scholarly journals A hierarchical analysis of the impact of methodological decisions on statistical downscaling of daily precipitation and air temperatures

2019 ◽  
Vol 39 (6) ◽  
pp. 2880-2900 ◽  
Author(s):  
Sara C. Pryor ◽  
Justin T. Schoof
Keyword(s):  
Statistical Downscaling ◽  
Daily Precipitation ◽  
Hierarchical Analysis ◽  
Air Temperatures ◽  
The Impact

scholarly journals Impact of Seasonal Changes of Precipitation and Air Temperature on Clay Excavation

2019 ◽  
Vol 11 (22) ◽  
pp. 6368 ◽  
Author(s):  
Denis Težak ◽  
Božo Soldo ◽  
Bojan Đurin ◽  
Nikola Kranjčić
Keyword(s):  
Air Temperature ◽  
Drought Index ◽  
Clay Soil ◽  
Daily Precipitation ◽  
Partial Sums ◽  
Air Temperatures ◽  
Time Period ◽  
Global Exploitation ◽  
Soil Excavation ◽  
The Impact

Excavation of clay soil is one of the most important economic branches in the northern part of Croatia. The impact of clay soil in Croatia compared to the global exploitation fields of clay soil is negligible. Modern methods of clay excavation during winter months due to negligible amounts are not profitable. Therefore, it is important to optimize clay soil excavation throughout the year to increase the efficiency of exploitation and increase profits. In the case of large amounts of precipitation (rain), clay absorbs water and becomes grain. For this reason, access to the exploitation field and excavation itself becomes impossible. Air temperature also plays an important role in excavation. Long-lasting low air temperatures below 0 °C during the winter months result in clay frost. As a result, excavation cannot occur at that time. The paper describes a new method of modeling the precipitation and air temperature on the exploitation fields of clay in Northwest Croatia on the exploitation fields of Cukavec and Cukavec II. The method involves the calculation of the drought index and use of the rescaled adjusted partial sums (RAPS) statistical method and its application on a time series of total daily precipitation and average daily temperatures as a climatic indicator of any observed area. Using this process, it is possible to determine the time period of the year when clay soil can be excavated.

scholarly journals Impact of Shade and Fogging on High Tunnel Production and Mineral Content of Organically Grown Lettuce, Basil, and Arugula in Georgia

Agriculture ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 625
Author(s):  
Savanah Laur ◽  
Andre Luiz Biscaia Ribeiro da Silva ◽  
Juan Carlos Díaz-Pérez ◽  
Timothy Coolong
Keyword(s):  
Mineral Content ◽  
Planting Date ◽  
High Tunnel ◽  
Lactuca Sativa L ◽  
Air Temperatures ◽  
Shade Cloth ◽  
High Tunnels ◽  
Soil Temperatures ◽  
Organically Grown ◽  
The Impact

This study evaluated the impact of shade cloth and fogging systems on the microclimate at the plant canopy level and yield of basil (Oscimum basilicum L.), arugula (Eruca vesicaria subsp. Sativa L.), and lettuce (Lactuca sativa L.) planted in mid-September and early October in high tunnels. Fogging systems were installed at canopy level in plots within shaded (30%) and non-shaded high tunnels. Average air temperatures in the shaded high tunnels were 0.9 °C lower than non-shaded high tunnels during the day. Shade cloth significantly reduced soil temperatures during the day and night periods by 1.5 °C and 1.3 °C, respectively, compared to non-shaded treatments. Fogging systems did not have an impact on air temperature, soil temperature, or relative humidity, but did increase canopy leaf wetness. Shade and fogging did not impact the yield of any of the crops grown. Yield was impacted by planting date, with earlier planting result in higher yields of lettuce and basil. Yields for arugula were greater during the second planting date than the first. Planting date and shade cloth interacted to affect the concentrations of macronutrients.

scholarly journals Cumulative Effects of Particulate Matter Pollution and Meteorological Variables on the Risk of Influenza-Like Illness

Viruses ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 556
Author(s):  
Kacper Toczylowski ◽  
Magdalena Wietlicka-Piszcz ◽  
Magdalena Grabowska ◽  
Artur Sulik
Keyword(s):  
Particulate Matter ◽  
Respiratory Infections ◽  
Nonlinear Models ◽  
Absolute Humidity ◽  
Influenza Viruses ◽  
Meteorological Variables ◽  
Exponential Relationship ◽  
Influenza Like Illness ◽  
Air Temperatures ◽  
The Impact

The cold season is usually accompanied by an increased incidence of respiratory infections and increased air pollution from combustion sources. As we are facing growing numbers of COVID-19 cases caused by the novel SARS-CoV-2 coronavirus, an understanding of the impact of air pollutants and meteorological variables on the incidence of respiratory infections is crucial. The incidence of influenza-like illness (ILI) can be used as a close proxy for the circulation of influenza viruses. Recently, SARS-CoV-2 has also been detected in patients with ILI. Using distributed lag nonlinear models, we analyzed the association between ILI, meteorological variables and particulate matter concentration in Bialystok, Poland, from 2013–2019. We found an exponential relationship between cumulative PM2.5 pollution and the incidence of ILI, which remained significant after adjusting for air temperatures and a long-term trend. Pollution had the greatest effect during the same week, but the risk of ILI was increased for the four following weeks. The risk of ILI was also increased by low air temperatures, low absolute humidity, and high wind speed. Altogether, our results show that all measures implemented to decrease PM2.5 concentrations would be beneficial to reduce the transmission of SARS-CoV-2 and other respiratory infections.

scholarly journals ENSO and Wintertime Extreme Precipitation Events over the Contiguous United States

2008 ◽  
Vol 21 (1) ◽  
pp. 22-39 ◽  
Author(s):  
Siegfried D. Schubert ◽  
Yehui Chang ◽  
Max J. Suarez ◽  
Philip J. Pegion
Keyword(s):  
United States ◽  
West Coast ◽  
Extreme Precipitation ◽  
East Coast ◽  
Daily Precipitation ◽  
Precipitation Variability ◽  
The West ◽  
Extreme Precipitation Events ◽  
The Impact ◽  
Precipitation Events

Abstract In this study the authors examine the impact of El Niño–Southern Oscillation (ENSO) on precipitation events over the continental United States using 49 winters (1949/50–1997/98) of daily precipitation observations and NCEP–NCAR reanalyses. The results are compared with those from an ensemble of nine atmospheric general circulation model (AGCM) simulations forced with observed SST for the same time period. Empirical orthogonal functions (EOFs) of the daily precipitation fields together with compositing techniques are used to identify and characterize the weather systems that dominate the winter precipitation variability. The time series of the principal components (PCs) associated with the leading EOFs are analyzed using generalized extreme value (GEV) distributions to quantify the impact of ENSO on the intensity of extreme precipitation events. The six leading EOFs of the observations are associated with major winter storm systems and account for more than 50% of the daily precipitation variability along the West Coast and over much of the eastern part of the country. Two of the leading EOFs (designated GC for Gulf Coast and EC for East Coast) together represent cyclones that develop in the Gulf of Mexico and occasionally move and/or redevelop along the East Coast producing large amounts of precipitation over much of the southern and eastern United States. Three of the leading EOFs represent storms that hit different sections of the West Coast (designated SW for Southwest coast, WC for the central West Coast, and NW for northwest coast), while another represents storms that affect the Midwest (designated by MW). The winter maxima of several of the leading PCs are significantly impacted by ENSO such that extreme GC, EC, and SW storms that occur on average only once every 20 years (20-yr storms) would occur on average in half that time under sustained El Niño conditions. In contrast, under La Niña conditions, 20-yr GC and EC storms would occur on average about once in 30 years, while there is little impact of La Niña on the intensity of the SW storms. The leading EOFs from the model simulations and their connections to ENSO are for the most part quite realistic. The model, in particular, does very well in simulating the impact of ENSO on the intensity of EC and GC storms. The main model discrepancies are the lack of SW storms and an overall underestimate of the daily precipitation variance.

Evaluating the Consistency between Statistically Downscaled and Global Dynamical Model Climate Change Projections

2008 ◽  
Vol 21 (22) ◽  
pp. 6052-6059 ◽  
Author(s):  
B. Timbal ◽  
P. Hope ◽  
S. Charles
Keyword(s):  
Global Warming ◽  
Statistical Downscaling ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Specific Humidity ◽  
Model Output ◽  
Winter Rainfall ◽  
Direct Model ◽  
The Impact

Abstract The consistency between rainfall projections obtained from direct climate model output and statistical downscaling is evaluated. Results are averaged across an area large enough to overcome the difference in spatial scale between these two types of projections and thus make the comparison meaningful. Undertaking the comparison using a suite of state-of-the-art coupled climate models for two forcing scenarios presents a unique opportunity to test whether statistical linkages established between large-scale predictors and local rainfall under current climate remain valid in future climatic conditions. The study focuses on the southwest corner of Western Australia, a region that has experienced recent winter rainfall declines and for which climate models project, with great consistency, further winter rainfall reductions due to global warming. Results show that as a first approximation the magnitude of the modeled rainfall decline in this region is linearly related to the model global warming (a reduction of about 9% per degree), thus linking future rainfall declines to future emission paths. Two statistical downscaling techniques are used to investigate the influence of the choice of technique on projection consistency. In addition, one of the techniques was assessed using different large-scale forcings, to investigate the impact of large-scale predictor selection. Downscaled and direct model projections are consistent across the large number of models and two scenarios considered; that is, there is no tendency for either to be biased; and only a small hint that large rainfall declines are reduced in downscaled projections. Among the two techniques, a nonhomogeneous hidden Markov model provides greater consistency with climate models than an analog approach. Differences were due to the choice of the optimal combination of predictors. Thus statistically downscaled projections require careful choice of large-scale predictors in order to be consistent with physically based rainfall projections. In particular it was noted that a relative humidity moisture predictor, rather than specific humidity, was needed for downscaled projections to be consistent with direct model output projections.

scholarly journals Green roofs and cool materials as retrofitting strategies for urban heat island mitigation: Case study in Belgrade, Serbia

2018 ◽  
Vol 22 (6 Part A) ◽  
pp. 2309-2324
Author(s):  
Marija Lalosevic ◽  
Mirko Komatina ◽  
Marko Milos ◽  
Nedzad Rudonja
Keyword(s):  
Green Roofs ◽  
Urban Heat Islands ◽  
Temperature Changes ◽  
Heat Islands ◽  
Air Temperatures ◽  
Urban Heat ◽  
Microclimatic Conditions ◽  
Typical Summer ◽  
Planning And Construction ◽  
The Impact

The effect of extensive and intensive green roofs on improving outdoor microclimate parameters of urban built environments is currently a worldwide focus of research. Due to the lack of reliable data for Belgrade, the impact of extensive and intensive green roof systems on mitigating the effects of urban heat islands and improving microclimatic conditions by utilizing high albedo materials in public spaces were studied. Research was conducted on four chosen urban units within existing residential blocks in the city that were representative of typical urban planning and construction within the Belgrade metropolitan area. Five different models (baseline model and four potential models of retrofitting) were designed, for which the temperature changes at pedestrian and roof levels at 07:00, 13:00, 19:00 h, on a typical summer day, and at 01:00 h, the following night in Belgrade were investigated. The ENVI-met software was used to model the simulations. The results of numerical modeling showed that utilizing green roofs in the Belgrade climatic area could reduce air temperatures in the surroundings up to 0.47, 1.51, 1.60, 1.80 ?C at pedestrian level and up to 0.53, 1.45, 0.90, 1.45 ?C at roof level for four potential retrofitting strategies, respectively.

scholarly journals Morphological features of Hylotelephium triphillum (Haw.) Holub (Crassulaceae DC.) under different light conditions when introduced into the steppe zone

2016 ◽  
Vol 5 (2) ◽  
pp. 47-51
Author(s):  
Lidiya Vasilyevna Privalko
Keyword(s):  
Fruit Set ◽  
Steppe Zone ◽  
Botanical Garden ◽  
Light Conditions ◽  
Biometric Data ◽  
Habitat Features ◽  
Lighting Conditions ◽  
Air Temperatures ◽  
Natural Flora ◽  
The Impact

In recent decades floral devices in a natural style has been becoming more common in gardening. In this connection there was a need for the introduction and study of the natural flora of plants in order to attract them to simulate the decorative and resistant plants. The article presents the results of studies of the effect of different light conditions on the habitat features and decorative biomorphological Hylotelephium triphyllum (Haw.) Holub (Crassulaceae DC.) when introduced in SE Donetsk Botanical Garden. This species is found naturally in the flora of Donbass, a decorative, but, according to the results of our analysis, is rarely used in green construction. Bioecological certification of this type has been done. It has been determined that the impact of site lighting conditions on the growth and development of H. triphyllum expressed in significantly smaller numbers of vegetative and generative shoots in the shaded areas. However, since the diameter of the plants does not change, more thickened planting in these areas is not recommended. The author found the dependence of the variation of the biometric data on the lighting conditions. In the study of seasonal dynamics of H. triphyllum the author revealed that the development of above-ground organs of his passes with a positive amount of average daily air temperatures. The growing season lasts an average of 225 days. Start of spring regrowth is observed in the second half of March - early April, flowering - in August - September, fruits - in September - October. Vegetation stops when temperature goes below zero. Illumination of this type of habitat affect the time of vegetation beginning, budding, flowering, fruit set and fruit-bearing. On the shaded areas due to the later start of budding and flowering the most decorative period of H. triphyllum is shorter by an average of 10 days. This type is recommended for creation of group planting, stony hills, dry streams, rock gardens, rockeries, mixborders, curbs, ornamental compositions in the coastal zone of ornamental ponds and fountains in the steppe zone in areas with different light conditions, taking into account the above factors.

scholarly journals Utility of daily vs. monthly large-scale climate data: an intercomparison of two statistical downscaling methods

2007 ◽  
Vol 4 (5) ◽  
pp. 3413-3440 ◽  
Author(s):  
E. P. Maurer ◽  
H. G. Hidalgo
Keyword(s):  
Statistical Downscaling ◽  
General Circulation ◽  
Large Scale ◽  
Impact Analysis ◽  
Climate Model ◽  
Daily Precipitation ◽  
Circulation Model ◽  
Reanalysis Data ◽  
Temperature Extremes ◽  
Daily Data

Abstract. Downscaling of climate model data is essential to most impact analysis. We compare two methods of statistical downscaling to produce continuous, gridded time series of precipitation and surface air temperature at a 1/8-degree (approximately 140 km² per grid cell) resolution over the western U.S. We use NCEP/NCAR Reanalysis data from 1950–1999 as a surrogate General Circulation Model (GCM). The two methods included are constructed analogues (CA) and a bias correction and spatial downscaling (BCSD), both of which have been shown to be skillful in different settings, and BCSD has been used extensively in hydrologic impact analysis. Both methods use the coarse scale Reanalysis fields of precipitation and temperature as predictors of the corresponding fine scale fields. CA downscales daily large-scale data directly and BCSD downscales monthly data, with a random resampling technique to generate daily values. The methods produce comparable skill in producing downscaled, gridded fields of precipitation and temperatures at a monthly and seasonal level. For daily precipitation, both methods exhibit some skill in reproducing both observed wet and dry extremes and the difference between the methods is not significant, reflecting the general low skill in daily precipitation variability in the reanalysis data. For low temperature extremes, the CA method produces greater downscaling skill than BCSD for fall and winter seasons. For high temperature extremes, CA demonstrates higher skill than BCSD in summer. We find that the choice of most appropriate downscaling technique depends on the variables, seasons, and regions of interest, on the availability of daily data, and whether the day to day correspondence of weather from the GCM needs to be reproduced for some applications. The ability to produce skillful downscaled daily data depends primarily on the ability of the climate model to show daily skill.

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