Precipitation variability has great economic, social, and environmental impacts across the globe, and in particular in China. This paper evaluates the historical precipitation variability based on 20 general circulation models from the Coupled Model Intercomparison Project Phase 5 (CMIP5) archive over the 20th century relative to two observational data sets and quantifies CMIP5 improvements over CMIP3. Multimodel ensemble means and individual models are assessed. Three future emission scenarios are used (representative concentration pathways (RCP) 8.5, RCP 4.5, and RCP 2.6), and 21st century CMIP5 estimates are put into context based on the 20th century biases. We find that CMIP5 models can reproduce the spatial pattern of precipitation over China during the 20th century, which represents an improvement over CMIP3. However, the models overestimate the magnitude of seasonal and annual precipitation in most regions of China, especially along the eastern edge of the Tibetan Plateau, and underestimate summer precipitation over southeastern China. For China as a whole, CMIP5's overestimation of annual precipitation is greater than CMIP3, which can be traced back to a greater underestimation of summer precipitation in CMIP3. There is a large spread among individual models, with the greatest uncertainties in simulating summer precipitation. Trends and correlations also suggest a better agreement of CMIP5 with observations than CMIP3. Throughout the 20th century, both the observations and models show an increasing trend in precipitation over parts of northwestern China and a decreasing trend over the Tibetan Plateau. There is poor agreement in precipitation trends over the southeast and northeast regions. In general, multimodel means cannot capture the amplitude of observed multidecadal precipitation variability. In the 21st century, precipitation is generally projected to increase across all of China under all three scenarios. RCP 8.5 exhibits the largest significant trend at a rate of +1.5 mm/yr, corresponding to 16% precipitation increase by the end of the century. The RCP 2.6 scenario shows the smallest increases, at +0.5 mm/yr (6%) by 2100. The greatest increases are projected to occur over the Tibetan Plateau and eastern China in summer, suggesting an altered monsoonal circulation in the future. However, due to the uncertainties in CMIP5, future precipitation projections should be interpreted with caution.
The Badain Jaran desert in western Inner Mongolia in China has a unique landscape that contains 72 lakes, with a total water surface area of 23 km2, and the world's highest stationary sand dunes, which are up to 500 m tall--despite the prevailing dry and windy weather conditions. Here we present evidence of a major groundwater system that underpins the factors leading to this landscape. Our finding could transform plans for the region's water resources.
To assess the biogeophysical impacts of land cover/land use change (LCLUC) on surface temperature, two observation-based metrics and their applicability in climate modeling were explored in this study. Both metrics were developed based on the surface energy balance, and provided insight into the contribution of different aspects of land surface change (such as albedo, surface roughness, net radiation and surface heat fluxes) to changing climate. A revision of the first metric, the intrinsic biophysical mechanism, can be used to distinguish the direct and indirect effects of LCLUC on surface temperature. The other, a decomposed temperature metric, gives a straightforward depiction of separate contributions of all components of the surface energy balance. These two metrics well capture observed and model simulated surface temperature changes in response to LCLUC. Results from paired FLUXNET sites and land surface model sensitivity experiments indicate that surface roughness effects usually dominate the direct biogeophysical feedback of LCLUC, while other effects play a secondary role. However, coupled climate model experiments show that these direct effects can be attenuated by large scale atmospheric changes (indirect feedbacks). When applied to real-time transient LCLUC experiments, the metrics also demonstrate usefulness for assessing the performance of climate models and quantifying land-atmosphere interactions in response to LCLUC.
Historical temperature variability over China during the twentieth century and projected changes under three emission scenarios for the twenty-first century are evaluated on the basis of a multimodel ensemble of 20 GCMs from phase 5 of the Coupled Model Intercomparison Project (CMIP5) and two observational datasets. Changes relative to phase 3 of the Coupled Model Intercomparison Project (CMIP3) are assessed, and the performance of individual GCMs is also quantified. Compared with observations, GCMs have substantial cold biases over the Tibetan Plateau, especially in the cold season. The timing and location of these biases also correspond to the greatest disagreement among the individual models, indicating GCMs’ limitations in reproducing climatic features in this complex terrain. The CMIP5 multimodel ensemble shows better agreement with observations than CMIP3 in terms of the temperature biases. Both CMIP3 and CMIP5 capture the climatic warming over the twentieth century. However, the magnitude of the annual mean temperature trends is underestimated. There is also limited agreement in the spatial and seasonal patterns of temperature trends over China. Based on six statistical measures, four individual models—the Max Planck Institute Earth System Model, low resolution (MPI-ESM-LR), Second Generation Canadian Earth System Model (CanESM2), Model for Interdisciplinary Research on Climate, Earth System Model (MIROC-ESM), and Community Climate System Model, version 4 (CCSM4)—best represent surface air temperature variability over China. The future temperature projections indicate that the representative concentration pathway (RCP) 8.5 and RCP 4.5 scenarios exhibit a gradual increase in annual temperature during the twenty-first century at a rate of 0.60° and 0.27°C (10 yr)−1, respectively. As the lowest-emission mitigation scenario, RCP 2.6 projects the lowest rate of temperature increase [0.10°C (10 yr)−1]. By the end of the twenty-first century, temperature is projected to increase by 1.7°–5.7°C, with larger warming over northern China and the Tibetan Plateau.
Agricultural irrigation has significant potential for altering local climate by reducing soil albedo, increasing evapotranspiration, and enabling greater leaf area. Numerous studies using regional or global climate models have demonstrated the cooling effects of irrigation on mean and extreme temperature, especially over regions where irrigation is extensive. However, these model‐based results have not been well validated due to the limitations of observational data sets. In this study, multiple satellite‐based products, including the Moderate Resolution Imaging Spectroradiometer (MODIS) and Soil Moisture Active Passive (SMAP) data sets, are used to isolate and quantify the local impacts of irrigation on surface climate over irrigated regions, which are derived from the Global Map of Irrigation Areas (GMIA). The relationships among soil moisture, albedo, evapotranspiration, and surface temperature are explored. Strong evaporative cooling by irrigation lowers daytime surface temperature over arid and semi‐arid regions, such as California's Central Valley, the Great Plains, central Asia, and northwestern India. However, the cooling effects are less evident in areas of eastern China and the Lower Mississippi River Basin despite extensive irrigation over these regions. Results are also compared with irrigation experiments using the Community Earth System Model (CESM) to assess the model's ability to represent land–atmosphere interactions in regards to irrigation. CESM greatly underestimates the surface temperature response to irrigation. The comparison between the offline and coupled simulations suggests that the irrigation‐induced cooling can be regulated by the interactions between land surface and atmosphere, and amplified signals are found over the “hot spot” regions. Meanwhile, model resolution can also influence the magnitude of the local cooling by irrigation.
Land use changes have great potential to influence temperature extremes. However, contradictory summer daytime temperature responses to deforestation are reported between observations and climate models. Here we present a pertinent comparison between multiple satellite-based datasets and climate model deforestation experiments. Observationally-based methods rely on a space-for-time assumption, which compares neighboring locations with contrasting land covers as a proxy for land use changes over time without considering possible atmospheric feedbacks. Offline land simulations or subgrid-level analyses agree with observed warming effects only when the space-for-time assumption is replicated. However, deforestation-related cloud and radiation effects manifest in coupled climate simulations and observations at larger scales, which show that a reduction of hot extremes with deforestationas simulated in a number of CMIP5 modelsis possible. Our study provides a design and analysis methodology for land use change studies and highlights the importance of including land-atmosphere coupling, which can alter deforestation-induced temperature changes.
This study investigates the impacts of historical land-cover change on summer afternoon precipitation over North America using the Community Earth System Model. Using land–atmosphere coupling metrics, this study examines the sensitivity of afternoon atmospheric conditions to morning land surface states and fluxes that are altered by land-cover changes before and since 1850. The deforestation in the eastern United States prior to 1850 leads to increased latent but decreased sensible heat flux during the morning and a reduction in afternoon precipitation over the southern regions of the U.S. East Coast. The agricultural expansion over the Great Plains since preindustrial times shows similar effects on surface fluxes but results in a significant widespread increase in precipitation over the crop area. The coupling metrics exhibit a strong positive soil moisture–precipitation relationship over the Great Plains. Impacts of land-cover change on precipitation manifest through changes in rainfall frequency, rather than intensity, that are largely controlled by the distribution of CAPE as the trigger of convective precipitation. However, deforestation and later reforestation over the eastern United States, where coupling properties are different than the Great Plains, do not have as dominant an effect on afternoon precipitation. Additionally, precipitation over parts of the U.S. Southwest decreases in this model during the earlier period of East Coast deforestation, owing to changes in the large-scale circulation over North America driven by land-use changes prior to 1850.
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