ALBERT

Description: The shapes of raindrops play an important role in inducing polarimetric rainfall algorithms with differential reflectivity (ZDR) and specific differential phase (KDP). The shapes of raindrops have a direct impact on rainfall estimation. However, the characteristics of raindrop size distribution (DSD) are different depending on precipitation type, storm stage of development, and regional and climatological conditions. Therefore, it is necessary to provide assumptions based on raindrop shapes that reflect the rainfall characteristics of the Korean peninsula. In this study, we presented a method to find optimal polarimetric rainfall algorithms on the Korean peninsula using the 2-Dimensional Video Disdrometer (2DVD) and Bislsan S-Band dual-polarization radar. First, a new axis ratio of raindrop relations was developed for the improvement of rainfall estimation. Second, polarimetric rainfall algorithms were derived using different axis ratio relations, and estimated radar-point one-hour rain rate for the differences in polarimetric rainfall algorithms were compared with the hourly rain rate measured by gauge. In addition, radar rainfall estimation was investigated in relation to calibration bias of reflectivity and differential reflectivity. The derived raindrop axis ratio relation from the 2DVD was more oblate than existing relations in the D 〈 1.5 mm and D 〉 5.5 mm range. The R(KDP, ZDR) algorithm based on a new axis ratio relation showed the best result on DSD statistics; however, the R(Zh, ZDR) algorithm showed the best performance for radar rainfall estimation, because the rainfall events used in the analysis were mainly weak precipitation and KDP is noisy at lower rain rates ( ≤ 5 mm hr−1). Thus, the R(KDP, ZDR) algorithm is suitable for heavy rainfall and R(Zh, ZDR) algorithm is suited for light rainfall. The calibration bias of reflectivity (ZH) and differential reflectivity (ZDR) were calculated from the comparison of measured with simulated ZH and ZDR from the 2DVD. The calculated ZH and ZDR bias was used to reduce radar bias, and to produce more accurate rainfall estimation.

Description: Regional frequency analysis is widely used to estimate more reliable quantiles of extreme hydro-meteorological events. The stationarity of data is required for its application. This assumption tends to be violated due to climate change. In this paper, four nonstationary index flood models were used to analyze the nonstationary regional data. Monte Carlo simulation was used to evaluate the performances of these models for the generalized extreme value distribution with linearly time varying location parameter and constant scale and shape parameters. As a results, it was found that the index flood model with time-invariant index flood and time-variant growth curve could yield more statistically efficient quantile when record is long enough to show significant nonstationarity.

Description: Debris flows caused by heavy rainfall in mountain areas near expressways lead to severe social and economic loss and sometimes even result in casualties. However, in Korea, the design of road structures that resist these debris flow incidents are generally not carried out in a systematic way with proper concepts or procedures. Therefore, the development of a real-time system for debris flow hazard assessment is necessary to provide preliminary information for rapid decision making of evacuations or restoration measures, and to prevent second-hand disasters caused by debris flows. Recently, various map-based approaches have been proposed using multi-attribute criteria and assessment methods for debris flow susceptibilities. However, for the macro-zonation of debris flow hazards at a national scale, a simplified method such as the Korea Expressway Corporation debris flow hazard assessment method is appropriate and also applicable for systemization based on GIS and monitoring networks. In this study, a GIS-based real-time framework of debris flow hazards for expressway sections was newly proposed based on the KEC debris flow hazard assessment method. First, the KEC-based method was standardized in a systematic fashion using ESRI ArcGIS, enabling the objective and quantitative acquisition of various attribute datasets. Also, for a more precise assessment, the quantification of rainfall criteria was considered. Finally, a safety management system for debris flow hazards was developed based on a GIS platform, and was applied and verified on three expressway sections in Korea.

Description: The objective of this study was to reduce the parameter uncertainty which has an effect on the identification of the relationship between the catchment characteristics and the catchment response dynamics in ungauged catchments. A water balance model calibrated to represent the rainfall runoff characteristics over long time scales had a potential limitation in the modelling capacity to accurately predict the hydrological effects of non-stationary catchment response dynamics under different climate conditions (distinct wet and dry periods). The accuracy and precision of hydrological modelling predictions was assessed to yield a better understanding for the potential improvement of the model's predictability. In the assessment of model structure suitability to represent the non-stationary catchment response characteristics, there was a flow-dependent bias in the runoff simulations. In particular, over-prediction of the streamflow was dominant for the dry period. The poor model performance during the dry period was associated with the largely different impulse response estimates for the entire period and the dry period. The refined calibration approach was established based on assessment of model deficiencies. The rainfall–runoff models were separately calibrated to different parts of the flow regime, and the calibrated models for the separated time series were used to establish the regional models of relevant parts of the flow regime (i.e. wet and dry periods). The effectiveness of the parameter values for the refined approach in regionalisation was evaluated through investigating the accuracy of predictions of the regional models. The predictability was demonstrated using only the dry period to highlight the improvement in model performance easily veiled by the performance of the model for the whole period. The regional models from the refined calibration approach clearly enhanced the hydrological behaviour by improving the identification of the relationships between the catchment attributes and the catchment response dynamics representing the time constants in fitting recession parts of hydrograph (i.e. improving the parameter identifiability representing the different behaviour of the catchment) in regionalisation.

Description: Air quality modeling demands accurate meteorological simulations. Observation nudging, also known as objective analysis (OA), is generally considered a low-cost and effective technique to improve meteorological simulations. However the meteorological impact of OA on chemistry has not been well characterized. This study involved two simulations (with/without OA) to analyze the impact of OA on the simulated meteorology and ozone concentrations during the Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) Texas campaign period in September 2013, using Weather Research and Forecasting (WRF) and Community Multiscale Air Quality (CMAQ) models. The results showed improved correlations between observed and simulated parameters from the OA case. The index of agreement (IOA) improved by about 9 % for surface temperature and 6–11 % for surface zonal (U-WIND) and meridional (V-WIND) winds when OA was employed. Analysis of a cold front event indicated that OA improved the timing of wind transition during front passage. Employing OA also reduced the model biases in the planetary boundary height predictions. For CMAQ simulated surface ozone during the whole simulated period, IOA improved by 6 % in the OA case. The high ozone episode on 25 September was a typical post-front ozone event in Houston. The small-scale morning wind-shifts near the Houston Ship Channel combined with higher aloft ozone from recirculation likely caused the day's ozone exceedance. While OA did not reproduce the wind shifts on that day and failed to reproduce the observed surface and aloft high ozone, analyses of surface and aircraft data found that OA results matched better with observations. In a two-hour period during the event, substantially better winds in OA noticeably improved the ozone. Further work on improving OA's capability to reproduce local meteorological events could enhance a chemistry model's ability to predict high ozone events.

Description: Nitrogen oxides (NOx) have fallen steadily across the US over the last fifteen years. At the same time, due to patterns diesel truck activities, NOx concentrations decrease on weekends relative to weekdays, largely without co-occurring changes in other gas-phase emissions. These trends taken together provide two independent constraints on the role of NOx in the nonlinear chemistry of atmospheric oxidation. In this context, we interpret interannual trends in wintertime ammonium nitrate (NH4NO3) in the San Joaquin Valley of California, a location with the worst aerosol pollution in the US and where a large portion of aerosol mass is NH4NO3. Here, we show that NOx reductions have simultaneously decreased nighttime and increased daytime NH4NO3 production over the last decade. We find a substantial decrease in NH4NO3 since 2000 and conclude that this decrease is due to reduced nitrate radical-initiated production at night in residual layers that are decoupled from fresh emissions at the surface. Further reductions in NOx are imminent in California, and nationwide, and we make a quantitative prediction of the response of NH4NO3. We show that the combination of rapid chemical production and efficient NH4NO3 loss via deposition of gas-phase nitric acid implies high aerosol days in cities in the San Joaquin Valley air basin are responsive to local changes in NOx within those individual cities. Our calculations indicate that large decreases in NOx in the future will not only lower wintertime NH4NO3 concentrations, they will also cause a transition in the dominant NH4NO3 source from nighttime to daytime chemistry.

Description: The San Joaquin Valley (SJV) in California experiences persistent air quality problems associated with elevated particulate matter (PM) concentrations due to anthropogenic emissions, topography, and meteorological conditions. Thus it is important to unravel the various sources and processes that affect the physico-chemical properties of PM in order to better inform pollution abatement strategies and improve parameterizations in air quality models. During January and February 2013, a ground supersite was installed at the Fresno-Garland California Air Resources Board (CARB) monitoring station, where comprehensive, real-time measurements of PM and trace gases were performed using instruments including an Aerodyne High Resolution Time-of-Flight Aerosol Mass Spectrometer (HR-ToF-AMS) and an Ionicon Proton Transfer Reaction Time-of-Flight Mass Spectrometer (PTR-TOF-MS) as part of the NASA Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) campaign. The average submicron aerosol (PM1) concentration was 31.0 μg m−3 and the total mass was dominated by organic aerosols (OA, 55 %), followed by ammonium nitrate (35 %). High PM pollution events were commonly associated with elevated OA concentrations, mostly from primary sources. Organic aerosols had average atomic oxygen-to-carbon (O / C), hydrogen-to-carbon (H / C), and nitrogen-to-carbon (N / C) ratios of 0.42, 1.70, and 0.017, respectively. Six distinct sources of organic aerosol were identified from positive matrix factorization (PMF) analysis of the AMS data: hydrocarbon-like OA (HOA; 9 % of total OA; O / C = 0.09) associated with local traffic, cooking OA (COA; 28 % of total OA; O / C = 0.19) associated with food cooking activities, two biomass burning OAs (BBOA1; 13 % of total OA; O / C = 0.33 and BBOA2; 20 % of total OA; O / C = 0.60) most likely associated with residential space heating from wood combustion, and semi-volatile oxygenated OA (SV-OOA; 16 % of total OA; O / C = 0.63) and low volatility oxygenated OA (LV-OOA; 24 % of total OA; O / C = 0.90) formed via chemical reactions in the atmosphere. Large differences in aerosol chemistry at Fresno were observed between the current campaign (winter 2013) and a previous wintertime campaign (winter 2010), most notably that PM1 concentrations were nearly three times higher in 2013 than in 2010. These variations were attributed to differences in the meteorological conditions, which influenced primary emissions and secondary aerosol formation. In particular, COA and BBOA concentrations were greater in 2013 than 2010, where colder temperatures in 2013 likely resulted in increased biomass burning activities. The influence from a nighttime formed residual layer that mixed down in the morning was found to be much more intense in 2013 than 2010, leading to sharp increases in ground-level concentrations of secondary aerosol species including nitrate, sulfate, and OOA, in the morning between 08:00 to 12:00 PST. This is an indication that nighttime chemistry might also be higher in 2013. As solar radiation was stronger in 2013 the higher nitrate and OOA concentrations in 2013 could also be partly due to greater photochemical production of secondary aerosol species. The greater solar radiation and larger range in temperature in 2013 also likely led to both SV-OOA and LV-OOA being observed in 2013 whereas only a single OOA factor was identified in 2010.

Description: We investigate the impact of convection on the thermal structure of the Tropical Tropopause Layer (TTL). We use temperature profiles measured by the Atmospheric Infrared Sounder (AIRS) onboard the Aqua satellite, and the time evolution of local convection determined by the National Centers for Environmental Protection/Aviation Weather Center (NCEP/AWS) half-hourly infrared global geostationary composite. The observations demonstrate that the TTL is cooled by convection, in agreement with previous observations and model simulations. By using a global data set, we are able to investigate the variations in this convective cooling by season and region. The estimated cooling rate during active convection is 7.5~9 K/day. While we cannot unambiguously identify the cause of this cooling, our analysis suggests that radiative cooling is likely not an explanation.

Description: Nitrogen dioxide vertical column density (NO2 VCD) measurements via satellite are compared with a fine-scale regional chemistry transport model, using a new approach that considers varying satellite footprint sizes. Space-borne NO2 VCD measurement has been used as a proxy for surface nitrogen oxide (NOx) emission, especially for anthropogenic urban emission, so accurate comparison of satellite and modeled NO2 VCD is important in determining the future direction of NOx emission policy. The National Aeronautics and Space Administration Ozone Monitoring Instrument (OMI) NO2 VCD measurements, retrieved by the Royal Netherlands Meteorological Institute (KNMI), are compared with a 12 km Community Multi-scale Air Quality (CMAQ) simulation from the National Oceanic and Atmospheric Administration. We found that OMI footprint pixel sizes are too coarse to resolve urban NO2 plumes, resulting in a possible underestimation in the urban core and overestimation outside. In order to quantify this effect of resolution geometry, we have made two estimates. First, we constructed pseudo-OMI data using fine-scale outputs of the model simulation. Assuming the fine-scale model output is a true measurement, we then collected real OMI footprint coverages and performed conservative spatial regridding to generate a set of fake OMI pixels out of fine-scale model outputs. When compared to the original data, the pseudo-OMI data clearly showed smoothed signals over urban locations, resulting in roughly 20–30 % underestimation over major cities. Second, we further conducted conservative downscaling of OMI NO2 VCD using spatial information from the fine-scale model to adjust the spatial distribution, and also applied Averaging Kernel (AK) information to adjust the vertical structure. Four-way comparisons were conducted between OMI with and without downscaling and CMAQ with and without AK information. Results show that OMI and CMAQ NO2 VCDs show the best agreement when both downscaling and AK methods are applied, with correlation coefficient R = 0.89. This study suggests that satellite footprint sizes might have a considerable effect on the measurement of fine-scale urban NO2 plumes. The impact of satellite footprint resolution should be considered when using satellite observations in emission policy making, and the new downscaling approach can provide a reference uncertainty for the use of satellite NO2 measurements over most cities.

Description: A regional air-quality forecast system's model of surface ozone variability based on cloud coverage is evaluated using satellite-observed cloud fraction (CF) information and a surface air-quality monitoring system. We compared CF and daily maximum ozone from the National Oceanic and Atmospheric Administration's National Air Quality Forecast Capability (NOAA NAQFC) with CFs from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the U.S. Environmental Protection Agency's AirNow surface ozone measurements during May to October 2014. We found that observed surface ozone shows a clear (negative) correlation with the MODIS CFs, showing around 1 ppb decrease for 10% MODIS CF change over the Contiguous United States, while the correlation of modeled surface ozone with the model CFs is much weaker, showing only −0.5 ppb per 10% NAQFC CF change. Further, daytime CF differences between MODIS and NAQFC are correlated with modeled surface-ozone biases between AirNow and NAQFC, showing −1.05 ppb per 10% CF change, implying that spatial- and temporal-misplacement of the modeled cloud field might have biased modeled surface ozone-level. Current NAQFC cloud fields seem to be too bright compared to MODIS cloud fields (mean NAQFC CF = 0.38 and mean MODIS CF = 0.55), contributing up to 35% of surface-ozone bias in the current NAQFC system.