Met Office Research Articles

Closing the Circulation Budget

AbstractCirculation budgets can identify physical processes underpinning tropical cyclones, mesoscale convective vortices, and other weather systems where there are interactions across scales. It is unclear, however, how well these budgets close in practice. The present study uses the rapid intensification of Tropical Cyclone Nepartak (2016) as a case study to quantify the practical limitations of calculating circulation budgets using standard reanalyzes and numerical weather model data. First, we evaluate the circulation budget with ERA5. The budget residual can be reduced considerably by including contributions to circulation changes from subgrid‐scale momentum transports, and reduced further with 24‐hr smoothing, which dampens the discontinuous effects of data assimilation. Second, using a high‐resolution Met Office Unified Model simulation, we examine how the choice of the path used (the domain boundary) affects the budget closure. Third, the truncation errors associated with numerical differentiation in time and space are investigated. The circulation budget improves as the model data are analyzed with more frequent time output intervals, and as the output grid spacing decreases. For the tropical convective examples evaluated here, the column mean budget residuals increase by up to 50% as the output intervals increase from 5 min to 3 hr. Errors also increase if the data are regridded to a coarser horizontal grid spacing and when convection straddles the domain boundary. A key result is that the circulation budget need not close for physical inferences made about the circulation and its evolution to be meaningful, thus validating the use of the technique in prior studies.

High prediction skill of decadal tropical cyclone variability in the North Atlantic and East Pacific in the met office decadal prediction system DePreSys4

The UK Met Office decadal prediction system DePreSys4 shows skill in predicting the number of tropical cyclones (TCs) and TC track density over the eastern Pacific and tropical Atlantic Ocean on the decadal timescale (up to ACC = 0.93 and ACC = 0.83, respectively, as measured by the anomaly correlation coefficient—ACC). The high skill in predicting the number of TCs is related to the simulation of the externally forced response, with internal climate variability also allowing the improvement in prediction skill. The Skill is due to the model’s ability to predict the temporal evolution of surface temperature and vertical wind shear over the eastern Pacific and tropical Atlantic Ocean. We apply a signal-to-noise calibration framework and show that DePreSys4 predicts an increase in the number of TCs over the eastern Pacific and the tropical Atlantic Ocean in the next decade (2023–2030), potentially leading to high economic losses.

Vera: A stochastic, polydisperse scheme for diagnosing fog and visibility

AbstractVera is a diagnostic visibility parametrisation designed to produce probabilistic output from an operational forecast model to provide guidance as to the likelihood of fog formation. The scheme is an extension of an existing visibility diagnostic, utilising very similar physics to hydrate a dry aerosol population. The three major improvements implemented by Vera are the expansion from monodisperse aerosol to polydisperse aerosol, the use of stochastic, synthethic noise to estimate the uncertainty in the computed visibility, and upgrading from geometric to Mie scattering to diagnose the aerosol scattering coefficient. Vera has been implemented in the Met Office's Unified Model.

Impact of host climate model on contrail cirrus effective radiative forcing estimates

Abstract. Estimates of aviation effective radiative forcing (ERF) indicate that contrail cirrus is currently its largest contributor, although with a substantial associated uncertainty of ∼ 70 %. Here, we implement the contrail parameterisation developed for the Community Atmosphere Model (CAM) in the UK Met Office Unified Model (UM), allowing us to compare, for the first time, the impact of key features of the host climate model on contrail cirrus ERF. We find that differences in background humidity between the models result in the UM-simulated contrail fractions being 2 to 3 times larger than in CAM. Additionally, the models show contrasting responses in overall global cloud fraction, with contrails increasing the total cloud fraction in the UM and decreasing it in CAM. Differences in the complexity of the cloud microphysics schemes lead to significant differences in simulated changes to cloud ice water content due to aviation. After compensating for the unrealistically low contrail optical depth in the UM, we estimate the 2018 contrail cirrus ERF to be 40.8 mW m−2 in the UM, compared to 60.1 mW m−2 in CAM. These values highlight the substantial uncertainty in contrail cirrus ERF due to differences in microphysics and radiation schemes between the two models. We also find a factor-of-8 uncertainty in contrail cirrus ERF due to existing uncertainty in contrail cirrus optical depth. Future research should focus on better representing microphysical and radiative contrail characteristics in climate models and on improved observational constraints.

An Update to the Central England Temperature Series—HadCET v2.1

ABSTRACTThe Central England Temperature (CET) series is one of the longest instrumental climate records in the world. The CET record from 1659 represents a roughly triangular area of England extending from the Lancashire plain in the north, to London in the south‐east and south‐west of the Midlands of England. HadCET is a composite series produced by the Met Office Hadley Centre, using data from a succession of observing sites for which the data have been adjusted to remove inhomogeneities to be consistent with the original long running series and be updated in near real time. This paper documents a technical update to the HadCET which is referred to as HadCET version 2 (v2), and at time of publication v2.1.0.0 is the latest available version.

Quantifying the impact of global nitrate aerosol on tropospheric composition fields and its production from lightning NOx

Abstract. Several global modelling studies have explored the effects of lightning-generated nitrogen oxides (LNOx) on gas-phase chemistry and atmospheric radiative transfer, but few have quantified LNOx's impact on aerosol, particularly when nitrate aerosol is included. This study addresses two key questions: (1) how does including nitrate aerosol affect properties such as tropospheric composition, and (2) how do these effects depend on lightning parameterisation and LNOx levels? Using the Met Office's Unified Model–United Kingdom Chemistry and Aerosol (UM–UKCA) global chemistry–climate model, which now includes a modal nitrate aerosol scheme, we investigate these effects with two lightning-flash-rate parameterisations. Our findings show that both nitrate aerosol and LNOx significantly impact tropospheric composition and aerosol responses. Including nitrate aerosol reduces global mean tropospheric OH by 5 %, decreases the tropospheric ozone burden by 4 %–5 %, increases methane lifetime by a similar amount, and alters the top-of-atmosphere (TOA) net downward radiative flux by −0.4 W m−2. The inclusion of nitrate also shifts the aerosol size distribution, particularly in the Aitken and accumulation modes. A 5.2 Tg N yr−1 increase in LNOx from a zero baseline results in global aerosol increases of 2.8 % in NH4, 4.7 % in fine NO3, 12 % in coarse NO3, and 5.8 % in SO4 mass burdens. This much LNOx increase causes relatively small positive changes in aerosol optical depth, TOA radiative flux, and cloud droplet number concentration compared to when nitrate is included. The results, based on a fast uptake rate for HNO3 to produce NH4NO3, likely represent an upper limit on nitrate effects.

Assessing the impact of future altimeter constellations in the Met Office global ocean forecasting system

Abstract. Satellite altimeter measurements of sea surface height (SSH) are a crucial component of current operational ocean forecasting systems. The launch of the Surface Water and Ocean Topography (SWOT) wide-swath altimeter (WiSA) mission is bringing a step change in our observing capacity with 2D mesoscale structures now able to be observed over the global ocean. Proposals are now being considered for the make-up of the future altimeter constellation. In this study we use Observing System Simulation Experiments (OSSEs) to compare the impact of additional altimeter observations from two proposed future satellite constellations. We focus on the expected impact on the Met Office operational ocean analysis and forecasting system of assimilating an observation network including either 12 nadir altimeters or 2 wide-swath altimeters. Here we show that an altimeter constellation of 12 nadir altimeters produces greater reductions in the errors for SSH, surface currents, temperature, and salinity fields compared to a constellation of 2 wide-swath altimeters. The impact is greatest in the dynamic western boundary current (WBC) regions where the nadir altimeters can reduce the SSH RMS (root-mean-square) error by half, while the wide-swath altimeter only reduces this by one-quarter. A comparison of the spatial scales resolved in daily SSH fields also highlights the superiority of the nadir constellation in our forecasting system. We also highlight the detrimental impact spatially correlated errors could have on the immediate use of wide-swath altimeter observations. However, we still achieve promising impacts from the assimilation of wide-swath altimetry, and work is ongoing to develop improved methods to account for spatially correlated observation errors within our data assimilation scheme.

Comparative Analysis of LSTM Architectures for Wind Speed Forecasting: A Case Study in Muş, Turkey

This study assesses the effectiveness of five distinct Long Short-Term Memory (LSTM) architectures for forecasting wind speed in Muş, Turkey. The models include Vanilla LSTM, Stacked LSTM, Bidirectional LSTM, Attention LSTM, and Residual LSTM. The data, obtained from the Muş Meteorological Office, underwent preprocessing to handle missing values by averaging the same day and month values between 1969 and 2023. The dataset, containing 20,088 daily wind speed measurements, was split into training and test sets, with 80% allocated for training and 20% for testing. Each model was trained over 100 epochs with a batch size of 32, and performance was assessed using Mean Squared Error (MSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE). The Vanilla LSTM model showed the lowest MSE and MAE values, indicating superior overall performance, while the Attention LSTM model achieved the lowest MAPE, demonstrating better percentage accuracy. These findings indicate that the Vanilla and Attention LSTM models are the most effective for wind speed forecasting, with the choice between them depending on the prioritization of total error versus percentage error.

Effective management of urban water resources under various climate scenarios in semiarid mediterranean areas

Climate change has a significant impact on water resources, making it essential to re-evaluate water management strategies and incorporate climate scenarios in assessments. The Municipal Department of Aigeiros is located in the northern part of Greece. Water consumption is high in Aigeiros and the increased future temperatures projected during the summer period will create significant pressures on water resources. The water resources management study of the region is carried out using the simulations of the RCA4 Regional Climate Model (RCM) driven by the HadGEM-ES global climate model of the Met Office Hadley Centre (MOHC) under 3 different climate emission scenarios, namely RCP 2.6, RCP 4.5 and RCP 8.5. For the simulation of the urban water balance of Aigeiros, Komotini, Greece and the assessment of water demand and supply for three climate scenarios (RCP 2.6, 4.5, and 8.5) over a 30-year period, the Aquacycle software was used. The data used in the assessment included projected climatic conditions for the area (i.e., precipitation and evapotranspiration), domestic water consumption, and natural and spatial characteristics. The results indicate that drinking water demand is likely to increase in the coming decades for RCP 4.5 (1323 m3/d for 2041–2050) and RCP 8.5 (1330 m3/d for 2041–2050) scenarios compared to 2020 (1320 m3/d). However, simulations for water supply suggest an increase in groundwater recharge in the future, but also the potential for long drought periods during summer months in RCP 4.5 and RCP 8.5 scenarios. The simulation results show both the current situation and the climate scenarios and can be the reference basis for recording the different types of water consumption in urban areas. Therefore, it is possible to control and predict how much of the total consumption is due to the consumer usage profile within a household or to the irrigation needs of green areas in line with the climatic conditions, consumer behavior and technical parameters.

The impact of preceding convection on the development of Medicane Ianos and the sensitivity to sea surface temperature

Abstract. Medicane Ianos in September 2020 was one of the strongest medicanes observed in the last 25 years. It was, like other medicanes, a very intense cyclone evolving from a baroclinic mid-latitude low into a tropical-like cyclone with an axisymmetric warm core. The dynamical elements necessary to improve the predictability of Ianos are explored with the use of simulations with the Met Office Unified Model (MetUM) at 2.2 km grid spacing for five different initialisation times, from 4 to 2 d before Ianos's landfall. Simulations are also performed with the sea surface temperature (SST) uniformly increased and decreased by 2 K from analysis to explore the impact of enhanced and reduced sea surface fluxes on Ianos's evolution. All the simulations with +2 K SST are able to simulate Medicane Ianos, albeit too intensely. The simulations with control SST initialised at the two earliest times fail to capture intense preceding precipitation events at the right locations and the subsequent development of Ianos. Amongst the simulations with −2 K SST, only the one initialised at the latest time develops the medicane. Links between sea surface fluxes and upper-level baroclinic processes are investigated. We find three elements that are important for Ianos's development. First, an area of low-valued potential vorticity (PV), termed a “low-PV bubble”, formed within a trough above where Ianos developed; diabatic heating associated with a preceding precipitation event triggered a balanced divergent flow in the upper levels, which contributed to the creation and maintenance of this low-PV bubble as shown by results from a semi-geostrophic inversion tool. Second, a quasi-geostrophic ascent was forced by middle and upper levels during Ianos's cyclogenesis. It is partially associated with the geostrophic vorticity advection, which is enhanced by the growth and advection of the low-PV bubble. Third, diabatic heating dominated by deep convection formed a vertical PV tower during Ianos's intensification and continued to produce diabatically induced divergent outflow aloft, thus sustaining Ianos’s development. Simulations missing any of these three elements do not develop Medicane Ianos. Our results imply the novel finding that preceding convection was essential for the subsequent development of Ianos, highlighting the importance of the interactions between near-surface small-scale diabatic processes and the upper-level quasi-geostrophic flow. A warmer SST strengthens the processes and thus enables Ianos to be predicted in simulations initiated at the earlier times.

Associations between extreme heat and hospital length of stay among those hospitalised with cardiovascular disease in Greater London: a population-based longitudinal study between 2007–2019

BackgroundIt is unclear whether a relationship exists between extreme heat and hospital length of stay in the UK. Using healthcare and climate data this study explores the effects of extreme heat on hospital length of stay for individuals hospitalised with cardiovascular disease, a common heat-sensitive condition, in Greater London. MethodsThis longitudinal study included patients registered to General Practices in Greater London (8·908 million inhabitants), hospitalised with cardiovascular disease during summer months of 2007–19. Administrative healthcare data was derived from Clinical Practice Research Datalink and Hospital Episode Statistics. Climate data from the Meteorological Office. The study exposure was extreme heat on day of hospital admission, defined using maximum daily temperature as per the UK Health Security Agency (low-level [28–31·9°C]; medium-level [32–39·9°C]; high-level [≥40°C]). The study outcome was hospital length of stay (days). In main analyses, linear fixed-effects models were used with fixed-effects for practice-by-calendar-day and practice-by-year and inclusion of covariates (daily rainfall, age, sex, deprivation, primary diagnosis, comorbidity). Findings24 435 hospital admissions were included. There were 72 low-level heat days, 11 medium-level heat days and 0 high-level heat days. There was no evidence of association between extreme heat and length of stay in unadjusted (0·03; 95% CI –0·10 to 0·15), and fully adjusted models (0·03; 95% CI –0·09 to 0·16). During medium-level heat, there was a significant association in unadjusted models (–0·27; 95% CI –0·50 to –0·03), and models adjusted by rainfall (–0·26; 95% CI –0·50 to –0·03), age (–0·25; 95% CI –0·45 to –0·04), sex (–0·25; 95% CI –0·46 to –0·05) and deprivation (–0·25; 95% CI –0·45 to –0·04). However, accounting for primary diagnosis (–0·15; 95% CI –0·44 to 0·14) and comorbidity (–0·17; 95% CI –0·46 to 0·12), there was no longer a significant association. InterpretationThis first UK-based study did not identify an association between low-level or medium-level heat on day of hospital admission and hospital length of stay. Further work is needed to evaluate the effects of extreme heat on the UK health system. FundingRP discloses funding from the Oxford Martin School as part of the Future of Cooling Programme. This funding allowed access to the data and paid for research assistant time to support the data management and partial analysis. The funder had no role in designing the question, the analysis or the interpretation of the results.

Assessing global ensemble systems’ forecasts of tropical cyclone genesis in differing environmental flow regimes in the western North Pacific

The forecast probability of tropical cyclone (TC) genesis in the western North Pacific from 2017 to 2020 was investigated using global ensembles from the Japan Meteorological Agency (JMA), the European Centre for Medium-Range Weather Forecasts (ECMWF), the U.S. National Centers for Environmental Prediction (NCEP), and the Met Office in the United Kingdom (UKMO). The time of TC genesis was defined as the time the TCs were first recorded in the best-track data (Case 1) and as the time they reached the intensity of a Tropical Storm (Case 2). The results in Case 1 showed that differences between the forecast probability based on each global ensemble were large, even for a 1-day forecast, and that mean probability were from 18 % to 74 %. The forecasts based on the NCEP had a large frequency bias and overpredicted TC genesis events. The results indicated that the representation of genesis events differed greatly between global ensembles. The effectiveness of multiple ensembles was investigated. The results from the threat score and the false alarm ratio indicated that multiple ensembles had skillful forecasts. When the forecast probability was examined for environmental patterns of synoptic low-level flow, the mean 5-day forecast probability was highest for the pattern in the confluence region. The results also showed that the forecast probability was much larger in Case 2 than in Case 1. In all global ensembles, the mean probability with a lead time of up to 1-week was below 10 % for both Case 1 and 2. This result indicates that even with today's operational forecasting systems, it is difficult to regularly predict TC genesis events with a 1-week lead time with high confidence. These results provide a better understanding of TC genesis forecast products in each global ensemble and will be useful information when multiple-ensemble products are created.

The Relative Importance of Ocean Advection and Surface Heat Fluxes During the Madden–Julian Oscillation in a Coupled Ocean–Atmosphere Model

AbstractIntraseasonal variability of ocean surface mixed layer temperature (MLT) in the tropics can be linked to the Madden–Julian Oscillation (MJO), the main source of intraseasonal atmospheric variability in the tropics. Here, we conduct a boreal winter mixed layer heat budget using 10‐day forecast composites of a coupled ocean–atmosphere Numerical Weather Prediction model of the UK Met Office to reveal that ocean advection plays a major role in modulating intraseasonal anomalies of MLT over the tropical Indian Ocean and the Maritime Continent. Large scale ( 10) intraseasonal anomalies of MLT ( 0.1 C) are driven by net surface heat flux. Ocean advection dominates at smaller horizontal scales ( 1), contributing up to 0.5 C to the intraseasonal MLT anomaly. Prior to the development of the enhanced MJO convection in the western Indian Ocean (phases 8 and 1), ocean advection reinforces the net heat flux warming in this region. However, ocean advection opposes the net heat flux warming in the Maritime Continent prior to the development of suppressed MJO convection in this region. When the MJO convection develops over the central Indian Ocean (phase 3), ocean advection (net surface heat flux) drives the intraseasonal MLT anomalies in the western Indian Ocean (central Indian Ocean and the Maritime Continent). Our results demonstrate the importance of ocean dynamics during the initiation and growth of the MJO, and raise implications for models that do not resolve these processes.

Cold-Frontal Rainbands over the United Kingdom: Sensitivity of Precipitation Processes to Microphysics Schemes in WRF Simulations

Abstract A narrow cold-frontal rainband (NCFR) and wide cold-frontal rainband (WCFR) over the United Kingdom on 24 January 2018 are selected to evaluate the sensitivity of cold-season precipitation to three bulk cloud microphysics schemes in the Weather Research and Forecasting (WRF) Model. The three simulations tend to overpredict the intensity and the areal coverage of NCFRs but underpredict those of WCFRs against the Met Office radar imagery. Nonetheless, the WRF double-moment 6-class (WDM6) simulation produces the most realistic NCFR and WCFR. More specifically, the intensity of the NCFR in the WDM6 simulation is overpredicted in the developing stage and underpredicted in the dissipating stage when compared to the Thompson and Morrison simulations. This phenomenon is mainly attributed to the rain mixing ratio at 1 km. The more intense and larger area of the WCFR in the WDM6 simulation is associated with more low-level snow, graupel, and rain than the other two simulations. In the WDM6 simulation, the larger low-level snow mixing ratios are due to the higher rates of aggregation between cloud ice and snow, whereas the larger rain mixing ratio is due to higher melting rates. Thus, differences in low-level ice-phase processes between microphysics schemes are large, strongly influencing the intensity of WCFRs, but the differences in warm-rain processes are smaller. Additionally, the small size of raindrops in the WDM6 simulation leads to wider and more intense WCFR as these raindrops are preferentially sent rearward relative to the cold front. Significance Statement Models are useful tools to predict weather but have errors in predicting different weather types. In the United Kingdom, precipitation is often predicted to be too strong at cold fronts and too weak behind the fronts compared to radar observations. Choosing different options for how precipitation is represented in one model produced different precipitation forecasts, with WDM6 being the best. One reason why WDM6 was the best was because it produced more and smaller raindrops, which would be transported behind the front, and it had higher melting rates at low levels, resulting in more precipitation behind the fronts than other options. Our results help identify why different options produce different forecasts, leading to possible future improvements in these options.

Long-range transport of coarse mineral dust: an evaluation of the Met Office Unified Model against aircraft observations

Abstract. Coarse mineral dust particles have been observed much further from the Sahara than expected based on theory. They have impacts different to finer particles on Earth's radiative budget, as well as carbon and hydrological cycles, though they tend to be under-represented in climate models. We use measurements of the full dust size distribution from aircraft campaigns over the Sahara, Canaries, Cabo Verde and Caribbean. We assess the observed and modelled dust size distribution over long-range transport at high vertical resolution using the Met Office Unified Model, which represents dust up to 63.2 µm diameter, greater than most climate models. We show that the model generally replicates the vertical distribution of the total dust mass but transports larger dust particles too low in the atmosphere. Importantly, coarse particles in the model are deposited too quickly, resulting in an underestimation of dust mass that is exacerbated with westwards transport; the 20–63 µm dust mass contribution between 2 and 3.7 km altitude is underestimated by factors of up to 11 in the Sahara, 140 in the Canaries and 240 in Cabo Verde. In the Caribbean, there is negligible modelled contribution of d > 20 µm particles to total mass, compared to 10 % in the observations. This work adds to the growing body of research that demonstrates the need for a process-based evaluation of climate model dust simulations to identify where improvements could be implemented.

The impact of weather patterns on inter-annual crop yield variability

Inter-annual variations in crop production have significant implications for global food security, economic stability, and environmental sustainability. Existing crop yield prediction models primarily using meteorological variables may not adequately encapsulate the full breadth of weather influences on crop development processes, such as compound or extreme events. Incorporating weather patterns into crop models could provide a more comprehensive understanding of the environmental conditions affecting growth, enabling more accurate and earlier yield predictions.Our study examines 30 distinct UK Met Office weather patterns (MO30) based on mean sea level pressure. We investigate their association with weather conditions that limit winter wheat yield in the UK (1990–2020). Blocked, negative North Atlantic Oscillation (NAO) patterns create the highest risk of temperatures that are below optimal for crop yield. However, the connection between weather patterns and yield is complex, with differing effects at a regional scale and even at which point in the growth cycle they appear. It was found that anticyclonic weather patterns during sowing, emergence, vernalisation, anthesis, and grain filling exhibit a relationship with good crop yields with a Spearman correlation coefficient of up to 0.55 for a single weather pattern (WP3 during vernalisation in South East England), whilst cyclonic patterns can help during the terminal spikelet phenological phase. The strongest positive correlations were during sowing, emergence, and vernalisation, whilst the largest negatives were observed in anthesis and grain filling.The potential of combining weather patterns with existing crop simulation models to produce earlier and more accurate yield predictions is shown. This would enable effective crop management and climate mitigation strategies, critical to strengthening food security. Projected changes in weather pattern occurrences in the late 21st century will likely reduce crop yields. This is due to increased cyclonic weather patterns, which bring warmer, wetter conditions during the wheat's vernalisation stage, followed by warmer, drier conditions during the anthesis and grain-filling phases.

Storm Ciarán – synoptic evolution and warning strategy of the intense mid‐latitude windstorm affecting parts of Northwest Europe on 1/2 November 2023

AbstractStorm Ciarán affected northern France, the Channel Islands and the United Kingdom as an intense North Atlantic depression on 1/2 November 2023, bringing damaging winds, large waves, heavy rain and an intense convective development spawning a tornado on Jersey. Amidst an extended period of stormy weather across Northwest Europe, Storm Ciarán was probably the most significant windstorm to affect the Channel Islands and northern France since the Great Storm of 1987 or Storm Lothar in 1999. Here we explore the storm’s evolution, forecasting strategies and challenges and climatological context from the perspective of Met Office operational meteorologists.

Rainfall Enhancement Downwind of Hills Due to Stationary Waves on the Melting Level and the Extreme Rainfall of December 2015 in the Lake District of Northwest England

This paper investigates how stationary gravity waves generated by flow over orography enhance rainfall, with particular attention to the role of induced waves in the melting level. The findings reveal a new mechanism by which gravity wave flow focuses precipitation, amplifying rainfall intensity downwind of hills. This mechanism, which depends on the differential velocities of rain and snow, offers fresh insights into how orographic effects can intensify rainfall. A two-dimensional diagnostic model based on linear gravity wave theory is used to investigate the record-breaking rainfall of December 2015 in the Lake District of northwest England. The pattern of ascent is shown to have a qualitatively good fit to that of the Met Office’s operational high-resolution UKV model averaged over 24 h, suggesting that orographically excited stationary waves were the principal cause of the rain. Precipitation trajectories imply that a persistent downstream elevated wave caused by the Isle of Man supported a spray of seeding ice particles directed towards the Lake District, and that these grew whilst suspended in strong upslope flow before being focused by the undulating melting-level into intense shafts of rain.

Turbulent Heat Fluxes over Arctic Sea Ice: Measurements and Evaluation of Recent Parameterizations

We present direct eddy covariance measurements of the surface heat flux in sea ice over a wide range of conditions across the Arctic Ocean made during two research cruises. Photographic imagery of the surface around the ship provides a local, in situ estimate of the ice fraction. Aerodynamically rough conditions prevail for the majority of the time in the consolidated pack ice. The results are analyzed in the framework of a recently-developed parameterization scheme in which the exchange coefficients over ice are functions of a roughness Reynolds number, R*, hence account for aerodynamic roughness variability. This parameterization accurately represents the measured fluxes under all conditions, while under aerodynamically rough conditions the existing parameterizations from both the Met Office Unified Model, and ECMWF Integrated Forecast System overestimate the fluxes. The results corroborate those of a previous airborne study over the marginal ice zone, and encompass a wider range of atmospheric stability conditions.

Short-term and long-term exposure to particles and their consequences in Poldokhtar City (Iran)

In Iran's biggest towns, deaths and hospitalizations from respiratory and cardiovascular diseases have a strong association with PM2.5 pollution concentrations. The WHO recommends assessing the health impacts using the Air Quality and Health Evaluation approach (Air Q 2.2.3). Data of particulates on both clear, dusty days have been provided by the Meteorology Office for Lorestan. Results indicated that in terms of mean AQI, May (162.46), July (121.7), and April (110.23) are the most polluted months in Poldokhtar city in 2022. May (16 days), July (6 days), March (5 days), and April (4 days) are the most contaminated months of the total number of polluted days. The days having the highest amounts of pollution in terms of the daily mean AQI are May 17th (407), April 10th (402), May 24th (393), July 31st (351), and April 18th (341). The maps extracted from HYSPLIT showed that the origin of the dust entering the city of Poldokhtar is the arid and semi-arid regions of Saudi Arabia, Egypt, Kuwait, and Turkey. May shows the maximum amount of pollution in comparison to other months, as shown by the mean AQI of 162.46. Furthermore, with an AQI score of 407 on May 17, it is assumed to be the most polluted day of the year. Hospitalized people who had respiratory diseases were most severely impacted by the short-term adverse effects of fine dust inhalation.