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Proxy-based precipitation reconstruction is essential to study the inter-annual to decadal variability and underlying mechanisms beyond the instrumental period that is critically needed for climate modeling, prediction and attribution. Based on 2912 annually resolved proxy series mainly derived from tree rings and historical documents, we present a set of standard precipitation index (SPI) reconstructions for each year (November–October), covering the whole of Asia, and for the wet season (i.e., November–April for western Asia and May–October for the others) since 1700, with the spatial resolution of 2.5 ∘. To screen the optimal candidate proxies for SPI reconstruction in each grid from available proxies in its connected region with a homogeneous rainfall regime and similar precipitation variability, a new approach is developed by adopting the grid-location-dependent division derived from the instrumental SPI data. The validation shows that these reconstructions are effective for most of Asia. The assessment of data quality compared with gauge precipitation before calibration time indicates that our reconstruction has high quality to show the precipitation variability in most of the study areas, except for a few grids in western Russia, the coastal area of southeast Asia and northern Japan. The full dataset can be obtained from https://doi.org/10.57760/sciencedb.01829 (Y. Liu et al., 2022). [ABSTRACT FROM AUTHOR]

• Paddy rice expansion resulted in a net cooling through the growing season. • Asymmetric pattern of LST change was found in the day and night. • Considerable seasonal variability in the cooling effects. • Nonradiative cooling exceeded radiative warming in paddy rice expansion. The pending extensive rice expansion in northeastern Asia, especially in northeast China, affects regional climate by altering both biogeochemical and biophysical processes. While the biogeochemical effects (e.g., CO 2 , CH 4) of rice expansion have attracted plenty of attention, its biophysical effects have not been well documented, especially its influences on diurnal and seasonal land surface temperature (LST). In this study, we used a pair-wise comparison approach to examine biophysical effects of paddy rice expansion at different temporal scales (diurnal and seasonal) in northeast China, based on satellite-derived biophysical proxies and a high-resolution crop map in 2017. We found that the daily mean LST of rice paddies was 0.5 °C lower than that of corn and soybean fields during the growing season (from May to September), as a result of daytime cooling (-1.8 and -2.0 °C) and nighttime warming (0.8 and 1.1 °C), which subsequently led to a narrower diurnal LST range (-2.6 and -3.0 °C) than in upland crops (i.e. corn and soybean). The cooling effects were stronger in the early period of the growing season (May and June) than in the late season (July to September). Using a temperature response model, we found that the nonradiative processes (i.e., evapotranspiration and sensible heat) dominated the LST response in paddy rice, while the radiative process (i.e., albedo) played a secondary role. The daytime cooling and nighttime warming implies that we need to consider the unsymmetrical diurnal LST dynamics when evaluating the short-term effects of paddy rice expansion. Stronger cooling effects in the early growing season has to be accounted for when modeling its biophysical impacts at seasonal scale. This study explained the local climate effects of rice expansion through the biophysical mechanism with both radiative and nonradiative controls on the surface energy balance, which can contribute to improved modeling of biophysical effects of land use change. [ABSTRACT FROM AUTHOR]

Large-scale palaeoclimate reconstructions can be very sensitive to the proxy records they are based on, and hence to the criteria used to select proxy records. Data selection rarely follows objective criteria that are applicable to all types of proxies, including both low- and high-resolution records. Thus, there is a need for a uniform and transparent approach to assess the suitability of input proxy data for a reconstruction. Here, we develop classification criteria that are applicable to multiple proxy types and evaluate different selection strategies using a network of 62 millennium-long terrestrial hydroclimate proxy records from Monsoon Asia. Our results reveal that robust evidence for a coherent climate signal and high dating accuracy are important criteria for benchmarking the suitability of each proxy record. We determine these criteria by reviewing the literature for each record (rather than screening against instrumental data). We show that the proposed selection approach can yield a network with a stronger common signal. By evaluating the uncertainty and centennial variability of composite reconstructions, from differently selected subsets of the proxy network, it appears beneficial to use suitable proxies stemming from different archives, as well as having a dense network of proxy sites. We suggest that future large-scale palaeoclimate reconstructions might be improved by evaluating proxy networks according to the universal categories presented here and, if indicated, removing less suitable records. This will strengthen the climate signal in the final reconstruction, allowing more precise inferences about past climate variability and more robust comparisons with climate model simulations. • Suitability of proxy records should be estimated based on literature review. • Semi-quantitative criteria: evidence for climate signal and dating accuracy. • Proposed selection approach can yield a network with a stronger common signal. • Multi-proxy approach is beneficial to preserve various frequency domains. [ABSTRACT FROM AUTHOR]