Can climate‐effective land management reduce regional warming?

Limiting global warming to well below 2°C is an imminent challenge for humanity. However, even if this global target can be met, some regions are still likely to experience substantial warming relative to others. Using idealized global climate simulations, we examine the potential of land management options in affecting regional climate, with a focus on crop albedo enhancement and irrigation (climate-effective land management). The implementation is performed over all crop regions globally to provide an upper bound. We find that the implementation of both crop albedo enhancement and irrigation can reduce hot temperature extremes by more than 2°C in North America, Eurasia, and India over the 21st century relative to a scenario without management application. The efficacy of crop albedo enhancement scales with the magnitude, where a cooling response exceeding 0.5°C for hot temperature extremes was achieved with a large (i.e., ≥0.08) change in crop albedo. Regional differences were attributed to the surface energy balance response with temperature changes mostly explained by latent heat flux changes for irrigation and net shortwave radiation changes for crop albedo enhancement. However, limitations do exist, where we identify warming over the winter months when climate-effective land management is temporarily suspended. This was associated with persistent cloud cover that enhances longwave warming. It cannot be confirmed if the magnitude of this feedback is reproducible in other climate models. Our results overall demonstrate that regional warming of hot extremes in our climate model can be partially mitigated when using an idealized treatment of climate-effective land management

Evaluating and improving the Community Land Model's sensitivity to land cover

Modeling studies have shown the importance of biogeophysical effects of deforestation on local climate conditions but have also highlighted the lack of agreement across different models. Recently, remote-sensing observations have been used to assess the contrast in albedo, evapotranspiration (ET), and land surface temperature (LST) between forest and nearby open land on a global scale. These observations provide an unprecedented opportunity to evaluate the ability of land surface models to simulate the biogeophysical effects of forests. Here, we evaluate the representation of the difference of forest minus open land (i.e., grassland and cropland) in albedo, ET, and LST in the Community Land Model version 4.5 (CLM4.5) using various remote-sensing and in situ data sources. To extract the local sensitivity to land cover, we analyze plant functional type level output from global CLM4.5 simulations, using a model configuration that attributes a separate soil column to each plant functional type. Using the separated soil column configuration, CLM4.5 is able to realistically reproduce the biogeophysical contrast between forest and open land in terms of albedo, daily mean LST, and daily maximum LST, while the effect on daily minimum LST is not well captured by the model. Furthermore, we identify that the ET contrast between forests and open land is underestimated in CLM4.5 compared to observation-based products and even reversed in sign for some regions, even when considering uncertainties in these products. We then show that these biases can be partly alleviated by modifying several model parameters, such as the root distribution, the formulation of plant water uptake, the light limitation of photosynthesis, and the maximum rate of carboxylation. Furthermore, the ET contrast between forest and open land needs to be better constrained by observations to foster convergence amongst different land surface models on the biogeophysical effects of forests. Overall, this study demonstrates the potential of comparing subgrid model output to local observations to improve current land surface models' ability to simulate land cover change effects, which is a promising approach to reduce uncertainties in future assessments of land use impacts on climate

Modelled biophysical impacts of conservation agriculture on local climates

Including the parameterization of land management practices into Earth System Models has been shown to influence the simulation of regional climates, particularly for temperature extremes. However, recent model development has focused on implementing irrigation where other land management practices such as conservation agriculture (CA) has been limited due to the lack of global spatially explicit datasets describing where this form of management is practiced. Here, we implement a representation of CA into the Community Earth System Model and show that the quality of simulated surface energy fluxes improves when including more information on how agricultural land is managed. We also compare the climate response at the subgrid scale where CA is applied. We find that CA generally contributes to local cooling (~1°C) of hot temperature extremes in mid-latitude regions where it is practiced, while over tropical locations CA contributes to local warming (~1°C) due to changes in evapotranspiration dominating the effects of enhanced surface albedo. In particular, changes in the partitioning of evapotranspiration between soil evaporation and transpiration are critical for the sign of the temperature change: a cooling occurs only when the soil moisture retention and associated enhanced transpiration is sufficient to offset the warming from reduced soil evaporation. Finally, we examine the climate change mitigation potential of CA by comparing a simulation with present-day CA extent to a simulation where CA is expanded to all suitable crop areas. Here, our results indicate that while the local temperature response to CA is considerable cooling (>2°C), the grid-scale changes in climate are counteractive due to negative atmospheric feedbacks. Overall, our results underline that CA has a nonnegligible impact on the local climate and that it should therefore be considered in future climate projections

Present‐day irrigation mitigates heat extremes

Irrigation is an essential practice for sustaining global food production and many regional economies. Emerging scientific evidence indicates that irrigation substantially affects mean climate conditions in different regions of the world. Yet how this practice influences climate extremes is currently unknown. Here we use ensemble simulations with the Community Earth System Model to assess the impacts of irrigation on climate extremes. An evaluation of the model performance reveals that irrigation has a small yet overall beneficial effect on the representation of present-day near-surface climate. While the influence of irrigation on annual mean temperatures is limited, we find a large impact on temperature extremes, with a particularly strong cooling during the hottest day of the year (−0.78 K averaged over irrigated land). The strong influence on extremes stems from the timing of irrigation and its influence on land-atmosphere coupling strength. Together these effects result in asymmetric temperature responses, with a more pronounced cooling during hot and/or dry periods. The influence of irrigation is even more pronounced when considering subgrid-scale model output, suggesting that local effects of land management are far more important than previously thought. Our results underline that irrigation has substantially reduced our exposure to hot temperature extremes in the past and highlight the need to account for irrigation in future climate projections

The Impact of the African Great Lakes on the Regional Climate

Although the African Great Lakes are important regulators for the East African climate, their influence on atmospheric dynamics and the regional hydrological cycle remains poorly understood. This study aims to assess this impact by comparing a regional climate model simulation that resolves individual lakes and explicitly computes lake temperatures to a simulation without lakes. The Consortium for Small-Scale Modelling model in climate mode (COSMO-CLM) coupled to the Freshwater Lake model (FLake) and Community Land Model (CLM) is used to dynamically downscale a simulation from the African Coordinated Regional Downscaling Experiment (CORDEX-Africa) to 7-km grid spacing for the period of 1999–2008. Evaluation of the model reveals good performance compared to both in situ and satellite observations, especially for spatiotemporal variability of lake surface temperatures (0.68-K bias), and precipitation (−116 mm yr−1 or 8% bias). Model integrations indicate that the four major African Great Lakes almost double the annual precipitation amounts over their surface but hardly exert any influence on precipitation beyond their shores. Except for Lake Kivu, the largest lakes also cool the annual near-surface air by −0.6 to −0.9 K on average, this time with pronounced downwind influence. The lake-induced cooling happens during daytime, when the lakes absorb incoming solar radiation and inhibit upward turbulent heat transport. At night, when this heat is released, the lakes warm the near-surface air. Furthermore, Lake Victoria has a profound influence on atmospheric dynamics and stability, as it induces circular airflow with over-lake convective inhibition during daytime and the reversed pattern at night. Overall, this study shows the added value of resolving individual lakes and realistically representing lake surface temperatures for climate studies in this region

Keep it SMPL: Automatic Estimation of 3D Human Pose and Shape from a Single Image

We describe the first method to automatically estimate the 3D pose of the human body as well as its 3D shape from a single unconstrained image. We estimate a full 3D mesh and show that 2D joints alone carry a surprising amount of information about body shape. The problem is challenging because of the complexity of the human body, articulation, occlusion, clothing, lighting, and the inherent ambiguity in inferring 3D from 2D. To solve this, we first use a recently published CNN-based method, DeepCut, to predict (bottom-up) the 2D body joint locations. We then fit (top-down) a recently published statistical body shape model, called SMPL, to the 2D joints. We do so by minimizing an objective function that penalizes the error between the projected 3D model joints and detected 2D joints. Because SMPL captures correlations in human shape across the population, we are able to robustly fit it to very little data. We further leverage the 3D model to prevent solutions that cause interpenetration. We evaluate our method, SMPLify, on the Leeds Sports, HumanEva, and Human3.6M datasets, showing superior pose accuracy with respect to the state of the art.Comment: To appear in ECCV 201

Analysis of the solar cycle and core rotation using 15 years of Mark-I observations:1984-1999. I. The solar cycle

High quality observations of the low-degree acoustic modes (p-modes) exist for almost two complete solar cycles using the solar spectrophotometer Mark-I, located at the Observatorio del Teide (Tenerife, Spain) and operating now as part of the Birmingham Solar Oscillations Network (BiSON). We have performed a Fourier analysis of 30 calibrated time-series of one year duration covering a total period of 15 years between 1984 and 1999. Applying different techniques to the resulting power spectra, we study the signature of the solar activity changes on the low-degree p-modes. We show that the variation of the central frequencies and the total velocity power (TVP) changes. A new method of simultaneous fit is developed and a special effort has been made to study the frequency-dependence of the frequency shift. The results confirm a variation of the central frequencies of acoustic modes of about 450 nHz, peak-to-peak, on average for low degree modes between 2.5 and 3.7 mHz. The TVP is anti-correlated with the common activity indices with a decrease of about 20% between the minimum and the maximum of solar cycle 22. The results are compared with those obtained for intermediate degrees, using the LOWL data. The frequency shift is found to increase with the degree with a weak l-dependence similar to that of the inverse mode mass. This verifies earlier suggestions that near surface effects are predominant.Comment: Accepted by A&A October 3 200

Diversifying selection and color-biased dispersal in the asp viper.

BACKGROUND: The presence of intraspecific color polymorphism can have multiple impacts on the ecology of a species; as a consequence, particular color morphs may be strongly selected for in a given habitat type. For example, the asp viper (Vipera aspis) shows a high level of color polymorphism. A blotched morph (cryptic) is common throughout its range (central and western Europe), while a melanistic morph is frequently found in montane populations, presumably for thermoregulatory reasons. Besides, rare atypical uniformly colored individuals are known here and there. Nevertheless, we found in a restricted treeless area of the French Alps, a population containing a high proportion (>50%) of such specimens. The aim of the study is to bring insight into the presence and function of this color morph by (i) studying the genetic structure of these populations using nine microsatellite markers, and testing for (ii) a potential local diversifying selection and (iii) differences in dispersal capacity between blotched and non-blotched vipers. RESULTS: Our genetic analyses support the occurrence of local diversifying selection for the non-blotched phenotype. In addition, we found significant color-biased dispersal, blotched individuals dispersing more than atypical individuals. CONCLUSION: We hypothesize that, in this population, the non-blotched phenotype possess an advantage over the typical one, a phenomenon possibly due to a better background matching ability in a more open habitat. In addition, color-biased dispersal might be partly associated with the observed local diversifying selection, as it can affect the genetic structure of populations, and hence the distribution of color morphs