The use of different climatological normal periods means the change of the evaluation results of meteorological elements, the abnormal state of climate events and their change characteristics, which have a substantial impact on the climate monitoring and prediction operations. Using temperature and precipitation observation data from national meteorological stations in Ningxia from 1981 to 2021, this study conducted a comparative analysis of the temperature and precipitation characteristics between the old climatological normal period (1981-2010) and the new climatological normal period (1991-2020). Additionally, it explored the changes in extreme characteristics of these factors. The results are as follows: Compared to the old climatological normal period, the annual and seasonal average temperatures in Ningxia are generally higher in the new climatological normal period, which is particularly evident in spring, summer and winter, and the frequency of abnormally high (low) temperatures increases (decreases) accordingly. Yinchuan, the western part of Wuzhong, and the northern part of Zhongwei are areas experiencing significant temperature increase. The overall intensity of extreme high (low) temperature has intensified (weakened), and their frequency has increased (decreased). In summer, the threshold and intensity of extreme high-temperature rise across various regions, especially in the central and northern areas, while in winter, the intensity of extreme low-temperature weakens in most regions, the amplitude of extreme low-temperature varies significantly. The average annual precipitation, as well as the summer, autumn and winter average precipitation, are greater in the new climatological normal period compared to the old. There’s an increased frequency of abnormally more precipitation in summer and autumn, whereas the opposite trend is observed in spring and winter. Meanwhile, the frequency of abnormally less precipitation in all seasons has decreased to some extents. There are significant spatial differences in seasonal precipitation, with a general increase in precipitation in summer and autumn, and a pattern of “decreasing in the north and increasing in the south” in spring and winter. The overall trend of extreme precipitation in spring and autumn (summer and winter) is intensifying (weakening), albeit with fewer (more) extreme precipitation events. In summer, the threshold and intensity variations of extreme precipitation are greater in the north and south, and smaller in the central region, with a notable increase in extreme precipitation in Shizuishan.

Heilongjiang Province is the major grain production base in China, the study of drought climate characteristics in Heilongjiang Province is of great importance for scientific prevention and management of drought disasters. Based on daily temperature and precipitation data from 80 national meteorological stations in Heilongjiang Province from May to September during 1971-2020, the daily meteorological drought composite index (MCI) of Heilongjiang Province was calculated, and the spatial and temporal distribution characteristics of drought, severe drought and extreme drought days in Heilongjiang Province were analyzed. At the same time, the circulation characteristics of typical dry and wet years were further analyzed. The results show that from May to September during 1971-2020, the southern part of the Greater Hinggan Mountains and the western part of Songnen Plain in Heilongjiang Province are drought-prone areas. The number of dry days is more in the west and some areas of the central hinterland and less in the east. The inter-decadal characteristics of medium drought, severe drought and extreme drought are obvious and show a decreasing trend. The decreasing trend of medium drought was the most obvious with a rate of -1.7 d·(10 a)^-1. There are significant differences in circulation patterns between typical dry years and wet years. In typical dry years, the area west of Lake Baikal is controlled by anticyclones, while Heilongjiang is controlled by the westerly jet stream, resulting in prevailing descending airflow, which is not conducive to the intersection of cold and warm air, and the water vapor transport channel is not obvious, so water vapor is difficult to reach the Heilongjiang region. Conversely, in typical wet years, the situation is the opposite.

Based on data such as first frost date in Ningxia, geopotential height, sea surface temperature (SST), snow cover area, and sea ice area from 1981 to 2019, the influence of external forcing factors including sea surface temperature, sea ice area, and snow cover area on the abnormally early and late first frost in Ningxia was studied. On the basis of above, a physical conceptual model and an objective prediction model for predicting first frost date were established. The results are as follows: (1) In the early years of first frost, the SST in the equatorial central and eastern Pacific continued to be significantly warmer in the early period, and the SST anomaly presented an obvious ENSO model. When the SST of the equatorial central and eastern Pacific was warmer in the early period, the east Asian trough was stronger and the subtropical high was weaker, which was conducive to cold air activity. So, first frost date was early, otherwise it was late. (2) The snow cover area in the northern hemisphere from May to August in the early period and the sea ice area of Greenland from January to July had a continuously and significantly negative correlation with the date of first frost. When the snow cover in the northern hemisphere decreased or the sea ice in Greenland decreased, the east Asian trough was weaker and the western Pacific subtropical high was relatively stronger, which was not conducive to active cold air, causing first frost to be late, and vice versa. (3) The main factors affecting the date of first frost in Ningxia were the intensity of the east Asian trough, the SST anomaly in the NINO3.4 area, the SST anomaly in the tropical south Atlantic, the snow area in the northern hemisphere, the intensity of the western Pacific subtropical high, and the area of Greenland sea ice. The objective prediction model established by using the multiple regression equation had a good prediction effect.

Based on the observational rainfall data in July of Ningxia, the NCEP/NCAR reanalysis data and the ERSSTv5 SST data from 1981 to 2018, the variation characteristics of precipitation in July in Ningxia and their formation causes were analyzed. This paper also discussed the influence of the equatorial Pacific SST anomaly on precipitation. The results are as follows: (1) In the past 38 years, the inter-annual variability of precipitation in July was significant, but the extremity and anomaly of precipitation both increased after 2000. (2) The 500 hPa geopotential height anomaly was low over the Balkash lake and it was high between North China, the Northeast China and the Sea of Japan in mid-high latitudes. The active low-pressure system from the Bay of Bengal to the South China Sea, coupled with water vapor transported by the southerly anomaly on 700 hPa from the Northwest Pacific, led to more precipitation in July in Ningxia. (3) Since the 21th century, the implication of equatorial Pacific SST on precipitation in July has strengthened, especially during late winter and early spring during the ENSO decaying phase. When the SST anomaly in the equatorial Pacific characterized  by a dipole pattern, namely, warm (cold) in the west and cold (warm) in the central, and the subtropical western Pacific anomaly cyclone (anticyclone) in July played an important role in transportation of water vapor. The pattern of lower in the west (east) and higher in the east (west) existed on 500 hPa height, which was favorable to more (less) precipitation and reflected the impact of the central pacific type of ENSO on precipitation in Ningxia to some extent.

Abstract: Based on the every 3-hour precipitation data from ERA-Interim dataset of European Centre for Medium-Range Weather Forecast (ECMWF) during 1979-2017, the spatial and temporal variation characteristics of precipitation in Qilian Mountain and its surrounding areas in the past 39 years were analyzed. The results show that the average annual precipitation in the study area was 232.4 mm, the precipitation had an increasing trend with a climate trend rate of 24.7 mm·(10 a)-1, and precipitation increased obviously in the semi-humid area, with a climate trend rate of 45.9 mm·(10 a)-1. The precipitation had a mutation between 1996 and 1997, and then increased significantly after 2000. The precipitation in the study area was largest in summer, accounting for 54.08% of the annual precipitation, while it was smallest in winter, accounting for 3.88% of the annual precipitation. The maximum monthly precipitation was 45.1 mm in July, while the minimum was 2.7 mm in December. The diurnal variation of precipitation had two peaks, the maximum peak value occurred during 14:00-20:00, and the second peak vaule occurred during 05:00-08:00. Both of the annual precipitation and climate trend rate in the study area had a good correspondence with the altitude. The higher the altitude was, the greater the precipitation would be, and the maximum precipitation was in the high altitude area in the central part of Qilian Mountains. The distribution of annual precipitation was mostly from northwest to southeast, and precipitation in the central and eastern parts of the Qilian Mountains was relatively larger.

Based on monthly temperature in winter from 20 meteorological stations in Ningxia, monthly sea ice concentration in autumn from the Hadley Centre of UK and monthly atmospheric reanalysis in winter from the NCEP/NCAR from 1961 to 2016, temperature anomaly and its causes in winter of 2016 in Ningxia were studied. The results show that the temperature in winter of 2016 was the highest in the same period since 1961 in Ningxia. In 2016, the 500 hPa zonal circulation was obvious over the middle and high latitudes of Eurasia, and the Ural mountains blocking high was unusually weak, and geopotential height over the mainland China was unusually higher, and position of polar vortex skewed Europe and North America. East Asian winter monsoon index was 1.3 m·s-1, which was the fifth low value since 1961, and Siberia high intensity anomaly was 1.5 hPa, which was the second low value since 2000. The sea ice concentration of  Greenland sea in autumn had a significant influence on temperature in winter in Ningxia. When the sea ice concentration was low, the East Asian winter wind was weaker,the wave pattern labeling “-+-”  on 500 hPa geopotential height in Arctic, Eurasia and Aleutian region enhanced the height difference between the Arctic and Eurasia in the middle and high latitudes, and the westerly airflow over the middle and high latitudes was stronger, and the zonal activity was strengthened. At the same time the weaker Siberian high in the sea level pressure field was not conducive to the Arctic cold air intruding into low latitude region. All above reasons resulted in  higher temperature anomaly in 2016 in Ningxia.

The variations of the accumulated temperature and the sunlight hours inMaqu grassland in recent 40 yearswere analyzed by using a non - parameterMann - Kendall testmethod and wavelet analysis. The results show that annual variation of accumulated temperature tended to increase, and the tendency rate of ≥ 0 ℃ accumulated temperature is 59. 5 ℃/10 a, and 33. 7 ℃/10 a for ≥ 10 ℃ accumulated temperature. The period corresponding to high oscillation center of ≥10 ℃ accumulated temperature is two yearsmore than that of ≥0 ℃ accumulated temperature; the low and high frequency oscillation tended to increase at the same time. The annual trend of sunlight hours is also increasing, and the tendency rate is 40. 2 h /10 a. By Spearman’s order correlation analysis, we know that the positive matching characteristic of light, heat and water is remarkable; the synchronous changes p resented inMay to Sep tember forwater and heat, and June to July for light and water. The app rop riate p recip itation, higher air temperature and the adequate sunshine are helpful to pasture’s growth ofMaqu grassland.