2 results
Search Results
Now showing 1 - 2 of 2
- ItemCalibration of Raman lidar water vapor profiles by means of AERONET photometer observations and GDAS meteorological data(München : European Geopyhsical Union, 2018) Dai, Guangyao; Althausen, Dietrich; Hofer, Julian; Engelmann, Ronny; Seifert, Patric; Bühl, Johannes; Mamouri, Rodanthi-Elisavet; Wu, Songhua; Ansmann, AlbertWe present a practical method to continuously calibrate Raman lidar observations of water vapor mixing ratio profiles. The water vapor profile measured with the multiwavelength polarization Raman lidar PollyXT is calibrated by means of co-located AErosol RObotic NETwork (AERONET) sun photometer observations and Global Data Assimilation System (GDAS) temperature and pressure profiles. This method is applied to lidar observations conducted during the Cyprus Cloud Aerosol and Rain Experiment (CyCARE) in Limassol, Cyprus. We use the GDAS temperature and pressure profiles to retrieve the water vapor density. In the next step, the precipitable water vapor from the lidar observations is used for the calibration of the lidar measurements with the sun photometer measurements. The retrieved calibrated water vapor mixing ratio from the lidar measurements has a relative uncertainty of 11 % in which the error is mainly caused by the error of the sun photometer measurements. During CyCARE, nine measurement cases with cloud-free and stable meteorological conditions are selected to calculate the precipitable water vapor from the lidar and the sun photometer observations. The ratio of these two precipitable water vapor values yields the water vapor calibration constant. The calibration constant for the PollyXT Raman lidar is 6.56 g kg−1 ± 0.72 g kg−1 (with a statistical uncertainty of 0.08 g kg−1 and an instrumental uncertainty of 0.72 g kg−1). To check the quality of the water vapor calibration, the water vapor mixing ratio profiles from the simultaneous nighttime observations with Raman lidar and Vaisala radiosonde sounding are compared. The correlation of the water vapor mixing ratios from these two instruments is determined by using all of the 19 simultaneous nighttime measurements during CyCARE. Excellent agreement with the slope of 1.01 and the R2 of 0.99 is found. One example is presented to demonstrate the full potential of a well-calibrated Raman lidar. The relative humidity profiles from lidar, GDAS (simulation) and radiosonde are compared, too. It is found that the combination of water vapor mixing ratio and GDAS temperature profiles allow us to derive relative humidity profiles with the relative uncertainty of 10–20 %.
- ItemDust mobilization and transport in the northern Sahara during SAMUM 2006 - A meteorological overview(Milton Park : Taylor & Francis, 2017) Knippertz, Peter; Ansmann, Albert; Althausen, Dietrich; Müller, Detlef; Tesche, Matthias; Bierwirth, Eike; Dinter, Tilman; Müller, Thomas; Von Hoyningen-Huene, Wolfgang; Schepanski, Kerstin; Wendisch, Manfred; Heinold, Bernd; Kandler, Konrad; Petzold, Andreas; Tegen, InaThe SAMUM field campaign in southern Morocco in May/June 2006 provides valuable data to study the emission, and the horizontal and vertical transports of mineral dust in the Northern Sahara. Radiosonde and lidar observations show differential advection of air masses with different characteristics during stable nighttime conditions and up to 5-km deep vertical mixing in the strongly convective boundary layer during the day. Lagrangian and synoptic analyses of selected dust periods point to a topographic channel from western Tunisia to central Algeria as a dust source region. Significant emission events are related to cold surges from the Mediterranean in association with eastward passing upper-level waves and lee cyclogeneses south of the Atlas Mountains. Other relevant events are local emissions under a distinct cut-off low over northwestern Africa and gust fronts associated with dry thunderstorms over the Malian and Algerian Sahara. The latter are badly represented in analyses from the European Centre for Medium–Range Weather Forecasts and in a regional dust model, most likely due to problems with moist convective dynamics and a lack of observations in this region. This aspect needs further study. The meteorological source identification is consistent with estimates of optical and mineralogical properties of dust samples.