A computational method to assess the impact of urban climate on buildings using modeled climatic data

Quantitatively assessing the spatial divergence of the sensitivity of crop yield to climate change is of great significance for reducing the climate change risk to food production. We use socio-economic and climatic data from 1981 to 2015 to examine how climate variability led to variation in yield, as simulated by an economy–climate model (C-D-C). The sensitivity of crop yield to the impact of climate change refers to the change in yield caused by changing climatic factors under the condition of constant non-climatic factors. An ‘output elasticity of comprehensive climate factor (CCF)’ approach determines the sensitivity, using the yields per hectare for grain, rice, wheat and maize in China’s main grain-producing areas as a case study. The results show that the CCF has a negative trend at a rate of −0.84/(10a) in the North region, while a positive trend of 0.79/(10a) is observed for the South region. Climate change promotes the ensemble increase in yields, and the contribution of agricultural labor force and total mechanical power to yields are greater, indicating that the yield in major grain-producing areas mainly depends on labor resources and the level of mechanization. However, the sensitivities to climate change of different crop yields to climate change present obvious regional differences: the sensitivity to climate change of the yield per hectare for maize in the North region was stronger than that in the South region. Therefore, the increase in the yield per hectare for maize in the North region due to the positive impacts of climate change was greater than that in the South region. In contrast, the sensitivity to climate change of the yield per hectare for rice in the South region was stronger than that in the North region. Furthermore, the sensitivity to climate change of maize per hectare yield was stronger than that of rice and wheat in the North region, and that of rice was the highest of the three crop yields in the South region. Finally, the economy–climate sensitivity zones of different crops were determined by the output elasticity of the CCF to help adapt to climate change and prevent food production risks.

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Nature-based cooling potential: a multi-type green infrastructure evaluation in Toronto, Ontario, Canada

International Journal of Biometeorology ◽

10.1007/s00484-021-02100-5 ◽

2021 ◽

Author(s):

Vidya Anderson ◽

William A. Gough

Keyword(s):

Urban Agriculture ◽

Air Temperature ◽

Green Infrastructure ◽

Urban Climate ◽

Surface Air Temperature ◽

Green Roofs ◽

Near Surface ◽

Green Walls ◽

The Impact ◽

Agriculture Systems

AbstractThe application of green infrastructure presents an opportunity to mitigate rising temperatures using a multi-faceted ecosystems-based approach. A controlled field study in Toronto, Ontario, Canada, evaluates the impact of nature-based solutions on near surface air temperature regulation focusing on different applications of green infrastructure. A field campaign was undertaken over the course of two summers to measure the impact of green roofs, green walls, urban vegetation and forestry systems, and urban agriculture systems on near surface air temperature. This study demonstrates that multiple types of green infrastructure applications are beneficial in regulating near surface air temperature and are not limited to specific treatments. Widespread usage of green infrastructure could be a viable strategy to cool cities and improve urban climate.

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The Regional Snowfall Index

Bulletin of the American Meteorological Society ◽

10.1175/bams-d-13-00101.1 ◽

2014 ◽

Vol 95 (12) ◽

pp. 1835-1848 ◽

Cited By ~ 11

Author(s):

Michael F. Squires ◽

Jay H. Lawrimore ◽

Richard R. Heim ◽

David A. Robinson ◽

Mathieu R. Gerbush ◽

...

Keyword(s):

United States ◽

Data Center ◽

Historical Perspective ◽

The United States ◽

Climatic Data ◽

National Climatic Data Center ◽

Impact Scale ◽

Population Information ◽

Regional Index ◽

The Impact

This paper describes a new snowfall index that quantifies the impact of snowstorms within six climate regions in the United States. The regional snowfall index (RSI) is based on the spatial extent of snowfall accumulation, the amount of snowfall, and the juxtaposition of these elements with population. Including population information provides a measure of the societal susceptibility for each region. The RSI is an evolution of the Northeast snowfall impact scale (NESIS), which NOAA's National Climatic Data Center began producing operationally in 2006. While NESIS was developed for storms that had a major impact in the Northeast, it includes all snowfall during the lifetime of a storm across the United States and as such can be thought of as a quasi-national index that is calibrated to Northeast snowstorms. By contrast, the RSI is a regional index calibrated to specific regions using only the snow that falls within that region. This paper describes the methodology used to compute the RSI, which requires region-specific parameters and thresholds, and its application within six climate regions in the eastern two-thirds of the nation. The process used to select the region-specific parameters and thresholds is explained. The new index has been calculated for over 580 snowstorms that occurred between 1900 and 2013 providing a century-scale historical perspective for these snowstorms. The RSI is computed for category 1 or greater storms in near–real time, usually a day after the storm has ended.

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SMALLHOLDER FARMERS’ RESOURCE ALLOCATION DECISIONS IN A MAIZE-FARMING SYSTEM UNDER CLIMATE RISKS IN MALAWI

AGROFOR ◽

10.7251/agreng2101086m ◽

2021 ◽

Vol 6 (1) ◽

Author(s):

Ruth MAGRETA ◽

Henderson NG’ONG’OLA ◽

Julius MANGISONI ◽

Kennedy MACHILA ◽

Sika GBEGBELEGBE

Keyword(s):

Resource Allocation ◽

Smallholder Farmers ◽

Farming Systems ◽

The Body ◽

Research Station ◽

Climatic Data ◽

Climatic Risk ◽

The Impact ◽

Allocation Decisions ◽

Resource Allocation Decisions

Using household data from Lilongwe districts, along with crop phenology, agronomic management and climatic data from Chitedze Research Station, the Target-MOTAD and DSSAT-CSM models examined the resource allocation decisions of smallholder farmers in maize farming systems under climate risk in Malawi. Specific aims were to evaluate the ability of DSSAT to predict and collate DTM and non-DTM yields under climatic risk and to use a bio-economic procedure developed using DSSAT and Target-MOTAD to explore the impact of climatic risk on allocation of resources to DTM and non-DTM production. The paper argues that higher average yields observed from DTM varieties make it the most optimal maize production plan, in maximizing household incomes, food security, and minimizing deviations from the mean while meeting the set target incomes of farmers compared to non-DTM varieties. The multidisciplinary nature of this paper has contributed to the body of research by providing a powerful analytical procedure of modelling farmers’ resource allocation decisions in maize based farming systems in Malawi. This study necessitates the use of a combination of biophysical and economic procedures when evaluating promising lines prior to variety release in order to identify the high yielding variety that will continuously bring sustained profits to the farmers amidst climate change.

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First Evidence of Human's Influence on Climate of Prague and Brno

Geografie ◽

10.37040/geografie1994099010014 ◽

1994 ◽

Vol 99 (1) ◽

pp. 14-19

Author(s):

Jan Munzar

Keyword(s):

Air Quality ◽

Urban Environment ◽

Urban Climate ◽

Quality Deterioration ◽

New Knowledge ◽

The Creation ◽

The Impact

The paper brings some new knowledge on air quality deterioration as a part of urban environment in Prague and Brno in the end of the 18th and in the 19th centuries. The impact of man-induced processes on the creation of specific features of urban climate is documented.

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Innovative urban climate model PALM-4U as a support tool for municipal climate adaptation strategies.

10.5194/egusphere-egu21-12563 ◽

2021 ◽

Author(s):

Antonina Kriuger ◽

Alexander Reinbold ◽

Martina Schubert-Frisius ◽

Jörg Cortekar

Keyword(s):

Climate Change ◽

High Performance ◽

Climate Model ◽

Urban Climate ◽

Performance Model ◽

Practical Implementation ◽

Adaptation Measures ◽

Funding Program ◽

The Impact ◽

Comfort Indices

Cities are particularly vulnerable to climate change. At the same time, cities change slowly. Accordingly, preparatory measures to adapt to climate change have to be taken urgently. High-performance urban climate models with various applications can form the basis for prospective planning decisions, however, as of today no such model exists that can be easily applied outside of the scientific community. Therefore, the funding program Urban Climate Under Change [UC]2 aims to further develop the new urban climate model PALM-4U (Parallelized Large-Eddy Simulation Model for Urban Applications) into a practice-oriented and user-friendly product that meets the needs of municipalities and other practical users in addition to scientific research.Specifically, the high-performance model PALM-4U allows simulation of entire large cities comprising the area over 1.000 km2 with a grid size of down to few meters. One of our goals within the project ProPolis is to design and test the practical implementation of PALM-4U in standard and innovative application fields which include thermal comfort (indices like PT, PET, UTCI), cold air balance (source areas, reach and others), local wind comfort (indices derived from medium winds and gusts) as well as dispersion of pollutants.In close cooperation with our practice partners, we explore the potential of PALM-4U to support the urban planning processes in each specific application setting. Additionally, with development of the fit for purpose graphic user interface, manuals and trainings we aim to enable practitioners to apply the model for their individual planning questions and adaptation measures.In our presentation, we will show an application case of PALM-4U in a major German city. We will investigate the effect of a planned development area on the local climate and the impact of different climate change adaptation measures (such as extensive vs. intensive green roofs). The comparative simulations of the current state and planning scenarios with integrated green and blue infrastructure should provide arguments for the municipal decision making in consideration of climate change aspects in a densely built-up environment, e.g. urban heat stress.

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The impact of climate change and urban growth on urban climate and heat stress in a subtropical city

International Journal of Climatology ◽

10.1002/joc.5998 ◽

2019 ◽

Vol 39 (6) ◽

pp. 3013-3030 ◽

Cited By ~ 6

Author(s):

Sarah Chapman ◽

Marcus Thatcher ◽

Alvaro Salazar ◽

James E.M. Watson ◽

Clive A. McAlpine

Keyword(s):

Climate Change ◽

Heat Stress ◽

Urban Growth ◽

Urban Climate ◽

Impact Of Climate Change ◽

The Impact

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Computational Test Design for High-Speed Liquid Impact and Dispersal

ASME/JSME 2011 8th Thermal Engineering Joint Conference ◽

10.1115/ajtec2011-44422 ◽

2011 ◽

Author(s):

Alexander L. Brown ◽

Kurt E. Metzinger

Keyword(s):

High Speed ◽

Water Channel ◽

Computational Method ◽

Computational Fluid Mechanics ◽

Reacting Flow ◽

Validation Data ◽

Sled Test ◽

The Impact ◽

Scale Data ◽

Limited Scope

Transportation accidents frequently involve liquids dispersing in the atmosphere. An example is that of aircraft impacts, which often result in spreading fuel and a subsequent fire. Predicting the resulting environment is of interest for design, safety, and forensic applications. This environment is challenging for many reasons, one among them being the disparate time and length scales that must be resolved for an accurate physical representation of the problem. A recent computational method appropriate for this class of problems has been developed for modeling the impact and subsequent liquid spread. This involves coupling a structural dynamics code to a turbulent computational fluid mechanics reacting flow code. Because the environment intended to be simulated with this capability is difficult to instrument and costly to test, the existing validation data are of limited scope, relevance, and quality. A rocket sled test is being performed where a scoop moving through a water channel is being used to brake a pusher sled. We plan to instrument this test to provide appropriate scale data for validating the new modeling capability. The intent is to get high fidelity data on the break-up and evaporation of the water that is ejected from the channel as the sled is braking. These two elements are critical to fireball formation for this type of event involving fuel in the place of water. We demonstrate our capability in this paper by describing the pre-test predictions which are used to locate instrumentation for the actual test. We also present a sensitivity analysis to understand the implications of length scale assumptions on the prediction results.

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