scholarly journals Distinguishing between early- and late-covering crops in the land surface model Noah-MP: impact on simulated surface energy fluxes and temperature

2020 ◽  
Vol 17 (10) ◽  
pp. 2791-2805
Author(s):  
Kristina Bohm ◽  
Joachim Ingwersen ◽  
Josipa Milovac ◽  
Thilo Streck
Keyword(s):  
Land Use ◽  
Heat Flux ◽  
Surface Energy ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Land Surface ◽  
Land Surface Model ◽  
Surface Model ◽  
Energy Fluxes ◽  
Surface Energy Fluxes

Abstract. Land surface models are essential parts of climate and weather models. The widely used Noah-MP land surface model requires information on the leaf area index (LAI) and green vegetation fraction (GVF) as key inputs of its evapotranspiration scheme. The model aggregates all agricultural areas into a land use class termed “cropland and pasture”. In a previous study we showed that, on a regional scale, the GVF has a bimodal distribution formed by two crop groups differing in phenology and growth dynamics: early-covering crops (ECC; e.g., winter wheat, winter rapeseed, winter barley) and late-covering crops (LCC; e.g., corn, silage maize, sugar beet). That result can be generalized for central Europe. The present study quantifies the effect of splitting the land use class cropland and pasture of Noah-MP into ECC and LCC on surface energy fluxes and temperature. We further studied the influence of increasing the LCC share, which in the study area (the Kraichgau region, southwest Germany) is mainly the result of heavily subsidized biomass production, on energy partitioning at the land surface. We used the GVF dynamics derived from high-resolution (5 m × 5 m) RapidEye satellite data and measured LAI data for the simulations. Our results confirm that the GVF and LAI strongly influence the partitioning of surface energy fluxes, resulting in pronounced differences between simulations of ECC and LCC. Splitting up the generic crop into ECC and LCC had the strongest effect on land surface exchange processes in July–August. During this period, ECC are at the senescence growth stage or already harvested, while LCC have a well-developed ground-covering canopy. The generic crop resulted in humid bias, i.e., an increase in evapotranspiration by +0.5 mm d−1 (latent heat flux is 1.3 MJ m−2 d−1), decrease in sensible heat flux (H) by 1.2 MJ m−2  d−1 and decrease in surface temperature by −1 ∘C. The bias increased as the shares of ECC and LCC became similar. The observed differences will impact the simulations of processes in the planetary boundary layer. Increasing the LCC share from 28 % to 38 % in the Kraichgau region led to a decrease in latent heat flux (LE) and a heating up of the land surface in the early growing season. Over the second part of the season, LE increased and the land surface cooled down by up to 1 ∘C.

scholarly journals Distinguishing between early and late covering crops in the land surface model Noah-MP: Impact on simulated surface energy fluxes and temperature

2019 ◽  
Author(s):  
Kristina Bohm ◽  
Joachim Ingwersen ◽  
Josipa Milovac ◽  
Thilo Streck
Keyword(s):  
Land Use ◽  
Surface Energy ◽  
Land Surface ◽  
Regional Scale ◽  
Land Surface Model ◽  
Surface Model ◽  
Energy Fluxes ◽  
Area Index ◽  
Surface Energy Fluxes ◽  
Vegetation Fraction

Abstract. Land surface models are essential parts of climate and weather models. The widely used Noah-MP land surface model requires information on the leaf area index (LAI) and green vegetation fraction (GVF) as key inputs of its evapotranspiration scheme. The model aggregates all agricultural areas into a land use class termed Cropland and Pasture. In a previous study we showed that, on a regional scale, GVF has a bimodal distribution formed by two crop groups differing in phenology and growth dynamics: early covering crops (ECC, ex.: winter wheat, winter rapeseed, winter barley) and late covering crops (LCC, ex.: corn, silage maize, sugar beet). That result can be generalized for Central Europe. The present study quantifies the effect of splitting the land use class Cropland and Pasture of Noah-MP into ECC and LCC on surface energy fluxes and temperature. We further studied the influence of increasing the LCC share, which in the study area (the Kraichgau region, southwest Germany) is mainly the result of heavily subsidized biomass production, on energy partitioning at the land surface. We used the GVF dynamics derived from high-resolution (5 m × 5 m) RapidEye satellite data and measured LAI data for the simulations. Our results confirm that GVF and LAI strongly influence the partitioning of surface energy fluxes, resulting in pronounced differences between ECC and LCC simulations. Splitting up the generic crop into ECC and LCC had the strongest effect on land surface exchange processes in July–August. During this period, ECC are at the senescence growth stage or already harvested, while LCC have a well-developed, ground-covering canopy. The generic crop resulted in humid bias, i.e. an increase of evapotranspiration by +0.5 mm d−1 (LE: 1.3 MJ m−2 d−1), decrease of H by 1.2 MJ m−2 d−1 and decrease of surface temperature by −1 °C. The bias increased as the shares of ECC and LCC became similar. The observed differences will impact the simulations of processes in the planetary boundary layer. Increasing the LCC share from 28 to 38 % in the Kraichgau region led to a decrease of LE and a heating up of the land surface in the early growing season. Over the second part of the season, LE increased and the land surface cooled down by up to 1 °C.

scholarly journals WRF v.3.9 sensitivity to land surface model and horizontal resolution changes over North America

2021 ◽  
Author(s):  
Almudena García-García ◽  
Francisco José Cuesta-Valero ◽  
Hugo Beltrami ◽  
Fidel González-Rouco ◽  
Elena García-Bustamante
Keyword(s):  
Heat Flux ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Land Surface ◽  
Land Surface Model ◽  
Horizontal Resolution ◽  
Convective Precipitation ◽  
Surface Model ◽  
Near Surface ◽  
Low Latitudes

Abstract. Understanding the differences between regional simulations of land-atmosphere interactions and near-surface conditions is crucial for a more reliable representation of past and future climate. Here, we explore the effect of changes in the model's horizontal resolution on the simulated energy balance at the surface and near-surface conditions using the Weather Research and Forecasting (WRF) model. To this aim, an ensemble of twelve simulations using three different horizontal resolutions (25 km, 50 km and 100 km) and four different Land Surface Model (LSM) configurations over North America from 1980 to 2013 is developed. Our results show that finer resolutions lead to higher surface net shortwave radiation and maximum temperatures at mid- and high latitudes. At low latitudes over coastal areas, an increase in resolution leads to lower values of sensible heat flux and higher values of latent heat flux, as well as lower values of surface temperatures and higher values of precipitation and soil moisture in summer. The use of finer resolutions leads then to an increase in summer values of latent heat flux, convective and non-convective precipitation and soil moisture at low latitudes. The effect of the LSM choice is larger than the effect of horizontal resolution on the near-surface temperature conditions. By contrast, the effect of the LSM choice on the simulation of precipitation is weaker than the effect of horizontal resolution, showing larger differences among LSM simulations in summer and over regions with high latent heat flux. Comparison between observations and the simulation of daily maximum and minimum temperatures and accumulated precipitation indicates that the CLM4 LSM yields the lowest biases in maximum and minimum mean temperatures, but the highest biases in extreme temperatures. Increasing horizontal resolution leads to larger biases in accumulated precipitation over all regions particularly in summer. The reasons behind relate the partition between convective and non-convective precipitation, specially noticeable over western US.

scholarly journals An Empirical Latent Heat Flux Parameterization for the Noah Land Surface Model

2010 ◽  
Vol 49 (8) ◽  
pp. 1696-1713 ◽  
Author(s):  
Christopher M. Godfrey ◽  
David J. Stensrud
Keyword(s):  
Heat Flux ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Land Surface ◽  
Initial Conditions ◽  
Land Surface Model ◽  
Vegetation Coverage ◽  
Surface Model ◽  
Oklahoma Mesonet ◽  
Surface Observations

Abstract Proper partitioning of the surface energy fluxes that drive the evolution of the planetary boundary layer in numerical weather prediction models requires an accurate representation of initial land surface conditions. Unfortunately, soil temperature and moisture observations are unavailable in most areas and routine daily estimates of vegetation coverage and biomass are not easily available. This gap in observational capabilities seriously hampers the evaluation and improvement of land surface parameterizations, since model errors likely relate to improper initial conditions as much as to inaccuracies in the parameterizations. Two unique datasets help to overcome these difficulties. First, 1-km fractional vegetation coverage and leaf area index values can be derived from biweekly maximum normalized difference vegetation index composites obtained from daily observations by the Advanced Very High Resolution Radiometer onboard NOAA satellites. Second, the Oklahoma Mesonet supplies multiple soil temperature and moisture measurements at various soil depths each hour. Combined, these two datasets provide significantly improved initial conditions for a land surface model and allow an evaluation of the accuracy of the land surface model with much greater confidence than previously. Forecasts that both include and neglect these unique land surface observations are used to evaluate the value of these two data sources to land surface initializations. The dense network of surface observations afforded by the Oklahoma Mesonet, including surface flux data derived from special sensors, provides verification of the model results, which indicate that predicted latent heat fluxes still differ from observations by as much as 150 W m−2. This result provides a springboard for assessing parameterization errors within the model. A new empirical parameterization developed using principal-component regression reveals simple relationships between latent heat flux and other surface observations. Periods of very dry conditions observed across Oklahoma are used advantageously to derive a parameterization for evaporation from bare soil. Combining this parameterization with an empirical canopy transpiration scheme yields improved sensible and latent heat flux forecasts and better partitioning of the surface energy budget. Surface temperature and mixing ratio forecasts show improvement when compared with observations.

scholarly journals Implementation of dynamic crop growth processes into a land surface model: evaluation of energy, water and carbon fluxes under corn and soybean rotation

2013 ◽  
Vol 10 (6) ◽  
pp. 9897-9945 ◽  
Author(s):  
Y. Song ◽  
A. K. Jain ◽  
G. F. McIsaac
Keyword(s):  
Heat Flux ◽  
Latent Heat ◽  
Land Surface ◽  
Root Distribution ◽  
Land Surface Model ◽  
Surface Model ◽  
Energy Fluxes ◽  
Rotation System ◽  
Dynamic Case ◽  
Dynamic Crop Growth

Abstract. Worldwide expansion of agriculture is impacting Earth's climate by altering the carbon, water and energy fluxes, but climate in turn is impacting crop production. To study this two-way interaction and its impact on seasonal dynamics of carbon, water and energy fluxes, we implemented dynamic crop growth processes into a land surface model, the Integrated Science Assessment Model (ISAM). In particular, we implement crop specific phenology schemes, which account for light, water, and nutrient stresses while allocating the assimilated carbon to leaf, root, stem and grain pools; dynamic vegetation structure growth, which better simulate the LAI and canopy height; dynamic root distribution processes in the soil layers, which better simulate the root response of soil water uptake and transpiration; and litter fall due to fresh and old dead leaves to better represent the water and energy interception by both stem and brown leaves of the canopy during leaf senescence. Observational data for LAI, above and below ground biomass, and carbon, water and energy fluxes were compiled from two Ameri-Flux sites, Mead, NE and Bondville, IL, to calibrate and evaluate the model performance under corn (C4)-soybean (C3) rotation system over the period 2001–2004. The calibrated model was able to capture the diurnal and seasonal patterns of carbon assimilation, water and energy fluxes under the corn-soybean rotation system at these two sites. Specifically, the calculated GPP, net radiation fluxes at the top of canopy and latent heat fluxes compared well with observations. The largest bias in model results is in sensible heat flux (H) for corn and soybean at both sites. With dynamic carbon allocation and root distribution processes, model simulated GPP and latent heat flux (LH) were in much better agreement with observation data than for the without dynamic case. Modeled latent heat improved by 12–27% during the growing season at both sites, leading to the improvement in modeled GPP by 13–61% compared to the without dynamic case.

scholarly journals Improving the representation of cropland sites in the Community Land Model (CLM) version 5.0

2020 ◽  
Author(s):  
Theresa Boas ◽  
Heye Bogena ◽  
Thomas Grünwald ◽  
Bernard Heinesch ◽  
Dongryeol Ryu ◽  
...  
Keyword(s):  
Land Use ◽  
Heat Flux ◽  
Winter Wheat ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Field Data ◽  
Energy Fluxes ◽  
Cash Crop ◽  
Cover Cropping ◽  
Community Land Model

Abstract. The incorporation of a comprehensive crop module in land surface models offers the possibility to study the effect of agricultural land use and land management changes on the terrestrial water, energy and biogeochemical cycles. It may help to improve the simulation of biogeophysical and biogeochemical processes on regional and global scales in the framework of climate and land use change. In this study, the performance of the crop module of the Community Land Model version 5 (CLM5) was evaluated at point scale with site specific field data focussing on the simulation of seasonal and inter-annual variations in crop growth, planting and harvesting cycles, and crop yields as well as water, energy and carbon fluxes. In order to better represent agricultural sites, the model was modified by (1) implementing the winter wheat subroutines after Lu et al. (2017) in CLM5; (2) implementing plant specific parameters for sugar beet, potatoes and winter wheat, thereby adding these crop functional types (CFT) to the list of actively managed crops in CLM5; (3) introducing a cover cropping subroutine that allows multiple crop types on the same column within one year. The latter modification allows the simulation of cropping during winter months before usual cash crop planting begins in spring, which is a common agricultural management technique in humid and sub-humid regions. We compared simulation results with field data and found that both the parameterization of the CFTs, as well as the winter wheat subroutines, led to a significant simulation improvement in terms of energy fluxes, leaf area index (LAI), net ecosystem exchange (RMSE reduction for latent and sensible heat by up to 57 % and 59 % respectively) and crop yield (up to 87 % improvement in winter wheat yield prediction) compared with default model results. The cover cropping subroutine yielded a substantial improvement in representation of field conditions after harvest of the main cash crop (winter season) in terms of LAI curve and latent heat flux (reduction of winter time RMSE for latent heat flux by 42 %). We anticipate that our model modifications offer opportunities to improve yield predictions, to study the effects of large-scale cover cropping on energy fluxes, soil carbon and nitrogen pools, and soil water storage in future studies with CLM5.

scholarly journals Implementation of dynamic crop growth processes into a land surface model: evaluation of energy, water and carbon fluxes under corn and soybean rotation

2013 ◽  
Vol 10 (12) ◽  
pp. 8039-8066 ◽  
Author(s):  
Y. Song ◽  
A. K. Jain ◽  
G. F. McIsaac
Keyword(s):  
Latent Heat ◽  
Land Surface ◽  
Root Distribution ◽  
Carbon Allocation ◽  
Land Surface Model ◽  
Crop Growth ◽  
Surface Model ◽  
Energy Fluxes ◽  
Growth Processes ◽  
Dynamic Crop Growth

Abstract. Worldwide expansion of agriculture is impacting the earth's climate by altering carbon, water, and energy fluxes, but the climate in turn is impacting crop production. To study this two-way interaction and its impact on seasonal dynamics of carbon, water, and energy fluxes, we implemented dynamic crop growth processes into a land surface model, the Integrated Science Assessment Model (ISAM). In particular, we implemented crop-specific phenology schemes and dynamic carbon allocation schemes. These schemes account for light, water, and nutrient stresses while allocating the assimilated carbon to leaf, root, stem, and grain pools. The dynamic vegetation structure simulation better captured the seasonal variability in leaf area index (LAI), canopy height, and root depth. We further implemented dynamic root distribution processes in soil layers, which better simulated the root response of soil water uptake and transpiration. Observational data for LAI, above- and belowground biomass, and carbon, water, and energy fluxes were compiled from two AmeriFlux sites, Mead, NE, and Bondville, IL, USA, to calibrate and evaluate the model performance. For the purposes of calibration and evaluation, we use a corn–soybean (C4–C3) rotation system over the period 2001–2004. The calibrated model was able to capture the diurnal and seasonal patterns of carbon assimilation and water and energy fluxes for the corn–soybean rotation system at these two sites. Specifically, the calculated gross primary production (GPP), net radiation fluxes at the top of the canopy, and latent heat fluxes compared well with observations. The largest bias in model results was in sensible heat flux (SH) for corn and soybean at both sites. The dynamic crop growth simulation better captured the seasonal variability in carbon and energy fluxes relative to the static simulation implemented in the original version of ISAM. Especially, with dynamic carbon allocation and root distribution processes, the model's simulated GPP and latent heat flux (LH) were in much better agreement with observational data than for the static root distribution simulation. Modeled latent heat based on dynamic growth processes increased by 12–27% during the growing season at both sites, leading to an improvement in modeled GPP by 13–61% compared to the estimates based on the original version of the ISAM.

scholarly journals Quantifying the thermodynamic entropy budget of the land surface: is this useful?

2011 ◽  
Vol 2 (1) ◽  
pp. 87-103 ◽  
Author(s):  
N. A. Brunsell ◽  
S. J. Schymanski ◽  
A. Kleidon
Keyword(s):  
Heat Flux ◽  
Entropy Production ◽  
Eddy Covariance ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Land Surface ◽  
Simultaneous Increase ◽  
Surface Model ◽  
Thermodynamic Entropy ◽  
Entropy Budget

Abstract. As a system is moved away from a state of thermodynamic equilibrium, spatial and temporal heterogeneity is induced. A possible methodology to assess these impacts is to examine the thermodynamic entropy budget and assess the role of entropy production and transfer between the surface and the atmosphere. Here, we adopted this thermodynamic framework to examine the implications of changing vegetation fractional cover on land surface energy exchange processes using the NOAH land surface model and eddy covariance observations. Simulations that varied the relative fraction of vegetation were used to calculate the resultant entropy budget as a function of fraction of vegetation. Results showed that increasing vegetation fraction increases entropy production by the land surface while decreasing the overall entropy budget (the rate of change in entropy at the surface). This is accomplished largely via simultaneous increase in the entropy production associated with the absorption of solar radiation and a decline in the Bowen ratio (ratio of sensible to latent heat flux), which leads to increasing the entropy export associated with the latent heat flux during the daylight hours and dominated by entropy transfer associated with sensible heat and soil heat fluxes during the nighttime hours. Eddy covariance observations also show that the entropy production has a consistent sensitivity to land cover, while the overall entropy budget appears most related to the net radiation at the surface, however with a large variance. This implies that quantifying the thermodynamic entropy budget and entropy production is a useful metric for assessing biosphere-atmosphere-hydrosphere system interactions.

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