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Several numerical simulations were performed, using a global climate model that includes a realistic land surface model, to investigate the impact of Asian tropical vegetation changes on the climate. The control simulation, under conditions of the actual vegetation, and three vegetation-change impact experiments were performed. The horizontal resolution of the model used in these simulations was finer than those of the models used in previous vegetation-change impact studies. In, which is a companion of this paper, the results of the Northern Hemisphere summer June–July–August (JJA) case were described. In the present paper, the results of the analysis concern the Northern Hemisphere winter; that is, the December–January–February (DJF) case are discussed as Part II. It was clarified, from the results of the bare soil and C4 grass experiments, that the decrease in the roughness length, and from the results of the green-less experiment, that the decrease in the latent heat flux exert strong influences on horizontal and convective atmospheric circulations and the distribution of precipitation. Other energy and water balances at the land surface are also significantly influenced by the vegetation changes. The vegetation changes were implemented only in the Asian tropical region. There were, however, possible influences of the vegetation change on the midlatitude atmospheric circulation. It was considered that the vegetation changes from the forest type to grassland or bare soil induced modifications in the Hadley and Walker circulations. In particular, the divergence/convergence anomaly pattern that appeared at the upper-atmospheric level in the C4 grass experiment was very similar to that of an ENSO event. The height anomalies at the 500-hPa level were also similar to those found in an ENSO event. The possibility exists that the deforestation of the Asian tropical region could induce similar teleconnections as those associated with ENSO events. [ABSTRACT FROM AUTHOR]

Solar radiation management (SRM) has been proposed as a form of geoengineering to reduce the climate effects of anthropogenic greenhouse gas emissions. Modeling studies have concluded that SRM, through a reduction in total solar irradiance by approximately 2%, roughly compensates for global mean temperature changes from a doubling of carbon dioxide concentrations. This paper examines the impact of SRM on the terrestrial hydrologic cycle using the Community Land Model, version 4, coupled to the Community Atmosphere Model, version 4, with reductions in solar radiation relative to simulations with present-day and elevated CO2 concentrations. There are significant global and regional impacts due to vegetation-climate interactions that are not compensated when reductions in total solar irradiance of 1%, 2%, and 3% are imposed on top of a doubling of present-day CO2 concentrations. Water cycling slows down under SRM, including decreases in global mean precipitation and evapotranspiration. Changes in runoff and soil moisture are spatially and temporally variable, with implications for local water availability. In the tropics, evapotranspiration decreases because of increases in vegetation water use efficiency. In northern midlatitudes, soil moisture increases when evapotranspiration decreases, with some exceptions during boreal summer. Changes in soil evaporation influence water cycling in the southern subtropics, rather than changes in transpiration. The hydrologic response to SRM is nonlinear, with global mean decreases greater than expected. These results imply that SRM may not compensate for higher greenhouse gas concentrations when one considers land-atmosphere interactions. [ABSTRACT FROM AUTHOR]

Vegetation around the Daihai Lake, northern China, is very sensitive to climate changes. In this paper, pollen-based quantitative climate reconstructions using three methods [weighted averaging partial least squares method (WAPLS), modern analog technique (MAT), and pollen response surface method (PRS)] were conducted to obtain robust reconstructions of Holocene climate changes in the Daihai Lake area. The result obtained by the three methods all consistently show the annual precipitation to have been 50–100 mm lower in the early Holocene, 100–200 mm higher in the Mid-Holocene, and 50–100 mm lower again in the late Holocene than at present. The WAPLS and the MAT methods also show quasi-synchronous oscillations of the mean annual temperature (Ta); 1°–2°C lower in the Early Holocene and 1°–3°C higher in the Mid-Holocene than today. The time period from 6200 to 5100 cal yr BP was the wettest and the warmest interval, with an annual precipitation (Pa) greater than 550 mm and mean annual temperature Ta higher than 6.5°C. Several cold and dry events can be identified to occur about 8200, 6000, and 4400 cal yr BP, with an annual precipitation less than 400 mm and a mean annual temperature colder than 4.5°C, respectively. The mean temperature of the warmest month (Tw) as reconstructed using both WAPLS and MAT methods was relatively stable during the Holocene, fluctuating about ±2°C relative to the present level, but the PRS method suggests more varied Tw values in both amplitude and frequency. After 1500 cal yr BP, no consistent pattern can be observed from these three different analyses, probably because of the impact of intensified human disturbances on the natural vegetation. The fluctuations of annual precipitation (Pa) correspond to that observed in Dongge Cave in southern China. The differences might be linked to Indian monsoon and East Asia monsoon climates or caused by the different degree of dating precision, different temporal resolution, and different sensitive response of climate proxies to the climate variations. [ABSTRACT FROM AUTHOR]

A large number of water- and climate-related applications, such as drought monitoring, are based on spaceborne-derived relationships between land surface temperature (LST) and the normalized difference vegetation index (NDVI). The majority of these applications rely on the existence of a negative slope between the two variables, as identified in site- and time-specific studies. The current paper investigates the generality of the LST–NDVI relationship over a wide range of moisture and climatic/radiation regimes encountered over the North American continent (up to 60°N) during the summer growing season (April–September). Information on LST and NDVI was obtained from long-term (21 years) datasets acquired with the Advanced Very High Resolution Radiometer (AVHRR). It was found that when water is the limiting factor for vegetation growth (the typical situation for low latitudes of the study area and during the midseason), the LST–NDVI correlation is negative. However, when energy is the limiting factor for vegetation growth (in higher latitudes and elevations, especially at the beginning of the growing season), a positive correlation exists between LST and NDVI. Multiple regression analysis revealed that during the beginning and the end of the growing season, solar radiation is the predominant factor driving the correlation between LST and NDVI, whereas other biophysical variables play a lesser role. Air temperature is the primary factor in midsummer. It is concluded that there is a need to use empirical LST–NDVI relationships with caution and to restrict their application to drought monitoring to areas and periods where negative correlations are observed, namely, to conditions when water—not energy—is the primary factor limiting vegetation growth. [ABSTRACT FROM AUTHOR]

A disproportionate increase in precipitation coming from intense rain events, in the situation of general warming (thus, an extension of the vegetation period with intensive transpiration), and an insignificant change in total precipitation could lead to an increase in the frequency of a potentially serious type of extreme events: prolonged periods without precipitation (even when the mean seasonal rainfall totals increase). This paper investigates whether this development is already occurring during the past several decades over the conterminous United States, for the same period when changes in frequency of intense precipitation events are being observed. Lengthy strings of “dry” days without sizeable (>1.0 mm) precipitation were assessed only during the warm season (defined as a period when mean daily temperature is above the 5°C threshold) when water is intensively used for transpiration and prolonged periods without sizable rainfall represent a hazard for terrestrial ecosystem’s health and agriculture. During the past four decades, the mean duration of prolonged dry episodes (1 month or longer in the eastern United States and 2 months or longer in the southwestern United States) has significantly increased. As a consequence the return period of 1-month-long dry episodes over the eastern United States has reduced more than twofold from 15 to 6–7 yr. The longer average duration of dry episodes has occurred during a relatively wet period across the country but is not observed over the northwestern United States. [ABSTRACT FROM AUTHOR]

This paper documents the sensitivity of the modeled evolution of the East Asian summer monsoon (EASM) to physical parameterization using the National Centers for Environmental Prediction (NCEP) Regional Spectral Model (RSM). To this end, perfect boundary condition experiments driven by analysis data are designed for August 2003 to investigate the individual role of the surface processes, boundary layer, and convection parameterization on the simulated monsoon. Also, 10-yr June–August (JJA) simulations from 1996 to 2005 are performed to evaluate the overall impacts of these revisions on the simulated EASM climatology. The one-month simulation for August 2003 reveals that the experiment with a realistic distribution of land use conditions and vegetation and smaller thermal roughness length simulates higher temperature and geopotential height. On the other hand, in the experiment with an improved boundary layer scheme, the rainfall amount is slightly decreased due to reduced vertical mixing. The simulation with revised subgrid-scale processes in the cumulus parameterization scheme reproduces a rainband over the subtropics, which is weakly simulated by the default package. The overall large-scale distribution from the experiment, which includes all three revised physics processes, shows the same direction as that of the revised convection run in the middle and upper troposphere, but is improved further when other newly enhanced processes are combined. These improvements are also achieved in a 10-yr summer simulation. It is distinct that the revised physics package improves the large-scale patterns by strengthening the intensity of the North Pacific high and reducing the intensity of the lower-level jet, which are critical components in the EASM. The general patterns of the interannual and intraseasonal variation of precipitation are also improved, in particular, over land. [ABSTRACT FROM AUTHOR]

In this paper the authors explore the spatial and temporal patterns of lightning strikes in northern Australia for the first time. In particular, the possible relationships between lightning strikes and elevation, vegetation type, and fire scars (burned areas) are examined. Lightning data provided by the Bureau of Meteorology were analyzed for a 6-yr period (1998–2003) over the northern, southern, and coastal regions of the Northern Territory (NT) through the use of Geographical Information Systems (GIS) to determine the spatial and temporal characteristics of lightning strikes. It was determined that the highest densities of lightning strikes occurred during the monsoon transitional period (dry to wet) and during the active monsoon periods, when atmospheric moisture is highest. For the period of this study, lightning was far more prevalent over the northern region (1.21 strikes per km2 yr-1) than over the southern (0.58 strikes per km2 yr-1) and coastal regions (0.71 strikes per km2 yr-1). Differences in vegetation cover were suggested to influence the lightning distribution over the northern region of the NT, but no relationship was found in the southern region. Lightning strikes in the southern region showed a positive relationship with elevations above 800 m, but no relationship was found in the northern region, which could be due to the low-lying topography of the area. A comparison of lightning densities between burned and unburned areas showed high variability; however, the authors suggest that, under ideal atmospheric conditions, large-scale fire scars (>500 m) could produce lightning strikes triggered by either enhanced free convection or mesoscale circulations. [ABSTRACT FROM AUTHOR]

A land surface model (LSM) has been included in the ECMWF Hamburg version 4 (ECHAM4) atmospheric general circulation model (AGCM). The LSM is an early version of the Organizing Carbon and Hydrology in Dynamic Ecosystems (ORCHIDEE) and it replaces the simple land surface scheme previously included in ECHAM4. The purpose of this paper is to document how a more exhaustive consideration of the land surface–vegetation processes affects the simulated boreal summer surface climate. To investigate the impacts on the simulated climate, different sets of Atmospheric Model Intercomparison Project (AMIP)-type simulations have been performed with ECHAM4 alone and with the AGCM coupled with ORCHIDEE. Furthermore, to assess the effects of the increase in horizontal resolution the coupling of ECHAM4 with the LSM has been implemented at different horizontal resolutions. The analysis reveals that the LSM has large effects on the simulated boreal summer surface climate of the atmospheric model. Considerable impacts are found in the surface energy balance due to changes in the surface latent heat fluxes over tropical and midlatitude areas covered with vegetation. Rainfall and atmospheric circulation are substantially affected by these changes. In particular, increased precipitation is found over evergreen and summergreen vegetated areas. Because of the socioeconomical relevance, particular attention has been devoted to the Indian summer monsoon (ISM) region. The results of this study indicate that precipitation over the Indian subcontinent is better simulated with the coupled ECHAM4–ORCHIDEE model compared to the atmospheric model alone. [ABSTRACT FROM AUTHOR]

A number of general circulation model (GCM) experiments have shown that changes in vegetation in the Sahel can cause substantial reductions in rainfall. In some studies, the climate sensitivity is large enough to trigger drought of the severity observed since the late 1960s. The extent and intensity of vegetation changes are crucial in determining the magnitude of the atmospheric response in the models. However, there is no accurate historical record of regional vegetation changes extending back to before the drought began. One important driver of vegetation change is land use practice. In this paper the hypothesis that recent changes in land use have been large enough to cause the observed drought is tested. Results from a detailed land use model are used to generate realistic maps of vegetation changes linked to land use. The land use model suggests that cropland coverage in the Sahel has risen from 5% to 14% in the 35 yr prior to 1996. It is estimated that this process of agricultural extensification, coupled with deforestation and other land use changes, translates to a conversion of 4% of the land from tree cover to bare soil over this period. The model predicts further changes in the composition of the land surface by 2015 based on changes in human population (rural and urban), livestock population, rainfall, cereals imports, and farming systems. The impact of land use change on Sahelian climate is assessed using a GCM, forced by the estimates of land use in 1961, 1996, and 2015. Relative to 1961 conditions, simulated rainfall decreases by 4.6% (1996) and 8.7% (2015). The decreases are closely linked to a later onset of the wet season core during July. Once the wet season is well developed, however, the sensitivity of total rainfall to the land surface is greatly reduced, and depends on the sensitivity of synoptic disturbances to the land surface. The results suggest that while the climate of the region is rather sensitive to small changes in albedo and... [ABSTRACT FROM AUTHOR]

The focus of this paper is the role of meridional distribution of vegetation in the dynamics of monsoons and rainfall over West Africa. A moist zonally symmetric atmospheric model coupled with a simple land surface scheme is developed to investigate these processes. Four primary experiments have been carried out to examine the sensitivity of West African monsoons to perturbations in the meridional distribution of vegetation. In the control experiment, the authors assume a distribution of vegetation that resembles the natural vegetation cover in West Africa. Each perturbation experiment is identical to the control experiment except that a change in vegetation cover is imposed for a latitudinal belt that is 10&deg in width. The results of the numerical experiments demonstrate that West African monsoons and therefore rainfall distribution depend critically on the location of the vegetation perturbations. Changes in vegetation cover along the border between the Sahara desert and West Africa (desertification) may have a minor impact on the simulated monsoon circulation. However, coastal deforestation may cause the collapse of the monsoon circulation and have a dramatic impact on the regional rainfall. The observed deforestation in West Africa is then likely to be a significant contributor to the observed drought. [ABSTRACT FROM AUTHOR]

Vertically integrated atmospheric water vapor (VIWV) over the Indo-Pacific warm pool (IPWP) indirectly affects terrestrial vegetation growth (TVG) patterns through atmospheric water vapor transmission. However, their linkages and mechanisms are poorly understood. This study intends to understand the contributions of VIWVIPWP to TVG and the mechanisms by which VIWVIPWP impacts TVG. Combining monthly SST, VIWV, and NDVI data from 1982 to 2015, the linkage between VIWVIPWP and NDVI is investigated during April–June (AMJ). A strong correlation between VIWVIPWP and NDVI suggests that VIWVIPWP is an important factor affecting TVG. A composite analysis of VIWVIPWP anomalies and their relation to NDVI patterns shows that VIWVIPWP positively influences the NDVI of 68.1% of global green land during high-VIWVIPWP years but negatively influences 74.7% in low years. Corresponding to these results, during high-VIWVIPWP years, the warm and humid terrestrial climate conditions improved TVG by 9% and 2% in the Northern and Southern Hemispheres, respectively, but cold and dry conditions inhibited TVG for both hemispheres during the low years. Additionally, strong spatial correlations between VIWVIPWP and precipitation imply that VIWVIPWP affects the spatial–temporal pattern of precipitation. There is a stronger interaction between the Pacific north–south ridge and the two land troughs during high-VIWVIPWP years than during low-VIWVIPWP years. The zonally averaged wind at 850 hPa and VIWV results indicate that, during high-VIWVIPWP years, the enhanced wind from the ocean brings more atmospheric water vapor to land, increasing the probability of precipitation and resulting in moist climate conditions that promote AMJ vegetation growth. In brief, VIWVIPWP indirectly induces vegetation growth by affecting the distributions of terrestrial VIWV and precipitation. [ABSTRACT FROM AUTHOR]

The Q10 value represents the soil respiration sensitivity to temperature often used for the parameterization of the soil decomposition process has been assumed to be a constant in conventional numerical models, whereas it exhibits significant spatial and temporal variation in the observations. This study develops a new parameterization method for determining Q10 by considering the soil respiration dependence on soil temperature and moisture obtained by multiple regression for each vegetation type. This study further investigates the impacts of the new parameterization on the global terrestrial carbon flux. Our results show that a nonuniform spatial distribution of Q10 tends to better represent the dependence of the soil respiration process on heterogeneous surface vegetation type compared with the control simulation using a uniform Q10. Moreover, it tends to improve the simulation of the relationship between soil respiration and soil temperature and moisture, particularly over cold and dry regions. The modification has an impact on the soil respiration and carbon decomposition process, which changes gross primary production (GPP) through controlling nutrient assimilation from soil to vegetation. It leads to a realistic spatial distribution of GPP, particularly over high latitudes where the original model has a significant underestimation bias. Improvement in the spatial distribution of GPP leads to a substantial reduction of global mean GPP bias compared with the in situ observation-based reference data. The results highlight that the enhanced sensitivity of soil respiration to the subsurface soil temperature and moisture introduced by the nonuniform spatial distribution of Q10 has contributed to improving the simulation of the terrestrial carbon fluxes and the global carbon cycle. [ABSTRACT FROM AUTHOR]

Changes in the seasonality of precipitation over Africa have high potential for detrimental socioeconomic impacts due to high societal dependence upon seasonal rainfall. Here, for the first time we conduct a continental-scale analysis of changes in wet season characteristics under the RCP4.5 and RCP8.5 climate projection scenarios across an ensemble of CMIP5 models using an objective methodology to determine the onset and cessation of the wet season. A delay in the wet season over West Africa and the Sahel of over 5–10 days on average, and later onset of the wet season over southern Africa, is identified and associated with increasing strength of the Saharan heat low in late boreal summer and a northward shift in the position of the tropical rain belt over August–December. Over the Horn of Africa rainfall during the "short rains" season is projected to increase by over 100 mm on average by the end of the twenty-first century under the RCP8.5 scenario. Average rainfall per rainy day is projected to increase, while the number of rainy days in the wet season declines in regions of stable or declining rainfall (western and southern Africa) and remains constant in central Africa, where rainfall is projected to increase. Adaptation strategies should account for shorter wet seasons, increasing rainfall intensity, and decreasing rainfall frequency, which will have implications for crop yields and surface water supplies. [ABSTRACT FROM AUTHOR]

Regions of shorter-than-Gaussian warm-side temperature anomaly distribution tails are shown to occur in spatially coherent patterns in global reanalysis. Under such conditions, future warming may be manifested in more complex ways than if the underlying distribution were close to Gaussian. For example, under a uniform warm shift, the simplest prototype for future warming, a location with a short tail would experience a greater increase in extreme warm exceedances relative to a fixed threshold compared to if the distribution were Gaussian. The associated societal and environmental impacts make realistic representation of these short tails an important target for climate models. Global evaluation of the ability for a suite of global climate models (GCMs) contributing to phase 5 of the Coupled Model Intercomparison Project (CMIP5) suggests that most models approximately capture the principal observed coherent regions of short tails. This suggests the underlying dynamics and physics occur on scales resolved by the models, and helps build confidence in model simulations of extremes. Furthermore, most GCMs show more rapid future increases in exceedances of the historical 95th percentile in regions exhibiting short tails in the historical climate. These regions, where the ratio of exceedances projected by the GCM compared to that expected from a Gaussian sometimes exceeds 1.5, are termed hot spots. Prominent hot spots include western North America, Central America, a broad swath of northwestern Eurasia, and the Indochina Peninsula during boreal winter. During boreal summer, central and western Australia, parts of southern Africa, and portions of central South America are major hot spots. [ABSTRACT FROM AUTHOR]

Using the Regional Climate Model (RegCM) coupled with the Community Land Model (CLM) including modules of carbon–nitrogen cycling (CN) and vegetation dynamics (DV), this study evaluates the performance of the model with different capacity of representing vegetation processes in simulating the present-day climate over China based on three 21-yr simulations driven with boundary conditions from the ERA-Interim reanalysis data during 1989–2009. For each plant functional type (PFT), the plant pheonology, density, and fractional coverage in RegCM-CLM are all prescribed as static from year to year; RegCM-CLM-CN prescribes static fractional coverage but predicts plant phenology and density, and RegCM-CLM-CN-DV predicts plant phenology, density, and fractional coverage. Compared against the observational data, all three simulations reproduce the present-day climate well, including the wind fields, temperature and precipitation seasonal cycles, extremes, and interannual variabilities. Relative to RegCM-CLM, both RegCM-CLM-CN and RegCM-CLM-CN-DV perform better in simulating the interannual variability of temperature and spatial distribution of mean precipitation, but produce larger biases in the mean temperature field. RegCM-CLM-CN overestimates leaf area index (LAI), which enhances the cold biases and alleviates the dry biases found in RegCM-CLM. RegCM-CLM-CN-DV underestimates vegetation cover and/or stature, and hence overestimates surface albedo, which enhances the wintertime cold and dry biases found in RegM-CLM. During summer, RegCM-CLM-CN-DV overestimates LAI in south and east China, which enhances the cold biases through increased evaporative cooling; in the west where evaporation is low, the albedo effect of the underestimated vegetation cover is still dominant, leading to enhanced cold biases relative to RegCM-CLM. [ABSTRACT FROM AUTHOR]

Generalized Equilibrium Feedback Assessment (GEFA) is a potentially valuable multivariate statistical tool for extracting vegetation feedbacks to the atmosphere in either observations or coupled models. GEFA's reliability at capturing the terrestrial impacts on regional climate is demonstrated using the Community Earth System Model (CESM). The feedback is assessed statistically by applying GEFA to output from a fully coupled control run. In order to reduce the sampling error caused by short data records, the traditional full GEFA is refined through stepwise GEFA by dropping unimportant forcings. Two ensembles of dynamical experiments, against which GEFA-based vegetation feedbacks are evaluated, are developed for the Sahel or West African monsoon region. In these experiments, regional leaf area index (LAI) is modified either alone or in conjunction with soil moisture. Stepwise GEFA boasts higher consistency between statistically- and dynamically-assessed atmospheric responses to land surface anomalies than full GEFA, especially with short data records. Both the statistical and dynamical assessments reveal a negative vegetation-rainfall feedback in the Sahel, associated with an atmospheric stability mechanism, versus a weaker, positive feedback in the West African monsoon region, associated with a moisture recycling mechanism, in CESM. [ABSTRACT FROM AUTHOR]

The natural composition of terrestrial ecosystems can be shaped by climate to take advantage of local environmental conditions. Ecosystem functioning (e.g., interaction between photosynthesis and temperature) can also acclimate to different climatological states. The combination of these two factors thus determines ecological-climate interactions. A global empirical map of the sensitivity of vegetation to climate is derived using the response of satellite-observed greenness to interannual variations in temperature and precipitation. Mechanisms constraining ecosystem functioning are inferred by analyzing how the sensitivity of vegetation to climate varies across climate space. Analysis yields empirical evidence for multiple physical and biological mediators of the sensitivity of vegetation to climate at large spatial scales. In hot and wet locations, vegetation is greener in warmer years despite temperatures likely exceeding thermally optimum conditions. However, sunlight generally increases during warmer years, suggesting that the increased stress from higher atmospheric water demand is offset by higher rates of photosynthesis. The sensitivity of vegetation transitions in sign (greener when warmer or drier to greener when cooler or wetter) along an emergent line in climate space with a slope of about 59 mm yr−1 °C−1, twice as steep as contours of aridity. The mismatch between these slopes is evidence at a global scale of the limitation of both water supply due to inefficiencies in plant access to rainfall and plant physiological responses to atmospheric water demand. This empirical pattern can provide a functional constraint for process-based models, helping to improve predictions of the global-scale response of vegetation to a changing climate. [ABSTRACT FROM AUTHOR]

Continued anthropogenic CO2 emissions are expected to drive widespread changes in precipitation characteristics. Nonetheless, projections of precipitation change vary considerably at the regional scale between climate models. Here, it is shown that the response of plant physiology to elevated CO2, or CO2 physiological forcing drives widespread hydrologic changes distinct from those associated with CO2 radiative forcing and has a role in shaping regional-scale differences in projected daily-scale precipitation changes. In a suite of simulations with the Community Climate System Model, version 4 (CCSM4), reduced stomatal conductance from projected physiological forcing drives large decreases in transpiration and changes the distribution of daily-scale precipitation within and adjacent to regions of dense vegetation and climatologically high transpiration. When atmospheric conditions are marginally favorable for precipitation, reduced transpiration dries the boundary layer and increases the likelihood of dry day occurrence. In CCSM4, the annual number of dry days increases by upward of 15 days yr-1 over tropical land and the continental midlatitudes. Decreases in transpiration from physiological forcing also increase the number of heavy precipitation events by up to 8 days yr-1 in many tropical forest regions. Despite reductions in the land surface contribution to atmospheric moisture, diminished surface latent heat fluxes warm the forest boundary layer and increase moisture convergence from nearby oceans, enhancing instability. The results suggest that consideration of the radiative impacts of CO2 alone cannot account for projected regional-scale differences in daily precipitation changes, and that CO2 physiological forcing may contribute to differences in projected precipitation characteristics among climate models. [ABSTRACT FROM AUTHOR]

This study explores the hypothesis that subtropical and tropical monsoon regions exhibit unique responses to vegetation feedbacks. Using the Community Climate System Model (CCSM), M. Notaro et al. concluded that reduced vegetation cover led to an earlier subtropical Chinese monsoon and a delayed, weaker tropical Australian monsoon, yet significant climate and leaf area index (LAI) biases obfuscated the hypothesis's reliability. To address these concerns, the Regional Climate Model, version 4 (RegCM4), likewise coupled to the Community Land Model but with 'observed' LAI boundary conditions, is applied across China and Australia. The model matches the observed dominance of crops, grass, and evergreen trees in southern China and grass and shrubs in northern Australia. The optimal model configuration is determined and applied in control runs for 1960-2013. Monsoon region LAI is modified in a RegCM4 ensemble, aimed at contrasting vegetation feedbacks between tropical and subtropical regions. Greater LAI supports reductions in albedo, temperature, wind speed, boundary layer height, ascending motion, and midlevel clouds and increases in diurnal temperature range (DTR), wind stress, evapotranspiration (ET), specific humidity, and low clouds. In response to greater LAI, rainfall is enhanced during Australia's pre-to-midmonsoon season but not for China. Modified LAI leads to dramatic changes in the temporal distribution and intensity of Australian rain events. Heterogeneous responses to biophysical feedbacks include amplified impacts (e.g., increased ET and DTR) across China's croplands and Australia's shrublands. Inconsistencies between China's monsoonal responses in the present RegCM4 study and prior CCSM study of M. Notaro et al. are attributed to CCSM's excessive forest cover and LAI, exaggerated roughness mechanism, and deficient ET response. [ABSTRACT FROM AUTHOR]

Model intercomparisons and evaluations against observations are essential for better understanding of models' performance and for identifying the sources of uncertainty in their output. The terrestrial vegetation carbon simulated by 11 Earth system models (ESMs) involved in phase 5 of the Coupled Model Intercomparison Project (CMIP5) was evaluated in this study. The simulated vegetation carbon was compared at three distinct spatial scales (grid, biome, and global) among models and against the observations (an updated database from Olson et al.'s 'Major World Ecosystem Complexes Ranked by Carbon in Live Vegetation: A Database'). Moreover, the underlying causes of the differences in the models' predictions were explored. Model-data fit at the grid scale was poor but greatly improved at the biome scale. Large intermodel variability was pronounced in the tropical and boreal regions, where total vegetation carbon stocks were high. While 8 out of 11 ESMs reproduced the global vegetation carbon to within 20% uncertainty of the observational estimate (560 ± 112 Pg C), the simulated global totals varied nearly threefold between the models. The goodness of fit of ESMs in simulating vegetation carbon depended strongly on the spatial scales. Sixty-three percent of the variability in contemporary global vegetation carbon stocks across ESMs could be explained by differences in vegetation carbon residence time across ESMs ( P < 0.01). The analysis indicated that ESMs' performance of vegetation carbon predictions can be substantially improved through better representation of plant longevity (i.e., carbon residence time) and its respective spatial distributions. [ABSTRACT FROM AUTHOR]

Vegetation greenness distributions [based on remote sensing normalized difference vegetation index (NDVI)] and their change are analyzed as functional vegetation-climate relations in a two-dimensional ecohydrological state space spanned by surface flux ratios of energy excess (U; loss by sensible heat H over supply by net radiation N) versus water excess (W; loss by discharge Ro over gain by precipitation P). An ecohydrological ansatz attributes state change trajectories in (U, W) space to external (or climate) and internal (or anthropogenic) causes jointly with vegetation greenness interpreted as an active tracer. Selecting the Tibetan Plateau with its complex topographic, climate, and vegetation conditions as target area, ERA-Interim weather data link geographic and (U, W) state space, into which local remote sensing Global Inventory Modeling and Mapping Studies (GIMMS) data (NDVI) are embedded; a first and second period (1982-93 and 1994-2006) are chosen for change attribution analysis. The study revealed the following results: 1) State space statistics are characterized by a bimodal distribution with two distinct geobotanic regimes (semidesert and steppe) of low and moderate vegetation greenness separated by gaps at aridity D ~ 2 (net radiation over precipitation) and greenness NDVI ~ 0.3. 2) Changes between the first and second period are attributed to external (about 70%) and internal (30%) processes. 3) Attribution conditioned joint distributions of NDVI (and its change) show 38.2% decreasing (61.8% increasing) area cover with low (moderate) greenness while high greenness areas are slightly reduced. 4) Water surplus regions benefit most from climate change (showing vegetation greenness growth) while the energy surplus change is ambiguous, because ecohydrological diagnostics attributes high mountainous regions (such as the Himalayas) as internal without considering the heat storage deficit due to increasing vegetation. [ABSTRACT FROM AUTHOR]

This study examines the impacts of global warming on the timing of plant habitat changes in the twenty-first century using climate scenarios from multiple global climate models (GCMs). The plant habitat changes are predicted by driving the bioclimate rule in a dynamic global vegetation model using the climate projections from 16 coupled GCMs. The timing of plant habitat changes is estimated by the first occurrence of specified fractional changes (10%, 20%, and 30%). All future projections are categorized into three groups by the magnitude of the projected global-mean land surface temperature changes: low (<2.5 K), medium (2.5-3.5 K), and high (>3.5 K) warming. During the course of the twenty-first century, dominant plant habitat changes are projected in ecologically transitional (i.e., from tropical to temperate and temperate to boreal) regions. The timing of plant habitat changes varies substantially according to regions. In the low-warming group, habitat changes of 10% in southern Africa occur in 2028, earlier than in the Americas by more than 70 yr. Differences in the timing between regions increase with the increase in warming and fractional threshold. In the subtropics, fast plant habitat changes are projected for the Asia and Africa regions, where countries of relatively small gross domestic product (GDP) per capita are concentrated. Ecosystems in these regions will be more vulnerable to global warming, because countries of low economic power lack the capability to deal with the warming-induced habitat changes. Thus, it is important to establish international collaboration via which developed countries provide assistance to mitigate the impacts of global warming. [ABSTRACT FROM AUTHOR]

This work discusses the land surface-atmosphere interactions during the severe drought of 2008 in southern South America, which was among the most severe in the last 50 years in terms of both intensity and extent. Once precipitation returned to normal values, it took about two months for the soil moisture content and vegetation to recover. The land surface effects were examined by contrasting long-term simulations using a consistent set of satellite-derived annually varying land surface biophysical properties against simulations using the conventional land-cover types in the Weather Research and Forecasting Model-Noah land surface model (WRF-Noah). The new land-cover dataset is based on ecosystem functional properties that capture changes in vegetation status due to climate anomalies and land-use changes. The results show that the use of realistic information of vegetation states enhances the model performance, reducing the precipitation biases over the drought region and over areas of excessive precipitation. The precipitation bias reductions are attributed to the corresponding changes in greenness fraction, leaf area index, stomatal resistance, and surface roughness. The temperature simulation shows a generalized increase, which is attributable to a lower vegetation greenness and a doubling of the stomatal resistance that reduces the evapotranspiration rate. The increase of temperature has a beneficial effect toward the eastern part of the domain with a notable reduction of the bias, but not over the central region where the bias is increased. The overall results suggest that an improved representation of the surface processes may contribute to improving the predictive skill of the model system. [ABSTRACT FROM AUTHOR]

Analyses of 30-yr four reanalysis datasets [NCEP-NCAR reanalysis (NCEP1), NCEP-Department of Energy reanalysis (NCEP2), Japanese 25-year Reanalysis Project (JRA-25), and Interim ECMWF Re-Analysis (ERA-Interim)] reveal remarkably interannual variability of the Hadley circulation (HC) in boreal summer (June-August). The two leading modes of interannual variability of boreal summer HC are obtained by performing empirical orthogonal function (EOF) analysis on the mass streamfunction. A general intensification of boreal summer HC is seen in EOF-1 mode among NCEP1, NCEP2, and JRA-25 but the corresponding EOF-2 mode in ERA-Interim, while a weakened northern Hadley cell and remarkable regional variation of a southern Hadley cell are captured by the EOF-2 mode (from NCEP1, NCEP2, and JRA-25) and EOF-1 mode (from ERA-Interim), as evidenced by the enhanced (decreased) southern Hadley cell in the southern tropics (the northern tropics and southern subtropics). Both modes are driven by El Niño-like SST forcing in boreal summer, but are relevant to different phases of El Niño events. The EOF-1 (or EOF-2 derived from ERA-Interim) [EOF-2 (or EOF-1 derived from ERA-Interim)] mode is driven by SST anomalies in developing (decaying) El Niño summers. The interannual variations of the northern Hadley cell in both modes are driven by El Niño through modulating the interannual variations of the East Asian summer monsoon, while anomalous local Hadley circulation (LHC) in the regions 30°S-20°N, 110°E-180° and 30°S-20°N, 160°E-120°W in response to El Niño forcing largely determine the interannual variations of southern Hadley cell in both modes, respectively. The different behaviors of the southern Hadley cell between two leading modes can be well explained by the southward shift of the tropical heating center from north of 10°N in developing El Niño summers to south of 10°N in decaying El Niño summers. [ABSTRACT FROM AUTHOR]

A more complete picture of the timing and patterns of the ENSO signal during the seasonal cycle for the whole of Africa over the three last decades is provided using the normalized difference vegetation index (NDVI). Indeed, NDVI has a higher spatial resolution and is more frequently updated than in situ climate databases, and highlights the impact of ENSO on vegetation dynamics as a combined result of ENSO on rainfall, solar radiation, and temperature. The month-by-month NDVI-Niño-3.4 correlation patterns evolve as follows. From July to September, negative correlations are observed over the Sahel, the Gulf of Guinea coast, and regions from the northern Democratic Republic of Congo to Ethiopia. However, they are not uniform in space and are moderate (~0.3). Conversely, positive correlations are recorded over the winter rainfall region of South Africa. In October-November, negative correlations over Ethiopia, Sudan, and Uganda strengthen while positive correlations emerge in the Horn of Africa and in the southeast coast of South Africa. By December with the settlement of the ITCZ south of the equator, positive correlations over the Horn of Africa spread southward and westward while negative correlations appear over Mozambique, Zimbabwe, and South Africa. This pattern strengthens and a dipole at 18°S is well established in February-March with reduced (enhanced) greenness during ENSO years south (north) of 18°S. At the same time, at ~2°N negative correlations spread northward. Last, from April to June negative correlations south of 18°S spread to the north (to 10°S) and to the east (to the south of Tanzania). [ABSTRACT FROM AUTHOR]

The demand for agricultural land in the Congo basin is expected to yield substantial deforestation over the coming decades. Although several studies exist on the climatological impact of deforestation in the Congo basin, deforestation scenarios that are implemented in climate models are generally crude. This study aims to refine current impact assessments by removing the primary forest according to an existing spatially explicit scenario, and replacing it by successional vegetation typically observed for the Congo basin. This is done within the Consortium for Small-Scale Modeling (COSMO) model in climate mode (COSMO-CLM), a regional climate model at 25-km grid spacing coupled to a state-of-the-art soil-vegetation-atmosphere transfer scheme (Community Land Model). An evaluation of the model shows good performance compared to in situ and satellite observations. Model integrations indicate that the deforestation, expected for the middle of the twenty-first century, induces a warming of about 0.7°C. This is about half the greenhouse gas-induced surface warming in this region, given an intermediate emission scenario (A1B) with COSMO-CLM driven by the ECHAM5 global climate model. This shows the necessity of taking into account deforestation to obtain realistic future climate projections. The deforestation-induced warming can be attributed to reduced evaporation, but this effect is mitigated by increased albedo and increased sensible heat loss to the atmosphere. Precipitation is also affected: as a consequence of surface warming resulting from deforestation, a regional heat low develops over the rain forest region. Resulting low-level convergence causes a redistribution of moisture in the boundary layer and a stabilization of the atmospheric column, thereby reducing convection intensity and hence precipitation by 5%-10% in the region of the heat low. [ABSTRACT FROM AUTHOR]

The biophysical-climate and combined biophysical and carbon-climate feedbacks of tropical deforestation rates are explored through sensitivity analyses using the Community Climate System Model 4 with prognostic carbon-nitrogen and dynamic vegetation. Simulations test 5%, 2%, 1%, and 0.5% annual deforestation rates, each paired with preservation targets of 10% per tropical tree type. Perturbations are applied over pan-tropical land but analyses also investigate responses over the subcontinental areas of the Amazon basin, central Africa, and Southeast Asia. Sensitivities [expressed as the change in a variable per million square kilometers (Mkm2) of change in tree cover] and means of selected biophysical, carbon, and climate variables during and after deforestation are compared across rates. The most apparent effect of the rates is in hastening/postponing climate change, but otherwise results show no consistent differences across rates and vary more across subcontinents (with the Amazon basin reflecting highest sensitivities in albedo and ground temperatures, and Southeast Asia for total ecosystem carbon). Additionally, biophysical feedbacks alone were found to have significant impact on climate over subcontinental scales. In the Amazon, ground temperature increase due to biophysical feedbacks is as much as 55%, and precipitation decrease up to 61%, of combined biophysical and carbon impacts. Replication with other models is required. Although it is still unclear whether a slow but prolonged deforestation differs in impacts from one that is rapid but short, the rate can still be relevant to planning with regards to the timing of impacts. [ABSTRACT FROM AUTHOR]

The fraction of absorbed photosynthetically active radiation (fAPAR) is an essential diagnostic variable to investigate the temporal and spatial dynamics of the terrestrial biosphere. The present study provides a new method to assess global vegetation greening phase dynamics, derived from fAPAR time series from four different remote sensing products. A robust algorithm is developed to detect intra-annual greening phase patterns and derive seasonality patterns of vegetation dynamics at the global scale. The comparison of four independent remote sensing datasets shows significantly consistent global spatiotemporal patterns at the 95% confidence level. Regions where the remote sensing datasets show consistent results, as well as regions where at least one of the used remote sensing datasets deviates, can be identified. The derived global greening phase dataset and analysis method provides a solid framework for the evaluation of global vegetation models. [ABSTRACT FROM AUTHOR]

The Community Land Model, version 4 (CLM4) includes the option to run the prognostic carbon-nitrogen (CN) model with dynamic vegetation (CNDV). CNDV, which simulates unmanaged vegetation, modifies the CN framework to implement plant biogeography updates. CNDV simulates a reasonable present-day distribution of plant functional types but underestimates tundra vegetation cover. The CNDV simulation is compared against a CN simulation using a vegetation distribution generated by CNDV and against a carbon-only simulation with prescribed nitrogen limitation (CDV). The comparisons focus on the means and variability of carbon pools and fluxes and biophysical factors, such as albedo, surface radiation, and heat fluxes. The study assesses the relative importance of incorporating interactive nitrogen (CDV to CNDV) versus interactive biogeography (CN to CNDV) in present-day equilibrium simulations. None of the three configurations performs consistently better in simulating carbon or biophysical variables compared to observational estimates. The interactive nitrogen ( N) cycle reduces annual means and interannual variability more than dynamic vegetation. Dynamic vegetation reduces seasonal variability in leaf area and, therefore, in moisture fluxes and surface albedo. The interactive N cycle has the opposite effect of enhancing seasonal variability in moisture fluxes and albedo. CNDV contains greater degrees of freedom than CN or CDV by adjusting both through nitrogen-carbon interactions and through vegetation establishment and mortality. Thus, in these equilibrium simulations, CNDV acts as a stronger 'regulator' of variability compared to the other configurations. Discussed are plausible explanations for this behavior, which has been shown in past studies to improve climate simulations through better represented climate-vegetation interactions. [ABSTRACT FROM AUTHOR]

Land use, vegetation, albedo, and soil-type data are combined in a global model that accounts for roofs and roads at near their actual resolution to quantify the effects of urban surface and white roofs on climate. In 2005, ~0.128%% of the earthrsquo;s surface contained urban land cover, half of which was vegetated. Urban land cover was modeled over 20 years to increase gross global warming (warming before cooling due to aerosols and albedo change are accounted for) by 0.06-0.11 K and population-weighted warming by 0.16-0.31 K, based on two simulations under different conditions. As such, the urban heat island (UHI) effect may contribute to 2%%-4%% of gross global warming, although the uncertainty range is likely larger than the model range presented, and more verification is needed. This may be the first estimate of the UHI effect derived from a global model while considering both UHI local heating and large-scale feedbacks. Previous data estimates of the global UHI, which considered the effect of urban areas but did not treat feedbacks or isolate temperature change due to urban surfaces from other causes of urban temperature change, imply a smaller UHI effect but of similar order. White roofs change surface albedo and affect energy demand. A worldwide conversion to white roofs, accounting for their albedo effect only, was calculated to cool population-weighted temperatures by ~0.02 K but to warm the earth overall by ~0.07 K. White roof local cooling may also affect energy use, thus emissions, a factor not accounted for here. As such, conclusions here regarding white roofs apply only to the assumptions made. [ABSTRACT FROM AUTHOR]

This article investigates the African easterly jet (AEJ), its structure, and the forcings contributing to its maintenance, critically revisiting previous work that attributed the maintenance of the jet to soil moisture gradients over tropical Africa. A state-of-the-art global model in a high-end computer framework is used to produce a three-member 73-yr ensemble run forced by observed SST to represent the control run. The AEJ as produced by the control is compared with the representation of the AEJ in the 40-yr ECMWF Re-Analysis (ERA-40) and other observational datasets and found to be very realistic. Five experiments are then performed, each represented by sets of three-member 22-yr-long (1980–2001) ensemble runs. The goal of the experiments is to investigate the role of meridional soil moisture gradients, different land surface properties, and orography. Unlike previous studies, which have suppressed soil moisture gradients within a highly idealized framework (i.e., the so-called bucket model), terrestrial evaporation control is here achieved with a highly sophisticated land surface treatment and with an extensively tested and complex methodology. The results show that the AEJ is suppressed by a combination of absence of meridional evaporation gradients over Africa and constant vegetation, even if the individual forcings taken separately do not lead to the AEJ disappearance, but only its modification. Moreover, the suppression of orography also leads to a different circulation in which there is no AEJ. This work suggests that it is not just soil moisture gradients but a unique combination of geographical features present only in northern tropical Africa that causes and maintains the jet. [ABSTRACT FROM AUTHOR]

Land surface phenology (LSP) is the spatiotemporal development of the vegetated land surface as revealed by synoptic sensors. Modeling LSP across northern Eurasia reveals the magnitude, significance, and spatial pattern of the influence of the northern annular mode. Here the authors fit simple LSP models to two normalized difference vegetation index (NDVI) datasets and calculate the Spearman rank correlations to link the start of the observed growing season (SOS) and the timing of the peak NDVI with the North Atlantic Oscillation (NAO) and Arctic Oscillation (AO) indices. The relationships between the northern annular mode and weather station data, accumulated precipitation derived from the Climate Prediction Center (CPC) Merged Analysis of Precipitation (CMAP) dataset, accumulated growing degree-days (AGDDs) derived from the NCEP–Department of Energy Atmospheric Model Intercomparison Project (AMIP-II) reanalysis, and the number of snow days from the National Snow and Ice Data Center are investigated. The analyses confirm strong relationships between the temporal behavior of temperature and precipitation and large-scale climatic variability across Eurasia. The authors find widespread influence of the northern annular mode (NAM) on the land surface phenologies across northern Eurasia affecting 200–300 Mha. The tundra ecoregions were especially impacted with significant results for about a quarter of the biome. The influence of the AO was also extensive (>130 Mha) for the boreal forests. The AO appears to affect the Asian part of northern Eurasia more strongly than the NAO, especially for the NDVI peak position as a function of AGDD. Significant responses of vegetation timing to NAO and AO in northeastern Russia have not been as well documented as the seasonal advancement in Europe. The two Advanced Very High Resolution Radiometer NDVI datasets yield fields of LSP model parameter estimates that are more similar in dates of peak position than in dates for SOS and more similar for AO than for NAO. As a result, the authors conclude that peak position appears to be a more robust characteristic of land surface phenology than SOS to link vegetation dynamics to variability and change in regional and global climates. [ABSTRACT FROM AUTHOR]

The impact of carbon–nitrogen dynamics in terrestrial ecosystems on the interaction between the carbon cycle and climate is studied using an earth system model of intermediate complexity, the MIT Integrated Global Systems Model (IGSM). Numerical simulations were carried out with two versions of the IGSM’s Terrestrial Ecosystems Model, one with and one without carbon–nitrogen dynamics. Simulations show that consideration of carbon–nitrogen interactions not only limits the effect of CO2 fertilization but also changes the sign of the feedback between the climate and terrestrial carbon cycle. In the absence of carbon–nitrogen interactions, surface warming significantly reduces carbon sequestration in both vegetation and soil by increasing respiration and decomposition (a positive feedback). If plant carbon uptake, however, is assumed to be nitrogen limited, an increase in decomposition leads to an increase in nitrogen availability stimulating plant growth. The resulting increase in carbon uptake by vegetation exceeds carbon loss from the soil, leading to enhanced carbon sequestration (a negative feedback). Under very strong surface warming, however, terrestrial ecosystems become a carbon source whether or not carbon–nitrogen interactions are considered. Overall, for small or moderate increases in surface temperatures, consideration of carbon–nitrogen interactions result in a larger increase in atmospheric CO2 concentration in the simulations with prescribed carbon emissions. This suggests that models that ignore terrestrial carbon–nitrogen dynamics will underestimate reductions in carbon emissions required to achieve atmospheric CO2 stabilization at a given level. At the same time, compensation between climate-related changes in the terrestrial and oceanic carbon uptakes significantly reduces uncertainty in projected CO2 concentration. [ABSTRACT FROM AUTHOR]

A regional atmospheric model with 60-km resolution is asynchronously coupled with a potential vegetation model to study the implications of twenty-first-century climate change for the tropical and subtropical climate and vegetation of South America. The coupled model produces an accurate simulation of the present day climate and vegetation. Future climate is simulated by increasing atmospheric CO2 levels to 757 ppmv and imposing lateral and surface boundary conditions derived from a GCM simulation for 2081–2100 from the Canadian Climate Center GCM. The coupled regional model simulation projects a 70% reduction in the extent of the Amazon rain forest by the end of the twenty-first century and a large eastward expansion of the caatinga vegetation that is prominent in the Nordeste region of Brazil today. These changes in vegetation are related to reductions in annual mean rainfall and a modification of the seasonal cycle that are associated with a weakening of tropical circulation systems. [ABSTRACT FROM AUTHOR]

The Euphrates Plain (EP) experiences large interannual variability in vegetation cover, especially in areas of marginal rain-fed agriculture. Vegetation in this region is primarily limited by available soil moisture, as determined by winter precipitation, spring precipitation, and air temperature. Satellite analyses indicate that the springtime normalized difference vegetation index (NDVI) is negatively correlated with surface albedo, and that interannual variability in albedo in the EP produces an estimated forcing on the radiation balance that peaks at 16.0 W m-2 in May. Simulations with a regional climate model indicate that surface energy fluxes during a drought year (1999) differed substantially from those during a year with normal precipitation (2003). These differences were geographically specific, with the EP exhibiting increased albedo and decreased sensible heat flux while the neighboring Zagros Plateau region showed no albedo effect, a large increase in sensible heat flux, and an offsetting reduction in latent heat flux. In both the EP and the Zagros there was a potential for positive feedbacks on temperature and drought in late spring, though the most likely feedback mechanisms differed between the two regions: in the EP surface brightening leads to cooling and reduced turbulent heat flux, while in the Zagros region reduced latent heat flux leads to warming and a deepening of the planetary boundary layer. [ABSTRACT FROM AUTHOR]

The vegetation in the core region of the North American monsoon (NAM) system changes dramatically after the onset of the summer rains so that large changes may be expected in the surface fluxes of radiation, heat, and moisture. Most of this region lies in the rugged terrain of western Mexico and very few measurements of these fluxes have been made in the past. Surface energy balance measurements were made at seven sites in Sonora, Mexico, and Arizona during the intensive observation period (IOP) of the North American Monsoon Experiment (NAME) in summer 2004 to better understand how land surface vegetation change alters energy flux partitioning. Satellite data were used to obtain time series for vegetation indices and land surface temperature for these sites. The results were analyzed to contrast conditions before the onset of the monsoon with those afterward. As expected, precipitation during the 2004 monsoon was highly variable from site to site, but it fell in greater quantities at the more southern sites. Likewise, large changes in the vegetation index were observed, especially for the subtropical sites in Sonora. However, the changes in the broadband albedo were very small, which was rather surprising. The surface net radiation was consistent with the previous observations, being largest for surfaces that are transpiring and cool, and smallest for surfaces that are dry and hot. The largest evaporation rates were observed for the subtropical forest and riparian vegetation sites. The evaporative fraction for the forest site was highly correlated with its vegetation index, except during the dry spell in August. This period was clearly detected in the land surface temperature data, which rose steadily in this period to a maximum at its end. [ABSTRACT FROM AUTHOR]

The interannual and intraseasonal variability of West African vegetation over the period 1982–2002 is studied using the normalized difference vegetation index (NDVI) from the Advanced Very High Resolution Radiometer (AVHRR). The novel independent component analysis (ICA) technique is applied to extract the main modes of the interannual variability of the vegetation, among which two modes are worth describing. The first component (IC1) describes NDVI variability over the Sahel from August to October. A strong photosynthetic activity over the Sahel is related to above-normal convection and rainfall within the intertropical convergence zone (ITCZ) in summertime and is partly associated with colder (warmer) SST in the eastern tropical Pacific (the Mediterranean). The second component (IC2) depicts a dipole pattern between the Sahelian and Guinean regions during the northern summer followed by a southward-propagating signal from October to December. It is associated with a north–south dipole in convection and rainfall induced by variations in the latitudinal location of the ITCZ as a response to the occurrence of the tropical Atlantic dipole. The analysis of the intraseasonal variability of the Sahelian vegetation relies on the analysis of the seasonal marches and their main phenological stages. Green-up usually starts in early July and shows a very low year-to-year variability, while senescence ends by mid-November and is prone to larger interannual variability. Six types of vegetative seasonal marches are discriminated according to variations in the timing of phenological stages as well as in the greening intensity. These types appear to be strongly dependent on rainfall distribution and amount, particularly those recorded in late August. Finally, year-to-year memory effects are highlighted: NDVI recorded during the green-up phase in year j appears to be strongly related to the maximum NDVI value recorded at year j - 1. [ABSTRACT FROM AUTHOR]

The authors demonstrate that variability in vegetation cover can potentially influence oceanic variability through the atmospheric bridge. Experiments aimed at isolating the impact of variability in forest cover along the poleward side of the Asian boreal forest on North Pacific SSTs are performed using the fully coupled model, Fast Ocean Atmosphere Model–Lund Potsdam Jena (FOAM-LPJ), with dynamic atmosphere, ocean, and vegetation. The northern edge of the simulated Asian boreal forest is characterized by substantial variability in annual forest cover, with an east–west dipole pattern marking its first EOF mode. Simulations in which vegetation cover is allowed to vary over north/central Russia exhibit statistically significant greater SST variance over the Kuroshio Extension. Anomalously high forest cover over North Asia supports a lower surface albedo with higher temperatures and lower sea level pressure, leading to a reduction in cold advection into northern China and in turn a decrease in cold air transport into the Kuroshio Extension region. Variability in the large-scale circulation pattern is indirectly impacted by the aforementioned vegetation feedback, including the enhancement in upper-level jet wind variability along the north–south flanks of the East Asian jet stream. [ABSTRACT FROM AUTHOR]

The African Humid Period (AHP), about 14 800 yr ago [14.8–5.5 ka (ka ≡ 1000 yr ago)], was a time of increased humidity over Africa. Paleoclimate evidence suggests that the West African summer monsoon was stronger and more extensive 6 ka than today, and that the Saharan Desert was green. Here, a regional climate model that produces an excellent simulation of today’s climate over northern Africa is used to study the dynamics of the monsoon 6 ka. Changes in insolation, atmospheric CO2, and vegetation are used to impose 6-ka conditions, and the role of each forcing is isolated. Vegetation is not interactive, and the large-scale circulation and SSTs are fixed at present-day values for the 6-ka simulations. The regional model produces precipitation increases across the Sahel and Sahara that are in good agreement with the paleodata. However, unobserved drying is simulated over the Guinean coast region where paleodata are sparse. Precipitation increases in the Sahel are related to a northward shift of the monsoon, the elimination of the African easterly jet, and an intensification and deepening of the low-level westerly jet on the west coast. The thermal low–Saharan high system of the present-day climate is replaced by a deep thermal low. When this system becomes fully developed in midsummer, cyclonic circulations transport moisture north into the Sahara, and rainfall increases there. Surface temperatures decrease despite the increased solar forcing 6 ka because of an increase in cloudiness. A moist static energy budget analysis shows that increased low-level moisture dominates the cooling to destabilize the vertical column and enhance convection. Even though solar forcing is the ultimate cause of the AHP, the model responds more strongly to the vegetation forcing, especially early in the summer season, emphasizing the importance of vegetation in maintaining the intensified monsoon system. [ABSTRACT FROM AUTHOR]

Transient simulations are presented of future climate and vegetation associated with continued rising levels of CO2. The model is a fully coupled atmosphere–ocean–land–ice model with dynamic vegetation. The impacts of the radiative and physiological forcing of CO2 are diagnosed, along with the role of vegetation feedbacks. While the radiative effect of rising CO2 produces most of the warming, the physiological effect contributes additional warming by weakening the hydrologic cycle through reduced evapotranspiration. Both effects cause drying over tropical rain forests, while the radiative effect enhances Arctic and Indonesian precipitation. A global greening trend is simulated primarily due to the physiological effect, with an increase in photosynthesis and total tree cover associated with enhanced water-use efficiency. In particular, tree cover is enhanced by the physiological effect over moisture-limited regions. Over Amazonia, South Africa, and Australia, the radiative forcing produces soil drying and reduced forest cover. A poleward shift of the boreal forest is simulated as both the radiative and physiological effects enhance vegetation growth in the northern tundra and the radiative effect induces drying and summertime heat stress on the central and southern boreal forest. Vegetation feedbacks substantially impact local temperature trends through changes in albedo and evapotranspiration. The physiological effect increases net biomass across most land areas, while the radiative effect results in an increase over the tundra and decrease over tropical forests and portions of the boreal forest. [ABSTRACT FROM AUTHOR]

Paleoevidence indicates that generally wetter conditions existed in the Sahara during the mid-Holocene. Climate modeling studies addressing this issue generally agree that mid-Holocene values of the earth’s orbital parameters favored an enhanced North African summer monsoon but also suggest that land surface and vegetation feedbacks must have been important factors. Attempts to reproduce the “green” mid-Holocene Sahara in model studies with interactive vegetation may be interpreted to indicate that the problem is highly sensitive to the atmospheric dynamics of each model employed. In other work, dynamical mechanisms have been hypothesized to affect monsoon poleward extent, particularly ventilation, by import of low-moist static energy air to the continent. Here, interactive vegetation and the ventilation mechanism are studied in an intermediate complexity atmospheric model coupled to simple land and vegetation components. Interactive vegetation is found to be effective at enhancing the precipitation and vegetation amount in regions where the monsoon has advanced because of changes in orbital parameters or ventilation yet not very effective in moving the monsoon boundary if ventilation is strong. The poleward extent of the mid-Holocene monsoon and the steppe boundary are primarily controlled by the strength of ventilation in the atmospheric model. Within this boundary, the largest changes in monsoon precipitation and vegetation occur when interactive vegetation and reduced ventilation act simultaneously, as these greatly reinforce each other. [ABSTRACT FROM AUTHOR]

The Community Land Model version 3 (CLM3) Dynamic Global Vegetation Model (CLM–DGVM) is used diagnostically to identify land and atmospheric model biases that lead to biases in the simulated vegetation. The CLM–DGVM driven with observed atmospheric data (offline simulation) underestimates global forest cover, overestimates grasslands, and underestimates global net primary production. These results are consistent with earlier findings that the soils in CLM3 are too dry. In the offline simulation an increase in simulated transpiration by changing this variable's soil moisture dependence and by decreasing canopy-intercepted precipitation results in better global plant biogeography and global net primary production. When CLM–DGVM is coupled to the Community Atmosphere Model version 3 (CAM3), the same modifications do not improve simulated vegetation in the eastern United States and Amazonia where the most serious vegetation biases appear. The dry bias in eastern U.S. precipitation is so severe that the simulated vegetation is insensitive to changes in the hydrologic cycle. In Amazonia, strong coupling among soil moisture, vegetation, evapotranspiration, and precipitation produces a highly complex hydrologic cycle in which small perturbations in precipitation are accentuated by vegetation. These interactions in Amazonia lead to a dramatic precipitation decrease and a collapse of the forest. These results suggest that the accurate parameterization of convection poses a complex and challenging scientific issue for climate models that include dynamic vegetation. The results also emphasize the difficulties that may arise when coupling any two highly nonlinear systems that have only been tested uncoupled. [ABSTRACT FROM AUTHOR]

Land surface variables, such as soil moisture, are among the most important components of memory for the climate system. A more accurate and long time series of land surface data is very important for real-time drought monitoring, for understanding land surface–atmosphere interaction, and for improving weather and climate prediction. Thus, the ultimate goal of the present work is to produce a long-term “land reanalysis” with 1) retrospective and 2) real-time update components that are both generated in a manner that remains temporally homogeneous throughout the record. As the first step of the above goal, the retrospective component is reported here. Specifically, a 51-yr (1948–98) set of hourly land surface meteorological forcing is produced and used to execute the Noah land surface model, all on the 1/8° grid of the North American Land Data Assimilation System (NLDAS). The surface forcing includes air temperature, air humidity, surface pressure, wind speed, and surface downward shortwave and longwave radiation, all derived from the National Centers for Environmental Prediction–National Center For Atmospheric Research (NCEP–NCAR) Global Reanalysis. Additionally, a newly improved precipitation analysis is used to provide realistic hourly precipitation forcing on the NLDAS grid. Some unique procedures are described and applied to yield retroactive forcing that is temporally homogeneous over the 51 yr at the spatial and temporal resolution, including a terrain height adjustment that accounts for the terrain differences between the global reanalysis and the NLDAS. The land model parameters and fixed fields are derived from existing high-resolution datasets of vegetation, soil, and orography. The land reanalysis output from the Noah land surface model consists of eight energy balance components and skin temperature, which are output at 3-hourly intervals, and 15 other variables (i.e., water balance components, surface state variables, etc.), which are output at daily intervals for the period of 1 January 1948 through 31 December 1998. Using soil moisture observations throughout Illinois over 1984–98 as validation, an improvement in the simulated soil moisture (of the Noah model versus a forerunner leaky bucket model) is illustrated in terms of an improved annual cycle (much better phasing) and somewhat higher anomaly correlation for the anomalies, especially in central and southern Illinois. Nonetheless, considerable room for model improvement remains. For example, the simulated anomalies are overly uniform in the vertical compared to the observations, and some likely routes for model improvement in this aspect are proposed. [ABSTRACT FROM AUTHOR]

This study explores the role of vegetation biophysical processes (VBPs) in the structure and evolution of the South American monsoon system (SAMS) with an emphasis on the precipitation field. The approach is based on comparing ensemble simulations by the National Centers for Environmental Prediction general circulation model (GCM) in which the land surface parameterization in one ensemble includes an explicit representation of vegetation processes in the calculation of surface fluxes while the other does not [GCM/Simplified Simple Biosphere Model (SSiB) and GCM/Soil, respectively], but with similar monthly mean surface albedo and initial soil moisture. The ensembles consist of five pairs of 1-yr integrations differing in the initial conditions for the atmosphere. The results show that, during the austral summer, consideration of explicit vegetation processes does not alter the monthly mean precipitation at the planetary scale. However, at continental scales, GCM/SSiB produces a more successful simulation of SAMS than GCM/Soil. The improvement is particularly clear in reference to the seasonal southward displacement of precipitation during the onset of the SAMS and its northward merging with the intertropical convergence zone during the monsoon mature stage, as well as better monthly mean austral summer precipitation over the South American continent. The changes in surface water and energy balances and circulation in October (monsoon onset) and December (the start of the monsoon mature stage) were analyzed for a better understanding of the results and mechanisms involved. It was found that the major difference between the simulations is in the partitioning of latent heat and sensible heat fluxes (i.e., different Bowen ratio), which produced different latitudinal and longitudinal thermal gradients at the surface. A stronger sensible heat flux gradient between continent and ocean in the GCM/SSiB simulation helped generate an enhanced ventilation effect, which lowered moist static energy (MSE) over the northeast coast of South America leading to stronger counterclockwise turning of the low-level wind from the Atlantic Ocean toward the continent during the premonsoon and early monsoon stages, modifying moisture flux convergence (MFC). It was further identified that the seasonality of savanna and shrublands to the south and east of the Amazon rain forest contributed to the variability of heating gradients and influenced the SAMS onset and its northward merge with the ITCZ at the early monsoon mature stage. The comparison of the differences between precipitation, evaporation, advection of MSE, and MFC based on simulations using two different land parameterizations suggested that the VBP modulated the surface water budget, but its impact on precipitation was determined by the changes in circulation via changes in heat gradient and MSE. [ABSTRACT FROM AUTHOR]

The feedback between global vegetation greenness and surface air temperature and precipitation is assessed using remote sensing observations of monthly fraction of photosynthetically active radiation (FPAR) for 1982 to 2000 with a 2.5° grid resolution. Lead/lag correlations are used to infer vegetation–climate interactions. Furthermore, a statistical method is used to quantify the efficiency of vegetation feedback on climate in the observations. This feedback analysis provides a first quantitative assessment of global vegetation feedback on climate. In northern mid- and high latitudes, vegetation variability is found to be driven predominantly by temperature; in the meantime, vegetation also exerts a strong positive feedback on temperature with the feedback accounting for over 10%–25% of the total monthly temperature variance. The strongest positive feedback occurs in the boreal regions of southern Canada/northern United States, northern Europe, and southern Siberia, where the feedback efficiency exceeds 1°C (0.1 FPAR)-1. Over most of the Tropics and subtropics (outside the equatorial rain belt), vegetation is driven primarily by precipitation. However, little vegetation feedback is found on local precipitation when averaged year-round, with the feedback explained variance usually accounting for less than 5% of the total precipitation variance. Nevertheless, in a few isolated small regions such as Northeast Brazil, East Africa, East Asia, and northern Australia, there appears to be some positive vegetation feedback on local precipitation, with the feedback efficiency over 1 cm month-1 (0.1 FPAR)-1. Further studies suggest a significant seasonal variation of the vegetation feedback in some regions. A preliminary analysis also seems to suggest an enhanced intensity of the vegetation feedback, especially on precipitation, at longer time scales and over a larger grid box area. Limitations and implications of the assessment of vegetation feedback are also discussed. The assessed vegetation feedback is shown to be valuable for the evaluation of vegetation–climate feedback in coupled climate–vegetation models. [ABSTRACT FROM AUTHOR]

A new physiology-based model of canopy stomatal conductance and photosynthesis is described and included in the latest version of the Goddard Institute for Space Studies (GISS) GCM, ModelE1. The submodel includes responses to atmospheric humidity and CO2 concentration, responses missing from previous GISS GCM land surface schemes. Measurements of moisture, energy, and CO2 fluxes over four vegetation types are used to test and calibrate the submodel. Photosynthetic leaf N is calibrated for each vegetation type from the flux measurements. The new submodel results in surface cooling over many regions previously too warm. Some warm biases of over 2°C are cooled by more than 0.5°C, including over central Eurasia, South America, the western United States, and Australia. In addition, some regions that were previously too cool are warmed, such as northern Eurasia and the Tibetan Plateau. A number of precipitation biases are also reduced, particularly over South America (by up to 1 mm day-1) and the oceanic ITCZs (by over ±1 mm day-1); coastal west Africa becomes significantly wetter. Cloud cover increases over many land areas previously too clear. Higher absolute canopy conductances, and positive feedbacks with atmospheric humidity, are largely responsible for the simulated vegetation influence on the atmosphere. High-latitude climate changes through remote effects of increased tropical latent heating, resulting directly from improved characterization of tropical forest canopy conductance. Realistic representation of the stomatal control on land evaporation is critical for accurate simulation of atmospheric dynamics in the GISS GCM. [ABSTRACT FROM AUTHOR]

The behavior of the terrestrial carbon cycle under historical and future climate change is examined using the University of Victoria Earth System Climate Model, now coupled to a dynamic terrestrial vegetation and global carbon cycle model. When forced by historical emissions of CO2 from fossil fuels and land-use change, the coupled climate–carbon cycle model accurately reproduces historical atmospheric CO2 trends, as well as terrestrial and oceanic uptake for the past two decades. Under six twenty-first-century CO2 emissions scenarios, both terrestrial and oceanic carbon sinks continue to increase, though terrestrial uptake slows in the latter half of the century. Climate–carbon cycle feedbacks are isolated by comparing a coupled model run with a run where climate and the carbon cycle are uncoupled. The modeled positive feedback between the carbon cycle and climate is found to be relatively small, resulting in an increase in simulated CO2 of 60 ppmv at the year 2100. Including non-CO2 greenhouse gas forcing and increasing the model’s climate sensitivity increase the effect of this feedback to 140 ppmv. The UVic model does not, however, simulate a switch from a terrestrial carbon sink to a source during the twenty-first century, as earlier studies have suggested. This can be explained by a lack of substantial reductions in simulated vegetation productivity due to climate changes. [ABSTRACT FROM AUTHOR]

Several numerical simulations were performed, using a global climate model that includes a realistic land surface model, to investigate the impact of Asian tropical vegetation changes on the climate. The control simulation, under conditions of the actual vegetation, and three vegetation-change impact experiments were performed. The results of the impact experiments were compared with those of the control simulation. The horizontal resolution of the model used in these simulations was 1.875°, being finer than that of the models used in previous vegetation-change impact studies. As a result, it was determined that the effects of vegetation changes in the Asian tropical region had spatially different features. The morphological, physiological, and physical changes of the land surface vegetation in the Asian tropical region certainly induce statistically significant climate changes in these and the surrounding areas. That is, from the results of the bare soil and C4 grass experiments, the decrease in the roughness length, and from the results of the green-less experiment, the decrease of the latent heat flux, exert strong influences on the horizontal and convective circulations of the atmosphere. Consequently, the distribution of precipitation will undergo a change. Other energy and water balances at the land surface are also influenced by the vegetation changes, and the induced changes are generally statistically significant. The influences of vegetation changes in the Asian tropical region were more complicated than those in the Amazon. One reason for this was that the Asian tropical region is strongly influenced by the Asian monsoon circulation; another reason is that the land–sea distribution and the distribution of vegetation in the Asian tropical region are not as simple as in a tropical rain forest like the Amazon. [ABSTRACT FROM AUTHOR]

Substantial evolution of Normalized Difference Vegetation Index (NVDI)-derived vegetation cover (Fg) exists in the southwestern United States and Mexico. The intraseasonal and wet-/dry-year fluctuations of Fg are linked to observed precipitation in the North American monsoon system (NAMS). The manner in which the spatial and temporal variability of Fg influences the land-atmosphere energy and moisture fluxes, and associated likelihood of moist convection in the NAMS regions, is examined. For this, the regional climate model (RCM) is employed, with three different Fg boundary conditions lo examine the influence of intraseasonal and wet-/dry-year vegetation variability. Results show that a strong link exists between evaporative fraction (EF). surface temperature, and relative humidity in the boundary layer (BL). which is consistent with a positive soil moisture feedback. However, contrary to expectations, higher Fg dots not consistently enhance EF across the NAMS region. This is because the low soil moisture values simulated by the land surface model (LSM) yield high canopy resistance values throughout the monsoon season. As a result, the experiment with the lowest Fg yields the greatest EF and precipitation in the NAMS region, and also modulates regional atmospheric circulation that steers the track of tropical cyclones. In conclusion, the simulated influence of vegetation on land-atmosphere exchanges depends strongly on the canopy stress index parameterized in the LSM. Therefore, a reliable dataset, at appropriate scales, is needed to calibrate transpiration schemes and to assess simulated and realistic vegetation-atmosphere interactions in the NAMS region. [ABSTRACT FROM AUTHOR]

Tropical land climate sensitivities to surface properties are studied using an intermediate complexity atmosphere model. The focus here is on land surface vegetation feedbacks to the atmosphere through surface conductance and albedo. Both properties are linked by a parameterization on leaf area index so that their relative impacts can be compared. For a given percent change in leaf area index, it is found that low and moderate vegetation regions such as the Sahel have a higher sensitivity than rain forest regions such as the Amazon in local total precipitation anomaly, as well as fractional change in precipitation. Comparison of sensitivities to changes in surface conductance and albedo shows that neither is negligible and their relative influence differs among local climatic regions, typified by different vegetation types. High precipitation rain forest regions are more influenced by surface conductance due to the large water recycling ratio there, while albedo has a larger influence in arid, low vegetation regions by modifying the energy balance and large-scale atmospheric circulation. In regions of moderate precipitation and vegetation, altered surface conductance and albedo have comparable effects on precipitation. Surface conductance and albedo have opposing effects on surface temperature but surface conductance has the dominant impact on both surface temperature and evapotranspiration. [ABSTRACT FROM AUTHOR]