Simulated Future Changes Research Articles

A Distinct Role for Aerosol and GHG Forcing in Historical CMIP6 Evapotranspiration Trends

AbstractEvapotranspiration (ET) is crucial for the global water balance, plant growth, and freshwater availability. It connects the surface water balance with surface energy fluxes, making its accurate representation vital for climate projections. However, global climate models (GCMs) struggle with ET representation due to resolution limitations and simplified depictions of soil, plant, and atmosphere interactions. Simulated future changes in ET are uncertain, and the role of driving processes remain unclear. Here, we explore the utility of a simple and interpretable method to disentangle these varying drivers. We investigate the sensitivity of JJA ET to different atmospheric variables through simple linear models predicting ET from atmospheric variables only. The model consistently yields good results across GCMs or forcing scenarios. We find that GCMs have shown strong decreases and subsequent increases in ET over the historical period, related to changes in net surface radiation. For future climate projections, decreases in water availability compete with higher available surface radiation, making future projections uncertain. Single forcing GCM realizations show that historical ET trends in densely populated regions have been more influenced by aerosol emissions than greenhouse gases. Finally, we investigate which atmospheric variables explain most short‐term (year‐to‐year) and long‐term (decadal) changes. While water availability may be the most important driver of short‐term variability, for certain regions, radiation trends dominate long‐term forcing. This paper leverages a simple approach to provide a comprehensive and understandable view into recent and future changes in ET, reconciling the evidence provided by more complex case studies.

Climate change impairs the effects of vegetation improvement on soil erosion control in the Qinghai-Tibetan Plateau

Water erosion is a wide ecosystem degradation threat for the Qinghai-Tibetan Plateau (QTP) region and surrounding areas. Climate wetting and vegetation greening in the QTP could have complex impacts on water erosion. However, there is limited information about the erosion dynamics under climate change and the effects of vegetation improvement on erosion control in this alpine region. By calibrating the Revised Universal Soil Loss Equation (RUSLE) model, we estimated water erosion in the QTP and simulated future changes using different Shared Socioeconomic Pathway-Representative Concentration Pathway (SSP) scenarios. We showed intensified erosion and that the benefits of vegetation improvement to erosion control was impaired under climate change. Under the SSP585 scenario, annual water erosion in the QTP was predicted to increase by 0.35 t∙ha−1∙yr−1 and be dominated by an accelerative rise of rainfall erosivity (R factor of RUSLE). Compared with historical observations, the C factor of RUSLE under the SSP585 scenario was believed to reduce by 4.35 % on average during the 2081–2100 period, but predicted soil loss will increase by more than 90 %. Although more considerable vegetation improvement could occur under high climate forcing, there may also be more intensified rainfall erosivity and water erosion across the QTP than those under SSP126 and SSP245 scenarios. Our results suggest that mitigating climate change rather than vegetation improvement is essential to address climate-dominated ecosystem degradation threats such as water erosion in the QTP.

Large simulated future changes in the nitrate radical under the CMIP6 SSP scenarios: implications for oxidation chemistry

Abstract. The nitrate radical (NO3) plays an important role in the chemistry of the lower troposphere, acting as the principle oxidant during the night together with ozone. Previous model simulations suggest that the levels of NO3 have increased dramatically since the preindustrial period. Here, we show projections of the evolution of the NO3 radical from 1850–2100 using the United Kingdom Earth System Model (UKESM1) under the Coupled Model Intercomparison Project Phase 6 (CMIP6) shared socioeconomic pathway (SSP) scenarios. Our model results highlight diverse trajectories for NO3, with some scenarios and regions undergoing rapid growth of NO3 to unprecedented levels over the course of the 21st century and others seeing sharp declines. The local increases in NO3 (up to 40 ppt above the preindustrial base line) are driven not only by local changes in emissions of nitrogen oxides but have an important climate component, with NO3 being favoured in warmer future climates. The changes in NO3 lead to changes in the oxidation of important secondary organic aerosol precursors, with potential impacts on particulate matter pollution regionally and globally. This work highlights the potential for substantial future growth in NO3 and the need to better understand the formation of secondary organic aerosol (SOA) from NO3 to accurately predict future air quality and climate implications.

Mineral dust aerosol impacts on global climate and climate change

Mineral dust aerosols impact the energy budget of Earth through interactions with radiation, clouds, atmospheric chemistry, the cryosphere and biogeochemistry. In this Review, we summarize these interactions and assess the resulting impacts of dust, and of changes in dust, on global climate and climate change. The total effect of dust interactions on the global energy budget of Earth — the dust effective radiative effect — is −0.2 ± 0.5 W m−2 (90% confidence interval), suggesting that dust net cools the climate. Global dust mass loading has increased 55 ± 30% since pre-industrial times, driven largely by increases in dust from Asia and North Africa, leading to changes in the energy budget of Earth. Indeed, this increase in dust has produced a global mean effective radiative forcing of −0.07 ± 0.18 W m−2, somewhat counteracting greenhouse warming. Current climate models and climate assessments do not represent the historical increase in dust and thus omit the resulting radiative forcing, biasing climate change projections and assessments of climate sensitivity. Climate model simulations of future changes in dust diverge widely and are very uncertain. Further work is thus needed to constrain the radiative effects of dust on climate and to improve the representation of dust in climate models. Dust influences the global energy budget through various Earth system interactions. This Review outlines these interactions, revealing a total radiative effect of −0.2 ± 0.5 W m−2, which, alongside 55 ± 30% historical increases in dust, have contributed a radiative forcing of −0.07 ± 0.18 W m−2.

Present and future European heat wave magnitudes: climatologies, trends, and their associated uncertainties in GCM-RCM model chains

Abstract. This study investigates present and future European heat wave magnitudes, represented by the Heat Wave Magnitude Index-daily (HWMId), for regional climate models (RCMs) and the driving global climate models (GCMs) over Europe. A subset of the large EURO-CORDEX ensemble is employed to study sources of uncertainties related to the choice of GCMs, RCMs, and their combinations. We initially compare the evaluation runs of the RCMs driven by ERA-interim reanalysis to E-OBS (observation-based estimates), finding that the RCMs can capture most of the observed spatial and temporal features of HWMId. With their higher resolution compared to GCMs, RCMs can reveal spatial features of HWMId associated with small-scale processes (e.g., orographic effects); moreover, RCMs represent large-scale features of HWMId satisfactorily (e.g., by reproducing the general pattern revealed by E-OBS with high values at western coastal regions and low values at the eastern part). Our results indicate a clear added value of the RCMs compared to the driving GCMs. Forced with the emission scenario RCP8.5, all the GCM and RCM simulations consistently project a rise in HWMId at an exponential rate. However, the climate change signals projected by the GCMs are generally attenuated when downscaled by the RCMs, with the spatial pattern also altered. The uncertainty in a simulated future change of heat wave magnitudes following global warming can be attributed almost equally to the difference in model physics (as represented by different RCMs) and to the driving data associated with different GCMs. Regarding the uncertainty associated with RCM choice, a major factor is the different representation of the orographic effects. No consistent spatial pattern in the ensemble spread associated with different GCMs is observed between the RCMs, suggesting GCM uncertainties are transformed by RCMs in a complex manner due to the nonlinear nature of model dynamics and physics. In summary, our results support the use of dynamical downscaling for deriving regional climate realization regarding heat wave magnitudes.

Post-processing R tool for SWAT efficiently studying climate change impacts on hydrology, water quality, and crop growth

Soil and Water Assessment Tool (SWAT) is widely used for watershed-scale assessment of climate change impacts, but post-processing of model outputs is a tedious job. An R tool was developed in this study for batch processing of SWAT output results. A case study was then performed in the Double Mountain Fork Brazos watershed in the Texas Panhandle using an improved SWAT model with the R tool to evaluate the simulated future changes in water balance components, total nitrogen (TN) load, and crop growth over the watershed. The results showed that the average annual future surface runoff increased by 8.9–17.9 mm and 11.5–22.6 mm in the irrigated and dryland cotton areas, respectively. Similarly, future TN load in irrigated and dryland cotton areas increased by approximately 0.4–0.9 kg ha−1 and 1.9–2.4 kg ha−1. The yields of irrigated and dryland cotton increased by 91.1%–122.1% and 47.5%–84.0% under the future climate scenarios, respectively.

How May the Choice of Downscaling Techniques and Meteorological Reference Observations Affect Future Hydroclimate Projections?

AbstractWe present an intercomparison of a suite of high‐resolution downscaled climate projections based on a six‐member General Circulation Model (GCM) ensemble from Coupled Models Intercomparison Project (CMIP6). The CMIP6 GCMs have been downscaled using dynamical and statistical downscaling techniques based on two meteorological reference observations over the conterminous United States. We use the regional climate model, RegCM4, for dynamical downscaling, double bias correction constructed analogs method for statistical downscaling, and Daymet and Livneh datasets as the reference observations for statistical training and bias‐correction. We evaluate the performances of downscaled data in both historical and future periods under the SSP585 scenario. While dynamical downscaling improves the simulation of some performance evaluation indices, it adds an extra bias in others, highlighting the need for statistical correction before its use in impact assessments. Downscaled datasets after bias‐correction compare exceptionally well with observations. However, the choice of downscaling techniques and the underlying reference observations influence the hydroclimate characteristics of downscaled data. For instance, the statistical downscaling generally preserves the GCMs climate change signal but overestimates the frequency of hot extremes. Similarly, simulated future changes are sensitive to the choice of reference observations, particularly for precipitation extremes that exhibit a higher projected increase in the ensembles trained and/or corrected by Daymet than Livneh. Overall, these results demonstrate that multiple factors, including downscaling techniques and reference observations, can substantially influence the outcome of downscaled climate projections and stress the need for a comprehensive understanding of such method‐based uncertainties.

Active Layer Thickness in the Northern Hemisphere: Changes From 2000 to 2018 and Future Simulations

AbstractActive layer dynamics are basic information for understanding permafrost degradation, but there are gaps in our knowledge of the active layer thickness (ALT) variations during the past two decades and their future changes; this is especially true for data with high spatial resolution. Here, based on permafrost monitoring data and ERA5 (the 5th generation reanalysis project from the European Centre for Medium‐Range Weather Forecasts)‐Land temperature data, we simulated spatial changes in ALT in the Northern Hemisphere during 2000–2018 at a spatial resolution of 1 km2 using the Stefan model. We also simulated future changes in the active layer based on the CMIP6 temperature data. The results showed that ALTs less than 50 cm were mainly distributed in northeastern Siberia in Russia, Alaska and Greenland. The areas with ALTs greater than 600 cm were mainly in southern Norway, and the Mongolian Plateau. The mean ALT of permafrost in the Northern Hemisphere from 2000 to 2018 increased from 127.19 to 145.37 cm at a linear rate of 0.65 cm year−1 (R2 = 0.37, p < 0.05). During 2000–2018, the ALT increased in 71.17% of the total permafrost area, and only 27.23% of the permafrost area showed a decreasing trend. Under different shared socioeconomic pathways (SSP1‐2.6, SSP2‐4.5, SSP3‐7.0, and SSP5‐8.5), the ALT will increase considerably by 2,100. There is a greater increase in ALT in low‐ and mid‐latitude permafrost areas such as the Mongolian Plateau and Qinghai‐Tibet Plateau, with the ALT increasing from 50 to 500 cm. Our results present an overall picture of contemporary distribution as well as future changes of ALT in the Northern Hemisphere.

Multi‐Century Changes in the Ocean Carbon Cycle Controlled by the Tropical Oceans and the Southern Ocean

AbstractThe oceanic absorption of anthropogenic carbon dioxide (CO2) is expected to continue in the following centuries, but the processes driving these changes remain uncertain. We studied these processes in a simulation of future changes in global climate and the carbon cycle following the RCP8.5 high emission scenario. The simulation shows increasing oceanic uptake of anthropogenic CO2 peaking towards the year 2080 and then slowing down but remaining significant in the period up to the year 2300. These multi‐century changes in uptake are dominated by changes in sea‐air CO2 fluxes in the tropical and southern oceans. In the tropics, reductions in upwelling and vertical gradients of dissolved carbon will reduce the vertical advection of carbon‐rich thermocline waters, suppressing natural outgassing of CO2. In the Southern Ocean, the upwelling of waters with relatively low dissolved carbon keeps the surface carbon relatively low, enhancing the uptake of CO2 in the next centuries. The slowdown in CO2 uptake in the subsequent centuries is caused by the decrease in CO2 solubility and storage capacity in the ocean due to ocean warming and changes in carbon chemistry. A collapse of the Atlantic Meridional Overturning Circulation (AMOC) predicted for the next century causes a substantial reduction in the uptake of anthropogenic CO2. In sum, predicting multi‐century changes in the global carbon cycle depends on future changes in carbon chemistry along with changes in oceanic and atmospheric circulations in the Southern and tropical oceans, together with a potential collapse of the AMOC.

Representing responses to climate change in spatial land system models.

Modelling future change to land use and land cover is done as part of many local and global scenario environmental assessments. Nevertheless, there are still considerable challenges related to simulating land‐use responses to climate change. Mostly, climate change is considered by changing the temperature and precipitation, affecting the spatial distribution and productivity of future land use and land cover as result of differential changes in growing conditions. Other climate change effects, such as changes in the water resources needed to support future cropland expansion and intensification, are often neglected. In this study, we demonstrate how including different types of responses to climate change influences the simulation of future changes to land use and land cover, and land management. We study the influence of including different climate change effects in land system modeling step by step. The results show that land system models need to include numerous simultaneous climate change effects, particularly when looking at adaptation options such as implementing irrigation. Otherwise, there is a risk of biased impact estimates leading either to under‐ or overestimation of the consequences of land use change, including land degradation. Spatial land system models therefore need to be developed accounting for a multitude of climate change impacts, uncertainties related to climate data, and an assessment of the sensitivity of the outcomes toward the decisions of modellers on representing climate change impacts.

Associations Between Simulated Future Changes in Climate, Air Quality, and Human Health

Future changes in climate are likely to adversely affect human health by affecting concentrations of particulate matter sized less than 2.5 μm (PM2.5) and ozone (O3) in many areas. However, the degree to which these outcomes may be mitigated by reducing air pollutant emissions is not well understood. To model the associations between future changes in climate, air quality, and human health for 2 climate models and under 2 air pollutant emission scenarios. This modeling study simulated meteorological conditions over the coterminous continental US during a 1995 to 2005 baseline and over the 21st century (2025-2100) by dynamically downscaling representations of a high warming scenario from the Community Earth System Model (CESM) and the Coupled Model version 3 (CM3) global climate models. Using a chemical transport model, PM2.5 and O3 concentrations were simulated under a 2011 air pollutant emission data set and a 2040 projection. The changes in PM2.5 and O3-attributable deaths associated with climate change among the US census-projected population were estimated for 2030, 2050, 2075, and 2095 for each of 2 emission inventories and climate models. Data were analyzed from June 2018 to June 2020. The main outcomes were simulated change in summer season means of the maximum daily 8-hour mean O3, annual mean PM2.5, population-weighted exposure, and the number of avoided or incurred deaths associated with these pollutants. Results are reported for 2030, 2050, 2075, and 2095, compared with 2000, for 2 climate models and 2 air pollutant emissions data sets. The projected increased maximum daily temperatures through 2095 were up to 7.6 °C for the CESM model and 11.8 °C for the CM3 model. Under each climate model scenario by 2095, compared with 2000, an estimated additional 21 000 (95% CI, 14 000-28 000) PM2.5-attributable deaths and 4100 (95% CI, 2200-6000) O3-attributable deaths were projected to occur. These projections decreased to an estimated 15 000 (95% CI, 10 000-20 000) PM2.5-attributable deaths and 640 (95% CI, 340-940) O3-attributable deaths when simulated using a future emission inventory that accounted for reduced anthropogenic emissions. These findings suggest that reducing future air pollutant emissions could also reduce the climate-driven increase in deaths associated with air pollution by hundreds to thousands.

Estimating the distribution and productivity characters of Larix kaempferi in response to climate change

Understanding the distribution, net primary productivity (NPP) and environmental constraints of Larix kaempferi is crucial to predict how global climate change will affect its growth and future dynamics. We simulated future changes in the globally suitable distribution patterns and the NPP dynamics under different representative concentration pathways (RCPs) using MaxEnt and Physiological Principles in Predicting Growth (3-PG) models. The results showed that suitable distribution areas for Larix kaempferi were concentrated in Europe and Asia, followed by North America, under current climate conditions. Globally, about 33.75% of the suitable area was in China. Suitable areas decreased and shifted northward in Asia, Europe and China in the RCP scenarios. Larix kaempferi could adapt or move to higher latitudes/altitudes to mitigate the negative impacts of climate change. The NPP of Larix kaempferi in China was 241.85–863.57 g m−2 a−1 simulated by the 3-PG model after local parameterization, which was consistent with the measured NPP. Changes in NPP were predicted in future climates. When the correlations between climate factors and NPP were examined, under the more optimistic scenarios, NPP would increase significantly. The key parameters of the 3-PG model were the optimal temperature for growth, forest age, and the number of days of lost productivity in each frost period. Therefore, climate change has a quantitative and significant impact on the distribution and productivity of L. kaempferi, which was estimated successfully with the two modeling approaches. Our results will contribute to the improved cultivation, environment and management of L. kaempferi and potentially of other deciduous gymnosperms.

Examination of potential impacts of future climate change on solar radiation in Togo, West Africa

This study investigates the potential impacts of future warming on Global Solar Radiation (GSR) in different parts of Togo, West Africa. It used regional climate simulations of the International Centre for Theoretical Physics version 4.7 (RegCM4) driven by HadGEM-ES and NorESM-M GCM for three different time-slice periods: baseline (1976–2005), near future (2031–2060) and far future (2070–2099). The models produced realistic simulations of GSR and temperature characteristics over the stations and the simulations spread are within the observation uncertainty. The simulations compared fairly well with the NASA observations. Biases in both the GSR (10–37 Wm−2 or 5–17%) and temperature (0.1–2.0 °C or 0.5–7.3%) were found to be insignificant at p < 0.05 across all the stations under investigation. The results revealed increasing but insignificant trends (0.025–0.043 °C year−1) in observed temperature but decreasing (0.225–0.567 Wm−2 year−1) in GSR during the baseline period. The estimated increasing trends (0.004–0.035% year−1) in cloud cover were partly attributed to the observed variations in surface GSR. All models projected increase in temperature (0.2–4.6 °C) but decrease in GSR (0.5–5.8%) over the entire country at both annual and seasonal time-scales. The simulated future changes in temperatures and GSR were expected to increase further and decrease, respectively, by the end of the century. The study has noteworthy implication in solar photovoltaic power production under warmer climate. It suggests a need for improved technology with the least climate change impacts over the republic of Togo, West Africa.

Simulations of future changes in thermal structure of Lake Erken: proof of concept for ISIMIP2b lake sector local simulation strategy

Abstract. This paper, as a part of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2b), assesses the impacts of different levels of global warming on the thermal structure of Lake Erken (Sweden). The General Ocean Turbulence Model (GOTM) one-dimensional hydrodynamic model was used to simulate water temperature when using ISIMIP2b bias-corrected climate model projections as input. These projections have a daily time step, while lake model simulations are often forced at hourly or shorter time steps. Therefore, it was necessary to first test the ability of GOTM to simulate Lake Erken water temperature using daily vs hourly meteorological forcing data. In order to do this, three data sets were used to force the model as follows: (1) hourly measured data, (2) daily average data derived from the first data set, and (3) synthetic hourly data created from the daily data set using generalised regression artificial neural network methods. This last data set is developed using a method that could also be applied to the daily time step ISIMIP scenarios to obtain hourly model input if needed. The lake model was shown to accurately simulate Lake Erken water temperature when forced with either daily or synthetic hourly data. Long-term simulations forced with daily or synthetic hourly meteorological data suggest that by the late 21st century the lake will undergo clear changes in thermal structure. For the representative concentration pathway (RCP) scenario, namely RCP2.6, surface water temperature was projected to increase by 1.79 and 1.36 ∘C when the lake model was forced at daily and hourly resolutions respectively, and for RCP6.0 these increases were projected to be 3.08 and 2.31 ∘C. Changes in lake stability were projected to increase, and the stratification duration was projected to be longer by 13 and 11 d under RCP2.6 scenario and 22 and 18 d under RCP6.0 scenario for daily and hourly resolutions. Model changes in thermal indices were very similar when using either the daily or synthetic hourly forcing, suggesting that the original ISIMIP climate model projections at a daily time step can be sufficient for the purpose of simulating lake water temperature.

Coupled rainfall and water vapour stable isotope time series reveal tropical atmospheric processes on multiple timescales

AbstractHigh‐frequency stable isotope data are useful for validating atmospheric moisture circulation models and provide improved understanding of the mechanisms controlling isotopic compositions in tropical rainfall. Here, we present a near‐continuous 6‐month record of O‐ and H‐isotope compositions in both water vapour and daily rainfall from Northeast Australia measured by laser spectroscopy. The data set spans both wet and dry seasons to help address a significant data and knowledge gap in the southern hemisphere tropics. We interpret the isotopic records for water vapour and rainfall in the context of contemporaneous meteorological observations. Surface air moisture provided near‐continuous tracking of the links between isotopic variations and meteorological events on local to regional spatial scales. Power spectrum analysis of the isotopic variation showed a range of significant periodicities, from hourly to monthly scales, and cross‐wavelet analysis identified significant regions of common power for hourly averaged water vapour isotopic composition and relative humidity, wind direction, and solar radiation. Relative humidity had the greatest subdiurnal influence on isotopic composition. On longer timescales (weeks to months), isotope variability was strongly correlated with both wind direction and relative humidity. The high‐frequency records showed diurnal isotopic variations in O‐ and H‐isotope compositions due to local dew formation and, for deuterium excess, as a result of evapotranspiration. Several significant negative isotope anomalies on a daily scale were associated with the activity of regional mesoscale convective systems and the occurrence of two tropical cyclones. Calculated air parcel back trajectories identified the predominant moisture transport paths from the Southwest Pacific Ocean, whereas moisture transport from northerly directions occurred mainly during the wet season monsoonal airflow. Water vapour isotope compositions reflected the same meteorological events as recorded in rainfall isotopes but provided much more detailed and continuous information on atmospheric moisture cycling than the intermittent isotopic record provided by rainfall. Improved global coverage of stable isotope data for atmospheric water vapour is likely to improve simulations of future changes to climate drivers of the hydrological cycle.

Influence of Sea Surface Temperature on Simulated Future Change in Extreme Rainfall in the Asia-Pacific

The changes in precipitation simulated by the 40-model CMIP5 ensemble for the Asia-Pacific region are assessed, focusing on the two periods 1986–2005 and 2080–2099 under the RCP8.5 scenario. The frequency distributions of both daily and monthly mean rain rates at model grid points in each of four seasons are considered. In spatial averages for the land domain and seven selected regions, there is both an increase in the frequency of dry days and a shift towards heavier rain. Three 20-year seasonal aggregate statistics, the mean, the top decile of monthly amounts, and top percentile of daily amounts are assessed. The percentage changes over land are on average 4% higher for monthly extremes than for the mean, and a further 10% higher for the daily extremes. Over Australia and central Indonesia in some seasons the mean decreases but daily extremes increase. In much of Asia the daily extremes increase by 30% or more. For these statistics, there is a range across the ensemble that can often be linked to a pattern of sea surface temperature change that is quantified by a Pacific-Indian Dipole (or difference, PID) index. Correlations with both mean and extreme rain are highly negative over Australia and Indonesia and moderately positive over parts of south and east Asia in some seasons. The mechanism for this is explored through additional simulations and links with water vapour path. The results provide some understanding of the range of projections of future rainfall change based on the CMIP5 results, with some potential for narrowing it.

Simulated future changes in ENSO dynamics in the framework of the linear recharge oscillator model

This study analysed the changes in El Nino Southern Oscillation (ENSO) dynamics as they are simulated in 25 models of the CMIP5 simulations for the RCP8.5 scenario relative to the historical control simulation. The ENSO linear recharge oscillator (ReOsc) framework is used to focus on changes in the growth rate of eastern equatorial Pacific sea surface temperature (T) and mean equatorial Pacific thermocline depth (h) anomalies, the coupling between the two and the noise forcing driving the ENSO variability. We further focused on the feedbacks controlling the growth rate of T, namely the Bjerknes wind to sea surface temperature (SST) feedback, the atmospheric net heat flux and the residual oceanic feedback. We find significant changes in nearly all of these important elements of the ENSO dynamics, despite the fact that the ensemble shows very little changes in the overall ENSO variability. The growth rate of T weakens resulting from a combination of increased negative atmospheric net heat flux feedbacks, increased positive Bjerknes wind-SST feedback and increased residual oceanic feedbacks. Further notable changes are, an increase in the growth rate of h and a stronger coupling of T to h. Sensitivity analysis of the ReOsc model can explain why these strong dynamical changes lead to effectively no changes in the overall ENSO variability, but are likely to affect the predictability of ENSO.

If Rain Falls in India and No One Reports It, Are Historical Trends in Monsoon Extremes Biased?

AbstractWith two thirds of the total Indian population employed by the agriculture sector, changes in Indian monsoon precipitation have widespread implications for human welfare. Increased extreme precipitation since 1950 has been widely reported for central India. Major studies have relied upon the gridded daily precipitation observations provided by the India Meteorological Department (IMD), which assimilate observations from a variable network of weather stations. Replicating the IMD's interpolation method on satellite‐based precipitation observations, however, indicates that temporal changes in the observing weather station network introduce a jump in the record toward more extreme rainfall after 1975. Trends evaluated across this jump are suspect, and trends evaluated subsequent to it are insignificant (p &gt; 0.1). This positive bias may also mask declines in average monsoon rainfall. Greater accuracy in these trends may resolve distinctions between climate model simulations of future changes. Access to the underlying data from IMD rain‐gauges would facilitate improved rainfall reconstruction.

Continuous separation of land use and climate effects on the past and future water balance

Understanding the combined and separate effects of climate and land use change on the water cycle is necessary to mitigate negative impacts. However, existing methodologies typically divide data into discrete (before and after) periods, implicitly representing climate and land use as step changes when in reality these changes are often gradual. Here, we introduce a new regression-based methodological framework designed to separate climate and land use effects on any hydrological flux of interest continuously through time, and estimate uncertainty in the contribution of these two drivers. We present two applications in the Yahara River Watershed (Wisconsin, USA) demonstrating how our approach can be used to understand synergistic or antagonistic relationships between land use and climate in either the past or the future: (1) historical streamflow, baseflow, and quickflow in an urbanizing subwatershed; and (2) simulated future evapotranspiration, drainage, and direct runoff from a suite of contrasting climate and land use scenarios for the entire watershed. In the historical analysis, we show that ∼60% of recent streamflow changes can be attributed to climate, with approximately equal contributions from quickflow and baseflow. However, our continuous method reveals that baseflow is significantly increasing through time, primarily due to land use change and potentially influenced by long-term increases in groundwater storage. In the simulation of future changes, we show that all components of the future water balance will respond more strongly to changes in climate than land use, with the largest potential land use effects on drainage. These results indicate that diverse land use change trajectories may counteract each other while the effects of climate are more homogeneous at watershed scales. Therefore, management opportunities to counteract climate change effects will likely be more effective at smaller spatial scales, where land use trajectories are unidirectional.

Vegetation masking effect on future warming and snow albedo feedback in a boreal forest region of northern Eurasia according to MIROC‐ESM

AbstractThe Earth system model, Model for Interdisciplinary Research on Climate‐Earth system model (MIROC‐ESM), in which the leaf area index (LAI) is calculated interactively with an ecological land model, simulated future changes in the snow water equivalent under the scenario of global warming. Using MIROC‐ESM, the effects of the snow albedo feedback (SAF) in a boreal forest region of northern Eurasia were examined under the possible climate future scenario RCP8.5. The simulated surface air temperature (SAT) in spring greatly increases across Siberia and the boreal forest region, whereas the snow cover decreases remarkably only in western Eurasia. The large increase in SAT across Siberia is attributed to strong SAF, which is caused by both the reduced snow‐covered fraction and the reduced surface albedo of the snow‐covered portion due to the vegetation masking effect in those grid cells. A comparison of the future changes with and without interactive LAI changes shows that in Siberia, the vegetation masking effect increases the spring SAF by about two or three times and enhances the spring warming by approximately 1.5 times. This implies that increases in vegetation biomass in the future are a potential contributing factor to warming trends and that further research on the vegetation masking effect is needed for reliable future projection.