25 research outputs found

    Relating surface backscatter response from TRMM precipitation radar to soil moisture: Results over a semi-arid region

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    The Tropical Rainfall Measuring Mission (TRMM) carries aboard the Precipitation Radar (TRMMPR) that measures the backscatter (σº) of the surface. σº is sensitive to surface soil moisture and vegetation conditions. Due to sparse vegetation in arid and semi-arid regions, TRMMPR σº primarily depends on the soil water content. In this study we relate TRMMPR σº measurements to soil water content (m(s)) in the Lower Colorado River Basin (LCRB). σº dependence on ms is studied for different vegetation greenness values determined through Normalized Difference Vegetation Index (NDVI). A new model of σº that couples incidence angle, m(s), and NDVI is used to derive parameters and retrieve soil water content. The calibration and validation of this model are performed using simulated and measured ms data. Simulated m(s) is estimated using the Variable Infiltration Capacity (VIC) model and measured m(s) is acquired from ground measuring stations in Walnut Gulch Experimental Watershed (WGEW). σº model is calibrated using VIC and WGEW m(s) data during 1998 and the calibrated model is used to derive m(s) during later years. The temporal trends of derived ms are consistent with VIC and WGEW ms data with a correlation coefficient (R) of 0.89 and 0.74, respectively. Derived ms is also consistent with the measured precipitation data with R=0.76. The gridded VIC data is used to calibrate the model at each grid point in LCRB and spatial maps of the model parameters are prepared. The model parameters are spatially coherent with the general regional topography in LCRB. TRMMPR σº derived soil moisture maps during May (dry) and August (wet) 1999 are spatially similar to VIC estimates with correlation 0.67 and 0.76, respectively. This research provides new insights into Ku-band σº dependence on soil water content in the arid regions

    Soil Moisture as an Indicator of Weather Extremes

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    In this paper, we investigate floods and droughts in the Upper Mississippi basin over a 50-year period (1950–1999) using a hydrological model (Variable Infiltration Capacity Model – 3 Layer). Simulations have been carried out between January 1950 and December 1999 at daily time-step and 1/8° spatial resolution for the water budget and at hourly time-step and 1° spatial resolution for the energy balance. This paper will provide valuable insights to the slow response components of the hydrological cycle and its diagnostic/predictive value in the case of floods and droughts. The paper compares the use of the Palmer Drought Severity Index against the anomalies of the third layer soil moisture for characterizing droughts and floods. Wavelet and coherency analysis is performed on the soil moisture, river discharge, precipitation and PDSI time series confirm our hypothesis of a strong relationship between droughts and the third layer soil moisture

    Relationships between climate variability, drought and model soil moisture

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    This research investigates the interannual variability of soil moisture as related to large scale climate variability. A three layer hydrological model VIC -3L (Variable Infiltration Capacity Model - 3 layers) was used in the Colorado River Basin and Mississippi River Basin over a 50 year period. The simulation focuses on the soil moisture generation and simulation have been developed between January 1950 and December 2002 at daily time step. Simulation was performed on 1/8 degree resolution for the water balance model of both basins and shows the interannual variability of deep soil moisture. Using wavelet analysis, deep soil moisture is compared to the Palmer Drought Severity Index (PDSI), precipitation, and streamflow to determine whether deep soil moisture is an indicator of climate extremes. Wavelet and coherency analysis for the Colorado River Basin and the upper Mississippi River basin indicate a strong relationship between droughts and the deep soil moisture. Relationships between soil moisture and other large scale climate variability (e.g., ENSO, PDO, sea surface temperatures) are also evaluated

    Relationships Between Oceanic-Atmospheric Patterns and Soil Moisture in the Upper Colorado River Basin

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    Soil moisture is an important drought index in the Upper Colorado River Basin (UCRB) and understanding its relationships with oceanic–atmospheric patterns provides valuable information for sustainable water management. To begin with, this study generated 50 years (1950–2000) of soil moisture data in the UCRB using the Variable Infiltration Capacity (VIC) model. This was followed by a temporal evaluation of Pacific Ocean Sea Surface Temperatures (SSTs) and soil moisture in the UCRB during drought, normal, and wet years. Besides in-phase analysis, lead time analysis was also performed in which the previous year’s SSTs were evaluated with the current year soil moisture. Furthermore, the Singular Value Decomposition (SVD) analysis revealed strong correlation between the first temporal expansion series of SSTs and soil moisture in the UCRB. Finally, this study examined the relationships between multiple oceanic–atmospheric patterns and soil moisture in the UCRB in drought, normal, and wet years. Both in-phase and lead time analyses indicated that the Pacific Decadal Oscillation (PDO) strongly influenced soil moisture by displaying positive coupled regions (significance \u3e95%). In drought and wet years, the lead time analysis showed a positive correlation between the El Niño-Southern Oscillation (ENSO) and soil moisture but the in-phase analysis resulted in a negative correlation. The Atlantic Multi-decadal Oscillation (AMO) displayed similar coupled regions for both in-phase and lead time analyses in drought and wet years. Understanding the relationships between soil moisture and oceanic–atmospheric patterns has increasingly important implications for the water resources management in the UCRB since soil moisture plays a key role in predicting the runoff and streamflow

    Dendritic cells actively limit interleukin-10 production under inflammatory conditions via DC-SCRIPT and dual-specificity phosphatase 4

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    Dendritic cell (DC)-based immunotherapy makes use of the DC's ability to direct the adaptive immune response toward activation or inhibition. DCs perform this immune orchestration in part by secretion of selected cytokines. The most potent anti-inflammatory cytokine interleukin-10 (IL-10) is under tight regulation, as it needs to be predominantly expressed during the resolution phase of the immune response. Currently it is not clear whether there is active suppression of IL-10 by DCs at the initial pro-inflammatory stage of the immune response. Previously, knockdown of the DC-specific transcription factor DC-SCRIPT has been demonstrated to mediate an extensive increase in IL-10 production upon encounter with pro-inflammatory immune stimuli. Here, we explored how DC-SCRIPT contributes to IL-10 suppression under pro-inflammatory conditions by applying chromatin immunoprecipitation sequencing analysis of DC-SCRIPT and the epigenetic marks H3K4me3 and H3K27ac in human DCs. The data showed binding of DC-SCRIPT to a GA-rich motif at H3K27ac-marked genomic enhancers that associated with genes encoding MAPK dual-specificity phosphatases (DUSPs). Functional studies revealed that upon knockdown of DC-SCRIPT, human DCs express much less DUSP4 and exhibit increased phosphorylation of the three major MAPKs (ERK, JNK, and p38). Enhanced ERK signaling in DC-SCRIPT-knockdown-DCs led to higher production of IL-10, which was reverted by rescuing DUSP4 expression. Finally, DC-SCRIPT-knockdown-DCs induced less IFN-γ and increased IL-10 production in naïve T cells, indicative for a more anti-inflammatory phenotype. In conclusion, we have delineated a new mechanism by which DC-SCRIPT allows DCs to limit IL-10 production under inflammatory conditions and potentiate pro-inflammatory Th1 responses. These insights may be exploited to improve DC-based immunotherapies

    Expression of the G72/G30 gene in transgenic mice induces behavioral changes

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    The G72/G30 gene complex is a candidate gene for schizophrenia and bipolar disorder. However, G72 and G30 mRNAs are expressed at very low levels in human brain, with only rare splicing forms observed. We report here G72/G30 expression profiles and behavioral changes in a G72/G30 transgenic mouse model. A human BAC clone containing the G72/G30 genomic region was used to establish the transgenic mouse model, on which gene expression studies, Western blot and behavioral tests were performed. Relative to their minimal expression in humans, G72 and G30 mRNAs were highly expressed in the transgenic mice, and had a more complex splicing pattern. The highest G72 transcript levels were found in testis, followed by cerebral cortex, with very low or undetectable levels in other tissues. No LG72 (the long putative isoform of G72) protein was detected in the transgenic mice. Whole-genome expression profiling identified 361 genes differentially-expressed in transgenic mice compared to wild-type, including genes previously implicated in neurological and psychological disorders. Relative to wild-type mice, the transgenic mice exhibited fewer stereotypic movements in the open field test, higher baseline startle responses in the course of the prepulse inhibition test, and lower hedonic responses in the sucrose preference test. The transcriptome profile changes and multiple mouse behavioral effects suggest that the G72 gene may play a role in modulating behaviors relevant to psychiatric disorders
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