Effects of Air Pollutants on Summer Precipitation in Different Regions of Beijing

Many studies have shown that air pollutants have complex impacts on urban precipitation. Meteorological weather station and satellite Aerosol Optical Depth (AOD) product data from the last 20 years, combined with simulation results from the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), this paper focuses on the effects of air pollutants on summer precipitation in different regions of Beijing. These results showed that air pollution intensity during the summer affected the precipitation contribution rate (PCR) of plains and mountainous regions in the Beijing area, especially in the plains. Over the past 20 years, plains PCR increased by ~10% when the AOD augmented by 0.15, whereas it decreased with lower pollution levels. In contrast, PCR in mountainous areas decreased with higher pollution levels and increased with lower pollution levels. Our analysis from model results indicated that aerosol increases reduce the effective particle size of cloud droplets and raindrops. Smaller cloud raindrops more readily transport to high air layers and participate in the generation of ice-phase substances in the clouds, increasing the total amount of cloud water in the air in a certain time, which ultimately enhanced precipitation intensity on the plains. The removal of pollutants caused by increased precipitation in the plains decreased rainfall levels in mountainous areas.

Radial Growth Decline of White Spruce (Picea glauca) During Hot Summers without Drought: Preliminary Results from a Study Site South of a Boreal Forest Border

Here we investigate the possible future response of white spruce (Picea glauca) to a warmer climate by studying trees planted 90 years ago near the southern limit of their climate tolerance in central New York, 300 km south of the boreal forest where this species is prevalent. We employed high-frequency recording dendrometers to determine radial growth phenology of six mature white spruce trees during 2013-2017. Results demonstrate significant reductions in the length of radial growth periods inversely proportional to the number of hot days with air temperature exceeding 30 oC. During years with very hot summers, the start of radial growth began about 3 days earlier than the 2013-2017 average. However, in those same years the end of radial growth was also about 17 days earlier resulting in a shorter (70 versus 100 day), radial growth season. Abundant (350-500 mm) summer precipitation, which resulted in soil moisture values of 20-30% allowed us to dismiss drought as a factor. Instead, a likely cause of reduced radial growth was mean temperature that exceeded daily average of 30^oC that lead to photoinhibition.

Multivariate Dam-Site Flood Frequency Analysis of the Three Gorges Reservoir Considering Future Reservoir Regulation and Precipitation

Under a changing environment, the current hydrological design values derived from historical flood data for the Three Gorges Reservoir (TGR) might be no longer applicable due to the newly-built reservoirs upstream from the TGR and the changes in climatic conditions. In this study, we perform a multivariate dam-site flood frequency analysis for the TGR considering future reservoir regulation and summer precipitation. The Xinanjiang model and Muskingum routing method are used to reconstruct the dam-site flood variables during the operation period of the TGR. Then the distributions of the dam-site flood peak and flood volumes with durations of 3, 7, 15, and 30 days are built by Pearson type III (PIII) distribution with time-varying parameters, which are expressed as functions of both reservoir index and summer precipitation anomaly (SPA). The multivariate joint distribution of the dam-site flood variables is constructed by a 5-D C-vine copula. Finally, by using the criteria of annual average reliability (AAR) associated with the exceedance probabilities of OR, AND and Kendall, we derive the multivariate dam-site design floods for the TGR from the predicted flood distributions during the future operation period of the reservoir. The results indicate that the mean values of all flood variables are positively linked to SPA and negatively linked to RI. In the future, the flood mean values are predicted to present a dramatic decrease due to the regulation of the reservoirs upstream from the TGR. As the result, the design dam-site floods in the future will be smaller than those derived from historical flood distributions. This finding indicates that the TGR would have smaller flood risk in the future.

Climate Change Attribution in the Lena and Selenga River Runoff: An Evaluation Based on the Earth System and Regional Hydrological Models

The main goal of this study was to obtain the attribution results of a physical assessment of the modern hydrological consequences of separately natural and anthropogenic components of climate change, based on the synthesis of detailed process-based models of river runoff formation and an ensemble of Earth system models (ESMs) within the large river basins in Eastern Siberia. This approach allows calculating the river flow using ESM-based data over the observation period under two scenarios, considering: (1) the anthropogenic impact of increasing greenhouse gas emissions and (2) only internal fluctuations of the climate system and natural external forcing. According to the results of the numerical experiments, the attributions of anthropogenic components of climate change in the dynamics of the Lena runoff are weak, i.e., during the observation period, the Lena River flow statistically significantly increases, but it occurs mainly due to natural climate variability. The changes in the Selenga runoff are intensely influenced by the anthropogenic component of climate change. Since the 1970s, the Selenga runoff increased under natural climatic conditions, but since the mid-1980s, it decreased under anthropogenic greenhouse gas emissions, due to reduced summer precipitation. This was the main reason for the last low-water period of 1996–2017 in the Selenga basin.

Impact of Solar Activity on Snow Cover Variation Over the Tibetan Plateau and Linkage to the Summer Precipitation in China

Solar activity is one of the main external forcing factors driving the Earth’s climate system to change. The snow cover over the Tibetan Plateau is an important physical factor affecting the East Asian climate. At present, insufficient research on the connection between solar activity and snow cover over the Tibetan Plateau has been carried out. Using Solar Radio Flux (SRF), Solar Sunspot Number (SSN), and Total Solar Irradiance (TSI) data, this paper calculated the correlation coefficients with snow indices over the Tibetan Plateau, such as winter and spring snow depth (WSD/SSD) and snow day number (WSDN/SSDN). These snow indices are obtained from the daily gauge snow data in the Tibetan Plateau. Through correlation analyses, it is found that there are significant synchronous or lag correlations between snow indices and solar parameters on multi-time scales. In particular, the Spring Snow Day Number (SSDN) is of significant synchronous or lag correlation with SRF, SSN, and TSI on multi-time scales. It is further found that SSDN over the Tibetan Plateau has more stable positive correlations with SRF by using the 21-year running mean and cross spectrum analyses. Therefore, SSDN can be ascertained to be the most sensitive snow index to the solar activity compared with other snow indices. Moreover, its influence on summer precipitation of China is strongly regulated by solar activity. In high solar activity years (HSAY), the significant correlated area of summer precipitation in China to SSDN is located further north than that in low solar activity years (LSAY). Such impact by solar activity is also remarkable after excluding the impact of ENSO (i.e., El Niño–Southern Oscillation) events. These results provide support for the application of snow indices in summer rainfall prediction in China.

The Spatially Inhomogeneous Influence of Snow on the Radial Growth of Schrenk Spruce (Picea schrenkiana Fisch. et Mey.) in the Ili-Balkhash Basin, Central Asia

Snow has an important impact on forest ecosystems in mountainous areas. In this study, we developed 14 tree-ring-width chronologies of Schrenk spruce (Picea schrenkiana Fisch. et Mey.) for the Ili-Balkhash Basin (IBB), Central Asia. We analyzed the response of radial growth to temperature, precipitation and snow parameters. The results show that previous winter and current summer precipitation have an important influence on the radial growth of P. schrenkiana. Further, we find spatially inhomogeneous effects of snow on subsequent growing-season tree growth in IBB. The radial growth response of P. schrenkiana to snow shows a weak–strong–weak trend from west to east across the Ili-Balkhash Basin. This spatial difference is mainly related to precipitation, as snow has little effect on tree growth in regions that receive more precipitation. Thus, winter snow has an important influence on the radial growth of trees in regions that receive limited amounts of precipitation.

Main environmental variables influencing the abundance of plant species under risk category

Determining climatic and physiographic variables in Mexico's major ecoregions that are limiting to biodiversity and species of high conservation concern is essential for their conservation. Yet, at the national level to date, few studies have been performed with large data sets and cross-confirmation using multiple statistical analyses. Here, we used 25 endemic, rare and endangered species from 3610 sampling points throughout Mexico and 25 environmental attributes, including average precipitation for different seasons of the year, annual dryness index, slope of the terrain; and maximum, minimum and average temperatures to test our hypothesis that these species could be assessed with the same weight among all variables, showing similar indices of importance. Our results using principal component analysis, covariation analysis by permutations, and random forest regression showed that summer precipitation, length of the frost-free period, spring precipitation, winter precipitation and growing season precipitation all strongly influence the abundance of tropical species. In contrast, annual precipitation and the balance at different seasons (summer and growing season) were the most relevant variables on the temperate region species. For dry areas, the minimum temperature of the coldest month and the maximum temperature of the warmest month were the most significant variables. Using these different associations in different climatic regions could support a more precise management and conservation plan for the preservation of plant species diversity in forests under different global warming scenarios.