Abstract

Earth system models (ESMs) from phase 5 of the Coupled Model Intercomparison Project (CMIP5) were diagnosed as having large discrepancies in their land carbon turnover times, which partly explains the differences in the future projections of terrestrial carbon storage from the models. Carvalhais et al. focused on evaluation of model-based ecosystem carbon turnover times τ _eco in relation with climate factors. In this study, τ _eco from models was analyzed separately for biomass and soil carbon pools, and its spatial dependency upon temperature and precipitation was evaluated using observational datasets. The results showed that 8 of 14 models slightly underestimated global biomass carbon turnover times τ _veg (modeled median of 8 yr vs observed 11 yr), and 11 models grossly underestimated the soil carbon turnover time τ _soil (modeled median of 16 yr vs observed 26 yr). The underestimation of global carbon turnover times in ESMs was mainly due to values for τ _veg and τ _soil being too low in the high northern latitudes and arid and semiarid regions. In addition, the models did not capture the observed spatial climate sensitivity of carbon turnover time in these regions. Modeled τ _veg and τ _soil values were generally weakly correlated with climate variables, implying that differences between carbon cycle models primarily originated from structural differences rather than from differences in atmospheric climate models (i.e., related to temperature and precipitation). This study indicates that most models do not reproduce the underlying processes driving regional τ _veg and τ _soil, highlighting the need for improving the model parameterization and adding key processes such as biotic disturbances and permafrost–carbon climate responses.

Abstract

Drought in spring and early summer has been shown to precede anomalous hot summer temperature. In particular, drought in the Mediterranean region has been recently shown to precede and to contribute to the development of extreme heat in continental Europe. In this paper, this mechanism is investigated by performing integrations of a regional mesoscale model at the scale of the European continent in order to reproduce hot summer inception, starting with different initial values of soil moisture south of 46°N. The mesoscale model is driven by the large-scale atmospheric conditions corresponding to the 10 hottest summers on record from the European Climate Assessment dataset. A northward progression of heat and drought from late spring to summer is observed from the Mediterranean regions, which leads to a further increase of temperature during summer in temperate continental Europe. Dry air formed over dry soils in the Mediterranean region induces less convection and diminished cloudiness, which gets transported northward by occasional southerly wind, increasing northward temperature and vegetation evaporative demand. Later in the season, drier soils have been established in western and central Europe where they further amplify the warming through two main feedback mechanisms: 1) higher sensible heat emissions and 2) favored upper-air anticyclonic circulation. Drier soils in southern Europe accelerate the northward propagation of heat and drying, increasing the probability of strong heat wave episodes in the middle or the end of the summer.

Abstract

Seventeen Earth system models (ESMs) from phase 5 of the Coupled Model Intercomparison Project (CMIP5) were evaluated, focusing on the seasonal sensitivities of net biome production (NBP), net primary production (NPP), and heterotrophic respiration (Rh) to interannual variations in temperature and precipitation during 1982–2005 and their changes over the twenty-first century. Temperature sensitivity of NPP in ESMs was generally consistent across northern high-latitude biomes but significantly more negative for tropical and subtropical biomes relative to satellite-derived estimates. The temperature sensitivity of NBP in both inversion-based and ESM estimates was generally consistent in March–May (MAM) and September–November (SON) for tropical forests, semiarid ecosystems, and boreal forests. By contrast, for inversion-based NBP estimates, temperature sensitivity of NBP was nonsignificant for June–August (JJA) for all biomes except boreal forest; whereas, for ESM NBP estimates, the temperature sensitivity for JJA was significantly negative for all biomes except shrublands and subarctic ecosystems. Both satellite-derived NPP and inversion-based NBP are often decoupled from precipitation, whereas ESM NPP and NBP estimates are generally positively correlated with precipitation, suggesting that ESMs are oversensitive to precipitation. Over the twenty-first century, changes in temperature sensitivities of NPP, Rh, and NBP are consistent across all RCPs but stronger under more intensive scenarios. The temperature sensitivity of NBP was found to decrease in tropics and subtropics and increase in northern high latitudes in MAM due to an increased temperature sensitivity of NPP. Across all biomes, projected temperature sensitivity of NPP decreased in JJA and SON. Projected precipitation sensitivity of NBP did not change across biomes, except over grasslands in MAM.

Abstract

There is a strong international demand for quantitative estimates of both carbon sources/sinks, and water availability at the land surface at various spatial scales (regional to global). These estimates can be derived (and usually are) from global biosphere models, which simulate physiological, biogeochemical, and biophysical processes, using a variety of plant functional types. Now, the representation of the large area covered with managed land (e.g., croplands, grasslands) is still rather basic in these models, which were first designed to simulate natural ecosystems, while more and more land is heavily disturbed by man (crops cover ∼35% and grasslands ∼30%–40% of western Europe's area as a result of massive deforestation mainly in the Middle Ages).

In this paper a methodology is presented that combines the use of a dynamic global vegetation model (DGVM) known as Organizing Carbon and Hydrology in Dynamic Ecosystems (ORCHIDEE) and a generic crop model [the Simulateur Multidisciplinaire pour les Cultures Standard (STICS)]. This association aims at improving the simulation of water vapor and CO₂ fluxes at the land–atmosphere interface over croplands, and thereby the calculation of the carbon and water budget. Variables that are much better computed in STICS (e.g., leaf area index, root density profile, nitrogen stress, vegetation height) are assimilated daily into ORCHIDEE, which continues to compute its own carbon and water balance from the fluxes simulated at the half-hourly time step. The allocation of photosynthates in ORCHIDEE was modified in order to maintain the coherence between leaf area index and leaf biomass, as well as between root density and root biomass. Soil moisture stress is computed using a more realistic root density profile. The maximum rates of carboxylation and RuBP (ribulosebisphosphate) regeneration were adjusted to more realistic values, while the actual rates can now be reduced following the nitrogen stress. Finally, harvest has been implemented into ORCHIDEE.

The improved model (ORCHIDEE-STICS) is evaluated against measurements of total aboveground biomass, evapotranspiration, and net CO₂ flux at four different sites covered with either winter wheat or corn.

Abstract

The likelihood and magnitude of the impacts of climate change on potential vegetation and the water cycle in Mesoamerica is evaluated. Mesoamerica is a global biodiversity hotspot with highly diverse topographic and climatic conditions and is among the tropical regions with the highest expected changes in precipitation and temperature under future climate scenarios. The biogeographic soil–vegetation–atmosphere model Mapped Atmosphere Plant Soil System (MAPSS) was used for simulating the integrated changes in leaf area index (LAI), vegetation types (grass, shrubs, and trees), evapotranspiration, and runoff at the end of the twenty-first century. Uncertainty was estimated as the likelihood of changes in vegetation and water cycle under three ensembles of model runs, one for each of the groups of greenhouse gas emission scenarios (low, intermediate, and high emissions), for a total of 136 runs generated with 23 general circulation models (GCMs). LAI is likely to decrease over 77%–89% of the region, depending on climate scenario groups, showing that potential vegetation will likely shift from humid to dry types. Accounting for potential effects of CO₂ on water use efficiency significantly decreased impacts on LAI. Runoff will decrease across the region even in areas where precipitation increases (even under increased water use efficiency), as temperature change will increase evapotranspiration. Higher emission scenarios show lower uncertainty (higher likelihood) in modeled impacts. Although the projection spread is high for future precipitation, the impacts of climate change on vegetation and water cycle are predicted with relatively low uncertainty.

There are very few large-scale observations of the chemical composition of the Siberian airshed. The Airborne Extensive Regional Observations in Siberia (YAKAEROSIB) French–Russian research program aims to fill this gap by collecting repeated aircraft high-precision measurements of the vertical distribution of CO2, CO, O3, and aerosol size distribution in the Siberian troposphere on a transect of 4,000 km during campaigns lasting approximately one week. This manuscript gives an overview of the results from five campaigns executed in April 2006, September 2006, August 2007, and early and late July 2008. The dense set of CO2 vertical profiles, consisting of some 50 profiles in each campaign, is shown to constrain large-scale models of CO2 synoptic transport, in particular frontal transport processes. The observed seasonal cycle of CO2 in altitude reduces uncertainty on the seasonal covariance between vegetation fluxes and vertical mixing, known as the “seasonal rectifier effect.” Regarding carbon dioxide, we illustrate the potential of the YAKAEROSIB data to cross-validate a global CO2 transport model. When compared to the CO2 data, the model is likely to be biased toward too-weak mixing in winter, as it overestimates the CO2 vertical gradient compared to the observation. Regarding pollutants, we illustrate through case studies the occurence of CO enhancements of 30–50 ppb above background values, coincident with high O3. These high CO values correspond to large-scale transport of anthropogenic emissions from Europe, and to wildfires in the Caspian Sea area, over much cleaner Arctic air (September 2006). An occurence of extremely high CO values above 5,000 km in eastern Siberia is found to be related to the very fast transport and uplift of Chinese anthropogenic emissions caused by a cold front (April 2006).

Abstract

Carbon balance of terrestrial ecosystems in the northern high latitudes (NHL) is sensitive to climate change. It remains uncertain whether current regional carbon uptake capacity can be sustained under future warming. Here the atmospheric CO₂ drawdown rate (CDR) between 1974 and 2014, defined as the CO₂ decrease in ppm over the number of days in spring or summer, is estimated using atmospheric CO₂ observations at Barrow (now known as Utqiaġvik), Alaska. We found that the sensitivity of CDR to interannual seasonal air temperature anomalies has trended toward less carbon uptake for a given amount of warming over this period. Changes in interannual temperature sensitivity of CDR suggest that relatively warm springs now result in less of a carbon uptake enhancement. Similarly, relatively warm summers now result in greater carbon release. These results generally agree with the sensitivity of net carbon exchange (NCE) estimated by atmospheric CO₂ inversion. When NCE was aggregated over North America (NA) and Eurasia (EA), separately, the temperature sensitivity of NCE in NA has changed more than in EA. To explore potential mechanisms of this signal, we also examine trends in interannual variability of other climate variables (soil temperature and precipitation), satellite-derived gross primary production (GPP), and Trends in Net Land–Atmosphere Carbon Exchanges (TRENDY) model ensemble results. Our analysis suggests that the weakened spring sensitivity of CDR may be related to the slowdown in seasonal soil thawing rate, while the summer sensitivity change may be caused by the temporally coincident decrease in temperature sensitivity of photosynthesis. This study suggests that the current NHL carbon sink may become unsustainable as temperatures warm further. We also found that current carbon cycle models do not represent the decrease in temperature sensitivity of net carbon flux. We argue that current carbon–climate models misrepresent important aspect of the carbon–climate feedback and bias the estimation of warming influence on NHL carbon balance.

Abstract

As an essential source of freshwater river flow comprises ~80% of the water consumed in China. Per capita water resources in China are only a quarter of the global average, and its economy is demanding in water resources; this creates an urgent need to quantify the factors that contribute to changes in river flow. Here, we used an offline process-based land surface model (ORCHIDEE) at high spatial resolution (0.1° × 0.1°) to simulate the contributions of climate change, rising atmospheric CO₂ concentration, and land-use change to the change in natural river flow for 10 Chinese basins from 1979 to 2015. We found that climate change, especially an increase in precipitation, was responsible for more than 90% of the changes in natural river flow, while the direct effect of rising CO₂ concentration and land-use change contributes at most 6.3%. Nevertheless, rising CO₂ concentration and land-use change cannot be neglected in most basins as these two factors significantly change transpiration. From 2003 to 2015, the increase in water consumption offset more than 30% of the increase in natural river flow in northern China, especially in the Yellow River basin (~140%), but it had little effect on observed river flow in southern China. Although the uncertainties of rainfall data and the statistical water consumption data could propagate the uncertainties in simulated river flow, this study could be helpful for water planning and management in China under the context of global warming.

Abstract

Leaf area index (LAI) is increasing throughout the globe, implying Earth greening. Global modeling studies support this contention, yet satellite observations and model simulations have never been directly compared. Here, for the first time, a coupled land–climate model was used to quantify the potential impact of the satellite-observed Earth greening over the past 30 years on the terrestrial water cycle. The global LAI enhancement of 8% between the early 1980s and the early 2010s is modeled to have caused increases of 12.0 ± 2.4 mm yr⁻¹ in evapotranspiration and 12.1 ± 2.7 mm yr⁻¹ in precipitation—about 55% ± 25% and 28% ± 6% of the observed increases in land evapotranspiration and precipitation, respectively. In wet regions, the greening did not significantly decrease runoff and soil moisture because it intensified moisture recycling through a coincident increase of evapotranspiration and precipitation. But in dry regions, including the Sahel, west Asia, northern India, the western United States, and the Mediterranean coast, the greening was modeled to significantly decrease soil moisture through its coupling with the atmospheric water cycle. This modeled soil moisture response, however, might have biases resulting from the precipitation biases in the model. For example, the model dry bias might have underestimated the soil moisture response in the observed dry area (e.g., the Sahel and northern India) given that the modeled soil moisture is near the wilting point. Thus, an accurate representation of precipitation and its feedbacks in Earth system models is essential for simulations and predictions of how soil moisture responds to LAI changes, and therefore how the terrestrial water cycle responds to climate change.

Abstract

Rapid warming has led to an aggregated environmental degradation over the Tibetan Plateau (TP) in the last few decades, including accelerated glacier retreat, early snowmelt, permafrost degradation, and forest fire occurrence. Attribution of this warming in recent decades has mainly been focused on anthropogenic forcing. Yet, linkages to the Atlantic multidecadal variability (AMV), an essential part of the climate system causing decadal to centennial fluctuations of temperature, remains poorly understood for the TP, especially at long time scales. Using well-replicated tree-ring width records, we reconstructed 358 years of summer minimum temperature (MinT) of the whole TP. This reconstruction matches the recent warming signal recorded since the 1980s, and captures 63% of the variance in 1950–2005 instrumental records. A teleconnection from the North Atlantic to the TP is further identified based in observations and simulations with an atmospheric general circulation model (AGCM). We propose that half of the multidecadal variability of TP summer MinT can be explained by the AMV over the past three and a half centuries. Both observations and AGCM simulations indicate that the AMV warm phase induces a zonal dipole response in sea level pressure across the Atlantic–Eurasia region, with anomalously high surface pressure and corresponding downward atmospheric motion over the TP. We propose that the descending motion during warm AMV phases causes negative rainfall and positive temperature anomalies over the TP. Our findings highlight that the AMV plays a role in the multidecadal temperature variability over the TP.