scholarly journals Evaluation of the near-surface evolution of Foehn events in COSMO-1

2021 ◽  
Author(s):  
Yue Tian ◽  
Juerg Schmidli ◽  
Julian Quimbayo-Duarte
Keyword(s):  
Land Surface ◽  
Monitoring Network ◽  
Automatic Monitoring ◽  
Bare Soil ◽  
Heat Fluxes ◽  
Grid Spacing ◽  
Surface Evolution ◽  
Near Surface ◽  
Model Biases ◽  
Downslope Wind

<p>Foehn is a downslope wind with a large impact on society due to its gusty nature and the associated high-temperature extremes. It is influenced by and interacts with near-surface processes, such as the cold air pool (CAP), an important phenomenon that is often present in the foehn valleys during the cold season. Therefore, it is challenging to accurately forecast the foehn characteristics, in terms of the onset, strength, and decay as the near-surface evolution is the result of multi-scale interactions between the larger atmosphere and the mountain/local valley topography. From a meso-/micro-scale perspective, this study investigates the skill of the COSMO model (v5.7) at 1.1 km grid spacing in simulating the near-surface foehn evolution for a set of south foehn events, representative of different foehn types around the Alps. The evaluation is based on a comparison to station data from the automatic monitoring network of MeteoSwiss, with a focus on the Rhine Valley. Significant cold and moist biases are found in the model during foehn hours in all the chosen cases. Biases in Foehn duration and spatial extent are also studied. The sensitivity of these biases to several land-surface parameterization choices, e.g., skin layer, bare soil evaporation, and resistance for heat fluxes, are investigated and presented. Simulations for the same foehn events with COSMO at 500 m grid spacing are also evaluated for a better understanding of the model biases. Further studies from the perspective of climatological statistics are needed to establish the relationships between model biases and foehn types.</p>

scholarly journals Shallow groundwater effect on land surface temperature and surface energy balance under bare soil conditions: modeling and description

2012 ◽  
Vol 16 (7) ◽  
pp. 1817-1831 ◽  
Author(s):  
F. Alkhaier ◽  
G. N. Flerchinger ◽  
Z. Su
Keyword(s):  
Energy Balance ◽  
Surface Temperature ◽  
Land Surface ◽  
Shallow Groundwater ◽  
Bare Soil ◽  
Heat Fluxes ◽  
Shortwave Radiation ◽  
Soil Conditions ◽  
Potential Evaporation ◽  
Available Energy

Abstract. Understanding when and how groundwater affects surface temperature and energy fluxes is significant for utilizing remote sensing in groundwater studies and for integrating aquifers within land surface models. To investigate the shallow groundwater effect under bare soil conditions, we numerically exposed two soil profiles to identical metrological forcing. One of the profiles had shallow groundwater. The different responses that the two profiles manifested were inspected regarding soil moisture, temperature and energy balance at the land surface. The findings showed that the two profiles differed in three aspects: the absorbed and emitted amounts of energy, the portioning out of the available energy and the heat fluency in the soil. We concluded that due to their lower albedo, shallow groundwater areas reflect less shortwave radiation and consequently get a higher magnitude of net radiation. When potential evaporation demand is sufficiently high, a large portion of the energy received by these areas is consumed for evaporation. This increases the latent heat flux and reduces the energy that could have heated the soil. Consequently, lower magnitudes of both sensible and ground heat fluxes are caused to occur. The higher soil thermal conductivity in shallow groundwater areas facilitates heat transfer between the top soil and the subsurface, i.e. soil subsurface is more thermally connected to the atmosphere. For the reliability of remote sensors in detecting shallow groundwater effect, it was concluded that this effect can be sufficiently clear to be detected if at least one of the following conditions occurs: high potential evaporation and high contrast between day and night temperatures. Under these conditions, most day and night hours are suitable for shallow groundwater depth detection.

scholarly journals Surface response to rain events throughout the West African monsoon

2013 ◽  
Vol 13 (7) ◽  
pp. 18581-18620 ◽  
Author(s):  
F. Lohou ◽  
L. Kergoat ◽  
F. Guichard ◽  
A. Boone ◽  
B. Cappelaere ◽  
...  
Keyword(s):  
Land Surface ◽  
Recovery Period ◽  
Bare Soil ◽  
Rain Event ◽  
Land Surface Models ◽  
Evaporative Fraction ◽  
Near Surface ◽  
African Monsoon ◽  
Surface Response ◽  
Surface Models

Abstract. This study analyses the response of the continental surface to a rain event, taking advantage of the long-term near-surface measurements over different vegetation covers at different latitudes, acquired during the African Monsoon Multidisciplinary Analysis (AMMA) experiment. The simulated surface response by nine land surface models involved in AMMA Land Model Intercomparison Project (ALMIP), is compared to the observations. The surface response, described via the evaporative fraction, evolves in two steps: the immediate surface response and the surface recovery. The immediate surface response corresponds to an increase in the evaporative fraction occurring immediately after the rain. For all the experimental sites, the immediate surface response is strongest when the surface is relatively dry. From the simulation point of view, this relationship is highly model and latitude dependent. The recovery period, characterized by a decrease of the evaporative fraction during several days after the rain, follows an exponential relationship whose rate is vegetation dependent: from 1 day over bare soil to 70 days over the forest. Land surface models correctly simulate the decrease of EF over vegetation covers whereas a slower and more variable EF decrease is simulated over bare soil.

scholarly journals Components of near-surface energy balance derived from satellite soundings – Part 2: Noontime latent heat flux

2014 ◽  
Vol 11 (24) ◽  
pp. 7369-7382 ◽  
Author(s):  
K. Mallick ◽  
A. Jarvis ◽  
G. Wohlfahrt ◽  
G. Kiely ◽  
T. Hirano ◽  
...  
Keyword(s):  
Heat Flux ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Land Surface ◽  
Vegetation Index ◽  
Bowen Ratio ◽  
Heat Fluxes ◽  
Simple Method ◽  
Near Surface ◽  
Available Energy

Abstract. This paper introduces a relatively simple method for recovering global fields of latent heat flux. The method focuses on specifying Bowen ratio estimates through exploiting air temperature and vapour pressure measurements obtained from infrared soundings of the AIRS (Atmospheric Infrared Sounder) sensor onboard NASA's Aqua platform. Through combining these Bowen ratio retrievals with satellite surface net available energy data, we have specified estimates of global noontime surface latent heat flux at the 1°×1° scale. These estimates were provisionally evaluated against data from 30 terrestrial tower flux sites covering a broad spectrum of biomes. Taking monthly average 13:30 data for 2003, this revealed promising agreement between the satellite and tower measurements of latent heat flux, with a pooled root-mean-square deviation of 79 W m−2, and no significant bias. However, this success partly arose as a product of the underspecification of the AIRS Bowen ratio compensating for the underspecification of the AIRS net available energy, suggesting further refinement of the approach is required. The error analysis suggested that the landscape level variability in enhanced vegetation index (EVI) and land surface temperature contributed significantly to the statistical metric of the predicted latent heat fluxes.

scholarly journals Urban-Induced Changes on Local Circulation in Complex Terrain: Central Mexico Basin

Atmosphere ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 904
Author(s):  
Lourdes P. Aquino-Martínez ◽  
Arturo I. Quintanar ◽  
Carlos A. Ochoa-Moya ◽  
Erika Danaé López-Espinoza ◽  
David K. Adams ◽  
...  
Keyword(s):  
Large Scale ◽  
Meridional Circulation ◽  
Circulation Pattern ◽  
Heat Fluxes ◽  
Local Circulation ◽  
Pressure System ◽  
Near Surface ◽  
Zonal Circulation ◽  
Downslope Wind ◽  
Mexico Basin

Land use land cover (LULC) significantly impacts local circulation in the Mexico Basin, particularly wind field circulations such as gap winds, convergence lines, and thermally induced upslope/downslope wind. A case study with a high-pressure system over the Mexico Basin isolates the influence of large-scale synoptic forcing. Numerical simulations reveal a wind system composed of meridional circulation and a zonal component. Thermal pressure gradients between the Mexico basin and its colder surroundings create near-surface convergence lines as part of the meridional circulation. Experiments show that the intensity and organization of meridional circulations and downslope winds increase when LULC changes from natural and cultivated land to urban. Zonal circulation exhibits a typical circulation pattern with the upslope flow and descending motion in the middle of the basin. Large values of moist static energy are near the surface where air parcels pick up energy from the surface either as fluxes of enthalpy or latent heat. Surface heat fluxes and stored energy in the ground are drivers of local circulation, which is more evident in zonal circulation patterns.

scholarly journals Application of the Land–Atmosphere Coupling Paradigm to the Operational Coupled Forecast System, Version 2 (CFSv2)

2016 ◽  
Vol 18 (1) ◽  
pp. 85-108 ◽  
Author(s):  
Paul A. Dirmeyer ◽  
Subhadeep Halder
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Atmospheric Stability ◽  
Surface States ◽  
Heat Fluxes ◽  
Forecast Skill ◽  
Surface Model ◽  
Forecast System ◽  
Potential Predictability ◽  
Near Surface

Abstract Retrospective forecasts from CFSv2 are evaluated in terms of three elements of land–atmosphere coupling at subseasonal to seasonal time scales: sensitivity of the atmosphere to variations in land surface states, the magnitude of variability of land states and fluxes, and the memory or persistence of land surface anomalies. The Northern Hemisphere spring and summer seasons are considered for the period 1982–2009. Ensembles are constructed from all available pairings of initial land and atmosphere/ocean states taken from the Climate Forecast System Reanalysis at the start of April, May, and June among the 28 years, so that the effect of initial land states on the evolving forecasts can be assessed. Finally, improvement and continuance of forecast skill derived from accurate land surface initialization is related to the three coupling elements. It is found that soil moisture memory is the most broadly important element for significant improvement of realistic land initialization on forecast skill. However, coupling strength manifested through the elements of sensitivity and variability are necessary to realize the potential predictability provided by memory of initial land surface anomalies. Even though there is clear responsiveness of surface heat fluxes, near-surface temperature, humidity, and daytime boundary layer development to variations in soil moisture over much of the globe, precipitation in CFSv2 is unresponsive. Failure to realize potential predictability from land surface states could be due to unfavorable atmospheric stability or circulation states; poor quality of what is considered realistic soil moisture analyses; and errors in the land surface model, atmospheric model, or their coupled interaction.

Subgrid-Scale Variability for Thermodynamic Variables in an Offline Land Surface Prediction System

2015 ◽  
Vol 17 (1) ◽  
pp. 171-193 ◽  
Author(s):  
Mélanie C. Rochoux ◽  
Stéphane Bélair ◽  
Maria Abrahamowicz ◽  
Pierre Pellerin
Keyword(s):  
High Resolution ◽  
Land Surface ◽  
Horizontal Resolution ◽  
Prediction System ◽  
Subgrid Scale ◽  
Grid Spacing ◽  
Model Bias ◽  
Near Surface ◽  
Surface Prediction ◽  
The Impact

Abstract This study presents a numerical analysis of the impact of the horizontal resolution on the forecast capability of the Canadian offline land surface prediction system (SPS; formerly known as GEM-Surf) forced by the 15-km Global Environmental Multiscale (GEM) atmospheric model. This system is used to quantify on a statistical basis the subgrid-scale variability of (near-)surface variables for 25-km grid spacing based on the 2.5- or 10-km SPS run at regional scale over the 2012 summer season. The model bias and the distributions characterizing the subgrid-scale variability drastically depend on the geographic areas as well as on the diurnal cycle. These results show the benefits of high-resolution land surface simulations to account for length scales that are more consistent with the scales at which the actual land surface balance is affected by the heterogeneous geophysical fields (i.e., roughness length, land–water mask, glacier mask, and soil texture). The model bias results highlight the potential of an SPS–GEM two-way coupling strategy for refining predictions near the surface through the upscaling of high-resolution surface heat fluxes to the coarser atmospheric grid spacing, with these fluxes being significantly different from those explicitly resolved at 25 km and featuring nonlinear behavior with respect to the horizontal resolution. Since the computational power of meteorological operational centers progressively increases, making it possible to run high-resolution limited-area models, solving the surface at high resolution in a surface–atmosphere fully coupled system becomes a key aspect for improving numerical weather and environmental forecast performance.

scholarly journals Sensitivity of the regional European boreal climate to changes in surface properties resulting from structural vegetation perturbations

2015 ◽  
Vol 12 (10) ◽  
pp. 3071-3087 ◽  
Author(s):  
J. H. Rydsaa ◽  
F. Stordal ◽  
L. M. Tallaksen
Keyword(s):  
Land Surface ◽  
Large Scale ◽  
Structural Changes ◽  
Mixed Forest ◽  
Surface Fluxes ◽  
Heat Fluxes ◽  
Energy Partitioning ◽  
The Arctic ◽  
Surface Model ◽  
Near Surface

Abstract. Amplified warming at high latitudes over the past few decades has led to changes in the boreal and Arctic climate system such as structural changes in high-latitude ecosystems and soil moisture properties. These changes trigger land–atmosphere feedbacks through altered energy partitioning in response to changes in albedo and surface water fluxes. Local-scale changes in the Arctic and boreal zones may propagate to affect large-scale climatic features. In this study, MODIS land surface data are used with the Weather Research and Forecasting model (WRF V3.5.1) and Noah land surface model (LSM), in a series of experiments to investigate the sensitivity of the overlying atmosphere to perturbations in the structural vegetation in the northern European boreal ecosystem. Emphasis is placed on surface energy partitioning and near-surface atmospheric variables, and their response to observed and anticipated land cover changes. We find that perturbations simulating northward migration of evergreen needleleaf forest into tundra regions cause an increase in latent rather than sensible heat fluxes during the summer season. Shrub expansion in tundra areas has only small effects on surface fluxes. Perturbations simulating the northward migration of mixed forest across the present southern border of the boreal forest, have largely opposite effects on the summer latent heat flux, i.e., they lead to a decrease and act to moderate the overall mean regional effects of structural vegetation changes on the near-surface atmosphere.

scholarly journals Linkages between land initialization of the NASA-Unified WRF v7 and biogenic isoprene emission estimates during the SEAC<sup>4</sup>RS and DISCOVER-AQ airborne campaigns

2017 ◽  
Author(s):  
Min Huang ◽  
Gregory R. Carmichael ◽  
James H. Crawford ◽  
Armin Wisthaler ◽  
Xiwu Zhan ◽  
...  
Keyword(s):  
Air Temperature ◽  
Land Surface ◽  
Initial Conditions ◽  
Wrf Model ◽  
Surface Air Temperature ◽  
Heat Fluxes ◽  
Temperature Fields ◽  
Surface Model ◽  
Near Surface ◽  
Isoprene Emission

Abstract. Land and atmospheric initial conditions of the Weather Research and Forecasting (WRF) model are often interpolated from a different model output. We perform case studies during NASA's SEAC4RS and DISCOVER-AQ Houston airborne campaigns, demonstrating that initializing the Noah land surface model directly using a coarser resolution dataset North American Regional Reanalysis (NARR) led to significant positive biases in the coupled NASA-Unified WRF (NUWRF, version 7)'s (near-) surface air temperature and planetary boundary layer height (PBLH) around the Missouri Ozarks and Houston, Texas, as well as poorly partitioned latent and sensible heat fluxes. Replacing the land initial conditions with the output from a long-term offline Land Information System (LIS) simulation can effectively reduce the positive biases in NUWRF's surface air temperature fields by ~ 2 °C. We also show that the LIS land initialization can modify the surface air temperature errors almost ten times as effectively as applying a different atmospheric initialization method. The LIS-NUWRF based isoprene emission calculations by the Model of Emissions of Gases and Aerosols from Nature (MEGAN, version 2.1) are at least 20 % lower than those computed using the NARR-initialized NUWRF run, and are closer to the aircraft observation-derived emissions. Higher resolution MEGAN calculations are prone to amplified errors on small scales, possibly resulted from some limitations of MEGAN's parameterization and its inputs' uncertainty. This study emphasizes the importance of proper land initialization to the coupled atmospheric weather modeling and the follow-on emission modeling, which we anticipate to be also critical to accurately representing other processes included in air quality modeling and chemical data assimilation. Having more confidence in the weather inputs is also beneficial for determining and quantifying the other sources of uncertainties (e.g., parameterization, other input data) of the models that they drive.

scholarly journals Memory of land surface and subsurface temperature (LST/SUBT) initial anomalies over Tibetan Plateau in different land models

2021 ◽  
Author(s):  
Yuan Qiu ◽  
Jinming Feng ◽  
Jun Wang ◽  
Yongkang Xue ◽  
Zhongfeng Xu
Keyword(s):  
Tibetan Plateau ◽  
Land Surface ◽  
Climate Model ◽  
Surface Soil ◽  
Soil Depth ◽  
Regional Climate ◽  
Heat Fluxes ◽  
Subsurface Temperature ◽  
Near Surface ◽  
Surface Heat Fluxes

Abstract This study applies three widely used land models (SSiB, CLM, and Noah-MP) coupled in a regional climate model to quantitatively assess their skill in preserving the imposed ± 5℃ anomalies on the initial land surface and subsurface temperature (LST/SUBT) and generating the 2-m air temperature (T2m) anomalies over Tibetan Plateau (TP) during May-August. The memory of the LST/SUBT initial anomalies (surface/soil memory) is defined as the first time when time series of the differences in daily LST/SUBT cross the zero line during the simulation, with the unit of days. The memory of the T2m anomalies (T2m memory) is defined in the same way. The ensemble results indicate that the simulated soil memory generally increases with soil depth, which is consistent with the results based on the observations with statistic methods. And the soil memory is found to change rapidly with depth above ~ 0.6-0.7m and vary gradually below it. The land models have fairly long soil memories, with the regional mean 1.0-m soil memory generally longer than 60 days. However, they have short T2m memory, with the regional means generally below 20 days. This may bring a big challenge to use the LST/SUBT approach on sub-seasonal to seasonal (S2S) prediction. Comparison between the three land models shows that CLM and Noah-MP have longer soil memory at the deeper layers ( > ~ 0.05m) while SSiB has longer T2m/surface memories and near-surface (\(\le\)~0.05m) soil memory. As a result, it is difficult to say which land model is optimal for the application of the LST/SUBT approach on the S2S prediction. The T2m/surface/soil memories are various over TP, distinct among the land models, and different between the + 5℃ and − 5℃ experiment, which can be explained by both changes in the surface heat fluxes and variances in the hydrological processes over the plateau.

An improved representation of the land surface temperature including the effects of vegetation in the COSMO model

2020 ◽  
Author(s):  
Jan-Peter Schulz ◽  
Gerd Vogel
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Surface Temperature ◽  
Land Surface ◽  
Surface Energy Balance ◽  
Heat Fluxes ◽  
Surface Processes ◽  
Atmospheric Models ◽  
Land Surface Processes ◽  
Near Surface

&lt;p&gt;Land surface processes have a significant impact on near-surface atmospheric phenomena. They determine, among others, near-surface sensible and latent heat fluxes and the radiation budget, and thus influence atmosphere and land characteristics, such as temperature and humidity, the structure of the planetary boundary layer, and even cloud formation processes. It is therefore important to simulate the land surface processes in atmospheric models as realistically as possible.&lt;/p&gt;&lt;p&gt;Verifications have shown that the amplitude of the diurnal cycle of the surface temperature simulated by the land surface scheme TERRA of the COSMO atmospheric model is systematically underestimated. In contrast, the diurnal cycles of the temperatures in the soil are overestimated, instead. This means that the other components of the surface energy balance are biased as well, for instance, the surface turbulent heat fluxes or the ground heat flux.&lt;/p&gt;&lt;p&gt;Data from the Meteorological Observatory Lindenberg of the German Meteorological Service (DWD) were used to analyse this model behaviour. In the standard model configuration of TERRA, there is no representation of the vegetation in the surface energy balance. This means, there is no energy budget including a temperature for the vegetation layer. Furthermore, the insulating effects by the vegetation at the sub-canopy level are missing as well. In this work, a scheme providing both of these missing model characteristics was implemented in TERRA. As a result, the simulated diurnal amplitude of the surface temperature is increased and the one of the soil temperature is reduced, both leading to better agreements with the measurements. These improvements are found in TERRA in offline mode, using Lindenberg observations, as well as in coupled mode in the atmospheric models of DWD, i.e. the limited-area COSMO model and the global ICON model.&lt;/p&gt;

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