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Volker Wulfmeyer, Oliver Branch, Kirsten Warrach-Sagi, Hans-Stefan Bauer, Thomas Schwitalla, and Klaus Becker

Abstract

Recent advances in technology permit the irrigation of dry, coastal areas, avoiding the use of fossil water and conflicts with other land use (e.g., for food production). Consequently, it becomes reasonable to consider large-scale plantations for mitigating increases in atmospheric concentrations by carbon sequestration and to study local modifications of weather and climate. This work investigates the impact of plantations in Oman and the Sonora Desert in Mexico assuming an area of about 100 km × 100 km. For this purpose, an advanced land surface–atmosphere model was adapted to the local changes of land cover and operated on the convection-permitting scale. Explicit simulations of the impact of the plantation on soil–vegetation–atmosphere feedback were performed for a duration of 1 yr. A strong modification of diurnal cycles of variables such as surface fluxes, temperature, and boundary layer depth was found. Over the plantations, the mean temperature decreased as a result of nonlinear changes of the diurnal cycle caused by less warming during the day than cooling during the night. Moreover, the plantations caused an increase in vertical instability and a modification of the horizontal flow leading to the development of convergence zones. During several isolated cases in summer, this process led to convection initiation and precipitation with an enhancement of about 30 mm in both areas, respectively. These convection-permitting simulations lend confidence that an increase in precipitation could be induced at the mesoscale by the introduction of vegetation in desert regions. Furthermore, this effect should be included in a quantitative assessment of climate engineering by afforestation.

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Volker Wulfmeyer, Hans-Stefan Bauer, Matthias Grzeschik, Andreas Behrendt, Francois Vandenberghe, Edward V. Browell, Syed Ismail, and Richard A. Ferrare

Abstract

Four-dimensional variational assimilation of water vapor differential absorption lidar (DIAL) data has been applied for investigating their impact on the initial water field for mesoscale weather forecasting. A case that was observed during the International H2O Project (IHOP_2002) has been selected. During 24 May 2002, data from the NASA Lidar Atmospheric Sensing Experiment were available upstream of a convective system that formed later along the dryline and a cold front. Tools were developed for routinely assimilating water vapor DIAL data into the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5). The results demonstrate a large impact on the initial water vapor field. This is due to the high resolution and accuracy of DIAL data making the observation of the high spatial variability of humidity in the region of the dryline and of the cold front possible. The water vapor field is mainly adjusted by a modification of the atmospheric wind field changing the moisture transport. A positive impact of the improved initial fields on the spatial/temporal prediction of convective initiation is visible. The results demonstrate the high value of accurate, vertically resolved mesoscale water vapor observations and advanced data assimilation systems for short-range weather forecasting.

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Andreas Behrendt, Volker Wulfmeyer, Thorsten Schaberl, Hans-Stefan Bauer, Christoph Kiemle, Gerhard Ehret, Cyrille Flamant, Susan Kooi, Syed Ismail, Richard Ferrare, Edward V. Browell, and David N. Whiteman

Abstract

The dataset of the International H2O Project (IHOP_2002) gives the first opportunity for direct intercomparisons of airborne water vapor lidar systems and allows very important conclusions to be drawn for future field campaigns. Three airborne differential absorption lidar (DIAL) systems were operated simultaneously during some IHOP_2002 missions: the DIAL of Deutsches Zentrum für Luft- und Raumfahrt (DLR), the Lidar Atmospheric Sensing Experiment (LASE) of the National Aeronautics and Space Administration (NASA) Langley Research Center, and the Lidar Embarque pour l’etude des Aerosols et des Nuages de l’interaction Dynamique Rayonnement et du cycle de l’Eau (LEANDRE II) of the Centre National de la Recherche Scientifique (CNRS). Data of one formation flight with DLR DIAL and LEANDRE II were investigated, which consists of 54 independent profiles of the two instruments measured with 10-s temporal average. For the height range of 1.14–1.64 km above sea level, a bias of (−0.41 ± 0.16) g kg−1 or −7.9% ± 3.1% was found for DLR DIAL compared to LEANDRE II (LEANDRE II drier) as well as root-mean-square (RMS) deviations of (0.87 ± 0.18) g kg−1 or 16.9% ± 3.5%. With these results, relative bias values of −9.3%, −1.5%, +2.7%, and +8.1% result for LEANDRE II, DLR DIAL, the scanning Raman lidar (SRL), and LASE, respectively, using the mutual bias values determined in Part I for the latter three sensors. From the three possible profile-to-profile intercomparisons between DLR DIAL and LASE, one case cannot provide information on the system performances due to very large inhomogeneity of the atmospheric water vapor field, while one of the two remaining two cases showed a difference of −4.6% in the height range of 1.4–3.0 km and the other of −25% in 1.3–3.8 km (in both cases DLR DIAL was drier than LASE). The airborne-to-airborne comparisons showed that if airborne water vapor lidars are to be validated down to an accuracy of better than 5% in the lower troposphere, the atmospheric variability of water vapor has to be taken into account down to scales of less than a kilometer unless a sufficiently large number of intercomparison cases is available to derive statistically solid biases and RMS deviations. In conclusion, the overall biases between the water vapor data of all three airborne lidar systems operated during IHOP_2002 are smaller than 10% in the present stage of data evaluation, which confirms the previous estimates of the instrumental accuracies for all the systems.

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Matthias Grzeschik, Hans-Stefan Bauer, Volker Wulfmeyer, Dirk Engelbart, Ulla Wandinger, Ina Mattis, Dietrich Althausen, Ronny Engelmann, Matthias Tesche, and Andrea Riede

Abstract

The impact of water vapor observations on mesoscale initial fields provided by a triangle of Raman lidar systems covering an area of about 200 km × 200 km is investigated. A test case during the Lindenberg Campaign for Assessment of Humidity and Cloud Profiling Systems and its Impact on High-Resolution Modeling (LAUNCH-2005) was chosen. Evaluation of initial water vapor fields derived from ECMWF analysis revealed that in the model the highly variable vertical structure of water vapor profiles was not recovered and vertical gradients were smoothed out. Using a 3-h data assimilation window and a resolution of 10–30 min, continuous water vapor data from these observations were assimilated in the fifth-generation Pennsylvania State University–NCAR Mesoscale Model (MM5) by means of a four-dimensional variational data analysis (4DVAR). A strong correction of the vertical structure and the absolute values of the initial water vapor field of the order of 1 g kg−1 was found. This occurred mainly upstream of the lidar systems within an area, which was comparable with the domain covered by the lidar systems. The correction of the water vapor field was validated using independent global positioning system (GPS) sensors. Much better agreement to GPS zenith wet delay was achieved with the initial water vapor field after 4DVAR. The impact region was transported with the mean wind and was still visible after 4 h of free forecast time.

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Andreas Behrendt, Volker Wulfmeyer, Hans-Stefan Bauer, Thorsten Schaberl, Paolo Di Girolamo, Donato Summa, Christoph Kiemle, Gerhard Ehret, David N. Whiteman, Belay B. Demoz, Edward V. Browell, Syed Ismail, Richard Ferrare, Susan Kooi, and Junhong Wang

Abstract

The water vapor data measured with airborne and ground-based lidar systems during the International H2O Project (IHOP_2002), which took place in the Southern Great Plains during 13 May–25 June 2002 were investigated. So far, the data collected during IHOP_2002 provide the largest set of state-of-the-art water vapor lidar data measured in a field campaign. In this first of two companion papers, intercomparisons between the scanning Raman lidar (SRL) of the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC) and two airborne systems are discussed. There are 9 intercomparisons possible between SRL and the differential absorption lidar (DIAL) of Deutsches Zentrum für Luft- und Raumfahrt (DLR), while there are 10 intercomparisons between SRL and the Lidar Atmospheric Sensing Experiment (LASE) of the NASA Langley Research Center. Mean biases of (−0.30 ± 0.25) g kg−1 or −4.3% ± 3.2% for SRL compared to DLR DIAL (DLR DIAL drier) and (0.16 ± 0.31) g kg−1 or 5.3% ± 5.1% for SRL compared to LASE (LASE wetter) in the height range of 1.3–3.8 km above sea level (450–2950 m above ground level at the SRL site) were found. Putting equal weight on the data reliability of the three instruments, these results yield relative bias values of −4.6%, −0.4%, and +5.0% for DLR DIAL, SRL, and LASE, respectively. Furthermore, measurements of the Snow White (SW) chilled-mirror hygrometer radiosonde were compared with lidar data. For the four comparisons possible between SW radiosondes and SRL, an overall bias of (−0.27 ± 0.30) g kg−1 or −3.2% ± 4.5% of SW compared to SRL (SW drier) again for 1.3–3.8 km above sea level was found. Because it is a challenging effort to reach an accuracy of humidity measurements down to the ∼5% level, the overall results are very satisfactory and confirm the high and stable performance of the instruments and the low noise errors of each profile.

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Mathias W. Rotach, Paolo Ambrosetti, Christof Appenzeller, Marco Arpagaus, Lionel Fontannaz, Felix Fundel, Urs Germann, Alessandro Hering, Mark A. Liniger, Marco Stoll, Andre Walser, Felix Ament, Hans-Stefan Bauer, Andreas Behrendt, Volker Wulfmeyer, François Bouttier, Yann Seity, Andrea Buzzi, Silvio Davolio, Matteo Corazza, Michael Denhard, Manfred Dorninger, Theresa Gorgas, Jacqueline Frick, Christoph Hegg, Massimiliano Zappa, Christian Keil, Hans Volkert, Chiara Marsigli, Andrea Montaini, Ron McTaggart-Cowan, Ken Mylne, Roberto Ranzi, Evelyne Richard, Andrea Rossa, Daniel Santos-Muñoz, Christoph Schär, Michael Staudinger, Yong Wang, and Johannes Werhahn

Abstract

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Mathias W. Rotach, Paolo Ambrosetti, Felix Ament, Christof Appenzeller, Marco Arpagaus, Hans-Stefan Bauer, Andreas Behrendt, François Bouttier, Andrea Buzzi, Matteo Corazza, Silvio Davolio, Michael Denhard, Manfred Dorninger, Lionel Fontannaz, Jacqueline Frick, Felix Fundel, Urs Germann, Theresa Gorgas, Christoph Hegg, Alessandro Hering, Christian Keil, Mark A. Liniger, Chiara Marsigli, Ron McTaggart-Cowan, Andrea Montaini, Ken Mylne, Roberto Ranzi, Evelyne Richard, Andrea Rossa, Daniel Santos-Muñoz, Christoph Schär, Yann Seity, Michael Staudinger, Marco Stoll, Hans Volkert, Andre Walser, Yong Wang, Johannes Werhahn, Volker Wulfmeyer, and Massimiliano Zappa

Demonstration of probabilistic hydrological and atmospheric simulation of flood events in the Alpine region (D-PHASE) is made by the Forecast Demonstration Project in connection with the Mesoscale Alpine Programme (MAP). Its focus lies in the end-to-end flood forecasting in a mountainous region such as the Alps and surrounding lower ranges. Its scope ranges from radar observations and atmospheric and hydrological modeling to the decision making by the civil protection agents. More than 30 atmospheric high-resolution deterministic and probabilistic models coupled to some seven hydrological models in various combinations provided real-time online information. This information was available for many different catchments across the Alps over a demonstration period of 6 months in summer/fall 2007. The Web-based exchange platform additionally contained nowcasting information from various operational services and feedback channels for the forecasters and end users. D-PHASE applications include objective model verification and intercomparison, the assessment of (subjective) end user feedback, and evaluation of the overall gain from the coupling of the various components in the end-to-end forecasting system.

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J. K. Andersen, Liss M. Andreassen, Emily H. Baker, Thomas J. Ballinger, Logan T. Berner, Germar H. Bernhard, Uma S. Bhatt, Jarle W. Bjerke, Jason E. Box, L. Britt, R. Brown, David Burgess, John Cappelen, Hanne H. Christiansen, B. Decharme, C. Derksen, D. S. Drozdov, Howard E. Epstein, L. M. Farquharson, Sinead L. Farrell, Robert S. Fausto, Xavier Fettweis, Vitali E. Fioletov, Bruce C. Forbes, Gerald V. Frost, Sebastian Gerland, Scott J. Goetz, Jens-Uwe Grooß, Edward Hanna, Inger Hanssen-Bauer, Stefan Hendricks, Iolanda Ialongo, K. Isaksen, Bjørn Johnsen, L. Kaleschke, A. L. Kholodov, Seong-Joong Kim, Jack Kohler, Zachary Labe, Carol Ladd, Kaisa Lakkala, Mark J. Lara, Bryant Loomis, Bartłomiej Luks, K. Luojus, Matthew J. Macander, G. V. Malkova, Kenneth D. Mankoff, Gloria L. Manney, J. M. Marsh, Walt Meier, Twila A. Moon, Thomas Mote, L. Mudryk, F. J. Mueter, Rolf Müller, K. E. Nyland, Shad O’Neel, James E. Overland, Don Perovich, Gareth K. Phoenix, Martha K. Raynolds, C. H. Reijmer, Robert Ricker, Vladimir E. Romanovsky, E. A. G. Schuur, Martin Sharp, Nikolai I. Shiklomanov, C. J. P. P. Smeets, Sharon L. Smith, Dimitri A. Streletskiy, Marco Tedesco, Richard L. Thoman, J. T. Thorson, X. Tian-Kunze, Mary-Louise Timmermans, Hans Tømmervik, Mark Tschudi, Dirk van As, R. S. W. van de Wal, Donald A. Walker, John E. Walsh, Muyin Wang, Melinda Webster, Øyvind Winton, Gabriel J. Wolken, K. Wood, Bert Wouters, and S. Zador
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