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In this study, we compare the CERES SYN1deg surface radiative fluxes to those measured during the MOSAiC icebreaker ship expedition in the Arctic.
The Arctic is one of the most sensitive regions of Earth to climate change, and yet remains one of the more difficult regions to both observe and simulate. The high latitude of the Arctic gives it some unusual features compared with much of Earth, such as large and variable sea ice cover, extensive mixed phase cloud cover, and the polar day/night cycle. These features significantly influence the radiative environment of the Arctic as well as the ability to observe it. The remoteness of the Arctic from most of civilization makes large volumes of in situ observations difficult to collect, and so satellite observations are a critical tool for observing the region, such as those from Clouds and the Earth’s Radiant Energy System (CERES). But validating the satellite radiative flux estimates is difficult because of the lack of in situ measurements. A useful remedy is utilizing measurements from field campaigns, such as the year-long Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition during 2019-2020. The extensive high-quality surface radiative flux and meteorological measurements collected from MOSAiC provide a useful check on flux retrievals from CERES instruments. Previous work compared MOSAiC and CERES surface radiative fluxes during the 2020 melt season (April-September). Errors in CERES fluxes were related to errors in estimated atmospheric optical depth and surface albedo. We conduct a similar assessment of CERES surface flux retrievals using MOSAiC data, but for the months of October through March instead. As this time period is mostly during polar night and twilight, the focus of the study is on longwave surface fluxes. To better understand the reasons for errors in CERES fluxes, we use the large set of meteorological measurements also collected by MOSAiC, including surface temperature, thermodynamic vertical profiles, surface turbulent fluxes, and cloud properties. For example, one notable possible source of error in the CERES estimate of surface downwelling longwave flux is the estimate of cloud base height when compared with MOSAiC W-band radar measurements – an overestimate of cloud base height yields an underestimate of the downwelling flux on the order of tens of W m2.
The Arctic is one of the most sensitive regions of Earth to climate change, and yet remains one of the more difficult regions to both observe and simulate. The remoteness of the Arctic from most of civilization makes large volumes of in situ observations difficult to collect, and so satellite observations are a critical tool for observing the region, such as those from Clouds and the Earth’s Radiant Energy System (CERES). But validating the satellite radiative flux estimates is difficult because of the lack of in situ measurements. A useful remedy is utilizing measurements from field campaigns, such as the year-long Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition during 2019-2020. The extensive high-quality surface radiative flux and meteorological measurements collected from MOSAiC provide a useful check on flux retrievals from CERES instruments. We compare MOSAiC and CERES surface radiative fluxes during October through March of 2019-2020. As this time period is mostly during polar night and twilight, the focus of the study is on longwave surface fluxes. To better understand the reasons for errors in CERES fluxes, we use the large set of meteorological measurements also collected by MOSAiC, including surface temperature, thermodynamic vertical profiles, surface turbulent fluxes, and cloud properties. Previous work identified a significant source of error in the CERES estimate of surface downwelling longwave flux as the estimate of low level cloud amount when compared with MOSAiC W-band radar measurements. An overestimate of low cloud amount yielded an underestimate of the downwelling flux on the order of tens of W m2. Continuing this work, we test other meteorological properties such as the vertical thermodynamic profile and surface turbulent fluxes. In addition, we examine different estimates of surface fluxes derived from CERES measurements. Previous work used the SYN1deg product, which had the limitation of having a 1º x 1 º horizontal resolution. A newer product estimates the surface fluxes at the CERES footprint resolution, which allows a more precise colocation, and thus a representative flux estimate, with the MOSAiC site.
Observing the Arctic from space is one of the most challenging tasks in climate science. Uncertainty in the NASA Clouds and the Earth’s Radiant Energy System (CERES)-derived irradiances is larger over sea ice than any other scene type and comes from several sources. The one-year long MOSAiC expedition in the central Arctic provides a rare opportunity to explore uncertainty in CERES-derived radiative fluxes. First, a systematic and statistically robust assessment of surface shortwave and longwave fluxes has been conducted using in-situ measurements from MOSAiC flux stations. The CERES SYN1deg product overestimates the SW_down flux by 11.40 Wm-2 and underestimates the SW_up flux by −15.70 Wm-2 and LW_down fluxes by −13.30 Wm-2 at the surface during summertime. In addition, large differences are found in the LW_up flux (~320 Wm-2) when the surface reaches melting point (~0℃). The large negative bias in upwelling shortwave flux can be attributed to the underestimation of surface albedo (−0.15) in SYN1deg. In addition to direct comparison, a series of perturbation experiments with a radiative transfer model are performed to estimate the contributions to the differences. By correcting both cloud and albedo inputs, the biases in SW_net flux and LW_net flux can be reduced to less than half of the control run biases to +19.90% and −10.53%, respectively. Furthermore, a compensating effect between underestimation of broadband albedo and overestimation of spectral albedo in visible and mid-infrared bands in SYN1deg datasets is found and contributes to the shortwave flux differences. The difference in CERES broadband albedo (~20 Wm 2) contributes to larger uncertainty in SW_up flux than spectral albedo shape (~3 Wm 2). The results of this study inform the future development of CERES products and will ultimately reduce uncertainties in Arctic surface radiation budget derived from satellite measurements.
The Arctic remains one of the more difficult regions observe, and so satellite observations are a critical tool for observing the region, such as those from Clouds and the Earth’s Radiant Energy System (CERES). But validating the satellite surface radiative flux estimates is difficult because of the lack of in situ measurements. The extensive high-quality surface radiative flux and meteorological measurements collected from MOSAiC provide a useful check on flux retrievals from CERES instruments. We compare MOSAiC and CERES surface radiative fluxes during October through March of 2019-2020 using the large set of meteorological measurements also collected by MOSAiC, specifically cloud properties. Previous work identified a significant source of error in the CERES estimate of surface downwelling longwave flux as the estimate of low level cloud amount when compared with MOSAiC W-band radar measurements. Continuing this work, we examine the effects of errors in cloud water path on surface radiative fluxes. When using all cloud conditions, errors in cloud water are also significantly correlated with surface radiative flux errors, though the size off the effect is only about half that of cloud amount. But when considering low cloud conditions only, the effects of cloud water and cloud amount are comparable.
The Arctic remains one of the more difficult regions observe, and so satellite observations are a critical tool for observing the region, such as those from Clouds and the Earth’s Radiant Energy System (CERES). But validating the satellite surface radiative flux estimates is difficult because of the lack of in situ measurements. The extensive high-quality surface radiative flux and meteorological measurements collected from MOSAiC provide a useful check on flux retrievals from CERES instruments. We compare MOSAiC and CERES surface radiative fluxes during October through March of 2019-2020 using the large set of meteorological measurements also collected by MOSAiC, specifically cloud properties. Previous work identified a significant source of error in the CERES estimate of surface downwelling longwave flux as the estimate of low level cloud amount when compared with MOSAiC W-band radar measurements. Continuing this work, we examine the effects of errors in cloud water path on surface radiative fluxes. When using all cloud conditions, errors in cloud water are also significantly correlated with surface radiative flux errors, though the size off the effect is only about half that of cloud amount. But when considering low cloud conditions only, the effects of cloud water and cloud amount are comparable. We compare MOSAiC and CERES surface radiative fluxes during October through March of 2019-2020 using the large set of meteorological measurements also collected by MOSAiC, specifically cloud properties. Previous work identified a significant source of error in the CERES estimate of surface downwelling longwave flux as the estimate of low level cloud amount when compared with MOSAiC W-band radar measurements. We further examine this source of error by examining selected case studies in which the disagreements in radiative fluxes and clouds are large.
Primitive bodies (asteroids and comets), which have remained relatively unaltered since their formation, are important targets for scientific missions that seek to understand the evolution of the solar system. Often the first step is to fly by these bodies with robotic spacecraft. The key to maximizing data returns from these flybys is to determine the spacecraft trajectory relative to the target body-in short, navigate the spacecraft- with sufficient accuracy so that the target is guaranteed to be in the instruments' field of view. The most powerful navigation data in these scenarios are images taken by the spacecraft of the target against a known star field (onboard astrometry). Traditionally, the relative trajectory of the spacecraft must be estimated hours to days in advance using images collected by the spacecraft. This is because of (1)!the long round-trip light times between the spacecraft and the Earth and (2)!the time needed to downlink and process navigation data on the ground, make decisions based on the result, and build and uplink instrument pointing sequences from the results. The light time and processing time compromise navigation accuracy considerably, because there is not enough time to use more accurate data collected closer to the target-such data are more accurate because the angular capability of the onboard astrometry is essentially constant as the distance to the target decreases, resulting in better "plane-of- sky" knowledge of the target. Excellent examples of these timing limitations are high-speed comet encounters. Comets are difficult to observe up close; their orbits often limit scientists to brief, rapid flybys, and their coma further restricts viewers from seeing the nucleus in any detail, unless they can view the nucleus at close range. Comet nuclei details are typically discernable for much shorter durations than the roundtrip light time to Earth, so robotic spacecraft must be able to perform onboard navigation. This onboard navigation can be accomplished through a self- contained system that by eliminating light time restrictions dramatically improves the relative trajectory knowledge and control and subsequently increases the amount of quality data collected. Flybys are one-time events, so the system's underlying algorithms and software must be extremely robust. The autonomous software must also be able to cope with the unknown size, shape, and orientation of the previously unseen comet nucleus. Furthermore, algorithms must be reliable in the presence of imperfections and/or damage to onboard cameras accrued after many years of deep-space operations. The AutoNav operational flight software packages, developed by scientists at the Jet Propulsion Laboratory (JPL) under contract with NASA, meet all these requirements. They have been directly responsible for the successful encounters on all of NASA's close-up comet-imaging missions (see Figure !1). AutoNav is the only system to date that has autonomously tracked comet nuclei during encounters and performed autonomous interplanetary navigation. AutoNav has enabled five cometary flyby missions (Table!1) residing on four NASA spacecraft provided by three different spacecraft builders. Using this software, missions were able to process a combined total of nearly 1000 images previously unseen by humans. By eliminating the need to navigate spacecraft from Earth, the accuracy gained by AutoNav during flybys compared to ground-based navigation is about 1!order of magnitude in targeting and 2!orders of magnitude in time of flight. These benefits ensure that pointing errors do not compromise data gathered during flybys. In addition, these benefits can be applied to flybys of other solar system objects, flybys at much slower relative velocities, mosaic imaging campaigns, and other proximity activities (e.g., orbiting, hovering, and descent/ascent).
The Radarsat Antarctic Mapping Project is a collaboration between NASA and the Canadian Space Agency to map Antarctica using synthetic aperture radar (SAR). The first Antarctic Mapping Mission (AMM-1) was successfully completed in October 1997. Data from the acquisition phase of the 1997 campaign have been used to achieve the primary goal of producing the first, high-resolution SAR image map of Antarctica. The limited amount of data suitable for interferometric analysis have also been used to produce remarkably detailed maps of surface velocity for a few selected regions. Most importantly, the results from AMM-1 are now available to the general science community in the form of various resolution, radiometrically calibrated and geometrically accurate image mosaics. The second Antarctic imaging campaign occurred during the fall of 2000. Modified from AMM-1, the satellite remained in north looking mode during AMM-2 restricting coverage to regions north of about -80 degrees latitude. But AMM-2 utilized for the first time RADARSAT-1 fine beams providing an unprecedented opportunity to image many of Antarctica's fast glaciers whose extent was revealed through AMM-1 data. AMM-2 also captured extensive data suitable for interferometric analysis of the surface velocity field. This report summarizes the science goals, mission objectives, and project status through the acquisition phase and the start of the processing phase. The reports describes the efforts of team members including Alaska SAR Facility, Jet Propulsion Laboratory, Vexcel Corporation, Goddard Space Flight Center, Wallops Flight Facility, Ohio State University, Environmental Research Institute of Michigan, White Sands Facility, Canadian Space Agency Mission Planning and Operations Groups, and the Antarctic Mapping Planning Group.
While polar orbiting satellites are essential in providing the needed observations over polar regions for data assimilation, weather diagnoses/forecasting, and flight guidance and situation awareness in airborne field campaigns, there is limited temporal coverage. Often, polar mosaics are created by overlaying multiple satellite imagers on top of each other which can lead to transition lines and discontinuities in the data products. To help ease some of these shortcomings, we utilize the NASA Langley Satellite ClOud and Radiation Property retrieval System (SatCORPS) Mosaic algorithm for optimally fusing and merging selected imager radiances from the Visible Infrared Imaging Radiometer Suite (VIIRS) instrument onboard the Suomi National polar-orbiting Partnership (SNPP), Joint Polar Satellite System (JPSS-1), and JPSS-2 satellites, and the MODerate resolution Imaging Spectroradiometer (MODIS) instruments onboard AQUA and TERRA satellites. Since multiple satellites overpasses and instruments are used in creating hourly 3-km composites over the polar regions, selection of the best satellite data for each 3-km composite pixel is based on aggregated ranking of satellite resolution, time, viewing zenith angle, and distance from terminator. This ranking system provides a smoother transition and improves data discontinuity in the merged output resulting in a more seamless polar region dataset. We will discuss the use of this near real-time dataset to support polar airborne field campaigns and SatCORPS satellite-derived Global Cloud Composite (GCC) generation.
The objective of the Dawn topography investigation is to derive the detailed shapes of 4 Vesta and 1 Ceres in order to create orthorectified image mosaics for geologic interpretation, as well as to study the asteroids' landforms, interior structure, and the processes that have modified their surfaces over geologic time. In this paper we describe our approaches for producing shape models, plans for acquiring the needed image data for Vesta, and the results of a numerical simulation of the Vesta mapping campaign that quantify the expected accuracy of our results. Multi-angle images obtained by Dawn's framing camera will be used to create topographic models with 100 m/pixel horizontal resolution and 10 m height accuracy at Vesta, and 200 m/pixel horizontal resolution and 20 m height accuracy at Ceres. Two different techniques, stereophotogrammetry and stereophotoclinometry, are employed to model the shape; these models will be merged with the asteroidal gravity fields obtained by Dawn to produce geodetically controlled topographic models for each body. The resulting digital topography models, together with the gravity data, will reveal the tectonic, volcanic and impact history of Vesta, and enable co-registration of data sets to determine Vesta's geologic history. At Ceres, the topography will likely reveal much about processes of surface modification as well as the internal structure and evolution of this dwarf planet.
The SOHO on-line catalogs will contain information about the observations from several made or planned campaigns, that must be available to scientists who wish to use SOHO data. The World Wide Web (WWW) was chosen as the interface to the SOHO on-line catalogs, because it is easy to use, well suited to a geographically distributed user community, and freely available. Through the use of a forms-capable WWW client such as Mosaic or Lynx, a scientist will be able to browse through the catalogs of observations in a very simple, self explanatory way. Data files can then be selected from the returned lists for either immediate transferring or sending on tape by mail, with appropriate checks for whether data is in the public domain or not.
The NASA Langley Satellite ClOud and Radiation Property retrieval System (SatCORPS) team provides low latency LEO and GEO satellite derived cloud and radiation products to end users for use in near real-time (NRT) applications. Hourly mosaics are fused from LEO (SNPP, JPSS-1, AQUA, MODIS) and GEO Satellite imagers (GOES-West, GOES-East, Metesat-11, Metesat-8, and Himawari-8) to create global cloud composites (GCC). SatCORPS GCC data are integrated into Esri ArcGIS system and transformed into Analysis Rady Data (ARD) to provide more efficient data access to support disaster management, weather diagnoses/forecasting, and Earth Sciences remote sensing applications. GCC data are exposed as RESTful APIs, ArcGIS Image Services, and Open Geospatial Consortium (OGC) Web Mapping Services/Web Coverage Services to provide a variety of end points for integration into user applications. We will preview the new interactive SatCORPS GCC web visualization tool and discuss initial integration of GCC product into NASA Airborne Mission Tool Suite (MTS) to support NASA and NOAA field campaigns.
During the period of performance, we have obtained the following observations and carried out the analysis of the Orion associations itemized below. Optical Photometry: The Quest camera that had been damaged by lightning on Sept. 2001 was reconfigured to use 10 chips and only 3 filters instead of the original 4 but retaining its spatial coverage of 2.3deg wide in declination. During the Winter and Fall 2002 observing campaigns, we obtained multifilter photometry using the Quest camera on the 1mt Schmidt of the Venezuelan National Observatory, to continue the survey of the Orion clouds. In the Winter 2002 season, we obtained photometry for 10 scans at DEC=+5, 7 scans at DEC=-5. Several additional scans at DEC=-3 were obtained during the Fall 2002 observing campaign. Slit spectroscopy of bright candidates: During 2002 spectra for some 235 candidate PMS stars were obtained with the FAST spectrograph at the SAO 1.5m telescope in Mt. Hopkins. These objects, all brighter than V=16, are located in two strips centered at DEC=+l and -5, and spanning from RA=5h-6h. The spectra are being analyzed. Multifiber spectroscopy: Spectroscopy for our fainter (V less than or equal to 16) candidates has not kept pace with our spectroscopy of brighter candidates, because of the delay in the commissioning of the Hectospec and Hectoechelle multi-object spectrographs at the new 6.5m MMT. We obtained some data with the Hydra spectrograph on the WIYN telescope: Feb 1-4, 2002. Time granted to the project: "A Large Scale Survey of the Low-Mass Young Population in the Orion OB1 Association" (P.I.: C. Briceno). Three half-nights (we used the first half of the night, the second half of the night was used with the Mini-Mosaic imager by another team). Only the first half night was clear. We observed 3 fields centered in a 2.3 deg wide strip centered at DEC=-1 and spanning RA=Sh to 6h. A total of 250 spectra were obtained for the same number of candidate PMS stars. Nov. 13-15, 2002. Time granted to the project "Cluster survey of protoplanetary disk evolution", (P.I.: A. Sicilia-Aguilar). Clear weather throughout. We obtained spectra for some 200 candidate PMS stars in 3 fields located in a 2.3 deg wide strip centered at DEC=+l and spanning from RA=5h20m to 5h35m. Data for both observing runs is partially reduced and is being analyzed. U photometry: During Nov.29-Dec.4, 2002 we were granted time with the 4-shooter CCD Mosaic Camera at the SAO 1.2m telescope, to obtain U-band photometry of a subset of the newly identified T Tauri stars in the strip centered at DEC=-1. This sample is composed of strong H(alpha) emitting PMS stars (Classical T Tauri stars) located mostly in the Orion OB lb association, around the Orion Belt area. Our data will be combined with our calibration of the U-band excess (Gullbring et al. 1998) to derive mass accretion rates. Because of bad weather we observed only 20 stars during 1.5 clear nights. Near IR photometry: During Dec. 14-19, 2002 we used the IR Camera on the SAO 1.2m telescope, to obtain L-band photometry of a set of 17 the newly identified Orion OB 1a and 1b stars, in order to look for IR excess emission coming from the hotter inner parts of circumstellar disks. Again, mediocre weather prevented a larger set to be observed. These stars were also observed with the OSCIR mid-IR camera on Gemini North during later 2001. Our goal is to construct SEDs from the visual out to the mid-IR (by combining our optical/IR data with 2MASS JHK magnitudes) in order to explore disk dissipation at the critical ages of 5-10 Myr spanned by these stars.