scholarly journals Leveraging legacy archaeological collections as proxies for climate and environmental research

2020 ◽  
Vol 117 (15) ◽  
pp. 8287-8294 ◽  
Author(s):  
Frankie St. Amand ◽  
S. Terry Childs ◽  
Elizabeth J. Reitz ◽  
Sky Heller ◽  
Bonnie Newsom ◽  
...  
Keyword(s):  
Climate Models ◽  
Regional Climate ◽  
Environmental Research ◽  
Cultural Resources ◽  
Field Methods ◽  
Radiocarbon Dates ◽  
Archaeological Collections ◽  
The Face ◽  
Ecological Baselines ◽  
Using Data

Understanding the causes and consequences of previous climate changes is essential for testing present-day climate models and projections. Archaeological sites are paleoenvironmental archives containing unique ecological baselines with data on paleoclimate transformations at a human timescale. Anthropogenic and nonanthropogenic forces have destroyed many sites, and others are under immediate threat. In the face of this loss, previously excavated collections from these sites—referred to as legacy collections—offer a source of climate and other paleoenvironmental information that may no longer exist elsewhere. Here, we 1) review obstacles to systematically using data from legacy archaeological collections, such as inconsistent or unreported field methods, inadequate records, unsatisfactory curation, and insufficient public knowledge of relevant collections; 2) suggest best practices for integrating archaeological data into climate and environmental research; and 3) summarize several studies to demonstrate the benefits and challenges of using legacy collections as archives of local and regional environmental proxies. Data from archaeological legacy collections contribute regional ecological baselines as well as serve to correct shifting baselines. They also enable regional climate reconstructions at various timescales and corroborate or refine radiocarbon dates. Such uses of legacy collections raise ethical concerns regarding ownership of and responsibility for cultural resources and highlight the importance of Indigenous involvement in planning and executing fieldwork and stewardship of cultural heritage. Finally, we discuss methodologies, practices, and policies pertaining to archaeological legacy collections and support calls for discipline-wide shifts in collections management to ensure their long-term utility in multidisciplinary research and public engagement.

scholarly journals Comparison of Linear Predictability of Surface Wind Components from Observations with Simulations from RCMs and Reanalysis

2018 ◽  
Vol 57 (4) ◽  
pp. 889-906
Author(s):  
Yiwen Mao ◽  
Adam Monahan
Keyword(s):  
Climate Models ◽  
Regional Climate ◽  
Surface Wind ◽  
Signal Strength ◽  
Regional Climate Models ◽  
Small Scale ◽  
Mountainous Terrain ◽  
Physical Processes ◽  
Tropospheric Circulation ◽  
Using Data

AbstractThis study compares the predictability of surface wind components by linear statistical downscaling using data from both observations and comprehensive models [regional climate models (RCM) and NCEP-2 reanalysis] in three domains: North America (NAM), Europe–Mediterranean Basin (EMB), and East Asia (EAS). A particular emphasis is placed on predictive anisotropy, a phenomenon referring to unequal predictability of surface wind components in different directions. Simulated predictability by comprehensive models is generally close to that found in observations in flat regions of NAM and EMB, but it is overestimated relative to observations in mountainous terrain. Simulated predictability in EAS shows different structures. In particular, there are regions in EAS where predictability simulated by RCMs is lower than that in observations. Overestimation of predictability by comprehensive models tends to occur in regions of low predictability in observations and can be attributed to small-scale physical processes not resolved by comprehensive models. An idealized mathematical model is used to characterize the predictability of wind components. It is found that the signal strength along the direction of minimum predictability is the dominant control on the strength of predictive anisotropy. The biases in the model representation of the statistical relationship between free-tropospheric circulation and surface winds are interpreted in terms of inadequate simulation of small-scale processes in regional and global models, and the primary cause of predictive anisotropy is attributed to such small-scale processes.

scholarly journals A Methodology for Assembling Future Weather Files Including Heatwaves for Building Thermal Simulations from the European Coordinated Regional Downscaling Experiment (EURO-CORDEX) Climate Data

Energies ◽  
2020 ◽  
Vol 13 (13) ◽  
pp. 3424 ◽  
Author(s):  
Anaïs Machard ◽  
Christian Inard ◽  
Jean-Marie Alessandrini ◽  
Charles Pelé ◽  
Jacques Ribéron
Keyword(s):  
Climate Models ◽  
Regional Climate ◽  
Climate Data ◽  
Data Accessibility ◽  
Climate Conditions ◽  
Building Simulations ◽  
Regional Downscaling ◽  
Using Data ◽  
Thermal Simulations ◽  
The Impact

With increasing mean and extreme temperatures due to climate change, it becomes necessary to use—not only future typical conditions—but future heatwaves in building thermal simulations as well. Future typical weather files are widespread, but few researchers have put together methodologies to reproduce future extreme conditions. Furthermore, climate uncertainties need to be considered and it is often difficult due to the lack of data accessibility. In this article, we propose a methodology to re-assemble future weather files—ready-to-use for building simulations—using data from the European Coordinated Regional Downscaling Experiment (EURO-CORDEX) dynamically downscaled regional climate multi-year projections. It is the first time that this database is used to assemble weather files for building simulations because of its recent availability. Two types of future weather files are produced: typical weather years (TWY) and heatwave events (HWE). Combined together, they can be used to fully assess building resilience to overheating in future climate conditions. A case study building in Paris is modelled to compare the impact of the different weather files on the indoor operative temperature of the building. The results confirm that it is better to use multiple types of future weather files, climate models, and or scenarios to fully grasp climate projection uncertainties.

Regional Climate Scenarios for use in Nordic Water Resources Studies

2003 ◽  
Vol 34 (5) ◽  
pp. 399-412 ◽  
Author(s):  
M. Rummukainen ◽  
J. Räisänen ◽  
D. Bjørge ◽  
J.H. Christensen ◽  
O.B. Christensen ◽  
...  
Keyword(s):  
Water Resources ◽  
Climate Models ◽  
Global Climate ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Climate Projections ◽  
Climate Scenarios ◽  
Soil Frost ◽  
Nordic Region ◽  
Regional Climate Projections

According to global climate projections, a substantial global climate change will occur during the next decades, under the assumption of continuous anthropogenic climate forcing. Global models, although fundamental in simulating the response of the climate system to anthropogenic forcing are typically geographically too coarse to well represent many regional or local features. In the Nordic region, climate studies are conducted in each of the Nordic countries to prepare regional climate projections with more detail than in global ones. Results so far indicate larger temperature changes in the Nordic region than in the global mean, regional increases and decreases in net precipitation, longer growing season, shorter snow season etc. These in turn affect runoff, snowpack, groundwater, soil frost and moisture, and thus hydropower production potential, flooding risks etc. Regional climate models do not yet fully incorporate hydrology. Water resources studies are carried out off-line using hydrological models. This requires archived meteorological output from climate models. This paper discusses Nordic regional climate scenarios for use in regional water resources studies. Potential end-users of water resources scenarios are the hydropower industry, dam safety instances and planners of other lasting infrastructure exposed to precipitation, river flows and flooding.

scholarly journals Cool season precipitation projections for California and the Western United States in NA-CORDEX models

2021 ◽  
Author(s):  
Kelly Mahoney ◽  
James D. Scott ◽  
Michael Alexander ◽  
Rachel McCrary ◽  
Mimi Hughes ◽  
...  
Keyword(s):  
United States ◽  
Climate Models ◽  
Snow Water Equivalent ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Western United States ◽  
Monthly Precipitation ◽  
Wet Season ◽  
Cool Season ◽  
Projected Change

AbstractUnderstanding future precipitation changes is critical for water supply and flood risk applications in the western United States. The North American COordinated Regional Downscaling EXperiment (NA-CORDEX) matrix of global and regional climate models at multiple resolutions (~ 50-km and 25-km grid spacings) is used to evaluate mean monthly precipitation, extreme daily precipitation, and snow water equivalent (SWE) over the western United States, with a sub-regional focus on California. Results indicate significant model spread in mean monthly precipitation in several key water-sensitive areas in both historical and future projections, but suggest model agreement on increasing daily extreme precipitation magnitudes, decreasing seasonal snowpack, and a shortening of the wet season in California in particular. While the beginning and end of the California cool season are projected to dry according to most models, the core of the cool season (December, January, February) shows an overall wetter projected change pattern. Daily cool-season precipitation extremes generally increase for most models, particularly in California in the mid-winter months. Finally, a marked projected decrease in future seasonal SWE is found across all models, accompanied by earlier dates of maximum seasonal SWE, and thus a shortening of the period of snow cover as well. Results are discussed in the context of how the diverse model membership and variable resolutions offered by the NA-CORDEX ensemble can be best leveraged by stakeholders faced with future water planning challenges.

scholarly journals Projecting Health Impacts of Future Temperature: A Comparison of Quantile-Mapping Bias-Correction Methods

2021 ◽  
Vol 18 (4) ◽  
pp. 1992
Author(s):  
Weijia Qian ◽  
Howard H. Chang
Keyword(s):  
Bias Correction ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Warm Season ◽  
Climate Science ◽  
Regional Climate Models ◽  
Health Impact ◽  
Quantile Mapping ◽  
Ed Visits

Health impact assessments of future environmental exposures are routinely conducted to quantify population burdens associated with the changing climate. It is well-recognized that simulations from climate models need to be bias-corrected against observations to estimate future exposures. Quantile mapping (QM) is a technique that has gained popularity in climate science because of its focus on bias-correcting the entire exposure distribution. Even though improved bias-correction at the extreme tails of exposure may be particularly important for estimating health burdens, the application of QM in health impact projection has been limited. In this paper we describe and apply five QM methods to estimate excess emergency department (ED) visits due to projected changes in warm-season minimum temperature in Atlanta, USA. We utilized temperature projections from an ensemble of regional climate models in the North American-Coordinated Regional Climate Downscaling Experiment (NA-CORDEX). Across QM methods, we estimated consistent increase in ED visits across climate model ensemble under RCP 8.5 during the period 2050 to 2099. We found that QM methods can significantly reduce between-model variation in health impact projections (50–70% decreases in between-model standard deviation). Particularly, the quantile delta mapping approach had the largest reduction and is recommended also because of its ability to preserve model-projected absolute temporal changes in quantiles.

scholarly journals Regional Climate Change Competitiveness—Modelling Approach

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3704
Author(s):  
Agnieszka Karman ◽  
Andrzej Miszczuk ◽  
Urszula Bronisz
Keyword(s):  
Climate Change ◽  
Regional Climate ◽  
Regional Climate Change ◽  
Measurement Scale ◽  
Practical Application ◽  
Adaptation To Climate Change ◽  
Regional Competitiveness ◽  
The Face ◽  
Competitiveness Index ◽  
Modelling Approach

The article deals with the competitiveness of regions in the face of climate change. The aim was to present the concept of measuring the Regional Climate Change Competitiveness Index. We used a comparative and logical analysis of the concept of regional competitiveness and heuristic conceptual methods to construct the index and measurement scale. The structure of the index includes six broad sub-indexes: Basic, Natural, Efficiency, Innovation, Sectoral, Social, and 89 indicators. A practical application of the model was presented for the Mazowieckie province in Poland. This allowed the region’s performance in the context of climate change to be presented, and regional weaknesses in the process of adaptation to climate change to be identified. The conclusions of the research confirm the possibility of applying the Regional Climate Change Competitiveness Index in the economic analysis and strategic planning. The presented model constitutes one of the earliest tools for the evaluation of climate change competitiveness at a regional level.

scholarly journals Observations and Simulations of Meteorological Conditions over Arctic Thick Sea Ice in Late Winter during the Transarktika 2019 Expedition

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 174
Author(s):  
Günther Heinemann ◽  
Sascha Willmes ◽  
Lukas Schefczyk ◽  
Alexander Makshtas ◽  
Vasilii Kustov ◽  
...  
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Climate Model ◽  
Regional Climate ◽  
Open Water ◽  
The Arctic ◽  
Late Winter ◽  
Good Representation ◽  
Hourly Temperature ◽  
Ice Model

The parameterization of ocean/sea-ice/atmosphere interaction processes is a challenge for regional climate models (RCMs) of the Arctic, particularly for wintertime conditions, when small fractions of thin ice or open water cause strong modifications of the boundary layer. Thus, the treatment of sea ice and sub-grid flux parameterizations in RCMs is of crucial importance. However, verification data sets over sea ice for wintertime conditions are rare. In the present paper, data of the ship-based experiment Transarktika 2019 during the end of the Arctic winter for thick one-year ice conditions are presented. The data are used for the verification of the regional climate model COSMO-CLM (CCLM). In addition, Moderate Resolution Imaging Spectroradiometer (MODIS) data are used for the comparison of ice surface temperature (IST) simulations of the CCLM sea ice model. CCLM is used in a forecast mode (nested in ERA5) for the Norwegian and Barents Seas with 5 km resolution and is run with different configurations of the sea ice model and sub-grid flux parameterizations. The use of a new set of parameterizations yields improved results for the comparisons with in-situ data. Comparisons with MODIS IST allow for a verification over large areas and show also a good performance of CCLM. The comparison with twice-daily radiosonde ascents during Transarktika 2019, hourly microwave water vapor measurements of first 5 km in the atmosphere and hourly temperature profiler data show a very good representation of the temperature, humidity and wind structure of the whole troposphere for CCLM.

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