Nocturnal-to-morning rains during the warm season in South China:characteristics and predictability

The characteristics of nocturnal-to-morning rainfall(NMR)during the warm season in South China are examined using hourly surface observations from 2015–2019.Results show that strong NMR is mainly located in coastal regions and mountainous areas.NMR mainly occurs during 0200–0800 LST.The distribution of NMR can be divided into two types.The first pattern is a coastal type where NMR is mainly located at windward sites,such as southern coastal mountain areas in Guangdong(GD)and in Guangxi(GX).The second type is an inland type where NMR is mainly located at windward sites,such as the northern mountainous areas in GX and the Pearl River Delta regions in GD.The strong convergence between the northerly wind over the mountainous regions and southerly wind,as well as the strong downhill winds strengthened by the narrow pipe effect over the valleys in mountainous areas,together contribute to the high frequency of inland NMR.The strong southeasterly onshore wind and the cyclonic circulations strengthened by the northeasterly wind over the northern mountainous areas contribute to the high frequency of coastal NMR.Though the GRAPES(Global/Regional Assimilation and Prediction System)model can capture the intensity and distribution of large-scale NMR,it exhibits low predictability of small-scale NMR,especially that in the warm sector.

Cloud Radiative Effects and Changes Simulated by the Coupled Model Intercomparison Project Phase 5 Models

Using 32 CMIP5（Coupled Model Intercomparison Project Phase 5） models, this study examines the veracity in the simulation of cloud amount and their radiative effects（CREs） in the historical run driven by observed external radiative forcing for 1850-2005, and their future changes in the RCP（Representative Concentration Pathway） 4.5 scenario runs for2006-2100. Validation metrics for the historical run are designed to examine the accuracy in the representation of spatial patterns for climatological mean, and annual and interannual variations of clouds and CREs. The models show large spread in the simulation of cloud amounts, specifically in the low cloud amount. The observed relationship between cloud amount and the controlling large-scale environment are also reproduced diversely by various models. Based on the validation metrics,four models-ACCESS1.0, ACCESS1.3, Had GEM2-CC, and Had GEM2-ES-are selected as best models, and the average of the four models performs more skillfully than the multimodel ensemble average.All models project global-mean SST warming at the increase of the greenhouse gases, but the magnitude varies across the simulations between 1 and 2 K, which is largely attributable to the difference in the change of cloud amount and distribution. The models that simulate more SST warming show a greater increase in the net CRE due to reduced low cloud and increased incoming shortwave radiation, particularly over the regions of marine boundary layer in the subtropics. Selected best-performing models project a significant reduction in global-mean cloud amount of about-0.99% K^-1and net radiative warming of 0.46 W m^-2K^-1, suggesting a role of positive feedback to global warming.

Responses of Climatic Change on the Lagging Time about Ground Temperature Reaching the Extremum at Shallow Layers Soil in Wuli

The air temperature of Wuli,which is located in seasonal frozen ground zone,is rising by 13 ℃ yearly.This paper discusses the days that each ground layers' temperature lags behind the surface temperature in reaching extremum.The results were shown:The time of each ground layers' lagging days was increasing;the lagging day in warm season was longer than that in cold season;the growth rate of lagging days in warm season was 0.5 d/y,while the growth rate of lagging days in cold season was 0.7 d/y.

Influence of Near Real-Time Green Vegetation Fraction Data on Numerical Weather Prediction by WRF over North China

The green vegetation fraction(GVF)can greatly influence the partitioning of surface sensible and latent heat fluxes in numerical weather prediction(NWP)models.However,the multiyear averaged monthly GVF climatology—the most commonly used representation of the vegetation state in models—cannot capture the real-time vegetation state well.In this study,a near real-time(NRT)GVF dataset generated from an 8-day composite of the normalized difference vegetation index is compared with the 10-yr averaged monthly GVF provided by the WRF model.The annual variability of the GVF over North China is examined in detail.Many differences between the two GVF datasets are found over dryland,grassland,and cropland/grassland mosaic areas.Two experiments using different GVF datasets are performed to assess the impacts of GVF on forecasts of screen-level temperature and humidity.The results show that using NRT GVF can lead to a widespread reduction of 2-m temperature forecast errors from April to October.Evaluation against in-situ observations shows that the positive impact on 2-m temperature forecasts in the morning is more distinct than that in the afternoon.Our study demonstrates that NRT GVF can provide a more realistic representation of the vegetation state,which in turn helps to improve short-range forecasts in arid and semiarid regions of North China.Moreover,our study shows that the negative effect of using NRT GVF is closely related to the initial soil moisture.

Decontamination efficiency and root structure change in the plant-intercropping model in vertical-flow constructed wetlands

Subtropical climatic conditions can contribute to the death of the aerial parts of constructed wetland plants in winter. This presents a barrier to the widespread application of constructed wetland and is an issue that urgently needs to be solved. Three contrasting experi- ments, the plant-intercropping model （A）, the warm- seasonal plant model （B）, and the non-plant model （C）, were studied in terms of their efficiency in removing pollutants, and the change in root structure of plants in the plant-intercropping model within the vertical-flow con- structed wetlands. The results indicate that model A was able to solve the aforementioned problem. Overall, average removal rates of three pollutants （CODcr, total nitrogen （TN） and total phosphorous （TP）） using model A were significantly higher than those obtained using models B and C （P 〈 0.01）. Moreover, no significant differences in removal rates of the three pollutants were detected between A and B during the higher temperature part of the year （P〉 0.05）. Conversely, removal rates of the three pollutants were found to be significantly higher using model A than those observed using model B during the lower temperature part of the year （P 〈 0.01）. Furthermore, the morphologies and internal structures of plant roots further demonstrate that numerous white roots, whose distribution in soil was generally shallow, extend further under model A. The roots of these aquatic plants have an aerenchyma structure composed of parenchyma cells, therefore, roots of the cold-seasonal plants with major growth advantages used in A were capable of creating a more favorable vertical-flow constructed wetlands media- microenvironment. In conclusion, the plant-intercropping model （A） is more suitable for use in the cold environment experienced by constructed wetland during winter.