Using National Oceanographic and Atmospheric Administration/Advanced Very High Resolution Radiometer (NOAA/AVHRR) and Climatic Research Unit (CRU) climate datasets, we analyzed interannual trends in the growing-season Normalized Difference Vegetation Index (NDVI) in China from 1982 to 2011, as well as the effects of climatic variables and human activities on vegetation variation. Growing-season (period between the onset and end of plant growth) NDVI significantly increased (p < 0.01) on a national scale and showed positive trends in 52.76% of the study area. A multiple regression model was used to investigate the response of vegetation to climatic factors during recent and previous time intervals. The interactions between growing-season NDVI and climatic variables were more complex than expected, and a lag existed between climatic factors and their effects on NDVI. The regression residuals were used to show that over 6% of the study area experienced significantly human-induced vegetation variations (p < 0.05). These regions were mostly located in densely populated, reclaimed agriculture, afforestation, and conservation areas. Similar conclusions were drawn based on land-use change over the study period.

In this study, the impacts of the El Niño–Southern Oscillation (ENSO) on daily precipitation regimes in China are examined using data from 713 meteorological stations from 1960 to 2013. We discuss the annual precipitation, frequency and intensity of rainfall events, and precipitation extremes for three phases (eastern Pacific El Niño – EP, Central Pacific El Niño – CP, and La Niña – LN) of ENSO events in both ENSO developing and ENSO decaying years. A Mann–Whitney U test was applied to assess the significance of precipitation anomalies due to ENSO. Results indicated that the three phases each had a different impact on daily precipitation in China and that the impacts in ENSO developing and decaying years were significantly different. EP phases caused less precipitation in developing years but more precipitation in decaying years; LN phases caused a reverse pattern. The precipitation anomalies during CP phases were significantly different than those during EP phases, and a clear pattern was found in decaying years across China, with positive anomalies over northern China and negative anomalies over southern China. Further analysis revealed that anomalies in frequency and intensity of rainfall accounted for these anomalies in annual precipitation; in EP developing years, negative anomalies in both frequency and intensity of rainfall events resulted in less annual precipitation, while in CP decaying years, negative anomalies in either frequency or intensity typically resulted in reduced annual precipitation. ENSO events tended to trigger extreme precipitation events. In EP and CP decaying years and in LN developing years, the number of very wet day precipitation (R_95 p), the maximum rainfall in 1 day ($R_{x_{\mathrm{1}\mathrm{d}}}$ ), and the number of consecutive wet days (CWD) all increased, suggesting an increased risk of flooding. On the other hand, more dry spells (DSs) occurred in EP developing years, suggesting an increased likelihood of droughts during this phase. Possible mechanisms responsible for these rainfall anomalies are speculated to be the summer monsoon and tropical cyclone anomalies in ENSO developing and decaying years.

Based on a high-quality dataset of 713 daily precipitation series, changes in daily precipitation events during 1960–2013 were observed in China’s ten largest river basins. Specifically, the amount of precipitation in four categories defined by fixed thresholds and their proportion on total precipitation were analyzed on annual and seasonal time scales. Results showed annual precipitation increased by 1.10 mm/10yr in China, but with obvious spatial differences. Regionally, annual precipitation increased significantly in northwestern rivers, upstream areas of the Yangtze River, the Yellow River, southwestern rivers (due to increase in light and moderate precipitation); and in southeastern rivers, downstream areas of the Yangtze River, and the Pearl River (due to increase in heavy and extreme precipitation). Annual precipitation decreased significantly in the mid-Yangtze River and upstream Pearl River (due to decrease in light, moderate, and heavy precipitation). Seasonally, precipitation decreased only in autumn; this was attributable to a decrease in light and moderate precipitation. Results show that the distribution of precipitation intensity over China has shifted to intense categories since the 1960s, there has been an increase in moderate precipitation in Northwestern and Northern China, and an increase in extreme precipitation in Southeastern China. This shift was detected in all seasons, especially in summer. Precipitation extremes were investigated in the categories of extreme precipitation and results show that the risk of flood has been exacerbated over the past half-century in the Huaihe River, the mid- and lower Yangtze River, the Pearl River, and southeastern rivers.

Climate change is rapidly altering composition, structure, and functioning of the boreal biome, across North America often broadly categorized into ecoregions. The resulting complex changes in different ecoregions present a challenge for efforts to accurately simulate carbon dioxide (CO₂) and energy exchanges between boreal forests and the atmosphere with terrestrial ecosystem models (TEMs). Eddy covariance measurements provide valuable information for evaluating the performance of TEMs and guiding their development. Here, we compiled a boreal forest model benchmarking dataset for North America by harmonizing eddy covariance and supporting measurements from eight black spruce (Picea mariana)-dominated, mature forest stands. The eight forest stands, located in six boreal ecoregions of North America, differ in stand characteristics, disturbance history, climate, permafrost conditions and soil properties. By compiling various data streams, the benchmarking dataset comprises data to parameterize, force, and evaluate TEMs. Specifically, it includes half-hourly, gap-filled meteorological forcing data, ancillary data essential for model parameterization, and half-hourly, gap-filled or partitioned component flux data on CO₂ (net ecosystem production, gross primary production [GPP], and ecosystem respiration [ER]) and energy (latent [LE] and sensible heat [H]) and their daily aggregates screened based on half-hourly gap-filling quality criteria. We present a case study with the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC) to: (1) demonstrate the utility of our dataset to benchmark TEMs and (2) provide guidance for model development and refinement. Model skill was evaluated using several statistical metrics and further examined through the flux responses to their environmental controls. Our results suggest that CLASSIC tended to overestimate GPP and ER among all stands. Model performance regarding the energy fluxes (i.e., LE and H) varied greatly among the stands and exhibited a moderate correlation with latitude. We identified strong relationships between simulated fluxes and their environmental controls except for H, thus highlighting current strengths and limitations of CLASSIC.

Arctic warming is causing substantial compositional, structural, and functional changes in tundra vegetation including shrub and tree‐line expansion and densification. However, predicting the carbon trajectories of the changing Arctic is challenging due to interacting feedbacks between vegetation composition and structure, and surface characteristics. We conduct a sensitivity analysis of the current‐date to 2100 projected surface energy fluxes, soil carbon pools, and CO₂ fluxes to different shrub expansion rates under future emission scenarios (intermediate—RCP4.5, and high—RCP8.5) using the Arctic‐focused configuration of E3SM Land Model (ELM). We focus on Trail Valley Creek (TVC), an upland tundra site in the western Canadian Arctic, which is experiencing shrub densification and expansion. We find that shrub expansion did not significantly alter the modeled surface energy and water budgets. However, the carbon balance was sensitive to shrub expansion, which drove higher rates of carbon sequestration as a consequence of higher shrubification rates. Thus, at low shrub expansion rates, the site would become a carbon source, especially under RCP8.5, due to higher temperatures, which deepen the active layer and enhance soil respiration. At higher shrub expansion rates, TVC would become a net CO₂ sink under both Representative Concentration Pathway scenarios due to higher shrub productivity outweighing temperature‐driven respiration increase. Our simulations highlight the effect of shrub expansion on Arctic ecosystem carbon fluxes and stocks. We predict that at TVC, shrubification rate would interact with climate change intensity to determine whether the site would become a carbon sink or source under projected future climate.

Drought conditions cause stress to terrestrial ecosystems and make their accurate representation in models challenging. The Canadian LAnd Surface Scheme Including biogeochemical Cycles (CLASSIC) employs an empirical approach to link soil moisture stress with stomatal conductance. Such approaches typically perform poorly during drought. Here, we implemented an explicit plant hydraulics parameterization, that is, Stomatal Optimization based on Xylem hydraulics (SOX), in CLASSIC, thereby connecting the soil‐plant‐atmosphere continuum through plant hydraulic traits. The resulting was evaluated against the carbon and water fluxes measured with eddy covariance at eight North American boreal forest flux tower sites. Compared to CLASSIC, better simulated gross primary productivity (GPP) at all sites (increased 0.51 to 0.59; decreased RMSE 1.85 to 1.54 g C and bias −0.99 to −0.57 g C ). During droughts, identified using the Palmer drought severity index (PDSI), GPP simulated with improved compared to CLASSIC. In contrast, generally overestimated evapotranspiration (ET) compared to CLASSIC ( increased 0.61 to 0.64, but RMSE and bias worsened 0.54–0.78 mm and 0.09–0.32 mm , respectively). The overestimated ET may be due to evaporation parameterization, parameter uncertainties, or SOX limitations. Wood density was used to derive plant hydraulic parameters, enabling a parameter‐parsimonious implementation. This explicit plant hydraulics parameterization in CLASSIC will improve its ability to predict ecosystem responses to increasing frequency and severity of drought in boreal forests. Future work aims to refine the simulated evapotranspiration while retaining the improved GPP drought response.