JGR–Atmospheres

Antarctic warm extremes impact the cryosphere, with very warm extremes driving surface melt on ice shelves. Here, we analyze temperatures exceeding the 90th percentile and the associated circulation patterns and radiation anomalies. ERA5 reanalysis data show positive geopotential height anomalies related to the occurrence of warm extremes. The highest temperature during warm extremes appears on the western periphery of high-pressure systems, consistent with anticyclonic advection. Temperature anomalies during warm extremes are strongest in winter due to the transport of warm and moist air and a strong meridional temperature gradient. In summer, the weak meridional gradients of top-of-atmosphere downward solar radiation flux and surface air temperature contribute to weak temperature anomalies. Warm extremes are associated with positive longwave radiation anomalies in all seasons, but with negative shortwave radiation anomalies at the surface except during polar night. These relationships are verified by station observations. Our results confirm that Antarctic warm extremes are mostly driven by meridional advection of warm air, and suggest that these warm air masses are predominantly moist and cloudy.

The detection efficiency (DE) of the World Wide Lightning Location Network (WWLLN) is evaluated in Southeast Asia by comparing WWLLN data with the Earth Network Total Lightning Network (ENTLN) data taking into account time, distance, and peak-current parameters. The performance of WWLLN is evaluated in the months of November and December in two different years (2020–2021). These periods are selected to assess the change (if any) in DE overtime and the inclusion of new stations. The strokes between the two networks were considered matched if they fell within a time criterion of 100 µs and a location difference of 25 km. Using this criterion, 5.2 × 106 WWLLN strokes were matched with ENTLN cloud-to-ground (CG) lightning strokes in November-December 2020, resulting in a DE of 32.9%. Similarly, 4.6 × 106 WWLLN strokes were found to match in November-December 2021, yielding a DE of 36.5%. Analysis of the peak-currents reveals that DE is lowest (<10%) for a peak-current below ±10 kA. However, for peak-current exceeding ±50 kA, the DE increases to ∼60%. During November-December 2021, WWLLN reported 38.95 × 106 lightning strokes globally; amongst them, Dhaka station detected 0.5 × 106 strokes, contributing to a 1.3% increase in the global DE. Dhaka station detects most lightning strokes within 8 × 103 km, which diminishes to zero after 10 × 103 km. The Dhaka station recorded a larger number of strokes at longer detection distances during midnight (22:00–02:00) than during noon (10:00–14:00). The results signify a positive impact of the Dhaka station on WWLLN's DE during the mentioned period.

In this study, the Atmospheric Infrared Sounder (AIRS) Observations for Model Intercomparison Projects (Obs4MIPs) V2.1 tropospheric air temperature, specific humidity, and relative humidity data are utilized to evaluate the global tropospheric temperature and humidity simulations in the fully coupled global climate models from the Coupled Model Intercomparison Project phases 3, 5, and 6 (CMIP3, CMIP5, and CMIP6), and possible simulation improvement in CMIP6 models in comparison to CMIP3 and CMIP5 models. Our analyses indicate that all three phases of CMIP models share similar tropospheric air temperature, specific humidity, and relative humidity biases in their multi-model ensemble means relative to AIRS. Cold biases up to 4 K and positive relative humidity biases up to 20% are found in the free troposphere almost globally with maxima over the mid-latitude storm tracks. Warm biases up to 2 K are seen over the Southern Ocean in the lower troposphere. Positive specific and relative humidity biases exist over the off-equatorial oceans while negative specific and relative humidity biases are seen near the equator in the tropical free troposphere, which are related to the double-intertropical convergence zone bias in the models. Both the air temperature and specific humidity biases are important to the relative humidity biases except in the tropical free troposphere where the specific humidity biases dominate. The tropospheric air temperature, specific humidity, and relative humidity biases are reduced from CMIP3 to CMIP5 and to CMIP6 at almost all pressure levels except at 300 hPa for specific humidity and in the boundary layer for relative humidity.

An independent evaluation of methane emissions data from GHGSat, a private company that operates a constellation of small microsatellites flying Fabry-Perot spectrometers operating at 1.6 µm, was performed. Data from multiple GHGSat commercial satellites, consisting of retrieved methane, diagnostics, and, where detected, plume and emissions information from roughly 250 scenes across Canada were analyzed. From these, 10 scenes contained methane plumes with a 2% detection rate for oil and gas scenes, and 10% for landfills. Methane precision was found to be 5%/2% on average for the C1/C2–C5 designs, with some variability due to scene albedo, terrain roughness, and airmass. Synthetic GHGSat plumes, generated using Lagrangian plume dispersion model and GHGSat characteristics, indicates typical detection limits of 240/180 kg/hr(C1/C2–C5), with a best case of roughly 100 kg/hr. Emissions and their uncertainties calculated using an alternative approach were in broad agreement with GHGSat-reported emissions. Overall, the performance of the GHGSat C2 design (also used for C3 onward) for favorable-viewing conditions was found to be largely consistent with company-advertised performance.

It was recently suggested that the Sun could switch to a high-activity regime which would lead to a rise of ultraviolet radiation with an amplitude of about four times larger than the amplitude of an average solar activity cycle and a simultaneous drop in total solar irradiance. Here, we applied the SOCOLv3-MPIOM model with an interacting ocean to simulate the response of chemistry, dynamics, and temperature of Earth's atmosphere to such a change in solar irradiance. We studied the effect of high activity regime on the atmosphere investigating the influence of the chemical and radiative processes on the climate, and chemistry of NOx, HOx, and O3. We find a climate cooling by up to 1K and a substantial increase in stratospheric ozone (up to 14%) and total ozone (up to 8%). To understand the role of the different processes we performed simulations with two sets of forcing accounting separately for the influence on chemical processes and for direct radiation energy balance. Our calculations show that the stratospheric O3 response is almost fully driven by the chemical processes. We also found that the direct radiation processes lead to near-surface cooling that results in the suppression of the Brewer-Dobson circulation. This, in turn, leads to the reduction of H2O influx from the low layers of the troposphere and to less intensive transport of ozone from the tropics to the middle latitudes. The surface climate response is dominated by direct radiation influence with only a small contribution from chemical processes.

Surface solar radiation is fundamental for terrestrial life. It provides warmth to make our planet habitable, drives atmospheric circulation, the hydrological cycle and photosynthesis. Europe has experienced an increase in surface solar radiation, termed “brightening,” since the 1980s. This study investigates the causative factors behind this brightening. A novel algorithm from the EUMETSAT satellite application facility on climate monitoring (CM SAF) provides the unique opportunity to simulate surface solar radiation under various atmospheric conditions for clouds (clear-sky or all-sky), aerosol optical depth (time-varying or climatological averages) and water vapor content (with or without its direct influence on surface solar radiation). Through a multiple linear regression approach, the study attributes brightening trends to changes in these atmospheric parameters. Analyzing 61 locations distributed across Europe from 1983 to 2020, aerosols emerge as key driver during 1983–2002, with Southern Europe and high elevations showing subdued effects (0%/decade–1%/decade) versus more pronounced impacts in Northern and Eastern Europe (2%/decade–6%/decade). Cloud effects exhibit spatial variability, inducing a negative effect on surface solar radiation (−3%/decade–−2%/decade) at most investigated locations in the same period. In the period 2001–2020, aerosol effects are much smaller, while cloud effects dominate the observed brightening (2%/decade–5%/decade). This study therefore finds a substantial decrease in the cloud radiative effect over Europe in the first two decades of the 21st century. Water vapor exerts negligible influence in both sub-periods.

The Mediterranean region is experiencing pronounced aridification and in certain areas higher occurrence of intense precipitation. In this work, we analyze the evolution of the precipitation probability distribution in terms of precipitating days (or “wet-days”) and all-days quantile trends, in Europe and the Mediterranean, using the ERA5 reanalysis. Looking at the form of wet-days quantile trends curves, we identify four regimes. Two are predominant: in most of northern Europe the precipitation quantiles all intensify, while in the Mediterranean the low-medium quantiles are mostly decreasing as extremes intensify or decrease. The wet-days distribution is then modeled by a Weibull law with two parameters, whose changes capture the four regimes. Assessing the significance of the parameters' changes over 1950–2020 shows that a signal on wet-days distribution has already emerged in northern Europe (where the distribution shifts to more intense precipitation), but not yet in the Mediterranean, where the natural variability is stronger. We extend the results by describing the all-days distribution change as the wet-days’ change plus a contribution from the dry-days frequency change, and study their relative contribution. In northern Europe, the wet-days distribution change is the dominant driver, and the contribution of dry-days frequency change can be neglected for wet-days percentiles above about 50%. In the Mediterranean, however, the change of precipitation distribution comes from the significant increase of dry-days frequency instead of an intensity change during wet-days. Therefore, in the Mediterranean the increase of dry-days frequency is crucial for all-days trends, even for heavy precipitation.

The topography in the Maritime Continent (MC) has significant impact on climate anomalies in the Asian-Australian monsoons region. In the present study, the Regional Climate Model Version 4.6 (RegCM4.6) is applied for the simulation of climate over the Asian-Australian monsoon region during the boreal summer. Results demonstrate that the RegcM4.6 is able to well reproduce precipitation, temperature and low-level and upper-level circulation patterns over the Asian-Australian monsoons region. A sensitivity experiment with zero topographic height in the MC region shows that the intensity of western Pacific subtropical high (WPSH) and Australian cold high both weaken simultaneously, while the cross-equatorial flows also decline and the East Asian-Australian monsoons become weaker. Meanwhile, the anomalous cyclonic circulation with significant convergence prevails in lower levels over the western Pacific, leading to more precipitation and higher temperature. In the MC region, there are more precipitation and high temperature in the north while there are less precipitation and low temperature in the south. Temperature increases over a large area from the Yunnan-Guizhou Plateau to the Loess Plateau but decreases in the southeastern coast of China and eastern India. These results have important implications for better understanding the topographic impact of the MC region on the interaction between the east Asian-Australian monsoons.

Deep atmospheric convection is often observed over the Kuroshio in the East China Sea (ECSK). However, the mechanisms by which warm oceanic currents fuel transient deep convection are not fully understood. This study investigates an atmospheric cold front that brought heavy precipitation as it traversed the ECSK in April 2004. The southwesterlies ahead of the cold front advected moist and warm air, creating a zone with high convective available potential energy (CAPE) values. As the cold front approached the ECSK, the pre-frontal high CAPE values coalesced with those over the warm current that substantially strengthened the deep convection, with precipitation rate increasing from 3 mm hr−1 to 10 mm hr−1. A numerical model well simulated the marked increase in precipitation over the ECSK, permitting the isolation of the ECSK's influence by contrasting the control (CTRL) run with an experiment with smoothed sea surface temperatures (SMTH run). Results show the ECSK contributed to 46% of the precipitation over the warm current. The ECSK was found to amplify ascending motion and elevate neutral buoyancy levels, extending its effect up to the tropopause. Furthermore, the strengthened deep convection significantly lowered the sea level pressure (SLP) over the ECSK and impressed upon the time-mean SLP field. An additional experiment with lowered SST underscored the high SST's critical role in deep convection. This case study suggests a novel pathway by which the effects of warm oceanic currents influence the upper troposphere under extreme conditions with strong baroclinic instability.

With urbanization, anthropogenic water vapor emissions have become a significant component of the urban atmosphere. Fossil fuel combustion-derived vapor (CDV) is a primary source of these emissions. Owing to the notably low CDV d-excess, stable hydrogen and oxygen isotopes are promising for distinguishing CDV from natural sources. Considering the limitations of in situ observations, this study aims to explore the feasibility of using IsoRSM, an isotopically enabled regional atmospheric model, to simulate CDV emissions in urban areas in winter. Two experiments were conducted: one in Salt Lake City (SLC) in January 2017 and another in Beijing in January 2007. The simulation results showed that the CDV addition significantly reduced the water vapor d-excess, particularly when the boundary layer was stable. The simulation with CDV emissions aligned better with the time series of in situ observations in SLC. The modification led to a more pronounced positive correlation between vapor d-excess and specific humidity, which was similar to the observation of SLC. The CDV inclusion significantly increased the vapor d-excess variability with varying wind directions in both sites. However, in Beijing, the underestimation of d-excess variation from natural sources caused a bigger discrepancy between the observed and simulated d-excess and CDV fraction. Thus, though there were still biases, the inclusion of CDV could improve the accuracy of isotopic simulation in the urban regions where CDV was one of the controlling factors of vapor d-excess.

The Tibetan Plateau (TP) provides vital water resources for downstream regions, with spring precipitation contributing considerably to the annual totals over the southeastern TP. The added value of convection-permitting modeling in simulating the spring climate over the TP is uncertain. Here, we conducted and compared decade-long regional convection-permitting (3.3 km) and convection-parameterized (13.2 km) Icosahedral Nonhydrostatic Weather and Climate Model (ICON) simulations to reproduce the atmospheric water cycle in spring over the TP. Results indicated that 3.3 km mesh ICON (ICON_3.3 km) exhibited notable added value in simulating the spring atmospheric water cycle over the TP. ICON_3.3 km reduced the wet biases of precipitation in the ERA5 reanalysis and 13.2 km mesh ICON (ICON_13.2 km) simulations, and improved the simulation of surface evaporation over the central and eastern TP. The reduction in the simulated precipitation in ICON_3.3 km was primarily followed by a decrease in surface evaporation from March to May, second by a reduction in water vapor flux convergence in May due to decreased water vapor inflow from the southeastern TP. Furthermore, compared to ICON_13.2 km, ICON_3.3 km alleviated the “drizzling” bias, leading to drier surface soils and decreased evaporation, and lead to 3% decrease in the fraction of evaporation converted into precipitation. Sensitivity experiments conducted at resolution of 13.2 km but turning off the convection parameterization demonstrated that both explicit representation of convection and enhanced horizontal resolution were crucial for accurately representing the spring atmospheric water cycle over the TP. Our results highlighted the need to develop kilometer-scale models for successfully reproducing the climate characteristics across the TP.

As a crucial element in the Earth's system, development of convective clouds is still insufficiently understood and simulated in both weather and climate models, particularly for small-scale regional convective clouds. In this study, a series of convective clouds cases with relatively small scales are selected over south China, and the evolution characteristics of those convective clouds are investigated using high spatiotemporal resolution geostationary satellite data. Statistical results show that the shorter the life cycle or the smaller the area, the higher the proportion of convective clouds. Notably, approximately 79.23% of convective clouds have a life cycle of less than 3 hr, and 63.81% have an area of less than 500 km2 for selected cases. In addition, there are significant differences in the cloud characteristics and meteorological parameters during various convective cloud stages and durations. Nevertheless, the relative proportions of convective clouds at three identified stages remain relatively constant with almost no dependence on duration of convective clouds, which are 33.50%, 23.92%, and 42.58% for the developing, mature, and dissipation stages, respectively. In addition, we find that the cloud-top cooling rate during the developing stage also affects the characteristics of the later stage of convective clouds. Quantitatively, the average cloud area and duration changed by 157.03 km2 and 0.17 hr when the cloud-top cooling rate varies by 15 K/h.

Accurate surface longwave downward radiation (SLDR) is crucial for understanding mountain climate dynamics. While existing algorithms notably improve the accuracy of clear-sky SLDR, a terrain correction algorithm that can correct remotely sensed and model-simulated all-sky SLDR on a large scale remains largely unexplored. Here, we propose a parameterization scheme for estimating all-sky SLDR in rugged terrain. We primarily improve the estimation of nearby terrain thermal contribution by considering topographic asymmetry and incorporate the effects of ice cloud thermal scattering under low water vapor conditions. We validate the reliability of our model using the Discrete Anisotropic Radiative Transfer (DART) model, demonstrating a good agreement with a bias value of −12.8 W/m2 and a RMSE value of 28.2 W/m2. Further evaluation against the Essential Thermal Infrared Remote Sensing (ELITE) SLDR product at three TIPEX-III in situ sites, located near the bottom of deep valleys with predominantly flat surfaces, indicates significant improvement in our model, reducing the mean bias by 7.4 W/m2 and the mean RMSE by 4.1 W/m2. Post-terrain correction, the ELITE SLDR difference map exhibits a spatial pattern of “small in the northwest and large in the southeast” in the study area, with the maximum differences reaching 67 W/m2 in the daytime and 54 W/m2 at nighttime. Comparison with existing methods reveals similar improvements due to the consideration of terrain effects. Overall, our SLDR correction model shows enormous potential for correcting remotely sensed and model-simulated SLDR products on a large scale.

Boundary layer height variations under sunny, rainy, and cloudy weather conditions.

The coastal boundary layer height (CBLH/Coastal-BLH) is critical in determining the exchange of heat, momentum, and materials between the land and ocean, thereby regulating the local climate and weather change. However, due to the complexity of geographical characteristics and meteorological conditions, accurate estimation of the CBLH remains challenging. Herein, based on continuous high-resolution measurements of CBL performed from November 2019 to April 2020 in coastal Ningbo city in eastern China, an optimal weighted ensemble model (OWEM) integrating multi-meteorological variables of the ERA5 reanalysis data sets is constructed and validated to estimate the CBLH. The mean absolute percentage error of the derived CBLH by OWEM is as low as 3%–5%, significantly lower than that of 36%–65% of the ERA5 CBLH products. Furthermore, three categories of different weather scenarios, that is, sunny, cloudy, and rainy, are separately discussed, and OWEM shows greater performance and higher accuracies in comparison with the traditional Least Absolute Shrinkage and Selection Operator, Random Forest, Adaboost, LightGBM, and ensemble model, among which, OWEM under fair weather days behave best, with a robust R 2 of 0.97 and a minimum mean absolute error (MAE) of 23 m. Further training results based on wind flow classification, that is, land breeze, sea breeze, and parallel wind, also indicate the outperformance of OWEM than other models, with a relatively large error in parallel wind of 50 m. Subsequent analysis of the Shapley Additive Explanations method strongly correlated with model feature importance, both reveal that thermodynamic factors such as temperature (T2m) and wind velocity (10 m U) are the major factors positively related to estimation accuracy during sunny days. Nevertheless, Relative Humidity dominates on rainy and cloudy days, TP on land breeze days, and dynamic variables like 10 m U and 10 m V on entire types of wind flow weather. In conclusion, the accurate estimation of CBLH from OWEM serves as a feasible and innovative approach, providing technical support for marine meteorology and related engineering applications, for example, onshore wind power, coastal ecological protection, etc.

The impacts of falling ice radiative effects (FIREs) on land-atmosphere feedback processes were examined, with a focus on the fidelity of land surface properties and their variability as inferred by global climate models (GCMs). We conducted a pair of sensitivity experiments using the National Center for Atmospheric Research (NCAR) Community Earth System Model Version 1 (CESM1) in fully coupled modes with FIREs turned on and off. This allowed us to investigate the seasonal response of land surface properties to changes in radiation fluxes and land surface temperature (LST) associated with FIREs across global land areas. Our findings indicate that during boreal winter, excluding FIREs results in less surface downward longwave and net flux (∼5–15 Wm−2), leading to a colder land surface (∼2–4 K) and air temperatures (∼1–4 K) at mid- and high latitudes. Consequently, the surface frozen soil layer and snow cover persist through spring, delaying snowmelt and thawing until summer. This delay reduces liquid soil moisture, thereby suppressing vegetation productivity in subsequent seasons. Conversely, tropical regions, exhibit contrasting responses, with a warmer land surface (∼0.5 K) and warmer air temperatures (∼0.1–0.5 K) due to increased surface downward shortwave and net flux (∼2–10 Wm−2). This enhancement in radiation fosters increased vegetation productivity throughout the seasonal cycle. These findings illustrate a local response of land surface properties to changes in the surface energy balance and LST, highlighting the significant role that FIREs play in land surface modeling within GCMs.

Variations in southern African precipitation have a major impact on local communities, increasing climate-related risks and affecting water and food security, as well as natural ecosystems. However, future changes in southern African precipitation are uncertain, with climate models showing a wide range of responses from near-term projections (2020–2040) to the end of the 21st century (2080–2100). Here, we assess the uncertainty in southern African precipitation change using five Ocean-Atmosphere General Circulation single model initial-condition large ensembles (30–50 ensemble members) and four emissions scenarios. We show that the main source of uncertainty in 21st Century projections of southern African precipitation is the internal climate variability. In addition, we find that differences between ensemble members in simulating future changes in the location of the Angola Low explain a large proportion (∼60%) of the uncertainty in precipitation change. Together, the internal variations in the large-scale circulation over the Pacific Ocean and the Angola Low explain ∼64% of the uncertainty in southern African precipitation change. We suggest that a better understanding of the future evolutions of the southern African precipitation may be achieved by understanding better the model's ability to simulate the Angola Low and its effects on precipitation.

In this study, we employ the Conformal Cubic Atmospheric Model (CCAM), a variable-resolution global atmospheric model, driven by two distinct sea surface temperature (SST) data sets: the 0.25° Optimum Interpolation Sea Surface Temperature (CCAM_OISST) version 2.1 and the 2° Extended Reconstruction SSTs Version 5 (CCAM_ERSST5). Model performance is assessed using a benchmarking framework, revealing good agreement between both simulations and the climatological rainfall spatial pattern, seasonality, and annual trends obtained from the Australian Gridded Climate Data (AGCD). Notably, wet biases are identified in both simulations, with CCAM_OISST displaying a more pronounced bias. Furthermore, we have examined CCAM’s ability to capture El Niño-Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) correlations with rainfall during Austral spring (SON) utilizing a novel hit rate metric. Results indicate that only CCAM_OISST successfully replicates observed SON ENSO- and IOD-rainfall correlations, achieving hit rates of 86.6% and 87.5%, respectively, compared to 52.7% and 41.8% for CCAM_ERSST5. Large SST differences are found surrounding the Australian coastline between OISST and ERSST5 (termed the “Coastal Effect”). Differences can be induced by the spatial interpolation error due to the discrepancy between model and driving SST. An additional CCAM experiment, employing OISST with SST masked by ERSST5 in 5° proximity to the Australian continent, underscores the “Coastal Effect” has a significant impact on IOD-Australian rainfall simulations. In contrast, its influence on ENSO-Australian rainfall is limited. Therefore, simulations of IOD-Australian rainfall teleconnection are sensitive to local SST representation along coastlines, probably dependent on the spatial resolution of driving SST.

In August 2017, a smoke plume from wildfires in British Columbia and the Northwest Territories recirculated and persisted over northern Canada for over two weeks. We compared a full-factorial set of NASA Goddard Institute for Space Studies ModelE simulations of the plume to satellite retrievals of aerosol optical depth and carbon monoxide, finding that ModelE performance was dependent on the model configuration, and more so on the choice of injection height approach, aerosol scheme and biomass burning emissions estimates than to the choice of horizontal winds for nudging. In particular, ModelE simulations with free-tropospheric smoke injection, a mass-based aerosol scheme and comparatively high fire NOx emissions led to unrealistically high aerosol optical depth. Using paired simulations with and without fire emissions, we estimated that for 16 days over an 850,000 km2 region, the smoke decreased planetary boundary layer heights by between 253 and 547 m, decreased downward shortwave radiation by between 52 and 172 Wm−2, and decreased surface temperature by between 1.5°C and 4.9°C, the latter spanning an independent estimate from operational weather forecasts of a 3.7°C cooling. The strongest surface climate effects were for ModelE configurations with more detailed aerosol microphysics that led to a stronger first indirect effect.

Satellite remote sensing of aerosol is largely conducted at moderate or coarse spatial resolution around 1–10 km. Nevertheless, at urban areas with high human activity, aerosol can originate from complex emission sources and may also vary strongly in space. Therefore, aerosol characterization at fine spatial resolution is essential for air quality study and assessment of anthropogenic pollution as well as climate effects. However, space-borne instruments with high spatial resolution are usually limited in swath width or spectral coverage which result in lowering information content required for aerosol and surface retrieval. Based on the Generalized Retrieval of Atmosphere and Surface Properties (GRASP) algorithm, we propose a hybrid approach by combining fine and coarse spatial resolution measurements to retrieve aerosol and surface properties simulataneously at fine spatial resolution. The instruments with coarse spatial resolution and high revisting time can provide advanced aerosol characterization. At the same time, the instruments with fine spatial resolution are sensitive to spatial variability of aerosol nearby sources. In this study, the GRASP/Hybrid approach is demonstrated and tested based on the European Space Agency Sentinel-5p/TROPOMI together with the Italian Space Agency PRISMA satellite data. Specifically, the detailed aerosol microphysical properties from Sentinel-5p/TROPOMI 10 km retrievals are used as a priori information for PRISMA to derive aerosol loading and surface properties at 100 meter (m) spatial resolution. The PRISMA 100 m aerosol and surface retrieval based on the developed GRASP/Hybrid approach are evaluated using available ground-based and satellite measurements, including AERONET, VIIRS/DB aerosol and PRISMA Level 2 surface reflectance products.

The Paluch diagram is a widely used tool for interpreting aircraft measurements of shallow cumulus clouds. A prior study conducted by Heus et al. (2008, https://doi.org/10.1175/2008jas2572.1) concluded that the source levels of in-cloud air inferred from the Paluch diagram exhibit biases, sometimes of several hundred meters, in comparison to those derived from Lagrangian particle tracking. In this short study we revisit this comparison. The results indicate that the upper source levels of in-cloud air determined from the Lagrangian Particle Tracking and the Paluch diagram are consistent, and the choice of statistical methods is crucial. The significance of this research lies in confirming the reliability of the Paluch analysis, enabling its confident application to aircraft data.