scholarly journals Estimation of Urbanization Impacts on Local Weather: A Case Study in Northern China (Jing-Jin-Ji District)

Water ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 797 ◽  
Author(s):  
Hui-Dong Su ◽  
Xuejian Cao ◽  
Da-Cheng Wang ◽  
Yang-Wen Jia ◽  
Guangheng Ni ◽  
...  
Keyword(s):  
Large Population ◽  
Management Strategies ◽  
Wrf Model ◽  
Single Layer ◽  
Northern China ◽  
Maximum Temperature ◽  
Rapid Urbanization ◽  
Temperature And Precipitation ◽  
The Mean ◽  
Local Weather

With the past rapid economic development and large population growth, Jing-Jin-Ji District has been undergoing rapid urbanization, which has caused considerable regional weather changes in local regions. In this paper, we used the Weather Research and Forecasting (WRF) model to quantitatively analyze the effects of past urbanization and potential future urbanization on the regional weather in the center of Jing-Jin-Ji District. The hydrometeorological data from two weeks in July 2019 were used to simulate the influence of urbanization on local weather in the Jing-Jin-Ji District at regional scales using a single-layer canopy parameterization scheme. To better quantify the differences in temperature and precipitation induced by urbanization, three simulation scenarios were designed, which were no urban cover (NU), current urbanization cover (CU), and full urban land cover (FU), respectively. The results showed that: (1) Urbanization progress (from NU to CU and from CU to FU) in Jing-Jin-Ji District increased the daytime temperature, night temperature, and temperature difference between day and night, while decreasing the total rainfall and peak rainfall. (2) Compared with NU, the mean temperature of the CU and FU increased 0.3 K and 0.6 K, respectively, and the mean precipitation of CU and FU decreased by approximately 6% and 8.4%, respectively. (3) The main influence of urbanization on weather was reflected by the maximum temperature and peak rainfall, while the other impacts were relatively insignificant. (4) Compared with NU, the maximum temperature of CU and FU increased 0.82 K and 1.35 K, respectively, and the peak rainfall of NU and FU decreased by approximately 9.5% and 19.0%, respectively; The results of this study bring to light the urban management strategies for policy makers.

scholarly journals Analyses of temperature and precipitation in the Indian Jammu and Kashmir region for the 1980–2016 period: implications for remote influence and extreme events

2019 ◽  
Vol 19 (1) ◽  
pp. 15-37 ◽  
Author(s):  
Sumira Nazir Zaz ◽  
Shakil Ahmad Romshoo ◽  
Ramkumar Thokuluwa Krishnamoorthy ◽  
Yesubabu Viswanadhapalli
Keyword(s):  
Climate Change ◽  
Statistical Tests ◽  
Wrf Model ◽  
Annual Rainfall ◽  
Maximum Temperature ◽  
Seasonal Temperature ◽  
Western Himalayas ◽  
Jammu And Kashmir ◽  
Temperature And Precipitation ◽  
Average Annual Temperature

Abstract. The local weather and climate of the Himalayas are sensitive and interlinked with global-scale changes in climate, as the hydrology of this region is mainly governed by snow and glaciers. There are clear and strong indicators of climate change reported for the Himalayas, particularly the Jammu and Kashmir region situated in the western Himalayas. In this study, using observational data, detailed characteristics of long- and short-term as well as localized variations in temperature and precipitation are analyzed for these six meteorological stations, namely, Gulmarg, Pahalgam, Kokarnag, Qazigund, Kupwara and Srinagar during 1980–2016. All of these stations are located in Jammu and Kashmir, India. In addition to analysis of stations observations, we also utilized the dynamical downscaled simulations of WRF model and ERA-Interim (ERA-I) data for the study period. The annual and seasonal temperature and precipitation changes were analyzed by carrying out Mann–Kendall, linear regression, cumulative deviation and Student's t statistical tests. The results show an increase of 0.8 ∘C in average annual temperature over 37 years (from 1980 to 2016) with higher increase in maximum temperature (0.97 ∘C) compared to minimum temperature (0.76 ∘C). Analyses of annual mean temperature at all the stations reveal that the high-altitude stations of Pahalgam (1.13 ∘C) and Gulmarg (1.04 ∘C) exhibit a steep increase and statistically significant trends. The overall precipitation and temperature patterns in the valley show significant decreases and increases in the annual rainfall and temperature respectively. Seasonal analyses show significant increasing trends in the winter and spring temperatures at all stations, with prominent decreases in spring precipitation. In the present study, the observed long-term trends in temperature (∘Cyear-1) and precipitation (mm year−1) along with their respective standard errors during 1980–2016 are as follows: (i) 0.05 (0.01) and −16.7 (6.3) for Gulmarg, (ii) 0.04 (0.01) and −6.6 (2.9) for Srinagar, (iii) 0.04 (0.01) and −0.69 (4.79) for Kokarnag, (iv) 0.04 (0.01) and −0.13 (3.95) for Pahalgam, (v) 0.034 (0.01) and −5.5 (3.6) for Kupwara, and (vi) 0.01 (0.01) and −7.96 (4.5) for Qazigund. The present study also reveals that variation in temperature and precipitation during winter (December–March) has a close association with the North Atlantic Oscillation (NAO). Further, the observed temperature data (monthly averaged data for 1980–2016) at all the stations show a good correlation of 0.86 with the results of WRF and therefore the model downscaled simulations are considered a valid scientific tool for the studies of climate change in this region. Though the correlation between WRF model and observed precipitation is significantly strong, the WRF model significantly underestimates the rainfall amount, which necessitates the need for the sensitivity study of the model using the various microphysical parameterization schemes. The potential vorticities in the upper troposphere are obtained from ERA-I over the Jammu and Kashmir region and indicate that the extreme weather event of September 2014 occurred due to breaking of intense atmospheric Rossby wave activity over Kashmir. As the wave could transport a large amount of water vapor from both the Bay of Bengal and Arabian Sea and dump them over the Kashmir region through wave breaking, it probably resulted in the historical devastating flooding of the whole Kashmir valley in the first week of September 2014. This was accompanied by extreme rainfall events measuring more than 620 mm in some parts of the Pir Panjal range in the south Kashmir.

scholarly journals Response of Near-Surface Meteorological Conditions to Advection under Impact of the Green Roof

Atmosphere ◽  
2019 ◽  
Vol 10 (12) ◽  
pp. 759
Author(s):  
Haochen Tan ◽  
Pallav Ray ◽  
Mukul Tewari ◽  
James Brownlee ◽  
Ajaya Ravindran
Keyword(s):  
Surface Temperature ◽  
Urban Areas ◽  
Green Roof ◽  
Wrf Model ◽  
Single Layer ◽  
Meteorological Conditions ◽  
Rapid Urbanization ◽  
Near Surface ◽  
Budget Analysis ◽  
The Impact

Due to rapid urbanization, the near-surface meteorological conditions over urban areas are greatly modulated. To capture such modulations, sophisticated urban parameterizations with enhanced hydrological processes have been developed. In this study, we use the single-layer urban canopy model (SLUCM) available within the Weather Research and Forecasting (WRF) model to assess the response of near-surface temperature, wind, and moisture to advection under the impact of the green roof. An ensemble of simulations with different planetary boundary layer (PBL) schemes is conducted in the presence (green roof (GR)) and absence (control (CTL)) of green roof systems. Our results indicate that the near-surface temperature is found to be driven primarily by the surface heat flux with a minor influence from the zonal advection of temperature. The momentum budget analysis shows that both zonal and meridional momentum advection during the evening and early nighttime plays an important role in modulating winds over urban areas. The near-surface humidity remains nearly unchanged in GR compared to CTL, although the physical processes that determine the changes in humidity were different, in particular during the evening when the GR tends to have less moisture advection due to the reduced temperature gradient between the urban areas and the surroundings. Implications of our results are discussed.

Comparing independent climate-sensitive models of aboveground biomass and diameter growth with their compatible simultaneous model system for three larch species in China

2019 ◽  
Vol 12 (07) ◽  
pp. 1950053
Author(s):  
Zhigang Gao ◽  
Qiuyan Wang ◽  
Zongda Hu ◽  
Peng Luo ◽  
Guangshuang Duan ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Growth Models ◽  
Model System ◽  
Maximum Temperature ◽  
Tree Biomass ◽  
Climate Zones ◽  
Temperature And Precipitation ◽  
Larch Species ◽  
The Mean ◽  
Simultaneous Model

Accurate estimate of tree biomass is essential for forest management. In recent years, several climate-sensitive allometric biomass models with diameter at breast height [Formula: see text] as a predictor have been proposed for various tree species and climate zones to estimate tree aboveground biomass (AGB). But the allometric models only account for the potential effects of climate on tree biomass and do not simultaneously explain the influence of climate on [Formula: see text] growth. In this study, based on the AGB data from 256 destructively sampled trees of three larch species randomly distributed across the five secondary climate zones in northeastern and northern China, we first developed a climate-sensitive AGB base model and a climate-sensitive [Formula: see text] growth base model using a nonlinear least square regression separately. A compatible simultaneous model system was then developed with the climate-sensitive AGB and [Formula: see text] growth models using a nonlinear seemingly unrelated regression. The potential effects of several temperature and precipitation variables on AGB and [Formula: see text] growth were evaluated. The fitting results of climatic sensitive base models were compared against those of their compatible simultaneous model system. It was found that a decreased isothermality ([mean of monthly (maximum temperature-minimum temperature)]/(Maximum temperature of the warmest month-Minimum temperature of the coldest month)) and total growing season precipitation, and increased annual precipitation significantly increased the values of AGB; an increase of temperature seasonality (a standard deviation of the mean monthly temperature) and precipitation seasonality (a standard deviation of the mean monthly precipitation) could lead to the increase of [Formula: see text]. The differences of the model fitting results between the compatible simultaneous system with the consideration of climate effects on both AGB and [Formula: see text] growth and its corresponding climate-sensitive AGB and [Formula: see text] growth base models were very small and insignificant [Formula: see text]. Compared to the base models, the inherent correlation of AGB with [Formula: see text] was taken into account effectively by the proposed compatible model system developed with the climate-sensitive AGB and [Formula: see text] growth models. In addition, the compatible properties of the estimated AGB and [Formula: see text] were also addressed substantially in the proposed model system.

scholarly journals Biases and Model Agreement in Projections of Climate Extremes over the Tropical Pacific

2011 ◽  
Vol 15 (24) ◽  
pp. 1-36 ◽  
Author(s):  
Sarah E. Perkins
Keyword(s):  
Minimum Temperature ◽  
General Circulation ◽  
Coupled Model ◽  
Climate Extremes ◽  
General Circulation Models ◽  
Maximum Temperature ◽  
Climate Indices ◽  
Temperature And Precipitation ◽  
Return Levels ◽  
The Mean

Abstract Using the Coupled Model Intercomparison Project phase 3 (CMIP3) general circulation models (GCMs), projections of a range of climate extremes are explored for the western Pacific. These projections include the 1-in-20-yr return levels and a selection of climate indices for minimum temperature, maximum temperature, and precipitation, and they are compared to corresponding mean projections for the Special Report on Emission Scenarios (SRES) A2 scenario during 2081–2100. Models are evaluated per variable based on their ability to simulate current extremes, as well as the overall daily distribution. Using the standardized evaluation scores for each variable, models are divided into four subsets where ensemble variability is calculated to measure model uncertainty and biases are calculated in respect to the multimodel ensemble (MME). Results show that higher uncertainty in projections of climate extremes exists when compared to the mean, even in those subsets consisting of higher-skilled models. Higher uncertainty exists for precipitation projections than for temperature, and biases and uncertainties in the 1-in-20-yr precipitation events are an order of magnitude higher than the corresponding mean. Poorer performing models exhibit a cooler bias in the mean and 1-in-20-yr return levels for maximum and minimum temperature, and ensemble variability is low among all subsets of mean minimum temperature, especially the lower-skilled subsets. Higher-skilled models project 1-in-20-yr precipitation return levels that are more intense than in the MME. The frequency of temperature extremes increase dramatically; however, this is explained by the underpinning small temperature range of the region. Although some systematic biases occur in the higher- and lower-skilled models and omitting the poorer performers is recommended, great care should be exercised when interpreting the reduction of uncertainty because the ensemble variability among the remaining models is comparable and in some cases greater than the MME. Such results should be treated on a case-by-case basis.

scholarly journals Factors Influencing the Geographical Distribution of Dendroctonus armandi (Coleoptera: Curculionidae: Scolytidae) in China

Forests ◽  
2019 ◽  
Vol 10 (5) ◽  
pp. 425
Author(s):  
Hang Ning ◽  
Lulu Dai ◽  
Danyang Fu ◽  
Bin Liu ◽  
Honglin Wang ◽  
...  
Keyword(s):  
Current Distribution ◽  
Species Distribution Models ◽  
Northern China ◽  
Climatic Conditions ◽  
Southwestern China ◽  
Qinling Mountains ◽  
Distribution Models ◽  
Temperature And Precipitation ◽  
Scale Levels ◽  
The Mean

In order to prevent any further spread of Dendroctonus armandi (Coleoptera: Curculionidae: Scolytidae), it is important to clarify its geographic distribution in China. Species Distribution Models were used to identify the variables influencing the distribution of D. armandi in China, and to create maps of its distribution. D. armandi almost exclusively attacked Pinus armandi Franch (IP (frequency of its incidence) = 98.2%), and its distribution is focused on the Qinling Mountains and the Ta-pa Mountains. The current distribution of P. armandi does not limit the distribution of D. armandi, despite the host occurring in in northern and southwestern China. Temperature and precipitation limit the current distribution of this beetle. The mean temperature of coldest quarter (−5 °C) does not guarantee that D. armandi larvae can overwinter in northern China, and the precipitation of wettest quarter plays an important role in the dispersal and colonization of D. armandi adults in southwestern China. Therefore, the ecological niche of this beetle is relatively narrow when it comes to these environmental variables. The climatic conditions where this beetle inhabit are different from the prevalent climate in the Qinling Mountains and the Ta-pa Mountains. At the meso- and micro-scale levels, terrain variables create habitat selection preferences for D. armandi. D. armandi predominately colonizes trees on the southern slopes of valleys and canyons with elevations between 1300 m a.s.l and 2400 m a.s.l.

scholarly journals The Study on Compound Drought and Heatwave Events in China Using Complex Networks

2021 ◽  
Vol 13 (22) ◽  
pp. 12774
Author(s):  
Kaiwen Li ◽  
Ming Wang ◽  
Kai Liu
Keyword(s):  
Extreme Events ◽  
Temporal Variations ◽  
Spatial And Temporal Variations ◽  
Maximum Temperature ◽  
Mean Frequency ◽  
Temperature And Precipitation ◽  
Annual Frequency ◽  
The Mean ◽  
Precipitation Changes ◽  
The Impact

Compound extreme events can severely impact water security, food security, and social and economic development. Compared with single-hazard events, compound extreme events cause greater losses. Therefore, understanding the spatial and temporal variations in compound extreme events is important to prevent the risks they cause. Only a few studies have analyzed the spatial and temporal relations of compound extreme events from the perspective of a complex network. In this study, we define compound drought and heatwave events (CDHEs) using the monthly scale standard precipitation index (SPI), and the definition of a heatwave is based on daily maximum temperature. We evaluate the spatial and temporal variations in CDHEs in China from 1961 to 2018 and discuss the impact of maximum temperature and precipitation changes on the annual frequency and annual magnitude trends of CDHEs. Furthermore, a synchronization strength network is established using the event synchronization method, and the proposed synchronization strength index (SSI) is used to divide the network into eight communities to identify the propagation extent of CDHEs, where each community represents a region with high synchronization strength. Finally, we explore the impact of summer Atlantic multidecadal oscillation (AMO) and Pacific decadal oscillation (PDO) on CDHEs in different communities. The results show that, at a national scale, the mean frequency of CDHEs takes on a non-significant decreasing trend, and the mean magnitude of CDHEs takes on a non-significant increasing trend. The significant trends in the annual frequency and annual magnitude of CDHEs are attributed to maximum temperature and precipitation changes. AMO positively modulates the mean frequency and mean magnitude of CDHEs within community 1 and 2, and negatively modulates the mean magnitude of CDHEs within community 3. PDO negatively modulates the mean frequency and mean magnitude of CDHEs within community 4. AMO and PDO jointly modulate the mean magnitude of CDHEs within community 6 and 8. Overall, this study provides a new understanding of CDHEs to mitigate their severe effects.

scholarly journals Planetary Nebulae in M31: Abundances, and comparison with bright Planetary Nebulae in the LMC

1997 ◽  
Vol 180 ◽  
pp. 475-476
Author(s):  
M. G. Richer ◽  
G. Stasińska ◽  
M. L. McCall
Keyword(s):  
Planetary Nebula ◽  
Luminosity Function ◽  
Large Population ◽  
Wavelength Region ◽  
Planetary Nebulae ◽  
Surprising Result ◽  
Population Synthesis ◽  
Abundance Distribution ◽  
Wide Range ◽  
The Mean

We have obtained spectra of 28 planetary nebulae in the bulge of M31 using the MOS spectrograph at the Canada-France-Hawaii Telescope. Typically, we observed the [O II] λ3727 to He I λ5876 wavelength region at a resolution of approximately 1.6 å/pixel. For 19 of the 21 planetary nebulae whose [OIII]λ5007 luminosities are within 1 mag of the peak of the planetary nebula luminosity function, our oxygen abundances are based upon a measured [OIII]λ4363 intensity, so they are based upon a measured electron temperature. The oxygen abundances cover a wide range, 7.85 dex < 12 + log(O/H) < 9.09 dex, but the mean abundance is surprisingly low, 12 + log(O/H)–8.64 ± 0.32 dex, i.e., roughly half the solar value (Anders & Grevesse 1989). The distribution of oxygen abundances is shown in Figure 1, where the ordinate indicates the number of planetary nebulae with abundances within ±0.1 dex of any point on the x-axis. The dashed line indicates the mean abundance, and the dotted lines indicate the ±1 σ points. The shape of this abundance distribution seems to indicate that the bulge of M31 does not contain a large population of bright, oxygen-rich planetary nebulae. This is a surprising result, for various population synthesis studies (e.g., Bica et al. 1990) have found a mean stellar metallicity approximately 0.2 dex above solar. This 0.5 dex discrepancy leads one to question whether the mean stellar metallicity is as high as the population synthesis results indicate or if such metal-rich stars produce bright planetary nebulae at all. This could be a clue concerning the mechanism responsible for the variation in the number of bright planetary nebulae observed per unit luminosity in different galaxies (e.g., Hui et al. 1993).

Quantification of temperature and precipitation changes in northern China during the “5000-year” Chinese History

2021 ◽  
Vol 255 ◽  
pp. 106819 ◽  
Author(s):  
Can Zhang ◽  
Cheng Zhao ◽  
Aifeng Zhou ◽  
Haixia Zhang ◽  
Weiguo Liu ◽  
...  
Keyword(s):  
Northern China ◽  
Chinese History ◽  
Temperature And Precipitation ◽  
Precipitation Changes

scholarly journals Projected Changes in Climate Extremes Using CMIP6 Simulations Over SREX Regions

2021 ◽  
Vol 5 (3) ◽  
pp. 481-497
Author(s):  
Mansour Almazroui ◽  
Fahad Saeed ◽  
Sajjad Saeed ◽  
Muhammad Ismail ◽  
Muhammad Azhar Ehsan ◽  
...  
Keyword(s):  
Spatial Variability ◽  
Extreme Events ◽  
First Century ◽  
Maximum Temperature ◽  
Annual Maximum ◽  
Temperature And Precipitation ◽  
Projected Change ◽  
Twenty First Century ◽  
Projected Changes ◽  
The Tropics

AbstractThis paper presents projected changes in extreme temperature and precipitation events by using Coupled Model Intercomparison Project phase 6 (CMIP6) data for mid-century (2036–2065) and end-century (2070–2099) periods with respect to the reference period (1985–2014). Four indices namely, Annual maximum of maximum temperature (TXx), Extreme heat wave days frequency (HWFI), Annual maximum consecutive 5-day precipitation (RX5day), and Consecutive Dry Days (CDD) were investigated under four socioeconomic scenarios (SSP1-2.6; SSP2-4.5; SSP3-7.0; SSP5-8.5) over the entire globe and its 26 Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (SREX) regions. The projections show an increase in intensity and frequency of hot temperature and precipitation extremes over land. The intensity of the hottest days (as measured by TXx) is projected to increase more in extratropical regions than in the tropics, while the frequency of extremely hot days (as measured by HWFI) is projected to increase more in the tropics. Drought frequency (as measured by CDD) is projected to increase more over Brazil, the Mediterranean, South Africa, and Australia. Meanwhile, the Asian monsoon regions (i.e., South Asia, East Asia, and Southeast Asia) become more prone to extreme flash flooding events later in the twenty-first century as shown by the higher RX5day index projections. The projected changes in extremes reveal large spatial variability within each SREX region. The spatial variability of the studied extreme events increases with increasing greenhouse gas concentration (GHG) and is higher at the end of the twenty-first century. The projected change in the extremes and the pattern of their spatial variability is minimum under the low-emission scenario SSP1-2.6. Our results indicate that an increased concentration of GHG leads to substantial increases in the extremes and their intensities. Hence, limiting CO2 emissions could substantially limit the risks associated with increases in extreme events in the twenty-first century.

scholarly journals Seasonal Variations of Daytime Land Surface Temperature and Their Underlying Drivers over Wuhan, China

2021 ◽  
Vol 13 (2) ◽  
pp. 323
Author(s):  
Liang Chen ◽  
Xuelei Wang ◽  
Xiaobin Cai ◽  
Chao Yang ◽  
Xiaorong Lu
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Maximum Temperature ◽  
Maximum Temperature Difference ◽  
Rapid Urbanization ◽  
The Impact ◽  
The City

Rapid urbanization greatly alters land surface vegetation cover and heat distribution, leading to the development of the urban heat island (UHI) effect and seriously affecting the healthy development of cities and the comfort of living. As an indicator of urban health and livability, monitoring the distribution of land surface temperature (LST) and discovering its main impacting factors are receiving increasing attention in the effort to develop cities more sustainably. In this study, we analyzed the spatial distribution patterns of LST of the city of Wuhan, China, from 2013 to 2019. We detected hot and cold poles in four seasons through clustering and outlier analysis (based on Anselin local Moran’s I) of LST. Furthermore, we introduced the geographical detector model to quantify the impact of six physical and socio-economic factors, including the digital elevation model (DEM), index-based built-up index (IBI), modified normalized difference water index (MNDWI), normalized difference vegetation index (NDVI), population, and Gross Domestic Product (GDP) on the LST distribution of Wuhan. Finally, to identify the influence of land cover on temperature, the LST of croplands, woodlands, grasslands, and built-up areas was analyzed. The results showed that low temperatures are mainly distributed over water and woodland areas, followed by grasslands; high temperatures are mainly concentrated over built-up areas. The maximum temperature difference between land covers occurs in spring and summer, while this difference can be ignored in winter. MNDWI, IBI, and NDVI are the key driving factors of the thermal values change in Wuhan, especially of their interaction. We found that the temperature of water area and urban green space (woodlands and grasslands) tends to be 5.4 °C and 2.6 °C lower than that of built-up areas. Our research results can contribute to the urban planning and urban greening of Wuhan and promote the healthy and sustainable development of the city.

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