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Journal articles on the topic 'Land Atmosphere'
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1
Späth, Florian, Verena Rajtschan, Tobias K. D. Weber, Shehan Morandage, Diego Lange, Syed Saqlain Abbas, Andreas Behrendt, Joachim Ingwersen, Thilo Streck, and Volker Wulfmeyer. "The land–atmosphere feedback observatory: a new observational approach for characterizing land–atmosphere feedback." Geoscientific Instrumentation, Methods and Data Systems 12, no. 1 (January 25, 2023): 25–44. http://dx.doi.org/10.5194/gi-12-25-2023.
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Abstract. Important topics in land–atmosphere (L–A) feedback research are water and energy balances and heterogeneities of fluxes at the land surface and in the atmospheric boundary layer (ABL). To target these questions, the Land–Atmosphere Feedback Observatory (LAFO) has been installed in southwestern Germany. The instrumentation allows comprehensive and high-resolution measurements from the bedrock to the lower free troposphere. Grouped into three components, atmosphere, soil and land surface, and vegetation, the LAFO observation strategy aims for simultaneous measurements in all three compartments. For this purpose the LAFO sensor synergy contains lidar systems to measure the atmospheric key variables of humidity, temperature and wind. At the land surface, eddy covariance stations are operated to record the energy distribution of radiation, sensible, latent and ground heat fluxes. Together with a water and temperature sensor network, the soil water content and temperature are monitored in the agricultural investigation area. As for vegetation, crop height, leaf area index and phenological growth stage values are registered. The observations in LAFO are organized into operational measurements and intensive observation periods (IOPs). Operational measurements aim for long time series datasets to investigate statistics, and we present as an example the correlation between mixing layer height and surface fluxes. The potential of IOPs is demonstrated with a 24 h case study using dynamic and thermodynamic profiles with lidar and a surface layer observation that uses the scanning differential absorption lidar to relate atmospheric humidity patterns to soil water structures. Both IOPs and long-term observations will provide new insight into exchange processes and their statistics for improving the representation of L–A feedbacks in climate and numerical weather prediction models. The lidar component in particular will support the investigation of coupling to the atmosphere.
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Dickinson, R. E. "Land-atmosphere interaction." Reviews of Geophysics 33, S2 (July 1995): 917–22. http://dx.doi.org/10.1029/95rg00284.
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Costa, Marcos Heil, Michael T. Coe, and David R. Galbraith. "Land-Atmosphere Interactions." Advances in Meteorology 2016 (2016): 1. http://dx.doi.org/10.1155/2016/2362398.
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Laguë, Marysa M., Gordon B. Bonan, and Abigail L. S. Swann. "Separating the Impact of Individual Land Surface Properties on the Terrestrial Surface Energy Budget in both the Coupled and Uncoupled Land–Atmosphere System." Journal of Climate 32, no. 18 (August 12, 2019): 5725–44. http://dx.doi.org/10.1175/jcli-d-18-0812.1.
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Abstract Changes in the land surface can drive large responses in the atmosphere on local, regional, and global scales. Surface properties control the partitioning of energy within the surface energy budget to fluxes of shortwave and longwave radiation, sensible and latent heat, and ground heat storage. Changes in surface energy fluxes can impact the atmosphere across scales through changes in temperature, cloud cover, and large-scale atmospheric circulation. We test the sensitivity of the atmosphere to global changes in three land surface properties: albedo, evaporative resistance, and surface roughness. We show the impact of changing these surface properties differs drastically between simulations run with an offline land model, compared to coupled land–atmosphere simulations that allow for atmospheric feedbacks associated with land–atmosphere coupling. Atmospheric feedbacks play a critical role in defining the temperature response to changes in albedo and evaporative resistance, particularly in the extratropics. More than 50% of the surface temperature response to changing albedo comes from atmospheric feedbacks in over 80% of land areas. In some regions, cloud feedbacks in response to increased evaporative resistance result in nearly 1 K of additional surface warming. In contrast, the magnitude of surface temperature responses to changes in vegetation height are comparable between offline and coupled simulations. We improve our fundamental understanding of how and why changes in vegetation cover drive responses in the atmosphere, and develop understanding of the role of individual land surface properties in controlling climate across spatial scales—critical to understanding the effects of land-use change on Earth’s climate.
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Zhou, Sha, A. Park Williams, Alexis M. Berg, Benjamin I. Cook, Yao Zhang, Stefan Hagemann, Ruth Lorenz, Sonia I. Seneviratne, and Pierre Gentine. "Land–atmosphere feedbacks exacerbate concurrent soil drought and atmospheric aridity." Proceedings of the National Academy of Sciences 116, no. 38 (September 3, 2019): 18848–53. http://dx.doi.org/10.1073/pnas.1904955116.
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Compound extremes such as cooccurring soil drought (low soil moisture) and atmospheric aridity (high vapor pressure deficit) can be disastrous for natural and societal systems. Soil drought and atmospheric aridity are 2 main physiological stressors driving widespread vegetation mortality and reduced terrestrial carbon uptake. Here, we empirically demonstrate that strong negative coupling between soil moisture and vapor pressure deficit occurs globally, indicating high probability of cooccurring soil drought and atmospheric aridity. Using the Global Land Atmosphere Coupling Experiment (GLACE)-CMIP5 experiment, we further show that concurrent soil drought and atmospheric aridity are greatly exacerbated by land–atmosphere feedbacks. The feedback of soil drought on the atmosphere is largely responsible for enabling atmospheric aridity extremes. In addition, the soil moisture–precipitation feedback acts to amplify precipitation and soil moisture deficits in most regions. CMIP5 models further show that the frequency of concurrent soil drought and atmospheric aridity enhanced by land–atmosphere feedbacks is projected to increase in the 21st century. Importantly, land–atmosphere feedbacks will greatly increase the intensity of both soil drought and atmospheric aridity beyond that expected from changes in mean climate alone.
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Wei, Jiangfeng, Paul A. Dirmeyer, and Zhichang Guo. "How Much Do Different Land Models Matter for Climate Simulation? Part II: A Decomposed View of the Land–Atmosphere Coupling Strength." Journal of Climate 23, no. 11 (June 1, 2010): 3135–45. http://dx.doi.org/10.1175/2010jcli3178.1.
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Abstract The Global Land–Atmosphere Coupling Experiment (GLACE) built a framework to estimate the strength of the land–atmosphere interaction across many weather and climate models. Within this framework, GLACE-type experiments are performed with a single atmospheric model coupled to three different land models. The precipitation time series is decomposed into three frequency bands to investigate the large-scale connection between external forcing, precipitation variability and predictability, and land–atmosphere coupling strength. It is found that coupling to different land models or prescribing subsurface soil moisture does not change the global pattern of precipitation predictability and variability too much. However, the regional impact of soil moisture can be highlighted by calculating the land–atmosphere coupling strength, which shows very different patterns for the three models. The estimated precipitation predictability and land–atmosphere coupling strength is mainly associated with the low-frequency component of precipitation (periods beyond 3 weeks). Based on these findings, the land–atmosphere coupling strength is conceptually decomposed into the impact of low-frequency external forcing and the impact of soil moisture. Because most models participating in GLACE have overestimated the low-frequency component of precipitation, a calibration to the GLACE-estimated land–atmosphere coupling strength is performed. The calibrated coupling strength is generally weaker, but the global pattern does not change much. This study provides an important clarification of land–atmosphere coupling strength and increases the understanding of the land–atmosphere interaction.
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Prinn, Ronald G. "Atmosphere, oceans, and land." Eos, Transactions American Geophysical Union 71, no. 50 (1990): 1855. http://dx.doi.org/10.1029/90eo00369.
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Nicholson, Sharon E. "Land surface atmosphere interaction." Progress in Physical Geography: Earth and Environment 12, no. 1 (March 1988): 36–65. http://dx.doi.org/10.1177/030913338801200102.
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Fowell, Martin. "Water?land?atmosphere interactions." Weather 59, no. 10 (October 1, 2004): 286–88. http://dx.doi.org/10.1256/wea.122.04.
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Santanello, Joseph A., Mark A. Friedl, and Michael B. Ek. "Convective Planetary Boundary Layer Interactions with the Land Surface at Diurnal Time Scales: Diagnostics and Feedbacks." Journal of Hydrometeorology 8, no. 5 (October 1, 2007): 1082–97. http://dx.doi.org/10.1175/jhm614.1.
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Abstract The convective planetary boundary layer (PBL) integrates surface fluxes and conditions over regional and diurnal scales. As a result, the structure and evolution of the PBL contains information directly related to land surface states. To examine the nature and magnitude of land–atmosphere coupling and the interactions and feedbacks controlling PBL development, the authors used a large sample of radiosonde observations collected at the southern Atmospheric Research Measurement Program–Great Plains Cloud and Radiation Testbed (ARM-CART) site in association with simulations of mixed-layer growth from a single-column PBL/land surface model. The model accurately predicts PBL evolution and realistically simulates thermodynamics associated with two key controls on PBL growth: atmospheric stability and soil moisture. The information content of these variables and their influence on PBL height and screen-level temperature can be characterized using statistical methods to describe PBL–land surface coupling over a wide range of conditions. Results also show that the first-order effects of land–atmosphere coupling are manifested in the control of soil moisture and stability on atmospheric demand for evapotranspiration and on the surface energy balance. Two principal land–atmosphere feedback regimes observed during soil moisture drydown periods are identified that complicate direct relationships between PBL and land surface properties, and, as a result, limit the accuracy of uncoupled land surface and traditional PBL growth models. In particular, treatments for entrainment and the role of the residual mixed layer are critical to quantifying diurnal land–atmosphere interactions.
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Zhang, Li, Paul A. Dirmeyer, Jiangfeng Wei, Zhichang Guo, and Cheng-Hsuan Lu. "Land–Atmosphere Coupling Strength in the Global Forecast System." Journal of Hydrometeorology 12, no. 1 (February 1, 2011): 147–56. http://dx.doi.org/10.1175/2010jhm1319.1.
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Abstract The operational coupled land–atmosphere forecast model from the National Centers for Environmental Prediction (NCEP) is evaluated for the strength and characteristics of its coupling in the water cycle between land and atmosphere. Following the protocols of the Global Land–Atmosphere Coupling Experiment (GLACE) it is found that the Global Forecast System (GFS) atmospheric model coupled to the Noah land surface model exhibits extraordinarily weak land–atmosphere coupling, much as its predecessor, the GFS–Oregon State University (OSU) coupled system. The coupling strength is evaluated by the ability of subsurface soil wetness to affect locally the time series of precipitation. The surface fluxes in Noah are also found to be rather insensitive to subsurface soil wetness. Comparison to another atmospheric model coupled to Noah as well as a different land surface model show that Noah is responsible for some of the lack of sensitivity, primarily because its thick (10 cm) surface layer dominates the variability in surface latent heat fluxes. Noah is found to be as responsive as other land surface models to surface soil wetness and temperature variations, suggesting the design of the GLACE sensitivity experiment (based only on subsurface soil wetness) handicapped the Noah model. Additional experiments, in which the parameterization of evapotranspiration is altered, as well as experiments where surface soil wetness is also constrained, isolate the GFS atmospheric model as the principal source of the weak sensitivity of precipitation to land surface states.
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Abudukade, Silalan, Fan Yang, Yongqiang Liu, Ali Mamtimin, Jiacheng Gao, Mingjie Ma, Wenbiao Wang, et al. "Effects of Artificial Green Land on Land–Atmosphere Interactions in the Taklamakan Desert." Land 12, no. 8 (August 3, 2023): 1541. http://dx.doi.org/10.3390/land12081541.
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Land–atmosphere interactions are influenced by the earth’s complex underlying subsurface, which in turn indirectly affects atmospheric motion and climate change. Human activities are increasingly exerting an influence on desert ecosystems, and artificial green land with clear functional orientation has been established in many desert areas. Consequently, the previously dominant, shifting, sand-covered, underlying surface in these desert regions is gradually transforming. This transformation has significant implications for the characteristics of land–atmosphere interactions, causing them to deviate from their original state. At present, existing studies still have not presented a systematic understanding of this change and have ignored the impact of human activities on land–atmosphere interactions in artificial green land. To address these research gaps, this study specifically targets artificial green land in the Tazhong region of Taklamakan Desert. We carried out observation experiments on land–atmosphere interactions in three different functional units from outside to inside: natural shifting sands, the shelter forest, and the living area. We also analyzed the differences and attribution of land–atmosphere interactions characteristics of different functional units. Compared with the natural shifting sands, the daily average maximum values of wind speed in the shelter forest decreased by 78%, and the daily average maximum air temperature and soil (0 cm) temperature decreased by 2.6 °C and 7 °C, respectively. Additionally, the soil moisture level was significantly increased throughout the green land due to the shelter forest. The surface albedo experienced a decrease, with an annual average of 0.21. Furthermore, the aerodynamic roughness and bulk transport coefficient increased by two orders of magnitude. The daily average maximum values of sensible heat flux and soil heat flux (G05) decreased by 18.7% and 75%, respectively, and the daily average maximum value of latent heat flux increased by 70.3%. This effectively improved the microclimate environment of the green land. The living area was greatly reduced by the shelter forest coverage and influenced by the buildings. Consequently, the environmental improvement was not as large as it was inside the shelter forest. However, it still provided a good shelter for production and living in the desert area. Throughout the year, a total of 4.60 × 105 t water was consumed through evapotranspiration in the artificial green land. The findings of this study have the potential to enhance our comprehension of land–atmosphere interactions in desert regions, thereby offering valuable insights for the establishment and effective management of artificial desert green lands.
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Comer, Ruth E., and Martin J. Best. "Revisiting GLACE: Understanding the Role of the Land Surface in Land–Atmosphere Coupling." Journal of Hydrometeorology 13, no. 6 (December 1, 2012): 1704–18. http://dx.doi.org/10.1175/jhm-d-11-0146.1.
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Abstract The Global Land–Atmosphere Coupling Experiment (GLACE) established a method for quantifying and comparing the influence of soil moisture on the atmosphere in AGCMs. The models included in the GLACE intercomparison displayed a wide range in the strength of this influence, with the Met Office Hadley Centre (MOHC) Atmosphere Model, version 3 (HadAM3), being one of the weakest. Applying the GLACE method to a much developed version of the MOHC model, the atmospheric component of the Hadley Centre Global Environmental Model version 3 (HadGEM3-A), it is demonstrated that this new model has a stronger coupling signal than its predecessor. Although this increase in the coupling strength cannot be attributed to changes in the land surface representation, the existence of the stronger signal enables an investigation of the signal’s dependence on key land surface parameters. The GLACE method is applied to four HadGEM3-A experiment cases, with soil hydraulic parameters specified using two methods of calculation from two different underlying soil texture datasets. These cases show differences in their volumetric soil moisture and their level of moisture availability for transpiration. A change in moisture availability produces a change in evaporation variability in the same direction, which is a key factor affecting the overall land–atmosphere coupling strength. For HadGEM3-A the parameter changes therefore produce a clear change in the GLACE diagnostic.
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Kumar, Sanjiv, Matthew Newman, David M. Lawrence, Min-Hui Lo, Sathish Akula, Chia-Wei Lan, Ben Livneh, and Danica Lombardozzi. "The GLACE-Hydrology Experiment: Effects of Land–Atmosphere Coupling on Soil Moisture Variability and Predictability." Journal of Climate 33, no. 15 (August 1, 2020): 6511–29. http://dx.doi.org/10.1175/jcli-d-19-0598.1.
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AbstractThe impact of land–atmosphere anomaly coupling on land variability is investigated using a new two-stage climate model experimental design called the “GLACE-Hydrology” experiment. First, as in the GLACE-CMIP5 experiment, twin sets of coupled land–atmosphere climate model (CAM5-CLM4.5) ensembles are performed, with each simulation using the same prescribed observed sea surface temperatures and radiative forcing for the years 1971–2014. In one set, land–atmosphere anomaly coupling is removed by prescribing soil moisture to follow the control model’s seasonally evolving soil moisture climatology (“land–atmosphere uncoupled”), enabling a contrast with the original control set (“land–atmosphere coupled”). Then, the atmospheric outputs from both sets of simulations are used to force land-only ensemble simulations, allowing investigation of the resulting soil moisture variability and memory under both the coupled and uncoupled scenarios. This study finds that in midlatitudes during boreal summer, land–atmosphere anomaly coupling significantly strengthens the relationship between soil moisture and evapotranspiration anomalies, both in amplitude and phase. This allows for decreased moisture exchange between the land surface and atmosphere, increasing soil moisture memory and often its variability as well. Additionally, land–atmosphere anomaly coupling impacts runoff variability, especially in wet and transition regions, and precipitation variability, although the latter has surprisingly localized impacts on soil moisture variability. As a result of these changes, there is an increase in the signal-to-noise ratio, and thereby the potential seasonal predictability, of SST-forced hydroclimate anomalies in many areas of the globe, especially in the midlatitudes. This predictability increase is greater for soil moisture than precipitation and has important implications for the prediction of drought.
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Williams, John L., and Reed M. Maxwell. "Propagating Subsurface Uncertainty to the Atmosphere Using Fully Coupled Stochastic Simulations." Journal of Hydrometeorology 12, no. 4 (August 1, 2011): 690–701. http://dx.doi.org/10.1175/2011jhm1363.1.
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Abstract Feedbacks between the land surface and the atmosphere, manifested as mass and energy fluxes, are strongly correlated with soil moisture, making soil moisture an important factor in land–atmosphere interactions. It is shown that a reduction of the uncertainty in subsurface properties such as hydraulic conductivity (K) propagates into the atmosphere, resulting in a reduction in uncertainty in land–atmosphere feedbacks that yields more accurate atmospheric predictions. Using the fully coupled groundwater-to-atmosphere model ParFlow-WRF, which couples the hydrologic model ParFlow with the Weather Research and Forecasting (WRF) atmospheric model, responses in land–atmosphere feedbacks and wind patterns due to subsurface heterogeneity are simulated. Ensembles are generated by varying the spatial location of subsurface properties while maintaining the global statistics and correlation structure. This approach is common to the hydrologic sciences but uncommon in atmospheric simulations where ensemble forecasts are commonly generated with perturbed initial conditions or multiple model parameterizations. It is clearly shown that different realizations of K produce variation in soil moisture, latent heat flux, and wind for both point and domain-averaged quantities. Using a single random field to represent a control case, varying amounts of K data are sampled and subsurface data are incorporated into conditional Monte Carlo ensembles to show that the difference between the ensemble mean prediction and the control saturation, latent heat flux, and wind speed are reduced significantly via conditioning of K. By reducing uncertainty associated with land–atmosphere feedback mechanisms, uncertainty is also reduced in both spatially distributed and domain-averaged wind speed magnitudes, thus improving the ability to make more accurate forecasts, which is important for many applications such as wind energy.
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Guo, Zhichang, and Paul A. Dirmeyer. "Interannual Variability of Land–Atmosphere Coupling Strength." Journal of Hydrometeorology 14, no. 5 (October 1, 2013): 1636–46. http://dx.doi.org/10.1175/jhm-d-12-0171.1.
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Abstract Recent studies in the Global Land–Atmosphere Coupling Experiment (GLACE) established a framework to estimate the extent to which anomalies in the land surface state (e.g., soil moisture) can affect rainfall generation and other atmospheric processes. Within this framework, a multiyear GLACE-type experiment is carried out with a coupled land–atmosphere general circulation model to examine the interannual variability of land–atmosphere coupling strength. Soil wetness with intermediate values are in the range at which rainfall generation, near-surface air temperature, and surface turbulent fluxes are most sensitive to soil moisture anomalies, and thus, land–atmosphere coupling strength peaks in this range. As a result, the “hot spots” with strong land–atmosphere coupling strength appear in regions with intermediate climatological soil wetness (e.g., transition zones between dry and wet climates), consistent with previous studies. Land–atmosphere coupling strength experiences significant year-to-year variation because of interannual variability of soil moisture and the local spatiotemporal evolution of hydrologic regime. Coupling strength over areas with dry (wet) climate is enhanced during wet (dry) years since the resultant soil wetness enters into the sensitive range from a relatively insensitive range, and soil moisture can have stronger potential impact on surface turbulent fluxes and convection. On the other hand, land–atmosphere coupling strength over areas with wet (dry) climate is weakened during wet (dry) years since the soil wetness moves further away from the sensitive range. This results in a positive correlation between the land–atmosphere coupling strength and soil moisture anomalies over areas with dry climate and a negative correlation over areas with wet climate.
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de Vrese, Philipp, and Stefan Hagemann. "Explicit Representation of Spatial Subgrid-Scale Heterogeneity in an ESM." Journal of Hydrometeorology 17, no. 5 (April 19, 2016): 1357–71. http://dx.doi.org/10.1175/jhm-d-15-0080.1.
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Abstract In present-day Earth system models, the coupling of land surface and atmosphere is based on simplistic assumptions. Often the heterogeneous land surface is represented by a set of effective parameters valid for an entire model grid box. Other models assume that the surface fluxes become horizontally homogeneous at the lowest atmospheric model level. For heterogeneity above a certain horizontal length scale this is not the case, resulting in spatial subgrid-scale variability in the fluxes and in the state of the atmosphere. The Max Planck Institute for Meteorology’s Earth System Model is used with three different coupling schemes to assess the importance of the representation of spatial heterogeneity at the land surface as well as within the atmosphere. Simulations show that the land surface–atmosphere coupling distinctly influences the simulated near-surface processes with respect to different land-cover types. The representation of heterogeneity also has a distinct impact on the simulated gridbox mean state and fluxes in a large fraction of land surface.
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Materia, Stefano, Andrea Borrelli, Alessio Bellucci, Andrea Alessandri, Pierluigi Di Pietro, Panagiotis Athanasiadis, Antonio Navarra, and Silvio Gualdi. "Impact of Atmosphere and Land Surface Initial Conditions on Seasonal Forecasts of Global Surface Temperature." Journal of Climate 27, no. 24 (December 10, 2014): 9253–71. http://dx.doi.org/10.1175/jcli-d-14-00163.1.
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Abstract The impact of land surface and atmosphere initialization on the forecast skill of a seasonal prediction system is investigated, and an effort to disentangle the role played by the individual components to the global predictability is done, via a hierarchy of seasonal forecast experiments performed under different initialization strategies. A realistic atmospheric initial state allows an improved equilibrium between the ocean and overlying atmosphere, increasing the model predictive skill in the ocean. In fact, in regions characterized by strong air–sea coupling, the atmosphere initial condition affects forecast skill for several months. In particular, the ENSO region, eastern tropical Atlantic, and North Pacific benefit significantly from the atmosphere initialization. On the mainland, the effect of atmospheric initial conditions is detected in the early phase of the forecast, while the quality of land surface initialization affects forecast skill in the following seasons. Winter forecasts in the high-latitude plains benefit from the snow initialization, while the impact of soil moisture initial state is particularly effective in the Mediterranean region and central Asia. However, the initialization strategy based on the full value technique may not be the best choice for land surface, since soil moisture is a strongly model-dependent variable: in fact, initialization through land surface reanalysis does not systematically guarantee a skill improvement. Nonetheless, using a different initialization strategy for land, as opposed to atmosphere and ocean, may generate inconsistencies. Overall, the introduction of a realistic initialization for land and atmosphere substantially increases skill and accuracy. However, further developments in the procedure for land surface initialization are required for more accurate seasonal forecasts.
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Avissar, Roni. "Scaling of land-atmosphere interactions: An atmospheric modelling perspective." Hydrological Processes 9, no. 5-6 (June 1995): 679–95. http://dx.doi.org/10.1002/hyp.3360090514.
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Donohoe, Aaron, and David S. Battisti. "The Seasonal Cycle of Atmospheric Heating and Temperature." Journal of Climate 26, no. 14 (July 12, 2013): 4962–80. http://dx.doi.org/10.1175/jcli-d-12-00713.1.
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Abstract The seasonal cycle of the heating of the atmosphere is divided into a component due to direct solar absorption in the atmosphere and a component due to the flux of energy from the surface to the atmosphere via latent, sensible, and radiative heat fluxes. Both observations and coupled climate models are analyzed. The vast majority of the seasonal heating of the northern extratropics (78% in the observations and 67% in the model average) is due to atmospheric shortwave absorption. In the southern extratropics, the seasonal heating of the atmosphere is entirely due to atmospheric shortwave absorption in both the observations and the models, and the surface heat flux opposes the seasonal heating of the atmosphere. The seasonal cycle of atmospheric temperature is surface amplified in the northern extratropics and nearly barotropic in the Southern Hemisphere; in both cases, the vertical profile of temperature reflects the source of the seasonal heating. In the northern extratropics, the seasonal cycle of atmospheric heating over land differs markedly from that over the ocean. Over the land, the surface energy fluxes complement the driving absorbed shortwave flux; over the ocean, they oppose the absorbed shortwave flux. This gives rise to large seasonal differences in the temperature of the atmosphere over land and ocean. Downgradient temperature advection by the mean westerly winds damps the seasonal cycle of heating of the atmosphere over the land and amplifies it over the ocean. The seasonal cycle in the zonal energy transport is 4.1 PW. Finally, the authors examine the change in the seasonal cycle of atmospheric heating in 11 models from phase 3 of the Coupled Model Intercomparison Project (CMIP3) due to a doubling of atmospheric carbon dioxide from preindustrial concentrations. The seasonal heating of the troposphere is everywhere enhanced by increased shortwave absorption by water vapor; it is reduced where sea ice has been replaced by ocean, which increases the effective heat storage reservoir of the climate system and thereby reduces the seasonal magnitude of energy fluxes between the surface and the atmosphere. As a result, the seasonal amplitude of temperature increases in the upper troposphere (where atmospheric shortwave absorption increases) and decreases at the surface (where the ice melts).
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Koster, Randal D., Yehui Chang, and Siegfried D. Schubert. "A Mechanism for Land–Atmosphere Feedback Involving Planetary Wave Structures." Journal of Climate 27, no. 24 (December 10, 2014): 9290–301. http://dx.doi.org/10.1175/jcli-d-14-00315.1.
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Abstract While the ability of land surface conditions to influence the atmosphere has been demonstrated in various modeling and observational studies, the precise mechanisms by which land–atmosphere feedback occurs are still largely unknown: particularly the mechanisms that allow land moisture state in one region to affect atmospheric conditions in another. Such remote impacts are examined here in the context of atmospheric general circulation model (AGCM) simulations, leading to the identification of one potential mechanism: the phase locking and amplification of a planetary wave through the imposition of a spatial pattern of soil moisture at the land surface. This mechanism, shown here to be relevant in the AGCM, apparently also operates in nature, as suggested by supporting evidence found in reanalysis data.
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Liu, Yuqiong, Hoshin V. Gupta, Soroosh Sorooshian, Luis A. Bastidas, and William J. Shuttleworth. "Constraining Land Surface and Atmospheric Parameters of a Locally Coupled Model Using Observational Data." Journal of Hydrometeorology 6, no. 2 (April 1, 2005): 156–72. http://dx.doi.org/10.1175/jhm407.1.
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Abstract In coupled land surface–atmosphere modeling, the possibility and benefits of constraining model parameters using observational data bear investigation. Using the locally coupled NCAR Single-column Community Climate Model (NCAR SCCM), this study demonstrates some feasible, effective approaches to constrain parameter estimates for coupled land–atmosphere models and explores the effects of including both land surface and atmospheric parameters and fluxes/variables in the parameter estimation process, as well as the value of conducting the process in a stepwise manner. The results indicate that the use of both land surface and atmospheric flux variables to construct error criteria can lead to better-constrained parameter sets. The model with “optimal” parameters generally performs better than when a priori parameters are used, especially when some atmospheric parameters are included in the parameter estimation process. The overall conclusion is that, to achieve balanced, reasonable model performance on all variables, it is desirable to optimize both land surface and atmospheric parameters and use both land surface and atmospheric fluxes/variables for error criteria in the optimization process. The results also show that, for a coupled land–atmosphere model, there are potential advantages to using a stepwise procedure in which the land surface parameters are first identified in offline mode, after which the atmospheric parameters are determined in coupled mode. This stepwise scheme appears to provide comparable solutions to a fully coupled approach, but with considerably reduced computational time. The trade-off in the ability of a model to satisfactorily simulate different processes simultaneously, as observed in most multicriteria studies, is most evident for sensible heat and precipitation in this study for the NCAR SCCM.
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Huang, Meng, Po-Lun Ma, Nathaniel W. Chaney, Dalei Hao, Gautam Bisht, Megan D. Fowler, Vincent E. Larson, and L. Ruby Leung. "Representing surface heterogeneity in land–atmosphere coupling in E3SMv1 single-column model over ARM SGP during summertime." Geoscientific Model Development 15, no. 16 (August 29, 2022): 6371–84. http://dx.doi.org/10.5194/gmd-15-6371-2022.
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Abstract. The Earth's land surface features spatial and temporal heterogeneity over a wide range of scales below those resolved by current Earth system models (ESMs). State-of-the-art land and atmosphere models employ parameterizations to represent their subgrid heterogeneity, but the land–atmosphere coupling in ESMs typically operates on the grid scale. Communicating the information on the land surface heterogeneity with the overlying atmospheric boundary layer (ABL) remains a challenge in modeling land–atmosphere interactions. In order to account for the subgrid-scale heterogeneity in land–atmosphere coupling, we implement a new coupling scheme in the Energy Exascale Earth system model version 1 (E3SMv1) that uses adjusted surface variances and covariance of potential temperature and specific water content as the lower boundary condition for the atmosphere model. The new lower boundary condition accounts for both the variability of individual subgrid land surface patches and the inter-patch variability. The E3SMv1 single-column model (SCM) simulations over the Atmospheric Radiation Measurement (ARM) Southern Great Plain (SGP) site were performed to assess the impacts. We find that the new coupling parameterization increases the magnitude and diurnal cycle of the temperature variance and humidity variance in the lower ABL on non-precipitating days. The impacts are primarily attributed to subgrid inter-patch variability rather than the variability of individual patches. These effects extend vertically from the surface to several levels in the lower ABL on clear days. We also find that accounting for surface heterogeneity increases low cloud cover and liquid water path (LWP). These cloud changes are associated with the change in cloud regime indicated by the skewness of the probability density function (PDF) of the subgrid vertical velocity. In precipitating days, the inter-patch variability reduces significantly so that the impact of accounting for surface heterogeneity vanishes. These results highlight the importance of accounting for subgrid heterogeneity in land–atmosphere coupling in next-generation ESMs.
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Mohanty, UC, HaraPrasad Nayak, MR Mohanty, P. Sinha, and KK Osuri. "Role of land surface processes on Indian summer monsoon rainfall: Understanding and impact assessment." MAUSAM 74, no. 2 (March 29, 2023): 345–60. http://dx.doi.org/10.54302/mausam.v74i2.6199.
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Indian Summer Monsoon is a synoptic-scale atmospheric circulation system manifested by the boundary forcing from both continents and tropical oceans. Unlike oceans, the land surface processes are complex in nature due to the heterogeneities in land surface characteristics and its associated feedbacks, thereby constraining theaccurate representation of the land surface in NWP models. Thus, understanding the land-atmosphere interaction becomes increasingly crucial especially during the Indian summer monsoon season due to the underlying warm and moist surface layer conducive forevapotranspiration, thereby fueling land atmosphere coupling during the season. The representation of surface heterogeneity and variability are constrained due to lack of surface measurements which necessitate development of land surface analysis. The major aimof the present studyisthree-fold;firstly, understanding land surfaces processes associated with the monsoonal rainfall events, secondly, preparation of a state-of-art high-resolution land surface data over India, andfinally, impact assessment of high-resolution land surface initialization on simulation monsoonalrainfall events. This study has implications for developing improved prediction system associated with the Indian Summer Monsoon.
Indian Summer Monsoon is a synoptic-scale atmospheric circulation system manifested by the boundary forcing from both continents and tropical oceans. Unlike oceans, the land surface processes are complex in nature due to the heterogeneities in land surface characteristics and its associated feedbacks, thereby constraining theaccurate representation of the land surface in NWP models. Thus, understanding the land-atmosphere interaction becomes increasingly crucial especially during the Indian summer monsoon season due to the underlying warm and moist surface layer conducive forevapotranspiration, thereby fueling land atmosphere coupling during the season. The representation of surface heterogeneity and variability are constrained due to lack of surface measurements which necessitate development of land surface analysis. The major aimof the present studyisthree-fold;firstly, understanding land surfaces processes associated with the monsoonal rainfall events, secondly, preparation of a state-of-art high-resolution land surface data over India, andfinally, impact assessment of high-resolution land surface initialization on simulation monsoonalrainfall events. This study has implications for developing improved prediction system associated with the Indian Summer Monsoon.
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Dirmeyer, Paul A., Randal D. Koster, and Zhichang Guo. "Do Global Models Properly Represent the Feedback between Land and Atmosphere?" Journal of Hydrometeorology 7, no. 6 (December 1, 2006): 1177–98. http://dx.doi.org/10.1175/jhm532.1.
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Abstract The Global Energy and Water Cycle Experiment/Climate Variability and Predictability (GEWEX/CLIVAR) Global Land–Atmosphere Coupling Experiment (GLACE) has provided an estimate of the global distribution of land–atmosphere coupling strength during boreal summer based on the results from a dozen weather and climate models. However, there is a great deal of variation among models, attributable to a range of sensitivities in the simulation of both the terrestrial and atmospheric branches of the hydrologic cycle. It remains an open question whether any of the models, or the multimodel estimate, reflects the actual pattern and strength of land–atmosphere coupling in the earth’s hydrologic cycle. The authors attempt to diagnose this by examining the local covariability of key atmospheric and land surface variables both in models and in those few locations where comparable, relatively complete, long-term measurements exist. Most models do not encompass well the observed relationships between surface and atmospheric state variables and fluxes, suggesting that these models do not represent land–atmosphere coupling correctly. Specifically, there is evidence that systematic biases in near-surface temperature and humidity among all models may contribute to incorrect surface flux sensitivities. However, the multimodel mean generally validates better than most or all of the individual models. Regional precipitation behavior (lagged autocorrelation and predisposition toward maintenance of extremes) between models and observations is also compared. Again a great deal of variation is found among the participating models, but remarkably accurate behavior of the multimodel mean.
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Suleiman, Ayman, and Richard Crago. "Analytical Land–Atmosphere Radiometer Model." Journal of Applied Meteorology 41, no. 2 (February 2002): 177–87. http://dx.doi.org/10.1175/1520-0450(2002)041<0177:alarm>2.0.co;2.
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Tuinenburg, O. A., R. W. A. Hutjes, C. M. J. Jacobs, and P. Kabat. "Diagnosis of Local Land–Atmosphere Feedbacks in India." Journal of Climate 24, no. 1 (January 1, 2011): 251–66. http://dx.doi.org/10.1175/2010jcli3779.1.
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Abstract Following the convective triggering potential (CTP)–humidity index (HIlow) framework by Findell and Eltahir, the sensitivity of atmospheric convection to soil moisture conditions is studied for India. Using the same slab model as Findell and Eltahir, atmospheric conditions in which the land surface state affects convective precipitation are determined. For India, CTP–HIlow thresholds for land surface–atmosphere feedbacks are shown to be slightly different than for the United States. Using atmospheric sounding data from 1975 to 2009, the seasonal and spatial variations in feedback strength have been assessed. The patterns of feedback strengths thus obtained have been analyzed in relation to the monsoon timing. During the monsoon season, atmospheric conditions where soil moisture positively influences precipitation are present about 25% of the time. During onset and retreat of the monsoon, the south and east of India show more potential for feedbacks than the north. These feedbacks suggest that large-scale irrigation in the south and east may increase local precipitation. To test this, precipitation data (from 1960 to 2004) for the period about three weeks just before the monsoon onset date have been studied. A positive trend in the precipitation just before the monsoon onset is found for irrigated stations. It is shown that for irrigated stations, the trend in the precipitation just before the monsoon onset is positive for the period 1960–2004. For nonirrigated stations, there is no such upward trend in this period. The precipitation trend for irrigated areas might be due to a positive trend in the extent of irrigated areas, with land–atmosphere feedbacks inducing increased precipitation.
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King, A. W., R. J. Andres, K. J. Davis, M. Hafer, D. J. Hayes, D. N. Huntzinger, B. de Jong, et al. "North America's net terrestrial carbon exchange with the atmosphere 1990–2009." Biogeosciences Discussions 11, no. 7 (July 17, 2014): 11027–59. http://dx.doi.org/10.5194/bgd-11-11027-2014.
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Abstract. Scientific understanding of the global carbon cycle is required for developing national and international policy to mitigate fossil-fuel CO2 emissions by managing terrestrial carbon uptake. Toward that understanding and as a contribution to the REgional Carbon Cycle Assessment and Processes (RECCAP) project, this paper provides a synthesis of net land–atmosphere CO2 exchange for North America over the period (1990–2009). This synthesis is based on results from three different methods: atmospheric inversion, inventory-based methods and terrestrial biosphere modeling. All methods indicate that the North America land surface was a sink for atmospheric CO2, with a net transfer from atmosphere to land. Estimates ranged from −890 to −280 Tg C yr−1, where the atmospheric inversion estimate forms the lower bound of that range (a larger land-sink) and the inventory-based estimate the upper (a smaller land sink). Integrating across estimates, "best" estimates (i.e., measures of central tendency) are −472 ± 281 Tg C yr−1 based on the mean and standard deviation of the distribution and −360 Tg C yr−1 (with an interquartile range of −496 to −337) based on the median. Considering both the fossil-fuel emissions source and the land sink, our analysis shows that North America was, however, a net contributor to the growth of CO2 in the atmosphere in the late 20th and early 21st century. The continent's CO2 source to sink ratio for this time period was likely in the range of 4 : 1 to 3 : 1.
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Dirmeyer, Paul A., C. Adam Schlosser, and Kaye L. Brubaker. "Precipitation, Recycling, and Land Memory: An Integrated Analysis." Journal of Hydrometeorology 10, no. 1 (February 1, 2009): 278–88. http://dx.doi.org/10.1175/2008jhm1016.1.
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Abstract A synthesis of several approaches to quantifying land–atmosphere interactions is presented. These approaches use data from observations or atmospheric reanalyses applied to atmospheric tracer models and stand-alone land surface schemes. None of these approaches relies on the results of general circulation model simulations. A high degree of correlation is found among these independent approaches, and constructed here is a composite assessment of global land–atmosphere feedback strength as a function of season. The composite combines the characteristics of persistence of soil moisture anomalies, strong soil moisture regulation of evaporation rates, and reinforcement of water cycle anomalies through recycling. The regions and seasons that have a strong composite signal predominate in both summer and winter monsoon regions in the period after the rainy season wanes. However, there are exceptions to this pattern, most notably over the Great Plains of North America and the Pampas/Pantanal of South America, where there are signs of land–atmosphere feedback throughout most of the year. Soil moisture memory in many of these regions is long enough to suggest that real-time monitoring and accurate initialization of the land surface in forecast models could lead to improvements in medium-range weather to subseasonal climate forecasts.
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Baker, Jessica C. A., Dayana Castilho de Souza, Paulo Y. Kubota, Wolfgang Buermann, Caio A. S. Coelho, Martin B. Andrews, Manuel Gloor, Luis Garcia-Carreras, Silvio N. Figueroa, and Dominick V. Spracklen. "An Assessment of Land–Atmosphere Interactions over South America Using Satellites, Reanalysis, and Two Global Climate Models." Journal of Hydrometeorology 22, no. 4 (April 2021): 905–22. http://dx.doi.org/10.1175/jhm-d-20-0132.1.
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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.
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Chen, Haishan, Bo Yu, Botao Zhou, Wanxin Zhang, and Jie Zhang. "Role of Local Atmospheric Forcing and Land–Atmosphere Interaction in Recent Land Surface Warming in the Midlatitudes over East Asia." Journal of Climate 33, no. 6 (March 15, 2020): 2295–309. http://dx.doi.org/10.1175/jcli-d-18-0856.1.
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AbstractSignificant summer land surface warming has been observed in the middle latitudes over East Asia, especially after the mid-1990s, which has evidently affected the East Asian weather and climate. Using multisource observations and reanalysis data during 1979–2013, this study explores the possible reasons for recent land surface warming over this region by considering atmospheric forcing and regional land–atmosphere interaction related to extratropical cyclones (ECs). Results show that there is a close relationship between land surface warming and weakened ECs over East Asia. Recent land surface warming was attributed to local atmospheric forcing and feedback of land–atmosphere interaction associated with weakened ECs. The abnormal large-scale circulation associated with anomalous ECs produced evident dynamic forcing on the land surface. Weakened ECs are usually accompanied by an abnormal high pressure system and anticyclonic circulation around Lake Baikal, which benefit the intensification of anomalous southerly wind in the rear of the anomalous anticyclone, leading to positive temperature advection and temperature increase over East Asia. Meanwhile, the anomalous adiabatic warming caused by abnormal descending motion associated with the anticyclonic anomaly also contributes to local warming. The feedback of local land–atmosphere interaction plays an important role in land surface warming. Weakened ECs increase both incident solar radiation and precipitation. The increased precipitation reduces the soil moisture and in turn weakens the surface evaporation and local cooling effect, resulting in land surface warming. Our findings are helpful for better understanding the mechanisms responsible for recent summer land surface warming over East Asia as well as its climatic effects.
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Dirmeyer, Paul A., and Subhadeep Halder. "Application of the Land–Atmosphere Coupling Paradigm to the Operational Coupled Forecast System, Version 2 (CFSv2)." Journal of Hydrometeorology 18, no. 1 (December 21, 2016): 85–108. http://dx.doi.org/10.1175/jhm-d-16-0064.1.
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Abstract Retrospective forecasts from CFSv2 are evaluated in terms of three elements of land–atmosphere coupling at subseasonal to seasonal time scales: sensitivity of the atmosphere to variations in land surface states, the magnitude of variability of land states and fluxes, and the memory or persistence of land surface anomalies. The Northern Hemisphere spring and summer seasons are considered for the period 1982–2009. Ensembles are constructed from all available pairings of initial land and atmosphere/ocean states taken from the Climate Forecast System Reanalysis at the start of April, May, and June among the 28 years, so that the effect of initial land states on the evolving forecasts can be assessed. Finally, improvement and continuance of forecast skill derived from accurate land surface initialization is related to the three coupling elements. It is found that soil moisture memory is the most broadly important element for significant improvement of realistic land initialization on forecast skill. However, coupling strength manifested through the elements of sensitivity and variability are necessary to realize the potential predictability provided by memory of initial land surface anomalies. Even though there is clear responsiveness of surface heat fluxes, near-surface temperature, humidity, and daytime boundary layer development to variations in soil moisture over much of the globe, precipitation in CFSv2 is unresponsive. Failure to realize potential predictability from land surface states could be due to unfavorable atmospheric stability or circulation states; poor quality of what is considered realistic soil moisture analyses; and errors in the land surface model, atmospheric model, or their coupled interaction.
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Hacker, Joshua P. "Spatial and Temporal Scales of Boundary Layer Wind Predictability in Response to Small-Amplitude Land Surface Uncertainty." Journal of the Atmospheric Sciences 67, no. 1 (January 1, 2010): 217–33. http://dx.doi.org/10.1175/2009jas3162.1.
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Abstract Predictability experiments with the Weather Research and Forecast (WRF) model as a proxy for the atmosphere are analyzed to quantify the spatial and temporal scales of boundary layer wind response to land surface perturbations. Soil moisture is chosen as the land surface variable subject to uncertainty because the atmosphere is known to be sensitive to its state. A range of experiments with spatially correlated, small-amplitude perturbations to soil moisture leads to results that show the dependence of predictability on atmospheric conditions. The primary conclusions are as follows: 1) atmospheric conditions, including static instability and the presence of deep convection, determine whether large errors and local loss of predictability are possible in response to soil moisture errors; 2) the scale of soil moisture uncertainty determines scales of PBL wind predictability when the atmosphere is resistant to upscale error transfer, but when the atmosphere is sensitive the scale and magnitude of soil moisture uncertainty are not important after a few hours; and 3) nonlinear error growth is present whether or not the atmosphere is relatively sensitive to soil moisture uncertainty, leading to doubling times of minutes to hours for finite-sized perturbations. Similar results could be expected from other land surface variables or parameters that exert time-dependent forcing on the atmosphere that is similar in magnitude and scale to that of soil moisture.
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Bagley, Justin E., Ankur R. Desai, Paul C. West, and Jonathan A. Foley. "A Simple, Minimal Parameter Model for Predicting the Influence of Changing Land Cover on the Land–Atmosphere System+." Earth Interactions 15, no. 29 (October 1, 2011): 1–32. http://dx.doi.org/10.1175/2011ei394.1.
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Abstract The impacts of changing land cover on the soil–vegetation–atmosphere system are numerous. With the fraction of land used for farming and grazing expected to increase, extensive alterations to land cover such as replacing forests with cropland will continue. Therefore, quantifying the impact of global land-cover scenarios on the biosphere is critical. The Predicting Ecosystem Goods and Services Using Scenarios boundary layer (PegBL) model is a new global soil–vegetation–boundary layer model designed to quantify these impacts and act as a complementary tool to computationally expensive general circulation models and large-eddy simulations. PegBL provides high spatial resolution and inexpensive first-order estimates of land-cover change on the surface energy balance and atmospheric boundary layer with limited input requirements. The model uses a climatological-data-driven land surface model that contains only the physics necessary to accurately reproduce observed seasonal cycles of fluxes and state variables for natural and agricultural ecosystems. A bulk boundary layer model was coupled to the land model to estimate the impacts of changing land cover on the lower atmosphere. The model most realistically simulated surface–atmosphere dynamics and impacts of land-cover change at tropical rain forest and northern boreal forest sites. Further, simple indices to measure the potential impact of land-cover change on boundary layer climate were defined and shown to be dependent on boundary layer dynamics and geographically similar to results from previous studies, which highlighted the impacts of land-cover change on the atmosphere in the tropics and boreal forest.
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Seo, Eunkyo, and Paul A. Dirmeyer. "Understanding the diurnal cycle of land–atmosphere interactions from flux site observations." Hydrology and Earth System Sciences 26, no. 20 (October 28, 2022): 5411–29. http://dx.doi.org/10.5194/hess-26-5411-2022.
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Abstract. Land–atmosphere interactions have been investigated at daily or longer timescales due to limited data availability and large errors for measuring high-frequency variations. Yet coupling at the subdaily timescale is characterized by the diurnal cycle of incoming solar radiation and surface fluxes. Based on flux tower observations, this study investigates the climatology of observed land–atmosphere interactions on subdaily timescales during the warm season. Process-based multivariate metrics are employed to quantitatively measure segmented coupling processes, and mixing diagrams are adopted to demonstrate the integrative moist and thermal energy budget evolution in the atmospheric mixed layer. The land, atmosphere, and combined couplings for the entire daily mean, midday, and midnight periods show different situations to which surface latent and sensible heat fluxes are relevant, and they also reveal the climate sensitivity to soil moisture and surface air temperature. The 24 h coevolution of the moist and thermal energy within the boundary layer traces a particular path on mixing diagrams, exhibiting different degrees of asymmetry (time shifts) in water- and energy-limited locations. Water- and energy-limited processes also show opposing long tails of low humidity during the daytime and nighttime, related to the impact on land and atmospheric couplings of latent heat flux and other diabatic processes like radiative cooling. This study illustrates the necessity of considering the entire diurnal cycle to understand land–atmosphere coupling processes comprehensively in observations and models.
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Martínez-de la Torre, Alberto, Eleanor Blyth, and Emma Robinson. "Evaluation of Drydown Processes in Global Land Surface and Hydrological Models Using Flux Tower Evapotranspiration." Water 11, no. 2 (February 20, 2019): 356. http://dx.doi.org/10.3390/w11020356.
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A key aspect of the land surface response to the atmosphere is how quickly it dries after a rainfall event. It is key because it will determine the intensity and speed of the propagation of drought and also affects the atmospheric state through changes in the surface heat exchanges. Here, we test the theory that this response can be studied as an inherent property of the land surface that is unchanging over time unless the above- and below-ground structures change. This is important as a drydown metric can be used to evaluate a landscape and its response to atmospheric drivers in models used in coupled land–atmosphere mode when the forcing is often not commensurate with the actual atmosphere. We explore whether the speed of drying of a land unit can be quantified and how this can be used to evaluate models. We use the most direct observation of drying: the rate of change of evapotranspiration after a rainfall event using eddy-covariance observations, or commonly referred to as flux tower data. We analyse the data and find that the drydown timescale is characteristic of different land cover types, then we use that to evaluate a suite of global hydrological and land surface models. We show that, at the site level, the data suggest that evapotranspiration decay timescales are longer for trees than for grasslands. The studied model’s accuracy to capture the site drydown timescales depends on the specific model, the site, and the vegetation cover representation. A more robust metric is obtained by grouping the modeled data by vegetation type and, using this, we find that land surface models capture the characteristic timescale difference between trees and grasslands, found using flux data, better than large-scale hydrological models. We thus conclude that the drydown metric has value in understanding land–atmosphere interactions and model evaluation.
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Song, Jiyun, and Zhi-Hua Wang. "Evaluating the impact of built environment characteristics on urban boundary layer dynamics using an advanced stochastic approach." Atmospheric Chemistry and Physics 16, no. 10 (May 24, 2016): 6285–301. http://dx.doi.org/10.5194/acp-16-6285-2016.
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Abstract. Urban land–atmosphere interactions can be captured by numerical modeling framework with coupled land surface and atmospheric processes, while the model performance depends largely on accurate input parameters. In this study, we use an advanced stochastic approach to quantify parameter uncertainty and model sensitivity of a coupled numerical framework for urban land–atmosphere interactions. It is found that the development of urban boundary layer is highly sensitive to surface characteristics of built terrains. Changes of both urban land use and geometry impose significant impact on the overlying urban boundary layer dynamics through modification on bottom boundary conditions, i.e., by altering surface energy partitioning and surface aerodynamic resistance, respectively. Hydrothermal properties of conventional and green roofs have different impacts on atmospheric dynamics due to different surface energy partitioning mechanisms. Urban geometry (represented by the canyon aspect ratio), however, has a significant nonlinear impact on boundary layer structure and temperature. Besides, managing rooftop roughness provides an alternative option to change the boundary layer thermal state through modification of the vertical turbulent transport. The sensitivity analysis deepens our insight into the fundamental physics of urban land–atmosphere interactions and provides useful guidance for urban planning under challenges of changing climate and continuous global urbanization.
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Pereira, Fábio Farias, and Cintia Bertacchi Uvo. "Simulating Weather Events with a Linked Atmosphere-Hydrology Model." Revista Brasileira de Meteorologia 35, no. 4 (December 2020): 703–15. http://dx.doi.org/10.1590/0102-77863540077.
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Abstract This study aims at assess the importance of a conceptual representation of hydrological processes when modelling atmospheric circulation. It compares results from a regional atmospheric model that interprets land surface hydrological processes based on parameterizations with results from a two-way coupled atmosphere-hydrological model that has a process-based approach to the land surface hydrological cycle. These numerical models were applied to a region covering the Rio Grande basin, Brazil. The same input data, initial and boundary conditions were used on a 31-day simulation period. Results obtained from these simulations were compared to visible satellite images and gauging rainfall stations for three case studies that included a cold front, deep convective clouds and stable atmospheric conditions. Both models could reproduce regional patterns of air circulation and rainfall influenced by the orography of the basin. However, atmospheric processes driven by spatial gradients of land surface temperature or local surface heating were spatially better represented by the atmospheric-hydrological modelling system rather than the regional atmospheric model. Since areas characterized by spatial gradients of land surface temperature and local surface heating were closely associated with convergent air flows near land surface and strong vertical motion in the mid troposphere, this finding enhanced the role of a good representation of land surface hydrological processes for a better modelling the atmospheric dynamics.
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Massad, Raia Silvia, Juliette Lathière, Susanna Strada, Mathieu Perrin, Erwan Personne, Marc Stéfanon, Patrick Stella, Sophie Szopa, and Nathalie de Noblet-Ducoudré. "Reviews and syntheses: influences of landscape structure and land uses on local to regional climate and air quality." Biogeosciences 16, no. 11 (June 11, 2019): 2369–408. http://dx.doi.org/10.5194/bg-16-2369-2019.
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Abstract. The atmosphere and the land surface interact in multiple ways, for instance through the radiative-energy balance, the water cycle or the emission and deposition of natural and anthropogenic compounds. By modifying the land surface, land use and land cover changes (LULCCs) and land management changes (LMCs) alter the physical, chemical, and biological processes of the biosphere and therefore all land–atmosphere interactions, from local to global scales. Through socio-economic drivers and regulatory policies adopted at different levels (local, regional, national, or supranational), human activities strongly interfere in the land–atmosphere interactions, and those activities lead to a patchwork of natural, semi-natural, agricultural, urban, and semi-urban areas. In this context, urban and peri-urban areas, which have a high population density, are of particular attention since land transformation can lead to important environmental impacts and affect the health and life of millions of people. The objectives of this review are to synthesize the existing experimental and modelling works that investigate physical, chemical, and/or biogeochemical interactions between land surfaces and the atmosphere, therefore potentially impacting local/regional climate and air quality, mainly in urban or peri-urban landscapes at regional and local scales. The conclusions we draw from our synthesis are the following. (1) The adequate temporal and spatial description of land use and land management practices (e.g. areas concerned, type of crops, whether or not they are irrigated, quantity of fertilizers used and actual seasonality of application) necessary for including the effects of LMC in global and even more in regional climate models is inexistent (or very poor). Not taking into account these characteristics may bias the regional projections used for impact studies. (2) Land–atmosphere interactions are often specific to the case study analysed; therefore, one can hardly propose general solutions or recommendations. (3) Adaptation strategies, proposed after climatic impacts on the targeted resource have been derived, are often biased as they do not account for feedbacks on local/regional climate. (4) There is space for considering atmospheric chemistry, through land–atmosphere interactions, as a factor for land management, helping to maintain air quality and supporting ecosystem functioning. (5) There is a lack of an integrated tool, which includes the many different processes of importance in an operational model, to test different land use or land management scenarios at the scale of a territory.
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Prior, Elizabeth M., Gretchen R. Miller, and Kelly Brumbelow. "Topographic and Landcover Influence on Lower Atmospheric Profiles Measured by Small Unoccupied Aerial Systems (sUAS)." Drones 5, no. 3 (August 26, 2021): 82. http://dx.doi.org/10.3390/drones5030082.
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Small unoccupied aerial systems (sUASs) are increasingly being used for field data collection and remote sensing purposes. Their ease of use, ability to carry sensors, low cost, and precise maneuverability and navigation make them a versatile tool for a field researcher. Procedures and instrumentation for sUASs are largely undefined, especially for atmospheric and hydrologic applications. The sUAS’s ability to collect atmospheric data for characterizing land–atmosphere interactions was examined at three distinct locations: Costa Rican rainforest, mountainous terrain in Georgia, USA, and land surfaces surrounding a lake in Florida, USA. This study aims to give further insight on rapid, sub-hourly changes in the planetary boundary layer and how land development alters land–atmosphere interactions. The methodology of using an sUAS for land–atmospheric remote sensing and data collection was developed and refined by considering sUAS wind downdraft influence and executing systematic flight patterns throughout the day. The sUAS was successful in gathering temperature and dew point data, including rapid variations due to changing weather conditions, at high spatial and temporal resolution over various land types, including water, forest, mountainous terrain, agriculture, and impermeable human-made surfaces. The procedure produced reliably consistent vertical profiles over small domains in space and time, validating the general approach. These findings suggest a healthy ability to diagnose land surface atmospheric interactions that influence the dynamic nature of the near-surface boundary layer.
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Martín Belda, David, Peter Anthoni, David Wårlind, Stefan Olin, Guy Schurgers, Jing Tang, Benjamin Smith, and Almut Arneth. "LPJ-GUESS/LSMv1.0: a next-generation land surface model with high ecological realism." Geoscientific Model Development 15, no. 17 (September 6, 2022): 6709–45. http://dx.doi.org/10.5194/gmd-15-6709-2022.
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Abstract. Land biosphere processes are of central importance to the climate system. Specifically, ecosystems interact with the atmosphere through a variety of feedback loops that modulate energy, water, and CO2 fluxes between the land surface and the atmosphere across a wide range of temporal and spatial scales. Human land use and land cover modification add a further level of complexity to land–atmosphere interactions. Dynamic global vegetation models (DGVMs) attempt to capture land ecosystem processes and are increasingly incorporated into Earth system models (ESMs), which makes it possible to study the coupled dynamics of the land biosphere and the climate. In this work we describe a number of modifications to the LPJ-GUESS DGVM, aimed at enabling direct integration into an ESM. These include energy balance closure, the introduction of a sub-daily time step, a new radiative transfer scheme, and improved soil physics. The implemented modifications allow the model (LPJ-GUESS/LSM) to simulate the diurnal exchange of energy, water, and CO2 between the land ecosystem and the atmosphere and thus provide surface boundary conditions to an atmospheric model over land. A site-based evaluation against FLUXNET2015 data shows reasonable agreement between observed and modelled sensible and latent heat fluxes. Differences in predicted ecosystem function between standard LPJ-GUESS and LPJ-GUESS/LSM vary across land cover types. We find that the emerging ecosystem composition and carbon fluxes are sensitive to both the choice of stomatal conductance model and the response of plant water uptake to soil moisture. The new implementation described in this work lays the foundation for using the well-established LPJ-GUESS DGVM as an alternative land surface model (LSM) in coupled land–biosphere–climate studies, where an accurate representation of ecosystem processes is essential.
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Dirmeyer, Paul A., Yan Jin, Bohar Singh, and Xiaoqin Yan. "Trends in Land–Atmosphere Interactions from CMIP5 Simulations." Journal of Hydrometeorology 14, no. 3 (June 1, 2013): 829–49. http://dx.doi.org/10.1175/jhm-d-12-0107.1.
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Abstract Data from 15 models of phase 5 of the Coupled Model Intercomparison Project (CMIP5) for preindustrial, historical, and future climate change experiments are examined for consensus changes in land surface variables, fluxes, and metrics relevant to land–atmosphere interactions. Consensus changes in soil moisture and latent heat fluxes for past-to-present and present-to-future periods are consistent with CMIP3 simulations, showing a general drying trend over land (less soil moisture, less evaporation) over most of the globe, with the notable exception of high northern latitudes during winter. Sensible heat flux and net radiation declined from preindustrial times to current conditions according to the multimodel consensus, mainly due to increasing aerosols, but that trend reverses abruptly in the future projection. No broad trends are found in soil moisture memory except for reductions during boreal winter associated with high-latitude warming and diminution of frozen soils. Land–atmosphere coupling is projected to increase in the future across most of the globe, meaning a greater control by soil moisture variations on surface fluxes and the lower troposphere. There is also a strong consensus for a deepening atmospheric boundary layer and diminished gradients across the entrainment zone at the top of the boundary layer, indicating that the land surface feedback on the atmosphere should become stronger both in absolute terms and relative to the influence of the conditions of the free atmosphere. Coupled with the trend toward greater hydrologic extremes such as severe droughts, the land surface seems likely to play a greater role in amplifying both extremes and trends in climate on subseasonal and longer time scales.
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Xu, L., R. D. Pyles, K. T. Paw U, S. H. Chen, and E. Monier. "Coupling the high-complexity land surface model ACASA to the mesoscale model WRF." Geoscientific Model Development 7, no. 6 (December 10, 2014): 2917–32. http://dx.doi.org/10.5194/gmd-7-2917-2014.
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Abstract. In this study, the Weather Research and Forecasting (WRF) model is coupled with the Advanced Canopy–Atmosphere–Soil Algorithm (ACASA), a high-complexity land surface model. Although WRF is a state-of-the-art regional atmospheric model with high spatial and temporal resolutions, the land surface schemes available in WRF, such as the popular NOAH model, are simple and lack the capability of representing the canopy structure. In contrast, ACASA is a complex multilayer land surface model with interactive canopy physiology and high-order turbulence closure that allows for an accurate representation of heat, momentum, water, and carbon dioxide fluxes between the land surface and the atmosphere. It allows for microenvironmental variables such as surface air temperature, wind speed, humidity, and carbon dioxide concentration to vary vertically within and above the canopy. Surface meteorological conditions, including air temperature, dew point temperature, and relative humidity, simulated by WRF-ACASA and WRF-NOAH are compared and evaluated with observations from over 700 meteorological stations in California. Results show that the increase in complexity in the WRF-ACASA model not only maintains model accuracy but also properly accounts for the dominant biological and physical processes describing ecosystem–atmosphere interactions that are scientifically valuable. The different complexities of physical and physiological processes in the WRF-ACASA and WRF-NOAH models also highlight the impact of different land surface models on atmospheric and surface conditions.
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Santanello, Joseph A., Paul A. Dirmeyer, Craig R. Ferguson, Kirsten L. Findell, Ahmed B. Tawfik, Alexis Berg, Michael Ek, et al. "Land–Atmosphere Interactions: The LoCo Perspective." Bulletin of the American Meteorological Society 99, no. 6 (June 2018): 1253–72. http://dx.doi.org/10.1175/bams-d-17-0001.1.
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AbstractLand–atmosphere (L-A) interactions are a main driver of Earth’s surface water and energy budgets; as such, they modulate near-surface climate, including clouds and precipitation, and can influence the persistence of extremes such as drought. Despite their importance, the representation of L-A interactions in weather and climate models remains poorly constrained, as they involve a complex set of processes that are difficult to observe in nature. In addition, a complete understanding of L-A processes requires interdisciplinary expertise and approaches that transcend traditional research paradigms and communities. To address these issues, the international Global Energy and Water Exchanges project (GEWEX) Global Land–Atmosphere System Study (GLASS) panel has supported “L-A coupling” as one of its core themes for well over a decade. Under this initiative, several successful land surface and global climate modeling projects have identified hot spots of L-A coupling and helped quantify the role of land surface states in weather and climate predictability. GLASS formed the Local Land–Atmosphere Coupling (LoCo) project and working group to examine L-A interactions at the process level, focusing on understanding and quantifying these processes in nature and evaluating them in models. LoCo has produced an array of L-A coupling metrics for different applications and scales and has motivated a growing number of young scientists from around the world. This article provides an overview of the LoCo effort, including metric and model applications, along with scientific and programmatic developments and challenges.
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Hobeichi, Sanaa, Gab Abramowitz, and Jason Evans. "Conserving Land–Atmosphere Synthesis Suite (CLASS)." Journal of Climate 33, no. 5 (March 1, 2020): 1821–44. http://dx.doi.org/10.1175/jcli-d-19-0036.1.
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AbstractAccurate estimates of terrestrial water and energy cycle components are needed to better understand climate processes and improve models’ ability to simulate future change. Various observational estimates are available for the individual budget terms; however, these typically show inconsistencies when combined in a budget. In this work, a Conserving Land–Atmosphere Synthesis Suite (CLASS) of estimates of simultaneously balanced surface water and energy budget components is developed. Individual CLASS variable datasets, where possible, 1) combine a range of existing variable product estimates, and hence overcome the limitations of estimates from a single source; 2) are observationally constrained with in situ measurements; 3) have uncertainty estimates that are consistent with their agreement with in situ observations; and 4) are consistent with each other by being able to solve the water and energy budgets simultaneously. First, available datasets of a budget variable are merged by implementing a weighting method that accounts both for the ability of datasets to match in situ measurements and the error covariance between datasets. Then, the budget terms are adjusted by applying an objective variational data assimilation technique (DAT) that enforces the simultaneous closure of the surface water and energy budgets linked through the equivalence of evapotranspiration and latent heat. Comparing component estimates before and after applying the DAT against in situ measurements of energy fluxes and streamflow showed that modified estimates agree better with in situ observations across various metrics, but also revealed some inconsistencies between water budget terms in June over the higher latitudes. CLASS variable estimates are freely available via https://doi.org/10.25914/5c872258dc183.
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Hirsch, A. L., A. J. Pitman, and V. Haverd. "Evaluating Land–Atmosphere Coupling Using a Resistance Pathway Framework." Journal of Hydrometeorology 17, no. 10 (October 1, 2016): 2615–30. http://dx.doi.org/10.1175/jhm-d-15-0204.1.
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Abstract This paper presents a methodology for examining land–atmosphere coupling in a regional climate model by examining how the resistances to moisture transfer from the land to the atmosphere control the surface turbulent energy fluxes. Perturbations were applied individually to the aerodynamic resistance from the soil surface to the displacement height, the aerodynamic resistance from the displacement height to the reference level, the stomatal resistance, and the leaf boundary layer resistance. Only perturbations to the aerodynamic resistance from the soil surface to the displacement height systematically affected 2-m air temperature for the shrub and evergreen boreal forest plant functional types (PFTs). This was associated with this resistance systematically increasing the terrestrial and atmospheric components of the land–atmosphere coupling strength through changes in the partitioning of the surface energy balance. Perturbing the other resistances did contribute to changing the partitioning of the surface energy balance but did not lead to systematic changes in the 2-m air temperature. The results suggest that land–atmosphere coupling in the modeling system presented here acts mostly through the aerodynamic resistance from the soil surface to the displacement height, which is a function of both the friction velocity and vegetation height and cover. The results show that a resistance pathway framework can be used to examine how changes in the resistances affect the partitioning of the surface energy balance and how this subsequently influences surface climate through land–atmosphere coupling. Limitations in the present analysis include grid-scale rather than PFT-scale analysis, the exclusion of resistance dependencies, and the linearity assumption of how temperature responds to a resistance perturbation.
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Dirmeyer, Paul A., Liang Chen, Jiexia Wu, Chul-Su Shin, Bohua Huang, Benjamin A. Cash, Michael G. Bosilovich, et al. "Verification of Land–Atmosphere Coupling in Forecast Models, Reanalyses, and Land Surface Models Using Flux Site Observations." Journal of Hydrometeorology 19, no. 2 (February 1, 2018): 375–92. http://dx.doi.org/10.1175/jhm-d-17-0152.1.
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Abstract This study compares four model systems in three configurations (LSM, LSM + GCM, and reanalysis) with global flux tower observations to validate states, surface fluxes, and coupling indices between land and atmosphere. Models clearly underrepresent the feedback of surface fluxes on boundary layer properties (the atmospheric leg of land–atmosphere coupling) and may overrepresent the connection between soil moisture and surface fluxes (the terrestrial leg). Models generally underrepresent spatial and temporal variability relative to observations, which is at least partially an artifact of the differences in spatial scale between model grid boxes and flux tower footprints. All models bias high in near-surface humidity and downward shortwave radiation, struggle to represent precipitation accurately, and show serious problems in reproducing surface albedos. These errors create challenges for models to partition surface energy properly, and errors are traceable through the surface energy and water cycles. The spatial distribution of the amplitude and phase of annual cycles (first harmonic) are generally well reproduced, but the biases in means tend to reflect in these amplitudes. Interannual variability is also a challenge for models to reproduce. Although the models validate better against Bowen-ratio-corrected surface flux observations, which allow for closure of surface energy balances at flux tower sites, it is not clear whether the corrected fluxes are more representative of actual fluxes. The analysis illuminates targets for coupled land–atmosphere model development, as well as the value of long-term globally distributed observational monitoring.
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Santanello, Joseph A., Sujay V. Kumar, Christa D. Peters-Lidard, Ken Harrison, and Shujia Zhou. "Impact of Land Model Calibration on Coupled Land–Atmosphere Prediction." Journal of Hydrometeorology 14, no. 5 (October 1, 2013): 1373–400. http://dx.doi.org/10.1175/jhm-d-12-0127.1.
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Abstract Land–atmosphere (LA) interactions play a critical role in determining the diurnal evolution of both planetary boundary layer (PBL) and land surface heat and moisture budgets, as well as controlling feedbacks with clouds and precipitation that lead to the persistence of dry and wet regimes. In this study, the authors examine the impact of improved specification of land surface states, anomalies, and fluxes on coupled Weather Research and Forecasting Model (WRF) forecasts during the summers of extreme dry (2006) and wet (2007) land surface conditions in the U.S. southern Great Plains. The improved land initialization and surface flux parameterizations are obtained through calibration of the Noah land surface model using the new optimization and uncertainty estimation subsystems in NASA's Land Information System (LIS-OPT/LIS-UE). The impact of the calibration on the 1) spinup of the land surface used as initial conditions and 2) the simulated heat and moisture states and fluxes of the coupled WRF simulations is then assessed. In addition, the sensitivity of this approach to the period of calibration (dry, wet, or average) is investigated. Results show that the offline calibration is successful in providing improved initial conditions and land surface physics for the coupled simulations and in turn leads to systematic improvements in land–PBL fluxes and near-surface temperature and humidity forecasts. Impacts are larger during dry regimes, but calibration during either primarily wet or dry periods leads to improvements in coupled simulations due to the reduction in land surface model bias. Overall, these results provide guidance on the questions of what, how, and when to calibrate land surface models for coupled model prediction.
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Yang, Dongfang, Haixia Li, Dongmei Jing, Mingjing Tian, and Longlei Zhang. "Mercury Content Transported from Atmosphere and Land to Jiaozhou Bay." E3S Web of Conferences 233 (2021): 03048. http://dx.doi.org/10.1051/e3sconf/202123303048.
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According to the data of May, August and October 1992, the range of Hg content in Jiaozhou Bay waters was 0.009-0.050 μg /L, which met the water quality standard of class I sea water. This showed that in terms of Hg content, in May, August and October, the water of Jiaozhou Bay was clean and free from any Hg pollution. In May, the range of Hg content in Jiaozhou Bay waters was 0.009-0.038 μg /L. In August, the range of Hg content in Jiaozhou Bay waters was 0.021-0.050 μg/L. In October, the range of Hg content in Jiaozhou Bay waters was 0.011-0.040 μg /L. There were two sources of Hg content in Jiaozhou Bay waters, surface runoff and atmospheric deposition. The Hg content from surface runoffwas 0.038-0.040 μg /L, and that from atmospheric deposition was 0.050 μg /L. The model diagram was established to show the different paths and contents of Hg content in the process of input into Jiaozhou Bay. In May and October, the surface runoff was not polluted by any Hg content. In August, atmospheric deposition was not contaminated by any Hg content. That revealed that Hg, humans issued to land and atmosphere, finally got to the ocean. There were two paths. One is that human beings discharge Hg into the atmosphere, and the Hg content reached into the ocean through atmospheric sedimentation. The Hg content from atmospheric sedimentation was relatively high, but the transportation time was relatively short. The other is that human beings discharge Hg content to the land. Through surface runoff, the Hg content reached into the ocean, and the Hg content from surface runoff was relatively low, but the transportation time was relatively short. With more and more paths, Hg content was decreasing.
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Koster, Randal D., Y. C. Sud, Zhichang Guo, Paul A. Dirmeyer, Gordon Bonan, Keith W. Oleson, Edmond Chan, et al. "GLACE: The Global Land–Atmosphere Coupling Experiment. Part I: Overview." Journal of Hydrometeorology 7, no. 4 (August 1, 2006): 590–610. http://dx.doi.org/10.1175/jhm510.1.
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Abstract The Global Land–Atmosphere Coupling Experiment (GLACE) is a model intercomparison study focusing on a typically neglected yet critical element of numerical weather and climate modeling: land–atmosphere coupling strength, or the degree to which anomalies in land surface state (e.g., soil moisture) can affect rainfall generation and other atmospheric processes. The 12 AGCM groups participating in GLACE performed a series of simple numerical experiments that allow the objective quantification of this element for boreal summer. The derived coupling strengths vary widely. Some similarity, however, is found in the spatial patterns generated by the models, with enough similarity to pinpoint multimodel “hot spots” of land–atmosphere coupling. For boreal summer, such hot spots for precipitation and temperature are found over large regions of Africa, central North America, and India; a hot spot for temperature is also found over eastern China. The design of the GLACE simulations are described in full detail so that any interested modeling group can repeat them easily and thereby place their model’s coupling strength within the broad range of those documented here.