Toward Global Snow from Space: Coverage of Snow Observation Constellation Configurations
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Engineering topics
Publications and source records attributed to Kim, Edward.
No abstract available
Background (what): SI (International System of Units)-traceable Microwave Radiometer calibration; Motivation (why): NWP (Numerical Weather Prediction), FCDR (Fundamental Climate Data Record); Technology (how): NIST (National Inst. of Standards and Technology) blackbody target for ; Standards: Status & Future Plans. Development of a National Standard for Microwave Brightness Temperature (TB) at NIST.
Permanently frozen and seasonally frozen soils occur over a large portion of the Earth's land surface. Changes in the freeze/thaw state of the land surface reflects major changes in thermal and hydraulic properties as well as acting as a "switch" for many ecological processes. In short, soil freeze/thaw state is a fundamental land surface variable in the water and energy cycles, and it connects to the carbon cycle. Surface freeze/thaw state is observable by passive and active microwave sensors. For example, NASA's Soil Moisture Active Passive (SMAP) mission includes a freeze/thaw data product. Such satellite sensing offers routine all-season and all-weather global observations of soil freeze/thaw state with the application of suitable algorithms. We describe early finding from the SLAPex Freeze/Thaw campaign, believed to be the first airborne campaign of its type, focusing on soil freeze/thaw.
The second Advanced Technology Microwave Sounder (ATMS) recently launched November 2017 on the Joint Polar Satellite System-l satellite (JPSS-l), now re-named NOAA-20. It joins the first ATMS flight unit aboard the Suomi NPP (S-NPP) satellite, as well as older sounders-the Advanced Microwave Sounding Units A & B (AMSU-A/B) and Microwave Humidity Sounder (MHS)-on polar-orbiting operational weather satellites. Together, these sounders provide critical all-weather temperature and humidity profile information for Numerical Weather Prediction (NWP) models. This paper presents results from a number of special post-launch tests used to characterize the instrument and provide unique calibration information. These special tests-long stares, alternate techniques for lunar intrusion mitigation and geolocation, spacecraft maneuvers, special scan modes, comparisons with NWP models-require non-standard modes of operation or data analysis, and can only be conducted during commissioning, prior to the start of regular forecast observations.
SnowEx is a multi-year airborne snow campaign with the primary goal of addressing the question: How much water is stored in Earths terrestrial snow-covered regions? Year 1 (2016-17) focused on the distribution of snow-water equivalent (SWE) and the snow energy balance in a forested environment. The year 1 primary site was Grand Mesa and the secondary site was the Senator Beck Basin, both in western, Colorado, USA. Nine sensors on five aircraft made observations using a broad range of sensing techniques, active and passive microwave, and active and passive optical infrared to determine the sensitivity and accuracy of these potential satellite remote sensing techniques, along with models, to measure snow under a range of forest conditions. SnowEx also included an extensive range of ground truth measurements in-situ manual samples, snow pits, ground based remote sensing measurements, and sophisticated new techniques. A detailed description of the data collected will be given and some preliminary results will be presented.
The Advanced Technology Microwave Sounder (ATMS) is a space-based, cross-track radiometer for operational atmospheric temperature and humidity sounding, utilizing 22 channels over a frequency range from 23 to 183 gigahertz. The ATMS for the Joint Polar Satellite System-1 has undergone two rounds of re-work in 2014-2015 and 2016, following performance issues discovered during and following thermal vacuum chamber (TVAC) testing at the instrument and observatory level. Final shelf-level testing, including measurement of pass band characteristics and spectral response functions, was completed in December 2016. Final instrument-level TVAC testing and calibration occurred during February 2017. Here we will describe the instrument-level TVAC calibration process, and illustrate with results from the final TVAC calibration effort.
SnowEx is a multi-year airborne snow campaign with the primary goal of addressing the question: How much water is stored in Earth's terrestrial snow-covered regions? Year 1(2016-17) focused on the distribution of snow-water equivalent (SWE) and the snow energy balance in a forested environment. The year 1 primary site was Grand Mesa and the secondary site was the Senator Beck Basin, both in western Colorado, USA. Nine sensors on five aircraft made observations using a broad range of sensing techniques - active and passive microwave, and active and passive optical/infrared - to determine the sensitivity and accuracy of these potential satellite remote sensing techniques, along with models, to measure snow under a range of forest conditions. SnowEx also included an extensive range of ground truth measurements - in-situ manual samples, snow pits, ground based remote sensing measurements, and sophisticated new techniques. A detailed description of the data collected will be given and some preliminary results will be presented.
The L-band (1 - 2 GHz) microwave remote sensing has been widely acknowledged as the most promising method to monitor regional to global soil moisture. Consequently, the Soil Moisture Active Passive (SMAP) satellite applied this technique to provide global soil moisture every 2 to 3 days. To verify the performance of SMAP, the fourth and fifth campaign of SMAP Experiments (SMAPEx-4 -5) were carried out at the beginning of the SMAP operational phase in the Murrumbidgee River catchment, southeast Australia. The airborne radar and radiometer observations together with ground sampling on soil moisture, vegetation water content, and surface roughness were collected in coincidence with SMAP overpasses. The SMAPEx-4 and -5 data sets will benefit to SMAP post-launch calibration andvalidation under Australian land surface conditions.
Soil freezing and thawing is an important process in the terrestrial water, energy, and carbon cycles, marking the change between two very different hydraulic, thermal, and biological regimes. NASA's Soil Moisture Active/Passive (SMAP) mission includes a binary freeze/thaw data product. While there have been ground-based remote sensing field measurements observing soil freeze/thaw at the point scale, and airborne campaigns that observed some frozen soil areas (e.g., BOREAS), the recently-completed SLAPex Freeze/Thaw (F/T) campaign is the first airborne campaign dedicated solely to observing frozen/thawed soil with both passive and active microwave sensors and dedicated ground truth, in order to enable detailed process-level exploration of the remote sensing signatures and in situ soil conditions. SLAPex F/T utilized the Scanning L-band Active/Passive (SLAP) instrument, an airborne simulator of SMAP developed at NASA's Goddard Space Flight Center, and was conducted near Winnipeg, Manitoba, Canada, in October/November, 2015. Future soil moisture missions are also expected to include soil freeze/thaw products, and the loss of the radar on SMAP means that airborne radar-radiometer observations like those that SLAP provides are unique assets for freeze/thaw algorithm development. This paper will present an overview of SLAPex F/T, including descriptions of the site, airborne and ground-based remote sensing, ground truth, as well as preliminary results.
The purpose of the Soil Moisture Active Passive (SMAP) radiometer calibration algorithm is to convert Level 0 (L0) radiometer digital counts data into calibrated estimates of brightness temperatures referenced to the Earth's surface within the main beam. The algorithm theory in most respects is similar to what has been developed and implemented for decades for other satellite radiometers; however, SMAP includes two key features heretofore absent from most satellite borne radiometers: radio frequency interference (RFI) detection and mitigation, and measurement of the third and fourth Stokes parameters using digital correlation. The purpose of this document is to describe the SMAP radiometer and forward model, explain the SMAP calibration algorithm, including approximations, errors, and biases, provide all necessary equations for implementing the calibration algorithm and detail the RFI detection and mitigation process. Section 2 provides a summary of algorithm objectives and driving requirements. Section 3 is a description of the instrument and Section 4 covers the forward models, upon which the algorithm is based. Section 5 gives the retrieval algorithm and theory. Section 6 describes the orbit simulator, which implements the forward model and is the key for deriving antenna pattern correction coefficients and testing the overall algorithm.
This paper evaluates the simulation of snow by the Community Land Model, version 4 (CLM4), the land model component of the Community Earth System Model, version 1.0.4 (CESM1.0.4). CLM4 was run in an offline mode forced with the corrected land-only replay of the Modern-Era Retrospective Analysis for Research and Applications (MERRA-Land) and the output was evaluated for the period from January 2001 to January 2011 over the Northern Hemisphere poleward of 30 deg N. Simulated snow-cover fraction (SCF), snow depth, and snow water equivalent (SWE) were compared against a set of observations including the Moderate Resolution Imaging Spectroradiometer (MODIS) SCF, the Interactive Multisensor Snow and Ice Mapping System (IMS) snow cover, the Canadian Meteorological Centre (CMC) daily snow analysis products, snow depth from the National Weather Service Cooperative Observer (COOP) program, and Snowpack Telemetry (SNOTEL) SWE observations. CLM4 SCF was converted into snow-cover extent (SCE) to compare with MODIS SCE. It showed good agreement, with a correlation coefficient of 0.91 and an average bias of -1.54 x 10(exp 2) sq km. Overall, CLM4 agreed well with IMS snow cover, with the percentage of correctly modeled snow-no snow being 94%. CLM4 snow depth and SWE agreed reasonably well with the CMC product, with the average bias (RMSE) of snow depth and SWE being 0.044m (0.19 m) and -0.010m (0.04 m), respectively. CLM4 underestimated SNOTEL SWE and COOP snow depth. This study demonstrates the need to improve the CLM4 snow estimates and constitutes a benchmark against which improvement of the model through data assimilation can be measured.
Scanning L-band Active Passive (SLAP) is a recently-developed NASA airborne instrument specially tailored to simulate the new Soil Moisture Active Passive (SMAP) satellite instrument suite. SLAP conducted its first test flights in December, 2013 and participated in its first science campaign-the IPHEX ground validation campaign of the GPM mission-in May, 2014. This paper will present results from additional test flights and science observations scheduled for 2015.
Discussions within the international snow remote sensing community over the past two years have led to encouraging consensus regarding the broad outlines of a dedicated snow observing mission. The primary consensus - that since no single sensor type is satisfactory across all snow types and across all confounding factors, a multi-sensor approach is required - naturally leads to questions about the exact mix of sensors, required accuracies, and so on. In short, the natural next step is to collect such multi-sensor snow observations (with detailed ground truth) to enable trade studies of various possible mission concepts. Such trade studies must assess the strengths and limitations of heritage as well as newer measurement techniques with an eye toward natural sensitivity to desired parameters such as snow depth and/or snow water equivalent (SWE) in spite of confounding factors like clouds, lack of solar illumination, forest cover, and topography, measurement accuracy, temporal and spatial coverage, technological maturity, and cost.
The first of a new generation of microwave sounders was launched aboard the Suomi-National Polar-Orbiting Partnership satellite in October 2011. The Advanced Technology Microwave Sounder (ATMS) combines the capabilities and channel sets of three predecessor sounders into a single package to provide information on the atmospheric vertical temperature and moisture profiles that are the most critical observations needed for numerical weather forecast models. Enhancements include size/mass/power approximately one third of the previous total, three new sounding channels, the first space-based, Nyquist-sampled cross-track microwave temperature soundings for improved fusion with infrared soundings, plus improved temperature control and reliability. This paper describes the ATMS characteristics versus its predecessor, the advanced microwave sounding unit (AMSU), and presents the first comprehensive evaluation of key prelaunch and on-orbit performance parameters. Two-year on-orbit performance shows that the ATMS has maintained very stable radiometric sensitivity, in agreement with prelaunch data, meeting requirements for all channels (with margins of ~40% for channels 1-15), and improvements over AMSU-A when processed for equivalent spatial resolution. The radiometric accuracy, determined by analysis from ground test measurements, and using on-orbit instrument temperatures, also shows large margins relative to requirements (specified as <1.0K for channels 1, 2, and 16-22 and <0.75 K for channels 3-15). A thorough evaluation of the performance of ATMS is especially important for this first proto-flight model unit of what will eventually be a series of ATMS sensors providing operational sounding capability for the U.S. and its international partners well into the next decade.
The Advanced Technology Microwave Sounder (ATMS) is a new satellite microwave sounding sensor designed to provide operational weather agencies with atmospheric temperature and moisture profile information for global weather forecasting and climate applications. A TMS will continue the microwave sounding capabilities first provided by its predecessors, the Microwave Sounding Unit (MSU) and Advanced Microwave Sounding Unit (AMSU). The first ATMS was launched October 28, 2011 on board the NPOESS Preparatory Project (NPP) satellite. Microwave soundings by themselves are the highest-impact input data used by Numerical Weather Prediction (NWP) models, especially under cloudy sky conditions. ATMS has 22 channels spanning 23-183 GHz, closely following the channel set of the MSU, AMSU-A1/2, AMSU-B, Microwave Humidity Sounder (MHS), and Humidity Sounder for Brazil (HSB). All this is accomplished with approximately 1/4 the volume, 1/2 the mass, and 1/2 the power of the three AMSUs. A description of ATMS cal/val activities will be presented followed by examples of its performance after its first 10 months on orbit.
Passive microwave remote sensing at L-band (1.4 GHz) is sensitive to soil moisture and sea surface salinity, both important climate variables. Science studies involving these variables can now take advantage of new satellite L-band observations. The first mission with regular global passive microwave observations at L-band is the European Space Agency's Soil Moisture and Ocean Salinity (SMOS), launched November, 2009. A second mission, NASA's Aquarius, was launched June, 201l. A third mission, NASA's Soil Moisture Active Passive (SMAP) is scheduled to launch in 2014. Together, these three missions may provide a decade-long data record -- provided that they are intercalibrated. The intercalibration is best performed at the radiance (brightness temperature) level, and Antarctica is proving to be a key calibration target. However, Antarctica has thus far not been fully characterized as a potential target. This paper will present evaluations of Antarctica as a microwave calibration target for the above satellite missions. Preliminary analyses have identified likely target areas, such as the vicinity of Dome-C and larger areas within East Antarctica. Physical sources of temporal and spatial variability of polar firn are key to assessing calibration uncertainty. These sources include spatial variability of accumulation rate, compaction, surface characteristics (dunes, micro-topography), wind patterns, and vertical profiles of density and temperature. Using primarily SMOS data, variability is being empirically characterized and attempts are being made to attribute observed variability to physical sources. One expected outcome of these studies is the potential discovery of techniques for remotely sensing--over all of Antarctica--parameters such as surface temperature.
ATMS is a new satellite microwave sounding sensor designed to provide operational weather agencies with atmospheric temperature and moisture profile information for global weather forecasting and climate applications. ATMS will continue the microwave sounding capabilities first provided by its predecessors, the Microwave Sounding Unit (MSU) and Advanced Microwave Sounding Unit (AMSU). The first ATMS was launched October 28, 2011 on board the Suomi National Polar-orbiting Partnership (S-NPP) satellite. Microwave soundings by themselves are the highest-impact input data used by Numerical Weather Prediction (NWP) models; and ATMS, when combined with the Cross-track Infrared Sounder (CrIS), forms the Cross-track Infrared and Microwave Sounding Suite (CrIMSS). The microwave soundings help meet NWP sounding requirements under cloudy sky conditions and provide key profile information near the surface
The SMAP is one of four first-tier missions recommended by the US National Research Council's Committee on Earth Science and Applications from Space (Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond, Space Studies Board, National Academies Press, 2007) [1]. It is to measure the global soil moisture and freeze/thaw from space. One of the spaceborne instruments is an L-band radiometer with a shared single feedhorn and parabolic mesh reflector. While the radiometer measures the emission over a footprint of interest, unwanted emissions are also received by the antenna through the antenna sidelobes from the cosmic background and other error sources such as the Sun, the Moon and the galaxy. Their effects need to be considered accurately, and the analysis of the overall performance of the radiometer requires end-to-end performance simulation from Earth emission to antenna brightness temperature, such as the global simulation of L-band brightness temperature simulation over land and sea [2]. To assist with the SMAP radiometer level 1B algorithm development, the SMAP forward brightness temperature simulator is developed by adapting the Aquarius simulator [2] with necessary modifications. This poster presents the current status of the SMAP forward brightness simulator s development including incorporating the land microwave emission model and its input datasets, and a simplified atmospheric radiative transfer model. The latest simulation results are also presented to demonstrate the ability of supporting the SMAP L1B algorithm development.