Courtney Schumacher
· Earl Cook Professorship in Geosciences; ProfessorVerifiedTexas A&M University · Atmospheric Sciences
Active 2000–2026
About
Professor Courtney Schumacher holds the Earl Cook Professorship in Geosciences at Texas A&M University in the College of Arts and Sciences, within the Department of Atmospheric Sciences. Her research focuses on atmospheric convective processes in the tropics, encompassing phenomena from small cumulus clouds to large mesoscale convective systems. She investigates the environmental factors that influence precipitation production and the organization of convection. Radar meteorology is a key tool in her work, utilizing both ground-based and space-borne radars to observe precipitation and storm structures, and to develop climatologies that enhance understanding of tropical convective processes and subtropical precipitating systems. Additionally, her research explores mesoscale-climate interactions by combining observations of precipitation and storm structure with mesoscale and global circulation models to better understand the interaction between mesoscale systems and large-scale atmospheric circulation.
Research topics
- Geology
- Geography
- Meteorology
- Climatology
- Oceanography
- Physics
- Atmospheric sciences
- Environmental science
- Biology
- Physical geography
- Archaeology
- Ecology
Selected publications
Supplementary material to "Isotopic Evidence for Ice Growth by Riming in Precipitation"
2026-03-05
articleOpen accessTable S1 (A-F), Table S2 Figures S1 -S8 Table S1 (A-F).Dates/times for which concurrent radar and isotope data were available.Daily averages of MDV were calculated for Summit and Dumont d'Urville.Averaging times were daily or sub-daily at Ny-lesund and Andenes, and 25or 30-min at Cazadero and Rio Claro.
Storm Chasing with the INCUS Mission
2025-01-07
articleThe overarching goal of the NASA INvestigation of Convective UpdraftS (INCUS) mission is to enhance our understanding of why, when and where tropical convective storms form, and why only some of these storms produce extreme weather. Convective storms transport air and water between Earth's surface and the upper troposphere. This vertical transport of air and water - often referred to as convective mass flux (CMF) - plays a critical role in Earth's weather and climate system through its impacts on large-scale atmospheric circulations, upper tropospheric moistening and high cloud-radiative feedbacks, precipitation rates, and extreme weather. Potential changes to CMF with changing climates may significantly impact these processes. In spite of the critical role of this vertical transport of water and air, representation of CMF remains a major source of error in weather and climate models, thereby limiting our ability to accurately predict convective storms and their impacts in current and future climates. The observations obtained from INCUS will enhance our understanding of tropical convective storm processes and provide guidance for representing these processes in weather and climate models.
The Land–Sea Breeze Circulation over the West Coast of Sumatra
Monthly Weather Review · 2025-08-25
articleAbstract The characteristics of the land and sea breeze near the west coast of Sumatra are studied using hourly 10-m wind observations from the Bengkulu Airport for the year 2018, with an emphasis on the properties of the land breeze. Spectral analysis shows that the land–sea breeze cycle is a dominant part of the overall circulation in the region, with disturbances at the diurnal frequency accounting for roughly half the overall disturbance kinetic energy. A method is presented for isolating the near-diurnal parts of the flow through a combination of high- and low-pass filtering, with land and sea breezes defined in terms of the shore-perpendicular component of the filtered winds. By this definition, a land breeze occurs each day, with a median onset time of 1900 LT, a median duration of 15 h, and a median maximum speed of 1.8 m s −1 occurring near 0200 LT. The characteristics of the land breeze are found to depend strongly on the phase of the Madden–Julian oscillation. A dependence was also found during the Asian and Australian monsoons, particularly for the onset time and maximum speed. Sea breezes occur almost every day but are much shorter (about 8.5 h) and stronger (>3 m s −1 ) than land breezes. Comparisons between airport observations and ERA5 surface winds show that while ERA5 accurately captures the onset time, duration, and timing of the maximum speed for sea breezes, it only captures the onset time and duration for land breezes. For both, the maximum speed is significantly underestimated. Significance Statement Detailed characteristics of tropical land and sea breezes are lacking in the literature. Utilizing 1 year of hourly wind observations from the west coast of Sumatra and a newly developed detection algorithm, we found that land and sea breezes occur essentially every day. Land breezes start just after sunset but last many hours after sunrise and reach their maximum speed almost halfway through their median 15-h duration. These properties vary intraseasonally and seasonally. Sea breezes begin around 1000 LT and are much shorter and stronger than land breezes. ERA5 does a reasonable job capturing many characteristics of the land–sea breeze circulation but underestimates the maximum wind speed in both cases.
2024-03-15 · 2 citations
preprintOpen accessThis study evaluates a lightning parameterization that utilizes only large-scale environmental variables (i.e., convective available potential energy (CAPE), column moisture, and lifting condensation level (LCL)) for present-day (2017-19) and end-of-century (2098-2100) RCP8.5 climate scenarios in the Community Atmosphere Model version 5 (CAM5). Using a single equation, the present-day prediction can produce a reasonable land/ocean ratio in lightning occurrence. The end-of-century prediction shows relative increases of about 50% over higher-latitude land, but much more variable increases and decreases across mid-latitude ocean and the tropics such that the overall global lightning occurrence is expected to slightly decrease. Lightning occurrence over land predicted from present-day CAM5 is less than that using MERRA-2 reanalysis because of differences in the basic-state variables used as predictors. In addition, the choice of dilute or undilute CAPE will impact future lightning predictions over land, but the environment-only parameterization results are more consistent than a CAPE x precipitation parameterization.
Geoscientific model development · 2024-09-25 · 4 citations
articleOpen accessAbstract. Lightning is an important atmospheric process for generating reactive nitrogen, resulting in the production of tropospheric ozone, as well as igniting wildland fires, which result in potentially large emissions of many pollutants and short-lived climate forcers. Lightning is also expected to change in frequency and location with the changing climate. As such, lightning is an important component of Earth system models. Until now, the Canadian Earth System Model (CanESM) did not contain an interactive-lightning parameterization. The fire parameterization in CanESM5.1 was designed to use prescribed monthly climatological lightning. In this study, we have added a logistical regression lightning model that predicts lightning occurrence interactively based on three environmental variables and their interactions in CanESM5.1's atmospheric model, CanAM5.1 (Canadian Atmospheric Model), creating the capacity to interactively model lightning, allowing for future projections under different climate scenarios. The modelled lightning and resulting burned area were evaluated against satellite measurements over the historical period, and model biases were found to be acceptable. Modelled lightning had a small negative bias and excellent land–ocean ratio compared to satellite measurements. The modified version of CanESM5.1 was used to simulate two future climate scenarios (SSP2-4.5 and SSP5-8.5; Shared Socioeconomic Pathway) to assess how lightning and burned area change in the future. Under the higher-emissions scenario (SSP5-8.5), CanESM5.1 predicts almost no change to the global mean lightning flash rate by the end of the century (2081–2100 vs. 2015–2035 average). However, there are substantial regional changes to lightning – particularly over land – such as a mean increase of 6 % in the northern mid-latitudes and decrease of −8 % in the tropics. By the century's end, the change in global total burned area with prescribed climatological lightning was about 2 times greater than that with interactive lightning (42 % vs. 26 % increase, respectively). Conversely, in the northern mid-latitudes the use of interactive lightning resulted in 3 times more burned area compared to that with unchanging lightning (48 % vs. 16 % increase, respectively). These results show that the future changes to burned area are greatly dependent on a model's lightning scheme, both spatially and overall.
2024-02-16 · 3 citations
preprintOpen accessCorrespondingAbstract. Lightning is an important atmospheric process for generating reactive nitrogen, resulting in production of tropospheric ozone, as well as igniting wildland fires, which result in potentially large emissions of many pollutants and short-lived climate forcers. Lightning is also expected to change in frequency and location with the changing climate. As such, lightning is an important component of Earth system models. Until now, the Canadian Earth System Model (CanESM) did not contain an interactive lightning parameterization. The fire parameterization in CanESM5.1 was designed to use prescribed monthly climatological lightning. In this study, we have added a logistical regression lightning model that predicts lightning occurrence interactively based on three environmental variables and their interactions into CanESM5.1’s atmospheric model, CanAM5.1, creating the capacity to interactively model lightning, allowing for future projections under different climate scenarios. The modelled lightning and resulting burned area were evaluated against satellite measurements over the historical period and model biases were found to be acceptable. Modelled lightning was within a factor of two of the measurements and had exceptionally accurate land/ocean ratios. The modified version of CanESM5.1 was used to simulate two future climate scenarios (SSP2-4.5 and SSP5-8.5) to assess how lightning and burned area change in the future. Under the higher emission scenario (SSP5-8.5), CanESM5.1 predicts an increase in northern mid-latitude lightning flashrate of 5 %, but a decrease in tropical lightning of -10 %, resulting in almost no change to the global mean lightning amount by the end-of-the century (2081–2100 vs 2015–2035 average). By century’s end, the change in global total burned area with prescribed climatological lightning was about two times greater than that with interactive lightning (43 % vs 19 % increase, respectively). Conversely, in the northern mid-latitudes the use of interactive lightning resulted in three times more area burned as that with unchanging lightning (36 % vs 13 % increase, respectively). These results show that the future changes to burned area are greatly dependent on a model’s lightning scheme, both spatially and overall.
Prediction of Tropical Pacific Rain Rates with Overparameterized Neural Networks
Artificial Intelligence for the Earth Systems · 2024-05-02 · 3 citations
articleOpen accessAbstract The prediction of tropical rain rates from atmospheric profiles poses significant challenges, mainly due to the heavy-tailed distribution exhibited by tropical rainfall. This study introduces overparameterized neural networks not only to forecast tropical rain rates but also to explain their heavy-tailed distribution. The investigation is separately conducted for three rain types (stratiform, deep convective, and shallow convective) observed by the Global Precipitation Measurement satellite radar over the west and east Pacific regions. Atmospheric profiles of humidity, temperature, and zonal and meridional winds from the MERRA-2 reanalysis are considered as features. Although overparameterized neural networks are well known for their “double descent phenomenon,” little has been explored about their applicability to climate data and capability of capturing the tail behavior of data. In our results, overparameterized neural networks accurately estimate the rain-rate distributions and outperform other machine learning methods. Spatial maps show that overparameterized neural networks also successfully describe the spatial patterns of each rain type across the tropical Pacific. In addition, we assess the feature importance for each overparameterized neural network to provide insight into the key factors driving the predictions, with low-level humidity and temperature variables being the overall most important. These findings highlight the capability of overparameterized neural networks in predicting the distribution of the rain rate and explaining extreme values. Significance Statement This study aims to introduce the capability of overparameterized neural networks, a type of neural network with more parameters than data points, in predicting the distribution of tropical rain rates from gridscale environmental variables and explaining their tail behavior. Rainfall prediction has been a topic of importance, yet it remains a challenging problem for its heavy-tailed nature. Overparameterized neural networks correctly captured rain-rate distributions and the spatial patterns and heterogeneity of the observed rain rates for multiple rain types, which could not be achieved by any other previous statistical or machine learning frameworks. We find that overparameterized neural networks can play a key role in general prediction tasks, with potential expanded applicability to other domains with heavy-tailed data distribution.
2024-04-23
peer-reviewOpen accessCorresponding<strong class="journal-contentHeaderColor">Abstract.</strong> Lightning is an important atmospheric process for generating reactive nitrogen, resulting in production of tropospheric ozone, as well as igniting wildland fires, which result in potentially large emissions of many pollutants and short-lived climate forcers. Lightning is also expected to change in frequency and location with the changing climate. As such, lightning is an important component of Earth system models. Until now, the Canadian Earth System Model (CanESM) did not contain an interactive lightning parameterization. The fire parameterization in CanESM5.1 was designed to use prescribed monthly climatological lightning. In this study, we have added a logistical regression lightning model that predicts lightning occurrence interactively based on three environmental variables and their interactions into CanESM5.1’s atmospheric model, CanAM5.1, creating the capacity to interactively model lightning, allowing for future projections under different climate scenarios. The modelled lightning and resulting burned area were evaluated against satellite measurements over the historical period and model biases were found to be acceptable. Modelled lightning was within a factor of two of the measurements and had exceptionally accurate land/ocean ratios. The modified version of CanESM5.1 was used to simulate two future climate scenarios (SSP2-4.5 and SSP5-8.5) to assess how lightning and burned area change in the future. Under the higher emission scenario (SSP5-8.5), CanESM5.1 predicts an increase in northern mid-latitude lightning flashrate of 5 %, but a decrease in tropical lightning of -10 %, resulting in almost no change to the global mean lightning amount by the end-of-the century (2081–2100 vs 2015–2035 average). By century’s end, the change in global total burned area with prescribed climatological lightning was about two times greater than that with interactive lightning (43 % vs 19 % increase, respectively). Conversely, in the northern mid-latitudes the use of interactive lightning resulted in three times more area burned as that with unchanging lightning (36 % vs 13 % increase, respectively). These results show that the future changes to burned area are greatly dependent on a model’s lightning scheme, both spatially and overall.
2024-02-16
preprintOpen access2024-04-23
peer-reviewOpen accessCorresponding<strong class="journal-contentHeaderColor">Abstract.</strong> Lightning is an important atmospheric process for generating reactive nitrogen, resulting in production of tropospheric ozone, as well as igniting wildland fires, which result in potentially large emissions of many pollutants and short-lived climate forcers. Lightning is also expected to change in frequency and location with the changing climate. As such, lightning is an important component of Earth system models. Until now, the Canadian Earth System Model (CanESM) did not contain an interactive lightning parameterization. The fire parameterization in CanESM5.1 was designed to use prescribed monthly climatological lightning. In this study, we have added a logistical regression lightning model that predicts lightning occurrence interactively based on three environmental variables and their interactions into CanESM5.1’s atmospheric model, CanAM5.1, creating the capacity to interactively model lightning, allowing for future projections under different climate scenarios. The modelled lightning and resulting burned area were evaluated against satellite measurements over the historical period and model biases were found to be acceptable. Modelled lightning was within a factor of two of the measurements and had exceptionally accurate land/ocean ratios. The modified version of CanESM5.1 was used to simulate two future climate scenarios (SSP2-4.5 and SSP5-8.5) to assess how lightning and burned area change in the future. Under the higher emission scenario (SSP5-8.5), CanESM5.1 predicts an increase in northern mid-latitude lightning flashrate of 5 %, but a decrease in tropical lightning of -10 %, resulting in almost no change to the global mean lightning amount by the end-of-the century (2081–2100 vs 2015–2035 average). By century’s end, the change in global total burned area with prescribed climatological lightning was about two times greater than that with interactive lightning (43 % vs 19 % increase, respectively). Conversely, in the northern mid-latitudes the use of interactive lightning resulted in three times more area burned as that with unchanging lightning (36 % vs 13 % increase, respectively). These results show that the future changes to burned area are greatly dependent on a model’s lightning scheme, both spatially and overall.
Recent grants
Frequent coauthors
- 35 shared
Gilberto Fisch
Universidade de Taubaté
- 27 shared
Rosa Maria Nascimento dos Santos
- 27 shared
Marcelo Chamecki
University of California, Los Angeles
- 27 shared
Tobias Gerken
- 27 shared
José D. Fuentes
- 27 shared
Amy M. Trowbridge
University of Wisconsin–Madison
- 26 shared
David R. Fitzjarrald
State University of New York
- 26 shared
Gabriel G. Katul
Duke University
- Resume-aware match score
- Save to shortlist
- AI-drafted outreach
See your match with Courtney Schumacher
PhdFit ranks faculty by your research interests, methods, and publications — grounded in their actual work, not templates.
- Free to start
- No credit card
- 30-second signup