A5077766374- Atmospheric aerosols and clouds
- Meteorological Phenomena and Simulations
- Atmospheric chemistry and aerosols
- Climate variability and models
- Atmospheric and Environmental Gas Dynamics
- Wind and Air Flow Studies
- Aeolian processes and effects
- Ionosphere and magnetosphere dynamics
- Quantum chaos and dynamical systems
- Forest Insect Ecology and Management
- Geology and Paleoclimatology Research
- Arctic and Antarctic ice dynamics
- Horticultural and Viticultural Research
- Advanced Fiber Optic Sensors
- Marine and environmental studies
- GNSS positioning and interference
- Wine Industry and Tourism
- Geophysics and Gravity Measurements
- Quantum Electrodynamics and Casimir Effect
- Nonlinear Dynamics and Pattern Formation
- Cryospheric studies and observations
- Air Quality Monitoring and Forecasting
- Hydrocarbon exploration and reservoir analysis
- Precipitation Measurement and Analysis
- Urban Heat Island Mitigation
University of East Anglia
2018-2025
Norwich Research Park
2022
Nikon (United States)
2013
Abstract Fog is a high-impact weather phenomenon affecting human activity, including aviation, transport, and health. Its prediction longstanding issue for forecast models. The success of depends on complex interactions among various meteorological topographical parameters; even very small changes in some these can determine the difference between thick fog good visibility. This makes one most challenging goals numerical prediction. Local Nonlocal Experiment (LANFEX) an attempt to improve...
Abstract Dense wintertime fog regularly impacts Delhi, severely affecting road and rail transport, aviation human health. Recent decades have seen an unexplained increase in events over northern India, coincident with a steep rise irrigation associated the introduction of double-cropping. Accurate forecasting is challenging due to high sensitivity numerous processes across many scales, uncertainties representing some these state-of-the-art numerical weather prediction models. Here we show...
Abstract The numerical weather prediction (NWP) of fog remains a challenge, with accurate forecasts relying on the representation many interacting physical processes. recent Local And Non‐local Fog EXperiment (LANFEX) has generated detailed observational dataset, creating unique opportunity to assess NWP events. We evaluate performance operational and research configurations Met Office Unified Model (MetUM) three horizontal grid lengths, 1.5 km 333 100 m, in simulating four LANFEX case...
Abstract Fog is a major hazard in wintertime over India, particularly the Indo‐Gangetic Plains, leading to significant impacts for transport and human health. Using 3‐hourly surface observations, from 69 sites across all fog dense events between 2000 2020 are identified. For each event, main formation mechanism objectively categorized using classification algorithm, distinguishing radiation, advection, evaporation, precipitation or cloud‐base lowering types. In contrast findings of other...
Between 1981–2000 and 1999–2018, growing season average temperatures (GST) in the main UK viticulture regions have warmed ~1.0 °C are now more reliably >14.0 GST. This warming has underpinned rapid expansion of sector its current focus on grape varieties for sparkling wine. Near-term (2021–2040) climate change may condition opportunities further variety and/or wine style changes. Using latest high-resolution (5 km) ensemble (×12) downscaled models (UK Climate Projections; UKCP18) under...
Abstract Rapid urbanization has subjected the megacities of developing countries to various environmental stresses. Delhi, a major Indian megacity, faces increasing urban stress leading reduction in air quality, and visibility. These challenges necessitate an integrated modeling framework mitigate adverse impacts on public health. Therefore, we have developed advanced version high-resolution Delhi Model with Chemistry Aerosol (DM-Chem) at National Centre for Medium Range Weather Forecasting...
Global climate models and reanalysis products have revealed large downwelling shortwave radiation biases over the Southern Ocean Antarctica. The are hypothesized to be caused by incapability of accurately simulate frequent occurrence low-level mixed-phase clouds in these regions. It’s crucial elucidate intricacy cloud microphysics aerosol-cloud interaction Antarctica order better system.In this study, we use ground-based observations colleted at Davis, East assess capability...
Clouds are a major source of uncertainty in climate model projections over the Southern Ocean and Antarctica1. The inaccurate representation clouds models results biases net radiative balance which has knock-on effects on ability to represent sea surface temperatures, ocean heat uptake, ice cover, ultimately large-scale circulation Hemisphere2,3,4,5,6. Evidence suggests that this is due poor mixed phase models—the dominant cloud type region. As part project, we have conducted two...
Abstract The Iceland Greenland Seas Project (IGP) is a coordinated atmosphere–ocean research program investigating climate processes in the source region of densest waters Atlantic meridional overturning circulation. During February and March 2018, field campaign was executed over southern that utilized range observing platforms to investigate critical region, including vessel, aircraft, moorings, sea gliders, floats, meteorological buoy. A remarkable feature highly deployment platforms,...
Abstract The current study highlights the importance of a detailed representation urban processes in numerical weather prediction models and emphasizes need for accurate morphology data improving near‐surface over Delhi, tropical Indian city. Met Office Reading Urban Surface Exchange Scheme (MORUSES), two‐tile energy‐budget parameterization scheme, is introduced high‐resolution (330‐m) model Delhi. A new empirical relationship established MORUSES scheme from local performance evaluated using...
Despite the impact it has on human activity, particularly transport, accurate forecasting of fog remains a major challenge for numerical weather prediction models. The complex interaction between various physical processes, many which are parametrised and highly sensitive to small changes, is one key reasons poor forecasts. One models predicting structure boundary layer, often undergoes transition from statically stable weakly unstable during life cycle event. recent local non‐local...
Clouds over the Southern Ocean and Antarctica are poorly represented within climate models. It is thought that our poor understanding of aerosol-cloud interaction at these latitudes could play a major role in biasing models towards consistently underpredicting cloud formation regions. Unfortunately, there few studies aerosols their impact on clouds high southern those do exist concentrate summer period. Here we present two years observations from Rothera Station Antarctic Peninsula....
Atmospheric and climate models have large biases in their short long wave radiative fluxes over the Southern Ocean, leading to significant errors sea surface temperature, ice scale circulation. The primary cause for these is representation of low-level clouds, both at macro- micro-scale. We assess performance a convection-permitting configuration Met Office Unified Model (MetUM) Ocean using satellite aircraft observations from 2023 special observing period Clouds (SOC) field experiment....