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Rolf Fuhrhop and Clemens Simmer

Abstract

The incidence angles of the SSM/I radiometers on the DMSP satellites vary from satellite to satellite and exhibit variations of up to 1.5° during one orbit. The effects of these variations on the measured brightness temperatures are investigated on the basis of simulated and measured data for oceanic arm. A deviation of 1° from the nominal incidence angle of 53.0° causes brightness temperature changes of up to 2 K depending on surface and atmospheric conditions. Errors of retrieved geophysical parameters on the order of 5%–10% result when the incidence angle variation is not taken into account. This is a common property of most published statistical algorithms. For total precipitable water and cloud liquid water content the error increases with increasing parameter value. For wind speed the error is largest for low wind speed and decreases with increasing wind speed. Due to the slowly varying latitudinal dependence of the incidence angle, these errors do not cancel out when monthly means are computed.

A correction method is developed on the basis of simulated data and tested successfully with measured data. Observed brightness temperature differences between DMSP F10 and F11 are reduced when using corrected data. If diurnal variations of geophysical parameters are investigated, the incidence angle correction is mandatory to obtain useful results, especially for DMSP F10.

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Susanne Crewell, Eberhard Ruprecht, and Clemens Simmer

Abstract

Nimbus-7 SMMR data and ship observations are combined to compute the latent heat flux using the bulk aerodynamic method. Sea surface temperature (SST) and the surface humidity are determined with the microwave data. The surface wind field is derived from an analysis of ship observations of wind speed and surface pressure by means of a boundary-layer model by Bumke and Hasse. The microwave-derived SSTs are calibrated against those calculated from Advanced Very High-Resolution Radiometer (AVHRR) data. To get reliable results in the northern parts of the North Atlantic, only ascending (daytime) orbits of Nimbus-7 were used. Daytime data show a larger bias due to solar heating of the instrument but lack the complicating effects of differential cooling when the satellite enters the earth's shadow at the beginning of the descending orbits.

The evaporation fields are derived over the North Atlantic for individual overpasses of the satellite during July 1983, with a spatial resolution of 1° × 1°. High temporal and spatial gradients are observed, which are consistent with the prevailing synoptic situations. In the area south of Greenland and east of Canada, where the Labrador Current is located, latent heat flux (LE) is negative even in the monthly mean. The reliability of the negative values is demonstrated by a case study. They coincide well with ship observations of fog events.

The flux of latent heat can be determined with an acceptable accuracy of 25–40 W m−2 for individual values if the bias of the SMMR data can be reliably removed.

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Quanhua Liu, Clemens Simmer, and Eberhard Ruprecht

Abstract

A neural network is used to calculate the longwave net radiation (L net) at the sea surface from measurements of the Special Sensor Microwave/Imager (SSM/I). The neural network applied in this study is able to account largely for the nonlinearity between L net and the satellite-measured brightness temperatures (TB). The algorithm can be applied for instantaneous measurements over oceanic regions with the area extent of satellite passive microwave observations (30–60 km in diameter). Comparing with a linear regression method the neural network reduces the standard error for L net from 17 to 5 W m−2 when applied to model results. For clear-sky cases, a good agreement with an error of less than 5 W m−2 for L net between calculations from SSM/I observations and pyrgeometer measurements on the German research vessel Poseidon during the International Cirrus Experiment (ICE) 1989 is obtained. For cloudy cases, the comparison is problematic due to the inhomogenities of clouds and the low and different spatial resolutions of the SSM/I data. Global monthly mean values of L net for October 1989 are computed and compared to other sources. Differences are observed among the climatological values from previous studies by H.-J. Isemer and L. Hasse, the climatological values from R. Lindau and L. Hasse, the values of W. L. Darnell et al., and results from this study. Some structures of L net are similar for results from W. L. Darnell et al. and the present authors. The differences between both results are generally less than 15 W m−2. Over the North Atlantic Ocean the authors found a poleward increase for L net, which is contrary to the results of H.-J. Isemer and L. Hasse.

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Ulrich Löhnert, Susanne Crewell, and Clemens Simmer

Abstract

A method is presented for deriving physically consistent profiles of temperature, humidity, and cloud liquid water content. This approach combines a ground-based multichannel microwave radiometer, a cloud radar, a lidar-ceilometer, the nearest operational radiosonde measurement, and ground-level measurements of standard meteorological properties with statistics derived from results of a microphysical cloud model. All measurements are integrated within the framework of optimal estimation to guarantee a retrieved profile with maximum information content. The developed integrated profiling technique (IPT) is applied to synthetic cloud model output as a test of accuracy. It is shown that the liquid water content profiles obtained with the IPT are significantly more accurate than common methods that use the microwave-derived liquid water path to scale the radar reflectivity profile. The IPT is also applied to 2 months of the European Cloud Liquid Water Network (CLIWA-NET) Baltic Sea Experiment (BALTEX) BRIDGE main experiment (BBC) campaign data, considering liquid-phase, nonprecipitating clouds only. Error analysis indicates root-mean-square uncertainties of less than 1 K in temperature and less than 1 g m−3 in humidity, where the relative error in liquid water content ranges from 15% to 25%. A comparison of the vertically integrated humidity profile from the IPT with the nearest operational radiosonde shows an acceptable bias error of 0.13 kg m−2 when the Rosenkranz gas absorption model is used. However, if the Liebe gas absorption model is used, this systematic error increases to −1.24 kg m−2, showing that the IPT humidity retrieval is significantly dependent on the chosen gas absorption model.

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Prabhat K. Koner, Alessandro Battaglia, and Clemens Simmer

Abstract

A dynamic regularization scheme for rain-rate retrievals from attenuated radar measurements is presented. Most regularization techniques, including the optimal estimation method, use the state-space parameters to regularize the problem, which will always lead to a bias in the solution. To avoid this problem the authors introduce an evolutionary regularization technique, which is based on the spatial derivative of the measured reflectivity profile and allows for a bias-free global solution. The regularization strength is determined by the quadratic eigenvalue solution using the regularized total least squares method. With the new method, the authors perform a retrieval of rain-rate profiles from simulated measurements of a nadir-pointing W-band (94 GHz) radar, in a configuration similar to the cloud radar employed on CloudSat. The simulations assume that multiple scattering is negligible and only liquid hydrometeors are taken into account. The authors compare the results of this method with the outcome of an optimal estimation method and demonstrate that their method is superior in terms of reliability, correlation coefficient, and dispersion to the optimal estimation method for layers experiencing high values of attenuation; therefore, the a priori bias typical for optimal estimation solutions is avoided.

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Alessandro Battaglia, Pablo Saavedra, Thomas Rose, and Clemens Simmer

Abstract

A groundbreaking new-concept multiwavelength dual-polarized Advanced Microwave Radiometer for Rain Identification (ADMIRARI) has been built and continuously operated in two field campaigns: the Convective and Orographically Induced Precipitation Study (COPS) and the European Integrated Project on Aerosol Cloud Climate Air Quality Interactions (EUCAARI). The radiometer has 6 channels working in horizontal and vertical polarization at 10.65, 21.0, and 36.5 GHz, and it is completely steerable both in azimuth and in elevation. The instrument is suited to be operated in rainy conditions and is intended for retrieving simultaneously water vapor, rain, and cloud liquid water paths. To this goal the authors implemented a Bayesian retrieval scheme based on many state realizations simulated by the Goddard Cumulus Ensemble model that build up a prior probability density function of rainfall profiles. Detailed three-dimensional radiative transfer calculations, which account for the presence of nonspherical particles in preferential orientation, simulate the downwelling brightness temperatures and establish the similarity of radiative signatures and thus the probability that a given profile is actually observed. Particular attention is devoted to the sensitivity of the ADMIRARI signal to 3D effects, raindrop size distribution, and axial ratio parameterizations. The polarization and multifrequency signals represent key information to separate the effects introduced by non-Rayleigh scatterers and to separate rainwater (r-LWP) from the cloud water component (c-LWP). Long-term observations demonstrate that observed brightness temperatures and polarization differences can be well interpreted and reproduced by the simulated ones for all three channels simultaneously. Rough estimates of r-LWP derived from collocated observations with a micro rain radar confirm the rain/no rain separation and the variability trend of r-LWP provided by the radiometer-based retrieval algorithm. With this work the authors demonstrate the potential of ADMIRARI to retrieve information about the rain/cloud partitioning for midlatitude precipitation systems; future studies with this instrument will provide crucial information on rain efficiency of clouds for cloud modelers that might lead toward a better characterization of rain processes.

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Henning Wilker, Matthias Drusch, Gisela Seuffert, and Clemens Simmer

Abstract

The impact of model and observation errors in the European Land Data Assimilation System (ELDAS) data assimilation system on the analyzed surface variables has been studied using the Southern Great Plains Hydrology Experiment (SGP) 1997 and 1999 datasets. The model error for soil moisture was derived from an error propagation experiment based on perturbed rainfall forcing data. It was found that the errors for the top three model layers are 0.010, 0.010, and 0.0015 m3 m−3, respectively. Data assimilation experiments based on screen-level variables (2-m temperature and humidity) and L-band brightness temperature observations from SGP97 with this error distribution result in improved soil moisture forecasts when compared to model runs with a vertically constant model error of 0.005 m3 m−3. In the second part of this study, the effect of the vertical soil moisture distribution—which can hardly be resolved by large-scale hydrological models—in the assimilation system has been quantified using SGP99 data. The vertical profile has a significant impact on the modeled brightness temperatures. Based on the time elapsed between a rainfall event and the observation, a correction scheme has been developed that can be applied in observation space. The assimilation of brightness temperatures led to more accurate predictions of soil moisture and surface fluxes when the correction scheme was used.

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Alessandro Battaglia, Satoru Kobayashi, Simone Tanelli, Clemens Simmer, and Eastwood Im

Abstract

In this paper, two different numerical methods capable of computing multiple scattering effects in pulsed-radar systems are compared. Both methods are based on the solution of the time-dependent vectorial form of the radiative transfer equation: one exploits the successive order of scattering approximation, the other a forward Monte Carlo technique.

Different benchmark results are presented (including layers of monodisperse spherical water and ice particles), which are of specific interest for W-band spaceborne cloud radars such as CloudSat’s or EarthCARE’s cloud profiling radars. Results demonstrate a good agreement between the two methods. The pros and cons of the two models are discussed, with a particular focus on the validity of the second order of scattering approximation.

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Malte Diederich, Alexander Ryzhkov, Clemens Simmer, Pengfei Zhang, and Silke Trömel

Abstract

In a two-part paper, radar rain-rate retrievals using specific attenuation A suggested by Ryzhkov et al. are thoroughly investigated. Continuous time series of overlapping measurements from two twin polarimetric X-band weather radars in Germany during the summers of 2011–13 are used to analyze various aspects of rain-rate retrieval, including miscalibration correction, mitigation of ground clutter contamination and partial beam blockage (PBB), sensitivity to precipitation characteristics, and the temperature assumptions of the R(A) technique. In this paper, the relations inherent to the R(A) method are used to estimate radar reflectivity Z from A and compare it to the measured Z in order to estimate PBB and calibration offsets for both radars. The fields of Z estimated from A for both radars are consistent, and the differences between Z(A) and measured Z are in good agreement with the ones calculated using either consistency relations between reflectivity at horizontal polarization Z H, differential reflectivity Z DR, and specific differential phase K DP in rain or a digital elevation model in the presence of PBB. In the analysis, the dependence of A on temperature appears to have minimal effects on the overall performance of the method. As expected, the difference between Z(A) and attenuation-corrected measured Z observations varies with rain type and exhibits a weak systematic dependency on rainfall intensity; thus, averaging over several rain events is required to obtain reliable estimates of the Z biases caused by radar miscalibration and PBB.

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Silke Trömel, Clemens Simmer, Jürgen Braun, Thomas Gerstner, and Michael Griebel

Abstract

The central objective of this analysis is to significantly enhance the quality of radar-derived precipitation estimates by as fully as possible exploiting the information contained in the spatial and temporal variability of 3D radar volume data. The results presented are based on pseudoradar data and rain rates of a regional weather forecasting model and 12 true radiosoundings as well. Two approaches are pursued: the first approach estimates total rainfall from an individual storm over its lifetime, whereas the second approach assesses the areawide instantaneous rainfall from a multiplicity of such storms by the use of measurements of the areal coverage of the storms exceeding a threshold radar reflectivity. The concept is extended by adding more predictors to significantly enhance the rainfall estimates. The horizontal expected value and the horizontal standard deviation of enclosed reflectivities at the ground, the mean brightband fraction and its trend, the fractional area with reflectivities exceeding a threshold τ, and an orographic rainfall amplifier provide relative errors smaller than 10% in approximately 75% of the considered rain events in the first approach. In the second approach, a relative error is achieved that is below 10% in approximately 63% elements of the test set.

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