Soil hydrology is a widely recognized low-pass filter for the interaction between land and atmosphere. However, the lack of adequate long-term measured data on soil moisture profiles has precluded ...examination of how soil wetness responds to long-term precipitation variations. Such a response can be characterized by its amplitude damping, phase shifting, and increasing persistence with soil depth. These should be correlated with the climate spectra through the interactions between the land and the atmosphere. The major objective of this study is to investigate how precipitation signals are manifested in vertical soil moisture profiles in the context of timescales. Thus, the natural variability of soil moisture profiles is documented using 16 yr of field observational data of soil moisture measured at 11 levels of various depths down to 2.0 m at 17 locations over Illinois. Detailed statistic analyses are made of the temporal variations of soil moisture profiles and concurrently measured precipitation over the 16-yr period of 1981–96. Cross-spectral analysis is performed to obtain the coherency pattern and phase correlation of surface and profile soil moisture time series to determine phase shift and amplitude damping. A composite of the drought events during this time period is analyzed and compared with the 16-yr climatology. The major findings are that 1) the amplitude decreases with soil depth, with the dryness signal penetrating more deeply than the wetness signal; 2) the phase shift with soil depth is correlated with the timescales of the variation, such that it is deeper with longer timescales; and 3) the seasonal variation of soil moisture is amplified in the drought-year composite, with an increased phase shift from soil surface to bottom. Hence, the observations provide a description of the soil moisture profile variability as a function of soil depth. Whether or not climate models can reproduce this variability should be a good test of their land process representations in the treatment of soil hydrology.
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BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
•4 derivatives were obtained by structural modification of the “triketone” moiety of UA.•The single crystal of the Cu(II) complex of the hydrolyzed mono-substituted 4 was obtained.•Derivatives 1–4 ...had much better antioxidant and anti-cholinesterase activities than UA.•Derivatives 1–4 had good metal chelating abilities.•The metal complexes of derivatives also have good anti-AD and anti-oxidative activities.
More and more evidence suggested that bio-metals including iron, zinc and copper play an important role in Alzheimer's disease (AD). Metal chelation agents may play an important role through promoting the metal homeostasis for AD treatment. In this study, UA (usnic acid), a natural product with antioxidant activity and metal chelation sites was selected as a lead compound. Different types of tertiary amine groups were introduced to synthesize four UA derivatives 1–4 as metal chelators and cholinesterase inhibitors since tertiary amine moiety was the key pharmacophore to inhibit cholinesterase. And the related activities such as antioxidant, anti-cholinesterase and metal chelation were evaluated. Results showed that 1–4 displayed excellent anti-oxidant activity, with lowest IC50 of 0.433 µM for ·OH scavenging ability and 8.808 µM for ·O2− scavenging ability. The mechanisms of anti-oxidant activities were furtherly studied by cyclic voltammetry. Besides, 1–4 also showed good anti-cholinesterase activities with lowest IC50 of 0.269 µM for acetylcholinesterase (AChE) and 0.361 µM for butyrylcholinesterase (BuChE). The results of molecular docking with AChE and BuChE were consistent with the experimental results. 1–4 displayed obvious chelating abilities with Cu(II) and Fe(III) by UV–vis spectra analysis and the metal complexes also showed good anti-AD activities. Interestingly, single crystal of Cu(II) complex of the hydrolyzed mono-substituted ligand was obtained which further substantiated the metal binding ability and provided clues to the anti-AD activities of the metal complex. Meanwhile, hydrolysis ratio of 4 was also tested by HPLC. Finally, BBB permeability of 1–4 was acceptable by ADMET prediction. Overall, these findings demonstrated that compounds 1–4 might be considered as potential candidates in the anti-AD therapy.
Four derivatives (1–4) of UA had excellent metal chelating, antioxidant and anti-cholinesterase activities related AD. The single crystal of the Cu(II) complex of the hydrolyzed mono-substituted 4 was obtained and the metal complexes also have good anti-AD activities. Display omitted
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
This study evaluated 24-, 6-, and 1-h radar precipitation estimated from the National Mosaic and Multisensor Quantitative Precipitation Estimation System (NMQ) and the Weather Surveillance Radar-1988 ...Doppler (WSR-88D) Precipitation Processing System (PPS) over the conterminous United States (CONUS) for the warm season April–September 2009 and the cool season October 2009–March 2010. Precipitation gauge observations from the Automated Surface Observing System (ASOS) were used as the ground truth. Gridded StageIV multisensor precipitation estimates were applied for supplementary verification. The comparison of the two systems consisted of a series of analyses including the linear correlation coefficient (CC) and the root-mean-square error (RMSE) between the radar precipitation estimates and the gauge observations, large precipitation amount detection categorical scores, and the reliability of precipitation amount distribution. Data stratified for the 12 CONUS River Forecast Centers (RFCs) and for the cold rains events with bright-band effects were analyzed additionally. Major results are 1) the linear CC of NMQ versus ASOS are generally higher than that of PPS versus ASOS over CONUS, while the spatial variations stratified by the RFCs may switch with seasons; 2) compared to the precipitation distribution of ASOS, NMQ shows less deviation than PPS; 3) for the cold rains verified against ASOS, NMQ has higher CC and PPS has lower RMSE for 6-h and higher RMSE for 1-h cold rains; and 4) for the precipitation detection categorical scores, either NMQ or PPS can be superior, depending on the time interval and season. The verification against StageIV gridded precipitation estimates showed that NMQ consistently had higher correlations and lower biases than did PPS.
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BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Hydrologic models operated by the National Weather Service call for an accurate, consistent, high‐resolution, multi‐decade, continental‐scale record of hydrometeorological fields to serve as forcing ...data for model calibration. To serve this purpose, the Analysis of Record for Calibration was developed, and version 1.1 of the dataset is described in this study. Geospatial and scientific requirements, methods used in dataset generation, and input data sources are described. Given the prominent role of precipitation in model calibration, accurate and consistent precipitation is a particularly high priority for the analysis. To evaluate the analysis from this perspective, its daily precipitation is compared with surface observing stations over 43 years. The analysis exhibits low bias compared with other similar products. It also displays nonstationary bias behavior after 2015 due to the lack of a climatological constraint, as well as frequent occurrences of heavy‐to‐extreme precipitation that are often difficult to verify. These findings should be taken into account when the product is used for model calibration.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
The warm‐season rainfall variability over the US Great Plains is examined in a climate simulation and compared with observations to explore the role of land‐atmosphere interaction in the model. The ...results show that compared to observations, the model simulations underestimate summertime rainfall by more than 12% but overestimate its standard deviation by 25–54%, with the larger value referring to interannual variability. Linear regression shows that the rainfall variability is connected with evapotranspiration (ET) anomalies, but mostly to evaporation rather than transpiration. Since the evaporation represents an immediate response of the land surface to atmospheric conditions but the transpiration reflects soil moisture memory with considerably longer time scales, the realism of the correlated variability between separate ET components and precipitation is an important aspect of how climate models realistically address land‐atmosphere interaction.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
The National Weather Service (NWS) Office of Water Prediction (OWP), in conjunction with the National Center for Atmospheric Research and the NWS National Centers for Environmental Prediction (NCEP) ...implemented version 2.1 of the National Water Model (NWM) into operations in April of 2021. As with the initial version implemented in 2016, NWM v2.1 is an hourly cycling analysis and forecast system that provides streamflow guidance for millions of river reaches and other hydrologic information on high‐resolution grids. The NWM provides complementary hydrologic guidance at current NWS river forecast locations and significantly expands guidance coverage and water budget information in underserved locations. It produces a full range of hydrologic fields, which can be leveraged by a broad cross section of stakeholders ranging from the emergency responder and water resource communities, to transportation, energy, recreation and agriculture interests, to other water‐oriented applications in the government, academic and private sectors. Version 2.1 of the NWM represents the fifth major version upgrade and more than doubles simulation skill with respect to hourly streamflow correlation, Nash Sutcliffe Efficiency, and bias reduction, over its original inception in 2016. This paper will discuss the driving factors underpinning the creation of the NWM, provide a brief overview of the model configuration and performance, and discuss future efforts to improve NWM components and services.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
The time scales of layered soil moisture memory in the Common Land Model (CLM) coupled with the National Center for Atmospheric Research Community Climate Model, version 3 (NCAR CCM3) have been ...examined using a 50-yr climate simulation. Such soil moisture memory has been characterized in terms of the spatial, seasonal, and vertical variations of 1-month-lag autocorrelation coefficients and the correspondinge-folding decay time scales. To understand this land memory mechanism, in terms of the variations that occur in the model, a cross-spectral analysis has been applied to the soil moisture profile with precipitation (P), runoff (R), evapotranspiration (ET), transpiration, and the residual ofP– ET –R, respectively, together with an examination of the surface water budget of the annual cycle. These collectively provide physical insights on time scales of layered soil moisture memory in the context of land–atmosphere interaction. The major findings are: 1) soil moisture memory in warm climates can be at least several times longer for drier conditions than when it is sufficiently rainy; and 2) under wet conditions the time scales of soil moisture appear to be controlled by temperature-dependent climatic demand; but for drier conditions they appear to depend largely on increasing time scales for the coupling of soil moisture to ET and especially runoff.
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BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Observations have described soil moisture profile variability in terms of phase shift, fluctuation damping, and persistence increasing with soil depth Wu et al., 2002. This variability as a function ...of soil depth couples to climate variability. Whether or not land models can reproduce this variability should be a good test of their parameterizations in soil hydrology both physically and numerically. A widely used multilayer land surface model was applied to simulate the soil moisture profile variability documented from observations to explore the sensitivity to various parameters and to evaluate the model performances through the detailed analysis of a case study. Sensitivity experiments assumed changes of (1) the initial soil moisture field; (2) the root sink term; (3) the soil texture; and (4) the atmospheric forcing at upper boundary. Their impacts on the soil moisture profile phase shift, amplitude damping, and corresponding evapotranspiration were examined. The key land surface prognostic variables, i.e., soil moisture and evapotranspiration, were evaluated against observations prior to the sensitivity integrations. All the factors that affected the soil moisture profile variability of amplitude damping and phase shift also influenced the amplitude and phase of evapotranspiration, suggesting that the simulation of soil moisture profile variability might be more important in the context of timescales than the soil wetness field itself.
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