The project Land-Use and Climate, Identification of Robust Impacts (LUCID) was conceived to address the robustness of biogeophysical impacts of historical land use–land cover change (LULCC). LUCID ...used seven atmosphere–land models with a common experimental design to explore those impacts of LULCC that are robust and consistent across the climate models. The biogeophysical impacts of LULCC were also compared to the impact of elevated greenhouse gases and resulting changes in sea surface temperatures and sea ice extent (CO2SST). Focusing the analysis on Eurasia and North America, this study shows that for a number of variables LULCC has an impact of similar magnitude but of an opposite sign, to increased greenhouse gases and warmer oceans. However, the variability among the individual models’ response to LULCC is larger than that found from the increase in CO2SST. The results of the study show that although the dispersion among the models’ response to LULCC is large, there are a number of robust common features shared by all models: the amount of available energy used for turbulent fluxes is consistent between the models and the changes in response to LULCC depend almost linearly on the amount of trees removed. However, less encouraging is the conclusion that there is no consistency among the various models regarding how LULCC affects the partitioning of available energy between latent and sensible heat fluxes at a specific time. The results therefore highlight the urgent need to evaluate land surface models more thoroughly, particularly how they respond to a perturbation in addition to how they simulate an observed average state.
Surface cooling in temperate regions is a common biogeophysical response to historical Land‐Use induced Land Cover Change (LULCC). The climate models involved in LUCID show, however, significant ...differences in the magnitude and the seasonal partitioning of the temperature change. The LULCC‐induced cooling is directed by decreases in absorbed solar radiation, but its amplitude is 30 to 50% smaller than the one that would be expected from the sole radiative changes. This results from direct impacts on the total turbulent energy flux (related to changes in land‐cover properties other than albedo, such as evapotranspiration efficiency or surface roughness) that decreases at all seasons, and thereby induces a relative warming in all models. The magnitude of those processes varies significantly from model to model, resulting on different climate responses to LULCC. To address this uncertainty, we analyzed the LULCC impacts on surface albedo, latent heat and total turbulent energy flux, using a multivariate statistical analysis to mimic the models' responses. The differences are explained by two major ‘features’ varying from one model to another: the land‐cover distribution and the simulated sensitivity to LULCC. The latter explains more than half of the inter‐model spread and resides in how the land‐surface functioning is parameterized, in particular regarding the evapotranspiration partitioning within the different land‐cover types, as well as the role of leaf area index in the flux calculations. This uncertainty has to be narrowed through a more rigorous evaluation of our land‐surface models.
Key Points
Non‐radiative effects of LULCC reduce by 30 to 50% the albedo‐induced cooling
Land use representation is a major cause of uncertainty in the LULCC impacts
LSMs' parameterizations lead to divergent evaporation responses to LULCC
Regional hot extremes are projected to increase more strongly than global mean temperature, with substantially larger changes than 2°C even if global warming is limited to this level. We investigate ...the role of soil moisture‐temperature feedbacks for this response based on multimodel experiments for the 21st century with either interactive or fixed (late 20th century mean seasonal cycle) soil moisture. We analyze changes in the hottest days in each year in both sets of experiments, relate them to the global mean temperature increase, and investigate processes leading to these changes. We find that soil moisture‐temperature feedbacks significantly contribute to the amplified warming of the hottest days compared to that of global mean temperature. This contribution reaches more than 70% in Central Europe and Central North America. Soil moisture trends are more important for this response than short‐term soil moisture variability. These results are relevant for reducing uncertainties in regional temperature projections.
Key Points
Soil moisture‐climate feedbacks contribute up to more than 70% of the additional warming of regional hot extremes beyond global mean warming
This feedback is mostly related to multidecadal trends in soil moisture rather than its subseasonal or interannual variability
Uncertainties in regional temperature projections can be linked to this long‐term soil moisture‐temperature feedback
The effects of land-use changes on climate are assessed using specified-concentration simulations complementary to the representative concentration pathway 2.6 (RCP2.6) and RCP8.5 scenarios performed ...for phase 5 of the Coupled Model Intercomparison Project (CMIP5). This analysis focuses on differences in climate and land–atmosphere fluxes between the ensemble averages of simulations with and without land-use changes by the end of the twenty-first century. Even though common land-use scenarios are used, the areas of crops and pastures are specific for each Earth system model (ESM). This is due to different interpretations of land-use classes. The analysis reveals that fossil fuel forcing dominates land-use forcing. In addition, the effects of land-use changes are globally not significant, whereas they are significant for regions with land-use changes exceeding 10%. For these regions, three out of six participating models—the Second Generation Canadian Earth System Model (CanESM2); Hadley Centre Global Environmental Model, version 2 (Earth System) (HadGEM2-ES); and Model for Interdisciplinary Research on Climate, Earth System Model (MIROC-ESM)—reveal statistically significant changes in mean annual surface air temperature. In addition, changes in land surface albedo, available energy, and latent heat fluxes are small but significant for most ESMs in regions affected by land-use changes. These climatic effects are relatively small, as land-use changes in the RCP2.6 and RCP8.5 scenarios are small in magnitude and mainly limited to tropical and subtropical regions. The relative importance of the climatic effects of land-use changes is higher for the RCP2.6 scenario, which considers an expansion of biofuel croplands as a climate mitigation option. The underlying similarity among all models is the loss in global land carbon storage due to land-use changes.
Seven climate models were used to explore the biogeophysical impacts of human‐induced land cover change (LCC) at regional and global scales. The imposed LCC led to statistically significant decreases ...in the northern hemisphere summer latent heat flux in three models, and increases in three models. Five models simulated statistically significant cooling in summer in near‐surface temperature over regions of LCC and one simulated warming. There were few significant changes in precipitation. Our results show no common remote impacts of LCC. The lack of consistency among the seven models was due to: 1) the implementation of LCC despite agreed maps of agricultural land, 2) the representation of crop phenology, 3) the parameterisation of albedo, and 4) the representation of evapotranspiration for different land cover types. This study highlights a dilemma: LCC is regionally significant, but it is not feasible to impose a common LCC across multiple models for the next IPCC assessment.
As climate change research becomes increasingly applied, the need for actionable information is growing rapidly. A key aspect of this requirement is the representation of uncertainties. The ...conventional approach to representing uncertainty in physical aspects of climate change is probabilistic, based on ensembles of climate model simulations. In the face of deep uncertainties, the known limitations of this approach are becoming increasingly apparent. An alternative is thus emerging which may be called a ‘storyline’ approach. We define a storyline as a physically self-consistent unfolding of past events, or of plausible future events or pathways. No a priori probability of the storyline is assessed; emphasis is placed instead on understanding the driving factors involved, and the plausibility of those factors. We introduce a typology of four reasons for using storylines to represent uncertainty in physical aspects of climate change: (i) improving risk awareness by framing risk in an event-oriented rather than a probabilistic manner, which corresponds more directly to how people perceive and respond to risk; (ii) strengthening decision-making by allowing one to work backward from a particular vulnerability or decision point, combining climate change information with other relevant factors to address compound risk and develop appropriate stress tests; (iii) providing a physical basis for partitioning uncertainty, thereby allowing the use of more credible regional models in a conditioned manner and (iv) exploring the boundaries of plausibility, thereby guarding against false precision and surprise. Storylines also offer a powerful way of linking physical with human aspects of climate change.
Objective
Lung cancer patients report among the highest distress rates of all cancer patients. Partners report similar distress rates. The present study examined the effectiveness of additional ...mindfulness‐based stress reduction (care as usual CAU + MBSR) versus solely CAU to reduce psychological distress in lung cancer patients and/or their partners.
Methods
We performed a multicentre, parallel‐group, randomized controlled trial. Mindfulness‐based stress reduction is an 8‐week group‐based intervention, including mindfulness practice and teachings on stress. Care as usual included anticancer treatment, medical consultations, and supportive care. The primary outcome was psychological distress. Secondary outcomes included quality of life, caregiver burden, relationship satisfaction, mindfulness skills, self‐compassion, rumination, and posttraumatic stress symptoms. Outcomes were assessed at baseline, post‐intervention, and 3‐month follow‐up. Linear mixed modeling was conducted on an intention‐to‐treat sample. Moderation (gender, disease stage, baseline distress, participation with/without partner) and mediation analyses were performed.
Results
A total of 31 patients and 21 partners were randomized to CAU + MBSR and 32 patients and 23 partners to CAU. After CAU + MBSR patients reported significantly less psychological distress (p = .008, d = .69) than after CAU. Baseline distress moderated outcome: those with more distress benefitted most from MBSR. Additionally, after CAU + MBSR patients showed more improvements in quality of life, mindfulness skills, self‐compassion, and rumination than after CAU. In partners, no differences were found between groups.
Conclusion
Our findings suggest that psychological distress in lung cancer patients can be effectively treated with MBSR. No effect was found in partners, possibly because they were more focused on patients' well‐being rather than their own.
This study investigates likely changes in mean and extreme precipitation over southern Africa in response to changes in radiative forcing using an ensemble of global climate models prepared for the ...Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4). Extreme seasonal precipitation is defined in terms of 10-yr return levels obtained by inverting a generalized Pareto distribution fitted to excesses above a predefined high threshold. Both present (control) and future climate precipitation extremes are estimated. The future-to-control climate ratio of 10-yr return levels is then used as an indicator for the likely changes in extreme seasonal precipitation.
A Bayesian approach to multimodel ensembling is adopted. The relative weights assigned to each of the model simulations is determined from bias, convergence, and correlation. Using this method, the probable limits of the changes in mean and extreme precipitation are estimated from their posterior distribution.
Over the western parts of southern Africa, an increase in the severity of dry extremes parallels a statistically significant decrease in mean precipitation during austral summer months. A notable delay in the onset of the rainy season is found in almost the entire region. An early cessation is found in many parts. This implies a statistically significant shortening of the rainy season.
A substantial reduction in moisture influx from the southwestern Indian Ocean during austral spring is projected. This and the preaustral spring moisture deficits are possible mechanisms delaying the rainfall onset in southern Africa. A possible offshore (northeasterly) shift of the tropical–temperate cloud band is consistent with more severe droughts in the southwest of southern Africa and enhanced precipitation farther north in Zambia, Malawi, and northern Mozambique.
This study shows that changes in the mean vary on relatively small spatial scales in southern Africa and differ between seasons. Changes in extremes often, but not always, parallel changes in the mean precipitation.
Drought and ecosystem carbon cycling van der Molen, M.K.; Dolman, A.J.; Ciais, P. ...
Agricultural and forest meteorology,
07/2011, Letnik:
151, Številka:
7
Journal Article
Recenzirano
► Intermittent droughts interact differently with the carbon cycle than gradual change. ► Direct effects on carbon exchange depend strongly on vegetation species strategie. ► Drought induced ...mortality is species sensitive and gives rise to competition. ► Disturbed nutrient and carbohydrate reservoirs cause carry-over effects. ► Models need to simulate these longer-term climate-carbon cycle feedbacks.
Drought as an intermittent disturbance of the water cycle interacts with the carbon cycle differently than the ‘gradual’ climate change. During drought plants respond physiologically and structurally to prevent excessive water loss according to species-specific water use strategies. This has consequences for carbon uptake by photosynthesis and release by total ecosystem respiration. After a drought the disturbances in the reservoirs of moisture, organic matter and nutrients in the soil and carbohydrates in plants lead to longer-term effects in plant carbon cycling, and potentially mortality. Direct and carry-over effects, mortality and consequently species competition in response to drought are strongly related to the survival strategies of species. Here we review the state of the art of the understanding of the relation between soil moisture drought and the interactions with the carbon cycle of the terrestrial ecosystems. We argue that plant strategies must be given an adequate role in global vegetation models if the effects of drought on the carbon cycle are to be described in a way that justifies the interacting processes.
The Plumbing of Land Surface Models Best, M. J.; Abramowitz, G.; Johnson, H. R. ...
Journal of hydrometeorology,
06/2015, Letnik:
16, Številka:
3
Journal Article
Recenzirano
Odprti dostop
The Protocol for the Analysis of Land Surface Models (PALS) Land Surface Model Benchmarking Evaluation Project (PLUMBER) was designed to be a land surface model (LSM) benchmarking intercomparison. ...Unlike the traditional methods of LSM evaluation or comparison, benchmarking uses a fundamentally different approach in that it sets expectations of performance in a range of metrics a priori—before model simulations are performed. This can lead to very different conclusions about LSM performance. For this study, both simple physically basedmodels and empirical relationships were used as the benchmarks. Simulations were performed with 13 LSMs using atmospheric forcing for 20 sites, and then model performance relative to these benchmarks was examined. Results show that even for commonly used statistical metrics, the LSMs’ performance varies considerably when compared to the different benchmarks. All models outperform the simple physically based benchmarks, but for sensible heat flux the LSMs are themselves outperformed by an out-of-sample linear regression against downward shortwave radiation. While moisture information is clearly central to latent heat flux prediction, the LSMs are still outperformed by a three-variable nonlinear regression that uses instantaneous atmospheric humidity and temperature in addition to downward shortwave radiation. These results highlight the limitations of the prevailing paradigm of LSM evaluation that simply compares an LSM to observations and to other LSMs without a mechanism to objectively quantify the expectations of performance. The authors conclude that their results challenge the conceptual view of energy partitioning at the land surface.