Climate change and its wide-ranging influence are driving countries worldwide to implement carbon neutrality strategies.Starting from the building theoretical system of carbon neutrality, this paper proposed the basic principles of carbon neutrality and climate adaptive building design and emphasized the dynamic-balance consideration between the energy-saving benefits (operational carbon) and implementation costs (embedded carbon) in the whole life cycle of passive buildings.According to regional climate characteristics and urban morphological features, this paper also focused on the adaptive feedback of passive buildings to the physical environmental characteristics such as wind, heat, and light at the site.Furthermore, this paper identifies the carbon source/sink scenarios of passive buildings in Chongqing from aspects of site and climate, building type, the envelope structure, ventilation, lighting, renewable energy utilization, and other technologies, and discusses the potential of applying passive strategies to reduce carbon emissions from buildings under the climates of "humid and hot, humid and cold, and weak winds" in Chongqing.This will promote the construction of a net-zero carbon city in Chongqing.

We analyzed two sudden local rainstorm processes in the Yuanbao Mountain area of Liuzhou, Guangxi Zhuang Autonomous Region, on June 24 and July 9, 2020, and discussed their triggering factors using conventional observation data, data from regional automatic stations and Doppler radar in Liuzhou, and ERA5 reanalysis data.The results showed that the dynamic uplift of Yuanbao Mountains further enhances the vertical upward movements near the mountain on the premise that the low-level southerly warm and humid airflow continues to transport.A large amount of accumulated energy during the day time leads to very unstable thermal conditions.The combination of the mesoscale convergence line on the ground and the mesoscale convergence center formed by the local terrain and the large-scale circulation causes the convection system to be triggered first on the southern side of the Yuanbao Mountains.The "train effect" and a high-efficiency and low-centroid rainfall system result in extremely large hourly precipitation intensities and cumulative precipitation.The two processes are closely related to the wind speed fluctuation of southwest airflow at 850 hPa.The strong convergence of warm and humid airflow with high temperature and high humidity in the Yuanbao Mountains provides favorable conditions for the increase of rainstorms, which is conducive to the maintenance of heavy rainfall in northern Liuzhou.During the process on June 24, weak cold air intrudes into the near-surface layer, the lower layer is saturated with water vapor, and dry and cold air is involved in the middle and high layers.While during the process on July 9, there is no cold air intrusion near the ground.Meanwhile, the wet layer is deep, and the whole layer is a high temperature and high humidity environment.

We selected 20 cases of two types of weather processes with different precipitation properties in Liaoning province from June to September in 2017 and 2018.These cases are used to evaluate the forecast capabilities of the meso- and small-scale systems in Liaoning province with the East China Model, the North China Model, the Global/Regional Assimilation and Prediction System (GRAPES)_3km Model, and the Northeast China Weather Research and Forecasting (WRF) Model, based on the Fraction Skill Score (FSS) in the fuzzy test neighborhood method.The results showed that for the regional precipitation process and local precipitation process, the smaller the radar echo intensity is, the larger the neighborhood radius is, and the better the prediction skill of the high-resolution model is.When the radar echo is greater than 30 dBz, the FSS scores of the radar echo prediction for localized precipitation are higher in all high-resolution models.When the neighborhood radius is 3 km, the forecasting skills of the North China Model for all-level radar echo during regional precipitation are better than other models, with a maximum FSS difference being 0.031.In the process of localized precipitation, the East China Model performs better, with a maximum FSS score of 0.127, indicating that the East China Model has a stronger capability to predict small and medium-scale convective systems.For the local precipitation process, among the forecast periods between 08:00 and 23:00 in the Northeast China WRF_3km model, the forecast performs better in the "middle" period than the "beginning and ending" period, with their maximum FSS difference of 0.121.

Based on the hourly meteorological observation data (relative humidity, wind speed, ground-air temperature difference, and visibility) and air quality index (AQI) data from 2015 to 2019 in Yiwu of Zhejiang province, we analyzed the distribution and meteorological conditions of low visibility (observed visibility lt; 10 km) in Yiwu.The Long Short-term Memory Neural Network (LSTM) was used to simulate the hourly visibility, and the simulation results with and without observed visibility as an input member were compared.According to the meteorological conditions of low visibility, the simulation period was divided into three periods (from November to February, from March to June, and from July to October).We compared the simulation performance in different periods and evaluated the model prediction steps.The results showed that the high humidity, high pollution, air temperature higher than the surface temperature, and low wind speed are the main meteorological characteristics influencing the low visibility weather in Yiwu.The LSTM has a good performance in simulating visibility at a single station.When the historical observed visibility has been used as an input parameter, the simulation accuracy can be greatly improved, with the root mean square error (RMSE) of 0.63 km, the mean absolute error (MAE) of 0.51 km, and the fitting goodness R² of 0.99.Better simulation can be reached after dividing different periods, and the best simulation occurred in winter (from November to February) using the input elements selected in this study, with RMSE=2.35 km and MAE=1.46 km, and for low visibility weather, the RMSE_10km=1.81 km, MAE_10km=1.13 km, and R²=0.83.In the simulation from March to June, the simulation of low visibility without AQI as one input member performs better, which means that low visibility in Yiwu is dominated by foggy weather in this period.Adding too many variables does not necessarily improve the accuracy of the model.With the increase in the forecast step size, the simulation performs worse.When the forecast step size equals 3 h, R² reaches 0.71 and the simulation result has no practical application significance.

Based on the long-term observation data of aerosol optical properties at Longfengshan regional background station in Heilongjiang province from 2010 to 2020, the variation of aerosol optical depth, Angström exponent, single scattering albedo, particle volume size distribution, and aerosol direct radiative effect were analyzed.The results show that the maximum aerosol optical depth in the background area appears in July, with an average value of 0.67.The smaller values occur in December, January, and February, with an average value of 0.17, 0.02, and 0.18, respectively.The daily aerosol optical depth reaches the highest value of 0.39 at 17:00. The Angström exponent decreases significantly in April and May, with an average value of 1.20 and 1.21, respectively.The Angström exponent reaches the largest value in December, with an average value of 1.74.The low value of single scattering albedo (SSA) occurs in April, August, and October, with the average values of 0.84, 0.82, and 0.84, respectively.The peak Angström exponent reaches 1.44 at noon.The maximum volume of coarse mode particles appears in May, which is about 0.04 μm³·μm^-2, and the effective radius is about 3.85 μm.The maximum volume of fine mode particles is 0.06 μm³·μm^-2 with an effective radius of 0.19 μm appeared in July.In autumn and winter, the volume of fine and coarse mode particles further decreases in Longfengshan.The maximum values of aerosol direct radiative effect at the ground and on the top of the atmosphere appear in July with values of -94.44 W·m^-2 and -22.33 W·m^-2, respectively.

Based on the daily precipitation and temperature data of eleven meteorological stations in Daxing'anling forest region in Inner Mongolia Autonomous Region from 1970 to 2019, the spatial and temporal variation characteristics of snowfall in this region were analyzed using trend analysis method, anomaly method, M-K mutation method and sliding t-test method after extracting the snowfall data.The results show that the total snowfall and all grades of snowfall indicate an increasing trend in the Daxing 'anling forest region, and the increasing trends of light snow and heavy snow were small.The amounts of light and moderate snow reach the maximum in the 2000s, and the amounts of heavy snow and snowstorm reach the maximum in the 2010s.The contribution rate of snowfall in each grade to the total precipitation is as follows: light snow>moderate snow>heavy snow>snowstorm.The monthly variation of snowfall in all grades shows an "M" shape, and the peak value of total snowfall occurs in November.In terms of mutation, the total snowfall has a significant mutation in 1995, while the snowfall of light snow, moderate snow, heavy snow, and heavy snow has no significant mutation.In space, the total snowfall and the snowfall of each grade (except snowstorms) generally show a trend, with more in the north and less in the south, more in the west, and less in the east.In the forest area, the beginning day of snowfall is delayed, and the end day is advanced.The length of the snow season is shortened by 2.3 days every 10 years.

Using MOD13Q1 data and meteorological observation data from 2000-2020, the temporal and spatial variation of the Normalized Difference Vegetation Index (NDVI) and its climatic response in Hulun Buir were analyzed using Sen trend analysis, M-K significance test, coefficient of variation, Hurst index, and correlation coefficient methods.The results show that the annual average NDVI in Hulun Buir is 0.63 during the growing season, and the annual average tendency rate is 0.028 per decade.Most regions show an increasing trend, especially in most forest areas and farmlands in the west of Daxing'anling.The average coefficient of variation in NDVI in Hulun Buir is 0.08 during the growing season, and the fluctuation in the grassland distribution in the western part of Hulun Buir is larger.The Hurst index indicates that the overall change of NDVI in the Hulunbuir area during the growing season shows an anti-persistent trend.Combined with the current change trend of NDVI, it shows a downward trend in the future, which is unfavorable to the protection of the ecological environment.As a whole, there is a positive correlation between NDVI and temperature in the forest during the growing season, while negative correlation between cultivated land and grassland.Generally, precipitation has a positive correlation with NDVI in most areas of Hulun Buir during the growing season, especially in cultivated land at the foothills of Hulun Buir grassland and Daxing'anling.That indicates that temperature is the main factor to mediate forest growth in northern Daxing'anling, while precipitation restricts the ecological balance between Hulun Buir grassland and the development of agriculture and animal husbandry.

Based on the phenological data of spring maize and meteorological observation data at Jinzhou agrometeorological observation station from 1980 to 1984 and 2004 to 2020, the changing trends of spring maize growth period length and hydrothermal factors at the same time were studied using the methods of trend coefficient, tendency rate, correlation analysis, and path analysis.In addition, the relationship between spring maize growth period length and hydrothermal conditions was discussed.The results show that each of the growth period lengths of spring maize in Jinzhou has different trends from 1980 to 1984 and 2004 to 2020.Except for tasseling period, maturity period, and reproductive growth period, the length of other growth periods shows a shortening trend.Particularly, the length of the vegetative growth period is significantly shortened, while the length of the reproductive growth period is significantly prolonged, The whole growth period shows a weak extension trend, and the change is not obvious.The changing trend of hydrothermal conditions in each growth period of spring maize is different.The variation of heat conditions is large, while the variation of water conditions is relatively small.The active accumulated temperature ≥ 10 ℃ (DT10) and Growth Degree Day (GDD) in most growth periods show an increasing trend, and there is a very significant increase in tasseling period, maturity period, reproductive growth period, and whole growth period.It can be seen that heat conditions have a great impact on the growth and development of spring maize.Correlation analysis and path analysis show that both DT10 and GDD have a great effect on the growth period length of spring maize, while water conditions have less effect.The length of seedling period, maturity period, and whole growth period are significantly correlated with water conditions.The water and heat factors restrict and influence each other, and jointly affect the whole growth period of spring maize.

Based on maize yield data, NCEP re-analysis data, self-calibrating Palmer drought severity index (scPDSI), standardized precipitation-evapotranspiration index (SPEI), soil water content and sea surface temperature (SST) data, the effect of pacific SST tripole on climatic yield of spring maize in northeast China was analyzed.It was found that the climatic yield of spring maize in northeast China was significantly correlated with the Pacific SST tripole from January to May of the harvest year.The Pacific SST tripole could influence the regional circulation field during the seeding stage and the whole growing season of spring maize in northeast China through the teleconnection pattern over the Pacific, and then affect regional precipitation, soil moisture content, scPDSI, and SPEI, which are closely related to the climatic yield of spring maize in northeast China.When the Pacific SST tripole strengthens, a Rossby-wave-like teleconnection pattern will be formed over the Pacific, resulting in a negative vorticity anomaly in the upper air of northeast China, which is conducive to the formation of local updraft and the increase of precipitation.The Pacific SST tripole is also conducive to the formation of the southeast wind anomaly from the northwest Pacific to northeast China at the low level, which further enhances the precipitation in northeast China through water vapor transport.

Based on the daily meteorological data from 69 meteorological stations from 1971 to 2018, the method recommended by FAO was used to calculate the water need by maize.In addition, the effective precipitation was calculated using the U.S.Department of Agriculture Soil Conservation method.Mann-Kendall test and GIS inverse distance weighted interpolation were used to analyze the coupling degree between maize water need and effective precipitation and its evolution characteristics in Heilongjiang province.The results showed that the effective precipitation increased in most areas during the growth period before maize jointing in Heilongjiang province, but it decreased in most areas during the growth period after maize jointing, and the changing trend was slightly different in different regions.Affected by meteorological factors such as the decrease in wind speed and daylight hours, the maize water need in most areas of Heilongjiang province decreased, and the speed of deceleration was the fastest in the east and the slowest in the north.The coupling degree of maize water requirement and effective precipitation was higher in the middle and northeast of Heilongjiang province, and it was lower in the west; the coupling degree was lower before jointing, and it was higher after jointing.The coupling degree of each region showed a trend of decrease-increase-decrease-increase in Heilongjiang province.From 2011 to 2012, it was the obvious mutation point of the coupling degree from low to high.

Based on the observation data of daily precipitation, wind speed, and maximum temperature in winter from 1961 to 2020 in Jilin province, the meteorological factors and their variations affecting winter tourism travel in Jilin province were analyzed, and the meteorological conditions for winter tourism travel were further evaluated.The results show that the average winter snowless period in Jilin province is long, the days with wind speed below grade 2 appear frequently, and the days with a daily maximum temperature of greater than -12 ℃ account for around 90% of the total winter days.There are 128.6 days highly suitable and suitable for tourism in winter in Jilin province, accounting for 85.2% of the total winter days with an increasing trend of 4.1 d /10 a.In the context of climate warming, the highly suitable and suitable days for tourism increased significantly from 1991 to 2020 after the sudden meteorology variations with the average days of 135.1 accounting for nearly 90% of the total winter days.However, the increase of the sliding mean square deviations of the highly suitable and suitable days also leads to an increase in their instability.

Based on the observation data of 10-minute wind at 9 national weather stations and 165 regional weather stations in the Dalian region of Liaoning province from May 2015 to April 2020, the maximum, mean, and minimum gust coefficients in the Dalian region were statistically analyzed in terms of wind direction, wind level, monthly variation, daily variation, spatial variation and weather influence system.The results show that the variation of the mean gust coefficients from January to December ranges from 1.66 to 1.77.The average gust coefficient of the wind direction corresponding to the cold air is larger than that corresponding to the warm air.The mean gust coefficient of the wind directions corresponding to cold air is greater than the wind directions corresponding to warm air.With the increase in wind level, the maximum and minimum gust coefficients converge to the average gust coefficient.The frequency distribution of the gust coefficient at different wind levels is unimodal, and the larger the wind level appears, the narrower the distribution ranges.Except for the southwesterly wind, the gust coefficients of other wind directions are high during the day and low at night.The gust coefficient in Dalian has obvious regional characteristics.The wind gust coefficient in the southeast and northwest coastal areas is smaller than that in inland and southwest coastal areas, and the wind direction does not affect the spatial distribution of the wind gust coefficient.The winding process in Dalian is mainly affected by the dual systems of a maritime cyclone and front high pressure, thus the average gust coefficient of a cyclone, typhoon, and thunderstorm gale is larger than the average of the same wind level.

Using sounding data from 2014 to 2018 in Liaoning province, the vertical wind profile variations in average horizontal wind speed were analyzed.Monthly and diurnal variations in the wind shear index of different height combinations were analyzed based on hourly gradient wind observation of two representative wind measuring towers.Wind speed and wind power at the upper tower were calculated by monthly, hourly, and annual wind shear indexes, respectively, which were then compared with observations.The results show that compared with Dalian, the wind speed in Shenyang increases more significantly with height, and the wind speed above 180 m remains constant, whereas the wind speed below 300 m rises uniformly in Dalian due to its low latitude and proximity to the ocean.Since the terrain is not complex enough, four layers of wind observation are set up at a certain height above 10 m from the ground, which are suitable for surface wind resource assessment.Influenced by solar radiation, underlying surface and thermal property discrepancies between sea and land, the diurnal variations of wind shear index in Liaoning province appear more significant than those of the monthly variations.Hourly wind shear index is superior to monthly and annual wind shear index in calculating wind speed and wind power at the upper tower.The more significant the diurnal variation of the wind shear index is, the better the calculation scheme using the hourly wind shear index appears compared with other calculation schemes.