scholarly journals Land-Cover and Surface Water Change Drive Large Albedo Increases in South America*

2011 ◽  
Vol 15 (7) ◽  
pp. 1-16 ◽  
Author(s):  
Scott R. Loarie ◽  
David B. Lobell ◽  
Gregory P. Asner ◽  
Christopher B. Field

Abstract Albedo is an important factor affecting global climate, but uncertainty in the sources and magnitudes of albedo change has led to simplistic treatments of albedo in climate models. Here, the authors examine nine years (2000–08) of historical 1-km Moderate Resolution Imaging Spectroradiometer (MODIS) albedo estimates across South America to advance understanding of the magnitude and sources of large-scale albedo changes. The authors use the magnitude of albedo change from the arc of deforestation along the southeastern edge of the Brazilian Amazon (+2.8%) as a benchmark for comparison. Large albedo increases (>+2.8%) were 2.2 times more prevalent than similar decreases throughout South America. Changes in surface water drove most large albedo changes that were not caused by vegetative cover change. Decreased surface water in the Santa Fe and Buenos Aires regions of Argentina was responsible for albedo increases exceeding that of the arc of deforestation in magnitude and extent. Although variations in the natural flooding regimes were likely the dominant mechanism driving changes in surface water, it is possible that human manipulations through dams and other agriculture infrastructure contributed. This study demonstrates the substantial role that land-cover and surface water change can play in continental-scale albedo trends and suggests ways to better incorporate these processes into global climate models.

2006 ◽  
Vol 19 (14) ◽  
pp. 3420-3429 ◽  
Author(s):  
Shang-Ping Xie ◽  
Haiming Xu ◽  
N. H. Saji ◽  
Yuqing Wang ◽  
W. Timothy Liu

Abstract The Asian summer monsoon is organized into distinct convection centers, but the mechanism for this organization is not well understood. Analysis of new satellite observations reveals that narrow mountain ranges are an important organizing agent anchoring monsoon convection centers on the windward side. The Bay of Bengal convection, in particular, features the heaviest precipitation on its eastern coast because of orographic lifting as the southwest monsoon impinges on the coastal mountains of Myanmar (also known as Burma). This is in contrast to the widely held view that this convection is centered over the open ocean as implied by coarse-resolution datasets, a view that would require an entirely different explanation for its formation. Narrow in width and modest in height (≤1 km), these mountains are hardly mentioned in conceptual depictions of the large-scale monsoon and poorly represented in global climate models. The numerical simulations of this study show that orographic rainbands are not a local phenomenon but exert far-reaching effects on the continental-scale monsoon. The realization that these overlooked geographical features are an important element of the Asian monsoon has important implications for studying the monsoon in the past, present, and future.


2021 ◽  
Vol 22 (4) ◽  
pp. 905-922
Author(s):  
Jessica C. A. Baker ◽  
Dayana Castilho de Souza ◽  
Paulo Y. Kubota ◽  
Wolfgang Buermann ◽  
Caio A. S. Coelho ◽  
...  

AbstractIn South America, land–atmosphere interactions have an important impact on climate, particularly the regional hydrological cycle, but detailed evaluation of these processes in global climate models has been limited. Focusing on the satellite-era period of 2003–14, we assess land–atmosphere interactions on annual to seasonal time scales over South America in satellite products, a novel reanalysis (ERA5-Land), and two global climate models: the Brazilian Global Atmospheric Model version 1.2 (BAM-1.2) and the U.K. Hadley Centre Global Environment Model version 3 (HadGEM3). We identify key features of South American land–atmosphere interactions represented in satellite and model datasets, including seasonal variation in coupling strength, large-scale spatial variation in the sensitivity of evapotranspiration to surface moisture, and a dipole in evaporative regime across the continent. Differences between products are also identified, with ERA5-Land, HadGEM3, and BAM-1.2 showing opposite interactions to satellites over parts of the Amazon and the Cerrado and stronger land–atmosphere coupling along the North Atlantic coast. Where models and satellites disagree on the strength and direction of land–atmosphere interactions, precipitation biases and misrepresentation of processes controlling surface soil moisture are implicated as likely drivers. These results show where improvement of model processes could reduce uncertainty in the modeled climate response to land-use change, and highlight where model biases could unrealistically amplify drying or wetting trends in future climate projections. Finally, HadGEM3 and BAM-1.2 are consistent with the median response of an ensemble of nine CMIP6 models, showing they are broadly representative of the latest generation of climate models.


2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Mateusz Taszarek ◽  
John T. Allen ◽  
Mattia Marchio ◽  
Harold E. Brooks

AbstractGlobally, thunderstorms are responsible for a significant fraction of rainfall, and in the mid-latitudes often produce extreme weather, including large hail, tornadoes and damaging winds. Despite this importance, how the global frequency of thunderstorms and their accompanying hazards has changed over the past 4 decades remains unclear. Large-scale diagnostics applied to global climate models have suggested that the frequency of thunderstorms and their intensity is likely to increase in the future. Here, we show that according to ERA5 convective available potential energy (CAPE) and convective precipitation (CP) have decreased over the tropics and subtropics with simultaneous increases in 0–6 km wind shear (BS06). Conversely, rawinsonde observations paint a different picture across the mid-latitudes with increasing CAPE and significant decreases to BS06. Differing trends and disagreement between ERA5 and rawinsondes observed over some regions suggest that results should be interpreted with caution, especially for CAPE and CP across tropics where uncertainty is the highest and reliable long-term rawinsonde observations are missing.


2008 ◽  
Vol 80 (2) ◽  
pp. 397-408 ◽  
Author(s):  
David M. Lapola ◽  
Marcos D. Oyama ◽  
Carlos A. Nobre ◽  
Gilvan Sampaio

We developed a new world natural vegetation map at 1 degree horizontal resolution for use in global climate models. We used the Dorman and Sellers vegetation classification with inclusion of a new biome: tropical seasonal forest, which refers to both deciduous and semi-deciduous tropical forests. SSiB biogeophysical parameters values for this new biome type are presented. Under this new vegetation classification we obtained a consensus map between two global natural vegetation maps widely used in climate studies. We found that these two maps assign different biomes in ca. 1/3 of the continental grid points. To obtain a new global natural vegetation map, non-consensus areas were filled according to regional consensus based on more than 100 regional maps available on the internet. To minimize the risk of using poor quality information, the regional maps were obtained from reliable internet sources, and the filling procedure was based on the consensus among several regional maps obtained from independent sources. The new map was designed to reproduce accurately both the large-scale distribution of the main vegetation types (as it builds on two reliable global natural vegetation maps) and the regional details (as it is based on the consensus of regional maps).


2017 ◽  
Author(s):  
Matthew C. Wozniak ◽  
Allison Steiner

Abstract. We develop a prognostic model of Pollen Emissions for Climate Models (PECM) for use within regional and global climate models to simulate pollen counts over the seasonal cycle based on geography, vegetation type and meteorological parameters. Using modern surface pollen count data, empirical relationships between prior-year annual average temperature and pollen season start dates and end dates are developed for deciduous broadleaf trees (Acer, Alnus, Betula, Fraxinus, Morus, Platanus, Populus, Quercus, Ulmus), evergreen needleleaf trees (Cupressaceae, Pinaceae), grasses (Poaceae; C3, C4), and ragweed (Ambrosia). This regression model explains as much as 57 % of the variance in pollen phenological dates, and it is used to create a climate-flexible phenology that can be used to study the response of wind-driven pollen emissions to climate change. The emissions model is evaluated in a regional climate model (RegCM4) over the continental United States by prescribing an emission potential from PECM and transporting pollen as aerosol tracers. We evaluate two different pollen emissions scenarios in the model: (1) using a taxa-specific land cover database, phenology and emission potential, and (2) a PFT-based land cover, phenology and emission potential. The resulting surface concentrations for both simulations are evaluated against observed surface pollen counts in five climatic subregions. Given prescribed pollen emissions, the RegCM4 simulates observed concentrations within an order of magnitude, although the performance of the simulations in any subregion is strongly related to the land cover representation and the number of observation sites used to create the empirical phenological relationship. The taxa-based model provides a better representation of the phenology of tree-based pollen counts than the PFT-based model, however we note that the PFT-based version provides a useful and climate-flexible emissions model for the general representation of the pollen phenology over the United States.


2017 ◽  
Author(s):  
Imme Benedict ◽  
Chiel C. van Heerwaarden ◽  
Albrecht H. Weerts ◽  
Wilco Hazeleger

Abstract. The hydrological cycle of river basins can be simulated by combining global climate models (GCMs) and global hydrological models (GHMs). The spatial resolution of these models is restricted by computational resources and therefore limits the processes and level of detail that can be resolved. To further improve simulations of precipitation and river-runoff on a global scale, we assess and compare the benefits of an increased resolution for a GCM and a GHM. We focus on the Rhine and Mississippi basin. Increasing the resolution of a GCM (1.125° to 0.25°) results in more realistic large-scale circulation patterns over the Rhine and an improved precipitation budget. These improvements with increased resolution are not found for the Mississippi basin, most likely because precipitation is strongly dependent on the representation of still unresolved convective processes. Increasing the resolution of vegetation and orography in the high resolution GHM (from 0.5° to 0.05°) shows no significant differences in discharge for both basins, because the hydrological processes depend highly on other parameter values that are not readily available at high resolution. Therefore, increasing the resolution of the GCM provides the most straightforward route to better results. This route works best for basins driven by large-scale precipitation, such as the Rhine basin. For basins driven by convective processes, such as the Mississippi basin, improvements are expected with even higher resolution convection permitting models.


2021 ◽  
Vol 34 (2) ◽  
pp. 509-525
Author(s):  
David P. Rowell ◽  
Rory G. J. Fitzpatrick ◽  
Lawrence S. Jackson ◽  
Grace Redmond

AbstractProjected changes in the intensity of severe rain events over the North African Sahel—falling from large mesoscale convective systems—cannot be directly assessed from global climate models due to their inadequate resolution and parameterization of convection. Instead, the large-scale atmospheric drivers of these storms must be analyzed. Here we study changes in meridional lower-tropospheric temperature gradient across the Sahel (ΔTGrad), which affect storm development via zonal vertical wind shear and Saharan air layer characteristics. Projected changes in ΔTGrad vary substantially among models, adversely affecting planning decisions that need to be resilient to adverse risks, such as increased flooding. This study seeks to understand the causes of these projection uncertainties and finds three key drivers. The first is intermodel variability in remote warming, which has strongest impact on the eastern Sahel, decaying toward the west. Second, and most important, a warming–advection–circulation feedback in a narrow band along the southern Sahara varies in strength between models. Third, variations in southern Saharan evaporative anomalies weakly affect ΔTGrad, although for an outlier model these are sufficiently substantive to reduce warming here to below that of the global mean. Together these uncertain mechanisms lead to uncertain southern Saharan/northern Sahelian warming, causing the bulk of large intermodel variations in ΔTGrad. In the southern Sahel, a local negative feedback limits the contribution to uncertainties in ΔTGrad. This new knowledge of ΔTGrad projection uncertainties provides understanding that can be used, in combination with further research, to constrain projections of severe Sahelian storm activity.


2006 ◽  
Vol 63 (11) ◽  
pp. 2813-2830 ◽  
Author(s):  
Roger Marchand ◽  
Nathaniel Beagley ◽  
Sandra E. Thompson ◽  
Thomas P. Ackerman ◽  
David M. Schultz

Abstract A classification scheme is created to map the synoptic-scale (large scale) atmospheric state to distributions of local-scale cloud properties. This mapping is accomplished by a neural network that classifies 17 months of synoptic-scale initial conditions from the rapid update cycle forecast model into 25 different states. The corresponding data from a vertically pointing millimeter-wavelength cloud radar (from the Atmospheric Radiation Measurement Program Southern Great Plains site at Lamont, Oklahoma) are sorted into these 25 states, producing vertical profiles of cloud occurrence. The temporal stability and distinctiveness of these 25 profiles are analyzed using a bootstrap resampling technique. A stable-state-based mapping from synoptic-scale model fields to local-scale cloud properties could be useful in three ways. First, such a mapping may improve the understanding of differences in cloud properties between output from global climate models and observations by providing a physical context. Second, this mapping could be used to identify the cause of errors in the modeled distribution of clouds—whether the cause is a difference in state occurrence (the type of synoptic activity) or the misrepresentation of clouds for a particular state. Third, robust mappings could form the basis of a new statistical cloud parameterization.


2015 ◽  
Vol 28 (14) ◽  
pp. 5583-5600 ◽  
Author(s):  
Jacob Scheff ◽  
Dargan M. W. Frierson

Abstract The aridity of a terrestrial climate is often quantified using the dimensionless ratio of annual precipitation (P) to annual potential evapotranspiration (PET). In this study, the climatological patterns and greenhouse warming responses of terrestrial P, Penman–Monteith PET, and are compared among 16 modern global climate models. The large-scale climatological values and implied biome types often disagree widely among models, with large systematic differences from observational estimates. In addition, the PET climatologies often differ by several tens of percent when computed using monthly versus 3-hourly inputs. With greenhouse warming, land P does not systematically increase or decrease, except at high latitudes. Therefore, because of moderate, ubiquitous PET increases, decreases (drying) are much more widespread than increases (wetting) in the tropics, subtropics, and midlatitudes in most models, confirming and expanding on earlier findings. The PET increases are also somewhat sensitive to the time resolution of the inputs, although not as systematically as for the PET climatologies. The changes in the balance between P and PET are also quantified using an alternative aridity index, the ratio , which has a one-to-one but nonlinear correspondence with . It is argued that the magnitudes of changes are more uniformly relevant than the magnitudes of changes, which tend to be much higher in wetter regions. The ratio and its changes are also found to be excellent statistical predictors of the land surface evaporative fraction and its changes.


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