An Analysis of the Importance of a Fully-Coupled Atmosphere and Land-Surface When Considering the Impact of Multi-Scale Land Spatial Heterogeneity on Cloud Development

2021 ◽  
Author(s):  
Jason Simon ◽  
Tyler Waterman ◽  
Finley Hay-Chapman ◽  
Paul Dirmeyer ◽  
Andrew Bragg ◽  
...  
Keyword(s):  
Land Surface ◽  
Wrf Model ◽  
Surface Heterogeneity ◽  
Land Surface Models ◽  
Bottom Boundary ◽  
Surface Models ◽  
Land Surface Heterogeneity ◽  
Land Surfaces ◽  
The Impact ◽  
Fully Coupled

<p><span>Land-surface heterogeneity is known to play an important role in land-surface hydrology, which drives the bottom boundary condition for atmospheric models in numerical weather prediction (NWP) applications. However, the ultimate impact of land-surface heterogeneity on atmospheric boundary layer (ABL) development is still an open problem with implications for sub-grid scale (SGS) parameterizations for both NWP and climate modeling. Large-eddy simulation (LES) is often used to study the effects of land-surface heterogeneity on ABL development, most typically via specified surface fields which are not influenced by the atmosphere (i.e. semi-coupled). Heterogeneous land surfaces have been seen in previous studies to have a significant influence on ABL dynamics, particularly cloud production, in certain cases when semi-coupled to the atmosphere. </span></p><p><span>Here we use the Weather Research and Forecasting (WRF) model as an LES with both semi-coupled and fully-coupled land surfaces to investigate the impact of two-way coupling on the interaction between heterogeneous land surfaces and daytime ABLs. For semi-coupled simulations, the HydroBlocks land-surface model is run offline, drive</span><span>n by 4-km NLDAS-2 meteorology with Stage-IV radar rainfall data, and then used to specify the bottom boundary in WRF. The WRF-Hydro model is used for cases where the land surface is fully coupled to the WRF model. Both land-surface models use the Noah-MP model as their underlying physics package and add both subsurface and overland flow routing. </span><span>The WRF model uses a 100-m horizontal resolution, and the land-surface models use </span><span>high resolution (30 m) datasets that were upscaled to match the LES resolution for elevation, landcover, and soil type using NED, NLCD, and POLARIS respectively. </span><span>These LES experiments are performed over the ARM Southern Great Plains Site</span><span> atmospheric observatory in Oklahoma during the Summer of 2017 with a grid size of 100 km x 100 km to imitate a single cell in a modern climate model. </span><span>The impact of land-surface heterogeneity on the atmosphere is evaluated by comparing simulations using the fully heterogeneous land surfaces with simulations where the land surface is homogenized at each timestep, taking a domain-wide spatial mean value at every grid cell. </span><span>Results are evaluated primarily by the differences in the development of clouds and evolution of turbulent kinetic energy in the ABL. </span></p>

Response of the surface climate to different land surface models: WRF sensitivity to surface model options

2021 ◽  
Author(s):  
Daniela C.A. Lima ◽  
Rita M. Cardoso ◽  
Pedro M.M. Soares
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Wrf Model ◽  
Land Surface Model ◽  
Heat Fluxes ◽  
Surface Processes ◽  
Surface Model ◽  
Land Surface Models ◽  
Land Surface Processes ◽  
Surface Models

<p>The Weather Research and Forecasting (WRF) model version 4.2 includes different land surface schemes, allowing a better representation of the land surface processes. Four simulations with the WRF model differing in land surface models and options were investigated as a sensitivity study over the European domain. These experiments span from 2004-2006 with a one-month spin-up and were performed at 0.11<sup>o</sup> horizontal resolution with 50 vertical levels, following the CORDEX guidelines. The lateral boundary conditions were driven by ERA5 reanalysis from European Centre for Medium-Range Weather Forecasts. For the first experiment, the Noah land surface model was used. For the remaining simulations, the Noah-MP (multi-physics) land surface model was used with different runoff and groundwater options: (1) original surface and subsurface runoff (free drainage), (2) TOPMODEL with groundwater and (3) Miguez-Macho & Fan groundwater scheme. The physical parameterizations options are the same for all simulations. These experiments allow the analysis of the sensitivity of different land surface options and to understand how the representation of land surface processes impacts on the atmosphere properties. This study focusses on the investigation of land-atmosphere feedbacks trough the analysis of the soil moisture – temperature and soil moisture – precipitation interactions, latent and sensible heat fluxes, and moisture fluxes. The influence of different surface model options on atmospheric boundary layer is also explored.</p><p>Acknowledgements. The authors wish to acknowledge the LEADING (PTDC/CTA-MET/28914/2017) project funded by FCT. The authors would like to acknowledge the financial support FCT through project UIDB/50019/2020 – Instituto Dom Luiz.</p>

scholarly journals How to reconstruct aerosol-induced diffuse radiation scenario for simulating GPP in land surface models? An evaluation of reconstruction methods with ORCHIDEE_DFv1.0_DFforc

2021 ◽  
Vol 14 (4) ◽  
pp. 2029-2039
Author(s):  
Yuan Zhang ◽  
Olivier Boucher ◽  
Philippe Ciais ◽  
Laurent Li ◽  
Nicolas Bellouin
Keyword(s):  
Land Surface ◽  
Volcanic Eruptions ◽  
Diffuse Radiation ◽  
Surface Model ◽  
Diffuse Light ◽  
Land Surface Models ◽  
Aerosol Emission ◽  
Reconstruction Methods ◽  
Surface Models ◽  
The Impact

Abstract. The impact of diffuse radiation on photosynthesis has been widely documented in field measurements. This impact may have evolved over time during the last century due to changes in cloudiness, increased anthropogenic aerosol loads over polluted regions, and to sporadic volcanic eruptions curtaining the stratosphere with sulfate aerosols. The effects of those changes in diffuse light on large-scale photosynthesis (GPP) are difficult to quantify, and land surface models have been designed to simulate them. Investigating how anthropogenic aerosols have impacted GPP through diffuse light in those models requires carefully designed factorial simulations and a reconstruction of background diffuse light levels during the preindustrial period. Currently, it remains poorly understood how diffuse radiation reconstruction methods can affect GPP estimation and what fraction of GPP changes can be attributed to aerosols. In this study, we investigate different methods to reconstruct spatiotemporal distribution of the fraction of diffuse radiation (Fdf) under preindustrial aerosol emission conditions using a land surface model with a two-stream canopy light transmission scheme that resolves diffuse light effects on photosynthesis in a multi-layered canopy, ORCHIDEE_DF. We show that using a climatologically averaged monthly Fdf, as has been done by earlier studies, can bias the global GPP by up to 13 PgC yr−1 because this reconstruction method dampens the variability of Fdf and produces Fdf that is inconsistent with shortwave incoming surface radiation. In order to correctly simulate preindustrial GPP modulated by diffuse light, we thus recommend that the Fdf forcing field should be calculated consistently with synoptic, monthly, and inter-annual aerosol and cloud variability for preindustrial years. In the absence of aerosol and cloud data, alternative reconstructions need to retain the full variability in Fdf. Our results highlight the importance of keeping consistent Fdf and radiation for land surface models in future experimental designs that seek to investigate the impacts of diffuse radiation on GPP and other carbon fluxes.

scholarly journals An Improved Land Surface Emissivity Parameter for Land Surface Models Using Global Remote Sensing Observations

2006 ◽  
Vol 19 (12) ◽  
pp. 2867-2881 ◽  
Author(s):  
Menglin Jin ◽  
Shunlin Liang
Keyword(s):  
Land Surface ◽  
Regression Equations ◽  
Surface Emissivity ◽  
Land Surface Models ◽  
Community Land Model ◽  
Land Surface Emissivity ◽  
Variable Surface ◽  
Surface Models ◽  
Sensitivity Studies ◽  
The Impact

Abstract Because land surface emissivity (ɛ) has not been reliably measured, global climate model (GCM) land surface schemes conventionally set this parameter as simply constant, for example, 1 as in the National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Prediction (NCEP) model, and 0.96 for bare soil as in the National Center for Atmospheric Research (NCAR) Community Land Model version 2 (CLM2). This is the so-called constant-emissivity assumption. Accurate broadband emissivity data are needed as model inputs to better simulate the land surface climate. It is demonstrated in this paper that the assumption of the constant emissivity induces errors in modeling the surface energy budget, especially over large arid and semiarid areas where ɛ is far smaller than unity. One feasible solution to this problem is to apply the satellite-based broadband emissivity into land surface models. The Moderate Resolution Imaging Spectroradiometer (MODIS) instrument has routinely measured spectral emissivities (ɛλ) in six thermal infrared bands. The empirical regression equations have been developed in this study to convert these spectral emissivities to broadband emissivity (ɛ) required by land surface models. The observed emissivity data show strong seasonality and land-cover dependence. Specifically, emissivity depends on surface-cover type, soil moisture content, soil organic composition, vegetation density, and structure. For example, broadband ɛ is usually around 0.96–0.98 for densely vegetated areas [(leaf area index) LAI > 2], but it can be lower than 0.90 for bare soils (e.g., desert). To examine the impact of variable surface broadband emissivity, sensitivity studies were conducted using offline CLM2 and coupled NCAR Community Atmosphere Models, CAM2–CLM2. These sensitivity studies illustrate that large impacts of surface ɛ occur over deserts, with changes up to 1°–2°C in ground temperature, surface skin temperature, and 2-m surface air temperature, as well as evident changes in sensible and latent heat fluxes.

The Effect of Land Surface Heterogeneity and Background Wind on Shallow Cumulus Clouds and the Transition to Deeper Convection

2019 ◽  
Vol 76 (2) ◽  
pp. 401-419 ◽  
Author(s):  
Jungmin M. Lee ◽  
Yunyan Zhang ◽  
Stephen A. Klein
Keyword(s):  
Wind Speed ◽  
Land Surface ◽  
Surface Heterogeneity ◽  
Secondary Circulation ◽  
Length Scale ◽  
Background Wind ◽  
Cumulus Clouds ◽  
Shallow Cumulus ◽  
Land Surface Heterogeneity ◽  
The Impact

Abstract Idealized large-eddy simulations (LESs) with prescribed heterogeneous land surface heat fluxes are performed to study the impact of the heterogeneity length scale and background wind speed on the development of shallow cumulus and the subsequent transition to congestus/deep convection. We study the impact of land surface heterogeneity in an atmosphere that favors shallow convection but is also conditionally unstable with respect to deeper convection. We find that before the convection transition, larger and thicker shallow cumulus clouds are attached to moisture pools near the PBL top over patches with low evaporative fraction (referred to as “DRY”). This feature is attributable to a surface-induced secondary circulation whose development depends on the heterogeneity size and the background wind speed. With large patches (≥5 km) under zero ambient wind, the secondary mesoscale circulation promotes the vertical transport of moisture forming a moisture pool over DRY patches, while with smaller patches, no such circulation develops. The influence of the background wind on the secondary circulation is strong such that any wind stronger than 2 m s−1 effectively eliminates the impact of surface heterogeneity on the PBL and brings no secondary circulation. This is because the triggered secondary circulation is not strong enough to withstand the imposed background wind. Based on these, we propose two criteria for the convection transition, namely, that the heterogeneity length scale is greater than 5 km and that the background wind speed is less than Uc0, where Uc0 is the near-surface cross-patch wind speed of the secondary circulation under zero background wind for a given patch size and is about 1.5 m s−1 in our cases.

scholarly journals L-Band Soil Moisture Retrievals Using Microwave Based Temperature and Filtering. Towards Model-Independent Climate Data Records

2021 ◽  
Vol 13 (13) ◽  
pp. 2480
Author(s):  
Robin van der Schalie ◽  
Mendy van der Vliet ◽  
Nemesio Rodríguez-Fernández ◽  
Wouter A. Dorigo ◽  
Tracy Scanlon ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Passive Microwave ◽  
Climate Data ◽  
Land Surface Models ◽  
Surface Models ◽  
L Band ◽  
The Impact ◽  
Microwave Sensors

The CCI Soil Moisture dataset (CCI SM) is the most extensive climate data record of satellite soil moisture to date. To maximize its function as a climate benchmark, both long-term consistency and (model-) independence are high priorities. Two unique L-band missions integrated into the CCI SM are SMOS and SMAP. However, they lack the high-frequency microwave sensors needed to determine the effective temperature and snow/frozen flagging, and therefore use input from (varying) land surface models. In this study, the impact of replacing this model input by temperature and filtering based on passive microwave observations is evaluated. This is derived from an inter-calibrated dataset (ICTB) based on six passive microwave sensors. Generally, this leads to an expected increase in revisit time, which goes up by about 0.5 days (~15% loss). Only the boreal regions have an increased coverage due to more accurate freeze/thaw detection. The boreal regions become wetter with an increased dynamic range, while the tropics are dryer with decreased dynamics. Other regions show only small differences. The skill was evaluated against ERA5-Land and in situ observations. The average correlation against ERA5-Land increased by 0.05 for SMAP ascending/descending and SMOS ascending, whereas SMOS descending decreased by 0.01. For in situ sensors, the difference is less pronounced, with only a significant change in correlation of 0.04 for SM SMOS ascending. The results indicate that the use of microwave-based input for temperature and filtering is a viable and preferred alternative to the use of land surface models in soil moisture climate data records from passive microwave sensors.

scholarly journals Biogeochemical model of CO<sub>2</sub> and CH<sub>4</sub> production in anoxic Arctic soil microcosms

2016 ◽  
Author(s):  
Guoping Tang ◽  
Jianqiu Zheng ◽  
Xiaofeng Xu ◽  
Ziming Yang ◽  
David E. Graham ◽  
...  
Keyword(s):  
Land Surface ◽  
Climate Model ◽  
Co2 Production ◽  
Biogeochemical Model ◽  
Land Surface Models ◽  
Soil Redox Potential ◽  
Community Land Model ◽  
Arctic Soils ◽  
Surface Models ◽  
The Impact

Abstract. Soil organic carbon turnover to CO2 and CH4 is sensitive to soil redox potential and pH conditions. However, land surface models do not consider redox and pH in the aqueous phase explicitly, thereby limiting their use for making predictions in anoxic environments. Using recent data from incubations of Arctic soils, we extend the Community Land Model Carbon Nitrogen (CLM-CN) decomposition cascade to include simple organic substrate turnover, fermentation, Fe(III) reduction, and methanogenesis reactions, and assess the efficacy of various temperature and pH response functions. Incorporating the Windermere Humic Aqueous Model (WHAM) enables us to approximately describe the observed pH evolution without additional parameterization. Although Fe(III) reduction is normally assumed to compete with methanogenesis, the model predicts that Fe(III) reduction raises the pH from acidic to neutral, thereby reducing environmental stress to methanogens and accelerating methane production when substrates are not limiting. The equilibrium speciation predicts a substantial increase in CO2 solubility as pH increases, and taking into account CO2 adsorption to surface sites of metal oxides further decreases the predicted headspace gas-phase fraction at low pH. Without adequate representation of these speciation reactions, and the impact of pH, temperature, and pressure, CO2 production from closed microcosms can be substantially underestimated based on headspace CO2 measurements only. Our results demonstrate the efficacy of geochemical models for simulating soil biogeochemistry and provide predictive understanding and mechanistic representations that can be tested in land surface models to improve climate model predictions.

scholarly journals How to reconstruct diffuse radiation scenario for simulating GPP in land surface models?

2020 ◽  
Author(s):  
Yuan Zhang ◽  
Olivier Boucher ◽  
Philippe Ciais ◽  
Laurent Li ◽  
Nicolas Bellouin
Keyword(s):  
Land Surface ◽  
Volcanic Eruptions ◽  
Diffuse Radiation ◽  
Surface Model ◽  
Diffuse Light ◽  
Land Surface Models ◽  
Anthropogenic Aerosols ◽  
Aerosol Emission ◽  
Surface Models ◽  
The Impact

Abstract. The impact of diffuse radiation on photosynthesis has been widely documented in field measurements. This impact may have evolved over time during the last century due to changes in cloudiness, increased anthropogenic aerosol loads over polluted regions, and to sporadic volcanic eruptions curtaining the stratosphere with sulfate aerosols. The effect of those changes in diffuse light on large-scale photosynthesis (GPP) are difficult to quantify, and land surface models have been designed to simulate them. Investigating how anthropogenic aerosols have impacted GPP through diffuse light in those models requires carefully designed factorial simulations and a reconstruction of background diffuse light levels during the pre-industrial period. Currently, it remains poorly understood how diffuse radiation reconstruction methods can affect GPP estimation and what fraction of GPP changes can be attributed to aerosols. In this study, we investigate different methods to reconstruct spatio-temporal distribution of the fraction of diffuse radiation (Fdf) under pre-industrial aerosol emission conditions using a land surface model with a two-stream canopy light transmission scheme that resolves diffuse light effects on photosynthesis in a multi-layered canopy, ORCHIDEE_DF. We show that using a climatologically-averaged monthly Fdf, as has been done by earlier studies, can bias the global GPP by up to 13 Pg C yr−1 because this reconstruction method dampens the variability of Fdf and produces Fdf that is inconsistent with short-wave incoming surface radiation. In order to correctly simulate pre-industrial GPP modulated by diffuse light, we thus recommend that the Fdf forcing field should be calculated consistently with synoptic, monthly and inter-annual aerosol and cloud variability for pre-industrial years. In the absence of aerosol and cloud data, alternative reconstructions need to retain the full variability in Fdf. Our results highlight the importance of keeping consistent Fdf and radiation for land surface models in future experimental designs that seek to investigate the impacts of diffuse radiation on GPP and other carbon fluxes.

Sign in / Sign up

Export Citation Format

Share Document