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Dive into the research topics where Michael A. Palecki is active.

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Featured researches published by Michael A. Palecki.


IEEE Transactions on Geoscience and Remote Sensing | 2016

Assessment of the SMAP Passive Soil Moisture Product

Steven Chan; Rajat Bindlish; Peggy E. O'Neill; Eni G. Njoku; Thomas J. Jackson; Andreas Colliander; Fan Chen; Mariko S. Burgin; R. Scott Dunbar; Jeffrey R. Piepmeier; Simon H. Yueh; Dara Entekhabi; Michael H. Cosh; Todd G. Caldwell; Jeffrey P. Walker; Xiaoling Wu; Aaron A. Berg; Tracy L. Rowlandson; Anna Pacheco; Heather McNairn; M. Thibeault; Ángel González-Zamora; Mark S. Seyfried; David D. Bosch; Patrick J. Starks; David C. Goodrich; John H. Prueger; Michael A. Palecki; Eric E. Small; Marek Zreda

The National Aeronautics and Space Administration (NASA) Soil Moisture Active Passive (SMAP) satellite mission was launched on January 31, 2015. The observatory was developed to provide global mapping of high-resolution soil moisture and freeze-thaw state every two to three days using an L-band (active) radar and an L-band (passive) radiometer. After an irrecoverable hardware failure of the radar on July 7, 2015, the radiometer-only soil moisture product became the only operational soil moisture product for SMAP. The product provides soil moisture estimates posted on a 36 km Earth-fixed grid produced using brightness temperature observations from descending passes. Within months after the commissioning of the SMAP radiometer, the product was assessed to have attained preliminary (beta) science quality, and data were released to the public for evaluation in September 2015. The product is available from the NASA Distributed Active Archive Center at the National Snow and Ice Data Center. This paper provides a summary of the Level 2 Passive Soil Moisture Product (L2_SM_P) and its validation against in situ ground measurements collected from different data sources. Initial in situ comparisons conducted between March 31, 2015 and October 26, 2015, at a limited number of core validation sites (CVSs) and several hundred sparse network points, indicate that the V-pol Single Channel Algorithm (SCA-V) currently delivers the best performance among algorithms considered for L2_SM_P, based on several metrics. The accuracy of the soil moisture retrievals averaged over the CVSs was 0.038 m3/m3 unbiased root-mean-square difference (ubRMSD), which approaches the SMAP mission requirement of 0.040 m3/m3.


Journal of Geophysical Research | 2010

On the reliability of the U.S. surface temperature record

Matthew J. Menne; Claude N. Williams; Michael A. Palecki

[1]xa0Recent photographic documentation of poor siting conditions at stations in the U.S. Historical Climatology Network (USHCN) has led to questions regarding the reliability of surface temperature trends over the conterminous United States (CONUS). To evaluate the potential impact of poor siting/instrument exposure on CONUS temperatures, trends derived from poor and well sited USHCN stations were compared. Results indicate that there is a mean bias associated with poor exposure sites relative to good exposure sites; however, this bias is consistent with previously documented changes associated with the widespread conversion to electronic sensors in the USHCN during the last 25 years. Moreover, the sign of the bias is counterintuitive to photographic documentation of poor exposure because associated instrument changes have led to an artificial negative (“cool”) bias in maximum temperatures and only a slight positive (“warm”) bias in minimum temperatures. These results underscore the need to consider all changes in observation practice when determining the impacts of siting irregularities. Further, the influence of nonstandard siting on temperature trends can only be quantified through an analysis of the data. Adjustments applied to USHCN Version 2 data largely account for the impact of instrument and siting changes, although a small overall residual negative (“cool”) bias appears to remain in the adjusted maximum temperature series. Nevertheless, the adjusted USHCN temperatures are extremely well aligned with recent measurements from instruments whose exposure characteristics meet the highest standards for climate monitoring. In summary, we find no evidence that the CONUS average temperature trends are inflated due to poor station siting.


international geoscience and remote sensing symposium | 2016

Evaluation of the validated Soil Moisture product from the SMAP radiometer

Peggy E. O'Neill; S. Chan; Andreas Colliander; R. Scott Dunbar; Eni G. Njoku; Rajat Bindlish; Fan Chen; Thomas J. Jackson; Mariko S. Burgin; Jeffrey R. Piepmeier; Simon H. Yueh; Dara Entekhabi; Michael H. Cosh; Todd G. Caldwell; Jeffrey P. Walker; Xiaoling Wu; Aaron A. Berg; Tracy L. Rowlandson; Anna Pacheco; Heather McNairn; M. Thibeault; Ángel González-Zamora; Mark S. Seyfried; David D. Bosch; Patrick J. Starks; David C. Goodrich; John H. Prueger; Michael A. Palecki; Eric E. Small; Marek Zreda

NASAs Soil Moisture Active Passive (SMAP) mission launched on January 31, 2015 into a sun-synchronous 6 am/6 pm orbit with an objective to produce global mapping of high-resolution soil moisture and freeze-thaw state every 2-3 days using an L-band (active) radar and an L-band (passive) radiometer. The SMAP radiometer began acquiring routine science data on March 31, 2015 and continues to operate nominally. SMAPs radiometer-derived soil moisture product (L2_SM_P) provides soil moisture estimates posted on a 36 km fixed Earth grid using brightness temperature observations from descending (6 am) passes and ancillary data. A beta quality version of L2_SM_P was released to the public in September, 2015, with the fully validated L2_SM_P soil moisture data expected to be released in May, 2016. Additional improvements (including optimization of retrieval algorithm parameters and upscaling approaches) and methodology expansions (including increasing the number of core sites, model-based intercomparisons, and results from several intensive field campaigns) are anticipated in moving from accuracy assessment of the beta quality data to an evaluation of the fully validated L2_SM_P data product.


International Journal of Applied Earth Observation and Geoinformation | 2016

Deploying temporary networks for upscaling of sparse network stations

Evan J. Coopersmith; Michael H. Cosh; Jesse E. Bell; Victoria Kelly; Mark Hall; Michael A. Palecki; Marouane Temimi

Abstract Soil observations networks at the national scale play an integral role in hydrologic modeling, drought assessment, agricultural decision support, and our ability to understand climate change. Understanding soil moisture variability is necessary to apply these measurements to model calibration, business and consumer applications, or even human health issues. The installation of soil moisture sensors as sparse, national networks is necessitated by limited financial resources. However, this results in the incomplete sampling of the local heterogeneity of soil type, vegetation cover, topography, and the fine spatial distribution of precipitation events. To this end, temporary networks can be installed in the areas surrounding a permanent installation within a sparse network. The temporary networks deployed in this study provide a more representative average at the 3xa0km and 9xa0km scales, localized about the permanent gauge. The value of such temporary networks is demonstrated at test sites in Millbrook, New York and Crossville, Tennessee. The capacity of a single U.S. Climate Reference Network (USCRN) sensor set to approximate the average of a temporary network at the 3xa0km and 9xa0km scales using a simple linear scaling function is tested. The capacity of a temporary network to provide reliable estimates with diminishing numbers of sensors, the temporal stability of those networks, and ultimately, the relationship of the variability of those networks to soil moisture conditions at the permanent sensor are investigated. In this manner, this work demonstrates the single-season installation of a temporary network as a mechanism to characterize the soil moisture variability at a permanent gauge within a sparse network.


international geoscience and remote sensing symposium | 2017

Development and validation of the SMAP enhanced passive soil moisture product

S. Chan; Rajat Bindlish; Peggy E. O'Neill; Thomas J. Jackson; Julian Chaubell; Jeffrey R. Piepmeier; S. Dunbar; Andreas Colliander; F. Chen; Dara Entekhabi; Simon H. Yueh; M. Cosh; Todd G. Caldwell; Jeffrey P. Walker; Xiaoling Wu; Aaron A. Berg; Tracy L. Rowlandson; Anna Pacheco; Heather McNairn; M. Thibeault; Ángel González-Zamora; Ernesto Lopez-Baeza; F. Uldall; Mark S. Seyfried; David D. Bosch; Patrick J. Starks; C. D. Holifield Collins; John H. Prueger; Zhongbo Su; R. van der Velde

Since the beginning of its routine science operation in March 2015, the NASA SMAP observatory has been returning interference-mitigated brightness temperature observations at L-band (1.41 GHz) frequency from space. The resulting data enable frequent global mapping of soil moisture with a retrieval uncertainty below 0.040 m3/m3 at a 36 km spatial scale. This paper describes the development and validation of an enhanced version of the current standard soil moisture product. Compared with the standard product that is posted on a 36 km grid, the new enhanced product is posted on a 9 km grid. Derived from the same time-ordered brightness temperature observations that feed the current standard passive soil moisture product, the enhanced passive soil moisture product leverages on the Backus-Gilbert optimal interpolation technique that more fully utilizes the additional information from the original radiometer observations to achieve global mapping of soil moisture with enhanced clarity. The resulting enhanced soil moisture product was assessed using long-term in situ soil moisture observations from core validation sites located in diverse biomes and was found to exhibit an average retrieval uncertainty below 0.040 m3/m3. As of December 2016, the enhanced soil moisture product has been made available to the public from the NASA Distributed Active Archive Center at the National Snow and Ice Data Center.


international geoscience and remote sensing symposium | 2017

Assessment of version 4 of the SMAP passive soil moisture standard product

Peggy E. O'Neill; S. Chan; Rajat Bindlish; Thomas J. Jackson; Andreas Colliander; Scott Dunbar; Fan Chen; Jeffrey R. Piepmeier; Simon H. Yueh; Dara Entekhabi; Michael H. Cosh; Todd G. Caldwell; Jeffrey P. Walker; Xiaoling Wu; Aaron A. Berg; Tracy L. Rowlandson; Anna Pacheco; Heather McNairn; M. Thibeault; Ángel González-Zamora; Ernesto Lopez-Baeza; F. Udall; Mark S. Seyfried; David D. Bosch; Patrick J. Starks; C. Holifield; John H. Prueger; Zhongbo Su; R. van der Velde; Jun Asanuma

NASAs Soil Moisture Active Passive (SMAP) mission launched on January 31, 2015 into a sun-synchronous 6 am/6 pm orbit with an objective to produce global mapping of high-resolution soil moisture and freeze-thaw state every 2–3 days. The SMAP radiometer began acquiring routine science data on March 31, 2015 and continues to operate nominally. SMAPs radiometer-derived standard soil moisture product (L2SMP) provides soil moisture estimates posted on a 36-km fixed Earth grid using brightness temperature observations and ancillary data. A beta quality version of L2SMP was released to the public in October, 2015, Version 3 validated L2SMP soil moisture data were released in May, 2016, and Version 4 L2SMP data were released in December, 2016. Version 4 data are processed using the same soil moisture retrieval algorithms as previous versions, but now include retrieved soil moisture from both the 6 am descending orbits and the 6 pm ascending orbits. Validation of 19 months of the standard L2SMP product was done for both AM and PM retrievals using in situ measurements from global core cal/val sites. Accuracy of the soil moisture retrievals averaged over the core sites showed that SMAP accuracy requirements are being met.


Remote Sensing of Environment | 2012

Land Surface Temperature product validation using NOAA's surface climate observation networks—Scaling methodology for the Visible Infrared Imager Radiometer Suite (VIIRS)

Pierre Guillevic; Jeffrey L. Privette; Benoit Coudert; Michael A. Palecki; Jérôme Demarty; Catherine Ottlé; John A. Augustine


Remote Sensing of Environment | 2018

Development and assessment of the SMAP enhanced passive soil moisture product

Steven Chan; Rajat Bindlish; Peggy E. O'Neill; Thomas J. Jackson; Eni G. Njoku; S. Dunbar; Julian Chaubell; Jeffrey R. Piepmeier; Simon H. Yueh; Dara Entekhabi; Andreas Colliander; F. Chen; Michael H. Cosh; Todd G. Caldwell; Jeffrey P. Walker; Aaron A. Berg; Heather McNairn; M. Thibeault; F. Uldall; Mark S. Seyfried; David D. Bosch; Patrick J. Starks; C. D. Holifield Collins; John H. Prueger; R. van der Velde; Jun Asanuma; Michael A. Palecki; Eric E. Small; Marek Zreda; Jean-Christophe Calvet


Vadose Zone Journal | 2015

Evaluation of the 2012 Drought with a Newly Established National Soil Monitoring Network

Jesse E. Bell; Ronald D. Leeper; Michael A. Palecki; Evan J. Coopersmith; Tim Wilson; Rocky Bilotta; Scott Embler


Vadose Zone Journal | 2013

U.S. Climate Reference Network Soil Moisture Observations with Triple Redundancy: Measurement Variability

Michael A. Palecki; Jesse E. Bell

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Dara Entekhabi

Massachusetts Institute of Technology

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David D. Bosch

Agricultural Research Service

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Jesse E. Bell

North Carolina State University

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John H. Prueger

Agricultural Research Service

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Mark S. Seyfried

Agricultural Research Service

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Michael H. Cosh

Agricultural Research Service

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Patrick J. Starks

Agricultural Research Service

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Peggy E. O'Neill

Goddard Space Flight Center

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