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Global measurements of horizontal winds in cloud and precipitating systems represent a gap in the global observing system. The WIVERN mission, one of the four candidates to be the ESA's Earth Explorer 11 mission, aims at filling this gap based on a conically scanning W-band Doppler radar instrument. The determination of the antenna boresight mispointing angles and the impact of their uncertainty on the line of sight velocities is critical to achieve the mission requirements. While substantial industrial efforts are on their ways for achieving accurate determination of the pointing, alternative (external) calibration approaches are currently under scrutiny. This work discusses four methods applicable to the WIVERN radar that can be used to correct antenna mispointing both in the azimuthal and in the elevation directions at different time scales. Results show that elevation mispointing is well corrected at very short time scales by monitoring the range at which the surface peak occurs. Azimuthal mispointing is harder but can be tackled by using the expected profiles of the non-moving surface Doppler. Biases in pointing at longer time scales can be monitored by using well established reference database (e.g. ECMWF reanalysis) or ad-hoc ground based calibrators. Although tailored to the WIVERN mission, the proposed methodologies can be extended to other Doppler concepts featuring conically scanning or slant viewing Doppler systems. [ABSTRACT FROM AUTHOR]

The planned and potential introduction in the global satellite observing systems of conically scanning Ka and W band atmospheric radars [e.g. the radars in the Tomorrow.IO constellation, https://www.tomorrow.io/space/, and the Wivern (WInd VElocity Radar Nephoscope) radar, www.wivern.polito.it] calls for the development of methodologies for calibrating and cross-calibrating these systems. Traditional calibration techniques pointing at the sea surface at about 12? incidence angle are in fact unfeasible for such fast rotating systems. This study proposes a cross-calibration method for conically scanning spaceborne radars based on ice cloud reflectivity probability distribution functions (PDF) provided by reference radars like the GPM Ka-band radar or theW-band radars planned for the ESA-JAXA EarthCARE or for the NASA Atmosphere Observing System missions. In order to establish the accuracy of the methodology, radar antenna boresight positions are propagated based on four configurations of expected satellite orbits so that the ground-track intersections can be calculated for different intersection criteria, defined by cross-over instrument footprints within a certain time and a given distance. The climatology of the calibrating clouds, derived from the W-band CloudSat and Ka-band GPM reflectivity records, can be used to compute the number and the spatial distribution of calibration points. Finally, the mean number of days required to achieve a given calibration accuracy is computed based on the number of calibration points needed to distinguish a biased reflectivity PDF from the sampling-induced noisiness of the reflectivity PDFitself. Findings demonstrate that it will be possible to cross-calibrate within 1 dB a Ka-band (W-band) conically scanning radar like that envisaged for the Tomorrow.io constellation (Wivern mission) every few days (a week). Such uncertainties are generally meeting the mission requirements and the standards currently achieved with absolute calibration accuracy. [ABSTRACT FROM AUTHOR]

A new method of accurately calculating the capacitance of realistic ice particles is described: such values are key to accurate estimates of deposition and evaporation (sublimation) rates in numerical weather models. The trajectories of diffusing water molecules are directly sampled, using random 'walkers.' By counting how many of these trajectories intersect the surface of the ice particle (which may be any shape) and how many escape outside a spherical boundary far from the particle, the capacitances of a number of model ice particle habits have been estimated, including hexagonal columns and plates, 'scalene' columns and plates, bullets, bullet rosettes, dendrites, and realistic aggregate snowflakes. For ice particles with sharp edges and corners this method is an efficient and straightforward way of solving Laplace's equation for the capacitance. Provided that a large enough number of random walkers are used to sample the particle geometry (~[10.sup.4]) the authors expect the calculated capacitances to be accurate to within -1%. The capacitance for the modeled aggregate snowflakes (C/[D.sub.max] = 0.25, normalized by the maximum dimension [D.sub.max]) is shown to be in close agreement with recent aircraft measurements of snowflake sublimation rates. This result shows that the capacitance of a sphere (C/[D.sub.max] = 0.5), which is commonly used in numerical models, overestimates the evaporation rate of snowflakes by a factor of 2. The effect of vapor 'screening' by crystals growing in the vicinity of one another has also been investigated. The results clearly show that neighboring crystals growing on a filament in cloud chamber experiments can strongly constrict the vapor supply to one another, and the resulting growth rate measurements may severely underestimate the rate for a single crystal in isolation (by a factor of 3 in this model setup).

This two-part study addresses the development of reliable estimates of the mass and fall speed of single ice particles and ensembles. Part I of the study reports temperature-dependent coefficients for the mass-dimensional relationship, m = a[D.sup.b], where D is particle maximum dimension. The fall velocity relationship, [V.sub.1] = [AD.sub.B], is developed from observations in synoptic and low-latitude, convectively generated, ice cloud layers, sampled over a wide range of temperatures using an assumed range for the exponent b. Values for a, A, and B were found that were consistent with the measured particle size distributions (PSD) and the ice water content (IWC). To refine the estimates of coefficients a and b to fit both lower and higher moments of the PSD and the associated values for A and B, Part II uses the PSD from Part I plus coincident, vertically pointing Doppler radar returns. The observations and derived coefficients are used to evaluate earlier, single-moment, bulk ice microphysical parameterization schemes as well as to develop improved, statistically based, microphysical relationships. They may be used in cloud and climate models, and to retrieve cloud properties from ground-based Doppler radar and spaceborne, conventional radar returns.

Most current general circulation models (GCMs) calculate radiative fluxes through partially cloudy grid boxes by weighting clear and cloudy fluxes by the fractional area of cloud cover ([C.sub.a]), but most GCM cloud schemes calculate cloud fraction as the volume of the grid box that is filled with cloud ([C.sub.v]). In this paper, 1 yr of cloud radar and lidar observations from Chilbolton in southern England, are used to examine this discrepancy. With a vertical resolution of 300 m it is found that, on average, [C.sub.a] is 20% greater than [C.sub.v], and with a vertical resolution of 1 km, [C.sub.a] is greater than [C.sub.v] by a factor of 2. The difference is around a factor of 2 larger for liquid water clouds than for ice clouds, and also increases with wind shear. Using [C.sub.a] rather than [C.sub.v], calculated on an operational model grid, increases the mean total cloud cover from 53% to 63%. and so is of similar importance to the cloud overlap assumption. A simple parameterization, [C.sub.a] = [1 + [e.sup.(-f) ([[C.sup.-1.sub.v])].sup.-1], is proposed to correct for this underestimate based on the observation that the observed relationship between the mean [C.sub.a] and [C.sub.v] is symmetric about the line [C.sub.a] = 1 - [C.sub.v]. The parameter f is a simple function of the horizontal (H) and vertical (V) grid-box dimensions, where for ice clouds f = 0.0880 [V.sup.0.7696] [H.sup.-0.2254] and for liquid clouds f = 0.1635 [V.sup.0.6694] [H.sup.-0.1882]. Implementing this simple parameterization, which excludes the effect of wind shear, on an independent 6-month dataset of cloud radar and lidar observations, accounts for the mean underestimate of [C.sub.a] for all horizontal and vertical resolutions considered to within 3% of the observed [C.sub.a], and reduces the rms error for each individual box from typically 100% to approximately 30%. Small biases remain for both weakly and strongly sheared cases, but this is significantly reduced by incorporating a simple shear dependence in the calculation of the parameter f. which also slightly improves the overall performance of the parameterization for all of the resolutions considered.

Stratocumulus is one of the most common cloud types globally, with a profound effect on the earth's radiation budget, and the drizzle process is fundamental in understanding the evolution of these boundary layer clouds. In this paper a combination of 94-GHz Doppler radar and backscatter lidar is used to investigate the microphysical properties of drizzle falling below the base of stratocumulus clouds. The ratio of the radar to lidar backscatter power is proportional to the fourth power of mean size, and so potentially it can provide an accurate size estimate. Information about the shape of the drop size distribution is then inferred from the Doppler spectral width. The algorithm estimates vertical profiles of drizzle parameters such as liquid water content, liquid water flux, and vertical air velocity, assuming that the drizzle size spectrum may be represented by a gamma distribution. The depletion time scale of cloud liquid water through the drizzle process can be estimated when the liquid water path of the cloud is available from microwave radiometers, and observations suggest that this time scale varies from a few days in light drizzle to a few hours in strong drizzle events. Radar and lidar observations from Chilbolton (in southern England) and aircraft size spectra taken during the Atlantic Stratocumulus Transition Experiment have both been used to derive the following power-law relationship between liquid water flux (LWF) (g [m.sup.-2] [s.sup.-1]) and radar reflectivity (Z) ([mm.sup.6] [m.sup.-3]): LWF = 0.0093[Z.sup.0.69]. (This relation is valid for frequencies up to 94 GHz and therefore would allow a forthcoming spaceborne radar to measure liquid water flux around the globe to within a factor of 2 for values of Z above -20 dBZ.

Cloud variability on scales smaller than the gridbox size of numerical forecast and climate models is believed to be important in determining the radiative effects of clouds, and increasingly attempts are being made to parameterize these fluctuations in the radiation schemes of current models. In order to calculate the radiative effects of an inhomogeneous cloud, a model needs to know not only the degree of variability within a gridbox but also the degree to which the inhomogeneities in vertically adjacent levels are overlapped. In this paper these two parameters are derived for ice clouds from an 18-month midlatitude 94-GHz cloud radar dataset and parameterized in terms of horizontal gridbox size (d), the vertical shear of the horizontal wind (s), and the vertical position in the cloud. The vertical decorrelation length [DELTA][Z.sub.0] (i.e., the depth over which the correlation coefficient of either ice water content or optical extinction coefficient in separate vertical levels falls to [e.sup.-1]) is found to be well represented in the mean by [log.sub.10][DELTA][Z.sub.0] = 0.3 [log.sub.10]d - 0.031s - 0.315, where [DELTA][Z.sub.0] and d are in kilometers and s is in meters per second per kilometer. As expected, higher shear results in more rapid decorrelation, although the rms deviation from this expression is around a factor of 2.5. It is found that the probability distribution of ice water content within a gridbox is usually well represented by a lognormal or gamma distribution. The fractional variance in ice water content ([f.sub.IWC]) may be expressed to within a factor of 2 by [log.sub.10] [f.sub.IWC] = 0.3 [log.sub.10]d - 0.04s - 0.93, valid for d < 60 km, above which [f.sub.IWC] is constant with increasing d. The expression for the fractional variance of visible extinction coefficient is the same except with the -0.93 term replaced by -0.96. The s dependence indicates a tendency for increased shear to result in decreased cloud variability. This can be explained by the presence of ice fallstreaks in a sheared flow: a parcel of air in the middle of a cloud is alternately fed from above by ice-rich and ice-poor air, resulting in a homogenization of the layer at a rate dependent on the shear. A more complicated formula is derived to express the dependence of [f.sub.IWC] on the vertical position within the cloud; it is found that fractional variance tends to be largest at cloud top and decreases into the interior before increasing again in the lowest third of the cloud. Thicker clouds tend to have lower fractional variance. No significant dependence on temperature or absolute altitude was found for either [f.sub.IWC] or [DELTA][Z.sub.0].

CloudSat is a satellite experiment designed to measure the vertical structure of clouds from space. The expected launch of CloudSat is planned for 2004, and once launched, CloudSat will orbit in formation as part of a constellation of satellites (the A-Train) that includes NASA's Aqua and Aura satellites, a NASA-CNES lidar satellite (CALIPSO), and a CNES satellite carrying a polarimeter (PARASOL). A unique feature that CloudSat brings to this constellation is the ability to fly a precise orbit enabling the fields of view of the CloudSat radar to be overlapped with the CALIPSO lidar footprint and the other measurements of the constellation. The precision and near simultaneity of this overlap creates a unique multisatellite observing system for studying the atmospheric processes essential to the hydrological cycle. The vertical profiles of cloud properties provided by CloudSat on the global scale fill a critical gap in the investigation of feedback mechanisms linking clouds to climate. Measuring these profiles requires a combination of active and passive instruments, and this will be achieved by combining the radar data of CloudSat with data from other active and passive sensors of the constellation. This paper describes the underpinning science and general overview of the mission, provides some idea of the expected products and anticipated application of these products, and the potential capability of the A-Train for cloud observations. Notably, the CloudSat mission is expected to stimulate new areas of research on clouds. The mission also provides an important opportunity to demonstrate active sensor technology for future scientific and tactical applications. The CloudSat mission is a partnership between NASA's JPL, the Canadian Space Agency, Colorado State University, the U.S. Air Force, and the U.S. Department of Energy. (Page 1771)

The atmospheric boundary layer (ABL) height defines the volume of air within which heat, moisture and pollutants released at the Earth's surface are rapidly diluted. Despite the importance for air quality interpretation, numerical weather prediction, greenhouse gas assessment and renewable energy applications, amongst others, quantitative knowledge on the temporal and spatial variation in ABL height is still scarce. With continuous profiling of the entire ABL vertical extent at high temporal and vertical resolution now increasingly possible due to recent advances in ground-based remote sensingmeasurement technology and algorithm development, there are also dense measurement networks emerging across Europe and other parts of the world. To effectively monitor the spatial and temporal evolution of the ABL continuously at continent-scale, harmonised operations and data processing are key. Autonomous ground-based remote sensing instruments, such as microwave radiometers, radar wind profilers, Doppler wind lidars or automatic lidars and ceilometers, each offer different capabilities. The overarching objective of this review is to emphasize how these instruments are best exploited with informed network design, algorithm implementation, and data interpretation. A summary of the capability and limitations of each instrument type is provided together with a review of the vast number of retrieval methods developed for ABL height detection from different atmospheric quantities (temperature, humidity, wind, turbulence, aerosol). It is outlined how the diurnal evolution of the ABL can be monitored effectively with a combination of methods, highlighting where instrument or methodological synergy promise to be particularly valuable. To demonstrate the vast potential of increased ABL monitoring efforts, long-term observational studies are reviewed summarising our current understanding of ABL height variations. The review emphasizes that harmonised data acquisition and careful data processing are key to obtaining high-quality products, which are essential to capture the spatial and temporal complexity of the lowest part of the atmosphere in which we live and breathe. [ABSTRACT FROM AUTHOR]

The WIVERN (WInd VElocity Radar Nephoscope) mission, soon entering in Phase-0 of the ESA Earth Explorer program, promises to complement Doppler wind lidar by globally observing, for the first time, vertical profiles of winds in cloudy areas. This work describes an end to end simulator of the WIVERN conically scanning 94 GHz Doppler radar, the only payload of the mission. Specific features of the simulator are: the conically scanning geometry; the inclusion of cross-polarization effects and of the simulation of a radiometric mode; the applicability to global cloud model outputs via an orbital model; the incorporation of a mispointing model accounting for thermo-elastic distortions, microvibrations, star-trackers uncertainties, etc.; the inclusion of the surface clutter. Some of the simulator capabilities are showcased for a case study involving a full rotational scan of the instrument. The simulator represents a very useful tool for studying the performances of the WIVERN concept and possible trade-offs for the different configurations (e.g. different antenna sizes, pulse lengths, antenna patterns, .....). Thanks to its modular structure the simulator can be easily adapted to different orbits, different scanning geometries and different frequencies. [ABSTRACT FROM AUTHOR]

A workshop on weather radar polarimetry for research and operational applications was held on 22 and 23 February 1994 at the National Center for Atmospheric Research. Polarization radar can provide estimates of the shapes, sizes, phase, and fall orientations of hydrometeors. This information can be used to remove some of the ambiguities present when only the reflectivity is measured. The morning of 22 February was devoted to 16 short presentations highlighting recent advances in polarimetric radar. The afternoon was dedicated to four discussion sessions that further developed important topics. On the following day, plans for the upgrading and development of the existing NCAR polarization radar capability were presented and debated. The workshop resulted in four recommendations: three of which proposed specific field measurement programs to quantify the potential improvements provided by the polarization techniques.