Based on hourly temperature and precipitation grid data of CMA land data assimilation system (CLDAS), ground meteorological observation data at 119 weather stations of Inner Mongolia and the spatial distribution of irrigated crop fields, the key meteorological factors and climatic division indexes were determined by considering fully planting technology and agricultural climatic characteristics of sunflower following spring wheat harvest in agro-climatic ecological regions of Inner Mongolia. And taking suitable growth days and climate suitability in the whole growth period as zoning indicators, the refined climatic suitability division of sunflower following spring wheat harvest in Inner Mongolia was studied under the operation of ArcGIS. The results show that the heat shortage and drought in growing season mainly restricted the regular growth and yield formation of sunflower following spring wheat harvest in Inner Mongolia, and the whole region was divided into unsuitable zone, more suitable zone, suitable zone and the most suitable zone. The irrigation conditions in Hetao irrigation district, Tumochuan plain and West Liaohe plain were better, which were particularly suitable to the growth of sunflower following spring wheat harvest, so these regions were the most suitable districts of sunflower growing. Due to serious shortage of heat resource in most areas of middle and eastern Inner Mongolia and the deficit of precipitation in the north of mid-western Inner Mongolia after the transplanting, the sunflower following spring wheat harvest was quite immature, so these regions were unsuitable areas of sunflower growing. The climatic suitability division of sunflower following spring wheat harvest based on grid data of CLDAS was consistent with the division distribution based on meteorological data of weather stations in Inner Mongolia, but the details of CLDAS data division were more refined than that of stations data. Hetao irrigation district was the most suitable area of sunflower following spring wheat harvest in Inner Mongolia, which was accord with the current layout of sunflower following spring wheat harvest. Therefore, this division result could provide some references for the rational layout of sunflower following spring wheat harvest in Inner Mongolia under the background of climate change.

Based on soil moisture and meteorological elements data at four pasture observation stations in typical steppe of Inner Mongolia from 1981 to 2015, the correlations between multi-time-scales meteorological drought indexes and soil relative moisture at different depths in spring, summer and autumn were comparatively analyzed, and the applicability of these drought indexes to drought monitoring was explored in typical steppe of Inner Mongolia. And on this basis, the prediction models of soil relative moisture at different depths were built by using multiple linear regression method in different seasons. The results show that the soil relative moisture at 0-20 cm depth in three seasons was affected by atmospheric water balance in the past two months, while the timescales influencing soil relative moisture at 0-50 cm and 0-100 cm depths were different in typical steppe of Inner Mongolia. In spring, the soil relative moistures at 0-50 cm and 0-100 cm depths were significantly regulated by previous annual precipitation. In summer, the soil relative moisture at 0-50 cm depth was closely related to atmospheric moisture balance in the past two months, while the soil drought at 0-100 cm depth was mainly controlled by precipitation deficit in the past 2-6 months. In autumn, the soil relative moisture at 0-50 cm depth was significantly influenced by previous precipitation for 3-6 months, while that at 0-100 cm depth was closely correlated with the balance between precipitation and evapotranspiration in the past three months, and the influence of meteorological droughts in the past six months and above was obvious. CI, MCI and PDSI had higher correlation with soil relative moisture at different depths than other meteorological drought indices in different seasons due to taking into account the comprehensive effects of long-term and short-term atmospheric water deficit. The established prediction models of soil relative moisture based on previous meteorological drought indexes could better capture the change of soil moisture in typical steppe, and they could support the drought monitoring and predication of pasture to some extent.

In order to forecast heavy precipitation processes in the Xijiang River Basin, the synoptic key regions were determined firstly on the basis of 500 hPa atmospheric circulation synthetic analysis in more heavy rainfall years by using daily rainfall data from 135 meteorological stations in the Xijiang River Basin and NCAR/NCEP daily reanalysis data of 500 hPa geopotential height in the northern hemisphere from 1960 to 2017. Furthermore, the dynamic similarity ensemble-mean method in synoptic key regions was adopted to perform extended-range forecast tests of heavy rainfall processes. Specifically, the empirical orthogonal functions (EOF) method was used to extract and reconstruct principle spatial patterns of 500 hPa geopotential height in past few months, and the years with most similarities were chosen by comparing the constructed circulation patterns at the same period in each year via an analogous precursor method. Finally, the periods of heavy precipitation processes in the Xijiang River Basin in June of 2008 were forecasted by using the above method, and the prediction effects of heavy precipitation processes in recent five years were tested. The results indicate that heavy precipitation processes over the Xijiang River Basins could be forecasted well based on the synoptic key region analogous method, which could be used in actual extended range weather forecast service.

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