scholarly journals Development and validation of a snow albedo algorithm for the MODIS instrument

2002 ◽  
Vol 34 ◽  
pp. 45-52 ◽  
Author(s):  
Andrew G. Klein ◽  
Julienne Stroeve
Keyword(s):  
Atmospheric Correction ◽  
Anisotropic Scattering ◽  
Daily Basis ◽  
Surface Radiation ◽  
Radiation Budget ◽  
Cloud Detection ◽  
Snow Albedo ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Using Data

AbstractA prototype snow albedo algorithm has been developed for the Moderate Resolution Imaging Spectroradiometer (MODIS). It complements existing MODIS products by providing albedo measurements for areas mapped as snow on a global daily basis by MODIS. Cloud detection and atmospheric correction are accomplished using existing MODIS products. Models of the bidirectional reflectance of snow created using a discrete-ordinate radiative transfer (DISORT) model are used to correct for anisotropic scattering effects over non-forested surfaces. Initial algorithm validation is undertaken through comparisons with broadband albedo measurements made at the U.S. National Oceanic and Atmospheric Administration (NOAA) Surface Radiation Budget Network (SURFRAD) site in Fort Peck, MT. In situ SURFRAD albedo measurements are compared to daily MODIS snow albedo retrievals for the period 21–26 November 2000 created from five narrow-to-broadband albedo conversion schemes. The prototype MODIS algorithm produces reasonable broadband albedo estimates. Maximum daily differences between the five MODIS broadband albedo retrievals and in situ albedo are 15%. Daily differences between the best MODIS broadband estimate and the measured SURFRAD albedo are 1–8%. However, no single conversion scheme consistently provides the closest albedo estimate. Further validation and algorithm development using data from North America and Greenland is ongoing.

scholarly journals Snow Albedo Seasonality and Trend from MODIS Sensor and Ground Data at Johnsons Glacier, Livingston Island, Maritime Antarctica

Sensors ◽  
2019 ◽  
Vol 19 (16) ◽  
pp. 3569
Author(s):  
Calleja ◽  
Corbea-Pérez ◽  
Fernández ◽  
Recondo ◽  
Peón ◽  
...  
Keyword(s):  
Moving Average ◽  
Data Sets ◽  
Snow Albedo ◽  
Livingston Island ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Sky Conditions ◽  
Cloud Mask

The aim of this work is to investigate whether snow albedo seasonality and trend under all sky conditions at Johnsons Glacier (Livingston Island, Antarctica) can be tracked using the Moderate Resolution Imaging Spectroradiometer (MODIS) snow albedo daily product MOD10A1. The time span is from December 2006 to February 2015. As the MOD10A1 snow albedo product has never been used in Antarctica before, we also assess the performance for the MOD10A1 cloud mask. The motivation for this work is the need for a description of snow albedo under all sky conditions (including overcast days) using satellite data with mid-spatial resolution. In-situ albedo was filtered with a 5-day windowed moving average, while the MOD10A1 data were filtered using a maximum filter. Both in-situ and MOD10A1 data follow an exponential decay during the melting season, with a maximum decay of 0.049/0.094 day−1 (in-situ/MOD10A1) for the 2006–2007 season and a minimum of 0.016/0.016 day−1 for the 2009–2010 season. The duration of the decay varies from 85 days (2007–2008) to 167 days (2013–2014). Regarding the albedo trend, both data sets exhibit a slight increase of albedo, which may be explained by an increase of snowfall along with a decrease of snowmelt in the study area. Annual albedo increases of 0.2% and 0.7% are obtained for in-situ and MOD10A1 data, respectively, which amount to respective increases of 2% and 6% in the period 2006–2015. We conclude that MOD10A1 can be used to characterize snow albedo seasonality and trend on Livingston Island when filtered with a maximum filter.

scholarly journals TURAC—A New Instrument Package for Radiation Budget Measurements and Cloud Detection

2005 ◽  
Vol 22 (10) ◽  
pp. 1473-1479 ◽  
Author(s):  
C. Ruckstuhl ◽  
R. Philipona
Keyword(s):  
Numerical Algorithms ◽  
Cloud Amount ◽  
Longwave Radiation ◽  
Surface Radiation ◽  
Radiation Budget ◽  
Cloud Detection ◽  
Radiation Fluxes ◽  
New Instrument ◽  
Temperature And Humidity ◽  
Flux Measurements

Abstract Atmospheric radiation flux measurements and the resulting surface radiation budget are important quantities for greenhouse effect and climate change investigations. Accurate net shortwave and longwave fluxes, in conjunction with numerical algorithms, also allow monitoring of the radiative effect of clouds and the nowcasting of the cloud amount. To achieve certain advantages on the accuracy of flux measurements a new instrument is developed that measures downward and upward shortwave and longwave radiation with the same sensors. Two high-quality instruments—a pyranometer for shortwave and a pyrgeometer for longwave measurements—are mounted on a pivotable sensor head, which is rotated up and down in 10-min intervals. To keep the instrument domes free from dew and ice, and to minimize the pyranometer thermal offset, both sensors are ventilated with slightly heated air. Additionally, a ventilated temperature and humidity sensor is integrated in the new instrument. The combination of measurements of radiation fluxes, temperature, and humidity allows for instrument use for autonomous and automatic cloud amount detection. The Temperature, Humidity, Radiation and Clouds (TURAC) sensor has been successfully tested under harsh alpine winter conditions, as well as under moderate lowland conditions. Comparisons to reference instruments showed all radiation fluxes to be within a maximum bias and rms difference of 1.6% or 1.4 W m−2 on daily averages.

scholarly journals Aerosol trends as a potential driver of regional climate in the central United States: evidence from observations

2017 ◽  
Vol 17 (22) ◽  
pp. 13559-13572 ◽  
Author(s):  
Daniel H. Cusworth ◽  
Loretta J. Mickley ◽  
Eric M. Leibensperger ◽  
Michael J. Iacono
Keyword(s):  
United States ◽  
Radiative Transfer ◽  
Southeastern United States ◽  
Radiant Energy ◽  
Surface Radiation ◽  
Radiation Budget ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Clear Sky

Abstract. In situ surface observations show that downward surface solar radiation (SWdn) over the central and southeastern United States (US) has increased by 0.58–1.0 Wm−2 a−1 over the 2000–2014 time frame, simultaneously with reductions in US aerosol optical depth (AOD) of 3.3–5.0  ×  10−3 a−1. Establishing a link between these two trends, however, is challenging due to complex interactions between aerosols, clouds, and radiation. Here we investigate the clear-sky aerosol–radiation effects of decreasing US aerosols on SWdn and other surface variables by applying a one-dimensional radiative transfer to 2000–2014 measurements of AOD at two Surface Radiation Budget Network (SURFRAD) sites in the central and southeastern United States. Observations characterized as clear-sky may in fact include the effects of thin cirrus clouds, and we consider these effects by imposing satellite data from the Clouds and Earth's Radiant Energy System (CERES) into the radiative transfer model. The model predicts that 2000–2014 trends in aerosols may have driven clear-sky SWdn trends of +1.35 Wm−2 a−1 at Goodwin Creek, MS, and +0.93 Wm−2 a−1 at Bondville, IL. While these results are consistent in sign with observed trends, a cross-validated multivariate regression analysis shows that AOD reproduces 20–26 % of the seasonal (June–September, JJAS) variability in clear-sky direct and diffuse SWdn at Bondville, IL, but none of the JJAS variability at Goodwin Creek, MS. Using in situ soil and surface flux measurements from the Ameriflux network and Illinois Climate Network (ICN) together with assimilated meteorology from the North American Land Data Assimilation System (NLDAS), we find that sunnier summers tend to coincide with increased surface air temperature and soil moisture deficits in the central US. The 1990–2015 trends in the NLDAS SWdn over the central US are also of a similar magnitude to our modeled 2000–2014 clear-sky trends. Taken together, these results suggest that climate and regional hydrology in the central US are sensitive to the recent reductions in aerosol concentrations. Our work has implications for severely polluted regions outside the US, where improvements in air quality due to reductions in the aerosol burden could inadvertently pose an enhanced climate risk.

scholarly journals UV Reflectance of the Ocean from DSCOVR/EPIC: Comparisons with a Theoretical Model and Aura/OMI Observations

2019 ◽  
Vol 36 (11) ◽  
pp. 2087-2099 ◽  
Author(s):  
Alexander Vasilkov ◽  
Alexei Lyapustin ◽  
B. Greg Mitchell ◽  
Dong Huang
Keyword(s):  
Radiative Transfer ◽  
Chlorophyll Concentration ◽  
Atmospheric Correction ◽  
Ocean Water ◽  
Cloud Detection ◽  
Ozone Monitoring Instrument ◽  
Inherent Optical Properties ◽  
Uv Reflectance ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer

AbstractUltraviolet (UV) data collected over the ocean by the Earth Polychromatic Imaging Camera (EPIC) on the Deep Space Climate Observatory (DSCOVR) are used. The Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm adapted for EPIC processing performs cloud detection, aerosol retrievals, and atmospheric correction providing the water-leaving reflectance of the ocean at 340 and 388 nm. The water-leaving reflectance is an indicator of the presence of absorbing and scattering constituents in seawater. The retrieved water-leaving reflectance is compared with full radiative transfer calculations based on a model of inherent optical properties (IOP) of ocean water in UV. The model is verified with data collected on the Aerosol Characterization Experiments (ACE) Asia cruise supported by the NASA Sensor Intercomparison for Marine Biological and Interdisciplinary Ocean Studies (SIMBIOS) project. The model assumes that the ocean water IOPs are parameterized through a chlorophyll concentration. The radiative transfer simulations were carried out using the climatological chlorophyll concentration from the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the Aqua satellite. The EPIC-derived water-leaving reflectance is also compared with climatological Lambertian-equivalent reflectivity (LER) of the ocean derived from measurements of the Ozone Monitoring Instrument (OMI) on board the NASA polar-orbiting Aura satellite. The EPIC reflectance agrees well (within 0.01) with the model reflectance except for oligotrophic oceanic areas. For those areas, the model reflectance is biased low by about 0.01 at 340 nm and up to 0.03 at 388 nm. The OMI-derived climatological LER is significantly higher than the EPIC water-leaving reflectance, largely due to the surface glint contribution. The globally averaged difference is about 0.04.

scholarly journals Sensitivity Analysis and Validation of Daytime and Nighttime Land Surface Temperature Retrievals from Landsat 8 Using Different Algorithms and Emissivity Models

2020 ◽  
Vol 12 (17) ◽  
pp. 2776 ◽  
Author(s):  
Aliihsan Sekertekin ◽  
Stefania Bonafoni
Keyword(s):  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
The United States ◽  
In Situ Measurements ◽  
Surface Radiation ◽  
Radiation Budget ◽  
Sensitivity Analyses ◽  
Landsat 8

Land Surface Temperature (LST) is a substantial element indicating the relationship between the atmosphere and the land. This study aims to examine the efficiency of different LST algorithms, namely, Single Channel Algorithm (SCA), Mono Window Algorithm (MWA), and Radiative Transfer Equation (RTE), using both daytime and nighttime Landsat 8 data and in-situ measurements. Although many researchers conducted validation studies of daytime LST retrieved from Landsat 8 data, none of them considered nighttime LST retrieval and validation because of the lack of Land Surface Emissivity (LSE) data in the nighttime. Thus, in this paper, we propose using a daytime LSE image, whose acquisition is close to nighttime Thermal Infrared (TIR) data (the difference ranges from one day to four days), as an input in the algorithm for the nighttime LST retrieval. In addition to evaluating the three LST methods, we also investigated the effect of six Normalized Difference Vegetation Index (NDVI)-based LSE models in this study. Furthermore, sensitivity analyses were carried out for both in-situ measurements and LST methods for satellite data. Simultaneous ground-based LST measurements were collected from Atmospheric Radiation Measurement (ARM) and Surface Radiation Budget Network (SURFRAD) stations, located at different rural environments of the United States. Concerning the in-situ sensitivity results, the effect on LST of the uncertainty of the downwelling and upwelling radiance was almost identical in daytime and nighttime. Instead, the uncertainty effect of the broadband emissivity in the nighttime was half of the daytime. Concerning the satellite observations, the sensitivity of the LST methods to LSE proved that the variation of the LST error was smaller than daytime. The accuracy of the LST retrieval methods for daytime Landsat 8 data varied between 2.17 K Root Mean Square Error (RMSE) and 5.47 K RMSE considering all LST methods and LSE models. MWA with two different LSE models presented the best results for the daytime. Concerning the nighttime accuracy of the LST retrieval, the RMSE value ranged from 0.94 K to 3.34 K. SCA showed the best results, but MWA and RTE also provided very high accuracy. Compared to daytime, all LST retrieval methods applied to nighttime data provided highly accurate results with the different LSE models and a lower bias with respect to in-situ measurements.

scholarly journals Aerosol trends as a potential driver of regional climate in the central United States: Evidence from observations

2017 ◽  
Author(s):  
Daniel H. Cusworth ◽  
Loretta J. Mickley ◽  
Eric M. Leibensperger ◽  
Michael J. Iacono
Keyword(s):  
United States ◽  
Radiative Transfer ◽  
Southeastern United States ◽  
Radiant Energy ◽  
Surface Radiation ◽  
Radiation Budget ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Clear Sky

Abstract. In situ surface observations show that downward surface solar radiation (SWdn) over the central and southeastern United States (U.S.) has increased by 0.58–1.0 W m−2 a−1 over the 2000–2014 timeframe, simultaneously with reductions in U.S. aerosol optical depth (AOD) of 3.3–5.0 × 10−3 a−1. Establishing a link between these two trends, however, is challenging due to complex interactions between aerosols, clouds, and radiation. Here we investigate the clear-sky aerosol–radiation effects of decreasing U.S. aerosols on SWdn and other surface variables by applying a one-dimensional radiative transfer to 2000 2014 measurements of AOD at two Surface Radiation Budget Network (SURFRAD) sites in the central and southeastern United States. Observations characterized as clear–sky may in fact include the effects of thin cirrus clouds, and we consider these effects by imposing satellite data from the Clouds and Earth's Radiant Energy System (CERES) into the radiative transfer model. The model predicts that 2000–2014 trends in aerosols may have driven clear-sky SWdn trends of +1.35 W m−2 a−1 at Goodwin Creek, MS, and +0.93 W m−2 a−1 at Bondville, IL. While these results are consistent in sign with observed trends, a cross-validated multivariate regression analysis shows that AOD reproduces 20–26 % of the seasonal (June–September, JJAS) variability in clear-sky direct and diffuse SWdn at Bondville, IL, but none of the JJAS variability at Goodwin Creek, MS. Using in situ soil and surface flux measurements from the Ameriflux network and Illinois Climate Network (ICN) together with assimilated meteorology from the North American Land Data Assimilation System (NLDAS), we find that sunnier summers tend to coincide with increased surface air temperature and soil moisture deficits in the central U.S. The 1990–2015 trends in the NLDAS SWdn over the central U.S. are also of a similar magnitude as our modeled 2000–2014 clear-sky trends. Taken together, these results suggest that climate and regional hydrology in the central U.S. are sensitive to the recent reductions in aerosol concentrations. Our work has implications for severely polluted regions outside the U.S., where improvements in air quality due to reductions in the aerosol burden could inadvertently increase vulnerability to drought.

scholarly journals Estimation of Aerosol-Corrected Surface Solar Irradiance at Local Incidence Angle over Different Physiographic Subdivisions of India and Adjoining Areas Using MODIS and SRTM Data

2020 ◽  
Vol 37 (2) ◽  
pp. 161-175 ◽  
Author(s):  
Libeesh Lukose ◽  
Dibyendu Dutta
Keyword(s):  
Solar Irradiance ◽  
Incidence Angle ◽  
Surface Radiation ◽  
Radiation Budget ◽  
Transmission Factor ◽  
Radiation Data ◽  
Surface Irradiance ◽  
Dewpoint Temperature ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer

AbstractSurface solar irradiance is considered as an important component of the surface radiation budget and constitutes one of the essential climate variables. In the present study, clear-sky instantaneous solar irradiance was estimated over 15 physiographic regions of India during January. Dewpoint temperature profiles were extracted from Moderate Resolution Imaging Spectroradiometer (MODIS) instrument onboard the Aqua satellite to calculate actual vapor pressure following Clausius–Clapeyron equation, which was further used in the Zillman parameterization for solar irradiance. The effect of terrain slope and aspect on direct radiation was taken into account by modifying the parameterized incoming shortwave flux by introducing the local incidence angle. A significant positive correlation was found between terrain-corrected MODIS irradiance and measured radiation data but the RMSE was very high (187 W m−2). Further, the effect of aerosol extinction was introduced by multiplying the terrain-corrected flux by a transmission factor obtained from satellite-derived aerosol optical depth and Ångström exponent. Due to the inclusion of the aerosol transmittance, the correlation was significantly improved (R2 = 0.84) and RMSE was reduced (31 W m−2). Further the effect of surface orientation on surface irradiance was evaluated on six hilly subdivisions. A large variation in the flux (135 to 161 W m−2) was noticed among different aspect classes. The variability was highest in the Eastern Himalayas subdivision (>250 W m−2) and was a minimum in the Eastern Hills subdivision (<28 W m−2). In absence of ground radiation data in hills, Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), was used for validation of model output but it performed poorly and got saturated at higher surface irradiance values.

scholarly journals Enhancing Model Skill by Assimilating SMOPS Blended Soil Moisture Product into Noah Land Surface Model

2015 ◽  
Vol 16 (2) ◽  
pp. 917-931 ◽  
Author(s):  
Jifu Yin ◽  
Xiwu Zhan ◽  
Youfei Zheng ◽  
Jicheng Liu ◽  
Li Fang ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Surface Radiation ◽  
Radiation Budget ◽  
Shortwave Radiation ◽  
Surface Model ◽  
Spatial Coverage ◽  
In Situ Observations ◽  
The Impact

Abstract Many studies that have assimilated remotely sensed soil moisture into land surface models have generally focused on retrievals from a single satellite sensor. However, few studies have evaluated the merits of assimilating ensemble products that are merged soil moisture retrievals from several different sensors. In this study, the assimilation of the Soil Moisture Operational Products System (SMOPS) blended soil moisture (SBSM) product, which is a combination of soil moisture products from WindSat, Advanced Scatterometer (ASCAT), and Soil Moisture and Ocean Salinity (SMOS) satellite sensors is examined. Using the ensemble Kalman filter (EnKF), a synthetic experiment is performed on the global domain at 25-km resolution to assess the impact of assimilating the SBSM product. The benefit of assimilating SBSM is assessed by comparing it with in situ observations from U.S. Department of Agriculture Soil Climate Analysis Network (SCAN) and the Surface Radiation Budget Network (SURFRAD). Time-averaged surface-layer soil moisture fields from SBSM have a higher spatial coverage and generally agree with model simulations in the global patterns of wet and dry regions. The impacts of assimilating SMOPS blended data on model soil moisture and soil temperature are evident in both sparsely and densely vegetated areas. Temporal correlations between in situ observations and net shortwave radiation and net longwave radiation are higher with assimilating SMOPS blended product than without the data assimilation.

scholarly journals Development and evaluation of surface shortwave flux parameterizations for use in sea-ice models

1997 ◽  
Vol 25 ◽  
pp. 33-37
Author(s):  
Jeffrey R. Key ◽  
Yong Liu ◽  
Robert S. Stone
Keyword(s):  
Sea Ice ◽  
Surface Radiation ◽  
Radiation Budget ◽  
Shortwave Radiation ◽  
The Arctic ◽  
Polar Regions ◽  
Computationally Efficient ◽  
Using Data ◽  
One Year ◽  
Mean Square Errors

The surface radiation budget of the polar regions strongly influences ice growth and melt. Thermodynamic sea-ice models therefore require accurate yet computationally efficient methods of computing radiative fluxes. In this paper a new parameterization of the downwelling shortwave radiation flux at the Arctic surface is developed and compared to a variety of existing schemes. Parameterized llnxes are compared to in situ measurements using data for one year at Barrow, Alaska. Our results show that the new parameterization can estimate the downwelling shortwave flux with mean and root mean square errors of 1 and 5%, respectively, for clear conditions and 5 and 20% for cloudy conditions. The new parameterization offers a unified approach to estimating downwelling shortwave fluxes under clear and cloudy conditions, and is more accurate than existing schemes.

scholarly journals Intercomparison of Independent Calibration Techniques Applied to the Visible Channel of the ISCCP B1 Data

2015 ◽  
Vol 32 (6) ◽  
pp. 1225-1240 ◽  
Author(s):  
Anand K. Inamdar ◽  
Kenneth R. Knapp
Keyword(s):  
Surface Radiation ◽  
Radiation Budget ◽  
Absolute Calibration ◽  
Climatic Data ◽  
Random Errors ◽  
National Climatic Data Center ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Earth’S Climate ◽  
Independent Calibration ◽  
Calibration Techniques

AbstractThe International Satellite Cloud Climatology Project (ISCCP) B1 data, which were recently rescued at the National Oceanic and Atmospheric Administration’s National Climatic Data Center (NOAA/NCDC), are a resource for the study of the earth’s climate. The ISCCP B1 data represent geostationary satellite imagery for all channels, including the infrared (IR), visible, and IR water vapor sensors. These are global 3-hourly snapshots from satellites around the world, covering the time period from 1979 to present at approximately 10-km spatial resolution. ISCCP B1 data will be used in the reprocessing of the cloud products, resulting in a higher-resolution ISCCP cloud climatology, surface radiation budget (SRB), etc. To realize the promise of a higher-resolution cloud climatology from the B1 data, an independent assessment of the calibration of the visible band was performed. The present study aims to accomplish this by cross-calibrating with the intercalibrated Advanced Very High Resolution Radiometer (AVHRR) reflectance data from the AVHRR Pathfinder Atmospheres–Extended (PATMOS-x) dataset. Since the reflectance calibration approach followed in the PATMOS-x dataset is radiometrically tied to the absolute calibration of the National Aeronautics and Space Administration’s (NASA) Moderate Resolution Imaging Spectroradiometer (MODIS) imager instrument, the present intercalibration scheme yields calibration coefficients consistent with MODIS. Results from this study show that the two independent sets (this study and the ISCCP) of results agree to within their mutual uncertainties. An independent approach to calibration based on multiyear observations over spatially and temporally invariant desert sites has also been used for validation. Results reveal that for most of the geostationary satellites, the mean difference with ISCCP calibration is less than 3% with the random errors under 2%. Another result is that this extends the intercalibrated record to beyond what ISCCP provides (prior to 1983 and beyond 2009).

Sign in / Sign up

Export Citation Format

Share Document