scholarly journals The fourth radiation transfer model intercomparison (RAMI-IV): Proficiency testing of canopy reflectance models with ISO-13528

2013 ◽  
Vol 118 (13) ◽  
pp. 6869-6890 ◽  
Author(s):  
J.-L. Widlowski ◽  
B. Pinty ◽  
M. Lopatka ◽  
C. Atzberger ◽  
D. Buzica ◽  
...  
2004 ◽  
Vol 109 (D6) ◽  
pp. n/a-n/a ◽  
Author(s):  
B. Pinty ◽  
J.-L. Widlowski ◽  
M. Taberner ◽  
N. Gobron ◽  
M. M. Verstraete ◽  
...  

2001 ◽  
Vol 106 (D11) ◽  
pp. 11937-11956 ◽  
Author(s):  
Bernard Pinty ◽  
Nadine Gobron ◽  
Jean-Luc Widlowski ◽  
Sigfried A. W. Gerstl ◽  
Michel M. Verstraete ◽  
...  

2011 ◽  
Vol 7 (S283) ◽  
pp. 520-521
Author(s):  
Dejan Vinković ◽  
Bruce Balick

AbstractNew Hubble images of the reflection nebula CRL 2688 from 0.6 to 1.6μm reveal significant variations of color and opacity in the distribution of scattered starlight. We have constructed a detailed radiation-transfer model consisting principally of an optically thick equatorial disk-like structure; bipolar lobes with density enhancements along the polar axis and at the base of lobes; an optically thin extended envelope containing spherical density-enhanced shells to mimic the outer rings of CRL 2688; and a pair of near-stellar caps that collimate and redden the dispersing starlight near its source. Our model nicely reproduces all of the basic features detected in the HST images, including the famous searchlights and arcs, as well as the measured spectral energy distribution (“SED”) of CRL 2688. Assuming a distance of 420 pc we estimate the light originates in a giant star with a temperature T ~ 7000 K and a luminosity L = 5500 ± 1100 L⊙.


2015 ◽  
Vol 2015 ◽  
pp. 1-12 ◽  
Author(s):  
Elizaveta Zabolotskikh ◽  
Bertrand Chapron

A new algorithm is derived for rain rate (RR) estimation from Advanced Microwave Sounding Radiometer 2 (AMSR2) measurements taken at 6.9, 7.3, and 10.65 GHz. The algorithm is based on the numerical simulation of brightness temperatures (TB) for AMSR2 lower frequency channels, using a simplified radiation transfer model. Simultaneous meteorological and hydrological observations, supplemented with modeled values of cloud liquid water content and rain rate values, are used for the calculation of an ensemble of AMSR2TBs and RRs. Ice clouds are not taken into account. AMSR2 brightness temperature differences at C- and X-band channels are then used as inputs to train a neural network (NN) function for RR retrieval. Validation is performed against Tropical Rain Measurement Mission (TRMM) Microwave Instrument (TMI) RR products. For colocated AMSR2-TMI measurements, obtained within 10 min intervals, errors are about 1 mm/h. The new algorithm is applicable for RR estimation up to 20 mm/h. ForRR<2 mm/h the retrieval error is 0.3 mm/h. ForRR>10 mm/h the algorithm significantly underestimates TMI RR.


2019 ◽  
Vol 224 ◽  
pp. 138-156 ◽  
Author(s):  
M.B. Korras-Carraca ◽  
V. Pappas ◽  
N. Hatzianastassiou ◽  
I. Vardavas ◽  
C. Matsoukas

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