atmosphere

Article Numerical Study of the Interaction between Oasis and Urban Areas within an Arid Mountains- System in Xinjiang, China

Peng Cai 1,2,3,4 , Rafiq Hamdi 1,5 , Huili He 1,2,3,4, Geping Luo 1,3,6,*, Jin Wang 7, Miao Zhang 1 , Chaofan Li 8, Piet Termonia 5,9 and Philippe De Maeyer 2,4

1 State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China; [email protected] (P.C.); rafi[email protected] (R.H.); [email protected] (H.H.); [email protected] (M.Z.) 2 Department of Geography, Ghent University, Gent 9000, Belgium; [email protected] 3 University of Chinese Academy of Science, Beijing 100094, China 4 Sino-Belgian Joint Laboratory of Geo-information, Urumqi 830011, China; Gent 9000, Belgium 5 Royal Meteorological Institute of Belgium, 1180 Brussels, Belgium; [email protected] 6 Research Center for Ecology and Environment of Central Asia, Chinese Academy of Sciences, Urumqi 830011, China 7 Remote Sensing Center of Xinjiang Meteorological Bureau, Urumqi 830011, China; [email protected] 8 Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disaster, School of Geographic Sciences, Nanjing University of Information Science and Technology, Nanjing 210044, China; [email protected] 9 Department of Physics and Astronomy, Ghent University, Gent 9000, Belgium * Correspondence: [email protected]; Tel.: +86-991-7823-127

 Received: 2 December 2019; Accepted: 7 January 2020; Published: 10 January 2020 

Abstract: The rapid oasis expansion and urbanization that occurred in Xinjiang province (China) in the last decades have greatly modified the land surface energy balance and influenced the local circulation under the arid mountains-plain background system. In this study, we first evaluated the ALARO regional climate model coupled to the land surface scheme SURFEX at 4 km resolution using 53 national climatological stations and 5 automatic weather stations. We found that the model correctly simulates daily and hourly variation of 2 m temperature and relative humidity. A 4-day clear sky period has been chosen to study both local atmospheric circulations and their mutual interaction. Observations and simulations both show that a low-level divergence over oasis appears between 19:00 and 21:00 Beijing Time when the background mountain-plain wind system is weak. The model simulates a synergistic interaction between the oasis-desert breeze and urban-rural breeze from 16:00 until 22:00 with a maximum effect at 20:00 when the downdraft over oasis (updraft over urban) areas increases by 0.8 (0.4) Pa/s. The results show that the oasis expansion decreases the nocturnal in the of Urumqi by 0.8 ◦C, while the impact of urban expansion on the oasis cold island is negligible.

Keywords: oasis-desert breeze circulation; urban-rural breeze circulation; urban heat island; town energy balance

1. Introduction Formed by the runoff from the mountains under arid climate and desert background, the oasis is a medium or small scale intrazonal landscape [1], which is the basis of human life and economic development in Central Asia. The distribution of the oasis in Central Asia is closely related

Atmosphere 2020, 11, 85; doi:10.3390/atmos11010085 www.mdpi.com/journal/atmosphere Atmosphere 2020, 11, 85 2 of 20 to the topography which is characterized by high mountains-basin system in which the oases are established in river deltas and the widely spread in the basin [2], forming a typical landscape of Mountains-Oasis-Desert within an arid mountains-desert system. The Tianshan Mountains together with the surrounding deserts in the Xinjiang province of China contain plenty of Mountains-Oasis-Desert landscapes with different spatial scales and is one of the typical mountains-desert systems in Central Asia. The significant differences between the oases and surrounding deserts in land surface conditions, such as soil moisture conditions and vegetation type, result in great differences in heat and moisture fluxes within the convective boundary layer [3]. The intense makes the near surface temperature lower and the humidity higher over oases areas than in the surrounding deserts, making the oasis as a wet-cold island called oasis cold island (OCI) effect or oasis effect [4,5]. The OCI effect, which has already been confirmed by observational and numerical simulations studies [6–8], is thought to have an important impact on the sustainability of oasis [9–12]. In fact, the OCI effect may generate local atmospheric circulation called oasis-desert breeze circulation (OBC) [13], with a low-level divergent flow from the oasis to the surroundings desert and a convergent flow in the upper boundary layer. The oasis-desert breeze circulation can protect the oasis in two ways: The updraft over the surrounding desert reduces low-level hot and dry air flowing from the desert to the oasis, and at the same time, the downdraft increases the atmospheric static stability that reduces the oasis evapotranspiration [10,14,15]. Moreover, the divergent flow from the oasis to the surrounding desert brings cold and wet air that helps to protect the vegetation of the desert ecosystem [16–18]. The oasis-desert interactions have been summarized by Li et al. [13]. The oasis effect and the corresponding oasis-desert breeze circulation are critically dependent on the background wind and synoptic forcing [5,19–21] and can be observed only when there is weak synoptic forcing. However, in the mountains-plain system, when the synoptic forcing is weak, mountains induce local winds called mountain-plains wind system, with mountain wind blowing from the mountains to the plain during nighttime and plain wind blowing from the plain to the mountains during the day [22]. However, in the recent literature, only Zhang et al. [18] studied the impacts of the mountains on the oasis effect by numerical simulations and found that the oasis breeze circulation is counteracted by the strong prevailing westerly wind and that the mountain-plains wind system pushes the oasis effects to the surrounding desert. Moreover, with the development of the population, economy and technology, the oasis area in the north slope of Tianshan Mountains has increased more than 4 times since the 1950s, resulting in a significant land-use and land-cover change and intensive urbanization [23,24]. This intense land use and land cover change has altered the land surface properties, such as , leaf area index and roughness length, resulting in the change of surface energy budget that may affect the oasis-desert breeze and local climate [25]. Besides, as it is widely known, the urbanization produces the urban heat island (UHI) effect, which is characterized by warmer temperatures in the city than in the surrounding rural areas and may generate the urban–rural breeze circulation (UBC) with low-level convergent flow toward the city and divergent flow in the upper boundary layer [26,27]. In the north of Tianshan Mountains both the oasis–desert breeze circulation and the urban–rural breeze circulation may interact with each other; however, to the knowledge of the authors, no previous studies explored the interaction between both circulations in the background of a mountains-plain system. Therefore, this study aims to (1) explore the dynamic of the oasis-desert breeze circulation in the context of a mountain-plain system using both field observations and numerical model simulations, (2) study the interaction between oasis–desert breeze circulation and urban–rural breeze circulation and their synergetic interaction, and (3) examine the historical oasis expansion induced OCI effect and urbanization induced UHI effect. Atmosphere 2020, 11, 85 3 of 20

2. Experiments

2.1. Study Area The Tianshan Mountains, which is the largest mountain range in the world arid area, is located in the hinterland of Central Asia. It lies in the central part of Xinjiang province (China) and is surrounded by two deserts, Gurbantunggut desert in the north and Taklimakan desert in the south, forming several typical mountains-desert systems. The oases in the north slope of Tianshan Mountains were first developed in the groundwater overflow zone and then were extended along the rivers, where resource wasAtmosphere abundant 2020, 11, [x1 FOR,24 PEER]. REVIEW 3 of 20 With the rapid development of the economy and the increase of the population, the anthropization forming several typical mountains-desert systems. The oases in the north slope of Tianshan of the oasisMountains area in were the first north developed slope in of the Tianshan groundwater Mountains overflow zone has and increased then were extended more than along four times since the 1950s,the rivers, resulting where water in aresource significant was abundant land [1,2 use4]. and land cover change including an intensive urbanization [23With,24 ].the Our rapid study development area includes of the theeconomy oases and areas the andincrease their of surrounding the population, deserts the and the anthropization of the oasis area in the north slope of Tianshan Mountains has increased more than mountainousfour areas timesin since the the north 1950s, slope resulting of Tianshan in a significant Mountains land use (withand land average cover change height including about 4000an m above sea level (asl),intensive highest urbanization point Thomuer [23,24]. Our 7439 study m area asl includes and lowest the oases point areas 154 and m their below surrounding sea level). deserts It is situated 2 between 84and◦50 0theE mountainous and 89◦080 areasE and in the 46 north◦150 slopeN and of Tianshan 43◦180 N,Mountains with a (with total average area ofheight 99,792 about km 4000 (Figure1a). This regionm has above a sea typical level (asl), continental highest point arid Thomuer and semi-arid7439 m asl and climate, lowest point with 154 a m mean below annualsea level). temperatureIt is situated between 84°50′ E and 89°08′ E and 46°15′ N and 43°18′ N, with a total area of 99,792 km2 around 6 ◦C(Figure and an1a). annualThis region precipitation has a typical amountcontinental around arid and 220 semi mm.-arid climate, In the pastwith a 50 mean years, annual the climate in this regiontemperature had a warmer around and 6 °C wetter and an trendannual precipitation [28–30], which amount will around continue 220 mm. under In the futurepast 50 years, climate change conditionsthe [31 climate]. Our in study this region area had contains a warmer 2 oasesand wetter covering trend [28 a– total30], which area will of c 220ontinue75 under km future and 40 25 km climate change conditions [31]. Our study area contains 2 oases covering a total area× of 220 × 75 km × (Figure1c).and The 40 analyses × 25 km (Figure in this 1c). study The analyses mainly in this focus study on mainly the first focus big on the oasis. first big oasis.

Figure 1. TheFigure two-nested 1. The two-nested ALARO ALARO modeling modeling domains, D1 D1and andD2 (a D2), and (a ),the and locations the locationsof the of the meteorologicalmeteorological stations stations in Xinjiang in Xinjiang province province (b ()b) and and the study study area area (c). The (c). shaded The shaded contour represents contour represents topography; the validation stations in (b,c) are national (climatological) and automatic weather topography;stations, the validation respectively. stations The red indotted (b,c and) are black national lines in (climatological)(c) represent the boundary and automatic of oasis and weather , stations, respectively.respectively The red. dotted and black lines in (c) represent the boundary of oasis and cities, respectively.

Atmosphere 2020, 11, 85 4 of 20

Daily observations from 53 national meteorological stations distributed over the Xinjiang province (see domain D2 in Figure1b), are used to validate the simulation results of 2 m mean, maximum and minimum air temperature and relative humidity from the 4 km runs during the summer (June, July and August) season of 2016. Considering the availability and integrity of the observation data, another 5 automatic meteorological stations distributed in the analysis area are used to validate the hourly output during the longest clear sky period (between 9 and 12 June) in the summer of 2016 (Figure1c). Among the 5 automatic meteorological stations, 4 stations (S1–S4) are distributed in the north, west, south and east boundaries, respectively. These 4 stations are used to detect the oasis breeze circulation. Another station (S5), which is located in the mountains, is used to detect the background mountain-plain winds.

2.2. Model Description and Configuration The climate model ALARO-0 is the newer version (version 0) of the Aire Limitée Adaptation Dynamique Développement International (ALADIN) model that has been updated with physical parameterizations to enable simulations at 3–10 km mesh-size [32,33]. The ALADIN model, which is the limited area model version of the global scale Action de Recherche Petite Echelle Grande Echelle Integrated Forecast system (ARPEGE-IFS) [34], has been further developed with updated parameterizations for the physics part, such as the microphysics processes, and widely used in weather prediction and regional climate modelling [33,35–39]. ARPEGE-IFS, used both at Météo-France and ECMWF (European Centre for Medium-Range Weather Forecasts), is a global spectral model with a Gaussian grid for the gird-point calculations. The vertical discretization in ARPEGE-IFS is done according to a following-terrain pressure hybrid coordinate [33]. The ALARO-0 model has been used at the Royal Meteorological Institute of Belgium for the operational numerical weather prediction applications since 2010. The land surface parameterization, which describes the exchanges of energy and water between the soil surface, vegetation and low-level atmosphere [40,41], is a key parameterization in regional climate modelling. The Météo-France SURFace Externalisée land surface model (SURFEX) [42], which consists of the ISBA (Interactions between Soil, Biosphere and Atmosphere) [43] scheme for natural surfaces and the TEB (Town Energy Balance) [44] scheme for urban surfaces, has been implemented in the ALARO-0 model [45]. The combined ALARO-SURFEX model has shown its potential for representing the regional climate and land surface processes [38,46–48]. In this study, the ALARO model is driven by the global reanalysis dataset ERA-Interim produced by the European Centre for Medium-Range Weather Forecasts with a spatial resolution of 0.75 ◦ × 0.75 [49] at 6 h interval and run at a horizontal resolution of 50 km with 169 117 grid points within ◦ × a domain that encompasses most of Asia (D1 in Figure1a). The aim is to participate later to the CORDEX-CA exercise (http://www.cordex.org/domains/region-8-central-asia/). Then, the outputs were used to drive the ALARO-SURFEX model on a smaller domain nested within the outer domain (D1) at a horizontal resolution of 4 km with 500 500 grid points (D2 in Figure1a,b). This inner × domain (D2) covers the three Mountains that are Altai Mountains in the north, Tianshan Mountains in the central and Kunlun Mountains in the south of Xinjiang province and the north part of the Tibetan Plateau to capture the synoptic-scale features. Our main region of interest is located in the central area of the inner domain, which consists of the typical mountain-oasis-desert system in the North Slope of Tianshan Mountains (Figure1c). Considering the facts that the physical parameterizations for ALARO used in both the 50 km and 4 km runs are identical and our analysis area that lies at the very center of the 4 km domain is very small compared to the total 4 km domain, which already eliminate a major source of mismatches between 50 and 4 km runs [50,51], we perform the downscaling from 50 to 4 km directly without an intermediate resolution domain. Hamdi et al. [35] and De Troch et al. [36] come to the same conclusion when running ALARO over western Europe with 50 and 4 km spatial resolutions finding that an intermediate domain at 10 km did not add value. Atmosphere 2020, 11, x FOR PEER REVIEW 5 of 20

2.3. Mapping of Land Use Land Cover Types The ECOCLIMAP dataset provides both the land cover data at 1 km horizontal resolution and its corresponding land surface parameters as input for the SURFEX land surface model [52]. In the original version of ECOCLIMAP-I/II [53], the land cover is divided into 243/573 types based on satellite observations (Figure 2a). However, the land cover data derived from AVHRR data from 1992 to 1993 failed to represent correctly the current land cover states in Xinjiang region because of the human activities and rapid expansion of the oasis (Figure 2b). Therefore, the ECOCLIMAP land cover within Xinjiang region has been updated using the independent local data generated by the Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences (Figure 2b). The implementation of the local land cover data set into ECOCLIMAP has been done in a few steps: (i) the original shape file was converted into raster file with a horizontal resolution of 20 m, (ii) the horizontal resolution of the data set was up-scaled from 20 m to 1 km (by selecting the most abundant land cover type), corresponding to the spatial resolution of ECOCLIMAP, (iii) ECOCLIMAP land covers have been then used within this study (for example oasis and cities are assigned to irrigated crops and urban and built-up covers, respectively in ECOCLIMAP; see Figure 2b) together with their corresponding physical parameters, such as albedo, leaf area index, roughness Atmosphere 2020, 11, 85 5 of 20 length and emissivity. For technical reasons, we updated most of the default land cover data over Xinjiang using a rectangle window which result in some sharp boundaries especially in the east part 2.3.of Xinjiang Mapping (Figure of Land 2b). Use However, Land Cover this Types will have a negligible effect on our study region. As it is clearly shown in Figure 2, the significant change between the default and the updated The ECOCLIMAP dataset provides both the land cover data at 1 km horizontal resolution and land cover map concerns mainly the rapid expansion of oasis and urban areas, which occurred mainly its corresponding land surface parameters as input for the SURFEX land surface model [52]. In the in the north and east parts within the oasis boundary. For example, in the default database, the oasis original version of ECOCLIMAP-I/II [53], the land cover is divided into 243/573 types based on satellite area covers only 46% of the total oases areas in the updated database, and it is concentrated mainly observations (Figure2a). However, the land cover data derived from AVHRR data from 1992 to 1993 in the western part with small scale oases spreading near to the lower mountains in the southern part failed to represent correctly the current land cover states in Xinjiang region because of the human (Figure 2a). With the acceleration of industrialization and the rise of population, Urumqi, the biggest activities and rapid expansion of the oasis (Figure2b). Therefore, the ECOCLIMAP land cover within city in Xinjiang province, has experienced a rapid urbanization and expanded around three times Xinjiang region has been updated using the independent local data generated by the Xinjiang Institute since the beginning of 1990s (Figure 2b). Compared to Urumqi, Shihezi, a smaller city located near to of Ecology and Geography, Chinese Academy of Sciences (Figure2b). the south boundary of oasis, expanded from 6.3 km2 to 52 km2.

Figure 2. The default land cover data from ECOCLIMAP (a) and the updated land cover data using Figure 2. The default land cover data from ECOCLIMAP (a) and the updated land cover data using the XIEG land cover database (b). The zoom-in figures (a1,b1), (a2,b2) show the land cover in oasis and the XIEG land cover database (b). The zoom-in figures (a1,b1), (a2,b2) show the land cover in oasis Urumqi, respectively. and Urumqi, respectively. The implementation of the local land cover data set into ECOCLIMAP has been done in a few steps: (i) the original shape filewas converted into raster file with a horizontal resolution of 20 m, (ii) the horizontal resolution of the data set was up-scaled from 20 m to 1 km (by selecting the most abundant land cover type), corresponding to the spatial resolution of ECOCLIMAP, (iii) ECOCLIMAP land covers have been then used within this study (for example oasis and cities are assigned to irrigated crops and urban and built-up covers, respectively in ECOCLIMAP; see Figure2b) together with their corresponding physical parameters, such as albedo, leaf area index, roughness length and emissivity. For technical reasons, we updated most of the default land cover data over Xinjiang using a rectangle window which result in some sharp boundaries especially in the east part of Xinjiang (Figure2b). However, this will have a negligible effect on our study region. As it is clearly shown in Figure2, the significant change between the default and the updated land cover map concerns mainly the rapid expansion of oasis and urban areas, which occurred mainly in the north and east parts within the oasis boundary. For example, in the default database, the oasis area covers only 46% of the total oases areas in the updated database, and it is concentrated mainly in the western part with small scale oases spreading near to the lower mountains in the southern part (Figure2a). With the acceleration of industrialization and the rise of population, Urumqi, the biggest city in Xinjiang province, has experienced a rapid urbanization and expanded around three times since the beginning of 1990s (Figure2b). Compared to Urumqi, Shihezi, a smaller city located near to the south boundary of oasis, expanded from 6.3 km2 to 52 km2. Atmosphere 2020, 11, 85 6 of 20

2.4. Set-Up for Modeling-Based Sensitivity Study In this study, 4 sensitivity simulations are conducted. The 4 simulations are performed with identical initial meteorological conditions, physical schemes and lateral boundary conditions but with different land-use types (see Table1). In the control (CTL, New_URB) experiment, the land cover is updated, representing the current state of the land cover map in Xinjiang region, especially the oasis and urban distribution in the North Slope of Tianshan Mountains. The single-layer version of the town energy balance (TEB) scheme is then activated. In New_NoURB, the land cover is kept the same as in the CTL simulation except that the urban areas are replaced by the surrounding natural land cover type such as shrub land and grass land. In Def_NoURB, the default ECOCLIMAP land cover data are used with the urban areas replaced by surrounding land covers. Finally, in Def_URB, the default ECOCLIMAP land cover data are used except that the urban areas are updated representing the current state of urbanization and the single-layer version of the TEB scheme is then activated. The configurations of land cover for these experiments are summarized in Table1. In each simulation, all the surface parameters (albedo, leaf area index, roughness height, building height, etc.) needed as input for the ISBA and TEB scheme are extracted from the ECOCLIMAP database. The oasis expansion effects (OASIS_Eff), urbanization effects either under default (URBAN_Eff_Def) or current state (URBAN_Eff_New) of oasis land cover and their combined effects (COMBI_Eff) can be derived from the difference of New_NoURB—Def_NoURB, Def_URB—Def_NoURB, CTL—New_NoURB and CTL—Def_NoURB, respectively (see Table1).

Table 1. Numerical experiments set-up.

Experiment Oasis Cover Urban Cover New_URB (CTL) updated updated (TEB on) New_NoURB updated replaced by surrounding Def_NoURB default replaced by surrounding natural vegetation (TEB off) Def_URB default updated (TEB on) OASIS_Eff = New_NoURB Def_NoURB oasis expansion effect − URBAN_Eff_New = CTL New_NoURB urban effect in present oasis condition − URBAN_Eff_Def = Def_URB Def_NoURB urban effect in default oasis condition − COMBI_Eff = CTL Def_NoURB oasis expansion and urbanization effect −

All simulations were initialized on 1 March 2016 and a 3-month spin-up period was used before the start of the analysis on 1 June, in order to ensure model equilibrium between external forcing and internal dynamics, especially in terms of soil variables [38]. A period of 3 months was sufficient for the deep soil moisture to reach equilibrium state (not shown). More details about the downscaling configuration used in this study can be found in reference [38]. A period of 4 days from 9 to 12 June 2016 has been chosen in order to investigate the interaction between the OBC and the UBC. This period is characterized by clear sky with no precipitation, long sunshine duration and weak background winds. With the aim of being able to represent correctly the different local circulations when running the model at high spatial resolution within the study domain, we focus only on the evaluation of the 4 km simulations.

3. Results and Discussions

3.1. Evaluation of ALARO-SURFEX over Xinjiang The CTL simulation has been validated at daily scale during the summer (June, July and August) of 2016 by comparing the model outputs with 53 national meteorological stations (http://cdc.cma.gov.cn) located in the Xinjiang province (Figure1b). The hourly validations for 2 m temperature and relative humidity of the 5 automatic meteorological stations are conducted during the 4 clear sky days (9–12 June) (Figure1c). We use mean bias error (MBE), root mean square error (RMSE) and correlation coefficients (R2) to evaluate the overall model performance at 4 km spatial resolution. Atmosphere 2020, 11, 85 7 of 20

Atmosphere 2020, 11, x FOR PEER REVIEW 7 of 20 The mean MBEs averaged over all the 53 stations are 4.12%, 1.62 C, 3.69 C and 0.54 C − − ◦ − ◦ − ◦ for dailyThe relative mean MBEs humidity averaged (RH), over daily all 2 the m mean,53 stations maximum are −4.12%, and minimum −1.62 °C, − temperature,3.69 °C and − respectively0.54 °C for (Tabledaily2 relative). Thus, humidity overall, the(RH), model daily simulations 2 m mean, underestimatemaximum and minimum the daily 2temperature, m mean, maximum respectively and minimum(Table 2). temperatureThus, overall, and the relative model simulations humidity (Figure underestimate3). As shown the daily by the2 m RMSE mean, values, maximum the errorand magnitudeminimum intemperature summer maximum and relative temperature humidity (3.86 (Figure◦C) 3). tends As toshown be larger by the than RMSE minimum values, temperature the error (1.11magnitude◦C) indicating in summer that maximum the correct temperature simulation (3.86 of maximum °C) tends temperatureto be larger than is more minimum challenging temperature during the(1.11 summer °C) indicating (see values that the for correct R2 in Table simulation2). The of underestimationmaximum temperature of the is maximum more challenging temperature during is mainlythe summer caused (see by twovalues aspects. for R One2 in Table aspect 2) is. theThe diunderestimationfficulties in reproducing of the maximum the cloud temperature cover correctly is duringmainly the caused summer by two for aspects. regional One climate aspect model is the ALARO,difficulties which in reproducing always gives the cloud more cover cloud. correctly Another isduring ALARO the overestimated summer for regional the soil climate moisture model in ALARO our study, which area, always resulting gives in more the underestimation cloud. Another is of maximumALARO overestimated temperature andthe overestimationsoil moisture in ofour relative study humidity.area, resulting Our in team the isunderestimation working on a newof irrigationmaximum scheme temperature in SURFEX and tooverestimation reproduce correctly of relative the soil humidity. moisture. Our Except team for is theseworking two aspects,on a new the complexirrigation terrain scheme in in our SURFEX study area to reproduce may contribute correctly to the the soil biases moisture. to some Except extent. for However, these two theaspects, cloud the complex terrain in our study area may contribute to the biases to some extent. However, the cloud cover misrepresentation-induced biases in maximum temperature are the same for oasis and desert cover misrepresentation-induced biases in maximum temperature are the same for oasis and desert stations. Therefore, this bias in maximum temperature has little influence on OCI. For the UHI, the stations. Therefore, this bias in maximum temperature has little influence on OCI. For the UHI, the high intensity normally takes place during the night. Therefore, the minimum temperature is more high intensity normally takes place during the night. Therefore, the minimum temperature is more important for UHI, which is well simulated in Figure3c. Previous downscaling studies have shown important for UHI, which is well simulated in Figure 3c. Previous downscaling studies have shown error magnitudes comparable to or lower than those computed in previous studies [18,54]. error magnitudes comparable to or lower than those computed in previous studies [18,54].

Figure 3. Comparisons of the observed and simulated (CTL) average (a) relative humidity, (b) maximum temperature,Figure 3. Com (c)parisons minimum of temperature the observed and and (d )simulated mean temperature (CTL) average over all (a the) relative 53 national humidity, stations (b) in maximum temperature, (c) minimum temperature and (d) mean temperature over all the 53 national the summer of 2016. stations in the summer of 2016.

AtmosphereAtmosphere 20202020, 11, ,11 x ,FOR 85 PEER REVIEW 88 of of 20 20

Table 2. Evaluation of the 4 km simulation for the summer of 2016 using the 53 stations. Table 2. Evaluation of the 4 km simulation for the summer of 2016 using the 53 stations. Variable MBE RMSE R2 Variable MBE RMSE R2 Maximum Temperature −3.69 (°C) 3.86 0.76 Maximum Temperature 3.69 ( C) 3.86 0.76 Minimum Temperature− −◦ 0.54 (°C) 1.11 0.75 Minimum Temperature 0.54 ( C) 1.11 0.75 − ◦ MeanMean Temperature Temperature 1.62 (−C)1.62 (°C) 1.901.90 0.77 0.77 − ◦ RelativeRelative Humidity Humidity 4.12 (%)−4.12 (%) 6.536.53 0.40 0.40 −

FigureFigure 4 shows4 shows that that the the model model can can reproduce reproduce the dynamicdynamic of of the the hourly hourly RH RH and and 2 m2 m temperature temperature 2 (T2m)(T2m) very very well well with with R R of2 of 0.82 0.82 and and 0.93 0.93 as as average average over over the 5 automatic weatherweather stations. stations. The The model model slightlyslightly overestimates overestimates the the hourly hourly RH RH while while it it underestimates underestimates the hourlyhourly T2mT2m with with the the MBE MBE of of 0.96% 0.96% andand −2.352.35 °C forC for RH RH and and T2m, T2m, respectively respectively ( (FigureFigure 44).). SimilarSimilar withwith the the daily daily scale scale validation, validation, the the − ◦ modelmodel reproduces reproduces minimum minimum T2m T2m better better than than the the maximum T2mT2m inin thethe 4 4 clear clear sky sky days days (Figure (Figure4b). 4b).

Figure 4. Comparisons of the observed and simulated (CTL) average relative humidity (a); 2 m Figure 4. Comparisons of the observed and simulated (CTL) average relative humidity (a); 2 m temperature (b) over all the 5 automatic stations in the 4 clear-sky days of 9–12 June. temperature (b) over all the 5 automatic stations in the 4 clear-sky days of 9–12 June. From the comparison between the simulated and observed hourly wind direction and speed, From the comparison between the simulated and observed hourly wind direction and speed, the model can capture correctly the hourly variation of the wind direction an average MBE of 7.58◦ the(Figure model5 ).can However, capture thecorrectly model failedthe hourly to reproduce variation the of hourly the wind wind direction speed variation an average with MBE an average of 7.58° 1 (FigureMBE 5 of). However,0.44 m s− the(Figure model5). failed to reproduce the hourly wind speed variation with an average MBE of −0.44− m s−1 (Figure 5).

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Figure 5. The hourly wind direction and wind speed validation at the 4 boundary stations during 9–12 Figure 5. The hourly wind direction and wind speed validation at the 4 boundary stations during 9– June 2016. 12 June 2016. 3.2. The Oasis–Desert Breeze Circulation in the Context of the Mountain-Desert System 3.2. The Oasis–Desert Breeze Circulation in the Context of the Mountain-Desert System 3.2.1. The Mountain-Plain Wind System 3.2.1. The Mountain-Plain Wind System Induced by the thermal difference between mountains and basins, there are upslope winds during the dayInduced time and by downslope the thermal winds difference (mountain between wind) mountains during the nightand basins, time [22 there]. The are station upslope observation winds S5during in the the mountains day time (seeand Figuredownslope1c) and winds the CTL (mountain simulation wind) present during the the mountain-plain night time [22] wind. The system station clearlyobservation (Figure S56 a–d).in the At mountains the mountain (see stationFigure 1c) S5, theand wind the CTL direction simulation changes present from upslopethe mountain winds-plain that startwind around system 09:00–10:00 clearly (Figure Beijing 6a Time–d). (BJT)At the and mountain downslope station winds S5, that the start wind around direction 23:00 changes BJT. The f CTLrom simulationupslope winds fits very that well start to around the observations 09:00–10:00 and Beijing reproduces Time correctly(BJT) and the downslope start of both winds mountain that start and plainaround circulations 23:00 BJT. (Figure The CTL6a–d). simulation However, fits the very simulated well to the wind observations speeds are and lower reproduces than the observations correctly the 1 withstart anof both average mountain MBE of and1.04 plain m scirculations− . (Figure 6a–d). However, the simulated wind speeds are lower than the observations− with an average MBE of −1.04 m s−1. 3.2.2. Oasis–Desert Breeze Circulation 3.2.2. Oasis–Desert Breeze Circulation We used 4 weather stations that are located at the north (S1), west (S2), south (S3) and east (S4) boundariesWe used of the4 weather oasis area stations to explore that are the located OBC (Figure at the1 c).north According (S1), west to (S2), previous south studies (S3) and [ 10 east,11], (S4) the oasisboundaries wet–cold of the island oasis eff areaect induces to explore the OBCthe OBC with (Figure low-level 1c). divergence According andto previous high-level studies convergence. [10,11], Sothe when oasis there wet– iscold strong island low-level effect divergenceinduces the occurs, OBC the with wind low should-level blowdivergence out from and the oasishigh-level area atconvergence. the 4 stations So simultaneously,when there is strong which low means-level that, divergence according occurs, to the the boundary wind should direction, blow theout windfrom directionsthe oasis area should at the vary 4 stations within simultaneously, 90◦ to 300◦, 0◦ towhich 180◦ means, 270◦ to that, 90◦ accordingand 180◦ to the 360 boundary◦ at the north, direction, west, souththe wind and directions east boundaries, should vary respectively. within 90° to 300°, 0° to 180°, 270° to 90° and 180° to 360° at the north, west,The south analysis and east of theboundaries, observed respectively. wind directions at the oasis boundary stations indicate that the appearanceThe analysis time and of the duration observed of the wind oasis directions divergence at arethe di oasisfferent boundary in each daystations (Figure indicate6e–h). Duringthat the theappearance study period, time and the duration earliest appearance of the oasis timedivergence of the clearare different divergence in each is at day 10:00 (Figure BJT on 6e 9–h). June During 2016, andthe study the latest period, appearance the earliest time appearance is at 19:00 time BJT of on the 12 clear June divergence 2016; the longest is at 10:00 duration BJT on lasts 9 June 11 2016 h on, 11and June the 2016,latest and appearance the shortest time duration is at 19:00 only BJT last on 3 h12 on June 12 June2016; 2016 the longest (Figure6 duratione–h). During lasts the11 h 4 days,on 11 theJune common 2016, and duration the shortest when duration the divergence only last occurs 3 h on is from12 June 19:00 2016 to 21:00(Figure BJT. 6e Therefore,–h). During contrarily the 4 days, to the common duration when the divergence occurs is from 19:00 to 21:00 BJT. Therefore, contrarily to previous studies [13,18], the low level divergence over oasis appears only between 19:00 and 21:00

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Atmosphere 2020, 11, x FOR PEER REVIEW 10 of 20 previous studies [13,18], the low level divergence over oasis appears only between 19:00 and 21:00 BJT BJT when the background mountain-plain wind system is weak during the late afternoon transition when the background mountain-plain wind system is weak during the late afternoon transition period. period.

Figure 6. The observed (S5) and simulated (M5) hourly wind direction in the mountain station and the Figure 6. The observed (S5) and simulated (M5) hourly wind direction in the mountain station and hourly observed wind direction in the oasis boundary stations (S1–S4). (a–d,e–h) present the four days: the hourly observed wind direction in the oasis boundary stations (S1–S4). (a–d,e–h) present the four 9, 10, 11 and 12 of June 2016; the green arrows present the mountain wind and the black arrows present days: 9, 10, 11 and 12 of June 2016; the green arrows present the mountain wind and the black arrows the plain wind (a–d); the red arrows show the obvious period where a divergent flow is observed (e–h). present the plain wind (a–d); the red arrows show the obvious period where a divergent flow is 3.3. Synergisticobserved (e Interaction–h). between the OBC and the UBC

3.3.1.3.3. Synergistic Spatial Distribution Interaction between of Temperature the OBC andand the Wind UBC at the Lowest Model Level Being the closest to the observations, the 11 June 2016 is chosen for further analysis on both 3.3.1. Spatial Distribution of Temperature and Wind at the Lowest Model Level oasis–desert and urban–rural breezes and their mutual interaction from the CTL simulation. Figure7a–c presentsBeing the the spatial closest pattern to the of observations, the simulated the wind 11 speedJune 2016 and is temperature chosen for atfurther the lowest analysis model on levelboth (20oasis m– abovedesert groundand urban level)–rural at 09:00, breezes 16:00 and and their 21:00 mutua BJT,l respectively.interaction from the CTL simulation. Figure 7a–c Atpresent 09:00s BJT,the spatial as it is clearlypattern shown of the simulated in Figure6 c,wind the windspeed pattern and temperature is controlled at bythe thelowest mountain model windlevel (20 with m no above obvious ground OBC level) or UBC at 09:00, (Figures 16:006g andand7 21:00a). The BJT, wind respectively. changes its direction between 10:00 and 11:00At 09:00 BJT BJT, with as low it is wind clearly speed show inn the in Figure mountains 6c, the (Figure wind6 patternc). From is 12:00 controlled to 18:00 by BJT, the themountain wind patternwind with is controlled no obvious by OBC the or plain UBC wind (Figures (Figures 6g and6c and 7a).7 b)The with wind a low-levelchanges its divergence direction between center in 10:00 the westand 11:00 part ofBJT the with oasis. low wind speed in the mountains (Figure 6c). From 12:00 to 18:00 BJT, the wind pattern is controlled by the plain wind (Figures 6c and 7b) with a low-level divergence center in the west part of the oasis. Different from what has been found in the previous studies [10,11,18,21], we found here that, in agreement with the observations (see Figure 6h), the significant OBC with the low level divergence

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Different from what has been found in the previous studies [10,11,18,21], we found here that, in agreement with the observations (see Figure6h), the significant OBC with the low level divergence Atmosphere 2020, 11, x FOR PEER REVIEW 11 of 20 occurs from 19:00 to 21:00 BJT (Figure7c). As seen from Figure7b, at 21:00 BJT, the wind flows out from the oasisoccurs to from the surrounding 19:00 to 21:00 desertBJT (Figure areas 7c). through As seen each from of Figure its boundaries 7b, at 21:00 and BJT, the the divergence wind flows centerout is locatedfrom near the to oasis the oasisto the center. surrounding During desert the late areas afternoon through period each of where its boundaries the background and the mountain-plaindivergence windcenter system is islocated weak near and to in the the oasis transition center. period,During thethe OBClate afternoon transfers period water where vapor the up background to 32 km to the surroundingmountain deserts-plain wind (not system shown), is weak which and is in in the agreement transition with period, the the findings OBC transfers of Zhang water et al.vapor [18 up]. After 22:00to BJT, 32 km the to wind the surrounding direction switches deserts (not to the shown) mountain, which wind is in (Figureagreement6d). with As the the findings mountain of Zhang wind gets strong,et al. the [18] OBC. After gets 22: weak,00 BJT, and the the wind low-level direction divergence switches to disappears. the mountain wind (Figure 6d). As the mountain wind gets strong, the OBC gets weak, and the low-level divergence disappears.

FigureFigure 7. The 7. The spatial spatial patterns pattern ofs of the the simulated simulated windwind direction (vectors) (vectors) and and temperature temperature (°C, (shaded◦C, shaded −1 1 contours)contours) at the at lowestthe lowest model model level level and and their their corresponding corresponding vertical vertical velocity velocity (Pa (Pa s ) s cross− ) cross section section at at 09:0009:00 (a,d), (a 16:00,d), 16:00 (b,e ()b and,e) and 21:00 21:00 (c ,(fc),f (Beijing) (Beijing Time,Time, BJT) for for 11 11 June June 2016. 2016. The The green green line lineAB in AB (a– inc) (a–c) representsrepresents the locationthe location of theof the vertical vertical cross cross section. section. In In ( (dd––f)f,), the the violet violet shaded shaded areas areas at the at bottom the bottom of of eacheach panel panel represent represent the the terrain; terrain; along along the thex xaxis axis (from A A to to B) B),, the the yellow yellow bar bar represents represents the extent the extent of of the desert; the green bar represents the extent of the oasis; the red bar represents the extent of the the desert; the green bar represents the extent of the oasis; the red bar represents the extent of the urban urban area; the olive green bar represents the extent of mountain areas and the number represents the area; the olive green bar represents the extent of mountain areas and the number represents the width width of the land use type. of the land use type.

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3.3.2. Vertical Velocity Cross Section Figure7d–f presents the corresponding vertical velocity cross sections along AB at 09:00, 16:00 and 21:00 BJT, respectively. Figure7d shows that the vertical velocity over oasis is very weak and close 1 to 0 Pa s− at 9:00 BJT, which means no signature of the OBC yet. At 16:00 BJT (Figure7e), the updraft becomes stronger over the urban areas with mean value of 1.1 Pa s 1, which indicates the presence of − − the urban–rural breeze circulation in the afternoon in agreement with the literature [27]. Moreover, 1 there is an obvious downdraft with mean value of 1.0 Pa s− over the north part of the oasis at the border with the desert areas. However, the oasis–desert breeze circulation has not started yet due to the strong plain wind. At 21:00 BJT (Figure7f), there is an updraft center over the desert with mean value of 2.0 Pa s 1, − − which indicates the presence of the OBC between the oases areas and the surrounding deserts [13]. It is noted that although there are clear updrafts over the urban area in the cross section of the vertical velocity, there is no convergent flows in the spatial patterns of the horizontal wind (Figure7b,c). This could be due to the channeling effect, as it is clearly seen in Figure7a–c, which increases the low level wind speed over the city [55,56]. The oasis–desert breeze circulation, the urban–rural breeze circulation and their synergistic interactions can be derived from the difference of the vertical velocity as it is calculated at 20:00 BJT from NoURB—Def_NoURB (Figure8a), CTL—NoURB (Figure8c) and CTL—Def_NoURB (Figure8b), respectively. By comparing NoURB—Def_NoURB (Figure8a) and CTL—Def_NoURB (Figure8b), we can see that the downward flow (red area over oasis) is enhanced, which is induced by the existence of UBC. Similarly, by comparing CTL—Def_NoURB (Figure8b) and CTL—NoURB (Figure8c), we can find the upward flow (blue area) over the urban is enhanced as well, which means the existence of OBC can enhance the UBC. Therefore, it is clearly seen that both the UBC and OBC enhance each other. This synergistic interaction lasts from 16:00 until 22:00 BJT with a maximum effect at 20:00 BJT when 1 the UBC increases the downdraft over the oasis areas by 0.8 Pa s− and the OBC increases the updraft 1 over urban areas by 0.4 Pa s− (Figure8).

3.3.3. Vertical Specific Humidity Cross Section Figure9a–c presents the vertical specific humidity cross section. At 09:00 BJT before the oasis circulation has started, higher values of specific humidity can reach as high as 3.6 km. At lower level, the difference of the specific humidity between the oasis and desert is obvious. In the afternoon at 16:00 BJT, the oasis wet island develops as a kind of wall up to 1.2 km in the vertical with higher humidity values over oasis than in the surrounding desert area. Due to the background plain wind, the maximum wet-island effect is not found in the center of the oasis area but shifted to the border with the urban areas, with higher specific humidity values in the north part of the city of Urumqi. In the afternoon, urban areas trigger the initiation of turbulence and large eddies that increase the vertical mixing and push the wet air into high levels over the urban area. At the high atmosphere levels, the oasis is drier than the urban area [10,16]. Atmosphere 2020, 11, 85 13 of 20 Atmosphere 2020, 11, x FOR PEER REVIEW 13 of 20

1 Figure 8. The vertical cross sections of vertical velocity (Pa s− ) along AB (the green line in Figure7a) Figure 8. The vertical cross sections of vertical velocity (Pa s−1) along AB (the green line in Figure 7a) at 20:00 BJT on the 11 June 2016 computed from: (a) NoURB—Def_NoURB, (b) CTL—Def_NoURB and at 20:00 BJT on the 11 June 2016 computed from: (a) NoURB—Def_NoURB, (b) CTL—Def_NoURB (c) CTL—NoURB. The violet shaded areas at the bottom of each panel represent the terrain; along the x and (c) CTL—NoURB. The violet shaded areas at the bottom of each panel represent the terrain; along axis (from A to B) the yellow bar represents the extent of the desert; the green bar represents the extent the x axis (from A to B) the yellow bar represents the extent of the desert; the green bar represents the of the oasis; the red bar represents the extent of the urban area; the olive bar represents the extent of mountainextent of the areas oasis and; the the red number bar represents represents the the extent width of thethe landurban use area type.; the olive bar represents the extent of mountain areas and the number represents the width of the land use type. At 21:00 BJT, the extension of the oasis wet island can reach up to 20 km into the surrounding desert (Figure9c) while previous study shows that, even for a relatively smaller (30 30 km) oasis, the × circulation can reach up to 40 km into the desert [10]. The absence of background winds such as the mountain/plain wind in their study region may partly explain the difference. With the development of the OBC at the interface with the surrounding desert areas, the wet atmosphere layers are closer (less than 0.8 km for values above 9.0 10 3 kg/kg) to the oasis areas (Figure9c), helping to keep the × − wet condition of the oasis. For the desert, the OBC brings the cold and wet air into the desert, which increases the humidity of the surrounding desert and protects the desert ecosystem [13,57].

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3 Figure 9. The vertical cross sections of specific humidity (10− kg/kg) along AB (the green line in −3 Figure7 9.a) The at 09:00 vertical ( a), cross 16:00 sections (b) and of 21:00 specific (c) BJThumidity on the (10 11 June kg/kg) 2016. along The AB violet (the shadedgreen line areas in Figure at the 7a)bottom at 09:00 of each (a), panel16:00 ( representb) and 21:00 the terrain;(c) BJT on along the the11 Junex axis 2016. (from The A toviolet B) the shaded yellow areas bar representsat the bottom the ofextent each of panel the desert; represent the greenthe terrain; bar represents along the the x axis extent (from of theA to oasis; B) the the yellow red bar bar represents represents the the extent extent of ofthe the urban desert area;; the the green olive bar bar represents represents the the extent extent of of the mountain oasis; the areas red b andar represents the number the represents extent of the widthurban area of the; the land olive use bar type. represents the extent of mountain areas and the number represents the width of the land use type. 3.3.4. Surface Energy Balance At 21:00 BJT, the extension of the oasis wet island can reach up to 20 km into the surrounding Figure 10 presents the diurnal evolution of the surface energy balance in three grid points desert (Figure 9c) while previous study shows that, even for a relatively smaller (30 × 30 km) oasis, representing the city center of Urumqi Figure 10a, the center of the oasis Figure 10b and in the desert the circulation can reach up to 40 km into the desert [10]. The absence of background winds such as area Figure 10c as an average for the 11 June 2016. Note that the sign convention is positive-downwards the mountain/plain wind in their study region may partly explain the difference. With the (negative flux is cooling the surface). During daytime, the radiation difference between the city center development of the OBC at the interface with the surrounding desert areas, the wet atmosphere of Urumqi (Figure 10a) and both the center of the oasis areas (Figure 10b), and the desert location layers are closer (less than 0.8 km for values above 9.0 × 10−3 kg/kg) to the oasis areas (Figure 9c), is positive; the urban areas gain more energy, an effect mainly controlled by the low effective urban helping to keep the wet condition of the oasis. For the desert,2 the OBC brings2 the cold and wet air albedo. The midday difference is typically around +36 W m− and +112 W m− between the city center into the desert, which increases the humidity of the surrounding desert and protects the desert of Urumqi and the center of oasis and between the city center of Urumqi and the desert location, ecosystem [13,57]. 2 respectively. The net radiation in the oasis is also higher (+75 W m− ) than that in the desert location, which is in agreement with previous observational studies [12,21,58–60]. Throughout the night, both 3.3.4. Surface Energy Balance the city center of Urumqi and the desert location lose more energy than the oasis [12,21]. Daytime sensibleFigure heat 10 values presents are the more diurn thanal twiceevolution (2.4) of as largethe surface in the energy desert areasbalance as inin thethree oasis grid location. points representing the city center of Urumqi Figure 10a, the center of the oasis Figure 10b and in the desert area Figure 10c as an average for the 11 June 2016. Note that the sign convention is positive-

Atmosphere 2020, 11, x FOR PEER REVIEW 15 of 20

downwards (negative flux is cooling the surface). During daytime, the radiation difference between the city center of Urumqi (Figure 10a) and both the center of the oasis areas (Figure 10b), and the desert location is positive; the urban areas gain more energy, an effect mainly controlled by the low effective urban albedo. The midday difference is typically around +36 W m−2 and +112 W m−2 between the city center of Urumqi and the center of oasis and between the city center of Urumqi and the desert location, respectively. The net radiation in the oasis is also higher (+75 W m−2) than that in the desert Atmospherelocation, 2020which, 11, 85is in agreement with previous observational studies [12,21,58–60]. Throughout15 of the 20 night, both the city center of Urumqi and the desert location lose more energy than the oasis [12,21]. Daytime sensible heat values are more than twice (2.4) as large in the desert areas as in the oasis 2 Thelocation. sensible The heat sensible in the heat desert in the is alsodesert higher is also (+ 14higher W m −(+14at W midday) m−2 at thanmidday) that than in the that city in center the city of Urumqi.center of Urumqi. The magnitude The magnitude of maximum of maximum daytime daytime sensible sensible heat is characteristicallyheat is characteristically around around 41% of 41% the maximumof the maximum daytime daytime net radiation net radiation in the desert in the location, desert location, 29% at the 29% city at center the city of center Urumqi of and Urumqi only 14%and inonly the 14% oasis in center. the oasis center.

Figure 10. The diurnal variation of the surface energy flux on the 11 June 2016 computed from the CTL simulationFigure 10. atThe Urumqi diurnal city variation center (ofa), the oasis surface center energy (b) and flux a grid on pointthe 11 representing June 2016 computed the desert from (c). RN:the netCTL radiation; simulation H: at sensible Urumqi heat; city LE:center latent (a),heat; oasis GFlux: center ( soilb) and heat a flux.grid point Note thatrepresenting the sign conventionthe desert (c is). positive-downwardsRN: net radiation; H: (negativesensible heat; flux LE: is cooling latent heat; the surface). GFlux: soil heat flux. Note that the sign convention is positive-downwards (negative flux is cooling the surface). Daytime maximum values of soil heat flux are typically three time as large in the urban areas as in theDaytime center of maximum oasis. Daytime values maximumof soil heat valuesflux are of typically storage heatthree are time 65%, as large 60% andin the 23% urban of daytime areas as maximumin the center net of radiation oasis. Daytime at city maximum center of Urumqi, values of the storage desert heat and are oasis 65%, center, 60% and respectively. 23% of daytime In the desertmaximum location net peakradiation values at are city reached center 1–2of Urumqi, h before thethe maximumdesert and intensity oasis center, of net radiationrespectively. is reached. In the Thedesert heat location stored duringpeak values the day are is released reached during 1–2 h the befo evening,re the whichmaximum slows intensity down urban of net surface radiation cooling. is Thereached. bigger The contribution heat stored coming during from the theday storage is released heat during flux with the respect evening to, the which sensible slow heats down in the urban city ofsurface Urumqi cooling. is in agreement The bigger with contribution other observational coming from studies the storage conducted heat flux in dry with climate respect cities to the [61 ].sensible In the desertheat in location, the city theof Urumqi storage is flux in isagreement dominant with in the other morning observational while the studies sensible conducted heat flux isin dominant dry climate in thecities afternoon. [61]. In the desert location, the storage flux is dominant in the morning while the sensible heat flux Contrarilyis dominant to in the the urban afternoon. and desert location, the latent heat flux represents the dominant contribution of theCo energyntrarily partitioning to the urban in theand oasis desert center location, with maximumthe latent dailyheat valueflux represents representing the 70% dominant of the daytimecontribution maximum of the netenergy radiation. partitioning In the center in the of oasis the oasis,center at with 20:00 maximum BJT, the latent daily heat value flux representing exceeds the available70% of the net daytime radiation, maximum and the net corresponding radiation. In sensible the center heat of flux the isoasis, negative at 20:00 indicating BJT, the the latent signature heat flux of theexceed oasiss the breeze available circulation net radiation [13]. , and the corresponding sensible heat flux is negative indicating the signature of the oasis breeze circulation [13]. 3.3.5. Oasis Cold Island and Urban Heat Island Interactions 3.3.5. Oasis Cold Island and Urban Heat Island Interactions Figure 11a presents the 4-day average mean of the diurnal evolution of the maximum UHI intensityFigure over 11a both presents Urumqi the (_U) 4-day and average Shihezi (_S)mean cities. of the The diurnal maximum evolution UHI intensities of the maximum are extracted UHI fromintensity 2 m temperatureover both Urumqi differences (_U) fromand Shihezi Def_URB—Def_NoURB, (_S) cities. The maximum CTL—NoURB UHI intensities and CTL—Def_NoURB are extracted withinfrom 2 the m boundaries temperature of Urumqi differences and Shihezi from cities.Def_URB The— timingDef_NoURB, of both sunrise CTL— (SR)NoURB and sunsetand CTL (SS)— is shownDef_NoURB with verticalwithin the lines. boundaries It is clear of that Urumqi the oasis and Shihezi expansion cities decreases. The timing the nocturnalof both sunrise UHI (SR) for both and Urumqisunset (SS) and is Shihezi shown bywith 0.8 vertical◦C and 0.7lines.◦C, It respectively. is clear that Duringthe oasis the expansion daytime thedecreases oasis expansion the nocturnal has a neutral effect on Urumqi while for Shihezi, being within the oasis areas, the UHI decreases from 13:00 BJT with difference up to 0.6 ◦C during the OBC event. The combined effect of urbanization and oasis expansion has a neutral effect during the night for both cities since both effects cancel each other. However, during the day, the combined effect increases the maximum UHI in Urumqi from the early morning 09:00 BJT up to 17:00 BJT with maximum increase of 1.2 ◦C at 11:00 BJT. Atmosphere 2020, 11, x FOR PEER REVIEW 16 of 20

UHI for both Urumqi and Shihezi by 0.8 °C and 0.7 °C, respectively. During the daytime the oasis expansion has a neutral effect on Urumqi while for Shihezi, being within the oasis areas, the UHI decreases from 13:00 BJT with difference up to 0.6 °C during the OBC event. The combined effect of urbanization and oasis expansion has a neutral effect during the night for both cities since both effects cancel each other. However, during the day, the combined effect increases the maximum UHI in Atmosphere 2020, 11, 85 16 of 20 Urumqi from the early morning 09:00 BJT up to 17:00 BJT with maximum increase of 1.2 °C at 11:00 BJT.

Figure 11. TheThe 4- 4-dayday average average mean mean of ofthe the diurnal diurnal evolution evolution of (a of) the (a) maximum the maximum UHI UHIintensity intensity over overboth Urumqi both Urumqi (_U) and (_U) Shihezi and Shihezi(_S) cities (_S) extracted cities extracted from 2 m fromtemperature 2 m temperature differences difromfferences Def_URB from— Def_URB—Def_NoURB,Def_NoURB, CTL—NoURB CTL—NoURB and CTL—Def_NoURB. and CTL—Def_NoURB. The timing Theof both timing sunrise of both (SR) sunrise and sunset (SR) and(SS) sunsetis shown (SS) with is shownvertical with lines vertical and (b) linesthe maximum and (b) the OCI maximum intensity OCIover intensitythe oases’ over areas the extracted oases’ areasfrom extracted2 m temperature from 2 mdifferences temperature between differences NoURB between − Def_NoURB NoURB andDef_NoURB CTL − Def_NoURB. and CTL TheDef_NoURB. timing of − − Thethe OB timingC event of the is shown OBC event with is green shown vertical with greenlines. vertical lines.

Figure 1111bb presents presents the the 4-day 4-day average average mean mean of the of diurnal the diurnal evolution evolution of the maximum of the maximum OCI intensity OCI overintensity theoases over areasthe oases extracted areas from extracted 2 m temperature from 2 m di fftemperatureerences between differences NoURB—Def_NoURB between NoURB and— CTL—Def_NoURB.Def_NoURB and CTL The—Def_NoURB. timing of the OBCThe timi eventng isof shown the OBC with event green is shown vertical with lines. green It is vertical clear that lines. the oasis expansion decreases the near surface temperature day and night with cooling effect up to 6.3 C It is clear that the oasis expansion decreases the near surface temperature day and night with −cooling◦ duringeffect up nighttime. to −6.3 °C The during OCI nighttime. is symmetric The to OCI the is UHI symmetric with bigger to the values UHI with during bigger the nightvalues than during during the the day, with minimum cooling effect of 0.7 C in the early morning around 10:00 BJT. Between 10:00 night than during the day, with minimum− cooling◦ effect of −0.7 °C in the early morning around 10:00 andBJT. 18:00Between BJT, 10:00 with and the increase18:00 BJT of, with the afternoon the increase evapotranspiration, of the afternoon evapotranspiration, the cooling effect increases the cooling at a 1 rateeffect of increases0.4 ◦C h at− awhile rate of during −0.4 °C the h OBC−1 while event dur (19:00–21:00ing the OBC BJT) event the (19:00 cooling–21:00 rate BJT) is more the thancooling double, rate − 1 with value around 0.9 C h . The impact of the−1 urbanization derived from the difference between is more than double−, with◦ value− around −0.9 °C h . The impact of the urbanization derived from the CTL—Def_NoURBdifference between andCTL NoURB—Def_NoURB—Def_NoURB and NoURB is neutral—Def_NoURB with a slight is neutral decrease with of the a slight cooling decrease effect byof 0.1the ◦coolingC during effect the night.by 0.1 °C during the night.

4. Conclusions 4. Conclusions In this study, the oasis breeze circulation is investigated from observations and model simulations In this study, the oasis breeze circulation is investigated from observations and model in the context of the mountain-plains wind system in the North Slope of the Tianshan Mountains. simulations in the context of the mountain-plains wind system in the North Slope of the Tianshan The oasis–desert and the urban–rural breeze circulations, as well as their interactions, are investigated Mountains. The oasis–desert and the urban–rural breeze circulations, as well as their interactions, are byinvestigated using the atmosphericby using the model atmospheric ALARO model coupled ALARO to the landcoupled surface to the model land SURFEX, surface whichmodel isSURFEX applied, forwhich the is first applied time infor arid the area.first time in arid area. We improvedimproved thethe defaultdefault landland covercover datadata ofof thethe ECOCLIMAPECOCLIMAP databasedatabase usingusing thethe landland covercover data thatthat werewere generatedgenerated byby thethe XinjiangXinjiang InstituteInstitute ofof EcologyEcology andand GeographyGeography andand evaluatedevaluated thethe ALARO-SURFEX performance with 53 national meteorological stations spread in the Xinjiang province of China and 5 automatic meteorological stations in the study area. The validation results show that the model can capture the daily and hourly variation of the 2 m temperature and relative humidity in summer, although it underestimates the relative humidity and the daily 2 m temperature. This underestimation is mainly caused by two reasons. One is that the climate model ALARO gives Atmosphere 2020, 11, 85 17 of 20 more clouds resulting in the underestimation of daily maximum temperature. Another is that the ALARO-SURFEX model fails to reproduce the dynamic of soil water content. Besides, the complex terrain in our study area may contribute to the biases to some extent. Firstly, we proved the existence of the oasis breeze circulation by analyzing the wind directions from four automatic stations distributed around the oasis boundary. We found that the appearance of the low-level divergence changes in the 4 clear sky days. However, the common time in the 4 days when the significant low-level divergence appears is from 19:00 to 21:00 BJT when the background mountain-plains wind system is very weak and in transition period. After 22:00 BJT, the oasis breeze is interrupted by the strong background wind. Meanwhile, we found that the mountain wind enhances the flow from oasis to desert, which would protect the vegetation in the surrounding desert by transporting much more water vapor into the desert. The model reproduces correctly the oasis–desert circulation with negative sensible heat flux and latent heat flux bigger than the net radiation at 20:00 BJT. The model simulates a synergistic interaction between oasis–desert breeze and urban–rural breeze from 16:00 BJT until 22:00 BJT with a maximum effect at 20:00 BJT when the downdraft over oasis 1 (updraft over urban) areas increases by 0.8 (0.4) Pa s− . Oasis expansion decreases the intensity of the nocturnal UHI for both Urumqi and Shihezi cities. During the day, the oasis expansion decreases the UHI in Shihezi while its effect is neutral in Urumqi. The combined effect of both oasis expansion and urbanization is neutral during the night for both cities; however, during the day, the UHI is bigger in Urumqi while for Shihezi the effect is neutral. Finally, the oasis cold island is symmetric to the urban heat island with bigger values during the night than during the day, and the impact of urbanization is found more during the night with a slight decrease of the oasis cooling effect. The new findings from this study enhance our understanding of the interaction between oasis and urban areas under the background of a mountain-desert system in Xinjiang.

Author Contributions: Conceptualization, R.H., G.L. and P.C.; methodology, R.H. and P.C.; software, P.T.; validation, P.C., R.H. and H.H.; formal analysis, P.C.; investigation, P.C.; resources, R.H. and P.T.; data curation, P.C.; writing—original draft preparation, P.C.; writing—review and editing, P.C., C.L. and M.Z.; visualization, P.C. and J.W.; supervision, G.L., P.T. and P.D.M.; project administration, G.L.; funding acquisition, G.L. and R.H. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by the International Partnership Program of the Chinese Academy of Sciences, grant number 131965KYSB20160004, the National Natural Science Foundation of China, grant number 41671108. Rafiq Hamdi is supported by the China Academy of Sciences President’s International Fellowship Initiative (PIFI), grant number 2018VMB0006. Acknowledgments: We want to thank the editor and anonymous reviewers for their valuable comments and suggestions to this paper. Conflicts of Interest: The authors declare no conflict of interest.

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