scholarly journals An extended global Earth system data record on daily landscape freeze–thaw status determined from satellite passive microwave remote sensing

2017 ◽  
Vol 9 (1) ◽  
pp. 133-147 ◽  
Author(s):  
Youngwook Kim ◽  
John S. Kimball ◽  
Joseph Glassy ◽  
Jinyang Du
Keyword(s):  
Land Surface ◽  
Grid Cell ◽  
Microwave Remote Sensing ◽  
Earth System ◽  
Ecological Processes ◽  
Barren Land ◽  
Freeze Thaw ◽  
Data Record ◽  
System Data ◽  
Snow And Ice

Abstract. The landscape freeze–thaw (FT) signal determined from satellite microwave brightness temperature (Tb) observations has been widely used to define frozen temperature controls on land surface water mobility and ecological processes. Calibrated 37 GHz Tb retrievals from the Scanning Multichannel Microwave Radiometer (SMMR), Special Sensor Microwave Imager (SSM/I), and SSM/I Sounder (SSMIS) were used to produce a consistent and continuous global daily data record of landscape FT status at 25 km grid cell resolution. The resulting FT Earth system data record (FT-ESDR) is derived from a refined classification algorithm and extends over a larger domain and longer period (1979–2014) than prior FT-ESDR releases. The global domain encompasses all land areas affected by seasonal frozen temperatures, including urban, snow- and ice-dominant and barren land, which were not represented by prior FT-ESDR versions. The FT retrieval is obtained using a modified seasonal threshold algorithm (MSTA) that classifies daily Tb variations in relation to grid-cell-wise FT thresholds calibrated using surface air temperature data from model reanalysis. The resulting FT record shows respective mean annual spatial classification accuracies of 90.3 and 84.3 % for evening (PM) and morning (AM) overpass retrievals relative to global weather station measurements. Detailed data quality metrics are derived characterizing the effects of sub-grid-scale open water and terrain heterogeneity, as well as algorithm uncertainties on FT classification accuracy. The FT-ESDR results are also verified against other independent cryospheric data, including in situ lake and river ice phenology, and satellite observations of Greenland surface melt. The expanded FT-ESDR enables new investigations encompassing snow- and ice-dominant land areas, while the longer record and favorable accuracy allow for refined global change assessments that can better distinguish transient weather extremes, landscape phenological shifts, and climate anomalies from longer-term trends extending over multiple decades. The dataset is freely available online (doi:10.5067/MEASURES/CRYOSPHERE/nsidc-0477.003).

scholarly journals An Extended Global Earth System Data Record on Daily Landscape Freeze-Thaw Status Determined from Satellite Passive Microwave Remote Sensing

2016 ◽  
Author(s):  
Youngwook Kim ◽  
John S. Kimball ◽  
Joseph Glassy ◽  
Jinyang Du
Keyword(s):  
Land Surface ◽  
Grid Cell ◽  
Microwave Remote Sensing ◽  
Earth System ◽  
Ecological Processes ◽  
Data Set ◽  
Barren Land ◽  
Freeze Thaw ◽  
Data Record ◽  
System Data

Abstract. The landscape freeze-thaw (FT) signal determined from satellite microwave brightness temperature (Tb) observations has been widely used to define frozen temperature controls on land surface water mobility and ecological processes. Calibrated 37 GHz Tb retrievals from the Scanning Multichannel Microwave Radiometer (SMMR), Special Sensor Microwave Imager (SSM/I), and SSM/I Sounder (SSMIS) were used to produce a consistent and continuous global daily data record of landscape FT status at 25-km grid cell resolution. The resulting FT Earth System Data Record (FT-ESDR) is derived from a refined classification algorithm and extends over a larger domain and longer period (1979–2014) than prior FT-ESDR releases. The global domain encompasses all land areas affected by seasonal frozen temperatures, including urban, snow-ice dominant and barren land. The FT retrieval is obtained using a modified seasonal threshold algorithm (MSTA) that classifies daily Tb variations in relation to grid cell-wise FT thresholds calibrated using surface air temperature data from model reanalysis. The resulting FT record shows mean annual spatial classification accuracies of 90.3 and 84.3 percent for PM and AM overpass retrievals relative to global weather station measurements. Detailed data quality metrics are derived characterizing effects of sub-grid scale open water and terrain heterogeneity, and algorithm uncertainties on FT classification accuracy. The FT-ESDR results are also verified against other independent cryospheric data, including in situ lake and river ice phenology, and satellite observations of Greenland surface melt. The expanded FT-ESDR enables new investigations encompassing snow and ice dominant land areas, while the longer record and favorable accuracy allow for refined global change assessments that can better distinguish transient weather extremes, landscape phenological shifts, and climate anomalies from longer-term trends extending over multiple decades. The data set is freely available online (http://dx.doi.org/10.5067/MEASURES/CRYOSPHERE/nsidc-0477.003).

scholarly journals Advances in Quantitative Earth Remote Sensing: Past, Present and Future

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5399 ◽  
Author(s):  
Ghassem R. Asrar
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Microwave Remote Sensing ◽  
Polar Regions ◽  
Earth System ◽  
Earth Remote Sensing ◽  
Earth’S System

A combination of multispectral visible, infra-red and microwave sensors on the constellation of international Earth-observing satellites are providing unprecedented observations for all Earth domains over multiple decades (i.e., atmosphere, land, oceans and polar regions). This Special Issue of Sensors is dedicated to papers that describe such advances in the field of Earth remote sensing and their applications to advance understanding of Earth’s planetary system and applying the resulting knowledge and information to meet the societal needs during recent decades. The papers accepted and published in this issue convey the exciting scientific and technical challenges and opportunities for remote sensing of all domains of Earth system, including terrestrial, aquatic and coastal ecosystems; bathymetry of coasts and islands; oceans and lakes; measurement of soil moisture and land surface temperature that affects both water resources and food production; and advances in use of sun-induced fluorescence (SIF) in measuring and monitoring the contribution of terrestrial vegetation in the cycling of carbon in Earth’s system. Measurements of SIF, for example, has had a profound impact on the field of terrestrial ecosystems research and modelling. The Earth Polychromatic Imaging Camera (EPIC) instrument on the Deep Space Climate Observatory (DSCVR) satellite located at the Sun–Earth Lagrange Point One, about 1.5 million miles away from Earth, is providing unique observations of the Earth’s full sun-lit disk from pole-to-pole and minute-by-minute, which overcomes a major limitation in temporal coverage of Earth by other polar-orbiting Earth-observing satellites. Active and passive microwave remote sensing instruments allow all-weather measurements and monitoring of clouds, weather phenomena, land-surface temperature and soil moisture by overcoming the presence of clouds that affect measurements by visible and infrared sensors. The use of powerful in-space lasers is allowing scientists and engineers to measure and monitor rapidly changing ice sheets in polar regions and mountain glaciers. These sensors and their measurements that are deployed on major space-based observatories and small- and micro-satellites, and the scientific knowledge they provide, are enhancing our understanding of planet Earth and development of Earth system models that are used increasingly to project future conditions due to Earth’s rapidly changing environmental conditions. Such knowledge and information are benefiting people, businesses and governments worldwide.

scholarly journals A Budyko framework for estimating how spatial heterogeneity and lateral moisture redistribution affect average evapotranspiration rates as seen from the atmosphere

2017 ◽  
Vol 21 (1) ◽  
pp. 217-233 ◽  
Author(s):  
Elham Rouholahnejad Freund ◽  
James W. Kirchner
Keyword(s):  
Spatial Heterogeneity ◽  
Land Surface ◽  
Potential Evapotranspiration ◽  
Aridity Index ◽  
Grid Cell ◽  
Earth System ◽  
Grid Cells ◽  
Closure Relation ◽  
System Models ◽  
Earth System Models

Abstract. Most Earth system models are based on grid-averaged soil columns that do not communicate with one another, and that average over considerable sub-grid heterogeneity in land surface properties, precipitation (P), and potential evapotranspiration (PET). These models also typically ignore topographically driven lateral redistribution of water (either as groundwater or surface flows), both within and between model grid cells. Here, we present a first attempt to quantify the effects of spatial heterogeneity and lateral redistribution on grid-cell-averaged evapotranspiration (ET) as seen from the atmosphere over heterogeneous landscapes. Our approach uses Budyko curves, as a simple model of ET as a function of atmospheric forcing by P and PET. From these Budyko curves, we derive a simple sub-grid closure relation that quantifies how spatial heterogeneity affects average ET as seen from the atmosphere. We show that averaging over sub-grid heterogeneity in P and PET, as typical Earth system models do, leads to overestimations of average ET. For a sample high-relief grid cell in the Himalayas, this overestimation bias is shown to be roughly 12 %; for adjacent lower-relief grid cells, it is substantially smaller. We use a similar approach to derive sub-grid closure relations that quantify how lateral redistribution of water could alter average ET as seen from the atmosphere. We derive expressions for the maximum possible effect of lateral redistribution on average ET, and the amount of lateral redistribution required to achieve this effect, using only estimates of P and PET in possible source and recipient locations as inputs. We show that where the aridity index P/PET increases with altitude, gravitationally driven lateral redistribution will increase average ET (and models that overlook lateral redistribution will underestimate average ET). Conversely, where the aridity index P/PET decreases with altitude, gravitationally driven lateral redistribution will decrease average ET. The effects of both sub-grid heterogeneity and lateral redistribution will be most pronounced where P is inversely correlated with PET across the landscape. Our analysis provides first-order estimates of the magnitudes of these sub-grid effects, as a guide for more detailed modeling and analysis.

Development of a consistent soil moisture decadal data record from multiple satellites

2020 ◽  
Author(s):  
Steven Chan
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Microwave Radiometer ◽  
Microwave Remote Sensing ◽  
Precipitation Measurement ◽  
X Band ◽  
Data Record ◽  
System Data ◽  
Global Precipitation Measurement ◽  
Global Precipitation

<p>In recent decades, passive microwave remote sensing at lower frequencies (1-10 GHz) has become a primary means to routinely monitor soil moisture on a global scale. Despite the success of a number of L- and C/X-band radiometers independently developed and launched by various government agencies over the last two decades, there has not been a concerted effort to leverage the combined brightness temperature (T<sub>B</sub>) observations from these instruments to derive an integrated soil moisture data record within a consistent geophysical inversion framework. The availability of such a consistent data record would provide critical insights into the dynamics of surface hydrological processes, including anomaly detection, interannual variability, and monitoring of the onset and evolution of long-term spatial and temporal variability due to natural or anthropogenic changes in land surface conditions.</p><p>Recent advances in T<sub>B</sub> intercalibration on current and historical satellites have resulted in the availability of consistent T<sub>B</sub> observations that extend from years to decades. For passive microwave remote sensing of soil moisture, satellite intercalibration undertaken by the Global Precipitation Measurement (GPM) mission [1-2] has resulted in a decadal repository of intercalibrated T<sub>B</sub> observations at X-band (10.7 GHz) frequencies from GMI (2014-present), AMSR2 (2012-present), WindSat (2003-present), TMI (1997-2015) and AMSR-E (2002-2011). Likewise, recent studies on relative calibration by SMOS (2009-present) and SMAP (2015-present) teams have also enabled the production of a similar repository of intercalibrated T<sub>B</sub> observations for soil moisture estimation at L-band (1.41 GHz) frequencies [3]. When used as inputs to a common geophysical inversion model, these T<sub>B</sub> observations can be used for soil moisture estimation. Because consistency has been reinforced at the level of T<sub>B</sub> observations among satellites, the resulting record of soil moisture retrieval is expected to exhibit the same internal consistency. Together, therefore, these T<sub>B</sub> repositories provide the foundation for the development of current and historical consistent soil moisture data records with more frequent and wider coverage than any single satellite can achieve alone.</p><p>In this presentation, we will describe a NASA-funded initiative [4] (MEaSUREs: Making Earth System Data Records for use in Research Environments) to create a consistent soil moisture decadal data record from multiple satellites for terrestrial hydrological applications. Preliminary results, ancillary data preparation, product delivery schedule, and deliverables of this initiative will be discussed in this presentation.</p><p>References:</p><ol><li>Berg, W., S. Bilanow, R. Chen, S. Datta, D. Draper, H. Ebrahimi, S. Farrar, W. Jones, R. Kroodsma, D. McKague, V. Payne, J. Wang, T. Wilheit, and J. Yang. 2016. “Intercalibration of the GPM Microwave Radiometer Constellation,” J. Atmos. Oceanic Technol., 33, pp. 2639–2654, doi: 10.1175/JTECH-D-16-0100.1.</li> <li>Biswas, S. K., S. Farrar, K. Gopalan, A. Santos-Garcia, W. L. Jones and S. Bilanow. 2013. “Intercalibration of Microwave Radiometer Brightness Temperatures for the Global Precipitation Measurement Mission,” in IEEE Transactions on Geoscience and Remote Sensing, vol. 51, no. 3, pp. 1465–1477. doi: 10.1109/TGRS.2012.2217148.</li> <li>Bindlish, R., S. Chan, T. Jackson, A. Colliander, and Y. Kerr. 2018. “Integration of SMAP and SMOS Observations,” 2018 IEEE IGARSS, Valencia, Spain.</li> <li>"MEaSUREs: Making Earth System Data Records for Use in Research Environments," Accessed Nov 8, 2018. [Online]. Available: https://earthdata.nasa.gov/community/community-data-system-programs/measures-projects</li> </ol>

scholarly journals A simplified permafrost-carbon model for long-term climate studies with the CLIMBER-2 coupled earth system model

2014 ◽  
Vol 7 (4) ◽  
pp. 4931-4992
Author(s):  
K. A. Crichton ◽  
D. M. Roche ◽  
G. Krinner ◽  
J. Chappellaz
Keyword(s):  
Soil Carbon ◽  
Land Surface ◽  
Measurement Data ◽  
Grid Cell ◽  
Earth System Model ◽  
Carbon Pool ◽  
System Model ◽  
Earth System ◽  
Carbon Release ◽  
Surface Scheme

Abstract. We present the development and validation of a simplified permafrost-carbon mechanism for use with the land surface scheme operating in the CLIMBER-2 earth system model. The simplified model estimates the permafrost fraction of each grid cell according to the balance between modelled cold (below 0 °C) and warm (above 0 °C) days in a year. Areas diagnosed as permafrost are assigned a reduction in soil decay, thus creating a slow accumulating soil carbon pool. In warming climates, permafrost extent reduces and soil decay increases, resulting in soil carbon release to the atmosphere. Four accumulation/decay rate settings are retained for experiments within the CLIMBER-2(P) model, which are tuned to agree with estimates of total land carbon stocks today and at the last glacial maximum. The distribution of this permafrost-carbon pool is in broad agreement with measurement data for soil carbon concentration per climate condition. The level of complexity of the permafrost-carbon model is comparable to other components in the CLIMBER-2 earth system model.

scholarly journals Best Practices in Crafting the Calibrated, Enhanced-Resolution Passive-Microwave EASE-Grid 2.0 Brightness Temperature Earth System Data Record

2018 ◽  
Vol 10 (11) ◽  
pp. 1793 ◽  
Author(s):  
Mary Brodzik ◽  
David Long ◽  
Molly Hardman
Keyword(s):  
Best Practices ◽  
Brightness Temperature ◽  
Passive Microwave ◽  
Earth System ◽  
Climate Data ◽  
Enhanced Resolution ◽  
Data Record ◽  
System Data ◽  
Land Surfaces ◽  
Climate Data Record

Since the late 1970s, satellite passive-microwave brightness temperatures have been a mainstay in remote sensing of the cryosphere. Polar snow and ice-covered ocean and land surfaces are especially sensitive to climate change and are observed to fluctuate on interannual to decadal timescales. In regions of limited sunlight and cloudy conditions, microwave measurements are particularly valuable for monitoring snow- and ice-covered ocean and land surfaces, due to microwave sensitivity to phase changes of water. Historically available at relatively low resolutions (25 km) compared to optical techniques (less than 1 km), passive-microwave sensors have provided short-timescale, large-area spatial coverage, and high temporal repeat observations for monitoring hemispheric-wide changes. However, historically available gridded passive microwave products have fallen short of modern requirements for climate data records, notably by using inconsistently-calibrated input data, including only limited periods of sensor overlaps, employing image-reconstruction methods that tuned for reduced noise rather than enhanced resolution, and using projection and grid definitions that were not easily interpreted by geolocation software. Using a recently completed Fundamental Climate Data Record of the swath format passive-microwave record that incorporated new, cross-sensor calibrations, we have produced an improved, gridded data record. Defined on the EASE-Grid 2.0 map projections and derived with numerically efficient image-reconstruction techniques, the Calibrated, Enhanced-Resolution Brightness Temperature (CETB) Earth System Data Record (ESDR) increases spatial resolution up to 3.125 km for the highest frequency channels, and satisfies modern Climate Data Record (CDR) requirements as defined by the National Research Council. We describe the best practices and development approaches that we used to ensure algorithmic integrity and to define and satisfy metadata, content and structural requirements for this high-quality, reliable, consistently gridded microwave radiometer climate data record.

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