scholarly journals Explicit Representation of Spatial Subgrid-Scale Heterogeneity in an ESM

2016 ◽  
Vol 17 (5) ◽  
pp. 1357-1371 ◽  
Author(s):  
Philipp de Vrese ◽  
Stefan Hagemann
Keyword(s):  
Land Surface ◽  
Large Fraction ◽  
Atmospheric Model ◽  
Surface Fluxes ◽  
Earth System ◽  
Subgrid Scale ◽  
Effective Parameters ◽  
Max Planck ◽  
Near Surface ◽  
Horizontal Length

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.

scholarly journals Assessing the Impact of Changes in Land Surface Conditions on WRF Predictions in Arid Regions

2020 ◽  
Vol 21 (12) ◽  
pp. 2829-2853 ◽  
Author(s):  
Marouane Temimi ◽  
Ricardo Fonseca ◽  
Narendra Nelli ◽  
Michael Weston ◽  
Mohan Thota ◽  
...  
Keyword(s):  
Eddy Covariance ◽  
Soil Texture ◽  
Land Surface ◽  
Surface Wind ◽  
Surface Fluxes ◽  
Abu Dhabi ◽  
Horizontal Wind ◽  
Cold Bias ◽  
Near Surface ◽  
The Impact

AbstractA thorough evaluation of the Weather Research and Forecasting (WRF) Model is conducted over the United Arab Emirates, for the period September 2017–August 2018. Two simulations are performed: one with the default model settings (control run), and another one (experiment) with an improved representation of soil texture and land use land cover (LULC). The model predictions are evaluated against observations at 35 weather stations, radiosonde profiles at the coastal Abu Dhabi International Airport, and surface fluxes from eddy-covariance measurements at the inland city of Al Ain. It is found that WRF’s cold temperature bias, also present in the forcing data and seen almost exclusively at night, is reduced when the surface and soil properties are updated, by as much as 3.5 K. This arises from the expansion of the urban areas, and the replacement of loamy regions with sand, which has a higher thermal inertia. However, the model continues to overestimate the strength of the near-surface wind at all stations and seasons, typically by 0.5–1.5 m s−1. It is concluded that the albedo of barren/sparsely vegetated regions in WRF (0.380) is higher than that inferred from eddy-covariance observations (0.340), which can also explain the referred cold bias. At the Abu Dhabi site, even though soil texture and LULC are not changed, there is a small but positive effect on the predicted vertical profiles of temperature, humidity, and horizontal wind speed, mostly between 950 and 750 hPa, possibly because of differences in vertical mixing.

scholarly journals Simulating carbon exchange using a regional atmospheric model coupled to an advanced land-surface model

2008 ◽  
Vol 5 (5) ◽  
pp. 4161-4207 ◽  
Author(s):  
H. W. Ter Maat ◽  
R. W. A. Hutjes
Keyword(s):  
Carbon Dioxide ◽  
Land Surface ◽  
Large Scale ◽  
Regional Scale ◽  
Atmospheric Model ◽  
Surface Fluxes ◽  
Heat Fluxes ◽  
Surface Model ◽  
Carbon Exchange ◽  
Regional Atmospheric Modelling System

Abstract. A large scale mismatch exists between our understanding and quantification of ecosystem atmosphere exchange of carbon dioxide at local scale and continental scales. This paper will focus on the carbon exchange on the regional scale to address the following question: What are the main controlling factors determining atmospheric carbon dioxide content at a regional scale? We use the Regional Atmospheric Modelling System (RAMS), coupled with a land surface scheme simulating carbon, heat and momentum fluxes (SWAPS-C), and including also sub models for urban and marine fluxes, which in principle include the main controlling mechanisms and capture the relevant dynamics of the system. To validate the model, observations are used which were taken during an intensive observational campaign in the central Netherlands in summer 2002. These included flux-site observations, vertical profiles at tall towers and spatial fluxes of various variables taken by aircraft. The coupled regional model (RAMS-SWAPS-C) generally does a good job in simulating results close to reality. The validation of the model demonstrates that surface fluxes of heat, water and CO2 are reasonably well simulated. The comparison against aircraft data shows that the regional meteorology is captured by the model. Comparing spatially explicit simulated and observed fluxes we conclude that in general simulated latent heat fluxes are underestimated by the model to the observations which exhibit large standard deviation for all flights. Sensitivity experiments demonstrated the relevance of the urban emissions of carbon dioxide for the carbon balance in this particular region. The same test also show the relation between uncertainties in surface fluxes and those in atmospheric concentrations.

scholarly journals Modeling the Effect of Desert Urbanization on Local Climate and Natural Dust Generation: A Case Study for Erbil, Iraq

Urban Science ◽  
2020 ◽  
Vol 4 (4) ◽  
pp. 46
Author(s):  
Sherzad T. Tahir ◽  
Huei-Ping Huang
Keyword(s):  
Land Surface ◽  
Numerical Models ◽  
Surface Wind ◽  
Surface Fluxes ◽  
Slight Reduction ◽  
Rapid Urbanization ◽  
Near Surface ◽  
Local Climate ◽  
Surface Dust ◽  
Dust Generation

This study uses a suite of meteorological and land-surface models to quantify the changes in local climate and surface dust fluxes associated with desert urbanization. Formulas connecting friction velocity and soil moisture to dust generation are used to quantify surface fluxes for natural wind-blown dust. The models are used to conduct a series of simulations for the desert city of Erbil across a period of rapid urbanization. The results show significant nighttime warming and weak but robust daytime cooling associated with desert urbanization. A slight reduction in near-surface wind speed is also found in the areas undergoing urbanization. These findings are consistent with previous empirical and modeling studies on other desert cities. Numerical models and empirical formulas are used to produce climatological maps of surface dust fluxes as a function of season, and for the pre- and post-urbanization eras. This framework can potentially be used to bridge the gap in observation on the trends in local dust generation associated with land-use changes and urban expansions.

Impact of improved land model depth and hydrology on climate change projections

2020 ◽  
Author(s):  
Norman Steinert ◽  
Fidel González-Rouco ◽  
Stefan Hagemann ◽  
Philipp de Vrese ◽  
Elena García-Bustamante ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Surface ◽  
Earth System ◽  
Energy Propagation ◽  
Near Surface ◽  
Bottom Boundary ◽  
System Models ◽  
Model Component ◽  
And Storage ◽  
Earth System Models

<p>The representation of the thermal and hydrological state in the land model component of Earth System Models is crucial to have a realistic simulation of subsurface processes and the coupling between the atmo-, lito- and biosphere. There is evidence suggesting an inaccurate simulation of subsurface thermodynamics in current-generation Earth System Models, which have Land Surface Models that are too shallow. In simulations with a bottom boundary too close to the surface, the energy propagation and spatio-temporal variability of subsurface temperatures are affected. This potentially restrains the simulation of land-air interactions and subsurface phenomena, e.g. energy/moisture balance and storage capacity, freeze/thaw cycles and permafrost evolution. We introduce modifications for a deeper soil into the JSBACH soil model component of the MPI-ESM for climate projections of the 21st century. Subsurface layers are added progressively to increase the bottom boundary depth from 10m to 1400m. This leads to near-surface cooling of the soil and encourages regional terrestrial energy uptake by one order of magnitude and more. <br>The depth-changes in the soil also have implications for the hydrological regime, in which the moisture between the surface and the bedrock is sensitive to variations in the thermal regime. Additionally, we compare two different global soil parameter datasets that have major implications for the vertical distribution and availability of soil moisture and its exchange with the land surface. The implementation of supercool water and water phase changes in the soil creates a coupling between the soil thermal and hydrological regimes. In both cases of bottom boundary and water depth changes, we explore the sensitivity of JSBACH from the perspective of changes in the soil thermodynamics, energy balance and storage, as well as the effect of including freezing and thawing processes and their influence on the simulation of permafrost areas in the Northern Hemisphere high latitudes. The latter is of particular interest due to their vulnerability to long-term climate change.</p>

scholarly journals Separation of the Effects of Land and Climate Model Errors on Simulated Contemporary Land Carbon Cycle Trends in the MPI Earth System Model version 1*

2014 ◽  
Vol 28 (1) ◽  
pp. 272-291 ◽  
Author(s):  
Daniela Dalmonech ◽  
Sönke Zaehle ◽  
Gregor J. Schürmann ◽  
Victor Brovkin ◽  
Christian Reick ◽  
...  
Keyword(s):  
Land Surface ◽  
Climate Model ◽  
Earth System Model ◽  
System Model ◽  
Surface Model ◽  
Earth System ◽  
Model Errors ◽  
Max Planck ◽  
C Cycle ◽  
C Stocks

Abstract The capacity of earth system models (ESMs) to make reliable projections of future atmospheric CO2 and climate is strongly dependent on the ability of the land surface model to adequately simulate the land carbon (C) cycle. Defining “adequate” performance of the land model requires an understanding of the contributions of climate model and land model errors to the land C cycle. Here, a benchmarking framework is applied based on significant, observed characteristics of the land C cycle for the contemporary period, for which sufficient evaluation data are available, to test the ability of the JSBACH land surface component of the Max Planck Institute Earth System Model (MPI-ESM) to simulate land C trends. Particular attention is given to the role of potential effects caused by climate biases, and therefore investigation is made of the results of model configurations in which JSBACH is interactively “coupled” to atmosphere and ocean components and of an “uncoupled” configuration, where JSBACH is driven by reconstructed meteorology. The ability of JSBACH to simulate the observed phase of phenology and seasonal C fluxes is not strongly affected by climate biases. Contrarily, noticeable differences in the simulated gross primary productivity and land C stocks emerge between coupled and uncoupled configurations, leading to significant differences in the decadal terrestrial C balance and its sensitivity to climate. These differences are strongly controlled by climate biases of the MPI-ESM, in particular those affecting soil moisture. To effectively characterize model performance, the potential effects of climate biases on the land C dynamics need to be considered during the development and calibration of land surface models.

scholarly journals Verification of Land–Atmosphere Coupling in Forecast Models, Reanalyses, and Land Surface Models Using Flux Site Observations

2018 ◽  
Vol 19 (2) ◽  
pp. 375-392 ◽  
Author(s):  
Paul A. Dirmeyer ◽  
Liang Chen ◽  
Jiexia Wu ◽  
Chul-Su Shin ◽  
Bohua Huang ◽  
...  
Keyword(s):  
Surface Energy ◽  
Land Surface ◽  
Model Development ◽  
Surface Flux ◽  
Surface Fluxes ◽  
Model Systems ◽  
Shortwave Radiation ◽  
Spatial And Temporal Variability ◽  
Near Surface ◽  
Flux Tower

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.

The evaluation of land surface parameters for model to derive land surface fluxes in the Tibetan Plateau

2021 ◽  
Author(s):  
Weiqiang Ma ◽  
Yaoming Ma ◽  
Yizhe Han ◽  
Wei Hu ◽  
Lei Zhong ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Land Surface ◽  
Atmospheric Model ◽  
Surface Fluxes ◽  
Heat Fluxes ◽  
The Tibetan Plateau ◽  
Default Model ◽  
Model Configuration

<p>Firstly, based on the difference of model and in-situ observations, a serious of sensitive experiments were done by using WRF. In order to use remote sensing products, a land-atmosphere model was initialized by ingesting land surface parameters, such as AMSR-E RS products, and the results were compared with the default model configuration and with in-situ long-term CAMP/Tibet observations.</p><p>Secondly, a land-atmosphere model was initialized by ingesting AMSR-E products, and the results were compared with the default model configuration and with in-situ long-term CAMP/Tibet observations. The differences between the AMSR-E initialized model runs with the default model configuration and in situ data showed an apparent inconsistency in the model-simulated land surface heat fluxes. The results showed that the soil moisture was sensitive to the specific model configuration. To evaluate and verify the model stability, a long-term modeling study with AMSR-E soil moisture data ingestion was performed. Based on test simulations, AMSR-E data were assimilated into an atmospheric model for July and August 2007. The results showed that the land surface fluxes agreed well with both the in-situ data and the results of the default model configuration. Therefore, the simulation can be used to retrieve land surface heat fluxes from an atmospheric model over the Tibetan Plateau.</p><p>All of the different methods will clarify the land surface heating field in complex plateau, it also can affect atmospheric cycle over the Tibetan Plateau even all of the global atmospheric cycle pattern.</p>

scholarly journals Flux Replacement as a Method to Diagnose Coupled Land–Atmosphere Model Feedback

2004 ◽  
Vol 5 (6) ◽  
pp. 1034-1048 ◽  
Author(s):  
Paul A. Dirmeyer ◽  
Mei Zhao
Keyword(s):  
Surface State ◽  
Land Surface ◽  
Climate Model ◽  
Initial Conditions ◽  
Systematic Errors ◽  
Surface Fluxes ◽  
Boreal Summer ◽  
Near Surface ◽  
Soil Wetness ◽  
The Impact

Abstract The potential role of the land surface state in improving predictions of seasonal climate is investigated with a coupled land–atmosphere climate model. Climate simulations for 18 boreal-summer seasons (1982–99) have been conducted with specified observed sea surface temperature (SST). The impact on prediction skill of the initial land surface state (interannually varying versus climatological soil wetness) and the effect of errors in downward surface fluxes (precipitation and longwave/shortwave radiation) over land are investigated with a number of parallel experiments. Flux errors are addressed by replacing the downward fluxes with observed values in various combinations to ascertain the separate roles of water and energy flux errors on land surface state variables, upward water and energy fluxes from the land surface, and the important climate variables of precipitation and near-surface air temperature. Large systematic errors are found in the model, which are only mildly alleviated by the specification of realistic initial soil wetness. The model shows little skill in simulating seasonal anomalies of precipitation, but it does have skill in simulating temperature variations. Replacement of the downward surface fluxes has a clear positive impact on systematic errors, suggesting that the land–atmosphere feedback is helping to exacerbate climate drift. Improvement in the simulation of year-to-year variations in climate is even more evident. With flux replacement, the climate model simulates temperature anomalies with considerable skill over nearly all land areas, and a large fraction of the globe shows significant skill in the simulation of precipitation anomalies. This suggests that the land surface can communicate climate anomalies back to the atmosphere, given proper meteorological forcing. Flux substitution appears to have the largest benefit to improving precipitation skill over the Northern Hemisphere midlatitudes, whereas use of realistic land surface initial conditions improves skill to significant levels over regions of the Southern Hemisphere. Correlations between sets of integrations show that the model has a robust and systematic global response to SST anomalies.

Common evaluation/evolution of cloud-radiation processes from 25km S2S to 3km NWP

2020 ◽  
Author(s):  
Stan Benjamin ◽  
Joseph Joseph Olson ◽  
Shan Sun ◽  
Georg Georg Grell ◽  
Curtis Curtis Alexander
Keyword(s):  
Solar Radiation ◽  
Turbulent Mixing ◽  
Earth System ◽  
Subgrid Scale ◽  
System Research ◽  
Shallow Convection ◽  
Near Surface ◽  
Land System ◽  
Scale Models ◽  
Physical Parameterizations

<p>Subgrid-scale cloud representation and the closely related surface-energy balance continue to be a central challenge from subseasonal-to-seasonal models down to storm-scale models applied for forecast duration of only a few hours. Previously, NOAA/ESRL confirmed this issue from 3-km model (HRRR using WRF-ARW) for short-range forecasting including sub-grid-scale cloud representation up to a 25-km subseasonal model (FV3-GFS) testing a common suite of scale-aware physical parameterizations.  </p><p>In a major physics suite component -- modified representation of subgrid cloud water resulted in much improved agreement with radiation measurements as shown with 2018-2020 testing of the 3km HRRR model. Latest results will be shown using SURFRAD radiation and METAR ceiling observations, indicating much improved bias in downward solar radiation and in cloud location (via mean absolute error metric), as well as with 2m temperature and precipitation.</p><p>In addition, new evaluations with the same convection-allowing suite (“mesoscale” suite) of physical parameterizations revised further for subseasonal 30-day tests over summer and winter periods with the 25km NOAA FV3-GFS model. These results are compared with CERES-estimated cloud and downward solar radiation fields. The radiation results from this very preliminary subseasonal test with the ESRL-HRRR physics suite will be compared with previous subseasonal tests using the GFS physics suite and at different horizontal resolution.  This global application now confirms much better downward solar-radiation results over oceans for both January and June from a Nov-2019 version over a 2018 of the “mesoscale” suite.</p><p>Background: NOAA Earth System Research Laboratory, together with NCAR, has developed this parameterization suite (turbulent mixing, deep/shallow convection, 9-layer land/snow/vegetation/lake model) to improve PBL biases (temperature and moisture) including better representation of clouds and precipitation. This parameterization suite development has been accompanied by an effort for improved data assimilation of clouds, near-surface observations and radar for the atmosphere-land system.</p><p>Subgrid-scale cloud representation continues to be a central challenge from subseasonal-to-seasonal models down to storm-scale models applied for forecast duration of only a few hours.   Previously, NOAA/ESRL confirmed this issue from 3-km model (HRRR) for short-range forecasting including sub-grid-scale cloud representation up to a 60-km subseasonal model testing a common suite of scale-aware physical parameterizations.   Some progress has been made in 2018-2019 to substantially reduce cloud deficiency and excessive downward solar radiation at least over land areas.</p><p>Recent development and refinements to this common suite of physical parameterizations for scale-aware deep/shallow convection and boundary-layer mixing over this wide range of time and spatial scales will be reported in this presentation showing some progress. Evaluation of components of this suite is being evaluated for cloud/radiation (using SURFRAD, CERES, METAR ceiling) and near-surface (METAR, mesonet, aircraft, rawinsonde).</p><p>NOAA Earth System Research Laboratory, together with NCAR, has developed this parameterization suite (turbulent mixing, deep/shallow convection, 9-layer land/snow/vegetation model) to improve PBL biases (temperature and moisture) including better representation of clouds and precipitation. This parameterization suite development has been accompanied by an effort for improved data assimilation of clouds, near-surface observations and radar for the atmosphere-land system.  </p><p>The MYNN boundary-layer EDMF scheme (Olson, et al 2019), RUC land-surface model (Smirnova et al. 2016 MWR), Grell-Freitas scheme (2014, Atmos. Chem. Phys.), and aerosol-aware cloud microphysics (Thompson and Eidhammer 2015) have been applied and tested extensively for the NOAA hourly updated 3-km High-Resolution Rapid Refresh (HRRR) and 13-km Rapid Refresh model/assimilation systems over the United States and North America.   This mesoscale but also scale-aware suite is being tested,</p>

scholarly journals A multi-layer land surface energy budget model for implicit coupling with global atmospheric simulations

2016 ◽  
Vol 9 (1) ◽  
pp. 223-245 ◽  
Author(s):  
J. Ryder ◽  
J. Polcher ◽  
P. Peylin ◽  
C. Ottlé ◽  
Y. Chen ◽  
...  
Keyword(s):  
Surface Layer ◽  
Energy Budget ◽  
Land Surface ◽  
Large Time ◽  
Atmospheric Model ◽  
Wave Radiation ◽  
Surface Model ◽  
System Modelling ◽  
Earth System ◽  
Specific Calculation

Abstract. In Earth system modelling, a description of the energy budget of the vegetated surface layer is fundamental as it determines the meteorological conditions in the planetary boundary layer and as such contributes to the atmospheric conditions and its circulation. The energy budget in most Earth system models has been based on a big-leaf approach, with averaging schemes that represent in-canopy processes. Furthermore, to be stable, that is to say, over large time steps and without large iterations, a surface layer model should be capable of implicit coupling to the atmospheric model. Surface models with large time steps, however, have difficulties in reproducing consistently the energy balance in field observations. Here we outline a newly developed numerical model for energy budget simulation, as a component of the land surface model ORCHIDEE-CAN (Organising Carbon and Hydrology In Dynamic Ecosystems – CANopy). This new model implements techniques from single-site canopy models in a practical way. It includes representation of in-canopy transport, a multi-layer long-wave radiation budget, height-specific calculation of aerodynamic and stomatal conductance, and interaction with the bare-soil flux within the canopy space. Significantly, it avoids iterations over the height of the canopy and so maintains implicit coupling to the atmospheric model LMDz (Laboratoire de Météorologie Dynamique Zoomed model). As a first test, the model is evaluated against data from both an intensive measurement campaign and longer-term eddy-covariance measurements for the intensively studied Eucalyptus stand at Tumbarumba, Australia. The model performs well in replicating both diurnal and annual cycles of energy and water fluxes, as well as the vertical gradients of temperature and of sensible heat fluxes.

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