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2022 ◽  
Vol 19 (1) ◽  
pp. 29-45
Author(s):  
Yujie Wang ◽  
Christian Frankenberg

Abstract. Lack of direct carbon, water, and energy flux observations at global scales makes it difficult to calibrate land surface models (LSMs). The increasing number of remote-sensing-based products provide an alternative way to verify or constrain land models given their global coverage and satisfactory spatial and temporal resolutions. However, these products and LSMs often differ in their assumptions and model setups, for example, the canopy model complexity. The disagreements hamper the fusion of global-scale datasets with LSMs. To evaluate how much the canopy complexity affects predicted canopy fluxes, we simulated and compared the carbon, water, and solar-induced chlorophyll fluorescence (SIF) fluxes using five different canopy complexity setups from a one-layered canopy to a multi-layered canopy with leaf angular distributions. We modeled the canopy fluxes using the recently developed land model by the Climate Modeling Alliance, CliMA Land. Our model results suggested that (1) when using the same model inputs, model-predicted carbon, water, and SIF fluxes were all higher for simpler canopy setups; (2) when accounting for vertical photosynthetic capacity heterogeneity, differences between canopy complexity levels increased compared to the scenario of a uniform canopy; and (3) SIF fluxes modeled with different canopy complexity levels changed with sun-sensor geometry. Given the different modeled canopy fluxes with different canopy complexities, we recommend (1) not misusing parameters inverted with different canopy complexities or assumptions to avoid biases in model outputs and (2) using a complex canopy model with angular distribution and a hyperspectral radiation transfer scheme when linking land processes to remotely sensed spectra.


Author(s):  
Qiaoyun Fan ◽  
Chunyu Chen ◽  
Gangyi Wang ◽  
Xinguo Wei

2021 ◽  
Author(s):  
Russell Doughty ◽  
Thomas Kurosu ◽  
Nicholas Parazoo ◽  
Philipp Köhler ◽  
Yujie Wang ◽  
...  

Abstract. The retrieval of solar induced chlorophyll fluorescence (SIF) from space is a relatively new advance in Earth observation science, having only become feasible within the last decade. Interest in SIF data has grown exponentially, and the retrieval of SIF and the provision of SIF data products has become an important and formal component of spaceborne Earth observation missions. Here, we describe the global Level 2 SIF Lite data products for the Greenhouse Gases Observing Satellite (GOSAT), the Orbiting Carbon Observatory-2 (OCO-2), and OCO-3 platforms, which are provided for each platform in daily netCDF files. We also outline the methods used to retrieve SIF and estimate uncertainty, describe all the data fields, and provide users the background information necessary for the proper use and interpretation of the data, such as considerations of retrieval noise, sun-sensor geometry, the indirect relationship between SIF and photosynthesis, and differences among the three platforms and their respective data products. OCO-2 and OCO-3 have the highest spatial resolution spaceborne SIF retrievals to date, and the target and snapshot area mode observation modes of OCO-2 and OCO-3 are unique. These modes provide hundreds to thousands of SIF retrievals at biologically diverse global target sites during a single overpass, and provide an opportunity to better inform our understanding of canopy-scale vegetation SIF emission across biomes.


Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6450
Author(s):  
Sharanabasaweshwara Asundi ◽  
Norman Fitz-Coy ◽  
Haniph Latchman

Pico- and nano-satellites, due to their form factor and size, are limited in accommodating multiple or redundant attitude sensors. For such satellites, Murrell’s implementation of the extended Kalman filter (EKF) can be exploited to accommodate multiple sensor configurations from a set of non redundant attitude sensors. The paper describes such an implementation involving a sun sensor suite and a magnetometer as attitude sensors. The implementation exploits Murrell’s EKF to enable three sensor configurations, which can be operationally commanded, for satellite attitude estimation. Among the three attitude estimation schemes, (i) sun sensor suite and magnetometer, (ii) magnetic field vector and its time derivative and (iii) magnetic field vector, it is shown that the third configuration is better suited for attitude estimation in terms of precision and accuracy, but can consume more time to converge than the other two.


2021 ◽  
Vol 118 (3) ◽  
pp. 34-42
Author(s):  
Yerkebulan Nurgizat

Nanosatellite (NS) began to perform complex missions that require high orientation. In this research, we developed a mathematical model of solar sensors to determine the orientation of a NS. Various moments of obtaining the angle of the sun's rays when they hit the solar sensors were presented. The test results of the solar sensors used to simulate various orbit scenarios are described in detail, and graphs of the solar sensor readings are plotted based on the results obtained. The article deals with modeling the motion of a NS in orbit. The NS is equipped with 6 solar panels. The VTS software was used to simulate the motion of the NS. Also, in the study of determining the orientation, two different problems were considered, that is, when the satellite is in the shadow part of the earth and when it is in the solar part of the earth. For these tasks, a mathematical model for determining the orientation was built. This method is very relevant for the study of small spacecraft.


Author(s):  
R. Gomez-Merchan ◽  
M. Lopez-Carmona ◽  
J. A. Lenero-Bardallo ◽  
A. Rodriguez-Vazquez

Author(s):  
R. Gomez-Merchan ◽  
M. Lopez-Carmona ◽  
J. A. Lenero-Bardallo ◽  
A. Rodriguez-Vazquez

2021 ◽  
Author(s):  
Yujie Wang ◽  
Christian Frankenberg

Abstract. Lack of direct carbon, water, and energy flux observations at global scales makes it difficult to calibrate land surface models (LSMs). The increasing number of remote sensing based products provide an alternative way to verify or constrain land models given its global coverage and satisfactory spatial and temporal resolutions. However, these products and LSMs often differ in their assumptions and model setups, for example, the canopy model complexity. The disagreements hamper the fusion of global scale datasets with LSMs. To evaluate how much the canopy complexity affects predicted canopy fluxes, we simulated and compared the carbon, water, and solar-induced chlorophyll fluorescence (SIF) fluxes using five different canopy complexity setups from a one-layered big-leaf canopy to a multi-layered canopy with leaf angular distributions. We modeled the canopy fluxes using a recently developed Land model by the Climate Modeling Alliance. Our model results suggested that (1) when using the same model inputs, model predicted carbon, water, and SIF fluxes were all higher for simpler canopy setups; (2) when accounting for vertical photosynthetic capacity heterogeneity, differences among canopy complexity levels increased compared to the scenario of a uniform canopy; (3) SIF fluxes modeled with different canopy complexity levels changed with sun-sensor geometry. Given the different modeled canopy fluxes with different canopy complexities, we recommend (1) not misusing parameters inverted with different canopy complexities or assumptions to avoid biases in model outputs, and (2) using complex canopy model with angular distribution and hyperspectral radiation transfer scheme when linking land processes to remotely sensed spectra.


Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4905
Author(s):  
Angel Porras-Hermoso ◽  
Daniel Alfonso-Corcuera ◽  
Javier Piqueras ◽  
Elena Roibás-Millán ◽  
Javier Cubas ◽  
...  

This paper presents the development of the UPMSat-2 sun sensor, from the design to on-orbit operation. It also includes the testing of the instrument, one of the most important tasks that needs to be performed to operate a sensor with precision. The UPMSat-2 solar sensor has been designed, tested, and manufactured at the Universidad Politécnica de Madrid (UPM) using 3D printing and COTS (photodiodes). The work described in this paper was carried out by students and teachers of the Master in Space Systems (Máster Universitario en Sistemas Espaciales—MUSE). The solar sensor is composed of six photodiodes that are divided into two sets; each set is held and oriented on the satellite by its corresponding support printed in Delrin. The paper describes the choice of components, the electrical diagram, and the manufacture of the supports. The methodology followed to obtain the response curve of each photodiode is simple and inexpensive, as it requires a limited number of instruments and tools. The selected irradiance source was a set of red LEDs and halogen instead of an AM0 spectrum irradiance simulator. Some early results from the UPMSat-2 mission have been analyzed in the present paper. Data from magnetometers and the attitude control system have been used to validate the data obtained from the sun sensor. The results indicate a good performance of the sensors during flight, in accordance with the data from the ground tests.


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