Reliable representations of global urban extent remain limited, hindering scientific progress across a range of disciplines that study functionality of sustainable cities. We present an efficient and ...low-cost machine-learning approach for pixel-based image classification of built-up areas at a large geographic scale using Landsat data. Our methodology combines nighttime-lights data and Landsat 8 and overcomes the lack of extensive ground-reference data. We demonstrate the effectiveness of our methodology, which is implemented in Google Earth Engine, through the development of accurate 30m resolution maps that characterize built-up land cover in three geographically diverse countries: India, Mexico, and the US. Our approach highlights the usefulness of data fusion techniques for studying the built environment and is a first step towards the creation of an accurate global-scale map of urban land cover over time.
•An approach is proposed to map built-up land cover at a large geographical scale.•Our data fusion approach utilizes nighttime-lights data and Landsat imagery.•The approach overcomes the lack of extensive ground-reference data for urban research.•Hexagonal tessellation partition improves classification of heterogeneous land cover.•High quality maps of built-up LC are produced for 3 geographically diverse countries.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
We use a combination of a regional climate model (RCM) and a global climate model (GCM) to explore potential changes to the complex precipitation regime in the semi‐arid and arid state of Arizona in ...the American Southwest. The RCM output for the contemporary period (2000–2009) compares well with a gridded precipitation dataset with respect to seasonality, amount, intensity, and diurnal patterns. Output from the GCM forced by the continued buildup of greenhouse gases was dynamically downscaled by the RCM for the period 2090–2099. Results indicate an increase in winter precipitation of 1–2 mm day−1 in the mountainous areas of the state with somewhat smaller increases for the summer and fall seasons; negligible changes were projected for spring precipitation. Extreme precipitation is projected to increase across much of the state in winter (10–30 mm day−1) and to a lesser extent in spring. Our results indicate an increase in the 99th percentile of winter season precipitation. However, we note there is substantial seasonal dependency: statewide‐averaged winter season precipitation is projected to undergo greater frequency of wet than dry extreme events, whereas the statewide‐averaged summer, fall, and spring seasons, broadly demonstrate an equal likelihood of increased and decreased extreme precipitation. While the RCM captured the unusual observed night‐time maximum in summer rainfall in the centre of the state, our results do not indicate any change in the diurnal character or sub‐diurnal duration (6–18 hr) of precipitation over the next 100 years.
We use a combination of a regional climate model and a global climate model to characterize changes to the precipitation regime in the state of Arizona in the American Southwest. Our results indicate an increase in end of century winter precipitation of 1–2 mm day−1, an increase in the 99th percentile of precipitation with substantial seasonal dependency, and no changes in the diurnal character of precipitation over the next 100 years.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
The growing concerns about floods have highlighted the need for accurate and detailed precipitation data as extreme precipitation occurrences can lead to catastrophic floods, resulting in significant ...economic losses and casualties. Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM IMERG) is a commonly used high-resolution gridded precipitation dataset and is recognized as trustworthy alternative sources of precipitation data. The aim of this study is to comprehensively evaluate the performance of GPM IMERG Early (IMERG-E), Late (IMERG-L), and Final Run (IMERG-F) in precipitation estimation and their capability in detecting extreme rainfall indices over southwestern Iran during 2001–2020. The Asfezari gridded precipitation data, which are developed using a dense of ground-based observation, were utilized as the reference dataset. The findings indicate that IMERG-F performs reasonably well in capturing many extreme precipitation events (defined by various indices). All three products showed a better performance in capturing fixed and non-threshold precipitation indices across the study region. The findings also revealed that both IMERG-E and IMERG-L have problems in rainfall estimation over elevated areas showing values of overestimations. Examining the effect of land cover type on the accuracy of the precipitation products suggests that both IMERG-E and IMERG-L show large and highly unrealistic overestimations over inland water bodies and permanent wetlands. The results of the current study highlight the potential of IMERG-F as a valuable source of data for precipitation monitoring in the region.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Maricopa County, Arizona, anchor to the fastest growing megapolitan area in the United States, is located in a hot desert climate where extreme temperatures are associated with elevated risk of ...mortality. Continued urbanization in the region will impact atmospheric temperatures and, as a result, potentially affect human health. We aimed to quantify the number of excess deaths attributable to heat in Maricopa County based on three future urbanization and adaptation scenarios and multiple exposure variables. Two scenarios (low and high growth projections) represent the maximum possible uncertainty range associated with urbanization in central Arizona, and a third represents the adaptation of high-albedo cool roof technology. Using a Poisson regression model, we related temperature to mortality using data spanning 1983–2007. Regional climate model simulations based on 2050-projected urbanization scenarios for Maricopa County generated distributions of temperature change, and from these predicted changes future excess heat-related mortality was estimated. Subject to urbanization scenario and exposure variable utilized, projections of heat-related mortality ranged from a decrease of 46 deaths per year (−95%) to an increase of 339 deaths per year (+359%). Projections based on minimum temperature showed the greatest increase for all expansion and adaptation scenarios and were substantially higher than those for daily mean temperature. Projections based on maximum temperature were largely associated with declining mortality. Low-growth and adaptation scenarios led to the smallest increase in predicted heat-related mortality based on mean temperature projections. Use of only one exposure variable to project future heat-related deaths may therefore be misrepresentative in terms of direction of change and magnitude of effects. Because urbanization-induced impacts can vary across the diurnal cycle, projections of heat-related health outcomes that do not consider place-based, time-varying urban heat island effects are neglecting essential elements for policy relevant decision-making.
•Extreme heat is a public health hazard in metropolitan Maricopa County, Arizona.•Urbanization is a key driver of future regional temperature changes.•Projections of heat–health impacts for 2050 vary across urbanization scenarios.•The sign and magnitude of projections are also sensitive to exposure variable choice.•Consideration of urbanization effects is critical for heat–health policymaking.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
With the rapid spread of COVID-19 related cases globally, national governments took different lockdown approaches to limit the spread of the virus. Among them, the Government of India imposed a ...complete nationwide lockdown starting on March 25, 2020. This presented a unique opportunity to explore how a complete standstill in regular daily activities might impact the local environment. In this study, we have analyzed the change in the air quality levels stemming from the reduced anthropogenic activities in one of the most polluted cities in the world, the Delhi Metropolitan Region (DMR). We analyzed station-level changes in particulate matter, PM10 and PM2.5, across the DMR between April 2019 and 2020. The results of our study showed widespread reduction in the levels of both pollutants, with substantial spatial variations. The largest decreases in particulate matter were associated with industrial and commercial areas. Highest levels of PM10 and PM2.5 were observed near sunrise with little change in the time of maximum between 2019 and 2020. The results of our study highlight the role of anthropogenic activities on the air quality at the local level.
•There was substantial decline in the levels of PM10 (20 to 70%) and PM2.5 (15 to 90%) in air quality across the DMR.•The highest decline was observed over the downtown core area and the adjacent industrial areas in the east and west.•Areas experiencing greater decline are associated with greater proportion of commercial land uses and economic activity.•Overall, the decline in PM10 was more widespread than PM2.5.•The diurnal patterns of peak time for average monthly levels occurred at midnight for PM10 and early morning for PM2.5.•The time of maximum values did not change significantly between 2019 and 2020
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Abstract This study examines the temporal and spatial variability of near‐surface air temperature and the canopy layer urban heat island (UHI CL ) of Kuwait City. Observations collected at 12 ...locations across the country of Kuwait and for the period 2010–2022 are analysed on an hourly and 3‐hourly basis to provide monthly and diurnal insights of the city's UHI CL characteristics. Research on Kuwait's UHI CL was first conducted by Nasrallah et al. ( International Journal of Climatology , 10, 401–405). Results presented here have been afforded the benefit of additional stations and more extensive data compared with the earlier study. Mean positive UHI CL intensities, ranging from 1.1°C to 3.8°C at night, are observed consistently across all months, owing to the prevalence of clear skies from winter to summer. Negative UHI CL intensities, indicating a typical daytime urban cool island (UCI CL ), are most prominent on summer days, exhibiting a mean hourly magnitude range between 0.6°C and 2.6°C that extends into the early parts of the evening. Heat and cool island effects are maintained up to wind speeds approaching 10 m s −1 at the urban periphery. A coastal site near the city demonstrates strong influences of the Arabian Gulf temperatures and associated sea and land breeze effects on UHI CL development. The results can be used for comparison with other desert locales, in the evaluation of urban climate models, for urban planning policies and improving local weather forecasts. This study honours in memoriam Dr. Hassan Nasrallah, who produced the first UHI CL study in the Arab World.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
The diurnal cycle of tropical convection over the Indian region has been analysed in this study for the period of March to June from the thunderstorm reports of ground-based observatories throughout ...India during 2016–2020. The analyses indicate that during this period of the year, when the land progressively heats up diurnally, under conditions of deficient moisture, synoptic systems interact with the semi-permanent features of the atmosphere over the region to define areas of moisture and wind convergence, which in turn determine the frequency and diurnal cycle of thunderstorm activity. While the easterly and westerly waves are the major synoptic scale weather systems that affect the Indian region during March to May, the atmospheric changes are associated with the onset of the monsoon season in June. Amongst the semi-permanent features, the gradual intensification and migration of the shallow heat low to northwest India during May and June reinforce the western disturbances over this region, thereby intensifying the thunderstorm activity during the afternoon to evening hours over the western Himalayas and northwest Indian region. The role of the low-level anticyclones over the Arabian Sea and the Bay of Bengal is seen in the east–west-oriented moisture gradient across the Indian subcontinent which makes the east Indian subcontinent generally more prone to thunderstorm activity during this season. The east–west-oriented discontinuity line across north India is particularly intense during the morning hours along the foothills of the Himalayas. Its location directs moisture from the Bay of Bengal into the Himalayas causing early initiation of thunderstorm activity over the Himalayas. The discontinuity line moves southwards to the north Indian plains later in the day, although the western end becomes less marked. The north–south-oriented discontinuity line across the Indian subcontinent between the two anticyclones intensifies during the afternoon hours due to land heating and combines with the east–west wind discontinuity to become a T-shaped maximum convergence zone for thunderstorm activity during the afternoon hours over the Indian region, which intensifies as the months progress. With the onset of the southwest monsoon over the south peninsula and east Indian regions in June, the change in wind pattern from an easterly to a southwesterly flow regime over the south peninsula is reflected in an abrupt shift of the afternoon maximum of thunderstorm activity over the inland regions of the south peninsula to an early morning maximum over the southwest peninsular coast. Simultaneously, with the weakening of the anticyclone over the north Bay of Bengal and gradual strengthening of the southerly moisture flow into east and northeast India, there was in-phase increase in thunderstorm activity during the afternoon hours over the plains of east-central India, east India, and adjoining southern parts of northeast India during June. The diurnal pattern of tropical convection significantly affects human lives over the Indian subcontinent.
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DOBA, EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, IZUM, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UILJ, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
The goal of this study is to assess the performance of four widely-used satellite precipitation products in capturing extreme precipitation indices across Iran over the period 2001–2018; these ...products include GPM IMERG (Integrated Multi-Satellite Retrievals for Global Precipitation Measurement), TRMM 3B42 (Tropical Rainfall Measuring Mission), CHIRPS (Climate Hazards Center InfraRed Precipitation with Station data), and PERSIANN-CDR (Precipitation Estimation From Remotely Sensed Information Using Artificial Neural Networks-Climate Data Record). For this aim, a national gridded precipitation dataset was developed using a dense network of rain gauges as a reference dataset. The results suggest that the IMERG product outperforms the other three precipitation products in capturing extreme precipitation indices both temporally and spatially. TRMM 3B42 data show promising results in identifying many extreme indices, while the CHIRPS and PERSIANN-CDR products show less performance in accurately generating many of the extreme precipitation indices.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
We investigate trends in extreme precipitation in Iran for 1951–2007 using the recently released APHRODITE daily rainfall time series. We find that seven different indices of extreme precipitation ...all show an upward trend through the study period. The seven different precipitation indices include annual precipitation total, number of days above a certain threshold, maximum precipitation received over a certain period of time, maximum one-day precipitation, and number of days with precipitation above the 90th percentile. A principal components analysis reveals one eigenvector explaining much of the variance in the seven indices and reveals that this component exhibits a strong upward trend for the whole of Iran. On a regional level, we find that the upward trend in extreme precipitation has a strong southwest-to-northeast gradient across the country for all the indices. We repeated all the analyses for 42 stations across the country to compare with the results from the gridded data; trends in extreme rainfall generated from the station data compare favorably with the results from the APHRODITE daily rainfall time series thereby reinforcing the robustness of our conclusions.
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FZAB, GIS, IJS, IZUM, KILJ, NLZOH, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBMB, UL, UM, UPUK
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