scholarly journals Cirrus Horizontal Heterogeneity and 3-D Radiative Effects on Cloud Optical Property Retrievals From MODIS Near to Thermal Infrared Channels as a Function of Spatial Resolution

2018 ◽  
Vol 123 (19) ◽  
pp. 11,141-11,153 ◽  
Author(s):  
T. Fauchez ◽  
S. Platnick ◽  
O. Sourdeval ◽  
C. Wang ◽  
K. Meyer ◽  
...  
Keyword(s):  
Optical Property ◽  
Spatial Resolution ◽  
Thermal Infrared ◽  
Radiative Effects ◽  
Horizontal Heterogeneity

scholarly journals Scale dependence of cirrus heterogeneity effects. Part II: MODIS NIR and SWIR channels

2018 ◽  
Vol 18 (16) ◽  
pp. 12105-12121 ◽  
Author(s):  
Thomas Fauchez ◽  
Steven Platnick ◽  
Tamás Várnai ◽  
Kerry Meyer ◽  
Céline Cornet ◽  
...  
Keyword(s):  
Radiative Transfer ◽  
Spatial Resolution ◽  
Thermal Infrared ◽  
Radiative Effects ◽  
Ice Clouds ◽  
Plane Parallel ◽  
Wide Range ◽  
The Impact ◽  
Side Illumination

Abstract. In a context of global climate change, the understanding of the radiative role of clouds is crucial. On average, ice clouds such as cirrus have a significant positive radiative effect, but under some conditions the effect may be negative. However, many uncertainties remain regarding the role of ice clouds on Earth's radiative budget and in a changing climate. Global satellite observations are particularly well suited to monitoring clouds, retrieving their characteristics and inferring their radiative impact. To retrieve ice cloud properties (optical thickness and ice crystal effective size), current operational algorithms assume that each pixel of the observed scene is plane-parallel and homogeneous, and that there is no radiative connection between neighboring pixels. Yet these retrieval assumptions are far from accurate, as real radiative transfer is 3-D. This leads to the plane-parallel and homogeneous bias (PPHB) plus the independent pixel approximation bias (IPAB), which impacts both the estimation of top-of-the-atmosphere (TOA) radiation and the retrievals. An important factor that determines the impact of these assumptions is the sensor spatial resolution. High-spatial-resolution pixels can better represent cloud variability (low PPHB), but the radiative path through the cloud can involve many pixels (high IPAB). In contrast, low-spatial-resolution pixels poorly represent the cloud variability (high PPHB), but the radiation is better contained within the pixel field of view (low IPAB). In addition, the solar and viewing geometry (as well as cloud optical properties) can modulate the magnitude of the PPHB and IPAB. In this, Part II of our study, we simulate TOA 0.86 and 2.13 µm solar reflectances over a cirrus uncinus scene produced by the 3DCLOUD model. Then, 3-D radiative transfer simulations are performed with the 3DMCPOL code at spatial resolutions ranging from 50 m to 10 km, for 12 viewing geometries and nine solar geometries. It is found that, for simulated nadir observations taken at resolution higher than 2.5 km, horizontal radiation transport (HRT) dominates biases between 3-D and 1-D reflectance calculations, but these biases are mitigated by the side illumination and shadowing effects for off-zenith solar geometries. At resolutions coarser than 2.5 km, PPHB dominates. For off-nadir observations at resolutions higher than 2.5 km, the effect that we call THEAB (tilted and homogeneous extinction approximation bias) due to the oblique line of sight passing through many cloud columns contributes to a large increase of the reflectances, but 3-D radiative effects such as shadowing and side illumination for oblique Sun are also important. At resolutions coarser than 2.5 km, the PPHB is again the dominant effect. The magnitude and resolution dependence of PPHB and IPAB is very different for visible, near-infrared and shortwave infrared channels compared with the thermal infrared channels discussed in Part I of this study. The contrast of 3-D radiative effects between solar and thermal infrared channels may be a significant issue for retrieval techniques that simultaneously use radiative measurements across a wide range of solar reflectance and infrared wavelengths.

scholarly journals Scale dependence of cirrus horizontal heterogeneity effects on TOA measurements – Part I: MODIS brightness temperatures in the thermal infrared

2017 ◽  
Vol 17 (13) ◽  
pp. 8489-8508 ◽  
Author(s):  
Thomas Fauchez ◽  
Steven Platnick ◽  
Kerry Meyer ◽  
Céline Cornet ◽  
Frédéric Szczap ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Optical Thickness ◽  
Approximation Error ◽  
Thermal Infrared ◽  
Sensitivity Study ◽  
Brightness Temperatures ◽  
Model Average ◽  
Horizontal Heterogeneity ◽  
Heterogeneity Effects ◽  
The Impact

Abstract. This paper presents a study on the impact of cirrus cloud heterogeneities on MODIS simulated thermal infrared (TIR) brightness temperatures (BTs) at the top of the atmosphere (TOA) as a function of spatial resolution from 50 m to 10 km. A realistic 3-D cirrus field is generated by the 3DCLOUD model (average optical thickness of 1.4, cloud-top and base altitudes at 10 and 12 km, respectively, consisting of aggregate column crystals of Deff = 20 µm), and 3-D thermal infrared radiative transfer (RT) is simulated with the 3DMCPOL code. According to previous studies, differences between 3-D BT computed from a heterogenous pixel and 1-D RT computed from a homogeneous pixel are considered dependent at nadir on two effects: (i) the optical thickness horizontal heterogeneity leading to the plane-parallel homogeneous bias (PPHB) and the (ii) horizontal radiative transport (HRT) leading to the independent pixel approximation error (IPAE). A single but realistic cirrus case is simulated and, as expected, the PPHB mainly impacts the low-spatial-resolution results (above ∼ 250 m) with averaged values of up to 5–7 K, while the IPAE mainly impacts the high-spatial-resolution results (below ∼ 250 m) with average values of up to 1–2 K. A sensitivity study has been performed in order to extend these results to various cirrus optical thicknesses and heterogeneities by sampling the cirrus in several ranges of parameters. For four optical thickness classes and four optical heterogeneity classes, we have found that, for nadir observations, the spatial resolution at which the combination of PPHB and HRT effects is the smallest, falls between 100 and 250 m. These spatial resolutions thus appear to be the best choice to retrieve cirrus optical properties with the smallest cloud heterogeneity-related total bias in the thermal infrared. For off-nadir observations, the average total effect is increased and the minimum is shifted to coarser spatial resolutions.

scholarly journals Scale dependence of cirrus heterogeneity effects. Part I: MODIS thermal infrared channels

2017 ◽  
Author(s):  
Thomas Fauchez ◽  
Steven Platnick ◽  
Kerry Meyer ◽  
Céline Cornet ◽  
Frédéric Szczap ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Optical Thickness ◽  
Approximation Error ◽  
Thermal Infrared ◽  
Sensitivity Study ◽  
Brightness Temperatures ◽  
Homogeneous Plane ◽  
Horizontal Heterogeneity ◽  
Heterogeneity Effects ◽  
The Impact

Abstract. This paper presents a study on the impact of cirrus cloud heterogeneities on MODIS simulated thermal infrared (TIR) brightness temperatures (BT) at the top of the atmosphere (TOA) as a function of spatial resolution from 50 m to 10 km. A realistic 3-D cirrus field is generated by the 3DCLOUD model, and 3-D thermal infrared radiative transfer (RT) is simulated with the 3DMCPOL code. According to previous studies, differences between 3-D BT computed from a heterogeneous pixel and 1-D RT computed from a homogeneous pixel are considered dependent, at nadir, on two effects: (i) the optical thickness horizontal heterogeneity leading to the homogeneous plane parallel bias (PPHB) and the (ii) horizontal radiative transport (HRT) leading to the independent pixel approximation error (IPAE). A unique but realistic cirrus case is simulated and, as expected, the PPHB impacts mainly the low spatial resolution results (above 250 m) with averaged values up to 5–7 K while the IPAE impacts mainly the high spatial resolution results (below 250 m) with average values up to 1–2 K. A sensitivity study has been performed in order to extend these results to various cirrus optical thicknesses and heterogeneities by sampling the cirrus in several ranges of parameters. For four optical thickness classes and four optical heterogeneity classes, we have found that, for nadir observations, the spatial resolution where the combination of PPHB and HRT effects is the smallest, falls between 100 m and 250 m. These spatial resolutions appear thus to be the best choice to retrieve cirrus optical properties with the smallest cloud heterogeneity related total bias in the thermal infrared. For off-nadir observations, the average total effect is increased and the minimum is shifted to coarser spatial resolutions.

Sea–ice concentration at 1 km resolution in summer from merged visible and microwave radiometer observations

2021 ◽  
Author(s):  
Valentin Ludwig ◽  
Gunnar Spreen
Keyword(s):  
Spatial Resolution ◽  
Microwave Radiometer ◽  
Thermal Infrared ◽  
Passive Microwave ◽  
The Arctic ◽  
Sea Ice Concentration ◽  
Ice Concentration ◽  
Statistical Consistency ◽  
Microwave Data ◽  
Infrared Data

<p>Sea–ice concentration, the surface fraction of ice in a given area, is a key component of the Arctic climate system, governing for example the ocean–atmosphere heat exchange. Satellite–based remote sensing offers the possibility for large–scale monitoring of the sea–ice concentration. Using passive microwave measurements, it is possible to observe the sea–ice concentration all year long, almost independently of cloud coverage. The spatial resolution of these measurements is limited to 5 km and coarser. Data from the visible and thermal infrared spectrum offer finer resolutions of 250 m–1 km, but need clear–sky scenes and, in case of visible data, sunlight. In previous work, we developed and analysed a merged dataset of passive microwave and thermal infrared data, combining AMSR2 and MODIS satellite data at 1 km spatial resolution. It has benefits over passive microwave data in terms of the finer spatial resolution and an enhanced potential for lead detection. At the same time, it outperforms thermal infrared data due to its spatially continuous coverage and the statistical consistency with the extensively evaluated passive microwave data. Due to higher surface temperatures in summer, the thermal–infrared based retrieval is limited to winter and spring months. In this contribution, we present first results of extending the existing dataset to summer by using visible data instead of thermal infrared data. The reflectance contrast between ice and water is used for the sea–ice concentration retrieval and results of merging visible and microwave data at 1 km spatial resolution are presented. Difficulties for both, the microwave and visual, data are surface melt processes during summer, which make sea–ice concentration retrieval more challenging. The merged microwave, infrared and visual dataset opens the possibility for a year–long, spatially continuous sea ice concentration dataset at a spatial resolution of 1 km.</p>

scholarly journals Applying the Tropical Peatland Combustion Algorithm to Landsat-8 Operational Land Imager (OLI) and Sentinel-2 Multi Spectral Instrument (MSI) Imagery

2020 ◽  
Vol 12 (23) ◽  
pp. 3958
Author(s):  
Parwati Sofan ◽  
David Bruce ◽  
Eriita Jones ◽  
M. Rokhis Khomarudin ◽  
Orbita Roswintiarti
Keyword(s):  
Spatial Resolution ◽  
Fire Detection ◽  
Ground Truth ◽  
Thermal Infrared ◽  
Landsat 8 ◽  
Ground Truth Data ◽  
Spectral Instrument ◽  
Tropical Peatland ◽  
Tropical Environments ◽  
Sentinel 2

This study establishes a new technique for peatland fire detection in tropical environments using Landsat-8 and Sentinel-2. The Tropical Peatland Combustion Algorithm (ToPeCAl) without longwave thermal infrared (TIR) (henceforth known as ToPeCAl-2) was tested on Landsat-8 Operational Land Imager (OLI) data and then applied to Sentinel-2 Multi Spectral Instrument (MSI) data. The research is aimed at establishing peatland fire information at higher spatial resolution and more frequent observation than from Landsat-8 data over Indonesia’s peatlands. ToPeCAl-2 applied to Sentinel-2 was assessed by comparing fires detected from the original ToPeCAl applied to Landsat-8 OLI/Thermal Infrared Sensor (TIRS) verified through comparison with ground truth data. An adjustment of ToPeCAl-2 was applied to minimise false positive errors by implementing pre-process masking for water and permanent bright objects and filtering ToPeCAl-2’s resultant detected fires by implementing contextual testing and cloud masking. Both ToPeCAl-2 with contextual test and ToPeCAl with cloud mask applied to Sentinel-2 provided high detection of unambiguous fire pixels (>95%) at 20 m spatial resolution. Smouldering pixels were less likely to be detected by ToPeCAl-2. The detected smouldering pixels from ToPeCAl-2 applied to Sentinel-2 with contextual testing and with cloud masking were only 35% and 56% correct, respectively; this needs further investigation and validation. These results demonstrate that even in the absence of TIR data, an adjusted ToPeCAl algorithm (ToPeCAl-2) can be applied to detect peatland fires at 20 m resolution with high accuracy especially for flaming. Overall, the implementation of ToPeCAl applied to cost-free and available Landsat-8 and Sentinel-2 data enables regular peatland fire monitoring in tropical environments at higher spatial resolution than other satellite-derived fire products.

Mapping the volcanic and postvolcanic activity and its revealing on thermal infrared satellite images of high spatial resolution

2019 ◽  
Vol 953 (11) ◽  
pp. 56-64
Author(s):  
M.Yu. Grischchenko ◽  
A.V. Ustyukhina
Keyword(s):  
Northern Hemisphere ◽  
Spatial Resolution ◽  
Satellite Images ◽  
High Spatial Resolution ◽  
Thermal Infrared ◽  
Infrared Images ◽  
Thermal Infrared Images ◽  
Active Volcanoes

The article deals with revealing the volcanic and postvolcanic activity on the thermal infrared images of high spatial resolution (ASTER, TM, ETM +, TIRS) and mapping based on the results of their interpretation. Active volcanoes of the temperate and subpolar zones of the Northern Hemisphere are considered

Static Target Identification Based on the Simulation of Thermal Infrared Image

2012 ◽  
Vol 505 ◽  
pp. 299-304
Author(s):  
Li Liu ◽  
Xing Fa Gu ◽  
Tao Yu ◽  
Xiao Ying Li ◽  
Jia Guo Li ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Target Identification ◽  
Infrared Image ◽  
Thermal Infrared ◽  
Thermal Image ◽  
Remote Sensors ◽  
The Difference ◽  
Static Target ◽  
Cement Surface

Based on the principle of the simulation of the infrared thermal image, the static aircraft in the background of cement surface, at 2:00, 11:00, 14:00, are simulated under the remote sensors with spatial resolution of 5m and 10m. The evaluation is based on the radiance of target and the background extracted from the simulation image. The results indicate that the method in this paper can reflect the difference of radiance between the static target and the background which is useful in the target identification.

scholarly journals Multisensor Fusion of Landsat Images for High-Resolution Thermal Infrared Images Using Sparse Representations

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Hong Sung Jin ◽  
Dongyeob Han
Keyword(s):  
High Resolution ◽  
Sparse Representation ◽  
Spatial Resolution ◽  
Land Surface ◽  
Spectral Response ◽  
Thermal Infrared ◽  
Environmental Research ◽  
Infrared Images ◽  
Thermal Infrared Images ◽  
Thermal Band

Land surface temperature (LST) is an important parameter in the analysis of climate and human-environment interactions. Landsat Earth observation satellite data including a thermal band have been used for environmental research and applications; however, the spatial resolution of this thermal band is relatively low. This study investigates an efficient method of fusing Landsat panchromatic and thermal infrared images using a sparse representation (SR) technique. The application of SR is used for the estimation of missing details of the available thermal infrared (TIR) image to enhance its spatial features. First, we propose a method of building a proper dictionary considering the spatial resolution of the original thermal image. Second, a sparse representation relation between low- and high-resolution images is constructed in terms of the Landsat spectral response. We then compare the fused images created with different sampling factors and patch sizes. The results of both qualitative and quantitative evaluation show that the proposed method improves spatial resolution and preserves the thermal properties of basic LST data for use with environmental problems.

scholarly journals High Spatial Resolution Thermal Infrared Spectroscopy with ALES: Resolved Spectra of the Benchmark Brown Dwarf Binary HD 130948BC

2019 ◽  
Vol 157 (6) ◽  
pp. 244 ◽  
Author(s):  
Zackery W. Briesemeister ◽  
Andrew J. Skemer ◽  
Jordan M. Stone ◽  
Travis S. Barman ◽  
Philip Hinz ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Thermal Infrared ◽  
Brown Dwarf ◽  
Thermal Infrared Spectroscopy
Sign in / Sign up

Export Citation Format

Share Document