Impacts of Agricultural Areas on Spatio-Temporal Variability of Daily Minimum Extreme Flows during the Transitional Seasons (Spring and Fall) in Southern Quebec

Several statistical methods were used to analyze the spatio-temporal variability of daily minimum extreme flows (DMEF) in 17 watersheds—divided into three homogenous hydroclimatic regions of southern Quebec—during the transitional seasons (spring and fall), during the 1930–2019 period. Regarding spatial variability, there was a clear difference between the south and north shores of the St. Lawrence River, south of 47° N. DMEF were lower in the more agricultural watersheds on the south shore during transitional seasons compared to those on the north shore. A correlation analysis showed that this difference in flows was mainly due to more agricultural areas ((larger area (>20%) on the south than on the north shore (<5%)). An analysis of the long-term trend of these flows showed that the DMEF of south-shore rivers have increased significantly since the 1960s, during the fall (October to December), due to an increase in rainfall and a reduction in cultivated land, which increased the infiltration in the region. Although there was little difference between the two shores in the spring (April to June), we observed a decrease in minimum extreme flows in half (50%) of the south-shore rivers located north of 47° N.

LightGBM Low-Temperature Prediction Model Based on LassoCV Feature Selection

Icing disasters on power grid transmission lines can easily lead to major accidents, such as wire breakage and tower overturning, that endanger the safe operation of the power grid. Short-term prediction of transmission line icing relies to a large extent on accurate prediction of daily minimum temperature. This study therefore proposes a LightGBM low-temperature prediction model based on LassoCV feature selection. A data set comprising four meteorological variables was established, and time series autocorrelation coefficients were first used to determine the hysteresis characteristics in relation to the daily minimum temperature. Subsequently, the LassoCV feature selection method was used to select the meteorological elements that are highly related to minimum temperature, with their lag characteristics, as input variables, to eliminate noise in the original meteorological data set and reduce the complexity of the model. On this basis, the LightGBM low-temperature prediction model is established. The model was optimized through grid search and crossvalidation and validated using daily minimum surface temperature data from Yongshan County (station number 56489), Zhaotong City, Yunnan Province. The root mean square error, MAE, and MAPE of the model minimum temperature prediction after feature selection are shown to be 1.305, 0.999, and 0.112, respectively. These results indicate that the LightGBM prediction model is effective at predicting low temperatures and can be used to support short-term icing prediction.

Diverse Responses of Phenology in Multi-Grassland to Environmental Factors on Qinghai-Tibetan Plateau in China

Revealing grassland growing season spatial patterns and their climatic controls is crucial for the understanding of the productivity change mechanism in regional terrestrial ecosystem. However, the multi-grassland phenological factors are different, which has not been well studied. In this paper, the spatio-temporal patterns of the grassland start of the growing season (SOS) and the end of growing season (EOS) were investigated using MODIS Normalized Difference Vegetation Index (NDVI) on the Qinghai-Tibetan Plateau (QTP) during 2000 to 2019. At the same time, we analyzed the factors (including extreme and mean climate, drought, solar radiation, etc.) regulating grassland phenology under ongoing climate change. The results showed that the SOS appeared first in mountain meadow, shrub-tussock, temperature steppe and desert, then in alpine steppe and alpine meadow, showed a significant advancing tendency in all types. The EOS appeared first in temperature steppe, alpine steppe and alpine meadow, then in mountain meadow, shrub-tussock and desert. Further analysis indicated that the decrease of yearly minimum value of daily minimum temperature (TNN), yearly maximum value of daily minimum temperature (TNX), Temperature vegetation dryness index (TVDI) and the increase of yearly maximum consecutive five-day precipitation (RX5day) advance the grassland spring phenology, whereas the increase of solar radiation (SR) delay the grassland spring phenology. Meanwhile, SOS and its change rate showed the trend of significant delay and decline with the increase of altitude, respectively. We also found that the decrease of TVDI, TNN and the increase of yearly mean value of temperature (MAT_MEAN), yearly mean value of daily maximum temperature (MAT_MAX) and yearly mean value of daily minimum temperature (MAT_MIN) advanced the autumn phenology. The EOS and its change rate advance and increase with increasing altitude, respectively.

Climate anomalies in south-west Romania in the spring of 2020, in the context of climate change.

The paper analyzes the climatic anomalies in Oltenia that occurred in spring 2020. After the Mediterranean winter of 2019-2020, the spring was excessively early on large areas, and on average very early. As a result, the vegetation started to develop very early, since the first part of March, and the flowering of the early fruit trees took place in the first half of March. In the first two months of spring there were 31 days in which the daily minimum temperatures were negative and there was hoar and frost on the soil surface. Thus, in March, minimum negative temperatures were registered in the intervals: 1.III, 6.III, 16-19.III, 23-31.III, ie 15 days. In April, minimum negative temperatures were registered in the intervals: 1-10.IV, 15-16. IV, 23-25.IV and 27.IV, totaling 16 days. The cooling of the weather culminated with the interval 22-25.III, in which the highest amounts of precipitation were registered in March but also in the whole cold season 2019-2020. There were blizzards that deposited a consistent layer of snow and banks formed, lasting 4 days being the longest in the cold season 2019-2020. The intense cooling of the weather after the warm winters are destructive climatic anomalies. The paper is part of an extensive series of studies on climate variability in southwestern Romania (Oltenia) in the context of climate change (I. Marinică, 2006, 2008; Marinicǎ I., Marinicǎ Andreea Floriana, 2016).

Ecological features of a Rana iberica population inhabiting a human-altered ecosystem

In this work, data are presented about spatial use and behaviour of Iberian brown frog (Rana iberica) during and after the breeding season in Pontevedra (north-western Spain). Field data were collected between November 2008 and February 2010 at a human-altered stream. The results suggest that there was a change in habitat use between the breeding and the non-breeding seasons. Rana iberica individuals concentrated in the upper part of the stream during the breeding season (November-March), moving to lower parts of the stream during late spring and summer. The estimated monthly frog abundance was inversely correlated to the recorded mean daily minimum temperatures.

Measurement report: Short-term variation in ammonia concentrations in an urban area increased by mist evaporation and emissions from a forest canopy with bird droppings

Local meteorological conditions and natural and anthropogenic sources affect atmospheric NH3 concentrations in urban areas. To investigate potential sources and processes of NH3 variation in urban areas, hourly NH3 and NH4+ concentrations were measured during November 2017–October 2019 in Nagoya, a central Japanese megacity. Average NH3 concentrations are high in summer and low in winter. Daily minimum NH3 concentrations are linearly correlated with daily minimum air temperatures. By contrast, daily maximum NH3 concentrations increase exponentially with temperature, suggesting that different nighttime and daytime processes and air temperatures affect concentrations. Short-term increases in NH3 concentrations of two types were examined closely. Infrequent but large increases (11 parts per billion (ppb) for 2 h) occurred after mist evaporation during daytime. During 2 years of observations, only one event of this magnitude was identified in Nagoya, although evaporation of mist and fog occurs frequently after rains. Also, short-term increases occur with a large morning peak in summer. Amplitudes of diurnal variation in NH3 concentration (daily maximum minus minimum) were analyzed on days with nonwet and low wind conditions. Amplitudes were small (ca. 2 ppb) in winter, but they increased from early summer along with new leaf growth. Amplitudes peaked in summer (ca. 20 ppb) because of droppings from hundreds of crows before roosting in trees on the campus. High daily maximum NH3 concentrations were characterized by a rapid increase occurring 2–4 h after local sunrise. In summer, peak NH3 concentrations at around 08:00 local time (LT) in sunny weather were greater than in cloudy weather, suggesting that direct sunlight particularly boosts the morning peak. Daily and seasonal findings related to the morning peak imply that stomatal emission at the site causes the increase. Differences between daily amplitudes during the two summers was explained by the different input amounts of reactive nitrogen from bird droppings and rain, suggesting that bird droppings, a temporary rich source of NH3, affected the small forest canopy.