Uncertainty In Trends Research Articles

Feasibility of ERA5 integrated water vapor trends for climate change analysis in continental Europe: An evaluation with GPS (1994–2019) by considering statistical significance

Although the statistical significances for the trends of integrated water vapor (IWV) are essential for a correct interpretation of climate change signals, obtaining accurate IWV trend estimates with realistic uncertainties remains a challenge. This study evaluates the feasibility of the IWV trends derived from the newly released fifth generation European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis (ERA5) for climate change analysis in continental Europe. This is achieved by comparing the trends derived from in-situ ground-based Global Positioning System (GPS)’s daily IWV series from 1994 to 2019 at 109 stations. The realistic uncertainties and statistical significances of the IWV trends are evaluated with the time series analysis on their noise characteristics and proper noise models. Results show that autoregressive moving average ARMA(1,1) noise model is preferred rather than the commonly assumed white noise (WN) or first-order autoregressive AR(1) noise for about 68% of the ERA5 and GPS IWV series. An improper noise model would misevaluate the trend uncertainty of an IWV time series, compared with its specific preferred noise model. For example, ARMA(1,1) may misevaluate the standard deviations of their trend estimates (0.1–0.3 kg m−2 decade−1) by 10%. Nevertheless, ARMA(1,1) is recommended as the default noise model for the ERA5 and GPS IWV series. However, the preferred noise model for each ERA5 minus GPS (E-G) IWV series should be specifically determined, because the AR(1)-related models can result in an underestimation on its trend uncertainty by 90%. In contrast, power-law (PL) model can lead to an overestimation by up to nine times. The E-G IWV trends are within −0.2–0.4 kg m−2 decade−1, indicating that the ERA5 is a potential data source of IWV trends for climate change analysis in continental Europe. The ERA5 and GPS IWV trends are consistent in their magnitudes and geographical patterns, lower in Northwest Europe (0–0.4 kg m−2 decade−1) but higher around the Mediterranean Sea (0.6–1.4 kg m−2 decade−1).

Mandatory annuitization and money's worth: evidence from Singapore

AbstractThis paper examines the impact of uncertainties in the future trends of mortality on annuity values in Singapore's compulsory purchase market. We document persistent population mortality improvement trends over the past few decades, which underscores the importance of longevity risk in this market. Using the money's worth framework, we find that the life annuities delivered expected payouts valued at 1.019–1.185 (0.973–1.170) per dollar of annuity premium for males (females). Even in a low mortality improvement scenario, the annuities provide an expected value exceeding 0.950. This suggests that participants in the national annuity pool have access to attractively priced annuities, regardless of sex, product, and premium invested.

Seasonally changing contribution of sea ice and snow cover to uncertainty in multi-decadal Eurasian surface air temperature trends based on CESM simulations

This study investigates the impact of sea ice and snow changes on surface air temperature (SAT) trends on the multidecadal time scale over the mid- and high-latitudes of Eurasia during boreal autumn, winter and spring based on a 30-member ensemble simulations of the Community Earth System Model (CESM). A dynamical adjustment method is used to remove the internal component of circulation-induced SAT trends. The leading mode of dynamically adjusted SAT trends is featured by same-sign anomalies extending from northern Europe to central Siberia and to the Russian Far East, respectively, during boreal spring and autumn, and confined to western Siberia during winter. The internally generated component of sea ice concentration trends over the Barents-Kara Seas contributes to the differences in the thermodynamic component of internal SAT trends across the ensemble over adjacent northern Siberia during all the three seasons. The sea ice effect is largest in autumn and smallest in winter. Eurasian snow changes contribute to the spread in dynamically adjusted SAT trends as well around the periphery of snow covered region by modulating surface heat flux changes. The snow effect is identified over northeast Europe-western Siberia in autumn, north of the Caspian Sea in winter, and over eastern Europe-northern Siberia in spring. The effects of sea ice and snow on the SAT trends are realized mainly by modulating upward shortwave and longwave radiation fluxes.

Functional Disability with Systematic Trends and Uncertainty: A Comparison between China and the U.S.

China and the U.S. are two contrasting countries in terms of functional disability and long-term care. China is experiencing declining family support for long-term care and developing private long-term care insurance. The U.S. has a more developed public aged care system and private long-term care insurance market than China. Changes in the demand for long-term care are driven by the levels, trends and uncertainty in mortality and functional disability. To understand the future potential demand for long-term care, we compare mortality and functional disability experiences in China and the U.S., using a multi-state latent factor intensity model with time trends and systematic uncertainty in transition rates. We estimate the model with the Chinese Longitudinal Healthy Longevity Survey (CLHLS) and the U.S. Health and Retirement Study (HRS) data. The estimation results show that if trends continue, both countries will experience longevity improvement with morbidity compression and a declining proportion of the older population with functional disability. Although the elderly Chinese have a shorter estimated life expectancy, they are expected to spend a smaller proportion of their future lifetime functionally disabled than the elderly Americans. Systematic uncertainty is shown to be significant in future trends in disability rates and our model estimates higher uncertainty in trends for the Chinese elderly, especially for urban residents.

Assessing the effects of climate variable and timescale selection on uncertainties in dryness/wetness trends in conterminous China

AbstractAnalysing dryness/wetness trends, which is typically achieved by examining drought indices, is an essential approach for assessing extreme climate events. However, since there are differences among studies in terms of selected climate variables and timescales used to calculate drought indices, there is uncertainty regarding the magnitude and direction of the dryness/wetness, trend even for the same region. We used 40 years weather station data (1970–2010) and studied the uncertainties of dryness/wetness trends in conterminous China. The effects of selected climate variables, timescales and their interaction on the dryness/wetness trends were quantified by comparing the Standardized Precipitation Index, Standardized Precipitation Evapotranspiration Index (SPEI) with the Thornthwaite equation and SPEI with the Penman–Monteith equation at 3‐, 12‐ and 24‐month timescales. The results indicated that (a) higher uncertainties occurred in relatively arid and humid regions; (b) timescale tended to exaggerate the effect of climate variables, even though its effect was substantially lower than climate variables; (c) relative humidity and precipitation were the primary climate variables affecting observed dryness/wetness trend uncertainties. Since the key climate variables changed depending on the selected timescale, the role of timescale should be further examined the Inner Mongolia and Northeast regions. In general, the study results suggest that the trend analysis of dryness/wetness should include the interaction of both climate variable and timescale selection, particularly when a single drought index is used to estimate the dryness/wetness trend in diverse regions.

A Review Characterizing 25 Ecosystem Challenges to Be Addressed by an Ecosystem Approach to Fisheries Management in Europe

The impacts of fisheries on ocean resources are no longer considered in isolation but should account for broader ecosystem effects. However, ongoing ecosystem-wide changes added to the inherent dynamics of marine ecosystems, create challenges for fisheries and fisheries management by affecting our ability to ensure future fishing opportunities and sustainable use of the seas. By reviewing a corpus of fisheries science literature, we contribute to informing managers and policymakers with considerations of the various threats to fisheries and the marine ecosystems that support them. We identify and describe 25 ecosystem challenges and 7 prominent families of management options to address them. We capture the challenges acting within three broad categories: (i) fishing impacts on the marine environments and future fishing opportunities, (ii) effects of environmental conditions on fish and fishing opportunities, and (iii) effects of context in terms of socioeconomics, fisheries management, and institutional set-up on fisheries. Our review shows that, while most EU fisheries are facing a similar array of challenges, some of them are specific to regions or individual fisheries. This is reflected in selected regional cases taking different perspectives to exemplify the challenges along with fishery-specific cases. These cases include the dramatic situation of the Baltic Sea cod, facing an array of cumulative pressures, the multiple and moving ecosystem interactions that rely on the North Sea forage fish facing climate change, the interaction of fishing and fish stocks in a fluctuating mixed fishery in the Celtic Sea, the bycatch of marine mammals and seabirds and habitat degradation in the Bay of Biscay, and finally the under capacity and lack of fundamental knowledge on some features of the EU Outermost Regions. In addition to these ecoregion specific findings, we discuss the outcomes of our review across the whole of European waters and we conclude by recognizing that there are knowledge gaps regarding the direction of causality, nonlinear responses, and confounding effects. All of the challenges we identify and characterize may guide further data collection and research coordination to improve our fundamental understanding of the system and to monitor real changes within it, both of which are required to inform an Ecosystem Approach to Fisheries Management (EAFM). An European EAFM could build upon an array of management measures currently tailored for fisheries management only, including promoting funding interdisciplinary research and ecosystem monitoring. Such integrative management should reduce uncertainties in environmental, social and economic trends, and lower the risk for disruptive events or ecosystem effects with far-reaching consequences, including a shift toward less productive marine ecosystems.

Local sea level trends, accelerations and uncertainties over 1993\u20132019

Satellite altimetry missions provide a quasi-global synoptic view of sea level variations over more than 25 years and provide regional sea level (SL) indicators such as trends and accelerations. Estimating realistic uncertainties on these quantities is crucial to address current climate science questions. While uncertainty estimates are available for the global mean sea level (GMSL), information is not available at local scales so far. We estimate a local satellite altimetry error budget and use it to derive local error variance-covariance matrices, and estimate confidence intervals on trends and accelerations at the 90% confidence level. Over 1993–2019, we find that the average local sea level trend uncertainty is 0.83 mm.yr−1 with values ranging from 0.78 to 1.22 mm.yr−1. For accelerations, uncertainties range from 0.057 to 0.12 mm.yr−1, with a mean value of 0.062. We also perform a sensitivity study to investigate a range of plausible error budgets. Local error levels, error variance-covariance matrices, SL trends and accelerations, along with corresponding uncertainties are provided.

Sustainable fishing can lead to improvements in marine ecosystem status: an ensemble-model forecast of the North Sea ecosystem

To effectively implement ecosystem-based fisheries management, tools are needed that are capable of exploring the likely consequences of potential management action for the whole ecosystem. Quantitative modelling tools can be used to explore how ecosystems might respond to potential management measures, but no one model can reliably forecast all aspects of future change. To build a robust basis for management advice, a suite of models can be used, but the interpretation of the joint output of multiple models can be difficult. We employ a newly developed ensemble approach to integrate 5 different ecosystem models and estimate changes in ecosystem state within a single probabilistic forecast. We provide evidence on the response of ecosystem state (measured using ecological indicators relating to plankton, fish and top predators) to potential fisheries management scenarios. We demonstrate that if future fishing mortality is consistent with maximum sustainable yield policy, the North Sea fish community will recover in terms of its size structure and species composition. However, there is currently large uncertainty in trends of future fish biomass, plankton and top predators. We conclude that (1) this ensemble approach can be applied directly to policy-relevant questions and add value for decision makers, as multiple aspects of uncertainty are considered; (2) future research should prioritise improvements in model skill via a reduction in uncertainty surrounding biomass estimates; and (3) fisheries management that leads to sustainable fishing levels can be considered appropriate for 2 crucial aspects of fish biodiversity: species composition and size structure.

Major Trends in Population Growth Around the World

The world’s population continues to grow, albeit at a slower pace. The decelerating growth is mainly attributable to fertility declines in a growing number of countries. However, there are substantial variations in the future trends of populations across regions and countries, with sub-Saharan African countries being projected to have most of the increase. Population momentum plays an important role in determining the future population growth in many countries and areas where fertility is in a rapid transition. With declines in fertility, the world’s population is unprecedentedly aging, and the numbers of households with smaller sizes are growing. International migration is also on the rise since the beginning of this century. The world’s population is also urbanizing due to increased internal rural to urban migration. Nevertheless, there are uncertainties in future population growth, not only because there are uncertainties in the future trends in fertility, mortality, and migration, but also because there are many other factors that could affect these trajectories. International consensus on climate change and ecosystem protections may trigger population control policies, and the ongoing pandemic is likely to have some impact on mortality, migration, or even fertility.

Trends and Challenges for Population and Health During Population Aging — China, 2015–2050

What is already known about this topic? As the largest country in the world, China experienced a demographic transition at a historic scale during the past 50 years with extraordinarily associated changes in the age structure of the population, declining fertility rates, accelerating process of population aging, and growing population scale. What is added by this report? This study presented future trends of five important population indicators in China. From 2015–2050, China experienced outstanding demographic changes — increases in life expectancy and declines in fertility rate — that have led to population aging. In addition, disability prevalence is growing, and life expectancy with disability is also increasing. What are the implications for public health practice? This study provided evidence of healthy life expectancy improvement and disease burden declining, healthy aging, and active aging. Due to the uncertainties of future trends of population structure changes, dynamic evaluations, timely adjustments, and innovations in population health strategy design and management should be strengthened to ensure quality of life under the background of population aging.

The Impact of the Coronavirus Pandemic on the Economy of Ukraine: a Sectoral Analysis of the Consequences and Opportunities for Recovery

The article examines the state and trends of the Ukrainian economy during the pandemic of coronavirus COVID-19, economic opportunities for economic recovery in the short term. The paper presents an analysis and structure of key sectoral socio-economic losses and losses (loss of income) by economic agents under the influence of the pandemic. The study identified and analysed the main economic groups of the consequences of COVID-19, such as: GDP reduction; decline in industrial production; significant reduction of revenues from economic activities of air carriers and maritime transport; shopping and entertainment centres, tourism industry; reduction of household incomes with a simultaneous increase in their expenditures; increase in profits of pharmaceutical companies and the gaming, educational and other online application's industry (in particular, food and medicine delivery); declining business and investment activity and growing investor demand for less risky assets in the Ukrainian market; changing trends in retail and online trade; digitalization of business processes. The paper examines the impact of the factor of “remote” and “hybrid” format of work on the employment market (both national and global dimension). According to the results of the study, conclusions were made about the key current opportunities (projected) recovery of the national economy by sectors (areas of economic activity) in the post-covenant period, provided that new lockdowns are not introduced in autumn 2021 due to the spread of a new strain Delta. The expected recovery of the national economy is projected to be gradual and slow due to significant economic, political and epidemiological risks (so far small volumes of vaccination and the risk of a new wave of pandemic). Given the high uncertainty of global economic and security trends, small and weak economies should develop short-term national recovery strategies, focusing primarily on their own financial resources and economic opportunities, providing financial and legislative support to national companies and the domestic market.

Spatial and Temporal Occurrence and Effects of Droughts on Crop Yields in Kenya

Increase in drought frequency, magnitude and duration affect crop production in Kenya. The limited food production resulting from drought leads to food insecurity in Arid and Semi-Arid Lands (ASALs) in the Kenya. This study reviewed literature on drought trends and its effects on crop yields in Kenya from 1950 to 2020. The systematic review was conducted in order to establish the drought trends and the effects of droughts on crop yields in the country. Content analysis was used for literature review on drought trends and its effects on maize, sorghum and wheat production in Kenya. From the study, a high uncertainty in global-scale drought trends in the last 60 years was established. However, an increase in drought frequency was observed from 1950 to 2002 in Africa. Few drought events were experienced in 1950s with a notable positive trend in drought frequency observed in 1960s in Kenya. In 1970s, an increased frequency and severity of droughts were observed while a decline in drought frequency was noted in 1980s. More frequent and severe droughts in Kenya were also established to have occurred in 1990s and 2000s. However, a decline in drought frequency and severity was reported in 2010s. The severity of the droughts negatively affected crop production where food insecurity was experienced in different regions of the country. The study also found that drought leads to famine and loss of human lives. Loss of livelihood such as livestock was also identified. The study identified limited information on decadal causes and recurrence of droughts and inadequate explanation on why 1950 to 2020 experienced global uncertainty in drought occurrence.

Dissecting effects of orbital drift of polar-orbiting satellites on accuracy and trends of climate data records of cloud fractional cover

Abstract. Radiometers such as the AVHRR (Advanced Very High Resolution Radiometer) mounted aboard a series of NOAA and MetOp (Meteorological Operational) polar-orbiting satellites provide 4-decade-long global climate data records (CDRs) of cloud fractional cover. Generation of such long datasets requires combining data from consecutive satellite platforms. A varying number of satellites operating simultaneously in the morning and afternoon orbits, together with satellite orbital drift, cause the uneven sampling of the cloudiness diurnal cycle along a course of a CDR. This in turn leads to significant biases, spurious trends, and inhomogeneities in the data records of climate variables featuring the distinct diurnal cycle (such as clouds). To quantify the uncertainty and magnitude of spurious trends in the AVHRR-based cloudiness CDRs, we sampled the 30 min reference CM SAF (European Organisation for the Exploitation of Meteorological Satellites – EUMETSAT – Satellite Application Facility on Climate Monitoring) Cloud Fractional Cover dataset derived from Meteosat First and Second Generation (COMET) at times of the NOAA and MetOp satellite overpasses. The sampled cloud fractional cover (CFC) time series were aggregated to monthly means and compared with the reference COMET dataset covering the Meteosat disc (up to 60∘ N, S, W, and E). For individual NOAA and MetOp satellites the errors in mean monthly CFC reach ±10 % (bias) and ±7 % per decade (spurious trends). For the combined data record consisting of several NOAA and MetOp satellites, the CFC bias is 3 %, and the spurious trends are 1 % per decade. This study proves that before 2002 the AVHRR-derived CFC CDRs do not comply with the GCOS (Global Climate Observing System) temporal stability requirement of 1 % CFC per decade just due to the satellite orbital-drift effect. After this date the requirement is fulfilled due to the numerous NOAA and MetOp satellites operating simultaneously. Yet, the time series starting in 2003 is shorter than 30 years, which makes it difficult to draw reliable conclusions about long-term changes in CFC. We expect that the error estimates provided in this study will allow for a correct interpretation of the AVHRR-based CFC CDRs and ultimately will contribute to the development of a novel satellite orbital-drift correction methodology widely accepted by the AVHRR-based CDR providers.

Integrating economic measures of adaptation effectiveness into climate change interventions: A case study of irrigation development in Mwea, Kenya.

As climate change adaptation is becoming a recognized policy issue, the need is growing for quantitative economic evaluation of adaptation-related public investment, particularly in the context of climate finance. Funds are meant to be allocated not to any types of beneficial investments with or without climate change but to projects regarded as effective for climate change adaptation based on some metrics. But attempts at such project-specific evaluation of adaptation effects are few, in part because such assessments require an integration of various types of simulation analyses. Against this background, we conduct a case study of a Kenyan irrigation development project using a combination of downscaled climate data, runoff simulations, yield forecasting, and local socioeconomic projections to examine the effects of interventions specifically attributable to climate change adaptation, i.e., how much irrigation development can reduce the negative effects of climate change in the future. The results show that despite the uncertainties in precipitation trends, increased temperatures due to climate change have a general tendency to reduce rice yields, and that irrigation development will mitigate income impacts from the yield loss-for example, for the median scenario, the household income loss of 6% in 2050 due to climate change without irrigation development is flipped to become positive with the project. This means that the irrigation development project will likely be effective as a means for climate change adaptation.

Multi‐Century Impacts of Ice Sheet Retreat on Sea Level and Ocean Tides in Hudson Bay

AbstractPast and modern large‐scale ice sheet loss results in geographically variable sea level changes. At present, in Hudson Bay, Canada, sea level is decreasing due to glacial isostatic adjustment, which represents a departure from the globally averaged sea level rise. However, there are large uncertainties in future sea level trends with further polar ice sheet retreat in the coming centuries. Sea level changes affect ocean tides considerably because tides are highly sensitive to changes in bathymetry. Here, we present multi‐century sea level projections associated with a suite of past and future ice loss scenarios and consider the impact of these changes on ocean tides using an established tidal model. Modern tides in Hudson Bay are poorly resolved due to large uncertainties in bathymetry. To establish an initial condition for our simulations, we constrain bathymetry in the bay using tide observations. Due to gravitational, Earth rotational and deformational effects, Greenland ice loss will produce a small sea level fall in the bay, while Antarctic ice loss will produce a larger than average sea level rise. Our results show that the response of the Antarctic ice sheet to climate change strongly impacts the magnitude and sign of future sea level and tidal amplitude changes in the region, with the largest changes predicted in Hudson Strait and Foxe Basin. We emphasize that further constraints on bathymetry and accurate projections of sea level and tides in Hudson Bay are imperative for assessing the associated impacts on coastal communities and ecosystems.

Lifetime radiation risk of stochastic effects - prospective evaluation for space flight or medicine.

The concept of lifetime radiation risk of stochastic detrimental health outcomes is important in contemporary radiation protection, being used either to calculate detriment-weighted effective dose or to express risks following radiation accidents or medical uses of radiation. The conventionally applied time-integrated risks of radiation exposure are computed using average values of current population and health statistical data that need to be projected far into the future. By definition, the lifetime attributable risk (AR) is an approximation to more general lifetime risk quantities and is only valid for exposures under 1 Gy. The more general quantities, such as excess lifetime risk (ELR) and risk of exposure-induced cancer, are free of dose range constraints, but rely on assumptions concerning the unknown total radiation effect on demographic and health statistical data, and are more computationally complex than AR. Consideration of highly uncertain competing risks for other radiation-attributed outcomes are required in appropriate assessments of time-integrated risks of specific outcomes following high-dose (>1 Gy) exposures, causing non-linear dose responses in the resulting ELR estimate.Being based on the current population and health statistical data, the conventionally applied time-integrated risks of radiation exposure are: (i) not well suited for projections many years into the future because of the large uncertainties in future secular trends in the population-specific disease rates; and (ii) not optimal for application to atypical groups of exposed persons not well represented by the general population. Specifically, medical patients are atypical in this respect because their prospective risks depend strongly on the original diagnosis, the treatment modality, general cure rates, individual radiation sensitivity, and genetic predisposition. Another situation challenging the application of conventional risk quantities is a projection of occupational radiation risks associated with space flight, both due to higher radiation doses and astronauts' generally excellent health condition due to pre-selection, training, and intensive medical screening.An alternative quantity, named 'radiation-attributed decrease of survival' (RADS), known in past general statistical literature as 'cumulative risk', is recommended here for applications in space and medicine to represent the cumulative radiation risk conditional on survival until a certain age. RADS is only based on the radiation-attributed hazard rendering an insensitivity to competing risks or projections of current population statistics far into the future. Therefore, RADS is highly suitable for assessing semi-personalised radiation risks after radiation exposures from space missions or medical applications of radiation.

Sensitivity of trends to estimation methods and quantification of subsampling effects in global radiosounding temperature and humidity time series

AbstractClimate trends estimated using historical radiosounding time series may be significantly affected by the choice of the regression method to use, as well as by a subsampling of the dataset often adopted in specific applications. These are contributions to the uncertainty of trend estimations, which have been quantified in literature, although on specific pairs of regression methods, and in the not very recent past characterized by smaller trends in temperature than those observed over the last two decades. This paper investigates the sensitivity of trend estimations to four linear regression methods (parametric and nonparametric) and to the artificial subsampling of the same dataset using historical radiosounding time series from 1978 onwards, available in the version 2 of the Integrated Global Radiosonde Archive (IGRA). Results show that long‐term decadal trends may have not negligible uncertainties related to the choice of the regression method, the percentage of data available, the amount of missing data and the number of stations selected in the dataset. The choice of the regression methods increases uncertainties in the decadal trends ranging from −0.10 to −0.01 K⋅da–1 for temperature in the lower stratosphere at 100 hPa and from 0.2 to 0.8% da–1 for relative humidity (RH) in the middle troposphere at 300 hPa. Differences can also increase up to 0.4 K⋅da–1 at 300 hPa when the amount of missing data exceeds 50% of the original dataset for temperature, while for RH, significant differences are observed in the lower troposphere at 925 hPa for almost all datasets. Finally, subsampling effects on trend estimation are quantified by artificially reducing the size of the IGRA dataset: Results show that subsampling effects on trend estimations when at least 60 stations, up to 76% of data available, are considered for temperature and at least 40 stations for RH.

Regional surface chlorophyll trends and uncertainties in the global ocean

Changes in marine primary productivity are key to determine how climate change might impact marine ecosystems and fisheries. Satellite ocean color sensors provide coverage of global ocean chlorophyll with a combined record length of ~ 20 years. Coupled physical–biogeochemical models can inform on expected changes and are used here to constrain observational trend estimates and their uncertainty. We produce estimates of ocean surface chlorophyll trends, by using Coupled Model Intercomparison Project (CMIP5) models to form priors as a “first guess”, which are then updated using satellite observations in a Bayesian spatio-temporal model. Regional chlorophyll trends are found to be significantly different from zero in 18/23 regions, in the range ± 1.8% year−1. A global average of these regional trends shows a net positive trend of 0.08 ± 0.35% year−1, highlighting the importance of considering chlorophyll changes at a regional level. We compare these results with estimates obtained with the commonly used “vague” prior, representing no independent knowledge; coupled model priors are shown to slightly reduce trend magnitude and uncertainties in most regions. The statistical model used here provides a robust framework for making best use of all available information and can be applied to improve understanding of global change.

Estimating changes and trends in ecosystem extent with dense time-series satellite remote sensing.

Quantifying trends in ecosystem extent is essential to understanding the status of ecosystems. Estimates of ecosystem loss are widely used to track progress toward conservation targets, monitor deforestation, and identify ecosystems undergoing rapid change. Satellite remote sensing has become an important source of information for estimating these variables. Despite regular acquisition of satellite data, many studies of change in ecosystem extent use only static snapshots, which ignores considerable amounts of data. This approach limits the ability to explicitly estimate trend uncertainty and significance. Assessing the accuracy of multiple snapshots also requires time-series reference data which is often very costly and sometimes impossible to obtain. We devised a method of estimating trends in ecosystem extent that uses all available Landsat satellite imagery. We used a dense time series of classified maps that explicitly accounted for covariates that affect extent estimates (e.g., time, cloud cover, and seasonality). We applied this approach to the Hukaung Valley Wildlife Sanctuary, Myanmar, where rapid deforestation is greatly affecting the lowland rainforest. We applied a generalized additive mixed model to estimate forest extent from more than 650 Landsat image classifications (1999-2018). Forest extent declined significantly at a rate of 0.274%/year (SE = 0.078). Forest extent declined from 91.70% (SE = 0.02) of the study area in 1999 to 86.52% (SE = 0.02) in 2018. Compared with the snapshot method, our approach improved estimated trends of ecosystem loss by allowing significance testing with confidence intervals and incorporation of nonlinear relationships. Our method can be used to identify significant trends over time, reduces the need for extensive reference data through time, and provides quantitative estimates of uncertainty.

Antarctic Surface Mass Balance: Natural Variability, Noise, and Detecting New Trends

AbstractThe emergence of new, statistically robust trends in Antarctic surface mass balance (SMB) requires an understanding of the underlying SMB variability (noise). We show that simple white or AR[1] noise models do not adequately represent the variability of SMB in both the RACMO2.3p2 SMB model output (1979–2017) and composite ice core records (1800–2010), underestimating low‐frequency variability. By testing a range of noise models, we find that a Generalized Gauss Markov (GGM) model better approximates the noise around a linear trend. The general preference for GGM noise applies over spatial scales from the total ice sheet down to individual drainage basins. Over the longest timescales considered, trend uncertainties are 1.3–2.3 times larger using a GGM model compared to using an AR1 model at the ice sheet scale. Overall, our results suggest that larger trends or longer periods are required before new SMB trends can be robustly separated from background noise.