Multirule Based Diagnostic Approach for the Fog Predictions Using WRF Modelling Tool

The prediction of fog onset remains difficult despite the progress in numerical weather prediction. It is a complex process and requires adequate representation of the local perturbations in weather prediction models. It mainly depends upon microphysical and mesoscale processes that act within the boundary layer. This study utilizes a multirule based diagnostic (MRD) approach using postprocessing of the model simulations for fog predictions. The empiricism involved in this approach is mainly to bridge the gap between mesoscale and microscale variables, which are related to mechanism of the fog formation. Fog occurrence is a common phenomenon during winter season over Delhi, India, with the passage of the western disturbances across northwestern part of the country accompanied with significant amount of moisture. This study implements the above cited approach for the prediction of occurrences of fog and its onset time over Delhi. For this purpose, a high resolution weather research and forecasting (WRF) model is used for fog simulations. The study involves depiction of model validation and postprocessing of the model simulations for MRD approach and its subsequent application to fog predictions. Through this approach model identified foggy and nonfoggy days successfully 94% of the time. Further, the onset of fog events is well captured within an accuracy of 30–90 minutes. This study demonstrates that the multirule based postprocessing approach is a useful and highly promising tool in improving the fog predictions

Fidelity of WRF model in simulating heat wave events over India

Abstract The evaluation of Weather Research and Forecasting (WRF) model has been performed for simulating episodic Heat Wave (HW) events of 2015 and 2016 with varied horizontal resolutions of 27 km for the entire India (d01), 9 km for the North West (NW (d02)) and South East (SE (d03)) domain. Study compares the maximum temperature (Tmax) simulated by WRF model, using six different combination of parameterization schemes, with observations from the India Meteorological Department (IMD) during the HW events. Among the six experiments, Exp2 (i.e., combination of WSM6 microphysics (MP) together with radiation parameterization CAM, Yonsei (PBL), NOAH land surface and Grell-3D convective schemes) is found closest to the observations in reproducing the temperature. The model exhibits an uncertainty of ± 2 °C in maximum temperature (Tmax) for both the regions, suggesting regional temperature is influenced by the location and complex orography. Overall, statistical results reveal that the best performance is achieved with Exp2. Further, to understand the dynamics of rising HW intensity, two case studies of HW days along with influencing parameters like Tmax, RH and prevailing wind distribution have been simulated. Model simulated Tmax during 2015 reaches up to 44 °C in NW and SE part of India. In 2016, HW is more prevailing towards NW, while in SE region Tmax reaches upto 34–38 °C with high RH (60–85%). The comparative research made it abundantly evident that these episodic events are unique in terms of duration and geographical spread which can be used to assess the WRF performance for future projections of HW

Evaluation of water vapour assimilation in the tropical upper troposphere and lower stratosphere by a chemical transport model

The present analysis deals with one of the most debated aspects of the studies on the upper troposphere/lower stratosphere (UTLS), namely the budget of water vapour (H$_{2}$O) at the tropical tropopause. Within the French project “Multiscale water budget in the upper troposphere and lower stratosphere in the TROpics” (TRO-pico), a global-scale analysis has been set up based on space-borne observations, models and assimilation techniques. The MOCAGEVALENTINA assimilation tool has been used to assimilate the Aura Microwave Limb Sounder (MLS) version 3.3 H$_{2}$O measurements within the 316–5 hPa range from August 2011 to March 2013 with an assimilation window of 1 h. Diagnostics based on observations minus analysis and forecast are developed to assess the quality of the assimilated H$_{2}$O fields. Comparison with an independent source of H$_{2}$O measurements in the UTLS based on the space-borne Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) observations and with meteorological ARPEGE analyses is also shown. Sensitivity studies of the analysed fields have been performed by (1) considering periods when no MLS measurements are available and (2) using H$_{2}$O data from another MLS version (4.2). The studies have been performed within three different spaces in time and space coincidences with MLS (hereafter referred to as MLS space) and MIPAS (MIPAS space) observations and with the model (model space) outputs and at three different levels: 121 hPa (upper troposphere), 100 hPa (tropopause) and 68 hPa (lower stratosphere) in January and February 2012. In the MLS space, the analyses behave consistently with the MLS observations from the upper troposphere to the lower stratosphere. In the model space, the analyses are wetter than the reference atmosphere as represented by ARPEGE and MLS in the upper troposphere (121 hPa) and around the tropopause (100 hPa), but are consistent with MLS and MIPAS in the lower stratosphere (68 hPa). In the MIPAS space, the sensitivity and the vertical resolution of the MIPAS data set at 121 and 100 hPa prevent assessment of the behaviour of the analyses at 121 and 100 hPa, particularly over intense convective areas as the South American, the African and the Maritime continents but, in the lower stratosphere (68 hPa), the analyses are very consistent with MIPAS. Sensitivity studies show the improvement on the H$_{2}$O analyses in the tropical UTLS when assimilating space-borne measurements of better quality, particularly over the convective areas

Intercomparison of Aerosol Optical Thickness Derived from MODIS and <i>in Situ</i> Ground Datasets over Jaipur, a Semi-arid Zone in India

The first detailed seasonal validation has been carried out for the Moderate Resolution Imaging Spectroradiometer (MODIS) Terra and Aqua satellites Level 2.0 Collection Version 5.1 AOT (τ_MODIS) with Aerosol Robotic Network (AERONET) Level 2.0 AOT (τ_AERONET) for the years 2009–2012 over semi-arid region Jaipur, northwestern India. The correlation between τ_MODIS versus τ_AERONET at 550 nm is determined with different spatial and temporal size windows. The τ_MODIS overestimates τ_AERONET within a range of +0.06 ± 0.24 during the pre-monsoon (April–June) season, while it underestimates the τ_AERONET with −0.04 ± 0.12 and −0.05 ± 0.18 during dry (December–March) and post-monsoon (October–November) seasons, respectively. Correlation without (with) error envelope has been found for pre-monsoon at 0.71 (0.89), post-monsoon at 0.76 (0.94), and dry season at 0.78 (0.95). τ_MODIS is compared to τ_AERONET at three more ground AERONET stations in India, i.e., Kanpur, Gual Pahari, and Pune. Furthermore, the performance of MODIS Deep Blue and Aqua AOT_550 nm (τ_DB550 nm and τ_Aqua550 nm) with τ_AERONET is also evaluated for all considered sites over India along with a U.S. desert site at White Sand, Tularosa Basin, NM. The statistical results reveal that τ_Aqua550 nm performs better over Kanpur and Pune, whereas τ_DB550 nm performs better over Jaipur, Gual Pahari, and White Sand High Energy Laser Systems Test Facility (HELSTF) (U.S. site)