Software for Agroclimatic Data Management
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Fatalities Associated with the Severe Weather Conditions in the Czech Republic, 2000–2019
Nat. Hazards Earth Syst. Sci., 21, 1355–1382, 2021 https://doi.org/10.5194/nhess-21-1355-2021 © Author(s) 2021. This work is distributed under the Creative Commons Attribution 4.0 License. Fatalities associated with the severe weather conditions in the Czech Republic, 2000–2019 Rudolf Brázdil1,2, Katerinaˇ Chromá2, Lukáš Dolák1,2, Jan Rehoˇ rˇ1,2, Ladislava Rezníˇ ckovᡠ1,2, Pavel Zahradnícekˇ 2,3, and Petr Dobrovolný1,2 1Institute of Geography, Masaryk University, Brno, Czech Republic 2Global Change Research Institute, Czech Academy of Sciences, Brno, Czech Republic 3Czech Hydrometeorological Institute, Brno, Czech Republic Correspondence: Rudolf Brázdil ([email protected]) Received: 12 January 2021 – Discussion started: 21 January 2021 Revised: 25 March 2021 – Accepted: 26 March 2021 – Published: 4 May 2021 Abstract. This paper presents an analysis of fatalities at- with fatal accidents as well as a decrease in their percent- tributable to weather conditions in the Czech Republic dur- age in annual numbers of fatalities. The discussion of results ing the 2000–2019 period. The database of fatalities de- includes the problems of data uncertainty, comparison of dif- ployed contains information extracted from Právo, a lead- ferent data sources, and the broader context. ing daily newspaper, and Novinky.cz, its internet equivalent, supplemented by a number of other documentary sources. The analysis is performed for floods, windstorms, convective storms, rain, snow, glaze ice, frost, heat, and fog. For each 1 Introduction of them, the associated fatalities are investigated in terms of annual frequencies, trends, annual variation, spatial distribu- Natural disasters are accompanied not only by extensive ma- tion, cause, type, place, and time as well as the sex, age, and terial damage but also by great loss of human life, facts easily behaviour of casualties. -
Downbursts: As Dangerous As Tornadoes? Winds Can Be Experienced Along the Leading Edge of This “Spreading Out” Air
DDoowwnnbbuurrssttss:: AAss DDaannggeerroouuss aass TToorrnnaaddooeess?? National Weather Service Greenville-Spartanburg, SC What is a Downburst? “It had to be a tornado!” This is a “updraft.” common statement made by citizens of the Carolinas and On a typical day in the warm season, North Georgia who experience once a cloud grows to 20,000 to damaging winds associated with 30,000 feet, it will begin to produce severe thunderstorms, especially heavy rain and lightning. The falling if those winds cause damage to rain causes a “downdraft,” or sinking their homes. However, the column of air to form. A thunderstorm combination of atmospheric may eventually grow to a height of ingredients that are necessary for 50,000 feet or more before it stops tornadoes occurs only rarely developing. Generally speaking, the across our area. In fact the 46 Fig. 1. Tracks of tornadoes across the “taller” the storm, the more likely it is Carolinas and Georgia from 1995 through counties that represent the to produce a strong downdraft. Once 2011. Compare this with the downburst Greenville-Spartanburg Weather reports during this time (Figure 3). the air within the downdraft reaches Forecast Offices’s County Warning the surface, it spreads out parallel to Area only experience a total of 12 the ground. Very strong to damaging to 15 tornadoes during an average year. However, thunderstorms and even severe thunderstorms are a relatively common occurrence across our area, especially from late spring through mid-summer. This is because a warm and humid (i.e., unstable) atmosphere is required for thunderstorm development. If some atmospheric process forces the unstable air Fig. -
T.C. Selçuk Ünġversġtesġ Fen Bġlġmlerġ Enstġtüsü Tuzlu
T.C. SELÇUK ÜNĠVERSĠTESĠ FEN BĠLĠMLERĠ ENSTĠTÜSÜ TUZLU TOPRAKLARDA KATALAZ ENZĠMĠNĠN AKTĠVĠTESĠ VE KĠNETĠĞĠ Emine YILDIRIM YÜKSEK LĠSANS TEZĠ TOPRAK BĠLĠMĠ VE BĠTKĠ BESLEME ANABĠLĠM DALI KONYA, 2010 ÖZET YÜKSEK LĠSANS TEZĠ TUZLU TOPRAKLARDA KATALAZ ENZĠMĠNĠN AKTĠVĠTESĠ VE KĠNETĠĞĠ Emine YILDIRIM Selçuk Üniversitesi Fen Bilimleri Enstitüsü Toprak Bilimi ve Bitki Besleme Anabilim Dalı DanıĢman: Yrd. Doç. Dr. Fariz MĠKAĠLSOY 2010, Sayfa: 72 Jüri: Yrd. Doç. Dr. Fariz MĠKAĠLSOY Prof. Dr. Nizamettin ÇĠFTÇĠ Doç. Dr. Refik UYANÖZ Bu araĢtırmada, Tuz gölü çevresi tarım dıĢı arazilerden alınan 3 toprak örneğinde çalıĢılmıĢtır. Gazometrik metod kullanılarak katalaz enziminin aktivitesi tayin edilerek kinetik parametreleri hesaplanmıĢtır. Fiziksel, kimyasal özellikleri ve % tuz oranı farklı toprakların katalaz enzim analizi 20+1 oC laboratuar koĢullarında değiĢik substrat konsantrasyonlarda (% 3, % 6, % 9, % 12, % 15, % 18, %2 1, % 24, % 27, % 30 H2O2) yürütülmüĢtür. Bu analizde ürün olarak açığa çıkan O2‟nin zamana göre değiĢimi (20, 40, 60, 80,….300 sn) kararlı hale gelmesine kadar devam edilmiĢtir. Katalaz enzim aktivitesi (υ) ve kinetik parametreleri (υ0, Vmax ve Km) her toprak için ayrı ayrı yapılmıĢtır. Sonuçlara göre, tuz konsantrasyonu yüksek toprakta katalaz enziminin kinetik parametresi olan Km‟nin değeri yüksek bulunmuĢtur. Vmax değeri ise en düĢük olarak bulunmuĢtur. Ayrıca reaksiyon hızının % 24 substrat konsantrasyonunda artıĢ gösterdiği ve daha sonra değiĢmediği tesbit edildi. Bu metod toprakta katalaz enzim aktivitesinin tesbitinde kullanılabilir. Anahtar Kelimeler: Toprak, enzim aktivitesi, katalaz, kinetik parametreler, tuz i ABSTRACT MASTER THESĠS ACTIVITY AND KINETICS OF CATALASE ENZYME IN SALINE SOILS Emine YILDIRIM Selçuk University Graduate School of Natural and Applied Sciences Department of Soil Science and Plant Nutrition Supervisor: Yrd. Doç. -
ESSENTIALS of METEOROLOGY (7Th Ed.) GLOSSARY
ESSENTIALS OF METEOROLOGY (7th ed.) GLOSSARY Chapter 1 Aerosols Tiny suspended solid particles (dust, smoke, etc.) or liquid droplets that enter the atmosphere from either natural or human (anthropogenic) sources, such as the burning of fossil fuels. Sulfur-containing fossil fuels, such as coal, produce sulfate aerosols. Air density The ratio of the mass of a substance to the volume occupied by it. Air density is usually expressed as g/cm3 or kg/m3. Also See Density. Air pressure The pressure exerted by the mass of air above a given point, usually expressed in millibars (mb), inches of (atmospheric mercury (Hg) or in hectopascals (hPa). pressure) Atmosphere The envelope of gases that surround a planet and are held to it by the planet's gravitational attraction. The earth's atmosphere is mainly nitrogen and oxygen. Carbon dioxide (CO2) A colorless, odorless gas whose concentration is about 0.039 percent (390 ppm) in a volume of air near sea level. It is a selective absorber of infrared radiation and, consequently, it is important in the earth's atmospheric greenhouse effect. Solid CO2 is called dry ice. Climate The accumulation of daily and seasonal weather events over a long period of time. Front The transition zone between two distinct air masses. Hurricane A tropical cyclone having winds in excess of 64 knots (74 mi/hr). Ionosphere An electrified region of the upper atmosphere where fairly large concentrations of ions and free electrons exist. Lapse rate The rate at which an atmospheric variable (usually temperature) decreases with height. (See Environmental lapse rate.) Mesosphere The atmospheric layer between the stratosphere and the thermosphere. -
Land Suitability Evaluation Using Gis for Vegetable Crops in Kathmandu Valley /Nepal
LAND SUITABILITY EVALUATION USING GIS FOR VEGETABLE CROPS IN KATHMANDU VALLEY /NEPAL Dissertation zur Erlangung des akademischen Grades Doctor rerum agriculturarum (Dr.rer.agr.) eingereicht an der Landwirtschaftlich-Gärtnerischen Fakultät der Humboldt-Universität zu Berlin von M.Sc. Nabarath Baniya geboren am 01.12.1969 in Kathmandu, Nepal dem Präsident der Humboldt-Universität zu Berlin Prof. Dr. Christoph Markschies Dekan der Landwirtschaftlich-Gärtnerischen Fakultät Prof. Dr. Dr. N.c. Otto Kaufmann Gutachter: Prof. Dr. sc Drs. h. c. Michael H. Böhme Dr. rer. agr. Michael La Rosa Perez Berlin, 13. Oktober 2008 Dedication To my parents, Udaya Bahadur Baniya and Til Kumari Baniya, who would have appreciated seeing it if they were still alive. II ACKNOWLEDGEMENT I wish to express my gratitude to all those who have given me assistance, help and support during the completion of my PhD in Faculty of Agriculture and Horticulture, Institute of Horticultural Sciences, Humboldt University of Berlin. I acknowledge a deep sense of gratitude to Prof. Dr. Michael Böhme my supervisor, who had always spread his helping hands during my PhD study periods, and given me guidance, valuable suggestion, critical comments and kindness during and completion of present work. His innovative research ideas kind patient and effective guidance throughout my work need not to be exaggerated. This thesis would never be accomplished in this shape without his selfless contributions in various aspects. I am very happy to state that I got to learn a lot from his experience in field of horticulture science. I gratefully acknowledge Dr. rer. agr. Michael La Rosa Perez, LGF, WISOLA, for guiding me on analytical aspect of the present dissertation. -
An Introduction SOIL CLASSIFICATION
Ngogo Mn. Ge:140 @2019 SOIL CLASSIFICATION An Introduction SAUT; Geography Dept Ngogo Mn. Ge:140 @2019 Introduction • Classification of soil is the separation of soil into classes or groups each having similar characteristics and potentially similar behaviour. • The criteria for grouping soils depend on the purposes of classification. • Soil is not uniformly distributed. Properties of soil vary due to several soil forming factors. properties vary very widely. Soil types are many. To identify, understand, and manage soils, soil scientists have developed a set of soil classification or taxonomy systems. SAUT; Geography Dept Ngogo Mn. Ge:140 @2019 Methods of Soil Classification Systems • Systems which use the properties of the soils are called TAXONOMIC SYSTEMS OF CLASSIFICATION. • Systems that employ soil usage are called CAPABILITY CLASSIFICATION. • Though these systems are considered to be subjective or utilitarian system of classification. • International soil classification are primarily for use by soil specialists. SAUT; Geography Dept Ngogo Mn. Ge:140 @2019 Soil Classification Used in the Tropics I. The FAO/UNESCO soil map of the world (FAO/UNESCO, 1977) II. The New Comprehensive Classification System or US Soil Taxonomy Classification (Soil-Survey Staff, 1975) III. The French Classification System (Aubert (1964) SAUT; Geography Dept Ngogo Mn. Ge:140 @2019 FAO Soil Classification System • In 1977 FAO/UNESCO published the first soil map with a uniform classification throughout. • The World Soil Map is not based on any one system, but rather, a collection of national soil maps influenced by US System. • In the FAO system, the soils that occur in a particular region and exhibit a certain relationship to one another are grouped in association or “ major soil Units” SAUT; Geography Dept Ngogo Mn. -
Classification of Soil Magnetic Susceptibility and Prediction of Metal Detector Performance – Case Study of Angola
Classification of soil magnetic susceptibility and prediction of metal detector performance – case study of Angola Holger Preetz*a, Sven Altfelderb, Volker Henningsb, Jan Igela aLeibniz Institute for Applied Geophysics, Stilleweg 2, D-30655 Hannover, Germany bFederal Institute for Geosciences and Natural Resources, Stilleweg 2, D-30655 Hannover, Germany Abstract Soil magnetic properties can seriously impede the performance of metal detectors used in landmine clearance operations. For a proper planning of clearance operations pre-existing information on soil magnetic susceptibility can be helpful. In this study we briefly introduce a classification system to assess soil magnetic susceptibilities from geoscientific maps. The classification system is based on susceptibility measurements conducted on archived lateritic soil samples from 15 tropical countries. The system is applied to a soil map of Angola, resulting in a map that depicts soil magnetic susceptibilities as a worst case scenario. An additional layer depicting the surveyed mine affected communities in Angola is added to the map, which demonstrates that a large number of those are located in areas where soil is expected to impede metal detector performance severely. Keywords: Angola, soils, soil classification, magnetic susceptibility, metal detector, landmine detection 1. INTRODUCTION Angola is one of more than 75 countries worldwide affected by landmines and/or unexploded ordnance (UXO). Many of these countries are located in the tropics and Angola belongs to the most contaminated places1. The country suffered from a long lasting civil war which began with its independence from Portugal in 1975 and ended in 2002. It is estimated that 500,000 to 1 million landmines remain as a legacy of the armed conflict and still represent a deadly hazard to large parts of the civil population. -
Global Status, Processes and Trends in Soil Erosion
Status of the World’s Main Report Soil Resources Chapter 6 Global soil status, processes and trends © FAO | Giuseppe Bizzarri © FAO INTERGOVERNMENTAL TECHNICAL PANEL ON SOILS Disclaimer and copyright Recommended citation: FAO and ITPS. 2015. Status of the World’s Soil Resources (SWSR) – Main Report. Food and Agriculture Organization of the United Nations and Intergovernmental Technical Panel on Soils, Rome, Italy The designations employed and the presentation of material in this information product do not imply the expression of any opinion whatsoever on the part of the Food and Agriculture Organization of the United Nations (FAO) concerning the legal or development status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. The mention of specific companies or products of manufacturers, whether or not these have been patented, does not imply that these have been endorsed or recommended by FAO in preference to others of a similar nature that are not mentioned. The views expressed in this information product are those of the author(s) and do not necessarily reflect the views or policies of FAO. ISBN 978-92-5-109004-6 © FAO, 2015 FAO encourages the use, reproduction and dissemination of material in this information product. Except where otherwise indicated, material may be copied, downloaded and printed for private study, research and teaching purposes, or for use in non-commercial products or services, provided that appropriate acknowledgement of FAO as the source and copyright holder is given and that FAO’s endorsement of users’ views, products or services is not implied in any way. -
Glossary of Severe Weather Terms
Glossary of Severe Weather Terms -A- Anvil The flat, spreading top of a cloud, often shaped like an anvil. Thunderstorm anvils may spread hundreds of miles downwind from the thunderstorm itself, and sometimes may spread upwind. Anvil Dome A large overshooting top or penetrating top. -B- Back-building Thunderstorm A thunderstorm in which new development takes place on the upwind side (usually the west or southwest side), such that the storm seems to remain stationary or propagate in a backward direction. Back-sheared Anvil [Slang], a thunderstorm anvil which spreads upwind, against the flow aloft. A back-sheared anvil often implies a very strong updraft and a high severe weather potential. Beaver ('s) Tail [Slang], a particular type of inflow band with a relatively broad, flat appearance suggestive of a beaver's tail. It is attached to a supercell's general updraft and is oriented roughly parallel to the pseudo-warm front, i.e., usually east to west or southeast to northwest. As with any inflow band, cloud elements move toward the updraft, i.e., toward the west or northwest. Its size and shape change as the strength of the inflow changes. Spotters should note the distinction between a beaver tail and a tail cloud. A "true" tail cloud typically is attached to the wall cloud and has a cloud base at about the same level as the wall cloud itself. A beaver tail, on the other hand, is not attached to the wall cloud and has a cloud base at about the same height as the updraft base (which by definition is higher than the wall cloud). -
Construction of an Yucatec Maya Soil Classification and Comparison with the WRB Framework Francisco Bautista1*†, J Alfred Zinck2†
Bautista and Zinck Journal of Ethnobiology and Ethnomedicine 2010, 6:7 http://www.ethnobiomed.com/content/6/1/7 JOURNAL OF ETHNOBIOLOGY AND ETHNOMEDICINE RESEARCH Open Access Construction of an Yucatec Maya soil classification and comparison with the WRB framework Francisco Bautista1*†, J Alfred Zinck2† Abstract Background: Mayas living in southeast Mexico have used soils for millennia and provide thus a good example for understanding soil-culture relationships and for exploring the ways indigenous people name and classify the soils of their territory. This paper shows an attempt to organize the Maya soil knowledge into a soil classification scheme and compares the latter with the World Reference Base for Soil Resources (WRB). Methods: Several participative soil surveys were carried out in the period 2000-2009 with the help of bilingual Maya-Spanish-speaking farmers. A multilingual soil database was built with 315 soil profile descriptions. Results: On the basis of the diagnostic soil properties and the soil nomenclature used by Maya farmers, a soil classification scheme with a hierarchic, dichotomous and open structure was constructed, organized in groups and qualifiers in a fashion similar to that of the WRB system. Maya soil properties were used at the same categorical levels as similar diagnostic properties are used in the WRB system. Conclusions: The Maya soil classification (MSC) is a natural system based on key properties, such as relief position, rock types, size and quantity of stones, color of topsoil and subsoil, depth, water dynamics, and plant-supporting processes. The MSC addresses the soil properties of surficial and subsurficial horizons, and uses plant communities as qualifier in some cases. -
Experimental and Observational Studies Find Contrasting Responses
RESEARCH ARTICLE Experimental and observational studies find contrasting responses of soil nutrients to climate change ZY Yuan1,2*†, F Jiao1,2*†, XR Shi1,2, Jordi Sardans3,4, Fernando T Maestre5, Manuel Delgado-Baquerizo5,6, Peter B Reich7,8, Josep Pen˜ uelas3,4 1State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation, Northwest A&F University, Yangling, China; 2Institute of Soil and Water Conservation, Chinese Academy of Science and Ministry of Water Resource, Yangling, China; 3Global Ecology Unit CREAF-CSIC- UAB, Consejo Superior de Investigaciones Cientı´ficas (CSIC), Bellaterra, Spain; 4CREAF, Cerdanyola del Valle`s, Spain; 5Departamento de Biologı´a y Geologı´a, Fı´sica y Quı´mica Inorga´nica, Universidad Rey Juan Carlos, Mo´stoles, Spain; 6Cooperative Institute for Research in Environmental Sciences, University of Colorado, Boulder, Colorado; 7Hawkesbury Institute for the Environment, University of Western Sydney, Penrith, Australia; 8Department of Forest Resources, University of Minnesota, Minnesota, United States Abstract Manipulative experiments and observations along environmental gradients, the two most common approaches to evaluate the impacts of climate change on nutrient cycling, are generally assumed to produce similar results, but this assumption has rarely been tested. We did *For correspondence: zyyuan@ so by conducting a meta-analysis and found that soil nutrients responded differentially to drivers of ms.iswc.ac.cn (ZYY); [email protected]. climate change depending on the approach considered. Soil carbon, nitrogen, and phosphorus ac.cn (FJ) concentrations generally decreased with water addition in manipulative experiments but increased †These authors contributed with annual precipitation along environmental gradients. -
10.6 ADVANCES in DOWNBURST MONITORING and PREDICTION with GOES-16 Kenneth L. Pryor Center for Satellite Applications and Resear
10.6 ADVANCES IN DOWNBURST MONITORING AND PREDICTION WITH GOES-16 Kenneth L. Pryor Center for Satellite Applications and Research (NOAA/NESDIS) College Park, MD 1. INTRODUCTION The three-channel GOES imager product (Pryor 2009) has been developed and The launch of Geostationary Operational experimentally implemented to assess downburst Environmental Satellite (GOES)-16 in November potential over the western United States with 2016 and subsequent activation of the Advanced improved temporal and spatial resolution. The Baseline Imager (ABI) in January 2017 has availability of the split-window channel in the resulted in the increased accessibility to high GOES-16 imager allows for the inference of spatial and temporal satellite image datasets for boundary layer moisture content. Wakimoto convective storm monitoring and nowcasting. (1985), based on his study of microbursts that The existing suite of GOES downburst prediction occurred during the Joint Airport Weather Studies algorithms employs the GOES imager and (JAWS) project, noted favorable environmental sounder to calculate potential of occurrence conditions over the western United States: (1) based on conceptual models of favorable intense solar heating of the surface and a environmental thermodynamic profiles for resulting superadiabatic surface layer; (2) a deep, downburst generation. Traditional meteorological dry-adiabatic convective boundary layer (Sorbjan satellite techniques for deep convective storm 1989) that extends upward to near the 500mb monitoring, including the water vapor – longwave level; (3) a well-mixed moisture profile with a infrared (WV – IR) brightness temperature large relative humidity gradient between the mid- difference (BTD), have recently been extended troposphere and the surface. The GOES-16 ABI by multichannel techniques for diagnosing microburst algorithm employs brightness attributes of a favorable downburst environment.