The Integrated Nowcasting through Comprehensive Analysis (INCA) System and Its Validation over the Eastern Alpine Region

Abstract This paper presents the Integrated Nowcasting through Comprehensive Analysis (INCA) system, which has been developed for use in mountainous terrain. Analysis and nowcasting fields include temperature, humidity, wind, precipitation amount, precipitation type, cloudiness, and global radiation. The analysis part of the system combines surface station data with remote sensing data in such a way that the observations at the station locations are reproduced, whereas the remote sensing data provide the spatial structure for the interpolation. The nowcasting part employs classical correlation-based motion vectors derived from previous consecutive analyses. In the case of precipitation the nowcast includes an intensity-dependent elevation effect. After 2–6 h of forecast time the nowcast is merged into an NWP forecast provided by a limited-area model, using a predefined temporal weighting function. Cross validation of the analysis and verification of the nowcast are performed. Analysis quality is high for temperature, but comparatively low for wind and precipitation, because of the limited representativeness of station data in mountainous terrain, which can be only partially compensated by the analysis algorithm. Significant added value of the system compared to the NWP forecast is found in the first few hours of the nowcast. At longer lead times the effects of the latest observations becomes small, but in the case of temperature the downscaling of the NWP forecast within the INCA system continues to provide some improvement compared to the direct NWP output.

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Linking thermal UAS-based imagery and Cosmic-Ray Neutron Sensing data

10.5194/egusphere-egu2020-19609 ◽

2020 ◽

Author(s):

Veronika Döpper ◽

Tobias Gränzig ◽

Michael Förster ◽

Birgit Kleinschmit

Keyword(s):

Remote Sensing ◽

Soil Moisture ◽

Hydrological Modeling ◽

Regional Scale ◽

Remote Sensing Data ◽

Cosmic Ray ◽

Added Value ◽

Innovative Technology ◽

Sensing Data ◽

Local Point

Soil moisture content (SMC) is of fundamental importance to many hydrological, biological, biochemical and atmospheric processes. Common soil moisture measurements range from local point measurements to global remote sensing-based SMC datasets. Nevertheless, they always compromise between temporal and spatial resolution. Thus, it is still challenging to quantify spatially and temporally distributed SMC at a regional scale which is extremely relevant for hydrological modeling or agricultural management. The innovative technology Cosmic-Ray Neutron Sensing (CRNS) shows significant potential to fill this gap by quantifying the present hydrogen pools within footprints larger than 0.1 ha.Owing to the difference in scale between the ground resolution of satellites used to retrieve soil moisture and the common point scale of ground-based soil moisture instruments, the large footprint of the CRNS poses a high potential for the validation of SMC remote sensing products. When linking the CRNS measurements with remote sensing data, the vertical and horizontal characteristics of its footprint need to be considered.To examine the influence of the CRNS footprint characteristics on the linkage of CRNS and remote sensing data, we couple CRNS measurements with high-resolution UAS-based thermal imagery acquired at two sites in Bavaria and Brandenburg (Germany) using a radiometrically calibrated FLIR Tau 2 336 (FLIR Systems, Inc., Wilsonville, OR, USA) with a focal length of 9 mm. Within this context, we evaluate the added value of applying a horizontal weighting function to the spatially distributed thermal data in comparison to an unweighted mean when statistically representing the corrected neutron counting rates.The project is part of the DFG-funded research group Cosmic Sense, which aims to provide interdisciplinary new representative insights into hydrological changes at the land surface.

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Empirical validation and proof of added value of MUSICA's tropospheric δD remote sensing products

Atmospheric Measurement Techniques Discussions ◽

10.5194/amtd-7-6917-2014 ◽

2014 ◽

Vol 7 (7) ◽

pp. 6917-6969 ◽

Cited By ~ 7

Author(s):

M. Schneider ◽

Y. González ◽

C. Dyroff ◽

E. Christner ◽

A. Wiegele ◽

...

Keyword(s):

Remote Sensing ◽

Water Vapour ◽

Lower Troposphere ◽

Remote Sensing Data ◽

Added Value ◽

Empirical Validation ◽

Transport Pathways ◽

Sensing Data ◽

Interferometer Observation

Abstract. The project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) integrates tropospheric water vapour isototopologue remote sensing and in-situ observations. This paper presents a first empirical validation of MUSICA's H2O and δD remote sensing products (generated from ground-based FTIR, Fourier Transform InfraRed, spectrometer and space-based IASI, Infrared Atmospheric Sounding Interferometer, observation). As reference we use well calibrated in-situ measurements made aboard an aircraft (between 200 and 6800 m a.s.l.) by the dedicated ISOWAT instrument and on the island of Tenerife at two different altitudes (at Izaña, 2370 m a.s.l., and at Teide, 3550 m a.s.l.) by two commercial Picarro L2120-i water isotopologue analysers. The comparison to the ISOWAT profile measurements shows that the remote sensors can well capture the variations in the water vapour isotopologues and the scatter with respect to the in-situ references suggests a δD random uncertainty for the FTIR product of much better than 45‰ in the lower troposphere and of about 15‰ for the middle troposphere. For the middle tropospheric IASI δD product the study suggests a respective uncertainty of about 15‰. In addition, we find indications for a positive δD bias in the remote sensing products. The δD data are scientifically interesting only if they add information to the H2O observations. We are able to qualitatively demonstrate the added value of the MUSICA δD remote sensing data by comparing δD-vs.-H2O curves. First, we show that the added value of δD as seen in the Picarro data is similarly seen in FTIR data measured in coincidence. Second, we document that the δD-vs.-H2O curves obtained from the different in-situ and remote sensing data sets (ISOWAT, Picarro at Izaña and Teide, FTIR, and IASI) consistently identify two different moisture transport pathways to the subtropical north eastern Atlantic free troposphere.

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Empirical validation and proof of added value of MUSICA's tropospheric δD remote sensing products

Atmospheric Measurement Techniques ◽

10.5194/amt-8-483-2015 ◽

2015 ◽

Vol 8 (1) ◽

pp. 483-503 ◽

Cited By ~ 16

Author(s):

M. Schneider ◽

Y. González ◽

C. Dyroff ◽

E. Christner ◽

A. Wiegele ◽

...

Keyword(s):

Remote Sensing ◽

Water Vapour ◽

Moisture Transport ◽

Lower Troposphere ◽

Remote Sensing Data ◽

Added Value ◽

Data Sets ◽

Empirical Validation ◽

Sensing Data

Abstract. The project MUSICA (MUlti-platform remote Sensing of Isotopologues for investigating the Cycle of Atmospheric water) integrates tropospheric water vapour isotopologue remote sensing and in situ observations. This paper presents a first empirical validation of MUSICA's H2O and δD remote sensing products, generated from ground-based FTIR (Fourier transform infrared), spectrometer and space-based IASI (infrared atmospheric sounding interferometer) observation. The study is made in the area of the Canary Islands in the subtropical northern Atlantic. As reference we use well calibrated in situ measurements made aboard an aircraft (between 200 and 6800 m a.s.l.) by the dedicated ISOWAT instrument and on the island of Tenerife at two different altitudes (at Izaña, 2370 m a.s.l., and at Teide, 3550 m a.s.l.) by two commercial Picarro L2120-i water isotopologue analysers. The comparison to the ISOWAT profile measurements shows that the remote sensors can well capture the variations in the water vapour isotopologues, and the scatter with respect to the in situ references suggests a δD random uncertainty for the FTIR product of much better than 45‰ in the lower troposphere and of about 15‰ for the middle troposphere. For the middle tropospheric IASI δD product the study suggests a respective uncertainty of about 15‰. In both remote sensing data sets we find a positive δD bias of 30–70‰. Complementing H2O observations with δD data allows moisture transport studies that are not possible with H2O observations alone. We are able to qualitatively demonstrate the added value of the MUSICA δD remote sensing data. We document that the δD–H2O curves obtained from the different in situ and remote sensing data sets (ISOWAT, Picarro at Izaña and Teide, FTIR, and IASI) consistently identify two different moisture transport pathways to the subtropical north eastern Atlantic free troposphere.

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Understanding heterogeneity in metropolitan India: The added value of remote sensing data for analyzing sub-standard residential areas

International Journal of Applied Earth Observation and Geoinformation ◽

10.1016/j.jag.2010.04.008 ◽

2010 ◽

Vol 12 (5) ◽

pp. 359-374 ◽

Cited By ~ 64

Author(s):

Isa Baud ◽

Monika Kuffer ◽

Karin Pfeffer ◽

Richard Sliuzas ◽

Sadasivam Karuppannan

Keyword(s):

Remote Sensing ◽

Remote Sensing Data ◽

Added Value ◽

Residential Areas ◽

Sensing Data

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A comprehensive analysis of terrestrial surface features using remote sensing data

10.5353/th_b5351026 ◽

2014 ◽

Author(s):

Liqun Sun

Keyword(s):

Remote Sensing ◽

Remote Sensing Data ◽

Comprehensive Analysis ◽

Surface Features ◽

Sensing Data

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Depth Faults Along The Regmatic Network Of The Chatkalo-Kuramin Region And Their Relationship With Seismicity

The American Journal of Applied Sciences ◽

10.37547/tajas/volume02issue12-11 ◽

2020 ◽

Vol 02 (12) ◽

pp. 68-76

Author(s):

Madinabonu Zaxritdinovna Fazliddinova ◽

◽

Akram Bayramovich Goipov ◽

Maftuna Asad qizi Saidova ◽

◽

...

Keyword(s):

Remote Sensing ◽

Satellite Images ◽

Remote Sensing Data ◽

Comprehensive Analysis ◽

Landsat 8 ◽

Strong Earthquakes ◽

Sensing Data ◽

Aster Gdem ◽

Digital Elevation ◽

Lineament Analysis

Lineaments were identified using LANDSAT-8 satellite images and digital elevation models obtained from the ASTER GDEM satellite over the Chatkal-Kuramin region. Taking into account the stock materials and a comprehensive analysis of the results of processing remote sensing data, a map of lineaments of a 1: 100,000 regmatic network was compiled. Based on the automated visual lineament analysis in the Geomatica PCI program, lineaments of the regmatic network were obtained, which are located in the focal zones of strong earthquakes.

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