As one of the largest arid and semi-arid regions in the world, central Asia (CA) is very sensitive to changes in regional climate. However, because of the poor continuity of daily observational precipitation records in CA, the spatial and temporal variations of extreme precipitation in recent decades remain unclear. Considering their good spatial and temporal continuity, gridded data, such as Climate Prediction Center (CPC) global precipitation, and reanalysis data, such as ERA-Interim (ERA), are helpful for exploring the spatial–temporal variations of extreme precipitation. This study evaluates how well CPC and ERA can represent observed precipitation extremes by comparing the differences in eight extreme precipitation indices and observation data at 84 meteorological stations. The results indicate that the CPC (except for 1979–1981) is more suitable for depicting changes in precipitation extremes. Based on the CPC data for the period 1982–2020, we found that seven indices of precipitation extremes, including consecutive wet days (CWD), max1-day precipitation amount (Rx1day), max5-day precipitation amount (Rx5day), number of heavy precipitation days (R10), very wet days (R95p), annual total precipitation in wet days (PRCPTOT), and simple precipitation intensity index (SDII) have increased by 0.2 d/10a, 0.9 mm/10a, 1.8 mm/10a, 0.3 d/10, 8.4 mm/10a, 14.3 mm/10a and 0.1 mm/d/10a, respectively, and the consecutive dry days (CDDs) have decreased by −3.10 d/10a. It is notable that CDDs decreased significantly in the north of Xinjiang (XJ) but increased in Kyrgyzstan (KG), Tajikistan (TI), and eastern Turkmenistan (TX). The other indices increased clearly in the west of XJ, north of Kazakhstan (KZ), and east of KG but decreased in the south of KG, TI, and parts of XJ. For most indices, the largest change occurred in spring, the main season of precipitation in CA. Therefore, the large-scale atmospheric circulation in April is analyzed to contrast between the most and least precipitation years for the region. A typical circulation pattern in April for those extremely wet years includes an abnormal low-pressure center at 850 hpa to the east of the Caspian Sea, which enhances the southerly winds from the Indian Ocean and hence the transportation of water vapor required for precipitation into CA. This abnormal circulation pattern occurred more frequently after 2001 than before, thus partly explaining the recent increasing trends of precipitation extremes in CA.

The temporal and spatial variations of 26 extreme temperature and precipitation indices for China and Greece were comparatively analysed. Also, their association with atmospheric circulation types was evaluated using multiple linear regression. The calculation of the extreme indices was based on homogenized daily temperature and precipitation time series from 1960 to 2010 for Greece and 2021 for China. Extreme precipitation, intensity, and short-term heavy precipitation increased, while persistent heavy precipitation has decreased since 1960 in China. Short-term heavy precipitation has also shown an increasing trend in Greece, though total precipitation and persistent heavy precipitation decreased there between 1960 and 2010. Extreme cold events have tended to decrease, and extreme warm events have increased in both countries, a fact that can be attributed to global warming. For comparison, climatic warming in China was mainly seen in the half year of winter, while the extreme indices relevant to cold seasons such as FD0 and ID0 presented a small trend in Greece. The observed changes in many climatic indices, including RX5day and WSDI in China and R20MM, RX5day, CDD, PRCPTOT and FD0 in Greece, could be partly explained by those of the main large-scale circulation types in the corresponding regions. The significant multiple correlation coefficients of the main circulation types were up to 0.53 for RX5day and 0.54 for WSDI in China, and 0.74 for PRCPTOT and 0.71 for R20MM in Greece. The relationships between climatic indices and circulation types were closer in Greece than in China, especially for the precipitation indices.

The American Geophysical Union (AGU) announces the new living collection “Impactful Datasets in Earth, Space, and Environmental Sciences” which recognizes the creation and curation of datasets enabling research, analysis, and decision making beyond what is captured by traditional academic impact metrics. The collection highlights datasets through the dimensions of People, Planet, and Prosperity, and includes a curated set of nominated datasets and accompanying special collection of data papers. Developed with the Earth Science Information Partners (ESIP) community, the nomination and review process initially invites contributors from across research, operations, and public service, to nominate datasets important to their work, and then submit a data paper that expands upon the nomination text for inclusion in the special collection. This commentary highlights the rationale for the living collection, and the process of nomination. The collection serves as a living reference that strengthens data culture, supports reproducible geoscience, and provides enduring access to critical information for science and society.