Local Climate Research Articles

Applying double cropping and interactive irrigation in the North China Plain using WRF4.5

Abstract. Irrigated cultivation exerts a significant influence on the local climate and the hydrological cycle. The North China Plain (NCP) is known for its intricate agricultural system, marked by expansive cropland, high productivity, compact rotation, a semi-arid climate, and intensive irrigation practices. As a result, there has been considerable attention on the potential impact of this intensive irrigated agriculture on the local climate. However, studying the irrigation impact in this region has been challenging due to the lack of an accurate simulation of crop phenology and irrigation practices within the climate model. By incorporating double cropping with interactive irrigation, our study extends the capabilities of the Weather Research Forecast (WRF) model, which has previously demonstrated commendable performance in simulating single-cropping scenarios. This allows for two-way feedback between irrigated crops and climate, further enabling the inclusion of irrigation feedback from both ground and vegetation perspectives. The improved crop modeling system shows significant enhancement in capturing vegetation and irrigation patterns, which is evidenced by its ability to identify crop stages, estimate field biomass, predict crop yield, and project monthly leaf area index. The improved simulation of large-scale irrigated crops in the NCP can further enhance our understanding of the intricate relationship between agricultural development and climate change.

Mainstreaming decarbonization through local climate budgets in Norwegian municipalities

ABSTRACT Climate budgets are increasingly being used in local climate governance, but it is not clear whether they have the potential to drive systemic change toward decarbonization. This study uses a political dynamics of decarbonization framework to assess the transformative potential of municipal climate budgets to catalyze changes across cultural, economic, political, and technological systems to overcome carbon lock-in. Document analysis and interviews with climate budget experts from Oslo, Fredrikstad, Hamar, Bergen, Arendal, Bærum, Asker and the county of Agder in Norway were employed in this study to identify and discuss transformative conditions for decarbonization. Climate budgets are used to integrate climate change mitigation as a core element of municipal governance. This approach aims to integrate climate change mitigation into existing decision-making mechanisms and expand the mandates of municipal departments and agencies in executing and overseeing climate actions. Local climate budgets are also being used to catalyze changes across cultural, economic, political, and technological systems through the alignment of new laws, regulations, financial and institutional capacities, inter-municipal coalitions, and cooperation with the private sector. However, climate budgeting in cities and local governments faces multiple barriers. These include a lack of jurisdiction over emissions accounted for in climate budgets; inadequate legal frameworks to support municipal climate actions; and competition for financial and institutional resources with other public services expected by city residents. These findings deepen our understanding of the transformative change potential in local climate action experiments by emphasizing the role of political dynamics in overcoming carbon lock-in.

Evaluating local climate policy: Municipal action plans through the lens of resilience and environmental justice

In the US, local governments are increasingly crucial in driving climate action. Drawing upon previous scholarly work, this study assesses nine local climate action plans in the state of Michigan. It introduces a comprehensive framework integrating climate resilience and environmental justice (EJ) indicators to evaluate plan content. Despite recognizing global climate concerns, qualitative content analysis shows that plans lack localized analyses and actions, hampering planning efforts as a result of insufficient data, minimal coordination, limited funds, and finite policy options. Key aspects like equitable resource distribution, environmental burdens, and community engagement are often overlooked. Without addressing these limitations, local governments lack the tools to effectively implement justice-oriented climate policies.

Exploring the natural ventilation potential of urban climate for high-rise buildings across different climatic zones

The natural cooling capacity of the environment can effectively reduce the building energy consumption by natural ventilation (NV). For architects, developing NV strategies requires a comprehensive understanding of the distribution characteristics of urban meteorology. This study investigates the vertical characteristics of urban local-scale meteorological parameters across climatic zones. It aims to assess the climatic potential for NV of outdoor air in high-rise buildings. Firstly, using Weather Research and Forecasting (WRF) model coupled with Local Climate Zone (LCZ) data and sounding data, the vertical distribution of meteorological parameters are explored in typical urban areas across different climatic zones. Then, based on an adaptive thermal comfort model, the climatic potential is assessed for NV in high-rise buildings via the indicator of annual natural ventilation hour (NVH). Finally, the characteristics of urban meteorology is further is analyzed in terms of its impact on the natural ventilation potential (NVP) in each climatic zone. Results indicate that air temperature decreases with height from 0 to 500 m, with more pronounced temperature gradients in compact building areas. Near the ground level, Kunming (Temperate Zone) has the most NVH, reaching 4,840 h annually. However, when building height exceeds 100 m, Guangzhou (Hot Summer and Warm Winter, HSWW) becomes more suitable for NV. In cold regions, low temperatures limit NVP during winter, while high humidity constrains it in Temperate and HSWW zones. Overall, the annual NVP in high-rise building areas exceeds that of low-rise building areas. These distribution characteristics of NVP are anticipated to promote the utilization of natural resources for sustainable urban development.

The effect of urban form parameters on annual and diurnal cycles of land surface temperature with 30-meter hourly resolution

Understanding dynamic changes in urban land surface temperature (U-LST) is vital for improving urban thermal environment. Previous studies noted a close association between two/three-dimensional (2D/3D) urban form parameters (UFPs) and U-LST, but divergent conclusions emerged due to study scale and data spatiotemporal resolution. This study investigated the effect of 2D/3D UFPs on multi-temporal (hourly, diurnal, and annual) U-LSTs with 30-m spatial resolution, which is the first exploration of such dynamics at this fine scale. In addition, the influence of local climate zones (LCZs) was considered. Results showed that 2D/3D vegetation UFPs have the greatest summer cooling effect at 21:00, while 3D building UFP sky view factor (SVF) impacts minimum nighttime temperature more (5:00). The independently total explained variances (R2) of 2D UFPs (0.2–0.7) on seasonal average U-LSTs were higher than that of 3D UFPs (0.1–0.4) in most LCZs. LCZ 3 and LCZ 2 had the highest seasonal and daytime U-LST, respectively. Interestingly, SVF replaced normalized difference vegetation index as the dominant factor in LCZs 4–6 and LCZs A-C after summer. Findings of this study are useful for guiding urban planning, formulating urban heat island mitigation policies, and promoting sustainable development goals (SDGs 11, 13, 15) of cities and communities.

Evaluating the impact of improved filter-wrapper input variable selection on long-term runoff forecasting using local and global climate information

Long-term runoff forecasting (LRF) is great important for water resources management. Employing accurate local and global climate information can significantly enhance the accuracy of LRF. The filter-wrapper input variables selection (FWIVS) method can efficiently select local and global climate indices for LRF. However, binary metaheuristic algorithms (BMAs) in wrapper input variable selection (WIVS), such as golden jackal optimization (GJO) and gray wolf optimizer (GWO), frequently encounter local optima, which significantly impact LRF accuracy and remain unexplored. Additionally, previous FWIVS methods overlooked physical relationship between local and global climate information. Consequently, an improved GJO (IGJO) that considers the complementarity of local weather and global climate indices and prevents local optima was proposed. Four machine learning models and an integrated model (IM) were used as learning models for WIVS. Finally, eight BMAs, including IGJO, improved GWO and so on, were constructed and integrated with five learning models to develop forty wrappers for evaluating impact of various BMAs and models on WIVS and LRF. The Jinsha River was served as a case study. Results demonstrated that the impact of the improved BMAs on wrapper fitness and variables selection was higher than learning model. IGJO retained critical variables for WIVS, especially local weather variables. Moreover, IGJO effectively reduced redundant information and extracted more robust complementary global climate indices for WIVS. In addition, LSTM-IGJO exhibited the greatest enhancement in wrapper fitness and LRF accuracy, achieving a NSE of 0.92 and a MAE of 575.83 m3/s. Specifically, this finding indicated that selecting the key variables and selecting the stronger complementary global climate indices instead the redundant local weather variables for retaining key information, while eliminating redundant information, can efficiently improve the LRF accuracy.

Determination of outdoor thermal comfort thresholds for hot and semi-arid climates: A field study of residential neighbourhoods in Jaipur city

Outdoor thermal comfort (OTC) plays a vital role in enhancing the livability and well-being of urban residents, making it an essential area of research, particularly in the context of climate change. However, few studies have specifically focused on hot and semi-arid regions, especially within residential environments. This study seeks to address this gap by assessing OTC in various residential areas classified as Local Climate Zones (LCZs), ensuring a diverse range of survey locations to evaluate people's comfort and stress levels. Using the Thermal Sensation Vote (TSV) index, the study calibrated the Physiologically Equivalent Temperature (PET) scale for hot and semi-arid climates. In Jaipur, micrometeorological data was monitored alongside thermal perceptions, resulting in 2,428 valid responses gathered during both summer and winter seasons, between 09:00 and 21:00 h, when outdoor activity is common. The analysis revealed that microclimate parameters significantly influence thermal sensations in outdoor environments. Respondents showed high tolerance levels during summer, with variations in thermoneutrality, acceptability, preferences, and comfort across different built typologies. The threshold values identified in this study offer valuable insights for urban planners and designers, enabling them to enhance outdoor thermal comfort during the planning stages, ultimately creating more comfortable and livable urban spaces for residents.

A Model‐Based Investigation of the Recent Rebound of Shelf Water Salinity in the Ross Sea

AbstractIntense atmosphere‐ocean‐ice interactions in the Ross Sea play a vital role in global overturning circulation by supplying saline and dense shelf waters. Since the 1960s, freshening of the Ross Sea shelf water has led to a decline in Antarctic Bottom Water formation. However, during 2012–2018, salinity of the western Ross Sea has rebounded. This study adopts a global ocean‐sea ice model to investigate the causes of this salinity rebound. Model‐based surface salinity budget analysis indicates that the salinity rebound was driven by increased brine rejection from sea ice formation, triggered by nearly equal effects of local anomalous winds and surface heat flux. The local divergent wind anomalies promoted local sea ice formation by creating a thin ice area, while cooling heat flux anomaly decreased the surface temperature, increasing sea ice production as well. This highlights the importance of understanding local climate variability in projecting future dense shelf water change.

Haplotype-based pangenomes reveal genetic variations and climate adaptations in moso bamboo populations

Moso bamboo (Phyllostachys edulis), an ecologically and economically important forest species in East Asia, plays vital roles in carbon sequestration and climate change mitigation. However, intensifying climate change threatens moso bamboo survival. Here we generate high-quality haplotype-based pangenome assemblies for 16 representative moso bamboo accessions and integrated these assemblies with 427 previously resequenced accessions. Characterization of the haplotype-based pangenome reveals extensive genetic variation, predominantly between haplotypes rather than within accessions. Many genes with allele-specific expression patterns are implicated in climate responses. Integrating spatiotemporal climate data reveals more than 1050 variations associated with pivotal climate factors, including temperature and precipitation. Climate-associated variations enable the prediction of increased genetic risk across the northern and western regions of China under future emissions scenarios, underscoring the threats posed by rising temperatures. Our integrated haplotype-based pangenome elucidates moso bamboo’s local climate adaptation mechanisms and provides critical genomic resources for addressing intensifying climate pressures on this essential bamboo. More broadly, this study demonstrates the power of long-read sequencing in dissecting adaptive traits in climate-sensitive species, advancing evolutionary knowledge to support conservation.

Local climate at breeding colonies influences pre-breeding arrival in a long-distance migrant

AbstractThe annual cycles of long-distance migrant species are synchronized with the local climatic conditions at their breeding areas, as they impact the availability of food resources. A timely arrival of individuals to the breeding grounds is crucial for achieving high fitness. Variation in factors influencing timing, including climate, may thus impact the life history of individuals. We studied between-individual variation in migration timing, in particular how local breeding climate influences arrival time and how early-arriving individuals achieve a timely arrival. We tracked individual Lesser Kestrel (Falco naumanni) with GPS tags across a gradient of latitude (37°–42° N) and longitude (6.5° W–16.5° E). Arrival time was influenced by the breeding latitude, the breeding longitude, and the local temperature, without any apparent influence of sex. The time of arrival at the breeding grounds was 6 days later for every degree increase in latitude and 2 days later for every degree increase in longitude. Lesser Kestrels from southwestern colonies achieve earlier arrival than conspecifics breeding at northeastern colonies, mostly due to earlier departure from their non-breeding grounds. While we found some effects of travel speed and stopover duration on arrival date, the latter was primarily influenced by food abundance and wind conditions en route. The large effect of departure date from West Africa on arrival date, relative to the more moderate influence of stopover duration close to breeding colonies, supports the idea that geographically uneven climate change may negatively affect fitness via ecological mismatches in the breeding area.

Impact of urban spatial dynamics and blue-green infrastructure on urban heat islands: A case study of Guangzhou using Local Climate Zones and predictive modeling

Amidst mounting concerns regarding health risks associated with excessive carbon emissions, attention has turned to the heat mitigation ability of blue-green infrastructure (BGI). BGI offers heat mitigation through transpiration cooling, effectively countering the urban heat island (UHI) effect while facilitating energy conservation and carbon reduction. This study adopted the InVEST model to assess the spatial pattern of UHI and heat mitigation service based on the Local Climate Zone (LCZ) classification, along with quantifying the energy savings in Guangzhou for 2019. The results revealed that the UHI effect exhibited greater intensity in the southwest built-up area. Compact Lowrise (LCZ-3) and Heavy Industry (LCZ-10) areas demonstrated higher UHI intensity, while Water (LCZ-G) and Dense Trees (LCZ-A) areas showcased the highest heat mitigation index (HMI) and optimal cooling capacities. Three urban development scenarios were devised to simulate the UHI distribution, heat mitigation capacity, and energy savings by 2025, using the CA-Markov model. In comparison to the Baseline scenario, the Environmental Protection scenario showed a modest 3.67 % decrease in the built-up area, but a noteworthy increase in HMI and energy saving, by 21.2 % and 6.6 % respectively. This scenario can serve as a reference pathway for urban energy conservation and sustainable development.

Microclimate analysis of Ganga riverfront in Patna: spatial form perspective

ABSTRACT The investigation in this research scrutinizes the influence of spatial form factors on thermal comfort along the Ganga riverfront trail during the spring season. Understanding how spatial form factors impact local climate parameters and PET values is crucial for optimizing thermal comfort in urban waterfronts. The research addresses the need to improve thermal comfort in rapidly urbanizing areas through strategic urban design. Data were collected from eight measurement points along the riverfront, analyzing Air Temperature (Ta), Relative Humidity (RH), Wind Velocity (v), Surface Temperature (Ts), Global Radiation (G) and Mean Radiant Temperature (Tmrt). The study employs a combination of field measurements and statistical analysis to assess the correlation between spatial form factors and thermal comfort indicators. Findings reveal that lower building height (Hb) values are associated with more favorable thermal comfort conditions, while higher Hb negatively impacts thermal comfort. The study also highlights that building spacing (ADb) influences thermal comfort, with findings contrasting those from composite climates, suggesting a need for context-specific design strategies. The research underscores the significant role of Ta and v in shaping Physiological Equivalent Temperature (PET), aligning with previous studies in diverse urban contexts. The results emphasize the critical impact of spatial form on microclimate and thermal comfort, informing urban design and planning to enhance livability along the Ganga riverfront. This study contributes to the field by providing empirical evidence and practical insights for developing thermally comfortable walking trails.

Reshaping landscape factorization through 3D landscape clustering for urban temperature studies

As urban populations grow and cities expand, the challenge of managing urban heat and its environmental impacts becomes increasingly critical. Traditional methods for analyzing urban temperature dynamics often fall short in precisely capturing the complexity of urban landscapes. This paper introduces the 3D Landscape Clustering (3LC) framework, a new tool designed to analyze urban temperature dynamics by factoring in landscape variables. It clusters landscapes into homogeneous groups using high-resolution 3D land cover maps. The 3LC adopts a clustering mechanism to enhance flexibility and objectivity in landscape categorization, thereby enhancing the depth and accuracy of urban climate studies and moving beyond traditional classification frameworks such as the Local Climate Zone (LCZ). Case studies demonstrate its capability to provide detailed insights into the relationships between urban landscape features and temperature variations. Additionally, the paper details how the framework can excel in multi-city analyses and outlines advanced analytical techniques. Promising research opportunities and limitations are identified. This research reshapes our approach to landscape categorization, advancing our understanding of the interactions between landscape and climate dynamics, and contributing to more sustainable, climate-resilient cities.

Research on the Spatial-Temporal Evolution of Changsha’s Surface Urban Heat Island from the Perspective of Local Climate Zones

Research on the Spatial-Temporal Evolution of Changsha’s Surface Urban Heat Island from the Perspective of Local Climate Zones

Why Local Governments Set Climate Targets: Effects of City Size and Political Costs

AbstractCities increasingly address climate change, e.g. by pledging city-level emission reduction targets. This is puzzling for the provision of a global public good: what are city governments’ reasons for doing so, and do pledges actually translate into emission reductions? Empirical studies have found a set of common factors which relate to these questions, but also mixed evidence. What is still pending is a theoretical framework to explain those findings and gaps. This paper thus develops a theoretical public choice model. It features economies of scale and distinguishes urban reduction targets from actual emission reductions. The model is able to explain the presence of targets and public good provision, yet only under specified conditions. It is also able to support some stylized facts from the empirical literature, e.g. on the effect of city size, and resolves some mixed evidence as special cases. Larger cities chose more ambitious targets if marginal net benefits of mitigation rise with city size—if they set targets at all. Whether target setting is more likely for larger cities depends on the city type. Two types are obtained. The first type reduces more emissions than a free-riding city. Those cities are more likely to set a target when they are larger. However, they miss the self-chosen target. Cities of the second type reach their target, but mitigate less than a free-riding city. A third type does not exist. With its special cases, the model can thus guide further empirical and theoretical work.

A sacrifice for the greater good? On the main drivers of excessive land take and land use change in Hungary

Despite continuous population decline or stagnation, many Central and Eastern European cities experience urban sprawl and expansion, accompanied by excessive land take and land use change. This paper investigates recent trends in land take and land use change in Hungarian cities, aiming to identify the drivers of these processes. The study utilizes the Urban Atlas (UA) databases from 2006 and 2018 to analyze land use change in selected Hungarian cities, employing QGIS software to compile the database and MS Excel to conduct the statistical analysis. A linear trajectory model is employed to project land use change by 2026, based on 2006–2018 UA data. Additionally, via the in-depth analysis of Debrecen, the study highlights the recent acceleration of land use change to compare the projected trend with the forecasted one. Local climate strategies focus on addressing environmental concerns, including changes in land use at the city level. Therefore, this study reviews the relevant documents associated with each city to assess its commitment to reducing land take. The results indicate that despite its declining population, Hungary has seen a significant expansion in artificial surfaces, primarily due to industrialization and population policies introduced by the central government, which is likely to continue in the coming years. Unfortunately, local climate strategies have been insufficient in preventing cities from experiencing urban sprawl and expansion and preserving local ecosystem services. This underscores the inability of municipalities to defend local interests against central government directives. The findings of this study indicate that the current central policies are the main drivers of land take and urban sprawl and expansion. Prioritizing the compact city model and brownfield developments could effectively mitigate these issues. Finally, the paper advocates that complete jurisdiction over land use decisions be restored to local governments, enabling them to reject investments that may jeopardize local environmental goals.

Influences of Central and Eastern Atlantic Niño on the West African and South American summer monsoons

The rainfall variabilities of the West African and South American summer monsoons, pivotal for local and global climate systems, are strongly influenced by tropical Atlantic sea surface temperature anomalies. This study investigates the impacts of two recently identified Atlantic Niño types, central and eastern Atlantic Niño (CAN and EAN), on these monsoon systems using observational data and numerical experiments. During boreal summer, EAN events exhibit increased rainfall over West Africa compared to CAN events, indicating a strengthened West African summer monsoon. Enhanced moisture flux convergence from eastern Atlantic warming drives these wetting conditions during EAN events. Conversely, CAN events have a more pronounced influence on South American monsoon rainfall during austral summer, causing a rainfall anomaly dipole between the Amazon and eastern Brazil, suggesting an eastward shift in the South American summer monsoon rainfall belt. These rainfall changes are linked to cyclonic circulation anomalies over the southwest Atlantic Ocean, attributed to central Atlantic warming during CAN events. Furthermore, a statistical model assesses hindcast skills of rainfall variability in the two summer monsoon regions, affirming the benefits of separating Atlantic Niño into CAN and EAN events for improved seasonal climate predictions.

Climatic controls of fire activity in the red pine forests of eastern North America

Large-scale modes of climate variability influence forest fire activity and may modulate the future patterns of natural disturbances. We studied the effects of long-term changes in climate upon the fire regime in the red pine forests of eastern North America using (a) a network of sites with dendrochronological reconstructions of fire histories over 1700–1900 A.D., (b) reconstructed chronologies of climate indices (1700–1900), and (c) 20th century observational records of climate indices, local surface climate and fire (1950s-2021). We hypothesized that (H1) there are states of atmospheric circulation that are consistently associated with increased fire activity, (H2) these states mark periods of increased climatological fire hazard, and (H3) the observed decline in fire activity in the 20th century is associated with a long-term decline in the frequency of fire-prone states.At the annual scale, years with significantly higher fire activity in the reconstructed and modern fire records were consistently associated with the positive phases of the Pacific North American pattern (PNA), either independently or in combination with the positive phase of the El Niño-Southern Oscillation index (ENSO). During years with both ENSO and PNA in their positive state, the region experienced positive mid-tropospheric heights and temperature anomalies resulting in drought conditions. The fire-prone climate states identified in the reconstructed records became less frequent in 1850 but re-emerged in the 20th century. While our study did not demonstrate a direct influence of climate on the observed decrease in fire activity in the 20th century, it does reveal a clear climate signal embedded within the fire history reconstruction of the region over the past centuries. This study underscores the importance of considering large-scale climatic patterns in understanding historical fire regimes and highlights their role for future fire dynamics in the region and shaping ecological effects of future fires.

Optimizing Local Climate Zones through Clustering for Surface Urban Heat Island Analysis in Building Height-Scarce Cities: A Cape Town Case Study

Studying air Urban Heat Islands (AUHI) in African cities is limited by building height data scarcity and sparse air temperature (Tair) networks, leading to classification confusion and gaps in Tair data. Satellite imagery used in surface UHI (SUHI) applications overcomes the gaps which befall AUHI, thus making it the primary focus of UHI studies in areas with limited Tair stations. Consequently, we used Landsat 30 m imagery to analyse SUHI patterns using Land Surface Temperature (LST) data. Local climate zones (LCZ) as a UHI study tool have been documented to not result in distinct thermal environments at the surface level per LCZ class. The goal in this study was thus to explore relationships between LCZs and LST patterns, aiming to create a building height (BH)-independent LCZ framework capable of creating distinct thermal environments to study SUHI in African cities where LiDAR data are scarce. Random forests (RF) classified LCZ in R, and the Single Channel Algorithm (SCA) extracted LST via the Google Earth Engine. Statistical analyses, including ANOVA and Tukey’s HSD, assessed thermal distinctiveness, using a 95% confidence interval and 1 °C threshold for practical significance. Semi-Automated Agglomerative Clustering (SAAC) and Automated Divisive Clustering (ADC) grouped LCZs into thermally distinct clusters based on physical characteristics and LST data internal patterns. Built LCZs (1–9) had higher mean LSTs; LCZ 8 reached 37.6 °C in Spring, with a smaller interquartile range (IQR) (34–36 °C) and standard deviation (SD) (1.85 °C), compared to natural classes (A–G) with LCZ 11 (A–B) at 14.9 °C/LST, 17–25 °C/IQR, and 4.2 °C SD. Compact LCZs (2, 3) and open LCZs (5, 6), as well as similar LCZs in composition and density, did not show distinct thermal environments even with building height included. The SAAC and ADC clustered the 14 LCZs into six thermally distinct clusters, with the smallest LST difference being 1.19 °C, above the 1 °C threshold. This clustering approach provides an optimal LCZ framework for SUHI studies, transferable to different urban areas without relying on BH, making it more suitable than the full LCZ typology, particularly for the African context. This clustered framework ensures a thermal distinction between clusters large enough to have practical significance, which is more useful in urban planning than statistical significance.

From trees to rain: enhancement of cloud glaciation and precipitation by pollen

Abstract The ability of pollen to enable the glaciation of supercooled liquid water has been demonstrated in laboratory studies; however, the potential large-scale effect of plants and pollen on clouds, precipitation and climate is pressing knowledge to better understand and project clouds in the current and future climate. Combining ground-based measurements of pollen concentrations and satellite observations of cloud properties within the United States, we show that enhanced pollen concentrations during springtime lead to an increase in cloud ice fraction of up to 0.1 in the temperature regime where pollen are considered to act as INP (−15 ∘ C and −25 ∘ C ). We further establish the link from the pollen-induced increase in cloud ice to a higher precipitation frequency. In light of anthropogenic climate change, the extended and strengthened pollen season and future alterations in biodiversity can introduce a localized climate forcing and a modification of the precipitation frequency and intensity.