Trends in aerosol optical properties over Eastern Europe based on MODIS-Aqua

This study provides characteristics of aerosol columnar properties, measured over ten countries in Eastern Europe from 2002 to 2019. Aerosol optical depth (AOD) and Ångström exponent (AE) were obtained with the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6.1 merged Dark Target and Deep Blue aerosol product. The product is validated using ground-based Aerosol Robotic Network (AERONET) situated at Minsk, Belsk, Moldova and Kyiv. The results showed that 76.15% of retrieved AOD data are within the expected error. It was established that 64.2% of AOD points are between 0 and 0.2 and 79.3% of all AE points are over 1. Mean AOD values in the region vary from 0.130 ​± ​0.04 (Moldova) to 0.193 ​± ​0.03 (Czech Republic) with mean value in the region 0.162 ​± ​0.05. Seasonal mean AOD (AE) values were at the maximum during the summer from 0.231 ​± ​0.05 (1.482 ​± ​0.09 in winter) to minimum 0.087 ​± ​0.04 during the winter (1.363 ​± ​0.17 in summer). Gradual AOD reduction is observed in all countries with annual trend from −0.0050 (Belarus) to −0.0029 (Russia). Finally, the relationship between AOD and AE was studied to classify various aerosol types and showed seasonal non-uniformity of their contribution depending on variation in sources. The entire region is under significant impact of various aerosol types, including clean continental (СС), mixed (MX) and anthropogenic/burning (AB) aerosols types that are at 59.77%, 24.72%, and 12.97% respectively. These results form an important basis for further regional studies of air quality and distribution of sources of pollution.     

Characterization of aerosol type based on aerosol optical properties over Baghdad,Iraq

Aerosol optical depth (AOD), Angstrom exponent (AE), and ozone monitoring instrument aerosols index (OMI-AI) data, derived from MODerate Resolution Imaging Spectroradiometer (MODIS) and OMI sensor on board NASA’s Aqua satellite and NASA-Aura satellite platforms, have been analyzed and classified over Baghdad, Iraq, for an 8-year period (2008–2015). In order to give an obvious understanding of temporal inconsistency in the characteristics and classification of aerosols during each season separately, PREDE POM-02 sky radiometer measurements of AOD, carried out during a 2-year period (2014–2015), were compared with MODIS–Aqua AODs. On seasonal bases, MODIS–Aqua AODs corroborate well with ground-based measurements, with correlation coefficients ranging between 0.74 and 0.8 and RMSE ranging from 0.097 to 0.062 during spring and autumn seasons respectively. The overall satellite- and ground-based measurement comparisons showed a good agreement with correlation coefficients of 0.78 and RMSE of 0.066. These results suggest that MODIS–Aqua gives a good estimate of AOD. Analysis of MODIS–Aqua data for the 8-year period showed that the overall mean AOD, AE, and OMI-AI over Baghdad were 0.44?±?0.16, 0.77?±?0.29, and 1.34?±?0.33 respectively. AOD records presented a unique peak which was extended from mid-spring (April) to mid-summer (July) while the AE annual variability indicated a more complicated behavior with minimum values during the period from late spring (May) to early autumn (September). The maximum AOD and OMI-AI values occurred during summer while their minimum values occurred during winter. The AE showed an opposite behavior to that of AOD such that the highest AE values occurred during autumn and winter and the lowest values happened during spring and summer. This behavior may be attributed to the domination of coarse aerosol particles during autumn and winter seasons and fine aerosol particles during spring and summer seasons. A Hybrid Single-Particle Lagrangian Integrated Trajectory model was utilized to determine the source of air mass transport and to recognize the variability of aerosol origin regions. Finally, AOD, AE, and OMI-AI values have been employed to identify several aerosol types and to present seasonal heterogeneity in their contribution based on their origins.     

Nature of the Decrease in Global Warming at the Beginning of the 21st Century

Variations in the temperature of the Earth’s surface over the period 1850–2014 are reproduced and analyzed using seven historical calculations in the INM-CM5 climate model following the scenarios suggested for the CMIP6 project of comparison of climate models. In all calculations, the mean surface temperature increased by 0.8 K to the date of final calculation (2014), which is consistent with observations. The periods of accelerated warming (1920–1940 and 1980–2000) and its stabilization (1950–1975 and 2000–2014) are correctly reproduced by the model. The decrease in global warming of 2000–2014, which is hardly reproduced by the models in the CMIP5 experiment, is reproduced due to the more precise scenario of variation in the solar constant of CMIP6 protocols. The spatial structure of warming for last 30 years is also reproduced by the model.

     

Relationship between MODIS based Aerosol Optical Depth and PM10 over Croatia

This study analyzes the relationship between Aerosol Optical Depth (AOD) obtained from Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) and ground-based PM10 mass concentration distribution over a period of 5 years (2008–2012), and investigates the applicability of satellite AOD data for ground PM10 mapping for the Croatian territory. Many studies have shown that satellite AOD data are correlated to ground-based PM mass concentration. However, the relationship between AOD and PM is not explicit and there are unknowns that cause uncertainties in this relationship. The relationship between MODIS AOD and ground-based PM10 has been studied on the basis of a large data set where daily averaged PM10 data from the 12 air quality stations across Croatia over the 5 year period are correlated with AODs retrieved from MODIS Terra and Aqua. A database was developed to associate coincident MODIS AOD (independent) and PM10 data (dependent variable). Additional tested independent variables (predictors, estimators) included season, cloud fraction, and meteorological parameters — including temperature, air pressure, relative humidity, wind speed, wind direction, as well as planetary boundary layer height — using meteorological data from WRF (Weather Research and Forecast) model. It has been found that 1) a univariate linear regression model fails at explaining the data variability well which suggests nonlinearity of the AOD-PM10 relationship, and 2) explanation of data variability can be improved with multivariate linear modeling and a neural network approach, using additional independent variables.     

撒哈拉地区沙尘气溶胶南北空间型分布特征及其成因

本次研究利用MODIS、CALIPSO等卫星观测资料以及MERRA-2再分析资料分析了2007–2017年撒哈拉地区气溶胶光学厚度的空间分布特征.结果表明,撒哈拉地区气溶胶光学厚度的空间分布具有明显的季节变化,夏季沙尘气溶胶光学厚度高值区位于撒哈拉北部地区,高达0.6以上;而冬季沙尘气溶胶光学厚度高值区位于撒哈拉南部地...     

2006年春季我国东部海域气溶胶光学厚度与沙尘天气

结合船基的太阳光度计观测资料和空基卫星遥感的MODIS气溶胶光学厚度资料,研究了我国东部海域气溶胶光学厚度与沙尘天气的关系。通过对不同天气条件下500 nm气溶胶光学厚度的分析,得出晴天(背景天气)、有云和浮尘以及只有浮尘时的平均值分别约为0.2、0.6和1.3以上;将MODIS的气溶胶光学厚度与船基观测资料进行对比之后发现,两者随时间的变化趋势非常一致,但前者在数值上明显偏高;利用订正后的MODIS资料,分析了2006年春季我国东部海域气溶胶光学厚度的时空分布特征,并与我国北方发生的沙尘天气进行了对比,发现两者之间关系密切。     

Data augmentation for bias correction in mapping PM2.5 based on satellite retrievals and ground observations

As most air quality monitoring sites are in urban areas worldwide, machine learning models may produce substantial estimation bias in rural areas when deriving spatiotemporal distributions of air pollutants. The bias stems from the issue of dataset shift, as the density distributions of predictor variables differ greatly between urban and rural areas. We propose a data-augmentation approach based on the multiple imputation by chained equations (MICE-DA) to remedy the dataset shift problem. Compared with the benchmark models, MICE-DA exhibits superior predictive performance in deriving the spatiotemporal distributions of hourly PM_2.5 in the megacity (Chengdu) at the foot of the Tibetan Plateau, especially for correcting the estimation bias, with the mean bias decreasing from –3.4 µg/m³ to –1.6 µg/m³. As a complement to the holdout validation, the semi-variance results show that MICE-DA decently preserves the spatial autocorrelation pattern of PM_2.5 over the study area. The essence of MICE-DA is strengthening the correlation between PM_2.5 and aerosol optical depth (AOD) during the data augmentation. Consequently, the importance of AOD is largely enhanced for predicting PM_2.5, and the summed relative importance value of the two satellite-retrieved AOD variables increases from 5.5% to 18.4%. This study resolved the puzzle that AOD exhibited relatively lower importance in local or regional studies. The results of this study can advance the utilization of satellite remote sensing in modeling air quality while drawing more attention to the common dataset shift problem in data-driven environmental research.     

High resolution aerosol data from MODIS satellite for urban air quality studies

The Moderate Resolution Imaging Spectroradiometer (MODIS) provides daily global coverage, but the 10 km resolution of its aerosol optical depth (AOD) product is not suitable for studying spatial variability of aerosols in urban areas. Recently, a new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for MODIS which provides AOD at 1 km resolution. Using MAIAC data, the relationship between MAIAC AOD and PM_2.5 as measured by the 27 EPA ground monitoring stations was investigated. These results were also compared to conventional MODIS 10 km AOD retrievals (MOD04) for the same days and locations. The coefficients of determination for MOD04 and for MAIAC are R² =0.45 and 0.50 respectively, suggested that AOD is a reasonably good proxy for PM_2.5 ground concentrations. Finally, we studied the relationship between PM_2.5 and AOD at the intra-urban scale (?10 km) in Boston. The fine resolution results indicated spatial variability in particle concentration at a sub-10 kilometer scale. A local analysis for the Boston area showed that the AOD-PM_2.5 relationship does not depend on relative humidity and air temperatures below ～7 °C. The correlation improves for temperatures above 7–16 °C. We found no dependence on the boundary layer height except when the former was in the range 250–500 m. Finally, we apply a mixed effects model approach to MAIAC aerosol optical depth (AOD) retrievals from MODIS to predict PM_2.5 concentrations within the greater Boston area. With this approach we can control for the inherent day-to-day variability in the AOD-PM_2.5 relationship, which depends on time-varying parameters such as particle optical properties, vertical and diurnal concentration profiles and ground surface reflectance. Our results show that the model-predicted PM_2.5 mass concentrations are highly correlated with the actual observations (out-of-sample R² of 0.86). Therefore, adjustment for the daily variability in the AOD-PM_2.5 relationship provides a means for obtaining spatially-resolved PM_2.5 concentrations.     

Surface water and aerosol spatiotemporal dynamics and influence mechanisms over drylands

Under the background of global warming and excessive human activities, much surface water in drylands is experiencing rapid degradation or shrinkage in recent years. The shrinkage of surface water, especially the degradation of lakes and their adjacent wetlands in drylands, may lead to the emergence of new salt dust storm hotspots, which causes greater danger. In this paper, based on high spatial resolution global surface water (GSW) and multiangle implementation of atmospheric correction (MAIAC) AOD data, we systematically analyze the dynamic characteristics of surface water and aerosols in typical drylands (Central Asia, CA) between 2000 and 2018. Simultaneously, combined with auxiliary environment variables, we explore the driving mechanisms of surface water on the regional salt/sand aerosols on different spatial scales. The results show that the seasonal surface water features an increasing trend, especially a more dramatic increase after 2015, and the permanent surface water indicates an overall decrease, with nearly 54.367 % at risk of receding and drying up. In typical lakes (Aral Sea and Ebinur Lake), the interannual change feature of the surface water area (WA) is that a continuous decrease during the study period occurs in Aral Sea area, yet a significant improvement has occurred in Ebinur Lake after 2015, and the degradation of Ebinur Lake takes place later and its recovery earlier than Aral Sea. The aerosol optical depth (AOD) in CA shows obvious seasonal variation, with the largest in spring (0.192 ± 0173), next in summer (0.169 ± 0.106), and the smallest in autumn (0.123 ± 0.065). The interannual variation of AOD exhibits an increase from 2000 to 2018 in CA, with high AOD areas mainly concentrated in the Taklamakan Desert and some lake beds resulting from lake degradation, including Aral Sea and Ebinur Lake. The AOD holds a similar trend between Aral Sea and Ebinur Lake on an interannual scale. And the AOD over Ebinur Lake is lower than that over Aral Sea in magnitude and lags behind in reaching the peak compared with Aral Sea. The WA change can significantly affect aerosol variation directly or indirectly on the aerosol load or mode size, but there are obvious differences in the driving mechanisms, acting paths, and influence magnitude of WA on aerosols on different spatial scales. In addition, the increase of WA can significantly directly suppress the increase of Ångström exponent (AE), and the effects of WA on AOD are realized majorly by an indirect approach. From the typical lake perspective, the effects of WA on aerosol in Aral Sea are achieved via an indirect path; and the decrease of WA can indirectly promote the AOD rise, and directly stimulate the AE growth in Ebinur Lake.     

Study on the gravity center evolution of air pollution in Yangtze River Delta of China

With the rapid development of China’s economy, air pollution is becoming extremely serious. The spatial–temporal evolution of air pollution is conducive to the management of air pollution. The paper is proceeded into three steps. Firstly, based on the generalization principal component analysis method, the comprehensive air pollution evaluation index is established. Then, the gravity center model is utilized to explore the spatial–temporal evolution of air pollution in Yangtze River Delta from January 2014 to December 2016. Finally, the contribution decomposition method is utilized to explore the contribution to gravity center evolution. The main results are as follows: (1) The air pollution have obvious seasonal and regional differences in Yangtze River Delta. (2) The gravity center of air pollution continues to westward after 2014 with the characteristic of the north–south circular movement. (3) Hefei City and Yangzhou City have huge impact on the gravity center evolution of air pollution. The conclusions could be helpful for Chinese government to control the air pollution in Yangtze River Delta.     

Climatology,trend of aerosol-cloud parameters and their correlation over the Northern Indian Ocean

Aerosols are one of the important atmospheric constituents and exert indirect impact on climate through the modification of microphysical and radiative properties of clouds that in turn perturb the precipitation pattern. Thus, the long term quantification of changes in aerosol and cloud characteristics and their interactions on both temporal as well as spatial scale will provide a crucial information for the better assessment of future climate change. In present study, 18 years (2003–2020) MODerate Resolution Imaging Spectro-radiometer (MODIS) derived aerosol-cloud dataset over the Northern Indian Ocean (NIO) were analysed to assess climatology and trend of aerosol, cloud characteristics and their correlation. We found a strong heterogeneity in spatio-temporal variation of aerosol and cloud parameters over the NIO that are more prominent for the coastal region. The climatological mean of aerosol loading is found high (AOD ≥ 0.5) over the outflow region along the Indian sub-continent and low (AOD ≤ 0.2) over the northern equatorial open ocean. The climatological mean of cloud properties shows dominance of optically thicker deep convective (CTP < 600 hPa and CTT < 260 K) clouds over the southern Bay of Bengal (BoB) and thinner shallow (CTP > 700 hPa and CTT > 273 K) over the northwestern Arabian Sea (AS). Similarly, bigger effective radii (>17 µm) observed along the equatorial open ocean whereas smaller CER (<17 µm) were found over Indian sub-continental coastline and western AS. Further, trend analysis reveals an increasing pattern in AOD (0.002 yr^?1), CER (0.051 µm yr^?1), LWP (0.033 gm^?2 yr^?1) and CF (0.002 yr^?1) while COD, CTT and CTP show negative trend in order of ?0.005 yr^?1, ?0.094 K yr^?1 and ?1.160 hPa yr^?1, respectively. We also perform similar analysis for seven sub-region of interest (R1 to R7) across the NIO and results show a decreasing pattern in AOD (?0.001 yr^?1) at R4 against maximum mean AOD (0.44 ± 0.03). However, coastal sub-regions R1 and R5 illustrate maximum increase in aerosol loading (>0.003 yr^?1) suggesting a significant impact of sub-continental outflow over the regions. The spatial correlation of cloud properties with respect to AOD shows a positive slope for CER (0.14) and CF (0.48) and a negative for COD (?0.19), LWP (?0.18), CTT (?0.37), CTP (?0.41). The present study provides in-depth information about the aerosol-cloud characteristics for a long term scale over NIO and could be useful in regional aerosol-cloud interaction induced climate forcing estimation.     

Influence of circulation parameters on the AOD variations over the Bay of Bengal during ICARB

MODIS (Moderate Resolution Imaging Spectroradiometer) level-3 aerosol data, NCEP (National Centers for Environmental Prediction) reanalysis winds and QuikSCAT ocean surface winds were made use of to examine the role of atmospheric circulation in governing aerosol variations over the Bay of Bengal (BoB) during the first phase of the ICARB (Integrated Campaign for Aerosols, gases and Radiation Budget) campaign (March 18–April 12, 2006). An inter-comparison between MODIS level-3 aerosol optical depth (AOD) data and ship-borne MICROTOPS measurements showed good agreement with correlation 0.92 (p < 0.0001) and a mean MODIS underestimation by 0.01. During the study period, the AOD over BoB showed high values in the northern/north western regions, which reduced towards the central and southern BoB. The wind patterns in lower atmospheric layers (> 850 hPa) indicated that direct transport of aerosols from central India was inhibited by the presence of a high pressure and a divergence over BoB in the lower altitudes. On the other hand, in the upper atmospheric levels, winds from central and northern India stretched south eastwards and converged over BoB with a negative vorticity indicative of a downdraft. These wind patterns pointed to the possibility of aerosol transport from central India to BoB by upper level winds. This mechanism was further confirmed by the significant correlations that AOD variations over BoB showed with aerosol flux convergence and flux vorticity at upper atmospheric levels (600–500 hPa). AOD in central and southern BoB away from continental influences displayed an exponential dependence on the QuikSCAT measured ocean surface wind speed. This study shows that particles transported from central and northern India by upper atmospheric circulations as well as the marine aerosols generated by ocean surface winds contributed to the AOD over the BoB during the first phase of ICARB.     

The significance of Gobi desert surfaces for dust emissions in China: an experimental study

A series of experiments to determine the direct emission of dust-sized particles from Gobi surfaces by clean wind (wind without sand), and the potential for aeolian abrasion of Gobi surfaces and beds of gravel and mobile sand to produce fine (<100 μm) and dust-sized (<10 μm, PM₁₀) particles under sand-laden winds were conducted. Parent material was obtained from Gobi areas of the Ala Shan Plateau, the region with high dust emissions in arid China. The fine particles produced by aeolian processes were collected using sand traps and sieved the captured materials to exclude particles >100 μm in diameter and then PM₁₀ by sedimentation was acquired. The Gobi surface provided most of the emitted fine particles during the initial dust emission processes, but subsequently, release of the clay coatings of particles by abrasion becomes the dominant source of fine materials. Under sand-laden winds, PM₁₀ production rates produced by aeolian abrasion of Gobi surfaces ranged between 0.002 and 0.244% of blown materials. After removal of sand, silt, or clay with low resistance to erosion from the Gobi surfaces by the wind, the PM₁₀ production rates caused by aeolian abrasion were similar to those from gravel and sand beds. The results also indicated that after the dust-sized particles with low resistance to erosion were removed, the production of dust-sized particles was unrelated to wind velocity. Under aeolian processes, Gobi deserts in this region therefore play a major role in dust emissions from arid and semiarid China.     

COVID-19 strict lockdown impact on urban air quality and atmospheric temperature in four megacities of India

COVID-19 pandemic has forced to lockdown entire India starting from 24th March 2020 to 14th April 2020 (first phase), extended up to 3rd May 2020 (second phase), and further extended up to 17th May 2020 (third phase) with limited relaxation in non-hotspot areas. This strict lockdown has severely curtailed human activity across India. Here, aerosol concentrations of particular matters (PM) i.e., PM₁₀, PM_2.5, carbon monoxide (CO), nitrogen dioxide (NO₂), sulphur dioxide (SO₂), ammonia (NH₃) and ozone (O₃), and associated temperature fluctuation in four megacities (Delhi, Mumbai, Kolkata, and Chennai) from different regions of India were investigated. In this pandemic period, air temperature of Delhi, Kolkata, Mumbai and Chennai has decreased about 3 °C, 2.5 °C, 2 °C and 2 °C respectively. Compared to previous years and pre-lockdown period, air pollutants level and aerosol concentration (?41.91%, ?37.13%, ?54.94% and ?46.79% respectively for Delhi, Mumbai, Kolkata and Chennai) in these four megacities has improved drastically during this lockdown period. Emission of PM_2.5 has experienced the highest decrease in these megacities, which directly shows the positive impact of restricted vehicular movement. Restricted emissions produce encouraging results in terms of urban air quality and temperature, which may encourage policymakers to consider it in terms of environmental sustainability.     

Correlations between air pollutant emission,logistic services,GDP, and urban population growth from vector autoregressive modeling: a case study of Beijing

Logistics in China has grown rapidly; in 2015, the freight volume has reached 41 billion ton, increasing by 4.4% year-on-year. At the same time, the pollutant emissions from freight cars account for 70% of total emissions of motor vehicles, which severely affected the air quality. The purpose of this paper is to investigate the effect of logistics on air pollution; we used a new methodology based on vector autoregression of freight turnover, gross domestic product, and urban population. We selected Beijing as our test and created a model using time series data for the period 2000–2014. In this model, permanent residents, freight turnover, and SO₂ emission were used as proxies for population size, logistic services, and degree of air pollution. Our analyses showed that the expansion of logistic services had the biggest effect on air pollution. Moreover, impulse response analysis revealed that logistic growth caused more serious air pollution over a short time, with an ongoing negative effect. GDP growth was only weakly correlated with air pollution, while urban population growth appeared to have little effect.     

Variations in annual winter mean temperature in South China since 1736

Modern meteorological observations in South China from 1960 to 2009 show a strong correlation between winter temperatures and two snowfall parameters, the southern boundary of the snow and the number of snowy days. Based on this relationship, the variation in annual winter mean temperature in South China from 1736 to 2009 was reconstructed using data acquired from Chinese historical documents dating from the Qing dynasty, such as memos and local gazettes. The reconstructed time series were used to analyse variations in winter temperature in South China. Significant interannual and interdecadal changes were found. The maximum temperature difference between neighbouring years was 3.1 °C for 1958–2009 and 3.0 °C for 1736–1957, whereas the maximum temperature difference between adjacent decades was 0.8 °C for the 1960s–2000s and 0.6 °C for the 1740s–1950s. The 2000s was the warmest decade; the mean temperature was 1.6 °C higher than that of the 1870s, which was the coldest decade between the 1740s and the 2000s. The mean winter temperature was warmer in the 18th and 20th centuries and coldest in the 19th century.     

Calcite U–Pb age of the Cretaceous vertebrate‐bearing Bayn Shire Formation in the Eastern Gobi Desert of Mongolia: Usefulness of caliche for age determination

To verify the usefulness of calcite U–Pb measurement for vertebrate‐bearing strata in the Eastern Gobi, Mongolia, we performed laser ablation‐inductively coupled plasma‐mass spectrometry calcite U–Pb and trace element analyses of three caliche (calcrete) of the Bayn Shire Formation. The trace element analysis demonstrates high concentration of U in the calcites. Two meaningful calcite U–Pb ages were obtained; 95.9 ± 6.0 and 89.6 ± 4.0 Ma, which are consistent with published ages from the Bayn Shire Formation. Our results demonstrate that the calcite U–Pb method can be powerful tool for age determination of vertebrate‐bearing strata in the Gobi that do not contain index fossils or beds, but do contain caliches. This would make it possible for a comparison of biostratigraphy between the Gobi and other areas yielding abundant vertebrate fossils in Asia, North America and Europe, based on chronological data.     

Influence of transboundary air pollution on air quality in southwestern China

Air pollution is a grand challenge of our time due to its multitude of adverse impacts on environment and society,with the scale of impacts more severe in developing countries,including China.Thus,China has initiated and implemented strict air pollution control measures over last several years to reduce impacts of air pollution.Monitoring data from Jan 2015 to Dec 2019 on six criteria air pollutants(SO2,NO2,CO,O3,PM2.5,and PM1o)at eight sites in southwestern China were investigated to understand the situation and analyze the impacts of transboundary air pollutants in this region.In terms of seasonal variation,the maximum concentrations of air pollutants at these sites were observed in winter or spring season depending on individual site.For diurnal variation,surface ozone peaked in the afternoon while the other pollutants had a bimodal pattern with peaks in the morning and late afternoon.There was limited trans-port of domestic emissions of air pollutants in China to these sites.Local emissions enhanced the concen-trations of air pollutants during some pollution events.Mostly,the transboundary transport of air pollution from South Asia and Southeast Asia was associated with high concentrations of most air pollu-tants observed in southwestern China.Since air pollutants can be transported to southwestern China over long distances from the source regions,it is necessary to conduct more research to properly attribute and quantify transboundary transport of air pollutants,which will provide more solid scientific guidance for air pollution management in southwestern China.     

Assessing the effects of the climate change on land cover changes in different time periods

The present research evaluated the relation between the normalized difference vegetation index (NDVI) changes and the climate change during 2000–2014 in Qazvin Plain, Iran. Daily precipitation and mean temperature values during 2015–2040 and 2040–2065 were predicted using the statistical downscaling model (SDSM), and these values were compared with the values of the base period (2000–2014). The MODIS images (MOD13A2) were used for NDVI monitoring. In order to investigate the effects of climate changes on vegetation, the relationship between the NDVI and climatic parameters was assessed in monthly, seasonal, and annual time periods. According to the obtained results under the B2 scenario, the mean annual precipitation at Qazvin Station during 2015–2040 and 2040–2065 was 6.7 mm (9.3%) and 8.2 mm (11.36%) lower than the values in the base period, respectively. Moreover, the mean annual temperature in the mentioned periods was 0.7 and 0.92 °C higher than that in the base period, respectively. Analysis of the correlations between the NDVI and climatic parameters in different periods showed that there is a significant correlation between the seasonal temperature and NDVI (P < 0.01). Moreover, the NDVI will increase 0.009 and 0.011 during 2015–2040 and 2040–2065, respectively.     

Surface air temperature changes over the Tibetan Plateau: Historical evaluation and future projection based on CMIP6 models

With its amplification simultaneously emerging in cryospheric regions, especially in the Tibetan Plateau, global warming is undoubtedly occurring. In this study, we utilized 28 global climate models to assess model performance regarding surface air temperature over the Tibetan Plateau from 1961 to 2014, reported spatiotemporal variability in surface air temperature in the future under four scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5), and further quantified the timing of warming levels (1.5, 2, and 3 °C) in the region. The results show that the multimodel ensemble means depicted the spatiotemporal patterns of surface air temperature for the past decades well, although with differences across individual models. The projected surface air temperature, by 2099, would warm by 1.9, 3.2, 5.2, and 6.3 °C relative to the reference period (1981–2010), with increasing rates of 0.11, 0.31, 0.53, and 0.70 °C/decade under the SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 scenarios for the period 2015–2099, respectively. Compared with the preindustrial periods (1850–1900), the mean annual surface air temperature over the Tibetan Plateau has hit the 1.5 °C threshold and will break 2 °C in the next decade, but there is still a chance to limit the temperature below 3 °C in this century. Our study provides a new understanding of climate warming in high mountain areas and implies the urgent need to achieve carbon neutrality.