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The Nanwenghe Wetlands Reserve in the Yile'huli Mountains is a representative region of the Xing'an permafrost. The response of permafrost to climate change remains unclear due to limited field investigations. Thus, longer-term responses of the ground thermal state to climate change since 2011 have been monitored at four sites with varied surface characteristics: Carex tato wetland (P1) and shrub-C. tato wetland (P2) with a multi-year average temperatures at the depth of zero annual amplitude (TZAA) of −0.52 and −1.19 °C, respectively; Betula platyphylla-Larix gmelinii (Rupr.) Kuzen mixed forest (P3) with TZAA of 0.17 °C, and; the forest of L. gmelinii (Rupr.) Kuzen (P4) with TZAA of 1.65 °C. Continuous observations demonstrate that the ecosystem-protected Xing'an permafrost experienced a cooling under a warming climate. The temperature at the top of permafrost (TTOP) rose (1.8 °C per decade) but the TZAA declined (−0.14 °C per decade), while the active layer thickness (ALT) thinned from 0.9 m in 2012 to 0.8 m in 2014 at P1. Both the TTOP and TZAA increased (0.89 and 0.06 °C per decade, respectively), but the ALT thinned from 1.4 m in 2012 to 0.7 m in 2016 at P2. Vertically detached permafrost at P3 disappeared in summer 2012, with warming rates of +0.42 and + 0.17 °C per decade for TTOP and TZAA, respectively. However, up to date, the ground thermal state has remained stable at P4. We conclude that the thermal offset is crucial for the preservation and persistence of the Xing'an permafrost at the southern fringe.

Study Region Mekong River Basin and surrounding areas. Study Focus: This study investigated the impacts of climate change on future meteorological and hydrological droughts in the Mekong River Basin and its surrounding areas. Our work is based on the output of five global climate models (GCMs) and simulations using the geomorphology-based hydrological model (GBHM) for the historical (1975–2004), near future (2010–2039), middle future (2040–2069), and far future (2070–2099) periods. The meteorological droughts in the study area were measured using SPI and SPEI, while the hydrological droughts were measured using SSI. New Hydrological Insights for the Region: The results suggest that droughts will generally reduce in the future over most of the study area, but will be more unevenly distributed with an eastward migration as compared to the historical period. Both meteorological and hydrological droughts will intensify in the near future, but will then reduce in intensity. Meteorological droughts will increase in the northeastern areas in the near future, followed by migration towards the south. Hydrological droughts showed similar aggravation followed by reduction, with upstream areas showing greater variability. In the general context of drought alleviation, southwestern China and the Mekong River estuary may suffer from a continuously increasing drought intensity in the future. This finding is based on 100-year extreme drought events.

There are many models presented that assess water quality. However, the applications of the models are limited due to the difficulty of preparing input data and interpreting model output. In this paper, we developed a Web-based platform to assist researchers in analyzing water quality. The data from sensors can be automatically imported to the platform according to the configured information of data structures. The platform also provides conventional methods and big data methods for the users to analyze water quality. Moreover, the users can choose the water quality parameters according to the water usage. The presented platform can show the model output in a text format and a graphic format, which allows for the analysis to be better understood by the user. The platform integrates the input, analysis, and output together well and brings great convenience to the research on water quality.

Southwest China (SWC), characterized by complex climate, undulating topography, intertwined mountains and basins, and diverse ecosystem, is a global hotspot in biodiversity. SWC also is sensitive to climate change, the effects of which can be expressed through alterations in bio-climatology indicators. In this study, we investigated the trends of the key bio-climatology indicators, including mean temperature of the warmest month (TWM), mean temperature of the coldest month (TCM), accumulated temperature above 5 °C (AT5) and 10 °C (AT10), number of days with daily mean temperature above 5 °C (DT5) and 10 °C (DT10), annual precipitation (P), precipitation days (DP), and moisture index (MI). The 105 meteorological stations data from 1961 to 2015 were selected to examine the trend of these indexes in SWC. The results suggested that TWM and TCM both experienced a significant upward trend, with the more pronounced increase in TCM than that in TWM. TWM increased by 0.011 °C year-1 and TCM increased by 0.025 °C year-1. AT5, AT10, DT5, and DT10 also exhibited increasing trend, with AT10 > AT5 and DT10 > DT5, and the trend in DT was found to be less significant than that in AT. The increment of AT5, AT10, DT5, and DT10 were 6.452 °C year-1, 7.158 °C year-1, 0.164 days year-1, and 0.263 days year-1, respectively. P, DP, and MI showed a downward trend, among which DP experienced a significant decrease with - 1.018 days year-1. In general, SWC tends to be drier and warmer, which may alter the structure and function of the local ecosystem, further then affect the role as a global diversity hotspot.

Abstract The emergence of new-generation geostationary satellites (such as Himawari-8 or FenYun-4) provides us an opportunity to obtain more accurate global horizontal irradiance (GHI) data. In this study, instantaneous GHI estimates (with a spatio-temporal resolution of 10 min and 5 km) are produced using the cloud products from the new-generation geostationary satellite Himawari-8 with a physically based algorithm. The hourly, daily, and monthly GHI estimates are aggregated using “snapshots” (or instantaneous estimates) at two different sampling frequencies (i.e., 1 h and 10 min), and validated against surface radiometry measurements collected in China. The root mean square errors (RMSE) for hourly, daily and monthly GHI estimates calculated using 1-h snapshots were 106.6, 27.9, and 17.7 W m−2, respectively, whereas those for hourly, daily and, monthly GHI calculated using 10-min snapshots decreased to 94.0, 24.0, and 16.6 W m−2, respectively. This result demonstrates that the accuracies of hourly, daily, and monthly GHI estimates are improved by increasing the frequency of satellite observations from 1 h (frequency of the previous-generation geostationary satellites) to 10 min (frequency of the new-generation geostationary satellites).

There has been much debate on the temporal change trend and existence of a turning point in spring green-up date (GUD) of plants on the Qinghai-Tibetan Plateau (QTP). Most previous studies on the QTP used remote sensing data, which have large uncertainties. In this study, using a large amount of long-term ground observation data at 27 phenological stations across the QTP (1694 GUD records), we showed that on the whole, QTP herbaceous plant GUD insignificantly advanced during 1982-2017. Although the direction of the GUD trend did not change from 1982 to 2017, the magnitude of the advancing trend greatly weakened after 1999. According to our estimated results from 28 paired GUD time series, the overall GUD trend shifted from -2.70 days/decade during 1982-1999 to -0.56 days/decade during 2000-2017. This finding contrasts with the conclusions of previous satellite-based studies, which either reported a continuous significant advancement of GUD or a turning point in the mid-to-late 1990s. Through partial correlation analysis and partial least squares regression, we found that winter and spring air temperatures were the primary climatic factors that influenced the temporal change in GUD, and both had negative effects on GUD. The decreased GUD trend was mainly attributable to the warming slowdown in spring. On average, the spring warming rate decreased by 52.43% after 1999, whereas the winter warming rate displayed no obvious change. This study also found that the GUD of forbs showed stronger sensitivity to air temperature change than that of sedges and grasses. This indicates that forbs are more competitive in adaptation to climate warming, which might shift plant community structure and affect ecosystem service function. Moreover, the declined advancement in GUD implies that the spring phenologically driven increase in carbon uptake may have also slowed in the past two decades.

AbstractGeoengineering has been proposed to stabilize global temperature, but its impacts on crop production and stability are not fully understood. A few case studies suggest that certain crops are likely to benefit from solar dimming geoengineering, yet we show that geoengineering is projected to have detrimental effects for groundnut. Using an ensemble of crop‐climate model simulations, we illustrate that groundnut yields in India undergo a statistically significant decrease of up to 20% as a result of solar dimming geoengineering relative to RCP4.5. It is somewhat reassuring, however, to find that after a sustained period of 50 years of geoengineering crop yields return to the nongeoengineered values within a few years once the intervention is ceased.