On the Horizontal Scale of Elevation Dependence of Australian Monthly Precipitation

Determination of the scale of the interaction between precipitation and topography is important for the accurate interpolation of rainfall in mountainous areas and also provides insight into the physical processes involved. In this paper, trivariate thin-plate smoothing splines are used to investigate the scale of interaction between monthly precipitation and topography by interpolating monthly rainfall over three subregions of the Australian continent, incorporating different climatic conditions and rainfall types. The interpolations are based upon elevations derived from digital elevation models (DEMs) of various resolutions. All of the DEMs are local averages of version 2.0 of the 9-s-resolution DEM of Australia. The results suggest that the optimal scale of the interaction between precipitation and topography, as it pertains to the elevation-dependent interpolation of monthly precipitation in Australia, is between 5 and 10 km. This is in agreement with results of similar studies that addressed daily precipitation over Switzerland.

A Comparison of the Conservation of Number Concentration for the Continuous Collection and Vapor Diffusion Growth Equations Using One- and Two-Moment Schemes

One- and two-moment parameterizations are integrated over hydrometeor diameters D(0, ∞) for vapor diffusion and the continuous collection growth processes. For the conditions specified, the total number concentration of collector particles should be conserved. To address the problem, the gamma distribution function is used for the spectral density function. Predicted variables can include total mixing ratio q, total number concentration Nt, and characteristic diameter Dn (inverse of the distribution slope λ). In all of the cases, the slope intercept no is diagnosed or specified. The popular one- and two-moment methods that are explored include the one-moment method in which q is predicted, no is specified, and Nt and Dn are diagnosed; the one-moment method in which q is predicted, Dn is specified, and Nt and no are diagnosed; the two-moment method in which q and Dn are predicted and Nt and no are diagnosed; and the two-moment method in which q and Nt are predicted and no and Dn are diagnosed. It is demonstrated for the processes examined that all of the schemes 1) fail to conserve Nt for the collector particles when Nt should be conserved and 2) have other unphysical attributes, except for the two-moment method in which q and Nt are predicted. In recent years there has been a dramatic increase in the use of more-sophisticated microphysical parameterizations in cloud, mesoscale, and climate models, and it is increasingly important for a model user to be cognizant of the strengths and weaknesses of the parameterizations in complex models.

Bulk Scattering Properties for the Remote Sensing of Ice Clouds. Part II: Narrowband Models

This study examines the development of bulk single-scattering properties of ice clouds, including single-scattering albedo, asymmetry factor, and phase function, for a set of 1117 particle size distributions obtained from analysis of the First International Satellite Cloud Climatology Project Regional Experiment (FIRE)-I, FIRE-II, Atmospheric Radiation Measurement Program intensive observation period, Tropical Rainfall Measuring Mission Kwajalein Experiment (KWAJEX), and the Cirrus Regional Study of Tropical Anvils and Cirrus Layers (CRYSTAL) Florida Area Cirrus Experiment (FACE) data. The primary focus is to develop band-averaged models appropriate for use by the Moderate Resolution Imaging Spectroradiometer (MODIS) imager on the Earth Observing System Terra and Aqua platforms, specifically for bands located at wavelengths of 0.65, 1.64, 2.13, and 3.75 μm. The results indicate that there are substantial differences in the bulk scattering properties of ice clouds formed in areas of deep convection and those that exist in areas of much lower updraft velocities. Band-averaged bulk scattering property results obtained from a particle-size-dependent mixture of ice crystal habits are compared with those obtained assuming only solid hexagonal columns. The single-scattering albedo is lower for hexagonal columns than for a habit mixture for the 1.64-, 2.13-, and 3.75-μm bands, with the differences increasing with wavelength. In contrast, the asymmetry factors obtained from the habit mixture and only the solid hexagonal column are most different at 0.65 μm, with the differences decreasing as wavelength increases. At 3.75 μm, the asymmetry factor results from the two habit assumptions are almost indistinguishable. The asymmetry factor, single-scattering albedo, and scattering phase functions are also compared with the MODIS version-1 (V1) models. Differences between the current and V1 models can be traced to the microphysical models and specifically to the number of both the smallest and the largest particles assumed in the size distributions.

A Large-Droplet Mode and Prognostic Number Concentration of Cloud Droplets in the Colorado State University Regional Atmospheric Modeling System (RAMS). Part II: Sensitivity to a Colorado Winter Snowfall Event

This paper is the second in a two-part series describing recent additions to the microphysics module of the Regional Atmospheric Modeling System (RAMS) at Colorado State University. These changes include the addition of a large-cloud-droplet mode (40–80 μm in diameter) into the liquid-droplet spectrum and the parameterization of cloud-droplet nucleation through activation of cloud condensation nuclei (CCN) and giant CCN (GCCN). The large-droplet mode was introduced to represent more precisely the natural dual mode of the cloud-droplet distribution. The parameterized droplet nucleation replaces the former estimation of cloud-droplet formation solely from supersaturation calculations. In Part I of this series, details of the improvements to the microphysics were presented, including the set of equations governing the development of cloud droplets in the Lagrangian parcel model that was employed to parameterize this complex process. Supercell simulations were examined with respect to the model sensitivity to the presence and concentration of large cloud droplets, CCN, and GCCN. Part II examines the sensitivity of the model microphysics to imposed aerosol variations in a wintertime snowfall event that occurred over Colorado on 28–29 February 2004. Model analyses and sensitivity are compared with the real-time forecast version 4.3 of RAMS as well as selected snowpack telemetry (SNOTEL) accumulated precipitation data and surface data from Storm Peak Laboratory in Steamboat Springs, Colorado.

Bulk Scattering Properties for the Remote Sensing of Ice Clouds. Part I: Microphysical Data and Models

This study reports on the use of in situ data obtained in midlatitude and tropical ice clouds from airborne sampling probes and balloon-borne replicators as the basis for the development of bulk scattering models for use in satellite remote sensing applications. Airborne sampling instrumentation includes the two-dimensional cloud (2D-C), two-dimensional precipitation (2D-P), high-volume precipitation spectrometer (HVPS), cloud particle imager (CPI), and NCAR video ice particle sampler (VIPS) probes. Herein the development of a comprehensive set of microphysical models based on in situ measurements of particle size distributions (PSDs) is discussed. Two parameters are developed and examined: ice water content (IWC) and median mass diameter Dm. Comparisons are provided between the IWC and Dm values derived from in situ measurements obtained during a series of field campaigns held in the midlatitude and tropical regions and those calculated from a set of modeled ice particles used for light-scattering calculations. The ice particle types considered in this study include droxtals, hexagonal plates, solid columns, hollow columns, aggregates, and 3D bullet rosettes. It is shown that no single habit accurately replicates the derived IWC and Dm values, but a mixture of habits can significantly improve the comparison of these bulk microphysical properties. In addition, the relationship between Dm and the effective particle size Deff, defined as 1.5 times the ratio of ice particle volume to projected area for a given PSD, is investigated. Based on these results, a subset of microphysical models is chosen as the basis for the development of ice cloud bulk scattering models in Part II of this study.

Relationships between the Irrigation-Pumping Electrical Loads and the Local Climate in Climate Division 9, Idaho

The electrical load from irrigation pumps is an important part of the overall electricity demand in many agricultural areas of the U.S. west. The date the pumps turn on and the total electrical load they present over the summer varies from year to year, partly because of climate fluctuations. Predicting this variability would be useful to electricity producers that supply the region. This work presents a contingency analysis and linear regression scheme for forecasting summertime irrigation pump loads in southeastern Idaho. The basis of the predictability is the persistence of spring soil moisture conditions into summer, and the effect it has on summer temperatures. There is a strong contemporaneous relationship between soil moisture and temperature in the summer and total summer pump electrical loads so that a reasonable prediction of summer pump electrical loads based on spring soil moisture conditions can be obtained in the region. If one assumes that decision makers will take appropriate actions based on the forecast output, the net economic benefit of forecast information is approximately $2.5 million per year, making this prediction problem an important seasonal summer forecasting issue with significant economic implications.

On the Vertical Structure of Modeled and Observed Deep Convective Storms: Insights for Precipitation Retrieval and Microphysical Parameterization

An understanding of the vertical structure of clouds is important for remote sensing of precipitation from space and for the parameterization of cloud microphysics in numerical weather prediction (NWP) models. The representation of cloud hydrometeor profiles in high-resolution NWP models has direct applications in inversion-type precipitation retrieval algorithms [e.g., the Goddard profiling (GPROF) algorithm used for retrieval of precipitation from passive microwave sensors] and in quantitative precipitation forecasting. This study seeks to understand how the vertical structure of hydrometeors (liquid and frozen water droplets in a cloud) produced by high-resolution NWP models with explicit microphysics, henceforth referred to as cloud-resolving models (CRMs), compares to observations. Although direct observations of 3D hydrometeor fields are not available, comparisons of modeled and observed radar echoes can provide some insight into the vertical structure of hydrometeors and, in turn, into the ability of CRMs to produce precipitation structures that are consistent with observations. Significant differences are revealed between the vertical structure of observed and modeled clouds of a severe midlatitude storm over Texas for which the surface precipitation is reasonably well captured. Possible reasons for this discrepancy are presented, and the need for future research is highlighted.

Interannual Variability of Water Demand and Summer Climate in Albuquerque, New Mexico

The effects of interannual climate variability on water demand in Albuquerque, New Mexico, are assessed. This city provides an ideal setting for examining the effects of climate on urban water demand, because at present the municipal water supply is derived entirely from groundwater, making supply insensitive to short-term climate variability. There is little correlation between interannual variability of climate and total water demand—a result that is consistent with several previous studies. However, summertime residential demand, which composes about one-quarter of total annual demand in Albuquerque, is significantly correlated with summer-season precipitation and average daily maximum temperature. Furthermore, regressions derived from year-to-year changes in these variables are shown to isolate the climatic modulation of residential water demand effectively. Over 60% of the variance of year-to-year changes in summer residential demand is accounted for by interannual temperature and precipitation changes when using a straightforward linear regression model, with precipitation being the primary correlate. Long-term trends in water demand follow population growth closely until 1994, after which time a major water conservation effort led to absolute decreases in demand in subsequent years. The effectiveness of the conservation efforts can be quantified by applying the regression model, thus removing the year-to-year variations associated with short-term climate fluctuations estimated from the preconservation period. The preconservation regression provides a good fit to interannual summer residential demand in subsequent years, demonstrating that the regression model has successfully isolated the climatic component of water demand. The quality of this fit during a period of sharply reduced demand suggests that the conservation program has effectively targeted the nonclimatically sensitive component of water demand and has sharpened the climatically sensitive component of demand to a level closer to the consumption that is “climatically needed.”

Simple Empirical Models for Estimating the Increase in the Central Pressure of Tropical Cyclones after Landfall along the Coastline of the United States

Modeling the increase in the central pressure of tropical cyclones following landfall plays a critical role in the estimation of the hurricane wind hazard at locations removed from the coastline. This paper describes the development of simple empirical models for estimating the rate at which tropical cyclones decay after making landfall. For storms making landfall along the Gulf of Mexico Coast and the coast of the Florida Peninsula, it is shown that the rate of storm filling is proportional to the central pressure difference and translation speed at the time of landfall and is inversely proportional to the radius to maximum winds. Along the Atlantic Coast the effect of radius to maximum winds does not play as significant a role in the rate of storm decay as compared with that seen in Florida and along the Gulf Coast. The models developed here can readily be included in any hurricane simulation model designed for estimating wind speeds in the United States.

Profiles of Raindrop Size Distributions as Retrieved by Microrain Radars

Data of vertically pointing microrain radars (MRRs), located at various sites around the Baltic Sea, were analyzed for a period of several years. From the Doppler spectra profiles of drop size distributions (DSDs) are obtained. A significant height dependence of the shape of the DSDs—and thus of the Z–R relations—is observed at high rain rates. This implies, for the considered sites, that ground-based Z–R relations lead to underestimation of high rain rates by weather radars.