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1
Johnston, Kerrylyn, and Belinda J. Robson. "Habitat use by the hymenosomatid crab Amarinus lacustris (Chilton) in two south-eastern Australian rivers." Marine and Freshwater Research 56, no. 1 (2005): 37. http://dx.doi.org/10.1071/mf04219.
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The hymenosomatid crab Amarinus lacustris is abundant in some south-eastern Australian rivers; however, little is known of its ecology. Patterns of habitat use by crabs in rivers may be affected by seasonal changes in river discharge. This study investigates population characteristics, timing of reproduction and patterns of habitat use by A. lacustris in five riffle and pool habitats from each of the Hopkins and Merri Rivers in south-west Victoria, Australia, sampled over a twelve-month period. Distribution of Amarinus lacustris was similar between the two rivers, but log-linear modelling showed that there was a strong association between crab sex, habitat occupied and time of year because female A. lacustris showed a shift from riffle to pool habitats during March and April, coinciding with the non-gravid period of the year. Male crabs also showed a change in relative occurrence, occurring most often in riffles during winter–spring (July–November) but being equally common in both habitats in summer–autumn (January–May). These patterns are probably the result of the reproductive cycle of A. lacustris, which appears to show both ontogenetic and sex-related changes in habitat use during its life cycle, taking advantage of seasonal fluctuations in flow regime that may assist egg/larval development and dispersal.
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Entwisle, TJ. "Phenology of the Cladophora-Stigeoclonium community in Two Urban Creeks of Melbourne." Marine and Freshwater Research 40, no. 5 (1989): 471. http://dx.doi.org/10.1071/mf9890471.
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Cladophora glomerata and Stigeoclonium tenue dominate lowland urban creeks in the Yarra River basin of south-central Victoria. In Darebin and Merri Creeks, Cladophora produces extensive mats in summer and autumn, and is mostly replaced by Stigeoclonium in winter and spring. Although Stigeoclonium can grow all year round, it only outcompetes Cladophora in winter and spring, when air temperatures range between a maximum of < 15� C and a nightly minimum of < 10� C (water temperature < 15� C, usually about 10� C). The seasonal composition and abundance of these macroalgae depend on temperature and on the severity of, and time since, the last floods, and the effect that these factors have on interspecific competition. Features of the microhabitat (e.g. photon irradiance, substratum stability and composition, and mean flow rates) determine the range of these variations. The biomass of both macroalgae fluctuates widely; this is due mainly to floods, which can remove almost the entire standing crop. In off-seasons, both species are maintained by small resilient plants or protected populations (in culture, plants remain viable after up to 6 months in complete darkness). Filaments of Cladophora readily produce zoospores and new vegetative growth following dormancy. The prostrate thallus of Stigeoclonium initiates new erect filaments before zoospores are produced. An understanding of the large local and seasonal variations in macroalgal biomass is essential for biological monitoring programmes.
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Baba, Mohamed, Simon Gascoin, Lionel Jarlan, Vincent Simonneaux, and Lahoucine Hanich. "Variations of the Snow Water Equivalent in the Ourika Catchment (Morocco) over 2000–2018 Using Downscaled MERRA-2 Data." Water 10, no. 9 (August 23, 2018): 1120. http://dx.doi.org/10.3390/w10091120.
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The Ourika River is an important tributary of the Tensift River in the water-stressed region of Marrakesh (Morocco). The Ourika river flow is dominated by the snow melt contribution from the High Atlas mountains. Despite its importance in terms of water resources, the snow water equivalent (SWE) is poorly monitored in the Ourika catchment. Here, we used MERRA-2 data to run a distributed energy-balance snowpack model (SnowModel) over 2000–2018. MERRA-2 data were downscaled to 250-m spatial resolution using a digital elevation model. The model outputs were compared to in situ measurements of snow depth, precipitation, river flow and remote sensing observations of the snow cover area from MODIS. The results indicate that the model provides an overall acceptable representation of the snow cover dynamics given the coarse resolution of the MERRA-2 forcing. Then, we used the model output to analyze the spatio-temporal variations of the SWE in the Ourika catchment for the first time. We suggest that MERRA-2 data, which are routinely available with a delay of a few weeks, can provide valuable information to monitor the snow resource in high mountain areas without in situ measurements.
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Marquardt Collow, Allison B., and Mark A. Miller. "The Seasonal Cycle of the Radiation Budget and Cloud Radiative Effect in the Amazon Rain Forest of Brazil." Journal of Climate 29, no. 21 (October 6, 2016): 7703–22. http://dx.doi.org/10.1175/jcli-d-16-0089.1.
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Abstract Changes in the climate system of the Amazon rain forest of Brazil can impact factors that influence the radiation budget such as clouds, atmospheric moisture, and the surface albedo. This study examines the relationships between clouds and radiation in this region using surface observations from the first year of the deployment of the Atmospheric Radiation Measurement (ARM) Program’s Mobile Facility 1 (AMF1) in Manacapuru, Brazil, and satellite measurements from the Clouds and the Earth’s Radiant Energy System (CERES). The seasonal cycles of the radiation budget and cloud radiative effects (CREs) are evaluated at the top of the atmosphere (TOA), at the surface, and within the atmospheric column using these observations and are placed into a regional context using the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). Water vapor and clouds are abundant throughout the year, even though slight decreases are observed in the dry season. The column water vapor load is large enough that the longwave radiative flux divergence is nearly constant throughout the year. Clouds produce a significant shortwave CRE at the surface and TOA, exceeding 200 W m−2 during the wet season. Discrepancies, especially in column shortwave radiative absorption, between the observations and MERRA-2 are demonstrated that warrant additional analysis of the microphysical and macrophysical cloud properties in MERRA-2. More trustworthy fields in the MERRA-2 product suggest that the expansive nearby river system impacts the regional radiation budget and thereby renders AMF1 observations potentially biased relative to regions farther removed from rivers within the Amazon rain forest.
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Mernild, Sebastian H., Glen E. Liston, Christopher A. Hiemstra, Jacob C. Yde, and Gino Casassa. "Annual River Runoff Variations and Trends for the Andes Cordillera." Journal of Hydrometeorology 19, no. 7 (July 1, 2018): 1167–89. http://dx.doi.org/10.1175/jhm-d-17-0094.1.
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Abstract We analyzed modeled river runoff variations west of the Andes Cordillera’s continental divide for 1979/80–2013/14 (35 years). Our foci were annual runoff conditions, runoff origins (rain, snowmelt, and glacier ice), and runoff spatiotemporal variability. Low and high runoff conditions were defined as occurrences that fall outside the 10th (low values) and 90th (high values) percentile values of the period of record. SnowModel and HydroFlow modeling tools were used at 4-km horizontal grid increments and 3-h time intervals. NASA Modern-Era Retrospective Analysis for Research and Applications (MERRA) datasets were used as atmospheric forcing. This modeling system includes evaporation and sublimation from snow-covered surfaces, but it does not take into account evapotranspiration from bare and vegetation-covered soils and from river and lake surfaces. In general for the Andes Cordillera, the simulated runoff decreased before 1997 and increased afterward. This could be due to a model precipitation artifact in the MERRA forcing. If so, this artifact would influence the number of years with low runoff values, which decreased over time, while the number of high runoff values increased over time. For latitudes south of ~40°S, both the greatest decrease in the number of low runoff values and the greatest increase in high runoff values occurred. High runoff values averaged 84% and 58% higher than low values for nonglacierized and glacierized catchments, respectively. Furthermore, for glacierized catchments, 61% and 62% of the runoff originated from rain-derived runoff during low and high runoff extreme years, respectively; 28% and 30% from snowmelt-derived runoff; and 11% and 8% from glacier-ice-melt-derived runoff. As the results could be MERRA dependent, more work with other precipitation forcings and/or in situ measurements is needed to assess whether these are real runoff behaviors or artifacts.
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Baba, Mohamed Wassim, Abdelghani Boudhar, Simon Gascoin, Lahoucine Hanich, Ahmed Marchane, and Abdelghani Chehbouni. "Assessment of MERRA-2 and ERA5 to Model the Snow Water Equivalent in the High Atlas (1981–2019)." Water 13, no. 7 (March 24, 2021): 890. http://dx.doi.org/10.3390/w13070890.
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Melt water runoff from seasonal snow in the High Atlas range is an essential water resource in Morocco. However, there are only few meteorological stations in the high elevation areas and therefore it is challenging to estimate the distribution of snow water equivalent (SWE) based only on in situ measurements. In this work we assessed the performance of ERA5 and MERRA-2 climate reanalysis to compute the spatial distribution of SWE in the High Atlas. We forced a distributed snowpack evolution model (SnowModel) with downscaled ERA5 and MERRA-2 data at 200 m spatial resolution. The model was run over the period 1981 to 2019 (37 water years). Model outputs were assessed using observations of river discharge, snow height and MODIS snow-covered area. The results show a good performance for both MERRA-2 and ERA5 in terms of reproducing the snowpack state for the majority of water years, with a lower bias using ERA5 forcing.
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He, Lijie, Aiwen Lin, Xinxin Chen, Hao Zhou, Zhigao Zhou, and Peipei He. "Assessment of MERRA-2 Surface PM2.5 over the Yangtze River Basin: Ground-based Verification, Spatiotemporal Distribution and Meteorological Dependence." Remote Sensing 11, no. 4 (February 23, 2019): 460. http://dx.doi.org/10.3390/rs11040460.
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A good understanding of how meteorological conditions exacerbate or mitigate air pollution is critical for developing robust emission reduction policies. Thus, based on a multiple linear regression (MLR) model in this study, the quantified impacts of six meteorological variables on PM2.5 (i.e., particle matter with diameter of 2.5 µm or less) and its major components were estimated over the Yangtze River Basin (YRB). The 38-year (1980–2017) daily PM2.5 and meteorological data were derived from the newly-released Modern-Era Retrospective Analysis and Research and Application, version 2 (MERRA-2) products. The MERRA-2 PM2.5 was underestimated compared with ground measurements, partly due to the bias in the MERRA-2 Aerosol Optical Depth (AOD) assimilation. An over-increasing trend in each PM2.5 component occurred for the whole study period; however, this has been curbed since 2007. The MLR model suggested that meteorological variability could explain up to 67% of the PM2.5 changes. PM2.5 was robustly anti-correlated with surface wind speed, precipitation and boundary layer height (BLH), but was positively correlated with temperature throughout the YRB. The relationship of relative humidity (RH) and total cloud cover with PM2.5 showed regional dependencies, with negative correlation in the Yangtze River Delta (YRD) and positive correlation in the other areas. In particular, PM2.5 was most sensitive to surface wind speed, and the sensitivity was approximately −2.42 µg m−3 m−1 s. This study highlighted the impact of meteorological conditions on PM2.5 growth, although it was much smaller than the anthropogenic emissions impact.
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Krylova, Alla I., and Natalya A. Lapteva. "STUDY OF THE INFLUENCE OF DRAIN REGULATION BY THE RESERVOIR OF THE CASCADE OF THE VILUIAN HYDROPOWER STATIONS - I, II ON THE WATER REGIME OF RIVER VILYUY." Interexpo GEO-Siberia 4, no. 1 (July 8, 2020): 66–73. http://dx.doi.org/10.33764/2618-981x-2020-4-1-66-73.
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Based on the use of a joint linear model for the formation of surface and river flows and a hydrologically correct digital relief model for the river basin. Vilyui, the influence of the Vilyui reservoir on the river flow of the river is considered. The results of long-term modeling of natural and regulated runoff based on data from the global MERRA reanalysis database for the period 1985-2005 are presented. Model results are compared with observations of water flow from the R-Arcticnet archive. According to the statistical criteria for the efficiency of the Nash-Sutcliff calculation Eff and the Bias systematic error, the joint linear model based on the correct model hydrographic network allows reproducing hydrographs of daily and monthly flows with good quality. This requires the calibration of two correction factors to the temperature of the surface air and to the redistribution of moisture content between the surface and underground runoff.
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Essou, Gilles R. C., François Brissette, and Philippe Lucas-Picher. "The Use of Reanalyses and Gridded Observations as Weather Input Data for a Hydrological Model: Comparison of Performances of Simulated River Flows Based on the Density of Weather Stations." Journal of Hydrometeorology 18, no. 2 (February 1, 2017): 497–513. http://dx.doi.org/10.1175/jhm-d-16-0088.1.
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Abstract Precipitation forcing is critical for hydrological modeling as it has a strong impact on the accuracy of simulated river flows. In general, precipitation data used in hydrological modeling are provided by weather stations. However, in regions with sparse weather station coverage, the spatial interpolation of the individual weather stations provides a rough approximation of the real precipitation fields. In such regions, precipitation from interpolated weather stations is generally considered unreliable for hydrological modeling. Precipitation estimates from reanalyses could represent an interesting alternative in regions where the weather station density is low. This article compares the performances of river flows simulated by a watershed model using precipitation and temperature estimates from reanalyses and gridded observations. The comparison was carried out based on the density of surface weather stations for 316 Canadian watersheds located in three climatic regions. Three state-of-the-art atmospheric reanalyses—ERA-Interim, CFSR, and MERRA—and one gridded observations database over Canada—Natural Resources Canada (NRCan)—were used. Results showed that the Nash–Sutcliffe values of simulated river flows using precipitation and temperature data from CFSR and NRCan were generally equivalent regardless of the weather station density. ERA-Interim and MERRA performed significantly better than NRCan for watersheds with weather station densities of less than 1 station per 1000 km2 in the mountainous region. Overall, these results indicate that for hydrological modeling in regions with high spatial variability of precipitation such as mountainous regions, reanalyses perform better than gridded observations when the weather station density is low.
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Sabarly, Florent, Gilles Essou, Philippe Lucas-Picher, Annie Poulin, and François Brissette. "Use of Four Reanalysis Datasets to Assess the Terrestrial Branch of the Water Cycle over Quebec, Canada." Journal of Hydrometeorology 17, no. 5 (April 28, 2016): 1447–66. http://dx.doi.org/10.1175/jhm-d-15-0093.1.
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Abstract Reanalyses have the potential to provide meteorological information in areas where few or no traditional observation records are available. The terrestrial branch of the water cycle of CFSR, MERRA, ERA-Interim, and NARR is examined over Quebec, Canada, for the 1979–2008 time period. Precipitation, evaporation, runoff, and water balance are studied using observed precipitation and streamflows, according to three spatial scales: 1) the entire province of Quebec, 2) five regions derived from a climate classification, and 3) 11 river basins. The results reveal that MERRA provides a relatively closed water balance, while a significant residual was found for the other three reanalyses. MERRA and ERA-Interim seem to provide the most reliable precipitation over the province. On the other hand, precipitation from CFSR and NARR do not appear to be particularly reliable, especially over southern Quebec, as they almost systematically showed the highest and the lowest values, respectively. Moreover, the partitioning of precipitation into evaporation and runoff from MERRA and NARR does not agree with what was expected, particularly over southern, central, and eastern Quebec. Despite the weaknesses identified, the ability of reanalyses to reproduce the terrestrial water cycle of the recent past (i.e., 1979–2008) remains globally satisfactory. Nonetheless, their potential to provide reliable information must be validated by comparing reanalyses directly with weather stations, especially in remote areas.
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米尔古丽•, 库尔班. "Study on the Change of Water Storage in the Ili River Basin Based on MERRA Reanalysis Data." Geographical Science Research 05, no. 03 (2016): 236–46. http://dx.doi.org/10.12677/gser.2016.53025.
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Zavadoff, Breanna L., and Ben P. Kirtman. "Dynamic and Thermodynamic Modulators of European Atmospheric Rivers." Journal of Climate 33, no. 10 (May 15, 2020): 4167–85. http://dx.doi.org/10.1175/jcli-d-19-0601.1.
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AbstractLarge-scale analysis of the dynamic and thermodynamic properties of landfalling atmospheric rivers (ARs) over western Europe is performed utilizing 38 years of the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), reanalysis dataset. A climatology of landfalling ARs from 1980 to 2017 is developed using a combination of integrated water vapor transport (IVT) calculations and a detection algorithm, which identified 578 ARs over the study period. Examination of the upper-level potential vorticity (PV) fields shows that 73% of these AR events are related to anticyclonic Rossby wave breaking (RWB), a dynamic feature which has been shown to play a role in AR strength and structure. Atmospheric river variability is also found to be closely tied to jet-stream latitude modulation by the North Atlantic Oscillation (NAO), such that during a positive NAO the North Atlantic jet is shifted north, creating an environment that is more favorable for anticyclonic RWB and AR landfalls over northern Europe, and during a negative NAO it is shifted south, creating such an environment over southern Europe.Through the use of linear regression analysis, AR strength is shown to be dependent on atmospheric moisture availability, which is found to increase as sea surface temperatures (SSTs) increase. Therefore, in a warming climate warmer SSTs leading to higher atmospheric moisture availability will result in an increase in the average strength and intensity of ARs over western Europe—a trend that has already been observed.
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Gossart, A., S. Helsen, J. T. M. Lenaerts, S. Vanden Broucke, N. P. M. van Lipzig, and N. Souverijns. "An Evaluation of Surface Climatology in State-of-the-Art Reanalyses over the Antarctic Ice Sheet." Journal of Climate 32, no. 20 (September 16, 2019): 6899–915. http://dx.doi.org/10.1175/jcli-d-19-0030.1.
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Abstract In this study, we evaluate output of near-surface atmospheric variables over the Antarctic Ice Sheet from four reanalyses: the new European Centre for Medium-Range Weather Forecasts ERA-5 and its predecessor ERA-Interim, the Climate Forecast System Reanalysis (CFSR), and the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). The near-surface temperature, wind speed, and relative humidity are compared with datasets of in situ observations, together with an assessment of the simulated surface mass balance (approximated by precipitation minus evaporation). No reanalysis clearly stands out as the best performing for all areas, seasons, and variables, and each of the reanalyses displays different biases. CFSR strongly overestimates the relative humidity during all seasons whereas ERA-5 and MERRA-2 (and, to a lesser extent, ERA-Interim) strongly underestimate relative humidity during winter. ERA-5 captures the seasonal cycle of near-surface temperature best and shows the smallest bias relative to the observations. The other reanalyses show a general temperature underestimation during the winter months in the Antarctic interior and overestimation in the coastal areas. All reanalyses underestimate the mean near-surface winds in the interior (except MERRA-2) and along the coast during the entire year. The winds at the Antarctic Peninsula are overestimated by all reanalyses except MERRA-2. All models are able to capture snowfall patterns related to atmospheric rivers, with varying accuracy. Accumulation is best represented by ERA-5, although it underestimates observed surface mass balance and there is some variability in the accumulation over the different elevation classes, for all reanalyses.
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Matthews, Jemima. "Inside Out and Outside In: The River Thames in William Shakespeare’s The Merry Wives of Windsor." Shakespeare 15, no. 4 (October 2, 2019): 410–27. http://dx.doi.org/10.1080/17450918.2019.1657172.
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Sun, Enwei, Huizheng Che, Xiaofeng Xu, Zhenzhu Wang, Chunsong Lu, Ke Gui, Hujia Zhao, et al. "Variation in MERRA-2 aerosol optical depth over the Yangtze River Delta from 1980 to 2016." Theoretical and Applied Climatology 136, no. 1-2 (May 3, 2018): 363–75. http://dx.doi.org/10.1007/s00704-018-2490-9.
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David, Mark B., Gregory F. McIsaac, Todd V. Royer, Robert G. Darmody, and Lowell E. Gentry. "Estimated Historical and Current Nitrogen Balances for Illinois." Scientific World JOURNAL 1 (2001): 597–604. http://dx.doi.org/10.1100/tsw.2001.283.
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The Midwest has large riverine exports of nitrogen (N), with the largest flux per unit area to the Mississippi River system coming from Iowa and Illinois. We used historic and current data to estimate N inputs, outputs, and transformations for Illinois where human activity (principally agriculture and associated landscape drainage) have had a dominant impact. Presently, ~800,000 Mg of N is added each year as fertilizer and another 420,000 Mg is biologically fixed, primarily by soybean (Glycine max L. Merr.). These annual inputs are greater than exports in grain, which results in surplus N throughout the landscape. Rivers within the state export approximately 50% of this surplus N, mostly as nitrate, and the remainder appears to be denitrified or temporarily incorporated into the soil organic matter pool. The magnitude of N losses for 1880, 1910, 1950, and 1990 are compared. Initial cultivation of the prairies released large quantities of N (~500,000 Mg N year�1), and resulted in riverine N transport during the late 19th century that appears to have been on the same order of magnitude as contemporary N losses. Riverine flux was estimated to have been at a minimum in about 1950, due to diminished net mineralization and low fertilizer inputs. Residual fertilizer N from corn (Zea mays L.), biological N fixed by soybean, short-circuiting of soil water through artificial drainage, and decreased cropping-system diversity appear to be the primary sources for current N export.
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Kuang, Q., and Y. P. Wang. "SPATIAL-TEMPORAL CHARACTERISTICS OF THE AEROSOL OPTICAL DEPTH (AOD) DERIVED FROM LONGTERM (1980–2018) MERRA-2 OVER GUANGDONG." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W9 (October 25, 2019): 103–8. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w9-103-2019.
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Abstract. This paper presents and compares the aerosol optical depth (AOD) spatial-temporal characteristics over five subsets in different locations of Guangdong, as well as Hong Kong and Macau (GDHM) since reform and opening-up. By means of GIS analysis tools and subset the onward MERRA-2 monthly mean value aerosol reanalysis dataset to the size of study area, the results reveal that the yearly mean AOD over the whole GDHM ranged from 0.18 to 0.69 during 1980 to 2018. The field average of AOD in five chosen areas approached to 0.40 and appeared linearly increased at 0.0077 per year. All the five selected areas reached their yearly mean AOD peaks at 2007. The field average AOD increased rapidly at 0.028 per year from 1997 till 2007 then appeared decreasing oscillation in a linear slope −0.0109 per year since 2007. But the average AOD of 2010–2018 is higher than the former three decadal averages. Comparing the former and the latter two decades, the high yearly mean AOD value clusters have moved from northern parts of Guangdong to central north Pearl River Delta, where also appeared more apparent AOD yearly change among the other three parts since late 1990s. Only six yearly mean AOD over southern cities of Pearl River estuary were lower than east or west comparing parts in 1980s. Eastern part of Guangdong stayed the lowest yearly mean AOD region in 21years of the past 39 years. Central, southern and western of GDHM had 36 years while northern and western of GDHM had 37 years their AOD values during February to April were the high values of the year.
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Huang, Chunlin, Junzhang Li, Weiwei Sun, Qixiang Chen, Qian-Jun Mao, and Yuan Yuan. "Long-Term Variation Assessment of Aerosol Load and Dominant Types over Asia for Air Quality Studies Using Multi-Sources Aerosol Datasets." Remote Sensing 13, no. 16 (August 6, 2021): 3116. http://dx.doi.org/10.3390/rs13163116.
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Long-term (2000–2019) assessment of aerosol loads and dominant aerosol types at spatiotemporal scales using multi-source datasets can provide a strong impetus to the investigation of aerosol loads and to the targeted prevention control of atmospheric pollution in densely populated regions with frequent anthropogenic activities and heavy aerosol emissions. This study uses multi-source aerosol datasets, including Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2), Moderate Resolution Imaging Spectroradiometer (MODIS), and Aerosol Robotic Network (AERONET), to conduct a long-term variation assessment of aerosol load, high aerosol load frequency, and dominant aerosol types over Asia. The results indicate that regional aerosol type information with adequate spatial resolution can be combined with aerosol optical depth (AOD) values and heavy aerosol load frequency characterization results to explore the key contributors to air pollution. During the study period, the aerosol load over the North China Plain, Central China, Yangtze River Delta, Red River Delta, Sichuan Basin, and Pearl River Delta exhibited an increasing trend from 2000–2009 due to a sharp rise in aerosol emissions with economic development and a declining trend from 2010–2019 under stricter energy conservation controls and emissions reductions. The growth of urban/industrial (UI) type and biomass burning (BB) type aerosol emissions hindered the improvement of the atmospheric environment. Therefore, in future pollution mitigation efforts, focus should be on the control of UI-type and BB-type aerosol emissions. The Indus–Ganges River Plain, Deccan Plateau, and Eastern Ghats show a continuously increasing trend; however, the aerosol load growth rate of the last decade was lower than that of the first decade, which was mainly due to the decrease in the proportion of the mixed type aerosols.
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Mundhenk, Bryan D., Elizabeth A. Barnes, and Eric D. Maloney. "All-Season Climatology and Variability of Atmospheric River Frequencies over the North Pacific." Journal of Climate 29, no. 13 (June 16, 2016): 4885–903. http://dx.doi.org/10.1175/jcli-d-15-0655.1.
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Abstract Recent work on atmospheric rivers (ARs) has led to a characterization of these impactful features as primarily cold-season phenomena. Here, an all-season analysis of AR incidence in the North Pacific basin is performed for the period spanning 1979–2014 using the NASA Modern-Era Retrospective Analysis for Research and Applications (MERRA) reanalysis dataset. An occurrence-based detection algorithm is developed and employed to identify and characterize ARs in instantaneous fields of anomalous vertically integrated water vapor transport. The all-season climatology and variability of AR frequencies due to the seasonal cycle, the El Niño–Southern Oscillation (ENSO), the Madden–Julian oscillation (MJO), and their interactions are presented based on composites of the detected features. The results highlight that ARs exist throughout the year over the North Pacific, although their preferred locations shift substantially throughout the year. This seasonal cycle manifests itself as northward and westward displacement of ARs during the Northern Hemisphere warm seasons, rather than an absolute change in the number of ARs within the domain. It is also shown that changes to the North Pacific mean-state due to ENSO and the MJO may enhance or completely offset the seasonal cycle of AR activity, but that such influences on AR frequencies vary greatly based on location.
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Payne, Ashley E., and Gudrun Magnusdottir. "Dynamics of Landfalling Atmospheric Rivers over the North Pacific in 30 Years of MERRA Reanalysis." Journal of Climate 27, no. 18 (September 10, 2014): 7133–50. http://dx.doi.org/10.1175/jcli-d-14-00034.1.
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Abstract A large-scale analysis of landfalling atmospheric rivers (ARs) along the west coast of North America and their association with the upper-tropospheric flow is performed for the extended winter (November–March) for the years 1979–2011 using Modern-Era Retrospective Analysis for Research and Applications (MERRA) reanalysis data. The climatology, relationship to the El Niño–Southern Oscillation and the Madden–Julian oscillation, and upper-level characteristics of approximately 750 landfalling ARs are presented based on the 85th percentile of peak daily moisture flux. AR occurrence along the West Coast is dominated by early season events. In composites of upper-level fields during AR occurrences, certain characteristics stand out irrespective of the tropical climate indices. This suggests that extratropical dynamical processes play a key role in AR dynamics. The influence of the large-scale circulation on AR intensity prior to landfall is examined by objectively selecting an extreme subset of 112 landfalling AR dates representing the 95th percentile of strongest cases. Each landfalling AR date that is identified is traced backward in time using a novel semiautomated tracking algorithm based on spatially and temporally connected organized features in integrated moisture transport. Composites of dynamical fields following the eastward progression of ARs show a close relationship of the location of the jet, Rossby wave propagation, and anticyclonic Rossby wave breaking in the upper troposphere of the eastern Pacific and moisture transport in the lower troposphere. Comparison between the strongest and the weakest ARs within the most extreme subset shows differences in both the intensity of moisture transport and the scale and development of anticyclonic Rossby wave breaking in the eastern Pacific.
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Guan, Bin, Duane E. Waliser, and F. Martin Ralph. "An Intercomparison between Reanalysis and Dropsonde Observations of the Total Water Vapor Transport in Individual Atmospheric Rivers." Journal of Hydrometeorology 19, no. 2 (February 1, 2018): 321–37. http://dx.doi.org/10.1175/jhm-d-17-0114.1.
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Abstract A recent study presented nearly two decades of airborne atmospheric river (AR) observations and concluded that, on average, an individual AR transports ~5 × 108 kg s−1 of water vapor. The study here compares those cases to ARs independently identified in reanalyses based on a refined algorithm that can detect less well-structured ARs, with the dual-purpose of validating reanalysis ARs against observations and evaluating dropsonde representativeness relative to reanalyses. The first comparison is based on 21 dropsonde-observed ARs in the northeastern Pacific and those closely matched, but not required to be exactly collocated, in ERA-Interim (MERRA-2), which indicates a mean error of −2% (−8%) in AR width and +3% (−1%) in total integrated water vapor transport (TIVT) and supports the effectiveness of the AR detection algorithm applied to the reanalyses. The second comparison is between the 21 dropsonde ARs and ~6000 ARs detected in ERA-Interim (MERRA-2) over the same domain, which indicates a mean difference of 5% (20%) in AR width and 5% (14%) in TIVT and suggests the limited number of dropsonde observations is a highly (reasonably) representative sampling of ARs in the northeastern Pacific. Sensitivities of the comparison to seasonal and geographical variations in AR width/TIVT are also examined. The results provide a case where dedicated observational efforts in specific regions corroborate with global reanalyses in better characterizing the geometry and strength of ARs regionally and globally. The results also illustrate that the reanalysis depiction of ARs can help inform the selection of locations for future observational and modeling efforts.
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Shields, Christine A., Jonathan J. Rutz, Lai-Yung Leung, F. Martin Ralph, Michael Wehner, Brian Kawzenuk, Juan M. Lora, et al. "Atmospheric River Tracking Method Intercomparison Project (ARTMIP): project goals and experimental design." Geoscientific Model Development 11, no. 6 (June 20, 2018): 2455–74. http://dx.doi.org/10.5194/gmd-11-2455-2018.
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Abstract. The Atmospheric River Tracking Method Intercomparison Project (ARTMIP) is an international collaborative effort to understand and quantify the uncertainties in atmospheric river (AR) science based on detection algorithm alone. Currently, there are many AR identification and tracking algorithms in the literature with a wide range of techniques and conclusions. ARTMIP strives to provide the community with information on different methodologies and provide guidance on the most appropriate algorithm for a given science question or region of interest. All ARTMIP participants will implement their detection algorithms on a specified common dataset for a defined period of time. The project is divided into two phases: Tier 1 will utilize the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) reanalysis from January 1980 to June 2017 and will be used as a baseline for all subsequent comparisons. Participation in Tier 1 is required. Tier 2 will be optional and include sensitivity studies designed around specific science questions, such as reanalysis uncertainty and climate change. High-resolution reanalysis and/or model output will be used wherever possible. Proposed metrics include AR frequency, duration, intensity, and precipitation attributable to ARs. Here, we present the ARTMIP experimental design, timeline, project requirements, and a brief description of the variety of methodologies in the current literature. We also present results from our 1-month “proof-of-concept” trial run designed to illustrate the utility and feasibility of the ARTMIP project.
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Muszynski, Grzegorz, Karthik Kashinath, Vitaliy Kurlin, and Michael Wehner. "Topological data analysis and machine learning for recognizing atmospheric river patterns in large climate datasets." Geoscientific Model Development 12, no. 2 (February 7, 2019): 613–28. http://dx.doi.org/10.5194/gmd-12-613-2019.
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Abstract. Identifying weather patterns that frequently lead to extreme weather events is a crucial first step in understanding how they may vary under different climate change scenarios. Here, we propose an automated method for recognizing atmospheric rivers (ARs) in climate data using topological data analysis and machine learning. The method provides useful information about topological features (shape characteristics) and statistics of ARs. We illustrate this method by applying it to outputs of version 5.1 of the Community Atmosphere Model version 5.1 (CAM5.1) and the reanalysis product of the second Modern-Era Retrospective Analysis for Research and Applications (MERRA-2). An advantage of the proposed method is that it is threshold-free – there is no need to determine any threshold criteria for the detection method – when the spatial resolution of the climate model changes. Hence, this method may be useful in evaluating model biases in calculating AR statistics. Further, the method can be applied to different climate scenarios without tuning since it does not rely on threshold conditions. We show that the method is suitable for rapidly analyzing large amounts of climate model and reanalysis output data.
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Essou, Gilles R. C., Florent Sabarly, Philippe Lucas-Picher, François Brissette, and Annie Poulin. "Can Precipitation and Temperature from Meteorological Reanalyses Be Used for Hydrological Modeling?" Journal of Hydrometeorology 17, no. 7 (July 1, 2016): 1929–50. http://dx.doi.org/10.1175/jhm-d-15-0138.1.
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Abstract This paper investigates the potential of reanalyses as proxies of observed surface precipitation and temperature to force hydrological models. Three global atmospheric reanalyses (ERA-Interim, CFSR, and MERRA), one regional reanalysis (NARR), and one global meteorological forcing dataset obtained by bias-correcting ERA-Interim [Water and Global Change (WATCH) Forcing Data ERA-Interim (WFDEI)] were compared to one gridded observation database over the contiguous United States. Results showed that all temperature datasets were similar to the gridded observation over most of the United States. On the other hand, precipitation from all three global reanalyses was biased, especially in summer and winter in the southeastern United States. The regional reanalysis precipitation was closer to observations since it indirectly assimilates surface precipitation. The WFDEI dataset was generally less biased than the reanalysis datasets. All datasets were then used to force a global conceptual hydrological model on 370 watersheds of the Model Parameter Estimation Experiment (MOPEX) database. River flows were computed for each watershed, and results showed that the flows simulated using NARR and gridded observations forcings were very similar to the observed flows. The simulated flows forced by the global reanalysis datasets were also similar to the observations, except in the humid continental and subtropical climatic regions, where precipitation seasonality biases degraded river flow simulations. The WFDEI dataset led to better river flows than reanalysis in the humid continental and subtropical climatic regions but was no better than reanalysis—and sometimes worse—in other climatic zones. Overall, the results indicate that global reanalyses have good potential to be used as proxies to observations to force hydrological models, especially in regions with few weather stations.
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Whatley, Edward. "Book Review: 100 Great War Movies: The Real History Behind the Films." Reference & User Services Quarterly 58, no. 2 (January 18, 2019): 124. http://dx.doi.org/10.5860/rusq.58.2.6940.
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The one hundred films covered by Robert Niemi’s 100 Great War Movies: The Real History Behind the Films were selected using an eclectic array of criteria (the preferences of the author based on his experience as a film teacher, the preferences of his friends and colleagues, and a survey of numerous best-of lists), and the result is of course a rather eclectic collection of entries. Coverage includes famous well-regarded films that most readers will expect to find in a collection such as this: The Bridge on the River Kwai, From Here to Eternity, and Saving Private Ryan. But readers will also encounter films with which they may not be as familiar, such as Merry Christmas, Mr. Lawrence starring David Bowie, and the film adaptation of Kurt Vonnegut’s Slaughterhouse-Five. The films included also cover a wide range of ideological viewpoints: from patriotic World War II–era films to more recent films that take a more skeptical view of warfare.
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Dirmeyer, Paul A., Jiangfeng Wei, Michael G. Bosilovich, and David M. Mocko. "Comparing Evaporative Sources of Terrestrial Precipitation and Their Extremes in MERRA Using Relative Entropy." Journal of Hydrometeorology 15, no. 1 (February 1, 2014): 102–16. http://dx.doi.org/10.1175/jhm-d-13-053.1.
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Abstract A quasi-isentropic, back-trajectory scheme is applied to output from the Modern-Era Retrospective Analysis for Research and Applications (MERRA) and a land-only replay with corrected precipitation to estimate surface evaporative sources of moisture supplying precipitation over every ice-free land location for the period 1979–2005. The evaporative source patterns for any location and time period are effectively two-dimensional probability distributions. As such, the evaporative sources for extreme situations like droughts or wet intervals can be compared to the corresponding climatological distributions using the method of relative entropy. Significant differences are found to be common and widespread for droughts, but not wet periods, when monthly data are examined. At pentad temporal resolution, which is more able to isolate floods and situations of atmospheric rivers, values of relative entropy over North America are typically 50%–400% larger than at monthly time scales. Significant differences suggest that moisture transport may be a key factor in precipitation extremes. Where evaporative sources do not change significantly, it implies other local causes may underlie the extreme events.
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Tengeleng, SIDDI. "Monthly Predicted Flow Values of the Sanaga River in Cameroon Using Neural Networks Applied to GLDAS, MERRA and GPCP Data." Journal of Water Resources and Ocean Science 3, no. 2 (2014): 22. http://dx.doi.org/10.11648/j.wros.20140302.12.
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Ferguson, Craig R., and David M. Mocko. "Diagnosing an Artificial Trend in NLDAS-2 Afternoon Precipitation." Journal of Hydrometeorology 18, no. 4 (March 28, 2017): 1051–70. http://dx.doi.org/10.1175/jhm-d-16-0251.1.
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Abstract While investigating linkages between afternoon peak rainfall amount and land–atmosphere coupling strength, a statistically significant trend in phase 2 of the North American Land Data Assimilation System (NLDAS-2) warm season (April–September) afternoon (1700–2259 UTC) precipitation was noted for a large fraction of the conterminous United States, namely, two-thirds of the area east of the Mississippi River, during the period from 1979 to 2015. To verify and better characterize this trend, a thorough statistical analysis is undertaken. The analysis focuses on three aspects of precipitation: amount, frequency, and intensity at 6-hourly time scale and for each calendar month separately. At the NLDAS-2 native resolution of 0.125° × 0.125°, Kendall’s tau and Sen’s slope estimators are used to detect and estimate trends and the Pettitt test is used to detect breakpoints. Parallel analyses are conducted on both NARR and Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), subdaily precipitation estimates. Widespread breakpoints of field significance at the α = 0.05 level are detected in the NLDAS-2 frequency and intensity series for all months and 6-h periods that are absent from the analogous NARR and MERRA-2 datasets. These breakpoints are shown to correspond with a July 1996 NLDAS-2 transition away from hourly 2° × 2.5° NOAA/CPC precipitation estimates to hourly 4-km stage II Doppler radar precipitation estimates in the temporal disaggregation of CPC daily gauge analyses. While NLDAS-2 may provide the most realistic diurnal precipitation cycle overall, users should be aware of this discontinuity and its direct effect on long-term trends in subdaily precipitation and indirect effects on trends in modeled soil moisture, surface temperature, surface energy and water fluxes, snow cover, snow water equivalent, and runoff/streamflow.
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Dembélé, Moctar, Bettina Schaefli, Nick van de Giesen, and Grégoire Mariéthoz. "Suitability of 17 gridded rainfall and temperature datasets for large-scale hydrological modelling in West Africa." Hydrology and Earth System Sciences 24, no. 11 (November 16, 2020): 5379–406. http://dx.doi.org/10.5194/hess-24-5379-2020.
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Abstract. This study evaluates the ability of different gridded rainfall datasets to plausibly represent the spatio-temporal patterns of multiple hydrological processes (i.e. streamflow, actual evaporation, soil moisture and terrestrial water storage) for large-scale hydrological modelling in the predominantly semi-arid Volta River basin (VRB) in West Africa. Seventeen precipitation products based essentially on gauge-corrected satellite data (TAMSAT, CHIRPS, ARC, RFE, MSWEP, GSMaP, PERSIANN-CDR, CMORPH-CRT, TRMM 3B42 and TRMM 3B42RT) and on reanalysis (ERA5, PGF, EWEMBI, WFDEI-GPCC, WFDEI-CRU, MERRA-2 and JRA-55) are compared as input for the fully distributed mesoscale Hydrologic Model (mHM). To assess the model sensitivity to meteorological forcing during rainfall partitioning into evaporation and runoff, six different temperature reanalysis datasets are used in combination with the precipitation datasets, which results in evaluating 102 combinations of rainfall–temperature input data. The model is recalibrated for each of the 102 input combinations, and the model responses are evaluated by using in situ streamflow data and satellite remote-sensing datasets from GLEAM evaporation, ESA CCI soil moisture and GRACE terrestrial water storage. A bias-insensitive metric is used to assess the impact of meteorological forcing on the simulation of the spatial patterns of hydrological processes. The results of the process-based evaluation show that the rainfall datasets have contrasting performances across the four climatic zones present in the VRB. The top three best-performing rainfall datasets are TAMSAT, CHIRPS and PERSIANN-CDR for streamflow; ARC, RFE and CMORPH-CRT for terrestrial water storage; MERRA-2, EWEMBI/WFDEI-GPCC and PGF for the temporal dynamics of soil moisture; MSWEP, TAMSAT and ARC for the spatial patterns of soil moisture; ARC, RFE and GSMaP-std for the temporal dynamics of actual evaporation; and MSWEP, TAMSAT and MERRA-2 for the spatial patterns of actual evaporation. No single rainfall or temperature dataset consistently ranks first in reproducing the spatio-temporal variability of all hydrological processes. A dataset that is best in reproducing the temporal dynamics is not necessarily the best for the spatial patterns. In addition, the results suggest that there is more uncertainty in representing the spatial patterns of hydrological processes than their temporal dynamics. Finally, some region-tailored datasets outperform the global datasets, thereby stressing the necessity and importance of regional evaluation studies for satellite and reanalysis meteorological datasets, which are increasingly becoming an alternative to in situ measurements in data-scarce regions.
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Dettinger, Michael D., F. Martin Ralph, and Jonathan J. Rutz. "Empirical Return Periods of the Most Intense Vapor Transports during Historical Atmospheric River Landfalls on the U.S. West Coast." Journal of Hydrometeorology 19, no. 8 (August 1, 2018): 1363–77. http://dx.doi.org/10.1175/jhm-d-17-0247.1.
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Abstract Atmospheric rivers (ARs) come in all intensities, and clear communication of risks posed by individual storms in observations and forecasts can be a challenge. Modest ARs can be characterized by the percentile rank of their integrated water vapor transport (IVT) rates compared to past ARs. Stronger ARs can be categorized more clearly in terms of return periods or, equivalently, historical probabilities that at least one AR will exceed a given IVT threshold in any given year. Based on a 1980–2016 chronology of AR landfalls on the U.S. West Coast from NASA’s Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), datasets, the largest instantaneous IVTs—greater than 1700 kg m−1 s−1—have occurred in ARs making landfall between 41° and 46°N with return periods longer than 20 years. IVT values with similar return periods are smaller to the north and, especially, to the south (declining to ~750 kg m−1 s−1). The largest storm-sequence IVT totals have been centered near 42.5°N, with scatter among the top few events, and these large storm-sequence totals depend more on sequence duration than on the instantaneous IVT that went into them. Maximum instantaneous IVTs are largest in the Pacific Northwest in autumn, with largest IVT values arriving farther south as winter and spring unfold, until maximum IVTs reach Northern California in spring.
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O'Brien, Travis A., Mark D. Risser, Burlen Loring, Abdelrahman A. Elbashandy, Harinarayan Krishnan, Jeffrey Johnson, Christina M. Patricola, et al. "Detection of atmospheric rivers with inline uncertainty quantification: TECA-BARD v1.0.1." Geoscientific Model Development 13, no. 12 (December 3, 2020): 6131–48. http://dx.doi.org/10.5194/gmd-13-6131-2020.
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Abstract. It has become increasingly common for researchers to utilize methods that identify weather features in climate models. There is an increasing recognition that the uncertainty associated with choice of detection method may affect our scientific understanding. For example, results from the Atmospheric River Tracking Method Intercomparison Project (ARTMIP) indicate that there are a broad range of plausible atmospheric river (AR) detectors and that scientific results can depend on the algorithm used. There are similar examples from the literature on extratropical cyclones and tropical cyclones. It is therefore imperative to develop detection techniques that explicitly quantify the uncertainty associated with the detection of events. We seek to answer the following question: given a “plausible” AR detector, how does uncertainty in the detector quantitatively impact scientific results? We develop a large dataset of global AR counts, manually identified by a set of eight researchers with expertise in atmospheric science, which we use to constrain parameters in a novel AR detection method. We use a Bayesian framework to sample from the set of AR detector parameters that yield AR counts similar to the expert database of AR counts; this yields a set of “plausible” AR detectors from which we can assess quantitative uncertainty. This probabilistic AR detector has been implemented in the Toolkit for Extreme Climate Analysis (TECA), which allows for efficient processing of petabyte-scale datasets. We apply the TECA Bayesian AR Detector, TECA-BARD v1.0.1, to the MERRA-2 reanalysis and show that the sign of the correlation between global AR count and El Niño–Southern Oscillation depends on the set of parameters used.
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Smith, Laurence C., Kang Yang, Lincoln H. Pitcher, Brandon T. Overstreet, Vena W. Chu, Åsa K. Rennermalm, Jonathan C. Ryan, et al. "Direct measurements of meltwater runoff on the Greenland ice sheet surface." Proceedings of the National Academy of Sciences 114, no. 50 (December 5, 2017): E10622—E10631. http://dx.doi.org/10.1073/pnas.1707743114.
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Meltwater runoff from the Greenland ice sheet surface influences surface mass balance (SMB), ice dynamics, and global sea level rise, but is estimated with climate models and thus difficult to validate. We present a way to measure ice surface runoff directly, from hourly in situ supraglacial river discharge measurements and simultaneous high-resolution satellite/drone remote sensing of upstream fluvial catchment area. A first 72-h trial for a 63.1-km2moulin-terminating internally drained catchment (IDC) on Greenland’s midelevation (1,207–1,381 m above sea level) ablation zone is compared with melt and runoff simulations from HIRHAM5, MAR3.6, RACMO2.3, MERRA-2, and SEB climate/SMB models. Current models cannot reproduce peak discharges or timing of runoff entering moulins but are improved using synthetic unit hydrograph (SUH) theory. Retroactive SUH applications to two older field studies reproduce their findings, signifying that remotely sensed IDC area, shape, and supraglacial river length are useful for predicting delays in peak runoff delivery to moulins. Applying SUH to HIRHAM5, MAR3.6, and RACMO2.3 gridded melt products for 799 surrounding IDCs suggests their terminal moulins receive lower peak discharges, less diurnal variability, and asynchronous runoff timing relative to climate/SMB model output alone. Conversely, large IDCs produce high moulin discharges, even at high elevations where melt rates are low. During this particular field experiment, models overestimated runoff by +21 to +58%, linked to overestimated surface ablation and possible meltwater retention in bare, porous, low-density ice. Direct measurements of ice surface runoff will improve climate/SMB models, and incorporating remotely sensed IDCs will aid coupling of SMB with ice dynamics and subglacial systems.
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Zhao, W., L. Sun, T. Cui, W. Cao, Y. Ma, and Y. Hao. "Mapping the distribution of suspended particulate matter concentrations influenced by storm surge in the Yellow River Estuary using FY-3A MERSI 250-m data." Aquatic Ecosystem Health & Management 17, no. 3 (July 3, 2014): 290–98. http://dx.doi.org/10.1080/14634988.2014.944821.
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Awange, Joseph L., and Ehsan Forootan. "Interannual variability of temperature in the UTLS region over Ganges–Brahmaputra–Meghna river basin based on COSMIC GNSS RO data." Atmospheric Measurement Techniques 9, no. 4 (April 15, 2016): 1685–99. http://dx.doi.org/10.5194/amt-9-1685-2016.
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Abstract. Poor reliability of radiosonde records across South Asia imposes serious challenges in understanding the structure of upper-tropospheric and lower-stratospheric (UTLS) region. The Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) mission launched in April 2006 has overcome many observational limitations inherent in conventional atmospheric sounding instruments. This study examines the interannual variability of UTLS temperature over the Ganges–Brahmaputra–Meghna (GBM) river basin in South Asia using monthly averaged COSMIC radio occultation (RO) data, together with two global reanalyses. Comparisons between August 2006 and December 2013 indicate that MERRA (Modern-Era Retrospective Analysis for Research Application) and ERA-Interim (European Centre for Medium-Range Weather Forecasts reanalysis) are warmer than COSMIC RO data by 2 °C between 200 and 50 hPa levels. These warm biases with respect to COSMIC RO data are found to be consistent over time. The UTLS temperature show considerable interannual variability from 2006 to 2013 in addition to warming (cooling) trends in the troposphere (stratosphere). The cold (warm) anomalies in the upper troposphere (tropopause region) are found to be associated with warm ENSO (El Niño–Southern Oscillation) phase, while quasi-biennial oscillation (QBO) is negatively (positively) correlated with temperature anomalies at 70 hPa (50 hPa) level. PCA (principal component analysis) decomposition of tropopause temperatures and heights over the basin indicate that ENSO accounts for 73 % of the interannual (non-seasonal) variability with a correlation of 0.77 with Niño3.4 index whereas the QBO explains about 10 % of the variability. The largest tropopause anomaly associated with ENSO occurs during the winter, when ENSO reaches its peak. The tropopause temperature (height) increased (decreased) by about 1.5 °C (300 m) during the last major El Niño event of 2009/2010. In general, we find decreasing (increasing) trend in tropopause temperature (height) between 2006 and 2013.
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Güher, Hüseyin, Burak Öterler, Belgin Elipek, Okan Yeler, and Gazel Aydin. "Spatial and temporal evaluation of physicochemical quality of drinking/using water in Kırklareli Reservoir (Turkish Thrace)." Journal of the Serbian Chemical Society, no. 00 (2021): 74. http://dx.doi.org/10.2298/jsc210601074g.
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K?rklareli Reservoir locating in Meri?-Ergene River Basin is an important drinking/using a freshwater resource of K?rklareli Province. In order to ensure the sustainable use of this important reservoir, its current situation should be examined periodically and evaluated by multivariate analyses. For this reason, the water samples were taken between the dates April 2018 and February 2019 at monthly intervals from 3 different stations. The data of environmental and physicochemical variables (water temperature, dissolved oxygen, pH, salinity, conductivity, total dissolved solids, Chlorophyll-a, light permeability, fluoride, chloride, NO2-N, NO3-N, PO4, SO4, and essential/potentially toxic elements) measured and evaluated according to the classes in surface water quality control regulation of Turkey. The parameters exceeding first-class water quality values (chlorophyll-a, pH, NO2-N, chloride, selenium) were mapped in GIS using Spline integration approach. Also, Sodium Absorbtion Ratio, Kelly Index Values, and Magnesium Ratio, were calculated to evaluate the water quality for agricultural irrigation water standards. The water quality of the reservoir was evaluated by using multivariance analyses (Bray-Curtis Similarity Index, Correspondence Analyses, Pearson Correlation Index). As a result, it was emphasized that using GIS approach is a potential useful method of monitoring the sustainable water quality of K?rklareli reservoir which is determined to have an oligomesotrophic character.
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Slinskey, Emily A., Paul C. Loikith, Duane E. Waliser, Bin Guan, and Andrew Martin. "A Climatology of Atmospheric Rivers and Associated Precipitation for the Seven U.S. National Climate Assessment Regions." Journal of Hydrometeorology 21, no. 11 (November 2020): 2439–56. http://dx.doi.org/10.1175/jhm-d-20-0039.1.
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AbstractAtmospheric rivers (ARs) are long, narrow filamentary regions of enhanced vertically integrated water vapor transport (IVT) that play an important role in regional water supply and hydrometeorological extremes. Here, an AR detection algorithm is applied to global reanalysis from Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), to objectively and consistently characterize ARs regionally across the continental United States (CONUS). The characteristics of AR and associated precipitation are computed at the gridpoint scale and summarized over the seven U.S. National Climate Assessment regions. ARs are most frequent in the autumn and winter in the West, spring in the Great Plains, and autumn in the Midwest and Northeast. ARs show regional and seasonal variability in basic geometry and IVT. AR IVT composites reveal annually consistent northeastward-directed moisture transport from the Pacific Ocean in the West, whereas moisture transport patterns vary seasonally across the Southern Great Plains and Midwest. Linked AR precipitation characteristics suggest that a substantial proportion of extreme events, defined as the top 5% of 3-day precipitation totals, are associated with ARs over many parts of CONUS, including the East. Regional patterns of AR-associated precipitation highlight that seasonally varying moisture transport and lifting mechanisms differ between the East and the West where orographic lifting is key. Our study aims to contribute a comprehensive and consistent CONUS-wide, regional-scale analysis of ARs in support of ongoing NCA efforts. Given the CONUS-wide role ARs play in extreme precipitation, findings motivate continued study of associated climate change impacts.
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Mattingly, Kyle S., Thomas L. Mote, Xavier Fettweis, Dirk van As, Kristof Van Tricht, Stef Lhermitte, Claire Pettersen, and Robert S. Fausto. "Strong Summer Atmospheric Rivers Trigger Greenland Ice Sheet Melt through Spatially Varying Surface Energy Balance and Cloud Regimes." Journal of Climate 33, no. 16 (August 15, 2020): 6809–32. http://dx.doi.org/10.1175/jcli-d-19-0835.1.
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ABSTRACTMass loss from the Greenland Ice Sheet (GrIS) has accelerated over the past two decades, coincident with rapid Arctic warming and increasing moisture transport over Greenland by atmospheric rivers (ARs). Summer ARs affecting western Greenland trigger GrIS melt events, but the physical mechanisms through which ARs induce melt are not well understood. This study elucidates the coupled surface–atmosphere processes by which ARs force GrIS melt through analysis of the surface energy balance (SEB), cloud properties, and local- to synoptic-scale atmospheric conditions during strong summer AR events affecting western Greenland. ARs are identified in MERRA-2 reanalysis (1980–2017) and classified by integrated water vapor transport (IVT) intensity. SEB, cloud, and atmospheric data from regional climate model, observational, reanalysis, and satellite-based datasets are used to analyze melt-inducing physical processes during strong, >90th percentile “AR90+” events. Near AR “landfall,” AR90+ days feature increased cloud cover that reduces net shortwave radiation and increases net longwave radiation. As these oppositely signed radiative anomalies partly cancel during AR90+ events, increased melt energy in the ablation zone is primarily provided by turbulent heat fluxes, particularly sensible heat flux. These turbulent heat fluxes are driven by enhanced barrier winds generated by a stronger synoptic pressure gradient combined with an enhanced local temperature contrast between cool over-ice air and the anomalously warm surrounding atmosphere. During AR90+ events in northwest Greenland, anomalous melt is forced remotely through a clear-sky foehn regime produced by downslope flow in eastern Greenland.
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DAUDU, Yusuf O. A., Olamide A. FALUSI, Abdulhakeem ABUBAKAR, Ibrahim A. SALIHU, Shaibu O. OTARU, and Muflihah A. UMAR. "Aqueous seed extracts of Jimson weed (Datura stramonium L.) stimulate morpho-agronomic attributes in selected soybean [Glycine max (L.) Merr.] varieties." Notulae Scientia Biologicae 13, no. 1 (February 3, 2021): 10876. http://dx.doi.org/10.15835/nsb13110876.
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Datura stramonium (L.) contains allelochemicals capable of affecting agro-morphological traits in plants. Thus, field experiment was carried out at Upper Niger River Basin Development Authority, Minna, Nigeria to examine the effects of different concentrations [25%, 50% and 100% and 0% (control)] of D. stramonium aqueous seed extracts on agro-morphological attributes of two soybean varieties (‘TG x 2018-5E’ and ‘TG x 2022-4E’), obtained from International Institute of Tropical Agriculture, Ibadan. Dry seeds of the soybean were pre-soaked in the Datura seed extracts for two hours before planting in a complete randomized block design (CRBD) with three replicates each. Data obtained were subjected to analysis of variance (ANOVA). At maturity, D. stramonium seed extracts significantly (P ≤ 0.05) increased plant height (38.37 cm) and length of petiole (2.93 cm) for ‘TG x 2018-5E’ at 100% concentration. Significantly highest plant height (29.20 cm) and number of branches (17.00) were enhanced in ‘TG x 2022-4E’ at 50% concentration. Both ‘TG x 2018-5E’ and ‘TG x 2022-4E’ leaf areas were significantly highest (23.11 cm2 and 28.41 cm2, respectively) at 100% concentration. Yield attributes such as number of seeds per plant, weight of fresh and dry pods per plant for both ‘TG x 2018-5E’ (3.33, 1.60 and 1.32, respectively) and ‘TG x 2022-4E’ (3.00, 0.60 and 0.26, respectively) were significantly stimulated in 50% concentration while number of pods per plant was significantly highest for ‘TG x 2018-5E’ and ‘TG x 2022- 4E’ (3.33 and 3.00, respectively) in 100% concentration. On these premises higher concentrations (50% and 100%) of D. stramonium seed extracts support better morphological growth and yield characters in soybean varieties.
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Bai, Bing, Qiang Zhang, Dan Tan, Pengcheng Huang, and Fei Yin. "Responses of the Optical Properties and Distribution of Aerosols to the Summer Monsoon in the Main Climate Zones of China." Atmosphere 12, no. 4 (April 11, 2021): 482. http://dx.doi.org/10.3390/atmos12040482.
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The influence of aerosols on climate varies greatly within different spatial zones. China has a very prominent summer monsoon climate and summer monsoon activity basically determines the climate distribution pattern. Consequently, we need to understand the aerosol optical properties and spatial distribution under the background of summer monsoon activity in China, which is the basis for further research on the impact of aerosols on the climate system. Based on Moderate Resolution Imaging Spectroradiometer (MODIS) and Modern-Era Retrospective Analysis for Research and Applications (MERRA-2) data, the spatial response of the high aerosol optical depth (AOD) region in China to the advance and retreat of summer monsoon was analyzed. The main types of aerosol and the contribution of each type of aerosol particles to the total AOD were discussed. The results showed that before the landing of summer monsoon, the high value areas of AOD were distributed in the eastern Sichuan Basin, Changsha, Wuhan and Pearl River Delta regions. With the northward advance of the monsoon, the high value areas moved to the transition region affected by the summer monsoon and the AOD in this region was highly sensitive to the summer monsoon. The main aerosol types were dust and sulfate in this region and the contribution to total AOD was 27% and 57%, respectively; before the monsoon onset, the contribution of dust to total AOD was 16%, and that of sulfate was 18%; after the monsoon onset, the contribution of dust decreased by half to 8%, while the contribution of sulfate aerosol increased to 20%.
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Zhang, Weixing, Yidong Lou, Jinfang Huang, Fu Zheng, Yunchang Cao, Hong Liang, Chuang Shi, and Jingnan Liu. "Multiscale Variations of Precipitable Water over China Based on 1999–2015 Ground-Based GPS Observations and Evaluations of Reanalysis Products." Journal of Climate 31, no. 3 (January 12, 2018): 945–62. http://dx.doi.org/10.1175/jcli-d-17-0419.1.
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Abstract The dense ground-based GPS provides a good tool to study water vapor distribution and multiscale variations, especially for linear trends on the interannual scale and short-term variations on the diurnal scale. It can also serve as an independent data source to evaluate performances of reanalyses. In this study, the 6-hourly precipitable water (PW) products at more than 260 GPS stations over China from 1999 to 2015 were analyzed and eight commonly used reanalyses, including 20CR version 2 (20CRv2), CFSR, ERA-Interim, JRA-25, JRA-55, MERRA, NCEP–NCAR, and NCEP–DOE AMIP-II, were evaluated. The climatological annual mean GPS PW distribution over China roughly shows a decreasing trend from southeast to northwest, with the largest annual and semiannual amplitudes in the lower reaches of the Yangtze River and mideastern China, respectively, and the smallest values in the Tibetan Plateau and southwestern China. All reanalyses (except for 20CRv2) can generally reproduce well the climatological annual mean PW (within 20%), annual amplitudes (within 20%), and semiannual amplitudes (within 20% except in the tropical monsoon region), but they all show wet biases in the Tibetan Plateau. Diurnal variation amplitudes reproduced by all reanalysis products are smaller than amplitudes estimated from GPS observations over China as a whole, and none of the reanalyses can capture the diurnal phases correctly. PW linear trends at most GPS stations in the recent 16 years are insignificant or with absolute values smaller than 0.10 mm yr−1. However, because of the assimilation of the unhomogenized radiosonde humidity data, most reanalyses show artificial decreasing PW trends (except in 20CRv2 and CFSR).
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Schubert, Siegfried, Yehui Chang, Hailan Wang, Randal Koster, and Max Suarez. "A Modeling Study of the Causes and Predictability of the Spring 2011 Extreme U.S. Weather Activity." Journal of Climate 29, no. 21 (October 21, 2016): 7869–87. http://dx.doi.org/10.1175/jcli-d-15-0673.1.
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Abstract This study examines the causes and predictability of the spring 2011 U.S. extreme weather using the Modern-Era Retrospective Analysis for Research and Applications (MERRA) and Goddard Earth Observing System Model, version 5, (GEOS-5) atmospheric general circulation model simulations. The focus is on assessing the impact on precipitation of sea surface temperature (SST) anomalies, land conditions, and large-scale atmospheric modes of variability. A key result is that the April record-breaking precipitation in the Ohio River valley was primarily the result of the unforced development of a positive North Atlantic Oscillation (NAO)-like mode of variability with unusually large amplitude, limiting the predictability of the precipitation in that region at 1-month leads. SST forcing (La Niña conditions) contributed to the broader continental-scale pattern of precipitation anomalies, producing drying in the southern plains and weak wet anomalies in the northeast, while the impact of realistic initial North American land conditions was to enhance precipitation in the upper Midwest and produce deficits in the Southeast. It was further found that 1) the 1 March atmospheric initial condition was the primary source of the ensemble mean precipitation response over the eastern United States in April (well beyond the limit of weather predictability), suggesting an influence on the initial state of the previous SST forcing and/or tropospheric–stratospheric coupling linked to an unusually persistent and cold polar vortex; and 2) stationary wave model experiments suggest that the SST-forced base state for April enhanced the amplitude of the NAO response compared to that of the climatological state, though the impact is modest and can be of either sign.
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Su, Zhi Yao, Yu Duan Ou, Yan Ming Li, and Yi Zhou. "Soil Heavy Metal Concentrations and Leaf Accumulation in Four Subtropical Plant Species from South China." Advanced Materials Research 455-456 (January 2012): 1310–16. http://dx.doi.org/10.4028/www.scientific.net/amr.455-456.1310.
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Four common subtropical understory sun plants from South China, i.e., Euodia lepta (Spreng.)Merr. (EL), Ilex asprella Champ. (IA), Mussaenda pubescens Ait.f. (MP), and Rhodomyrtus tomentosa (Ait.) Hassk. (RT), were sampled and determined for leaf Cu, Zn, Cd, and Pb concentrations, with an aim to investigate geographic variations in leaf heavy metal concentrations and phytoaccumulation. Significant differences were found among the 4 sampling sites for soil pH and heavy metal concentrations of Zn, Cd and Pb, with higher acidity in the 3 sampling sites from the Pearl River Delta industrial area. However, leaf pH did not vary significantly among the geographic populations of El and MP. For leaf heavy metal concentrations, significant variations were observed among the geographic populations of El for Cd; IA for Zn, Cd, and Pb; MP for Cu, Zn, Pb, and Cd; RT for Zn and Pb. The mean Biological Accumulation Coefficients (BACs) of IA for Zn, Cd, and Pb were as high as 10.38 for Zn, 18.29 for Cd, and 1.76 for Pb, respectively. Coefficient of Variation (CV) of BACs for heavy metals among different geographic populations of each species ranged from 41.99~221.83%, indicating high geographic variability in phytoaccumulation of heavy metals, and their accumulation capacity declined with the increase of soil heavy metal concentrations. This study revealed that some particular populations of IA can serve as potential hyperaccumulators for Zn and Cd, while those of MP and RT as hyperaccumulators for Pb, and the toxicity and safety of RT and IA should be further studied and assessed.
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Hoppe, Aaron R., Grant H. Mehring, and Hans Kandel. "Soybean Productivity as Affected by Raised Seedbeds Under Dry Environments." Open Agriculture Journal 11, no. 1 (November 24, 2017): 46–59. http://dx.doi.org/10.2174/1874331501711010046.
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Background: Raised seedbeds may be a practice for reducing waterlogging in the rooting zone in soils of the Red River of the North Valley (RRNV). However, it was not known if there would be a negative yield effect of raised beds in drier environments. Aims / Method: The objectives of this research were to evaluate soybean [Glycine max (L.) Merr.] response to early season iron deficiency chlorosis (IDC), agronomic characteristics, and productivity when grown on raised seedbeds compared with flat seedbeds. Soybean grain yield on raised seedbeds, averaged across six drier environments in 2012, was similar to flat seedbeds. Although grain yield did not increase on raised seedbeds, grain yield was not reduced in a dry year. Across environments there were no differences in vigor, IDC, canopy closure, plant height, thousand kernel weights, seed protein or oil content, number of seeds or pods per plant, or grain yield comparing raised with flat seedbeds. At the Rothsay environment, there was more IDC with flat seedbeds compared with raised beds. Soybean cultivars significantly differed in their IDC response and in most yield components measured. Averaged across hour of day, soil temperature was significantly higher in the raised seedbed treatments at Fargo and Hitterdal by 0.4 and 0.8 °C, respectively. When averaged across two cultivars and environments, soybean root mass was 0.37 g root-system-1 higher on raised seedbeds. Result: Raised seedbeds may be a useful tool to manage IDC and improve soybean productivity in the RRNV, and do not reduce grain yield in environments with below average moisture.
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Ryoo, J. M., D. E. Waliser, and E. J. Fetzer. "Trajectory analysis on the origin of air mass and moisture associated with Atmospheric Rivers over the west coast of the United States." Atmospheric Chemistry and Physics Discussions 11, no. 4 (April 11, 2011): 11109–42. http://dx.doi.org/10.5194/acpd-11-11109-2011.
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Abstract. The origins and pathways of air masses leading to heavy rainfall over the west coast of the United States are examined by computing the back-trajectories in a Lagrangian quasi-isentropic trajectory model. Extreme precipitation over the west coast of the United States often coincides with transport in a deep and narrow corridor of concentrated water vapor band from the ocean, commonly referred to as Atmospheric Rivers (ARs). They also occur in conjunction with moisture plumes emanating from the tropics, or along the mid-latitude storm track. However, the actual moisture sources and the dynamic and thermodynamic processes of the moisture transport, are still unclear. Trajectories are found to be insensitive to the reanalysis data set used; we examined NCEP, GMAO MERRA, and ECMWF ERA-Interim. Reconstructed water vapor mixing ratios along trajectories are in generally good agreement among the reanalysis datasets in most of the subtropics and extratropics, indicating that the large-scale circulation is a primary control for moisture transport over those regions. Clustering and pdf (probability density function) analyses illustrate that trajectories over the west coast of United States have different origins. One group of trajectories (cluster 1) originates in the warm part of extratropical cyclones in the low level. The other group of trajectories (cluster 2) originates in the cold and dry regions in the mid-level (pressures less than 600 hPa) over northeastern Asia, then cross the Pacific Ocean. This study demonstrates that the quasi-isentropic Lagrangian trajectory model and clustering analysis (that have been typically used to analyze trajectories in the upper troposphere and higher altitudes) can be used to examine sources of air masses and moisture, and also associated transport processes in the lower troposphere.
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He, Sicheng, Jing Yang, Qing Bao, Lei Wang, and Bin Wang. "Fidelity of the Observational/Reanalysis Datasets and Global Climate Models in Representation of Extreme Precipitation in East China." Journal of Climate 32, no. 1 (December 10, 2018): 195–212. http://dx.doi.org/10.1175/jcli-d-18-0104.1.
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AbstractRealistic reproduction of historical extreme precipitation has been challenging for both reanalysis and global climate model (GCM) simulations. This work assessed the fidelities of the combined gridded observational datasets, reanalysis datasets, and GCMs [CMIP5 and the Chinese Academy of Sciences Flexible Global Ocean–Atmospheric Land System Model–Finite-Volume Atmospheric Model, version 2 (FGOALS-f2)] in representing extreme precipitation over East China. The assessment used 552 stations’ rain gauge data as ground truth and focused on the probability distribution function of daily precipitation and spatial structure of extreme precipitation days. The TRMM observation displays similar rainfall intensity–frequency distributions as the stations. However, three combined gridded observational datasets, four reanalysis datasets, and most of the CMIP5 models cannot capture extreme precipitation exceeding 150 mm day−1, and all underestimate extreme precipitation frequency. The observed spatial distribution of extreme precipitation exhibits two maximum centers, located over the lower-middle reach of Yangtze River basin and the deep South China region, respectively. Combined gridded observations and JRA-55 capture these two centers, but ERA-Interim, MERRA, and CFSR and almost all CMIP5 models fail to capture them. The percentage of extreme rainfall in the total rainfall amount is generally underestimated by 25%–75% in all CMIP5 models. Higher-resolution models tend to have better performance, and physical parameterization may be crucial for simulating correct extreme precipitation. The performances are significantly improved in the newly released FGOALS-f2 as a result of increased resolution and a more realistic simulation of moisture and heating profiles. This work pinpoints the common biases in the combined gridded observational datasets and reanalysis datasets and helps to improve models’ simulation of extreme precipitation, which is critically important for reliable projection of future changes in extreme precipitation.
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Beckie, Hugh J., Robert H. Gulden, Nasir Shaikh, Eric N. Johnson, Christian J. Willenborg, Clark A. Brenzil, Scott W. Shirriff, Chris Lozinski, and Greg Ford. "Glyphosate-resistant kochia (Kochia scoparia L. Schrad.) in Saskatchewan and Manitoba." Canadian Journal of Plant Science 95, no. 2 (March 2015): 345–49. http://dx.doi.org/10.4141/cjps-2014-328.
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Beckie, H. J., Gulden, R. H., Shaikh, N., Johnson, E. N., Willenborg, C. J., Brenzil, C. A., Shirriff, S. W., Lozinski, C. and Ford, G. 2015. Glyphosate-resistant kochia (Kochia scoparia L. Schrad.) in Saskatchewan and Manitoba. Can. J. Plant Sci. 95: 345–349. Previous surveys have documented the occurrence of glyphosate-resistant (GR) kochia in Alberta in 2011 and 2012. To determine the incidence of GR kochia in Saskatchewan and Manitoba, a stratified-randomized survey of 342 sites (one population per site) in southern and central regions of Saskatchewan and a similar survey of 283 sites in southern Manitoba was conducted in the fall of 2013. Mature plants were collected, seed threshed, and progeny screened by spraying with a discriminating glyphosate dose of 900 g ae ha–1 under greenhouse conditions. Screening confirmed 17 GR kochia populations in nine municipalities in west-central or central Saskatchewan, but only two GR populations from different municipalities in the Red River Valley of Manitoba. While the majority of GR kochia populations in Saskatchewan originated in chemical-fallow fields, some populations were found in cropped fields (wheat, Triticum aestivum L.; lentil, Lens culinaris Medik.; GR canola, Brassica napus L.) and non-cropped areas (oil well, roadside ditch). In Manitoba, the two populations occurred in fields cropped to GR corn (Zea mays L.) and soybean (Glycine max L. Merr.). Agronomic and economic impact of this GR weed biotype is compounded because of consistent multiple resistance to acetolactate synthase-inhibiting herbicides. However, GR kochia is susceptible to dicamba, an increasingly important auxinic herbicide used for control of this multiple-resistant weed biotype.
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Peiris, K. H. S., G. G. Dull, R. G. Leffler, and S. J. Kays. "Spatial Variability of Soluble Solids or Dry-matter Content within Individual Fruits, Bulbs, or Tubers: Implications for the Development and Use of NIR Spectrometric Techniques." HortScience 34, no. 1 (February 1999): 114–18. http://dx.doi.org/10.21273/hortsci.34.1.114.
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Spatial variation in soluble solids content (SSC) of fruits of apple (Malus ×domestica Borkh. cv. Red Delicious), cantaloupe (Cucumis melo L. Cantaloupensis group), grapefruit (Citrus paradisi Macf. cv. Indian River Ruby Red), honeydew melon (Cucumis melo L. Inodorus group), mango (Mangifera indica L. cv. Hayden), orange (Citrus sinensis L. Osbeck. cv. Valencia), peach (Prunus persica L. Batsch. cv. Windblow), pineapple (Ananas comosus L. Merr. cv. Kew) and tomato (Lycopersicon esculentum Mill.), and of bulbs of onion (Allium cepa L. Cepa group) and in dry-matter content (DMC) of potato (Solanum tuberosum L. cv. Russet Burbank) tubers was measured along three directional orientations (i.e., proximal to distal, circumferentially midway along the proximal to distal axis, and radially from the center of the interior to the outer surface). The pattern and magnitude of constituent variation depended on the type of product and the direction of measurement. Radial and proximal to distal variation was greater than circumferential variation in all the products tested. Honeydew had the highest radial variation with a SSC difference of 6.0 % and a cv of 22.8%, while tomato displayed lower radial variation with a cv of 1.0%. Pineapple had a proximal to distal SSC difference of 4.6% with a cv of 13.8%, while the difference in tomato was 0.6% with a cv of 5.1%. Circumferential variation of SSC in all products tested was <2% with cv ranging from 1.1% to 3.8%. The results confirm that considerable constituent variability exists within individual fruit and vegetable organs. This variability may affect the accuracy of calibration equations and their prediction capability. Therefore, within-unit constituent variability should be meticulously assessed when an NIR spectrometric method is being developed for the nondestructive quality evaluation and sorting of a product.
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Gao, Le, Shi Sun, Kai Li, Liwei Wang, Wensheng Hou, Cunxiang Wu, Haijian Zhi, and Tianfu Han. "Spatio-temporal characterisation of changes in the resistance of widely grown soybean cultivars to Soybean mosaic virus across a century of breeding in China." Crop and Pasture Science 69, no. 4 (2018): 395. http://dx.doi.org/10.1071/cp17296.
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Soybean mosaic virus (SMV) causes significant yield losses and seed-quality deterioration in the soybean (Glycine max (L.) Merr.) growing areas of China, and breeding disease-resistant cultivars is the most common approach for controlling the spread of the disease and the destruction of soybean crop. In this study, 97 widely grown soybean cultivars representing nine decades (1923–2006) of breeding from the four main soybean-producing subregions in China (Northern Heilongjiang (NH), Mid-Southern Heilongjiang (MSH), Jilin-Liaoning (JL) and Yellow–Huai-Hai River Valleys (YHH)) were inoculated with six prevalent SMV strains: SC3, SC7, SC8, SC11, SC15 and SC18. The average disease index (ADI) of the six SMV strains ranged from 26.95 to 48.97, and the numbers of resistant and susceptible cultivars to the six SMV strains ranged from 27 (27.8%) to 64 (66.0%) and 33 (34.0%) to 70 (72.2%), respectively. The ADIs of cultivars from NH, MSH, JL and YHH were 50.82, 47.27, 43.10 and 33.05, respectively. Soybean cultivars released in the 1940s and 1960s had the highest and lowest ADI values, 53.95 and 32.03, respectively. From NH and JL, all individual strain disease index (DI) values exhibited decreasing trend over time, but no decreasing trend in DI values was observed from MSH. From YHH, DI values for SC3 and SC18 displayed apparent increasing trend over time, and DI values for SC15 showed an obvious decreasing trend. In all, 24 soybean cultivars were identified as having broad-spectrum resistance, with ADI values ranging from 0.80 to 35.52 for the six SMV strains, and 13 soybean cultivars were identified as highly resistant to at least one SMV strain. The findings of this study will contribute to monitoring the pattern of spatio-temporal variation in SMV resistance in different soybean-producing areas of China and facilitate conventional and molecular breeding programs for SMV resistance in soybean.
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Salve, Kristi. "Secretly through Salatsi: place names in Estonian runic songs related to Livonian settlement areas." Eesti ja soome-ugri keeleteaduse ajakiri. Journal of Estonian and Finno-Ugric Linguistics 7, no. 1 (September 14, 2016): 87–103. http://dx.doi.org/10.12697/jeful.2016.7.1.04.
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The article searches for an answer to the question whether Estonian runic songs contain references to Livonians. Using the materials from the database of Estonian runic songs, the article observes some names of countries, rivers and towns. The name of Courland proved to be extremely popular; it appears, however, in very different contexts. Thus, concrete place names have been used as generalisations for distant lands. Among town names, both Riga and Võnnu (Latv. Cēsis) are obviously centres of the Teutonic Order like the Estonian towns mentioned in parallel verses. As hydronyms are generally ancient, the names of rivers (Salatsi, Latv. Salaca; Koiva, Latv. Gauja; Väina, Latv. Daugava) proved to be the most interesting. First, their distribution area is concrete and expressive: The Salatsi is known in South-West Estonia, the Väina in South-East Estonia. The Koiva is like a connecting link, as it appears as the parallel word of both the Salatsi and the Väina. The names of these three rivers have been used in clearly mythical songs where they denote dangerous places connected with the otherworld.Kokkuvõte. Kristi Salve: Salaja Salatsi kaudu: Eesti regilaulude kohanimed, mis on seotud liivlaste asualadega. Artikkel otsib vastust küsimusele, kas eesti regilauludes leidub viiteid liivlastele. Kasutades eesti regilaulude andmebaasi, jälgitakse artiklis mõningaid maade, jõgede ja linnade nimesid. Kuramaa nimetus osutub väga populaarseks; see ilmneb siiski erinevates kontekstides, mis on sageli määratud alliteratsiooni poolt. Linnanimede hulgas on Riia äärmiselt sage. Kuna hüdronüümid on üldiselt iidsed, on ka jõenimede (Salatsi, läti Salaca; Koiva, läti Gauja; Väina, läti Daugava) esinemus eriti huvitav. Esiteks on nende levikuala kindlapiiriline ja tähenduslik: Salatsi on tuntud Edela-Eestis, Väina Kagu-Eestis. Koiva on nagu ühenduslüli, sest see ilmneb paralleelsõnana nii Salatsi kui ka Väina puhul. Väina ja Koiva vasteks paralleelvärsides võib olla Narva jõgi ja meri; kõik need on isikustatud.Märksõnad: eesti keel, liivi keel, regilaulud, ajalooline onomastika, kohanimedKubbõvõttõks. Kristi Salve: Salliz Salāts kouți: Līvõ kūožnimūd ēsti vaņīmis ro’vlōlis. Kēra vȯtšūb vastõkst kizzimizõn või ēsti vaņīmis ro’vlōlis um tǟtõkši iļ līvlizt. Ēsti vaņīmist rovlōlõd dattõdbǭzõ kȭlbatõs kēras sǭbõd vaņțõltõd mǭd, jougūd ja jālgabõd mingizt nimūd. Kurmǭ’ nim um väggi populār, kuigid se tulāb jeddõ ädsmingižis kontekstis, mis saggõld attõ lõvdõd alliteratsijst. Jālgabõd nimīst ātõ Riia ‘Rīgõ’ ja Võnnu (lețkīel Cēsis) ī’žkiz sagdizt. Ku viedkubūd nimūd iļamīņ attõ väggi vanād, siz ka jougūd nimūd (Salatsi ‘Salāts’, lețkīel Salaca; Koiva lețkīel Gauja; Väina ‘Vēna’, lețkīel Daugava) īžkiz interesant. Salatsi um tundtõd Lǟnd Ēstimǭl, Väina Lȭinag Ēstimǭl, Koiva um neiku ītõbpǭsmõz, ku se um parālelsõnāks nei Salatsi kui Väina jūs. Nänt kuolm joug nimīdi um kȭlbatõd sieldõ mītiližis lōlis kus ne ātõ tuoiz īlmaks sidtõd kārtabizt kūožõd.
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Trenberth, Kevin E., John T. Fasullo, and Jessica Mackaro. "Atmospheric Moisture Transports from Ocean to Land and Global Energy Flows in Reanalyses." Journal of Climate 24, no. 18 (September 15, 2011): 4907–24. http://dx.doi.org/10.1175/2011jcli4171.1.
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Abstract An assessment is made of the global energy and hydrological cycles from eight current atmospheric reanalyses and their depiction of changes over time. A brief evaluation of the water and energy cycles in the latest version of the NCAR climate model referred to as CCSM4 is also given. The focus is on the mean ocean, land, and global precipitation P; the corresponding evaporation E; their difference corresponding to the surface freshwater flux E–P; and the vertically integrated atmospheric moisture transports. Using the model-based P and E, the time- and area-average E–P for the oceans, P–E for land, and the moisture transport from ocean to land should all be identical but are not close in most reanalyses, and often differ significantly from observational estimates of the surface return flow based on net river discharge into the oceans. Their differences reveal outstanding issues with atmospheric models and their biases, which are manifested as analysis increments in the reanalyses. The NCAR CCSM4, along with most reanalysis models, the exception being MERRA, has too-intense water cycling (P and E) over the ocean although ocean-to-land transports are very close to observed. Precipitation from reanalyses that assimilate moisture from satellite observations exhibits large changes identified with the changes in the observing system, as new and improved temperature and water vapor channels are assimilated and, while P improves after about 2002, E–P does not. Discrepancies among hydrological cycle components arise from analysis increments that can add or subtract moisture. The large-scale moisture budget divergences are more stable in time and similar across reanalyses than model-based estimates of E–P. Results are consistent with the view that recycling of moisture is too large in most models and the lifetime of moisture is too short. For the energy cycle, most reanalyses have spurious imbalances of ~10 W m−2 within the atmosphere, and ~5–10 W m−2 in net fluxes into the surface and to space. Major improvements are needed in model treatment and assimilation of moisture, and surface fluxes from reanalyses should only be used with great caution.