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In 2022, intense heat waves occur all around the world. In this study, we project these heat waves into the future with futuristic projection of hourly varying spatially distributed anthropogenic heat for three megacities—Delhi, London, and Tokyo. Different future climate forcing (CMIP5 and CMIP6) was also compared. We found that if similar heat waves occur in the future, they may be 0.8 to 1.5 °C hotter than the past events, on average. Urbanization in Delhi may severely worsen the heat wave, while projected decrease in energy usage in London and Tokyo may make the heat waves less severe. For the concerned heat wave events, urbanization effect was also found to be stronger in nighttime than daytime and exhibits large spatial heterogeneity and dependence on background climate forcing. Difference between CMIP5 and CMIP6 was significant but was much less than the difference between CMIP5/CMIP6 and the present.

KHANH, D. N., VARQUEZ, A. C., & KANDA, M. (2024). MULTI-MEGACITY INVESTIGATION OF HEAT WAVE EVENTS UNDER VARIOUS CLIMATE CHANGE AND URBANIZATION SCENARIOS. Journal of JSCE12(2), 23-16120.
 
https://doi.org/10.2208/journalofjsce.23-16120
Chicago 

Historical land cover data is crucial for understanding urbanization dynamics, climate modeling, and monitoring water resources. Following recent advancements in deep learning for processing Landsat archive data, prior studies have released high-resolution historical land cover maps on a global scale. However, these works often present prediction results limited to specific periods of coverage, which hinders their utility in conducting time series analysis across different urban agglomerations. To address this issue, we propose deep-learning models for land cover classification from Landsat images at a 30-meter spatial resolution. Our models are specifically designed for urban areas and are trained to be compatible with the sensors used in the Landsat series from 1972 to the present. Experimental results demonstrate that our models are highly effective in predicting land cover maps in new cities, particularly in built-up land and water regions. Our research provides pretrained models for land cover classification, facilitating future studies in related fields.

CHINCHUTHAKUN, W., WINDERL, D., VARQUEZ, A. C., YAMASHITA, Y., & KANDA, M. (2024). ANNUAL PAST-PRESENT LAND COVER CLASSIFICATION FROM LANDSAT USING DEEP LEARNING FOR URBAN AGGLOMERATIONS. Journal of JSCE, 12(2), 23-16151.

https://doi.org/10.2208/journalofjsce.23-16151

Cities warm up due to two main factors: global climate change and urbanization-induced warming (so-called, urban heat island effect). In the projection of future climate, coarse-resolution global climate models are not suitable for looking into the heterogeneous urban surface and their changes. On the other hand, regional climate models, which are capable of looking into cities in detail, have never been used to investigate the global urban climate. Here we show that urbanization significantly increases exposure to extreme warming for megacity residents. We reflect urbanization between the 2010s and the 2050s into our model by considering the spatiotemporal change in urban surface (buildings and anthropogenic heat emissions) induced by urban population and economic growth. We found that in the 2050s, under the worst-case scenario, 78 percent of megacity residents will be exposed to 2.5°Cwarming, much higher than the projection of 65 percent when urban warming is left out. Our results highlight the importance of accounting for local urbanization in future global urban climate projection.

Reference: D.N. Khanh, A.C.G. Varquez and M. Kanda, Impact of urbanization on exposure to extreme warming in megacities, Heliyon, 9, e15511, doi: https://doi.org/10.1016/j.heliyon.2023.e15511.

Abstract

Plausible urban growth projections aid in the understanding and treatment of multidisciplinary issues faced in society. In this work, we investigated the possible effects of train stations on urban growth by comparing urban projections from a cellular-automata-based land use change model, named SLEUTH, with versions (i.e. SLEUTsH and SLEUTsHGA introduced in this study) that can consider railway-induced urban growth and those (i.e. SLEUTH and SLEUTHGA) that do not. It was found that the influence of the railway stations on urban growth varied with time and according to each city. In general, railway stations induced urbanization in their immediate surroundings. However, edge growth, which is growth at the urban boundaries was slow in the first five years of the future prediction. As demonstrated by the higher urban growth rates simulated for the first few years in the SLEUTsH cases than the SLEUTH cases, the presence of railway stations will lead to more rapid urbanization in the 2040s. Mainly relying on publicly available GIS datasets, this work demonstrates the potential for modeling railway-induced urban growth on a global scale. The findings can be further confirmed with other cellular-automata models using a similar methodology.

Reference: Varquez, A. C., Dong, S., Hanaoka, S., & Kanda, M. (2023). Evaluating future railway-induced urban growth of twelve cities using multiple SLEUTH models with open-source geospatial inputs. Sustainable Cities and Society, 104442. (https://www.sciencedirect.com/science/article/pii/S2210670723000537)

(This work is written in Japanese)

There is growing concern about the health risks posed by global warming and the heat island effect. In order to properly assess health risks, it is important to evaluate them in terms of thermal comfort. This study evaluated the long-term trend of the Universal Thermal Climate Index (UTCI) in Japan in summer from 1980 to 2020, and the relationship between UTCI and the number of heat stroke patients. Regarding the long-term trend of UTCI, increasing trends were detected at 109 out of 140 AMeDAS sites. Thermal comfort had worsen since the rise in air temperatures, MRT, and decreasing wind speeds. Regarding the relationship between UTCI and the number of heat stroke cases, we found that the UTCI threshold at which the number of heat stroke cases drastically increase differs across cities geographically and lower in northern cities than southern cities.

Hiroki, R., Khanh, D. N., Varquez, A. C., & Kanda, M. (2022). Analysis of Summer Thermal Comfort in Japan from 1980 TO 2020 Using Utci. Journal of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering), 78(2), I_79-I_84.

https://doi.org/10.2208/jscejhe.78.2_I_79

Flood risks associated with changes in land use and climate are a common concern, especially in relation to their potential effects on many cities around the world. Jakarta is a typical urbanized Asian city in Indonesia where flooding presents a consistent challenge. This study aimed to quantify the effects of land use and climate change using a flood inundation model to analyze future urban growth and climate change scenarios. The projected rainfall data of RCP2.6-SSP1 and RCP8.5-SSP3, based on the WRF simulation, were used as inputs for rainfall-runoff and flood inundation simulations in Jakarta. In addition, RCP2.6 and RCP8.5, without urban development scenarios, were investigated to determine the effects of urbanization in Jakarta. The results showed that rainfall intensity, peak discharge, and flood inundation generally increased in the high RCP and SSP future scenarios. Significantly, the RCP2.6-SSP1 scenario showed a higher peak discharge value than RCP8.5, owing to the combination of land-use change and increased rainfall. We conclude that the effects of urban development on atmospheric and runoff processes should be considered in climate change studies in urban areas.

Bambang Adhi Priyambodoho, Shuichi Kure, Nurul Fajar Januriyadi, Mohammad Farid, Alvin Christopher Galang Varquez, Manabu Kanda, and So Kazama, “Effects of Urban Development on Regional Climate Change and Flood Inundation in Jakarta, Indonesia,” J. Disaster Res., Vol.17, No.4, pp. 516-525, 2022.

Simulation of seven sea-breeze days (SBD) during dry season in tropical megacity of Jakarta was carried out using WRF with detailed urban representation. Model simulations were evaluated using satellite derived cloud line and high-temporal-resolution meteorological data obtained from observation campaign in 2017 and 2018. Result shows that WRF with detailed urban representation was able to simulate sea-breeze features and the associative boundary layer development. In the early stage of sea-breeze, model convergence line associated with sea-breeze front were matched against cloud line derived from satellite imagery. WRF tend to produce earlier sea-breeze occurrence due to overestimation of shortwave radiation and underestimation of latent heat flux. In general, simulated wind speed, temperature and relative humidity shows good agreement with observed values. Model also able to well simulate sea-breeze features, including lower boundary layer over Jakarta associated with thermal induced boundary layer (TIBL). Sea-breeze TIBL is influenced by coastal form of Jakarta and might plays important factor in air quality over the city.

 

 

 

I Dewa G. A. JUNNAEDHI, INAGAKI, A., VARQUEZ, A. C., & KANDA, M. (2021). Evaluation of multiple simulated sea-breeze events in tropical megacity using high-temporal-resolution observation data. Journal of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering), 77(2). https://doi.org/10.2208/jscejhe.77.2_i_1309

Numerical weather prediction models are progressively used to downscale future climate in cities at increasing spatial resolutions. Boundary conditions representing rapidly growing urban areas are imperative to more plausible future predictions. In this work, 1-km global anthropogenic heat emission (AHE) datasets of the present and future are constructed. To improve present AHE maps, 30 arc-second VIIRS satellite imagery outputs such as nighttime lights and night-fires were incorporated along with the LandScanTM population dataset. A futuristic scenario of AHE was also developed while considering pathways of radiative forcing (i.e. representative concentration pathways), pathways of social conditions (i.e. shared socio-economic pathways), a 1-km future urbanization probability map, and a model to estimate changes in population distribution. The new dataset highlights two distinct features; (1) a more spatially-heterogeneous representation of AHE is captured compared with other recent datasets, and (2) consideration of future urban sprawls and climate change in futuristic AHE maps. Significant increases in projected AHE for multiple cities under a worst-case scenario strengthen the need for further assessment of futuristic AHE.

Reference: Varquez, A.C.G., Kiyomoto, S., Khanh, D.N. et al. Global 1-km present and future hourly anthropogenic heat flux. Sci Data 8, 64 (2021). https://doi.org/10.1038/s41597-021-00850-w

Urbanization is an essential, yet underrepresented, parameter when investigating futuristic climate change of cities. The change in 2 m  air temperature in August between the 2006–2015 period and the 2046–2055 period for 33 megacities and 10 emerging megacities under RCP8.5 emission forcing and SSP3 was projected with the consideration of both global climate change (using pseudo-global warming method) and local urbanization (using global urban sprawling map, distributed urban morphological parameters, and hourly anthropogenic heat emission dataset). In newly urbanized area, the urbanization effect will be significant, accounting for (13.5 ± 5.9) %  of the total temperature change. In existing urban areas, the effect will vary depending on the current degree of urbanization. When viewed over a regional scale, the effect will be rather insignificant. It was observed in some cities that urbanization effect originating from urban area was advected by the wind to non-urban area located kilometers downwind.

Do, N.K., Varquez, A.C.G., Kanda, M. Future Climate Projection of Megacities considering Urbanization Scenarios. Journal of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering), 76(2), I_103-I_108, 2020.

Heat-risk evaluations are needed by societies for adapting to and mitigating the social/health impacts attributed to climate change and urbanization. Meanwhile, big data and numerical models are advancing.

In this study, we propose an integrated approach to utilize both big data and existing models for estimat-ing heat-related risk. By combining products of a 3D-City irradiance model and Google big data services, a geospatial framework for mapping heat-related risks(Hazard×Exposure×Vulnerability) was devel-oped .Hazard and exposure(individual HR factor) were estimated using thresholds of wetbulb globe tem-perature(WBGT) and mobility from frequented locations to nearest station exits; Vulnerability(HR proba-bility factor) was estimated using popular times of frequented locations. Through this framework, multiple perspectives for understanding heat risks may be observed at various districts. For example, ATMs were found to have high heat risks mainly because of its high HR probability factor.

Seki, H., Varquez, A.C.G., Ashie, Y., Nakayoshi, M., Kanda, M. Evaluation of Mobility-induced Heat Risk using Numerical Weather Simulation and Quasi-real-time Congestion Data, 土木学会論文集B1(水工学), 72(2), I_283-I_288, 2020

Increasing population in urban areas drives urban cover expansion and spatial growth. Developing urban growth models enables better understanding and planning of sustainable urban areas. The SLEUTH model is an urban growth simulation model which uses the concept of cellular automata to predict land cover change using six spatial inputs of historical data (slope, land use, exclusion, urban, transportation, and hill-shade). This study investigates the potential of SLEUTH to capture railway-induced urban growth by testing methods that can consider railways as input to the model, namely (1) combining the exclusion layer with a station map; (2) creating a new input layer representing stations in addition to the default six inputs. Districts in Tsukuba, Japan and Gurugram, India which historically showed evidence of urban growth by railway construction are investigated. Results reveal that both proposed methods can capture railway impact on urban growth, while the former algorithm under the right settings may perform better than the latter at finer resolutions. Coarser resolution representation (300-m grid-spacing) eventually reduces the differences in accuracy among the default SLEUTH model and the proposed algorithms.

Varquez, A.C.G.; Dong, S.; Hanaoka, S.; Kanda, M. Improvement of an Urban Growth Model for Railway-Induced Urban Expansion. Sustainability 2020, 12, 6801.

Urban dwellers are at risk of heat-related mortality in the onset of climate change. In this study, future changes in heat-related mortality of elderly citizens were estimated while considering the combined effects of spatially-varying megacity’s population growth, urbanization, and climate change. The target area is the Jakarta metropolitan area of Indonesia, a rapidly developing tropical country. 1.2 × 1.2 km2 daily maximum temperatures were acquired from weather model outputs for the August months from 2006 to 2015 (present 2010s) and 2046 to 2055 (future 2050s considering pseudo-global warming of RCP2.6 and RCP8.5). The weather model considers population-induced spatial changes in urban morphology and anthropogenic heating distribution. Present and future heat-related mortality was mapped out based on the simulated daily maximum temperatures. The August total number of heat-related elderly deaths in Jakarta will drastically increase by 12~15 times in the 2050s compared to 2010s because of population aging and rising daytime temperatures under “compact city” and “business-as-usual” scenarios. Meanwhile, mitigating climate change (RCP 2.6) could reduce the August elderly mortality count by up to 17.34%. The downwind areas of the densest city core and the coastal areas of Jakarta should be avoided by elderly citizens during the daytime.

 

Varquez, A.C.G., Darmanto, N.S., Honda, Y. et al. Future increase in elderly heat-related mortality of a rapidly growing Asian megacity. Sci Rep 10, 9304 (2020). https://doi.org/10.1038/s41598-020-66288-z

In order to analyze the effects of urban warming, it is essential to estimate Urban Heat Island (UHI) and elucidate its mechanism. However, the method to estimate UHI, which has been studied by previous nu-merical simulation, is simplified by replacing land use before urbanization with vegetation not necessarily representing the background climate of the region. This leads to inaccurate UHI estimates

In this study, we construct a land use global database representing pre-urbanization for an improved numerical modeling of the UHI. This database makes it possible to compare urban meteorological condi-tions using current land use and those utilizing typical land use before urbanization for any city around the world. This study demonstrates the usage of the global database by comparing two simulation cases for 35 large cities and examining the tendency of UHI. Temperature rises are seen in both cities during the daytime and nighttime in many cities. The current work also hints the possible dependence of UHI on topography, building geometry, etc.

Narita, Y., Varquez, A.C.G., Nakayoshi, M., Kanda, M. Construction of land use database before urbanization for global urban climate analyses. Journal of Japan Society of Civil Engineers, Ser.B1(Hydraulic Engineering), Vol.75, No.2, I_1039-I_1044, 2019 (Japanese)

The urban heat island (UHI) is caused by the progress of urbanization, but is considered to be influenced by various factors that differ depending on the cities, such as the geography and the background climate. However, the comprehensive mechanism is not clear yet. In this study, we tried to clarify the influence of not only urbanization, but geography and background climate by comparing the heat island phenomena of multiple cities in the world using numerical simulation. The wind speed is the main contributor to the urban heat island intensity; the heat of the city is transferred more effectively to the surrounding area as the wind speed is stronger. The wind speed is considered to be a comprehensive indicator reflecting the effect of geography around the city, and the roughness of the buildings.

Asami, M., Nakayoshi, M., Varquez, A.C.G., Kanda, M. Mechanism of the urban heat island considering geography and background climate. Journal of Japan Society of Civil Engineers, Ser.B1(Hydraulic Engineering), Vol.75, No.2, I_37-I_42, 2019 (Japanese)

As urban population is forecast to exceed 60% of the world’s population by 2050, urban growth can be expected. However, research on spatial projections of urban growth at a global scale are limited. We constructed a framework to project global urban growth based on the SLEUTH urban growth model and a database with a resolution of 30 arc-seconds containing urban growth probabilities from 2020 to 2050. Using the historical distribution of the global population from LandScanTM as a proxy for urban land cover, the SLEUTH model was calibrated for the period from 2000 to 2013. This model simulates urban growth using two layers of 50 arc-minutes grids encompassing global urban regions. While varying growth rates are observed in each urban area, the global urban cover is forecast to reach 1.7 × 106 km2 by 2050, which is approximately 1.4 times that of the year 2012. A global urban growth database is essential for future environmental planning and assessments, as well as numerical investigations of future urban climates.

Zhou, Y., Varquez, A.C.G., Kanda, M.: High-resolution global urban growth projection based on multiple applications of the SLEUTH urban growth model, Scientific Data, Vol 6, 34, 2019 

The effects of urbanization on the future atmospheric environments of cities worldwide remain uncertain in the context of climate change. We introduce a general method for modeling the effects of climate change and urbanization that can be applied to any city and apply the model to Greater Jakarta megacity. Global climate change scenarios (RCP2.6 and RCP8.5) were coupled with distributed urbanization scenarios (compact and business-as-usual (BaU), based on projections of future urban morphology and anthropogenic heating) in a mesoscale weather model. Despite the predominant influence of global effects, the urban effects of individual grids were spatially varied. The highest temperature increase caused by RCP8.5&BaU scenario was detected in the northwestern outskirts of Jakarta. Meanwhile, the projected temperature was one-third lower in the RCP2.6&Compact scenario. Overall, this study offers a general method for projecting future urban climates, not only for Jakarta but also for other megacities in developing countries.

Darmanto, N.S., Varquez, A.C.G, Kanda, M.: Future urban climate projection in a tropical megacity based on global climate change and local urbanization scenarios, Urban Climate, Vol. 29, 100482, 2019 

Air temperature trends (1960–2009) based on stations in cities, minus those based on global surface temperature datasets, are defined herein as urban heat island (UHI) trends. Urban climate was examined globally by comparing UHI trends with indices of geophysical factors, including background climate, latitude, and diurnal temperature range (DTR) and indices of artificial factors, including anthropogenic heat emission (AHE) and population indices. Surprisingly, a better relationship was found between UHI trends and DTR—an integrated geophysical index representing thermal inertia—than with the indices of artificial factors. Thus, while an increase in sensible heat (mechanism 1) triggers UHI formation, this study infers that large thermal inertia (mechanism 2) contributes significantly on UHI. The correlation of UHI trends with other indices can be explained by both mechanisms.

Varquez, A.C.G., Kanda, M.: Global urban climatology: a meta-analysis of air temperature trends (1960–2009), Nature Partner Journal Climate and Atmospheric Science. Vol 1, 31, 2018

In Asian megacities, not only climate change but also heat island phenomena are expected to pose air temperature increase. Therefore, effective adaptation measures to alleviate health damage caused by temperature increase are becoming more crucial. The objective of this study is to evaluate the effect of air conditioner on health damages using disability-adjusted life year(DALY)and considering an adverse effect from temperature increase accompanied by exhaust heating from outdoor units and uncertainty of the effect caused by inter-annual variability in temperature in Jakarta, Indonesia. Health damages to be assessed were sleep disturbance and fatigue. By increasing the usage rate of air conditioners, it was estimated that the DALY reduction per person per month in August of the average temperature year is 2.48 × 10-4 years for sleep disturbance, 1.43 × 10-5 years for fatigue, and totally 2.62 × 10-4 years. It corresponded with 29.8% reduction from the present situation. The effect of interannual variability in temperature was not large, which was 7.94 × 10-5 years at most. Air conditioner will be one of effective adaptations throughout the year considering small monthly variability in temperature and the residents’thermal perception.

Kuwayama, T., Yamaguchi, K., Okada, K., Kikegawa, Y., Kanda, M., Varquez, A.C.G., Darmanto, N.S., Darmanto, P.S., Ihara, T.: エアコンによる睡眠困難および疲労の生涯調整生存年(DALY)の軽減効果-インドネシア・ジャカルタにおける評価, Journal of Life Cycle Assessment Japan, Vol 15(1), pp. 2-9, 2019

The contribution of anthropogenic heat (AH) to the energy balance is widely known. However, further investigation of actual AH emitted in cities to their actual atmospheric environment is still limited. Furthermore, localization of studies limits a more robust understanding of the impacts of AH. In this study, a realistic spatial and temporal distribution of modern-day AH was used as surface boundary input into a weather model. With monthly-representative typical diurnal climatic pattern from 2006 to 2015 as lateral boundary, weather simulation of atmospheric environment of 15 large Asian cities included in the world’s top 30 largest cities declared by the United Nations was conducted. Results suggest that the effect of AH per location is largely influenced by the background climate. An empirical equation useful for urban planners was developed to approximate the amount of temperature increase for any location of a given AH and background monthly temperature.

Varquez, A.C.G., Kawano, N., Kanda, M., Nakayoshi, M.: Numerical Investigation of Anthropogenic Heat Emission Impacts on Large Asian Cities. Journal of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering), Vol. 74, No. 5, I_1177-I_1182, 2018

Global anthropogenic heat flux (AHF) with high spatial resolution is needed to deepen understanding of climate in cities. Existing datasets require improvements in the spatial estimation of AHF. Specifically, AHF point sources of industrial facilities, power plants, or oil refineries were not detected. In this study, we improved the spatial estimation of AHF globally by estimating the emissions of point sources using a coupling of short-wavelength infrared data measured by satellite (VIIRS-Nightfire) with conventional top-down approach methodology. Using VIIRS-Nightfire, we have validated the location of point sources and partitioned the bulk estimates of energy consumption in Japan. Most of the detected AHF from point sources were coming from either blast furnaces or thermal power plants.

Kiyomoto, S., Varquez, A.G.C., Kanda, M.: Anthropogenic Heat Flux Distribution With Point Sources for Global Urban Climatology, Journal of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering), Vol. 74, No. 5, I_1171-I_1176, 2018 (Japanese)

Recently, temperature in urban areas continue to rise as an effect of climate change and urbanization. Asian megacities are projected to expand rapidly resulting to serious in the future atmospheric environment. Thus, detailed analysis of urban meteorology for Asian megacities is needed to prescribe optimum coun-termeasure for these warming. A building-resolving large eddy simulation (LES) offline coupled with an energy balance model is conducted for a highly urbanized district in central Jakarta on typical daytime hours. Six cases were considered; two cases which utilized present urban scenario and four cases represent different urban configurations in 2050. The present case was used for validation by comparison with a moving observation of wet bulb temperature (WBGT). Meteorological inputs of the other present case and four future cases were acquired from a downscaling model. The future configurations were based on representative concentration pathways (RCP) and shared socio-economic pathways (SSP). Using the standard new effective temperature (SET*), thermal comfort in urban area in Jakarta was calculated and analyzed. Construction of dense high-rise buildings can reduce SET* (thermal comfort) due to increased shading throughout the district during daytime. Near-surface winds and temperatures were affected by the projected changes in morphology. For example, homogeneous high-rise buildings (case 3 and 4) prevented cooler downdrafts thereby maintaining high potential temperature within the street canyons.

居石貴史,Yucel, M., 足永靖信,稲垣厚至,仲吉信人,Varquez A.C.G.,Darmanto N.S.,神田学:全球・都市の将来シナリオを考慮した都市街区の温熱環境予測.土木学会論文集B1(水工学) 74(4): I_259-I_264, 2018 (Japanese)

A systematic method to project the future distribution of population in megacities is introduced. Two general steps were discussed: (1) estimation of urban sprawl by an urban growth model, SLEUTH; (2) estimation of population distribution by a logistic model with variable empirical coefficients. Predicting the annual change from 2014 to 2050, Jakarta megacity was used as a benchmark urban agglomeration. The key inputs are historical land cover and geographic information, transportation networks, high-spatial resolution population density, and country-level projection of population as defined by various shared socio-economic pathways (SSP). Coefficients were modified in SLEUTH to predict urban sprawling (and auxiliary probability map) compatible with a suitable SSP faced by the encompassing country. Utilizing the predicted annual probability of urbanization and the key inputs into a discrete logistic model with empirical coefficients fitted to minimize the difference of total predicted population with that provided by SSP, population distribution of the target urban agglomeration, Jakarta, was obtained.

Varquez, A.C.G., Takakuwa, S., Kanda, M. and Xin, Z.: Future population distribution of an urban agglomeration given climate change scenarios. Journal of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering) Vol 62, Ⅰ_223-228, 2018

This study developed a top-down method for estimating global anthropogenic heat emission (AHE), with a high spatial resolution of 30 arc-seconds and temporal resolution of 1 h. Annual average AHE was derived from human metabolic heating and primary energy consumption, which was further divided into three components based on consumer sector. The first and second components were heat loss and heat emissions from industrial sectors equally distributed throughout the country and populated areas, respectively. The third component comprised the sum of emissions from commercial, residential, and transportation sectors (CRT). Bulk AHE from the CRT was proportionally distributed using a global population dataset, with a radiance-calibrated nighttime lights adjustment. An empirical function to estimate monthly fluctuations of AHE based on gridded monthly temperatures was derived from various Japanese and American city measurements. Finally, an AHE database with a global coverage was constructed for the year 2013. Comparisons between our proposed AHE and other existing datasets revealed that the problem of overestimation of AHE intensity in previous top-down models was mitigated by the separation of energy consumption sectors; furthermore, the problem of AHE underestimation at central urban areas was solved by the nighttime lights adjustment. A strong agreement in the monthly profiles of AHE between our database and other bottom-up datasets further proved the validity of the current methodology. Investigations of AHE for the 29 largest urban agglomerations globally highlighted that the share of heat emissions from CRT sectors to the total AHE at the city level was 40–95%; whereas that of metabolic heating varied with the city’s level of development by a range of 2–60%. A negative correlation between gross domestic product (GDP) and the share of metabolic heating to a city’s total AHE was found. Globally, peak AHE values were found to occur between December and February, while the lowest values were found around June to August. The northern mid-latitudes contributed most to the global AHE.

Dong, Y., Varquez, A.C.G., Kanda, M. Global anthropogenic heat flux database with high spatial resolution. Atmospheric Environment. 150: 276-294. 2017

Despite increasing utilization and accuracy of models to predict the future climate and hydrology at higher resolutions, urban areas are still underrepresented. A method to determining future distribution of urban parameters in accordance with the global climate and socio-ecoonomic pathways of the future is proposed. An urban growth model was used to project the expansion of urban areas in 2050 of Jakarta. From shared socio-economic pathways (SSP), total population in the future was acquired. Using historical population distribution data, spatial distribution of population was projected until the year 2050. From empirical relationships acquired from population with nighttime lights adjustment, actual urban parameters, and GDP, futuristic urban parameters were calculated. Finally, the calculated future distribution of urban parameters was used in downscaling the future climate of Jakarta using the pseudo-global warming method.

Varquez, A.C.G., Darmanto, N.S., Kawano, N., Takakuwa, S., Kanda, M. and Xin, Z.: Representative Urban Growing Scenarios for Future Climate Models, Journal of Japan Society of Civil Engineers, Ser. B1 (Hydraulic Engineering), Vol. 73, No. 4, I_103-I_108 2017

Approaches to understanding urban atmospheric phenomena in cities include mesoscale models coupled with urban canopy models (UCMs). To improve the accuracy of these models, urban morphological parameters of higher spatial resolution are necessary. In this paper, we introduce an approach to derive 1-km scale urban parameters from globally available satellite images of Landsat 8, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Global Multi-resolution Terrain Elevation Data 2010 (GMTED2010), and nighttime light (NL) images from the Defense Meteorological Satellite Program Operational Linescan System (DMSP-OLS) for use in numerical weather models. Empirical equations derived from linear fittings were used to calculate urban geometric parameter plane area index from satellite images, which were then compared with values derived from real plane area index. To calculate urban geometric parameters average building height, an artificial neural network fitting was conducted. From the basic urban geometric parameters, other necessary urban parameters were derived. After validating the method, a weather simulation was conducted using the derived parameters for Jakarta, Indonesia. Results showed that urban parameters made from global datasets could improve the performance of the single-layer urban canopy model; and these estimated parameters can be used as a substitute when actual building information are lacking.

Darmanto, N.S., Varquez, A.C.G., Kanda, M., 2017. Urban roughness parameters estimation from globally available datasets for mesoscale modeling in megacities, Urban Climate Vol 21, 243–261. 2017

    Recent studies have proven the need for realistic urban representation in weather models. However, cities modeled using distributed urban parameters with updated urban parameterization are still few and limited to highly developed countries. Furthermore, real building datasets used to estimate the urban parameters are unavailable or lacking in other cities. This study was conducted to address both issues by expanding the advance weather model methodology to another megacity and utilizing global datasets to readily estimate a distribution of urban and other surface parameters. Sensitivity of the models to either real or global-estimated urban parameters was conducted; and the urban effect to a synoptic circulation over Istanbul was investigated. The simulation results for a typical summer day over Istanbul suggest that global datasets can be used as alternative to real building data for estimating distributed urban parameters.

    Yucel, M., Varquez, A.C.G., Darmanto, N.S. and Kanda, M.: Improvements of Urban Representation in Weather Models Using Global Datasets, Journal of Japan Society of Civil Engineers, Ser. B1, 72, 4, I_91-I_96, 2016

    Weather models coupled with urban parameterizations require robust and realistic urban parameter inputs such as actual building distribution. Acquiring real building parameters often require huge amount of time and money. In this study, we introduce a simplified but precise approximation of urban parameters through a readily-available, high-resolution global dataset. Regression equations were derived from the spatial relationship of global 1-km population dataset adjusted by nightlight distribution to real urban parameters in Japan and Istanbul, Turkey. These equations can readily estimate urban parameters globally. Derived global urban parameters were incorporated into a weather model to investigate urban heat island in neighboring megacities in South and Southeast Asia. UHI phenomena of 5 mega cities depended a great deal on location and climate zone of each city.

    河野なつ美,董玥, Yucel, M., Varquez, A.C.G.,神田学: グローバル都市気象学-都市温暖化の汎用解析手法の提案,土木学会論文集B1(水工学),Vol.72,4,I_97-I_102,2016 (Japanese)

    Global urban climatology (GUC) is proposed as a subfield of urban climatology. The main focus of GUC is uniform understanding of urban climates across all cities, globally. By utilizing globally applicable methodologies to quantify and compare urban heat islands of cities with diverse backgrounds, including their geography, climate, socio-demography, and other factors, a universal understanding of the mechanisms underlying the formation of the phenomenon can be established. The implementation of GUC involves the use of globally acquired historical observation networks, gridded meteorological parameters from climate models, global geographic information system datasets, the construction of a distributed urban parameter database, and the development of techniques necessary to model the urban climate. Here, the GUC concept, the pathways through which GUC assessments can be undertaken, and current implementations are discussed together with some examples of its application.

    Varquez, A.C.G.. Global Urban Climatology. J Japan Soc Hydrol and Water Resour 29(5): pp. 313 – 325. 2016

    We consider the effects of detailed urban roughness parameters on a sea-breeze simulation. An urban roughness database, constructed using a new aerodynamic parametrization derived from large-eddy simulations, was incorporated as a surface boundary condition in the advanced Weather Research and Forecasting model. The zero-plane displacement and aerodynamic roughness length at several densely built-up urban grids were three times larger than conventional values due to the consideration of building-height variability. A comparison between simulations from the modified model and its default version, which uses uniform roughness parameters within a conventional method, was conducted for a 2-month period during summer. Results showed a significant improvement in the simulation of surface wind speed but not with temperature. From the 2-month study period, a day with an evident sea-breeze penetration was selected and simulated at higher temporal resolution. Sea-breeze penetration weakened and was more delayed over urbanized areas. The slow sea-breeze penetration also lessened heat advection downwind allowing stronger turbulent mixing and a deeper boundary layer above urban areas. Horizontal wind-speed reduction due to the increased urban surface drag reached heights of several hundreds of metres due to the strong convection.

    Varquez, A. C. G., Nakayoshi, M. and Kanda, M.: The Effects of Highly Detailed Urban Roughness Parameters on a Sea-Breeze Numerical Simulation, Boundary-Layer Meteorology. Springer, 154(3), pp. 449–469, 2015

    Numerical weather prediction models have been improved to adequately represent the growing influence of urban areas to surrounding weather. Recently, updated LES-derived empirical equations on the aero-dynamic urban surface parameters displacement height d, and roughness length for momentum z0m, have been introduced. Using a high spatial resolution d, z0m, and anthropogenic heat emission distribution, dry case simulation was conducted using Weather Research and Forecasting Model with domains covering Tokyo, Nagoya, and Osaka. It was found that default WRF generally underestimate roughness. Results were also compared with actual observations of 2 m air temperature and surface wind speed, and were found to be well represented in the model when detailed parameters were used.

    Varquez, A.C.G., Nakayoshi, M., Makabe, T. and Kanda, M.: WRF Application of High-Resolution Parameters on Some Major Cities in Japan, Journal of Japan Society of Civil Engineers, Ser.B1(Hydraulic Engineering), Vol.70, No.4, I_175-I_180, 2014

    Numerical weather prediction models for urban weather require various urban parameters such as urban geometry and anthropogenic heat emission. Preparing databases of these urban parameters is essential for better reproducibility of urban weather simulation.
    In this paper, a database of urban geometric parameters for the whole Japan is created using a detailed building GIS. This database includes average, maximum, and standard deviation of building heights, plane and frontal area indices, roughness length for momentum, displacement height, and sky view factor. Furthermore, to expand this database to areas where detailed building GIS is not well prepared, methods of estimating the surface parameters are proposed. These methods require only a global digital elevation models and aerial imagery, which are now open to public inspection and easy to obtain. The results are compared with values derived from high-resolution building heights data.

    真壁拓也,仲吉信人,Varquez, A.C.G.,神田学:気象解析のための全日本都市幾何データベースの構築と世界への拡張可能性,土木学会論文集B1(水工学),Vol.70,No.4,I_331-I_336,2014 (Japanese)

    Urban localized heavy rainfall has become a serious issue especially during summer in the Tokyo metropolitan area. In order to analyze its relationship with urbanization, improved urban parameters were implemented into WRF together with high spatial resolution sea surface temperature (SST). For the simulation, the aerodynamic parameters such as roughness length and displacement height were prepared using a new feedback parameterization derived from large eddy simulations of real urban morphology. Applying the new urban parameterization realized a more accurate simulation of localized heavy rainfall. The stagnation of heat and water vapor around city, and also the delay of sea breeze caused by the drag of urban geometry, increased heavy rain in Tokyo.

    仲野久美子,仲吉信人,Varquez, A.C.G..,神田 学,足立幸穂,日下博幸:最新の都市パラメタリゼーションを導入した集中豪雨シュミレーション, 土木学会論文集B1(水工学),69巻,4号,I335-I360,2013 (Japanese)

    This paper analyzed the behavior of sea breeze (hereafter SB) penetration to urban area in Kanto. In order to analyze SB penetration, we proposed a new method for SB-front detection using very high-resolution-geostationary satellite images, or MTSAT-2 Rapid Scan, with 1 km-spatial and 5 min.-temporal resolution. From the images, the detailed behaviors of SB were successfully visualized. For the selected SB events, the penetrations to in-land from Tokyo bay and Sagami bay were discussed using the point data of AMeDAS and Atmospheric Environmental Regional Observation System (AEROS), and also a result from the meso-scale simulation, where the important urban effects were parameterized (e.g., actual aero-thermodynamic parameters, anthropogenic heat and vapor emission). Along Tokyo-Saitama line, SB stagnation occurred in every sea breeze event. The observed higher air temperature and convergence resulted in increased vertical mixing, leading to SB stagnation.

    仲吉信人,大久保洸平,Varquez A.C.G.,,神田 学,藤原忠誠:東京-練馬-埼玉ラインに見られる海風よどみ領域,土木学会論文集B1(水工学),69巻,4号,I741-I746,2013 (Japanese)

    This paper highlights the application of Water and Energy Transfer Processes (WEP) Model to two highly urbanized watersheds within Tokyo, Japan; Nomikawa and Meguro watershed. Major model improvements include refinement of time-resolution input rainfall data from 1 hr. to 10 min. intervals, and addition of subroutine to accommodate weir/side-weir effects and rainfall input. 2007 heavy rainfall data from Tokyo AMESH were used in Nomikawa watershed simulation. 2008 heavy rainfall data from Tokyo Metropolitan Construction Bureau were also used to simulate runoffs for Meguro watershed. The improved model was validated using comparative analysis of previous and new model using simulated river discharges and actual gauge measurements. Results show the new model simulates rapid runoffs well.

    Varquez A.C.G.., Kobayashi, K., Kanda, M., and Kinouchi., T.: Applicability of an Improved Water and Energy Transfer Processes Model on Rapid Rainfall-Runoff Events of Toyo Urban Watersheds, 水工学論文集, 第55巻, 25-30, (2011)

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