scholarly journals Lagrange Point Missions: The Key to next Generation Integrated Earth Observations. DSCOVR Innovation

2021 ◽  
Vol 2 ◽  
Author(s):  
Francisco P. J. Valero ◽  
Alexander Marshak ◽  
Patrick Minnis
Keyword(s):  
Temporal Resolution ◽  
Large Scale ◽  
Surface Radiation ◽  
Atmospheric Composition ◽  
Radiation Budget ◽  
High Temporal Resolution ◽  
Polar Regions ◽  
The Moon ◽  
Next Generation ◽  
Lagrange Points

A new perspective for studying Earth processes has been soundly demonstrated by the Deep Space Climate Observatory (DSCOVR) mission. For the past 6 years, the first Earth-observing satellite orbiting at the Lagrange 1 (L1) point, the DSCOVR satellite has been viewing the planet in a fundamentally different way compared to all other satellites. It is providing unique simultaneous observations of nearly the entire sunlit face of the Earth at a relatively high temporal resolution. This capability enables detailed coverage of evolving atmospheric and surface systems over meso- and large-scale domains, both individually and as a whole, from sunrise to sunset, under continuously changing illumination and viewing conditions. DSCOVR’s view also contains polar regions that are only partially seen from geostationary satellites (GEOs). To exploit this unique perspective, DSCOVR instruments provide multispectral imagery and measurements of the Earth’s reflected and emitted radiances from 0.2 to 100 µm. Data from these sensors have been and continue to be utilized for a great variety of research involving retrievals of atmospheric composition, aerosols, clouds, ocean, and vegetation properties; estimates of surface radiation and the top-of-atmosphere radiation budget; and determining exoplanet signatures. DSCOVR’s synoptic and high temporal resolution data encompass the areas observed during the day from low Earth orbiting satellites (LEOs) and GEOs along with occasional views of the Moon. Because the LEO and GEO measurements can be easily matched with simultaneous DSCOVR data, multiangle, multispectral datasets can be developed by integrating DSCOVR, LEO, and GEO data along with surface and airborne observations, when available. Such datasets can open the door for global application of algorithms heretofore limited to specific LEO satellites and development of new scientific tools for Earth sciences. The utility of the integrated datasets relies on accurate intercalibration of the observations, a process that can be facilitated by the DSCOVR views of the Moon, which serves as a stable reference. Because of their full-disc views, observatories at one or more Lagrange points can play a key role in next-generation integrated Earth observing systems.

scholarly journals DSCOVR/EPIC-derived global hourly and daily downward shortwave and photosynthetically active radiation data at 0.1° × 0.1° resolution

2020 ◽  
Vol 12 (3) ◽  
pp. 2209-2221
Author(s):  
Dalei Hao ◽  
Ghassem R. Asrar ◽  
Yelu Zeng ◽  
Qing Zhu ◽  
Jianguang Wen ◽  
...  
Keyword(s):  
Temporal Resolution ◽  
Photosynthetically Active Radiation ◽  
Spatial Scales ◽  
Radiant Energy ◽  
Surface Radiation ◽  
Radiation Budget ◽  
High Temporal Resolution ◽  
Active Radiation ◽  
Global Coverage ◽  
Mean Square Errors

Abstract. Downward shortwave radiation (SW) and photosynthetically active radiation (PAR) play crucial roles in Earth system dynamics. Spaceborne remote sensing techniques provide a unique means for mapping accurate spatiotemporally continuous SW–PAR, globally. However, any individual polar-orbiting or geostationary satellite cannot satisfy the desired high temporal resolution (sub-daily) and global coverage simultaneously, while integrating and fusing multisource data from complementary satellites/sensors is challenging because of co-registration, intercalibration, near real-time data delivery and the effects of discrepancies in orbital geometry. The Earth Polychromatic Imaging Camera (EPIC) on board the Deep Space Climate Observatory (DSCOVR), launched in February 2015, offers an unprecedented possibility to bridge the gap between high temporal resolution and global coverage and characterize the diurnal cycles of SW–PAR globally. In this study, we adopted a suite of well-validated data-driven machine-learning models to generate the first global land products of SW–PAR, from June 2015 to June 2019, based on DSCOVR/EPIC data. The derived products have high temporal resolution (hourly) and medium spatial resolution (0.1∘×0.1∘), and they include estimates of the direct and diffuse components of SW–PAR. We used independently widely distributed ground station data from the Baseline Surface Radiation Network (BSRN), the Surface Radiation Budget Network (SURFRAD), NOAA's Global Monitoring Division and the U.S. Department of Energy's Atmospheric System Research (ASR) program to evaluate the performance of our products, and we further analyzed and compared the spatiotemporal characteristics of the derived products with the benchmarking Clouds and the Earth's Radiant Energy System Synoptic (CERES) data. We found both the hourly and daily products to be consistent with ground-based observations (e.g., hourly and daily total SWs have low biases of −3.96 and −0.71 W m−2 and root-mean-square errors (RMSEs) of 103.50 and 35.40 W m−2, respectively). The developed products capture the complex spatiotemporal patterns well and accurately track substantial diurnal, monthly, and seasonal variations in SW–PAR when compared to CERES data. They provide a reliable and valuable alternative for solar photovoltaic applications worldwide and can be used to improve our understanding of the diurnal and seasonal variabilities of the terrestrial water, carbon and energy fluxes at various spatial scales. The products are freely available at https://doi.org/10.25584/1595069 (Hao et al., 2020).

scholarly journals DSCOVR/EPIC-derived global hourly/daily downward shortwave and photosynthetically active radiation data at 0.1° × 0.1° resolution

2020 ◽  
Author(s):  
Dalei Hao ◽  
Ghassem R. Asrar ◽  
Yelu Zeng ◽  
Qing Zhu ◽  
Jianguang Wen ◽  
...  
Keyword(s):  
Temporal Resolution ◽  
Photosynthetically Active Radiation ◽  
Spatial Scales ◽  
Surface Radiation ◽  
Radiation Budget ◽  
High Temporal Resolution ◽  
Active Radiation ◽  
Global Coverage ◽  
Spatio Temporal ◽  
Mean Square Errors

Abstract. Downward shortwave radiation (SW) and photosynthetically active radiation (PAR) play crucial roles in Earth system dynamics. Spaceborne remote sensing techniques provide a unique means for mapping accurate spatio-temporally-continuous SW/PAR, globally. However, any individual polar-orbiting or geostationary satellite cannot satisfy the desired high temporal resolution (sub-daily) and global coverage simultaneously, while integrating and fusing multi-source data from complementary satellites/sensors is challenging because of co-registration, inter-calibration, near real-time data delivery and the effects of discrepancies in orbital geometry. The Earth Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR), launched in February 2015, offers an unprecedented possibility to bridge the gap between high temporal resolution and global coverage, and characterize the diurnal cycles of SW/PAR globally. In this study, we adopted a suite of well-validated data-driven machine-learning models to generate the first global land products of SW/PAR, from June 2015 to June 2019, based on DSCOVR/EPIC data. The derived products have high temporal resolution (hourly) and medium spatial resolution (0.1° × 0.1°), and include estimates of the direct and diffuse components of SW/PAR. We used independently widely-distributed ground station data from the Baseline Surface Radiation Network (BSRN), the Surface Radiation Budget Network (SURFRAD), NOAA's Global Monitoring Division and the U.S. Department of Energy’s Atmospheric System Research (ASR) program to evaluate the performance of our products, and further analyzed and compared the spatio-temporal characteristics of the derived products with the benchmarking Clouds and the Earth's Radiant Energy System Synoptic (CERES) data. We found both the hourly and daily products to be consistent with ground-based observations (e.g., hourly and daily total SWs have low biases of −3.96 and −0.71 W/m2 and root mean square errors (RMSEs) of 103.50 and 35.40 W/m2, respectively). The developed products capture the complex spatio-temporal patterns well and accurately track substantial diurnal, monthly, and seasonal variations of SW/PAR when compared to CERES data. They provide a reliable and valuable alternative for solar photovoltaic applications worldwide and can be used to improve our understanding of the diurnal and seasonal variabilities of the terrestrial water, carbon and energy fluxes at various spatial scales. The products are freely available at https://doi.org/10.25584/1595069 (Hao et al., 2020).

scholarly journals Spatial and Temporal Sampling of Polar Regions from Two-Satellite System on Molniya Orbit

2011 ◽  
Vol 28 (8) ◽  
pp. 977-992 ◽  
Author(s):  
Alexander P. Trishchenko ◽  
Louis Garand
Keyword(s):  
Temporal Resolution ◽  
Arctic Region ◽  
Satellite System ◽  
Elliptical Orbit ◽  
High Temporal Resolution ◽  
Polar Regions ◽  
Temporal Sampling ◽  
Continuous Coverage ◽  
Depth Analysis

Abstract There has been a significant increase of interest in the building of a comprehensive Arctic observing system in recent years to properly and timely track the environmental and climate processes in this vast region. In this regard, a satellite observing system on highly elliptical orbit (HEO) with 12-h period (Molniya type) is of particular interest, because it enables continuous coverage of the entire Arctic region (58°–90°N) from a constellation of two satellites. Canada is currently proposing to operate such a constellation by 2017. Extending the pioneering study of S. Q. Kidder and T. H. Vonder Haar, this paper presents in-depth analysis of spatiotemporal sampling properties of the imagery from this system. This paper also discusses challenges and advantages of this orbit for various applications that require high temporal resolution and angular sampling.

Large-scale Arctic sea ice motion from Sentinel-1 and the RADARSAT Constellation Mission

2021 ◽  
Author(s):  
Stephen Howell ◽  
Mike Brady ◽  
Alexander Komarov
Keyword(s):  
Sea Ice ◽  
Spatial Resolution ◽  
Temporal Resolution ◽  
Large Scale ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
High Temporal Resolution ◽  
Sar Images ◽  
Sea Ice Extent ◽  
Arctic Sea

<p>As the Arctic’s sea ice extent continues to decline, remote sensing observations are becoming even more vital for the monitoring and understanding of this process.  Recently, the sea ice community has entered a new era of synthetic aperture radar (SAR) satellites operating at C-band with the launch of Sentinel-1A in 2014, Sentinel-1B in 2016 and the RADARSAT Constellation Mission (RCM) in 2019. These missions represent a collection of 5 spaceborne SAR sensors that together can routinely cover Arctic sea ice with a high spatial resolution (20-90 m) but also with a high temporal resolution (1-7 days) typically associated with passive microwave sensors. Here, we used ~28,000 SAR image pairs from Sentinel-1AB together with ~15,000 SAR images pairs from RCM to generate high spatiotemporal large-scale sea ice motion products across the pan-Arctic domain for 2020. The combined Sentinel-1AB and RCM sea ice motion product provides almost complete 7-day coverage over the entire pan-Arctic domain that also includes the pole-hole. Compared to the National Snow and Ice Data Center (NSIDC) Polar Pathfinder and Ocean and Sea Ice-Satellite Application Facility (OSI-SAF) sea ice motion products, ice speed was found to be faster with the Senintel-1AB and RCM product which is attributed to the higher spatial resolution of SAR imagery. More sea ice motion vectors were detected from the Sentinel-1AB and RCM product in during the summer months and within the narrow channels and inlets compared to the NSIDC Polar Pathfinder and OSI-SAF sea ice motion products. Overall, our results demonstrate that sea ice geophysical variables across the pan-Arctic domain can now be retrieved from multi-sensor SAR images at both high spatial and temporal resolution.</p>

A Technique for the Measurement of Wall Shear Stress Based on Micro Fabricated Hot-Film Sensor

2013 ◽  
Author(s):  
Takuya Sawada ◽  
Osamu Terashima ◽  
Yasuhiko Sakai ◽  
Kouji Nagata ◽  
Mitsuhiro Shikida ◽  
...  
Keyword(s):  
Shear Stress ◽  
Wall Shear Stress ◽  
Turbulent Flows ◽  
Temporal Resolution ◽  
Large Scale ◽  
High Temporal Resolution ◽  
Film Sensor ◽  
Wall Shear ◽  
Hot Film ◽  
Hot Film Sensor

The objective of this study is to establish a technique for accurately measuring the wall shear stress in turbulent flows using a micro-fabricated hot-film sensor. Previously, we developed a hot-film sensor with a flexible polyimide-film substrate. This sensor can be attached to curved walls and be used in various situations. Furthermore, the sensor has a 20-μm-wide, heated thin metal film. However, the temporal resolution of this hot-film sensor is not very high owing to its substrate’s high heat capacity. Consequently, its performance is inadequate for measuring the wall shear stress “fluctuations” in turbulent flows. Therefore, we have developed another type of hot-film sensor in which the substrate is replaced with silicon, and a cavity has been introduced under the hot-film for reducing heat loss from the sensor and achieving high temporal resolution. Furthermore, for improving the sensor’s spatial resolution, the width of the hot-film is decreased to 10 μm. The structure of the hot-film’s pattern and the flow-detection mechanism are similar to those of the previous sensor. Experimental results show that new hot-film sensor works as expected and has better temporal resolution than the previous hot-film sensor. As future work, we will measure the wall shear stress for a turbulent wall-jet and discuss the relationship between a large-scale coherent vortex structure and wall shear stress based on data obtained using the new hot-film sensor.

scholarly journals Ultrasound functional neuroimaging reveals propagation of task-related brain activity in behaving primates

2018 ◽  
Author(s):  
Alexandre Dizeux ◽  
Marc Gesnik ◽  
Harry Ahnine ◽  
Kevin Blaize ◽  
Fabrice Arcizet ◽  
...  
Keyword(s):  
Temporal Resolution ◽  
Large Scale ◽  
Functional Neuroimaging ◽  
Anterior Cingulate ◽  
Global Network ◽  
High Temporal Resolution ◽  
Wide Field ◽  
Spatiotemporal Resolution ◽  
Macro Scale ◽  
The Brain

ABSTRACTIn recent decades, neuroimaging has played an invaluable role in improving the fundamental understanding of the brain. At the macro scale, neuroimaging modalities such as MRI, EEG, and MEG, exploit a wide field of view to explore the brain as a global network of interacting regions. However, this comes at the price of either limited spatiotemporal resolution or limited sensitivity. At the micro scale, electrophysiology is used to explore the dynamic aspects of neuronal activity with a very high temporal resolution. However, this modality requires a statistical averaging of several tens of single task responses. A large-scale neuroimaging modality of sufficient spatial and temporal resolution and sensitivity to study brain region activation dynamically would open new territories of possibility in neuroscienceWe show that neurofunctional ultrasound imaging (fUS) is both able to assess brain activation during single cognitive tasks within superficial and deeper areas of the frontal cortex areas, and image the directional propagation of information within and between these regions. Equipped with an fUS device, two macaque rhesus monkeys were instructed before a stimulus appeared to rest (fixation) or to look towards (saccade) or away (antisaccade) from a stimulus. Our results identified an abrupt transient change in activity for all acquisitions in the supplementary eye field (SEF) when the animals were required to change a rule regarding the task cued by a stimulus. Simultaneous imaging in the anterior cingulate cortex and SEF revealed a time delay in the directional functional connectivity of 0.27 ± 0.07 s and 0.9 ± 0.2 s for animals S and Y, respectively. These results provide initial evidence that recording cerebral hemodynamics over large brain areas at a high spatiotemporal resolution and sensitivity with neurofunctional ultrasound can reveal instantaneous monitoring of endogenous brain signals and behavior.

Secondary Volcanically-Induced Lunar Atmosphere and Lunar Volatiles: 3-D Modeling and Analysis

2020 ◽  
Author(s):  
Igor Aleinov ◽  
Michael Way ◽  
Kostas Tsigaridis ◽  
Eric Wolf ◽  
Chester Harman ◽  
...  
Keyword(s):  
General Circulation ◽  
Circulation Model ◽  
Atmospheric Temperature ◽  
Atmospheric Composition ◽  
Polar Regions ◽  
The Moon ◽  
Modeling And Analysis ◽  
Orbital Parameters ◽  
Atmospheric Escape ◽  
Major Eruption

<p>The fact that the Moon could have a transient secondary atmosphere due to volcanic outgassing has been known for some time, though typically such an atmosphere was believed to be extremely thin (~10<sup>-8</sup> bar) [1]. But recent research by Needham and Kring (NK) [2] suggests that during the peak of volcanic activity ~3.5 Ga such a volcanically-outgassed atmosphere could reach ~10<sup>-2</sup> bar of surface pressure. In similar research Wilson et al. [3] proposed a more conservative estimate, arguing that the thickness of such an atmosphere would depend on the intervals between major eruptions and may not exceed microbar densities. In either case a collisional atmosphere could be present, which would control transport of outgassed volatiles (such as H<sub>2</sub>O) and their deposition in polar regions, where they could be preserved until modern day frozen in permanently shadowed regions (PSR) or buried beneath the regolith.</p><p>Here we study such a hypothetical atmosphere to investigate its stability, meteorological properties and the effect on transport of volatiles. We use the ROCKE-3D planetary 3-D General Circulation Model (GCM)[4]. The insolation and orbital parameters were set to conditions 3.5 Ga. The atmospheric composition, based on the list of outgassed species presented by NK in combination with our estimates for atmospheric escape, condensation and the results from our 1-D chemistry model, was chosen to be either CO-dominated or CO<sub>2</sub>-dominated (depending on atmospheric temperature). In this study we restricted ourselves to relatively "thick" lunar atmospheres of 1-10 mb, though we believe that our results will scale to thinner atmospheres as well.</p><p>We present the results for ground and atmospheric temperature for modeled atmospheres over a wide parameter space. In particular we consider  different atmospheric compositions (CO or CO<sub>2</sub> dominated), a set of atmospheric pressures from 1 mb to 10 mb and a set of obliquities from 0<sup>o</sup> to 40<sup>o</sup>. We also present an experiment of a single major eruption [5] and show that in just 3 years ~80% of the outgassed water is deposited in polar regions. This demonstrates the efficiency of such an atmosphere in delivering volatiles. We argue that a secondary lunar atmosphere could play a significant role in forming volatile deposits currently observed in the polar regions of the Moon. </p><p>References:<br>[1] Stern S. A. (1999) Rev. of Geophysics, 37, 453-492.<br>[2] Needham D. H. and Kring D. A. (2017) Earth and Planetary Sci. Lett., 478, 175-178.<br>[3] Wilson L. et al. (2019) LPSC 50, Abstract 1343. <br>[4] Way M. J. et al. (2017) ApJS, 231, 12.<br>[5] Wilson L. and Head J. W. (2018) GRL, 45, 5852-5859.</p><p> </p>

scholarly journals Analysis of Long-Term Moon-Based Observation Characteristics for Arctic and Antarctic

2019 ◽  
Vol 11 (23) ◽  
pp. 2805 ◽  
Author(s):  
Yue Sui ◽  
Huadong Guo ◽  
Guang Liu ◽  
Yuanzhen Ren
Keyword(s):  
Global Climate Change ◽  
Large Scale ◽  
Global Climate ◽  
Earth Observation ◽  
Polar Regions ◽  
The Moon ◽  
The North ◽  
The Earth ◽  
The Antarctic

The Antarctic and Arctic have always been critical areas of earth science research and are sensitive to global climate change. Global climate change exhibits diversity characteristics on both temporal and spatial scales. Since the Moon-based earth observation platform could provide large-scale, multi-angle, and long-term measurements complementary to the satellite-based Earth observation data, it is necessary to study the observation characteristics of this new platform. With deepening understanding of Moon-based observations, we have seen its good observation ability in the middle and low latitudes of the Earth’s surface, but for polar regions, we need to further study the observation characteristics of this platform. Based on the above objectives, we used the Moon-based Earth observation geometric model to quantify the geometric relationship between the Sun, Moon, and Earth. Assuming the sensor is at the center of the nearside of the Moon, the coverage characteristics of the earth feature points are counted. The observation intervals, access frequency, and the angle information of each point during 100 years were obtained, and the variation rule was analyzed. The research showed that the lunar platform could carry out ideal observations for the polar regions. For the North and South poles, a continuous observation duration of 14.5 days could be obtained, and as the latitude decreased, the duration time was reduced to less than one day at the latitude of 65° in each hemisphere. The dominant observation time of the North Pole is concentrated from mid-March to mid-September, and for the South Pole, it is the rest of the year, and as the latitude decreases, it extends outward from both sides. The annual coverage time and frequency will change with the relationship between the Moon and the Earth. This study also proves that the Moon-based observation has multi-angle observation advantages for the Arctic and the Antarctic areas, which can help better understand large-scale geoscientific phenomena. The above findings indicate that the Moon-based observation can be applied as a new type of remote sensing technology to the observation field of the Earth’s polar regions.

scholarly journals Retrieving high-resolution surface solar radiation with cloud parameters derived by combining MODIS and MTSAT data

2016 ◽  
Vol 16 (4) ◽  
pp. 2543-2557 ◽  
Author(s):  
Wenjun Tang ◽  
Jun Qin ◽  
Kun Yang ◽  
Shaomin Liu ◽  
Ning Lu ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Temporal Resolution ◽  
Surface Radiation ◽  
Mean Bias Error ◽  
Haihe River Basin ◽  
High Temporal Resolution ◽  
Spatiotemporal Resolution ◽  
Surface Solar Radiation ◽  
Radiation Data ◽  
Cloud Parameters

Abstract. Cloud parameters (cloud mask, effective particle radius, and liquid/ice water path) are the important inputs in estimating surface solar radiation (SSR). These parameters can be derived from MODIS with high accuracy, but their temporal resolution is too low to obtain high-temporal-resolution SSR retrievals. In order to obtain hourly cloud parameters, an artificial neural network (ANN) is applied in this study to directly construct a functional relationship between MODIS cloud products and Multifunctional Transport Satellite (MTSAT) geostationary satellite signals. In addition, an efficient parameterization model for SSR retrieval is introduced and, when driven with MODIS atmospheric and land products, its root mean square error (RMSE) is about 100 W m−2 for 44 Baseline Surface Radiation Network (BSRN) stations. Once the estimated cloud parameters and other information (such as aerosol, precipitable water, ozone) are input to the model, we can derive SSR at high spatiotemporal resolution. The retrieved SSR is first evaluated against hourly radiation data at three experimental stations in the Haihe River basin of China. The mean bias error (MBE) and RMSE in hourly SSR estimate are 12.0 W m−2 (or 3.5 %) and 98.5 W m−2 (or 28.9 %), respectively. The retrieved SSR is also evaluated against daily radiation data at 90 China Meteorological Administration (CMA) stations. The MBEs are 9.8 W m−2 (or 5.4 %); the RMSEs in daily and monthly mean SSR estimates are 34.2 W m−2 (or 19.1 %) and 22.1 W m−2 (or 12.3 %), respectively. The accuracy is comparable to or even higher than two other radiation products (GLASS and ISCCP-FD), and the present method is more computationally efficient and can produce hourly SSR data at a spatial resolution of 5 km.

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