Impact on short-lived climate forcers (SLCFs) from a realistic land-use change scenario via changes in biogenic emissions

More than one quarter of natural forests have been cleared by humans to make way for other land-uses, with changes to forest cover projected to continue. The climate impact of land-use change (LUC) is dependent upon the relative strength of several biogeophysical and biogeochemical effects. In addition to affecting the surface albedo and exchanging carbon dioxide (CO2) and moisture with the atmosphere, vegetation emits biogenic volatile organic compounds (BVOCs), altering the formation of short-lived climate forcers (SLCFs) including aerosol, ozone (O3) and methane (CH4). Once emitted, BVOCs are rapidly oxidised by O3, and the hydroxyl (OH) and nitrate (NO3) radicals. These oxidation reactions yield secondary organic products which are implicated in the formation and growth of aerosol particles and are estimated to have a negative radiative effect on the climate (i.e. a cooling). These reactions also deplete OH, increasing the atmospheric lifetime of CH4, and directly affect concentrations of O3; the latter two being greenhouse gases which impose a positive radiative effect (i.e. a warming) on the climate. Our previous work assessing idealised deforestation scenarios found a positive radiative effect due to changes in SLCFs; however, since the radiative effects associated with changes to SLCFs result from a combination of non-linear processes it may not be appropriate to scale radiative effects from complete deforestation scenarios according to the deforestation extent. Here we combine a land-surface model, a chemical transport model, a global aerosol model, and a radiative transfer model to assess the net radiative effect of changes in SLCFs due to historical LUC between the years 1850 and 2000.

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Contrasting the direct radiative effect and direct radiative forcing of aerosols

Atmospheric Chemistry and Physics ◽

10.5194/acp-14-5513-2014 ◽

2014 ◽

Vol 14 (11) ◽

pp. 5513-5527 ◽

Cited By ~ 105

Author(s):

C. L. Heald ◽

D. A. Ridley ◽

J. H. Kroll ◽

S. R. H. Barrett ◽

K. E. Cady-Pereira ◽

...

Keyword(s):

Energy Balance ◽

Radiative Forcing ◽

Transport Model ◽

Radiative Transfer Model ◽

Transfer Model ◽

Radiative Effect ◽

Chemical Transport Model ◽

Anthropogenic Aerosols ◽

Anthropogenic Aerosol ◽

Direct Radiative Forcing

Abstract. The direct radiative effect (DRE) of aerosols, which is the instantaneous radiative impact of all atmospheric particles on the Earth's energy balance, is sometimes confused with the direct radiative forcing (DRF), which is the change in DRE from pre-industrial to present-day (not including climate feedbacks). In this study we couple a global chemical transport model (GEOS-Chem) with a radiative transfer model (RRTMG) to contrast these concepts. We estimate a global mean all-sky aerosol DRF of −0.36 Wm−2 and a DRE of −1.83 Wm−2 for 2010. Therefore, natural sources of aerosol (here including fire) affect the global energy balance over four times more than do present-day anthropogenic aerosols. If global anthropogenic emissions of aerosols and their precursors continue to decline as projected in recent scenarios due to effective pollution emission controls, the DRF will shrink (−0.22 Wm−2 for 2100). Secondary metrics, like DRE, that quantify temporal changes in both natural and anthropogenic aerosol burdens are therefore needed to quantify the total effect of aerosols on climate.

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Representation of fire, land-use change and vegetation dynamics in the Joint UK Land Environment Simulator vn4.9 (JULES)

Geoscientific Model Development ◽

10.5194/gmd-12-179-2019 ◽

2019 ◽

Vol 12 (1) ◽

pp. 179-193 ◽

Cited By ~ 11

Author(s):

Chantelle Burton ◽

Richard Betts ◽

Manoel Cardoso ◽

Ted R. Feldpausch ◽

Anna Harper ◽

...

Keyword(s):

Land Use ◽

Land Use Change ◽

Land Cover ◽

Vegetation Cover ◽

Land Surface ◽

Vegetation Dynamics ◽

Fire Disturbance ◽

Substantial Contribution ◽

Surface Model ◽

The Impact

Abstract. Disturbance of vegetation is a critical component of land cover, but is generally poorly constrained in land surface and carbon cycle models. In particular, land-use change and fire can be treated as large-scale disturbances without full representation of their underlying complexities and interactions. Here we describe developments to the land surface model JULES (Joint UK Land Environment Simulator) to represent land-use change and fire as distinct processes which interact with simulated vegetation dynamics. We couple the fire model INFERNO (INteractive Fire and Emission algoRithm for Natural envirOnments) to dynamic vegetation within JULES and use the HYDE (History Database of the Global Environment) land cover dataset to analyse the impact of land-use change on the simulation of present day vegetation. We evaluate the inclusion of land use and fire disturbance against standard benchmarks. Using the Manhattan metric, results show improved simulation of vegetation cover across all observed datasets. Overall, disturbance improves the simulation of vegetation cover by 35 % compared to vegetation continuous field (VCF) observations from MODIS and 13 % compared to the Climate Change Initiative (CCI) from the ESA. Biases in grass extent are reduced from −66 % to 13 %. Total woody cover improves by 55 % compared to VCF and 20 % compared to CCI from a reduction in forest extent in the tropics, although simulated tree cover is now too sparse in some areas. Explicitly modelling fire and land use generally decreases tree and shrub cover and increases grasses. The results show that the disturbances provide important contributions to the realistic modelling of vegetation on a global scale, although in some areas fire and land use together result in too much disturbance. This work provides a substantial contribution towards representing the full complexity and interactions between land-use change and fire that could be used in Earth system models.

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Exploring the observational constraints on the simulation of brown carbon

Atmospheric Chemistry and Physics ◽

10.5194/acp-18-635-2018 ◽

2018 ◽

Vol 18 (2) ◽

pp. 635-653 ◽

Cited By ~ 44

Author(s):

Xuan Wang ◽

Colette L. Heald ◽

Jiumeng Liu ◽

Rodney J. Weber ◽

Pedro Campuzano-Jost ◽

...

Keyword(s):

Optical Properties ◽

Transport Model ◽

Model Simulation ◽

Radiative Transfer Model ◽

Transfer Model ◽

Observational Constraints ◽

Aircraft Measurements ◽

Radiative Effect ◽

Brown Carbon ◽

Direct Measurements

Abstract. Organic aerosols (OA) that strongly absorb solar radiation in the near-UV are referred to as brown carbon (BrC). The sources, evolution, and optical properties of BrC remain highly uncertain and contribute significantly to uncertainty in the estimate of the global direct radiative effect (DRE) of aerosols. Previous modeling studies of BrC optical properties and DRE have been unable to fully evaluate model performance due to the lack of direct measurements of BrC absorption. In this study, we develop a global model simulation (GEOS-Chem) of BrC and test it against BrC absorption measurements from two aircraft campaigns in the continental US (SEAC4RS and DC3). To the best of our knowledge, this is the first study to compare simulated BrC absorption with direct aircraft measurements. We show that BrC absorption properties estimated based on previous laboratory measurements agree with the aircraft measurements of freshly emitted BrC absorption but overestimate aged BrC absorption. In addition, applying a photochemical scheme to simulate bleaching/degradation of BrC improves model skill. The airborne observations are therefore consistent with a mass absorption coefficient (MAC) of freshly emitted biomass burning OA of 1.33 m2 g−1 at 365 nm coupled with a 1-day whitening e-folding time. Using the GEOS-Chem chemical transport model integrated with the RRTMG radiative transfer model, we estimate that the top-of-the-atmosphere all-sky direct radiative effect (DRE) of OA is −0.344 Wm−2, 10 % higher than that without consideration of BrC absorption. Therefore, our best estimate of the absorption DRE of BrC is +0.048 Wm−2. We suggest that the DRE of BrC has been overestimated previously due to the lack of observational constraints from direct measurements and omission of the effects of photochemical whitening.

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Global Calibration of the GEOS-5 L-Band Microwave Radiative Transfer Model over Nonfrozen Land Using SMOS Observations

Journal of Hydrometeorology ◽

10.1175/jhm-d-12-092.1 ◽

2013 ◽

Vol 14 (3) ◽

pp. 765-785 ◽

Cited By ~ 67

Author(s):

Gabriëlle J. M. De Lannoy ◽

Rolf H. Reichle ◽

Valentijn R. N. Pauwels

Keyword(s):

Soil Moisture ◽

Radiative Transfer ◽

Land Surface ◽

Radiative Transfer Model ◽

Absolute Difference ◽

Surface Model ◽

Transfer Model ◽

Global Average ◽

L Band ◽

Parameter Values

Abstract A zero-order (tau-omega) microwave radiative transfer model (RTM) is coupled to the Goddard Earth Observing System, version 5 (GEOS-5) catchment land surface model in preparation for the future assimilation of global brightness temperatures (Tb) from the L-band (1.4 GHz) Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) missions. Simulations using literature values for the RTM parameters result in Tb biases of 10–50 K against SMOS observations. Multiangular SMOS observations during nonfrozen conditions from 1 July 2011 to 1 July 2012 are used to calibrate parameters related to the microwave roughness h, vegetation opacity τ and/or scattering albedo ω separately for each observed 36-km land grid cell. A particle swarm optimization is used to minimize differences in the long-term (climatological) mean values and standard deviations between SMOS observations and simulations, without attempting to reduce the shorter-term (seasonal to daily) errors. After calibration, global Tb simulations for the validation year (1 July 2010 to 1 July 2011) are largely unbiased for multiple incidence angles and both H and V polarization [e.g., the global average absolute difference is 2.7 K for TbH(42.5°), i.e., at 42.5° incidence angle]. The calibrated parameter values depend to some extent on the specific land surface conditions simulated by the GEOS-5 system and on the scale of the SMOS observations, but they also show realistic spatial distributions. Aggregating the calibrated parameter values by vegetation class prior to using them in the RTM maintains low global biases but increases local biases [e.g., the global average absolute difference is 7.1 K for TbH(42.5°)].

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MIROC-INTEG-LAND version 1: a global biogeochemical land surface model with human water management, crop growth, and land-use change

Geoscientific Model Development ◽

10.5194/gmd-13-4713-2020 ◽

2020 ◽

Vol 13 (10) ◽

pp. 4713-4747

Author(s):

Tokuta Yokohata ◽

Tsuguki Kinoshita ◽

Gen Sakurai ◽

Yadu Pokhrel ◽

Akihiko Ito ◽

...

Keyword(s):

Climate Change ◽

Water Management ◽

Land Use ◽

Land Use Change ◽

Land Surface ◽

Crop Yields ◽

Land Surface Model ◽

Climate System ◽

Surface Model ◽

Earth System

Abstract. Future changes in the climate system could have significant impacts on the natural environment and human activities, which in turn affect changes in the climate system. In the interaction between natural and human systems under climate change conditions, land use is one of the elements that play an essential role. On the one hand, future climate change will affect the availability of water and food, which may impact land-use change. On the other hand, human-induced land-use change can affect the climate system through biogeophysical and biogeochemical effects. To investigate these interrelationships, we developed MIROC-INTEG-LAND (MIROC INTEGrated LAND surface model version 1), an integrated model that combines the land surface component of global climate model MIROC (Model for Interdisciplinary Research on Climate) with water resources, crop production, land ecosystem, and land-use models. The most significant feature of MIROC-INTEG-LAND is that the land surface model that describes the processes of the energy and water balance, human water management, and crop growth incorporates a land use decision-making model based on economic activities. In MIROC-INTEG-LAND, spatially detailed information regarding water resources and crop yields is reflected in the prediction of future land-use change, which cannot be considered in the conventional integrated assessment models. In this paper, we introduce the details and interconnections of the submodels of MIROC-INTEG-LAND, compare historical simulations with observations, and identify various interactions between the submodels. By evaluating the historical simulation, we have confirmed that the model reproduces the observed states well. The future simulations indicate that changes in climate have significant impacts on crop yields, land use, and irrigation water demand. The newly developed MIROC-INTEG-LAND could be combined with atmospheric and ocean models to develop an integrated earth system model to simulate the interactions among coupled natural–human earth system components.

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Simulation of Monsoon Low Pressure System and its Associated Rainfall Over Bangladesh Using WRF Model

Dhaka University Journal of Science ◽

10.3329/dujs.v66i1.54541 ◽

2018 ◽

Vol 66 (1) ◽

pp. 29-35

Author(s):

Deepa Roy ◽

Md Abdus Samad ◽

SM Quamrul Hassan

Keyword(s):

Land Surface ◽

Wrf Model ◽

Vertical Wind Shear ◽

Low Pressure ◽

Radiative Transfer Model ◽

Surface Model ◽

Transfer Model ◽

Pressure System ◽

Hourly Data ◽

Low Pressure System

In this paper an effort has been made to simulate the monsoon Low Pressure System (LPS) and its associated rainfall event of 16-20 August, 2013 using Weather Research and Forecasting (WRF) model. The model was run for 24-h, 48-h and 72-h in a single domain of 10 km horizontal resolution using The National Centre for Environmental Prediction (NCEP) high-resolution Global Final (FNL) Analysis 6-hourly data using initial and lateral boundary conditions. WRF double-moment 5 class micro physics scheme, Kain–Fritsch (new Eta) cumulus physics scheme,Yonsei University planetary boundary layer scheme, Revised MM5 surface layer physics scheme, Unified Noah LSM as land surface model, Rapid Radiative Transfer Model (RRTM) for long-wave and Dudhia scheme for short-wave scheme are used for the simulation. The performance of the model is evaluated analyzing Mean Sea Level Pressure (MSLP), Wind Pattern, Vorticity, Vertical Wind Shear and Rainfall Distribution. The model successfully captured the low pressure system, initial condition, propagation, landfall time and location reasonably well. The model simulated rainfall amount and associated areas sensibly well compared with the observed data by BMD and Tropical Rainfall Measuring Mission (TRMM). Dhaka Univ. J. Sci. 66(1): 29-35, 2018 (January)

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Longwave Radiative Effect of the Cloud-Aerosol Transition Zone Based on CERES Observations

10.5194/acp-2021-421 ◽

2021 ◽

Author(s):

Babak Jahani ◽

Hendrik Andersen ◽

Josep Calbó ◽

Josep-Abel González ◽

Jan Cermak

Keyword(s):

Radiative Transfer ◽

Transition Zone ◽

Radiant Energy ◽

Energy System ◽

Radiative Transfer Model ◽

Transfer Model ◽

Radiative Effect ◽

Radiative Effects ◽

Clear Sky ◽

Moderate Resolution Imaging Spectroradiometer

Abstract. This study presents an approach for quantification of cloud-aerosol transition zone broadband longwave radiative effects at the top of the atmosphere (TOA) during daytime over the ocean, based on satellite observations and radiative transfer simulation. Specifically, we used several products from MODIS (Moderate Resolution Imaging Spectroradiometer) and CERES (Clouds and the Earth’s Radiant Energy System) sensors for identification and selection of CERES footprints with horizontally homogeneous transition zone and clear-sky conditions. For the selected transition zone footprints, radiative effect was calculated as the difference between the instantaneous CERES TOA upwelling broadband longwave radiance observations and corresponding clear-sky radiance simulations. The clear-sky radiances were simulated using the Santa Barbara DISORT Atmospheric Radiative Transfer model fed by the hourly ERA5 reanalysis (fifth generation ECMWF reanalysis) atmospheric and surface data. The CERES radiance observations corresponding to the clear-sky footprints detected were also used for validating the simulated clear-sky radiances. We tested this approach using the radiative measurements made by the MODIS and CERES instruments onboard Aqua platform over the south-eastern Atlantic Ocean during August 2010. For the studied period and domain, transition zone radiative effect (given in flux units) is on average equal to 8.0 ± 3.7 W m−2 (heating effect; median: 5.4 W m−2), although cases with radiative effects as large as 50 W m−2 were found.

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Exploring the observational constraints on the simulation of brown carbon

10.5194/acp-2017-655 ◽

2017 ◽

Author(s):

Xuan Wang ◽

Colette L. Heald ◽

Jiumeng Liu ◽

Rodney J. Weber ◽

Pedro Campuzano-Jost ◽

...

Keyword(s):

Optical Properties ◽

Biomass Burning ◽

Transport Model ◽

Model Simulation ◽

Radiative Transfer Model ◽

Transfer Model ◽

Observational Constraints ◽

Radiative Effect ◽

Brown Carbon ◽

Direct Measurements

Abstract. Organic aerosols (OA) that strongly absorbs solar radiation in the near-UV are referred to as brown carbon (BrC). However the sources, evolution, and optical properties of BrC remain highly uncertain, and contribute significantly to uncertainty in the estimate of the global direct radiative effect (DRE) of aerosols. Previous modeling studies of BrC optical properties and DRE have been unable to fully evaluate model performance due to the lack of direct measurements of BrC absorption. In this study, we develop a global model simulation (GEOS-Chem) of BrC and test it against BrC absorption measurements from two aircraft campaigns in the continental U.S. (SEAC4RS and DC3). To our knowledge, this is the first study to compare simulated BrC absorption with direct ambient measurements. We show that the BrC absorption properties from biomass burning estimated based on previous laboratory measurements overestimate the aircraft measurements of ambient BrC absorption. In addition, applying a photochemical scheme to simulate bleaching/degradation of BrC improves model skill. The airborne observations are consistent with a mass absorption coefficient (MAC) of freshly emitted biomass burning OA of 0.57 m2 g−1 at 365 nm with an absorption Ångström exponents (AAE) = 3.1 for 300 & 600 wavelengths pair, coupled with a 1 day whitening e-folding time. Using the GEOS-Chem chemical transport model integrated with the RRTMG radiative transfer model, we estimate that the top-of-atmosphere all-sky direct radiative effect (DRE) of OA is −0.350 Wm−2, 10 % higher than that without consideration of BrC absorption. Therefore, our best estimate of the absorption DRE of BrC is +0.042 Wm−2. We suggest that the DRE of BrC has been overestimated previously due to the lack of observational constraints from direct measurements and omission of the effects of photochemical whitening.

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Land-use change may exacerbate climate change impacts on water resources in the Ganges basin

Hydrology and Earth System Sciences ◽

10.5194/hess-22-1411-2018 ◽

2018 ◽

Vol 22 (2) ◽

pp. 1411-1435 ◽

Cited By ~ 5

Author(s):

Gina Tsarouchi ◽

Wouter Buytaert

Keyword(s):

Climate Change ◽

Land Use ◽

Water Resources ◽

Land Use Change ◽

Land Surface ◽

Land Surface Model ◽

Coupled Model ◽

Surface Model ◽

Climate Change Scenarios ◽

Ganges River

Abstract. Quantifying how land-use change and climate change affect water resources is a challenge in hydrological science. This work aims to quantify how future projections of land-use and climate change might affect the hydrological response of the Upper Ganges river basin in northern India, which experiences monsoon flooding almost every year. Three different sets of modelling experiments were run using the Joint UK Land Environment Simulator (JULES) land surface model (LSM) and covering the period 2000–2035: in the first set, only climate change is taken into account, and JULES was driven by the CMIP5 (Coupled Model Intercomparison Project Phase 5) outputs of 21 models, under two representative concentration pathways (RCP4.5 and RCP8.5), whilst land use was held fixed at the year 2010. In the second set, only land-use change is taken into account, and JULES was driven by a time series of 15 future land-use pathways, based on Landsat satellite imagery and the Markov chain simulation, whilst the meteorological boundary conditions were held fixed at years 2000–2005. In the third set, both climate change and land-use change were taken into consideration, as the CMIP5 model outputs were used in conjunction with the 15 future land-use pathways to force JULES. Variations in hydrological variables (stream flow, evapotranspiration and soil moisture) are calculated during the simulation period. Significant changes in the near-future (years 2030–2035) hydrologic fluxes arise under future land-cover and climate change scenarios pointing towards a severe increase in high extremes of flow: the multi-model mean of the 95th percentile of streamflow (Q5) is projected to increase by 63 % under the combined land-use and climate change high emissions scenario (RCP8.5). The changes in all examined hydrological components are greater in the combined land-use and climate change experiment. Results are further presented in a water resources context, aiming to address potential implications of climate change and land-use change from a water demand perspective. We conclude that future water demands in the Upper Ganges region for winter months may not be met.

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Hyper-resolution land surface modeling enables 30-m SMAP-based soil moisture at continental scales

10.5194/egusphere-egu2020-12717 ◽

2020 ◽

Author(s):

Noemi Vergopolan ◽

Nathaniel W. Chaney ◽

Hylke E. Beck ◽

Ming Pan ◽

Justin Sheffield ◽

...

Keyword(s):

Soil Moisture ◽

Brightness Temperature ◽

Spatial Resolution ◽

Land Surface ◽

Large Scale ◽

Radiative Transfer Model ◽

Surface Model ◽

Transfer Model ◽

Field Scale ◽

Remotely Sensed Data

Accurate and detailed soil moisture information is essential for, among other things, irrigation, drought and flood prediction, water resources management, and field-scale (i.e., tens of m) decision making. Microwave-based satellite remote sensing offers unique opportunities for the large-scale monitoring of soil moisture at frequent temporal intervals. However, the utility of these satellite products is limited by the large footprint of the microwave sensors. Several downscaling techniques based on high-resolution remotely sensed data proxies have been proposed (1 km to 100 m). Although these techniques yield aesthetically pleasing maps, by neglecting how the water and energy fluxes physically interact with the landscape, these approaches often fail to provide soil moisture estimates that are hydrologically consistent.This work introduces a state-of-the-art framework that combines a process-based hyper-resolution land surface model (LSM), a radiative transfer model (RTM), and a Bayesian scheme to merge and downscale coarse resolution brightness temperature to a 30-m spatial resolution. The framework is based on HydroBlocks, an LSM that solves the field-scale spatial heterogeneity of land surface processes through interacting hydrologic response units (HRUs). We demonstrate this framework by coupling HydroBlocks with the Tau-Omega RTM used in the Soil Moisture Active Passive (SMAP) mission and subsequently merging the HydroBlocks-RTM and the SMAP L3-enhanced brightness temperature at the HRU scale. This allows for hydrologically consistent SMAP-based soil moisture retrievals at an unprecedented 30-m spatial resolution over continental domains.&#160;We applied this framework to obtain 30-m SMAP-based soil moisture retrievals over the contiguous United States (2015-2018). When evaluated against sparse and dense in-situ soil moisture networks, the 30-m soil moisture retrievals showed substantial improvements in performance at field and watershed scales, outperforming both the SMAP L3-enhanced and the SMAP L4 soil moisture products. This work leads the way towards hydrologically consistent field-scale soil moisture retrievals and highlights the value of hyper-resolution modeling to bridge the gap between coarse-scale satellite retrievals and field-scale hydrological applications.&#160;

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