Guangdong Key Laboratory for Urbanization and Geo-simulation Sun Yat-sen University, Guangzhou, China. University of California, Irvine, USA

Similar documents
Constraining MODIS snow albedo at large solar zenith angles: Implications for the surface energy budget in Greenland

JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 110, D01104, doi: /2004jd005190, 2005

THE LAND-SAF SURFACE ALBEDO AND DOWNWELLING SHORTWAVE RADIATION FLUX PRODUCTS

The LSA-SAF Albedo products

SUPPLEMENTARY INFORMATION

Algorithm for MERIS land surface BRDF/albedo retrieval and its validation using contemporaneous EO data products

Characterization of Canadian High Arctic glacier surface albedo

ISO MODIS NDVI Weekly Composites for Canada South of 60 N Data Product Specification

Continuous Quality Monitoring of Copernicus Global Land Albedo products based on SPOT/VGT observations

HIGH TEMPORAL AND SPATIAL RESOLUTION AIR TEMPERATURE RETRIEVAL FROM SEVIRI AND MODIS COMBINED DATA

Using VIIRS Land Surface Temperature to Evaluate NCEP North American Mesoscale Model (NAM) Forecast

Developing a spatially continuous 1 km surface albedo data set over North America from Terra MODIS products

Documentation for the Global Urban Heat Island (UHI) Data Set, 2013

A new perspective on aerosol direct radiative effects in South Atlantic and Southern Africa

Evaluation of the MODIS (MOD10A1) daily snow albedo product over the Greenland ice sheet

Evaluation of Moderate Resolution Imaging Spectroradiometer land surface visible and shortwave albedo products at FLUXNET sites

Software requirements * : Part III: 2 hrs.

A COMPARISON OF TOTAL SHORTWAVE SURFACE ALBEDO RETRIEVALS FROM MODIS AND TM DATA

VALIDATION OF DUAL-MODE METOP AMVS

RESEARCH METHODOLOGY

Climate Roles of Land Surface

Using MODIS BRDF/Albedo Data to Evaluate and Improve Land Surface Albedo in Weather and Climate Models

ERBE Geographic Scene and Monthly Snow Data

The global MODIS burned area product

Evaluation of MODIS, VIIRS and Landsat albedos at BSRN sites: Development of CEOS/WGCV/LPV albedo ECV protocols

POLAR-ORBITING wide-field-of-view sensors provide

Global-Scale Comparison of MISR and MODIS Land Surface Albedos

MERIS, A-MODIS, SeaWiFS, AATSR and PARASOL over the Salar de Uyuni March 2006 MAVT 2006 Marc Bouvet, ESA/ESTEC

AATSR atmospheric correction

The use of spatial-temporal analysis for noise reduction in MODIS NDVI time series data

Yan Chen, Sunny Sun-Mack, and Robert F. Arduini Science Application International Corporation, Hampton, VA USA 23666

and Engineering Laboratory Cold Regions Research Changes in the Albedo of the Pegasus and Phoenix Runways, ERDC/CRREL TR-17-10

Investigations into the Spatial Pattern of Annual and Interannual Snow Coverage of Brøgger Peninsula, Svalbard,

and Atmospheric Science, University of Miami, 4600 Rickenbacker Causeway, Miami, FL 33149, USA.

Evaluation of a MODIS Triangle-based Algorithm for Improving ET Estimates in the Northern Sierra Nevada Mountain Range

NSIDC Metrics Report. Lisa Booker February 9, 2012

The University of Texas at Austin, Jackson School of Geosciences, Austin, Texas 2. The National Center for Atmospheric Research, Boulder, Colorado 3

8.2 GLOBALLY DESCRIBING THE CURRENT DAY LAND SURFACE AND HISTORICAL LAND COVER CHANGE IN CCSM 3.0 USING AVHRR AND MODIS DATA AT FINE SCALES

Agriculture Development-induced Surface Albedo Changes and Climatic Implications Across Northeastern China

Application and impacts of the GlobeLand30 land cover dataset on the Beijing Climate Center Climate Model

VIIRS Radiometric Calibration for Reflective Solar Bands: Antarctic Dome C Site and Simultaneous Nadir Overpass Observations

Comparison of seasonal and spatial variations of albedos from Moderate-Resolution Imaging Spectroradiometer (MODIS) and Common Land Model

Comparison of MSG-SEVIRI and SPOT-VEGETATION data for vegetation monitoring over Africa

P1.30 THE ANNUAL CYCLE OF EARTH RADIATION BUDGET FROM CLOUDS AND THE EARTH S RADIANT ENERGY SYSTEM (CERES) DATA

Derivation of Ice Thickness and Age for Use with GOES-R ABI Data

Lake parameters climatology for cold start runs (lake initialization) in the ECMWF forecast system

The Climatology of Clouds using surface observations. S.G. Warren and C.J. Hahn Encyclopedia of Atmospheric Sciences.

Using MODIS BRDF and Albedo Data to Evaluate Global Model Land Surface Albedo

Observing land from space: Interacting with land data from NASA s LP DAAC

A direct method for estimating net surface shortwave radiation from MODIS data

Studying snow cover in European Russia with the use of remote sensing methods

MODIS-derived Snow Metrics Algorithm

IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, VOL. 7, NO. 12, DECEMBER

Surface Radiation Budget from ARM Satellite Retrievals

MSI aerosol retrieval algorithm for the Multi- Spectral Imager (MSI) on EarthCare

VALIDATION OF MSG DERIVED SURFACE INCOMING GLOBAL SHORT-WAVE RADIATION PRODUCTS OVER BELGIUM

Validation of Moderate Resolution Imaging Spectroradiometer (MODIS) albedo retrieval algorithm: Dependence of albedo on solar zenith angle

Solar Insolation and Earth Radiation Budget Measurements

Actual and insolation-weighted Northern Hemisphere snow cover and sea-ice between

The relationship analysis of vegetation cover, rainfall and land surface temperature based on remote sensing in Tibet, China

An initial assessment of Suomi NPP VIIRS vegetation index EDR

Areal-Averaged Spectral Surface Albedo from Ground-Based Transmission Data Alone: Toward an Operational Retrieval

NESDIS Global Automated Satellite Snow Product: Current Status and Recent Results Peter Romanov

imagery For Cyclone Bob

Status of Land Surface Temperature Product Development for JPSS Mission

LAND SURFACE ALBEDO AND DOWNWELLING SHORTWAVE RADIATION FROM MSG GEOSTATIONARY SATELLITE (METHOD FOR RETRIEVAL, VALIDATION, AND APPLICATION)

Creating a cloud-free MODIS snow cover product using spatial and temporal interpolation and temperature thresholds

The MODIS Cloud Data Record

Gio Global Land Component - Lot I Operation of the Global Land Component

Land surface albedo from MSG/SEVIRI: retrieval method, validation, and application for weather forecast

A AVHRR NDVI dataset for Svalbard. Stian Solbø, Inge Lauknes, Cecilie Sneberg Grøtteland, Stine Skrunes, Hannah Vickers, Kjell Arild Høgda

Supporting Information for

Article Measuring Landscape Albedo Using Unmanned Aerial Vehicles

Shortwave versus longwave direct radiative forcing by Taklimakan dust aerosols

RETRIEVAL OF AEROSOL OPTICAL DEPTH OVER URBAN AREAS USING TERRA/MODIS DATA

VIIRS narrowband to broadband land surface albedo conversion: formula and validation

Mean monthly radiation surfaces for Australia at 1 arc-second resolution

A Facility for Producing Consistent Remotely Sensed Biophysical Data Products of Australia

Statistics Research in Remote Sensing Data Analysis for Climate Science at the Jet Propulsion Laboratory

Feature-tracked 3D Winds from Satellite Sounders: Derivation and Impact in Global Models

GLOBAL LAND DATA ASSIMILATION SYSTEM (GLDAS) PRODUCTS FROM NASA HYDROLOGY DATA AND INFORMATION SERVICES CENTER (HDISC) INTRODUCTION

P1.6 DIURNAL CYCLES OF THE SURFACE RADIATION BUDGET DATA SET

WATER VAPOUR RETRIEVAL FROM GOME DATA INCLUDING CLOUDY SCENES

An algorithm for estimating downward shortwave radiation from GMS 5 visible imagery and its evaluation over China

NESDIS Global Automated Satellite Snow Product: Current Status and Planned Upgrades Peter Romanov

Satellite Land Surface Temperature production at STAR

Report Benefits and Challenges of Geostationary Ocean Colour Remote Sensing - Science and Applications. Antonio Mannino & Maria Tzortziou

SATELLITE OBSERVATIONS OF CLOUD RADIATIVE FORCING FOR THE AFRICAN TROPICAL CONVECTIVE REGION

Permanent Ice and Snow

Assimilation of Snow and Ice Data (Incomplete list)

Geog183: Cartographic Design and Geovisualization Spring Quarter 2018 Lecture 11: Dasymetric and isarithmic mapping

MODIS Snow Products Collection 6 User Guide. George A. Riggs Dorothy K. Hall

Current Status of the Stratospheric Ozone Layer From: UNEP Environmental Effects of Ozone Depletion and Its Interaction with Climate Change

VALIDATION OF ENVISAT PRODUCTS USING POAM III O 3, NO 2, H 2 O AND O 2 PROFILES

Defining microclimates on Long Island using interannual surface temperature records from satellite imagery

Software requirements * : Part III: 2 hrs.

Energy and the Earth AOSC 200 Tim Canty

Comparison of Results Between the Miniature FASat-Bravo Ozone Mapping Detector (OMAD) and NASA s Total Ozone Mapping Spectrometer (TOMS)

Statistical comparison of MISR, ETMz and MODIS land surface reflectance and albedo products of the BARC land validation core site, USA

Surface UV Irradiance from OMI on EOS Aura. Atmospheric Science Conference ESRIN, 8-12 May 2006 Aapo Tanskanen

Transcription:

Auxiliary Material Submission for Paper: Reply to Schaaf, Wang and Strahler: Commentary on Wang and Zender MODIS snow albedo bias at high solar zenith angles relative to theory and to in situ observations in Greenland Introduction: 1,2 Xianwei Wang and 2 Charles S. Zender 1 School of Geography and Planning Guangdong Key Laboratory for Urbanization and Geo-simulation Sun Yat-sen University, Guangzhou, China 2 Department of Earth System Science University of California, Irvine, USA We have analyzed the 500m MODIS albedo product (MCD43A3) and its quality flag (MCD43A2), and the 0.05 product (MCD43C3) in 2005 for examples. These data have been downloaded from the NASA's Land Processes Distributed Active Archive Center (LP DAAC) at: https://wist.echo.nasa.gov/wist-bin/api/ims.cgi. Four MCD43A product tiles (h15v02, h16v02, h16v01, h17v01) have been downloaded to cover the entire Greenland. The MODIS Reprojection Tool (MRT) is used to mosaic the four tiles into one image, and then to resample the sinusoidal to Geographic coordinate, and to spatially subset to cover the almost entire Greenland, 60 N-80 N and 60 W-20 W. The 500 m BRDF albedo quality flag (BRDF_Albedo_Quality) in MCD43A2 only has two valid values, Q=0 processed, good quality (or full BRDF inversions), and Q=1 processed, magnitude BRDF inversions. There is no data labeled as Q=2, and 3, except for Q= 4, the fill value for the 500 m product. The quality flag for the aggregated 0.05 product in MCD43C3 has five values. Q=0 best quality, 75% or more with best full inversions; Q=1 good quality, 75% or more with full inversions; Q= 2 mixed, 75% or less full inversions and 25% or less fill values; Q=3 all magnitude inversions or 50% or less fill values; Q=4, over 50% fill value. We use these quality flag values to separate the MODIS shortwave broadband snow albedo into different classes. All statistic analysis is constrained by these quality flags. The results are plotted in the following 10 figures. S.Figure 1 compares the snow albedo values from the 500 m product (MCD43A3) and from the 0.05 product (MCD43C3) within one 0.05 grid at Summit in Greenland. There are 16 MCD43A3 500m grids within one 0.05 grid at Summit. Snow albedo values from the 500 m and the 0.05 data are virtually identical, and both decrease with solar zenith angle (SZA) increase when SZA is larger than ~55. This indicates that spatial representative from the 500 m and the 0.05 data and from the BSW and WSA is near identical. S.Figures 2 and 3 display the mean MODIS snow albedo from the 0.05 product (MCD43C3) and 500 m product (MCD43A3) respectively for each retrieval quality categories within each solar zenith angle (SZA) in the central Greenland from 60 N to 80 N and from 40 W to 50 W on days 41-297 in 2005. Only pixels whose albedo value is larger than 0.5 and snow cover fraction (SCF) is 100% (for snow) are counted. According to the 0.05 product (MCD43C3) in 1

S.Figure 2, it clearly shows that the reduced albedo trend at high SZA is much less pronounced for Q=0 data than for Q>0 data; for Q=0 the decline trend only appears for SZA > ~70, whereas for Q>0 the trend appears "earlier", i.e., albedos begin decreasing after SZA >~60. The White Sky Albedo (WSA) decreases more quickly with SZA (for large SZA) than does the Black Sky Albedo (BSA). What is the sensitivity of our results from the 0.05 product (MCD43C3) to the resolution and quality of the input data used, i.e., the 500 m product (MCD43A3)? According to S.Figure 3, the retrieved albedo from the 500 m product decreases with SZA for SZA > ~60. This is the same qualitative behavior seen in the 0.05 data in S.Figure 2. Quantitatively, the 500 m albedo has a similar pattern with that of the 0.05 product and decreases faster with SZA than the 0.05 data. Second, the retrieved 500m albedo shows only a small difference with quality levels (Q=0, 1, or all) for different SZAs. S.Figure 4 shows pixel ratio (pixel ratio = pixel_count_qx/pixel_count_all_q, x=0,1,2,3,4) of the 0.05 product (MCD43C3) and 500 m product (MCD43A3) for each retrieval quality flag within each solar zenith angle (SZA) in the central Greenland from 60 N to 80 N and from 40 W to 50 W on days 41-297 in 2005. Only pixels whose albedo value is larger than 0.5 and snow cover fraction (SCF) is 100% are counted. The pixel ratio (pixel count for Q=0 divided by the total pixels for all Q levels) for high quality flag values (Q=0) at large SZAs (65-80 ) from 500 m data demonstrate a increase trend while it is a decrease trend in the 0.05 data. The highquality retrieval (Q=0) snow albedo data are ~35% of all retrievals in a year in Greenland and have very sparse coverage of northern Greenland. S.Figures 5-8 shows the zonal mean white-sky and black-sky shortwave snow albedo for the high-quality retrievals of Q=0 and low-quality retrievals of Q>0 from the 0.05 product (MCD43C3) and 500 m product (MCD43A3) respectively within each latitude zone (e.g., N62 to N77 ) from 50 W to 40 W in central Greenland. These figures are complementary to Figure 8 in Wang and Zender (2010a), which does not separate the high-quality retrievals from the lowquality retrievals that have been complained by Schaaf et al. (2011). These figures verify that the decrease trend of MODIS snow albedo with SZAs is dominated by the low-quality retrievals when SZAs are larger than ~55 and by all-quality retrievals when SZAs are larger than ~70. The results from 500m MODIS snow albedo data (MCD43A3) confirms the results derived from the 0.05 product (MCD43C3). S.Figures 9 and 10 shows examples of the spatial distributions of the high/low-quality retrievals and corresponding snow albedo values from the 0.05 product (MCD43C3) and 500 m product (MCD43A3) on day 73, 2005 in Greenland, respectively. The SZA at 65 N and 75 N are near 65 and 75 on day 73, respectively. These figures illustrate that the high-quality retrievals concentrates in the southern Greenland, while low-quality retrievals are in the northern Greenland. The low-quality retrievals display unrealistic snow albedo values and dominate significant fractions of Greenland. The dearth of the high-quality retrievals requires the community to use the low-quality retrieval data in order to obtain a full spatial and temporal coverage (Oleson et al., 2003; Zhou et al., 2003; Wang et al., 2004), but such low-quality retrieval data can not be directly used unless similar adjustments as suggested by Wang and Zender (2010b) are implemented. 2

S.Figure 1. Comparison of MCD43A3 (500m) and MCD43C3 (0.05 ) albedo values within one 0.05 grid at Summit in Greenland. There are 16 MCD43A3 500m grids within one 0.05 grid at Summit. 3

S.Figure 2. Mean MODIS snow albedo (MCD43C3, A for White-sky albedo, B for Black-sky albedo) for each retrieval quality categories within each solar zenith angle (SZA) in the central Greenland from 60 N to 80 N and from 40 W to 50 W on days 41-297 in 2005. Only pixels whose albedo value is larger than 0.5 and snow cover fraction (SCF) is 100% (for snow) are counted. 4

S.Figure 3. Mean MODIS snow albedo (MCD43A3, A for White-sky albedo, B for Black-sky albedo) for each retrieval quality categories within each solar zenith angle (SZA) in the central Greenland from 60 N to 80 N and from 40 W to 50 W on days 41-297 in 2005. 5

S.Figure 4. MODIS albedo (A. MCD43C3 (0.05 ), B. MCD43A3 (500m) pixel ratio (pixel ratio = pixel_count_qx/pixel_count_all_q, x=0,1,2,3,4) for each retrieval quality flag within each solar zenith angle (SZA) in the central Greenland from 60 N to 80 N and from 40 W to 50 W on days 41-297 in 2005. Only pixels whose albedo value is larger than 0.5 and snow cover fraction (SCF) is 100% are counted. 6

S.Figure 5. Zonal mean MCD43C3 (0.05 ) white-sky shortwave snow albedo within each latitude zone (e.g., N62 to N77 ) from 50 W to 40 W in central Greenland. A is for the best retrieval that Q=0, and B is for Q=1, 2, 3 and 4 for magnitude inversions. F 7

S.Figure 6. Zonal mean MCD43C3 (0.05 ) black-sky shortwave snow albedo within each latitude zone (e.g., N62 to N77 ) from 50 W to 40 W in central Greenland. A is for the best retrieval that Q=0, and B is for Q=1, 2, 3 and 4 for magnitude inversions. 8

S.Figure 7. Zonal mean MCD43A3 (500 m) white-sky shortwave snow albedo within each latitude zone (e.g., N62 to N77 ) from 50 W to 40 W in central Greenland. A is for the best retrieval that Q=0, and B is for Q=1 for magnitude inversions. 9

S.Figure 8. Zonal mean MCD43A3 (500 m) black-sky shortwave snow albedo within each latitude zone (e.g., N62 to N77 ) from 50 W to 40 W in central Greenland. A is for the best retrieval that Q=0, and B is for Q=1 for magnitude inversions. 10

S.Figure 9. MCD43C3 (0.05 ) black-sky (left) and white-sky (right) albedo map for those quality flags of Q=0 (top) and for all Q retrievals (bottom) Greenland on day 73, 2005. The SZA at 65 N and 75 N are near 65 and 75 on day 73, respectively. 11

S.Figure 10. MCD43A3 (500m) black-sky (left) and white-sky (right) albedo map for those quality flags of Q=0 (top) and for all Q retrievals (bottom) Greenland on day 73, 2005. The SZA at 65 N and 75 N are near 65 and 75 on day 73, respectively. 12