Evaluation of MODIS Albedo Product over Ice Caps in Iceland and Impact of Volcanic Eruptions on Their Albedo

Albedo is a key variable in the response of glaciers to climate. In Iceland, large albedo variations in the ice caps may be caused by the deposition of volcanic ash (tephra). Sparse in situ field measurements are insufficient to characterize the spatial variation of albedo over the ice caps. Here we evaluate the latest MCD43 MODIS albedo product (collection 6) to monitor albedo over the Icelandic ice caps using albedo from ten automatic weather stations in Vatnajökull and Langjökull as ground truth. We examine the influence of the albedo variability within MODIS pixels by comparing the results with a collection of Landsat scenes. The results indicate a good ability of the MODIS product to characterize the seasonal and interannual albedo changes with correlation coefficients ranging from 0.47 to 0.90 (median 0.84) and a small bias ranging from -0.07 to 0.09. The root-mean square errors (RMSE) ranging from 0.08 and 0.21, is larger than that from previous studies, but we did not discard the retrievals flagged as bad quality to maximize the amount of observations given the frequent cloud obstruction in Iceland. We find a positive but non-significant relationship between the RMSE and the subpixel variability as indicated by the standard deviation of the Landsat albedo within the MODIS pixel (R=0.48). The summer albedo maps and time series computed from the MODIS product show that the albedo decreased significantly after the Eyjafjallajökull and Grímsvötn eruptions in 2010 and 2011 in all the main ice caps (except the northernmost Drangajökull), with albedo reduction up to 0.6 over large regions of the accumulation areas. Following this validation, these data will be assimilated in an energy and mass balance model of to better understand the relative influence of the volcanic and climate forcing to the ongoing mass losses of Icelandic ice caps.

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A new Snow-SVAT to simulate the accumulation and ablation of seasonal snow cover beneath a forest canopy

Journal of Glaciology ◽

10.3189/172756504781830187 ◽

2004 ◽

Vol 50 (169) ◽

pp. 171-182 ◽

Cited By ~ 24

Author(s):

Melody J. Tribbeck ◽

Robert J. Gurney ◽

Elizabeth M. Morris ◽

David W. C. Pearson

Keyword(s):

Solar Radiation ◽

Snow Cover ◽

Forest Canopy ◽

Correlation Coefficients ◽

Field Measurements ◽

Radiation Model ◽

Physically Based ◽

Boreal Ecosystem ◽

Snow Model

AbstractA new snow—soil—vegetation—atmosphere transfer (Snow-SVAT) scheme, which simulates the accumulation and ablation of the snow cover beneath a forest canopy, is presented. The model was formulated by coupling a canopy optical and thermal radiation model to a physically based multi-layer snow model. This canopy radiation model is physically based yet requires few parameters, so can be used when extensive in situ field measurements are not available. Other forest effects such as the reduction of wind speed, interception of snow on the canopy and the deposition of litter were incorporated within this combined model, SNOWCAN, which was tested with data taken as part of the Boreal Ecosystem—Atmosphere Study (BOREAS) international collaborative experiment. Snow depths beneath four different canopy types and at an open site were simulated. Agreement between observed and simulated snow depths was generally good, with correlation coefficients ranging between r2 = 0.94 and r2 = 0.98 for all sites where automatic measurements were available. However, the simulated date of total snowpack ablation generally occurred later than the observed date. A comparison between simulated solar radiation and limited measurements of sub-canopy radiation at one site indicates that the model simulates the sub-canopy downwelling solar radiation early in the season to within measurement uncertainty.

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Elevation change, mass balance, dynamics and surging of Langjökull, Iceland from 1997 to 2007

Journal of Glaciology ◽

10.1017/jog.2016.55 ◽

2016 ◽

Vol 62 (233) ◽

pp. 497-511 ◽

Cited By ~ 3

Author(s):

ALLEN POPE ◽

IAN C. WILLIS ◽

FINNUR PÁLSSON ◽

NEIL S. ARNOLD ◽

W. GARETH REES ◽

...

Keyword(s):

Mass Balance ◽

Source Area ◽

Lapse Rate ◽

Balance Model ◽

Mass Balances ◽

Elevation Change ◽

Ice Dynamics ◽

Surface Mass ◽

Ice Caps

ABSTRACTGlaciers and ice caps around the world are changing quickly, with surge-type behaviour superimposed upon climatic forcing. Here, we study Iceland's second largest ice cap, Langjökull, which has both surge- and non-surge-type outlets. By differencing elevation change with surface mass balance, we estimate the contribution of ice dynamics to elevation change. We use DEMs, in situ stake measurements, regional reanalyses and a mass-balance model to calculate the vertical ice velocity. Thus, we not only compare the geodetic, modelled and glaciological mass balances, but also map spatial variations in glacier dynamics. Maps of emergence and submergence velocity successfully highlight the 1998 surge and subsequent quiescence of one of Langjökull's outlets by visualizing both source and sink areas. In addition to observing the extent of traditional surge behaviour (i.e. mass transfer from the accumulation area to the ablation area followed by recharge of the source area), we see peripheral areas where the surge impinged upon an adjacent ridge and subsequently retreated. While mass balances are largely in good agreement, discrepancies between modelled and geodetic mass balance may be explained by inaccurate estimates of precipitation, saturated adiabatic lapse rate or degree-day factors. Nevertheless, the study was ultimately able to investigate dynamic surge behaviour in the absence of in situ measurements during the surge.

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Modeling volcanic ash aggregation processes and related impacts on the April–May 2010 eruptions of Eyjafjallajökull volcano with WRF-Chem

Natural Hazards and Earth System Science ◽

10.5194/nhess-20-2721-2020 ◽

2020 ◽

Vol 20 (10) ◽

pp. 2721-2737 ◽

Cited By ~ 1

Author(s):

Sean D. Egan ◽

Martin Stuefer ◽

Peter W. Webley ◽

Taryn Lopez ◽

Catherine F. Cahill ◽

...

Keyword(s):

Volcanic Ash ◽

Field Measurements ◽

Volcanic Eruptions ◽

Sensitivity Study ◽

Collision Kernel ◽

Aggregation Process ◽

Airborne Measurements ◽

Aggregation Processes ◽

Ash Transport

Abstract. Volcanic eruptions eject ash and gases into the atmosphere that can contribute to significant hazards to aviation, public and environment health, and the economy. Several volcanic ash transport and dispersion (VATD) models are in use to simulate volcanic ash transport operationally, but none include a treatment of volcanic ash aggregation processes. Volcanic ash aggregation can greatly reduce the atmospheric budget, dispersion and lifetime of ash particles, and therefore its impacts. To enhance our understanding and modeling capabilities of the ash aggregation process, a volcanic ash aggregation scheme was integrated into the Weather Research Forecasting with online Chemistry (WRF-Chem) model. Aggregation rates and ash mass loss in this modified code are calculated in line with the meteorological conditions, providing a fully coupled treatment of aggregation processes. The updated-model results were compared to field measurements of tephra fallout and in situ airborne measurements of ash particles from the April–May 2010 eruptions of Eyjafjallajökull volcano, Iceland. WRF-Chem, coupled with the newly added aggregation code, modeled ash clouds that agreed spatially and temporally with these in situ and field measurements. A sensitivity study provided insights into the mechanics of the aggregation code by analyzing each aggregation process (collision kernel) independently, as well as by varying the fractal dimension of the newly formed aggregates. In addition, the airborne lifetime (e-folding) of total domain ash mass was analyzed for a range of fractal dimensions, and a maximum reduction of 79.5 % of the airborne ash lifetime was noted.

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Full-physics 3-D heterogeneous simulations of electromagnetic induction fields on level and deformed sea ice

Annals of Glaciology ◽

10.3189/2015aog69a737 ◽

2015 ◽

Vol 56 (69) ◽

pp. 405-414 ◽

Cited By ~ 3

Author(s):

Jesse P. Samluk ◽

Cathleen A. Geiger ◽

Chester J. Weiss

Keyword(s):

Sea Ice ◽

Sea Water ◽

Three Dimensional ◽

Field Measurements ◽

Ground Truth ◽

Field Surveys ◽

Finite Volume Discretization ◽

New Finding ◽

Em Field

AbstractIn this paper we explore simulated responses of electromagnetic (EM) signals relative to in situ field surveys and quantify the effects that different values of conductivity in sea ice have on the EM fields. We compute EM responses of ice types with a three-dimensional (3-D) finite-volume discretization of Maxwell’s equations and present 2-D sliced visualizations of their associated EM fields at discrete frequencies. Several interesting observations result: First, since the simulator computes the fields everywhere, each gridcell acts as a receiver within the model volume, and captures the complete, coupled interactions between air, snow, sea ice and sea water as a function of their conductivity; second, visualizations demonstrate how 1-D approximations near deformed ice features are violated. But the most important new finding is that changes in conductivity affect EM field response by modifying the magnitude and spatial patterns (i.e. footprint size and shape) of current density and magnetic fields. These effects are demonstrated through a visual feature we define as ‘null lines’. Null line shape is affected by changes in conductivity near material boundaries as well as transmitter location. Our results encourage the use of null lines as a planning tool for better ground-truth field measurements near deformed ice types.

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Performance Assessment of a New Stationarity-Based Parameter Estimation Method with a Simplified Land Surface Model Using In Situ and Remotely Sensed Surface States

Journal of Hydrometeorology ◽

10.1175/jhm-d-12-0118.1 ◽

2014 ◽

Vol 15 (1) ◽

pp. 340-358 ◽

Cited By ~ 1

Author(s):

Jian Sun ◽

Guido D. Salvucci

Keyword(s):

Parameter Estimation ◽

Surface State ◽

Estimation Method ◽

Surface States ◽

Remotely Sensed ◽

Surface Fluxes ◽

Balance Model ◽

Surface Model ◽

Mean Square Errors

Abstract This study evaluates the performance of a new stationarity-based method for parameter estimation of a simple coupled water and energy balance model using in situ and remotely sensed surface soil moisture [from Advanced Microwave Scanning Radiometer for Earth Observing System (EOS; AMSR-E)] and surface temperature [from a combined Moderate Resolution Imaging Spectroradiometer (MODIS) and AMSR-E product]. Parameter estimation is carried out using both direct calibration to measured surface fluxes (latent, sensible, and ground heat) and a recently published method based on enforcing stationarity of model-predicted surface state tendency terms. The latter stationarity-based method was developed for parameter estimation without knowledge of observed fluxes—that is, it requires only forcing terms (e.g., radiation, wind speed, air temperature) and surface states (moisture and temperature). In addition, the stationarity-based method can easily handle gaps in atmospheric forcing and surface state data, as it does not integrate over time to simulate fluxes. The evaluation is conducted at three AmeriFlux sites. Changing the data sources of surface states (in situ measured and remotely sensed data) leads to little degradation in estimating turbulent fluxes despite the relatively poor quality of satellite data at some sites. In all cases, direct calibration yields marginally better predictions than the stationarity-based method, with site-averaged root-mean-square errors for daily total energy fluxes approximately 5–6 W m−2 lower. However, direct calibration requires observed fluxes in the objective function, which imposes a strong limit on its application.

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Estimation of Downwelling Surface Longwave Radiation under Heavy Dust Aerosol Sky

10.20944/preprints201612.0064.v1 ◽

2016 ◽

Author(s):

Chunlei Wang ◽

Bo-Hui Tang ◽

Hua Wu ◽

Ronglin Tang ◽

Zhao-Liang Li

Keyword(s):

Satellite Data ◽

Land Surface ◽

Radiative Forcing ◽

Longwave Radiation ◽

Field Measurements ◽

Dust Aerosol ◽

Climate Forcing ◽

Proposed Model ◽

Atmospheric Profile ◽

Mean Square Errors

The variation of aerosols, especially dust aerosol, in time and space plays an important role in climate forcing studies. Aerosols can effectively reduce land surface longwave emission and re-emit energy at a colder temperature, making estimation of downwelling surface longwave radiation (DSLR) with satellite data difficult. Using the latest atmospheric radiative transfer code (MODTRAN 5.0), we simulate the outgoing longwave radiation (OLR) and DSLR under different land surface and atmospheric profile conditions. The results show that dust aerosol has an obvious “warming” effect to longwave radiation compared with other aerosols, that aerosol longwave radiative forcing (ALRF) increased with increasing aerosol optical depth (AOD), and that the atmospheric water vapor content (WVC) is critical to the understanding of ALRF. A method is proposed to improve the accuracy of DSLR estimation from satellite data for the skies under heavy dust aerosols. The AOD and atmospheric WVC under cloud-free conditions with a relatively simple satellite-based radiation model that yields the high accurate DSLR under heavy dust aerosol are used explicitly as model input to reduce the effects of dust aerosol on the estimation of DSLR. Validations of the proposed model with satellites data and field measurements show that it estimates the DSLR accurately under heavy dust aerosol skies. The root mean square errors (RMSEs) are 20.4 W/M2 and 24.2 W/M2 for Terra and Aqua satellites, respectively, at the Yingke site, and the biases are 2.7 W/M2 and 9.6 W/M2, respectively. For the Arvaikheer site, the RMSEs are 23.2 W/M2 and 19.8 W/M2 for Terra and Aqua, respectively, and the biases are 7.8 W/M2 and 10.5 W/M2, respectively. The proposed method is especially applicable to acquire relatively high accurate DSLR under heavy dust aerosol using MODIS data with available WVC and AOD data.

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Modeling volcanic ash aggregation processes and related impacts on the April/May 2010 eruptions of Eyjafjallajökull Volcano with WRF-Chem

10.5194/nhess-2019-382 ◽

2019 ◽

Author(s):

Sean D. Egan ◽

Martin Stuefer ◽

Peter W. Webley ◽

Taryn Lopez ◽

Catherine F. Cahill ◽

...

Keyword(s):

Fractal Dimension ◽

Volcanic Ash ◽

Field Measurements ◽

Volcanic Eruptions ◽

Collision Kernel ◽

Aggregation Process ◽

Airborne Measurements ◽

Aggregation Processes ◽

Ash Transport

Abstract. Volcanic eruptions eject ash and gases into the atmosphere that can contribute to significant hazards to aviation, public and environment health, and the economy. Several volcanic ash transport and dispersion (VATD) models are in use to simulate volcanic ash transport operationally, but none include a treatment of volcanic ash aggregation processes. Volcanic ash aggregation can greatly reduce the atmospheric budget, dispersion and lifetime of ash particles and therefore its impacts. To enhance our understanding and modeling capabilities of the ash aggregation process, a volcanic ash aggregation scheme was integrated into the Weather Research Forecasting with online Chemistry (WRF-Chem) model. Aggregation rates and ash mass loss in this modified code are calculated in-line with the meteorological conditions, providing a fully coupled treatment of aggregation processes. The updated-model results were compared to field measurements of tephra fallout and in situ airborne measurements of ash particles from the April/May 2010 eruptions of Eyjafjallajökull Volcano, Iceland. WRF-Chem, coupled with the newly added aggregation code, modeled ash clouds that agreed spatially and temporally with these in situ and field measurements. A sensitivity study provided insights into the mechanics of the aggregation code by analyzing each aggregation process (collision kernel) independently, as well as by varying the fractal dimension of the newly formed aggregates. In addition, the airborne lifetime (e-folding) of total domain ash mass was analyzed for a range of fractal dimension, and a maximum reduction of 79.5 % of the airborne ash lifetime was noted.

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Evaluation of HF Radar Wave Measurements in Iberian Peninsula by Comparison with Satellite Altimetry and in Situ Wave Buoy Observations

Remote Sensing ◽

10.3390/rs12213623 ◽

2020 ◽

Vol 12 (21) ◽

pp. 3623

Author(s):

Isabel Bué ◽

Álvaro Semedo ◽

João Catalão

Keyword(s):

Iberian Peninsula ◽

Time Window ◽

Correlation Coefficients ◽

Ground Truth ◽

Hf Radar ◽

Extreme Wave ◽

Wave Measurements ◽

Wave Heights ◽

In Situ Observations

The skills of CODAR SeaSonde coastal high-frequency radars (HFR) located in the West Iberian Peninsula on measuring wave parameters are compared to in situ (buoy) and satellite altimeters (SA) wave observations. Significant wave heights (SWH), wave periods, and wave directions are compared over a time window of 36-months, from January 2017 to December 2019. The ability of HFR systems to capture extreme wave events is also assessed by comparing SWH measurements during the Emma storm, which hit the Iberian Peninsula in March 2018. The analysis presented in this study shows a slight overestimation of the SWH by the HFR systems. Comparisons with in situ observations revealed correlation coefficients (R) of the order of 0.69–0.87, biases below 0.60 m, root-mean-squared errors (RMSE) between 0.89 m to 1.18 m, and a slope regression between 1.01 and 1.26. Using buoy observations as reference ground truth, the comparisons with SA revealed Rs higher than 0.94, biases under 0.19 m, and RMSEs between 0.17 m and 0.42 m. Since in situ observations do not overlap all the HFR range cells (RC), and its correlation coefficients with SA have shown good agreement (R > 0.94), Sentinel-3 SA (SRAL) SWH measurements are further used for the validation of the HFR systems SWH observations. The comparison between the HFR and the SA collocated SWH observations allowed the evaluation of the ability of the radars to retrieve wave data as a function of the distance to the coast, particularly during extreme wave events. The comparison of the lower frequency (4.86 MHz) HFR coastal radars with the SA measurements showed an R of 0.94–0.99, a negative but reduced bias (−0.37), and an RMSE of 0.53 m. The higher frequency HFR systems (12–13.5 MHz) showed R between 0.53 and 0.82, and a clear overestimation of the SWH by the HFR sites.

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Consistency of Radiometric Satellite Data over Lakes and Coastal Waters with Local Field Measurements

Remote Sensing ◽

10.3390/rs12040616 ◽

2020 ◽

Vol 12 (4) ◽

pp. 616 ◽

Cited By ~ 3

Author(s):

Krista Alikas ◽

Ilmar Ansko ◽

Viktor Vabson ◽

Ave Ansper ◽

Kersti Kangro ◽

...

Keyword(s):

Coastal Waters ◽

Atmospheric Correction ◽

Field Measurements ◽

Ground Truth ◽

Local Data ◽

Ground Truth Data ◽

In Situ Data ◽

Global Coverage

The Sentinel-3 mission launched its first satellite Sentinel-3A in 2016 to be followed by Sentinel-3B and Sentinel-3C to provide long-term operational measurements over Earth. Sentinel-3A and 3B are in full operational status, allowing global coverage in less than two days, usable to monitor optical water quality and provide data for environmental studies. However, due to limited ground truth data, the product quality has not yet been analyzed in detail with the fiducial reference measurement (FRM) dataset. Here, we use the fully characterized ground truth FRM dataset for validating Sentinel-3A Ocean and Land Colour Instrument (OLCI) radiometric products over optically complex Estonian inland waters and Baltic Sea coastal areas. As consistency between satellite and local data depends on uncertainty in field measurements, filtering of the in situ data has been made based on the uncertainty for the final comparison. We have compared various atmospheric correction methods and found POLYMER (POLYnomial-based algorithm applied to MERIS) to be most suitable for optically complex waters under study in terms of product accuracy, amount of usable data and also being least influenced by the adjacency effect.

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Reference Measurements in Developing UAV Systems for Detecting Pests, Weeds, and Diseases

Remote Sensing ◽

10.3390/rs13071238 ◽

2021 ◽

Vol 13 (7) ◽

pp. 1238

Author(s):

Jere Kaivosoja ◽

Juho Hautsalo ◽

Jaakko Heikkinen ◽

Lea Hiltunen ◽

Pentti Ruuttunen ◽

...

Keyword(s):

Reference Data ◽

Measurement Techniques ◽

Synthetic Data ◽

Ground Truth ◽

Precision Farming ◽

Aerial Imaging ◽

Aerial Vehicle ◽

Uav Images ◽

Reference Measurements

The development of UAV (unmanned aerial vehicle) imaging technologies for precision farming applications is rapid, and new studies are published frequently. In cases where measurements are based on aerial imaging, there is the need to have ground truth or reference data in order to develop reliable applications. However, in several precision farming use cases such as pests, weeds, and diseases detection, the reference data can be subjective or relatively difficult to capture. Furthermore, the collection of reference data is usually laborious and time consuming. It also appears that it is difficult to develop generalisable solutions for these areas. This review studies previous research related to pests, weeds, and diseases detection and mapping using UAV imaging in the precision farming context, underpinning the applied reference measurement techniques. The majority of the reviewed studies utilised subjective visual observations of UAV images, and only a few applied in situ measurements. The conclusion of the review is that there is a lack of quantitative and repeatable reference data measurement solutions in the areas of mapping pests, weeds, and diseases. In addition, the results that the studies present should be reflected in the applied references. An option in the future approach could be the use of synthetic data as reference.

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