Geology Research Works

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    Using Satellite Data to Represent Tropical Instability Waves (TIWs)-Induced Wind for Ocean Modeling: A Negative Feedback onto TIW Activity in the Pacific
    (MDPI, 2013-05-24) Zhang, Rong-Hua; Li, Zhongxian; Min, Jinzhong
    Recent satellite data and modeling studies indicate a pronounced role Tropical Instability Waves (TIW)-induced wind feedback plays in the tropical Pacific climate system. Previously, remotely sensed data were used to derive a diagnostic model for TIW-induced wind stress perturbations (τTIW), which was embedded into an ocean general circulation model (OGCM) to take into account TIW-induced ocean-atmosphere coupling in the tropical Pacific. While the previous paper by Zhang (2013) is concerned with the effect on the mean ocean state, the present paper is devoted to using the embedded system to examine the effects on TIW activity in the ocean, with τTIW being interactively determined from TIW-scale sea surface temperature (SSTTIW) fields generated in the OGCM, written as τTIW = αTIW·F(SSTTIW), where αTIW is a scalar parameter introduced to represent the τTIW forcing intensity. Sensitivity experiments with varying αTIW (representing TIW-scale wind feedback strength) are performed to illustrate a negative feedback induced by TIW-scale air-sea coupling and its relationship with TIW variability in the ocean. Consistent with previous modeling studies, TIW wind feedback tends to have a damping effect on TIWs in the ocean, with a general inverse relationship between the τTIW intensity and TIWs. It is further shown that TIW-scale coupling does not vary linearly with αTIW: the coupling increases linearly with intensifying τTIW forcing at low values of αTIW (in a weak τTIW forcing regime); it becomes saturated at a certain value of αTIW; it decreases when αTIW goes above a threshold value as the τTIW forcing increases further. This work presents a clear demonstration of using satellite data to effectively represent TIW-scale wind feedback and its multi-scale interactions with large-scale ocean processes in the tropical Pacific.
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    Urban Evolution: The Role of Water
    (MDPI, 2015-07-27) Kaushal, Sujay S.; McDowell, William H.; Wollheim, Wilfred M.; Newcomer Johnson, Tamara A.; Mayer, Paul M.; Belt, Kenneth T.; Pennino, Michael J.
    The structure, function, and services of urban ecosystems evolve over time scales from seconds to centuries as Earth’s population grows, infrastructure ages, and sociopolitical values alter them. In order to systematically study changes over time, the concept of “urban evolution” was proposed. It allows urban planning, management, and restoration to move beyond reactive management to predictive management based on past observations of consistent patterns. Here, we define and review a glossary of core concepts for studying urban evolution, which includes the mechanisms of urban selective pressure and urban adaptation. Urban selective pressure is an environmental or societal driver contributing to urban adaptation. Urban adaptation is the sequential process by which an urban structure, function, or services becomes more fitted to its changing environment or human choices. The role of water is vital to driving urban evolution as demonstrated by historical changes in drainage, sewage flows, hydrologic pulses, and long-term chemistry. In the current paper, we show how hydrologic traits evolve across successive generations of urban ecosystems via shifts in selective pressures and adaptations over time. We explore multiple empirical examples including evolving: (1) urban drainage from stream burial to stormwater management; (2) sewage flows and water quality in response to wastewater treatment; (3) amplification of hydrologic pulses due to the interaction between urbanization and climate variability; and (4) salinization and alkalinization of fresh water due to human inputs and accelerated weathering. Finally, we propose a new conceptual model for the evolution of urban waters from the Industrial Revolution to the present day based on empirical trends and historical information. Ultimately, we propose that water itself is a critical driver of urban evolution that forces urban adaptation, which transforms the structure, function, and services of urban landscapes, waterways, and civilizations over time.
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    Mesozoic subduction shaped lower mantle structures beneath the East Pacific Rise
    (2024) Wang, Jingchuan; Lekic, Vedran; Schmerr, Nicholas; Gu, Yu Jeffrey; Guo, Yi; Lin, Rongzhi; Lekic, Vedran; Schmerr, Nicholas
    The morphology of the Large Low Shear Velocity Provinces (LLSVPs) has been a subject of debate for decades. Large-scale features of the Pacific LLSVP, as revealed by cluster analysis of global tomographic models, suggest three distinct portions. Notably, the East Pacific Anomaly and the Superswell Anomaly are characterized by a ~20 deg wide gap. The cause of the structural gap remains unclear, and there has been no direct evidence for a subduction episode beneath the region. In this study, we take advantage of an up-to-date SS precursor data set that samples the Nazca Plate and investigate the high-resolution seismic structure at mantle transition zone (MTZ) depths. We find that much of the southern East Pacific Rise is underlain by a thin MTZ due to the depressed 410 by up to 15 km, which suggests along-ridge temperature variations extending into the MTZ. East of the East Pacific Rise, the MTZ is characterized by anomalous thickening and fast seismic velocities from seismic tomography, consistent with the presence of cold subducted slab material intersecting the MTZ. Furthermore, recent global tomographic models reveal a slab-like structure throughout the MTZ and lower mantle, which is also evidenced by tomographic vote maps, albeit with less visibility. The observations reconcile with Mesozoic intraoceanic subduction beneath the present-day Nazca Plate, which is predicted by an earlier plate reconstruction model of proto-Pacific Ocean. The subduction initiated ~250 Myr ago and ceased before 120 Myr ago. The implications of this discovery are that the shape of the eastern portion of the Pacific LLSVP was separated by downwelling associated with this ancient subducted slab.
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    Nutrient Retention in Restored Streams and Rivers: A Global Review and Synthesis
    (MDPI, 2016-03-25) Newcomer Johnson, Tamara A.; Kaushal, Sujay S.; Mayer, Paul M.; Smith, Rose M.; Sivirichi, Gwen M.
    Excess nitrogen (N) and phosphorus (P) from human activities have contributed to degradation of coastal waters globally. A growing body of work suggests that hydrologically restoring streams and rivers in agricultural and urban watersheds has potential to increase N and P retention, but rates and mechanisms have not yet been analyzed and compared across studies. We conducted a review of nutrient retention within hydrologically reconnected streams and rivers, including 79 studies. We developed a typology characterizing different forms of stream and river restoration, and we also analyzed nutrient retention across this typology. The studies we reviewed used a variety of methods to analyze nutrient cycling. We performed a further intensive meta-analysis on nutrient spiraling studies because this method was the most consistent and comparable between studies. A meta-analysis of 240 experimental additions of ammonium (NH4+), nitrate (NO3−), and soluble reactive phosphorus (SRP) was synthesized from 15 nutrient spiraling studies. Our results showed statistically significant relationships between nutrient uptake in restored streams and specific watershed attributes. Nitrate uptake metrics were significantly related to watershed surface area, impervious surface cover, and average reach width (p < 0.05). Ammonium uptake metrics were significantly related to discharge, velocity, and transient storage (p < 0.05). SRP uptake metrics were significantly related to watershed area, discharge, SRP concentrations, and chl a concentrations (p < 0.05). Given that most studies were conducted during baseflow, more research is necessary to characterize nutrient uptake during high flow. Furthermore, long-term studies are needed to understand changes in nutrient dynamics as projects evolve over time. Overall analysis suggests the size of the stream restoration (surface area), hydrologic connectivity, and hydrologic residence time are key drivers influencing nutrient retention at broader watershed scales and along the urban watershed continuum.
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    Satellite Climate Data Records: Development, Applications, and Societal Benefits
    (MDPI, 2016-04-15) Yang, Wenze; John, Viju O.; Zhao, Xuepeng; Lu, Hui; Knapp, Kenneth R.
    This review paper discusses how to develop, produce, sustain, and serve satellite climate data records (CDRs) in the context of transitioning research to operation (R2O). Requirements and critical procedures of producing various CDRs, including Fundamental CDRs (FCDRs), Thematic CDRs (TCDRs), Interim CDRs (ICDRs), and climate information records (CIRs) are discussed in detail, including radiance/reflectance and the essential climate variables (ECVs) of land, ocean, and atmosphere. Major international CDR initiatives, programs, and projects are summarized. Societal benefits of CDRs in various user sectors, including Agriculture, Forestry, Fisheries, Energy, Heath, Water, Transportation, and Tourism are also briefly discussed. The challenges and opportunities for CDR development, production and service are also addressed. It is essential to maintain credible CDR products by allowing free access to products and keeping the production process transparent by making source code and documentation available with the dataset.
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    Phosphorus Retention in Stormwater Control Structures across Streamflow in Urban and Suburban Watersheds
    (MDPI, 2016-09-09) Duan, Shuiwang; Newcomer-Johnson, Tamara; Mayer, Paul; Kaushal, Sujay
    Recent studies have shown that stormwater control measures (SCMs) are less effective at retaining phosphorus (P) than nitrogen. We compared P retention between two urban/suburban SCMs and their adjacent free-flowing stream reaches at the Baltimore Long-Term Ecological Study (LTER) site, and examined changes in P retention in SCMs across flow conditions. Results show that, when compared with free-flowing stream reaches, the SCMs had significantly lower dissolved oxygen (%DO) and higher P concentrations, as well as lower mean areal retention rates and retention efficiencies of particulate P (PP). In all the SCMs, concentrations of total dissolved phosphorus (TDP) consistently exhibited inverse correlations with %DO that was lower during summer base flows. Particulate phosphorus (PP) concentrations peaked during spring high flow period in both streams and in-line pond/SCMs, but they were also higher during summer base flows in suburban/urban SCMs. Meanwhile, PP areal retention rates and retention efficiencies of the SCMs changed from positive (indicating retention) during high flows to negative (indicating release) during low flows, while such changes across flow were not observed in free-flowing stream reaches. We attribute the changing roles of SCMs from a PP sink to a PP source to changes in SCM hydrologic mass balances, physical sedimentation and biogeochemical mobilization across flows. This study demonstrates that in suburban/urban SCMs, P retained during high flow events can be released during low flows. Cultivation of macrophytes and/or frequent sediment dredging may provide potential solutions to retaining both P and nitrogen in urban SCMs.
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    Land Use, Climate, and Water Resources—Global Stages of Interaction
    (MDPI, 2017-10-24) Kaushal, Sujay S.; Gold, Arthur J.; Mayer, Paul M.
    Land use and climate change can accelerate the depletion of freshwater resources that support humans and ecosystem services on a global scale. Here, we briefly review studies from around the world, and highlight those in this special issue. We identify stages that characterize increasing interaction between land use and climate change. During the first stage, hydrologic modifications and the built environment amplify overland flow via processes associated with runoff-dominated ecosystems (e.g., soil compaction, impervious surface cover, drainage, and channelization). During the second stage, changes in water storage impact the capacity of ecosystems to buffer extremes in water quantity and quality (e.g., either losses in snowpack, wetlands, and groundwater recharge or gains in water and nutrient storage behind dams in reservoirs). During the third stage, extremes in water quantity and quality contribute to losses in ecosystem services and water security (e.g., clean drinking water, flood mitigation, and habitat availability). During the final stage, management and restoration strategies attempt to regain lost ecosystem structure, function, and services but need to adapt to climate change. By anticipating the increasing interaction between land use and climate change, intervention points can be identified, and management strategies can be adjusted to improve outcomes for realistic expectations. Overall, global water security cannot be adequately restored without considering an increasing interaction between land use and climate change across progressive stages and our ever-increasing human domination of the water cycle from degradation to ecosystem restoration.
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    The Global Precipitation Climatology Project (GPCP) Monthly Analysis (New Version 2.3) and a Review of 2017 Global Precipitation
    (MDPI, 2018-04-07) Adler, Robert F.; Sapiano, Mathew R. P.; Huffman, George J.; Wang, Jian-Jian; Gu, Guojun; Bolvin, David; Chiu, Long; Schneider, Udo; Becker, Andreas; Nelkin, Eric; Xie, Pingping; Ferraro, Ralph; Shin, Dong-Bin
    The new Version 2.3 of the Global Precipitation Climatology Project (GPCP) Monthly analysis is described in terms of changes made to improve the homogeneity of the product, especially after 2002. These changes include corrections to cross-calibration of satellite data inputs and updates to the gauge analysis. Over-ocean changes starting in 2003 resulted in an overall precipitation increase of 1.8% after 2009. Updating the gauge analysis to its final, high-quality version increases the global land total by 1.8% for the post-2002 period. These changes correct a small, incorrect dip in the estimated global precipitation over the last decade given by the earlier Version 2.2. The GPCP analysis is also used to describe global precipitation in 2017. The general La Niña pattern for 2017 is noted and the evolution from the early 2016 El Niño pattern is described. The 2017 global value is one of the highest for the 1979–2017 period, exceeded only by 2016 and 1998 (both El Niño years), and reinforces the small positive trend. Results for 2017 also reinforce significant trends in precipitation intensity (on a monthly scale) in the tropics. These results for 2017 indicate the value of the GPCP analysis, in addition to research, for climate monitoring.
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    Maximizing the Information Content of Ill-Posed Space-Based Measurements Using Deterministic Inverse Method
    (MDPI, 2018-06-22) Koner, Prabhat K.; Dash, Prasanjit
    For several decades, operational retrievals from spaceborne hyperspectral infrared sounders have been dominated by stochastic approaches where many ambiguities are pervasive. One major drawback of such methods is their reliance on treating error as definitive information to the retrieval scheme. To overcome this drawback and obtain consistently unambiguous retrievals, we applied another approach from the class of deterministic inverse methods, namely regularized total least squares (RTLS). As a case study, simultaneous simulated retrieval of ozone (O3) profile and surface temperature (ST) for two different instruments, Cross-track Infrared Sounder (CrIS) and Tropospheric Emission Spectrometer (TES), are considered. To gain further confidence in our approach for real-world situations, a set of ozonesonde profile data are also used in this study. The role of simulation-based comparative assessment of algorithms before application on remotely sensed measurements is pivotal. Under identical simulation settings, RTLS results are compared to those of stochastic optimal estimation method (OEM), a very popular method for hyperspectral retrievals despite its aforementioned fundamental drawback. Different tweaking of error covariances for improving the OEM results, used commonly in operations, are also investigated under a simulated environment. Although this work is an extension of our previous work for H2O profile retrievals, several new concepts are introduced in this study: (a) the information content analysis using sub-space analysis to understand ill-posed inversion in depth; (b) comparison of different sensors for same gas profile retrieval under identical conditions; (c) extended capability for simultaneous retrievals using two classes of variables; (d) additional stabilizer of Laplacian second derivative operator; and (e) the representation of results using a new metric called “information gain”. Our findings highlight issues with OEM, such as loss of information as compared to a priori knowledge after using measurements. On the other hand, RTLS can produce “information gain” of ~40–50% deterministically from the same set of measurements.
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    Hydrological Evaluation of Flow Diversion Terraces Using Downhill-Slope Calculation Method for High Resolution and Accuracy DEMs
    (MDPI, 2018-07-11) Qi, Junyu; Liang, Kang; Li, Sheng; Wang, Lichun; Meng, Fan-Rui
    Slope is an important topographical parameter in hydrological models. Dramatic changes in slope are produced due to micro variations of topography in flow diversion terrace (FDT) systems. Assessing the effectiveness of FDT on soil conservation yields different results using different slope calculation methods with different resolution and accuracy digital elevation models (DEMs). In this study, the ArcGIS built-in average-neighborhood-slope (ANS) method and a downhill-slope (DHS) method were used to calculate slopes for a small agricultural watershed in New Brunswick, Canada. Six DEMs were used, i.e., 1, 5 and 10 m resolution DEMs generated with conventional photogrammetric techniques, and 1, 5, and 10 m resolution DEMs derived from light detection and ranging (LiDAR) data. Calculated slopes were summarized for the whole watershed, a patch of FDT systems, and grassed flow channels in front of embankments in the patch. Results indicated that the DHS method produced smaller slopes than the ANS method with LiDAR-1m DEM along grasses flow channels. Furthermore, the mean L-factor derived from the DHS method was smaller than that derived from the ANS in terraces and grassed flow channels for the LiDAR-1m DEM. Finally, soil loss estimated from the DHS method using RUSLE was more consistent with measurement for the watershed than that from the ANS method when the LiDAR-1m DEM was used. The DHS method can provide accurate slopes along grassed flow channels and can be used to assess FDT systems using USLE-based models with high resolution and accuracy DEMs.
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    The VIIRS Sea-Ice Albedo Product Generation and Preliminary Validation
    (MDPI, 2018-11-17) Peng, Jingjing; Yu, Yunyue; Yu, Peng; Liang, Shunlin
    Ice albedo feedback amplifies climate change signals and thus affects the global climate. Global long-term records on sea-ice albedo are important to characterize the regional or global energy budget. As the successor of MODIS (Moderate Resolution Imaging Spectroradiometer), VIIRS (Visible Infrared Imaging Radiometer Suite) started its observation from October 2011 on S-NPP (Suomi National Polar-orbiting Partnership). It has improved upon the capabilities of the operational Advanced Very High Resolution Radiometer (AVHRR) and provides observation continuity with MODIS. We used a direct estimation algorithm to produce a VIIRS sea-ice albedo (VSIA) product, which will be operational in the National Oceanic and Atmospheric Administration’s (NOAA) S-NPP Data Exploration (NDE) version of the VIIRS albedo product. The algorithm is developed from the angular bin regression method to simulate the sea-ice surface bidirectional reflectance distribution function (BRDF) from physical models, which can represent different sea-ice types and vary mixing fractions among snow, ice, and seawater. We compared the VSIA with six years of ground measurements at 30 automatic weather stations from the Programme for Monitoring of the Greenland Ice Sheet (PROMICE) and the Greenland Climate Network (GC-NET) as a proxy for sea-ice albedo. The results show that the VSIA product highly agreed with the station measurements with low bias (about 0.03) and low root mean square error (RMSE) (about 0.07) considering the Joint Polar Satellite System (JPSS) requirement is 0.05 and 0.08 at 4 km scale, respectively. We also evaluated the VSIA using two datasets of field measured sea-ice albedo from previous field campaigns. The comparisons suggest that VSIA generally matches the magnitude of the ground measurements, with a bias of 0.09 between the instantaneous albedos in the central Arctic and a bias of 0.077 between the daily mean albedos near Alaska. The discrepancy is mainly due to the scale difference at both spatial and temporal dimensions and the limited sample size. The VSIA data will serve for weather prediction applications and climate model calibrations. Combined with the historical observations from MODIS, current S-NPP VIIRS, and NOAA-20 VIIRS observations, VSIA will dramatically contribute to providing high-accuracy routine sea-ice albedo products and irreplaceable records for monitoring the long-term sea-ice albedo for climate research.
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    Impact of Snow Darkening by Deposition of Light-Absorbing Aerosols on Snow Cover in the Himalayas–Tibetan Plateau and Influence on the Asian Summer Monsoon: A Possible Mechanism for the Blanford Hypothesis
    (MDPI, 2018-11-12) Lau, William K. M.; Kim, Kyu-Myong
    The impact of snow darkening by deposition of light-absorbing aerosols (LAAs) on snow cover over the Himalayas–Tibetan Plateau (HTP) and the influence on the Asian summer monsoon were investigated using the NASA Goddard Earth Observing System Model Version 5 (GEOS-5). The authors found that during April–May–June, the deposition of LAAs on snow led to a reduction in surface albedo, initiating a sequence of feedback processes, starting with increased net surface solar radiation, rapid snowmelt in the HTP and warming of the surface and upper troposphere, followed by enhanced low-level southwesterlies and increased dust loading over the Himalayas–Indo-Gangetic Plain. The warming was amplified by increased dust aerosol heating, and subsequently amplified by latent heating from enhanced precipitation over the Himalayan foothills and northern India, via the elevated heat pump (EHP) effect during June–July–August. The reduced snow cover in the HTP anchored the enhanced heating over the Tibetan Plateau and its southern slopes, in conjunction with an enhancement of the Tibetan Anticyclone, and the development of an anomalous Rossby wave train over East Asia, leading to a weakening of the subtropical westerly jet, and northward displacement and intensification of the Mei-Yu rain belt. The authors’ results suggest that the atmosphere-land heating induced by LAAs, particularly desert dust, plays a fundamental role in physical processes underpinning the snow–monsoon relationship proposed by Blanford more than a century ago.
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    Assessment of Himawari-8 AHI Aerosol Optical Depth Over Land
    (MDPI, 2019-05-09) Zhang, Wenhao; Xu, Hui; Zhang, Lili
    This study conducted the first comprehensive assessment of the aerosol optical depth (AOD) product retrieved from the observations by the Advanced Himawari Imager (AHI) onboard the Himawari-8 satellite. The AHI Level 3 AOD (Version 3.0) was evaluated using the collocated Aerosol Robotic Network (AERONET) level 2.0 direct sun AOD measurements over the last three years (May 2016–December 2018) at 58 selected AERONET sites. A comprehensive comparison between AHI and AERONET AOD was carried out, which yielded a correlation coefficient (R) of 0.82, a slope of 0.69, and a root mean square error (RMSE) of 0.16. The results indicate a good agreement between AHI and AERONET AOD, while revealing that the AHI aerosol retrieval algorithm tends to underestimate the atmospheric aerosol load. In addition, the expected uncertainty of AHI Level 3 AOD (Version 3.0) is ± (0.1 + 0.3 × AOD). Furthermore, the performance of the AHI aerosol retrieval algorithm exhibits regional variation. The best performance is reported over East Asia (R 0.86), followed by Southeast Asia (R 0.79) and Australia (R 0.35). The monthly and seasonal comparisons between AHI and AERONET show that the best performance is found in summer (R 0.93), followed by autumn (R 0.84), winter (R 0.82), and spring (R 0.76). The worst performance was observed in March (R 0.75), while the best performance appeared in June (R 0.94). The variation in the annual mean AHI AOD on the scale of hours demonstrates that AHI can perform continuous (no less than ten hours) aerosol monitoring.
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    Evapotranspiration Data Product from NESDIS GET-D System Upgraded for GOES-16 ABI Observations
    (MDPI, 2019-11-12) Fang, Li; Zhan, Xiwu; Schull, Mitchell; Kalluri, Satya; Laszlo, Istvan; Yu, Peng; Carter, Corinne; Hain, Christopher; Anderson, Martha
    Evapotranspiration (ET) is a major component of the global and regional water cycle. An operational Geostationary Operational Environmental Satellite (GOES) ET and Drought (GET-D) product system has been developed by the National Environmental Satellite, Data and Information Service (NESDIS) in the National Oceanic and Atmospheric Administration (NOAA) for numerical weather prediction model validation, data assimilation, and drought monitoring. GET-D system was generating ET and Evaporative Stress Index (ESI) maps at 8 km spatial resolution using thermal observations of the Imagers on GOES-13 and GOES-15 before the primary operational GOES satellites transitioned to GOES-16 and GOES-17 with the Advanced Baseline Imagers (ABI). In this study, the GET-D product system is upgraded to ingest the thermal observations of ABI with the best spatial resolution of 2 km. The core of the GET-D system is the Atmosphere-Land Exchange Inversion (ALEXI) model, which exploits the mid-morning rise in the land surface temperature to deduce the land surface fluxes including ET. Satellite-based land surface temperature and solar insolation retrievals from ABI and meteorological forcing from NOAA NCEP Climate Forecast System (CFS) are the major inputs to the GET-D system. Ancillary data required in GET-D include land cover map, leaf area index, albedo and cloud mask. This paper presents preliminary results of ET from the upgraded GET-D system after a brief introduction of the ALEXI model and the architecture of GET-D system. Comparisons with in situ ET measurements showed that the accuracy of the GOES-16 ABI based ET is similar to the results from the legacy GET-D ET based on GOES-13/15 Imager data. The agreement with the in situ measurements is satisfactory with a correlation of 0.914 averaged from three Mead sites. Further evaluation of the ABI-based ET product, upgrade efforts of the GET-D system for ESI products, and conclusions for the ABI-based GET-D products are discussed.
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    Comparison of the Remapping Algorithms for the Advanced Technology Microwave Sounder (ATMS)
    (MDPI, 2020-02-18) Zhou, Jun; Yang, Hu
    One of the limitations in using spaceborne, microwave radiometer data for atmospheric remote sensing is the nonuniform spatial resolution. Remapping algorithms can be applied to the data to ameliorate this limitation. In this paper, two remapping algorithms, the Backus–Gilbert inversion (BGI) technique and the filter algorithm (AFA), widely used in the operational data preprocessing of the Advanced Technology Microwave Sounder (ATMS), are investigated. The algorithms are compared using simulations and actual ATMS data. Results show that both algorithms can effectively enhance or degrade the resolution of the data. The BGI has a higher remapping accuracy than the AFA. It outperforms the AFA by producing less bias around coastlines and hurricane centers where the signal changes sharply. It shows no obvious bias around the scan ends where the AFA has a noticeable positive bias in the resolution-enhanced image. However, the BGI achieves the resolution enhancement at the expense of increasing the noise by 0.5 K. The use of the antenna pattern instead of the point spread function in the algorithm causes the persistent bias found in the AFA-remapped image, leading not only to an inaccurate antenna temperature expression but also to the neglect of the geometric deformation of the along-scan field-of-views.
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    Scale Impact of Soil Moisture Observations to Noah-MP Land Surface Model Simulations
    (MDPI, 2020-04-06) Yin, Jifu; Zhan, Xiwu
    Due to the limitations of satellite antenna technology, current operational microwave soil moisture (SM) data products are typically at tens of kilometers spatial resolutions. Many approaches have thus been proposed to generate finer resolution SM data using ancillary information, but it is still unknown if assimilation of the finer spatial resolution SM data has beneficial impacts on model skills. In this paper, a synthetic experiment is thus conducted to identify the benefits of SM observations at a finer spatial resolution on the Noah-MP land surface model. Results of this study show that the performance of the Noah-MP model is significantly improved with the benefits of assimilating 1 km SM observations in comparison with the assimilation of SM data at coarser resolutions. Downscaling satellite microwave SM observations from coarse spatial resolution to 1 km resolution is recommended, and the assimilation of 1 km remotely sensed SM retrievals is suggested for NOAA National Weather Service and National Water Center.
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    A Study of Lunar Microwave Radiation Based on Satellite Observations
    (MDPI, 2020-04-02) Yang, Hu; Burgdorf, Martin
    In recent years, the study of microwave radiation from the Moon’s surface has been of interest to the astronomy and remote sensing communities. Due to the stable geophysical properties of the Moon’s surface, microwave lunar radiation is highly predictable and can be accurately modeled, given sufficient observations from reliable instruments. Specifically, for microwave remote sensing study, if International System of Unit (SI) traceable observations of the Moon are available, the Moon can thus be used as an SI traceable calibration reference for microwave instruments to evaluate their calibration accuracies and assess their long-term calibration stabilities. Major challenges of using the Moon as a radiometric source standard for microwave sensors include the uncertainties in antenna pattern measurements, the reliability of measurements of brightness temperature (Tb) in the microwave spectrum of the lunar surface, and knowledge of the lunar phase lag because of penetration depths at different detection frequencies. Most microwave-sounding instruments can collect lunar radiation data from space-view observations during so-called lunar intrusion events that usually occur several days each month. Addressed in this work based on Moon observations from the Advanced Technology Microwave Sounder and the Advanced Microwave Sounding Unit/Microwave Humidity Sounder are two major issues in lunar calibration: the lunar surface microwave Tb spectrum and phase lag. The scientific objective of this study is to present our most recent progress on the study of lunar microwave radiation based on satellite observations. Reported here are the lunar microwave Tb spectrum and phase lag from 23 to 183 GHz based on observations of microwave-sounding instruments onboard different satellite platforms. For current Moon microwave radiation research, this study can help toward better understanding lunar microwave radiation features over a wide spectrum range, laying a solid foundation for future lunar microwave calibration efforts.
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    NOAA Satellite Soil Moisture Operational Product System (SMOPS) Version 3.0 Generates Higher Accuracy Blended Satellite Soil Moisture
    (MDPI, 2020-09-03) Yin, Jifu; Zhan, Xiwu; Liu, Jicheng
    Soil moisture plays a vital role for the understanding of hydrological, meteorological, and climatological land surface processes. To meet the need of real time global soil moisture datasets, a Soil Moisture Operational Product System (SMOPS) has been developed at National Oceanic and Atmospheric Administration to produce a one-stop shop for soil moisture observations from all available satellite sensors. What makes the SMOPS unique is its near real time global blended soil moisture product. Since the first version SMOPS publicly released in 2010, the SMOPS has been updated twice based on the users’ feedbacks through improving retrieval algorithms and including observations from new satellite sensors. The version 3.0 SMOPS has been operationally released since 2017. Significant differences in climatological averages lead to remarkable distinctions in data quality between the newest and the older versions of SMOPS blended soil moisture products. This study reveals that the SMOPS version 3.0 has overwhelming advantages of reduced data uncertainties and increased correlations with respect to the quality controlled in situ measurements. The new version SMOPS also presents more robust agreements with the European Space Agency’s Climate Change Initiative (ESA_CCI) soil moisture datasets. With the higher accuracy, the blended data product from the new version SMOPS is expected to benefit the hydrological, meteorological, and climatological researches, as well as numerical weather, climate, and water prediction operations.
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    Developing Sensor Proxies for “Chemical Cocktails” of Trace Metals in Urban Streams
    (MDPI, 2020-10-14) Morel, Carol J.; Kaushal, Sujay S.; Tan, Maggie L.; Belt, Kenneth T.
    Understanding transport mechanisms and temporal patterns in the context of metal concentrations in urban streams is important for developing best management practices and restoration strategies to improve water quality. In some cases, in-situ sensors can be used to estimate unknown concentrations of trace metals or to interpolate between sampling events. Continuous sensor data from the United States Geological Survey were analyzed to determine statistically significant relationships between lead, copper, zinc, cadmium, and mercury with turbidity, specific conductance, dissolved oxygen, and discharge for the Hickey Run, Watts Branch, and Rock Creek watersheds in the Washington, D.C. region. We observed a significant negative linear relationship between concentrations of Cu and dissolved oxygen at Rock Creek (p < 0.05). Sometimes, turbidity had significant positive linear relationships with Pb and Hg concentrations. There were negative or positive linear relationships between Pb, Cd, Zn, and Hg and specific conductance. There also appeared to be relationships between watershed areal fluxes of Pb, Cu, Zn, and Cd in streams with turbidity. Watershed monitoring approaches using continuous sensor data have the potential to characterize the frequency, magnitude, and composition of pulses in concentrations and loads of trace metals, which could improve the management and restoration of urban streams.
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    Development of a Machine Learning-Based Radiometric Bias Correction for NOAA’s Microwave Integrated Retrieval System (MiRS)
    (MDPI, 2020-09-26) Zhou, Yan; Grassotti, Christopher
    We present the development of a dynamic over-ocean radiometric bias correction for the Microwave Integrated Retrieval System (MiRS) which accounts for spatial, temporal, spectral, and angular dependence of the systematic differences between observed and forward model-simulated radiances. The dynamic bias correction, which utilizes a deep neural network approach, is designed to incorporate dependence on the atmospheric and surface conditions that impact forward model biases. The approach utilizes collocations of observed Suomi National Polar-orbiting Partnership/Advanced Technology Microwave Sounder (SNPP/ATMS) radiances and European Centre for Medium-Range Weather Forecasts (ECMWF) model analyses which are used as input to the Community Radiative Transfer Model (CRTM) forward model to develop training data of radiometric biases. Analysis of the neural network performance indicates that in many channels, the dynamic bias is able to reproduce realistically both the spatial patterns of the original bias and its probability distribution function. Furthermore, retrieval impact experiments on independent data show that, compared with the baseline static bias correction, using the dynamic bias correction can improve temperature and water vapor profile retrievals, particularly in regions with higher Cloud Liquid Water (CLW) amounts. Ocean surface emissivity retrievals are also improved, for example at 23.8 GHz, showing an increase in correlation from 0.59 to 0.67 and a reduction of standard deviation from 0.035 to 0.026.