I work primarily with observations (i.e. data). I am interested in the large-scale monitoring of the Earth’s surface and climate. My past and current work include the mapping and change detection of Earth’s topography, bathymetry and gravity field, as observed by radars, lidars, imagery, sonars and gravimeters, among others. I develop algorithms for remote-sensing applications and use high-performance computing (clusters) to process large-scale satellite measurements. I am a strong advocate of open source and open data!
Time-varying melt rates from Antarctica
A Greatly Improved 25-year Record of Ice Shelf Elevation at High Temporal and Spatial Resolution
Constructing ice-shelf melt-rate time series (meltwater production) at unprecedented spatiotemporal resolution. Satellites: ERS-1 + ERS-2 + Envisat + CryoSat-2 + ICESat + ICESat-2. Time span: 1992-present (27+ years). Temporal resolution: 3 months. Spatial resolution: 3-5 km. Grid posting: 1 km. Authors: Paolo, Nilsson, Gardner (JPL).
Ice-sheet mass change
Integration of nearly 30 years of disparate satellite altimetry observations of the Antarctic ice sheet, 1985-present
State-of-the-art surface elevation-change time series for the majority of the Antarctic Ice Sheet since 1985 to present, estimated from six satellite missions (Geosat, ERS-1, ERS-2, Envisat, ICESat and CryoSat-2). This allows us to study decadal and multi-decadal trends as well as short-term variability at fine spatial resolution; providing an invaluable dataset for advancing ice-sheet data assimilation efforts into climate models and for disentangling the causal mechanisms responsible for ice-sheet mass change.
NASA MEaSUREs Inter-mission Time Series of Land Ice Velocity and Elevation (ITS_LIVE)
We will accelerate ice sheet and glacier change research by producing a globally-comprehensive and temporally dense multi-sensor record of land ice and ice shelf velocity and elevation, updated in near-real time as new data become available. Such a record is not presently available to the community, slowing scientific discovery from these information-rich data streams. Authors: PI: Gardner (JPL), Co-I’s: Agram, Hua, Linick, Nilsson, Paolo, Walker (JPL), Scambos (U.Colorado), Fahnestock, Meyer (U.Alaska). Budget: $4.2M, 2018-2023.
JPL Cryosphere Altimetry Processing Toolkit (a Python Library)
Set of Python tools for processing and integrating multi-satellite and airborne altimetry data. Authors: F.S. Paolo (Lead developer), J. Nilsson (Core developer), A. Gardner (Project PI).
NASA’s Ice, Cloud and Elevation Satellite 2.
The ICESat-2 will measure the height of a changing Earth, one laser pulse at a time, 10,000 laser pulses a second. Launched September 15, 2018, ICESat-2 carries a photon-counting laser altimeter that will allow scientists to measure the elevation of ice sheets, glaciers, sea ice and more - all in unprecedented detail.
Our planet’s frozen and icy areas, called the cryosphere, are a key focus of NASA’s Earth science research. ICESat-2 will help scientists investigate why, and how much, our cryosphere is changing in a warming climate. The satellite will also measure heights across Earth’s temperate and tropical regions, and take stock of the vegetation in forests worldwide.
Estimating the Circulation and Climate of the Ocean (ECCO)
The ECCO consortium is directed at making the best possible estimates of ocean circulation and its role in climate. Solutions are obtained by combining state-of-the-art ocean circulation models with nearly complete global ocean data sets in a physically and statistically consistent manner. Products are being utilized to understanding ocean variability, biological cycles, coastal physics, and geodesy, and are available for general applications.
Climate Variability and Ice-shelf Change
Investigating how the Antarctic ice shelves respond to climate variability such as El Niño/Southern Oscillation.
Figure: Relative influence of ENSO along the Antarctic Pacific margin. (a) Regional variation of the similarity index (size and color of squares) between ice-shelf height-anomaly records and the time-integrated Oceanic Niño Index (ONI). (b) 12-month running integral of ONI (that is, ENSO) lagged by ~6 months (top plot) and 12-month running means of ice-shelf height anomalies for the combined Amundsen (AMU) ice shelves and six individual ice shelves; the shaded area highlights the large height change resulting from the 1997–2001 El Niño-to-La Niña transition.
Check out our paper in Nature Geoscience
ICESat(-1) and CryoSat-2 studies
Multi-sensor analyses of Antarctic ice shelf response to climate variability
Developing a detailed history of Antarctic ice-shelf mass and stress changes on seasonal-to-interannual time scales and small spatial scales; improve our understanding of the environmental processes that cause these changes; and assess whether proxies for variability of the ice-shelf mass budget can be obtained from coarse-grid global climate models (GCMs). Our main data sources for this study are: ICESat laser altimeter data (2003-2009); Operation IceBridge (OIB) airborne laser altimeter and radio echo sounding (RES) ice thickness data (2009-present); CryoSat-2 radar altimeter (RA) data (2010-present); and European Space Agency (ESA) RA satellites ERS-1, ERS-2 and Envisat (1992-2012). Authors: PI: Padman (ESR), Co-I: Fricker (Scripps). Budget: $637k, 2013–2016; $385k, 2017–2019.
Multi-satellite Data Fusion
Constructing long-term continous time series of ice-shelf height change from multiple satellite altimeters.
Figure: Representation of our multi-referenced time series approach. (Left) individual time series of cumulative change. (Right) diagram representing the matrix formed with the time series on the left (one time series per row). From top to bottom is depicted the process of forming single-grid-cell frequency-average time series.
Check out our paper in Remote Sensing of Environment
Geophysical Data Analysis
Large-scale processing, statistical modeling and time series analysis applied to Earth observations.
Figure: Modes of oscillation in the ice-shelf height time series. (left) The empirical orthogonal functions paired as EOFs 1–2, 3–4 (interannual components) and 5–6 (annual component). Note the phase quadrature (∼π/2 shift) between pairs. (right) The reconstruction of each pair of modes in the time domain. This is equivalent to filtering the original time series (in gray) with respect to particular frequencies.
Check out my PhD Dissertation
Ice-shelf thickness change from Satellite Altimetry
Multi-mission satellite altimetry to investigate long-term trends and variability in Antarctic ice-shelf thickness.
Figure: Eighteen years of changes in the Antarctic ice shelves. Color map is rate of thickness change, circles are percentage thickness gained or lost, time series are mean ice-volume change over 18 years. There is considerable variability in the height-change signal, and trends on short time intervals are not representative of the underlying decadal trends.
Check out our paper in Science
Marine Gravity Field from Satellite Altimetry
Satellite altimeter-derived sea surface gradient and shipborne gravity for an integrated marine gravity field.
Figure: Integrated gravity models constructed using sea surface gradients (slopes), derived from satellite altimetry (Geosat and ERS-1), and marine gravity data (ships) along the Brazilian coast: (left) free-air gravity anomaly and (right) geoid height. Unlike spectral methods (deterministic approach), the least squares collocation (stochastic approach) presented a low content of high-frequency noise in the predicted gravity anomalies.
Check out our paper in Journal of Geodynamics