scholarly journals Climatic Impact of Vegetation Change in the Asian Tropical Region. Part I: Case of the Northern Hemisphere Summer

2005 ◽  
Vol 18 (3) ◽  
pp. 410-428 ◽  
Author(s):  
Kazuo Mabuchi ◽  
Yasuo Sato ◽  
Hideji Kida
Keyword(s):  
Land Surface ◽  
Vegetation Change ◽  
Tropical Region ◽  
Surface Model ◽  
Monsoon Circulation ◽  
Vegetation Changes ◽  
Control Simulation ◽  
Change Impact ◽  
The Impact ◽  
Impact Experiments

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

scholarly journals Climatic Impact of Vegetation Change in the Asian Tropical Region. Part II: Case of the Northern Hemisphere Winter and Impact on the Extratropical Circulation

2005 ◽  
Vol 18 (3) ◽  
pp. 429-446 ◽  
Author(s):  
Kazuo Mabuchi ◽  
Yasuo Sato ◽  
Hideji Kida
Keyword(s):  
Northern Hemisphere ◽  
Land Surface ◽  
Vegetation Change ◽  
Bare Soil ◽  
Enso Event ◽  
Tropical Region ◽  
Vegetation Changes ◽  
C4 Grass ◽  
Change Impact ◽  
Hemisphere Winter

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

scholarly journals Vegetation Dynamic Assessment by NDVI and Field Observations for Sustainability of China’s Wulagai River Basin

2021 ◽  
Vol 18 (5) ◽  
pp. 2528
Author(s):  
Panpan Chen ◽  
Huamin Liu ◽  
Zongming Wang ◽  
Dehua Mao ◽  
Cunzhu Liang ◽  
...  
Keyword(s):  
Species Diversity ◽  
River Basin ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Dynamic Assessment ◽  
Indicator System ◽  
Vegetation Changes ◽  
Vegetation Dynamic ◽  
Management Policies ◽  
The Impact

Accurate monitoring of grassland vegetation dynamics is essential for ecosystem restoration and the implementation of integrated management policies. A lack of information on vegetation changes in the Wulagai River Basin restricts regional development. Therefore, in this study, we integrated remote sensing, meteorological, and field plant community survey data in order to characterize vegetation and ecosystem changes from 1997 to 2018. The residual trend (RESTREND) method was utilized to detect vegetation changes caused by human factors, as well as to evaluate the impact of the management of pastures. Our results reveal that the normalized difference vegetation index (NDVI) of each examined ecosystem type showed an increasing trend, in which anthropogenic impact was the primary driving force of vegetation change. Our field survey confirmed that the meadow steppe ecosystem increased in species diversity and aboveground biomass; however, the typical steppe and riparian wet meadow ecosystems experienced species diversity and biomass degradation, therefore suggesting that an increase in NDVI may not directly reflect ecosystem improvement. Selecting an optimal indicator or indicator system is necessary in order to formulate reasonable grassland management policies for increasing the sustainability of grassland ecosystems.

scholarly journals Influence of Land Cover and Soil Moisture on the Horizontal Distribution of Sensible and Latent Heat Fluxes in Southeast Kansas during IHOP_2002 and CASES-97

2007 ◽  
Vol 8 (1) ◽  
pp. 68-87 ◽  
Author(s):  
Margaret A. LeMone ◽  
Fei Chen ◽  
Joseph G. Alfieri ◽  
Mukul Tewari ◽  
Bart Geerts ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Latent Heat ◽  
Land Surface ◽  
Field Experiments ◽  
Time Of Day ◽  
Horizontal Distribution ◽  
Heat Fluxes ◽  
Surface Model ◽  
Green Vegetation ◽  
The Impact

Abstract Analyses of daytime fair-weather aircraft and surface-flux tower data from the May–June 2002 International H2O Project (IHOP_2002) and the April–May 1997 Cooperative Atmosphere Surface Exchange Study (CASES-97) are used to document the role of vegetation, soil moisture, and terrain in determining the horizontal variability of latent heat LE and sensible heat H along a 46-km flight track in southeast Kansas. Combining the two field experiments clearly reveals the strong influence of vegetation cover, with H maxima over sparse/dormant vegetation, and H minima over green vegetation; and, to a lesser extent, LE maxima over green vegetation, and LE minima over sparse/dormant vegetation. If the small number of cases is producing the correct trend, other effects of vegetation and the impact of soil moisture emerge through examining the slope ΔxyLE/ΔxyH for the best-fit straight line for plots of time-averaged LE as a function of time-averaged H over the area. Based on the surface energy balance, H + LE = Rnet − Gsfc, where Rnet is the net radiation and Gsfc is the flux into the soil; Rnet − Gsfc ∼ constant over the area implies an approximately −1 slope. Right after rainfall, H and LE vary too little horizontally to define a slope. After sufficient drying to produce enough horizontal variation to define a slope, a steep (∼−2) slope emerges. The slope becomes shallower and better defined with time as H and LE horizontal variability increases. Similarly, the slope becomes more negative with moister soils. In addition, the slope can change with time of day due to phase differences in H and LE. These trends are based on land surface model (LSM) runs and observations collected under nearly clear skies; the vegetation is unstressed for the days examined. LSM runs suggest terrain may also play a role, but observational support is weak.

scholarly journals Coupling a land-surface model with a crop growth model to improve ET flux estimations in the Upper Ganges basin, India

2014 ◽  
Vol 18 (10) ◽  
pp. 4223-4238 ◽  
Author(s):  
G. M. Tsarouchi ◽  
W. Buytaert ◽  
A. Mijic
Keyword(s):  
Growth Model ◽  
Land Surface ◽  
Coupled Model ◽  
Crop Growth ◽  
Original Model ◽  
Surface Model ◽  
Strong Impact ◽  
Crop Growth Model ◽  
Mean Error ◽  
The Impact

Abstract. Land-Surface Models (LSMs) are tools that represent energy and water flux exchanges between land and the atmosphere. Although much progress has been made in adding detailed physical processes into these models, there is much room left for improved estimates of evapotranspiration fluxes, by including a more reasonable and accurate representation of crop dynamics. Recent studies suggest a strong land-surface–atmosphere coupling over India and since this is one of the most intensively cultivated areas in the world, the strong impact of crops on the evaporative flux cannot be neglected. In this study we dynamically couple the LSM JULES with the crop growth model InfoCrop. JULES in its current version (v3.4) does not simulate crop growth. Instead, it treats crops as natural grass, while using prescribed vegetation parameters. Such simplification might lead to modelling errors. Therefore we developed a coupled modelling scheme that simulates dynamically crop development and parametrized it for the two main crops of the study area, wheat and rice. This setup is used to examine the impact of inter-seasonal land cover changes in evapotranspiration fluxes of the Upper Ganges River basin (India). The sensitivity of JULES with regard to the dynamics of the vegetation cover is evaluated. Our results show that the model is sensitive to the changes introduced after coupling it with the crop model. Evapotranspiration fluxes, which are significantly different between the original and the coupled model, are giving an approximation of the magnitude of error to be expected in LSMs that do not include dynamic crop growth. For the wet season, in the original model, the monthly Mean Error ranges from 7.5 to 24.4 mm month−1, depending on different precipitation forcing. For the same season, in the coupled model, the monthly Mean Error's range is reduced to 5.4–11.6 mm month−1. For the dry season, in the original model, the monthly Mean Error ranges from 10 to 17 mm month−1, depending on different precipitation forcing. For the same season, in the coupled model, the monthly Mean Error's range is reduced to 2.2–3.4 mm month−1. The new modelling scheme, by offering increased accuracy of evapotranspiration estimations, is an important step towards a better understanding of the two-way crops–atmosphere interactions.

scholarly journals Continuous high-resolution midlatitude-belt simulations for July–August 2013 with WRF

2017 ◽  
Vol 10 (5) ◽  
pp. 2031-2055 ◽  
Author(s):  
Thomas Schwitalla ◽  
Hans-Stefan Bauer ◽  
Volker Wulfmeyer ◽  
Kirsten Warrach-Sagi
Keyword(s):  
High Resolution ◽  
Land Surface ◽  
Large Scale ◽  
Temperature Fields ◽  
Surface Model ◽  
Limited Area ◽  
Data Set ◽  
Latitude Belt ◽  
Simulated Precipitation ◽  
The Impact

Abstract. Increasing computational resources and the demands of impact modelers, stake holders, and society envision seasonal and climate simulations with the convection-permitting resolution. So far such a resolution is only achieved with a limited-area model whose results are impacted by zonal and meridional boundaries. Here, we present the setup of a latitude-belt domain that reduces disturbances originating from the western and eastern boundaries and therefore allows for studying the impact of model resolution and physical parameterization. The Weather Research and Forecasting (WRF) model coupled to the NOAH land–surface model was operated during July and August 2013 at two different horizontal resolutions, namely 0.03 (HIRES) and 0.12° (LOWRES). Both simulations were forced by the European Centre for Medium-Range Weather Forecasts (ECMWF) operational analysis data at the northern and southern domain boundaries, and the high-resolution Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) data at the sea surface.The simulations are compared to the operational ECMWF analysis for the representation of large-scale features. To analyze the simulated precipitation, the operational ECMWF forecast, the CPC MORPHing (CMORPH), and the ENSEMBLES gridded observation precipitation data set (E-OBS) were used as references.Analyzing pressure, geopotential height, wind, and temperature fields as well as precipitation revealed (1) a benefit from the higher resolution concerning the reduction of monthly biases, root mean square error, and an improved Pearson skill score, and (2) deficiencies in the physical parameterizations leading to notable biases in distinct regions like the polar Atlantic for the LOWRES simulation, the North Pacific, and Inner Mongolia for both resolutions.In summary, the application of a latitude belt on a convection-permitting resolution shows promising results that are beneficial for future seasonal forecasting.

scholarly journals The Impact of Error Accounting in a Bayesian Approach to Calibrating Modeled Turbulent Fluxes in an Open-Canopy Forest

2017 ◽  
Vol 18 (7) ◽  
pp. 2029-2042
Author(s):  
Tony E. Wong ◽  
William Kleiber ◽  
David C. Noone
Keyword(s):  
Markov Chain ◽  
Land Surface ◽  
Hydrological Modeling ◽  
Soil Layer ◽  
Turbulent Fluxes ◽  
Surface Model ◽  
Model Parameters ◽  
Top Soil ◽  
The Impact ◽  
Calibration Approach

Abstract Land surface models are notorious for containing many parameters that control the exchange of heat and moisture between land and atmosphere. Properly modeling the partitioning of total evapotranspiration (ET) between transpiration and evaporation is critical for accurate hydrological modeling, but depends heavily on the treatment of turbulence within and above canopies. Previous work has constrained estimates of evapotranspiration and its partitioning using statistical approaches that calibrate land surface model parameters by assimilating in situ measurements. These studies, however, are silent on the impacts of the accounting of uncertainty within the statistical calibration framework. The present study calibrates the aerodynamic, leaf boundary layer, and stomatal resistance parameters, which partially control canopy turbulent exchange and thus the evapotranspiration flux partitioning. Using an adaptive Metropolis–Hastings algorithm to construct a Markov chain of draws from the joint posterior distribution of these resistance parameters, an ensemble of model realizations is generated, in which latent and sensible heat fluxes and top soil layer temperature are optimized. A set of five calibration experiments demonstrate that model performance is sensitive to the accounting of various sources of uncertainty in the field observations and model output and that it is critical to account for model structural uncertainty. After calibration, the modeled fluxes and top soil layer temperature are largely free from bias, and this calibration approach successfully informs and characterizes uncertainty in these parameters, which is essential for model improvement and development. The key points of this paper are 1) a Markov chain Monte Carlo calibration approach successfully improves modeled turbulent fluxes; 2) ET partitioning estimates hinge on the representation of uncertainties in the model and data; and 3) despite these inherent uncertainties, constrained posterior estimates of ET partitioning emerge.

scholarly journals Development and application of the WRFPLUS-Chem online chemistry adjoint and WRFDA-Chem assimilation system

2015 ◽  
Vol 8 (6) ◽  
pp. 1857-1876 ◽  
Author(s):  
J. J. Guerrette ◽  
D. K. Henze
Keyword(s):  
Land Surface ◽  
Vertical Mixing ◽  
Model Performance ◽  
Land Surface Model ◽  
Sensitivity Study ◽  
Climate Impacts ◽  
Surface Model ◽  
Time Period ◽  
Develop Land ◽  
The Impact

Abstract. Here we present the online meteorology and chemistry adjoint and tangent linear model, WRFPLUS-Chem (Weather Research and Forecasting plus chemistry), which incorporates modules to treat boundary layer mixing, emission, aging, dry deposition, and advection of black carbon aerosol. We also develop land surface and surface layer adjoints to account for coupling between radiation and vertical mixing. Model performance is verified against finite difference derivative approximations. A second-order checkpointing scheme is created to reduce computational costs and enable simulations longer than 6 h. The adjoint is coupled to WRFDA-Chem, in order to conduct a sensitivity study of anthropogenic and biomass burning sources throughout California during the 2008 Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS) field campaign. A cost-function weighting scheme was devised to reduce the impact of statistically insignificant residual errors in future inverse modeling studies. Results of the sensitivity study show that, for this domain and time period, anthropogenic emissions are overpredicted, while wildfire emission error signs vary spatially. We consider the diurnal variation in emission sensitivities to determine at what time sources should be scaled up or down. Also, adjoint sensitivities for two choices of land surface model (LSM) indicate that emission inversion results would be sensitive to forward model configuration. The tools described here are the first step in conducting four-dimensional variational data assimilation in a coupled meteorology–chemistry model, which will potentially provide new constraints on aerosol precursor emissions and their distributions. Such analyses will be invaluable to assessments of particulate matter health and climate impacts.

scholarly journals High-resolution fully-coupled atmospheric–hydrological modeling: a cross-compartment regional water and energy cycle evaluation

2020 ◽  
Author(s):  
Benjamin Fersch ◽  
Alfonso Senatore ◽  
Bianca Adler ◽  
Joël Arnault ◽  
Matthias Mauder ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Land Surface ◽  
Hydrological Modeling ◽  
Weather Prediction ◽  
Surface Model ◽  
Near Surface ◽  
Ground Heat Flux ◽  
The Impact ◽  
Fully Coupled ◽  
Regional Water

<p>The land surface and the atmospheric boundary layer are closely intertwined with respect to the exchange of water, trace gases and energy. Nonlinear feedback and scale dependent mechanisms are obvious by observations and theories. Modeling instead is often narrowed to single compartments of the terrestrial system or bound to traditional viewpoints of definite scientific disciplines. Coupled terrestrial hydrometeorological modeling systems attempt to overcome these limitations to achieve a better integration of the processes relevant for regional climate studies and local area weather prediction. We examine the ability of the hydrologically enhanced version of the Weather Research and Forecasting Model (WRF-Hydro) to reproduce the regional water cycle by means of a two-way coupled approach and assess the impact of hydrological coupling with respect to a traditional regional atmospheric model setting. It includes the observation-based calibration of the hydrological model component (offline WRF-Hydro) and a comparison of the classic WRF and the fully coupled WRF-Hydro models both with identical calibrated parameter settings for the land surface model (Noah-MP). The simulations are evaluated based on extensive observations at the pre-Alpine Terrestrial Environmental Observatory (TERENO Pre-Alpine) for the Ammer (600 km²) and Rott (55 km²) river catchments in southern Germany, covering a five month period (Jun–Oct 2016).</p><p>The sensitivity of 7 land surface parameters is tested using the <em>Latin-Hypercube One-factor-At-a-Time</em> (LH-OAT) method and 6 sensitive parameters are subsequently optimized for 6 different subcatchments, using the Model-Independent <em>Parameter Estimation and Uncertainty Analysis software</em> (PEST).</p><p>The calibration of the offline WRF-Hydro leads to Nash-Sutcliffe efficiencies between 0.56 and 0.64 and volumetric efficiencies between 0.46 and 0.81 for the six subcatchments. The comparison of classic WRF and fully coupled WRF-Hydro shows only tiny alterations for radiation and precipitation but considerable changes for moisture- and energy fluxes. By comparison with TERENO Pre-Alpine observations, the fully coupled model slightly outperforms the classic WRF with respect to evapotranspiration, sensible and ground heat flux, near surface mixing ratio, temperature, and boundary layer profiles of air temperature. The subcatchment-based water budgets show uniformly directed variations for evapotranspiration, infiltration excess and percolation whereas soil moisture and precipitation change randomly.</p>

scholarly journals Exploring how groundwater buffers the influence of heatwaves on vegetation function during multi-year droughts

2021 ◽  
Vol 12 (3) ◽  
pp. 919-938
Author(s):  
Mengyuan Mu ◽  
Martin G. De Kauwe ◽  
Anna M. Ukkola ◽  
Andy J. Pitman ◽  
Weidong Guo ◽  
...  
Keyword(s):  
Land Surface ◽  
Forest Canopy ◽  
Climate Models ◽  
Root Zone ◽  
Stomatal Closure ◽  
Capillary Rise ◽  
Vapour Pressure Deficit ◽  
Global Climate Models ◽  
Surface Model ◽  
The Impact

Abstract. The co-occurrence of droughts and heatwaves can have significant impacts on many socioeconomic and environmental systems. Groundwater has the potential to moderate the impact of droughts and heatwaves by moistening the soil and enabling vegetation to maintain higher evaporation, thereby cooling the canopy. We use the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model, coupled to a groundwater scheme, to examine how groundwater influences ecosystems under conditions of co-occurring droughts and heatwaves. We focus specifically on south-east Australia for the period 2000–2019, when two significant droughts and multiple extreme heatwave events occurred. We found groundwater plays an important role in helping vegetation maintain transpiration, particularly in the first 1–2 years of a multi-year drought. Groundwater impedes gravity-driven drainage and moistens the root zone via capillary rise. These mechanisms reduced forest canopy temperatures by up to 5 ∘C during individual heatwaves, particularly where the water table depth is shallow. The role of groundwater diminishes as the drought lengthens beyond 2 years and soil water reserves are depleted. Further, the lack of deep roots or stomatal closure caused by high vapour pressure deficit or high temperatures can reduce the additional transpiration induced by groundwater. The capacity of groundwater to moderate both water and heat stress on ecosystems during simultaneous droughts and heatwaves is not represented in most global climate models, suggesting that model projections may overestimate the risk of these events in the future.

scholarly journals SMOS Neural Network Soil Moisture Data Assimilation in a Land Surface Model and Atmospheric Impact

2019 ◽  
Author(s):  
Nemesio Rodriguez-Fernandez ◽  
Patricia de Rosnay ◽  
Clement Albergel ◽  
Philippe Richaume ◽  
Filipe Aires ◽  
...  
Keyword(s):  
Neural Network ◽  
Soil Moisture ◽  
Data Assimilation ◽  
Land Surface ◽  
Positive Impact ◽  
Land Surface Model ◽  
Surface Model ◽  
Northern Asia ◽  
The Impact

The assimilation of Soil Moisture and Ocean Salinity (SMOS) data into the ECMWF (European Centre for Medium Range Weather Forecasts) H-TESSEL (Hydrology revised - Tiled ECMWF Scheme for Surface Exchanges over Land) model is presented. SMOS soil moisture (SM) estimates have been produced specifically by training a neural network with SMOS brightness temperatures as input and H-TESSEL model SM simulations as reference. This can help the assimilation of SMOS information in several ways: (1) the neural network soil moisture (NNSM) data have a similar climatology to the model, (2) no global bias is present with respect to the model even if regional differences can exist. Experiments performing joint data assimilation (DA) of NNSM, 2 metre air temperature and relative humidity or NNSM-only DA are discussed. The resulting SM was evaluated against a large number of in situ measurements of SM obtaining similar results to those of the model with no assimilation, even if significant differences were found from site to site. In addition, atmospheric forecasts initialized with H-TESSEL runs (without DA) or with the analysed SM were compared to measure of the impact of the satellite information. Although, NNSM DA has an overall neutral impact in the forecast in the Tropics, a significant positive impact was found in other areas and periods, especially in regions with limited in situ information. The joint NNSM, T2m and RH2m DA improves the forecast for all the seasons in the Southern Hemisphere. The impact is mostly due to T2m and RH2m, but SMOS NN DA alone also improves the forecast in July- September. In the Northern Hemisphere, the joint NNSM, T2m and RH2m DA improves the forecast in April-September, while NNSM alone has a significant positive effect in July-September. Furthermore, forecasting skill maps show that SMOS NNSM improves the forecast in North America and in Northern Asia for up to 72 hours lead time.

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