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Mark Smalley and Tristan L’Ecuyer

Abstract

The spatial distribution of precipitation occurrence has important implications for numerous applications ranging from defining cloud radiative effects to modeling hydrologic runoff, statistical downscaling, and stochastic weather generation. This paper introduces a new method of describing the spatial characteristics of rainfall and snowfall that takes advantage of the high sensitivity and high resolution of the W-band cloud precipitation radar aboard CloudSat. The resolution dependence of precipitation occurrence is described by a two-parameter exponential function defined by a shape factor that governs the variation in the distances between precipitation events and a scale length that represents the overall probability of precipitation and number density of distinct events.

Geographic variations in the shape factor and scale length are consistent with large-scale circulation patterns and correlate with environmental conditions on local scales. For example, a large contrast in scale lengths between land and ocean areas reflects the more extensive, widespread nature of precipitation over land than over ocean. An analysis of warm rain in the southeast Pacific reveals a shift from frequent isolated systems to less frequent but more regularly spaced systems along a transect connecting stratocumulus and trade cumulus cloud regimes. A similar analysis during the Amazon wet season reveals a relationship between the size and frequency of convection and zonal wind direction with precipitation exhibiting a more oceanic character during periods of westerly winds. These select examples demonstrate the utility of this approach for capturing the sensitivity of the spatial characteristics of precipitation to environmental influences on both local and larger scales.

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Mark Smalley, Tristan L'Ecuyer, Matthew Lebsock, and John Haynes

Abstract

Because of its extensive quality control procedures and uniform space–time grid, the NCEP Stage IV merged Weather Surveillance Radar-1988 Doppler (WSR-88D) radar and surface rain gauge dataset is often considered to be the best long-term gridded dataset of precipitation observations covering the contiguous United States. Stage IV accumulations are employed in a variety of applications, and while the WSR-88D systems are well suited for observing heavy rain events that are likely to affect flooding, limitations in surface radar and gauge measurements can result in missed precipitation, especially near topography and in the western United States. This paper compares hourly Stage IV observations of precipitation occurrence to collocated observations from the 94-GHz CloudSat Cloud Profiling Radar, which provides excellent sensitivity to light and frozen precipitation. Statistics from 4 yr of comparisons show that the CloudSat observes precipitation considerably more frequently than the Stage IV dataset, especially in northern states where frozen precipitation is prevalent in the cold season. The skill of Stage IV for precipitation detection is found to decline rapidly when the near-surface air temperature falls below 0°C. As a result, agreement between Stage IV and CloudSat tends to be best in the southeast, where radar coverage is good and moderate-to-heavy liquid precipitation dominates. Stage IV and CloudSat precipitation detection characteristics are documented for each of the individual river forecast centers that contribute to the Stage IV dataset to provide guidance regarding potential sampling biases that may impact hydrologic applications.

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Mark Smalley, Pierre-Emmanuel Kirstetter, and Tristan L’Ecuyer

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High temporal and spatial resolution observations of precipitation occurrence from the NEXRAD-based Multi-Radar Multi-Sensor (MRMS) system are compared to matched observations from CloudSat for 3 years over the contiguous United States (CONUS). Across the CONUS, precipitation is generally reported more frequently by CloudSat (7.8%) than by MRMS (6.3%), with dependence on factors such as the NEXRAD beam height, the near-surface air temperature, and the surface elevation. There is general agreement between ground-based and satellite-derived precipitation events over flat surfaces, especially in widespread precipitation events and when the NEXRAD beam heights are low. Within 100 km of the nearest NEXRAD site, MRMS reports a precipitation frequency of 7.54% while CloudSat reports 7.38%. However, further inspection reveals offsetting biases between the products, where CloudSat reports more snow and MRMS reports more rain. The magnitudes of these discrepancies correlate with elevation, but they are observed in both the complex terrain of the Rocky Mountains and the relatively flat midwestern areas of the CONUS. The findings advocate for caution when using MRMS frequency and accumulations in complex terrain, when temperatures are below freezing, and at ranges greater than 100 km. A multiresolution analysis shows that no more than 1.88% of CloudSat pixels over flat terrain are incorrectly identified as nonprecipitating as a result of shallow showers residing the CloudSat clutter-filled blind zone when near-surface air temperatures are above 15°C.

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Mark Smalley, Kay Sušelj, Matthew Lebsock, and Joao Teixeira

Abstract

A single-column model (SCM) is used to simulate a variety of environmental conditions between Los Angeles, California, and Hawaii in order to identify physical elements of parameterizations that are required to reproduce the observed behavior of marine boundary layer (MBL) cloudiness. The SCM is composed of the JPL eddy-diffusivity/mass-flux (EDMF) mixing formulation and the RRTMG radiation model. Model forcings are provided by the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA2). Simulated low cloud cover (LCC), rain rate, albedo, and liquid water path are compared to collocated pixel-level observations from A-Train satellites. This framework ensures that the JPL EDMF is able to simulate a continuum of real-world conditions. First, the JPL EDMF is shown to reproduce the observed mean LCC as a function of lower-tropospheric stability. Joint probability distributions of lower-tropospheric cloud fraction, height, and lower-tropospheric stability (LTS) show that the JPL EDMF improves upon its MERRA2 input but struggles to match the frequency of observed intermediate-range LCC. We then illustrate the physical roles of plume lateral entrainment and eddy-diffusivity mixing length in producing a realistic behavior of LCC as a function of LTS. In low-LTS conditions, LCC is mostly sensitive to the ability of convection to mix moist air out of the MBL. In high-LTS conditions, LCC is also sensitive to the turbulent mixing of free-tropospheric air into the MBL. In the intermediate LTS regime typical of stratocumulus–cumulus transition there is proportional sensitivity to both mixing mechanisms, emphasizing the utility of a combined eddy-diffusivity/mass-flux approach for representing mixing processes.

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Kay Suselj, Derek Posselt, Mark Smalley, Matthew D. Lebsock, and Joao Teixeira

Abstract

We develop a methodology for identification of candidate observables that best constrain the parameterization of physical processes in numerical models. This methodology consists of three steps: (i) identifying processes that significantly impact model results, (ii) identifying observables that best constrain the influential processes, and (iii) investigating the sensitivity of the model results to the measurement error and vertical resolution of the constraining observables. This new methodology is applied to the Jet Propulsion Laboratory stochastic multiplume Eddy-Diffusivity/Mass-Flux (JPL-EDMF) model for two case studies representing nonprecipitating marine stratocumulus and marine shallow convection. The uncertainty of physical processes is characterized with uncertainty of model parameters. We find that the most uncertain processes in the JPL-EDMF model are related to the representation of lateral entrainment for convective plumes and parameterization of mixing length scale for the eddy-diffusivity part of the model. The results show a strong interaction between these uncertain processes. Measurements of the water vapor profile for shallow convection and of the cloud fraction profile for the stratocumulus case are among those measurements that best constrain the uncertain JPL-EDMF processes. The interdependence of the required vertical resolution and error characteristics of the observational system are shown. If the observations are associated with larger error, their vertical resolution has to be finer and vice versa. We suggest that the methodology and results presented here provide an objective basis for defining requirements for future observing systems such as future satellite missions to observe clouds and the planetary boundary layer.

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James M. Kurdzo, Earle R. Williams, David J. Smalley, Betty J. Bennett, David C. Patterson, Mark S. Veillette, and Michael F. Donovan

Abstract

Chaff is a radar countermeasure typically used by military branches in training exercises around the United States. Chaff within view of the S-band WSR-88D beam can appear prominently on radar users’ displays. Knowledge of chaff characteristics is useful for radar users to discriminate between chaff and weather echoes and for automated algorithms to do the same. The WSR-88D network provides dual-polarimetric capabilities across the United States, leading to the collection of a large database of chaff cases. This database is analyzed to determine the characteristics of chaff in terms of the reflectivity factor and polarimetric variables on large scales. Particular focus is given to the dynamics of differential reflectivity Z DR in chaff and its dependence on height. In contrast to radar observations of chaff for a single event, this study is able to reveal a repeatable and new pattern of radar chaff observations. A discussion about the observed characteristics is presented, and hypotheses for the observed Z DR dynamics are put forth.

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