U. Löhnert

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.

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.

Cloud remote sensing by combining synergetic sensor information

Abstract The accurate determination of the cloud liquid water (LWC) profile from one single remote sensing instrument is not possible. We present a technique, which allows the merging of measurements from different instruments. Additionally, the method can take into account climatological (virtual) information of cloud microphysics. The method is applied to measurements from a cloud radar and a 2-channel passive microwave radiometer. With the EU-project CLIWA-NET, which aims at the determination of highly accurate fields of the liquid water path (LWP) from a combination of ground-based stations and satellite measurements, more detailed input will be available for our method. Example measurements from a Pre-CLIWA-NET campaign are presented to demonstrate the potential of the upcoming CLIWA-NET campaigns, which will lead to long-term statistics of the LWC profile.

A ground based multi-sensor system for the remote sensing of clouds

Abstract A ground based system combining active and passive remote sensing instruments from different spectral ranges has been set up at the Meteorological Institute in Bonne to investigate cloud processes. Currently, the sensor package includes a laser ceilometer, an infrared radiometer, an X-Band Radar, and a 4-channel microwave radiometer. Cloud base height and temperature, precipitation, and the integrated quantities of water vapor and cloud liquid water can be measured on small time scales (≤ 15 s). The system will be extended in fall 1998 with a 22-channel microwave to derive profiles of humidity, temperature and liquid water content. A case study using measurements from April 1, 1998 demonstrates the ability of the system to characterize various types of clouds.

A novel microwave radiometer for assessment of atmospheric propagation conditions for 10 and 90 GHz frequency bands

In order to quantify atmospheric perturbations on satellite signals a new ground based ultra stable microwave radiometer is developed. In addition to several K- and V-band channels two further Ku- and W-band channels are implemented. This frequency combination provides sensitivity towards atmospheric water vapour and oxygen, as well as to rain and cloud droplets. To perform high stable measurements, the radiometer is equipped by a continuous calibration method using a Dicke switch and a noise diode. This yields to radiometer stability for integration times up to 2000 seconds.