainfall (>150 mm). The MCS developed well north of a surface warm front above a cool, stable boundary layer and moved east–southeast across the state. Although some features of the synoptic environment agree with the frontal flash flood composite model, predicting the elevated thunderstorms that composed the MCS posed a unique forecasting challenge. This paper first describes the diagnostic parameters of the prestorm environment that would have been helpful to predict the initiation of the MCS and the resultant locally excessive precipitation. Attention is then drawn to the MCS itself via IR satellite and WSR-88D imagery. Finally, the similarities and differences of this episode to previous studies of flash flooding and elevated thunderstorms are noted, and a summary of key parameters useful in the anticipation of this type of convection and associated heavy rainfall are offered.

Potentiality of Landsat, SPOT and IRS satellite imagery, for recognition of salt affected soils in Indian Arid Zone

Abstract Landsat, SPOT and IRS data, black and white and false colour composite (FCC) imagery of the summer (April, May), rainfed crop season (October) and winter irrigated crop season (January, February) of Indian Arid Zone were interpreted for recognition or three types of salt affected soils, viz. (1) natural salt affected; slight, moderate and severe, (2) saline soils due to saline water irrigation, (3) sodic soils due to high residual sodium carbonate (RSC) water irrigation. These were field checked and supported by analytical data. The Landsat-MSS band 4 could only provide the overall extent of salinity. The moderate and severe natural salt affected soils were identified by Landsat-MSS band 2, Landsat-MSS and TM, IRS LISS-I and LISS-II and SPOT HRV2 data for April and January. But the differentiation between the saline and sodic soils was possible only by the use of multi-date imagery (October and January) and the clue provided by the cropping pattern. The potentiality of remote sensing data product...

A comparison of satellite‐derived and aircraft‐measured regional surface sensible heat fluxes over the Beaufort Sea

Motivated by the importance of quantifying the regional surface heat balance over Arctic sea ice in studying climate processes, Lindsay and Rothrock (1994) developed a methodology for computing regional surface sensible heat fluxes using readily available advanced very high resolution (AVHRR) IR satellite imagery. Their technique is based upon the determination of the pixel‐by‐pixel sea ice surface temperature from which estimates of sensible heat fluxes are then made. We compare the sensible heat fluxes over the Beaufort Sea computed using their methodology with those measured by a gust probe system on the National Oceanic and Atmospheric Administration P‐3 aircraft on April 18, 1992, during the Leads Experiment. We use an AVHRR image recorded during the P‐3 flight at 2303 UTC. We show that individual lead heat fluxes can be large, 115 W m−2 for 1‐km average fluxes obtained from flight legs that included a 300‐m‐wide lead, but that regional values of sensible flux over 50–200 km of sea ice were small and positive, ∼8 W m−2. The sensible heat flux computed from the P‐3 showed that a value of CS = 1.1×10−3, where CS is the heat transfer coefficient relative to 10 m, is appropriate for the spring Beaufort Sea. We suggest that more realistic winds derived, for example, from the National Meteorological Center sea level pressure analyses be used instead of the constant value of 5 m s−1 now employed by Lindsay and Rothrock. We also found that the maximum value of ΔT, the difference between air and surface temperature, used in the calculation of sensible heat flux using the Lindsay and Rothrock technique was underestimated by a factor of 1.9 when compared with direct measurements. Use of this ΔT correction factor, synoptic scale winds, and the calculated value of CS gave a good comparison between the AVHRR approach and aircraft fluxes measured over the region. The effective regional momentum drag coefficient CD relative to 10 m was 2.1×10−3, typical of Arctic pack ice.

Eddies southwest of the Denmark Strait

Numerous cold cyclonic eddies (20–40 km diameter) have been observed in satellite IR imagery (NOAA-11, Ch 3 and 4) along the edge of the East Greenland Shelf to the southwest of the Denmark Strait. The eddies move southwestward along the southeast edge of the East Greenland Current. The path of the eddies is coincident with the location of numerous deep current meter observations from previous surveys during which the strong pulses of overflow water (recorded speeds of over 150 cm s−1) had spectra peaked at periods of 1.5−2.5 days. It is suggested that the pulses are the signal observed from energetic, propagating cyclonic vortices extending up to the surface layer and formed by vortex stretching associated with the sinking of dense overflow water downstream from the sill of the Denmark Strait and along the shelf slope. The signature of the vortices at the sea surface appears in the IR imagery as a cold cyclonic eddy often exhibiting a pronounced spiral configuration. Because the entire water column in the slope region would be subjected to strong mixing by the vortices, considerable modification of not only the cold overflow water but also the intermediate and surface layers would occur.