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Shixuan Pang and Hartmut Graßl

Abstract

A high-frequency Doppler sodar for precipitation measurements has been developed. Such a Doppler sodar (6–20 kHz) can almost always measure precipitation and turbulence spectra simultaneously. Therefore, the mean vertical wind and spectral broadening effects can be directly removed. As the acoustic refractive indices for ice and liquid water are almost the same, the acoustic retrieval of precipitation can also be applied to rain with small hail (e.g., diameter D < 10 mm) or large hail, but for the latter, neglecting the effects of different orientations and shapes of hailstones.

The authors’ single-board minisodar is based on the digital signal processing (DSP) technique. The first prototype has been continuously operated at a coastal weather station since 25 October 2002. For stratiform rain events, the minisodar showed good agreement with a Joss–Waldvogel disdrometer and an optical rain gauge. However, for convective heavy showers, the minisodar always observed higher rain rates.

The continuous, nonattended automatic operation of the minisodar has shown its capability for all kinds of precipitation measurements. The retrieval of precipitation rates for snow and graupel will be provided in a subsequent paper.

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Shixuan Pang, Hartmut Graßl, and Horst Jäger

Abstract

A common feature of all capacitance humidity sensors is their undesirable hysteresis effect due to the unequal adsorption and desorption of water vapor on the surfaces of their dielectric porous materials. To eliminate this error, an improved humidity sensor has been used composed of a commercial capacitive polymer sensor chip and an infrared (IR) radiation corrector emitting at a wavelength of 0.93 µm. The IR photons excite water molecule vibrations and destroy the bonds between water vapor and the material surface molecules, thus reducing residual hysteresis. Linearity is also improved, drift at high humidity is diminished, and response time is decreased.

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Christian-Philipp Klepp, Stephan Bakan, and Hartmut Graßl

Abstract

Case studies of rainfall, derived from Special Sensor Microwave Imager (SSM/I) satellite data during the passage of individual cyclones over the North Atlantic, are presented to enhance the knowledge of rainfall processes associated with frontal systems. A multisatellite method is applied for complete coverage of the North Atlantic twice a day. Different SSM/I precipitation algorithms have been tested for individual cyclones and compared to the Global Precipitation Climatology Project (GPCP) datasets. An independent rainfall pattern and intensity validation method is presented using voluntary observing ship (VOS) datasets and Advanced Very High Resolution Radiometer (AVHRR) images.

Intense cyclones occur frequently in the wintertime period, with cold fronts propagating far south over the North Atlantic. Following upstream, large cloud clusters are frequently embedded in the cellular structured cold air of the backside regions, which produce heavy convective rainfall events, especially in the region off Newfoundland around 50°N. These storms can be easily identified on AVHRR images. It transpired that only the SSM/I rainfall algorithm of Bauer and Schlüssel is sensitive enough to detect the rainfall patterns and intensities observed by VOS for those cyclone types over the North Atlantic. In contrast, the GPCP products do not recognize this backside rainfall, whereas the frontal rainfall conditions are well represented in all tested datasets. This is suggested from the results of an intensive intercomparison study with ship reports from the time period of the Fronts and Atlantic Storm Track Experiment (FASTEX) field campaign. For this purpose, a new technique has been developed to transfer ship report codes into rain-rate estimates. From the analysis of a complete life cycle of a cyclone, it follows that these mesoscale backside rainfall events contribute up to 25% to the total amount of rainfall in North Atlantic cyclones.

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Dan Lubin, David Cutchin, William Conant, Hartmut Grassl, Ulrich Schmid, and Werner Biselli

Abstract

Longwave emission by the tropical western Pacific atmosphere has been measured at the ocean surface by a Fourier Transform Infrared (FTIR) spectroradiometer deployed aboard the research vessel John Vickers as part of the Central Equatorial Pacific Experiment. The instrument operated throughout a Pacific Ocean crossing, beginning on 7 March 1993 in Honiara. Solomon Islands, and ending on 29 March 1993 in Los Angeles, and recorded longwave emission spectra under atmospheres associated with sea surface temperatures ranging from 291.0 to 302.8 K. Precipitable water vapor abundances ranged from 1.9 to 5.5 column centimeters. Measured emission spectra (downwelling zenith radiance) covered the middle infrared (5–20, μm) with one inverse centimeter spectral resolution. FTIR measurements made under an entirely clear field of view are compared with spectra generated by LOWTRAN 7 and MODTRAN 2, as well as downwelling flux calculated by the NCAR Community Climate Model (CCM-2) radiation code, using radiosonde profiles as input data for these calculations.

In the spectral interval 800–1000 cm−1, these comparisons show a discrepancy between FTIR data and MODTRAN 2 having an overall variability of 6–7 mW m−2 sr−1 cm and a concave shape that may be related to the representation of water vapor continuum emission in MODTRAN 2. Another discrepancy appears in the spectral interval 1200–1300 cm−1, where MODTRAN 2 appears to overestimate zenith radiance by 5 mW m−2 sr−1 cm. These discrepancies appear consistently; however, they become only slightly larger at the highest water vapor abundances. Because these radiance discrepancies correspond to broadband (500–2000 cm−1) flux uncertainties of around 3 W m−2, there appear to be no serious inadequacies with the performance of MODTRAN 2 or LOWTRAN 7 at high atmospheric temperatures and water vapor abundances. On average, CCM-2 flux calculations agree to within 1 W m−2 with downwelling flux estimates from the FTIR data over all sea surface temperatures, although this result has a scatter Of ±12 W m−2 at high sea surface temperatures.

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Axel Andersson, Christian Klepp, Karsten Fennig, Stephan Bakan, Hartmut Grassl, and Jörg Schulz

Abstract

Today, latent heat flux and precipitation over the global ocean surface can be determined from microwave satellite data as a basis for estimating the related fields of the ocean surface freshwater flux. The Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data (HOAPS) is the only generally available satellite-based dataset with consistently derived global fields of both evaporation and precipitation and hence of freshwater flux for the period 1987–2005. This paper presents a comparison of the evaporation E, precipitation P, and the resulting freshwater flux EP in HOAPS with recently available reference datasets from reanalysis and other satellite observation projects as well as in situ ship measurements. In addition, the humidity and wind speed input parameters for the evaporation are examined to identify sources for differences between the datasets. Results show that the general climatological patterns are reproduced by all datasets. Global mean time series often agree within about 10% of the individual products, while locally larger deviations may be found for all parameters. HOAPS often agrees better with the other satellite-derived datasets than with the in situ or the reanalysis data. The agreement usually improves in regions of good in situ sampling statistics. The biggest deviations of the evaporation parameter result from differences in the near-surface humidity estimates. The precipitation datasets exhibit large differences in highly variable regimes with the largest absolute differences in the ITCZ and the largest relative biases in the extratropical storm-track regions. The resulting freshwater flux estimates exhibit distinct differences in terms of global averages as well as regional biases. In comparison with long-term mean global river runoff data, the ocean surface freshwater balance is not closed by any of the compared fields. The datasets exhibit a positive bias in EP of 0.2–0.5 mm day−1, which is on the order of 10% of the evaporation and precipitation estimates.

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Martin Weil, Hartmut Grassl, Gholamali Hoshyaripour, Silvia Kloster, Jasmin Kominek, Stergios Misios, Juergen Scheffran, Steven Starr, Georgiy Stenchikov, Natalia Sudarchikova, Claudia Timmreck, Dan Zhang, and Martin Kalinowski
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