Selection of Heat Recovery Ventilators in Different Climate Zones of China

Considering four different climate zones in China, an investigation on the choice of heat recovery ventilator for the buildings with little moisture emissions is carried out. The annual composition of energy consumption of air intake for per unitary air ventilation flow rate is evaluated by employing the testing data of climatic parameters in eight selected cities. The analysis shows that the total heat recovery is suitable in a controlled ventilation system with air humidity controlled during heating period of all the climates. For the building without air humidity controlled in winter, the sensible heat recovery ventilators can be used in severe cold and cold regions, and total heat recovery systems are more suitable for energy saving in hot summer and cold winter and hot summer and warm winter regions.

Variations in Surface Urban Heat Island and Urban Cool Island Intensity:A Review Across Major Climate Zones

The climate has an impact on the urban thermal environment,and the magnitude of the surface urban heat island(SUHI)and urban cool island(UCI)vary across the world’s climatic zones.This literature review investigated:1)the variations in the SUHI and UCI intensity under different climatic backgrounds,and 2)the effect of vegetation types,landscape composition,urban configuration,and water bodies on the SUHI.The SUHI had a higher intensity in tropical(Af(tropical rainy climate,Köppen climate classification),Am(tropical monsoon climate),subtropical(Cfa,subtropical humid climate),and humid continental(Dwa,semi-humid and semi-arid monsoon climate)climate zones.The magnitude of the UCI was low compared to the SUHI across the climate zones.The cool and dry Mediterranean(Cfb,temperate marine climate;Csb,temperate mediterranean climate;Cfa)and tropical climate(Af)areas had a higher cooling intensity.For cities with a desert climate(BWh,tropical desert climate),a reverse pattern was found.The difference in the SUHI in the night-time was greater than in the daytime for most cities across the climate zones.The extent of green space cooling was related to city size,the adjacent impervious surface,and the local climate.Additionally,the composition of urban landscape elements was more significant than their configuration for sustaining the urban thermal environment.Finally,we identified future research gaps for possible solutions in the context of sustainable urbanization in different climate zones.

CHARACTERISTICS OF CLIMATE WARMING AND IMPACT ON CLIMATE ZONES CHANGE IN GUANGDONG

Based on temperature data in Guangdong in the past 50years, statistical methods are used to analyze the characteristics of temperature in spatial and temporal variation. The results show that land surface temperature warms by 0.16℃/1 0a in Guangdong. The range of warming was lower than the average of nationwide and global land surface. Furthermore, the temperature has a larger increase tendency in winter and spring and coastal areas than in summer and autumn and inland areas. Climate zones move towards the north obviously. North tropical zone is expanding, south subtropical zone is reducing and central subtropical zone is relatively stable. Under the global climate warming, characteristics of climate warming in Guangdong were influenced by atmosphere general circulation, sea surface temperature and human activities etc.

Spatiotemporal Evolution Characteristics of Urban Land Surface Temperature Based on Local Climate Zones in Xi’an Metropolitan,China

Local climate zones(LCZs)are an effective nexus linking internal urban structures to the local climate and have been widely used to study urban thermal environment.However,few studies considered how much the temperature changed due to LCZs transformation and their synergy.This paper quantified the change of urban land surface temperature(LST)in LCZs transformation process by combining the land use transfer matrix with zonal statistics method during 2000–2019 in the Xi’an metropolitan.The results show that,firstly,both LCZs and LST had significant spatiotemporal variations and synchrony.The period when the most LCZs were converted was also the LST rose the fastest,and the spatial growth of the LST coincided with the spatial expansion of the built type LCZs.Secondly,the LST difference between land cover type LCZs and built type LCZs gradually widened.And LST rose more in both built type LCZs transferred in and out.Finally,the Xi’an-Xianyang profile showed that the maximum temperature difference between the peaks and valleys of the LST increased by 4.39℃,indicating that localized high temperature phenomena and fluctuations in the urban thermal environment became more pronounced from 2000 to 2019.

ADAPTIVE BUILDING AND SKIN:AN INNOVATIVE COMPUTATIONAL WORKFLOW TO DESIGN ENERGY EFFICIENT BUILDINGS IN DIFFERENT CLIMATE ZONES

This research aims at developing an innovative methodology and the related computational workflow to design energy efficient buildings equipped with climate responsive building skins able to respond dynamically to environmental conditions changing over the time.This methodology,called Adaptive Building and Skin(AB&S),is applicable in different climate zones and consists of a computational form-finding method,which supports architects and engineers in the buildings’design process resulting in buildings with optimized energy performance and a high level of indoor and outdoor comfort under changing environmental conditions.The innovativeness of AB&S lies in the fact that it includes the entire design process and considers several internal and external inputs to find the best solutions at all scales of a project:starting from the micro urban-scale with the design of the site and of the building shape,down to the building-scale and finally the skin-scale.Applicability and functionality of AB&S has been tested and improved in the design of office buildings located in specific cities located in different climate zones(cold,temperate,tropical and subtropical).Results of the application in Berlin,Germany,are presented in detail in this paper.

Impact of Local Climate Zones on the Urban Heat and Dry Islands in Beijing:Spatial Heterogeneity and Relative Contributions

Based on the building height and density data on a 100-m resolution,hourly 2-m temperature and humidity data at83 automatic weather stations,and gridded local climate zone(LCZ)data on a 120-m resolution in urban Beijing in2020,this study first employs the semivariogram combined with building parameters to calculate spatial correlations and has identified an LCZ grid resolution of 500 m suitable for best usage of the available observation data.Then,how the spatially heterogeneous LCZs affect and contribute to the canopy urban heat island intensity(UHII)and urban dry island intensity(UDII)are quantitatively investigated.It is found that UHII is high in winter and low in summer with a unimodal diurnal variation while UDI is low in winter but high in summer with a bimodal diurnal variation.The LCZ with compact mid-rise(open high-rise)buildings exhibits the highest UHII(UDII),followed by the compact high-rise(compact low-rise),while the LCZ of scattered trees presents both the lowest UHII and the lowest UDII.The most significant difference in the UHII(UDII)among the nine LCZ types in the urban area of Beijing is2.62℃(1.1 g kg^(-1)).Area-weighted averaging analysis reveals that the open mid-rise LCZ is the most significant contributor to the UHII(UDII),immediately followed by compact mid-rise(open low-rise),with the least contribution from bare rock or paved(scattered trees).The results also indicate that beyond the intrinsic physical properties of the LCZs of a city,their area proportions cannot be overlooked in evaluating their impact on the UHI and UDI.These quantitatively findings could help urban planners to create a livable urban climate and environment by adjusting the relevant land use.

Potential application of radiant floor cooling systems for residential buildings in different climate zones

A radiant floor cooling system(RFCS)is a high-comfort and low energy consumption system suitable for residential buildings.Radiant floor systems usually work with fresh air,and their operating performance is affected by climatic conditions.Indoor and outdoor environmental disturbances and the system’s control strategy affect the indoor thermal comfort and energy efficiency of the system.Firstly,a multi-story residential building model was established in this study.Transient system simulation program was used to study the operation dynamics of three control strategies of the RFCS based on the calibrated model.Then,the performance of the control strategies in five climate zones in China were compared using multi-criteria decision-making in combination.The results show that control strategy has a negligible effect on condensation risk,but the thermal comfort and economic performance differ for different control strategies.The adaptability of different control strategies varies in different climate zones based on the consideration of multiple factors.The performance of the direct-ground cooling source system is better in Hot summer and warm winter zone.The variable air volume control strategy scores higher in Serve cold and Temperate zones,and the hours exceeding thermal comfort account for less than 3%of the total simulation period.Therefore,it is suggested to choose the RFCS control strategy for residential buildings according to the climate zone characteristics,to increase the energy savings.Our results provide a reliable reference for implementing RFCSs in residential buildings.

Epidemiological features of seasonal influenza transmission among 11 climate zones in Chinese mainland

Background Previous studies provided some evidence of meteorological factors influence seasonal influenza transmission patterns varying across regions and latitudes. However, research on seasonal influenza activities based on climate zones are still in lack. This study aims to utilize the ecological-based Koppen Geiger climate zones classification system to compare the spatial and temporal epidemiological characteristics of seasonal influenza in Chinese mainland and assess the feasibility of developing an early warning system.Methods Weekly influenza cases number from 2014 to 2019 at the county and city level were sourced from China National Notifiable Infectious Disease Report Information System. Epidemic temporal indices, time series seasonality decomposition, spatial modelling theories including Moran’s/ and local indicators of spatial association were applied to identify the spatial and temporal patterns of influenza transmission.Results All climate zones had peaks in Winter-Spring season. Arid, desert, cold (BWk) showed up the first peak. Only Tropical, savannah (Aw) and Temperate, dry winter with hot summer (Cwa) zones had unique summer peak. Temperate, no dry season and hot summer (Cfa) zone had highest average incidence rate (IR) at 1.047/100,000. The Global Moran’s/ showed that average IR had significant clustered trend (z = 53.69,P < 0.001), with local Moran’s/ identified high-high cluster in Cfa and Cwa. IR differed among three age groups between climate zones (0-14 years old:F = 26.80,P < 0.001;15-64 years old:F = 25.04,P < 0.001;Above 65 years old:F = 5.27,P < 0.001). Age group 0-14 years had highest average IR in Cwa and Cfa (IR= 6.23 and 6.21) with unique dual peaks in winter and spring season showed by seasonality decomposition.Conclusions Seasonal influenza exhibited distinct spatial and temporal patterns in different climate zones. Seasonal influenza primarily emerged in BWk, subsequently in Cfa and Cwa. Cfa, Cwa and BSk pose high risk for seasonal influenza epidemics. The research finds will provide scientific evidence for developing seasonal influenza early warning system based on climate zones.

Projected changes in Köppen-Trewartha climate zones under 1.5-4℃global warming targets over mid-high latitudes of Northern Asia using an ensemble of RegCM4 simulations

Mid-high latitude Northern Asia is one of the most vulnerable and sensitive areas to global warming,but relatively less studied previously.We used an ensemble of a regional climate model(RegCM4)projections to assess future changes in surface air temperature,precipitation and Köppen-Trewartha(K-T)climate types in Northern Asia under the 1.5-4℃global warming targets.RegCM4 is driven by five CMIP5 global models over an East Asia domain at a grid spacing of 25 km.Validation of the present day(1986-2005)simulations shows that the ensembles of RegCM4(ensR)and driving GCMs(ensG)reproduce the major characters of the observed temperature,precipitation and K-T climate zones reasonably well.Greater and more realistic spatial detail is found in RegCM4 compared to the driving GCMs.A general warming and overall increases in precipitation are projected over the region,with these changes being more pronounced at higher warming levels.The projected warming by ensR shows different spatial patterns,and is in general lower,compared to ensG in most months of the year,while the percentage increases of precipitation are maximum during the cold months.The future changes in K-T climate zones are characterized by a substantial expansion of Dc(temperature oceanic)and retreat of Ec(sub-arctic continental)over the region,reaching∼20%under the 4℃warming level.The most notable change in climate types in ensR is found over Japan(∼60%),followed by Southern Siberia,Mongolia,and the Korean Peninsula(∼40%).The largest change in the K-T climate types is found when increasing from 2 to 3℃.The results will help to better assess the impacts of climate change and in implementation of appropriate adaptation measures over the region.

Mapping urban carbon emissions in relation to local climate zones:Case of the building sector in Bangkok Metropolitan Administration,Thailand

This study focuses on carbon emissions of the building sector in relation to local climate zone(LCZ)classification,concentrating on two major parts.First,we estimated carbon emissions in the building sector,which were cal-culated for weekdays and weekends real-time daily energy consumption patterns.The estimations were divided into direct(from petroleum products consumption)and indirect emissions(from electricity consumption).Sec-ond,we examined urban carbon emissions mapping in relation to LCZ.Bangkok Metropolitan Administration(BMA)was used as the case study and 2016 as the base year for examination.The results illustrate that indirect emissions in Bangkok can be up to ten times higher than direct emissions.The analysis indicates that LCZ,such as compact high-rise,large low-rise,light industry,and warehouse zones had a relatively higher carbon emission intensity than others.Additionally,we identified that the compact high-rise zone has the highest indirect emission intensity,while the light industry and warehouse zone have the greatest direct emission intensity.These results provide insights into the dynamics of carbon emission characteristics in the building sector and the methodology purported here can be used to support low carbon city planning and policymaking in Bangkok.

Enhanced geographic information system-based mapping of local climate zones in Beijing, China

The vague urban-rural dichotomy severely restricts effective comparisons and communications among urban heat island studies.A local climate zone(LCZ) scheme has therefore been developed to classify urban and natural landscapes in a standardized and universal manner. Despite LCZ mapping efforts in worldwide cities, this study attempts to propose an enhanced geographic information system-based workflow to enable the hierarchical classification of LCZs with fewer indicators but higher accuracies while considering supplementary classes and subclasses. Specifically, five morphological and coverage indicators that were easily obtained and well differentiated among LCZs were derived from a city street map and satellite images, and 25 LCZs(including 16 standard, 3 supplementary, and 6 sub-classified zones) were determined at a block-level according to the indicator hierarchy and criteria. The method was performed over Beijing, China, and evaluations by field surveys and google earth images showed a high accuracy with little noise and sharp boundaries, outperforming the widely-used remote sensing-based method of the World Urban Database and Access Portal Tools, particularly in terms of building height and heavy industry. Results also demonstrate that the Beijing core was dominated by open(including extremely open) mid-rise buildings(28.7%) and open lowrise buildings(12.8%), forming an inner-low-middle-high-outer-low annular building-height pattern. Significant land surface temperature differences were detected among the LCZs, where the low-rise and compact LCZs had higher temperatures than the mid-/high-rise and open LCZs during daytime, and subclasses LCZ XB/C/D(LCZ XE/F) generated lower(higher) temperatures than their parent classes in May. This method was proposed to augment the LCZ mapping system and further support applications(e.g., urban planning/management and climate/weather modeling) in high-density cities similar to Beijing.

Mapping and analyzing the local climate zones in China’s 32 major cities using Landsat imagery based on a novel convolutional neural network

The Local Climate Zone(LCZ)scheme provides researchers with a standard method to monitor the Urban Heat Island(UHI)effect and conduct temperature studies.How to generate reliable LCZ maps has therefore become a research focus.In recent years,researchers have attempted to use Landsat imagery to delineate LCZs and generate maps worldwide based on the World Urban Database and Access Portal Tools(WUDAPT).However,the mapping results obtained by the WUDAPT method are not satisfactory.In this paper,to generate more accurate LCZ maps,we propose a novel Convolutional Neural Network(CNN)model(namely,LCZ-CNN),which is designed to cope with the issues of LCZ classification using Landsat imagery.Furthermore,in this study,we applied the LCZ-CNN model to generate LCZ mapping results for China’s 32 major cities distributed in various climatic zones,achieving a significantly better accuracy than the traditional classification strategies and a satisfactory computational efficiency.The pro-posed LCZ-CNN model achieved satisfactory classification accuracies in all 32 cities,and the Overall Accuracies(OAs)of more than half of the cities were higher than 80%.We also designed a series of experiments to comprehensively analyze the proposed LCZ-CNN model,with regard to the transferability of the network and the effectiveness of multiseasonal information.It was found that the first convolutional stage,corresponding to low-level features,shows better transferability than the second and third convolutional stages,which extract high-level and more image-or task-oriented features.It was also confirmed that the multi-seasonal information can improve the accuracy of LCZ classifica-tion.The thermal characteristics of the different LCZ classes were also analyzed based on the mapping results for China’s 32 major cities,and the experimental results confirmed the close relationship between the LCZ classes and the magnitude of the Land Surface Temperature(LST).

Deep learning-based local climate zone classification using Sentinel-1 SAR and Sentinel-2 multispectral imagery

As a newly developed classification system,the LCZ scheme provides a research framework for Urban Heat Island(UHI)studies and standardizes the worldwide urban temperature observa-tions.With the growing popularity of deep learning,deep learning-based approaches have shown great potential in LCZ mapping.Three major cities in China are selected as the study areas.In this study,we design a deep convolutional neural network architecture,named Residual combined Squeeze-and-Excitation and Non-local Network(RSNNet),that consists of the Squeeze-and-Excitation(SE)block and non-local block to classify LCZ using freely available Sentinel-1 SAR and Sentinel-2 multispectral imagery.Overall Accuracy(OA)of 0.9202,0.9524 and 0.9004 for three selected cities are obtained by applying RSNNet and training data of individual city,and OA of 0.9328 is obtained by training RSNNet with data from all three cities.RSNNet outperforms other popular Convolutional Neural Networks(CNNs)in terms of LCZ mapping accuracy.We further design a series of experiments to investigate the effect of different characteristics of Sentinel-1 SAR data on the performance of RSNNet in LCZ mapping.The results suggest that the combination of SAR and multispectral data can improve the accuracy of LCZ classification.The proposed RSNNet achieves an OA of 0.9425 when integrat-ing the three decomposed components with Sentinel-2 multispectral images,2.44%higher than using Sentinel-2 images alone.

Local climate zone mapping using remote sensing:a synergetic use of daytime multi-view Ziyuan-3 stereo imageries and Luojia-1 nighttime lightdata

The local climate zone(LCZ)scheme has been widely utilized in regional climate modeling,urban planning,and thermal comfort investigations.However,existing LCz classification methods face challenges in characterizing complex urban structures and human activities involving local climatic environments.In this study,we proposed a novel LCZ mapping method that fully uses space-borne multi-view and diurnal observations,i.e.daytime Ziyuan-3 stereo imageries(2.1 m)and Luojia-1 nighttime light(NTL)data(130 m).Firstly,we performed land cover classification using multiple machine learning methods(i.e.random forest(RF)and XGBoost algorithms)and various features(i.e.spectral,textural,multi-view features,3D urban structure parameters(USPs),and NTL).In addition,we developed a set of new cumulative elevation indexes to improve building roughness assessments.The indexes can estimate building roughness directly from fused point clouds generated by both along-and across-track modes.Finally,based on the land cover and building roughness results,we extracted 2D and 3D USPs for different land covers and used multi-classifiers to perform LCZ mapping.The results for Beijing,China,show that our method yielded satisfactory accuracy for LCZ mapping,with an overall accuracy(OA)of 90.46%.The overall accuracy of land cover classification using 3D USPs generated from both along-and across-track modes increased by 4.66%,compared to that of using the single along-track mode.Additionally,the OA value of LCZ mapping using 2D and 3D USPs(88.18%)achieved a better result than using only 2D USPs(83.83%).The use of NTL data increased the classification accuracy of LCZs E(bare rock or paved)and F(bare soil or sand)by 6.54%and 3.94%,respectively.The refined LCZ classification achieved through this study will not only contribute to more accurate regional climate modeling but also provide valuable guidance for urban planning initiatives aimed at enhancing thermal comfort and overall livabillity in urban areas.Ultimately,this study paves the way for more comprehensive and effective strategies in addressing the challenges posed by urban microclimates.

Projected Changes in the Climate Zoning of Côte d’Ivoire

This study assesses the projected changes in the climate zoning of Côte d’Ivoire using the hierarchical classification of principal components (HCPC) method applied to the daily precipitation data of an ensemble of 14 CORDEX-AFRICA simulations under RCP4.5 and RCP8.5 scenarios. The results indicate the existence of three climate zones in Côte d’Ivoire (the coastal, the centre and the north) over the historical period (1981-2005). Moreover, CORDEX simulations project an extension of the surface area of drier climatic zones while a reduction of wetter zones, associated with the appearance of an intermediate climate zone with surface area varying from 77,560 km2 to 134,960 km2 depending on the period and the scenario. These results highlight the potential impacts of climate change on the delimitation of the climate zones of Côte d’Ivoire under the greenhouse gas emission scenarios. Thus, there is a reduction in the surface areas suitable for the production of cash crops such as cocoa and coffee. This could hinder the country’s economy and development, mainly based on these cash crops.

Building climate zones of major marine islands in China defined using two-stage zoning method and clustering analysis

The current scheme of building climate zones in China generally assumes that building climate zones of island cities are identical to adjacent land stations.Consequently,building design strategies for island buildings usually refer to those developed for inland cities.This approach has to some extent hindered the energy-saving design and green development of island buildings in China.This research takes a first step on this issue by defining the building climate zones of 36 marine islands over China marine area using two-stage zoning methodology adopted by current building climate zoning standard(GB50178-1993).The meteorological data used for analysis was obtained from the National Climate Center of China over the 30-year period from 1985 to 2014.As comparison,40 coastal stations which are adjacent to the inves-tigated marine islands were also included in this study.Subsequently a more obiective techni-que-cluster analysis was operated as an effective supplement to discover the climate characteristics among different observations.The results of both methodologies consistentlyshow that among the 36 islands investigated,the majority of islands located in northern and eastern marine area belong to the same climate zones as their adjacent coastal cities.Howev-er,island cities in southern marine area cannot be assigned to any current climate zone,which was demonstrated by its distinctive climate features different from any other sites investi-gated through cluster analysis as well as different energy use patterns.Thus a new zone was defined to supplement the current building climate zoning scheme to cover marine area of China.

Clustering Analysis of the Climate in Tobacco Planting Zone of Yunnan

[Objective] The research aimed to study clustering of the six climatic factors in Yunnan tobacco planting zone. [Method] 6 meteorological elements in 89 tobacco-growing counties and 12 sub-prefectures were conducted clustering analysis. According to indicator and climate characteristics of the each type, climate in tobacco planting area of Yunnan Province was divided. [Result] Climate in tobacco planting area of Yunnan Province could be divided into eight types: Jiangchuan (24 counties, belonged to northern and central subtropical climate belts), Songming (27 counties, belonged to northern subtropical and central, south, north temperate climate belts), Tengchong (3 counties, belonged to northern subtropical climate belt), Mile (12 counties, belonged to central and southern subtropical climate belts), Qiubei (11 counties, belonged to southern subtropical climate belt), Yanjin (4 counties, belonged to central subtropical humid climate belt), Yuanjiang (4 counties, belonged to southern subtropical and northern tropical climate belts), Zhenxiong (3 counties, belonged to warm temperate and northern subtropical climate belts) were eight representatives. Among 1-8 eco-zones, domestic and foreign cities where climate reached level-one similarity were respectively 3, 1, 1, 0, 1, 1, 0 and 1, up to level-two similarity, respectively 12, 15, 3, 13, 13, 1, 5 and 3. Among 8 major ecological zones, similar distance of the city reaching level-one similarity was in the range of 0.28 to 0.45, and similar degree was the highest. Variety introduction among these places would be successful. Similar distance of the city reaching level-two similarity was between 0.51 and 1.00, and similar degree was higher. Mutual variety introduction had high successful rate in these places. [Conclusion] The research provided theoretical basis for selecting new suitable tobacco variety and optimizing tobacco variety layout in different zones.

Different environmental factors drive tree species diversity along elevation gradients in three climatic zones in Yunnan,southern China

Elevational patterns of tree diversity are well studied worldwide.However,few studies have examined how seedlings respond to elevational gradients and whether their responses vary across climatic zones.In this study,we established three elevational transects in tropical,subtropical and subalpine mountain forests in Yunnan Province,southern China,to examine the responses of tree species and their seedlings to elevational gradients.Within each transect,we calculated species diversity indices and composition of both adult trees and seedlings at different elevations.For both adult trees and seedlings,we found that species diversity decreased with increasing elevation in both tropical and subalpine transects.Species composition showed significant elevational separation within all three transects.Many species had specific elevational preferences,but abundant tree species that occurred at specific elevations tended to have very limited recruitment in the understory.Our results highlight that the major factors that determine elevational distributions of tree species vary across climatic zones.Specifically,we found that the contribution of air temperature to tree species composition increased from tropical to subalpine transects,whereas the contribution of soil moisture decreased across these transects.

Evaluation on Terrain-Climate Superiority Degree at County Level in Yunnan Province

Terrain slope and climate zone(heat zone)are important factors affecting land use zoning and agricultural production layout in mountainous areas.Using"weight grade method",a quantitative index of comprehensively evaluating terrain slope and climatic(thermal)conditions in mountainous areas was proposed:terrain-climate superiority degree(TCSD),and TCSD,terrain superiority degree(TSD),and climate superiority degree(CSD)in 129 counties(cities and districts)of Yunnan Province were measured and analyzed.The results showed that TCSD in 50.39%of counties of Yunnan Province was relatively better(levels I and II),and TCSD in 38.76%of counties was moderate(level III),while TCSD in 10.85%of counties was relatively poorer(levels IV and V).

Dry/wet climate zoning and delimitation of arid areas of Northwest China based on a data-driven fashion

The division of arid areas is important in water and land resources management, planning and for a long-term agricultural, economic and social planning. Northwest China （NW） dominates the main arid areas in China. There is thus a need to adopt adequate concepts relative to the scope of arid areas of NW China and identify its climate types and characteristics. In this study, we analyzed climatic data over the last 30 years （1981-2010） from 191 stations in three provinces and three autonomous regions of NW China. The factor-cluster analysis technique （FC）, an objective and automated method was employed to classify the dry/wet climate zones. The traditional methods with predefined thresholds were adopted for providing a comparison with FC. The results showed that the wet/dry climate zones by FC were mainly distributed along mountains, rivers and desert borders. Climate-division boundaries relied heavily on the major terrain features surrounding the grouped stations. It also showed that the climate was dry in the plain sandy areas but relatively wet in the high mountain areas. FC method can reflect the climate characteristics more fully in NW China with varied and complicated topography, and outperform the tradi- tional climate classifications. Arid areas of NW China were defined as four climate types, including five resultant classes in FC classifications. The Qinling and Da Hinggan Mountains were two important boundaries, besides main administrative boundaries. The results also indicated that there are some differences between two traditional clas- sifications. The precipitation moved and fluctuated to an extent, which confirmed that climate change played an important role in the dry/wet climate zoning, and the boundaries of dry/wet climate zones might change and migrate with time. This paper is expected to provide a more in-depth understanding on the climate characteristics in arid areas of NW China, and then contribute to formulate reasonable water and land management planning and agri- cultural production programs.