Assessment of Planetary Boundary Layer parametrizations and urban heat island comparison: Impacts and implications for tracer transport.

Accurate simulation of planetary boundary layer height (PBLH) is key to greenhouse gas emission estimation, air quality prediction and weather forecasting. This manuscript describes an extensive performance assessment of several Weather Research and Forecasting (WRF) model configurations where novel observations from ceilometers, surface stations and a flux tower were used to study their ability to reproduce planetary boundary layer heights (PBLH) and the impact that the urban heat island (UHI) has on the modeled PBLHs in the greater Washington, D.C. area. In addition, CO2 measurements at two urban towers were compared to tracer transport simulations. The ensemble of models used 4 PBL parameterizations, 2 sources of initial and boundary conditions and 1 configuration including the building energy parameterization (BEP) urban canopy model. Results have shown low biases over the whole domain and period for wind speed, wind direction and temperature with no drastic differences between meteorological drivers. We find that PBLH errors are mostly positively correlated with sensible heat flux errors, and that modeled positive UHI intensities are associated with deeper modeled PBLs over the urban areas. In addition, we find that modeled PBLHs are typically biased low during nighttime for most of the configurations with the exception of those using the MYNN parametrization and that these biases directly translate to tracer biases. Overall, the configurations using MYNN scheme performed the best, reproducing the PBLH and CO2 molar fractions reasonably well during all hours, thus opening the door to future nighttime inverse modeling.

Characteristics of Lake Chad level variability and links to ENSO, precipitation, and river discharge.

This study used trend, correlation, and wavelet analysis to characterize Lake Chad (LC) level fluctuations, river discharge, El Niño Southern Oscillation (ENSO), and precipitation regimes and their interrelationships. Linear correlation results indicate a negative association between ENSO and LC level, river discharge and precipitation. Trend analysis shows increasing precipitation in the Lake Chad Basin (LCB) but decreasing LC level. The mode of interannual variability in LC level, rainfall, and ENSO analyzed using wavelet analysis is dominated by 3-4-year periods. Results show that variability in ENSO could explain only 31% and 13% of variations in LC level at Kindjeria and precipitation in the northern LCB, respectively. The wavelet transform coherency (WTC) between LC level of the southern pool at Kalom and ENSO is statistically significant at the 95% confidence level and phase-locked, implying a cause-and-effect association. These strong coherencies coincide with the La Niña years with the exception of 1997-1998 El Niño events. The WTC shows strong covariance between increasing precipitation and LC level in the northern pool at a 2- to 4-year band and 3- to 4-year band localized from 1996 to 2010. Implications for water resource planning and management are discussed.

Validation of the Raman lidar algorithm for quantifying aerosol extinction.

To calculate aerosol extinction from Raman lidar data, it is necessary to evaluate the derivative of a molecular Raman signal with respect to range. The typical approach taken in the lidar community is to make an a priori assumption about the functional behavior of the data to calculate the derivative. It has previously been shown that the use of the chi-squared technique to determine the most likely functional behavior of the data prior to actually calculating the derivative eliminates the need for making a priori assumptions. Here that technique is validated through numerical simulation and by application to a significant body of Raman lidar measurements. In general, we show that the chi-squared approach for evaluating extinction yields lower extinction uncertainty than traditional techniques. We also use the technique to study the feasibility of developing a general characterization of the extinction uncertainty that could permit the uncertainty in Raman lidar aerosol extinction measurements to be estimated accurately without the need of the chi-squared technique.

Active Raman sounding of the earth's water vapor field.

The typically weak cross-sections characteristic of Raman processes has historically limited their use in atmospheric remote sensing to nighttime application. However, with advances in instrumentation and techniques, it is now possible to apply Raman lidar to the monitoring of atmospheric water vapor, aerosols and clouds throughout the diurnal cycle. Upper tropospheric and lower stratospheric measurements of water vapor using Raman lidar are also possible but are limited to nighttime and require long integration times. However, boundary layer studies of water vapor variability can now be performed with high temporal and spatial resolution. This paper will review the current state-of-the-art of Raman lidar for high-resolution measurements of the atmospheric water vapor, aerosol and cloud fields. In particular, we describe the use of Raman lidar for mapping the vertical distribution and variability of atmospheric water vapor, aerosols and clouds throughout the evolution of dynamic meteorological events. The ability of Raman lidar to detect and characterize water in the region of the tropopause and the importance of high-altitude water vapor for climate-related studies and meteorological satellite performance are discussed.

Numerical simulation of light backscattering by spheres with off-center inclusion. Application to the lidar case.

A Mie backscattering model for spherical particles with off-center inclusion has been developed and tested. The program is capable of dealing with size parameter values up to approximately 1000, thus allowing one to simulate the optical behavior of a large variety of atmospheric aerosols, as well as cloud and precipitation particles. On the basis of this model, we simulated the optical properties of polydisperse composite atmospheric particles as observed by ground-based and airborne lidar systems. We have characterized optical properties in terms of host and inclusion radii, considering water particles with different composition inclusions. The performed modeling provides some insight into the so-called lidar bright- and dark-band phenomenon.