scholarly journals Observed slump of sea land breeze in Brisbane under the effect of aerosols from remote transport during 2019 Australia mega fire events

2021 ◽  
Author(s):  
Lixing Shen ◽  
Chuanfeng Zhao ◽  
Xingchuan Yang ◽  
Yikun Yang ◽  
Ping Zhou
Keyword(s):  
Wind Field ◽  
Large Scale ◽  
Reanalysis Data ◽  
Feedback Mechanism ◽  
Coastal Pollution ◽  
Land Breeze ◽  
Heating Effect ◽  
Free Diffusion ◽  
Pollution Dispersion ◽  
Aerosol Emission

Abstract. The 2019 Australia mega fires were unprecedented considering its intensity and consistency. There have been many researches on the environmental and ecological effects of the mega fires, most of which focused on the effect of huge aerosol loadings and the ecological devastation. Sea land breeze (SLB) is a regional thermodynamic circulation closely related to coastal pollution dispersion yet few have looked into how it is influenced by different types of aerosols transported from either nearby or remote areas. Mega fires provide an optimal scenario of large aerosol loadings. Near the coastal site of Brisbane Archerfield during January in 2020 when mega fires were the strongest, reanalysis data from Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) showed that mega fires did release huge amounts of aerosols, making aerosol optical depth (AOD) of total aerosols, Black Carbon (BC) and Organic Carbon (OC) approximately 240 %, 425 %, 630 % of the averages of other non-fire years. Using 20 years’ wind observations of hourly time resolution from global observation network managed by National Oceanic and Atmospheric Administration (NOAA), we found that SLB day number during that month was only four, accounting for 33.3 % of the multi-years’ average. The land wind (LW) speed and sea wind (SW) speed also decreased by 22.3 % and 14.8 % compared with their averages respectively. Surprisingly, fire spot and fire radiative power (FRP) analysis showed that heating effect and aerosol emission of the nearby fire spots were not the main cause of local SLB anomaly while the remote transport of aerosols from the fire center was mainly responsible for the decrease of SW, which was partially offset by the heating effect of nearby fire spots and warming effect of long-range transported BC and CO2. The large scale cooling effect of aerosols on sea surface temperature (SST) and the burst of BC contributed to the slump of LW. The remote transport of total aerosols was mainly caused by free diffusion while large scale wind field played a secondary role at 500 m. Large scale wind field played a more important role in aerosol transport at 3 km than at 500 m, especially for the gathered smoke, but free diffusion remained the major contributor. The decrease of SLB speed boosted the local accumulation of aerosols, thus further made SLB speed decrease, forming a positive feedback mechanism.

scholarly journals Observed slump of sea land breeze in Brisbane under the effect of aerosols from remote transport during 2019 Australian mega fire events

2022 ◽  
Vol 22 (1) ◽  
pp. 419-439
Author(s):  
Lixing Shen ◽  
Chuanfeng Zhao ◽  
Xingchuan Yang ◽  
Yikun Yang ◽  
Ping Zhou
Keyword(s):  
Wind Field ◽  
Large Scale ◽  
Reanalysis Data ◽  
Feedback Mechanism ◽  
Coastal Pollution ◽  
Land Breeze ◽  
Free Diffusion ◽  
Pollution Dispersion ◽  
Aerosol Emission ◽  
Radiative Power

Abstract. The 2019 Australian mega fires were unprecedented considering their intensity and consistency. There has been much research on the environmental and ecological effects of these mega fires, most of which focused on the effect of huge aerosol loadings and the ecological devastation. Sea land breeze (SLB) is a regional thermodynamic circulation closely related to coastal pollution dispersion, yet few have looked into how it is influenced by different types of aerosols transported from either nearby or remote areas. Mega fires provide an optimal scenario of large aerosol emissions. Near the coastal site of Brisbane Archerfield during January 2020, when mega fires were the strongest, reanalysis data from Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) showed that mega fires did release huge amounts of aerosols, making aerosol optical depth (AOD) of total aerosols, black carbon (BC) and organic carbon (OC) approximately 240 %, 425 % and 630 % of the averages in other non-fire years. Using 20 years' wind observations of hourly time resolution from a global observation network managed by the National Oceanic and Atmospheric Administration (NOAA), we found that the SLB day number during that month was only 4, accounting for 33.3 % of the multi-years' average. The land wind (LW) speed and sea wind (SW) speed also decreased by 22.3 % and 14.8 % compared with their averages respectively. Surprisingly, fire spot and fire radiative power (FRP) analysis showed that heating effects and aerosol emission of the nearby fire spots were not the main causes of the local SLB anomaly, while the remote transport of aerosols from the fire centre was mainly responsible for the decrease of SW, which was partially offset by the heating effect of nearby fire spots and the warming effect of long-range transported BC and CO2. The large-scale cooling effect of aerosols on sea surface temperature (SST) and the burst of BC contributed to the slump of LW. The remote transport of total aerosols was mainly caused by free diffusion, while the large-scale wind field played a secondary role at 500 m. The large-scale wind field played a more important role in aerosol transport at 3 km than at 500 m, especially for the gathered smoke, but free diffusion remained the major contributor. The decrease of SLB speed boosted the local accumulation of aerosols, thus making SLB speed decrease further, forming a positive feedback mechanism.

Method for Identifying and Clustering Rossby Wave Breaking Events in the Northern Hemisphere

2021 ◽  
pp. 17-28
Author(s):  
A. V. Gochakov ◽  
◽  
O. Yu. Antokhina ◽  
V. N. Krupchatnikov ◽  
Yu. V. Martynova ◽  
...  
Keyword(s):  
Rossby Wave ◽  
Potential Vorticity ◽  
Wave Breaking ◽  
Large Scale ◽  
Method Development ◽  
Spatial Clustering ◽  
Potential Temperature ◽  
Reanalysis Data ◽  
Rossby Wave Breaking ◽  
Dynamic Phenomena

Many large-scale dynamic phenomena in the Earth’s atmosphere are associated with the processes of propagation and breaking of Rossby waves. A new method for identifying the Rossby wave breaking (RWB) is proposed. It is based on the detection of breakings centers by analyzing the shape of the contours of potential vorticity or temperature on quasimaterial surfaces: isentropic and iserthelic (surfaces of constant Ertel potential vorticity (PV)), with further RWB center clustering to larger regions. The method is applied to the set of constant PV levels (0.3 to 9.8 PVU with a step of 0.5 PVU) at the level of potential temperature of 350 K for 12:00 UTC. The ERA-Interim reanalysis data from 1979 to 2019 are used for the method development. The type of RWB (cyclonic/anticyclonic), its area and center are determined by analyzing the vortex geometry at each PV level for every day. The RWBs obtained at this stage are designated as elementary breakings. Density-Based Spatial Clustering of Applications with Noise algorithm (DBSCAN) was applied to all elementary breakings for each month. As a result, a graphic dataset describing locations and dynamics of RWBs for every month from 1979 to 2019 is formed. The RWB frequency is also evaluated for each longitude, taking into account the duration of each RWB and the number of levels involved, as well as the anomalies of these parameters.

scholarly journals Using Empirical Orthogonal Teleconnections to evaluate interannual rainfall variability over China in the Met Office Unified Model Global Atmosphere 6.0 and Global Coupled 2.0 configurations

2017 ◽  
Author(s):  
Claudia Christine Stephan ◽  
Nicholas P. Klingaman ◽  
Pier Luigi Vidale ◽  
Andrew G. Turner ◽  
Marie-Estelle Demory ◽  
...  
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Rainfall Variability ◽  
Reanalysis Data ◽  
Horizontal Resolution ◽  
Unified Model ◽  
Seasonal Precipitation ◽  
Climate Simulations ◽  
Interannual Rainfall Variability ◽  
The Mean

Abstract. Six climate simulations of the Met Office Unified Model Global Atmosphere 6.0 and Global Coupled 2.0 configurations are evaluated against observations and reanalysis data for their ability to simulate the mean state and year-to-year variability of precipitation over China. To analyze the sensitivity to air-sea coupling and horizontal resolution, atmosphere-only and coupled integrations at atmospheric horizontal resolutions of N96, N216 and N512 (corresponding to ~ 200, 90, and 40 km in the zonal direction at the equator, respectively) are analyzed. The mean and interannual variance of seasonal precipitation are too high in all simulations over China, but improve with finer resolution and coupling. Empirical Orthogonal Teleconnection (EOT) analysis is applied to simulated and observed precipitation to identify spatial patterns of temporally coherent interannual variability in seasonal precipitation. To connect these patterns to large-scale atmospheric and coupled air-sea processes, atmospheric and oceanic fields are regressed onto the corresponding seasonal-mean timeseries. All simulations reproduce the observed leading pattern of interannual rainfall variability in winter, spring and autumn; the leading pattern in summer is present in all but one simulation. However, only in two simulations are the four leading patterns associated with the observed physical mechanisms. Coupled simulations capture more observed patterns of variability and associate more of them with the correct physical mechanism, compared to atmosphere-only simulations at the same resolution. However, finer resolution does not improve the fidelity of these patterns or their associated mechanisms. This shows that evaluating climate models by only geographical distribution of mean precipitation and its interannual variance is insufficient. The EOT analysis adds knowledge about coherent variability and associated mechanisms.

scholarly journals Utility of daily vs. monthly large-scale climate data: an intercomparison of two statistical downscaling methods

2007 ◽  
Vol 4 (5) ◽  
pp. 3413-3440 ◽  
Author(s):  
E. P. Maurer ◽  
H. G. Hidalgo
Keyword(s):  
Statistical Downscaling ◽  
General Circulation ◽  
Large Scale ◽  
Impact Analysis ◽  
Climate Model ◽  
Daily Precipitation ◽  
Circulation Model ◽  
Reanalysis Data ◽  
Temperature Extremes ◽  
Daily Data

Abstract. Downscaling of climate model data is essential to most impact analysis. We compare two methods of statistical downscaling to produce continuous, gridded time series of precipitation and surface air temperature at a 1/8-degree (approximately 140 km² per grid cell) resolution over the western U.S. We use NCEP/NCAR Reanalysis data from 1950–1999 as a surrogate General Circulation Model (GCM). The two methods included are constructed analogues (CA) and a bias correction and spatial downscaling (BCSD), both of which have been shown to be skillful in different settings, and BCSD has been used extensively in hydrologic impact analysis. Both methods use the coarse scale Reanalysis fields of precipitation and temperature as predictors of the corresponding fine scale fields. CA downscales daily large-scale data directly and BCSD downscales monthly data, with a random resampling technique to generate daily values. The methods produce comparable skill in producing downscaled, gridded fields of precipitation and temperatures at a monthly and seasonal level. For daily precipitation, both methods exhibit some skill in reproducing both observed wet and dry extremes and the difference between the methods is not significant, reflecting the general low skill in daily precipitation variability in the reanalysis data. For low temperature extremes, the CA method produces greater downscaling skill than BCSD for fall and winter seasons. For high temperature extremes, CA demonstrates higher skill than BCSD in summer. We find that the choice of most appropriate downscaling technique depends on the variables, seasons, and regions of interest, on the availability of daily data, and whether the day to day correspondence of weather from the GCM needs to be reproduced for some applications. The ability to produce skillful downscaled daily data depends primarily on the ability of the climate model to show daily skill.

Interannual Rainfall Extremes over Southwest Western Australia Linked to Indian Ocean Climate Variability

2006 ◽  
Vol 19 (10) ◽  
pp. 1948-1969 ◽  
Author(s):  
Matthew H. England ◽  
Caroline C. Ummenhofer ◽  
Agus Santoso
Keyword(s):  
Indian Ocean ◽  
Western Australia ◽  
Wind Field ◽  
Large Scale ◽  
Extreme Rainfall ◽  
Ekman Transport ◽  
Eastern Indian Ocean ◽  
Basin Scale ◽  
Rainfall Extremes ◽  
The Indian Ocean

Abstract Interannual rainfall extremes over southwest Western Australia (SWWA) are examined using observations, reanalysis data, and a long-term natural integration of the global coupled climate system. The authors reveal a characteristic dipole pattern of Indian Ocean sea surface temperature (SST) anomalies during extreme rainfall years, remarkably consistent between the reanalysis fields and the coupled climate model but different from most previous definitions of SST dipoles in the region. In particular, the dipole exhibits peak amplitudes in the eastern Indian Ocean adjacent to the west coast of Australia. During dry years, anomalously cool waters appear in the tropical/subtropical eastern Indian Ocean, adjacent to a region of unusually warm water in the subtropics off SWWA. This dipole of anomalous SST seesaws in sign between dry and wet years and appears to occur in phase with a large-scale reorganization of winds over the tropical/subtropical Indian Ocean. The wind field alters SST via anomalous Ekman transport in the tropical Indian Ocean and via anomalous air–sea heat fluxes in the subtropics. The winds also change the large-scale advection of moisture onto the SWWA coast. At the basin scale, the anomalous wind field can be interpreted as an acceleration (deceleration) of the Indian Ocean climatological mean anticyclone during dry (wet) years. In addition, dry (wet) years see a strengthening (weakening) and coinciding southward (northward) shift of the subpolar westerlies, which results in a similar southward (northward) shift of the rain-bearing fronts associated with the subpolar front. A link is also noted between extreme rainfall years and the Indian Ocean Dipole (IOD). Namely, in some years the IOD acts to reinforce the eastern tropical pole of SST described above, and to strengthen wind anomalies along the northern flank of the Indian Ocean anticyclone. In this manner, both tropical and extratropical processes in the Indian Ocean generate SST and wind anomalies off SWWA, which lead to moisture transport and rainfall extremes in the region. An analysis of the seasonal evolution of the climate extremes reveals a progressive amplification of anomalies in SST and atmospheric circulation toward a wintertime maximum, coinciding with the season of highest SWWA rainfall. The anomalies in SST can appear as early as the summertime months, however, which may have important implications for predictability of SWWA rainfall extremes.

A novel method to identify subseasonal clustering episodes of extreme precipitation events and their contribution to large accumulations

2021 ◽  
Author(s):  
Jérôme Kopp ◽  
Pauline Rivoire ◽  
S. Mubashshir Ali ◽  
Yannick Barton ◽  
Olivia Martius
Keyword(s):  
Time Scales ◽  
Extreme Precipitation ◽  
Large Scale ◽  
Time Window ◽  
Heat Waves ◽  
Reanalysis Data ◽  
Data Set ◽  
Temporal Clustering ◽  
Extreme Precipitation Events ◽  
Precipitation Events

<p>Temporal clustering of extreme precipitation events on subseasonal time scales is a type of compound event, which can cause large precipitation accumulations and lead to floods. We present a novel count-based procedure to identify subseasonal clustering of extreme precipitation events. Furthermore, we introduce two metrics to characterise the frequency of subseasonal clustering episodes and their relevance for large precipitation accumulations. The advantage of this approach is that it does not require the investigated variable (here precipitation) to satisfy any specific statistical properties. Applying this methodology to the ERA5 reanalysis data set, we identify regions where subseasonal clustering of annual high precipitation percentiles occurs frequently and contributes substantially to large precipitation accumulations. Those regions are the east and northeast of the Asian continent (north of Yellow Sea, in the Chinese provinces of Hebei, Jilin and Liaoning; North and South Korea; Siberia and east of Mongolia), central Canada and south of California, Afghanistan, Pakistan, the southeast of the Iberian Peninsula, and the north of Argentina and south of Bolivia. Our method is robust with respect to the parameters used to define the extreme events (the percentile threshold and the run length) and the length of the subseasonal time window (here 2 – 4 weeks). The procedure could also be used to identify temporal clustering of other variables (e.g. heat waves) and can be applied on different time scales (e.g. for drought years). <span>For a complementary study on the subseasonal clustering of European extreme precipitation events and its relationship to large-scale atmospheric drivers, please refer to Barton et al.</span></p>

Increased frequency of Eurasian double jets linked to summer heat extremes in Europe

2021 ◽  
Author(s):  
Efi Rousi ◽  
Kai Kornhuber ◽  
Goratz Beobide Arsuaga ◽  
Fei Luo ◽  
Dim Coumou
Keyword(s):  
Zonal Wind ◽  
Large Scale ◽  
Driving Forces ◽  
Linear Regression Analysis ◽  
Reanalysis Data ◽  
Self Organizing Maps ◽  
Upper Troposphere ◽  
The North ◽  
Heat Extremes ◽  
Different Levels

<p>Persistent summer extremes, such as heatwaves and droughts, can have considerable impacts on nature and societies. There is evidence that weather persistence has increased in Europe over the past decades, in association to changes in atmosphere dynamics, but uncertainties remain and the driving forces are not yet well understood. </p><p>Particularly for Europe, the jet stream may affect surface weather significantly by modulating the North Atlantic storm tracks. Here, we examine the hypothesis that high-latitude warming and decreased westerlies in summer result in more double jets, consisting of two distinct maxima of the zonal wind in the upper troposphere, over the Eurasian sector. Previous work has shown that such double jet states are related to persistent blocking-like circulation in the mid-latitudes. </p><p>We adapt a dynamical perspective of heat extreme trends by looking at large scale circulation and in particular, changes in the zonal mean zonal wind in different levels of the upper troposphere. We define clusters of jet states with the use of Self-Organizing Maps and analyze their characteristics. We find an increase in frequency and persistence of a cluster of double jet states for the period 1979-2019 during July-August (in ERA5 reanalysis data). Those states are linked to increased surface temperature and more frequent heatwaves compared to climatology over western, central, and northern Europe. Significant positive double jet anomalies are found to be dominant in the days preceding and/or coinciding with some of the most intense historical heatwaves in Europe, such as those of 2003 and 2018. A linear regression analysis shows that the increase in frequency and persistence of double jet states may explain part of the strong upward trend in heat extremes over these European regions.</p>

In-cloud scavenging scheme for sectional aerosol modules – implementation in the framework of the Sectional Aerosol module for Large Scale Applications version 2.0 (SALSA2.0) global aerosol module

2021 ◽  
Author(s):  
Eemeli Holopainen ◽  
Harri Kokkola ◽  
Anton Laakso ◽  
Thomas Kühn
Keyword(s):  
Wet Deposition ◽  
Large Scale ◽  
Climate Model ◽  
Radiation Budget ◽  
Cloud Formation ◽  
The Arctic ◽  
Vertical Profiles ◽  
Size Classes ◽  
Aerosol Emission ◽  
Aerosol Module

<p><span>Black carbon (BC) affects the radiation budget of the Earth by absorbing solar radiation, darkening snow and ice covers, and influencing cloud formation and life cycle. Modelling BC in remote regions, such as the Arctic, has large inter-model variability which causes variation in the modelled aerosol effect over the Arctic. This variability can be due to differences in the transport of aerosol species which is affected by how wet deposition is modelled. </span></p><p><span> In this study we developed an aerosol size-resolved in-cloud wet deposition scheme for liquid and ice clouds for models which use a size-segregated aerosol description. This scheme was tested in the ECHAM-HAMMOZ global aerosol-climate model. The scheme was compared to the original wet deposition scheme which uses fixed scavenging coefficients for different sized particles. The comparison included vertical profiles and mass and number wet deposition fluxes, and it showed that the current scheme produced spuriously long BC lifetimes when compared to the estimates made in other studies. Thus, to find a better setup for simulating aerosol lifetimes and vertical profiles we conducted simulations where we altered the aerosol emission distribution and hygroscopicity.</span></p><p><span> We compared the modelled BC vertical profiles to the ATom aircraft campaign measurements. In addition, we compared the aerosol lifetimes against those from AEROCOM model means. We found that, without further tuning, the current scheme overestimates the BC concentrations and lifetimes more than the fixed scavenging scheme when compared to the measurements. Sensitivity studies showed that the model skill of reproducing the measured vertical BC mass concentrations improved when BC emissions were directed to larger size classes, they were mixed with soluble compounds during emission, or BC-containing particles were transferred to soluble size classes after aging. These changes also produced atmospheric BC lifetimes which were closer to AEROCOM model means. The best comparison with the measured vertical profiles and estimated BC lifetimes was when BC was mixed with soluble aerosol compounds during emission.</span></p>

Enhancement of seasonal hydrological forecasting with “pattern-based” large-scale climatology 

2021 ◽  
Author(s):  
Wei Yang ◽  
Kean Foster ◽  
Ilias G. Pechlivanidis
Keyword(s):  
Large Scale ◽  
Fuzzy Rule ◽  
River System ◽  
Reanalysis Data ◽  
Streamflow Prediction ◽  
Seasonal Forecasts ◽  
Local Climate ◽  
Weather Regimes ◽  
Hydrological Forecasting ◽  
Teleconnection Indices

<p>The hydrological forecasting on seasonal (up to 7 months ahead) timescales is needed for decision-making in the hydropower sector. Being one of the vital influencing factors on hydro-production, a lot of development in dynamical forecasting at seasonal timescales has been done recently. However, the forecast bias still remains in different variables and consequently the skill of corresponding streamflow forecasts varies from month to month.</p><p>This study aims to explore the potential for “pattern-based” seasonal hydrological forecasts that make use of hydrological weather regimes and teleconnection indices to improve forecast skill. The work is built on the hypothesis that hydrological weather regimes and teleconnection indices can be used to select analogue years (setting an ensemble) from a record of historical precipitation and temperature data with which to force a hydrological model to generate tailored seasonal forecasts of reservoir inflows. The hydrological weather regimes have been classified based on the concept of fuzzy sets using the anomalies of daily mean sea level pressure from reanalysis data (i.e., ERA-Interim). Precipitation records, measured in the Umeälven river basin during 1981-2016 are used as local observations to optimize each fuzzy rule that describes a type of “average” variability of local climate in terms of the frequency and magnitude of precipitation events. The teleconnection indices are compiled from the Climate Prediction Center, which describe global atmospheric variability. The methodology has been applied to 84 sub-catchments across seven of the most important hydropower producing river systems in Northern Sweden. However, the performance for the Umeälven river system is of particular interest here.</p><p>Comparing to the traditional Ensemble Streamflow Prediction (ESP) method, the “pattern-based” seasonal hydrological forecasting shows a marked improvement, which is likely due to the weighted analogue-ESP approach as well as the selected analogues using the large-scale climate information described by hydrological weather regimes and teleconnection indices. The general performance of the two different approaches for selecting the analogues are similar; however, occasionally there are large differences in both the best analysis lead times and the spread of skill across the sub-catchments suggesting that those results are achieved using analogues based on different physical processes.</p>

Atmospheric forcing of coastal polynyas in the south-western Weddell Sea

2015 ◽  
Vol 27 (4) ◽  
pp. 388-402 ◽  
Author(s):  
Verena Haid ◽  
Ralph Timmermann ◽  
Lars Ebner ◽  
Günther Heinemann
Keyword(s):  
Sea Ice ◽  
Large Scale ◽  
Reanalysis Data ◽  
Ocean Model ◽  
Weddell Sea ◽  
Small Scale ◽  
Atmospheric Conditions ◽  
Atmospheric Forcing ◽  
The South ◽  
Ice Production

AbstractThe development of coastal polynyas, areas of enhanced heat flux and sea ice production strongly depend on atmospheric conditions. In Antarctica, measurements are scarce and models are essential for the investigation of polynyas. A robust quantification of polynya exchange processes in simulations relies on a realistic representation of atmospheric conditions in the forcing dataset. The sensitivity of simulated coastal polynyas in the south-western Weddell Sea to the atmospheric forcing is investigated with the Finite-Element Sea ice-Ocean Model (FESOM) using daily NCEP/NCAR reanalysis data (NCEP), 6 hourly Global Model Europe (GME) data and two different hourly datasets from the high-resolution Consortium for Small-Scale Modelling (COSMO) model. Results are compared for April to August in 2007–09. The two coarse-scale datasets often produce the extremes of the data range, while the finer-scale forcings yield results closer to the median. The GME experiment features the strongest winds and, therefore, the greatest polynya activity, especially over the eastern continental shelf. This results in higher volume and export of High Salinity Shelf Water than in the NCEP and COSMO runs. The largest discrepancies between simulations occur for 2008, probably due to differing representations of the ENSO pattern at high southern latitudes. The results suggest that the large-scale wind field is of primary importance for polynya development.

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