scholarly journals Global disparities in agricultural climate index-based insurance research

2022 ◽  
pp. 100394
Author(s):  
Adewuyi Ayodele Adeyinka ◽  
Jarrod Kath ◽  
Thong Nguyen-Huy ◽  
Shahbaz Mushtaq ◽  
Maxime Souvignet ◽  
...  
Keyword(s):  
Climate Index

scholarly journals Urban Heat Islands and Thermal Comfort: A Case Study of Zorrotzaurre Island in Bilbao

2021 ◽  
Vol 13 (11) ◽  
pp. 6106
Author(s):  
Irantzu Alvarez ◽  
Laura Quesada-Ganuza ◽  
Estibaliz Briz ◽  
Leire Garmendia
Keyword(s):  
Thermal Comfort ◽  
Heat Waves ◽  
Urban Environments ◽  
Urban Heat Islands ◽  
Extreme Weather Events ◽  
Climate Index ◽  
Physiological Equivalent Temperature ◽  
Heat Islands ◽  
The North ◽  
The Impact

This study assesses the impact of a heat wave on the thermal comfort of an unconstructed area: the North Zone of the Island of Zorrotzaurre (Bilbao, Spain). In this study, the impact of urban planning as proposed in the master plan on thermal comfort is modeled using the ENVI-met program. Likewise, the question of whether the urbanistic proposals are designed to create more resilient urban environments is analyzed in the face of increasingly frequent extreme weather events, especially heat waves. The study is centered on the analysis of temperature variables (air temperature and average radiant temperature) as well as wind speed and relative humidity. This was completed with the parameters of thermal comfort, the physiological equivalent temperature (PET) and the Universal Temperature Climate Index (UTCI) for the hours of the maximum and minimum daily temperatures. The results demonstrated the viability of analyzing thermal comfort through simulations with the ENVI-met program in order to analyze the behavior of urban spaces in various climate scenarios.

scholarly journals High-Resolution Modelling of Thermal Exposure during a Hot Spell: A Case Study Using PALM-4U in Prague, Czech Republic

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 175
Author(s):  
Jan Geletič ◽  
Michal Lehnert ◽  
Pavel Krč ◽  
Jaroslav Resler ◽  
Eric Scott Krayenhoff
Keyword(s):  
Czech Republic ◽  
Urban Areas ◽  
Heat Exposure ◽  
Thermal Exposure ◽  
Urban Environments ◽  
Cooling Effect ◽  
Spatiotemporal Variability ◽  
Climate Index ◽  
Street Canyons ◽  
General Terms

The modelling of thermal exposure in outdoor urban environments is a highly topical challenge in modern climate research. This paper presents the results derived from a new micrometeorological model that employs an integrated biometeorology module to model Universal Thermal Climate Index (UTCI). This is PALM-4U, which includes an integrated human body-shape parameterization, deployed herein for a pilot domain in Prague, Czech Republic. The results highlight the key role of radiation in the spatiotemporal variability of thermal exposure in moderate-climate urban areas during summer days in terms of the way in which this directly affects thermal comfort through radiant temperature and indirectly through the complexity of turbulence in street canyons. The model simulations suggest that the highest thermal exposure may be expected within street canyons near the irradiated north sides of east–west streets and near streets oriented north–south. Heat exposure in streets increases in proximity to buildings with reflective paints. The lowest heat exposure during the day may be anticipated in tree-shaded courtyards. The cooling effect of trees may range from 4 °C to 9 °C in UTCI, and the cooling effect of grass in comparison with artificial paved surfaces in open public places may be from 2 °C to 5 °C UTCI. In general terms, this study illustrates that the PALM modelling system provides a new perspective on the spatiotemporal differentiation of thermal exposure at the pedestrian level; it may therefore contribute to more climate-sensitive urban planning.

scholarly journals Parametric Design Structures in Low Rise Buildings in Relation to the Urban Context in UAE

2021 ◽  
Vol 13 (15) ◽  
pp. 8595
Author(s):  
Lindita Bande ◽  
Abeer Alshamsi ◽  
Anoud Alhefeiti ◽  
Sarah Alderei ◽  
Sebah Shaban ◽  
...  
Keyword(s):  
Heat Stress ◽  
Parametric Design ◽  
Residential Buildings ◽  
Cost Evaluation ◽  
Outdoor Thermal Comfort ◽  
Climate Index ◽  
Cooling Load ◽  
Design Structure ◽  
Al Ain ◽  
The City

The city of Al Ain (Abu Dhabi, UAE) has a mainly low rise residential buildings. Villas as part of a compound or separate units represent the majority of the residential areas in the city. Due to the harsh hot arid climate of Al Ain, the energy demand for the cooling load is quite high. Therefore, it is relevant finding new retrofit strategies that are efficient in reducing the cooling load of the villas. The aim of this study is to analyze one particular strategy (parametric shading structure) in terms of design, construction, cost, energy impact on the selected villa. The main data for this study is taken from the local sources. There are six steps followed in this analysis: case study analysis; climate analysis; parametric structure and PV panels; building energy consumption and outdoor thermal comfort; modelling, simulation, and validation; materials, construction, and cost evaluation. The model of the villa was validated for the full year 2020 based on the electricity bills obtained. After adding the parametric design structure, the reduction after shading is approximately 10%. Meanwhile the UTCI (Universal Thermal Climate Index) dropped from extreme heat stress to strong heat stress (average for the month of March and September). These findings are promising in the retrofit industry due to the advanced calculations used to optimize the parametric design structure.

scholarly journals Deep Learning Forecasts of Soil Moisture: Convolutional Neural Network and Gated Recurrent Unit Models Coupled with Satellite-Derived MODIS, Observations and Synoptic-Scale Climate Index Data

2021 ◽  
Vol 13 (4) ◽  
pp. 554
Author(s):  
A. A. Masrur Ahmed ◽  
Ravinesh C Deo ◽  
Nawin Raj ◽  
Afshin Ghahramani ◽  
Qi Feng ◽  
...  
Keyword(s):  
Neural Network ◽  
Soil Moisture ◽  
Deep Learning ◽  
Convolutional Neural Network ◽  
Climate Index ◽  
Climate Indices ◽  
High Temporal Resolution ◽  
Synoptic Scale ◽  
Time Step ◽  
Gated Recurrent Unit

Remotely sensed soil moisture forecasting through satellite-based sensors to estimate the future state of the underlying soils plays a critical role in planning and managing water resources and sustainable agricultural practices. In this paper, Deep Learning (DL) hybrid models (i.e., CEEMDAN-CNN-GRU) are designed for daily time-step surface soil moisture (SSM) forecasts, employing the gated recurrent unit (GRU), complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), and convolutional neural network (CNN). To establish the objective model’s viability for SSM forecasting at multi-step daily horizons, the hybrid CEEMDAN-CNN-GRU model is tested at 1st, 5th, 7th, 14th, 21st, and 30th day ahead period by assimilating a comprehensive pool of 52 predictor dataset obtained from three distinct data sources. Data comprise satellite-derived Global Land Data Assimilation System (GLDAS) repository a global, high-temporal resolution, unique terrestrial modelling system, and ground-based variables from Scientific Information Landowners (SILO) and synoptic-scale climate indices. The results demonstrate the forecasting capability of the hybrid CEEMDAN-CNN-GRU model with respect to the counterpart comparative models. This is supported by a relatively lower value of the mean absolute percentage and root mean square error. In terms of the statistical score metrics and infographics employed to test the final model’s utility, the proposed CEEMDAN-CNN-GRU models are considerably superior compared to a standalone and other hybrid method tested on independent SSM data developed through feature selection approaches. Thus, the proposed approach can be successfully implemented in hydrology and agriculture management.

scholarly journals Parametric Design and Comfort Optimization of Dynamic Shading Structures

2021 ◽  
Vol 13 (14) ◽  
pp. 7670
Author(s):  
Doris A. Chi ◽  
Edwin González M. ◽  
Renato Valdivia ◽  
Eduardo Gutiérrez J.
Keyword(s):  
Thermal Comfort ◽  
Social Dynamics ◽  
Parametric Design ◽  
Environmental Parameters ◽  
Outdoor Thermal Comfort ◽  
Climate Index ◽  
Parametric Modelling ◽  
The Social ◽  
Thermal Climate ◽  
Dynamic Time

This work implements parametric tools to optimize the environmental design of urban adaptive shadings through multiobjective evolutionary algorithms that look for solutions of dynamic (time-changing) structures used in open public spaces. The proposal is located in Malecon Cancun Tajamar in the southeast part of Mexico, and the main objective is to enhance the thermal comfort of users as well as to become part of the social dynamics of the place reinforcing identity through appropriation. The proposed workflow includes four steps: (1) geometric modelling by parametric modelling tools; (2) simulation of environmental parameters by using BPS tools; (3) shape optimization by using an evolutionary algorithm; and (4) environmental verification of the results. The Universal Thermal Climate Index (UTCI) was used to assess the outdoor thermal comfort derived from the dynamic shadings. The results showed a significant improvement in the thermal comfort with absolute UTCI differences of 3.9, 7.4, and 3.1 °C at 8, 12, and 16 h, respectively, during the summer; and absolute differences of 1.4, 3.5, and 2 °C at 8, 12, and 16 h, respectively, during the winter. The proposed workflow can help to guide the early design process of dynamic shadings by finding optimal solutions that enhance outdoor thermal comfort.

Research on The Construction of Hangzhou Power Economic Climate Index Model

2021 ◽  
Author(s):  
Bingyi Liu ◽  
Lin Xia ◽  
Li Han ◽  
Jianfei Shen ◽  
Erli Dan ◽  
...  
Keyword(s):  
Climate Index ◽  
Index Model ◽  
Economic Climate ◽  
Power Economic

Climate Index Weighting Schemes for NWS ESP-Based Seasonal Volume Forecasts

2004 ◽  
Vol 5 (6) ◽  
pp. 1076-1090 ◽  
Author(s):  
Kevin Werner ◽  
David Brandon ◽  
Martyn Clark ◽  
Subhrendu Gangopadhyay
Keyword(s):  
Nearest Neighbor ◽  
Southern Oscillation ◽  
Climate Index ◽  
Climate Information ◽  
Streamflow Prediction ◽  
Forecast System ◽  
Ensemble Forecasts ◽  
Weighting Schemes ◽  
Temperature And Precipitation ◽  
Spring Runoff

Abstract This study compares methods to incorporate climate information into the National Weather Service River Forecast System (NWSRFS). Three small-to-medium river subbasins following roughly along a longitude in the Colorado River basin with different El Niño–Southern Oscillation signals were chosen as test basins. Historical ensemble forecasts of the spring runoff for each basin were generated using modeled hydrologic states and historical precipitation and temperature observations using the Ensemble Streamflow Prediction (ESP) component of the NWSRFS. Two general methods for using a climate index (e.g., Niño-3.4) are presented. The first method, post-ESP, uses the climate index to weight ensemble members from ESP. Four different post-ESP weighting schemes are presented. The second method, preadjustment, uses the climate index to modify the temperature and precipitation ensembles used in ESP. Two preadjustment methods are presented. This study shows the distance-sensitive nearest-neighbor post-ESP to be superior to the other post-ESP weighting schemes. Further, for the basins studied, forecasts based on post-ESP techniques outperformed those based on preadjustment techniques.

CIS4: Climate Index of SMEs Survey Support System

2021 ◽  
Author(s):  
Linping Xu ◽  
James Ho ◽  
Zhiwei Zhang
Keyword(s):  
Support System ◽  
Climate Index

UTCI as the NWP model ALADIN (CHMI) output – first experiences

2021 ◽  
Vol 94 (2) ◽  
pp. 237-249
Author(s):  
Martin Novák
Keyword(s):  
Numerical Weather Prediction ◽  
Meteorological Data ◽  
Weather Prediction ◽  
Climate Index ◽  
Basic Information ◽  
Universal Thermal Climate Index ◽  
Numerical Weather ◽  
Weather Forecasters ◽  
Thermal Climate ◽  
Nwp Model

The article includes a summary of basic information about the Universal Thermal Climate Index (UTCI) calculation by the numerical weather prediction (NWP) model ALADIN of the Czech Hydrometeorological Institute (CHMI). Examples of operational outputs for weather forecasters in the CHMI are shown in the first part of this work. The second part includes results of a comparison of computed UTCI values by ALADIN for selected place with UTCI values computed from real measured meteorological data from the same place.

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