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Satellite Ocean Color Sensor Design Concepts and Performance Requirements

In late 1978, the National Aeronautics and Space Administration (NASA) launched the Nimbus-7 satellite with the Coastal Zone Color Scanner (CZCS) and several other sensors, all of which provided major advances in Earth remote sensing. The inspiration for the CZCS is usually attributed to an article in Science by Clarke et al. who demonstrated that large changes in open ocean spectral reflectance are correlated to chlorophyll-a concentrations. Chlorophyll-a is the primary photosynthetic pigment in green plants (marine and terrestrial) and is used in estimating primary production, i.e., the amount of carbon fixed into organic matter during photosynthesis. Thus, accurate estimates of global and regional primary production are key to studies of the earth's carbon cycle. Because the investigators used an airborne radiometer, they were able to demonstrate the increased radiance contribution of the atmosphere with altitude that would be a major issue for spaceborne measurements. Since 1978, there has been much progress in satellite ocean color remote sensing such that the technique is well established and is used for climate change science and routine operational environmental monitoring. Also, the science objectives and accompanying methodologies have expanded and evolved through a succession of global missions, e.g., the Ocean Color and Temperature Sensor (OCTS), the Seaviewing Wide Field-of-view Sensor (SeaWiFS), the Moderate Resolution Imaging Spectroradiometer (MODIS), the Medium Resolution Imaging Spectrometer (MERIS), and the Global Imager (GLI). With each advance in science objectives, new and more stringent requirements for sensor capabilities (e.g., spectral coverage) and performance (e.g., signal-to-noise ratio, SNR) are established. The CZCS had four bands for chlorophyll and aerosol corrections. The Ocean Color Imager (OCI) recommended for the NASA Pre-Aerosol, Cloud, and Ocean Ecosystems (PACE) mission includes 5 nanometers hyperspectral coverage from 350 to 800 nanometers with three additional discrete near infrared (NIR) and shortwave infrared (SWIR) ocean aerosol correction bands. Also, to avoid drift in sensor sensitivity from being interpreted as environmental change, climate change research requires rigorous monitoring of sensor stability. For SeaWiFS, monthly lunar imaging accurately tracked stability at an accuracy of approximately 0.1% that allowed the data to be used for climate studies [2]. It is now acknowledged by the international community that future missions and sensor designs need to accommodate lunar calibrations. An overview of ocean color remote sensing and a review of the progress made in ocean color remote sensing and the variety of research applications derived from global satellite ocean color data are provided. The purpose of this chapter is to discuss the design options for ocean color satellite radiometers, performance and testing criteria, and sensor components (optics, detectors, electronics, etc.) that must be integrated into an instrument concept. These ultimately dictate the quality and quantity of data that can be delivered as a trade against mission cost. Historically, science and sensor technology have advanced in a "leap-frog" manner in that sensor design requirements for a mission are defined many years before a sensor is launched and by the end of the mission, perhaps 15-20 years later, science applications and requirements are well beyond the capabilities of the sensor. Section 3 provides a summary of historical mission science objectives and sensor requirements. This progression is expected to continue in the future as long as sensor costs can be constrained to affordable levels and still allow the incorporation of new technologies without incurring unacceptable risk to mission success. The IOCCG Report Number 13 discusses future ocean biology mission Level-1 requirements in depth.

Ocean Color↗

SMAP Instrument Mechanical System Engineering

The Soil Moisture Active Passive (SMAP) mission, scheduled for launch by the end of 2014, is being developed to measure the soil moisture and soil freeze/thaw state on a global scale over a three-year period. The accuracy, resolution, and global coverage of SMAP measurements are invaluable across many science and applications disciplines including hydrology, climate, carbon cycle, and the meteorological, environment, and ecology applications communities. The SMAP observatory is composed of a despun bus and a spinning instrument platform that includes both a deployable 6 meter aperture low structural frequency Astromesh reflector and a spin control system. The instrument section has engendered challenging mechanical system issues associated with the antenna deployment, flexible antenna pointing in the context of a multitude of disturbances, spun section mass properties, spin control system development, and overall integration with the flight system on both mechanical and control system levels. Moreover, the multitude of organizations involved, including two major vendors providing the spin subsystem and reflector boom assembly plus the flight system mechanical and guidance, navigation, and control teams, has led to several unique system engineering challenges. Capturing the key physics associated with the function of the flight system has been challenging due to the many different domains that are applicable. Key interfaces and operational concepts have led to complex negotiations because of the large number of organizations that integrate with the instrument mechanical system. Additionally, the verification and validation concerns associated with the mechanical system have had required far-reaching involvement from both the flight system and other subsystems. The SMAP instrument mechanical systems engineering issues and their solutions are described in this paper.

mechanical systems.↗

Utilization of Ancillary Data Sets for Conceptual SMAP Mission Algorithm Development and Product Generation

The planned Soil Moisture Active Passive (SMAP) mission is one of the first Earth observation satellites being developed by NASA in response to the National Research Council's Decadal Survey, Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond [1]. Scheduled to launch late in 2014, the proposed SMAP mission would provide high resolution and frequent revisit global mapping of soil moisture and freeze/thaw state, utilizing enhanced Radio Frequency Interference (RFI) mitigation approaches to collect new measurements of the hydrological condition of the Earth's surface. The SMAP instrument design incorporates an L-band radar (3 km) and an L band radiometer (40 km) sharing a single 6-meter rotating mesh antenna to provide measurements of soil moisture and landscape freeze/thaw state [2]. These observations would (1) improve our understanding of linkages between the Earth's water, energy, and carbon cycles, (2) benefit many application areas including numerical weather and climate prediction, flood and drought monitoring, agricultural productivity, human health, and national security, (3) help to address priority questions on climate change, and (4) potentially provide continuity with brightness temperature and soil moisture measurements from ESA's SMOS (Soil Moisture Ocean Salinity) and NASA's Aquarius missions. In the planned SMAP mission prelaunch time frame, baseline algorithms are being developed for generating (1) soil moisture products both from radiometer measurements on a 36 km grid and from combined radar/radiometer measurements on a 9 km grid, and (2) freeze/thaw products from radar measurements on a 3 km grid. These retrieval algorithms need a variety of global ancillary data, both static and dynamic, to run the retrieval models, constrain the retrievals, and provide flags for indicating retrieval quality. The choice of which ancillary dataset to use for a particular SMAP product would be based on a number of factors, including its availability and ease of use, its inherent error and resulting impact on the overall soil moisture or freeze/thaw retrieval accuracy, and its compatibility with similar choices made by the SMOS mission. All decisions regarding SMAP ancillary data sources would be fully documented by the SMAP Project and made available to the user community.

freeze/thaw↗

Radar and Lidar Radar DEM

Using radar and lidar data, the aim is to improve 3D rendering of terrain, including digital elevation models (DEM) and estimates of vegetation height and biomass in a variety of forest types and terrains. The 3D mapping of vegetation structure and the analysis are useful to determine the role of forest in climate change (carbon cycle), in providing habitat and as a provider of socio-economic services. This in turn will lead to potential for development of more effective land-use management. The first part of the project was to characterize the Shuttle Radar Topography Mission DEM error with respect to ICESat/GLAS point estimates of elevation. We investigated potential trends with latitude, canopy height, signal to noise ratio (SNR), number of LiDAR waveform peaks, and maximum peak width. Scatter plots were produced for each variable and were fitted with 1st and 2nd degree polynomials. Higher order trends were visually inspected through filtering with a mean and median filter. We also assessed trends in the DEM error variance. Finally, a map showing how DEM error was geographically distributed globally was created.

remote sensing↗

The Prototype HyspIRI Thermal Infrared Radiometer (PHyTIR): A High Speed, Multispectral, Thermal Instrument Development in Support of HyspIRI-TIR

The Prototype HyspIRI Thermal Infrared Radiometer (PHyTIR) is being developed as part of the risk reduction activities associated with the Hyperspectral Infrared Imager (HyspIRI). The HyspIRI mission was recommended by the National Research Council Decadal Survey and includes a visible shortwave infrared (SWIR) pushboom spectrometer and a multispectral whiskbroom thermal infrared (TIR) imager. Data from the HyspIRI mission will be used to address key science questions related to the Solid Earth and Carbon Cycle and Ecosystems focus areas of the NASA Science Mission Directorate. The HyspIRI TIR system will have 60m ground resolution, better than 200mK noise equivalent delta temperature (NEDT), 0.5C absolute temperature resolution with a 5-day repeat from LEO orbit. PHyTIR addresses the technology readiness level (TRL) of certain key subsystems of the TIR imager, primarily the detector assembly and scanning mechanism. PHyTIR will use Mercury Cadmium Telluride (MCT) technology at the focal plane and operate in time delay integration mode. A custom read out integrated circuit (ROIC) will provide the high speed readout hence allowing the high data rates needed for the 5 day repeat. PHyTIR will also demonstrate a newly developed interferometeric metrology system. This system will provide an absolute measurement of the scanning mirror to an order of magnitude better than conventional optical encoders. This will minimize the reliance on ground control points hence minimizing post-processing (e.g. geo-rectification computations).

National Research Council Decadal Survey↗

The Soil Moisture Active and Passive Mission (SMAP): Science and Applications

The Soil Moisture Active and Passive mission (SMAP) will provide global maps of soil moisture content and surface freeze/thaw state. Global measurements of these variables are critical for terrestrial water and carbon cycle applications. The SMAP observatory consists of two multipolarization L-band sensors, a radar and radiometer, that share a deployable-mesh reflector antenna. The combined observations from the two sensors will allow accurate estimation of soil moisture at hydrometeorological (10 km) and hydroclimatological (40 km) spatial scales. The rotating antenna configuration provides conical scans of the Earth surface at a constant look angle. The wide-swath (1000 km) measurements will allow global mapping of soil moisture and its freeze/thaw state with 2-3 days revisit. Freeze/thaw in boreal latitudes will be mapped using the radar at 3 km resolution with 1-2 days revisit. The synergy of active and passive observations enables measurements of soil moisture and freeze/thaw state with unprecedented resolution, sensitivity, area coverage and revisit.

radiometry↗

Deformation, Ecosystem Structure, and Dynamics of Ice (DESDynI)

The National Research Council Earth Science Decadal Survey, Earth Science Applications from Space, recommends that DESDynI (Deformation, Ecosystem Structure, and Dynamics of Ice), an integrated L-band InSAR and multibeam Lidar mission, launch in the 2010- 2013 timeframe. The mission will measure surface deformation for solid Earth and cryosphere objectives and vegetation structure for understanding the carbon cycle. InSAR has been used to study surface deformation of the solid Earth and cryosphere and more recently vegetation structure for estimates of biomass and ecosystem function. Lidar directly measures topography and vegetation structure and is used to estimate biomass and detect changes in surface elevation. The goal of DESDynI is to take advantage of the spatial continuity of InSAR and the precision and directness of Lidar. There are several issues related to the design of the DESDynI mission, including combining the two instruments into a single platform, optimizing the coverage and orbit for the two techniques, and carrying out the science modeling to define and maximize the scientific output of the mission.

Donnellan, Andrea↗

PHyTIR - A Prototype Thermal Infrared Radiometer

This paper describes the PHyTIR (Prototype HyspIRI Thermal Infrared Radiometer) instrument, which is the engineering model for the proposed HyspIRI (Hyperspectral Infrared Imager) earth observing instrument. The HyspIRI mission would be comprised of the HyspIRI TIR (Thermal Infrared Imager), and a VSWIR (Visible Short-Wave Infra-Red Imaging Spectrometer). Both instruments would be used to address key science questions related to the earth's carbon cycle, ecosystems, climate, and solid earth properties. Data gathering of volcanic activities, earthquakes, wildfires, water use and availability, urbanization, and land surface compositions and changes, would aid the predictions and evaluations of such events and the impact they create. Even though the proposed technology for the HyspIRI imager is mature, the PHyTIR prototype is needed to advance the technology levels for several of the instrument's key components, and to reduce risks, in particular to validate 1) the higher sensitivity, spatial resolution, and higher throughput required for this focal plane array, 2) the pointing accuracy, 2) the characteristics of several spectral channels, and 4) the use of ambient temperature optics. The PHyTIR telescope consists of the focal plane assembly that is housed within a cold housing located inside a vacuum enclosure; all mounted to a bulkhead, and an optical train that consists of 3 powered mirrors; extending to both sides of the bulkhead. A yoke connects the telescope to a scan mirror. The rotating mirror enables to scan- a large track on the ground. This structure is supported by kinematic mounts, linking the telescope assembly to a base plate that would also become the spacecraft interface for HyspIRI. The focal plane's cooling units are also mounted to the base plate, as is an overall enclosure that has two viewing ports with large exterior baffles, shielding the focal plane from incoming stray light. PHyTIR's electronics is distributed inside and near the vacuum enclosure, and in a nearby rack. The data acquisition technique would be to take measurements over a 51deg wide swath in the cross spacecraft velocity direction, which is brought into view through the rotating scan mirror. A landscape mosaic thus can be assembled by overlaying rows of measurements. The paper briefly outlines the proposed HyspIRI mission and its data acquisition technique; it then describes the prototype PHyTIR instrument.

Space Instrument↗

Chlorophyll Variability in the Oligotrophic Gyres: Mechanisms, Seasonality and Trends

A 16-year (1998-2013) analysis of trends and seasonal patterns was conducted for the 5 subtropical ocean gyres using chlorophyll-a (Chl-a) retrievals from ocean color satellite data, sea surface temperature (SST) obtained from optimally interpolated Advanced Very High Resolution Radiometer (AVHRR) data, and sea-level anomaly (SLA) from Aviso multi-sensor altimetry data. Trend analysis was also performed on mixed-layer data derived from gridded temperature and salinity profiles (1998-2010) from the Simple Ocean Data Assimilation (SODA) model. The Chl-a monthly composites were constructed from the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Moderate-resolution Imaging Spectroradiometer (MODIS) on Aqua using two different algorithms: the standard algorithm (STD) that has been in use since the start of the SeaWiFS mission in 1997, and a more recently developed Ocean Color Index (OCI) algorithm that is purported to provide improved accuracy in low chlorophyll waters such as the oligotrophic regions of the subtropical gyres. Trends were obtained for all gyres using both STD and OCI algorithms, which demonstrated generally consistent results. The North Pacific, Indian Ocean, North Atlantic and South Atlantic gyres showed significant downward trends in Chl-a, while the South Pacific gyre has a much weaker upward trend with no statistical significance. Time series of satellite-derived net primary production (NPP) showed downward trends for all the gyres, while all 5 gyres exhibited positive trends in SST and SLA. The seasonal variability of Chl-a in each gyre is tightly coupled to the variability in mixed layer depth (MLD) with peak values in winter in both hemispheres when vertical mixing is more vigorous, reaching depths approaching the nutricline (ZNO3, here defined as the depth of the 0.2 micron nitrate concentration). On a seasonal basis, Chl-a concentrations increase when the MLD approaches or is deeper than the nutricline depth, in agreement with the concept that vertical mixing is the major driving mechanism for phytoplankton photosynthesis in the interior of the gyres. In addition, MLD and SST seasonal changes are well correlated indicating that SST is a reasonable index of vertical mixing in the gyres. The combination of surface warming trends and biomass reduction over the 16-year period has the potential to reduce atmospheric CO2 uptake by the gyres and therefore influence the global carbon cycle.

Long-term trends↗

CASA Forest Cover Change Data Sets

Deforestation and forest fires are global land cover changes that can be caused by both natural and human factors. Although monitoring forest fires in near-real time is critical for operational wildfire management, mapping historical wildfires in a spatially explicit fashion is also important for a number of reasons, including climate change studies (e.g., examining the relationship between rising temperatures and frequency of fires), fuel load management (e.g., deciding when and where to conduct controlled burns), and carbon cycle studies (e.g., quantifying how much CO2 is emitted by fires and for emissions reduction efforts under the United Nations programs for Reducing Emissions from Deforestation and Degradation -- REDD).

Mapping↗

Optical Parametric Technology for Methane Measurements

Atmospheric methane (CH4) is the second most important anthropogenic greenhouse gas, with approximately 25 times the radiative forcing of carbon dioxide (CO2) per molecule. Yet, lack of understanding of the processes that control CH4 sources and sinks and its potential release from stored carbon reservoirs contributes significant uncertainty to our knowledge of the interaction between carbon cycle and climate change. At Goddard Space Flight Center (GSFC) we have been developing the technology needed to remotely measure CH4 from orbit. Our concept for a CH4 lidar is a nadir viewing instrument that uses the strong laser echoes from the Earth's surface to measure CH4. The instrument uses a tunable, narrow-frequency light source and photon-sensitive detector to make continuous measurements from orbit, in sunlight and darkness, at all latitudes and can be relatively immune to errors introduced by scattering from clouds and aerosols. Our measurement technique uses Integrated Path Differential Absorption (IPDA), which measures the absorption of laser pulses by a trace gas when tuned to a wavelength coincident with an absorption line. We have already demonstrated ground-based and airborne CH4 detection using Optical Parametric Amplifiers (OPA) at 1651 nm using a laser with approximately 10 microJ/pulse at 5kHz with a narrow linewidth. Next, we will upgrade our OPO system to add several more wavelengths in preparation for our September 2015 airborne campaign, and expect that these upgrades will enable CH4 measurements with 1% precision (10-20 ppb).

oscillator↗

An Overview of Production and Validation of the SMAP Passive Soil Moisture Product

The Soil Moisture Active Passive (SMAP) mission is an L-band mission scheduled for launch in Jan. 2015. The SMAP instruments consist of a radar and a radiometer to obtain complementary information from space for soil moisture and freeze/thaw state research and applications. By utilizing novel designs in antenna construction, retrieval algorithms, and acquisition hardware, SMAP provides a capability for global mapping of soil moisture and freeze/thaw state with unprecedented accuracy, resolution, and coverage. This improvement in hydrosphere state measurement is expected to advance our understanding of the processes that link the terrestrial water, energy and carbon cycles, improve our capability in flood prediction and drought monitoring, and enhance our skills in weather and climate forecast. For swath-based soil moisture measurement, SMAP generates three operational geophysical data products: (1) the radiometer-only soil moisture product (L2_SM_P) posted at 36-kilometer resolution, (2) the radar-only soil moisture product (L2_SM_A) posted at 3-kilometers resolution, and (3) the radar-radiometer combined soil moisture product (L2_SM_AP) posted at 9-kilometers resolution. Each product draws on the strengths of the underlying sensor(s) and plays a unique role in hydroclimatological and hydrometeorological applications. A full suite of SMAP data products is given in Table 1.

passive microwave↗

The AgMIP Coordinated Global and Regional Assessments (CGRA) of Climate Change Impacts on Agriculture and Food Security

The Agricultural Model Intercomparison and Improvement Project (AgMIP) has been working since 2010 to construct a protocol-based framework enabling regional assessments (led by regional experts and modelers) that can provide consistent inputs to global economic and integrated assessment models. These global models can then relay important global-level information that drive regional decision-making and outcomes throughout an interconnected agricultural system. AgMIPs community of nearly 800 climate, crop, livestock, economics, and IT experts has improved the state-of-the-art through model intercomparisons, validation exercises, regional integrated assessments, and the launch of AgMIP programs on all six arable continents. AgMIP is now launching Coordinated Global and Regional Assessments (CGRA) of climate change impacts on agriculture and food security to link global and regional crop and economic models using a protocol-based framework. The CGRA protocols are being developed to utilize historical observations, climate projections, and RCPsSSPs from CMIP5 (and potentially CMIP6), and will examine stakeholder-driven agricultural development and adaptation scenarios to provide cutting-edge assessments of climate changes impact on agriculture and food security. These protocols will build on the foundation of established protocols from AgMIPs 30+ activities, and will emphasize the use of multiple models, scenarios, and scales to enable an accurate assessment of related uncertainties. The CGRA is also designed to provide the outputs necessary to feed into integrated assessment models (IAMs), nutrition and food security assessments, nitrogen and carbon cycle models, and additional impact-sector assessments (e.g., water resources, land-use, biomes, urban areas). This presentation will describe the current status of CGRA planning and initial prototype experiments to demonstrate key aspects of the protocols before wider implementation ahead of the IPCC Sixth Assessment Report.

models↗

Development of Double and Triple-Pulsed 2-micron IPDA Lidars for Column CO2 Measurements

Carbon dioxide (CO2) is an important greenhouse gas that significantly contributes to the carbon cycle and globalradiation budget on Earth. CO2 role on Earth’s climate is complicated due to different interactions with various climatecomponents that include the atmosphere, the biosphere and the hydrosphere. Although extensive worldwide efforts formonitoring atmospheric CO2 through various techniques, including in-situ and passive sensors, are taking place highuncertainties exist in quantifying CO2 sources and sinks. These uncertainties are mainly due to insufficient spatial andtemporal mapping of the gas. Therefore it is required to have more rapid and accurate CO2 monitoring with higheruniform coverage and higher resolution. CO2 DIAL operating in the 2-μm band offer better near-surface CO2measurement sensitivity due to the intrinsically stronger absorption lines. For more than 15 years, NASA LangleyResearch Center (LaRC) contributed in developing several 2-m CO2 DIAL systems and technologies. This paperfocuses on the current development of the airborne double-pulsed and triple-pulsed 2-m CO2 integrated pathdifferential absorption (IPDA) lidar system at NASA LaRC. This includes the IPDA system development andintegration. Results from ground and airborne CO2 IPDA testing will be presented. The potential of scaling suchtechnology to a space mission will be addressed.

Singh, Upendra N.↗

Inconsistent Strategies to Spin up Models in CMIP5: Implications for Ocean Biogeochemical Model Performance Assessment

During the fifth phase of the Coupled Model Intercomparison Project (CMIP5) substantial efforts were made to systematically assess the skill of Earth system models. One goal was to check how realistically representative marine biogeochemical tracer distributions could be reproduced by models. In routine assessments model historical hindcasts were compared with available modern biogeochemical observations. However, these assessments considered neither how close modeled biogeochemical reservoirs were to equilibrium nor the sensitivity of model performance to initial conditions or to the spin-up protocols. Here, we explore how the large diversity in spin-up protocols used for marine biogeochemistry in CMIP5 Earth system models (ESMs) contributes to model-to-model differences in the simulated fields. We take advantage of a 500-year spin-up simulation of IPSL-CM5A-LR to quantify the influence of the spin-up protocol on model ability to reproduce relevant data fields. Amplification of biases in selected biogeochemical fields (O2, NO3, Alk-DIC) is assessed as a function of spin-up duration. We demonstrate that a relationship between spin-up duration and assessment metrics emerges from our model results and holds when confronted with a larger ensemble of CMIP5 models. This shows that drift has implications for performance assessment in addition to possibly aliasing estimates of climate change impact. Our study suggests that differences in spin-up protocols could explain a substantial part of model disparities, constituting a source of model-to- model uncertainty. This requires more attention in future model intercomparison exercises in order to provide quantitatively more correct ESM results on marine biogeochemistry and carbon cycle feedbacks.

histories↗

Non-Topographic Space-Based Laser Remote Sensing

In the past 20+ years, NASA Goddard Space Flight Center (GSFC) has successfully developed and flown lidars for mapping of Mars, the Earth, Mercury and the Moon. As laser and electro-optics technologies expand and mature, more sophisticated instruments that once were thought to be too complicated for space are being considered and developed. We will present progress on several new, space-based laser instruments that are being developed at GSFC. These include lidars for remote sensing of carbon dioxide and methane on Earth for carbon cycle and global climate change; sodium resonance fluorescence lidar to measure environmental parameters of the middle and upper atmosphere on Earth and Mars and a wind lidar for Mars orbit; in situ laser instruments include remote and in-situ measurements of the magnetic fields; and a time-of-flight mass spectrometer to study the diversity and structure of nonvolatile organics in solid samples on missions to outer planetary satellites and small bodies.

Laser↗

Automating the SMAP Ground Data System to Support Lights-Out Operations

The Soil Moisture Active Passive (SMAP) Mission is a first tier mission in NASA's Earth Science Decadal Survey. SMAP will provide a global mapping of soil moisture and its freeze/thaw states. This mapping will be used to enhance the understanding of processes that link the terrestrial water, energy, and carbon cycles, and to enhance weather and forecast capabilities. NASA's Jet Propulsion Laboratory has been selected as the lead center for the development and operation of SMAP. The Jet Propulsion Laboratory (JPL) has an extensive history of successful deep space exploration. JPL missions have typically been large scale Class A missions with significant budget and staffing. SMAP represents a new area of JPL focus towards low cost Earth science missions. Success in this new area requires changes to the way that JPL has traditionally provided the Mission Operations System (MOS)/Ground Data System (GDS) functions. The operation of SMAP requires more routine operations activities and support for higher data rates and data volumes than have been achieved in the past. These activities must be addressed by a reduced operations team and support staff. To meet this challenge, the SMAP ground data system provides automation that will perform unattended operations, including automated commanding of the SMAP spacecraft.

GDS↗

Temperature Knowledge and Model Correlation for the Soil Moisture Active and Passive (SMAP) Reflector Mesh

NASA's Earth observing Soil Moisture Active & Passive (SMAP) Mission is scheduled to launch in November 2014 into a 685 km near-polar, sun synchronous orbit. SMAP will provide comprehensive global mapping measurements of soil moisture and freeze/thaw state in order to enhance understanding of the processes that link the water, energy, and carbon cycles. The primary objectives of SMAP are to improve worldwide weather and flood forecasting, enhance climate prediction, and refine drought and agriculture monitoring during its 3 year mission. The SMAP instrument architecture incorporates an L-band radar and an L-band radiometer which share a common feed horn and parabolic mesh reflector. The instrument rotates about the nadir axis at approximately 15 rpm, thereby providing a conically scanning wide swath antenna beam that is capable of achieving global coverage within 3 days. In order to make the necessary precise surface emission measurements from space, a temperature knowledge of 60 deg C for the mesh reflector is required. In order to show compliance, a thermal vacuum test was conducted using a portable solar simulator to illuminate a non flight, but flight-like test article through the quartz window of the vacuum chamber. The molybdenum wire of the antenna mesh is too fine to accommodate thermal sensors for direct temperature measurements. Instead, the mesh temperature was inferred from resistance measurements made during the test. The test article was rotated to five separate angles between 10 deg and 90 deg via chamber breaks to simulate the maximum expected on-orbit solar loading during the mission. The resistance measurements were converted to temperature via a resistance versus temperature calibration plot that was constructed from data collected in a separate calibration test. A simple thermal model of two different representations of the mesh (plate and torus) was created to correlate the mesh temperature predictions to within 60 deg C. The on-orbit mesh temperature will be predicted using the correlated analytical thermal model since direct measurements from in-situ flight thermal sensors are not possible.

Mikhaylov, Rebecca↗