scholarly journals Spatial and temporal variations in near‐surface energy fluxes in an Alpine valley under synoptically undisturbed and clear‐sky conditions

2021 ◽  
Author(s):  
Manuela Lehner ◽  
Mathias W. Rotach ◽  
Eleni Sfyri ◽  
Friedrich Obleitner
Keyword(s):  
Surface Energy ◽  
Temporal Variations ◽  
Spatial And Temporal Variations ◽  
Energy Fluxes ◽  
Near Surface ◽  
Alpine Valley ◽  
Surface Energy Fluxes ◽  
Clear Sky ◽  
Sky Conditions

scholarly journals Combining ground-based microwave radiometer and the AROME convective scale model through 1DVAR retrievals in complex terrain: an Alpine valley case study

2017 ◽  
Vol 10 (9) ◽  
pp. 3385-3402 ◽  
Author(s):  
Pauline Martinet ◽  
Domenico Cimini ◽  
Francesco De Angelis ◽  
Guylaine Canut ◽  
Vinciane Unger ◽  
...  
Keyword(s):  
Complex Terrain ◽  
Microwave Radiometer ◽  
Scale Model ◽  
Near Surface ◽  
Field Campaign ◽  
Alpine Valley ◽  
Clear Sky ◽  
Convective Scale ◽  
Temperature Inversions ◽  
Sky Conditions

Abstract. A RPG-HATPRO ground-based microwave radiometer (MWR) was operated in a deep Alpine valley during the Passy-2015 field campaign. This experiment aims to investigate how stable boundary layers during wintertime conditions drive the accumulation of pollutants. In order to understand the atmospheric processes in the valley, MWRs continuously provide vertical profiles of temperature and humidity at a high time frequency, providing valuable information to follow the evolution of the boundary layer. A one-dimensional variational (1DVAR) retrieval technique has been implemented during the field campaign to optimally combine an MWR and 1 h forecasts from the French convective scale model AROME. Retrievals were compared to radiosonde data launched at least every 3 h during two intensive observation periods (IOPs). An analysis of the AROME forecast errors during the IOPs has shown a large underestimation of the surface cooling during the strongest stable episode. MWR brightness temperatures were monitored against simulations from the radiative transfer model ARTS2 (Atmospheric Radiative Transfer Simulator) and radiosonde launched during the field campaign. Large errors were observed for most transparent channels (i.e., 51–52 GHz) affected by absorption model and calibration uncertainties while a good agreement was found for opaque channels (i.e., 54–58 GHz). Based on this monitoring, a bias correction of raw brightness temperature measurements was applied before the 1DVAR retrievals. 1DVAR retrievals were found to significantly improve the AROME forecasts up to 3 km but mainly below 1 km and to outperform usual statistical regressions above 1 km. With the present implementation, a root-mean-square error (RMSE) of 1 K through all the atmospheric profile was obtained with values within 0.5 K below 500 m in clear-sky conditions. The use of lower elevation angles (up to 5°) in the MWR scanning and the bias correction were found to improve the retrievals below 1000 m. MWR retrievals were found to catch deep near-surface temperature inversions very well. Larger errors were observed in cloudy conditions due to the difficulty of ground-based MWRs to resolve high level inversions that are still challenging. Finally, 1DVAR retrievals were optimized for the analysis of the IOPs by using radiosondes as backgrounds in the 1DVAR algorithm instead of the AROME forecasts. A significant improvement of the retrievals in cloudy conditions and below 1000 m in clear-sky conditions was observed. From this study, we can conclude that MWRs are expected to bring valuable information into numerical weather prediction models up to 3 km in altitude both in clear-sky and cloudy-sky conditions with the maximum improvement found around 500 m. With an accuracy between 0.5 and 1 K in RMSE, our study has also proven that MWRs are capable of resolving deep near-surface temperature inversions observed in complex terrain during highly stable boundary layer conditions.

scholarly journals Comparison of FASST and SNTHERM in Three Snow Accumulation Regimes

2008 ◽  
Vol 9 (6) ◽  
pp. 1443-1463 ◽  
Author(s):  
Susan Frankenstein ◽  
Anne Sawyer ◽  
Julie Koeberle
Keyword(s):  
Surface Energy ◽  
Single Layer ◽  
Soil Strength ◽  
Snow Accumulation ◽  
Dynamic State ◽  
Energy Fluxes ◽  
One Dimensional ◽  
Surface Energy Fluxes ◽  
Snow Model ◽  
Surface Ice

Abstract Numerical experiments of snow accumulation and depletion were carried out as well as surface energy fluxes over four Cold Land Processes Experiment (CLPX) sites in Colorado using the Snow Thermal model (SNTHERM) and the Fast All-Season Soil Strength model (FASST). SNTHERM is a multilayer snow model developed to describe changes in snow properties as a function of depth and time, using a one-dimensional mass and energy balance. The model is intended for seasonal snow covers and addresses conditions found throughout the winter, from initial ground freezing in the fall to snow ablation in the spring. It has been used by many researchers over a variety of terrains. FASST is a newly developed one-dimensional dynamic state-of-the-ground model. It calculates the ground’s moisture content, ice content, temperature, and freeze–thaw profiles as well as soil strength and surface ice and snow accumulation/depletion. Because FASST is newer and not as well known, the authors wanted to determine its use as a snow model by comparing it with SNTHERM, one of the most established snow models available. It is demonstrated that even though FASST is only a single-layer snow model, the RMSE snow depth compared very favorably against SNTHERM, often performing better during the accumulation phase. The surface energy fluxes calculated by the two models were also compared and were found to be similar.

scholarly journals Simulated Sensitivity of Tropical Cyclone Size and Structure to the Atmospheric Temperature Profile

2016 ◽  
Vol 73 (11) ◽  
pp. 4553-4571 ◽  
Author(s):  
Diana R. Stovern ◽  
Elizabeth A. Ritchie
Keyword(s):  
Tropical Cyclone ◽  
Surface Energy ◽  
Temperature Profile ◽  
Convective Available Potential Energy ◽  
Atmospheric Temperature ◽  
Outer Core ◽  
Specific Humidity ◽  
Energy Fluxes ◽  
Surface Energy Fluxes ◽  
Size And Structure

Abstract This study uses the WRF ARW to investigate how different atmospheric temperature environments impact the size and structure development of a simulated tropical cyclone (TC). In each simulation, the entire vertical virtual temperature profile is either warmed or cooled in 1°C increments from an initial specified state while the initial relative humidity profile and sea surface temperature are held constant. This alters the initial amount of convective available potential energy (CAPE), specific humidity, and air–sea temperature difference such that, when the simulated atmosphere is cooled (warmed), the initial specific humidity and CAPE decrease (increase), but the surface energy fluxes from the ocean increase (decrease). It is found that the TCs that form in an initially cooler environment develop larger wind and precipitation fields with more active outer-core rainband formation. Consistent with previous studies, outer-core rainband formation is associated with high surface energy fluxes, which leads to increases in the outer-core wind field. A larger convective field develops despite initializing in a low CAPE environment, and the dynamics are linked to a wider field of surface radial inflow. As the TC matures and radial inflow expands, large imports of relative angular momentum in the boundary layer continue to drive expansion of the TC’s overall size.

scholarly journals Using a thermal-based two source energy balance model with time-differencing to estimate surface energy fluxes with day–night MODIS observations

2013 ◽  
Vol 17 (7) ◽  
pp. 2809-2825 ◽  
Author(s):  
R. Guzinski ◽  
M. C. Anderson ◽  
W. P. Kustas ◽  
H. Nieto ◽  
I. Sandholt
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
The United States ◽  
Surface Fluxes ◽  
Diurnal Changes ◽  
Energy Fluxes ◽  
Surface Energy Fluxes ◽  
Vegetation Fraction ◽  
Geostationary Satellites ◽  
Green Vegetation

Abstract. The Dual Temperature Difference (DTD) model, introduced by Norman et al. (2000), uses a two source energy balance modelling scheme driven by remotely sensed observations of diurnal changes in land surface temperature (LST) to estimate surface energy fluxes. By using a time-differential temperature measurement as input, the approach reduces model sensitivity to errors in absolute temperature retrieval. The original formulation of the DTD required an early morning LST observation (approximately 1 h after sunrise) when surface fluxes are minimal, limiting application to data provided by geostationary satellites at sub-hourly temporal resolution. The DTD model has been applied primarily during the active growth phase of agricultural crops and rangeland vegetation grasses, and has not been rigorously evaluated during senescence or in forested ecosystems. In this paper we present modifications to the DTD model that enable applications using thermal observations from polar orbiting satellites, such as Terra and Aqua, with day and night overpass times over the area of interest. This allows the application of the DTD model in high latitude regions where large viewing angles preclude the use of geostationary satellites, and also exploits the higher spatial resolution provided by polar orbiting satellites. A method for estimating nocturnal surface fluxes and a scheme for estimating the fraction of green vegetation are developed and evaluated. Modification for green vegetation fraction leads to significantly improved estimation of the heat fluxes from the vegetation canopy during senescence and in forests. When the modified DTD model is run with LST measurements acquired with the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the Terra and Aqua satellites, generally satisfactory agreement with field measurements is obtained for a number of ecosystems in Denmark and the United States. Finally, regional maps of energy fluxes are produced for the Danish Hydrological ObsErvatory (HOBE) in western Denmark, indicating realistic patterns based on land use.

scholarly journals Remotely sensed land-surface energy fluxes at sub-field scale in heterogeneous agricultural landscape and coniferous plantation

2014 ◽  
Vol 11 (18) ◽  
pp. 5021-5046 ◽  
Author(s):  
R. Guzinski ◽  
H. Nieto ◽  
R. Jensen ◽  
G. Mendiguren
Keyword(s):  
Surface Energy ◽  
Spatial Resolution ◽  
Land Surface ◽  
Agricultural Landscape ◽  
Remotely Sensed ◽  
Energy Fluxes ◽  
Surface Energy Fluxes ◽  
Coniferous Plantation ◽  
Polar Orbiting Satellite ◽  
Agricultural Site

Abstract. In this study we evaluate a methodology for disaggregating land surface energy fluxes estimated with the Two-Source Energy Balance (TSEB)-based Dual-Temperature Difference (DTD) model which uses day and night polar orbiting satellite observations of land surface temperature (LST) as a remotely sensed input. The DTD model is run with MODIS input data at a spatial resolution of around 1 km while the disaggregation uses Landsat observations to produce fluxes at a nominal spatial resolution of 30 m. The higher-resolution modelled fluxes can be directly compared against eddy covariance (EC)-based flux tower measurements to ensure more accurate model validation and also provide a better visualization of the fluxes' spatial patterns in heterogeneous areas allowing for development of, for example, more efficient irrigation practices. The disaggregation technique is evaluated in an area covered by the Danish Hydrological Observatory (HOBE), in the west of the Jutland peninsula, and the modelled fluxes are compared against measurements from two flux towers: the first one in a heterogeneous agricultural landscape and the second one in a homogeneous conifer plantation. The results indicate that the coarse-resolution DTD fluxes disaggregated at Landsat scale have greatly improved accuracy as compared to high-resolution fluxes derived directly with Landsat data without the disaggregation. At the agricultural site the disaggregated fluxes display small bias and very high correlation (r ≈ 0.95) with EC-based measurements, while at the plantation site the results are encouraging but still with significant errors. In addition, we introduce a~modification to the DTD model by replacing the "parallel" configuration of the resistances to sensible heat exchange by the "series" configuration. The latter takes into account the in-canopy air temperature and substantially improves the accuracy of the DTD model.

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