The climatic impacts of land surface change and carbon management, and the implications for climate-change mitigation policy

Strategies to mitigate anthropogenic climate change recognize that carbon sequestration in the terrestrial biosphere can reduce the build-up of carbon dioxide in the Earth’s atmosphere. However, climate mitigation policies do not generally incorporate the effects of these changes in the land surface on the surface albedo, the fluxes of sensible and latent heat to the atmosphere, and the distribution of energy within the climate system. Changes in these components of the surface energy budget can affect the local, regional, and global climate. Given the goal of mitigating climate change, it is important to consider all of the effects of changes in terrestrial vegetation and to work toward a better understanding of the full climate system. Acknowledging the importance of land surface change as a component of climate change makes it more challenging to create a system of credits and debits wherein emission or sequestration of carbon in the biosphere is equated with emission of carbon from fossil fuels. Recognition of the complexity of human-caused changes in climate does not, however, weaken the importance of actions that would seek to minimize our disturbance of the Earth’s environmental system and that would reduce societal and ecological vulnerability to environmental change and variability.     

Glacial meltwater cooling of the Gulf of Mexico: GCM implications for Holocene and present-day climates

An atmospheric general circulation model, the NCAR CCM, has been used to investigate the possible effects that reduced Gulf of Mexico sea surface temperatures (SST) could have on regional and hemispheric climates. ¹⁸O records and terrestrial evidence indicate at least two major glacial meltwater discharges into the Gulf of Mexico subsequent to the last glacial maximum. It is probable that these discharges reduced Gulf of Mexico SST. We have conducted three numerical experiments, with imposed gulf-wide SST coolings of 3°C, 6°C, and 12°C, and find in all three experiments significant reductions in the North Atlantic storm-track intensity, along with a strong decrease in transient eddy water vapor transport out of the Gulf of Mexico. Surface pressures are higher over the North Atlantic, indicating a reduction of the climatological Icelandic low. The region is generally cooler and drier, with a reduction in precipitation that agrees well with evidence from Greenland ice cores. Other statistically significant changes occur across the Northern Hemisphere, but vary between the three experiments. In particular, warmer, wetter conditions are found over Europe for both the 6°C and 12°C SST reductions, but cooler conditions are found for the 3°C reduction. This indicates a dependence, in both the sign and magnitude of the model response, on the magnitude of the imposed SST anomaly. The results suggest that the present-day North Atlantic storm track is dependent on warm Gulf of Mexico SST for much of its intensity. They also suggest that meltwater-induced coolings may help account, in part, for some of the climatic oscillations that occurred during the last glacial/interglacial transition.     

Observations on the use of analytical and numerical models for the description of transfer to porous surface vegetation such as lichen

Convective deposition of submicron-size aerosol to porous surface vegetation was studied by electrochemical simulation, under Reynolds and Schmidt similarity, to a rectangular array of closely-packed lichen and artificial wire roughness layers. Results, showing an approximate tenfold increase in deposition velocity over that of a flat plate placed at the same position, were compared with predictions made on the basis of various rough-surface transfer models, including those based on statistical eddy renewal, as well as with numerical solutions of the diffusion equation in statistically-renewed surface cavities. Most analytical models could be made to fit the observed data, at least for a limited range of flow velocities, but poorly known and poorly defined parameters limit their usefulness for predictive purposes; and their validity across a large variation in molecular diffusivity (or Schmidt number Sc) is generally not assured. Numerical models also depend on poorly substantiated physical assumptions but the effect of such assumptions on transfer can be calculated for a wider range of conditions than those permitting an analytical solution. This allows more direct feedback between model assumptions and calculated or observed transfer. Numerically calculated values for deposition velocity in air for Sc from 0.7 to 7000 and flow velocities from 0.2 to 5 m s^-1 are presented for different model assumptions, with values ranging from < 0.01 to > 1 cms^-1.     

The use of general circulation models in the analysis of the ecosystem impacts of climatic change

The use of general circulation models in the estimation of the impact of climatic change on the global ecosystem is seen to depend primarily on their ability to reliably depict the seasonal and geographical distribution of the changes in surface climate variables. While present GCMs generally simulate the observed distribution of surface air temperature reasonably well, they show significantly different changes in the equilibrium temperature as a result of doubled CO₂, for example. These disagreements are attributed to differences in the model's resolution and parameterization of subgrid-scale processes. Such model-dependent errors notwithstanding, much more information of possible use in impact analysis can be extracted from general circulation model simulations than has generally been done so far. The completeness, consistency and experimental possibilities offered by simulated data sets permit the systematic extraction of a wide variety of statistics important to the surface ecosystem, such as the length of the growing season, the duration of rainless periods, and the surface moisture stress.Assuming further model improvements, the elements of a model-assisted methodology for climate impact analysis are seen to be: (1) the determination of the seasonal and geographical distribution of that portion of simulated climatic changes which are both statistically and physically significant; (2) the transformation of the (significant) large-scale climatic changes onto the local scale of impact (the climate inversion problem); and (3) the design of specific statistical parameters or functions relevant to local ecosystem impacts.     

Modeling impacts of vegetation in western China on the summer climate of northwestern China

Using the monthly NCEP-NCAR reanalysis dataset, the monthly temperature and precipitation at surface stations of China, and the MM5 model, we examine impacts of vegetation cover changes in western China on the interdecadal variability of the summer climate over northwestern China during the past 30 years. It is found that the summer atmospheric circulation, surface air temperature, and rainfall in the 1990s were different from those in the 1970s over northwestern China, with generally more rainfall and higher temperatures in the 1990s. Associated with these changes, an anomalous wave train appears in the lower troposphere at the midlatitudes of East Asia and the low-pressure system to the north of the Tibetan Plateau is weaker. Meanwhile, the South Asian high in the upper troposphere is also located more eastward. Numerical experiments show that change of vegetation cover in western China generally forces anomalous circulations and temperatures and rainfall over these regions. This consistency between the observations and simulations implies that the interdecadal variability of the summer climate over northwestern China between the 1990s and 1970s may result from a change of vegetation cover over western China.     

城市植被对冬季气象要素影响的数值模拟研究

为认识并量化城市地区自然植被对城市气象特征的综合影响及其在不同季节的变化趋势,本文基于区域边界层模式(Regional Boundary Layer Model,RBLM),利用敏感性数值试验的方法量化评估了冬季背景下,城市植被对苏州地区气象要素的综合影响,及其在不同绿化情境下的变化特征。研究结果表明:冬季城市植被会导致气温及城市热岛强度的下降,下降幅度随着植被覆盖率的提高而增大,当市区树木覆盖率分别为0、20%和40%时,日平均城市热岛强度分别为1. 8、1. 4和1. 0℃。与苏州市真实绿化情境相比,市区树木覆盖率分别为20%和40%的理想试验方案,可以导致市区日平均气温分别下降约0. 23℃和0. 84℃。城市植被还会通过叶面及土壤表面的蒸发蒸腾作用,增加空气中的水汽含量,当市区树木覆盖率分别为0、20%和40%时,中午时空气比湿分别为2. 46、2. 61和2. 78 g·kg~(-1)。相同覆盖率条件下,草地绿化方案对气温和空气湿度的影响要明显弱于树木。城市植被会对区域地表能量平衡过程产生明显影响,使到达地面的太阳辐射减少,地面温度降低。当树木覆盖率分别为0、20%和40%时,中午地表净辐射通量最大值分别为433、382和332 W·m~(-2)。地面温度的下降以及植被、土壤的蒸发蒸腾作用,使感热减少,潜热增加。自然植被对城市气象要素的影响在冬季要明显弱于夏季。     

Some aspects of the relation between monthly temperatures and rainfall,and its use in evaluating earlier climates in the Middle East

The quantitative relation between mean monthly temperatures and rainfall has been investigated for a hundred years period at Jerusalem. It was found that a decrease of 1°C in the mean monthly temperature is associated with an average increase of 13 mm in monthly precipitation, on the seasonal scale. The findings are consonant with previous results pointing to an increase of about 100 mm in annual rainfall for a decrease of 1°C in the seasonal temperature. Such coefficients may, to a first approximation and with some qualifications, be used in estimating rainfall in earlier periods in the Middle East, and to evaluate hydrological effects and potential risks in future centuries.     

Evaluation of the individual allocation scheme and its impacts in a dynamic global vegetation model

植物的生长策略不仅影响生态系统结构,而且对全球碳、水循环也起着至关重要的作用。本文以中国科学院大气物理研究所研发的第一代全球植被动力学模式IAP-DGVM1.0为平台,考察森林生态系统中树的个体生长方案及其影响。结果表明,与观测相比,模式高估了个体茎生物量,低估了个体叶生物量,从而进一步高估了中国森林生态系统的总生物量和成熟林受干扰后恢复的时间尺度,低估了生态系统净初级生产力和叶面积指数。     

A framework for testing the ability of models to project climate change and its impacts

Models used for climate change impact projections are typically not tested for simulation beyond current climate conditions. Since we have no data truly reflecting future conditions, a key challenge in this respect is to rigorously test models using proxies of future conditions. This paper presents a validation framework and guiding principles applicable across earth science disciplines for testing the capability of models to project future climate change and its impacts. Model test schemes comprising split-sample tests, differential split-sample tests and proxy site tests are discussed in relation to their application for projections by use of single models, ensemble modelling and space-time-substitution and in relation to use of different data from historical time series, paleo data and controlled experiments. We recommend that differential-split sample tests should be performed with best available proxy data in order to build further confidence in model projections.     

Retrospective and prospective model simulations of sea level rise impacts on Gulf of Mexico coastal marshes and forests in Waccasassa Bay, Florida

The State of Florida (USA) is especially threatened by sea level rise due to extensive low elevation coastal habitats (approximately 8,000?km²?<?1?m above sea level) where the majority of the human population resides. We used the Sea Level Affecting Marshes Model (SLAMM) simulation to improve understanding of the magnitude and location of these changes for 58,000?ha of the Waccasassa Bay region of Florida??s central Gulf of Mexico coast. To assess how well SLAMM portrays changes in coastal wetland systems resulting from sea level rise, we conducted a hindcast in which we compared model results to 30?years of field plot data. Overall, the model showed the same pattern of coastal forest loss as observed. Prospective runs of SLAMM using 0.64?m, 1?m and 2?m sea level rise scenarios predict substantial changes over this century in the area covered by coastal wetland systems including net losses of coastal forests (69%, 83%, and 99%, respectively) and inland forests (33%, 50%, and 88%), but net gains of tidal flats (17%, 142%, and 3,837%). One implication of these findings at the site level is that undeveloped, unprotected lands inland from the coastal forest should be protected to accommodate upslope migration of this natural community in response to rising seas. At a broader scale, our results suggest that coastal wetland systems will be unevenly affected across the Gulf of Mexico as sea level rises. Species vulnerable to these anticipated changes will experience a net loss or even elimination.     

Toward Bayesian uncertainty quantification for forestry models used in the United Kingdom Greenhouse Gas Inventory for land use, land use change, and forestry

The Greenhouse Gas Inventory for the United Kingdom currently uses a simple carbon-flow model, CFLOW, to calculate the emissions and removals associated with forest planting since 1920. Here, we aim to determine whether a more complex process-based model, the BASic FORest (BASFOR) simulator, could be used instead of CFLOW. The use of a more complex approach allows spatial heterogeneity in soils and weather to be accounted for, but places extra demands on uncertainty quantification. We show how Bayesian methods can be used to address this problem.     

气候变化、植被改变及人类用水与黄河流域水循环的研究进展

受气候增暖和人类活动的双重影响,黄河流域的水循环正在发生显著变化,水资源供需矛盾突出。陆地水循环是一个复杂的非线性系统,为清晰认识水循环变化的全貌,并合理高效利用有限的水资源量,需要综合考虑水循环各个要素之间的协同变化机制。同时,在“人类世”背景下,黄河流域水循环研究必须考虑人类活动的影响,主要包括植被变化和人类用水,其中人类用水主体为农业灌溉。自从实施生态恢复工程以来,黄土高原植被覆盖明显改善的同时也引发了对径流、蒸散发、降水、土壤湿度以及地下水的一系列影响,且研究结论还存在一些争议,但黄土高原植被覆盖改善使得该地区蒸散发量增加基本达成共识,大多数研究支持植被改善减少径流的结论。黄河流域的农业灌溉方式主要为大水漫灌,其对地表蒸散发、地表水及地下水多个过程具有重要影响。本文主要针对黄河流域的水循环研究,讨论相关研究进展以及发展方向。     

An overview of the performance of CMIP6 models in the tropical Atlantic: mean state,variability, and remote impacts

General circulation models of the Coupled Model Intercomparison Project Phase 6 (CMIP6) are examined with respect to their ability to simulate the mean state and variability of the tropical Atlantic and its linkage to the tropical Pacific. While, on average, mean state biases have improved little, relative to the previous intercomparison (CMIP5), there are now a few models with very small biases. In particular the equatorial Atlantic warm SST and westerly wind biases are mostly eliminated in these models. Furthermore, interannual variability in the equatorial and subtropical Atlantic is quite realistic in a number of CMIP6 models, which suggests that they should be useful tools for understanding and predicting variability patterns. The evolution of equatorial Atlantic biases follows the same pattern as in previous model generations, with westerly wind biases during boreal spring preceding warm sea-surface temperature (SST) biases in the east during boreal summer. A substantial portion of the westerly wind bias exists already in atmosphere-only simulations forced with observed SST, suggesting an atmospheric origin. While variability is relatively realistic in many models, SSTs seem less responsive to wind forcing than observed, both on the equator and in the subtropics, possibly due to an excessively deep mixed layer originating in the oceanic component. Thus models with realistic SST amplitude tend to have excessive wind amplitude. The models with the smallest mean state biases all have relatively high resolution but there are also a few low-resolution models that perform similarly well, indicating that resolution is not the only way toward reducing tropical Atlantic biases. The results also show a relatively weak link between mean state biases and the quality of the simulated variability. The linkage to the tropical Pacific shows a wide range of behaviors across models, indicating the need for further model improvement.

     

ENSEMBLES-based assessment of regional climate effects in Luxembourg and their impact on vegetation

Projected future regional climate changes in Luxembourg are assessed based on a six-member ensemble of regional climate models (RCM) from the ENSEMBLES project. The key aspects are projected changes in air temperature and their impacts on vegetation. Up to now, there have been only few assessments of future climate conditions for Luxembourg. As agriculture is the dominant land use in Luxembourg, possible effects on crops and vegetation in general are highly relevant. Different RCMs at 25 km spatial and a daily temporal resolution, ranging from 1961 to 2100 based on the SRES A1B emission scenario are used. To reduce systematic biases in the RCM-derived time series, a bias correction is applied. Multi-model annual mean temperatures are projected to increase by 3.1 °C between the reference time span (1961 to 1990) and the far future (2069 to 2098). Clear change signals are found in seasonal bivariate frequency distributions of air temperature and precipitation. Derived impacts are an elongation of the thermal vegetation period by 6.2 days per decade due to an earlier onset in spring; growing degree day sums show a substantial increase leading to potentially better growth conditions; the earlier onset of the vegetation period causes an increase in late frost risk, especially in the near future (2021 to 2050) projections compared to the reference period.     

Rainfall and foliar dynamics in tropical Southern Africa: Potential impacts of global climatic change on savanna vegetation

Foliar dynamics in tropical southern Africa are examined using meteorological satellite observations (NOAA-AVHRR) collected from 1981–1990, processed as monthly Normalized Difference Vegetation Index (NDVI) images, and resampled to 7.6 km resolution. Time series of NDVI and raingauge data are presented and analyzed using a variety of statistics. The analysis of time series from individual locations revealed positive correlations between NDVI and rainfall at semiarid locations where rainfall tended to be highly variable; whereas the relationships between these variables was insignificant in more mesic sites where the climate tended to be more predictable. In addition, there appeared to be an annual rainfall threshold of approximately 600 mm beyond which relationships between rainfall and NDVI were insignificant at the monthly time scale. Relationships between rainfall and NDVI were stronger at annual time scale, which suggests that factors other than contemporaneous rainfall account for photosynthetic activity in any given growing season. Using a rainfall surface and NDVI imagery, a large area of early greening behavior is identified, which corresponded approximately to the distribution of mesic, plateau woodlands. These so-called, miombo woodlands may be especially vulnerable if the arrival of spring rainfall were to undergo a positive shift in phase.     

An annual cycle of vegetation in a GCM. Part II: global impacts on climate and hydrology

The Met Office Hadley Centre Unified Model (HadAM3) with the tiled version of the Met Office Surface Exchange Scheme (MOSES2) land surface scheme is used to assess the impact of a comprehensive imposed vegetation annual cycle on global climate and hydrology. Two 25-year numerical experiments are completed: the first with structural vegetation characteristics (Leaf Area Index, LAI, canopy height, canopy water capacity, canopy heat capacity, albedo) held at annual mean values, the second with realistic seasonally varying vegetation characteristics. It is found that the seasonalities of latent heat flux and surface temperature are widely affected. The difference in latent heat flux between experiments is proportional to the difference in LAI. Summer growing season surface temperatures are between 1 and 4 K lower in the phenology experiment over a majority of grid points with a significant vegetation annual cycle. During winter, midlatitude surface temperatures are also cooler due to brighter surface albedo over low LAI surfaces whereas during the dry season in the tropics, characterized by dormant vegetation, surface temperatures are slightly warmer due to reduced transpiration. Precipitation is not as systematically affected as surface temperature by a vegetation annual cycle, but enhanced growing season precipitation rates are seen in regions where the latent heat flux (evaporation) difference is large. Differences between experiments in evapotranspiration, soil moisture storage, the timing of soil thaw, and canopy interception generate regional perturbations to surface and sub-surface runoff annual cycles in the model.