Stephen W. Nesbitt’s research while affiliated with University of Illinois Urbana-Champaign and other places

This research attempts to use operational radar and satellite products to identify potential locations of quasi-linear convective system (QLCS) tornadogenesis, which can be difficult to predict. It is hypothesized that deep, discrete updrafts indicate portions of the QLCS capable of producing tornadoes, whereas shallower convection indicates more benign portions of the QLCS. To address this hypothesis, storm reports and storm surveys on 30-31 March 2022, during the second Intensive Observing Period of the 2022 Propagation, Evolution, and Rotation in Linear Storms (PERiLS) field campaign are used to identify locations of tornadoes within the QLCS. These tornado locations are then compared to representations of upper-tropospheric updrafts, namely overshooting tops (OTs), which are identified with an algorithm using 1-minute resolution mesoscale sector data from GOES-16 Advanced Baseline Imager infrared brightness temperatures, and radar reflectivity cores aloft, identified with multi-radar multi-sensor (MRMS) 3D mosaic reflectivity products. Only a fraction (less than 30%) of tornadoes within the QLCS are associated with OTs, though over 85% of tornadoes are located near convective cores as indicated by cores of enhanced reflectivity at 9 km MSL. A numerical simulation of the event is also conducted using the Weather Research and Forecasting model (WRF) which shows a strong relationship between simulated updraft intensity and reflectivity aloft. Given this apparent support of the hypothesis, the identification of updraft signatures within MRMS and high-resolution geostationary satellite data may ultimately help improve the identification of regions within QLCSs most likely to result in tornadoes.

Quasi-linear convective systems (QLCSs) are responsible for approximately a quarter of all tornado events in the U.S., but no field campaigns have focused specifically on collecting data to understand QLCS tornadogenesis. The Propagation, Evolution, and Rotation in Linear System (PERiLS) project was the first observational study of tornadoes associated with QLCSs ever undertaken. Participants were drawn from more than 10 universities, laboratories, and institutes, with over 100 students participating in field activities. The PERiLS field phases spanned two years, late winters and early springs of 2022 and 2023, to increase the probability of intercepting significant tornadic QLCS events in a range of large-scale and local environments. The field phases of PERiLS collected data in nine tornadic and nontornadic QLCSs with unprecedented detail and diversity of measurements. The design and execution of the PERiLS field phase and preliminary data and ongoing analyses are shown.

Microphysical observations of precipitating particles are critical data sources for numerical weather prediction models and remote sensing retrieval algorithms. However, obtaining coherent data sets of particle microphysics is challenging as they are often unindexed, distributed across disparate institutions, and have not undergone a uniform quality control process. This work introduces a unified, comprehensive Northern Hemisphere particle microphysical data set from the National Aeronautics and Space Administration precipitation imaging package (PIP), accessible in a standardized data format and stored in a centralized, public repository. Data is collected from 10 measurement sites spanning 34° latitude (37°N–71°N) over 10 years (2014–2023), which comprise a set of 1,070,000 precipitating minutes. The provided data set includes measurements of a suite of microphysical attributes for both rain and snow, including distributions of particle size, vertical velocity, and effective density, along with higher‐order products including an approximation of volume‐weighted equivalent particle densities, liquid equivalent snowfall, and rainfall rate estimates. The data underwent a rigorous standardization and quality assurance process to filter out erroneous observations to produce a self‐describing, scalable, and achievable data set. Case study analyses demonstrate the capabilities of the data set in identifying physical processes like precipitation phase‐changes at high temporal resolution. Bulk precipitation characteristics from a multi‐site intercomparison also highlight distinct microphysical properties unique to each location. This curated PIP data set is a robust database of high‐quality particle microphysical observations for constraining future precipitation retrieval algorithms, and offers new insights toward better understanding regional and seasonal differences in bulk precipitation characteristics.

The poor representation of the macrophysical properties of shallow oceanic cumuli in climate models contributes to the large uncertainty in cloud feedback. These properties are also difficult to measure because it requires high-resolution satellite imagery that is seldomly collected over ocean. Here, we examine cumulus cloud macrophysical properties, their size, shape, and spatial distributions, over the tropical western Pacific using 170 15 m resolution scenes from Terra's Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) collected during the 2019 Cloud, Aerosol and Monsoon Processes Philippines Experiment (CAMP2Ex) mission. The average cloud fraction (CF) was 0.12, half of which was contributed by clouds less than 1.6 km in area-equivalent diameter. This compared well to Terra's Multi-angle Imaging SpectroRadiometer (MISR) resolution-corrected CF of 0.14 but less than the 0.19 measured by Terra's Moderate Resolution Imaging Spectroradiometer (MODIS). The cloud size distribution exhibited a power law form with an exponent of 2.93 and an area–perimeter power law with a dimension of 1.25. ASTER, MISR, and CAMP2Ex aircraft lidar showed excellent agreement in the cloud top height (CTH) distribution peak altitude of ∼ 750 m. We examined cumulus properties in relation to meteorological variables and found that the variation in mean CTH is controlled most by the total column water vapor, lower-tropospheric stability (LTS), and estimated inversion strength (EIS). The variation in CF is most controlled by surface wind speed and near-cloud relative humidity instead of LTS/EIS, suggesting the need to improve low-cloud parameterizations in climate models that use LTS/EIS based on stratocumulus studies.

Overshooting tops (OTs) are manifestations of deep convective updrafts that extend above the tropopause into the stratosphere. They can induce dynamic perturbations and result in irreversible transport of aerosols, water vapor and other mass from the troposphere into the stratosphere, thereby impacting the chemical composition and radiative processes of the stratosphere. These and other effects of OTs depend on their characteristics such as depth and area, which are understood to connect to mid‐tropospheric updraft speed and width, respectively. Less understood is how static stability in the lower stratosphere (LS) potentially modulates these OT–updraft connections, thus motivating the current study. Here, LS static stability and observed OT characteristics are quantified and compared using a combination of reanalysis data, observed rawinsonde data and geostationary satellite data. A weak to moderate relationship between OT depth and LS lapse rate and Brunt‐Väisälä frequency (N²) (R = 0.38, −0.37, respectively) is found, implying that OT depth is reduced with an increasingly stable LS. In contrast, a weak relationship (R = −0.03, 0.03, respectively) is found between OT area and LS static stability, implying that OT area is controlled primarily by mid to upper tropospheric updraft area. OT duration has a weak relationship to LS lapse rate and N² (R = 0.02, −0.02, respectively). These relationships may be useful in interpreting mid‐ and low‐level storm dynamics from satellite‐observed characteristics of OTs in near real‐time.

The poor representation of the macrophysical properties of shallow oceanic cumuli in climate models contributes to the large uncertainty in cloud feedback. These properties are also difficult to measure because it requires high-resolution satellite imagery that are seldomly collected over ocean. Here, we examine cumulus cloud macrophysical properties, their size, shape, and spatial distributions, over the tropical western Pacific using 170 15-m resolution scenes from Terra’s Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) collected during the 2019 Cloud, Aerosol and Monsoon Processes Philippines Experiment (CAMP2Ex) mission. The average cloud fraction (CF) was 0.12, half of which was contributed by clouds less than 1.6 km in area-equivalent diameter. This compared well to Terra’s Multiangle Imaging Spectroradiometer (MISR) resolution-corrected CF of 0.13, but less than the 0.19 measured by Terra’s Moderate Resolution Imaging Spectroradiometer (MODIS). The cloud size distribution exhibited a power law form with exponent of 2.93 and an area-perimeter power law with dimension of 1.24. ASTER, MISR, and CAMP2Ex aircraft lidar showed excellent agreement in the cloud top height (CTH) distribution peak altitude of ~750 m. We examined cumulus properties in relation to meteorological variables and found that the variation in mean CTH is most controlled by the total column water vapor, lower-tropospheric stability (LTS), and estimated inversion strength (EIS). The variation in CF is most controlled by surface wind speed and near-cloud relative humidity instead of LTS/EIS, suggesting the need to improve low cloud parameterizations in climate models that use LTS/EIS based on stratocumulus studies.

Overshooting tops (OTs) are manifestations of deep convective updrafts that extend above the tropopause into the stratosphere. They can induce dynamic perturbations and result in irreversible transport of aerosols, water vapor and other mass from the troposphere into the stratosphere, thereby impacting the chemical composition and radiative processes of the stratosphere. These and other effects of OTs depend on their characteristics such as depth and area, which are understood to connect to mid-tropospheric updraft speed and width, respectively. Less understood is how static stability in the upper troposphere/lower stratosphere (UTLS) potentially modulates these OT–updraft connections, thus motivating the current study. Here, UTLS static stability and observed OT characteristics are quantified and compared using a combination of reanalysis data, observed rawinsonde data and geostationary satellite data. A strong relationship between OT depth and UTLS lapse rate and Brunt-Väisälä frequency N2 (R > 0.9, < -0.9, respectively) is found, implying that OT depth is reduced with an increasingly stable UTLS. In contrast, a weak relationship (R > 0.5) is found between OT area and UTLS static stability, implying that OT area is controlled primarily by mid to upper tropospheric updraft area. OT duration has a weak relationship to UTLS lapse rate and N2 (R = -0.27, 0.27, respectively). These relationships may be useful in describing mid- and low-level storm dynamics from satellite-observed characteristics of OTs in near real-time.

Cumulus clouds are common over maritime regions. They are important regulators of the global radiative energy budget and global hydrologic cycle, as well as a key contributor to the uncertainty in anthropogenic climate change projections due to uncertainty in aerosol–cloud interactions. These interactions are regionally specific owing to their strong influences on aerosol sources and meteorology. Here, our analysis focuses on the statistical properties of marine boundary layer (MBL) aerosol chemistry and the relationships of MBL aerosol to cumulus cloud properties just above cloud base as sampled in 2019 during the NASA Cloud, Aerosol and Monsoon Processes Philippines Experiment (CAMP2Ex). The aerosol and clouds were sampled by instruments on the NASA P-3 aircraft over three distinct maritime regions around the Philippines: the West Pacific, the South China Sea, and the Sulu Sea. Our analysis shows three primary sources influenced the aerosol chemical composition: clean marine (ocean source), industrial (Southeast Asia, Manila, and cargo and tanker ship emissions), and biomass burning (Borneo and Indonesia). The clean marine aerosol chemical composition had low values of all sampled chemical signatures, specifically median values of 2.2 µg m-3 of organics (ORG), 2.3 µg m-3 of SO4, 0.3 µg m-3 of NO3, 1.4 µg m-3 of NH4, 0.04 µg m-3 of Cl, and 0.0074 µg m-3 of refractory black carbon (BC). Chemical signatures of the other two aerosol source regions were industrial, with elevated SO4 having a median value of 6.1 µg m-3, and biomass burning, with elevated median concentrations of ORG 21.2 µg m-3 and BC 0.1351 µg m-3. Based on chemical signatures, the industrial component was primarily from ship emissions, which were sampled within 60 km of ships and within projected ship plumes. Normalized cloud droplet size distributions in clouds sampled near the MBL passes of the P-3 showed that clouds impacted by industrial and biomass burning contained higher concentrations of cloud droplets, by as much as 1.5 orders of magnitude for diameters < 13 µm compared to clean marine clouds, while at size ranges between 13.0–34.5 µm the median concentrations of cloud droplets in all aerosol categories were nearly an order of magnitude less than the clean marine category. In the droplet size bins centered at diameters > 34.5 µm concentrations were equal to, or slightly exceeded, the concentrations of the clean marine clouds. These analyses show that anthropogenic aerosols generated from industrial and biomass burning sources significantly influenced cloud base microphysical structure in the Philippine region enhancing the small droplet concentration and reducing the concentration of mid-sized droplets.

Soil moisture-precipitation (SM-PPT) feedbacks at the mesoscale represent a major challenge for numerical weather prediction, especially for subtropical regions that exhibit large variability in surface SM. How does surface heterogeneity, specifically mesoscale gradients in SM and land surface temperature (LST), affect convective initiation (CI) over South America? Using satellite data, we track nascent, daytime convective clouds and quantify the underlying antecedent (morning) surface heterogeneity. We find that convection initiates preferentially on the dry side of strong SM/LST boundaries with spatial scales of tens of kilometers. The strongest alongwind gradients in LST anomalies at 30 km length scale underlying the CI location occur during weak background low-level wind (<2.5m/s), high convective available potential energy (>1500J/kg) and low convective inhibition (<250J/kg) over sparse vegetation. At 100 km scale, strong gradients occur at the CI location during convectively unfavorable conditions and strong background flow. The location of PPT is strongly sensitive to the strength of the background flow. The wind profile during weak background flow inhibits propagation of convection away from the dry regions leading to negative SM-PPT feedback whereas strong background flow is related to longer lifecycle and rainfall hundreds of kilometers away from the CI location. Thus, the sign of the SM-PPT feedback is dependent on the background flow. This work presents the first observational evidence that CI over subtropical South America is associated with dry soil patches on the order of tens of kilometers. Convection-permitting numerical weather prediction models need to be examined for accurately capturing the effect of SM heterogeneity in initiating convection over such semi-arid regions.

Soil moisture-precipitation (SM-PPT) feedbacks at the mesoscale represent a major challenge for numerical weather prediction, especially for subtropical regions that exhibit large variability in surface SM. How does surface heterogeneity, specifically mesoscale gradients in SM and land surface temperature (LST), affect convective initiation (CI) over South America? Using satellite data, we track nascent, daytime convective clouds and quantify the underlying antecedent (morning) surface heterogeneity. We find that convection initiates preferentially on the dry side of strong SM/LST boundaries with spatial scales of tens of kilometers. The strongest alongwind gradients in LST anomalies at 30 km length scale underlying the CI location occur during weak background low-level wind (<2.5m/s), high convective available potential energy (>1500J/kg) and low convective inhibition (<250J/kg) over sparse vegetation. At 100 km scale, strong gradients occur at the CI location during convectively unfavorable conditions and strong background flow. The location of PPT is strongly sensitive to the strength of the background flow. The wind profile during weak background flow inhibits propagation of convection away from the dry regions leading to negative SM-PPT feedback whereas strong background flow is related to longer lifecycle and rainfall hundreds of kilometers away from the CI location. Thus, the sign of the SM-PPT feedback is dependent on the background flow. This work presents the first observational evidence that CI over subtropical South America is associated with dry soil patches on the order of tens of kilometers. Convection-permitting numerical weather prediction models need to be examined for accurately capturing the effect of SM heterogeneity in initiating convection over such semi-arid regions.