scholarly journals Simulation of microwave emission from physically modeled snowpacks

2000 ◽  
Vol 31 ◽  
pp. 397-405 ◽  
Author(s):  
Andreas Wiesmann ◽  
Charles Fierz ◽  
Christian Mätzler
Keyword(s):  
Microwave Radiation ◽  
Meteorological Data ◽  
High Sensitivity ◽  
Microwave Remote Sensing ◽  
Microwave Emission ◽  
Detailed Knowledge ◽  
Emission Model ◽  
Snowpack Properties ◽  
Good Agreement

AbstractDetailed knowledge of snowpack properties is crucial for the interpretation and modeling of thermal microwave radiation. Here we use two well-known snow models, Crocus and SNTHERM, to obtain snow profiles from meteorological data. These profiles are compared with pit profiles and used as input to the Microwave Emission Model of Layered Snowpacks (MEMLS) for the simulation of microwave radiation. The snow-profile data can be applied almost directly. Adaptation is needed only in the conversion of the grain-size used in the snow models to the correlation length used in the emission model; it is based on empirical fits. The resulting emissivities are compared with in situ microwave measurements. The computed snow depths are in good agreement with observations. Comparison of selected profiles shows that Crocus is in good agreement with the pit profile, but the density of simulated melt-freeze crusts is underestimated. The SNTHERM profiles show no such crusts, and the density deviates from the pit profiles. The computed temporal behavior of the snowpack emissivity is reasonable. Comparison of selected situations with in situ measurements indicates good agreement. However, the polarization difference tends to be underestimated because of inaccuracies in the simulation of density profiles. The results show the potential of combined snow-physical and microwave-emission models for understanding snow signatures and for developing snow algorithms for microwave remote sensing. Based on the frequency-selective penetration and on the high sensitivity to snow texture, density and wetness, microwave radiometry can offer a new dimension to snow physics. Potential applications are described.

scholarly journals MEMLS3&a: Microwave Emission Model of Layered Snowpacks adapted to include backscattering

2015 ◽  
Vol 8 (8) ◽  
pp. 2611-2626 ◽  
Author(s):  
M. Proksch ◽  
C. Mätzler ◽  
A. Wiesmann ◽  
J. Lemmetyinen ◽  
M. Schwank ◽  
...  
Keyword(s):  
Microwave Remote Sensing ◽  
Horizontal Layer ◽  
Microwave Emission ◽  
Emission Model ◽  
Input Parameters ◽  
Fitting Procedures ◽  
Splitting Parameter ◽  
Set Up ◽  
Passive Measurements ◽  
Active Microwave Remote Sensing

Abstract. The Microwave Emission Model of Layered Snowpacks (MEMLS) was originally developed for microwave emissions of snowpacks in the frequency range 5–100 GHz. It is based on six-flux theory to describe radiative transfer in snow including absorption, multiple volume scattering, radiation trapping due to internal reflection and a combination of coherent and incoherent superposition of reflections between horizontal layer interfaces. Here we introduce MEMLS3&a, an extension of MEMLS, which includes a backscatter model for active microwave remote sensing of snow. The reflectivity is decomposed into diffuse and specular components. Slight undulations of the snow surface are taken into account. The treatment of like- and cross-polarization is accomplished by an empirical splitting parameter q. MEMLS3&a (as well as MEMLS) is set up in a way that snow input parameters can be derived by objective measurement methods which avoid fitting procedures of the scattering efficiency of snow, required by several other models. For the validation of the model we have used a combination of active and passive measurements from the NoSREx (Nordic Snow Radar Experiment) campaign in Sodankylä, Finland. We find a reasonable agreement between the measurements and simulations, subject to uncertainties in hitherto unmeasured input parameters of the backscatter model. The model is written in Matlab and the code is publicly available for download through the following website: http://www.iapmw.unibe.ch/research/projects/snowtools/memls.html.

Characterization of Errors in a Coupled Snow Hydrology–Microwave Emission Model

2008 ◽  
Vol 9 (1) ◽  
pp. 149-164 ◽  
Author(s):  
Konstantinos M. Andreadis ◽  
Ding Liang ◽  
Leung Tsang ◽  
Dennis P. Lettenmaier ◽  
Edward G. Josberger
Keyword(s):  
Forest Cover ◽  
Microwave Radiometer ◽  
Coupled Model ◽  
Microwave Remote Sensing ◽  
Quantitative Information ◽  
Microwave Emission ◽  
Prediction Errors ◽  
Emission Model ◽  
Snow Hydrology ◽  
Infiltration Capacity

Abstract Traditional approaches to the direct estimation of snow properties from passive microwave remote sensing have been plagued by limitations such as the tendency of estimates to saturate for moderately deep snowpacks and the effects of mixed land cover within remotely sensed pixels. An alternative approach is to assimilate satellite microwave emission observations directly, which requires embedding an accurate microwave emissions model into a hydrologic prediction scheme, as well as quantitative information of model and observation errors. In this study a coupled snow hydrology [Variable Infiltration Capacity (VIC)] and microwave emission [Dense Media Radiative Transfer (DMRT)] model are evaluated using multiscale brightness temperature (TB) measurements from the Cold Land Processes Experiment (CLPX). The ability of VIC to reproduce snowpack properties is shown with the use of snow pit measurements, while TB model predictions are evaluated through comparison with Ground-Based Microwave Radiometer (GBMR), aircraft [Polarimetric Scanning Radiometer (PSR)], and satellite [Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E)] TB measurements. Limitations of the model at the point scale were not as evident when comparing areal estimates. The coupled model was able to reproduce the TB spatial patterns observed by PSR in two of three sites. However, this was mostly due to the presence of relatively dense forest cover. An interesting result occurs when examining the spatial scaling behavior of the higher-resolution errors; the satellite-scale error is well approximated by the mode of the (spatial) histogram of errors at the smaller scale. In addition, TB prediction errors were almost invariant when aggregated to the satellite scale, while forest-cover fractions greater than 30% had a significant effect on TB predictions.

scholarly journals CREST-Snow Field Experiment: analysis of snowpack properties using multi-frequency microwave remote sensing data

2013 ◽  
Vol 17 (2) ◽  
pp. 783-793 ◽  
Author(s):  
T. Y. Lakhankar ◽  
J. Muñoz ◽  
P. Romanov ◽  
A. M. Powell ◽  
N. Y. Krakauer ◽  
...  
Keyword(s):  
Grain Size ◽  
Field Experiment ◽  
Brightness Temperature ◽  
Snow Depth ◽  
Winter Season ◽  
Microwave Remote Sensing ◽  
Microwave Emission ◽  
Substantial Impact ◽  
Brightness Temperatures ◽  
Snowpack Properties

Abstract. The CREST-Snow Analysis and Field Experiment (CREST-SAFE) was carried out during January–March 2011 at the research site of the National Weather Service office, Caribou, ME, USA. In this experiment dual-polarized microwave (37 and 89 GHz) observations were accompanied by detailed synchronous observations of meteorology and snowpack physical properties. The objective of this long-term field experiment was to improve understanding of the effect of changing snow characteristics (grain size, density, temperature) under various meteorological conditions on the microwave emission of snow and hence to improve retrievals of snow cover properties from satellite observations. In this paper we present an overview of the field experiment and comparative preliminary analysis of the continuous microwave and snowpack observations and simulations. The observations revealed a large difference between the brightness temperature of fresh and aged snowpack even when the snow depth was the same. This is indicative of a substantial impact of evolution of snowpack properties such as snow grain size, density and wetness on microwave observations. In the early spring we frequently observed a large diurnal variation in the 37 and 89 GHz brightness temperature with small depolarization corresponding to daytime snowmelt and nighttime refreeze events. SNTHERM (SNow THERmal Model) and the HUT (Helsinki University of Technology) snow emission model were used to simulate snowpack properties and microwave brightness temperatures, respectively. Simulated snow depth and snowpack temperature using SNTHERM were compared to in situ observations. Similarly, simulated microwave brightness temperatures using the HUT model were compared with the observed brightness temperatures under different snow conditions to identify different states of the snowpack that developed during the winter season.

scholarly journals Favorable climatic regime for maintaining the present-day geometry of the Gregoriev Glacier, Inner Tien Shan

2011 ◽  
Vol 5 (3) ◽  
pp. 539-549 ◽  
Author(s):  
K. Fujita ◽  
N. Takeuchi ◽  
S. A. Nikitin ◽  
A. B. Surazakov ◽  
S. Okamoto ◽  
...  
Keyword(s):  
Mass Balance ◽  
Meteorological Data ◽  
Tien Shan ◽  
Balance Model ◽  
Glacier Mass Balance ◽  
Current State ◽  
Climatic Regime ◽  
Good Agreement

Abstract. We conducted 2 yr (2005–2007) of in situ meteorological and glaciological observations on the Gregoriev Glacier, a flat-top glacier within the Inner Tien Shan, Kyrgyzstan. Relative carrier-phase GPS surveys reveal a vertical lowering at the summit of the glacier. Based on snow density data and an energy-mass balance model, we estimate that the annual precipitation and summer mean temperature required to maintain the glacier in the current state are 289 mm and −3.8 °C at the glacier summit (4600 m a.s.l.), respectively. The good agreement between dynamically derived precipitation and the long-term observed precipitation at a nearby station in the Tien Shan (296 mm at 3614 m a.s.l. for the period 1930–2002) suggests that the glacier has been in a near steady-state in terms of mass supply. The glacier mass-balance, reconstructed based on meteorological data from the Tien Shan station for the past 80 yr, explains the observed fluctuations in glacier extent, particularly the negative mass balance in the 1990s.

scholarly journals Study of the snow melt–freeze cycle using multi-sensor data and snow modeling

2004 ◽  
Vol 50 (170) ◽  
pp. 419-426 ◽  
Author(s):  
Anselmo Cagnati ◽  
Andrea Crepaz ◽  
Giovanni Macelloni ◽  
Paolo Pampaloni ◽  
Roberto Ranzi ◽  
...  
Keyword(s):  
Meteorological Data ◽  
High Sensitivity ◽  
Microwave Emission ◽  
Sensor Data ◽  
Snow Melt ◽  
Snow Modeling ◽  
Snow Model ◽  
Electromagnetic Models ◽  
Underlying Soil ◽  
Insight Into

AbstractThe melt cycle of snow is investigated by combining ground-based microwave radiometric measurements with conventional and meteorological data and by using a hydrological snow model. Measurements at 2000 m a.s.l in the basin of the Cor-devole river in the eastern Italian Alps confirm the high sensitivity of microwave emission at 19 and 37 GHz to the snow melt−freeze cycle, while the brightness at 6.8 GHz is mostly related to underlying soil. Simulations of snowpack changes performed by means of hydrological and electromagnetic models, driven with meteorological and snow data, provide additional insight into these processes and contribute to the interpretation of the experimental data.

scholarly journals Ideal climatic variables for the present-day geometry of the Gregoriev Glacier, Inner Tien Shan, Kyrgyzstan, derived from GPS data and energy-mass balance measurements

2011 ◽  
Vol 5 (2) ◽  
pp. 855-883
Author(s):  
K. Fujita ◽  
N. Takeuchi ◽  
S. A. Nikitin ◽  
A. B. Surazakov ◽  
S. Okamoto ◽  
...  
Keyword(s):  
Mass Balance ◽  
Meteorological Data ◽  
Vertical Surface ◽  
Tien Shan ◽  
Balance Model ◽  
Glacier Mass Balance ◽  
Differential Gps ◽  
Good Agreement

Abstract. We conducted 2 yr (2005–2007) of in situ meteorological and glaciological observations on the Gregoriev Glacier, a flat-top glacier within the Inner Tien Shan, Kyrgyzstan. Differential GPS surveys reveal a vertical surface deletion at the summit of the glacier. Based on snow density data and an energy-mass balance model, we estimate that the annual precipitation and summer mean temperature required to maintain the glacier in the modern state are 289 mm and −3.85 °C at the glacier summit (4600 m above sea level, a.s.l.), respectively. The good agreement between the long-term estimated and observed precipitation at a nearby station in the Tien Shan (292 mm at 3614 m a.s.l. for the period 1930–2002) suggests that the glacier dynamics have been regulated by the long-term average accumulation. The glacier mass-balance, reconstructed based on meteorological data from the Tien Shan station for the past 80 yr, explains the observed fluctuations in glacier extent, particularly the negative mass balance in the 1990s.

scholarly journals Using TRMM/TMI to Retrieve Surface Soil Moisture over the Southern United States from 1998 to 2002

2006 ◽  
Vol 7 (1) ◽  
pp. 23-38 ◽  
Author(s):  
H. Gao ◽  
E. F. Wood ◽  
T. J. Jackson ◽  
M. Drusch ◽  
R. Bindlish
Keyword(s):  
United States ◽  
Soil Moisture ◽  
Hydrological Modeling ◽  
Dynamic Range ◽  
Microwave Remote Sensing ◽  
Microwave Emission ◽  
Southern United States ◽  
Retrieval Algorithm ◽  
Brightness Temperatures

Abstract Passive microwave remote sensing has been recognized as a potential method for measuring soil moisture. Combined with field observations and hydrological modeling brightness temperatures can be used to infer soil moisture states and fluxes in real time at large scales. However, operationally acquiring reliable soil moisture products from satellite observations has been hindered by three limitations: suitable low-frequency passive radiometric sensors that are sensitive to soil moisture and its changes; a retrieval model (parameterization) that provides operational estimates of soil moisture from top-of-atmosphere (TOA) microwave brightness temperature measurements at continental scales; and suitable, large-scale validation datasets. In this paper, soil moisture is retrieved across the southern United States using measurements from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) X-band (10.65 GHz) radiometer with a land surface microwave emission model (LSMEM) developed by the authors. Surface temperatures required for the retrieval algorithm were obtained from the Variable Infiltration Capacity (VIC) hydrological model using North American Land Data Assimilation System (NLDAS) forcing data. Because of the limited information content on soil moisture in the observed brightness temperatures over regions characterized by heavy vegetation, active precipitation, snow, and frozen ground, quality control flags for the retrieved soil moisture are provided. The resulting retrieved soil moisture database will be available through the NASA Goddard Space Flight Center (GSFC) Distributed Active Archive Center (DAAC) at a 1/8° spatial resolution across the southern United States for the 5-yr period of January 1998 through December 2002. Initial comparisons with in situ observations obtained from the Oklahoma Mesonet resulted in seasonal correlation coefficients exceeding 0.7 for half of the time covered by the dataset. The dynamic range of the satellite-derived soil moisture dataset is considerably higher compared to the in situ data. The spatial pattern of the TMI soil moisture product is consistent with the corresponding precipitation fields.

scholarly journals Influence of meter-scale wind-formed features on the variability of the microwave brightness temperature around Dome C in Antarctica

2013 ◽  
Vol 7 (4) ◽  
pp. 3675-3716 ◽  
Author(s):  
G. Picard ◽  
A. Royer ◽  
L. Arnaud ◽  
M. Fily
Keyword(s):  
Numerical Simulations ◽  
Brightness Temperature ◽  
High Sensitivity ◽  
Microwave Emission ◽  
Emission Model ◽  
Density Profiles ◽  
Microwave Brightness Temperature ◽  
Snow Properties ◽  
The Difference ◽  
Microwave Radiometers

Abstract. Space-borne passive microwave radiometers are widely used to retrieve information in snowy regions by exploiting the high sensitivity of microwave emission to snow properties. For the Antarctic Plateau, many studies presenting retrieval algorithms or numerical simulations have assumed, explicitly or not, that the subpixel-scale heterogeneity is negligible and that the retrieved properties were representative of whole pixels. In this paper, we investigate the spatial variations of brightness temperature over a range of a few kilometers in the Dome C area. Using ground-based radiometers towed by a vehicle allowing measurements with meter resolution, we collected brightness temperature transects at 11, 19 and 37 GHz at horizontal and vertical polarizations. The most remarkable observation was a series of regular undulations of the signal with a significant amplitude of up to 10 K at 37 GHz and a quasi-period of 30–50 m. In contrast, the variability at longer length scales seemed to be weak in the investigated area and the mean brightness temperature was close to AMSR-E and WindSat satellite observations for all the frequencies and polarisations. To establish a link between the snow characteristics and undulation-scale variations of microwave emission, we collected detailed snow grain size and density profiles to run the DMRT-ML microwave emission model at two points where opposite extrema of brightness temperature were observed. The numerical simulations revealed that the difference in density of the upper first meter of the snowpack explained most of the brightness temperature variations. In addition, we found in the field that these variations of density were linked to the hardness of the snowpack. Areas of hard snow – probably formed by the wind – were clearly visible and covered as much as 39% of the investigated area. Their brightness temperature was higher than in normal areas. This result implied that the microwave emission measured by satellites over Dome C is more complex than expected and very likely depends on the areal proportion of the two different types of areas having distinct snow properties.

scholarly journals Impact of spatial averaging on radar reflectivity at internal snowpack layer boundaries

2016 ◽  
Vol 62 (236) ◽  
pp. 1065-1074 ◽  
Author(s):  
N. RUTTER ◽  
H.-P. MARSHALL ◽  
K. TAPE ◽  
R. ESSERY ◽  
J. KING
Keyword(s):  
Continuous Wave ◽  
Microwave Remote Sensing ◽  
Surface Scattering ◽  
Spatial Averaging ◽  
Microwave Radar ◽  
Snow Stratigraphy ◽  
Wave Radar ◽  
Snowpack Properties ◽  
The Impact

ABSTRACTMicrowave radar amplitude within a snowpack can be strongly influenced by spatial variability of internal layer boundaries. We quantify the impact of spatial averaging of snow stratigraphy and physical snowpack properties on surface scattering from near-nadir frequency-modulated continuous-wave radar at 12–18 GHz. Relative permittivity, density, grain size and stratigraphic boundaries were measured in-situ at high resolution along the length of a 9 m snow trench. An optimal range of horizontal averaging (4–6 m) was identified to attribute variations in surface scattering at layer boundaries to dielectric contrasts estimated from centimetre-scale measurements of snowpack stratigraphy and bulk layer properties. Single vertical profiles of snowpack properties seldom captured the complex local variability influencing near-nadir radar surface scattering. We discuss implications of scaling in-situ measurements for snow radiative transfer modelling and evaluation of airborne microwave remote sensing of snow.

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