Susanne Crewell

Accuracy of cloud liquid water path from ground-based microwave radiometry 1. Dependency on cloud model statistics

[1]xa0This paper investigates the influence of cloud model statistics on the accuracy of statistical multiple-frequency liquid water path (LWP) retrievals for a ground-based microwave radiometer. Statistical algorithms were developed from a radiosonde data set in which clouds were modeled by using a relative humidity threshold and a modified adiabatic assumption. Evaluation of the algorithms was then performed by applying the algorithms to four data sets in which clouds were generated in different ways (i.e., threshold method, gradient method, and cloud microphysical model). While classical two-channel algorithms, in this case using frequencies at 22.985 and 28.235 GHz, do not show a significant dependency on the cloud model, the inclusion of an additional 50-GHz channel can introduce significant systematic errors. The addition of a 90-GHz frequency to the two-channel algorithm leads to a larger increase in LWP accuracy than in case of the 50-GHz channel and is less sensitive to the choice of cloud model. A drizzle case from the cloud microphysical model shows no significant loss of accuracy for the microwave radiometer algorithms, in contrast to simple cloud radar retrievals of liquid water. In case of rain, however, the results deteriorate when the total liquid water path is larger than 700 g m−2.

Accuracy of cloud liquid water path from ground‐based microwave radiometry 2. Sensor accuracy and synergy

[1]xa0The influence of microwave radiometer accuracy on retrieved cloud liquid water path (LWP) was investigated. Sensor accuracy was assumed to be the sum of the relative (i.e., Gaussian noise) and the absolute accuracies of brightness temperatures. When statistical algorithms are developed the assumed noise should be as close as possible to the real measurements in order to avoid artifacts in the retrieved LWP distribution. Typical offset errors of 1 K in brightness temperatures can produce mean LWP errors of more than 30 g m−2 for a two-channel radiometer retrieval, although positively correlated brightness temperature offsets in both channels reduce this error to 16 g m−2. Large improvements in LWP retrieval accuracy of about 50% can be achieved by adding a 90-GHz channel to the two-channel retrieval. The inclusion of additional measurements, like cloud base height from a lidar ceilometer and cloud base temperature from an infrared radiometer, is invaluable in detecting cloud free scenes allowing an indirect evaluation of LWP accuracy in clear sky cases. This method was used to evaluate LWP retrieval algorithms based on different gas absorption models. Using two months of measurements, the Liebe 93 model provided the best results when the 90-GHz channel was incorporated into the standard two-channel retrievals.

Accuracy of Boundary Layer Temperature Profiles Retrieved With Multifrequency Multiangle Microwave Radiometry

The potential of a ground-based microwave temperature profiler to combine full tropospheric profiling with high-resolution profiling of the boundary layer is investigated. For that purpose, statistical retrieval algorithms that incorporate observations from different elevation angles and frequencies are derived from long-term radiosonde data. A simulation study shows the potential to significantly improve the retrieval performance in the lowest kilometer by combining angular information from relatively opaque channels with zenith-only information from more transparent channels. Observations by a state-of-the-art radiometer employed during the International Lindenberg campaign for assessment of humidity and cloud profiling systems and its impact on High-resolution modeling (LAUNCH) in Lindenberg, Germany, are used for an experimental evaluation with observations from a 99-m mast and radiosondes. The comparison not only reveals the high accuracy achieved by combining angular and spectral observations (overall, less than 1 K below 1.5 km), but also emphasizes the need for a realistic description of radiometer noise within the algorithm. The capability of the profiler to observe the height and strength of low-level temperature inversions is highlighted.

Profiling Cloud Liquid Water by Combining Active and Passive Microwave Measurements with Cloud Model Statistics

A method for combining ground-based passive microwave radiometer retrievals of integrated liquid water (LWP), radar reflectivity profiles (Z), and statistics of a cloud model is proposed for deriving cloud liquid water profiles (LWC). A dynamic cloud model is used to determine Z–LWC relations and their errors as functions of height above cloud base. The cloud model is also used to develop an LWP algorithm based on simulations of brightness temperatures of a 20–30-GHz radiometer. For the retrieval of LWC, the radar determined Z profile, the passive microwave retrieved LWP, and a model climatology are combined by an inverse error covariance weighting method. Model studies indicate that LWC retrievals with this method result in rms errors that are about 10%–20% smaller in comparison to a conventional LWC algorithm, which constrains the LWC profile exactly to the measured LWP. According to the new algorithm, errors in the range of 30%–60% are to be anticipated when profiling LWC. The algorithm is applied to a time series measurement of a stratocumulus layer at GKSS in Geesthacht, Germany. The GKSS 95-GHz cloud radar, a 20–30-GHz microwave radiometer, and a laser ceilometer were collocated within a 5-m radius and operated continuously during the measurement period. The laser ceilometer was used to confirm the presence of drizzle-sized drops.

Surrogate cloud fields generated with the iterative amplitude adapted Fourier transform algorithm

A new method of generating two-dimensional and three-dimensional cloud fields is presented, which share several important statistical properties with real measured cloud fields.Well-known algorithms such as the Fourier method and the Bounded Cascade method generate fields with a specified Fourier spectrum. The new iterative method allows for the specification of both the power spectrum and the amplitude distribution of the parameter of interest, e.g. the liquid water content or liquid water path. As such, the method is well suited to generate cloud fields based on measured data, and it is able to generate broken cloud fields. Important applications of such cloud fields are e.g. closure studies. The algorithm can be supplied with additional spatial constraints which can reduce the number of measured cases needed for such studies. In this study the suitability of the algorithm for radiative questions is evaluated by comparing the radiative properties of cloud fields from cloud resolving models of cumulus and stratocumulus with their surrogate fields at nadir, and for a solar zenith angle of 0◦ and 60◦. The cumulus surrogate clouds ended up to be identical to the large eddy simulation (LES) clouds on which they are based, except for translations and reflections. The root mean square differences of the stratocumulus transmittance and reflectance fields are less than 0.03% of the radiative budget. The radiances and mean actinic fluxes fit better than 2%. These results demonstrate that these LES clouds are well described from a radiative point of view, using only a power spectrum together with an amplitude distribution.

THE BALTEX BRIDGE CAMPAIGN: An Integrated Approach for a Better Understanding of Clouds

Clouds affect our daily life in many ways. They dominate our perception of weather and, thus, have an enormous influence on our everyday activities and our health. This fact is completely at odds with our knowledge about clouds, their representation in climate and weather forecast models, and our ability to predict clouds. It is their high variability in time and space that makes clouds both hard to monitor and to model. Clouds are the major concern in the climate modeling community, as stated by the Intergovernmental Panel on Climate Change (IPCC; information available online at www.ipcc.ch) x93the most urgent scientific problems requiring attention to determine the rate and magnitude of climate change and sea level rise are the factors controlling the distribution of clouds and their radiative characteristics.x94 A similar conclusion was obtained within the Atmospheric Model Intercomparison Project (AMIP; e.g., Gates et al. 1999). The great challenge of climate research is to correctly account for the fact that the global state of our climate system is largely driven by various small-scale processes and their interaction with each other. Clouds are the most visible examples of this situation. On a global scale, clouds have a strong cooling effect on our climate: more solar radiation is reflected back to space than thermal surface radiation is trapped in the atmosphere. However, because radiation reacts on the instantaneous cloudy atmosphere and not on some climatological mean, the physical processes leading to the overall radiative effect strongly depend on the spatial distribution and structure of clouds.

Advances in Continuously Profiling the Thermodynamic State of the Boundary Layer: Integration of Measurements and Methods

This paper describes advances in ground-based thermodynamic profiling of the lower troposphere through sensor synergy. The well-documented integrated profiling technique (IPT), which uses a microwave profiler, a cloud radar, and a ceilometer to simultaneously retrieve vertical profiles of temperature, humidity, and liquid water content (LWC) of nonprecipitating clouds, is further developed toward an enhanced performance in the boundary layer and lower troposphere. For a more accurate temperature profile, this is accomplished by including an elevation scanning measurement modus of the microwave profiler. Heightdependent RMS accuracies of temperature (humidity) ranging from 0.3 to 0.9 K (0.5–0.8 g m 3 )i n the boundary layer are derived from retrieval simulations and confirmed experimentally with measurements at distinct heights taken during the 2005 International Lindenberg Campaign for Assessment of Humidity and Cloud Profiling Systems and its Impact on High-Resolution Modeling (LAUNCH) of the German Weather Service. Temperature inversions, especially of the lower boundary layer, are captured in a very satisfactory way by using the elevation scanning mode. To improve the quality of liquid water content measurements in clouds the authors incorporate a sophisticated target classification scheme developed within the European cloud observing network CloudNet. It allows the detailed discrimination between different types of backscatterers detected by cloud radar and ceilometer. Finally, to allow IPT application also to drizzling cases, an LWC profiling method is integrated. This technique classifies the detected hydrometeors into three different size classes using certain thresholds determined by radar reflectivity and/or ceilometer extinction profiles. By inclusion into IPT, the retrieved profiles are made consistent with the measurements of the microwave profiler and an LWC a priori profile. Results of IPT application to 13 days of the LAUNCH campaign are analyzed, and the importance of integrated profiling for model evaluation is underlined.

Discrimination of cloud and rain liquid water path by groundbased polarized microwave radiometry

We propose a new approach for groundbased remote sensing of liquid water path (LWP) in the presence of precipitating clouds. Dual polarized groundbased microwave radiometers are capable of detecting the unique scattering signature of nonspherical precipitation sized particles. This polarization signal is only produced by the precipitation particles for which the brightness temperature emission has a different sensitivity to LWP than the smaller cloud drops. By using the information that is contained in the polarization difference of the downwelling brightness temperature the cloud and rain liquid water fractions can be estimated independently. Future retrieval algorithms based on our proposed approach will enable the detection of small precipitation fractions in thick clouds and also allow for estimates of cloud and rain LWP in raining conditions.

Path length distributions for solar photons under cloudy skies : Comparison of measured first and second moments with predictions from classical and anomalous diffusion theories

[1]xa0Using high-resolution oxygen A band spectrometry (λ/Δλ = 60000) in the 767.7–770.7 nm wavelength range, we investigate the first and second moments of the distributions of path lengths of photons in transmitted skylight for different cloud conditions. Our observations are supported by measurements of column liquid water path by multichannel microwave radiometry, cloud structure by millimeter cloud radar observations, and cloud base by a laser ceilometer. For the investigated multilayer cloud covers (decks of stratus, cumulus, altostratus, and cirrus), our measurements indicate that the photon path statistics are mostly governed by anomalous diffusion, whereby classical diffusion occurs in the limiting case of a single compact (plane parallel) cloud layer. The ratio for the inferred second and first moments of the path lengths confirms the relation recently derived by Davis and Marshak (2002) for photon diffusion in single optically thick cloud layers and extends it to more complex cloud geometry.

Assimilation of radar data in mesoscale models: Physical initialization and latent heat nudging

Abstract The increasing availability of quality controlled remotely sensed data (e.g. products from weather radar networks) as well as enhanced computer capacity allows an efficient use of these data in numerical weather prediction (NWP) models. In this paper two different assimilation techniques for radar measurements in mesoscale models are presented: a physical initialization (PI), currently under development at the University of Bonn, and a latent heat nudging (LHN) method implemented at the German Weather Service (DWD). Both algorithms are designed for the non-hydrostatic limited-area model LM (Lokal-Model) of DWD. Input data are standard DWD measurements: national radar composites (reflectivities) and synoptical observations (temperature and dew point). Within the PI scheme the LM profiles of vertical wind, specific water vapor, and cloud water content are adjusted in such a way, that the model reproduces the radar derived precipitation. In the LHN scheme the prognostic variables temperature and specific humidity are changed. In PI and LHN runs with synthetic radar data the life-cycle of a single convective storm was well represented.