High Resolution Spatio-Temporal Variability of Heat Wave Impacts Quantified by Thermal Comfort Indices

2021 ◽  
Author(s):  
C NEETHU ◽  
KV Ramesh
Keyword(s):  
High Resolution ◽  
Thermal Comfort ◽  
Temporal Variability ◽  
Heat Waves ◽  
Wrf Model ◽  
Apparent Temperature ◽  
Average Intensity ◽  
Human Thermal Comfort ◽  
Spatio Temporal ◽  
Comfort Indices

Abstract Heat waves are increasing in frequency and also exhibit high spatial variability in its distribution over India. There are limited studies focused on the weather related human thermal comfort over India due to non-availability of high resolution (HR) climate data. Here we develop dynamically downscaled HR (4x4 km) daily climate information for the months of April to June during 2001-2016 using a regional climate model called Weather Research and Forecasting (WRF) Model, which are validated with station observations. The thermal comfort and its spatio-temporal variability over India are quantified in terms of indices like Excessive Heat Factor (EHF), Heat Index (HI), Humidex, Apparent Temperature (AT) and Wet Bulb Globe Temperature (WBGT). The daily surface air temperature and thermal comfort indices of HR WRF model simulations are in good agreement with station observations. The results show that there is an increasing trend in annual heat waves coverage (22240km2/year), annual frequency (0.07 days/year) and average intensity (0.04 °C/year) during 2001-2016. The distributions of indices have spatial and temporal variability. The days with severe discomfort are significantly increasing (99% significance level) over north India and it is quantified with increase of extreme category of indices at the rate of EHF (15.9%), HI (14.9%), Humidex (15.9%), AT (13.4%) and WBGT (13.8%). During heat waves, prolonged exposure or physical activity under sun will led to adverse health impacts and it is mostly observed over northwest and south eastern states. These findings stress the need for developing suitable mitigation strategies for a sustainable ecosystem

scholarly journals ERA5‐HEAT: A global gridded historical dataset of human thermal comfort indices from climate reanalysis

2020 ◽  
Author(s):  
Claudia Di Napoli ◽  
Christopher Barnard ◽  
Christel Prudhomme ◽  
Hannah L. Cloke ◽  
Florian Pappenberger
Keyword(s):  
Thermal Comfort ◽  
Human Thermal Comfort ◽  
Comfort Indices

scholarly journals Heat Waves and Human Well-Being in Madrid (Spain)

Atmosphere ◽  
2019 ◽  
Vol 10 (5) ◽  
pp. 288 ◽  
Author(s):  
Domingo Rasilla ◽  
Fernando Allende ◽  
Alberto Martilli ◽  
Felipe Fernández
Keyword(s):  
Air Quality ◽  
Thermal Comfort ◽  
Land Surface ◽  
Heat Waves ◽  
Well Being ◽  
Urban Heat Islands ◽  
Canopy Layer ◽  
Physiological Equivalent Temperature ◽  
Human Thermal Comfort ◽  
The City

Heat waves pose additional risks to urban spaces because of the additional heat provided by urban heat islands (UHIs) as well as poorer air quality. Our study focuses on the analysis of UHIs, human thermal comfort, and air quality for the city of Madrid, Spain during heat waves. Heat wave periods are defined using the long-term records from the urban station Madrid-Retiro. Two types of UHI were studied: the canopy layer UHI (CLUHI) was evaluated using air temperature time-series from five meteorological stations; the surface UHI (SUHI) was derived from land surface temperature (LST) images from MODIS (Moderate Resolution Imaging Spectroradiometer) products. To assess human thermal comfort, the Physiological Equivalent Temperature (PET) index was applied. Air quality was analyzed from the records of two air quality networks. More frequent and longer heat waves have been observed since 1980; the nocturnal CLUHI and both the diurnal and nocturnal SUHI experience an intensification, which have led to an increasing number of tropical nights. Conversely, thermal stress is extreme by day in the city due to the lack of cooling by winds. Finally, air quality during heat waves deteriorates because of the higher than normal amount of particles arriving from Northern Africa.

scholarly journals Ability of an Australian reanalysis dataset to characterise sub-daily precipitation

2020 ◽  
Vol 24 (6) ◽  
pp. 2951-2962
Author(s):  
Suwash Chandra Acharya ◽  
Rory Nathan ◽  
Quan J. Wang ◽  
Chun-Hsu Su ◽  
Nathan Eizenberg
Keyword(s):  
High Resolution ◽  
Spatial Scale ◽  
Temporal Variability ◽  
Daily Precipitation ◽  
Spatial Scales ◽  
Daily Rainfall ◽  
Spatial Displacement ◽  
Reanalysis Dataset ◽  
Spatio Temporal ◽  
Spatial Evaluation

Abstract. The high spatio-temporal variability of precipitation is often difficult to characterise due to limited measurements. The available low-resolution global reanalysis datasets inadequately represent the spatio-temporal variability of precipitation relevant to catchment hydrology. The Bureau of Meteorology Atmospheric high-resolution Regional Reanalysis for Australia (BARRA) provides a high-resolution atmospheric reanalysis dataset across the Australasian region. For hydrometeorological applications, however, it is essential to properly evaluate the sub-daily precipitation from this reanalysis. In this regard, this paper evaluates the sub-daily precipitation from BARRA for a period of 6 years (2010–2015) over Australia against point observations and blended radar products. We utilise a range of existing and bespoke metrics for evaluation at point and spatial scales. We examine bias in quantile estimates and spatial displacement of sub-daily rainfall at a point scale. At a spatial scale, we use the fractions skill score as a spatial evaluation metric. The results show that the performance of BARRA precipitation depends on spatial location, with poorer performance in tropical relative to temperate regions. A possible spatial displacement during large rainfall is also found at point locations. This displacement, evaluated by comparing the distribution of rainfall within a day, could be quantified by considering the neighbourhood grids. On spatial evaluation, hourly precipitation from BARRA is found to be skilful at a spatial scale of less than 100 km (150 km) for a threshold of 75th percentile (90th percentile) at most of the locations. The performance across all the metrics improves significantly at time resolutions higher than 3 h. Our evaluations illustrate that the BARRA precipitation, despite discernible spatial displacements, serves as a useful dataset for Australia, especially at sub-daily resolutions. Users of BARRA are recommended to properly account for possible spatio-temporal displacement errors, especially for applications where the spatial and temporal characteristics of rainfall are deemed very important.

Evaluation of a WRF model in forecasting extreme rainfall in the urban data-scarce coastal city of Alexandria, Egypt

2021 ◽  
Author(s):  
Adele Young ◽  
Biswa Bhattacharya ◽  
Emma Daniels ◽  
Chris Zevenbergen
Keyword(s):  
High Resolution ◽  
Boundary Conditions ◽  
Temporal Variability ◽  
Weather Prediction ◽  
Wrf Model ◽  
Extreme Rainfall ◽  
Small Scale ◽  
Lead Times ◽  
Spatial And Temporal Variability ◽  
Urban Drainage

<p>High-resolution precipitation models are essential to forecast urban pluvial floods. Global Numerical Weather Prediction Models (NWPs) are considered too coarse to accurately forecast flooding at the city scale. High-resolution radar nowcasting can be either unavailable or insufficient to forecast at the required lead-times.  Downscaling models are used to increase the resolution and extend forecast by several days when initialised with global NWPs. However, resolving weather processes at smaller spatial scales and sub-daily temporal resolutions has its challenges and does not necessarily result in more accurate forecast but instead only increase the computational requirements. Additionally, in ungauged regions, forecast verification is a challenge as in-situ measurements and radar estimates remain scarce or non-existent. This research evaluates the ability of a dynamically downscaled WRF model to capture the spatial and temporal variability of rainfall suitable for an urban drainage flood forecast model and evaluated against IMERG Global Precipitation Model (GPM) Satellite Precipitation Products (SPPs).<br> A WRF model was set-up with one-way nesting, three nested domains at horizontal grid resolutions 10km, 3.33km and 1km, a 1hourly temporal output, a spin-up time of 12 hours and evaluated at different lead times up to 48 hrs. The analysis was performed for three (3)  winter frontal systems during the period 2015-2019 in the highly urbanised coastal Mediterranean city of Alexandria in Egypt which experiences floods from extreme precipitation. The Global Forecast System (GFS), and European Centre for Medium Range (ECMWF) forecast were used as initial and lateral boundary conditions. <br>Initial results indicate the WRF models could capture extreme rainfall for all events. There is some agreement with the IMERG data and the model correctly forecasted a decrease in rainfall as the systems transition from coastal to inland areas. In general, GFS and ECMWF initialised WRF models overestimated rainfall estimates compared to IMERG data. Differences in GFS and ECMWF initialised models (multi-model approach) highlight the sensitivity of models to initial and boundary conditions and emphasises the need for post-processing and data assimilation when possible to generate accurate small-scale features. A study such as this provides knowledge for understanding, future applications and limitations of using Quantitative Precipitation Forecasts (QPFs) in urban drainage models. Additionally, the potential use of IMERG GPM to verify spatial and temporal variability of forecast in ungauged and data-scarce regions. Future analysis will evaluate the skill of ensembles precipitation systems in characterising forecast uncertainty in such applications. </p>

scholarly journals Índices de (des) conforto humano em um município de clima semiárido

2020 ◽  
Vol 13 (07) ◽  
pp. 3287
Author(s):  
Rebecca Luna Lucena ◽  
Jório Bezerra Cabral Júnior ◽  
Ercília Torres Steinke
Keyword(s):  
Thermal Comfort ◽  
Urban Climate ◽  
Heat Island ◽  
Temperature Index ◽  
Human Thermal Comfort ◽  
Data Loggers ◽  
De Se ◽  
Humidity Index ◽  
Semi Arid ◽  
Comfort Indices

O objetivo principal neste trabalho consistiu em analisar e comparar índices de (des) conforto térmico humano em um município de clima semiárido. Para isso foram adquiridos e utilizados equipamentos termo-higrômetros automáticos datalogger Akso AK170, sendo esses distribuídos espacialmente em onze pontos (dez em áreas urbanizadas e um em área rural), durante um período de 32 dias, em Caicó-RN. De posse dos dados horários de temperatura e umidade relativa do ar (maio/junho), realizaram-se análises estatísticas descritivas e aplicaram-se três índices de conforto humano, a saber: Índice de Desconforto (ID), índice de Temperatura Efetiva (TE), e o Índice de Temperatura e Umidade (ITU). Os resultados indicaram que o município de Caicó está propenso aos efeitos do processo de urbanização, registrando-se frequências de temperaturas mais elevadas nas áreas urbanizadas, especialmente nas de menor arborização e maior concentração de pavimentos urbanos. Em termos médios a maior parte da população de Caicó sente desconforto devido ao calor (ID), as temperaturas ficaram sempre acima do considerado calor moderado (TE) e de acordo com o ITU a classificação foi de extremamente desconfortável. Portanto, é imprescindível minimizar o os efeitos da ilha de calor no município a fim de se obter melhores índices de conforto térmico humano. Human (dis) comfort indices in a semi-arid municipality in Brazil A B S T R A C TThe main aim of this study was to analyse and compare the human thermal (dis)comfort indices in a Brazilian municipality with a semi-arid climate: Caicó, in the state of Rio Grande do Norte. Akso AK170 thermo-hygrometer data loggers were acquired for this purpose, which were distributed at eleven points in the study area – ten in built-up areas and one in a rural area – over a 32-day period covering the months of May to June. Having collected the time- and date-stamped temperature and relative humidity data, descriptive statistical analyses were conducted using three human comfort indices: discomfort index (DI), effective temperature index (ETI), and temperature-humidity index (THI). The results indicate that the municipality under study is affected by urbanization processes that propitiate higher temperatures in the built-up areas, especially where there are fewer trees and more of the roads are paved. On average, most of the population of Caicó feels discomfort because of the heat (ID), and the temperature always remains above the range rated as moderately hot (ETI). The municipal climate was classified as “extremely uncomfortable” by the THI. It is therefore of the utmost importance to minimize the effects of the heat island in the municipality to improve the human thermal comfort indices.Keywords: Urban climate. Caicó-RN. Human thermal comfort indices.

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