52 research outputs found

    Toward a Better Quality Control of Weather Data

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    Development of the Soil Moisture Index to Quantify Agricultural Drought and Its “User Friendliness” in Severity-Area-Duration Assessment

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    This paper examines the role of soil moisture in quantifying drought through the development of a drought index using observed and modeled soil moisture. In Nebraska, rainfall is received primarily during the crop-growing season and the supply of moisture from the Gulf of Mexico determines if the impending crop year is either normal or anomalous and any deficit of rain leads to a lack of soil moisture storage. Using observed soil moisture from the Automated Weather Data Network (AWDN), the actual available water content for plants is calculated as the difference between observed or modeled soil moisture and wilting point, which is subsequently normalized with the site-specific, soil property–based, idealistic available water for plants that is calculated as the difference between field capacity and wilting point to derive the soil moisture index (SMI). This index is categorized into five classes from no drought to extreme drought to quantitatively assess drought in both space and time. Additionally, with the aid of an in-house hydrology model, soil moisture was simulated in order to compute model-based SMI and to compare the drought duration and severity for various sites. The results suggest that the soil moisture influence, a positive feedback process reported in many earlier studies, is unquestionably a quantitative indicator of drought. Also, the severity and duration of drought across Nebraska has a clear gradient from west to east, with the Panhandle region experiencing severe to extreme drought in the deeper soil layers for longer periods (\u3e200 days), than the central and southwestern regions (125–150 days) or the eastern regions about 100 days or less. The anomalous rainfall years can eliminate the distinction among these regions with regard to their drought extent, severity, and persistence, thus making drought a more ubiquitous phenomenon, but the recovery from drought can be subject to similar gradations. The spatial SMI maps presented in this paper can be used with the Drought Monitor maps to assess the local drought conditions more effectively

    Spatial Accuracy of Climate Networks: A Case Study in Nebraska

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    Climate data are increasingly scrutinized for accuracy because of the need for reliable input for climaterelated decision making and assessments of climate change. Over the last 30 years, vast improvements to U.S. instrumentation, data collection, and station siting have created more accurate data. This study explores the spatial accuracy of daily maximum and minimum air temperature data in Nebraska networks, including the U.S. Historical Climatology Network (HCN), the Automated Weather Data Network (AWDN), and the more recent U.S. Climate Reference Network (CRN). The spatial structure of temperature variations at the earth’s surface is compared for timeframes 2005–09 for CRN and AWDN and 1985–2005 for AWDN and HCN. Individual root-mean-square errors between candidate station and surrounding stations were calculated and used to determine the spatial accuracy of the networks. This study demonstrated that in the 5-yr analysis CRN and AWDN were of high spatial accuracy. For the 21-yr analysis the AWDN proved to have higher spatial accuracy (smaller errors) than the HCN for both maximum and minimum air temperature and for all months. In addition, accuracy was generally higher in summer months and the subhumid area had higher accuracy than did the semiarid area. The findings of this study can be used for Nebraska as an estimate of the uncertainty associated with using a weather station’s data at a decision point some distance from the station

    Quality Assessment of Meteorological Data for the Beaufort and Chukchi Sea Coastal Region using Automated Routines

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    Meteorological observations from more than 250 stations in the Beaufort and Chukchi Sea coastal, interior, and offshore regions were gathered and quality-controlled for the period 1979 through 2009. These stations represent many different observing networks that operate in the region for the purposes of aviation, fire weather, coastal weather, climate, surface radiation, and hydrology and report data hourly or sub-hourly. A unified data quality control (QC) has been applied to these multi-resource data, incorporating three main QC procedures: the threshold test (identifying instances of an observation falling outside of a normal range); the step change test (identifying consecutive values that are excessively different); and the persistence test (flagging instances of excessively high or low variability in the observations). Methods previously developed for daily data QC do not work well for hourly data because they flag too many data entries. Improvements were developed to obtain the proper limits for hourly data QC. These QC procedures are able to identify the suspect data while producing far fewer Type I errors (the erroneous flagging of valid data). The fraction of flagged data for the entire database illustrates that the persistence test was failed the most often (1.34%), followed by the threshold (0.99%) and step change tests (0.02%). Comparisons based on neighboring stations were not performed for the database; however, correlations between nearby stations show promise, indicating that this type of check may be a viable option in such cases. This integrated high temporal resolution dataset will be invaluable for weather and climate analysis, as well as regional modeling applications, in an area that is undergoing significant climatic change.Des observations météorologiques provenant de plus de 250 stations des régions côtières, intérieures et extracôtières de la mer de Beaufort et de la mer des Tchouktches ont été recueillies pendant la période allant de 1979 à 2009, puis elles ont fait l’objet d’un contrôle de la qualité. Ces stations relèvent de plusieurs réseaux d›observation différents qui existent dans la région à des fins d›aviation, de météorologie forestière, de météorologie côtière, de climat, de rayonnement de surface et d’hydrologie, et elles fournissent des données horaires ou subhoraires. Un contrôle de la qualité (CQ) unifié des données a été appliqué à ces données provenant de sources multiples en faisant appel à trois méthodes principales de CQ, soit le test d’acceptabilité (qui a permis de déterminer dans quels cas une observation ne faisait pas partie de la gamme normale); le test de la variation discrète (qui a permis de détecter les valeurs consécutives qui sont excessivement différentes); et le test de la persistance (qui a permis de repérer les cas de variabilité excessivement élevée ou basse). Les anciennes méthodes de CQ des données quotidiennes ne donnent pas de bons résultats dans le cas des données horaires parce qu’elles se trouvent à signaler un trop grand nombre d’entrées de données. Des améliorations ont été apportées afin d’obtenir les bonnes limites en vue du CQ des données horaires. Ces méthodes de CQ permettent de repérer les données douteuses et produisent beaucoup moins d’erreurs de type I (le signalement erroné de données valables). La fraction de données signalées pour l’ensemble de la base de données illustre que le test de persistance a échoué le plus souvent (1,34 %), suivi du test d’acceptabilité (0,99 %) et des tests de la variation discrète (0,02 %). Des comparaisons effectuées avec les données de stations avoisinantes n’ont pas été effectuées pour la base de données. Cependant, des corrélations entre les stations annexes s’avéraient prometteuses, ce qui a laissé entendre que ce type de vérification pourrait présenter une option viable dans de tels cas. Cet ensemble de données intégrées à haute résolution temporelle aura une très grande valeur pour l’analyse météorologique et climatique ainsi que pour les applications de modélisation régionale dans une région où le changement climatique est important

    Necrostatin-1 Reduces Histopathology and Improves Functional Outcome after Controlled Cortical Impact in Mice

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    Necroptosis is a newly identified type of programmed necrosis initiated by the activation of tumor necrosis factor alpha (TNF?)/Fas. Necrostatin-1 is a specific inhibitor of necroptosis that reduces ischemic tissue damage in experimental stroke models. We previously reported decreased tissue damage and improved functional outcome after controlled cortical impact (CCI) in mice deficient in TNF? and Fas. Hence, we hypothesized that necrostatin-1 would reduce histopathology and improve functional outcome after CCI in mice. Compared with vehicle-/inactive analog-treated controls, mice administered necrostatin-1 before CCI had decreased propidium iodide-positive cells in the injured cortex and dentate gyrus (6 h), decreased brain tissue damage (days 14, 35), improved motor (days 1 to 7), and Morris water maze performance (days 8 to 14) after CCI. Improved spatial memory was observed even when drug was administered 15 mins after CCI. Necrostatin-1 treatment did not reduce caspase-3-positive cells in the dentate gyrus or cortex, consistent with a known caspase-independent mechanism of necrostatin-1. However, necrostatin-1 reduced brain neutrophil influx and microglial activation at 48 h, suggesting a novel anti-inflammatory effect in traumatic brain injury (TBI). The data suggest that necroptosis plays a significant role in the pathogenesis of cell death and functional outcome after TBI and that necrostatin-1 may have therapeutic potential for patients with TBI

    A Multi-sensor View of the 2012 Central Plains Drought from Space

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    In summer of 2012, the Central Plains of the United States experienced its most severe drought since the ground-based data record began in the late 1900s. By using comprehensive satellite data from MODIS (Moderate Resolution Imaging Spectroradiometer) and TRMM (Tropical Rainfall Measuring Mission), along with in-situ observations, this study documents the geophysical parameters associated with this drought, and thereby providing, for the first time, a large-scale observation-based view of the extent to which the land surface temperature and vegetation can likely be affected by both the severe drought and the agricultural response (irrigation) to the drought. Over non-irrigated area, 2012 summer daytime land surface temperature (LSl) , and Normalized Difference Vegetation Index (NDVI) monthly anomalies (with respect to climate in 2002-2011) are often respectively greater than 5 K and negative, with some extreme values of 10K and -0.2 (Le., no green vegetation). In contrast, much smaller anomalies \u3c 2 K) of LST and nearly the same NDVI are found over irrigated areas. Precipitation received was an average of 5.2 cm less, while both fire counts and fire radiative power were doubled, thus contributing in part to a nearly 100% increase of aerosol optical depth in many forested areas (close to intermountain west). Water vapor amount, while decreased over the southern part, indeed slightly increased in the northern part of Central Plains. As expected, cloud fraction anomaly is negative in the entire Central Plains; however, the greatest reduction of cloud fraction is found over the irrigated areas, which is in contrast to past modeling studies showing that more irrigation, because of its impact on LST, may lead to increase of cloud fraction

    Neuronal Deletion of Caspase 8 Protects against Brain Injury in Mouse Models of Controlled Cortical Impact and Kainic Acid-Induced Excitotoxicity

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    system. mice demonstrated superior survival, reduced seizure severity, less apoptosis, and reduced caspase 3 processing. Uninjured aged knockout mice showed improved learning and memory, implicating a possible role for caspase 8 in cognitive decline with aging.Neuron-specific deletion of caspase 8 reduces brain damage and improves post-traumatic functional outcomes, suggesting an important role for this caspase in pathophysiology of acute brain trauma

    GJB2 mutation spectrum in 2063 Chinese patients with nonsyndromic hearing impairment

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    Background: Mutations in GJB2 are the most common molecular defects responsible for autosomal recessive nonsyndromic hearing impairment (NSHI). The mutation spectra of this gene vary among different ethnic groups. Methods: In order to understand the spectrum and frequency of GJB2 mutations in the Chinese population, the coding region of the GJB2 gene from 2063 unrelated patients with NSHI was PCR amplified and sequenced. Results: A total of 23 pathogenic mutations were identified. Among them, five (p.W3X, c.99delT, c.155_c.158delTCTG, c.512_c.513insAACG, and p.Y152X) are novel. Three hundred and seven patients carry two confirmed pathogenic mutations, including 178 homozygotes and 129 compound heterozygotes. One hundred twenty five patients carry only one mutant allele. Thus, GJB2 mutations account for 17.9% of the mutant alleles in 2063 NSHI patients. Overall, 92.6% (684/739) of the pathogenic mutations are frame-shift truncation or nonsense mutations. The four prevalent mutations; c.235delC, c.299_c.300delAT, c.176_c.191del16, and c.35delG, account for 88.0% of all mutantalleles identified. The frequency of GJB2 mutations (alleles) varies from 4% to 30.4% among different regions of China. It also varies among different sub-ethnic groups. Conclusion: In some regions of China, testing of the three most common mutations can identify at least one GJB2 mutant allele in all patients. In other regions such as Tibet, the three most common mutations account for only 16% the GJB2 mutant alleles. Thus, in this region, sequencing of GJB2 would be recommended. In addition, the etiology of more than 80% of the mutant alleles for NSHI in China remains to be identified. Analysis of other NSHI related genes will be necessary

    Some Concerns when Using Data from the Cooperative Weather Station Networks: A Nebraska Case Study

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    In this study, daily temperature and precipitation amounts that are observed by the Cooperative Observer Program (COOP) were compared among geographically close stations. Hourly observations from nearby Automatic Weather Data Network (AWDN) stations were utilized to resolve the discrepancies between the observations during the same period. The statistics of maximum differences in temperature and precipitation between COOP stations were summarized. In addition, the quantitative measures of the deviations between COOP and AWDN stations were expressed by root-mean-square error, mean absolute error, and an index of agreement. The results indicated that significant discrepancies exist among the daily observations between some paired stations because of varying observation times, observation error, sensor error, and differences in microclimate exposure. The purpose of this note is to bring attention to the problem and offer guidance on the use of daily observations in the comparison and creation of weather maps. In addition, this study demonstrates approaches for identifying the sources of the discrepancies in daily temperature and precipitation observations. The findings will be useful in the quality assurance (QA) procedures of climate data
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