Nicolo E. DiGirolamo

MODIS Snow-Cover Products

Abstract On December 18, 1999, the Terra satellite was launched with a complement of five instruments including the Moderate Resolution Imaging Spectroradiometer (MODIS). Many geophysical products are derived from MODIS data including global snow-cover products. MODIS snow and ice products have been available through the National Snow and Ice Data Center (NSIDC) Distributed Active Archive Center (DAAC) since September 13, 2000. MODIS snow-cover products represent potential improvement to or enhancement of the currently available operational products mainly because the MODIS products are global and 500-m resolution, and have the capability to separate most snow and clouds. The MODIS snow-mapping algorithms are automated, which means that a consistent data set may be generated for long-term climate studies that require snow-cover information. Extensive quality assurance (QA) information is stored with the products. The MODIS snow product suite begins with a 500-m resolution, 2330-km swath snow-cover map, which is then gridded to an integerized sinusoidal grid to produce daily and 8-day composite tile products. The sequence proceeds to a climate-modeling grid (CMG) product at 0.05° resolution, with both daily and 8-day composite products. Each pixel of the daily CMG contains fraction of snow cover from 40% to 100%. Measured errors of commission in the CMG are low, for example, on the continent of Australia in the spring, they vary from 0.02% to 0.10%. Near-term enhancements include daily snow albedo and fractional snow cover. A case study from March 6, 2000, involving MODIS data and field and aircraft measurements, is presented to show some early validation work.

A biophysical process-based estimate of global land surface evaporation using satellite and ancillary data I. Model description and comparison with observations

Abstract A biophysical process-band model is used to estimate transpiration, soil evaporation and interception over the global land surface for a 24-month period (January 1987 to December 1988). The model parameters are determined from published records, and their geographical distribution has been prescribed according to land use and land cover data. Satellite observations are used to obtain fractional vegetation cover, isothermal net and photosynthetically active radiation, air temperature and vapor pressure deficit. Precipitation and friction velocity are derived as blended products (disaggregated and assimilated data). The calculated seasonal and geographical variations of evaporation, net radiation and soil moisture are in good agreement with field observations, catchment water balance data, and atmospheric water budget analysis; explained variances being greater than 75%. Uncertainties in the estimated evaporation are about 15 and 20%, respectively, for annual and monthly values.

A biophysical process-based estimate of global land surface evaporation using satellite and ancillary data II. Regional and global patterns of seasonal and annual variations

A process-based biophysical model of evaporation described previously was run using spatially representative data to calculate global fields of monthly total transpiration, soil evaporation and interception for a period of 24 months (January 1987 to December 1988). Solution of the energy balance equation provided net radiation and sensible heat flux, complementing the evaporative flux. The zonally averaged (area weighted 5° latitude bands) values of annual total evaporation and evaporative fraction (ratio of evaporation and net radiation) are in broad agreement with previous estimates. Transpiration was found to be the dominant component of annual total evaporation in 20 out of the 28 latitude bands. Partitioning of annual total evaporation over the global land area is calculated to be, 52% transpiration, 28% soil evaporation and 20% interception. Seasonal variations of total evaporation and its components are presented for some specific types of vegetation (e.g., tundra, taiga, rainforest, crop land) and compared with field observations.

Greenland ice sheet surface temperature, melt and mass loss : 2000-06

Author Posting.

Intersensor Calibration Between F13 SSMI and F17 SSMIS for Global Sea Ice Data Records

An intercalibration between F13 Special Sensor Microwave Imager (SSMI) and F17 Special Sensor Microwave Imager Sounder (SSMIS) sea ice extents and areas for a full year of overlap is undertaken preparatory to extending the 1979-2007 National Aeronautics and Space Administration (NASA) Goddard Space Flight Center NASA Team algorithm time series of global sea ice extents and areas. The 1979-2007 time series was created from Scanning Multichannel Microwave Radiometer (SMMR) and SSMI data. After intercalibration, the yearly mean F17 and F13 difference in northern hemisphere (NH) sea ice extents is - 0.0156%, with a standard deviation (SD) of the differences of 0.6204%, and the yearly mean difference in NH sea ice areas is 0.5433%, with an SD of 0.3519%. For the southern hemisphere, the yearly mean difference in sea ice extents is 0.0304% ±0.4880%, and the mean difference in sea ice areas is 0.1550% ±0.3753%. This F13/F17 intercalibration enables the extension of the 29-year 1979-2007 SMMR/SSMI sea ice time series for as long as there are stable F17 SSMIS brightness temperatures available.

A Satellite-Derived Climate-Quality Data Record of the Clear-Sky Surface Temperature of the Greenland Ice Sheet

AbstractThe authors have developed a climate-quality data record of the clear-sky surface temperature of the Greenland Ice Sheet using the Moderate-Resolution Imaging Spectroradiometer (MODIS) ice-surface temperature (IST) algorithm. Daily and monthly quality-controlled MODIS ISTs of the Greenland Ice Sheet beginning on 1 March 2000 and continuing through 31 December 2010 are presented at 6.25-km spatial resolution on a polar stereographic grid along with metadata to permit detailed accuracy assessment. The ultimate goal is to develop a climate data record (CDR) that starts in 1981 with the Advanced Very High Resolution Radiometer (AVHRR) Polar Pathfinder (APP) dataset and continues with MODIS data from 2000 to the present, and into the Visible Infrared Imager Radiometer Suite (VIIRS) era (the first VIIRS instrument was launched in October 2011). Differences in the APP and MODIS cloud masks have thus far precluded merging the APP and MODIS IST records, though this will be revisited after the APP dataset h...

Greenland Ice Sheet Melt from MODIS and Associated Atmospheric Variability

Daily June-July melt fraction variations over the Greenland ice sheet (GIS) derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) (2000–2013) are associated with atmospheric blocking forming an omega-shape ridge over the GIS at 500 hPa height. Blocking activity with a range of time scales, from synoptic waves breaking poleward (<5 days) to full-fledged blocks (≥5 days), brings warm subtropical air masses over the GIS controlling daily surface temperatures and melt. The temperature anomaly of these subtropical air mass intrusions is also important for melting. Based on the years with the greatest melt (2002 and 2012) during the MODIS era, the area-average temperature anomaly of 2 standard deviations above the 14 year June-July mean results in a melt fraction of 40% or more. Though the summer of 2007 had the most blocking days, atmospheric temperature anomalies were too small to instigate extreme melting. Key Points Short-term atmospheric blocking over Greenland contributes to melt episodes Associated temperature anomalies are equally important for the melt Duration and strength of blocking events contribute to surface melt intensity

Comparison of Near-Surface Air Temperatures and MODIS Ice-Surface Temperatures at Summit, Greenland (2008–13)

AbstractThe stability of the Moderate Resolution Imaging Spectroradiometer (MODIS) ice-surface temperature (IST) product from Terra was investigated for use as a climate-quality data record. The availability of climate-quality air temperature data TA from a NOAA observatory at Greenland’s Summit Station has enabled this high-temporal-resolution study of MODIS ISTs. During a >5-yr period (July 2008–August 2013), more than 2500 IST values were compared with ±3-min-average TA values from NOAA’s primary 2-m temperature sensor. This enabled an expected small offset between air and ice-sheet surface temperatures (TA > IST) to be investigated over multiple annual cycles. The principal findings of this study show 1) that IST values are slightly colder than the TA values near freezing but that this offset increases as temperature decreases and 2) that there is a pattern in IST–TA differences as the solar zenith angle (SoZA) varies annually. This latter result largely explains the progressive offset from the in sit...

Quantifying the effect of emissivity on the relations between AVHRR split window temperature difference and atmospheric precipitable water over land surfaces

Abstract The effect of emissivity on the relations between the NOAA-9 AVHRR infrared split window temperature difference (Δ T = difference of brightness of temperatures for 10.1–11.5 μm and 11.2–12.6 μm bands) and atmospheric precipitable water (W), namely, ΔT = α + βW and W = α ′ + β ′ ΔT , is quantified in terms of red reflectance (0.55-0.72 μm) observed by the AVHRR. Two years (1987 and 1988) of AVHRR and radiosonde observations at 44 globally distributed land surface locations have been used in the analysis. Predictions of a radiative transfer model are tested using these observations, which indicate possible discrepancies between the predicted and the observed results. Estimates of 10.1–11.5 μm band emissivity have been made by interpreting the intercept of ΔT − W regression according to the theoretical predictions, and these emissivities were found to be linearly related to the red reflectance. Precipitable water estimated from the observed ΔT and red reflectance (by the AVHRR) for the two years at 11 locations over South American and Europe when compared with the observed precipitable water (from radiosonde) gave a mean absolute error of 5 mm and a bias of 4 mm, with the explained variance of 79%. Some inherent uncertainties in the data used in the present analysis have been noted.

A comparison of reflectances and vegetation indices from three methods of compositing the AVHRR‐GAC data over Northern Africa

Abstract Quantitative relationships are derived among visible (0.58–0.68 μm) and near‐infrared (0.73–1.1 μm) reflectances selected according to three monthly compositing methods of the global area coverage (GAC) data of the advanced very high resolution radiometer (AVHRR) and vegetation indices (normalized difference vegetation index, NDVI, and soil adjusted vegetation index, SAVI) calculated from these reflectances. This analysis has been done using the GAC data over northern Africa (7°N‐20°N, 10°W‐10°E) for January and August of 1987. The three methods of compositing used to obtain the monthly values of the reflectances are: (1) maximum difference of near‐infrared and visible channel counts (DVI compositing), (2) maximum normalized difference vegetation index calculated from reflectances (NDVI compositing), and (3) maximum Channel 4 (10.3–11.3 μm) temperature (T4 compositing). The present analysis shows that biophysical results derived from the DVI and NDVI compositing would be more closely related and ...