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During the early 20th century, the Arctic experienced a period of remarkable warming, often called the early 20th century warming (ETCW). However, the degree of the response to external climate forcing on the Arctic surface air temperature is not well understood. Climate simulations using a state‐of‐the‐art climate model of Meteorological Research Institute (MRI‐ESM2.0) and multimodel analyses were conducted to better understand ETCW. The MRI‐ESM2.0 historical simulations successfully reproduced the observed ETCW and the corresponding decreases in sea ice extent. Detection and attribution experiments using MRI‐ESM2.0 suggest that internal climate variability and external natural forcings by solar and volcanic activities had major influences on the model‐simulated ETCW, rather than external anthropogenic forcings. Multimodel analyses indicate that the Arctic warming trend during 1911–1940 induced by natural forcings is comparable to the unforced multidecadal internal variability, suggesting major contributions of the internal dynamics and natural forcings to ETCW. Plain Language Summary: Instrumental records show that there was significant warming in the Arctic during the first half of the 20th century, known as the early 20th century warming (ETCW). Climate simulations using a state‐of‐the‐art climate model of Meteorological Research Institute (MRI‐ESM2.0) suggest that external natural forcings, i.e., long‐lasting quiet volcanic activity and increased solar activity, influenced the model‐simulated ETCW and associated sea ice decrease. Multimodel analyses indicate the robustness of the MRI‐ESM2.0 results and suggest that the climatic response of Arctic surface air temperature to external natural forcings in the ETCW period is comparable to the unforced multidecadal internal variability of the models, suggesting a major contribution of unforced multidecadal internal variability and natural forcings to ETCW. Key Points: Climate model MRI‐ESM2.0 reproduces the Arctic surface air temperature rising and associated sea ice loss observed in the early 20th centuryMRI‐ESM2.0 results indicate that the natural forcings and the internal variability are main contributors to Arctic warming during 1920–1940Multimodel analyses suggest the Arctic warming response to natural forcings in 1911–1940 is comparable to the unforced internal variability [ABSTRACT FROM AUTHOR]

The effects of the emissions of anthropogenic greenhouse gases (GHGs), aerosols, and natural forcing on the summer-mean surface air temperature (TAS) in the East Asia (EA) land surface in the 20th century are analyzed using six-member coupled model inter-comparison project 5 (CMIP5) general circulation model (GCM) ensembles from five single-forcing simulations. The simulation with the observed GHG concentrations and aerosol emissions reproduces well the land-mean EA TAS trend characterized by warming periods in the early (1911−1940; P1) and late (1971−2000; P3) 20th century separated by a cooling period (1941−1970; P2). The warming in P1 is mainly due to the natural variability related to GHG increases and the long-term recovery from volcanic activities in late-19th/early-20th century. The cooling in P2 occurs as the combined cooling by anthropogenic aerosols and increased volcanic eruptions in the 1960s exceeds the warming by the GHG increases and the nonlinear interaction term. In P3, the combined warming by GHGs and the interaction term exceeds the cooling by anthropogenic aerosols to result in the warming. The SW forcing is not driving the TAS increase in P1/P3 as the shortwave (SW) forcing is heavily affected by the increased cloudiness and the longwave (LW) forcing dominates the SW forcing. The LW forcing to TAS cannot be separated from the LW response to TAS, preventing further analyses. The interaction among these forcing affects TAS via largely modifying the atmospheric water cycle, especially in P2 and P3. Key forcing terms on TAS such as the temperature advection related to large-scale circulation changes cannot be analyzed due to the lack of model data.

Cores of Schrenk spruce from seven sites of eastern Tien Shan were used to develop a regional tree-ring chronology to extend the climate record. We developed an August–July Standardized Precipitation Evapotranspiration Index (SPEI) reconstruction that spans AD 1725–2013 based on the regional tree-ring chronology. The reconstruction model accounts for 45.3% of the SPEI variance from 1959 to 2013. The SPEI reconstruction agrees reasonably well with the dry and wet periods previously estimated from tree rings in northern Xinjiang. The correlation analysis revealed that temperature plays an important role in regional drought variability, and some extreme wet years also coincide with the volcanic eruptions. [ABSTRACT FROM AUTHOR]

• Mangrove Forests (MFs) in RRD has upward trend between 1986–2019 with severe loss between 2000–2006. • Human activities are responsible for 49% of the MFs loss during 1986–2019. • MFs in RRD appear to have reached their potential seaward expansion limit due to strong wave action. Mangrove forests (MFs), which occur along tropical and subtropical coastal zone, are among the most productive and richest carbon-rich ecosystems in the world. However, MFs have experienced great losses worldwide due to the impacts of intensive human activities and relative sea level rise. Here, the recent dynamic changes in the MFs of the Red River Delta (RRD), the second largest delta in Vietnam, were quantified using the random forest algorithm based on 328 remote images obtained by Landsat TM/ETM+/OLI during 1986–2019. The results show obvious increasing trends in the MF area with a change rate of 39 ha/y from 1,655 ha in 1986 to 2,944 ha in 2019. The change rates in the northern RRD (NP) and southern RRD (SP) were 8.44 ha/y and 30.62 ha/y, respectively, even though MFs in the tropics worldwide encountered significant losses. Further, approximately 1,091 ha of MF was converted into aquaculture ponds during 2000–2006 in the interior of the RRD, while the shoreline of MFs in the NP and SP continually expanded seaward to the northeast and southwest at average rates of 38.9 m/y and 17.9 m/y, respectively. Moreover, although the fluvial sediment supply declined dramatically from 199.57 to 16.41 mt/y during 1986–2017, the sediment supply was not responsible for the present seaward expansion of MFs. Wave action drove sediments to overwash barriers, and tidal dynamics carried this sediment into tidal channels, depositing sediments behind the barriers and on both sides of tidal channels with continuing MF growth. In addition, the conversion of MFs into aquaculture ponds by human activities was responsible for the massive losses of MFs in 2000–2006, but these impacts were alleviated as conservation policies were implemented by local governments in subsequent years. This study indicates that the growth, loss and recovery of MFs are affected by various factors, and it is vital to map the variations in MFs to better implement regional ecological restoration programs for coastal MFs. [ABSTRACT FROM AUTHOR]

The effects of the emissions of anthropogenic greenhouse gases (GHGs), aerosols, and natural forcing on the summer-mean surface air temperature (TAS) in the East Asia (EA) land surface in the 20th century are analyzed using six-member coupled model inter-comparison project 5 (CMIP5) general circulation model (GCM) ensembles from five single-forcing simulations. The simulation with the observed GHG concentrations and aerosol emissions reproduces well the land-mean EA TAS trend characterized by warming periods in the early (1911–1940; P1) and late (1971–2000; P3) 20th century separated by a cooling period (1941–1970; P2). The warming in P1 is mainly due to the natural variability related to GHG increases and the long-term recovery from volcanic activities in late-19th/early-20th century. The cooling in P2 occurs as the combined cooling by anthropogenic aerosols and increased volcanic eruptions in the 1960s exceeds the warming by the GHG increases and the nonlinear interaction term. In P3, the combined warming by GHGs and the interaction term exceeds the cooling by anthropogenic aerosols to result in the warming. The SW forcing is not driving the TAS increase in P1/P3 as the shortwave (SW) forcing is heavily affected by the increased cloudiness and the longwave (LW) forcing dominates the SW forcing. The LW forcing to TAS cannot be separated from the LW response to TAS, preventing further analyses. The interaction among these forcing affects TAS via largely modifying the atmospheric water cycle, especially in P2 and P3. Key forcing terms on TAS such as the temperature advection related to large-scale circulation changes cannot be analyzed due to the lack of model data. [ABSTRACT FROM AUTHOR]