About

Pavlos Kollias is a SUNY Empire Innovation Professor of Atmospheric Sciences at Stony Brook University, with a joint appointment at the Environmental Science and Technologies Department at Brookhaven National Laboratory since 2016. He is also an Adjunct Professor at McGill University, Canada. With over two decades of experience in atmospheric experimentation, Kollias is internationally recognized as a leading expert in the use of radars for atmospheric research. His work encompasses radar engineering, signal processing, smart sensors, and advanced instrumentation, and he is actively involved in national and international projects focused on developing and applying novel phased array and spaceborne radar systems for weather and climate science. Kollias has authored or co-authored over 230 peer-reviewed publications in fields including millimeter-wavelength radar, radar technology, signal processing, and the dynamics and microphysics of clouds and precipitation. His research contributions are supported by numerous grants, and he has received prestigious awards such as the Humboldt Research Fellowship (2013) and the American Geophysical Union Atmospheric Sciences Ascent Award (2020).

Research topics

• Computer Science
• Environmental science
• Meteorology
• Geography
• Geology
• Remote sensing
• Atmospheric sciences
• Engineering
• Aerospace engineering
• Climatology
• Cartography
• Systems engineering
• Telecommunications
• Oceanography
• Physics

Selected publications

• Rapid SACR Observations of Convection at Bankhead National Forest (RAPID) Field Campaign Report

  2025-11-01

  reportOpen access
  PublisherOA PDFDOI

• A radar view of ice microphysics and turbulence in Arctic cloud systems

  Atmospheric chemistry and physics · 2025-11-24

  articleOpen accessCorresponding

  Abstract. Ice microphysical processes are inherently complex because of their sensitivity to temperature and humidity, the diversity of ice crystal habits, and their interaction with supercooled liquid water (SCL) and turbulence. Long-term surface-based radar observations have been systematically used to unravel the different processes that affect ice particle growth. In this study, we present a statistical analysis of 6.5 years of Ka-band radar observations in Arctic cloud systems, combined with thermodynamic profiles derived from radiosonde measurements. For the first time, ice particle growth and sublimation – diagnosed from vertical gradients of radar reflectivity and mean Doppler velocity – are systematically mapped across a broad range of temperature and moisture conditions. These vertical gradients correspond closely to saturation levels relative to ice and exhibit a strong temperature dependence in supersaturated regions. Notably, distinct signatures near −15 °C are indicative of dendritic growth. Turbulence, quantified via the eddy dissipation rate (EDR), is most frequently observed in regions containing SCL. The co-occurrence of SCL and elevated turbulence results in significantly enhanced ice particle growth compared to conditions in which either is present alone. This work provides new observational constraints that are critical for improving the representation of ice microphysics in atmospheric models.

  PublisherOA PDFDOI

• Characterization of surface clutter signal in the presence of orography for a spaceborne conically scanning W-band Doppler radar

  Atmospheric measurement techniques · 2025-05-28 · 2 citations

  articleOpen accessSenior author

  Abstract. The Earth's surface radar reflection is one of the most important signals received by spaceborne radar systems. It is used in several scientific applications, including geolocation, terrain classification, and path-integrated attenuation estimation. A simulator based on the ray-tracing approach has been developed to reproduce the clutter reflectivity and the Doppler velocity signal for a conically scanning spaceborne Doppler radar system. The simulator exploits topographic information through a raster digital elevation model, land types from a regional classification database, and a normalized radar surface cross-section look-up table. The simulator is applied to the WInd VElocity Radar Nephoscop (WIVERN) mission, which proposes a conically scanning W-band Doppler radar to study in-cloud winds. Using an orbital model, detailed simulations for conical scans over the Piedmont region of Italy, which offers a variety of landscape conditions, are presented. The results highlight the strong departure of the reflectivity and Doppler velocity profiles in the presence of marked orography and the significant gradient in the surface radar backscattering properties. The simulations demonstrate the limitations and advantages of using the surface Doppler velocity over land as an antenna-pointing characterization technique. They represent the full strength range of the surface radar clutter over land surfaces for the WIVERN radar. The surface clutter tool applies to other spaceborne radar missions, such as the nadir-pointing EarthCARE and CloudSat Cloud Profiling Radar (CPR), or the cross-track scanning Global Precipitation Measurement (GPM) precipitation radars.

  PublisherOA PDFDOI

• Characteristics of Ice Nucleating Particles From the Long‐Range Transport of Saharan Dust

  Geophysical Research Letters · 2025-06-08 · 2 citations

  articleOpen access

  Abstract Transported mineral dust in a Saharan air layer (SAL) contains active ice‐nucleating particles (INPs) that may be transported across the Atlantic Ocean and subsequently seed clouds in the Caribbean and the Americas. During an aircraft campaign around Houston and the western U.S. Gulf Coast, a widespread SAL advected into the sampling region allowing for measurement of the ice‐nucleating ability of SD following long‐range transport. Results showed that the mean INP concentrations were 3–4.5 times higher than non‐Saharan dust (nSD), but only at temperatures <−21°C. Active surface site densities were also enhanced in the SD, exceeding the mean for nSD by over an order of magnitude at temperatures <−21°C. These INP measurements confirmed that SD remains an active INP even after >8,000 km westward transport across the Atlantic Ocean.

  PublisherOA PDFDOI

• Studying Aerosol, Clouds, and Air Quality in the Coastal Urban Environment of Southeastern Texas

  Bulletin of the American Meteorological Society · 2025-08-04 · 3 citations

  article

  Abstract A multi-agency succession of field campaigns was conducted in southeastern Texas during July 2021 through October 2022 to study the complex interactions of aerosols, clouds and air pollution in the coastal urban environment. As part of the Tracking Aerosol Convection interactions Experiment (TRACER), the TRACER- Air Quality (TAQ) campaign the Experiment of Sea Breeze Convection, Aerosols, Precipitation and Environment (ESCAPE) and the Convective Cloud Urban Boundary Layer Experiment (CUBE), a combination of ground-based supersites and mobile laboratories, shipborne measurements and aircraft-based instrumentation were deployed. These diverse platforms collected high-resolution data to characterize the aerosol microphysics and chemistry, cloud and precipitation micro- and macro-physical properties, environmental thermodynamics and air quality-relevant constituents that are being used in follow-on analysis and modeling activities. We present the overall deployment setups, a summary of the campaign conditions and a sampling of early research results related to: (a) aerosol precursors in the urban environment, (b) influences of local meteorology on air pollution, (c) detailed observations of the sea breeze circulation, (d) retrieved supersaturation in convective updrafts, (e) characterizing the convective updraft lifecycle, (f) variability in lightning characteristics of convective storms and (g) urban influences on surface energy fluxes. The work concludes with discussion of future research activities highlighted by the TRACER model-intercomparison project to explore the representation of aerosol-convective interactions in high-resolution simulations.

  PublisherDOI

• Convective–Stratiform Identification Neural Network (CONSTRAINN) for the WIVERN Mission

  Remote Sensing · 2025-07-25 · 1 citations

  articleOpen access

  The WIVERN mission promises to deliver the first global observations of the three-dimensional wind field and the associated cloud and precipitation structure in a wide range of atmospheric phenomena, including isolated thunderstorms, tropical cyclones, mid-latitude frontal systems, and polar lows. A critical element in the development of the mission’s wind products is the differentiation between stratiform and convective regions. Convective regions are defined as those where vertical wind velocities exceed 1 m/s. This work introduces CONSTRAINN, a family of U-Net-based neural network models that utilise all of WIVERN observables—including vertical profiles of reflectivity and Doppler velocity, as well as brightness temperatures—to reconstruct convective wind activity within the Earth’s atmosphere. Results show that the retrieved convective/stratiform masks are well reconstructed, with an equitable threat score exceeding 0.6. Ablation experiments further reveal that Doppler velocity signals are the most informative for the reconstruction task.

  PublisherDOI

• A radar view of ice microphysics and turbulence in Arctic stratiform cloud systems

  2025-05-28

  preprintOpen accessCorresponding

  Abstract. Ice microphysical processes are inherently complex because of their sensitivity to temperature and humidity, the diversity of ice crystal habits, and their interaction with supercooled liquid water (SCL) and turbulence. Long-term surface-based radar observations have been systematically used to unravel the different processes that affect ice particle growth. In this study, we present a statistical analysis of 6.5 years of Ka-band radar observations, combined with thermodynamic profiles derived from radiosonde measurements. For the first time, ice particle growth and sublimation—diagnosed from vertical gradients of radar reflectivity and mean Doppler velocity—are systematically mapped across a broad range of temperature and moisture conditions. These vertical gradients correspond closely with saturation levels relative to ice and exhibit a strong temperature dependence in supersaturated regions. Notably, distinct signatures near -15 °C are indicative of dendritic growth. Turbulence, quantified via the eddy dissipation rate (EDR), is most frequently observed in regions containing SCL. When SCL is located near cloud base, it often appears decoupled from high EDR values, suggesting that latent heat release from SCL alone is insufficient to generate strong turbulence. Instead, the presence of turbulence appears to actively support the formation and maintenance of SCL. The co-occurrence of SCL and elevated turbulence results in significantly enhanced ice particle growth compared to conditions in which either is present alone. This work provides new observational constraints that are critical for improving the representation of ice microphysics in atmospheric models.

  PublisherOA PDFDOI

• The Estimation of Path Integrated Attenuation for the EarthCARE Cloud Profiling Radar

  Atmospheric measurement techniques · 2025-08-15

  articleOpen accessSenior authorCorresponding

  Abstract. The joint ESA and JAXA Earth Cloud, Aerosol and Radiation Explorer (EarthCARE) satellite, launched on 28 May 2024, carries the first spaceborne 94 GHz Cloud Profiling Radar (CPR) with Doppler velocity measurement capability. As a successor to the highly successful NASA CloudSat CPR, the EarthCARE CPR offers an additional 7 dB of sensitivity largely due to its larger antenna size (2.5 m vs. 1.8 m) and lower orbit (400 vs. 700 km), and a receiver point target response that significantly improves our ability to detect clouds in the lowest km of the atmosphere. The EarthCARE CPR measurements can also be indirectly used to estimate the Path-Integrated Attenuation (PIA, in dB), a measure of two-way attenuation caused by hydrometeors by quantifying the depression in the measured normalized radar cross section (NRCS) relative to a reference NRCS in the absence of hydrometeors. PIA is a key constraint for improving the accuracy of cloud and precipitation retrievals. This paper presents the PIA estimation methodology currently operationally implemented in the EarthCARE CPR L2A C-PRO data product. The retrieval approach follows a hybrid strategy, where the reference unattenuated NRCS is either estimated using calibration points surrounding the cloudy profile where PIA is estimated or a model-based estimation that uses a geophysical model that calculates NRCS as a function of wind speed and sea surface temperature (SST). The methodology provides a full characterization of the uncertainty in PIA estimates and is expected to lead to improved estimates of PIA compared to the methodology adopted for the CloudSat CPR. This method is particularly useful in PIA estimation in the commissioning phase of the mission, as it is robust for radar miscalibration and bias of gas attenuation or NRCS modeling.

  PublisherOA PDFDOI

• Vertical wind and drop size distribution retrieval with the CloudCube G-band Doppler radar

  Atmospheric measurement techniques · 2025-10-07 · 1 citations

  articleOpen accessSenior author

  Abstract. Macrophysical properties of clouds are influenced by underlying microphysical processes. In practice, there is often an observational gap in bridging the two. For example, our current understanding of aerosol–cloud interaction and cloud–climate feedback is hindered by a lack of robust measurements of the distribution of drop sizes within clouds, especially for the smallest drop sizes. Doppler radar measurements have proven useful in estimating rainfall drop size distributions (DSDs) but face an intermediate challenge of requiring a correction for the presence of vertical air motion. Recent advances in millimeter-wave technology have made radar measurements at increasingly smaller wavelengths possible, allowing for analysis of particle-size-dependent scattering effects to derive estimates of vertical winds and thereby DSDs. This work demonstrates a method of deriving range-resolved DSDs using Doppler spectra at 238 GHz measured by the CloudCube ground-based G-band atmospheric Doppler radar. The observations utilized are of marine boundary layer clouds during March and April 2023 in La Jolla, CA, USA, taken as part of CloudCube's participation in the Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE) campaign. This method first identifies notches in the velocity spectra and compares them to the theoretical notch velocities predicted by size-dependent backscattering and terminal velocity models to estimate the range-dependent vertical wind. After removing the vertical wind, binned DSDs are retrieved from the zero-wind spectrum. Bulk properties of the precipitation are then derived, including the number concentration, liquid water content, characteristic drop size, and precipitation rate. For the case study presented here, calculated bulk properties are found to be relatively invariant to the forward-model assumptions made in the estimation of the full DSD retrieval. Validation of this method on larger volumes of data would make such retrievals useful tools in assessing physical models of drizzle.

  PublisherOA PDFDOI

• Evaluation of the EarthCARE Cloud Profiling Radar (CPR) Doppler velocity measurements using surface-based observations

  2025-06-18

  preprintOpen access

  Abstract. The Earth Cloud, Aerosol and Radiation Explorer (EarthCARE) mission was launched on May 28, 2024. One of the most exciting new measurement capabilities of the EarthCARE mission is the CPR Doppler velocity measurement. The availability of Doppler measurements from space will offer a unique opportunity for the collection of a global dataset of vertical motions in clouds and precipitation. An important step in realizing this opportunity is to evaluate the CPR Doppler velocity measurements against those collected by surface-based observatories. Validation with two high-latitude surface-based Doppler radar observatories demonstrates that the CPR Level-2 Doppler velocities exhibit minimal biases (within a few cm/s), especially in ice clouds. Even in low-level mixed-phase clouds, the CPR’s Doppler velocity measurements provide reliable values, although careful consideration is needed for specific limitations such as vertical smoothing effects due to the radar’s pulse length. Despite the inherent challenges associated with space-based Doppler measurements, these results suggest strong potential for the EarthCARE mission to provide unprecedented global climatological insights into hydrometeor sedimentation velocities.

  PublisherDOI

Recent grants

• Collaborative Research: Studies of the Microphysical Processes in Ice and Mixed-Phase Clouds and Precipitation Using Multiparameter Radar Observations Combined with Cloud Modeling

  NSF · $330k · 2019–2024

• CIF: Millimeter-wavelength Radar Facility for Cloud and Precipitation Research

  NSF · $335k · 2021–2025

• Collaborative Research: Experiment of Sea Breeze Convection, Aerosols, Precipitation and Environment (ESCAPE)

  NSF · $1.3M · 2021–2025

Frequent coauthors

• Mariko Oue

  Stony Brook University

  315 shared

• Edward Luke

  Brookhaven National Laboratory

  220 shared

• Ann M. Fridlind

  Goddard Institute for Space Studies

  213 shared

• Maximilian Maahn

  Leipzig University

  210 shared

• Greg M. McFarquhar

  163 shared

• Virendra P. Ghate

  Argonne National Laboratory

  162 shared

• Susanne Crewell

  University of Cologne

  162 shared

• Katia Lamer

  Brookhaven National Laboratory

  161 shared

Education

• Ph.D.

  Stony Brook University

Awards & honors

• Humboldt Research Fellowship (2013)
• American Geophysical Union (AGU) Atmospheric Sciences Ascent…