Visible Satellite Imagery Research Articles

ProxyVis—A Proxy for Nighttime Visible Imagery Applicable to Geostationary Satellite Observations

Abstract Visible satellite imagery is widely used by operational weather forecast centers for tropical and extratropical cyclone analysis and marine forecasting. The absence of visible imagery at night can significantly degrade forecast capabilities, such as determining tropical cyclone center locations or tracking warm-topped convective clusters. This paper documents ProxyVis imagery, an infrared-based proxy for daytime visible imagery developed to address the lack of visible satellite imagery at night and the limitations of existing nighttime visible options. ProxyVis was trained on the VIIRS day/night band imagery at times close to the full moon using VIIRS IR channels with closely matching GOES-16/17/18, Himawari-8/9, and Meteosat-9/10/11 channels. The final operational product applies the ProxyVis algorithms to geostationary satellite data and combines daytime visible and nighttime ProxyVis data to create full-disk animated GeoProxyVis imagery. The simple versions of the ProxyVis algorithm enable its generation from earlier GOES and Meteosat satellite imagery. ProxyVis offers significant improvement over existing operational products for tracking nighttime oceanic low-level clouds. Further, it is qualitatively similar to visible imagery for a wide range of backgrounds and synoptic conditions and phenomena, enabling forecasters to use it without special training. ProxyVis was first introduced to National Hurricane Center (NHC) operations in 2018 and was found to be extremely useful by forecasters becoming part of their standard operational satellite product suite in 2019. Currently, ProxyVis implemented for GOES-16/18, Himawari-9, and Meteosat-9/10/11 is being used in operational settings and evaluated for transition to operations at multiple NWS offices and the Joint Typhoon Warning Center. Significance Statement This paper describes ProxyVis imagery, a new method for combining infrared channels to qualitatively mimic daytime visible imagery at nighttime. ProxyVis demonstrates that a simple linear regression can combine just a few commonly available infrared channels to develop a nighttime proxy for visible imagery that significantly improves a forecaster’s ability to track low-level oceanic clouds and circulation features at night, works for all current geostationary satellites, and is useful across a wide range of backgrounds and meteorological scenarios. Animated ProxyVis geostationary imagery has been operational at the National Hurricane Center since 2019 and is also currently being transitioned to operations at other NWS offices and the Joint Typhoon Warning Center.

Targeted Balloon Observations of Stratosphere‐To‐Troposphere Transport From a Mesoscale Convective System

AbstractStratosphere‐troposphere exchange (STE) is important to the global radiation budget because it is capable of inducing significant changes in trace greenhouse gases such as ozone and water vapor. In the extratropics, stratosphere‐to‐troposphere—or downward—transport (STT) dominates and is routinely driven by upper‐troposphere jet circulations and cyclones. Tropopause‐overshooting convection provides a more rapid STE pathway, but STT in convection is less understood and targeted observations are limited to a handful of fortuitous aircraft encounters. In this study, we seek to improve understanding of STT near thunderstorm anvils using balloon observations of ozone, ground‐based radar observations, visible satellite imagery, and model output. Radar and satellite imagery are used to identify and ultimately target convection driving the “ozone‐wrapping” process. Herein, observations from a single mesoscale convective system in central Oklahoma are reported. A significant ozone enhancement 40%–60% greater than background concentrations in the free troposphere was observed during the balloon ascent underneath and within the anvil of the storm. Backwards particle trajectories were calculated to rule out other sources of this feature such as long‐range transport of stratospheric air and smoke pollution from nearby wildfires. To our knowledge, this work presents the first targeted ozonesonde launch and sampling of this STT process.

Improved estimation of hourly direct normal solar irradiation (DNI) using geostationary satellite visible channel images over moderate albedo areas

An accurate knowledge of the direct solar irradiance at normal incidence (DNI) is required to size solar energy systems, specially those using solar concentration technologies. In the absence of measurements, DNI can be estimated over an arbitrary site with a dedicated satellite model or by using satellite-derived global horizontal irradiance (GHI) and a phenomenological diffuse-direct separation model. This second procedure is error-prone, specially under partial cloudiness conditions and low solar elevation angles. A novel and simple semi-empirical satellite-based model to estimate DNI in moderate albedo regions using a physical clear sky model and a cloudiness index obtained from visible satellite imagery is proposed and assessed. An ergodic assumption in which the images are spatially averaged to better represent the hourly time basis is used. Over the target region (Southeastern South America, SESA), the new DNI satellite model outperforms the alternative strategy at the hourly level, with an average uncertainty of 20% (versus 25%) when compared with three measurement station’s data sets located in center Argentina, southern Brazil and Uruguay.

Spatial characteristics of frazil streaks in the Terra Nova Bay Polynya from high-resolution visible satellite imagery

Abstract. Coastal polynyas around the Antarctic continent are regions of very strong ocean–atmosphere heat and moisture exchange that are important for local and regional weather, sea ice production, and water mass formation. Due to extreme atmospheric conditions (very strong offshore winds, low air temperature, as well as humidity) the surface ocean layer in polynyas is highly turbulent, with mixing due to combined Langmuir, wind-induced, and buoyancy-driven turbulence. One of the visible signs of complex interactions between the mixed-layer dynamics and the forming sea ice are frazil streaks, elongated patches of high ice concentration separated by areas of open water. In spite of their ubiquity, observational and modelling analyses of frazil streaks have been very limited largely due to the fact that their significance for heat flux and ice production is only just becoming apparent. In this study, the first comprehensive analysis of the spatial variability of surface frazil concentration is performed for the Terra Nova Bay Polynya (TNBP). Frazil streaks are identified in high-resolution (pixel size 10–15 m) visible satellite imagery, and their properties (surface area, width, spacing, and orientation) are linked to the meteorological forcing (wind speed and air temperature). This provides a simple statistical tool for estimating the extent and ice coverage of the region of high ice production under given meteorological conditions. It is also shown that the orientation of narrow streaks tends to agree with the wind direction, suggesting the dominating role of the local wind forcing in their formation. Very wide streaks, in turn, deviate from that pattern, as they are presumably influenced by several additional factors, including local water circulation and the associated convergence zones. An analysis of peak wavelengths and directions determined from the images, compared to analogous open-water wavelengths computed with a spectral wave model, demonstrates a significant slow-down in the observed wave growth in TNBP. This suggests an important role of frazil streaks in modifying wind-wave growth and/or dissipation in polynyas.

The Brettenham storm of 25 July 2021

The <scp>Brettenham</scp> storm of 25 <scp>July</scp> 2021

A space view of agricultural and industrial changes during the Syrian civil war

The agricultural sector in Syria was heavily affected by the civil war that started in 2011. We investigate the war’s impact on the country’s atmospheric ammonia (NH3) from 2008 to 2019, using measurements from the infrared atmospheric sounding interferometer instrument on board the Metop satellites. We examine the changes in NH3 close to a fertilizer industry, whose activities were suspended due to conflict-related events. We also explore the effect of war-induced land use/land cover changes on agriculture-emitted ammonia in north-east Syria that has witnessed battles between different groups. The interpretation of the changes in NH3 is supported by different datasets: visible satellite imagery to assess the effect on industrial activity, reanalysis data from the European center for medium-range weather forecasts to look at the effect of meteorology (temperature, wind speed, and precipitation), and land cover and burned area products from the moderate resolution imaging spectroradiometer (MODIS) to examine land use/land cover changes and fire events during the study period. We show that the NH3 columns are directly affected by the war. Periods of intense conflict are reflected in lower values over the industry reaching –17%, –47%, and –32% in 2013, 2014, and 2016, respectively, compared to the [2008–2012] average, and a decrease reaching –14% and –15% in the croplands’ area in northeast Syria during 2017 and 2018 (compared to 2011), respectively. Toward the end of the control of Islamic State in Iraq and Syria, an increase in atmospheric NH3 was accompanied by an increase in croplands’ area that reached up to +35% in 2019 as compared to prewar (2011). This study shows the relevance of remote-sensing data of atmospheric composition in studying societal changes at a local and regional scale.

Environments of Significant Tornadoes Occurring within the Warm Sector versus those Occurring along Surface Baroclinic Boundaries

Archived, hourly-analysis proximity soundings from the operational Rapid Update Cycle (RUC) model are used to examine the vertical wind profiles and thermodynamic parameter space associated with significant tornadoes (rated F2+/EF2+) occurring in the warm sector (33 events) of synoptic cyclones, as well as those occurring along surface baroclinic boundaries (52 events), during the period 1999-2010 over the central and eastern United States. These tornadoes were associated with either the warm sector or a surface baroclinic boundary through the use of subjective surface analyses, supplemented by visible satellite and WSR-88D imagery. A key finding is that measures of ground-relative wind speed, storm-relative helicity, and bulk wind difference are much stronger for warm-sector significant tornado events. In contrast, thermodynamic parameters did not distinguish between the two regimes. Among all of the parameters examined, the observed and predicted speed of the parent supercell showed the most substantial differences between warm-sector and boundary significant tornado environments.&#x0D;

Geomorphology and InSAR-Tracked Surface Displacements in an Ice-Rich Yedoma Landscape

Ice-ridge Yedoma terrain is susceptible to vertical surface displacements by thaw and refreeze of ground ice, and geomorphological processes of mass wasting, erosion and sedimentation. Here we explore the relation between a 3 year data set of InSAR measurements of vertical surface displacements during the thaw season, and geomorphological features in an area in the Indigirka Lowlands, Northeast Siberia. The geomorphology is presented in a geomorphological map, based on interpretation of high resolution visible spectrum satellite imagery, field surveys and available data from paleo-environmental research. The main landforms comprise overlapping drained thaw lake basins and lakes, erosion remnants of Late Pleistocene Yedoma deposits, and a floodplain of a high-sinuosity anastomosing river with ancient river terrace remnants. The spatial distribution of drained thaw lake basins and Yedoma erosion remnants in the study area and its surroundings is influenced by neotectonic movements. The 3 years of InSAR measurement include 2 years of high snowfall and extreme river flooding (2017–2018) and 1 year of modest snowfall, early spring and warm summer (2019). The magnitude of surface displacements varies among the years, and show considerable spatial variation. Distinct spatial clusters of displacement trajectories can be discerned, which relate to geomorphological processes and ground ice conditions. Strong subsidence occurred in particular in 2019. In the wet year of 2017, marked heave occurred at Yedoma plateau surfaces, likely by ice accumulation at the top of the permafrost driven by excess precipitation. The spatial variability of surface displacements is high. This is explored by statistical analysis, and is attributed to the interaction of various processes. Next to ground ice volume change, also sedimentation (peat, colluvial deposition) and shrinkage or swelling of soils with changing water content may have contributed. Tussock tundra areas covered by the extreme 2017 and 2018 spring floods show high subsidence rates and an increase of midsummer thaw depths. We hypothesize that increased flood heights along Siberian lowland rivers potentially induce deeper thaw and subsidence on floodplain margins, and also lowers the drainage thresholds of thaw lakes. Both mechanisms tend to increase floodplain area. This may increase CH4 emission from floodplains, but also may enhance carbon storage in floodplain sedimentary environments.

Evaluating the state-of-the-art in remote volcanic eruption characterization Part I: Raikoke volcano, Kuril Islands

Raikoke, a small, unmonitored volcano in the Kuril Islands, erupted in June 2019. We integrate data from satellites (including Sentinel-2, TROPOMI, MODIS, Himawari-8), the International Monitoring System (IMS) infrasound network, and global lightning detection network (GLD360) with information from local authorities and social media to retrospectively characterize the eruptive sequence and improve understanding of the pre-, syn- and post- eruptive behavior. We observe six infrasound pulses beginning on 21 June at 17:49:55 UTC as well as the main Plinian phase on 21 June at 22:29 UTC. Each pulse is tracked in space and time using lightning and satellite imagery as the plumes drift eastward. Post-eruption visible satellite imagery shows expansion of the island's surface area, an increase in crater size, and a possibly-linked algal bloom south of the island. We use thermal satellite imagery and plume modeling to estimate plume height at 10–12 km asl and 1.5–2 × 106 kg/s mass eruption rate. Remote infrasound data provide insight into syn-eruptive changes in eruption intensity. Our analysis illustrates the value of interdisciplinary analyses of remote data to illuminate eruptive processes. However, our inability to identify deformation, pre-eruptive outgassing, and thermal signals, which may reflect the relatively short duration (~12 h) of the eruption and minimal land area around the volcano and/or the character of closed-system eruptions, highlights current limitations in the application of remote sensing for eruption detection and characterization.

The scale of the whale: using video-tag data to evaluate sea-surface ice concentration from the perspective of individual Antarctic minke whales

BackgroundAdvances in biologging technology allow researchers access to previously unobservable behavioral states and movement patterns of marine animals. To relate behaviors with environmental variables, features must be evaluated at scales relevant to the animal or behavior. Remotely sensed environmental data, collected via satellites, often suffers from the effects of cloud cover and lacks the spatial or temporal resolution to adequately link with individual animal behaviors or behavioral bouts. This study establishes a new method for remotely and continuously quantifying surface ice concentration (SIC) at a scale relevant to individual whales using on-animal tag video data.ResultsMotion-sensing and video-recording suction cup tags were deployed on 7 Antarctic minke whales (Balaenoptera bonaerensis) around the Antarctic Peninsula in February and March of 2018. To compare the scale of camera-tag observations with satellite imagery, the area of view was simulated using camera-tag parameters. For expected conditions, we found the visible area maximum to be ~ 100m2 which indicates that observations occur at an equivalent or finer scale than a single pixel of high-resolution visible spectrum satellite imagery. SIC was classified into one of six bins (0%, 1–20%, 21–40%, 41–60%, 61–80%, 81–100%) by two independent observers for the initial and final surfacing between dives. In the event of a disagreement, a third independent observer was introduced, and the median of the three observer’s values was used. Initial results (n = 6) show that Antarctic minke whales in the coastal bays of the Antarctic Peninsula spend 52% of their time in open water, and only 15% of their time in water with SIC greater than 20%. Over time, we find significant variation in observed SIC, indicating that Antarctic minke occupy an extremely dynamic environment. Sentinel-2 satellite-based approaches of sea ice assessment were not possible because of persistent cloud cover during the study period.ConclusionTag-video offers a means to evaluate ice concentration at spatial and temporal scales relevant to the individual. Combined with information on underwater behavior, our ability to quantify SIC continuously at the scale of the animal will improve upon current remote sensing methods to understand the link between animal behavior and these dynamic environmental variables.

CLOUD DETECTION FOR NIGHT-TIME PANCHROMATIC VISIBLE AND NEAR-INFRARED SATELLITE IMAGERY

Abstract. Cloud detection for night-time panchromatic visible and near-infrared (VNIR) satellite imagery is typically performed based on synchronized observations in the thermal infrared (TIR). To be independent of TIR and to improve existing algorithms, we realize and analyze cloud detection based on VNIR only, here NPP/VIIRS/DNB observations. Using Random Forest for classifying cloud vs. clear and focusing on urban areas, we illustrate the importance of features describing a) the scattering by clouds especially over urban areas with their inhomogeneous light emissions and b) the normalized differences between Earth’s surface and cloud albedo especially in presence of Moon illumination. The analyses substantiate the influences of a) the training site and scene selections and b) the consideration of single scene or multi-temporal scene features on the results for the test sites. As test sites, diverse urban areas and the challenging land covers ocean, desert, and snow are considered. Accuracies of up to 85% are achieved for urban test sites.

Optimized Performance Parameters for Nighttime Multispectral Satellite Imagery to Analyze Lightings in Urban Areas.

Contrary to its daytime counterpart, nighttime visible and near infrared (VIS/NIR) satellite imagery is limited in both spectral and spatial resolution. Nevertheless, the relevance of such systems is unquestioned with applications to, e.g., examine urban areas, derive light pollution, and estimate energy consumption. To determine optimal spectral bands together with required radiometric and spatial resolution, at-sensor radiances are simulated based on combinations of lamp spectra with typical luminances according to lighting standards, surface reflectances, and radiative transfers for the consideration of atmospheric effects. Various band combinations are evaluated for their ability to differentiate between lighting types and to estimate the important lighting parameters: efficacy to produce visible light, percentage of emissions attributable to the blue part of the spectrum, and assessment of the perceived color of radiation sources. The selected bands are located in the green, blue, yellow-orange, near infrared, and red parts of the spectrum and include one panchromatic band. However, these nighttime bands tailored to artificial light emissions differ significantly from the typical daytime bands focusing on surface reflectances. Compared to existing or proposed nighttime or daytime satellites, the recommended characteristics improve, e.g., classification of lighting types by >10%. The simulations illustrate the feasible improvements in nocturnal VIS/NIR remote sensing which will lead to advanced applications.

Machine learning approaches to retrieve pan-Arctic melt ponds from visible satellite imagery

Melt ponds on sea ice play an important role in the seasonal evolution of the summer ice cover. In this study we present two machine learning algorithms, one (multi-layer neural network) for the retrieval of melt pond binary classification and another (multinomial logistic regression) for melt pond fraction using moderate resolution visible satellite imagery from the Moderate Resolution Imaging Spectroradiometer (MODIS). To minimize the impact of the anisotropic reflectance characteristics of sea ice and melt ponds, normalized MODIS band reflectance differences from top-of-the-atmosphere (TOA) measured reflectances were used. The training samples for the machine learning were based on MODIS reflectances extracted for sea ice, melt ponds and open water classifications based on high resolution (~2 m) WorldView (WV) data. The accuracy assessment for melt pond binary classification and fraction is further evaluated against WV imagery, showing mean overall accuracy (85.5%), average mean difference (0.09), and mean RMSE (0.18). In addition to cross-validation with WV, retrieved melt pond data are validated against melt pond fractions from satellite and ship-based observations, showing average mean differences (MD), root-mean-square-error (RMSE), and correlation coefficients (R) of 0.05, 0.12, and 0.41, respectively. We further investigate a case study of the spectral characteristics of melt ponds and ice during refreezing, and demonstrate an approach to mask out refrozen pixels by using yearly maps of melt onset and freeze-up data together with ice surface temperatures (IST). Finally, an example of monthly mean pan-Arctic melt pond binary classification and fraction are shown for July 2001, 2004, 2007, 2010, 2013, 2016, and 2019. Bulk processing of the entire 20 years of MODIS data will provide the science community with a much needed pan-Arctic melt pond data set.

Finding inhabited settlements and tracking vaccination progress: the application of satellite imagery analysis to guide the immunization response to confirmation of previously-undetected, ongoing endemic wild poliovirus transmission in Borno State, Nigeria

BackgroundFour wild polio-virus cases were reported in Borno State, Nigeria 2016, 1 year after Nigeria had been removed from the list of polio endemic countries by the World Health Organization. Resulting from Nigeria’s decade long conflict with Boko Haram, health officials had been unable to access as much as 60% of the settlements in Borno, hindering vaccination and surveillance efforts. This lack of accessibility made it difficult for the government to assess the current population distribution within Borno. This study aimed to use high resolution, visible band satellite imagery to assess the habitation of inaccessible villages in Borno State.MethodsUsing high resolution (31–50 cm) imagery from DigitalGlobe, analysts evaluated the habitation status of settlements in Borno State identified by Nigeria’s Vaccination Tracking System. The analysts looked at imagery of each settlement and, using vegetation (overgrowth vs. cleared) as a proxy for human habitation, classified settlements into three categories: inhabited, partially abandoned, and abandoned. Analysts also classified the intact percentage of each settlement starting at 0% (totally destroyed since last assessment) and increasing in 25% intervals through 100% (completely intact but not expanded) up to 200+% (more than doubled in size) by looking for destroyed buildings. These assessments were then used to adjust previously established population estimates for each settlement. These new population distributions were compared to vaccination efforts to determine the number of children under 5 unreached by vaccination teams.ResultsOf the 11,927 settlements assessed 3203 were assessed as abandoned (1892 of those completely destroyed), 662 as partially abandoned, and 8062 as fully inhabited as of December of 2017. Comparing the derived population estimates from the new assessments to previous assessment and the activities of vaccination teams shows that an estimated 180,155 of the 337,411 under five children who were unreached in 2016 were reached in 2017 (70.5% through vaccination efforts in previously inaccessible areas, 29.5% through displacement to accessible areas).ConclusionsThis study’s methodology provides important planning and situation awareness information to health workers in Borno, Nigeria, and may serve as a model for future data gathering efforts in inaccessible regions.

Analysis of intra-day solar irradiance variability in different Brazilian climate zones

One of the main barriers to increasing the solar energy share is its intermittency. Solar energy’s large variability in different timescales is driven by natural solar astronomical cycles and weather. Ground-based measurements are important for evaluating variability at high temporal resolutions, but they are only representative of small areas close to the measurement sites. Satellite observations come as an alternative to analysis over large areas. However, they have coarse temporal and spatial resolutions. In our study, we first evaluated the variability in different time steps, using one-year of 1-min resolution ground-based irradiance measured at three sites located in different Brazilian climate regimes. The results showed that more humid months have the largest variability. By contrast, the driest locations presented more variability on short timescales, probably due to the presence of a large number of clouds, even in very dry conditions. This characteristic can be of concern to Brazilian energy planning since the site is located in the most prominent region for solar energy generation. We also compared ground observations with satellite cloud variability, with 30-min resolution. For the same timescale, the results were promising, with a Pearson correlation of up to 0.93, depending on the site. However, when the frequency of the solar irradiance measurements increased, the correlation decreased. A solution may be to analyze a larger pixel area around the sites. Another option would be the use of downscaling methods. This topic, however, will be the subject of the future study. The most important result achieved in this study was the development of a simple methodology for evaluating the surface solar irradiance variability using cloud cover obtained from visible satellite imagery.

Remarks by Jonathan Drake

Since 2005, the American Association for the Advancement of Science (AAAS) has been exploring the use of Geospatial Technologies in a Human Rights Context. These efforts began under the auspices of the Science and Human Rights Program, and focused primarily on establishing whether and to what extent satellite imagery could be used to document human rights violations resulting from armed conflict. In partnership with Amnesty International, the project's first applications of this technology involved using visible and near-infrared satellite imagery to investigate reports of villages being burned in Darfur, Sudan. These efforts established the usefulness of satellite imagery as a tool that allowed investigators access areas that would otherwise be completely off-limits due to governmental restrictions, security considerations, remoteness, or some combination of all three. They likewise established a model of collaboration that has proven itself time and again in the application of these new tools to human rights responses.

Detections and simulations of tropospheric water vapor fluctuations due to trapped lee waves by ALOS-2/PALSAR-2 ScanSAR interferometry

Detailed wave-like spatial patterns of atmospheric propagation delay signals associated with mountain lee waves were detected in Hokkaido and Tohoku by synthetic aperture radar (SAR) interferometry (InSAR) with the ScanSAR mode observation data of a Phased Array-type L-band Synthetic Aperture Radar 2 on board the Advanced Land Observing Satellite 2. Both cases occurred under stable atmosphere conditions. The InSAR-observed peak-to-trough line of sight changes in the mountain wave signals was 4 and 5 cm with the horizontal wavelengths of 9 and 15 km in Hokkaido and Tohoku, respectively. Locations of positive phase maxima in the mountain wave signals coincides with locations of cloud streets observed by visible satellite imagery, indicating that crests of mountain waves contain relatively much water vapor compared with wave troughs. Numerical weather simulations with the horizontal grid spacing of 1 km were performed to reproduce InSAR phase variations, and as a result those simulations could reasonably reproduce observed wave amplitudes and wavelengths in both cases. On the other hand, numerical simulations tended to overestimate wave attenuation rates: simulated mountain waves decreased as the wave propagated faster than those of observed signals. Because the simulated wave attenuation rate is sensitive to physics in the planetary boundary layer (PBL), we investigated the reproducibility of five PBL schemes implemented in the WRF model. As a result, all the PBL schemes showed little attenuation except for the Yonsei University scheme (YSU), while the wavelength in the YSU was most close to the observation. Our study demonstrated the uniqueness and usefulness of InSAR for meteorological application as the ability to map the detailed water vapor distribution regardless of cloud cover. In addition, the reasonable reproducibility of the water vapor delay signal due to lee waves by the numerical weather model encourages researchers who tackle the correction of the tropospheric propagation delay, increasing the accuracy in detecting surface deformations.Graphical abstract.

Feasibility of managed domestic rainwater harvesting in South Asian rural areas using remote sensing

Rainwater harvesting is a simple, low-energy and cost effective solution for meeting drinking and domestic water demand in rural communities. In this study, the feasibility of Domestic Rainwater Harvesting (DRH) in South Asia region was assessed using rainfall climatology, remote sensing and water balance concept to improve the rural public health condition. Long term satellite precipitation data was used for analyzing the precipitation climatology as in situ stations are sparsely located in this region. The study area was divided into smaller regions and average roof area for each region was approximated from the satellite visible imagery. It was found that DRH is a viable option in most of Bangladesh, Sri Lanka, Himalayan range, North-Eastern, Central, Eastern and coastal parts of Southern India as the rainfall and household architecture can satisfy potable (7.5liters per capita per day-lpcd for drinking and cooking) water demand for significant portion the year even in worst case scenario. The study demonstrated that DRH system is not a realistic option in most parts of Pakistan, Northern and Western India. DRH would not a feasible option to fulfill the domestic (20 lpcd for drinking, cooking and basic hygienic needs) water demand for significant portion of the year except North-Eastern India. This study is perhaps the first comprehensive assessment of rainwater harvesting potential in rural South Asia using satellite-precipitation climatology and can inform the policy makers on where to invest geographically for building distributed rainwater harvesting systems.

Reducing the Impact of Thin Clouds on Arctic Ocean Sea Ice Concentration From FengYun-3 MERSI Data Single Cavity

Arctic sea ice concentration information can provide technical support for the safety of Arctic shipping routes using visible and near-infrared satellite imagery, but clouds reduce detection accuracy. According to the reflectance changes of ice, clouds, and water, and because the near-infrared reflectances of clouds are much higher than that of ice and water, we propose a new method for identifying clouds. On this basis, thin clouds are extracted using atmospheric precipitation. The Arctic Ocean sea ice distribution under thin cloud cover over can be obtained based on the proposed influential factor iteration method. Finally, we obtain the sea ice concentration in the critical region of Baffin Bay and Davis Strait on June 15, 2014 from the Medium Resolution Imaging Spectrometer (MERSI) data. MERSI is one of the major payloads of the Chinese second-generation polar-orbiting meteorological satellite, FengYun-3, and is similar to the Moderate-resolution Imaging Spectroradiometer. The proposed method is shown to accurately detect sea ice concentration under thin clouds by comparison with the sea ice results from the National Snow and Ice Data Center.

A long-lived tornado on 7 December 2010 in mainland Portugal

On 7 December 2010 a long lived convective storm formed southwest of Lisbon in an instability line that developed in a very moist and unstable airmass, in the circulation of an extra-tropical cyclone propagating north-eastwards. This storm crossed the Lisbon district and spawned an F3 tornado a few dozens of kilometers to the northeast. Several parameters evaluating buoyancy, available moisture and vertical wind shear, were derived from Lisbon rawinsonde and ECMWF analyses, highlighting an environment that is favourable for tornadic development. The tornado touchdown occurred by 14:15 UTC, lasting for about 45min and producing an exceptionally long damage path of around 54km, according to the damage survey. It caused about 18 million Euros damage, >40 injured people, but no fatalities. This storm had a very long lifetime of at least 5h, intensified inland, sustained strong updrafts during, at least, 1h and hold large hail cores as observed on radar. Exhibiting several supercell like features, it also produced intense lightning, with a predominance of cloud-to-ground flashes before the tornado touchdown and intra-cloud flashes during the tornado lifetime. Furthermore, in high resolution visible satellite imagery, a pattern of feeder clouds was identified one hour before tornadogenesis. This pattern has been associated to storm intensification and the onset of severe weather.