scholarly journals FORCAST: A Mid-Infrared Camera for SOFIA

2018 ◽  
Vol 07 (04) ◽  
pp. 1840005 ◽  
Author(s):  
T. L. Herter ◽  
J. D. Adams ◽  
G. E. Gull ◽  
J. Schoenwald ◽  
L. D. Keller ◽  
...  

We describe the Faint Object infraRed CAmera for the SOFIA Telescope (FORCAST) which is presently operating as a facility instrument on the Stratospheric Observatory For Infrared Astronomy (SOFIA). FORCAST provides imaging and moderate resolution spectroscopy capability over the 5–40[Formula: see text][Formula: see text]m wavelength range. In imaging mode, FORCAST has a 3.4[Formula: see text] field-of-view with 0.768[Formula: see text] pixels. Using grisms, FORCAST provides long-slit low-resolution ([Formula: see text]–300) and short-slit, cross-dispersed medium-resolution spectroscopic modes ([Formula: see text]–1200) over select wavelengths. Preceded by both Spitzer and Herschel, the discovery phase space for FORCAST lies in providing unique photometric bands and/or spectroscopic coverage, higher spatial resolution and exploration of the brightest sources which typically saturate space observatories.

Author(s):  
Daniel Gezari ◽  
Frank Varosi ◽  
Eli Dwek ◽  
William Danchi ◽  
Jonathan Tan ◽  
...  

We have modeled two mid-infrared imaging photometry data sets to determine the spatial distribution of physical conditions in the BN/KL infrared complex. We observed the BN/KL region using the 10-m Keck I telescope and the LWS in the direct imaging mode, over a 13” × 19” field (Figure 1, left). We also modeled images obtained with COMICS (Kataza et al. 2000) at the 8.2-m SUBARU telescope, over a total field of view is 31” × 41” (Figure 1, right), in a total of nine bands: 7.8, 8.8, 9.7, 10.5, 11.7, 12.4, 18.5, 20.8 and 24.8 μm with ~1 μm bandwidth interference filters.


2005 ◽  
Vol 14 ◽  
pp. 337-342 ◽  
Author(s):  
M. Dolci ◽  
G. Valentini ◽  
O. Straniero ◽  
G. Di Rico ◽  
M. Ragni ◽  
...  

2021 ◽  
Vol 13 (5) ◽  
pp. 920
Author(s):  
Zhongting Wang ◽  
Ruru Deng ◽  
Pengfei Ma ◽  
Yuhuan Zhang ◽  
Yeheng Liang ◽  
...  

Aerosol distribution with fine spatial resolution is crucial for atmospheric environmental management. This paper proposes an improved algorithm of aerosol retrieval from 250-m Medium Resolution Spectral Image (MERSI) data of Chinese FY-3 satellites. A mixing model of soil and vegetation was used to calculate the parameters of the algorithm from moderate-resolution imaging spectroradiometer (MODIS) reflectance products in 500-m resolution. The mixing model was used to determine surface reflectance in blue band, and the 250-m aerosol optical depth (AOD) was retrieved through removing surface contributions from MERSI data over Guangzhou. The algorithm was used to monitor two pollution episodes in Guangzhou in 2015, and the results displayed an AOD spatial distribution with 250-m resolution. Compared with the yearly average of MODIS aerosol products in 2015, the 250-m resolution AOD derived from the MERSI data exhibited great potential for identifying air pollution sources. Daily AODs derived from MERSI data were compared with ground results from CE318 measurements. The results revealed a correlation coefficient between the AODs from MERSI and those from the ground measurements of approximately 0.85, and approximately 68% results were within expected error range of ±(0.05 + 15%τ).


2012 ◽  
Vol 5 (2) ◽  
pp. 2169-2220 ◽  
Author(s):  
A. M. Sayer ◽  
N. C. Hsu ◽  
C. Bettenhausen ◽  
M.-J. Jeong ◽  
B. N. Holben ◽  
...  

Abstract. This study evaluates a new spectral aerosol optical depth (AOD) dataset derived from Sea-viewing Wide Field-of-view Sensor (SeaWiFS) measurements over land. First, the data are validated against Aerosol Robotic Network (AERONET) direct-sun AOD measurements, and found to compare well on a global basis. If only data with the highest quality flag are used, the correlation is 0.86 and 72% of matchups fall within an expected absolute uncertainty of 0.05 + 20% (for the wavelength of 550 nm). The quality is similar at other wavelengths and stable over the 13-yr (1997–2010) mission length. Performance tends to be better over vegetated, low-lying terrain with typical AOD of 0.3 or less, such as found over much of North America and Eurasia. Performance tends to be poorer for low-AOD conditions near backscattering geometries, where SeaWiFS overestimates AOD, or optically-thick cases of absorbing aerosol, where SeaWiFS tends to underestimate AOD. Second, the SeaWiFS data are compared with midvisible AOD derived from the Moderate Resolution Imaging Spectrometer (MODIS) and Multiangle Imaging Spectroradiometer (MISR). All instruments show similar spatial and seasonal distributions of AOD, although there are regional and seasonal offsets between them. At locations where AERONET data are available, these offsets are largely consistent with the known validation characteristics of each dataset. With the results of this study in mind, the SeaWiFS over-land AOD record is suitable for quantitative scientific use.


2020 ◽  
Author(s):  
Thomas G. Müller ◽  
Martin J. Burgdorf ◽  
Stefan A. Buehler ◽  
Marc Prange

<p>We present a thermophysical model (TPM) of the Moon which matches the observed, global, disk-integrated thermal flux densities of the Moon in the mid-infrared wavelength range for a phase angle range from -90° to +90°.<br />The model was tested and verified against serendipitous multi-channel HIRS measurements of the Moon obtained by different meteorological satellites (NOAA-11, NOAA-14, NOAA-15, NOAA-17, NOAA-18, NOAA-19, MetOp-A, MetOp-B). The sporadic intrusions of the Moon in the deep space view of these instruments have been extracted in cases where the entire Moon was within the instruments' field of view. The HIRS long-wavelengths channels 1-12 cover the range from 6.5 to 15 μm, the short-wavelengths channels 13-19 are in the 3.7 to 4.6 μm range.</p> <p>The model is based on an asteroid TPM concept (Lagerros 1996, 1997, 1998; Müller & Lagerros 1998, 2002), using the known global properties of the Moon (like size, shape, spin properties, geometric albedo, thermal inertia, surface roughness, see Keihm 1984; Racca 1995; Rozitis & Green 2011; Hayne et al. 2017), combined with a model for the spectral hemispherical emissivity which varies between 0.6 and 1.0 in the HIRS wavelength range (Shaw 1998; ECOSTRESS data base: https://ecostress.jpl.nasa.gov/). The spectral emissivity as well as characteristics of the surface roughness are crucial to explain the well-calibrated measurements.</p> <p>Our Moon model fits the flux densities for the currently available 22 epochs (each time up to 19 channels) with an absolute accuracy of 5-10%. The phase curves at the different wavelengths are well explained. The spectral energy distributions are very sensitive to emissivity and roughness properties. Here, we see minor variations in the model fits, depending on the origin (phase and aspect angle related) of the thermal emission. We also investigated the influence of reflected sunlight at short wavelengths.</p> <p>Our TPM of the Moon has a wide range of applications: (i) for Earth-observing weather satellites in the context of field of view and photometric calibration (e.g., Burgdorf et al. 2020); (ii) for interplanetary space missions (e.g., Hayabusa2, OSIRIS-REx or BepiColombo) with infrared instruments on board for an in-space characterization of instrument properites (e.g., Okada et al. 2018); (iii) to shed light on the thermal mid-infrared properties of the lunar surface on a global scale; and, (iv) to benchmark thermophysical model techniques for asteroids in the regime below 10 μm (e.g., observed by WISE in the W1 and W2 bands at 3.4 and 4.6 μm, by Spitzer-IRAC at 3.55 and 4.49 μm or from ground in M band at around 5 μm).</p> <p><br />References:<br />Burgdorf M., et al. 2020, Remote Sens. 12, 1488; Hayne, P. et al. 2017, JGRE 122, 237; Keihm, S.J. 1984, Icarus 60, 568; Lagerros 1996,  A&A 310, 1011; Lagerros 1997, A&A 325, 1226; Lagerros 1998, A&A 332, 1123; Müller & Lagerros 1998, A&A 338, 340; Müller & Lagerros 2002, A&A 381, 324; Okada T. et al. 2018, P&SS 158, 46; Racca G. 1995, P&SS 43, 835; Rozitis & Green 2011, MNRAS 415, 2042.</p> <p> </p>


2008 ◽  
Author(s):  
Charles M. Telesco ◽  
Christopher Packham ◽  
Christ Ftaclas ◽  
James H. Hough ◽  
Margaret M. Moerchen ◽  
...  

2003 ◽  
Author(s):  
Yoshiko K. Okamoto ◽  
Hirokazu Kataza ◽  
Takuya Yamashita ◽  
Takashi Miyata ◽  
Shigeyuki Sako ◽  
...  
Keyword(s):  

2010 ◽  
Vol 2010 ◽  
pp. 1-10 ◽  
Author(s):  
Daxiang Xiang ◽  
Liangming Liu ◽  
Qiao Wang ◽  
Na Yang ◽  
Tao Han

FY-3A is the second Chinese Polar Orbital Meteorological Satellite with global, three-dimensional, quantitative, and multispectral capabilities. Its missions include monitoring global disasters and environment changes. This study describes some basic parameters and major technical indicators of the FY-3A and evaluates data quality and drought monitoring capability of the Medium-Resolution Imager (MERSI) onboard the FY-3A. Data obtained with the MERSI was compared with that of the MODerate-resolution Imaging Spectroradiometer (MODIS), imaged at the same time period and geographic zone. In addition, the Temperature/Vegetation Drought Index (TVDI), a highly accurate and stable monitoring model, was used to monitor drought condition with MERSI and MODIS sensors. It is found in the study that the relative accuracy of data, obtained with these two devices, was consistent with the acceptable overall accuracy of 93.8. Furthermore, spatial resolution of MERSI is superior as compared to that of MODIS. Therefore, FY-3A MERSI can serve a reliable and new data source for drought monitoring.


Author(s):  
Shinki Oyabu ◽  
Naofumi Fujishiro ◽  
Hirokazu Kataza ◽  
Takehiko Wada ◽  
Yuji Ikeda ◽  
...  

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