Understanding potential patterns in future population levels is crucial for anticipating and planning for changing age structures, resource and health-care needs, and environmental and economic ...landscapes. Future fertility patterns are a key input to estimation of future population size, but they are surrounded by substantial uncertainty and diverging methodologies of estimation and forecasting, leading to important differences in global population projections. Changing population size and age structure might have profound economic, social, and geopolitical impacts in many countries. In this study, we developed novel methods for forecasting mortality, fertility, migration, and population. We also assessed potential economic and geopolitical effects of future demographic shifts.
We modelled future population in reference and alternative scenarios as a function of fertility, migration, and mortality rates. We developed statistical models for completed cohort fertility at age 50 years (CCF50). Completed cohort fertility is much more stable over time than the period measure of the total fertility rate (TFR). We modelled CCF50 as a time-series random walk function of educational attainment and contraceptive met need. Age-specific fertility rates were modelled as a function of CCF50 and covariates. We modelled age-specific mortality to 2100 using underlying mortality, a risk factor scalar, and an autoregressive integrated moving average (ARIMA) model. Net migration was modelled as a function of the Socio-demographic Index, crude population growth rate, and deaths from war and natural disasters; and use of an ARIMA model. The model framework was used to develop a reference scenario and alternative scenarios based on the pace of change in educational attainment and contraceptive met need. We estimated the size of gross domestic product for each country and territory in the reference scenario. Forecast uncertainty intervals (UIs) incorporated uncertainty propagated from past data inputs, model estimation, and forecast data distributions.
The global TFR in the reference scenario was forecasted to be 1·66 (95% UI 1·33–2·08) in 2100. In the reference scenario, the global population was projected to peak in 2064 at 9·73 billion (8·84–10·9) people and decline to 8·79 billion (6·83–11·8) in 2100. The reference projections for the five largest countries in 2100 were India (1·09 billion 0·72–1·71, Nigeria (791 million 594–1056), China (732 million 456–1499), the USA (336 million 248–456), and Pakistan (248 million 151–427). Findings also suggest a shifting age structure in many parts of the world, with 2·37 billion (1·91–2·87) individuals older than 65 years and 1·70 billion (1·11–2·81) individuals younger than 20 years, forecasted globally in 2100. By 2050, 151 countries were forecasted to have a TFR lower than the replacement level (TFR <2·1), and 183 were forecasted to have a TFR lower than replacement by 2100. 23 countries in the reference scenario, including Japan, Thailand, and Spain, were forecasted to have population declines greater than 50% from 2017 to 2100; China's population was forecasted to decline by 48·0% (−6·1 to 68·4). China was forecasted to become the largest economy by 2035 but in the reference scenario, the USA was forecasted to once again become the largest economy in 2098. Our alternative scenarios suggest that meeting the Sustainable Development Goals targets for education and contraceptive met need would result in a global population of 6·29 billion (4·82–8·73) in 2100 and a population of 6·88 billion (5·27–9·51) when assuming 99th percentile rates of change in these drivers.
Our findings suggest that continued trends in female educational attainment and access to contraception will hasten declines in fertility and slow population growth. A sustained TFR lower than the replacement level in many countries, including China and India, would have economic, social, environmental, and geopolitical consequences. Policy options to adapt to continued low fertility, while sustaining and enhancing female reproductive health, will be crucial in the years to come.
Bill & Melinda Gates Foundation.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Commonly used bias correction methods such as quantile mapping (QM) assume the function of error correction values between modeled and observed distributions are stationary or time invariant. This ...article finds that this function of the error correction values cannot be assumed to be stationary. As a result, QM lacks justification to inflate/deflate various moments of the climate change signal. Previous adaptations of QM, most notably quantile delta mapping (QDM), have been developed that do not rely on this assumption of stationarity. Here, we outline a methodology called scaled distribution mapping (SDM), which is conceptually similar to QDM, but more explicitly accounts for the frequency of rain days and the likelihood of individual events. The SDM method is found to outperform QM, QDM, and detrended QM in its ability to better preserve raw climate model projected changes to meteorological variables such as temperature and precipitation.
Understanding the level and characteristics of protection from past SARS-CoV-2 infection against subsequent re-infection, symptomatic COVID-19 disease, and severe disease is essential for predicting ...future potential disease burden, for designing policies that restrict travel or access to venues where there is a high risk of transmission, and for informing choices about when to receive vaccine doses. We aimed to systematically synthesise studies to estimate protection from past infection by variant, and where data allow, by time since infection.
In this systematic review and meta-analysis, we identified, reviewed, and extracted from the scientific literature retrospective and prospective cohort studies and test-negative case-control studies published from inception up to Sept 31, 2022, that estimated the reduction in risk of COVID-19 among individuals with a past SARS-CoV-2 infection in comparison to those without a previous infection. We meta-analysed the effectiveness of past infection by outcome (infection, symptomatic disease, and severe disease), variant, and time since infection. We ran a Bayesian meta-regression to estimate the pooled estimates of protection. Risk-of-bias assessment was evaluated using the National Institutes of Health quality-assessment tools. The systematic review was PRISMA compliant and was registered with PROSPERO (number CRD42022303850).
We identified a total of 65 studies from 19 different countries. Our meta-analyses showed that protection from past infection and any symptomatic disease was high for ancestral, alpha, beta, and delta variants, but was substantially lower for the omicron BA.1 variant. Pooled effectiveness against re-infection by the omicron BA.1 variant was 45·3% (95% uncertainty interval UI 17·3–76·1) and 44·0% (26·5–65·0) against omicron BA.1 symptomatic disease. Mean pooled effectiveness was greater than 78% against severe disease (hospitalisation and death) for all variants, including omicron BA.1. Protection from re-infection from ancestral, alpha, and delta variants declined over time but remained at 78·6% (49·8–93·6) at 40 weeks. Protection against re-infection by the omicron BA.1 variant declined more rapidly and was estimated at 36·1% (24·4–51·3) at 40 weeks. On the other hand, protection against severe disease remained high for all variants, with 90·2% (69·7–97·5) for ancestral, alpha, and delta variants, and 88·9% (84·7–90·9) for omicron BA.1 at 40 weeks.
Protection from past infection against re-infection from pre-omicron variants was very high and remained high even after 40 weeks. Protection was substantially lower for the omicron BA.1 variant and declined more rapidly over time than protection against previous variants. Protection from severe disease was high for all variants. The immunity conferred by past infection should be weighed alongside protection from vaccination when assessing future disease burden from COVID-19, providing guidance on when individuals should be vaccinated, and designing policies that mandate vaccination for workers or restrict access, on the basis of immune status, to settings where the risk of transmission is high, such as travel and high-occupancy indoor settings.
Bill & Melinda Gates Foundation, J Stanton, T Gillespie, and J and E Nordstrom.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The North American monsoon is a major focus of modern and paleoclimate research, but relatively little is known about interannual‐ to decadal‐scale monsoon moisture variability in the ...pre‐instrumental era. This study draws from a new network of subannual tree‐ring latewood width chronologies and presents a 470‐year reconstruction of monsoon (June–August) standardized precipitation for southwestern North America. Comparison with an independent reconstruction of cool‐season (October–April) standardized precipitation indicates that southwestern decadal droughts of the last five centuries were characterized not only by cool‐season precipitation deficits but also by concurrent failure of the summer monsoon. Monsoon drought events identified in the past were more severe and persistent than any of the instrumental era. The relationship between winter and summer precipitation is weak, at best, and not time stable. Years with opposing‐sign seasonal precipitation anomalies, as noted by other studies, were anomalously frequent during the mid to late 20th century.
Key Points
New network of tree‐ring latewood records reconstructs monsoon precipitation
Monsoon failure implicated in major southwestern droughts of last 470 years
Winter‐summer precipitation relationship is found to be weak and time unstable
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
•Current groundwater recharge in the western US is synthesized.•Recharge components are compared across the selected aquifers.•Climate-change is analyzed to determine impact on total recharge and ...mechanism.•Geographical patterns in total recharge and mechanism changes are described.•Knowledge gaps that limit predictions of future changes in recharge are identified.
Existing studies on the impacts of climate change on groundwater recharge are either global or basin/location-specific. The global studies lack the specificity to inform decision making, while the local studies do little to clarify potential changes over large regions (major river basins, states, or groups of states), a scale often important in the development of water policy. An analysis of the potential impact of climate change on groundwater recharge across the western United States (west of 100° longitude) is presented synthesizing existing studies and applying current knowledge of recharge processes and amounts. Eight representative aquifers located across the region were evaluated. For each aquifer published recharge budget components were converted into four standard recharge mechanisms: diffuse, focused, irrigation, and mountain-systems recharge. Future changes in individual recharge mechanisms and total recharge were then estimated for each aquifer. Model-based studies of projected climate-change effects on recharge were available and utilized for half of the aquifers. For the remainder, forecasted changes in temperature and precipitation were logically propagated through each recharge mechanism producing qualitative estimates of direction of changes in recharge only (not magnitude). Several key patterns emerge from the analysis. First, the available estimates indicate average declines of 10–20% in total recharge across the southern aquifers, but with a wide range of uncertainty that includes no change. Second, the northern set of aquifers will likely incur little change to slight increases in total recharge. Third, mountain system recharge is expected to decline across much of the region due to decreased snowpack, with that impact lessening with higher elevation and latitude. Factors contributing the greatest uncertainty in the estimates include: (1) limited studies quantitatively coupling climate projections to recharge estimation methods using detailed, process-based numerical models; (2) a generally poor understanding of hydrologic flowpaths and processes in mountain systems; (3) difficulty predicting the response of focused recharge to potential changes in the frequency and intensity of extreme precipitation events; and (4) unconstrained feedbacks between climate, irrigation practices, and recharge in highly developed aquifer systems.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Evidence for surface and atmosphere coupling is corroborated in both modeling and observation-based field experiments. Recent advances in high-performance computing and development of ...convection-permitting regional-scale atmospheric models combined with high-resolution hydrologic models have made modeling of surface–atmosphere interactions feasible for the scientific community. These hydrological models can account for the impacts of the overland flow and subsurface flow components of the hydrologic cycle and account for the impact of lateral flow on moisture redistribution at the land surface.One such model is the Weather Research and Forecasting (WRF) regional atmospheric model that can be coupled to the WRF-Hydro hydrologic model. In the present study, both the uncoupled WRF (WRF-ARW) and otherwise identical WRF-Hydro model are executed for the 2017 and 2018 summer time North American monsoon (NAM) seasons in semiarid central Arizona. In this environment, diurnal convection is impacted by precipitation recycling from the land surface. The goal of this work is to evaluate the impacts that surface runoff and shallow subsurface flow, as depicted in WRF-Hydro, have on surface–atmosphere interactions and convection in a coupled atmospheric simulation. The current work assesses the impact of surface hydrologic processes on 1) local surface energy budgets during the NAM throughout Arizona and 2) the spectral behavior of diurnally driven NAM convection. Model results suggest that adding surface and subsurface flow from WRF-Hydro increases soil moisture and latent heat near the surface. This increases the amount of instability and moisture available for deep convection in the model simulations and enhances the organization of convection at the peak of the diurnal cycle.
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BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
While pesticide vapor and particles from agricultural spray drift have been reported to pose a risk to public health, limited baseline ambient measurements exist to warrant an accurate assessment of ...their impacts at community-to-county-wide scale. Here, we present an initial modeling investigation of the transport and deposition of applied pesticides in an agricultural county in Arizona (Yuma County), to provide initial estimates on the corresponding enhancements in ambient levels of these spray drifts downwind of application sites. With a 50 × 50 km domain, we use the dispersion model CALPUFF with meteorology from the Weather Research and Forecasting (WRF) to investigate the spatiotemporal distribution of pesticide abundance due to spray drift from a representative sample of nine application sites. Data records for nine application days in September and October 2011, which are the peak months of pesticide application, were retroactively simulated for 48-h for all nine application sites using an active ingredient lambda-cyhalothrin, which is a commonly-used pesticide in the county. Twenty-one WRF/CALPUFF simulations were conducted with varying emissions, chemical lifetime, deposition rate, application height, and meteorology inputs, allowing for an ensemble-based analysis on the possible ranges in modeled abundance. Our results show that dispersion of vapors released at time of application heavily depends on prevailing meteorology, particularly wind speed and direction. Dispersion is limited to thin plumes that are easily transported out of the domain. The ensemble-mean vapor concentrations of the 48-h average (> 90 percentile domain-wide) range from 0.2 nanograms (ng)/m
to 200 ng/m
, and the peak can be as high as 1000 ng/m
near the application sites. Pesticide particles are mainly deposited within 1-2 km from the application sites at an average rate of 10
ng/km
/h but vary with particle mean diameter and standard deviation. While these findings are generally consistent with reported ambient levels in the literature, the associated ensemble-spread on these estimates are in the same order of magnitude as their ensemble-mean. At the two nearby communities downwind of these sites, we find that peak vapor concentrations are less than 50 ng/m
with exposure times of less than an hour, as approximately 99.4% of the vapors are advected out and 99.5% of the particles deposit within the domain. Results of this study indicate pesticide spray drift from a sample of application sites and representative days in Fall may have a limited impact on neighboring communities. However, we strongly suggest that field measurements should be collected for model validation and more rigorous investigation of the actual scale of these impacts when the bulk of pesticide applications across the county, variation in active pesticide ingredients, and potential resuspension of deposited particles are considered.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The value restored and added by dynamical downscaling is quantitatively evaluated by considering the spectral behavior of the Regional Atmospheric Modeling System (RAMS) in relation to its domain ...size and grid spacing. A regional climate model (RCM) simulation is compared with NCEP Reanalysis data regridded to the RAMS grid at each model analysis time for a set of six basic experiments. At large scales, RAMS underestimates atmospheric variability as determined by the column integrated kinetic energy and integrated moisture flux convergence. As the grid spacing increases or domain size increases, the underestimation of atmospheric variability at large scales worsens. The model simulated evolution of the kinetic energy relative to the reanalysis regridded kinetic energy exhibits a decrease with time, which is more pronounced with larger grid spacing. Additional follow‐on experiments confirm that the surface boundary forcing is the dominant factor in generating atmospheric variability for small‐scale features and that it exerts greater control on the RCM solution as the influence of lateral boundary conditions diminish. The sensitivity to surface forcing is also influenced by the model parameterizations, as demonstrated by using a different convection scheme. For the particular case considered, dynamical downscaling with RAMS in RCM mode does not retain value of the large scale which exists in the larger global reanalysis. The utility of the RCM, or value added, is to resolve the smaller‐scale features which have a greater dependence on the surface boundary. This conclusion regarding RAMS is expected to be true for other RCMs as well.
In August 2016, the National Weather Service Office of Water Prediction (NWS/OWP) of the National Oceanic and Atmospheric Administration (NOAA) implemented the operational National Water Model (NWM) ...to simulate and forecast streamflow, soil moisture, and other model states throughout the contiguous United States. Based on the architecture of the WRF-Hydro hydrologic model, the NWM does not currently resolve channel infiltration, an important component of the water balance of the semiarid western United States. Here, we demonstrate the benefit of implementing a conceptual channel infiltration function (from the KINEROS2 semidistributed hydrologic model) into the WRF-Hydro model architecture, configured as NWM v1.1. After calibration, the updated WRF-Hydro model exhibits reduced streamflow errors for the Walnut Gulch Experimental Watershed (WGEW) and the Babocomari River in southeast Arizona. Model calibration was performed using NLDAS-2 atmospheric forcing, available from the NOAA National Centers for Environmental Prediction (NCEP), paired with precipitation forcing from NLDAS-2, NCEP Stage IV, or local gauge precipitation. Including channel infiltration within WRF-Hydro results in a physically realistic hydrologic response in the WGEW, when the model is forced with high-resolution, gauge-based precipitation in lieu of a national product. The value of accounting for channel loss is also demonstrated in the Babocomari basin, where the drainage area is greater and the cumulative effect of channel infiltration ismore important. Accounting for channel infiltration loss thus improves the streamflow behavior simulated by the calibrated model and reduces evapo-transpiration bias when gauge precipitation is used as forcing. However, calibration also results in increased high soil moisture bias,which is likely due to underlying limitations of the NWM structure and calibration methodology.
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