ResearchPad - oceanography:-general https://www.researchpad.co Default RSS Feed en-us © 2020 Newgen KnowledgeWorks <![CDATA[Stringent Emission Control Policies Can Provide Large Improvements in Air Quality and Public Health in India]]> https://www.researchpad.co/article/Nb1098b2b-f8d1-46e9-80dc-86448468f6a3 Air pollution is a major risk factor for human health in IndiaPopulation aging and growth will increase the disease burden due to exposure to particulate air pollution even under no emission changeStringent emission control reduces mortality rate in 2050 below 2015 levels although total premature mortality increases

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<![CDATA[New Approaches to Identifying and Reducing the Global Burden of Disease From Pollution]]> https://www.researchpad.co/article/Nbf7723dd-5647-4f8e-be7f-e9600ebe8e30

Abstract

Pollution from multiple sources causes significant disease and death worldwide. Some sources are legacy, such as heavy metals accumulated in soils, and some are current, such as particulate matter. Because the global burden of disease from pollution is so high, it is important to identify legacy and current sources and to develop and implement effective techniques to reduce human exposure. But many limitations exist in our understanding of the distribution and transport processes of pollutants themselves, as well as the complicated overprint of human behavior and susceptibility.

New approaches are being developed to identify and eliminate pollution in multiple environments. Community‐scale detection of geogenic arsenic and fluoride in Bangladesh is helping to map the distribution of these harmful elements in drinking water. Biosensors such as bees and their honey are being used to measure heavy metal contamination in cities such as Vancouver and Sydney. Drone‐based remote sensors are being used to map metal hot spots in soils from former mining regions in Zambia and Mozambique. The explosion of low‐cost air monitors has allowed researchers to build dense air quality sensing networks to capture ephemeral and local releases of harmful materials, building on other developments in personal exposure sensing. And citizen science is helping communities without adequate resources measure their own environments and in this way gain agency in controlling local pollution exposure sources and/or alerting authorities to environmental hazards. The future of GeoHealth will depend on building on these developments and others to protect a growing population from multiple pollution exposure risks.

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<![CDATA[Prevalence and Characterization of Staphylococcus aureus and Methicillin‐Resistant Staphylococcus aureus on Public Recreational Beaches in Northeast Ohio]]> https://www.researchpad.co/article/Nc2cf7d05-879f-4ce2-8ce7-439c7751833c

Abstract

Staphylococcus aureus can cause severe life‐threatening illnesses such as sepsis and endocarditis. Although S. aureus has been isolated from marine water and intertidal beach sand, only a few studies have been conducted to assess prevalence of S. aureus at freshwater recreational beaches. As such, we aimed to determine prevalence and molecular characteristics of S. aureus in water and sand at 10 freshwater recreational beaches in Northeast Ohio, USA. Samples were analyzed using standard microbiology methods, and resulting isolates were typed by spa typing and multilocus sequence typing. The overall prevalence of S. aureus in sand and water samples was 22.8% (64/280). The prevalence of methicillin‐resistant S. aureus (MRSA) was 8.2% (23/280). The highest prevalence was observed in summer (45.8%; 55/120) compared to fall (4.2%; 5/120) and spring (10.0%; 4/40). The overall prevalence of Panton‐Valentine leukocidin genes among S. aureus isolates was 21.4% (15/70), and 27 different spa types were identified. The results of this study indicate that beach sand and freshwater of Northeast Ohio were contaminated with S. aureus, including MRSA. The high prevalence of S. aureus in summer months and presence of human‐associated strains may indicate the possibility of role of human activity in S. aureus contamination of beach water and sand. While there are several possible routes for S. aureus contamination, S. aureus prevalence was higher in sites with wastewater treatment plants proximal to the beaches.

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<![CDATA[Identifying Environmental Risk Factors and Mapping the Distribution of West Nile Virus in an Endemic Region of North America]]> https://www.researchpad.co/article/N1df86112-92c0-47c4-bc7e-b31b90b1d872

Abstract

Understanding the geographic distribution of mosquito‐borne disease and mapping disease risk are important for prevention and control efforts. Mosquito‐borne viruses (arboviruses), such as West Nile virus (WNV), are highly dependent on environmental conditions. Therefore, the use of environmental data can help in making spatial predictions of disease distribution. We used geocoded human case data for 2004–2017 and population‐weighted control points in combination with multiple geospatial environmental data sets to assess the environmental drivers of WNV cases and to map relative infection risk in South Dakota, USA. We compared the effectiveness of (1) land cover and physiography data, (2) climate data, and (3) spectral data for mapping the risk of WNV in South Dakota. A final model combining all data sets was used to predict spatial patterns of disease transmission and characterize the associations between environmental factors and WNV risk. We used a boosted regression tree model to identify the most important variables driving WNV risk and generated risk maps by applying this model across the entire state. We found that combining multiple sources of environmental data resulted in the most accurate predictions. Elevation, late‐season humidity, and early‐season surface moisture were the most important predictors of disease distribution. Indices that quantified interannual variability of climatic conditions and land surface moisture were better predictors than interannual means. We suggest that combining measures of interannual environmental variability with static land cover and physiography variables can help to improve spatial predictions of arbovirus transmission risk.

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<![CDATA[Quantification of Rotavirus Diarrheal Risk Due to Hydroclimatic Extremes Over South Asia: Prospects of Satellite‐Based Observations in Detecting Outbreaks]]> https://www.researchpad.co/article/N1c514245-56ef-4185-b93e-7462d32dd374

Abstract

Rotavirus is the most common cause of diarrheal disease among children under 5. Especially in South Asia, rotavirus remains the leading cause of mortality in children due to diarrhea. As climatic extremes and safe water availability significantly influence diarrheal disease impacts in human populations, hydroclimatic information can be a potential tool for disease preparedness. In this study, we conducted a multivariate temporal and spatial assessment of 34 climate indices calculated from ground and satellite Earth observations to examine the role of temperature and rainfall extremes on the seasonality of rotavirus transmission in Bangladesh. We extracted rainfall data from the Global Precipitation Measurement and temperature data from the Moderate Resolution Imaging Spectroradiometer sensors to validate the analyses and explore the potential of a satellite‐based seasonal forecasting model. Our analyses found that the number of rainy days and nighttime temperature range from 16°C to 21°C are particularly influential on the winter transmission cycle of rotavirus. The lower number of wet days with suitable cold temperatures for an extended time accelerates the onset and intensity of the outbreaks. Temporal analysis over Dhaka also suggested that water logging during monsoon precipitation influences rotavirus outbreaks during a summer transmission cycle. The proposed model shows lag components, which allowed us to forecast the disease outbreaks 1 to 2 months in advance. The satellite data‐driven forecasts also effectively captured the increased vulnerability of dry‐cold regions of the country, compared to the wet‐warm regions.

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<![CDATA[Half‐Century Ammonia Emissions From Agricultural Systems in Southern Asia: Magnitude, Spatiotemporal Patterns, and Implications for Human Health]]> https://www.researchpad.co/article/N6ce220af-6a1d-4bf2-8e7a-31de41e56df3

Abstract

Much concern has been raised about the increasing threat to air quality and human health due to ammonia (NH3) emissions from agricultural systems, which is associated with the enrichment of reactive nitrogen (N) in southern Asia (SA), home of more than 60% the world's population (i.e., the people of West, central, East, South, and Southeast Asia). Southern Asia consumed more than half of the global synthetic N fertilizer and was the dominant region for livestock waste production since 2004. Excessive N application could lead to a rapid increase of NH3 in the atmosphere, resulting in severe air and water pollution in this region. However, there is still a lack of accurate estimates of NH3 emissions from agricultural systems. In this study, we simulated the agricultural NH3 fluxes in SA by coupling the Bidirectional NH3 exchange module (Bi‐NH3) from the Community Multi‐scale Air Quality model with the Dynamic Land Ecosystem Model. Our results indicated that NH3 emissions were 21.3 ± 3.9 Tg N yr−1 from SA agricultural systems with a rapidly increasing rate of ~0.3 Tg N yr−2 during 1961−2014. Among the emission sources, 10.8 Tg N yr−1 was released from synthetic N fertilizer use, and 10.4 ± 3.9 Tg N yr−1 was released from manure production in 2014. Ammonia emissions from China and India together accounted for 64% of the total amount in SA during 2000−2014. Our results imply that the increased NH3 emissions associated with high N inputs to croplands would likely be a significant threat to the environment and human health unless mitigation efforts are applied to reduce these emissions.

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<![CDATA[Spatial Accessibility and Social Inclusion: The Impact of Portugal's Last Health Reform]]> https://www.researchpad.co/article/Nfdc1fbe5-ff6a-4d7a-b20c-9f51d93f1a6a

Abstract

Health policies seek to promote access to health care and should provide appropriate geographical accessibility to each demographical functional group. The dispersal demand of health‐care services and the provision for such services at fixed locations contribute to the growth of inequality in their access. Therefore, the optimal distribution of health facilities over the space/area can lead to accessibility improvements and to the mitigation of the social exclusion of the groups considered most vulnerable. Requiring for such, the use of planning practices joined with accessibility measures. However, the capacities of Geographic Information Systems in determining and evaluating spatial accessibility in health system planning have not yet been fully exploited. This paper focuses on health‐care services planning based on accessibility measures grounded on the network analysis. The case study hinges on mainland Portugal. Different scenarios were developed to measure and compare impact on the population's accessibility. It distinguishes itself from other studies of accessibility measures by integrating network data in a spatial accessibility measure: the enhanced two‐step floating catchment area. The convenient location for health‐care facilities can increase the accessibility standards of the population and consequently reduce the economic and social costs incurred. Recently, the Portuguese government implemented a reform that aimed to improve, namely, the access and equity in meeting with the most urgent patients. It envisaged, in terms of equity, the allocation of 89 emergency network points that ensured more than 90% of the population be within 30 min from any one point in the network. Consequently, several emergency services were closed, namely, in rural areas. This reform highlighted the need to improve the quality of the emergency care, accessibility to each care facility, and equity in their access. Hence, accessibility measures become an efficient decision‐making tool, despite its absence in effective practice planning. According to an application of this type of measure, it was possible to verify which levels of accessibility were decreased, including the most disadvantaged people, with a larger time of dislocation of 12 min between 2001 and 2011.

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<![CDATA[Identifying Source Regions and the Distribution of Cross‐Tropopause Convective Outflow Over North America During the Warm Season]]> https://www.researchpad.co/article/Nba38a661-9ecf-4b13-ba55-b636e4f23237

Abstract

We analyzed the interaction between the North American monsoon anticyclone (NAMA) and summertime cross‐tropopause convective outflow by applying a trajectory analysis to a climatology of convective overshooting tops (OTs) identified in GOES satellite images, which covers the domain from 29°S to 68°N and from 205 to 1.25°W for the time period of May through September 2013. With this analysis we identified seasonally, geographically, and altitude‐dependent variability in NAMA strength and in cross‐tropopause convection that control their interaction. We find that the NAMA has the strongest impact on the circulation of convectively influenced air masses in August. Over the entire time period examined the intertropical convergence zone contributes the majority of OTs with a larger fraction of total OTs at 370 K (on average 70%) than at 400 K (on average 52%). During August at 370 K, the convectively influenced air masses within the NAMA circulation, as determined by the trajectory analysis, are primarily sourced from the intertropical convergence zone (monthly average of 66.1%), while at 400 K the Sierra Madres and the Central United States combined constitute the dominant source region (monthly average of 44.1%, compared to 36.6% of the combined Intertropical Convergence Zone regions). When evaluating the impact of cross‐tropopause convection on the composition and chemistry of the upper troposphere and lower stratosphere, the effects of the NAMA on both the distribution of convective outflow and the residence time of convectively influenced air masses within the NAMA region must be considered.

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<![CDATA[Insignificant QBO‐MJO Prediction Skill Relationship in the SubX and S2S Subseasonal Reforecasts]]> https://www.researchpad.co/article/N80d62339-fdd5-4539-8af8-fbb9aaf795dd

Abstract

The impact of the stratospheric quasi‐biennial oscillation (QBO) on the prediction of the tropospheric Madden‐Julian oscillation (MJO) is evaluated in reforecasts from nine models participating in subseasonal prediction projects, including the Subseasonal Experiment (SubX) and Subseasonal to Seasonal (S2S) projects. When MJO prediction skill is analyzed for December to February, MJO prediction skill is higher in the easterly phase of the QBO than the westerly phase, consistent with previous studies. However, the relationship between QBO phase and MJO prediction skill is not statistically significant for most models. This insignificant QBO‐MJO skill relationship is further confirmed by comparing two subseasonal reforecast experiments with the Community Earth System Model v1 using both a high‐top (46‐level) and low‐top (30‐level) version of the Community Atmosphere Model v5. While there are clear differences in the forecasted QBO between the two model top configurations, a negligible change is shown in the MJO prediction, indicating that the QBO in this model may not directly control the MJO prediction and supporting the insignificant QBO‐MJO skill relationship found in SubX and S2S models.

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<![CDATA[Considering the Role of Adaptive Evolution in Models of the Ocean and Climate System]]> https://www.researchpad.co/article/Nfe9152c8-e79c-4817-9ec2-593d8a0ca732

Abstract

Numerical models have been highly successful in simulating global carbon and nutrient cycles in today's ocean, together with observed spatial and temporal patterns of chlorophyll and plankton biomass at the surface. With this success has come some confidence in projecting the century‐scale response to continuing anthropogenic warming. There is also increasing interest in using such models to understand the role of plankton ecosystems in past oceans. However, today's marine environment is the product of billions of years of continual evolution—a process that continues today. In this paper, we address the questions of whether an assumption of species invariance is sufficient, and if not, under what circumstances current model projections might break down. To do this, we first identify the key timescales and questions asked of models. We then review how current marine ecosystem models work and what alternative approaches are available to account for evolution. We argue that for timescales of climate change overlapping with evolutionary timescales, accounting for evolution may to lead to very different projected outcomes regarding the timescales of ecosystem response and associated global biogeochemical cycling. This is particularly the case for past extinction events but may also be true in the future, depending on the eventual degree of anthropogenic disruption. The discipline of building new numerical models that incorporate evolution is also hugely beneficial in itself, as it forces us to question what we know about adaptive evolution, irrespective of its quantitative role in any specific event or environmental changes.

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<![CDATA[Efficacy of Climate Forcings in PDRMIP Models]]> https://www.researchpad.co/article/N277a3652-7bfa-4ad6-af18-e20af9ecbbd6

Abstract

Quantifying the efficacy of different climate forcings is important for understanding the real‐world climate sensitivity. This study presents a systematic multimodel analysis of different climate driver efficacies using simulations from the Precipitation Driver and Response Model Intercomparison Project (PDRMIP). Efficacies calculated from instantaneous radiative forcing deviate considerably from unity across forcing agents and models. Effective radiative forcing (ERF) is a better predictor of global mean near‐surface air temperature (GSAT) change. Efficacies are closest to one when ERF is computed using fixed sea surface temperature experiments and adjusted for land surface temperature changes using radiative kernels. Multimodel mean efficacies based on ERF are close to one for global perturbations of methane, sulfate, black carbon, and insolation, but there is notable intermodel spread. We do not find robust evidence that the geographic location of sulfate aerosol affects its efficacy. GSAT is found to respond more slowly to aerosol forcing than CO2 in the early stages of simulations. Despite these differences, we find that there is no evidence for an efficacy effect on historical GSAT trend estimates based on simulations with an impulse response model, nor on the resulting estimates of climate sensitivity derived from the historical period. However, the considerable intermodel spread in the computed efficacies means that we cannot rule out an efficacy‐induced bias of ±0.4 K in equilibrium climate sensitivity to CO2 doubling when estimated using the historical GSAT trend.

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<![CDATA[Reassessing Southern Ocean Air‐Sea CO 2 Flux Estimates With the Addition of Biogeochemical Float Observations]]> https://www.researchpad.co/article/N52b24823-1e08-4ca3-a65d-a54e81e297ed

Abstract

New estimates of pCO2 from profiling floats deployed by the Southern Ocean Carbon and Climate Observations and Modeling (SOCCOM) project have demonstrated the importance of wintertime outgassing south of the Polar Front, challenging the accepted magnitude of Southern Ocean carbon uptake (Gray et al., 2018, https://doi:10.1029/2018GL078013). Here, we put 3.5 years of SOCCOM observations into broader context with the global surface carbon dioxide database (Surface Ocean CO2 Atlas, SOCAT) by using the two interpolation methods currently used to assess the ocean models in the Global Carbon Budget (Le Quéré et al., 2018, https://doi:10.5194/essd-10-2141-2018) to create a ship‐only, a float‐weighted, and a combined estimate of Southern Ocean carbon fluxes (<35°S). In our ship‐only estimate, we calculate a mean uptake of −1.14 ± 0.19 Pg C/yr for 2015–2017, consistent with prior studies. The float‐weighted estimate yields a significantly lower Southern Ocean uptake of −0.35 ± 0.19 Pg C/yr. Subsampling of high‐resolution ocean biogeochemical process models indicates that some of the differences between float and ship‐only estimates of the Southern Ocean carbon flux can be explained by spatial and temporal sampling differences. The combined ship and float estimate minimizes the root‐mean‐square pCO2 difference between the mapped product and both data sets, giving a new Southern Ocean uptake of −0.75 ± 0.22 Pg C/yr, though with uncertainties that overlap the ship‐only estimate. An atmospheric inversion reveals that a shift of this magnitude in the contemporary Southern Ocean carbon flux must be compensated for by ocean or land sinks within the Southern Hemisphere.

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<![CDATA[Disentangling Drivers of Meteorological Droughts in the European Greater Alpine Region During the Last Two Centuries]]> https://www.researchpad.co/article/N1dd11cc4-1cd6-404e-8c74-4b242dc87ec9

Abstract

This study investigates the atmospheric drivers of severe precipitation deficits in the Greater Alpine Region during the last 210 years utilizing a daily atmospheric circulation type reconstruction. Precipitation deficit tends to be higher during periods with more frequent anticyclonic (dry) and less frequent cyclonic (wet) circulation types, as would be expected. However, circulation characteristics are not the main drivers of summer precipitation deficit. Dry soils in the warm season tend to limit precipitation, which is particularly the case for circulation types that are sensitive to a soil moisture‐precipitation feedback. This mechanism is of specific relevance in explaining the major drought decades of the 1860s and 1940s. Both episodes show large negative precipitation anomalies in spring followed by increasing frequencies of circulation types sensitive to soil moisture precipitation feedbacks. The dry springs of the 1860s were likely caused by circulation characteristics that were quite different from those of recent decades as a consequence of the large spatial extent of Arctic sea ice at the end of the Little Ice Age. On the other hand, the dry springs of the 1940s developed under a persistent positive pressure anomaly across Western and Central Europe, triggered by positive sea surface temperatures in the western subtropical Atlantic.

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<![CDATA[Quantifying the Timescale and Strength of Southern Hemisphere Intraseasonal Stratosphere‐troposphere Coupling]]> https://www.researchpad.co/article/Ne2d0b07a-2452-4f6d-ba26-c3d3b5569795

Abstract

The Southern Hemisphere zonal circulation manifests a downward influence of the stratosphere on the troposphere from late spring to early summer. However, the strength and timescale of the connection, given the stratospheric state, have not been explicitly quantified. Here, SH zonal wind reanalysis time series are analyzed with a methodology designed to detect the minimal set of statistical predictors of multiple interacting variables via conditional independence tests. Our results confirm from data that the variability of the stratospheric polar vortex is a predictor of the tropospheric eddy‐driven jet between September and January. The vortex variability explains about 40% of monthly mean jet variability at a lead time of 1 month and can entirely account for the observed jet persistence. Our statistical model can quantitatively connect the multidecadal trends observed in the vortex and jet during the satellite era. This shows how short‐term variability can help understand statistical links in long‐term changes.

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<![CDATA[Quantifying Stratospheric Temperature Signals and Climate Imprints From Post‐2000 Volcanic Eruptions]]> https://www.researchpad.co/article/Nc8f53688-9428-448b-9f34-38bdaf6f31f8

Abstract

Small volcanic eruptions and their effects have recently come into research focus. While large eruptions are known to strongly affect stratospheric temperature, the impacts of smaller eruptions are hard to quantify because their signals are masked by natural variability. Here, we quantify the temperature signals from small volcanic eruptions between 2002 and 2016 using new vertically resolved aerosol data and precise temperature observations from radio occultation. We find characteristic space‐time signals that can be associated with specific eruptions. In the lower stratosphere, robust warming signals are observed, while in the midstratosphere also cooling signals of some eruptions appear. We find that the volcanic contribution to the temperature trend is up to 20%, depending on latitude and altitude. We conclude that detailed knowledge of the vertical structure of volcanic temperature impacts is crucial for comprehensive trend analysis in order to separate natural from anthropogenic temperature changes.

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<![CDATA[Hybrid Mass Balance/4D‐Var Joint Inversion of NO x and SO 2 Emissions in East Asia]]> https://www.researchpad.co/article/Ne104e45a-33d7-45d3-b79c-9974fe345cef

Abstract

Accurate estimates of NOx and SO2 emissions are important for air quality modeling and management. To incorporate chemical interactions of the two species in emission estimates, we develop a joint hybrid inversion framework to estimate their emissions in China and India (2005–2012). Pseudo observation tests and posterior evaluation with surface measurements demonstrate that joint assimilation of SO2 and NO2 can provide more accurate constraints on emissions than single‐species inversions. This occurs through synergistic change of O3 and OH concentrations, particularly in conditions where satellite retrievals of the species being optimized have large uncertainties. The percentage changes of joint posterior emissions from the single‐species posterior emissions go up to 242% at grid scales, although the national average of monthly emissions, seasonality, and interannual variations are similar. In China and India, the annual budget of joint posterior SO2 emissions is lower, but joint NOx posterior emissions are higher, because NOx emissions increase to increase SO2 concentration and better match Ozone Monitoring Instrument SO2 observations in high‐NOx regions. Joint SO2 posterior emissions decrease by 16.5% from 2008 to 2012, while NOx posterior emissions increase by 24.9% from 2005 to 2011 in China—trends which are consistent with the MEIC inventory. Joint NOx and SO2 posterior emissions in India increase by 15.9% and 19.2% from 2005 to 2012, smaller than the 59.9% and 76.2% growth rate using anthropogenic emissions from EDGARv4.3.2. This work shows the benefit and limitation of joint assimilation in emission estimates and provides an efficient framework to perform the inversion.

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<![CDATA[SO 2 Emission Estimates Using OMI SO 2 Retrievals for 2005–2017]]> https://www.researchpad.co/article/N6a783255-8e13-48df-b62e-7af6e7554ff5

Abstract

SO2 column densities from Ozone Monitoring Instrument provide important information on emission trends and missing sources, but there are discrepancies between different retrieval products. We employ three Ozone Monitoring Instrument SO2 retrieval products (National Aeronautics and Space Administration (NASA) standard (SP), NASA prototype, and BIRA) to study the magnitude and trend of SO2 emissions. SO2 column densities from these retrievals are most consistent when viewing angles and solar zenith angles are small, suggesting more robust emission estimates in summer and at low latitudes. We then apply a hybrid 4D‐Var/mass balance emission inversion to derive monthly SO2 emissions from the NASA SP and BIRA products. Compared to HTAPv2 emissions in 2010, both posterior emission estimates are lower in United States, India, and Southeast China, but show different changes of emissions in North China Plain. The discrepancies between monthly NASA and BIRA posterior emissions in 2010 are less than or equal to 17% in China and 34% in India. SO2 emissions increase from 2005 to 2016 by 35% (NASA)–48% (BIRA) in India, but decrease in China by 23% (NASA)–33% (BIRA) since 2008. Compared to in situ measurements, the posterior GEOS‐Chem surface SO2 concentrations have reduced NMB in China, the United States, and India but not in South Korea in 2010. BIRA posteriors have better consistency with the annual growth rate of surface SO2 measurement in China and spatial variability of SO2 concentration in China, South Korea, and India, whereas NASA SP posteriors have better seasonality. These evaluations demonstrate the capability to recover SO2 emissions using Ozone Monitoring Instrument observations.

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<![CDATA[The Low‐Resolution Version of HadGEM3 GC3.1: Development and Evaluation for Global Climate]]> https://www.researchpad.co/article/5c75654ed5eed0c484cbd987

Abstract

A new climate model, HadGEM3 N96ORCA1, is presented that is part of the GC3.1 configuration of HadGEM3. N96ORCA1 has a horizontal resolution of ~135 km in the atmosphere and 1° in the ocean and requires an order of magnitude less computing power than its medium‐resolution counterpart, N216ORCA025, while retaining a high degree of performance traceability. Scientific performance is compared to both observations and the N216ORCA025 model. N96ORCA1 reproduces observed climate mean and variability almost as well as N216ORCA025. Patterns of biases are similar across the two models. In the northwest Atlantic, N96ORCA1 shows a cold surface bias of up to 6 K, typical of ocean models of this resolution. The strength of the Atlantic meridional overturning circulation (16 to 17 Sv) matches observations. In the Southern Ocean, a warm surface bias (up to 2 K) is smaller than in N216ORCA025 and linked to improved ocean circulation. Model El Niño/Southern Oscillation and Atlantic Multidecadal Variability are close to observations. Both the cold bias in the Northern Hemisphere (N96ORCA1) and the warm bias in the Southern Hemisphere (N216ORCA025) develop in the first few decades of the simulations. As in many comparable climate models, simulated interhemispheric gradients of top‐of‐atmosphere radiation are larger than observations suggest, with contributions from both hemispheres. HadGEM3 GC3.1 N96ORCA1 constitutes the physical core of the UK Earth System Model (UKESM1) and will be used extensively in the Coupled Model Intercomparison Project 6 (CMIP6), both as part of the UK Earth System Model and as a stand‐alone coupled climate model.

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<![CDATA[Estimating Subseasonal Variability and Trends in Global Atmosphere Using Reanalysis Data]]> https://www.researchpad.co/article/5c75654cd5eed0c484cbd947

Abstract

A new measure of subseasonal variability is introduced that provides a scale‐dependent estimation of vertically and meridionally integrated atmospheric variability in terms of the normal modes of linearized primitive equations. Applied to the ERA‐Interim data, the new measure shows that subseasonal variability decreases for larger zonal wave numbers. Most of variability is due to balanced (Rossby mode) dynamics but the portion associated with the inertio‐gravity (IG) modes increases as the scale reduces. Time series of globally integrated variability anomalies in ERA‐Interim show an increase in variability after year 2000. In recent years the anomalies have been about 2% above the 1981–2010 average. The relative increase in variability projecting on the IG modes is larger and more persistent than for the Rossby modes. Although the IG part is a small component of the subseasonal variability, it is an important effect likely reflecting the observed increase in the tropical precipitation variability.

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