Search

Red oak (Quercus rubra L.) is projected to expand into the northern hardwood forest over the coming century. We explored the connection between red oak basal area growth and a number of factors (tree age and size, stand dynamics, site elevation, and climate and acid deposition variables) for 213 trees in 11 plots throughout Vermont, USA. Red oak growth generally increased over the course of the chronology (1935-2014) and has been particularly high in recent decades. Growth differed among elevational groups but did not differ between age or size groups. Summer moisture metrics were consistently and positively associated with growth, whereas fall moisture was associated with reduced growth in recent decades. Higher summer temperatures were often negatively associated with growth, though there was evidence that low temperatures in the summer (higher elevations) and fall (lower elevations) constrain growth. Several pollution metrics were associated with reduced growth, a surprising result for a species not known to be sensitive to inputs of acid deposition that have predisposed other species in the region to decline. While red oak growth is currently robust, increases in summer temperatures, reductions in growing season precipitation, or increases in fall precipitation could reduce future growth potential. Key words: Quercus rubra, dendrochronology, tree rings, climate change, acid deposition. Le chene rouge (Quercus rubra L.) devrait augmenter sa presence dans la zone des forets de feuillus nordiques au cours du prochain siecle. A partir de 213 arbres repartis dans 11 placettes etablies dans l'Etat du Vermont, aux Etats-Unis, nous avons explore les liens entre la croissance en surface terriere du chene rouge et les facteurs suivants: l'age et la taille des arbres, la dynamique des peuplements, l'altitude de la station, et des variables climatiques et de depots acides. La croissance du chene rouge a generalement augmente pendant la periode couverte par la chronologie (1935-2014) et a ete particulierement elevee au cours des dernieres decennies. La croissance etait differente entre les classes d'altitude, mais pas entre les classes d'age ou de taille. Les mesures d'humidite estivale etaient systematiquement et positivement associees a la croissance, tandis que l'humidite automnale etait negativement associee a la croissance au cours des dernieres decennies. Des temperatures estivales elevees etaient souvent associees negativement a la croissance, bien que de basses temperatures estivales (altitudes plus elevees) et automnales (altitudes plus basses) aient aussi limite la croissance. Plusieurs mesures de pollution ont ete associees a une reduction de croissance, ce qui est un resultat surprenant pour une espece qui n'est pas reconnue pour sa sensibilite aux depots acides qui ont, par ailleurs, predispose d'autres especes de la region a un declin. Bien que la croissance du chene rouge soit actuellement robuste, l'augmentation des temperatures estivales, la reduction des precipitations pendant la saison de croissance ou l'augmentation des precipitations automnales pourraient reduire son futur potentiel de croissance. [Traduit par la Redaction] Mots-cles : Quercus rubra, dendrochronologie, anneaux de croissance, changements climatiques, depots acides., Introduction As climate change progresses, efforts are underway to understand how and when forests and constituent tree species will respond. Numerous studies have applied models to estimate the composition and [...]

Renovating historical buildings with valuable facades often includes interior retrofitting, perhaps entailing an increased durability risk. However, the urban heat island effect and the ongoing climate change might mitigate the severity of frost action and mould growth. By means of heat air moisture (HAM) simulations in Delphin, this study evaluates interior retrofitting of solid masonry on three scales. First, the sensitivity to the intra-urban climatic differences of the freeze-thaw cycles in Ghent is analysed. Secondly, the spatial pattern of freeze-thaw behaviour across Europe is assessed. Finally, the influence of observed climate change on the European freeze-thaw pattern is investigated. A decreasing number of critical freeze- thaw cycles is found when comparing the rural area with the city centre of Ghent. Furthermore, due to climate change, the number of freeze-thaw cycles across Europe generally decreases as well, except at northern latitudes exposed to increased wind-driven rain loads. Key words: heat air moisture (HAM) simulations, solid historical masonry, retrofit, urban heat island, climate change. La renovation d'edifices historiques ayant de belles facades comprend souvent l'application de l'isolation thermique par l'interieur, ce qui peut entrainer un risque accru pour la durabilite. Toutefois, l'effet d'ilot de chaleur urbain et le changement climatique en cours pourraient attenuer la gravite de l'action du gel et de la formation de moisissure. Au moyen de simulations hygrothermiques << HAM >> a Delphin, cette etude evalue l'application de l'isolation interieure de la maconnerie solide sur trois plans. Premierement, la sensibilite du gel-degel aux differences climatiques intra-urbaines a Gand est analysee. Deuxiemement, le profil spatial du comportement au gel-degel en Europe est evalue. Enfin, les effets du changement climatique observe sur le profil europeen de gel-degel est etudiee. Un nombre decroissant de cycles critiques de gel-degel est constate en comparant la zone rurale et le centre-ville de Gand. De plus, en raison du changement climatique, le nombre de cycles de gel-degel en Europe diminue egalement, sauf aux latitudes septentrionales exposees a une augmentation des charges de pluie battante. [Traduit par la Redaction] Mots-cles: simulations hygrothermiques (<< heat air moisture >>, HAM), maconnerie historique solide, isolation thermique interieure, ilot de chaleur urbain, changement climatique., 1. Introduction A major part of the building stock in Belgium consists of buildings, either historical or contemporary, with masonry brick walls. Along with their structural purpose, masonry wall assemblies [...]

Identifying the provenance of aeolian sediments in deserts is of great importance for understanding the Earth surface processes. In this context, we conducted detailed fieldwork in the Ordos Deserts (Maowusu and Kubuqi) in the middle portion of the desert belt in northern China, and measured the major, trace and rare earth elements (REE) of aeolian sands and their potential source rocks and sediments. Our results show that aeolian sands in the eastern (northeastern) and western (southwestern) Maowusu (Mu Us) Sandy Land exhibit different degrees of mineralogical maturity and Eu/Eu* values. Thus, we interpret that these aeolian sands have different provenances, though in the same sandy land. Our data suggest that the local lacustrine sediments and sandstones are the main sources of aeolian sands in the eastern province of the Maowusu Sandy Land, while aeolian sands in the western Maowusu Sandy Land and the Kubuqi Desert have the same external sources. The comparison of geochemical compositions of sediments in the Ordos Deserts with their potential sources in adjacent regions indicates that there is no genetic linkage between the Helan Mountains, the Yinshan Mountains and the Ordos Deserts although they are not far apart. The Qilian Orogenic Belt in the northeastern margin of the Tibetan Plateau is, however, the most likely original provenance for the western Maowusu (Mu Us) Sandy Land and the Kubuqi (Hobq) Desert, but with fluvial sediments in the Ningxia-Inner Mongolian section of the Yellow River as the immediate source. In one side, our results demonstrate that dune fields that are close to each other can have significantly different source sediments. On the other hand, our work suggests that some dune fields and landforms that are far apart from one another, e.g., the Badain Jaran Desert in western Inner Mongolia, the Ordos Deserts and the fluvial sediments in Ningxia-Inner Mongolian section of the Yellow River, can share the same ultimate sources. [ABSTRACT FROM AUTHOR]

This study performed a sensitivity analysis to see the effects of different climates of New Mexico on pavement performance using the mechanistic empirical (ME) pavement design analysis. Results show that the predicted distresses vary significantly for different climate conditions. However, there were only 13 weather stations available in New Mexico for the ME design climate database. These limited number of stations might not cover the complete territorial diversities of this large state. Furthermore, the existing data were outdated, and limited in length by year. To this end, this study updated the existing 13 weather stations to 2015 using the National Climatic Data Center (NCDC) database. In addition, 11 new stations within the state, and 13 weather stations from surrounding states were included in climate database. Later, a comparative study was performed to see the effects of the climate change on predicted distresses in New Mexico. Results show that the climate change for a 10 years period have insignificant effects on pavement distresses. Then, the effectiveness of interpolation method for generating virtual station was investigated. Results show that the interpolation method is not effective enough to reflect the actual climate conditions for many sites. To solve this problem, a temperature zone map was developed using the NCDC database. The objective of this map is to select appropriate weather stations during interpolation. It is found that the temperature zone map reduces the error significantly. Therefore, this study suggests developing a temperature zone map when the number of the weather station is limited. [ABSTRACT FROM AUTHOR]

The Advanced Very High Resolution Radiometer (AVHRR) Pathfinder Atmospheres-Extended (PATMOS-x) dataset offers over three decades of global observations from the NOAA Polar-orbiting Operational Environmental Satellite (POES) project and the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) [Meteorological Operational (MetOp)] satellite series. The AVHRR has flown since 1978 and continues to provide radiometrically consistent observations with a spatial resolution of roughly 4 km and a temporal resolution of an ascending and descending node per satellite per day, achieving global coverage. The AVHRR PATMOS-x data provide calibrated AVHRR observations in addition to properties about tropospheric clouds and aerosols, Earth's surface, Earth's radiation budget, and relevant ancillary data. To provide three decades of data in a convenient format, PATMOS-x generates mapped and sampled results with a spatial resolution of 0.1° on a global latitude-longitude grid. This format avoids spatial or temporal averaging of data, thus maintaining the flexibility to conduct multidimensional analysis. Comparison of this format against the unsampled record demonstrates the ability to reproduce the pixel distribution to a high level of accuracy. AVHRR PATMOS-x is composed of data from 17 different sensors. An examination of cloud amount and total-sky albedo time series demonstrates that intersatellite biases are less than 2%. The comparison of the cloud amount time series to the Interim European Centre for Medium-Range Weather Forecasts (ECMWF) ReAnalysis (ERA-Interim) demonstrates a high degree of correlation, indicating that sensor-to-sensor differences are also not contributing significantly to the observed climate variability in PATMOSx. AVHRR PATMOS-x data are hosted by the National Climatic Data Center (NCDC) (available at www.ncdc.noaa.gov/cdr/operationalcdrs.html)., The National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) Pathfinder Atmospheres-Extended (PATMOS-x) project provides a new satellite-based climate dataset that is now available to the public. [...]

The potential impact of climate change on the existing drainage infrastructure has been an essential aspect of many hydrological studies. Climate change that will increase the intensity of precipitation will also increase the magnitude of the design discharge and thus would probably result in adverse effects on the existing drainage facilities. This paper aims to evaluate the potential impact of rainfall intensity variation due to climate change on the existing drainage infrastructure by investigating whether (1) the stormwater drainage infrastructure designed for preclimate conditions is able to sustain future higher discharges, and (2) new design guidelines are necessary to be established to include the potential rainfall intensity variation due to climate change. A case study was conducted using 34 years of rainfall data (1980-2013) obtained from the National Climatic Data Center (NCDC). These data and the weather scenario data projected by the four run global circulation model (GCMs) under the three emissions scenarios coupled with stochastic weather generator model which generates dailyweather time series statisticallywere used to update the current intensity-duration-frequency curve to reflect the rainfall intensity variation due to climate change. Furthermore, runoff simulation using a storm and sanitary software program was performed to analyze whether the increase in the intensity of rainfall due to climate changewould have an adverse impact on the current drainage systemto convey excess runoff. The results showed thatmost elements of the current drainage infrastructure in the boundary of the study areawere inadequate to convey excess runoff. However, climate change magnifies the problems that already exist in an aging drainage infrastructure. Furthermore, considering the rehabilitation or replacement rates of these aging infrastructures are relatively slow, emphasismust not lie only on the future climate change, but also on identifying the weak spots in the system coupled with, the economic and environmental factors before any changes in design criteria can be recommended due to climate change. [ABSTRACT FROM AUTHOR]

The article offers information on ACIS Version 2 web site located at http://rcc-acis.org, from the U.S. National Climatic Data Center's Regional Climate Center Program.

This paper presents a case study of an EF3 tornado that adversely impacted Greene and Pitt Counties in eastern North Carolina on 16 April 2011. This was one of the [...]

Degradation in visibility occurs extensively across China, creating the urgent need to better understand visibility patterns and characteristics in China. Using daily observation data from the U.S. National Climatic Data Center (NCDC) during 1976-2010, the spatial distribution and temporal trends of visibility in China, as well as seasonal and regional characteristics, were determined. The distribution of visibility was characterized by a longitudinal gradient between west and east China. The northwest of China generally experienced consistent high visibility of >20 km, while central and eastern China experienced visibility degradation and increase in haziness. The 133 stations with significant downward trends in visibility were clustered around central-east China and the average reduction rate was −1.65 km/decade (from 18.5 km). The 96 stations with increasing trends of visibility were mostly on the Qinghai-Tibet Plateau and Xinjiang and were closely related to a reduction in local sand storms. The average visibility in 12 key regions in China varied between 9.9-17.8 km (except for 23.9 km in Urumqi), which was lower than the national average of 18.7 km. The Taiyuan-Hohhot, Guanzhong, Yangtze River Delta, Pearl River Delta and Fuzhou-Xiamen areas all encountered significant decreases in visibility, while minor increases were observed in Beijing-Tianjin-Hebei and the Cheng-Yu region. At most stations, the worst visibility was measured in winter, but the season with best visibility varied between regions. A comparison of visibility trends with the emission trends of various pollutants revealed that SO emissions dominated the visibility degradation in eastern China with NO and volatile organic compounds playing ascending roles during the 2000s. [ABSTRACT FROM AUTHOR]

The 1981-2010 'U.S. Climate Normals' released by the National Oceanic and Atmospheric Administration's (NOAA) National Climatic Data Center include a suite of monthly, seasonal, and annual statistics that are based on precipitation, snowfall, and snow-depth measurements. This paper describes the procedures used to calculate the average totals, frequencies of occurrence, and percentiles that constitute these normals. All parameters were calculated from a single, state-of-the-art dataset of daily observations, taking care to produce normals that were as representative as possible of the full 1981-2010 period, even when the underlying data records were incomplete. In the resulting product, average precipitation totals are available at approximately 9300 stations across the United States and parts of the Caribbean Sea and Pacific Ocean islands. Snowfall and snow-depth statistics are provided for approximately 5300 of those stations, as compared with several hundred stations in the 1971-2000 normals. The 1981-2010 statistics exhibit the familiar climatological patterns across the contiguous United States. When compared with the same calculations for 1971-2000, the later period is characterized by a smaller number of days with snow on the ground and less total annual snowfall across much of the contiguous United States; wetter conditions over much of the Great Plains, Midwest, and northern California; and drier conditions over much of the Southeast and Pacific Northwest. These differences are a reflection of the removal of the 1970s and the addition of the 2000s to the 30-yr-normals period as part of this latest revision of the normals. [ABSTRACT FROM AUTHOR]

This paper presents a tool for calculating the Palmer Drought Severity Index (PDSI) and associated drought indices. The PDSI is a widely used drought index, yet the complexity and lack of transparency associated with the calculation of the PDSI makes it difficult for a researcher to independently calculate the index. Researchers are often forced to use PDSI values supplied by the National Climatic Data Center (NCDC) of the National Oceanic and Atmospheric Administration (NOAA) or some other third party. The MATLAB tool presented here is easy to use, thoroughly documented, and transparent. The tool was developed by checking an independently developed code against NCDC's FORTRAN code. Discrepancies between the MATLAB tool and the NCDC code are documented. Researchers using the tool will be able to easily calculate the Palmer drought indices for data inputs of any length and at any spatial scale. [ABSTRACT FROM AUTHOR]

The article describes the National Climatic Data Center's (NCDC) Global Historical Climatology Network (GHCN)-Daily dataset (GHCN), which refers to a global land gridded dataset of climate extremes. There are nearly 29,000 stations with daily maximum and minimum temperature covered by GHCN-Daily as of October 2012. Information on global climate indices is provided, as well as observation-based datasets of climate extremes and the key objective of GHCN dataset.

The relationship between convective precipitation and cloud-to-ground (CG) lightning is examined over a study area in southwest Arizona and northwest Mexico. Using seasonal-to-daily and hourly time resolution, the National Climatic Data Center (NCDC) stage IV precipitation product and the U.S. National Lightning Detection Network lightning data have been analyzed with the aim of developing an improved understanding of the relationship between these variables. A Gaussian method of spatially smoothing discrete lightning counts is used to estimate convective rainfall and improve the quality and spatial coverage of radar-derived precipitation in areas of complex terrain. For testing the dependence of the relationship between CG lightning and precipitation, a precipitation 'sensor coverage' analysis has been performed. If locations that have poor sensor coverage are excluded, R2 between lightning and precipitation improves by up to 15%. A complementary way to estimate convective precipitation is proposed based on 1-h lightning occurrence intervals, which is the maximum time resolution in this study. We find that ~67% of the seasonal 2005 precipitation over the analysis domain is associated with CG lightning. Daily precipitation estimates are improved by specifying a 'diurnal day' based on the diurnal maxima and minima in precipitation and CG lightning within the domain. Our method for improving quantitative precipitation estimation (QPE) using lightning is able to track and estimate convective precipitation over regions that have poor sensor coverage, particularly in both air mass storms and large multicellular events, with R2 up to 70%. [ABSTRACT FROM AUTHOR]

Monthly climatologies (1971-2000 monthly averages) for stations in the western United States, obtained from the NOAA/National Climatic Data Center (NCDC), are used to illustrate the spatial variations in the annual cycle of climate. Animated map sequences of temperature and precipitation, their average, intermonthly changes, and the local timing of annual maxima or minima provide a comprehensive spatiotemporal baseline of regional climate. The animated maps illustrate three scales of variation: 1) broadscale patterns related to the annual cycle of insolation and hemispheric-scale atmospheric circulation features; 2) mesoscale patterns related to location on the continent and the influence of specific regional circulation features like those associated with the North American monsoon; and 3) smaller-scale spatial variations, related to the mediation by local physiography of the influence of large-scale circulation. Although most western U.S. stations have temperature maxima in July, a delay occurs at stations along the West Coast and interior Washington, northern Idaho, and Montana. A seesaw pattern of precipitation maxima is evident between coastal areas (winter dominated) and the interior (summer dominated). Cluster analyses of the ratio of monthly-to-annual precipitation values for each station identify regions with similar annual cycles of precipitation. Regions of high spatial heterogeneity in the timing of when precipitation occurs include the northern Rocky Mountains, Utah, Arizona, and northwestern Montana. The superimposition of these three scales of spatial variability leads to steep gradients and, in some regions, considerable spatial heterogeneity in annual precipitation. The regional patterns of precipitation heterogeneity highlight vulnerability to drought, especially in regions of the interior west that do not have a dominant precipitation month or season. [ABSTRACT FROM AUTHOR]

The article focuses on the weather conditions in the U.S. and Canada from May-June 2010. It highlights the huge cluster of thunderstorms called mesoscale convective complex (MCC) which caused the night-time rains in the Great Plains. According to the preliminary data given by the U.S. National Climatic Data Center, the country experienced its 52nd coolest and 37th wettest May since 1895.

The article provides information on the weather conditions in the U.S. in July 2009. It states that the weather in the month was the coolest temperature on record in the central and eastern part of the country where the monthly averaged was eight degrees Fahrenheit below normal as depicted by the National Climatic Data Center. It cites that the most intense heat was noticed in the west region for 49 days from May 22 to July 9, where the maximum temperature ended with 86 degrees Fahrenheit.

The National Oceanic and Atmospheric Administration (NOAA), National Environmental Satellite Data and Information Service (NESDIS) operates a fleet of civilian, polar-orbiting, environmental satellites that provide users and researchers with a continuous suite of atmospheric and surface products on a global scale. The first advanced TIROS operational vertical sounder (ATOVS) radiometer configuration, onboard NOAA-15, was successfully launched into an early evening orbit on 13 May 1998. The ATOVS featured the new 13 channel advanced microwave sounding unit (AMSU) module A1, the 2 channel AMSU-A2 and 5 channel AMSU-B radiometers, which replaced the MSU and SSU, along with a similar HIRS and AVHRR instrument payload (Goodrun G., Kidwell, K.B. and Winston, W., 2000, NOAA-KLM users guide: September 2000 revision, Technical Document, National Oceanic and Atmospheric Administration, National Environmental Satellite Data and Information Service, National Climatic Data Center) that had been operational since 1979. The ATOVS onboard NOAA-16 was successfully launched into an afternoon orbit on 21 September 2000, followed by NOAA-17 into a late evening orbit on 24 June 2002, creating the first ever three-satellite constellation of operational polar satellites (ATOVS). The following report summarizes the online and offline scientific processing systems, respectively, for deriving the NESDIS operational ATOVS sounding products and presents a series of results for the unique three-operational-satellite configuration of NOAA-15, 16 and 17. Results focus on the value of the derived products in the analyses of global and regional scale weather, including direct comparisons against collocated numerical weather prediction (NWP) forecast and radiosonde data. The report is prefaced by a brief history of satellite weather products and concludes with future plans to meet expanding user requirements. [ABSTRACT FROM AUTHOR]

The Bayesian processor of forecast (BPF) is developed for a continuous predictand. Its purpose is to process a deterministic forecast (a point estimate of the predictand) into a probabilistic forecast (a distribution function, a density function, and a quantile function). The quantification of uncertainty is accomplished via Bayes theorem by extracting and fusing two kinds of information from two different sources: (i) a long sample of the predictand from the National Climatic Data Center, and (ii) a short sample of the official National Weather Service forecast from the National Digital Forecast Database. The official forecast is deterministic and hence deficient: it contains no information about uncertainty. The BPF remedies this deficiency by outputting the complete and well-calibrated characterization of uncertainty needed by decision makers and information providers. The BPF comes furnished with (i) the meta-Gaussian model, which fits meteorological data well as it allows all forms of marginal distribution functions, and nonlinear and heteroscedastic dependence structures, and (ii) the statistical procedures for estimation of parameters from asymmetric samples and for coping with nonstationarities in the predictand and the forecast due to the annual cycle and the lead time. A comprehensive illustration of the BPF is reported for forecasts of the daily maximum temperature issued with lead times of 1, 4, and 7 days for three stations in two seasons (cool and warm). [ABSTRACT FROM AUTHOR]

The sampling error variances of the 5° × 5° Global Historical Climatological Network (GHCN) monthly surface air temperature data are estimated from January 1851 to December 2001. For each GHCN grid box and for each month in the above time interval, an error variance is computed. The authors’ error estimation is determined by two parameters: the spatial variance and a correlation factor determined by using a regression. The error estimation procedures have the following steps. First, for a given month for each grid box with at least four station anomalies, the spatial variance of the grid box’s temperature anomaly, &sigmacirc;2s, is calculated by using a 5-yr moving time window (MTW). Second, for each grid box with at least four stations, a regression is applied to find a correlation factor, αs, in the same 5-yr MTW. Third, spatial interpolation is used to fill the spatial variance and the correlation factor in grid boxes with less than four stations. Fourth, the sampling error variance is calculated by using the formula E2 = αs&sigmacirc;2s/N, where N is the total number of observations for the grid box in the given month. The two parameters of the authors’ error estimation are compared with those of the University of East Anglia’s Climatic Research Unit for the decadal data. The comparison shows a close agreement of the parameters’ values for decadal data. An advantage of this new method is the generation of monthly error estimates. The authors’ error product will be available at the U.S. National Climatic Data Center. [ABSTRACT FROM AUTHOR]

The article presents the study which investigates the relationship between weather conditions and hospital emergency department (ED) utilization in New York City. This study analyzes the weather data which were obtained from the Web site of the National Climatic Data Center, that is estimated to be 3.3 miles away from the hospital's ED. Furthermore, direct correlation between weather conditions and ED patient volume were assessed.

The Mesoscale Modeling system, version 3.6 (MM5) regional modeling system has been applied to Central America and has been evaluated against National Oceanic and Atmospheric Administration/National Climatic Data Center (NOAA/NCDC) daily observations and the Global Precipitation Climatology Project (GPCP) precipitation data. We compare model results and observations for 1997 and evaluate various climate parameters (temperature, wind speed, precipitation and water vapor mixing ratio), emphasizing the differences within the context of the station dependent geographical features and the land use (LU) categories. At 9 of the 16 analyzed stations the modeled temperature, wind speed and vapor mixing ratio are in agreement with observations with average model-observation differences consistently lower than 25%. MM5 has better performance at stations strongly impacted by monsoon systems, regions typified by low topography in coastal areas and areas characterized by evergreen, broad-leaf and shrub land vegetation types. At four stations the model precipitation is about a factor of 3-5 higher than the observations, while the simulated wind is roughly twice what is observed. These stations include two inland stations characterized by croplands close to water bodies; one coastal station in El Salvador adjacent to a mountain-based cropland area and one station at sea-level. This suggests that the model does not adequately represent the influence of topographic features and water bodies close to these stations. In general, the model agrees reasonably well with measurements and therefore provides an acceptable description of regional climate. The simulations in this study use only two seasonal maps of land cover. The main model discrepancies are likely attributable to the actual annual cycle of land-atmosphere vapor and energy exchange that has a temporal scale of days to weeks. These fluxes are impacted by surface moisture availability, albedo and thermal inertia parameters. Copyright © 2006 Royal Meteorological Society. [ABSTRACT FROM AUTHOR]

It is widely known that the TD3200 (Summary of the Day Cooperative Network) database held by the National Climatic Data Center contains tens of thousands of erroneous daily values resulting from data-entry, data-recording, and data-reformatting errors. TD3200 serves as a major baseline dataset for detecting global climate change. It is of paramount importance to the climate community that these data be as error-free as possible. Many of these errors are systematic in nature. If a deterministic approach is taken, using empirically developed criteria, many if not most of these errors can be corrected or removed. A computer program utilizing Backus Normal Form structure design and a series of chain-linked tests in the form of encoded rules has been developed as a means of modeling the human subjective process of inductive data review. This objective automated correction process has proven extremely effective. A manual review and validation of 138 stations of a 1300-station subset of TD3200 data closely matched the automated correction process. Applications of this technique are expected to be utilized in the production of a nearly error-free TD3200 dataset.

The article offers information on the government agencies in the U.S. that tackle earth's climate. The National Oceanic and Atmospheric Administration covers atmosphere, ocean and earth's interaction with the sun. The world's largest archive of weather data is the National Climatic Data Center covering extreme climatic events and paleoclimatology. The National Oceanographic Data Center focuses on oceans and coastal areas for understanding of overall climatic and environmental conditions.

The article focuses on the increase in average temperature in the U.S. according to the 1981-2010 normals to be released by the National Climatic Data Center on July 1, 2011.

The article explains that University of Wisconsin-Madison scientists used streamlined data to establish a connection between warming seawaters and more powerful Atlantic Ocean hurricanes. The research team revised hurricane data obtained from satellites in the period 1983-2005 that is stored in the U.S. National Climatic Data Center's (NCDC) archives. Researchers simplified the data to make them consistent with information collected twenty years ago. Study leader James Kossin pointed out that the aim was to resolve the debate on the quality of hurricane data.

The article reports that the U.S. National Climatic Data Center (NCDC) has revealed that a January 2007 Earth temperature of 12.85 degrees Centigrade, equivalent to 55.13 degrees Fahrenheit surpassed the world record set in January 2002. The temperature represents combined global land and ocean-surface temperature. NCDC scientific services chief David Easterling expressed his surprise at the January 2007 temperature, which is attributed to warm wintertime temperatures in the northern latitudes and to the El Niño phenomenon.

Discusses the outcome of the meeting of drought experts from the U.S., Canada and Mexico at the National Climatic Data Center in Asheville, Carolina to develop a plan for drought monitoring in North America. Success of the U.S. Drought Monitor in assessing and communicating the state of drought in the U.S. on a weekly basis; Negativek effects of drought on the economy.

Floods are the leading cause of fatalities connected with natural disasters in Texas. A combination of physiography and precipitation often result in extreme hydrologic conditions that cause floods in the state. This paper reviews flood-related fatalities in Texas between 1959 and 2008. Information on flood-fatality victims and the flood-causing events was obtained from the National Climatic Data Center. The data collected included the date, time, location, and weather conditions and the gender and age of the flood victims. Comparison with other states reveals that the size of the population of Texas is a major factor in the increased number of fatalities. The data also suggest that driving or walking into floodwaters may be responsible for more than 93% of flood fatalities in Texas. Although most high-fatality counties are located in the Texas 'Flash Flood Alley' that includes major urban centers, normalization of fatality data shows that the flood-fatality risk is actually higher in other areas of the state. The analysis also indicates that the annual flood-fatality rates are decreasing significantly. A combination of improved hydrometeorological forecasting, educational programs aimed at enhancing public awareness of flood risk and the seriousness of flood warnings, and timely and appropriate action by local emergency and safety authorities will help further reduce flood fatalities in Texas. [ABSTRACT FROM AUTHOR]