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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

On the Estimation of In-Cloud Vertical Air Motion Using Radar Doppler Spectra

Measurements of in-cloud vertical air motion are key to quantitatively describe cloud dynamics and their role in cloud microphysics. Here, a retrieval technique for estimating the in-cloud vertical air motion using the upward edge of the radar Doppler spectrum is presented. An additional broadening correction factor that depends on the signal-to-noise ratio (SNR) is introduced. A variety of independent measurements are used to assess the performance of the new technique. The vertical air motion is unbiased with an uncertainty of 0.2 m s –1 for SNR <30. Here, the properties of in-cloud vertical air motion are investigated from 1 year of ground-based observations of warm marine boundary layer clouds. Clouds with higher LWP are characterized by stronger vertical air motions compared to those having lower LWP values.

42 ENGINEERING↗
DOE OSTI2021

Aquifer Monitoring Using Ambient Seismic Noise Recorded With Distributed Acoustic Sensing (DAS) Deployed on Dark Fiber

Abstract Groundwater is a critical resource for human activities worldwide, and a vital component of many natural ecosystems. However, the state and dynamics of water‐bearing aquifers remain uncertain, mostly due to the paucity of subsurface data at high spatial and temporal resolution. Here, we show that analysis of infrastructure‐generated ambient seismic noise acquired on distributed acoustic sensing (DAS) arrays has potential as a tool to track variations in seismic velocities (d v / v ) caused by groundwater level fluctuations. We analyze 5 months of ambient noise acquired along an unused, 23 km‐long telecommunication fiber‐optic cable in the Sacramento Valley, CA, a so‐called “dark fiber." Three array subsections, ∼6 km apart, are processed and the stretching technique is applied to retrieve daily d v / v beneath each location. Near the Sacramento river, d v / v variations in the order of 2%–3% correlate with precipitation events and fluctuations in river stage of ∼1.5 m. In contrast, regions away (2.5 km) from the river do not experience large d v / v variations. These observations reveal short‐scale spatial variability in aquifer dynamics captured by this approach. Dispersion analysis and surface wave inversion of noise gathers reveal that seismic velocity perturbations occur at depths of 10–30 m. Rock physics modeling confirms that observed d v / v are linked to pore pressure changes at these depths, caused by groundwater table fluctuations. Our results suggest that DAS combined with ambient noise interferometry provides a means of tracking aquifer dynamics at high spatial and temporal resolutions at local to regional scales, relevant for effective groundwater resource management.

58 GEOSCIENCES↗
DOE OSTI2020

Impact of Cloud Longwave Scattering on Radiative Fluxes Associated With the Madden-Julian Oscillation in the Indian Ocean and Maritime Continent

Previous studies suggested that cloud longwave radiation contributes to the development and maintenance of the Madden-Julian Oscillation (MJO) and model-based convection is highly sensitive to the radiation scheme. However, currently used radiation schemes do not take cloud longwave scattering into account, resulting in an overestimation of the outgoing longwave radiation (OLR) and an underestimation of the downward longwave flux at the surface. We use combined active and passive satellite cloud property retrievals to quantify the one-layer cloud OLR and heating rate (HR) biases introduced by neglecting cloud longwave scattering in the Indian Ocean and Maritime Continent in the context of MJO, with a focus on its phases 3, 5, and 6. Here, the results show that the satellite-detected one-layer cloud area consists primarily of ice clouds, particularly during the boreal winter in the 4-year study period. An increased ice cloud area fraction of one-layer cloud groups is present up to 5 days before the onset of MJO events. If longwave scattering is neglected, the composite mean OLR overestimation over the one-layer ice cloud area from 5 days before to 4 days after the MJO passage is approximately 3.5 to 5.0 W m –2 . Neglecting longwave scattering also leads to a HR underestimation at cloud base and an overestimation at cloud top, making the base-to-top heating gradient less sharp at the cloud-resolving scale.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Simulating Observations of Southern Ocean Clouds and Implications for Climate

Southern Ocean (S. Ocean) clouds are important for climate prediction. Yet previous global climate models failed to accurately represent cloud phase distributions in this observation-sparse region. In this study, data from the Southern Ocean Clouds, Radiation, Aerosol, Transport Experimental Study (SOCRATES) experiment is compared to constrained simulations from a global climate model (the Community Atmosphere Model, CAM). Nudged versions of CAM are found to reproduce many of the features of detailed in situ observations, such as cloud location, cloud phase, and boundary layer structure. The simulation in CAM6 has improved its representation of S. Ocean clouds with adjustments to the ice nucleation and cloud microphysics schemes that permit more supercooled liquid. Comparisons between modeled and observed hydrometeor size distributions suggest that the modeled hydrometeor size distributions represent the dual peaked shape and form of observed distributions, which is remarkable given the scale difference between model and observations. Comparison to satellite observations of cloud physics is difficult due to model assumptions that do not match retrieval assumptions. Some biases in the model's representation of S. Ocean clouds and aerosols remain, but the detailed cloud physical parameterization provides a basis for process level improvement and direct comparisons to observations. This is crucial because cloud feedbacks and climate sensitivity are sensitive to the representation of S. Ocean clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

An Overview of Atmospheric Features Over the Western North Atlantic Ocean and North American East Coast—Part 2: Circulation, Boundary Layer, and Clouds

The Western North Atlantic Ocean (WNAO) is a complex land-ocean-atmosphere system that experiences a wide range of atmospheric phenomena, which in turn drive unique aerosol transport pathways, cloud morphologies, and boundary layer variability. This work, Part 2 of a 2-part paper series, provides an overview of the atmospheric circulation, boundary layer variability, three-dimensional cloud structure, and precipitation over the WNAO; the companion paper (Part 1) focused on chemical characterization of aerosol, gas, and wet deposition. Seasonal changes in the circulation and sea surface temperature explain a clear transition in cloud morphologies from small shallow cumulus clouds, convective clouds, and tropical storms in summer, to stratus/stratocumulus and multi-layer cloud systems associated with winter storms. Synoptic variability in cloud fields is estimated using satellite-based weather states, and the role of postfrontal conditions (cold-air outbreaks) in the development of stratiform clouds is further analyzed. Precipitation is persistent over the ocean, with a regional peak over the Gulf Stream path, where offshore sea surface temperature gradients are large and surface fluxes reach a regional peak. Satellite data show a clear annual cycle in cloud droplet number concentration along the coast in winter, and minima in summer, suggesting a marked annual cycle in aerosol-cloud interactions. The performance of four climate models are assessed against satellite cloud retrievals. The models qualitatively reproduce the annual cycle in cloud cover and liquid water path, but with large discrepancies across models, especially in the extra-tropics. The paper concludes with a summary of outstanding issues and recommendations for future work.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A Global High‐Resolution Mesoscale Convective System Database Using Satellite‐Derived Cloud Tops, Surface Precipitation, and Tracking

Abstract A new methodology is developed to construct a global (60°S–60°N) long‐term (2000–2019) high‐resolution (∼10‐km h) mesoscale convective system (MCS) database by tracking MCS jointly using geostationary satellite infrared brightness temperature ( T b ) and precipitation feature (PF) characteristics from the Integrated Multi‐satellitE Retrievals for GPM precipitation data sets. Independent validation shows that the satellite‐based MCS data set is able to reproduce important MCS statistics derived from ground‐based radar network observations in the United States and China. We show that by carefully considering key PF characteristics in addition to T b signatures, the new method significantly improves upon previous T b ‐only methods in detecting MCSs in the midlatitudes for all seasons. Results show that MCSs account for over 50% of annual total rainfall across most of the tropical belt and in selected regions of the midlatitudes, with a strong seasonality over many regions of the globe. The tracking database allows Lagrangian aspects such as MCS lifetime and translational speed and direction to be analyzed. The longest‐lived MCSs preferentially occur over the subtropical oceans. The land MCSs have higher cloud‐tops associated with more intense convection, and oceanic MCSs have much higher rainfall production. While MCSs are observed in many regions of the globe, there are fundamental differences in their dynamic and thermodynamic structures that warrant a better understanding of processes that control their evolution. This global database provides significant opportunities for observational and modeling studies of MCSs, their characteristics, and roles in regional and global water and energy cycles, as well as their hydrologic and other impacts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Impacts of Degradation on Water, Energy, and Carbon Cycling of the Amazon Tropical Forests

Selective logging, fragmentation, and understory fires directly degrade forest structure and composition. However, studies addressing the effects of forest degradation on carbon, water, and energy cycles are scarce. Here, we integrate field observations and high-resolution remote sensing from airborne lidar to provide realistic initial conditions to the Ecosystem Demography Model (ED-2.2) and investigate how disturbances from forest degradation affect gross primary production (GPP), evapotranspiration (ET), and sensible heat flux (H). We used forest structural information retrieved from airborne lidar samples (13,500 ha) and calibrated with 817 inventory plots (0.25 ha) across precipitation and degradation gradients in the eastern Amazon as initial conditions to ED-2.2 model. Our results show that the magnitude and seasonality of fluxes were modulated by changes in forest structure caused by degradation. During the dry season and under typical conditions, severely degraded forests (biomass loss ≥66%) experienced water stress with declines in ET (up to 34%) and GPP (up to 35%) and increases of H (up to 43%) and daily mean ground temperatures (up to 6.5°C) relative to intact forests. In contrast, the relative impact of forest degradation on energy, water, and carbon cycles markedly diminishes under extreme, multiyear droughts, as a consequence of severe stress experienced by intact forests. Our results highlight that the water and energy cycles in the Amazon are driven by not only climate and deforestation but also the past disturbance and changes of forest structure from degradation, suggesting a much broader influence of human land use activities on the tropical ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Can We Better Constrain the Timing of GNAIW/UNADW Variability in the Western Equatorial Atlantic and Its Relationship to Climate Change During the Last Deglaciation?

We have revisited the well-trod VM28-122 core retrieved from the deep Colombian Basin, which includes sediments that reflect modern Upper North Atlantic Deep Water and extends through the last deglaciation into the last glacial period when the site was bathed in Glacial North Atlantic Intermediate Water. Here, we leverage the nearby Cariaco Basin's surface water radiocarbon reconstruction (reservoir age, and ΔR) on the IntCal20 timescale to recast the period of the last deglaciation with a newly constrained age model. Based on the revised age model, we observe that the multimillennial decrease in benthic δ 13 C and B/Ca (which record δ 13 C of dissolved inorganic carbon and Δ[CO 3 –2 ], respectively) began at 18,100 ± 240 (95% CI) calibrated years BP, synchronous with Termination 1, as identified by changes in the Antarctic Ice Sheet composite and by the onset of rapid glacier recession in the Southern Hemisphere (Denton et al., 2010, https://doi.org/10.1126/science.1184119; Denton et al., 2021, https://10.1016/j.quascirev.2020.106771). The beginning of the decrease in benthic δ 18 O is concurrent with the changes in carbon chemistry or at most, a few hundred years later. It is no later than 17,700 ± 300 (95% CI) yrs BP in our record, at the putative start of Heinrich Stadial 1. With sufficient data density (more than 2–3 control points per kyr) and an independent record of past surface water radiocarbon variations, it is possible to achieve late glacial and deglacial chronologies with fidelities similar to those of ice cores. Furthermore, doing so in more oceanographic locations should shed light more broadly on the mechanisms instrumental to abrupt climate change.

58 GEOSCIENCES↗
DOE OSTI2020

Evaluation of Methods for Causal Discovery in Hydrometeorological Systems

Understanding causal relations is of utmost importance in hydrology and climate research for systems identification, prediction, and understanding systems behavior in a changing climate. Traditionally, researchers in hydrometeorology attempted to study causal questions by conducting controlled experiments using numerical models. This approach, however, in most cases of interest provides uncertain results because the models are approximate representation of the natural system. An alternative approach that has recently drawn significant attention in several fields is to infer causal relations from purely observational data. It possesses several traits to its utility particularly in hydrometeorology due to the rapid accumulation of in situ and remotely sensed data records. The first objective of this study is to present a brief description of four causal discovery methods (Granger causality, Transfer Entropy, graph-based algorithms, and Convergent Cross Mapping) with special emphasis on the assumptions on which they are built. Second, using synthetic data generated from a hydrological model, we assess their performance in retrieving causal information taking into account sensitivity to sample size and presence of noise. Last, we use causal analysis to examine and formulate hypotheses on causal drivers of evapotranspiration in a shrubland region during summer and winter seasons. An interpretation of the hypotheses based on canopy seasonal dynamics and evapotranspiration processes is presented. It is hoped that the results presented here can be useful in guiding researchers studying hydrometeorological systems as to which causal method is most appropriate to the characteristics of the system under study.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

The Diurnal Variation of the Aerosol Optical Depth at the ARM SGP Site

Abstract This study examines the diurnal variation of the aerosol optical depth (AOD) at 355 nm observed by Raman lidar (RL) at the Atmospheric Radiation Measurement Program Southern Great Plains (SGP) site under both clear and cloudy‐sky conditions. Here only cloudy‐skies when the lidar signal is not fully attenuated are considered. The daytime AOD and its variation from the RL showed an excellent agreement with the Aerosol Robotic Network, demonstrating that the RL‐retrieved AOD is not affected by solar background contamination. The climatological annual‐mean daytime‐mean AOD is only slightly larger than the nighttime‐mean AOD (by 1%–3%). However, day‐to‐day variations are observed such that the daytime‐ and nighttime‐mean AOD difference for a given day can be large (about 95% of days have differences within 0.2). The seasonal AOD diurnal range (i.e., the difference between the maximum and minimum values) relative to the mean was 10%–15% except in the winter when it was 44%. The seasonal‐mean cloudy‐sky AOD diurnal variation is similar to that for clear‐sky, except that the AODs are larger (the annual‐mean cloudy‐sky AOD is larger than the clear‐sky by 24%). The aerosol lidar ratio diurnal variations are also examined, which are 10%–20% for all seasons with a minimum near 9 a.m. to 15 p.m. for all seasons except winter. Also presented is the annual‐mean AOD from the Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite at SGP site: its daytime AOD is about 0.1 smaller than nighttime AOD because of daytime solar background contamination.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Evidence for the 3D Radiative Effects of Boundary-Layer Clouds From Observations of Direct and Diffuse Surface Solar Fluxes

Numerical experiments have revealed the importance of horizontal transport of light in the presence of clouds (“3D effects”), with consequences for climate, weather, and solar resource availability predictions. Yet, analysis of 3D effects from observations remain sparse because of the difficulty to isolate the effect of horizontal transport in radiation measurements. In this study, we provide observational evidence for 3D effects based on the direct-diffuse partition of surface solar fluxes. It is compared to outputs from the ecRad radiative transfer scheme run on retrieved cloud profiles. Furthermore, the direct-beam calculation takes careful account of the field-of-view of the pyrheliometer to ensure consistency between observed and modeled direct fluxes. Only the solver that accounts for 3D effects is able to reproduce the observed mean direct-diffuse partition as a function of solar zenith angle and cloud cover, in particular at large solar zenith angles where cloud sides intercept most of the direct beam.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Remotely Sensed Carbonyl Sulfide Constrains Model Estimates of Amazon Primary Productivity

We report understanding the magnitude of tropical gross primary production (GPP) is critical for carbon cycle modeling and climate projections, but this quantity is poorly constrained at regional scales. Biospheric uptake of carbonyl sulfide (OCS) provides a promising approach to estimating regional GPP. Here, we simulate OCS concentrations driven by surface flux scenarios encompassing a wide range of GPP estimates for the Amazon basin. We compare the model output to satellite retrievals and find a regional GPP estimate of 2375 ± 914 g(C) m –2 yr –1 , consistent with previous estimates, including the TRENDY model ensemble range of 1431–3812 g(C) m –2 yr –1 .

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Synthetic Evaluation of Infrasonic Multipole Waveform Inversion

Acoustic source inversions estimate the mass flow rate of volcanic explosions or yield of chemical explosions and provide insight into potential source directionality. However, the limitations of applying these methods to complex sources and their ability to resolve a stable solution have not been investigated in detail. We perform synthetic infrasound waveform inversions that use 3-D Green’s functions for a variety of idealized and realistic deployment scenarios using both a flat plane and Yasur volcano, Vanuatu as examples. We investigate the ability of various scenarios to retrieve the input source functions and relative amplitudes for monopole and multipole (monopole and dipole) inversions. Infrasound waveform inversions appear to be a robust method to quantify mass flow rates from simple sources (monopole) using deployments of infrasound sensors placed around a source, but care should be taken when analyzing and interpreting results from more complex acoustic sources (multipole) that have significant directional components. In the examples we consider the solution is stable for monopole inversions with a signal-to-noise ratio greater than five and the dipole component is small. For most scenarios investigated, the vertical dipole component of the multipole explosion source is poorly constrained and can impact the ability to recover the other source term components. Because multipole inversions are ill-posed for many deployments, a low residual does not necessarily mean the proper source vector has been recovered. Synthetic studies are able to help investigate the limitations and place bounds on information that may be missing using monopole and multipole inversions for potentially directional sources.

58 GEOSCIENCES↗
DOE OSTI2021

Evaluation of the CAM6 Climate Model Using Cloud Observations at McMurdo Station, Antarctica

A comparative analysis between observational data from McMurdo Station, Antarctica and the Community Atmosphere Model version 6 (CAM6) simulation is performed focusing on cloud characteristics and their thermodynamic conditions. Ka-band Zenith Radar (KAZR) and High Spectral Resolution Lidar (HSRL) retrievals are used as the basis of cloud fraction and cloud phase identifications. Radiosondes released at 12-hour increments provide atmospheric profiles for evaluating the simulated thermodynamic conditions. Our findings show that the CAM6 simulation consistently overestimates (underestimates) cloud fraction above (below) 3 km in four seasons of a year. Normalized by total in-cloud samples, ice and mixed phase occurrence frequencies are underestimated and liquid phase frequency is overestimated by the model at cloud fractions above 0.6, while at cloud fractions below 0.6 ice phase frequency is overestimated and liquid-containing phase frequency is underestimated by the model. The cloud fraction biases are closely associated with concurrent biases in relative humidity (RH), i.e., high (low) RH biases above (below) 2 km. Frequencies of correctly simulating ice and liquid-containing phase increase when the absolute biases of RH decrease. Cloud fraction biases also show a positive correlation with RH biases. Water vapor mixing ratio biases are the primary contributor to RH biases, and hence, likely a key factor controlling the cloud biases. Finally, this diagnosis of the evident shortfalls of representations of cloud characteristics in CAM6 simulation at McMurdo Station brings new insight in improving the governing model physics therein.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Wavelet Analysis of Properties of Marine Boundary Layer Mesoscale Cells Observed From AMSR–E

Marine boundary layer clouds tend to organize into closed or open mesoscale cellular convection (MCC). Here, two-dimensional wavelet analysis is applied for the first time to passive microwave retrievals of cloud water path (CWP), water vapor path (WVP), and rain rate (RR) from Advanced Microwave Scanning Radiometer for Earth Observing System in 2008 over the Northeast and Southeast Pacific, and the Southeast Atlantic subtropical stratocumulus to cumulus transition regions. The (co-)variability between CWP, WVP, and RR in 160 × 160 km 2 analysis boxes is partitioned between four mesoscale wavelength octaves (20, 40, 80, and 160 km). The cell scale is identified as the wavelength of the peak CWP variance. Together with a machine-learning classification of cell type, this allows the statistical characteristics of open and closed MCC of various scales, and its relation to WVP, RR, and potential environmental controlling factors to be analyzed across a very large set of cases. Here, the results show that the cell wavelength is most commonly 40–80 km. Cell-scale CWP perturbations are good predictors of the WVP and RR perturbations. For cells larger than 20 km, there is no obvious dependence of cell scale on the environmental controlling factors tested, suggesting that the cell scale may depend more on its historical evolution than the current environmental conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Factors Governing Cloud Growth and Entrainment Rates in Shallow Cumulus and Cumulus Congestus During GoAmazon2014/5

Shallow cumulus and cumulus congestus clouds play an important role in the large-scale tropical circulation by mixing heat and moisture vertically and preconditioning the environment for deeper convection. Different representations of these shallow clouds account for much of the spread in General Circulation Model (GCMs) climate sensitivity, potentially because of how entrainment is represented in GCM parameterizations. This study uses observations from the Department of Energy's Atmospheric Radiation Measurement (ARM) mobile facility deployed at Manacapuru, Brazil, during the Green Ocean Amazon (GoAmazon2014/5) Campaign. Environmental thermodynamic profiles and observations of cloud top height (CTH) are used to constrain an entraining plume model to estimate bulk entrainment rates (ERs). Estimates of CTH are obtained from a combination of vertically pointing W-band ARM cloud radar and 1,290 MHz Radar Wind Profiler observations. A combination of radiosonde, microwave radiometer profiler, and microwave radiometer observations provides new best estimates of the environmental thermodynamic state. We quantify uncertainty in ERs considering uncertainties in estimated CTH, environmental thermodynamic properties, and assumed initial parcel characteristics. We find ERs ranging from 0.16 to 2.8 km -1 with an average of 0.58 ± 0.10 km -1 over a selected population of 469 shallow cumulus and cumulus congestus clouds. Using the retrieved estimates of ER, we evaluate several entrainment closures that are currently used in atmospheric models or have been proposed based on theory or large eddy simulation. Finally, entrainment rates in cumulus clouds are weakly correlated with low-level buoyancy, cloud depth, and cloud size.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Climatology of Melting Layer Heights Estimated From Cloud Radar Observations at Various Locations

A melting layer (ML) detection algorithm for cloud radar with polarimetric capability was developed and applied to the cloud radar data collected from five different sites around the world for several years. The retrieved melting layer top height (MLH) showed a very good correspondence with the ECMWF Reanalysis 5 zero degree level data for all five sites. The ML characteristics were distinctively different for different sites, revealing climatological characteristics of ML forming clouds in different regions. Generally, ML tended to occur more frequently in summer than in winter except for a maritime site, where low stratiform clouds formed frequently in summer, the top of which might be lower than the freezing level. In contrast, at two Arctic sites, ML occurred almost exclusively in summer because it was too cold to have an ML in the other seasons. The MLH also varied significantly from site to site but generally was higher during warmer seasons. Based on MLH, two new indices, bulk temperature lapse rate (BLR) and relative depth (RD) of liquid cloud below MLH (RD) were developed, which were useful to explain the environmental characteristics of the five sites. BLR generally increased with the surface temperature at all sites except at the marine site that showed an opposite trend, where a unique synoptic pattern in winter generated high BLR in this cold season. Finally, these findings confirm that studies on thermodynamic structures using cloud radars can be broadened, taking advantage of BLR and RD information, as these indices can represent environmental thermodynamic characteristics of the clouds that have ML.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Southern Ocean Precipitation Characteristics Observed From CloudSat and Ground Instrumentation During the Macquarie Island Cloud & Radiation Experiment (MICRE): April 2016 to March 2017

A 1-year blended surface precipitation data set using Parsivel disdrometer, surface W-band radar, and tipping bucket measurements is produced for the Macquarie Island Cloud and Radiation Experiment (MICRE) and compared with retrievals from CloudSat (spaceborne 94 GHz radar). Surface precipitation was observed 44% ± 4% of the time between April 2016 and March 2017. Precipitation composed primarily of small particles (diameter <1 mm) occurred about 36% ± 2% of the time, constituting 10% of total accumulation. Remaining precipitation contained enough large particles such that the disdrometer could be used to identify the precipitation type as rain, ice, snow or wet snow. Seasonal and annual statistics on frequency of occurrence and accumulation for each precipitation type observed during MICRE are presented. Most ice and mixed phase precipitation was shallow, originating at a height of 3 km or lower, and occurred most often when Macquarie Island was to the northwest of the nearest cyclonic low-pressure center. In contrast, rain was more often deep and occurred most frequently when the island was to the southeast of cyclonic lows. A weak diurnal cycle in frequency and mean rate was present with a minimum between 12:00 and 14:00 local time and maximum between 03:00 and 06:00 local time. The CloudSat 2C-Precip-Column product missed the lightest precipitation (because the near-surface reflectivity is <-15 dBZ) and overestimated total liquid precipitation and occurrence of mixed phase precipitation, but captured reasonably well the distribution of rain rates for rates >0.5 mm/hr.

54 ENVIRONMENTAL SCIENCES↗