Annual data on the number of deaths registered in England and Wales by age group, sex, year and underlying cause of death, as defined using the International Classification of Diseases, Tenth Revision.

This dataset is about books and is filtered where the book is Database nation : the death of privacy in the 21st century, featuring 7 columns including author, BNB id, book, book publisher, and ISBN. The preview is ordered by publication date (descending).

Dataset for the paper "Mass loss of the Greenland ice sheet until the year 3000 under a sustained late-21st-century climate" (Journal of Glaciology, https://doi.org/10.1017/jog.2022.9).

Please see the README for details.

V1.2: Now providing compressed netCDF files with reduced size.

V1.1: Scalar flux variable 'dlimdt' (total ice mass change) added. README updated.

V1: Initial upload.

The following script may be used to download the entire content of the archive on a Unix/Linux system:

!/bin/bash

--- download_all.sh ---

wget https://zenodo.org/record/6029867/files/_README.pdf

wget https://zenodo.org/record/6029867/files/run_specs_headers.zip

for aexp in hist ctrl_proj_long \

exp05\_long exp06\_long exp07\_long exp08\_long exp09\_long exp10\_long \ 

expa01\_long expa02\_long expa03\_long \ 

expb01\_long expb02\_long expb03\_long expb04\_long expb05\_long; do 

wget https://zenodo.org/record/6029867/files/${aexp}.zip 

done

Users should cite the original publication when using all or parts of these data.

To meet the climate change planning and adaptation needs of Alaska managers and decision makers, I developed a set of statewide summaries of available climate change projections that can be further subset using GIS techniques for requests by management unit, watershed, or other location. This facilitates the development of tailored climate futures for decision makers’ regional or subregional management context. This file describes the source data and summaries for purposes of technical /scientific documentation. The methods and presentation for these datasets were adapted from products in previous USGS-approved IP products for the AKCASC Building Resilience Today project (e.g, Community of Kotlik et al. 2019). For each data product included, summaries (averages or totals) are presented for multiple climate models or specific global warming levels and are average dover two time periods: 2040-2069, or the “2050s”, for near-term decision framing; and 2070-2099, or the “2080s”, for longer-term decision framing. In all cases where possible, both moderate emissions (RCP4.5 or +2C global level) and higher emissions (RCP8.5, or +4C global level) are presented. These choices (model averaging, temporal averaging, and scenario presentation) are tailored to the main sources of uncertainty (Hawkins and Sutton 2009) in climate model projections, specifically differences in climate model construction, climatic variability, and emissions scenario uncertainty (e.g., Littell et al. 2011, Snover et al. 2013, Terando et al. 2020). Not all scenario planning or climate impacts modeling needs can be met with these projections – these are intended to characterize a range of futures indicated by the available data products and facilitate further exploration of climate impacts modeling and adaptation development options.

These data represent simulated soil temperature and moisture conditions for current climate, and for future climate represented by all available climate models at two time periods during the 21st century. These data were used to: 1) quantify the direction and magnitude of expected changes in several measures of soil temperature and soil moisture, including the key variables used to distinguish the regimes used in the R and R categories; 2) assess how these changes will impact the geographic distribution of soil temperature and moisture regimes; and 3) explore the implications for using R and R categories for estimating future ecosystem resilience and resistance.

This dataset is about book subjects and is filtered where the books is The new face of war : how war will be fought in the 21st century. It has 4 columns: authors, book subject, books, and publication dates. The data is ordered by earliest publication date (descending).

Crop production is among the most extensive human activities on the planet – with critical importance for global food security, land use, environmental burden, and climate. Yet despite the key role that croplands play in global land use and Earth systems, there remains little understanding of how spatial patterns of global crop cultivation have recently evolved and which crops have contributed most to these changes. Here we construct a new data library of subnational crop-specific irrigated and rainfed harvested area statistics and combine it with global gridded land cover products to develop a global gridded (5-arcminute) irrigated and rainfed cropped area (MIRCA-OS) dataset for the years 2000 to 2015 for 23 crop classes. These global data products support critical insights into the spatially detailed patterns of irrigated and rainfed cropland change since the start of the century and provide an improved foundation for a wide array of global assessments spanning agriculture, water resource management, land use change, climate impact, and sustainable development.

About this dataset

Context

The dataset tabulates the Century population distribution across 18 age groups. It lists the population in each age group along with the percentage population relative of the total population for Century. The dataset can be utilized to understand the population distribution of Century by age. For example, using this dataset, we can identify the largest age group in Century.

Key observations

The largest age group in Century, FL was for the group of age 15-19 years with a population of 202 (10.21%), according to the 2021 American Community Survey. At the same time, the smallest age group in Century, FL was the 85+ years with a population of 42 (2.12%). Source: U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Variables / Data Columns

• Age Group: This column displays the age group in consideration
• Population: The population for the specific age group in the Century is shown in this column.
• % of Total Population: This column displays the population of each age group as a proportion of Century total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Century Population by Age. You can refer the same here

This resource contains code and input data to develop a high-resolution (0.1°) gridded global glacier and ice sheet fractional area dataset, which is also available in this resource. The dataset is developed from Randolph Glacier Inventory v6.0 shapefiles and supplementary shapefiles for the Antarctic and Greenland ice sheets. The approach is adapted from Li et al., (2021; https://doi.org/10.1017/jog.2021.28). The dataset provides estimates of the fraction (0 to 1) of land cover that is glaciated in each 0.1° x 0.1° grid cell. The dataset was designed for use in the SPEAR model (https://www.gfdl.noaa.gov/spear/) from the NOAA Geophysical Fluid Dynamics Laboratory (GFDL), but may be useful for other applications as well.

This work is documented in a NOAA Technical Memorandum (citation information to follow).

Attitudes to the political, social and economic Transformation . Topics: Economic situation; economic transformations; development of private business, privatization of land and of large enterprises; buying and selling land; willingness to work for a private company; direction of foreign policy; freedom of expression of political views; return to socialism vs. develop capitalism; role of social groups; trust in family and relatives, oneself, neighbors, fellow citizens, god, colleagues, church, astrologers, mass media; police, communist party, political parties, "Rukh", nationalists, Verkhovna Rada (parliament), armed forces, government, president, private entrepreneurs, mangers of large state enterprises, trade unions (traditional and new); membership in organizations; leisure activities; newspapers read last week; interests in politics; capable political leaders; strong leader vs. democracy; multiparty system; political parties and movements, that deserve power; important political movements; participation and voting in the Verkhovna Rada (parliament) Elections (March 1998); trust in deputy elected in one´s district; opinion about the President Kuchma; preferred role of the president; preferred priority in the policies of the president; general political situation in Ukraine and Russia; joining the union of Russia and Belarus; Russian language as a official language; satisfaction with one´s own present position in society, one´s own contribution to society and with that what one gets from society; predominant influence on one´s own life; satisfied with outlook on life; mood last days; social position in society; ability to live under changing social conditions as regards to health, working, clothing, housing, economic knowledge, confidence in one´s own abilities, medical assistance, fashionable clothing, basic furniture, contemporary political knowledge, resolve in pursuing one´s goals, legal protection for defending one´s rights and interests, ability to have an adequate vacation, having a second, unofficial job, buying the most necessary products, initiative and independence in solving daily problems, adequate leisure time, opportunity to work to full potential, opportunity to eat according to one´s own tastes; general health condition; suffering from any chronic illnesses; frequency of catching a cold/flu last year; frequency of being sick; stressful situations during last year; consequences of the Chornobyl catastrophe for one´s own health; satisfaction with quality of life in one´s resident; close relatives living outside Ukraine; leaving current residence (influential factors); preferred place to live; satisfaction with living conditions; current living conditions; number of rooms; size of family; number of people living together in one room; equipment in the household; possession of goods; second resident; domestic animals/pets; material level of the family´s life (scale); second income; income group; salary last month and anything left for next months; responsibility for delayed payments of wages; average income of the last month; monthly income (per person) providing average life of one´s own family; monthly average income (per person) counted as poor/rich; changes of material conditions for medical services, vacation, leisure time, reliable information about events in Ukraine and in the world, raising children, freedom to express views, participation in cultural events, environmental situation, personal security, protection from the whims of bureaucrats and bodies of power, security of employment; frequency of hooliganism and robberies in one´s own district; decision which encroached on people´s interests and actions against it; probability of mass protest actions and participation in them; political protests; death penalty; attitudes towards ethnic groups; violation of ethnic groups; maintain of peace and order; frequency of changing place of employment; work in public or private sector; job satisfied; religious confession; nationality; native language; spoken languages; language of the interview. Einstellung zur politischen, sozialen und ökonomischen Transformation. Themen: Ökonomische Situation; ökonomische Transformation; Entwicklung der Privatwirtschaft; Privatisierung von Grund und Boden sowie großer Unternehmen; Kauf und Verkauf von Land; Bereitschaft in einem privaten Betrieb zu arbeiten; Ausrichtung der Außenpolitik; Meinungsfreiheit; Rückkehr zum Sozialismus oder Entwicklung des Kapitalismus; Rolle sozialer Gruppen; Vertrauen in Institutionen; Freizeitaktivitäten; Zeitungslesen letzte Woche; Interesse an Politik; fähige politische Führer; starker Führer vs. Demokratie; Mehrparteiensystem; politische Parteien und Bewegungen, die die Macht verdienen; wichtige politische Bewegungen; Wahlbeteiligung und Wahlverhalten in der Parlamentswahl 1998; Vertrauen in die gewählten Abgeordneten des Distrikts; Meinung über Prof. Kuchma; bevorzugte Rolle des Präsidenten; bevorzugte Prioritäten der Politik des Präsidenten; allgemeine politische Situation in Ukraine und Russland; Beitritt der Vereinigung von Weißrussland und Russland; Russisch als offizielle Sprache; Zufriedenheit mit der eigenen Position in der Gesellschaft, dem eigenen Beitrag zur Gesellschaft und mit dem, was man von der Gesellschaft bekommt; vorherrschender Einfluss auf das eigene Leben; Zufriedenheit mit den Lebensaussichten; Stimmung in den letzten Tagen; soziale Position in der Gesellschaft; Fähigkeit, unter sich verändernden Bedingungen zu leben; Häufigkeit von Erkältungskrankheiten im letzten Jahr; Krankheitshäufigkeit; Stress im letzten Jahr; Folgen der Tschernobyl-Katastrophe für die eigene Gesundheit; Zufriedenheit mit der Lebensqualität in der eigenen Wohnumgebung; enge Verwandte im Ausland; Bereitschaft den Wohnort zu wechseln; bevorzugter Wohnort; Zufriedenheit mit den Lebensbedingungen; Anzahl der Wohnräume; Familiengröße; Haushaltsgröße; Haushaltsausstattung; Besitz von Gütern; zweiter Wohnsitz; Haustiere; materielles Lebensniveau der Familie (Skala); Zweiteinkommen; Einkommensgruppe; Einkommen des letzten Monats und was davon übrig ist; Verantwortlichkeiten für verspätete Zahlung; Durchschnittseinkommen des letzten Monats; monatliches Einkommen (pro Person); Durchschnittsleben für Familie gewährleisten; arm/reich; veränderte Bedingungen für die medizinische Versorgung; Urlaub; Freizeit; zuverlässige Informationen über die Ereignisse in der Ukraine und der Welt; Kindererziehung; Meinungsfreiheit; Teilnahme an kulturellen Veranstaltungen; Umweltsituation; persönliche Sicherheit; Schutz vor Behördenwillkür; Arbeitsplatzsicherheit; Häufigkeit von Überfällen in der Wohnumgebung; Übergriffe auf die Interessen der Menschen und Aktionen dagegen; Wahrscheinlichkeit von Massenprotesten und Teilnahme daran; politischer Protest; Todesstrafe; Haltung gegenüber ethnischen Gruppen; Menschenrechtsverletzungen ethnischer Gruppen; Aufrecherhaltung von Ruhe und Ordnung; Häufigkeit des Wechsels der Arbeitsstelle; Arbeit im öffentlichen oder privaten Sektor; Arbeitszufriedenheit; Religion; Nationalität; Muttersprache; weitere Sprachen; Interviewsprache. Quota sample (combined with route selection). Average bias from current social statistics does not exceed 2.0 percent. Quotenstichprobe (kombiniert mit Random Route). Durchschnittliche Abweichung von amtlicher Statistik nicht mehr als 2%.

About this dataset

Context

The dataset tabulates the population of Century by gender across 18 age groups. It lists the male and female population in each age group along with the gender ratio for Century. The dataset can be utilized to understand the population distribution of Century by gender and age. For example, using this dataset, we can identify the largest age group for both Men and Women in Century. Additionally, it can be used to see how the gender ratio changes from birth to senior most age group and male to female ratio across each age group for Century.

Key observations

Largest age group (population): Male # 25-29 years (99) | Female # 15-19 years (179). Source: U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Age groups:

• Under 5 years
• 5 to 9 years
• 10 to 14 years
• 15 to 19 years
• 20 to 24 years
• 25 to 29 years
• 30 to 34 years
• 35 to 39 years
• 40 to 44 years
• 45 to 49 years
• 50 to 54 years
• 55 to 59 years
• 60 to 64 years
• 65 to 69 years
• 70 to 74 years
• 75 to 79 years
• 80 to 84 years
• 85 years and over

Scope of gender :

Please note that American Community Survey asks a question about the respondents current sex, but not about gender, sexual orientation, or sex at birth. The question is intended to capture data for biological sex, not gender. Respondents are supposed to respond with the answer as either of Male or Female. Our research and this dataset mirrors the data reported as Male and Female for gender distribution analysis.

Variables / Data Columns

• Age Group: This column displays the age group for the Century population analysis. Total expected values are 18 and are define above in the age groups section.
• Population (Male): The male population in the Century is shown in the following column.
• Population (Female): The female population in the Century is shown in the following column.
• Gender Ratio: Also known as the sex ratio, this column displays the number of males per 100 females in Century for each age group.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Century Population by Gender. You can refer the same here

Reports, images, GIS and gridded products describing the Palaeozoic geology and conventional petroleum systems of parts of the UK offshore. Devonian and Carboniferous rocks are the focus in and around the Mid North Sea High, Central North Sea, the Moray Firth and Orcadian Basin. In the greater Irish Sea area, Carboniferous rocks are described. The peer-reviewed products were produced for the 21CXRM Palaeozoic Project by BGS for DECC/OGA, Oil and Gas UK and oil company sponsors between November 2014 and May 2016, to improve regional digital datasets and knowledge of the underexplored Palaeozoic petroleum systems, and to stimulate exploration. The petroleum systems analysis was based on new interpretations of extensive well, seismic, gravity-magnetic and source rock datasets, integrated with petrophysical studies, basin modelling and UK onshore knowledge. Released data were collated and interpreted, and interpretations of unreleased data were included with agreement of the data owners. Unreleased raw data is excluded, as is the UK Government Seismic data released in 2016. The datasets are applicable for use at scales between 1: 750,000 to 1: 3,000,000.

GIS versions of a regional structural summary and palaeogeographic reconstructions describing the Palaeozoic geology of parts of the UK offshore and onshore, plus a set of summary posters and a summary presentation capturing the conventional petroleum systems. Devonian and Carboniferous rocks are the focus in and around the Mid North Sea High, Central North Sea, the Moray Firth and Orcadian Basin. In the greater Irish Sea area, Carboniferous rocks are described. The peer-reviewed products were produced for the 21CXRM Palaeozoic Project by BGS for DECC/OGA, Oil and Gas UK and oil company sponsors between November 2014 and May 2016, to improve regional digital datasets and knowledge of the underexplored Palaeozoic petroleum systems, and to stimulate exploration. The petroleum systems analysis was based on new interpretations of extensive well, seismic, gravity-magnetic and source rock datasets, integrated with petrophysical studies, basin modelling and UK onshore knowledge. Released data were collated and interpreted, and interpretations of unreleased data were included with agreement of the data owners. Unreleased raw data is excluded, as is the UK Government Seismic data released in 2016. The GIS layers were digitised from figures prepared for project reports and are applicable for use at scales between 1:1,000,000 and 1:3,000,000.

This dataset provides the Greenland ice sheet model output produced as part of the Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6, Eyring et al., 2016; Nowicki et al. 2016). These simulations focus on 21st century evolution of the Greenland ice sheet under selected CMIP scenarios (RCP2.6, RCP8.5, SSP126 and SSP585) and CMIP models. Results of ISMIP6-Projection-Greenland have been published in Goelzer et al. (2020) and Payne et al. (2021).

See here and Nowicki et al. (2020) for the experimental protocol, CMIP models, forcing datasets and requested model output data. The ocean forcing datasets are also described in Slater et al. (2019, 2020). The sampling methodology for the CMIP5 models (MIROC5, NorESM, HadGEM2-ES, IPSL-CM5-MR, CSIRO-Mk3.6, ACCESS1.3) is described in Barthel et al. (2020). As CMIP6 models became available, ISMIP6 prepared dataset for CNRM-CM6 (SSP585 and SSP126), CESM2 (SSP585) and UKEM1-CM6 (SSP585). Unlike for the rigorous analysis for the CMIP5 models, the CMIP6 models were selected because of their availability. The forcing dataset is also available via GHub.

To view available experiments and individual ice sheet model contributions see the summary table in the attached documentation.

This archive only contains time varying 2D variables (see Table A1 of ISMIP6 wiki). The data have been conservatively interpolated to a 5km grid by ISMIP6. Polar stereo-graphic projection with standard parallel at 70° N and a central meridian of 45° W (315° E) on datum WGS84 (EPSG3413 projection). The lower left cell center is at (-720000m,-3450000m) with nx=1681 and ny=2881 cells in x and y-direction at full km positions (xmin = -720 km, xmax = +960 km, ymin = -3450 km, ymax = -570 km). The original submission from modeling groups are available upon request by emailing ismip6-at-gmail.com.

A brief overview of participating models and characteristics is shown in the table below (see Goelzer et al. 2020).

Downloading Data

The data can be downloaded from the Globus GHub-ISMIP6-Projections endpoint. Please log in and click on the Download tab to receive the Download instructions.

Acknowledgements

The experimental protocol and datasets for the ISMIP6-Projections-Greenland standalone ice sheet simulations would not have been possible without the effort of many scientists that have given their time and expertise, and have run models to convert the CMIP models output into datasets that standalone ice sheet models can use. ISMIP6 would like to thank the ocean focus group under the leadership of Fiamma Straneo, the atmospheric focus group under the leadership of Bill Lipscomb and Robin Smith, and the CMIP5 model evaluation focus group under the leadership of Alice Barthel. Donald Slater, Denis Felixson, Mathieu Morlinghem and Heiko Goelzer have been instrumental in the development of the ice front retreat and melt parameterization and associated dataset. Xavier Fettweis, Patrick Alexander and Heiko Goelzer prepared the atmospheric dataset. Alice Barthel, Chris Little, Cecile Agosta, and Jamie Holte provided a rigorous analysis of the CMIP5 models against historical data, which allowed the CMIP5 model evaluation group and the ISMIP6 steering committee to select the CMIP5 models used in this effort. Finally, we thank the ISMIP6 ice sheet modelers for their feedback on the design of the protocol and their willingness to participate in ISMIP6.

As part of this national strategy, the Ministry of Education, Culture, Sports, Science and Technology (MEXT) had launched a 5-year (FY2007 - 2011) initiative called the Innovative Program of Climate Change Projection for the 21st Century (KAKUSHIN Program), using the Earth Simulator (ES) to address emerging research challenges, such as those derived from the outcomes of the MEXT's Kyosei Project (FY2002 - 2006), that had made substantial contributions to the Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC). The KAKUSHIN Program was expected to further contribute to the Fifth Assessment Report (AR5).

The research items include the advancement and forecasting of global warming models, the quantification and reduction of model uncertainty, and the evaluation of the impacts of natural disasters based on forecast information. Much of the data submitted to CMIP5 from Japan were generated under this KAKUSHIN program using the global climate models and the Earth system models developed in Japan. This dataset is the result of using the Earth System Model MIROC-ESM-CHEM.

All CMIP5 data are collected, managed, and published by the Earth System Grid Federation (ESGF), and DIAS serves as an ESGF node. All public datasets, including this dataset, are available from ESGF. For information on how to use these datasets, including this dataset, see "CMIP5 Data - Getting Started" (URL is available in the online information below). Please note that an ESGF account is required to download the CMIP5 data.

Because the terms of use for CMIP5 data are different from CMIP6 in many respects, please check the following Terms of Use carefully: https://pcmdi.llnl.gov/mips/cmip5/terms-of-use.html Currently, all CMIP5 data, including this dataset, is classified as "unrestricted" within it.

About this dataset

Context

The dataset tabulates the Century population by age cohorts (Children: Under 18 years; Working population: 18-64 years; Senior population: 65 years or more). It lists the population in each age cohort group along with its percentage relative to the total population of Century. The dataset can be utilized to understand the population distribution across children, working population and senior population for dependency ratio, housing requirements, ageing, migration patterns etc.

Key observations

The largest age group was 18 to 64 years with a poulation of 1,087 (55.12% of the total population). Source: U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates.

Age cohorts:

• Under 18 years
• 18 to 64 years
• 65 years and over

Variables / Data Columns

• Age Group: This column displays the age cohort for the Century population analysis. Total expected values are 3 groups ( Children, Working Population and Senior Population).
• Population: The population for the age cohort in Century is shown in the following column.
• Percent of Total Population: The population as a percent of total population of the Century is shown in the following column.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Century Population by Age. You can refer the same here

These data were compiled as a supplement to a previously published journal article (Bradford et al., 2019), that employed a ecosystem water balance model to characterize current and future patterns in soil temperature and moisture conditions in dryland areas of western North America. Also, these data are associated with a published USGS data release (Bradford and Schlaepfer, 2019). The objectives of our study were to (1) characterize current and future patterns in soil temperature and moisture conditions in dryland areas of western North America, (2) evaluate the impact of these changes on estimation of resilience and resistance among a representative set of climate scenarios. These data represent geographic patterns in simulated soil temperature and soil moisture conditions and underlying variables based on SOILWAT2 simulations under climate conditions representing historical (current) time period (1980-2010) and two future projected time periods (2020-2050, d40yrs) and (2070-2100, d90yrs) for two representative concentration pathways (RCP4.5, RCP8.5) as medians across simulation runs based on output from each of the available downscaled global circulation models that participated in CMIP5 (RCP4.5, 37 GCMs; RCP8.5, 35 GCMs; Maurer et al. 2007). Additional information about the SOILWAT2 simulation experiments can be found in Bradford et al. 2019. These data were created in 2018, 2019, and 2021 for the area of the sagebrush region in the western North America. These data were created by a collaborative research project between the U.S. Geological Survey, Marshall University and Yale University. These data can be used with the high-resolution matching as defined by Renne et al. (in prep.), and within the scope of Bradford et al. 2019. These data may also be used to evaluate the potential impact of changing climate conditions on geographic patterns in simulated soil temperature and soil moisture conditions.

Hydroclimate and terrestrial hydrology greatly influence the local communities, ecosystems, and economies across Alaska and Yukon River Basin. Therefore, we utilized the Regional Arctic Systems Model (RASM) to model the coupled land-atmosphere, and generated a climate and hydrology dataset at 4-km grid spacing to improve our understanding of the regional hydroclimate and terrestrial hydrology. Our model domain encompasses all of the U.S. State of Alaska, the entire Yukon River Basin, part of Western Canada, and the eastern coastal region of Russia. This dataset includes 1) one simulation of the historical climate (Water Years 1991-2021), which serves as a benchmark for climate change studies, and 2) two future simulations (Equivalent Water Years 2035-2065) using the Pseudo-Global Warming method under future greenhouse gas emission scenario SSP2-4.5. The two future scenarios represent median and high changes derived from ensemble means across different Global Climate Models in the Coupled Model Intercomparison Project Phase 6 within SSP2-4.5 respectively. The microphysics schemes in the Weather Research and Forecast (WRF) atmospheric model were manually tuned for optimal model performance. The land component in RASM was replaced using the Community Terrestrial Systems Model (CTSM) given its comprehensive process representations for cold regions. We conducted optimization for uncoupled CTSM to improve its performance in terrestrial hydrologic simulations, especially streamflow and snow (Cheng et al., 2023). In order to maintain the quality for both hydroclimate and terrestrial hydrologic simulation, we implemented a strategy of iterative testing and re-optimization of CTSM. This dataset was then generated using RASM with optimized CTSM parameters and manually tuned WRF microphysics. The historical simulation was evaluated against multiple observational datasets for five key weather variables and hydrologic fluxes, including precipitation, air temperature, snow fraction, evaporation-to-precipitation ratios, and streamflow. The evaluation details can be found in Cheng et al. (2024).

The Nordic dataset from the survey Journalistic Roles, Values and Qualifications in the 21st century: How Journalism Educators across the Globe View the Future of a Profession in Transition (2020–2021).

The survey data is available as a SPSS file (.sav) and a comma-separated text file (.csv).

Although the Black Death peaked in Europe between 1348 and 1351, plague was almost always present in Britain for the next four centuries. In most years, plague was a dormant threat that affected very few people, and diseases such as smallpox and influenza were much more widespread; however, bubonic plague was prone to outbreaks that could decimate populations in a few short years. In London, plague outbreaks occurred every few decades, usually with death tolls in the tens of thousands. The duration and severity of these epidemics varied, sometimes having high death tolls but subsiding quickly, while others had relatively lower death tolls but could last for a number of years. As London's population and density also grew drastically during this period, plague affected the city differently in the sixteenth and seventeenth centuries. Great Plague of London The final major plague epidemic observed in Britain took place in 1665 and 1666. It became known as the "Great Plague" as it was the last of its kind in Britain, and its death toll eclipsed all other epidemics in the preceding century (although it was much smaller than that of the Black Death). The plague lasted for eighteen months, and had a reported death toll of more than 70,000 in this time; although modern historians estimate that the actual death toll exceeded 100,000. At its peak in September 1665, it is reported that there were more than 7,000 deaths per week, although this may have also been much higher due to the limited records kept at the time. Another reason for the lack of accurate records relating to this epidemic is because of the Great Fire of London in 1666. The fire started on September 02. 1666, and destroyed almost all of the city within the walls, leaving thousands homeless. Historians continue to debate the fire's significance, some citing that it destroyed the unsanitary dwellings where infected rats lived and drove them from the city, while others claim that the timings were purely coincidental and that the epidemic had already begun to subside in February.