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The Global Historical Climatology Network (GHCN) monthly precipitation dataset contains historical time series for thousands of land surface stations worldwide. Initially released in 1992 and revised in 1998, the dataset has been employed in a variety of applications over the past three decades, including operational monitoring, applied research, and international assessments. This paper describes the data and methods used to compile the latest edition (version 4), which has three major enhancements. The first enhancement is to the station network, which increased in size by a factor of five due to the inclusion of dozens of new source datasets, most notably GHCN Daily (GHCNd). The second improvement is the application of a rule-based algorithm to compare and merge records representing the same location. The third enhancement is to the quality assurance approach, now consisting of 18 new checks based on GHCNd and other operational systems. Updated monthly, the resulting dataset consists of time series of monthly precipitation totals at more than 120,000 worldwide stations, including more than 33,000 active observing sites.
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A data set of observed daily precipitation, maximum and minimum temperature, gridded to a 1/16° (~6 km) resolution, is described that spans the entire country of Mexico, the conterminous U.S. (CONUS), and regions of Canada south of 53° N for the period 1950-2013. The dataset improves previous products in spatial extent, orographic precipitation adjustment over Mexico and parts of Canada, and reduction of transboundary discontinuities. The impacts of adjusting gridded precipitation for orographic effects are quantified by scaling precipitation to an elevation-aware 1981-2010 precipitation climatology in Mexico and Canada. Differences are evaluated in terms of total precipitation as well as by hydrologic quantities simulated with a land surface model. Overall, orographic correction impacts total precipitation by up to 50% in mountainous regions outside CONUS. Hydrologic fluxes show sensitivities of similar magnitude, with discharge more sensitive than evapotranspiration and soil moisture. Because of the consistent gridding methodology, the current product reduces transboundary discontinuities as compared with a commonly used reanalysis product, making it suitable for estimating large-scale hydrometeorologic phenomena.
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Conceitos Meteorológicos , Canadá , México , Estados UnidosRESUMO
Much study has been devoted to the possible causes of an apparent decrease in the upward trend of global surface temperatures since 1998, a phenomenon that has been dubbed the global warming "hiatus." Here, we present an updated global surface temperature analysis that reveals that global trends are higher than those reported by the Intergovernmental Panel on Climate Change, especially in recent decades, and that the central estimate for the rate of warming during the first 15 years of the 21st century is at least as great as the last half of the 20th century. These results do not support the notion of a "slowdown" in the increase of global surface temperature.
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Air and water quality are impacted by extreme weather and climate events on time scales ranging from minutes to many months. This review paper discusses the state of knowledge of how and why extreme events are changing and are projected to change in the future. These events include heat waves, cold waves, floods, droughts, hurricanes, strong extratropical cyclones such as nor'easters, heavy rain, and major snowfalls. Some of these events, such as heat waves, are projected to increase, while others, with cold waves being a good example, will decrease in intensity in our warming world. Each extreme's impact on air or water quality can be complex and can even vary over the course of the event.
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Mudança Climática , Desastres , Qualidade da Água , Tempo (Meteorologia) , Ar , Estados UnidosRESUMO
Increased clouds and precipitation normally decrease the diurnal temperature range (DTR) and thus have commonly been offered as explanation for the trend of reduced DTR observed for many land areas over the last several decades. Observations show, however, that the DTR was reduced most in dry regions and especially in the West African Sahel during a period of unprecedented drought. Furthermore, the negative trend of DTR in the Sahel appears to have stopped and may have reversed after the rainfall began to recover. This study develops a hypothesis with climate model sensitivity studies showing that either a reduction in vegetation cover or a reduction in soil emissivity would reduce the DTR by increasing nighttime temperature through increased soil heating and reduced outgoing longwave radiation. Consistent with empirical analyses of observational data, our results suggest that vegetation removal and soil aridation would act to reduce the DTR during periods of drought and human mismanagement over semiarid regions such as the Sahel and to increase the DTR with more rainfall and better human management. Other mechanisms with similar effects on surface energy balance, such as increased nighttime downward longwave radiation due to increased greenhouse gases, aerosols, and clouds, would also be expected to have a larger impact on DTR over drier regions.
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Urbanization and other changes in land use have an impact on surface-air temperatures. Kalnay and Cai report that the observed surface-temperature trend in part of the United States exceeds the trend in the NCEP/NCAR 50-year reanalysis (NNR) and conclude that changes in land use account for the difference (0.035 degrees C per decade according to their corrected values). Although land-use change may explain some of this discrepancy, the authors do not quantify the impact of the many changes in observational practice that occurred during the analysis period. Our findings indicate that these 'non-climatic' changes have a systematic effect that overwhelms the reported difference in trends and therefore calls Kalnay and Cai's central conclusion into question.