Multi-model Simulations Research Articles

Mechanisms for Spatially Inhomogeneous Changes in East Asian Summer Monsoon Precipitation during the Mid-Holocene

AbstractThe East Asian summer monsoon (EASM) intensified during the early to mid-Holocene relative to the present primarily due to orbital forcing. However, on the regional scale, changes in the monsoonal precipitation exhibit considerable spatial disparity, and the underlying mechanisms remain unresolved. In this study, the dynamic processes responsible for the difference of the EASM precipitation between the mid-Holocene and preindustrial period are systematically examined using the CMIP5 multimodel simulations. The moisture budget diagnostic identifies vertical motion as the key factor determining the cross-like precipitation pattern in East Asia. Relative to the preindustrial period, the mid-Holocene anomalous ascending motion corresponds well with the excessive precipitation over northern and southern China, and vice versa for west-central China, the Korean peninsula, Japan, and its marginal seas. In the framework of the moist static energy budget, the increased insolation and the attendant intensification of land–sea thermal contrast give rise to anomalous ascending motions, while descending motions are fundamentally forced by the decreased latitudinal insolation gradient. In particular, thermodynamic changes, namely, the reduced pole–equator temperature and humidity gradients, account for the downward motions over the northwestern Pacific. Dynamic changes, namely, the weakened westerlies, play a leading role in suppressing updrafts in west-central China. This study highlights that the orbital-scale monsoonal precipitation changes are not solely determined by local radiative forcing as repeatedly emphasized before. The latitudinal uneven distribution of insolation is crucial to explain the spatial inhomogeneity in the EASM precipitation changes during the Holocene.

Arid/humid patterns over Asia in response to national-committed emission reductions under the Paris agreement

The evolution of regional arid/humid patterns caused by global climate change deserves attention. We investigated the changes in the area of arid/humid climate regions over Asia under the aegis of national-committed emission reductions to comply with the Paris Agreement using an ensemble of 17 global climate models (GCMs) from the Fifth Coupled Climate Model Intercomparison Project (CMIP5) archives. Our results indicated an overall trend towards aridity in a future warmer climate based on an aridity index (AI), defined as the ratio of precipitation to potential evapotranspiration (PET). In the future, the humid region will contract and the arid region and arid/humid transition zones will expand. Compared with the present period, arid/humid region switch is projected to occur in a land area of 2512.8 × 103 km2 over Asia under the Intended Nationally Determined Contributions (INDC)-pledge scenario. If global warming is controlled to the ambitious 2.0 °C and 1.5 °C scenarios instead of that of the INDC-pledge scenario, a decrease in the changes in the area of arid/humid regions by more than half would be expected. In addition, the arid/humid regions with continuous global warming are estimated to contract/expand greatly. Changes in the spatial pattern of the arid/humid zones over Asia show strong similarities between multi-model simulations, although there are some differences in detail.

Multimodel simulation of vertical gas transfer in a temperate lake

Abstract. In recent decades, several lake models of varying complexity have been developed and incorporated into numerical weather prediction systems and climate models. To foster enhanced forecasting ability and verification, improvement of these lake models remains essential. This especially applies to the limited simulation capabilities of biogeochemical processes in lakes and greenhouse gas exchanges with the atmosphere. Here we present multi-model simulations of physical variables and dissolved gas dynamics in a temperate lake (Harp Lake, Canada). The five models (ALBM, FLake, LAKE, LAKEoneD, MTCR-1) considered within this most recent round of the Lake Model Intercomparison Project (LakeMIP) all captured the seasonal temperature variability well. In contrast, none of the models is able to reproduce the exact dates of ice cover and ice off, leading to considerable errors in the simulation of eddy diffusivity around those dates. We then conducted an additional modeling experiment with a diffusing passive tracer to isolate the effect of the eddy diffusivity on gas concentration. Remarkably, sophisticated k−ε models do not demonstrate a significant difference in the vertical diffusion of a passive tracer compared to models with much simpler turbulence closures. All the models simulate less intensive spring overturn compared to autumn. Reduced mixing in the models consequently leads to the accumulation of the passive tracer distribution in the water column. The lake models with a comprehensive biogeochemical module, such as the ALBM and LAKE, predict dissolved oxygen dynamics adequate to the observed data. However, for the surface carbon dioxide concentration the correlation between modeled (ALBM, LAKE) and observed data is weak (∼0.3). Overall our results indicate the need to improve the representation of physical and biogeochemical processes in lake models, thereby contributing to enhanced weather prediction and climate projection capabilities.

Comparing global hydrological models and combining them with GRACE by dynamic model data averaging (DMDA)

Historically, hydrological models have been developed to represent land-atmosphere interactions by simulating water storage and water fluxes. These models, however, have their own unique characteristics (strength and weakness) in capturing different aspects of the water cycle, and their results are typically compared to or calibrated against in-situ observations such as river runoff measurements. As a result, there may be gross inaccuracies in the estimation of water storage states produced by these models. In this study, we present the novel approach of Dynamic Model Data Averaging (DMDA), which can be used to compare and merge multi-model water storage simulations with monthly Terrestrial Water Storage (TWS, a vertical summation of surface and sub-surface water storage) estimates from the Gravity Recovery And Climate Experiment (GRACE) satellite mission. Here, the main hypothesis is that merging GRACE data with multi-model outputs likely provides more skillful hydrological estimations compared to a single model or data set. Theoretically, the proposed DMDA combines the benefits of the Kalman Filter (KF) and Bayesian Model Averaging (BMA) techniques and has the capability to deal with various observations and models with different error structures. Based on the Bayes theory, DMDA provides time-variable weights for hydrological models to compute an average of their outputs that are best fited to GRACE TWS estimates. Numerically, the DMDA method is implemented by integrating the output of six hydrological and land surface models (PCR-GLOBWB, SURFEX-TRIP, LISFLOOD, HBV-SIMREG, W3RA, and ORCHIDEE) and monthly GRACE TWS estimates (2002–2012) within the world’s 33 largest river basins, while considering the inherent uncertainties of all inputs. Our results indicate that DMDA correctly separates GRACE TWS estimates into surface water, soil moisture and groundwater compartments. Linear trends fitted to the DMDA-derived groundwater compartment are found to be different from those of original models. This means that anthropogenic influences within the GRACE data, which are not well reflected by models, are introduced by DMDA. We also find that temporal correlation coefficients between the DMDA-derived individual water storage estimations (surface water, soil moisture, and groundwater) and the El Niño Southern Oscillation (ENSO) index are considerably increased compared to those derived between individual model simulations and ENSO (e.g., an increase from −0.2 to 0.6 in the Murray River Basin). For the Nile River Basin, they changed from 0.1 to 0.4 for the soil moisture, and from 0.3 to 0.7 for the surface water compartment. Comparisons between the DMDA-derived surface water and those from independent satellite altimetry observations indicate that after implementing DMDA, temporal correlation coefficients within major lakes are increased. Based on these results, we have gained confidence in the DMDA water storage estimates to be used for improving the characterization of water storage over broad regions of the globe.

Projection and possible causes of summer precipitation in eastern China using self-organizing map

Self-organizing map (SOM) is used to simulate summer daily precipitation over the Yangtze–Huaihe river basin in Eastern China, including future projections. SOM shows good behaviors in terms of probability distribution of daily rainfall and spatial distribution of rainfall indices, as well as consistency of multi-model simulations. Under RCP4.5 Scenario, daily rainfall at most sites (63%) is projected to shift towards larger values. For the early 21st century (2016–2035), precipitation in the central basin increases, yet decreases occur over the middle reaches of the Yangtze River as well as a part of its southeast area. For the late 21st century (2081–2100), the mean precipitation and extreme indices experience an overall increase except for a few southeast stations. The total precipitation in the lower reaches of the Yangtze River and in its south area is projected to increase from 7% at 1.5 °C global warming to 11% at 2 °C, while the intensity enhancement is more significant in southern and western sites of the domain. A clustering allows to regroup all SOM nodes into four distinct regimes. Such regional synoptic regimes show remarkable stability for future climate. The overall intensification of precipitation in future climate is linked to the occurrence-frequency rise of a wet regime which brings longitudinally closer the South Asia High (eastward extended) and the Western Pacific Subtropical High (westward extended), as well as the reduction of a dry pattern which makes the two atmospheric centers of action move away from each other.

Diagnostic Metrics for Evaluating Model Simulations of the East Asian Monsoon

AbstractThe distinctive monsoon climate over East Asia, which is affected by the vast Eurasian continent and Pacific Ocean basin and the high-altitude Tibetan Plateau, provides arguably the best testbed for evaluating the competence of Earth system climate models. Here, a set of diagnostic metrics, consisting of 14 items and 7 variables, is specifically developed. This physically intuitive set of metrics focuses on the essential features of the East Asian summer monsoon (EASM) and East Asian winter monsoon (EAWM), and includes fields that depict the climatology, the major modes of variability, and unique characteristics of the EASM. The metrics are applied to multimodel historical simulations derived from 20 models that participated in phases 3 and 5 of the Coupled Model Intercomparison Project (CMIP3 and CMIP5, respectively), along with the newly developed Nanjing University of Information Science and Technology Earth System Model, version 3. The CMIP5 models show significant improvements over the CMIP3 models in terms of the simulated East Asian monsoon circulation systems on a regional scale, major modes of EAWM variability, the monsoon domain and precipitation intensity, and teleconnection associated with the heat source over the Philippine Sea. Clear deficiencies persist from CMIP3 to CMIP5 with respect to capturing the major modes of EASM variability, as well as the relationship between the EASM and ENSO during El Niño developing and decay phases. The possible origins that affect models’ performance are also discussed. The metrics provide a tool for evaluating the performance of Earth system climate models, and facilitating the assessment of past and projected future changes of the East Asian monsoon.

Understanding atmospheric methane sub-seasonal variability over India

Atmospheric methane (CH4) is considered to be one of the most important greenhouse gases due to its increasing atmospheric concentrations and the fact that it has a warming potential 28 times that of atmospheric carbon dioxide (CO2). Over the Indian sub-continent, fluxes and transport both contribute towards CH4 seasonal variability. Its intra-seasonal variability however is more complex as it is additionally influenced by monsoonal activity during the Asian Summer Monsoon (ASM) period. In this study, the intra-seasonal variability of atmospheric CH4 is examined using ground-based observations at two sites located in the Southern Indian Peninsula, Sinhagad (SNG) and Cape Rama (CRI); and outputs from three different model simulations. Both, the ground based observations and multi-model simulations show that the dominant spectral variability of CH4 is coherent with 20–90 day oscillations in the dynamics of the monsoon (termed hereafter as Intra-Seasonal Oscillations, ISOs). The multi-model analysis revealed that CH4 is heavily influenced by advection due to this intra-seasonal variability. The simulations also display a clear northward propagation of CH4 anomalies over India. The co-evolution of CH4, outgoing long wave radiation (to represent convection) and OH radicals (proxy to CH4 sinks) is presented. The study quantifies CH4 variability at intra-seasonal timescales and also its spatial extent. The results suggest that the effect of ISOs on CH4 needs to be considered along with the corresponding observations for future inverse modeling.

Recent recovery of the boreal spring sensible heating over the Tibetan Plateau will continue in CMIP6 future projections

The spring sensible heating (SH) over the Tibetan Plateau (TP) serves as a huge ‘air pump’, significantly influencing the Asian summer monsoon, has experienced a decreasing trend. However, it remains unclear whether this decline will continue. Therefore, we here examine the long-term trends of spring SH over the central and eastern TP (CETP) based on a meteorological station-based calculated SH dataset, and CMIP6 multi-model simulations. These two sources confirmed the previous finding that the SH peaks in May. Further, we find that the declining SH was replaced by a fast recovery after approximate 2000 in the station-based SH. This is to some extent verified by the historical simulations of CMIP6 models. Importantly, CMIP6 future projections suggest that this increasing trend will continue, and get stronger with higher radiative forcing from SSP126 to SSP585. Mechanism analysis indicates that the previous decreasing trend in SH was mainly caused by the decline of 10 m wind speed, while the recent and future increasing trend results from the rising ground-air temperature difference. We suggest that this increasing trend of spring SH over the CETP may serve as an alternative driver for the enhancement of the East Asian summer monsoon in the future.

Future floods using hydroclimatic simulations and peaks over threshold: An alternative to nonstationary analysis inferred from trend tests

Nonstationary flood frequency analysis (NFFA) has increasingly been applied to predict future floods under climate change. The inference of nonstationarity from trend tests (INTT) on historical floods is a widespread practice used to justify the application of NFFA; however, its reliability has seldom been investigated. This research examines future floods from interpretations of INTT compared to those obtained from cause-and-effect processes by a hydrological model (INCE). The study uses INCE to quantify the changes in the regime and magnitude of floods due to potential climate change in the mid-21st century using multi-model ensemble simulations under two greenhouse gas emissions scenarios (i.e., RCP 2.6 and RCP 8.5). Independent peaks over threshold from simulated streamflow were used to estimate the changes in future (2040–2064) flood regimes and magnitudes compared to their historical (1983–2007) counterparts for 29 unregulated catchments across Alberta, Canada. Separation of extreme events and their fittings to generalized Pareto distributions (GPD) were based on a hybrid approach that combined two developed automated threshold selection methods and four estimators for the parameters of the GPD. Based on comparing the results of INTT and INCE, we show that future changes in floods contradict. We also show that the future frequency curves shifted differently at different return periods compared to historical curves, while in some instances, future climate tended to decrease small floods and increase larger floods or vice versa. Finally, flood magnitudes in 2/3 of the studied catchments in Alberta are predicted to intensify, accompanied by increases in the rate of occurrence and earlier shifts in the timing of floods for both climate scenarios, whereas no considerable change in the duration was recognized.

Multimodel simulations of a springtime dust storm over northeastern China: implications of an evaluation of four commonly used air quality models (CMAQ v5.2.1, CAMx v6.50, CHIMERE v2017r4, and WRF-Chem v3.9.1)

Abstract. Mineral dust particles play an important role in the Earth system, imposing a variety of effects on air quality, climate, human health, and economy. Accurate forecasts of dust events are highly desirable to provide an early warning and inform the decision-making process. East Asia is one of the largest dust sources in the world. This study applies and evaluates four widely used regional air quality models to simulate dust storms in northeastern China. Three dust schemes in the Weather Research and Forecasting model with Chemistry (WRF-Chem) (version 3.9.1), two schemes in both CHIMERE (version 2017r4) and CMAQ (version 5.2.1), and one scheme in CAMx (version 6.50) were applied to a dust event during 4–6 May 2015 in northeastern China. Most of these models were able to capture this dust event with the exception of CAMx, which has no dust source map covering the study area; hence, another dust source mask map was introduced to replace the default one for the subsequent simulation. Although these models reproduced the spatial pattern of the dust plume, there were large discrepancies between predicted and observed PM10 concentrations in each model. In general, CHIMERE had relatively better performance among all simulations with default configurations. After parameter tuning, WRF-Chem with the Air Force Weather Agency (AFWA) scheme using a seasonal dust source map from Ginoux et al. (2012) showed the best performance, followed by WRF-Chem with the UOC_Shao2004 scheme, CHIMERE, and CMAQ. The performance of CAMx had significantly improved by substituting the default dust map and removing the friction velocity limitation. This study suggested that the dust source maps should be carefully selected on a regional scale or replaced with a new one constructed with local data. Moreover, further study and measurement of sandblasting efficiency of different soil types and locations should be conducted to improve the accuracy of estimated vertical dust fluxes in air quality models.

Spatiotemporal Reliability Ensemble Averaging of Multimodel Simulations

AbstractMultimodel combining approaches can extract reliable climate information from a large number of climate projections by exploiting the strengths and discounting the weaknesses of each climate simulator; however, most of them (e.g., reliability ensemble averaging [REA]) assign weights to climate simulators without accounting for spatial and temporal variabilities in climate model skills. Here we tested several REAs and proposed a full version that reflects the spatiotemporal (ST) variability of climate model skills. Interperformance evaluations between REA versions showed that, on average, ST‐REA reduced the bias by 33.78% and the root mean square error by 11.61%. Therefore, spatial and temporal variabilities in climate model skills can enhance the overall reliability of precipitation projections. ST‐REA was applied to project future precipitations over South Korea by combining seven climate models: The spatially averaged projected changes were 2.77%, 8.15%, and 7.58% for the 2020–2039, 2040–2069, and 2070–2099 periods, respectively.

Mechanisms Reducing ENSO Amplitude and Asymmetry via an Enhanced Seasonal Cycle in the Mid-Holocene

Abstract Paleo proxy records have suggested that El Niño–Southern Oscillation (ENSO) variability during the mid-Holocene [8200 to 4200 years ago (8.2–4.2 ka)] was weaker than during the instrumental periods, but the mechanisms remain unclear. We examined processes of ENSO suppression using a coupled general circulation model (CGCM) that simulates ENSO amplitude and skewness under the present climate reasonably well. Two long simulations were performed: one using the preindustrial condition (CTRL) and the other using the 8-ka insolation having a greater seasonal cycle (MH8K). Consistent with proxy records and previous modeling studies, the ENSO amplitude weakened by 20% in MH8K compared to CTRL, mainly because of reduced thermocline feedback during the mature and decay phases. The weak thermocline feedback, likely a result of the loose equatorial thermocline in the mid-Holocene, suppresses the occurrence of extreme El Niño events and consequently explains the reduction in both ENSO amplitude and asymmetry. In MH8K, strengthened trade winds over the western-central Pacific Ocean act to cool the surface via evaporation while warmer water in the southern subtropical Pacific is transported beneath the equatorial thermocline, both contributing to diffuse the thermocline. Multimodel simulations for the mid-Holocene showed mean state changes and ENSO weakening similar to MH8K, but most models did not show reduced ENSO skewness, probably because of the failure in reproducing extreme El Niño events under the present climate.

Uncertainties in the Effects of Climate Change on Maize Yield Simulation in Jilin Province: A Case Study

Measuring the impacts of uncertainties identified from different global climate models (GCMs), representative concentration pathways (RCPs), and parameters of statistical crop models on the projected effects of climate change on crop yields can help to improve the availability of simulation results. The quantification and separation of different sources of uncertainty also help to improve understanding of impacts of uncertainties and provide a theoretical basis for their reduction. In this study, uncertainties of maize yield predictions are evaluated by using 30 sets of parameters from statistical crop models together with eight GCMs with reference to three emission scenarios for Jilin Province of northeastern China. Regression models using replicates based on bootstrap resampling reveal that yields are maximized when the optimum average growing season temperature is 20.1°C for 1990–2009. The results of multi-model ensemble simulations show a maize yield reduction of 11%, with 75% probability for 2040–69 relative to the baseline period of 1976–2005. We decompose the variance so as to understand the relative importance of different sources of uncertainty, such as GCMs, RCPs, and statistical model parameters. The greatest proportion of uncertainty (> 50%) is derived from GCMs, followed by RCPs with a proportion of 28% and statistical crop model parameters with a proportion of 20% of total ensemble uncertainty.

Mechanisms for an Amplified Precipitation Seasonal Cycle in the U.S. West Coast under Global Warming

Abstract The mean precipitation along the U.S. West Coast exhibits a pronounced seasonality change under warming. Here we explore the characteristics of the seasonality change and investigate the underlying mechanisms, with a focus on quantifying the roles of moisture (thermodynamic) versus circulation (dynamic). The multimodel simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5) show a simple “wet-get-wetter” response over Washington and Oregon but a sharpened seasonal cycle marked by a stronger and narrower wet season over California. Moisture budget analysis shows that changes in both regions are predominantly caused by changes in the mean moisture convergence. The thermodynamic effect due to the mass convergence of increased moisture dominates the wet-get-wetter response over Washington and Oregon. In contrast, mean zonal moisture advection due to seasonally dependent changes in land–sea moisture contrast originating from the nonlinear Clausius–Clapeyron relation dominates the sharpened wet season over California. More specifically, the stronger climatological land–sea thermal contrast in winter with warmer ocean than land results in more moisture increase over ocean than land under warming and hence wet advection to California. However, in fall and spring, the future change of land–sea thermal contrast with larger warming over land than ocean induces an opposite moisture gradient and hence dry advection to California. These results have important implications for projecting changes in the hydrological cycle of the U.S. West Coast.

Mid-Holocene drylands: A multi-model analysis using Paleoclimate Modelling Intercomparison Project Phase III (PMIP3) simulations

This study examines changes in aridity levels during the mid-Holocene (approximately 6000 cal. yr ago) using multi-model simulations from the Paleoclimate Modelling Intercomparison Project Phase III. Overall, there is little difference in the total area of drylands from the preindustrial period; global drylands are 8% wetter than during the preindustrial period as measured by an aridity index; and 16% of preindustrial drylands convert to a wetter climate subtype, double the sum of zones that are replaced by a drier category. Considerable variations are present among regions with major contractions of each dryland subtype from northern Africa to South Asia and the main expansions of arid, semiarid, and dry subhumid climates in southern hemisphere continents. The difference in precipitation is the leading factor of the aforementioned changes. The second factor is the altered potential evapotranspiration as mainly induced by relative humidity, which contributes to additional aridity changes in a same direction as precipitation does. The collective effects of precipitation and relative humidity account for more than 80% of the dryland variations. In comparison, the simulated aridity change is in reasonable agreement with reconstructions, while there are model–data discrepancies for Australia and uncertainties across proxies for southern Africa.

Impact of Solar Radiation Modification on Allowable CO2 Emissions: What Can We Learn From Multimodel Simulations?

AbstractSolar radiation modification (SRM) is known to strengthen both land and ocean carbon uptake because of its impacts on surface temperature, solar radiation, and other potential drivers of the global carbon cycle. However, the magnitude and timing of the response of both land and ocean carbon uptake to SRM and its consequence on allowable CO2 emissions remain poorly understood. Here we use the results of six Earth system models simulating a continuous stratospheric injection of 5 Tg of sulfur dioxide per year between 2020 and 2069 under the representative concentration pathways 4.5 to investigate the impact of SRM on land and ocean carbon uptake. We find that 50 years of SRM under this protocol increases the allowable CO2 emissions by 40 ± 19 GtC; 85% of this additional uptake of carbon is stored in the land biosphere and 15% in the ocean. This increase in allowable CO2 emissions is however not sustainable after the stoppage of SRM. Earth system models predict a mean release of 8 ± 11 GtC of the carbon back to the atmosphere 20 years after the stoppage which is dominated by large uncertainties in the response of the simulated land carbon cycle to rising temperature and solar radiation. We demonstrate that the time scales of carbon dioxide removal (CDR) potential of SRM are smaller than the time scales of the geological storage assumed in well‐established CDR options. This shows that the CDR potential of SRM should be compared to well‐established CDR options with caution.

Global Heat Wave Hazard Considering Humidity Effects during the 21st Century.

Humidity is a significant factor contributing to heat stress, but without enough consideration in studies of quantifying heat hazard or heat risk assessment. Here, the simplified wet-bulb globe temperature (WBGT) considering joint effects of temperature and humidity was utilized as a heat index and the number of annual total heat wave days (HWDs) was employed to quantify heat hazard. In order to evaluate the humidity effects on heat waves, we quantified the difference in the number of HWDs over global land based on air temperature and WBGT. Spatial and temporal changes in surface air temperature, relative humidity, WBGT, and the difference in HWDs were analyzed using multi-model simulations for the reference period (1986–2005) and different greenhouse gas emission scenarios. Our analysis suggests that annual mean WBGT has been increasing since 1986, which is consistent with the rising trend in surface air temperature despite a slight decrease in relative humidity. Additionally, changes in annual mean WBGT are smaller and more spatially uniform than those in annual mean air temperature as a cancelation effect between temperature and water vapor. Results show that there is an underestimation of around 40–140 days in the number of HWDs per year in most regions within 15° latitude of the equator (the humid and warm tropics) during 2076–2095 without considering humidity effects. However, the estimation of HWDs has limited distinction between using WBGT and temperature alone in arid or cold regions.

Strengthened linkage between midlatitudes and Arctic in boreal winter

Early studies have suggested a linkage between the surface warming over the Barents-Kara Seas and the strength of the Siberian high in boreal winter. Here, we show that the linkage is not stable, and with an apparent interdecadal change in the late-1990s. Coinciding with Arctic surface warm anomalies in recent decades (1997–2017), the Siberian high has been significantly intensified, the East Asian jet stream has expanded westward, and an apparent Rossby wave has propagated from the Arctic to East Asia, suggesting an atmospheric teleconnection between midlatitudes and Arctic. In contrast, midlatitude atmospheric circulation anomalies coinciding with Arctic surface warm anomalies were barely statistically significant during 1979–1996. The associated strong anomalous ascending/descending motions and divergent/convergent upper troposphere air masses over the Arctic-Eurasian sector seem to have favored the midlatitude-Arctic linkage during 1997–2017. We further hypothesize that Arctic mid-tropospheric warming plays a crucial role for the linkage between midlatitudes and Arctic in boreal winter. Multi-model simulations support this, and also point to internal atmospheric variability as the cause for the interdecadal shift in the strength of the midlatitude-Arctic linkage.

Model consensus projections of US regional hydroclimates under greenhouse warming

We investigate ensemble-mean (‘consensus’) values of resolution-weighted CMIP5 multi-model simulations of 1976–2005 summer regional hydroclimates, and of their projected 2070–2099 changes under three progressively more severe representative concentration pathways greenhouse scenarios. Uncertainties in these consensus values are estimated from the cross-ensemble scatter. We analyze differences among 30 year present-day and future consensus summer hydroclimates that are averaged over three disparate regions of the United States: the semi-arid Southern Great Plains, the arid Southwest, and the humid Southeast. Our study considers the impact of several scenarios of greenhouse forcing on the regional averages of both single hydroclimatic variables and on ratios of variables which are indicative of continental drying, as well as the partitioning of surface moisture or available energy into their respective subcomponents. In all three study regions, there is a projected robust increase in surface temperature as the severity of the greenhouse scenario increases; but the regional-average hydroclimatic changes are comparatively uncertain, and often are not proportional to the change in surface warming. There is, however, a projected robust increase in continental drying that is manifested by several complementary measures, but that differs in magnitude by region. The prospect of future continental aridification should be viewed with some caution, however, since it may be a result of various shortcomings in current-generation climate models or in the specified greenhouse scenarios.

Evaluating the influence of climate change on the fate and transport of fecal coliform bacteria using the modified SWAT model

Fecal coliform bacteria (FCB) contamination of natural waters is a serious public health issue. Therefore, understanding and anticipating the fate and transport of FCB are important for reducing the risk of contracting diseases. The objective of this study was to analyze the impacts of climate change on the fate and transport of FCB. We modified both the soil and the in-stream bacteria modules in the soil and water assessment tool (SWAT) model and verified the prediction accuracy of seasonal variability of FCB loads using observations. Forty bias-correcting GCM-RCM projections were applied in the modified SWAT model to examine various future climate conditions at the end of this century (2076–2100). Lastly, we also compared the variability of FCB loads under current and future weather conditions using multi-model ensemble simulations (MMES). The modified SWAT model yielded a satisfactory performance with regard to the seasonal variability of FCB amounts in the soil and FCB loading to water bodies. The modified SWAT model presented substantial proliferation of FCB in the soil (30.1%–147.5%) due to an increase in temperature (25.1%). Also, increase in precipitation (53.3%) led to an increase in FCB loads (96.0%–115.5%) from the soil to water body. In the in-stream environment, resuspension from the stream bed was the dominant process affecting the amount of FCB in stream. Therefore, the final FCB loads increased by 71.2% because of the growing peak channel velocity and volume of water used due to an increase in precipitation. Based on the results of MMES, we concluded that the level of FCB would increase simultaneously in the soil as well as in stream by the end of this century. This study will aid in understanding the future variability of FCB loads as well as in preparing an effective management plan for FCB levels in natural waters.