Vertical Distribution of Aerosols during Deep-Convective Event in the Himalaya Using WRF-Chem Model at Convection Permitting Scale

The Himalayan region is facing frequent cloud bursts and flood events during the summer monsoon season. The Kedarnath flooding of 2013 was one of the most devastating recent events, which claimed thousands of human lives, heavy infrastructure, and economic losses. Previous research reported that the combination of fast-moving monsoon, pre-existing westerlies, and orographic uplifting were the major reasons for the observed cloud burst over Kedarnath. Our study illustrates the vertical distribution of aerosols during this event and its possible role using the Weather Research and Forecasting model coupled with chemistry (WRF-Chem) simulations. Model performance evaluation shows that simulations can capture the spatial and temporal patterns of observed precipitation during this event. Model simulation at 25 km and 4 km horizontal grid resolution, without any changes in physical parameterization, shows a very minimal difference in precipitation. Simulation at convection-permitting scale shows detailed information related to parcel motion compared to coarser resolution. This indicates that the parameterization at different resolutions needs to be further examined for a better outcome. The modeled result shows changes of up to 20–50% in the rainfall over the area near Kedarnath due to the presence of aerosols. Simulation at both resolutions shows the significant vertical transport of natural (increases by 50%+) and anthropogenic aerosols (increases by 200%+) during the convective event, which leads to significant changes in cloud properties, rain concentration, and ice concentration in the presence of these aerosols. Simulations can detect changes in important instability indices such as convective available potential energy (CAPE), convective inhibition energy (CIN), vorticity, etc., near Kedarnath due to aerosol–radiation feedback.

Vertical Distribution of Aerosols During Deep-convective Event in the Himalaya Using WRF-Chem Model at Convection Permitting Scale

The Himalayan region is facing frequent cloud burst and flood events during the summer monsoon e.g., Kedarnath flood of 2013. It was one of the most devastating event which claimed thousands of human lives, heavy infrastructure and economic losses. Fast moving monsoon, pre-existing westerlies, and orographic uplifting was reported as the major reason for cloud burst over Kedarnath in previous research. Our study illustrates the vertical distribution of aerosols during this event and its possible role using Weather Research and Forecasting model coupled with chemistry (WRF-Chem) simulations. Model performance evaluation shows that simulations can capture the spatial and temporal pattern of observed precipitation during this event. Model simulation at 25km and 4km horizontal grid resolution without any changes in physical parameterization shows very minimal average difference in precipitation. Whereas simulation at convection permitting scale shows de-tailed information related to parcel motion compared to coarser resolution simulation. This indicates parameterization at different resolution needs to examine for better outcome. The result shows up to 20-50% changes in rain over area near Kedarnath due to the presence of aerosols. The simulation at both resolution shows significant vertical transport of natural (increases by 50%+) and anthropo-genic aerosols (increases by 200%+) during the convective event. Which leads to significant changes in cloud property, rain concentration and ice concentration in presence of aerosols. Due to aero-sol–radiation feedback, the important instability indices like convective available potential energy, convective inhibition energy, vorticity etc. shows changes near Kedarnath.

Stochastic Rain Generator Based on Disaggregation of Precipitation into Convective and Stratiform for Climate Change Studies

<p>The outputs from regional climate models (RCMs) have to be further downscaled. This is usually done via a bias correction method.  This study presents a novel approach to statistical downscaling of outputs from RCMs. The novelty lies primarily in distinguishing the convective and stratiform precipitation by rain generator operating in 6-hour time step. For this purpose, the technique based on determination of threshold rainfall intensity is used, built on the observation that the convective precipitation amounts follow exponential distribution.</p><p>The resulting rain generator operates in the following steps: disaggregation of 6-hour cumulative precipitation into convective and stratiform types, fitting of the first order 3-state discrete time Markov chain to the data, and simulation of long time series of precipitation. Then the mixture of log-normal and Generalized Pareto distribution is fitted to stratiform events and the Generalized extreme value distribution to convective events.</p><p>The impact of climate change on precipitation is represented by change factors that are identified for precipitation occurrence (by comparing the transition matrices for the future and control period) and for precipitation amounts (by comparing the scale and location parameters of distributions fitted for the future and control period). The observational data are then altered with the obtained change factors.</p><p>From evaluation of observational data it stems that the average volume of a convective event is higher for the western region than the eastern region of the Czech Republic. Additionally, statistically significant trends in the number and volume of convective events were identified for the western region. The analysis of the RCM simulations shows that even though the overall precipitation is projected to be lower in future, the proportion of convective events (versus stratiform ones) would be higher. In a future climate, the number of convective events is projected to be lower while the mean volume of a convective event to be larger.</p>

Verification of modeling of convective events based on radar reflectivity

<p>The use of numerical modeling for atmospheric research is complicated by the problem of verification by a limited set of measurement data. Comparison with radar measurements is widely used for assessing the quality of the simulation. The probabilistic nature of the development of convective phenomena determines the complexity of the verification process: the reproduction of the pattern of the convective event is prior to the quantitative agreement of the values at a particular point at a particular moment.</p><p>We propose a method for verifying the simulation results based on comparing areas with the same reflectivity. The method is applied for verification of WRF-modeling of convective events in the Aragats highland massif in Armenia. It is shown that numerical simulation demonstrates approximately the same form of distribution of areas of equal reflectivity as for radar-measured reflectivity. In this case, the model tends to overestimate on average reflectivity, while enabling us to obtain the qualitatively correct description of the convective phenomenon.</p><p>The proposed technique can be used to verify the simulation results using data on reflectivity obtained by a satellite or a meteoradar. The technique allows one to avoid subjectivity in the interpretation of simulation results and estimate the quality of reproducing the “general pattern” of the convective event.</p>

Convective uplift of pollution from the Sichuan Basin into the Asian monsoon anticyclone during the StratoClim aircraft campaign

The StratoClim airborne campaign took place in Nepal from 27 July to 10 August 2017 to document the physical and chemical properties of the South Asian upper troposphere–lower stratosphere (UTLS) during the Asian summer monsoon (ASM). In the present paper, simulations with the Meso-NH cloud-chemistry model at a horizontal resolution of 15 km are performed over the Asian region to characterize the impact of monsoon deep convection on the composition of Asian monsoon anticyclone (AMA) and on the formation of the Asian tropopause aerosol layer (ATAL) during the StratoClim campaign. StratoClim took place during a break phase of the monsoon with intense convective activity over South China and Sichuan. Comparisons between brightness temperatures (BTs) at 10.8 µm observed by satellite sensors and simulated by Meso-NH highlight the ability of the model to correctly reproduce the life cycle of deep convective clouds. A comparison between CO and O3 concentrations from Meso-NH and airborne observations (StratoClim and IAGOS (In-service Aircraft for a Global Observing System)) demonstrates that the model captures most of the observed variabilities. Nevertheless, for both gases, the model tends to overestimate the concentrations and misses some thin CO plumes related to local convective events probably because the resolution is too coarse, but the convective uplift of pollution is very well captured by the model. We have therefore focused on the impact of Sichuan convection on the AMA composition. A dedicated sensitivity simulation showed that the 7 August convective event brought large amounts of CO deep into the AMA and even across the 380 K isentropic level located at 17.8 km. This Sichuan contribution enhanced the CO concentration by ∼15 % to reach more than 180 ppbv over a large area around 15 km height. It is noteworthy that Meso-NH captures the impact of the diluted Sichuan plume on the CO concentration during a StratoClim flight south of Kathmandu, highlighting its ability to reproduce the transport pathway of Sichuan pollution. According to the model, primary organic aerosol and black carbon particles originating from Sichuan are transported following the same pathway as CO. The large particles are heavily scavenged within the precipitating part of the convective clouds but remain the most important contributor to the particle mass in the AMA. Over the whole AMA region, the 7 August convective event resulted in a 0.5 % increase in CO concentration over the 10–20 km range that lasted about 2 d. The impact of pollution uplift from three regions (India, China, and Sichuan) averaged over the first 10 d of August has also been evaluated with sensitivity simulations. Even during this monsoon break phase, the results confirm the predominant role of India relative to China with respective contributions of 11 % and 7 % to CO concentration in the 10–15 km layer. Moreover, during this period a large part (35 %) of the Chinese contribution comes from the Sichuan Basin alone.