scholarly journals Weather Reasearch and Forecasting Model Simulation of a Snowfall Event in Southern Brazil

2021 ◽  
Vol 14 (2) ◽  
pp. 1194
Author(s):  
Ricardo Antonio Mollmann Junior ◽  
Rita de Cássia Marquês Alves ◽  
Gabriel Bonow Münchow ◽  
Osvaldo Luiz Leal de Moraes ◽  
Caroline Azzolini Pontel
Keyword(s):  
Land Surface ◽  
Model Simulation ◽  
Land Surface Model ◽  
Temporal Distribution ◽  
Surface Model ◽  
Southern Brazil ◽  
Single Moment ◽  
Model Scheme ◽  
Snowfall Event ◽  
South Of Brazil

 This study evaluates the reliability of the Weather Research and Forecasting (WRF) to simulate a snowfall event in the south of Brazil. The event in August 2013 was considered one of the most intense in recent years in the region with the highest topographic elevations between the states of Rio Grande do Sul (RS) and Santa Catarina (SC). The Snowfall in the mountain region of RS and SC was associated with the configuration involving a polar anticyclone and the intensification of an extratropical cyclone over the Atlantic Ocean. The WRF simulation results demonstrated the model's viability to predict the event, but without the magnitude representation of the phenomenon. The WRF simulation underestimated the results for the accumulated and area of the snowfall region, which may be linked to overestimations of surface and vertical air temperature and liquid water precipitation.  These results were attributed to the choice of WRF Single–moment 6–class (WSM6) microphysics and in the Noah Land Surface Model scheme. Despite these limitations, WRF has proved to be an important tool for predicting the spatial and temporal distribution of snowfall and precipitation in the higher regions of southern Brazil.

scholarly journals Multidataset Study of Optimal Parameter and Uncertainty Estimation of a Land Surface Model with Bayesian Stochastic Inversion and Multicriteria Method

2004 ◽  
Vol 43 (10) ◽  
pp. 1477-1497 ◽  
Author(s):  
Youlong Xia ◽  
Mrinal K. Sen ◽  
Charles S. Jackson ◽  
Paul L. Stoffa
Keyword(s):  
Land Surface ◽  
Root Zone ◽  
Model Simulation ◽  
Optimal Parameter ◽  
Land Surface Model ◽  
Heat Fluxes ◽  
Surface Model ◽  
Optimal Parameters ◽  
Stochastic Inversion ◽  
The Impact

Abstract This study evaluates the ability of Bayesian stochastic inversion (BSI) and multicriteria (MC) methods to search for the optimal parameter sets of the Chameleon Surface Model (CHASM) using prescribed forcing to simulate observed sensible and latent heat fluxes from seven measurement sites representative of six biomes including temperate coniferous forests, tropical forests, temperate and tropical grasslands, temperate crops, and semiarid grasslands. Calibration results with the BSI and MC show that estimated optimal values are very similar for the important parameters that are specific to the CHASM model. The model simulations based on estimated optimal parameter sets perform much better than the default parameter sets. Cross-validations for two tropical forest sites show that the calibrated parameters for one site can be transferred to another site within the same biome. The uncertainties of optimal parameters are obtained through BSI, which estimates a multidimensional posterior probability density function (PPD). Marginal PPD analyses show that nonoptimal choices of stomatal resistance would contribute most to model simulation errors at all sites, followed by ground and vegetation roughness length at six of seven sites. The impact of initial root-zone soil moisture and nonmosaic approach on estimation of optimal parameters and their uncertainties is discussed.

scholarly journals Evaluating the performance of the land surface model ORCHIDEE-CAN on water and energy flux estimation with a single- and a multi- layer energy budget scheme

2016 ◽  
Author(s):  
Yiying Chen ◽  
James Ryder ◽  
Vladislav Bastrikov ◽  
Matthew J. McGrath ◽  
Kim Naudts ◽  
...  
Keyword(s):  
Energy Budget ◽  
Land Surface ◽  
Model Simulation ◽  
Canopy Structure ◽  
Land Surface Model ◽  
Single Layer ◽  
Surface Model ◽  
Forest Types ◽  
Layer Model ◽  
Single Layer Model

Abstract. Canopy structure is one of the most important vegetation characteristics for land-atmosphere interactions, as it determines the energy and scalar exchanges between the land surface and the overlying air mass. In this study we evaluated the performance of a newly developed multi-layer energy budget in the land surface model ORCHIDEE-CAN (Organising Carbon and Hydrology In Dynamic Ecosystems – CANopy), which simulates canopy structure and can be coupled to an atmospheric model using an implicit coupling procedure. We aim to provide a set of acceptable parameter values for a range of forest types. Top-canopy and sub-canopy flux observations from eight sites were collected in order to conduct this evaluation. The sites crossed climate zones from temperate to boreal and the vegetation types included deciduous, evergreen broad leaved and evergreen needle leaved forest with a maximum LAI (all-sided) ranging from 3.5 to 7.0. The parametrization approach proposed in this study was based on three selected physical processes – namely the diffusion, advection and turbulent mixing within the canopy. Short-term sub-canopy observations and long-term surface fluxes were used to calibrate the parameters in the sub-canopy radiation, turbulence and resistances modules with an automatic tuning process. The multi-layer model was found to capture the dynamics of sub-canopy turbulence, temperature and energy fluxes. The performance of the new multi-layer model was further compared against the existing single-layer model. Although, the multi-layer model simulation results showed little or no improvements to both the nighttime energy balance and energy partitioning during winter compared with a single-layer model simulation, the increased model complexity does provide a more detailed description of the canopy micrometeorology of various forest types. The multi-layer model links to potential future environmental and ecological studies such as the assessment of in-canopy species vulnerability to climate change, the climate effects of disturbance intensities and frequencies, and the consequences of biogenic volatile organic compounds (BVOC) emissions from the terrestrial ecosystem.

scholarly journals Improving the ISBA<sub>CC</sub> land surface model simulation of water and carbon fluxes and stocks over the Amazon forest

2015 ◽  
Vol 8 (6) ◽  
pp. 1709-1727 ◽  
Author(s):  
E. Joetzjer ◽  
C. Delire ◽  
H. Douville ◽  
P. Ciais ◽  
B. Decharme ◽  
...  
Keyword(s):  
Land Surface ◽  
Model Simulation ◽  
Meta Analysis ◽  
Land Surface Model ◽  
Carbon Fluxes ◽  
Surface Model ◽  
Amazon Forest ◽  
Autotrophic Respiration ◽  
Soil Water Stress ◽  
Use Efficiency

Abstract. We evaluate the ISBACC (Interaction Soil Biosphere Atmosphere Carbon Cycle) land surface model (LSM) over the Amazon forest, and propose a revised parameterization of photosynthesis, including new soil water stress and autotrophic respiration (RA) functions. The revised version allows the model to better capture the energy, water and carbon fluxes when compared to five Amazonian flux towers. The performance of ISBACC is slightly site dependent although similar to the widely evaluated LSM ORCHIDEE (Organizing Carbon and Hydrology In Dynamic Ecosystems – version 1187), which is based on different assumptions. Changes made to the autotrophic respiration functions, including a vertical profile of leaf respiration, lead to yearly simulated carbon use efficiency (CUE) and carbon stocks which is consistent with an ecophysiological meta-analysis conducted on three Amazonian sites. Despite these major improvements, ISBACC struggles to capture the apparent seasonality of the carbon fluxes derived from the flux tower estimations. However, there is still no consensus on the seasonality of carbon fluxes over the Amazon, stressing a need for more observations as well as a better understanding of the main drivers of autotrophic respiration.

scholarly journals Improving the ISBA<sub>CC</sub> land surface model simulation of water and carbon fluxes and stocks over the Amazon forest

2015 ◽  
Vol 8 (2) ◽  
pp. 1293-1336
Author(s):  
E. Joetzjer ◽  
C. Delire ◽  
H. Douville ◽  
P. Ciais ◽  
B. Decharme ◽  
...  
Keyword(s):  
Land Surface ◽  
Model Simulation ◽  
Meta Analysis ◽  
Land Surface Model ◽  
Carbon Fluxes ◽  
Surface Model ◽  
Amazon Forest ◽  
Autotrophic Respiration ◽  
Soil Water Stress ◽  
Use Efficiency

Abstract. We evaluate the ISBACC land surface model over the Amazon forest, and propose a revised parameterization of photosynthesis, including new soil water stress and autotrophic respiration functions. The revised version allows the model to better capture the energy, water and carbon fluxes when compared to five Amazonian fluxtowers. The performance of ISBACC is slightly site-dependent but similar to the widely evaluated land surface model ORCHIDEE, based on different assumptions. Changes made to the autotrophic respiration functions, including a vertical profile of leaf respiration, leads to simulate yearly carbon use efficiency and carbon stocks consistent with an ecophysiological meta analysis conducted on three Amazonian sites. Despite these major improvements, ISBACC struggles to capture the apparent seasonality of the carbon fluxes derived from the fluxtower estimations. However, there is still no consensus on the seasonality of carbon fluxes over the Amazon, stressing a need for more observations as well as a better understanding of the main drivers of autotrophic respiration.

Diagnosing Present and Future Permafrost from Climate Models

2013 ◽  
Vol 26 (15) ◽  
pp. 5608-5623 ◽  
Author(s):  
Andrew G. Slater ◽  
David M. Lawrence
Keyword(s):  
Land Surface ◽  
Climate Models ◽  
Land Surface Model ◽  
Coupled Model ◽  
Temporal Distribution ◽  
Surface Model ◽  
Permafrost Region ◽  
Near Surface ◽  
Surface Climate ◽  
Soil Temperatures

Abstract Permafrost is a characteristic aspect of the terrestrial Arctic and the fate of near-surface permafrost over the next century is likely to exert strong controls on Arctic hydrology and biogeochemistry. Using output from the fifth phase of the Coupled Model Intercomparison Project (CMIP5), the authors assess its ability to simulate present-day and future permafrost. Permafrost extent diagnosed directly from each climate model's soil temperature is a function of the modeled surface climate as well as the ability of the land surface model to represent permafrost physics. For each CMIP5 model these two effects are separated by using indirect estimators of permafrost driven by climatic indices and compared to permafrost extent directly diagnosed via soil temperatures. Several robust conclusions can be drawn from this analysis. Significant air temperature and snow depth biases exist in some model's climates, which degrade both directly and indirectly diagnosed permafrost conditions. The range of directly calculated present-day (1986–2005) permafrost area is extremely large (~4–25 × 106 km2). Several land models contain structural weaknesses that limit their skill in simulating cold region subsurface processes. The sensitivity of future permafrost extent to temperature change over the present-day observed permafrost region averages (1.67 ± 0.7) × 106 km2 °C−1 but is a function of the spatial and temporal distribution of climate change. Because of sizable differences in future climates for the representative concentration pathway (RCP) emission scenarios, a wide variety of future permafrost states is predicted by 2100. Conservatively, the models suggest that for RCP4.5, permafrost will retreat from the present-day discontinuous zone. Under RCP8.5, sustainable permafrost will be most probable only in the Canadian Archipelago, Russian Arctic coast, and east Siberian uplands.

scholarly journals Stomatal optimization based on xylem hydraulics (SOX) improves land surface model simulation of vegetation responses to climate

2020 ◽  
Vol 226 (6) ◽  
pp. 1622-1637 ◽  
Author(s):  
Cleiton B. Eller ◽  
Lucy Rowland ◽  
Maurizio Mencuccini ◽  
Teresa Rosas ◽  
Karina Williams ◽  
...  
Keyword(s):  
Land Surface ◽  
Model Simulation ◽  
Land Surface Model ◽  
Surface Model ◽  
Vegetation Responses

scholarly journals Modelling sun-induced fluorescence and photosynthesis with a land surface model at local and regional scales in northern Europe

2016 ◽  
Author(s):  
Tea Thum ◽  
Sönke Zaehle ◽  
Philipp Köhler ◽  
Tuula Aalto ◽  
Mika Aurela ◽  
...  
Keyword(s):  
Chlorophyll Fluorescence ◽  
Land Surface ◽  
Large Scale ◽  
Model Simulation ◽  
Gross Primary Production ◽  
Coniferous Forest ◽  
Land Surface Model ◽  
Flux Measurement ◽  
Surface Model ◽  
Fluorescence Measurements

Abstract. Recent satellite observations of sun-induced chlorophyll fluorescence (SIF) are thought to provide a large-scale proxy for gross primary production (GPP), thus providing a new way to assess the performance of land surface models (LSMs). In this study, we assessed how well SIF is able to predict GPP in the Fenno-Scandinavian region and what potential limitations for its application exist. We implemented a SIF model into the JSBACH LSM and used active leaf level chlorophyll fluorescence measurements (ChlF) to evaluate the performance of the SIF module at a coniferous forest at Hyytiälä, Finland. We also compared simulated GPP and SIF at four Finnish micrometeorological flux measurement sites to observed GPP as well as to satellite observed SIF. Finally, we conducted a regional model simulation for the Fenno-Scandinavian region with JSBACH and compared the results to SIF retrievals from the GOME-2 (Global Ozone Monitoring Experiment-2) space-borne spectrometer and to observation-based regional GPP estimates. Both observations and simulations revealed that SIF can be used to estimate GPP at both site and regional scales. The GOME-2 based SIF was a better proxy for GPP than the remotely sensed fAPAR (fraction of absorbed photosynthetic active radiation by vegetation), even though high SIF values occurred during early spring at the northern latitudes, although these are not likely to be associated with photosynthesis.

Stone Content Influence on Land Surface Model Simulation of Soil Moisture and Evapotranspiration at Reynolds Creek Watershed

2020 ◽  
Vol 21 (8) ◽  
pp. 1889-1904
Author(s):  
Kshitij Parajuli ◽  
Scott B. Jones ◽  
David G. Tarboton ◽  
Lawrence E. Hipps ◽  
Lin Zhao ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Soil Profile ◽  
Land Surface ◽  
Model Simulation ◽  
Land Surface Model ◽  
Surface Model ◽  
Hydraulic Parameters ◽  
Reynolds Creek ◽  
Soil Hydraulic Parameters ◽  
Soil Hydraulic

AbstractConsiderable advancement in spatiotemporal resolution of remote sensing and ground-based measurements has enabled refinement of parameters used in land surface models for simulating surface water fluxes. However, land surface modeling capabilities are still inadequate for accurate representation of subsurface properties and processes, which continue to limit the accuracy of land surface model simulation. Our objective in this study was to examine the performance of the variously parameterized Noah land surface model with multiphysics option (Noah-MP) in simulating evapotranspiration (ET) and soil moisture dynamics in stony soils using verification from eddy covariance ET and in situ soil moisture data during the growing season of year 2015, obtained from the Lower Sheep subcatchment within the Reynolds Creek Experimental Watershed in southwestern Idaho. We evaluated the performance of Noah-MP considering four different scenarios with 1) a one-layer soil profile with Noah-MP default soil hydraulic parameters and three more five-layer soil profiles using 2) Noah-MP default soil hydraulic parameters; 3) soil hydraulic parameters derived from a pedotransfer function using field observations; and 4) hydraulic parameters from scenario 3, which also accounted for stone content in each layer. Each modeling experiment was forced with the same set of initial conditions, atmospheric input, and vegetation parameters. Our results indicate that enhanced representation of soil profile properties and stone content information noticeably improve the Noah-MP land surface model simulation of soil moisture content and evapotranspiration.

scholarly journals Evaluating the performance of land surface model ORCHIDEE-CAN v1.0 on water and energy flux estimation with a single- and multi-layer energy budget scheme

2016 ◽  
Vol 9 (9) ◽  
pp. 2951-2972 ◽  
Author(s):  
Yiying Chen ◽  
James Ryder ◽  
Vladislav Bastrikov ◽  
Matthew J. McGrath ◽  
Kim Naudts ◽  
...  
Keyword(s):  
Energy Budget ◽  
Land Surface ◽  
Model Simulation ◽  
Canopy Structure ◽  
Land Surface Model ◽  
Single Layer ◽  
Surface Model ◽  
Forest Types ◽  
Layer Model ◽  
Single Layer Model

Abstract. Canopy structure is one of the most important vegetation characteristics for land–atmosphere interactions, as it determines the energy and scalar exchanges between the land surface and the overlying air mass. In this study we evaluated the performance of a newly developed multi-layer energy budget in the ORCHIDEE-CAN v1.0 land surface model (Organising Carbon and Hydrology In Dynamic Ecosystems – CANopy), which simulates canopy structure and can be coupled to an atmospheric model using an implicit coupling procedure. We aim to provide a set of acceptable parameter values for a range of forest types. Top-canopy and sub-canopy flux observations from eight sites were collected in order to conduct this evaluation. The sites crossed climate zones from temperate to boreal and the vegetation types included deciduous, evergreen broad-leaved and evergreen needle-leaved forest with a maximum leaf area index (LAI; all-sided) ranging from 3.5 to 7.0. The parametrization approach proposed in this study was based on three selected physical processes – namely the diffusion, advection, and turbulent mixing within the canopy. Short-term sub-canopy observations and long-term surface fluxes were used to calibrate the parameters in the sub-canopy radiation, turbulence, and resistance modules with an automatic tuning process. The multi-layer model was found to capture the dynamics of sub-canopy turbulence, temperature, and energy fluxes. The performance of the new multi-layer model was further compared against the existing single-layer model. Although the multi-layer model simulation results showed few or no improvements to both the nighttime energy balance and energy partitioning during winter compared with a single-layer model simulation, the increased model complexity does provide a more detailed description of the canopy micrometeorology of various forest types. The multi-layer model links to potential future environmental and ecological studies such as the assessment of in-canopy species vulnerability to climate change, the climate effects of disturbance intensities and frequencies, and the consequences of biogenic volatile organic compound (BVOC) emissions from the terrestrial ecosystem.

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