Evaluation Of Adaptation Strategies Research Articles

Development of climate informed management scenarios for fisheries in the eastern Bering Sea

Abstract In recognition of the impact of climate change on marine ecosystems worldwide, integrated research teams have coupled climate change projections with social-ecological models to inform management and evaluate adaptation strategies for the fishing industry and fishing communities. A key step in this process is the selection of scenarios that enable improved adaptation strategies and decision-making through engagements with constituents with diverse interests in the future use of marine resources. This paper presents an approach to selecting and refining climate-informed social-ecological scenarios for groundfish and crab fisheries in the eastern Bering Sea. The approach involved: (a) initial model development to provide worked examples; (b) engagement with stakeholders to seek input on climate-related concerns, priorities, and adaptation options; and (c) establishment of pathways for uptake of climate-informed decision support information into existing management systems. This approach narrowed the range of candidate scenarios, identified pressing climate concerns of constituents, and clarified timelines for scheduling modeling projects to address these concerns. Separating evaluation of management strategies (research modeling) from proposed changes to Fishery Management Plans preserved opportunities for public debate of proposed changes through a well-established regulatory review process. Collectively, these outcomes help to advance the development of a regionally relevant climate-ready harvest policy.

Perception of Adaptation Strategies to Climate Variability in Machakos County, Kenya

The study was designed to assess climate variability trends on rainfall and temperature data between 1990 and 2020, analyse community perception to climate variability, evaluate adaptation strategies and their effectiveness and examined the challenges of adaptation to climate variability. Farmers were randomly selected and questionnaires administered, while focused group discussions were conducted to obtain farmer’s perceptions of climate variability. Rainfall and temperature data was statistically analysed using Mann Kendall test and Sen’s slope estimator (p<0.05. The study found out there was a significant variation in the amount of annual rainfall received of (p< 0.004) (S= -53) which showed a decreasing trend, while temperature showed a warming trend of (p>0.099) (S=29). Also, farmers perceived that climate variability events were real with (71.1%) and (68.0%) noticing a change in rainfall and temperature respectively over the same period. The study established that community perceptions on rainfall and temperature trends agreed with meteorological data on observed climatic trends. Planting of drought resistant crops was most popular with (89.8%) (n=255) agreeing, while (79.2%) said it was the most effective strategy. The study found that although some farmers have adopted some adaptation strategies, they were constrained with (82.4%) agreeing that age was a great challenge to adaptation and had a moderate negative correlation with adaptation of (0.097) with labour and (25.5%) saying it was not a challenge. The study recommends farmers use the study findings on rainfall and temperature trends and data recordings on local agricultural performances to enhance their ability to adapt. To researchers and academic community the study recommends the intensification of research on ecosystem-based adaptation and the use of the results in mainstreaming policy making, planning and implementation of climate related decisions. The results reveal important knowledge that if effectively applied will inform the county government in climate management decisions and reduce farmer’s vulnerability.

The application of a plant community model to evaluate adaptation strategies for alleviating climate change impacts on grassland productivity, biodiversity and forage quality

Grasslands are environments characterized by an elevated biodiversity in plant species, which dynamically evolves over time as a function of management practices, soil properties, and climate conditions. Climate change can locally affect grassland growth and floristic composition and, in turn, the quality and quantity of provided ecosystem services. We show how the use of the plant community model CoSMo allows to explicitly account for the dynamics of floristic composition as response to environmental variables. This, in turn, allows quantifying climate change impacts on grasslands growth and composition and evaluating alternative strategies to improve adaptation in the mid-term. As a case study, we focused on mountain areas in the northern Apennines (Italy), where temporary alfalfa (Medicago sativa L.)-dominated grasslands are sown for the production of Parmesan cheese. Five sites and four alternative climate scenarios (RCP4.5 and RCP8.5 projections as provided by the HadGEM2 and GISS general circulation models) were considered, to explore a wide range of agro-environmental conditions. Results showed that the observed dynamics of floristic composition and biomass accumulation were successfully simulated, with a mean absolute error lower than 10% for floristic composition and less than 1 t ha−1 for total biomass. Climate change impacts were globally negative, with a clear decrease of forage production as compared to the baseline (from -3.6% to -14.3% according to the climate scenario). The biodiversity of the plant community also declined (12.5% average decrease in the inverse Simpson index) due to the increase in alfalfa dominance. The latter, however, led to preserve the forage crude protein content (+0.9% on average). Guidelines for optimizing grassland productivity and forage protein under future climate were defined, mainly focused on reducing the alfalfa field duration, sowing grass-legume mixtures, and delaying the last cut of the season. These practices can be easily adopted under operational farming conditions to support the adaptation of temporary grasslands to climate change. According to our knowledge, this is one of the first study of climate change impact that uses a plant community model to explicitly considers phytocoenosis dynamics, biodiversity, and their effect on forage production (quantity and quality). Considering the role of grasslands as providers of key ecosystem services ‒ especially in marginal areas ‒ we believe that our modelling approach can support the identification of effective adaptation strategies to address future climate challenges.

Interactive effects of atmospheric CO2 concentration and water stress on the phenology and physiology of faba bean (Vicia faba L.)

Crop modelling is a critical tool for assessing the impact of climate change and for evaluating adaptation strategies to ensure the sustainability of agricultural systems. In addition to increased temperature and reduced precipitation, studying the effects of increased atmospheric CO2 concentration ([CO2]) and water stress on water efficiency of crops is highly relevant for identifying and evaluating impacts and new adaptation measures. We carried out 12 experiments with 4 faba bean cultivars under controlled conditions of [CO2], temperature and water supply. An increase of [CO2] from 430 to 650 ppm caused a 20% reduction in stomatal conductance under optimal irrigation supply but had almost zero effect under water stress conditions. Our study shows that the beneficial effect of a higher atmospheric [CO2] on faba bean growth is counteracted by water stress, with the beneficial effect only detected when proper water management is applied. Thus, stomatal conductance appeared to be more sensitive to water stress than to elevated [CO2], indicating that the beneficial effects of elevated [CO2] on faba bean are largely dependent on the plant water status. This is particularly relevant in Mediterranean agricultural systems, where water shortage associated with droughts will become more frequent, even in areas of irrigation. Although differences in the response between cultivars were observed in our study when the water status was intermediate between optimal and severe drought, no single genotype among those studied will be sufficient to improve or fully guarantee yield under conditions of increasing [CO2] and water shortage. Therefore, the introduction of irrigation and/or sowing date strategies currently represent the only adaptation measures. The gaps in knowledge of the response of faba bean to climate change, and the limited number of adaptation measures available highlight the need for continued research, with breeding of drought-tolerant and high-yielding faba bean genotypes as one of the most promising alternatives.

ORGANIZATIONAL AGILITY AND SURVIVING CRISIS SITUATIONS DURING THE COVID-19 PANDEMIC

This article aims to identify and evaluate adaptation strategies used by companies during crises, with a particular focus on the development of organizational agility. The article presents the results of a survey conducted in April and May of 2023. The sample consisted of 303 respondents. The conducted research showed that business conditions’ variability led companies to make quick decisions, increase flexibility, implement remote work, and decentralize responsibility. The analysis of the studies suggests that the pandemic might have accelerated companies’ transformation towards greater agility.

Crowdsourcing air temperature data for the evaluation of the urban microscale model PALM—A case study in central Europe

In summertime and during heat events the urban heat island can negatively impact human health in urban areas. In the context of climate change, climate adaptation receives more attention in urban planning. Microscale urban climate modelling can identify risk areas and evaluate adaptation strategies. Concurrently, evaluating the model results with observational data is essential. So far, model evaluation is mostly limited to short-term field campaigns or a small number of stations. This study uses novel crowdsourcing data from Netatmo citizen weather stations (CWS) to evaluate the urban microscale model PALM for a hot day (Tmax ≥ 30°C) in Bochum in western Germany with anticyclonic atmospheric conditions. Urban-rural air temperature differences are represented by the model. A quality control procedure is applied to the crowdsourced data prior to evaluation. The comparison between the model and the crowdsourced air temperature data reveals a good model performance with a high coefficient of determination (R2) of 0.86 to 0.88 and a root mean squared error (RMSE) around 2 K. Model accuracy shows a temporal pattern and night-time air temperatures during the night are underestimated by the model, likely due to unresolved cloud cover. The crowdsourced air temperature data proved valuable for model evaluation due to the high number of stations within urban areas. Nevertheless, weaknesses related to data quality such as radiation errors must be considered during model evaluation and only the information derived from multiple stations is suitable for model evaluation. The procedure presented here can easily be transferred to planning processes as the model and the crowdsourced air temperature data are freely available. This can contribute to making informed decisions for climate adaptation in urban areas.

Assessment of Climate Change Impact and Adaptation Strategies for Rainfed Maize (Zea mays L.)

The study was performed to assess the impact of climate change on spatiotemporal changes in rainfed maize yield. Climate projections data of MIROC-ESM-CHEM model from CMIP6 was used for future climatic scenarios in the maize growing areas of Dindigul and Perambalur districts of Tamil Nadu. The DSSAT model was used to simulate maize yield and evaluate adaptation strategies for base period (1991-2020), the mid (2040-2069) and end centuries (2070-2099) under SSP245 and SSP585 scenarios. The simulation finding shows that, in all scenarios maize yield declined in both Dindigul (7 to 9% and 11 to 12%) and Perambalur (6 to 9% and 11 to 13%) during mid and end centuries respectively from the base period (1991-2020). Following the adaptation strategies such as delayed sowing, the yield was increased in both Dindigul (5 to 6% and 4 to 5%) and Perambalur (4 to 5% and 5 to 6%) with respect to normal sowing date. The results of this study would help in developing adaptation strategies for minimizing the adverse effects of the projected climate in maize-growing districts of Tamil Nadu.

Physiological and Metabolic Adaptation to Heat Stress at Different Altitudes in Yaks.

Yaks have strong adaptability to extremely cold and hypoxic conditions but are susceptible to high ambient temperature when yaks are raised in low-altitude areas during the high-temperature season. Twenty-four adult male yaks with similar weights and ages were randomly divided into TN (Thermoneutral, altitude = 3464 m), LHS (Light heat stress, altitude = 1960 m), and MHS (Medium heat stress, altitude = 906 m) groups to evaluate adaptation strategies to HS. Non-targeted and targeted metabolomics were applied to investigate the effects of different extents of HS on yaks. LHS- and MHS-yaks showed higher rectal temperatures and respiratory rates than TN-yaks. MHS-yaks had higher levels of red blood cells (RBCs), hemoglobin (Hb), whole blood relative index of middle shear at a shear rate of 5 S-1 (WMS), whole blood relative index of high shear at a shear rate of 200 S-1 (WHS), Casson viscosity (CV), middle shear flow resistance at a shear rate of 5 S-1 (MSFR), and high shear flow resistance at a shear rate of 200 S-1 (HSFR) as compared to TN- and LHS-yaks. Differential metabolites and metabolic pathways, including fatty acid metabolism, lipid metabolism, glucose metabolism, and amino acid metabolism, were altered by HS. Metabolites in the glucose metabolism pathway in LHS- and MHS-yaks were lower than those in TN-yaks. However, LHS-yaks showed higher levels of metabolites in the HIF-1 signaling pathway compared to TN- and MHS-yaks. Most of the tricarboxylic acid cycle (TCA) intermediates and fatty acids were significantly decreased in MHS-yaks compared to the other two groups. As a whole, yaks raised at a low altitude (25.6 °C) suffered from severe HS, but they adapted to HS with vasodilatation for dissipating heat and the increased antioxidants and metabolite levels of energy substrates.

Artisanal fishers in small island developing states and their perception of environmental change: the case study of Mauritius.

The online version contains supplementary material available at 10.1007/s11160-022-09735-6.

An artificial neural network‐hydrodynamic coupled modeling approach to assess the impacts of floods under changing climate in the East Rapti Watershed, Nepal

AbstractRecurring floods have devastating consequences on the East Rapti Watershed (ERW), but effective mitigation/adaptation measures are lacking. This article aims at establishing a rainfall‐runoff (RR) relationship; estimating depth and extent of inundation under climate change scenarios; assessing impacts on the socio‐economy; and identifying and evaluating adaptation strategies in the ERW. Artificial Neural Network (ANN) was used to generate peak flows which were then entered into a hydraulic model to simulate inundation. Results were validated with field survey. The calibrated and validated RR and hydraulic models were fed with projected future climate (2021–2050) derived from multiple regional‐climate‐models to assess the changes in inundation. Results showed the peak discharge likely exceeds 10,500 m3/s at the ERW outlet in the extreme future flood scenario with corresponding inundation of 80 km2 and up to a depth of 11 m sweeping away over 1000 houses and 19 km2 of agricultural land in the critical areas. Constructing a 17 km long embankment in the critical areas along the right bank of the East Rapti River could reduce the flood spread by 35%, safeguarding 78% of the houses and saving 51% agricultural land compared with the scenarios without the embankment.

Evaluating area-specific adaptation strategies for rainfed maize under future climates of India

This study investigates the spatio-temporal changes in maize yield under projected climate and identified the potential adaptation measures to reduce the negative impact. Future climate data derived from 30 general circulation models were used to assess the impact of future climate on yield in 16 major maize growing districts of India. DSSAT model was used to simulate maize yield and evaluate adaptation strategies during mid (2040-69) and end-centuries (2070-99) under RCP 4.5 and 8.5. Genetic coefficients were calibrated and validated for each of the study locations. The projected climate indicated a substantial increase in mean seasonal maximum (0.9–6.0 °C) and minimum temperatures (1.1–6.1 °C) in the future (the range denotes the lowest and highest change during all the four future scenarios). Without adaptation strategies, climate change could reduce maize yield in the range of 16% (Tumkur) to 46% (Jalandhar) under RCP 4.5 and 21% (Tumkur) to 80% (Jalandhar) under RCP 8.5. Only at Dharwad, the yield could remain slightly higher or the same compared to the baseline period (1980–2009). Six adaptation strategies were evaluated (delayed sowing, increase in fertilizer dose, supplemental irrigation, and their combinations) in which a combination of those was found to be effective in majority of the districts. District-specific adaptation strategies were identified for each of the future scenarios. The findings of this study will enable in planning adaptation strategies to minimize the negative impact of projected climate in major maize growing districts of India.

Impact network analysis and the ina r package: Decision support for regional management interventions

Abstract The success of intervention projects for species management depends on both the effectiveness of management technologies and the geographical landscape of management adoption. Impact network analysis (INA) is a new framework for evaluating the likely level of success of regional species management before, during and after projects, for project implementers, policymakers and funders. INA evaluates the effects of management performance in a multilayer network analysis. The socioeconomic network represents manager communication about technologies and influence about technology adoption decisions in an agent‐based model. The linked biophysical network represents species dispersal, resulting in regional success or failure of species management. The specific objectives of this paper are to (a) introduce the INA framework and ina r package; (b) illustrate the identification of key nodes for smart surveillance strategies; (c) illustrate the application of the INA framework for evaluating the likely degree of success of a project in intervention ecology, before, during and after an intervention; and (d) illustrate the use of INA for evaluating adaptation strategies under global change scenarios with pulse and press stressors, introducing ‘adaptation functions’ to evaluate the management response required for sustainability and resilience. Examples of use of the ina package show key outcomes of analyses: identifying the limiting factors for effective regional management, pointing out when systems may be non‐responsive to the system components that are readily changed through management decisions, and identifying the additional adaptations that may be necessary for intervention success. The broader goals for the development of impact network analysis and the ina package are to provide a common framework that integrates across intervention ecology, to enhance opportunities for lessons learned across systems and scientific disciplines, to support the development of a community of practice, and to create a general platform to operationalize analysis of sustainability, resilience and economic viability in intervention ecology applications.

Future Hydrology of the Cryospheric Driven Lake Como Catchment in Italy under Climate Change Scenarios

We present an assessment of climate change impact on the hydrology of the Lago di Como lake catchment of Italy. On one side, the lake provides water for irrigation of the Po valley during summer, and on the other side its regulation is crucial to prevent flood risk, especially in fall and winter. The dynamics of lake Como are linked to the complex cryospheric hydrology of its Alpine contributing catchment, which is in turn expected to change radically under prospective global warming. The Poli-Hydro model is used here to simulate the cryospheric processes affecting the hydrology of this high-altitude catchment. We demonstrated the model’s accuracy against historical hydrological observations, available during 2002–2018. We then used four Representative Concentration Pathways scenarios, provided by three Global Circulation Models under the AR6 of IPCC, to project potential climate change until 2100. We thereby derived daily series of rainfall and temperature, to be used as inputs for hydrological simulations. The climate projections here highlight a substantial increase in temperature at the end of the century, between +0.61° and +5.96°, which would lead to a decrease in the total ice volume in the catchment, by −50% to −77%. Moreover, there would be a decrease in the contribution of snow melt to the annual lake inflow, and an increase in ice melt under the worst-case scenarios. Overall, the annual Lake inflows would increase during autumn and winter and would decrease in summer. Our study may provide a tool to help policy makers to henceforth evaluate adaptation strategies in the area.

Cost and Benefit Analysis of Climate Change Adaptation Strategies in Coastal Areas at Risk

Cardona, F.S.; Ferreira, J.C., and Lopes, A.M., 2020. Cost and benefit analysis of climate change adaptation strategies in coastal areas at risk. In: Malvárez, G. and Navas, F. (eds.), Global Coastal Issues of 2020. Journal of Coastal Research, Special Issue No. 95, pp. 764-768. Coconut Creek (Florida), ISSN 0749-0208.This paper addresses a cost analysis and evaluation of the benefits associated with different climate change adaptation strategies in coastal areas, considering high risk scenarios. For that, a cost analysis of adaptation strategies was carried out over a period of 50 years for Furadouro Beach, Ovar Portugal, a low-lying coastal area with high coastal erosion and frequent overtopping. The results show that cumulative costs of adaptation measures in the combination of defense and accommodation strategies are € 276M, € 164M in accommodation, € 112M in defense and € 75M in retreat. These results are an example of the importance of evaluating adaptation strategies in high-risk areas and show the usefulness of the approach taken as a support to decision making for processes that involve urban management and territorial planning of coastal zones vulnerable to the coastal erosion, wave overtopping and coastal flooding.

Adaptation to risks related to ecotourism: development at Boabeng in the Bono East Region, Ghana

Purpose: The purpose of this study was to evaluate adaptation strategies developed by residents in order to minimize the risks caused by the ecotourism project at Boabeng in the Bono East region of Ghana. Research methodology: Data collection instruments included schedules and interview guides. A sample of 404 heads of households was randomly selected for the administration of schedules, whilst 12 respondents each were purposively selected for focus group discussions and indepth interviews. Household data were analyzed using percentages, frequencies and mean responses. Findings: Findings indicate that households adapted to ecotourism risks by patrolling and farming off the feeding range of the monkeys. Limitations: Household heads and opinion leaders were made to assess the ecotourism project in terms of how they cope with it. These community leaders, some of whom were direct beneficiaries of the projects, may not give the right information and this may affect the results of the study. Respondents were however; assured of confidentiality of their responses so as to enable them give the right information on their adaptation to risks related to the ecotourism project in the community. Contribution: This study recommends the intensification of livelihood diversification schemes in the study area. Keywords: Destination, Limitations, Livelihood diversification, Local community, Local households, Monkey sanctuary, Vulnerable households

Predicting the Effect of Climate Change on Potato Production in Fereidunshahr (Isfahan, Central Iran) and Evaluation of Adaptation Strategies (Adopting Cultivars and Planting Dates)

Predicting the Effect of Climate Change on Potato Production in Fereidunshahr (Isfahan, Central Iran) and Evaluation of Adaptation Strategies (Adopting Cultivars and Planting Dates)

An economic evaluation of adaptation pathways in coastal mega cities: An illustration for Los Angeles

Sea level rise and uncertainty in its projections pose a major challenge to flood risk management and adaptation investments in coastal mega cities. This study presents a comparative economic evaluation method for flood adaptation measures, which couples a cost–benefit analysis with the concept of adaptation pathways. Our approach accounts for uncertainty in sea level rise projections by allowing for flexibility of adaptation strategies over time. Our method is illustrated for Los Angeles County which is vulnerable to flooding and sea level rise. Results for different sea level rise scenarios show that applying adaptation pathways can result in higher economic efficiency (up to 10%) than individual adaptation strategies, despite the loss of efficiency at the initial strategy. However, we identified ‘investment tipping points’, after which a transition could decrease the economic efficiencies of a pathway significantly. Overall, we recommend that studies evaluating adaptation strategies should integrate cost–benefit analysis frameworks with adaptation pathways since this allows for better informing decision makers about the robustness and economic desirability of their investment choices.

New York City Panel on Climate Change 2019 Report Chapter 1: Introduction

While urban areas like New York City and its surrounding metropolitan region are key drivers of climate change through emissions of greenhouse gases, cities are also significantly impacted by climate shifts, both chronic changes and extreme events. These are already affecting the New York metropolitan region, including the five boroughs of New York City through higher temperatures, more intense precipitation, and higher sea levels, and will increasingly do so in the coming decades. The City of New York has embarked on a flexible adaptation pathway (i.e., strategies that can evolve through time as climate risk assessment, evaluation of adaptation strategies, and monitoring continues) to respond to climate change challenges. This entails significant programs to develop resilience in communities and critical infrastructure to observed and projected changes in temperature, precipitation, and sea level. The first NPCC Report laid out the risk management framing for the city and region via flexible adaptation pathways. The second New York City Panel on Climate Change Report (NPCC2) developed the “climate projections of record” that are currently being used by the City of New York in its resilience programs . The NPCC3 2019 Report co-generates new tools and methods for the next generation of climate risk assessments and implementation of region-wide resilience. Co-generation is an interactive process by which stakeholders and scientists work together to produce climate change information that is targeted to decision-making needs. These tools and methods can be used to observe, project, and map climate extremes; monitor risks and responses; and engage with communities to develop effective programs. They are especially important at “transformation points” in the adaptation process when large changes in the structure and function of physical, ecological, and social systems of the city and region are undertaken.

Evaluation of olive response and adaptation strategies to climate change under semi-arid conditions

AdaptaOlive is a simplified physically-based model that has been developed to assess the behavior of olive under future climate conditions in Andalusia, southern Spain. The integration of different approaches based on experimental data from previous studies, combined with weather data from 11 climate models, is aimed at overcoming the high degree of uncertainty in the simulation of the response of agricultural systems under predicted climate conditions.The AdaptaOlive model was applied in a representative olive orchard in the Baeza area, one of the main producer zone in Spain, with the cultivar ‘Picual’. Simulations for the end of the 21st century showed olive oil yield increases of 7.1 and 28.9% under rainfed and full irrigated conditions, respectively, while irrigation requirements decreased between 0.5 and 6.2% for full irrigation and regulated deficit irrigation, respectively. These effects were caused by the positive impact of the increase in atmospheric CO2 that counterbalanced the negative impacts of the reduction in rainfall. The high degree of uncertainty associated with climate projections translated into a high range of yield and irrigation requirement projections, confirming the need for an ensemble of climate models in climate change impact assessment.The AdaptaOlive model also was applied for evaluating adaptation strategies related to cultivars, irrigation strategies and locations. The best performance was registered for cultivars with early flowering dates and regulated deficit irrigation. Thus, in the Baeza area full irrigation requirements were reduced by 12% and the yield in rainfed conditions increased by 7% compared with late flowering cultivars. Similarly, regulated deficit irrigation requirements and yield were reduced by 46% and 18%, respectively, compared with full irrigation. The results confirm the promise offered by these strategies as adaptation measures for managing an olive crop under semi-arid conditions in a changing climate.

Assessing summertime urban warming and the cooling efficacy of adaptation strategy in the Chengdu-Chongqing metropolitan region of China

Western China has experienced rapid urbanization since the Chinese reform process began in the late 1970s. It is essential to study the spatiotemporal patterns of warming induced by historical and future urban expansion and to evaluate adaptation strategies for the Chengdu–Chongqing metropolitan region (CCMR) in western China. The observed urban heat island intensity was ~1.5K in July 2009–2011. We employed the weather research and forecasting (WRF) model using real and projected urban land-use data to simulate near-surface air temperatures for a crop, urban in 2010 and urban in 2030 scenarios in summer over the CCMR. The difference between urban 2010 and cropland scenarios is 0.93K. Warming induced by urban development in 2010–2030 is in the range of 1–1.5K, but warming induced by future urban development will be less intense than historical warming over eastern China. We increased roof albedo to 0.8 to assess the difference in near-surface air temperature between cool roofs (CR) and urban 2030 scenarios, which represents the maximum potential impact of CR; we also assessed the cooling caused by green roofs (GR) (i.e., the difference between the GR and urban 2030 scenarios). Greater cooling occurs during the day due to reflection of solar radiation by CR and additional water evaporation by GR. We provided an evaluation criterion, cooling efficiency (CE), to measure the local performances of CR and GR. CE represents the local cooling capability based on urban warming rather than absolute cooling over a larger spatial scale. CE reveals a lower nocturnal cooling capability, which poses a significant challenge to the applications of CR and GR at night. CR has a better cooling capability across CCMR than GR, only when roof albedo of CR exceeds 0.68. Measures enacted should be appropriately adjusted to optimize for cost, technology and energy savings.