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In the early summer (June) of 2022, the spatial mean precipitation in northeast China (NEC) was 62% higher than normal and broke the historical record since 1951. Based on the precipitation data of 245 meteorological stations in NEC and the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis, this paper analyzes the role of large-scale circulation and sea-surface temperature (SST) associated with anomalous precipitation over NEC in June using singular value decomposition (SVD), correlation analysis, regression analysis, and composite analysis methods, and further investigates the possible cause of the abnormal precipitation in June 2022. Results show that the northeast China cold vortex (NCCV) accompanying the blocking high in the Okhotsk Sea (BHOS) has been the primary mid-to-high latitude atmospheric circulation pattern affecting NEC precipitation in June since 2001. This circulation pattern is closely related to the tripole SST pattern over the North Atlantic (NAT) in March. In June 2022, the NAT SST anomaly in March stimulates eastward-propagating wave energy, resulting in the downstream anomalous circulation pattern in which the NCCV cooperates with the BHOS in the mid-high latitudes of East Asia. Under this background atmospheric circulation favorable for precipitation, the Kuroshio region SST anomaly in June led to a more northward and stronger anomalous anticyclone in the northwestern Pacific through local air–sea interaction, which provides more sufficient water vapor for NEC, resulting in unprecedented precipitation in June 2022. [ABSTRACT FROM AUTHOR]

Climate is a key factor in agriculture, but we are unable to adequately predict future climates. Although some studies have addressed the short and long-run impacts of climate change on agriculture, few of them specifically focused on the analysis of its thermal component. Climatic regions with an extreme thermal range are a special case, as seasonal contrasts complicate the picture. Based on the above, the purpose of the paper is twofold. First, we review methods and indices used for the estimation of changes in the thermal component of the climate and demonstrate the usefulness of a sensitivity assessment methodology that gives some indication of the likely spatial extent of areas of high or low sensitivity to climate change and the size of the potential impact of that change, which is specifically beneficial in regions with high temperature extremes. Secondly, we constructed a composite indicator, called the Growing Degree Day Sensitivity Index (GDDSI) and defined as the percentage change in Growing Degree Day (GDD) for warming scenarios +1, +2 and +3 °C. GDDs were calculated for threshold base air temperatures of 0, 5, 10 and 15 °C, and a high-temperature limit of 30 °C. A GDD sensitivity analysis was applied to the thermally extreme climate of the Russian Far East. We analyzed the data of 50 weather stations across the study region over the period 1966–2017. The results show a strong GDDSI north-to-south gradient. In most cases, the sensitivity does not increase significantly as the warming rate increases. The higher the base threshold, the higher the sensitivity: GDDs with a threshold at 15 °C had the highest sensitivity in the far north of the study area where conditions are currently marginal for crop growth. The sensitivity analysis circumnavigates the difficulty of uncertainty in knowing what future climate to expect and informs planning decisions. The mapped results are useful for identifying areas of high sensitivity to climate change as well as the magnitude of the potential impact of that change. [ABSTRACT FROM AUTHOR]

Short-term fluctuations in air temperature, called the daily temperature range (DTR), or its daily amplitude, have a strong impact on ecosystems, as well as on the health and well-being of people. The pronounced effect of DTR on mortality from all causes and especially on cardiovascular mortality is well documented in the scientific literature, but little is known about spatial, inter-annual, and inter-seasonal fluctuations of DTR in the Russian Far East (RFE), an area with high annual dynamics of air temperature. Data from 99 weather stations for the period from 2000 to 2019 was used to evaluate spatial and temporal DTR patterns at the RFE. A higher DTR, up to 16 °C in Toko on the border with Sakha (Yakutia) as a mean for the entire period, is typical for continental areas further to the north. Lower values are observed at continental weather stations in the south and in coastal climates (4.7 °C in Mys Alevina, Magadan Region). In general, a distinct seasonal change in DTR was found for continental locations with a significant difference from month to month throughout the year. On the annual cycle, the maximum DTR at the continental northern stations is observed in April and June–July, and at the continental southern areas in February; the minimum DTR is shown in November and December. The DTR ranges as much as from 6 °C in December to 17 °C in April in the continental Korkodon in the far north. Locations with a marine climate are characterized by a smoothed seasonal change in DTR, with obvious peaks in February–March and October, and a minimum in July–August. The downward trend in DTR for the period from 2000 to 2019, up to −0.7 °C in coastal Bolsheretsk, is based on a faster increase in the minimum daily temperature compared to the maximum, which is typical for most weather stations at the RFE and is known worldwide as a diurnal asymmetry of global warming. At the same time, an increase in the daily amplitude of air temperature (up to +0.6 °C in continental Dolinovka) was found for some localities, associated with a higher positive trend of maximum temperatures, which contradicts global patterns. [ABSTRACT FROM AUTHOR]

The Plum Rains process is a complex process, and its spatiotemporal variations and influencing factors on different time scales still need further study. Based on a dataset on the Plum Rains in the Yangtze River Delta, from 33 meteorological stations during the period of 1960 to 2012, we investigated the spatiotemporal variations of Plum Rains and their relation with the East Asian Summer Monsoon (EASM), the El Niño-Southern Oscillation (ENSO), and the Pacific Decadal Oscillation (PDO) using an integrated approach that combines ensemble empirical mode decomposition (EEMD), empirical orthogonal function (EOF), and correlation analysis. The main conclusions were as follows: (1) the plum rainfall (i.e., the rainfall during the period of Plum Rains) showed a trend of increasing first and then decreasing, and it had a three-year and six-year cycle on the inter-annual scale and a 13-year and 33-year cycle on the inter-decadal scale. The effect of the onset and termination of Plum Rains and the daily intensity of plum rainfall on plum rainfall on the inter-annual scale was greater than the inter-decadal scale, (2) the EOF analysis of plum rainfall revealed a dominant basin-wide in-phase pattern (EOF1) and a north-south out-of-phase pattern (EOF2), and (3) ENSO and EASM were the main influencing factors in the three-year and six-year periods, respectively. [ABSTRACT FROM AUTHOR]