scholarly journals Próba uporządkowania polskiego nazewnictwa bambusów przydatnych do uprawy w rodzimych warunkach klimatycznych

2018 ◽  
Vol 61 ◽  
Author(s):  
Szymon Hoser ◽  
Wojciech Hoser ◽  
Katarzyna Nawrocka
Keyword(s):  
Web Sites ◽  
Selection Criteria ◽  
Local Climate ◽  
Climate Conditions ◽  
Distinctive Features ◽  
Spontaneous Process ◽  
Polish Language ◽  
Cultivated Species

Próba uporządkowania polskiego nazewnictwa bambusów przydatnych do uprawy w rodzimych warunkach klimatycznych W Polsce, w wyniku wzrostu popularności bambusów, zaczynają funkcjonować potoczne nazwy dla najczęściej uprawianych gatunków. W efekcie tego spontanicznie postępującego procesu pojawiają się zarówno liczne nazwy oboczne w odniesieniu do pojedynczych taksonów, jak i błędne formy nazewnicze. Celem niniejszej publikacji jest uporządkowanie powstającego polskiego nazewnictwa bambusów. Opracowanie obejmuje taksony o największym znaczeniu, wybrane na podstawie przydatności do uprawy w warunkach klimatycznych Polski, występowania w polskojęzycznych publikacjach i tematycznych stronach internetowych oraz obecności w ofertach krajowych szkółek i centrów ogrodniczych. Dla omawianych taksonów sformułowano polskie nazwy w oparciu o etymologię, dotychczasowe propozycje nazewnicze i cechy dystynktywne roślin. Zestawienie obejmuje 43 gatunki należące do 9 rodzajów z plemienia <em>Bambuseae</em>, spośród których najliczniej reprezentowane są tu rodzaje <em>Phyllostachys</em> (23 taksony), <em>Fargesia</em> (7 taksonów) i <em>Sasa</em> (4 taksony). An attempt to settle Polish names for bamboos useful for cultivation in the local climate As a result of the growing popularity of bamboos in Poland, common names for the most often cultivated species are beginning to be used. As a result of this spontaneous process, many double as well as wrong names appear according to one taxa. The purpose of this publication is to organize Polish names for bamboos. The most important taxa have been chosen. As selection criteria were taken: usefulness for cultivation in the Polish climate conditions, occurrence in Polish language publications and thematic web sites, and presence in offer of Polish nurseries and garden centers. For this selection Polish names have been formulated in consideration of etymology, so far suggested nomenclature and distinctive features. The article includes 43 species belonging to 9 genera from Bambuseae tribe. Most represented are <em>Phyllostachys</em> (23 taxa), <em>Fargesia</em> (7 taxa), and <em>Sasa</em> (4 taxa).

Skill assessment of post-processing methods for ECMWF SEAS5 seasonal forecasts over Europe

2021 ◽  
Author(s):  
Alice Crespi ◽  
Marcello Petitta ◽  
Lucas Grigis ◽  
Paola Marson ◽  
Jean-Michel Soubeyroux ◽  
...  
Keyword(s):  
Large Scale ◽  
Production Management ◽  
Spatial Scales ◽  
Research Field ◽  
Skill Assessment ◽  
Post Processing ◽  
Seasonal Forecasts ◽  
Climate Services ◽  
Local Climate ◽  
Climate Conditions

&lt;p&gt;Seasonal forecasts provide information on climate conditions several months ahead and therefore they could represent a valuable support for decision making, warning systems as well as for the optimization of industry and energy sectors. However, forecast systems can be affected by systematic biases and have horizontal resolutions which are typically coarser than the spatial scales of the practical applications. For this reason, the reliability of forecasts needs to be carefully assessed before applying and interpreting them for specific applications. In addition, the use of post-processing approaches is recommended in order to improve the representativeness of the large-scale predictions of regional and local climate conditions. The development and evaluation downscaling and bias-correction procedures aiming at improving the skills of the forecasts and the quality of derived climate services is currently an open research field. In this context, we evaluated the skills of ECMWF SEAS5 forecasts of monthly mean temperature, total precipitation and wind speed over Europe and we assessed the skill improvements of calibrated predictions.&lt;/p&gt;&lt;p&gt;For the calibration, we combined a bilinear interpolation and a quantile mapping approach to obtain corrected monthly forecasts on a 0.25&amp;#176;x0.25&amp;#176; grid from the original 1&amp;#176;x1&amp;#176; values. The forecasts were corrected against the reference ERA5 reanalysis over the hindcast period 1993&amp;#8211;2016. The processed forecasts were compared over the same domain and period with another calibrated set of ECMWF SEAS5 forecasts obtained by the ADAMONT statistical method.&lt;/p&gt;&lt;p&gt;The skill assessment was performed by means of both deterministic and probabilistic verification metrics evaluated over seasonal forecasted aggregations for the first lead time. Greater skills of the forecast systems in Europe were generally observed in spring and summer, especially for temperature, with a spatial distribution varying with the seasons. The calibration was proved to effectively correct the model biases for all variables, however the metrics not accounting for bias did not show significant improvements in most cases, and in some areas and seasons even small degradations in skills were observed.&lt;/p&gt;&lt;p&gt;The presented study supported the activities of the H2020 European project SECLI-FIRM on the improvement of the seasonal forecast applicability for energy production, management and assessment.&lt;/p&gt;

scholarly journals Diverse local epidemics reveal the distinct effects of population density, demographics, climate, depletion of susceptibles, and intervention in the first wave of COVID-19 in the United States

2020 ◽  
Author(s):  
Niayesh Afshordi ◽  
Benjamin Holder ◽  
Mohammad Bahrami ◽  
Daniel Lichtblau
Keyword(s):  
United States ◽  
Population Density ◽  
The United States ◽  
Effective Response ◽  
Susceptible Population ◽  
Local Climate ◽  
Climate Conditions ◽  
Mortality And Morbidity ◽  
Social Distancing ◽  
The Impact

The SARS-CoV-2 pandemic has caused significant mortality and morbidity worldwide, sparing almost no community. As the disease will likely remain a threat for years to come, an understanding of the precise influences of human demographics and settlement, as well as the dynamic factors of climate, susceptible depletion, and intervention, on the spread of localized epidemics will be vital for mounting an effective response. We consider the entire set of local epidemics in the United States; a broad selection of demographic, population density, and climate factors; and local mobility data, tracking social distancing interventions, to determine the key factors driving the spread and containment of the virus. Assuming first a linear model for the rate of exponential growth (or decay) in cases/mortality, we find that population-weighted density, humidity, and median age dominate the dynamics of growth and decline, once interventions are accounted for. A focus on distinct metropolitan areas suggests that some locales benefited from the timing of a nearly simultaneous nationwide shutdown, and/or the regional climate conditions in mid-March; while others suffered significant outbreaks prior to intervention. Using a first-principles model of the infection spread, we then develop predictions for the impact of the relaxation of social distancing and local climate conditions. A few regions, where a significant fraction of the population was infected, show evidence that the epidemic has partially resolved via depletion of the susceptible population (i.e., “herd immunity”), while most regions in the United States remain overwhelmingly susceptible. These results will be important for optimal management of intervention strategies, which can be facilitated using our online dashboard.

scholarly journals Applications of Models and Tools for Mesoscale and Microscale Thermal Analysis in Mid-Latitude Climate Regions—A Review

2021 ◽  
Vol 13 (22) ◽  
pp. 12385
Author(s):  
Gabriele Lobaccaro ◽  
Koen De Ridder ◽  
Juan Angel Acero ◽  
Hans Hooyberghs ◽  
Dirk Lauwaet ◽  
...  
Keyword(s):  
High Temperatures ◽  
Numerical Models ◽  
Spatial Scales ◽  
Built Environments ◽  
Local Climate ◽  
Climate Conditions ◽  
The Social ◽  
Climatic Environment ◽  
Intense Solar Radiation ◽  
Mobile Measurements

Urban analysis at different spatial scales (micro- and mesoscale) of local climate conditions is required to test typical artificial urban boundaries and related climate hazards such as high temperatures in built environments. The multitude of finishing materials and sheltering objects within built environments produce distinct patterns of different climate conditions, particularly during the daytime. The combination of high temperatures and intense solar radiation strongly perturb the environment by increasing the thermal heat stress at the pedestrian level. Therefore, it is becoming common practice to use numerical models and tools that enable multiple design and planning alternatives to be quantitatively and qualitatively tested to inform urban planners and decision-makers. These models and tools can be used to compare the relationships between the micro-climatic environment, the subjective thermal assessment, and the social behaviour, which can reveal the attractiveness and effectiveness of new urban spaces and lead to more sustainable and liveable public spaces. This review article presents the applications of selected environmental numerical models and tools to predict human thermal stress at the mesoscale (e.g., satellite thermal images and UrbClim) and the microscale (e.g., mobile measurements, ENVI-met, and UrbClim HR) focusing on case study cities in mid-latitude climate regions framed in two European research projects.

scholarly journals Millennial variations of atmospheric CO<sub>2</sub> during the early Holocene (11.7–7.4 ka)

2021 ◽  
Author(s):  
Jinhwa Shin ◽  
Jinho Ahn ◽  
Jai Chowdhry Beeman ◽  
Hun-Gyu Lee ◽  
Edward J. Brook
Keyword(s):  
North Atlantic ◽  
Ice Core ◽  
Polar Front ◽  
Equatorial Pacific ◽  
Early Holocene ◽  
Atmospheric Co2 ◽  
Solar Forcing ◽  
Local Climate ◽  
Climate Conditions ◽  
Siple Dome

Abstract. We present a new high-resolution record of atmospheric CO2 from the Siple Dome ice core, Antarctica over the early Holocene (11.7–7.4 ka) that quantifies natural CO2 variability on millennial timescales under interglacial climate conditions. Atmospheric CO2 decreased by ~10 ppm between 11.3 and 7.3 ka. The decrease was punctuated by local minima at 11.1, 10.1, 9.1 and 8.3 ka with amplitude of 2–6 ppm. These variations correlate with proxies for solar forcing and local climate in the South East Atlantic polar front, East Equatorial Pacific and North Atlantic. These relationships suggest that weak solar forcing changes might have impacted CO2 by changing CO2 outgassing from the Southern Ocean and the East Equatorial Pacific and terrestrial carbon storage in the Northern Hemisphere over the early Holocene.

Experimental study of the basin type solar still under local climate conditions

2000 ◽  
Vol 41 (9) ◽  
pp. 883-890 ◽  
Author(s):  
Bilal A Akash ◽  
Mousa S Mohsen ◽  
Waleed Nayfeh
Keyword(s):  
Experimental Study ◽  
Solar Still ◽  
Local Climate ◽  
Climate Conditions

The influence of global climate and local hydrological features over streamflow extremes.  Case of study in a tropical Andean basin

2021 ◽  
Author(s):  
Alex Avilés ◽  
Juan Contreras ◽  
Daniel Mendoza ◽  
Jheimy Pacheco
Keyword(s):  
Global Climate ◽  
Standardized Precipitation Index ◽  
Additive Models ◽  
Mitigation Strategies ◽  
Climate Indices ◽  
Local Climate ◽  
Climate Conditions ◽  
Lulc Changes ◽  
Daily Streamflow ◽  
Floods And Droughts

&lt;p&gt;Hydrological extremes such as floods and droughts are the most common and threatening natural disasters worldwide. Particularly, tropical Andean headwaters systems are prone to hazards due to their complex climate conditions. However, little is known about the underlying mechanisms triggering such extremes events. In this study, the Generalized Additive Models for Location, Scale and Shape (GAMLSS) were used for investigating the relations between the Annual- Peak-Flows (APF) and Annual-Low-Flows (ALF), respecting to climate and land use/land cover (LULC) changes. Thirty years of daily streamflow data-sets taken from two Andean catchments of southern Ecuador are used for the experimental research. Global climate indices (CI), describing the large-scale climate variability were used as hypothetical drivers explaining the extreme&amp;#8217;s variations on streamflow measures. Additionally, the Antecedent-Cumulative-Precipitation (AP) and the Standardized-Precipitation-Index (SPI), and LULC percentages were also included as possible direct drivers &amp;#8211; synthetizing local climate conditions and localized hydrological changes. The results indicate that AP and SPI clearly explain the extreme streamflow variability. Nonetheless, global variables play a significant role underneath the local climate. For instance, ENSO and CAR exert influence over the APF, while ENSO, TSA, PDO and AMO control ALF. Furthermore, it was found that LULC changes strongly influence both extremes; although this is particularly important for relative more disturbed catchments. These results provide valuable insights for future forecasting of floods and droughts based on precipitation and climate indices, and for the development of mitigation strategies for mountain catchments.&lt;/p&gt;

Climate controlled root zone parameters show potential to improve water flux simulations by land surface models

2021 ◽  
Author(s):  
Fransje van Oorschot ◽  
Ruud van der Ent ◽  
Andrea Alessandri ◽  
Markus Hrachowitz
Keyword(s):  
Land Surface ◽  
Root Zone ◽  
Surface Model ◽  
Water Fluxes ◽  
Land Surface Models ◽  
Climate Control ◽  
Local Climate ◽  
Climate Conditions ◽  
Surface Models ◽  
Zone Parameters

&lt;p&gt;The root zone storage capacity (S&lt;sub&gt;r&lt;/sub&gt; ) is the maximum volume of water in the subsurface that can potentially be accessed by vegetation for transpiration. It influences the seasonality of transpiration as well as fast and slow runoff processes. Many studies have shown that S&lt;sub&gt;r&lt;/sub&gt; is heterogeneous as controlled by local climate conditions, which affect vegetation strategies in sizing their root system able to support plant growth and to prevent water shortages. Root zone parameterization in most land surface models does not account for this climate control on root development, being based on look-up tables that prescribe worldwide the same root zone parameters for each vegetation class. These look-up tables are obtained from measurements of rooting structure that are scarce and hardly representative of the ecosystem scale. The objective of this research was to quantify and evaluate the effects of a climate-controlled representation of S&lt;sub&gt;r&lt;/sub&gt; on the&amp;#160; water fluxes modeled by the HTESSEL land surface model. Climate controlled S&lt;sub&gt;r&lt;/sub&gt; was here estimated with the &quot;memory method&quot; (hereinafter MM) in which S&lt;sub&gt;r&lt;/sub&gt; is derived from the vegetation's memory of past root zone water storage deficits. S&lt;sub&gt;r,MM&lt;/sub&gt; was estimated for 15 river catchments over Australia across three contrasting climate regions: tropical, temperate and Mediterranean. Suitable representations of S&lt;sub&gt;r,MM&lt;/sub&gt; were then implemented in HTESSEL (hereinafter MD) by accordingly modifying the soil depths to obtain a model S&lt;sub&gt;r,MD &lt;/sub&gt;that matches S&lt;sub&gt;r,MM&lt;/sub&gt; in the 15 catchments. In the control version of HTESSEL (hereinafter CTR), S&lt;sub&gt;r,CTR&lt;/sub&gt; was larger than S&lt;sub&gt;r,MM&lt;/sub&gt; in 14 out of 15 catchments. Furthermore, the variability among the individual catchments of S&lt;sub&gt;r,MM&lt;/sub&gt; (117&amp;#8212;722 mm) was considerably larger than of S&lt;sub&gt;r,CTR&lt;/sub&gt; (491&amp;#8212;725 mm). The HTESSEL MD version resulted in a significant and consistent improvement version of the modeled monthly seasonal climatology (1975--2010) and inter-annual anomalies of river discharge compared with observations. However, the effects on biases in long-term annual mean fluxes were small and mixed. The modeled monthly seasonal climatology of the catchment discharge improved in MD compared to CTR: the correlation with observations increased significantly from 0.84 to 0.90 in tropical catchments, from 0.74 to 0.86 in temperate catchments and from 0.86 to 0.96 in Mediterranean catchments. Correspondingly, the correlations of the inter-annual discharge anomalies improved significantly in MD from 0.74 to 0.78 in tropical catchments, from 0.80 to 0.85 in temperate catchments and from 0.71 to 0.79 in Mediterranean catchments. Based on these results, we believe that a global application of climate controlled root zone parameters has the potential to improve the timing of modeled water fluxes by land surface models, but a significant reduction of biases is not expected.&amp;#160;&lt;/p&gt;

A Simulation Study on Energy Consumption of Cluster Distribution of Residential Buildings in Cold Zones

2011 ◽  
Vol 243-249 ◽  
pp. 5822-5827
Author(s):  
Jing Yuan Zhao ◽  
Qi Bo Liu
Keyword(s):  
Energy Consumption ◽  
Simulation Study ◽  
Residential Buildings ◽  
Thermal Conditions ◽  
Minimal Energy ◽  
Local Climate ◽  
Climate Conditions ◽  
Cluster Distribution ◽  
Different Seasons ◽  
Energy Consumption Simulation

The distribution of residential buildings is closely related to local climate conditions. This paper takes Xi’an region as its representative city to study the thermal conditions of various shapes of cluster distribution by utilizing energy consumption simulation. By sequentially changing the dimensions of each unit building in the cluster, it sets up models of mathematical examples which meet the requirements of different seasons. Based on the annual minimal energy consumption of buildings, the paper quantitatively expounds the influence of cluster distribution on buildings’ energy consumption. This study finally works out a recommendation for the cluster distribution in Xi’an region, i.e. the annual comprehensive energy consumption of buildings is at its minimum when buildings facing both south and north are “L”-shaped enclosures and when they have no westward extension and their length ratio between eastward extended exterior walls and southward level exterior walls is 0.5:1.

scholarly journals Using a Statistical Preanalysis Approach as an Ensemble Technique for the Unbiased Mapping of GCM Changes to Local Stations

2018 ◽  
Vol 19 (9) ◽  
pp. 1447-1465 ◽  
Author(s):  
Cristián Chadwick ◽  
Jorge Gironás ◽  
Sebastián Vicuña ◽  
Francisco Meza ◽  
James McPhee
Keyword(s):  
Climatic Variability ◽  
Alternative Methods ◽  
Absolute Difference ◽  
Climate Projections ◽  
Mean Absolute Difference ◽  
Local Climate ◽  
Climate Conditions ◽  
Ensemble Technique ◽  
Climatic Scenarios

Abstract Accounting for climate change, GCM-based projections and their uncertainty are relevant to study potential impacts on hydrological regimes as well as to analyze, operate, and design water infrastructure. Traditionally, several downscaled and/or bias-corrected GCM projections are individually or jointly used to map the raw GCMs’ changes to local stations and evaluate uncertainty. However, the preservation of GCMs’ statistical attributes is by no means guaranteed, and thus alternative methods to cope with this issue are needed. This work develops an ensemble technique for the unbiased mapping of GCM changes to local stations, which preserves local climate variability and the GCMs’ statistics. In the approach, trend percentiles are extracted from the GCMs to represent the range of future long-term climate conditions to which local climatic variability is added. The approach is compared against a method in which each GCM is individually used to build future climatic scenarios from which percentiles are computed. Both approaches were compared to study future precipitation conditions in three Chilean basins under future climate projections based on 45 GCM runs under the RCP8.5 scenario. Overall, the approaches produce very similar results, even if a few trend percentiles are adopted in the GCM preanalysis. In fact, using 5–10 percentiles produces a mean absolute difference of 0.4% in the estimation of the probabilities of consecutive years under different precipitation thresholds, which is ~60% less than the error obtained using the median trend. Thus, the approach successfully preserves the GCM’s statistical attributes while incorporating the range of projected climates.

scholarly journals Realtime monitoring for groundwater level and local climate based on universal communication system

2021 ◽  
Vol 2 (2) ◽  
pp. 67-76
Author(s):  
Rony Teguh ◽  
Hepryandi Usup
Keyword(s):  
Real Time ◽  
Groundwater Level ◽  
Meteorological Data ◽  
Current Method ◽  
Local Climate ◽  
Climate Conditions ◽  
Weather Patterns ◽  
The People ◽  
Universal Communication

The groundwater level and weather patterns and climate conditions are several of the very significant factors which influence the quality of livelihood and the other activity of the tropical peatland environment. The current method of groundwater level and meteorological information aggregate build the use of certain expensive weather station devices, prominent to a lack of vast monitoring suitable to cost barriers and disturbance in some countries. In this research, we have developed and implemented a hardware module based on an Arduino microcontroller and mobile communication, which measures the groundwater level and meteorological data, including air temperature, air humidity, and soil temperature, and humidity, rainfall in peatland area. The data groundwater level is received by a specially developed application interface running on an Internet of Things (IoT) connected through a Global Mobile System (GSM) communication. In this work, our proposed system is a model system that can able to generate alerts based on the real-time groundwater level and data weather as potential peat fire in Indonesia. It provides online and data real-time monitoring. In this works, we have resulted in a system to monitor the groundwater level and data weather alert, condition mapping, and warn the people from its disastrous effects.

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