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Sea surface temperature (SST) observations in the North Atlantic since 1870 reveal a region of enhanced warming off the northeastern coast of North America, and a region of cooling to the south of Greenland. It has been hypothesized that these adjacent SST trends are a result of long‐term changes in the buoyancy‐driven ocean circulation—a slowdown of the Atlantic Meridional Overturning Circulation. The impacts of these historical SST trends on the atmosphere are estimated using idealized atmospheric general circulation model experiments in which the global atmosphere is exposed to modern climatological forcing minus the aforementioned regional SST trends. The local response includes a negative North Atlantic Oscillation tendency and southward shift of the wind forcing for the subtropical gyre. Due to planetary wave propagation, the regional SST trends also induce a northward shift of the intertropical convergence zone over the Indian Ocean. Implications for climate feedbacks and projections are discussed. Plain Language Summary: The ocean surface is warming over most of the planet, with a couple of notable exceptions. One is over the North Atlantic Ocean, just south of Greenland, where the temperature of the ocean surface has actually been cooling by about 1°C since 1870. Nearby, extending off the northeastern coastline of North America is a region where the ocean surface has been warming much faster than the global ocean on average—by about 1.5°C since 1870. This side‐by‐side pair of accelerated warming and cooling trends is likely due to a slowdown of the ocean's overturning circulation, which carries large amounts of heat energy from the tropics toward the poles. This paper reveals the effects of those unusual ocean temperature trends in the North Atlantic on the atmospheric circulation using a computer model of the global atmosphere. The model simulations indicate that these ocean temperature trends are causing shifts in the jet stream, changing the way the winds propel the upper ocean currents, and even have impacts quite far away by moving the tropical rain belt northward in the Indian Ocean. Key Points: The impact of historical sea surface temperature trends in the North Atlantic since 1870 is simulated with a global atmospheric modelAdjacent warming and cooling trends in the North Atlantic Ocean induce a negative NAO‐like response and southward‐shifted gyre forcingPropagation of planetary waves away from the North Atlantic induces a northward‐shifted intertropical convergence zone in the Indian Ocean [ABSTRACT FROM AUTHOR]

Recent studies have shown that spring land surface temperature (LST) and subsurface temperature (SUBT) over the high elevation areas in the western US (WUS) have significant impacts on the downstream summer droughts/floods in North America. In this paper, both the National Centers for Environmental Prediction—Global Forecast System (NCEP-GFS) general circulation model (GCM) and the weather research and forecasting (WRF) regional climate model (RCM) are employed, where RCM scenarios utilized initial and lateral boundary conditions derived from the corresponding NCEP-GFS scenarios. Here we use a late spring flood in the US Southern Great Plains (SGP) case to examine whether simulation of the LST/SUBT downstream effects is sensitive to the domain size choice, change in dynamical cores within the same model, as well as to the representation of surface processes parameterizations. Although all RCM experiments with different settings simulate reasonably geographical patterns of observed LST and precipitation anomalies, we found that the choice of the domain size is crucial for proper downscaling the LST/SUBT downstream effects to accurately produce the observed precipitation/LST anomalies over the SGP/WUS, respectively, along with the associated large-scale features. The southern boundary location has been identified to be crucial in producing the SGP Low Level Jet strength, which in turn brings more moisture from the Gulf of Mexico to the SGP and thereby resulting in a better simulation of the precipitation anomaly in that area. The sensitivity of the simulation of the LST/SUBT downstream effect to dynamical cores is assessed by inter-comparing the Non-hydrostatic Mesoscale Model (NMM) and the Advanced Research WRF dynamic cores. We find NMM was better at generating the large-scale eastward wave train, a crucial process associated with the LST/SUBT downstream effect. Meanwhile, this study also shows that the LST/SUBT downstream effects were not significantly dependent on the surface process parameterizations, although the Simplified Simple Biosphere model version 3 (SSiB3) highlighted a better performance over SSiB2. [ABSTRACT FROM AUTHOR]

We examine the impact of horizontal resolution and model time step on the climate of the OpenIFS version 43r3 atmospheric general circulation model. A series of simulations for the period 1979–2019 are conducted with various horizontal resolutions (i.e. ∼100 , ∼50 , and ∼25 km) while maintaining the same time step (i.e. 15 min) and using different time steps (i.e. 60, 30, and 15 min) at 100 km horizontal resolution. We find that the surface zonal wind bias is significantly reduced over certain regions such as the Southern Ocean and the Northern Hemisphere mid-latitudes and in tropical and subtropical regions at a high horizontal resolution (i.e. ∼25 km). Similar improvement is evident too when using a coarse-resolution model (∼100 km) with a smaller time step (i.e. 30 and 15 min). We also find improvements in Rossby wave amplitude and phase speed, as well as in weather regime patterns, when a smaller time step or higher horizontal resolution is used. The improvement in the wind bias when using the shorter time step is mostly due to an increase in shallow and mid-level convection that enhances vertical mixing in the lower troposphere. The enhanced mixing allows frictional effects to influence a deeper layer and reduces wind and wind speed throughout the troposphere. However, precipitation biases generally increase with higher horizontal resolutions or smaller time steps, whereas the surface air temperature bias exhibits a small improvement over North America and the eastern Eurasian continent. We argue that the bias improvement in the highest-horizontal-resolution (i.e. ∼25 km) configuration benefits from a combination of both the enhanced horizontal resolution and the shorter time step. In summary, we demonstrate that, by reducing the time step in the coarse-resolution (∼100 km) OpenIFS model, one can alleviate some climate biases at a lower cost than by increasing the horizontal resolution. [ABSTRACT FROM AUTHOR]

This paper assesses linear regression-based methods in downscaling daily precipitation from the general circulation model (GCM) scale to a regional climate model (RCM) scale (45- and 15-km grids) and down to a station scale across North America. Traditional downscaling experiments (linking reanalysis/dynamical model predictors to station precipitation) as well as nontraditional experiments such as predicting dynamic model precipitation from larger-scale dynamic model predictors or downscaling dynamic model precipitation from predictors at the same scale are conducted. The latter experiments were performed to address predictability limit and scale issues. The results showed that the downscaling of daily precipitation occurrence was rarely successful at all scales, although results did constantly improve with the increased resolution of climate models. The explained variances for downscaled precipitation amounts at the station scales were low, and they became progressively better when using predictors from a higher-resolution climate model, thus showing a clear advantage in using predictors from RCMs driven by reanalysis at its boundaries, instead of directly using reanalysis data. The low percentage of explained variances resulted in considerable underestimation of daily precipitation mean and standard deviation. Although downscaling GCM precipitation from GCM predictors (or RCM precipitation from RCM predictors) cannot really be considered downscaling, as there is no change in scale, the exercise yields interesting information as to the limit in predictive ability at the station scale. This was especially clear at the GCM scale, where the inability of downscaling GCM precipitation from GCM predictors demonstrates that GCM precipitation-generating processes are largely at the subgrid scale (especially so for convective events), thus indicating that downscaling precipitation at the station scale from GCM scale is unlikely to be successful. Although results became better at the RCM scale, the results indicate that, overall, regression-based approaches did not perform well in downscaling precipitation over North America. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Key mechanisms important for the simulation and better understanding of the precipitation of the North American monsoon (NAM) were analyzed in this paper. Three experiments with the Providing Regional Climates for Impacts Studies (PRECIS) regional climate model, the Hadley Centre Regional Model version 3P (HadRM3P), driven by different boundary conditions were carried out. After a detailed analysis of the moisture and low-level winds derived from the models, the authors conclude that the Gulf of Mexico (GoM) moisture and the Great Plains low-level jet (GPLLJ) play an important role in the northern portion of the NAM. Moreover, the realistic simulation of these features is necessary for a better simulation of precipitation in the NAM. Previous works suggest that the influence of moisture from the GoM in Arizona--New Mexico (AZNM) takes place primarily via the middle- and upper-tropospheric flow (above 700 mb). However, it is shown here that if the GoM does not supply enough moisture and the GPLLJ at lower levels (below 700 mb) does not reach the AZNM region, then a dry westerly flow dominates that area and the summer precipitation is below normal. The implications of these findings for studies of climate change are demonstrated with the analysis of two general circulation models (GCMs) commonly used for climate change prediction, which are shown not to reproduce correctly the GPLLJ intensity nor the moisture in the GoM. This implies that the precipitation in AZNM would not be correctly represented by a regional model driven by these GCMs. [ABSTRACT FROM AUTHOR]

In northwestern North America, which is a large area with complex physiography, Climatic Research Unit (CRU) Time Series, version 2.1, (TS 2.1) gridded monthly mean 2-m temperatures are systematically lower than interpolated monthly averaged North American Regional Reanalysis (NARR) pressure-level temperatures----in particular, in the winter. Quantification of these differences based on CRU gridded observations can be used to estimate pressure-level temperatures from CRU 2-m temperatures (1901--2002) that predate the NARR period (since 1979). Such twentieth-century pressure-level temperature fields can be used in glacier mass-balance modeling and as an alternative to calibrating general circulation model control runs, avoiding the need for accurate boundary layer parameterization. In this paper, an approach is presented that is transferable to moisture, wind, and other 3D fields with potential applications in wind power generation, ecology, and air quality. At each CRU grid point, the difference between CRU and NARR is regressed against seven predictors in CRU (mean temperature, daily temperature range, precipitation, vapor pressure, cloud cover, and number of wet and frost days) for the period of overlap between CRU and NARR (1979--2002). Bayesian model averaging (BMA) is used to avoid overfitting the CRU--NARR differences and underestimating uncertainties. In cross validations, BMA provides reliable posterior predictions of the CRU--NARR differences and outperforms predictions from three alternative models: the constant model (24-yr mean), the regression model of highest Bayesian model probability, and the full model retaining all seven predictors in CRU. [ABSTRACT FROM AUTHOR]

The extent to which wintertime North American surface temperature can be specified based on simultaneous sea surface temperature (SST) is quantified for the period 1982–98. The term specification indicates that the predictor and predictands are not lagged in time, as would be the case for true prediction. Four state-of-the-art general circulation models (GCMs) and linear empirical models with predictors derived from observations and dynamical models are considered. Predictors are derived from model hindcasts using principal component analysis (PCA), canonical correlation analysis (CCA), and discriminant analysis. The last technique has appeared in the climate literature, but its use in the present context appears new. A distinguishing feature of this paper is that several methods and models are compared in a common framework. The specification skill of GCMs for the period 1982–98 is statistically significant in the northwestern region near Washington State, British Columbia, and central Canada, with some local correlations exceeding 0.6. The specification skill of GCMs is comparable to, or better than, the skill of the best empirical model for the particular 17-yr period examined. No single specification strategy was found to improve the model hindcast skill in all cases. Predictors derived from discriminant analysis generally lead to larger skill than predictors based on PCA or CCA. The signal-to-noise ratio varies greatly among models and appears to be, if anything, inversely related to the specification skill when discriminants are used as predictors. Predictors based on 500-hPa geopotential height can lead to specification skill at least as good as predictors based on land surface temperature. Evidence is presented for the existence of at least two distinct dynamically predictable components of land surface temperature arising from two distinct “flavors” of SST anomalies associated with El Niño and La Niña. [ABSTRACT FROM AUTHOR]

Using Climate Forecast System Reanalysis (CFSR) data and numerical simulations, the impacts of the multi‐scale sea surface temperature (SST) anomalies in the North Pacific on the boreal winter atmospheric circulations are investigated. The basin‐scale SST anomaly as the Pacific Decadal Oscillation (PDO) pattern, a narrow meridional band of frontal‐scale smoothed SST anomaly in the subtropical front zone (STFZ) and the spatial dispersed eddy‐scale SST anomalies within the STFZ are the three types of forcings. The results of statistical methods find that all three oceanic forcings may correspond to the winter North Pacific jet changing with the similar pattern. Furthermore, several atmospheric general circulation model simulations are used to reveal the differences and detail processes of the three forcings. The basin‐scale cold PDO‐pattern SST anomaly first causes negative turbulent heat flux anomalies, atmospheric cooling, and wind deceleration in the lower atmosphere. Subsequently, the cooling temperature with an amplified southern lower temperature gradient and baroclinity brings a lagging middle warming because of the enhanced atmospheric eddy heat transport. The poleward and upward development of baroclinic fluctuations eventually causes the acceleration of the upper jet. The smoothed frontal‐ and eddy‐scales SST anomalies in the STFZ cause comparable anomalous jet as the basin‐scale by changing the upward baroclinic energy and Eliassen‐Palm fluxes. The forcing effects of multi‐scales SST anomalies coexist simultaneously in the mid‐latitude North Pacific, which can cause similar anomalous upper atmospheric circulations. This is probably why it is tricky to define the certain oceanic forcing to the specific observed atmospheric circulation variation. Plain Language Summary: The impacts of multi‐scale interannual oceanic forcings on the winter North Pacific upper jet are studied such as the basin‐scale Pacific Decadal Oscillation pattern SST anomaly, a narrow meridional band of frontal‐scale smoothed SST anomaly in the subtropical front zone (STFZ) and the spatial dispersed eddy‐scale SST anomalies within the STFZ. Using Liang‐Kleeman information flow method, it is found that the above three oceanic forcings may change the upper jet over the North Pacific with the similar intensity and location characteristics. Further Community Atmosphere Model Version 5.3 simulations reveal that the basin‐scale PDO‐pattern cold SST anomaly first forces the lower atmosphere by the anomalous surface turbulent heat flux, which quickly brings air cooling and wind deceleration. After that, northward and upward eddy heat transports induced by temperature gradient south to SST anomaly cause atmospheric baroclinic variation and eventually lead to the acceleration of westerly upper jet over the cold SST. Differing the basin‐scale anomaly, frontal‐ and eddy‐scale SST anomalies in the STFZ directly change the uploading baroclinic waves and E‐P fluxes divergence resulting in comparable atmospheric responses. This study will be beneficial to the weather and climate forecasts over the North Pacific and North America. Key Points: Basin‐, frontal‐, and eddy‐scale oceanic forcing effects on the winter North Pacific jet exist simultaneously, which are of equal importanceThe feedback between the lower baroclinity and the upward and northward eddy heat transport dominates the basin‐scale oceanic forcing effectFrontal‐ and eddy‐scale SST anomalies in the subtropical front zone cause comparable anomalous jet as the basin‐scale by changing the upward E‐P flux directly [ABSTRACT FROM AUTHOR]

Assessing space weather modeling capability is a key element in improving existing models and developing new ones. In order to track improvement of the models and investigate impacts of forcing, from the lower atmosphere below and from the magnetosphere above, on the performance of ionosphere‐thermosphere models, we expand our previous assessment for 2013 March storm event (Shim et al., 2018, https://doi.org/10.1029/2018SW002034). In this study, we evaluate new simulations from upgraded models (the Coupled Thermosphere Ionosphere Plasmasphere Electrodynamics (CTIPe) model version 4.1 and the Global Ionosphere Thermosphere Model (GITM) version 21.11) and from the NCAR Whole Atmosphere Community Climate Model with thermosphere and ionosphere extension (WACCM‐X) version 2.2 including eight simulations in the previous study. A simulation from the NCAR Thermosphere‐Ionosphere‐Electrodynamics General Circulation Model version 2 (TIE‐GCM 2.0) is also included for comparison with WACCM‐X. TEC and foF2 changes from quiet‐time background are considered to evaluate the model performance on the storm impacts. For evaluation, we employ four skill scores: Correlation coefficient (CC), root‐mean square error (RMSE), ratio of the modeled to observed maximum percentage changes (Yield), and timing error (TE). It is found that the models tend to underestimate the storm‐time enhancements of foF2 (F2‐layer critical frequency) and TEC (Total Electron Content) and to predict foF2 and/or TEC better in North America but worse in the Southern Hemisphere. The ensemble simulation for TEC is comparable to results from a data assimilation model (Utah State University‐Global Assimilation of Ionospheric Measurements (USU‐GAIM)) with differences in skill score less than 3% and 6% for CC and RMSE, respectively. Plain Language Summary: The Earth's ionosphere‐thermosphere (IT) system, which is present between the lower atmosphere and the magnetosphere, is highly variable due to external forcings from below and above as well as internal forcings mainly associated with ion‐neutral coupling processes. The variabilities of the IT system can adversely affect our daily lives, therefore, there is a need for both accurate and reliable weather forecasts to mitigate harmful effects of space weather events. In order to track the improvement of predictive capabilities of space weather models for the IT system, and to investigate the impacts of the forcings on the performance of IT models, we evaluate new simulations from upgraded models (Coupled Thermosphere Ionosphere Plasmasphere Electrodynamics model version 4.1 and Global Ionosphere Thermosphere Model version 21.11) and from NCAR Whole Atmosphere Community Climate Model with thermosphere and ionosphere extension (WACCM‐X) version 2.2 together with 8 simulations in the previous study. A simulation of NCAR Thermosphere‐Ionosphere‐Electrodynamics General Circulation Model version 2 is also included for the comparison with WACCM‐X. Quantitative evaluation is performed by using four skill scores including Correlation coefficient, root‐mean square error, ratio of the modeled to observed maximum percentage changes (Yield), and timing error. The findings of this study will provide a baseline for future validation studies of new and improved models. Key Points: F2‐layer critical frequency/Total Electron Content (foF2/TEC) and their changes during a storm predicted by ionosphere‐thermosphere coupled models are evaluated against Global Ionosphere Radio Observatory foF2 and GPS TEC measurementsModel simulations tend to underestimate the storm‐time enhancements of foF2 and TEC and to predict them better in the northern hemisphereEnsemble of all simulations for TEC is comparable to the data assimilation model (USU‐GAIM) [ABSTRACT FROM AUTHOR]

Research in the last decades revealed that rapidly ascending airstreams in extratropical cyclones – so-called warm conveyor belts (WCBs) – play an important role in extratropical atmospheric dynamics. However on the subseasonal time scale, the modulation of their occurrence frequency, henceforth referred to as WCB activity, has so far received little attention. Also, it is not yet clear whether WCB activity may affect tropospheric teleconnection patterns, which constitute a source of predictability on this subseasonal time scale. Using reanalysis data, this study analyzes the modulation of WCB activity by the Madden-Julian Oscillation (MJO). A key-finding is that WCB activity increases significantly over the western North Pacific when the convection of the MJO is located over the Indian Ocean. This increased WCB activity, which is particularly pronounced during La Niña conditions, is related to enhanced poleward moisture fluxes driven by the circulation of subtropical Rossby gyres associated with the MJO. In contrast, when the convection of the MJO is located over the western North Pacific, WCB activity increases significantly over the eastern North Pacific. This increase stems from a southward shift and eastward extension of the North Pacific jet stream. However, while these mean increases are significant, individual MJO events exhibit substantial variability, with some events even exhibiting anomalously low WCB activity. Individual events of the same MJO phase with anomalously low WCB activity over the North Pacific tend to be followed by the known canonical teleconnection patterns in the Atlantic-European region, i.e., the occurrence frequency of the positive phase of the North Atlantic Oscillation (NAO) is enhanced when convection of the MJO is located over the Indian Ocean, and similarly for the negative phase of the NAO when MJO convection is over the western North Pacific. However, the canonical teleconnection patterns are modified when individual events of the same MJO phase are accompanied by anomalously high WCB activity over the North Pacific. In particular, the link between MJO and the negative phase of the NAO weakens considerably. Reanalysis data and experiments with an idealized general circulation model reveal that this is related to anomalous ridge building over western North America favoured by enhanced WCB activity. Overall, our study highlights the potential role of WCBs in shaping tropical-extratropical teleconnection patterns and underlines the importance of representing them adequately in numerical weather prediction models in order to fully exploit the sources of predictability emerging from the tropics. [ABSTRACT FROM AUTHOR]

Satellite-derived products and reanalyses show consistent increases in downward surface solar radiation (SSR) and decreases in cloud cover over North America and Europe from the 1980s to 2010s. These trends show a strong seasonality, with the largest changes in boreal summer. A set of timeslice experiments with an atmospheric general circulation model (AGCM) forced with prescribed changes in sea surface temperature/sea ice extent (SST/SIE), greenhouse gas (GHG) concentrations, and anthropogenic aerosol (AA) emissions, together and separately, is performed to assess the relative roles of different forcings in these observed trends. The model reproduces the main observed features over Europe and North America, including the seasonality of trends, suggesting a dominant role of forced changes in the recent trends in SSR and cloud cover. Responses to individual forcings indicate that recent decadal trends in SSR over Europe are predominantly driven by AA emission reductions, with an additional influence from SST/SIE and GHG changes. In contrast, changes in AA, SST/SIE, and GHG contribute more equally to simulated decadal trends in SSR and cloud cover over North America, although SST/SIE play the most important role. In our simulations, responses of SSR to AA emission reductions are primarily governed by aerosol-radiation interactions. Responses to SST/SIE and GHG changes are predominantly due to cloud cover changes, which are driven by atmospheric circulation and humidity changes. This process level understanding of how different forcing factors influence decadal trends in SSR and cloud cover is valuable for understanding past changes and future projections in global and regional surface energy budgets, surface warming, and global and regional hydrological cycles. [ABSTRACT FROM AUTHOR]

During the last glacial cycle (LGC), ice sheets covered large parts of Eurasia and North America, which resulted in ∼120 m of sea level change. Ice sheet–climate interactions have considerable influence on temperature and precipitation patterns and therefore need to be included when simulating this time period. Ideally, ice sheet–climate interactions are simulated by a high-resolution Earth system model. While these models are capable of simulating climates at a certain point in time, such as the pre-industrial (PI) or the Last Glacial Maximum (LGM; 21 000 years ago), a full transient glacial cycle is currently computationally unfeasible as it requires a too-large amount of computation time. Nevertheless, ice sheet models require forcing that captures the gradual change in climate over time to calculate the accumulation and melt of ice and its effect on ice sheet extent and volume changes. Here we simulate the LGC using an ice sheet model forced by LGM and PI climates. The gradual change in climate is modelled by transiently interpolating between pre-calculated results from a climate model for the LGM and the PI. To assess the influence of ice sheet–climate interactions, we use two different interpolation methods: the climate matrix method, which includes a temperature–albedo and precipitation–topography feedback, and the glacial index method, which does not. To investigate the sensitivity of the results to the prescribed climate forcing, we use the output of several models that are part of the Paleoclimate Modelling Intercomparison Project Phase III (PMIP3). In these simulations, ice volume is prescribed, and the climate is reconstructed with a general circulation model (GCM). Here we test those models by using their climate to drive an ice sheet model over the LGC. We find that the ice volume differences caused by the climate forcing exceed the differences caused by the interpolation method. Some GCMs produced unrealistic LGM volumes, and only four resulted in reasonable ice sheets, with LGM Northern Hemisphere sea level contribution ranging between 74–113 m with respect to the present day. The glacial index and climate matrix methods result in similar ice volumes at the LGM but yield a different ice evolution with different ice domes during the inception phase of the glacial cycle and different sea level rates during the deglaciation phase. The temperature–albedo feedback is the main cause of differences between the glacial index and climate matrix methods. [ABSTRACT FROM AUTHOR]

This study analyzes a simulation of the Arctic winter 2016–2017 with focus on multi‐step vertical coupling (MSVC) by primary, secondary, and higher‐order gravity waves (GWs). We employ the HIgh Altitude Mechanistic general Circulation Model with nudging of the large scales to MERRA‐2 reanalysis. Simulation results confirm the well‐known effects from primary GWs in the winter middle atmosphere regarding strong westward GW drag and a warm winter polar stratopause during the strong‐vortex period in late December 2016, as well as weak eastward GW drag and mesospheric cooling during the sudden stratospheric warming (SSW) in late January and early February 2017. Since the amplitudes of the primary GWs that dissipate in the middle atmosphere are weaker for a reversed or weakened polar vortex, the theory for secondary GW generation predicts reduced MSVC in this case. This is confirmed by strongly reduced secondary and higher‐order GW amplitudes during the SSW and the weak‐vortex period in February. The wintertime higher‐order GWs show partial concentric ring structures above their sources in the lower thermosphere. We find that mostly those higher‐order GWs propagate to higher altitudes that have horizontal propagation directions against the tidal winds. The simulated GWs at 300 km height and observed perturbations of total electron content over Europe and North America during selected days of low geomagnetic activity show very good agreement regarding (a) the wave characteristics and (b) the reduction of amplitudes during the SSW and early February as compared to late December. Plain Language Summary: We analyze the Arctic winter 2016–2017 using a whole atmosphere model with resolved gravity waves (GWs) and nudging of the large scales to MERRA‐2 reanalysis. Model results confirm the well‐known effects from primary GWs in the winter middle atmosphere regarding strong westward GW drag and a warm winter polar stratopause during the strong‐vortex period in late December 2016, as well as weak eastward GW drag and mesospheric cooling during the sudden stratospheric warming (SSW), which started in late January 2017 and was followed by a weak vortex in February. Since secondary and higher‐order GWs are the predominant GWs in the winter mesopause region and thermosphere, the vertical coupling from the lower to the upper atmosphere by GWs is termed multi‐step vertical coupling (MSVC). We find that MSVC is strongly reduced during and after the SSW. The simulated GWs at 300 km height and observed total electron content (TEC) perturbations over Europe and North America during days of low geomagnetic activity show very good agreement regarding the wave characteristics. Furthermore, we find a clear reduction in the TEC perturbation amplitudes during and after the SSW. This agreement between model and observations strongly suggests that quiet‐time TEC perturbations in the winter thermosphere are caused by GWs from MSVC. Key Points: Wintertime thermospheric gravity waves (GWs) simulated by a whole atmosphere model are strongly reduced during the January 2017 sudden stratospheric warming (SSW) and the subsequent weak‐vortex periodObserved quiet‐time total electron content (TEC) perturbations show reduced amplitudes during the SSW and weak‐vortex period as wellPropagation directions, wavelengths, and periods of the simulated thermospheric GWs agree with observed quiet‐time TEC perturbations [ABSTRACT FROM AUTHOR]

The consecutive occurrence of meteorological dry and wet extremes has been receiving increasing attention due to potentially larger social and environmental impacts than single extremes. However, the changing characteristics of transitions between dry and wet periods remain poorly understood. Here we investigate the dynamic evolution of dry‐to‐wet transitions in response to climate warming, using the Standardized Precipitation Evapotranspiration Index as well as observations and general circulation models for the periods of 1954–2014 and 2040–2100. We find that approximately three‐fifths of global land area are projected to experience an accelerated dry‐to‐wet transition. Southern Asia has been experiencing the most severe dry‐to‐wet transitions and is projected to suffer more frequent, more intense, and accelerated dry‐to‐wet transitions. The increasing potential evapotranspiration (PET) variability plays an important role in accelerating the dry‐to‐wet transition in Southern Asia, while precipitation and PET variabilities contribute to the intensification of dry‐to‐wet transitions in Southern North America. Plain Language Summary: The consecutive occurrence of droughts and floods has widespread impacts on agriculture, the ecosystem, and the environment. Here we examine the changes in frequency, intensity, and elapsed time of transitions between dry and wet periods under a warming climate, based on observations and an ensemble of 10 Coupled Model Intercomparison Project Phase 6 climate simulations. We find that approximately 59% of global land area are expected to experience a shorter transition time between dry and wet periods. Southern Asia suffers the most severe dry‐to‐wet transition. Furthermore, our findings reveal that enhanced potential evapotranspiration (PET) variability contributes to the accelerated transition between dry and wet periods over Southern Asia, and the acceleration of dry‐to‐wet transitions in Southern North America is associated with an increase in precipitation and PET variabilities as climate warms. Key Points: Approximately three‐fifths (59%) of global land area are projected to experience accelerated transition between dry and wet periodsSouthern Asia suffers the most from severe transition between dry and wet periodsEnhanced precipitation and potential evapotranspiration variabilities contribute to the accelerated dry‐to‐wet transitions [ABSTRACT FROM AUTHOR]

Atmospheric gravity waves (GWs) during the February 2018 sudden stratospheric warming (SSW) event are simulated using the T639L340 whole neutral atmosphere general circulation model. Their characteristic morphology around the drastically evolving polar vortex is revealed by three‐dimensional (3D) visualization and ray‐tracing analyses. The 3D morphology of simulated GWs is described for the three key days that represent the pre‐SSW conditions, the mature stage for the vortex splitting, and the late SSW. The combination of strong winds along the polar vortex edge and underneath the tropospheric winds with similar wind directions consist of the deep waveguide for the upward‐propagating GWs, forming GW hot spots in the middle atmosphere. The GW hot spots associated with the development of the SSW are limited to North America and Greenland, and they include the typical upward‐propagating orographic GWs with relatively long vertical wavelengths. Different types of characteristic GW signatures are also recognized around the Canadian sub‐vortex (CV). GWs having short vertical wavelengths form near the surface and obliquely propagate over long distances along the CV winds. The non‐orographic GWs with short vertical wavelengths form in the middle stratosphere through the spontaneous adjustment of flow imbalance around the CV. Those GWs cyclonically ascend into the mesosphere along CV winds. Plain Language Summary: Atmospheric gravity waves (GWs) have three‐dimensional (3D) phase structures and propagate three‐dimensionally from their sources. Examples include flow over mountains, convection, fronts, and dynamically imbalanced flow systems. For the first time, we simulated and visualized their 3D global morphology from the surface to an altitude of ∼100 km by focusing on the February 2018 sudden stratospheric warming event, when the stratospheric polar vortex split into two sub‐vortices. The most interesting findings in the 3D and ray‐tracing analyses are the formation of narrow GW hotspots along the south to east rim of the Canadian sub‐vortex (CV) and the cyclonical ascent of GWs around the edge of the CV. Key Points: Gravity waves during the 2018 sudden stratospheric warming were simulated using a whole neutral atmosphere general circulation modelThree‐dimensional visualization analyses revealed their characteristic morphology around the dramatically evolving polar vortexPaths of gravity waves near the Canadian sub‐vortex were estimated by ray tracing, highlighting long‐distance gravity wave propagation [ABSTRACT FROM AUTHOR]

Seasonal forecasts of summer continental United States (CONUS) rainfall have relatively low skill, partly due to a lack of consensus about its sources of predictability. The East Asian monsoon (EAM) can excite a cross-Pacific Rossby wave train, also known as the Asia–North America (ANA) teleconnection. In this study, we analyze the ANA teleconnection in observations and model simulations from the Community Atmospheric Model, version 5 (CAM5), comparing experiments with prescribed climatological SSTs and prescribed observed SSTs. Observations indicate a statistically significant relationship between a strong EAM and increased probability of positive precipitation anomalies over the US west coast and the Plains-Midwest. The ANA teleconnection and CONUS rainfall patterns are improved in the CAM5 experiment with prescribed observed SSTs, suggesting that SST variability is necessary to simulate this teleconnection over CONUS. We find distinct ANA patterns between ENSO phases, with the La Niña-related patterns in CAM5 disagreeing with observations. Using linear steady-state quasi-geostrophic theory, we conclude that incorrect EAM forcing location greatly contributed to CAM5 biases, and jet stream disparities explained the ENSO-related biases. Finally, we compared EAM forcing experiments with different mean states using a simple dry nonlinear atmospheric general circulation model. Overall, the ANA pattern over CONUS and its modulation by ENSO forcing are well described by dry dynamics on seasonal-to-interannual timescales, including the constructive (destructive) interference between El Niño (La Niña) modulation and the ANA patterns over CONUS. [ABSTRACT FROM AUTHOR]

Even though winter land–sea thermal contrast (LSC) is expected to undergo a strong weakening in the future warmer climate, its effects have been poorly investigated. Here we run a set of idealized winter simulations featuring reduced LSC in the Northern Hemisphere (NH) extratropics, or in individual extratropical sectors of the NH (Atlantic and Pacific), using an intermediate-complexity atmospheric general circulation model. Reduced LSC is obtained by imposing a warming of surface land temperatures in East Asia and North America. For similar warming intensities over the two regions, the response of the model to East Asia forcing is significantly stronger and dominates the response to the sum of the two forcing patterns. We find that the LSC reduction causes a weakening and poleward shift of the midlatitude jet streams, and a strong interference with zonal wavenumbers 1 and 2. In particular, East Asian warming reduces the amplitude of waves 1 and 2, producing a strengthening of the stratospheric vortex, while a weaker vortex due to a moderate amplification of wave 1 is detected when warming North America. Eventually, stratospheric signals propagate downward in the troposphere affecting the midlatitude winter NH even remotely from the forcing. In this work we pinpoint some mechanisms by which weakened winter LSC influences the NH extratropical circulation: the results may become useful to interpret the response to long-term projections displaying reduced LSC along with other climate change forcing patterns. [ABSTRACT FROM AUTHOR]

The frequency of atmospheric blocking has been largely underestimated by general circulation models (GCMs) participating in the Coupled Model Intercomparison Project (CMIP). Errors in the onset, persistence, barotropicity, geographical preference, seasonality, intensity, and moving speed of global blocking were diagnosed in 10 Geophysical Fluid Dynamics Laboratory (GFDL) GCMs for recent CMIP5 and CMIP6 using a detection approach that combines zonal eddies and the reversal of zonal winds. The blocking frequency, similar at 500 and 250 hPa, is underestimated by 50% in the Atlantic–Europe region during December–February but is overestimated by 60% in the Pacific–North America region during that season and by 70% in the southwest Pacific during July–August. These blocking biases at 500 hPa were investigated in the five CMIP6 models that showed improvements over the CMIP5 versions. The Atlantic–Europe underestimate corresponds to lower instantaneous blocking rates, lower persistent blocking rates, and higher persistent stationary ridge rates; the number of blocks with a duration of 4–5 days is only 40%–65% of that in observations. In contrast, the overestimate consists of excessive blocks with a duration longer than 12 days in the Pacific–North America and up to twice as many 4–6-day events in the southwest Pacific. Simulated December–February blocks up to 12 days in the Pacific–North America region tend to be stronger and to move more slowly than those in observations. Diagnostic sensitivity tests indicated that the zonal mean and zonal eddy components of the mean state play a key role, as replacing each with that of observations substantially reduced many of the outstanding biases in these GCMs. [ABSTRACT FROM AUTHOR]

Future changes in boreal winter MJO teleconnections over the Pacific–North America (PNA) region are examined in 15 Coupled Model Intercomparison Project phase 6 models (CMIP6s) under SSP585 (i.e., Shared Socioeconomic Pathway 5 following approximately the representative concentration pathway RCP8.5) scenarios. The most robust and significant change is an eastward extension (∼4° eastward for the multimodel mean) of MJO teleconnections in the North Pacific. Other projected changes in MJO teleconnections include a northward extension, more consistent patterns between different MJO events, stronger amplitude, and shorter persistence; however, these changes are more uncertain and less significant with a large intra- and intermodel spread. Mechanisms of the eastward teleconnection extension are investigated by comparing impacts of the future MJO and basic state changes on the anomalous Rossby wave source (RWS) and teleconnection pathways with a linear baroclinic model (LBM). The eastward extended jet in the future plays a more important role than the eastward-extended MJO in influencing the east–west position of MJO teleconnections. It leads to more eastward teleconnection propagation along the jet due to the eastward extension of turning latitudes before they propagate into North America. MJO teleconnections thus are positioned 2.9° more eastward in the North Pacific in the LBM. The eastward extended MJO, on the other hand, helps to generate a more eastward-extended RWS. However, negligible change is found in the east–west position of MJO teleconnections (only 0.3° more eastward in the LBM) excited from this RWS without the jet impacts. The above results suggest the dominant role of the jet change in influencing future MJO teleconnection position by altering their propagation pathways. [ABSTRACT FROM AUTHOR]

Recent high-spatial-resolution regional simulations from the global program, coordinated regional climate downscaling experiment-coordinated output for regional evaluations (CORDEX-CORE), are examined to evaluate the capability of regional climate models (RCMs) to represent the El Niño–Southern Oscillation (ENSO) precipitation and surface air temperature teleconnections over five regions of the world. We find that the ensemble and individual RCM simulations generally preserve the broad regional scale ENSO signal from the general circulation models (GCMs) over different regions around of the world, reproducing the majority of the observed regional responses to ENSO forcing. Furthermore, in some cases, the RCM ensemble and individual models can improve the spatial pattern of teleconnections and the amplitudes of these patterns compared to the driving global models. Among such cases are the precipitation teleconnections over southern Africa, North America and the Arabian–Asian region. Our study presents the first analysis of ENSO teleconnections in GCM-driven RCMs over multiple regions, and it clearly shows the potential value of using such models non only in a climate change research context, but also in seasonal to annual prediction. [ABSTRACT FROM AUTHOR]

Using a high-resolution atmospheric general circulation model simulation of unprecedented ensemble size, we examine potential predictability of monthly anomalies under El Niño–Southern Oscillation (ENSO) forcing and background internal variability. This study reveals the pronounced month-to-month evolution of both the ENSO forcing signal and internal variability. Internal variance in upper-level geopotential height decreases (~10%) over the North Pacific during El Niño as the westerly jet extends eastward, allowing forced signals to account for a greater fraction of the total variability, and leading to increased potential predictability. We identify February and March of El Niño years as the most predictable months using a signal-to-noise analysis. In contrast, December, a month typically included in teleconnection studies, shows little to no potential predictability. We show that the seasonal evolution of SST forcing and variability leads to significant signal-to-noise relationships that can be directly linked to both upper-level and surface variable predictability for a given month. The stark changes in forced response, internal variability, and thus signal-to-noise across an ENSO season indicate that subseasonal fields should be used to diagnose potential predictability over North America associated with ENSO teleconnections. Using surface air temperature and precipitation as examples, this study provides motivation to pursue "windows of forecast opportunity" in which statistical skill can be developed, tested, and leveraged to determine times and regions in which this skill may be elevated. [ABSTRACT FROM AUTHOR]

In this study, the interdecadal variability of the relationship between ENSO and winter synoptic temperature variability (STV) over the Asian–Pacific–American region is investigated based on observational data from 1951 to 2018. An interdecadal shift in the ENSO–STV relationship occurred in the 1980s over Eastern China, changing from significant in period 1 (P1; 1951–87) to insignificant in period 2 (P2; 1988–2018). But the ENSO–STV relationship is significantly stable over North America for the whole period. In addition, a possible reason for this interdecadal shift in the ENSO–STV relationship over Eastern China is also investigated. During P1, the ENSO pattern is significantly correlated to the temperature gradient over Northeast Asia, which is the key region influencing the intensification of extratropical eddies. The intensification of extratropical eddies over Northeast Asia is directly associated with the magnitude of STV over Eastern China. But in P2, the ENSO pattern is not related to the temperature over Northeast Asia. Therefore, the change in the ENSO pattern from P1 to P2 contributes to the interdecadal shift in the ENSO–STV relationship in the 1980s over Eastern China by influencing the temperature gradient over Northeast Asia, while ENSO can influence the temperature gradient over North America for the whole period. Furthermore, the possible role of the ENSO patterns in P1 and P2 is also examined by using an atmospheric general circulation model, highlighting that the pattern of SST variation is a determining factor in regulating STV in different regions. [ABSTRACT FROM AUTHOR]

During the summer when an El Niño event is transitioning to a La Niña event, the extratropical teleconnections exert robust warming anomalies over the U.S. Midwest threatening agricultural production. This study assesses the performance of current climate models in capturing the prominent observed extratropical responses over North America during the transitioning La Niña summer, based on atmospheric general circulation model experiments and coupled models from the North American Multimodel Ensemble (NMME). The ensemble mean of the SST-forced experiments across the transitioning La Niña summers does not capture the robust warming in the Midwest. The SST-forced experiments do not produce consistent subtropical western Pacific (WP) negative precipitation anomalies and this leads to the poor simulations of extratropical teleconnections over North America. In the NMME models, with active air–sea interaction, the negative WP precipitation anomalies show better agreement across the models and with observations. However, the downstream wave train pattern and the resulting extratropical responses over North America exhibit large disagreement across the models and are consistently weaker than in observations. Furthermore, in these climate models, an anomalous anticyclone does not robustly translate into a warm anomaly over the Midwest, in disagreement with observations. This work suggests that, during the El Niño to La Niña transitioning summer, active air–sea interaction is important in simulating tropical precipitation over the WP. Nevertheless, skillful representations of the Rossby wave propagation and land–atmosphere processes in climate models are also essential for skillful simulations of extratropical responses over North America. [ABSTRACT FROM AUTHOR]

The effects of changing climate and disturbance on mountain forest carbon (C) stocks vary with tree species distributions and over elevational gradients. Warming can not only increase C uptake by stimulating productivity at high elevations but also enhance C release by increasing respiration and the frequency, intensity and size of wildfires.To understand the consequences of climate change for temperate mountain forests, we simulated interactions among climate, wildfire, tree species and their combined effects on regional C stocks in forests of the Greater Yellowstone Ecosystem, USA (GYE) with the LANDIS‐II landscape change model. Simulations used historical climate and future potential climate represented by downscaled projections from five general circulation models (GCMs) that bracket the range of variability under the representative concentration pathway (RCP) 8.5 emissions scenario.Total ecosystem C increased by 67% through 2100 in simulations with historical climate, and by 38%–69% with GCM climate. Differences in C uptake among GCMs resulted primarily from variation in area burned, not productivity. Warming increased productivity by extending the growing season, especially near upper tree line, but did not offset biomass losses to fire. By 2100, simulated area burned increased by 27%–215% under GCM climate, with the largest increases after 2050. With warming >3°C in mean annual temperature, the increased frequency of large fires reduced live C stocks by 4%–36% relative to the control, historical climate scenario. However, relative losses in total C were delayed under GCMs with large increases in summer precipitation and buffered by C retained in soils and the wood of fire‐killed trees. Increasing fire size limited seed dispersal, and reductions in soil moisture limited seedling establishment; both effects will likely constrain long‐term forest regeneration and C uptake.Synthesis. Forests in the GYE can maintain a C sink through the mid‐century in a warming climate but continued warming may cause the loss of forest area, live above‐ground biomass and, ultimately, ecosystem C. Future changes in C stocks in similar forests throughout western North America will depend on regional thresholds for extensive wildfire and forest regeneration and therefore, changes may occur earlier in drier regions. [ABSTRACT FROM AUTHOR]

Summertime temperatures in marginal seas are, in general, colder than on the surrounding continent because of the large contrast in heat capacity between the land and the ocean. The Okhotsk Sea, which is covered by sea ice until early summer, is much colder than the surrounding continent in summer. The Okhotsk Sea is thus located in an area with one of the largest temperature contrasts of all the marginal seas in summertime midlatitudes. Cooled air over the Okhotsk Sea may have an impact on remote summer climates, such as by serving as the source of cold-air advection that results in a poor crop harvest in Japan. Here, we examine the role of the Okhotsk Sea on the early summer climate of the western part of the North Pacific through an ideal numerical experiment by artificially changing the model's default oceanic condition in the Okhotsk Sea to a condition of land cover. Simulation results reveal that the presence of the Okhotsk Sea increases precipitation of the baiu/mei-yu front through strengthening of the northward moisture flux at the western edge of an intensified North Pacific subtropical high. The Okhotsk influence farther extends toward western North America to which the strengthened jet stream with a storm track extends. This remote influence is achievable through feedback from a transient eddy anomaly that is activated by the surface temperature gradient between the cold Okhotsk Sea and the warm Pacific Ocean. The findings imply that the existence of the Okhotsk Sea strengthens the East Asian summer monsoons. [ABSTRACT FROM AUTHOR]

The extent to which decadal-to-multidecadal climate trends forced by carbon dioxide ( CO 2 ) and anthropogenic aerosol (AER) emissions depend on the phase and amplitude of internal modes of climate variability, such as Atlantic Multidecadal Variability (AMV), is an open question. This study uses a fully coupled CMIP5-era general circulation model (GCM) to investigate climate trends forced by increasing CO 2 and AER in the presence of opposite decaying phases of the AMV. Ensembles of simulations are initialized from extreme warm ( AMV (+) ) and cold ( AMV (-) ) phases of AMV and, while the global mean temperature trends are similar, significant regional differences are found over the Arctic and northern extratropics. Specifically, the response to CO 2 forcing is hemispherically asymmetric, with western Eurasia warming 20–30% more, and North America and the extratropical North Pacific warming 20–30% less, in AMV (+) than in AMV (-) . This asymmetry is explained by the atmospheric response to differences in the initial concentration of sea ice in the Atlantic Arctic sector, and by a large-scale atmospheric teleconnection pattern originating in the tropical Indo-Pacific. A decomposition of the temperature trends reveals that the AMV influence occurs mostly through atmospheric dynamics; however, thermodynamic processes are important in regions of sea ice change, western Eurasia, and eastern North America. The difference in the responses to CO 2 and AER forcing between AMV phases reveals that some aspects of the AMV modulation of the response, such as a more positive (negative) temperature trend in AMV (+) than in AMV (-) in western Eurasia (the extratropical North Pacific), are largely independent of the sign, magnitude and spatial pattern of external forcing. [ABSTRACT FROM AUTHOR]

El Niño–Southern Oscillation (ENSO) is a main driver of climate variability worldwide, but the presence of atmospheric internal variability makes accurate assessments of its atmospheric teleconnections a challenge. Here, we use a multimodel large ensemble of simulations to investigate the ENSO teleconnection response to a low global warming scenario that represents Paris Agreement targets. The ensemble comprises five atmospheric general circulation models with two experiments (present-day and +2°C) in which the same set of ENSO events is prescribed, which allows for quantification of the uncertainty in the ENSO response due to internal variability. In winter, the teleconnection during the positive ENSO phase features a strong negative anomaly in sea level pressure over the northeast Pacific (and vice versa for the negative phase); this anomaly shifts northeastward and strengthens in the warming experiment ensemble. At least 50–75 ENSO events are required to detect a significant shift or strengthening, emphasizing the need to adequately sample the internal variability to isolate the forced response of the ENSO teleconnection under a low warming scenario. Even more events may be needed if one includes other sources of uncertainty not considered in our experimental setup, such as changes in ENSO itself. Over North America, precipitation changes are generally more robust than temperature changes for the regions considered, despite large internal variability, and are shaped primarily by changes in atmospheric circulation. These results suggest that the observational period is likely too short for assessing changes in the ENSO teleconnection under Paris Agreement warming targets. [ABSTRACT FROM AUTHOR]

The relative influence of El Niño Southern Oscillation (ENSO) forced response versus internally generated atmospheric variability or noise on the upper tropospheric Pacific North American circulation is investigated. The analysis is performed on the boreal winter (December–January–February) 200 hPa circulation and the associated precipitation based on observational records and modeling experiments. The model experiment includes an ocean eddy-resolving coupled general circulation model (CGCM) and an atmospheric noise reduced ocean eddy-resolving CGCM. The noise reduction technique is the interactive ensemble approach, adopted to reduce the effects of internal atmospheric dynamics noise at the air-sea interface. Tropical rainfall anomalies associated with ENSO forces a teleconnection pattern that is a combination of the so-called Pacific North American (PNA) pattern, themed here as state-dependent atmospheric noise, and a pattern distinct from the PNA, themed here as ENSO-signal. The ENSO signal has a meridional structure in the streamfunction associated with significant poleward Rossby wave flux emanating from the eastern Pacific. Conversely, the PNA teleconnection pattern is zonally oriented, with most of the wave flux in the zonal direction from the Pacific towards North America. The mid-latitude ENSO forced response is asymmetric between warm and cold events. This asymmetry is strongly dependent on the amplitude of atmospheric noise. It is shown that the ENSO forced response is masked by atmospheric noise, with the latter being 3–10 times larger in amplitude. We show that the PNA pattern was positive during the 2015–2016 boreal winter and prevented the large 2015–2016 El Niño event from alleviating the persistent drought in the western US. [ABSTRACT FROM AUTHOR]

Current generation general circulation models (GCMs) simulate synoptic-scale climate state variables such as geopotential heights, specific humidity, and integrated vapor transport (IVT) more reliably than mesoscale precipitation. Statistical downscaling methods that condition precipitation on GCM-based, synoptic-scale climate features have shown promise in the reproduction of local precipitation. However, current approaches to climate-state-informed downscaling impose some limitations on the skill of precipitation reproduction, including hard clustering of climate modes into a discrete set of states, utilization of numerical clustering methodologies poorly suited to nonnormal data, and a tendency to focus on relationships to a limited set of large-scale climate modes. This study presents a methodology based on emerging machine learning techniques to develop global approximators of regional precipitation and discharge extremes given a suite of synoptic-scale climate state variables. Archetypal analysis is first used to define regional modes of winter and summer extreme precipitation and discharge across the eastern contiguous United States. A 2D convolution neural network (NN) is then used to predict the co-occurrence of the archetypes using 300- and 700-hPa geopotential heights, 300- and 700-hPa specific humidity, and IVT. Results suggest that 300-hPa geopotential height, 700-hPa specific humidity, and IVT yield the most reliable predictions, although with some important differences by season and region. Finally, we demonstrate that the trained activations of NN convolutional layers can be used to infer the causal pathways between synoptic-scale climate features and regional extremes. [ABSTRACT FROM AUTHOR]

Estimates of climate sensitivity from general circulation model (GCM) simulations still present a large spread despite the continued improvements in climate modeling since the 1970s. This variability is partially caused by the dependence of several long-term feedback mechanisms on the reference climate state. Indeed, state-of-the-art GCMs present a large spread of control climate states probably due to the lack of a suitable reference for constraining the climatology of preindustrial simulations. We assemble a new gridded database of long-term ground surface temperatures (LoST database) obtained from geothermal data over North America, and we explore its use as a potential reference for the evaluation of GCM preindustrial simulations. We compare the LoST database with observations from the Climate Research Unit (CRU) database, as well as with five past millennium transient climate simulations and five preindustrial control simulations from the third phase of the Paleoclimate Modelling Intercomparison Project (PMIP3) and the fifth phase of the Coupled Model Intercomparison Project (CMIP5). The database is consistent with meteorological observations as well as with both types of preindustrial simulations, which suggests that LoST temperatures can be employed as a reference to narrow down the spread of surface temperature climatologies on GCM preindustrial control and past millennium simulations. [ABSTRACT FROM AUTHOR]

Large volumes of gridded climate data have become available in recent years including interpolated historical data from weather stations and future predictions from general circulation models. These datasets, however, are at various spatial resolutions that need to be converted to scales meaningful for applications such as climate change risk and impact assessments or sample-based ecological research. Extracting climate data for specific locations from large datasets is not a trivial task and typically requires advanced GIS and data management skills. In this study, we developed a software package, ClimateNA, that facilitates this task and provides a user-friendly interface suitable for resource managers and decision makers as well as scientists. The software locally downscales historical and future monthly climate data layers into scale-free point estimates of climate values for the entire North American continent. The software also calculates a large number of biologically relevant climate variables that are usually derived from daily weather data. ClimateNA covers 1) 104 years of historical data (1901–2014) in monthly, annual, decadal and 30-year time steps; 2) three paleoclimatic periods (Last Glacial Maximum, Mid Holocene and Last Millennium); 3) three future periods (2020s, 2050s and 2080s); and 4) annual time-series of model projections for 2011–2100. Multiple general circulation models (GCMs) were included for both paleo and future periods, and two representative concentration pathways (RCP4.5 and 8.5) were chosen for future climate data. [ABSTRACT FROM AUTHOR]

Background: Chagas disease kills approximately 45 thousand people annually and affects 10 million people in Latin America and the southern United States. The parasite that causes the disease, Trypanosoma cruzi, can be transmitted by insects of the family Reduviidae, subfamily Triatominae. Any study that attempts to evaluate risk for Chagas disease must focus on the ecology and biogeography of these vectors. Expected distributional shifts of vector species due to climate change are likely to alter spatial patterns of risk of Chagas disease, presumably through northward expansion of high risk areas in North America. Methodology/Principal Findings: We forecast the future (2050) distributions in North America of Triatoma gerstaeckeri and T. sanguisuga, two of the most common triatomine species and important vectors of Trypanosoma cruzi in the southern United States. Our aim was to analyze how climate change might affect the future shift of Chagas disease in North America using a maximum entropy algorithm to predict changes in suitable habitat based on vector occurrence points and predictive environmental variables. Projections based on three different general circulation models (CCCMA, CSIRO, and HADCM3) and two IPCC scenarios (A2 and B2) were analyzed. Twenty models were developed for each case and evaluated via cross-validation. The final model averages result from all twenty of these models. All models had AUC >0.90, which indicates that the models are robust. Our results predict a potential northern shift in the distribution of T. gerstaeckeri and a northern and southern distributional shift of T. sanguisuga from its current range due to climate change. Conclusions/Significance: The results of this study provide baseline information for monitoring the northward shift of potential risk from Chagas disease in the face of climate change. Author Summary: Chagas disease kills thousands of people annually. Triatomine insects (family Reduviidae, sub-family Triatominae), can be potential vectors of the parasite (Trypanosoma cruzi) that causes the disease. There are often no symptoms until cardiac and digestive system dysfunction (possibly including heart failure) after 10 to 30 years of infection. Climate change can shift the distribution of triatomine insects, favoring the spread of the disease to non-original areas. We used distributional information on the most commonly found triatomine species and the most important vectors of Trypanosoma cruzi in South Texas and North Mexico (T. gerstaeckeri and T. sanguisuga), and explanatory climatic variables to forecast the potential distribution of the insects in the year 2050. We used two different scenarios of climate change and three different general circulation models. Our results showed that the triatomine species studied will likely shift their distribution northwards in the future. There is thus a need to monitor areas that are not currently endemic for Chagas disease but may potentially be affected in the future due to climate change. [ABSTRACT FROM AUTHOR]

Producing reliable estimates of changes in precipitation at local and regional scales remains an important challenge in climate science. Statistical downscaling methods are often utilized to bridge the gap between the coarse resolution of general circulation models (GCMs) and the higher resolutions at which information is required by end users. As the skill of GCM precipitation, particularly in simulating temporal variability, is not fully understood, statistical downscaling typically adopts a perfect prognosis (PP) approach in which high-resolution precipitation projections are based on real-world statistical relationships between large-scale atmospheric predictors and local-scale precipitation. Using a nudged simulation of the ECHAM5 GCM, in which the large-scale weather states are forced toward observations of large-scale circulation and temperature for the period 1958-2001, previous work has shown ECHAM5 skill in simulating temporal variability of precipitation to be high in many parts of the world. Here, the same nudged simulation is used in an alternative downscaling approach, based on model output statistics (MOS), in which statistical corrections are derived for simulated precipitation. Cross-validated MOS corrections based on maximum covariance analysis (MCA) and principal component regression (PCR), in addition to a simple local scaling, are shown to perform strongly throughout much of the extratropics. Correlation between downscaled and observed monthly-mean precipitation is as high as 0.8-0.9 in many parts of Europe, North America, and Australia. For these regions, MOS clearly outperforms PP methods that use temperature and circulation as predictors. The strong performance of MOS makes such an approach to downscaling attractive and potentially applicable to climate change simulations. [ABSTRACT FROM AUTHOR]

In recent decades, the need of future climate information at local scales have pushed the climate modelling community to perform increasingly higher resolution simulations and to develop alternative approaches to obtain fine-scale climatic information. In this article, various nested regional climate model (RCM) simulations have been used to try to identify regions across North America where high-resolution downscaling generates fine-scale details in the climate projection derived using the 'delta method'. Two necessary conditions were identified for an RCM to produce added value (AV) over lower resolution atmosphere-ocean general circulation models in the fine-scale component of the climate change (CC) signal. First, the RCM-derived CC signal must contain some non-negligible fine-scale information-independently of the RCM ability to produce AV in the present climate. Second, the uncertainty related with the estimation of this fine-scale information should be relatively small compared with the information itself in order to suggest that RCMs are able to simulate robust fine-scale features in the CC signal. Clearly, considering necessary (but not sufficient) conditions means that we are studying the 'potential' of RCMs to add value instead of the AV, which preempts and avoids any discussion of the actual skill and hence the need for hindcast comparisons. The analysis concentrates on the CC signal obtained from the seasonal-averaged temperature and precipitation fields and shows that the fine-scale variability of the CC signal is generally small compared to its large-scale component, suggesting that little AV can be expected for the time-averaged fields. For the temperature variable, the largest potential for fine-scale added value appears in coastal regions mainly related with differential warming in land and oceanic surfaces. Fine-scale features can account for nearly 60 % of the total CC signal in some coastal regions although for most regions the fine scale contributions to the total CC signal are of around ∼5 %. For the precipitation variable, fine scales contribute to a change of generally less than 15 % of the seasonal-averaged precipitation in present climate with a continental North American average of ∼5 % in both summer and winter seasons. In the case of precipitation, uncertainty due to sampling issues may further dilute the information present in the downscaled fine scales. These results suggest that users of RCM simulations for climate change studies in a delta method framework have little high-resolution information to gain from RCMs at least if they limit themselves to the study of first-order statistical moments. Other possible benefits arising from the use of RCMs-such as in the large scale of the downscaled fields- were not explored in this research. [ABSTRACT FROM AUTHOR]

The characteristics of summertime heat waves in North America are examined using reanalysis data and simulations by two general circulation models with horizontal resolution of 50 and 200 km. Several 'key regions' with spatially coherent and high amplitude fluctuations in daily surface air temperature are identified. The typical synoptic features accompanying warm episodes in these regions are described. The averaged intensity, duration, and frequency of occurrence of the heat waves in various key regions, as simulated in the two models for twentieth-century climate, are in general agreement with the results based on reanalysis data. The impact of climate change on the heat wave characteristics in various key regions is assessed by contrasting model runs based on a scenario for the twenty-first century with those for the twentieth century. Both models indicate considerable increases in the duration and frequency of heat wave episodes, and in number of heat wave days per year, during the twenty-first century. The duration and frequency statistics of the heat waves in the mid-twenty-first century, as generated by the model with 50-km resolution, can be reproduced by adding the projected warming trend to the daily temperature data for the late twentieth century, and then recomputing these statistics. The detailed evolution of the averaged intensity, duration, and frequency of the heat waves through individual decades of the twentieth and twenty-first centuries, as simulated and projected by the model with 200-km resolution, indicates that the upward trend in these heat wave measures should become apparent in the early decades of the twenty-first century. [ABSTRACT FROM AUTHOR]

A framework for the construction of probabilistic projections of high-resolution monthly temperature over North America using available outputs of opportunity from ensembles of multiple general circulation models (GCMs) and multiple regional climate models (RCMs) is proposed. In this approach, a statistical relationship is first established between RCM output and that from the respective driving GCM and then this relationship is applied to downscale outputs from a larger number of GCM simulations. Those statistically downscaled projections were used to estimate empirical quantiles at high resolution. Uncertainty in the projected temperature was partitioned into four sources including differences in GCMs, internal variability simulated by GCMs, differences in RCMs, and statistical downscaling including internal variability at finer spatial scale. Large spatial variability in projected future temperature changes is found, with increasingly larger changes toward the north in winter temperature and larger changes in the central United States in summer temperature. Under a given emission scenario, downscaling from large scale to small scale is the most important source of uncertainty, though structural errors in GCMs become equally important by the end of the twenty-first century. Different emission scenarios yield different projections of temperature change. This difference increases with time. The difference between the IPCC's Special Report on Emissions Scenarios (SRES) A2 and B1 in the median values of projected changes in 30-yr mean temperature is small for the coming 30 yr, but can become almost as large as the total variance due to internal variability and modeling errors in both GCM and RCM later in the twenty-first century. [ABSTRACT FROM AUTHOR]

The early twentieth-century North American pluvial (1905-17) was one of the most extreme wet periods of the last 500 yr and directly led to overly generous water allotments in the water-limited American west. Here, the causes and dynamics of the pluvial event are examined using a combination of observation-based datasets and general circulation model (GCM) experiments. The character of the moisture surpluses during the pluvial differed by region, alternately driven by increased precipitation (the Southwest), low evaporation from cool temperatures (the central plains), or a combination of the two (the Pacific Northwest). Cool temperature anomalies covered much of the West and persisted through most months, part of a globally extensive period of cooler land and sea surface temperatures (SST). Circulation during boreal winter favored increased moisture import and precipitation in the Southwest, while other regions and seasons were characterized by near-normal or reduced precipitation. Anomalies in the mean circulation, precipitation, and SST fields are partially consistent with the relatively weak El Niño forcing during the pluvial and, also, reflect the impacts of positive departures in the Arctic Oscillation that occurred in 10 of the 13 pluvial winters. Differences between the reanalysis dataset, an independent statistical drought model, and GCM simulations highlight some of the remaining uncertainties in understanding the full extent of SST forcing of North American hydroclimatic variability. [ABSTRACT FROM AUTHOR]

Global climate models are constantly being upgraded, but it is often not clear what these changes have on climate change impact projections. We used difference maps to directly compare downscaled projections of temperature and precipitation across North America for two versions (or generations) of three different Atmospheric-Ocean General Circulation Models (AOGCM)s. We found that AOGCM versions differed in their projections for the end of the current century by up to 4 °C for annual mean temperature and 60% for annual precipitation. To place these changes in an ecological context, we reanalyzed our work on shifts in tree climate envelopes (CEs) using the newer-generation AOGCM projections. Based on the updated AOGCMs, by the 2071-2100 period, tree CEs shifted up to 2.4 degrees further north or 2.6 degrees further south (depending on the AOGCM) and were about 10% larger in size. Despite considerable differences between versions of a given AOGCM, projections made by the newer version of each AOGCM were in general agreement, suggesting convergence across the three models studied here. Assessing the AOGCM outputs in this way provides insight into the magnitude and importance of change associated with AOGCM upgrades as they continue to evolve through time. [ABSTRACT FROM AUTHOR]

Wetlands are ecosystems of important functions in the earth's climate system. Through relatively high evapotranspiration, they affect surface water and energy exchange with the atmosphere directly influencing the physical climate. Through CH, CO and NO fluxes, they regulate the biogeochemical cycles, indirectly influencing the physical climate. However, current models do not explicitly include the water table, present under all large and stable wetlands; model wetlands are identified as flat land with wet soil resulting from precipitation events. That is, the wetlands are only 'wetted' from above but not from below by the high water table. Furthermore, without the knowledge of the water table position, estimates of CH and other gases (e.g., CO and NO) are poorly constrained. We present a simple hydrologic framework for simulating wetlands based on water table depth. A synthesis of hydrologic controls on wetlands highlights the key role that groundwater plays. It directly feeds wetlands, supports surface-water fed wetlands by maintaining a saturated substrate, and links land drainage to sea level by impeding drainage in lowlands. Forced by routine climate model output (precipitation-evapotranspiration-surface runoff), land topography, and sea level, we simulate the present-day water table in North America at the 1 km scale. We validate the simulation with water table observations and compare regions of shallow water table to mapped wetlands. Our results show that the framework captures the salient features of wetland distribution and extent at regional and continental scales, a direct result of large-scale groundwater convergence that nourishes the lowlands even in arid climates. The low requirement of forcing and computation make the framework easy to adopt in climate and earth system models for simulating wetland responses to climate and sea level change for the present, paleo reconstructions, and future projections. [ABSTRACT FROM AUTHOR]

In winter, northeastern North America and northeastern Asia are both colder than other regions at similar latitudes. This has been attributed to the effects of stationary weather systems set by elevated terrain (orography), and to a lack of maritime influences from the prevailing westerly winds. However, the differences in extent and orography between the two continents suggest that further mechanisms are involved. Here we show that this anomalous winter cold can result in part from westward radiation of large-scale atmospheric waves-nearly stationary Rossby waves-generated by heating of the atmosphere over warm ocean waters. We demonstrate this mechanism using simulations with an idealized general circulation model, with which we show that the extent of the cold region is controlled by properties of Rossby waves, such as their group velocity and its dependence on the planetary rotation rate. Our results show that warm ocean waters contribute to the contrast in mid-latitude winter temperatures between eastern and western continental boundaries not only by warming western boundaries, but also by cooling eastern boundaries. [ABSTRACT FROM AUTHOR]

The optimal anomalous sea surface temperature (SST) pattern for forcing North American drought is identified through atmospheric general circulation model integrations in which the response of the Palmer drought severity index (PDSI) is determined for each of 43 prescribed localized SST anomaly “patches” in a regular array over the tropical oceans. The robustness and relevance of the optimal pattern are established through the consistency of results obtained using two different models, and also by the good correspondence of the projection time series of historical tropical SST anomaly fields on the optimal pattern with the time series of the simulated PDSI in separate model integrations with prescribed time-varying observed global SST fields for 1920–2005. It is noteworthy that this optimal drought forcing pattern differs markedly in the Pacific Ocean from the dominant SST pattern associated with El Niño–Southern Oscillation (ENSO), and also shows a large sensitivity of North American drought to Indian and Atlantic Ocean SSTs. [ABSTRACT FROM AUTHOR]

Climate change may dramatically affect the distribution and abundance of organisms. With the world's population size expected to increase significantly during the next 100 years, we need to know how climate change might impact our food production systems. In particular, we need estimates of how future climate might alter the distribution of agricultural pests. We used the climate projections from two general circulation models (GCMs) of global climate, the Canadian Centre for Climate Modelling and Analysis GCM (CGCM2) and the Hadley Centre model (HadCM3), for the A2 and B2 scenarios from the Special Report on Emissions Scenarios in conjunction with a previously published bioclimatic envelope model (BEM) to predict the potential changes in distribution and abundance of the swede midge, Contarinia nasturtii, in North America. The BEM in conjunction with either GCM predicted that C. nasturtii would spread from its current initial invasion in southern Ontario and northwestern New York State into the Canadian prairies, northern Canada, and midwestern United States, but the magnitude of risk depended strongly on the GCM and the scenario used. When the CGCM2 projections were used, the BEM predicted an extensive shift in the location of the midges' climatic envelope through most of Ontario, Quebec, and the maritime and prairie provinces by the 2080s. In the United States, C. nasturtii was predicted to spread to all the Great Lake states, into midwestern states as far south as Colorado, and west into Washington State. When the HadCM3 was applied, southern Ontario, Saskatchewan, and Washington State were not as favourable for C. nasturtii by the 2080s. Indeed, when used with the HadCM3 climate projections, the BEM predicted the virtual disappearance of ‘very favourable’ regions for C. nasturtii. The CGCM2 projections generally caused the BEM to predict a small increase in the mean number of midge generations throughout the course of the century, whereas, the HadCM3 projections resulted in roughly the same mean number of generations but decreased variance. Predictions of the likely potential of C. nasturtii spatial spread are thus strongly dependent on the source of climate projections. This study illustrates the importance of using multiple GCMs in combination with multiple scenarios when studying the potential for spatial spread of an organism in response to climate change. [ABSTRACT FROM AUTHOR]

This study evaluates the fidelity of North American monsoon and associated intraseasonal variability in the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) coupled general circulation models (CGCMs). Twenty years of monthly precipitation data from each of the 22 models’ twentieth-century climate simulations, together with the available daily precipitation data from 12 of them, are analyzed and compared with Global Precipitation Climatology Project (GPCP) monthly and daily precipitation. The authors focus on the seasonal cycle and horizontal pattern of monsoon precipitation in conjunction with the two dominant convectively coupled equatorial wave modes: the eastward-propagating Madden–Julian oscillation (MJO) and the westward-propagating easterly waves. The results show that the IPCC AR4 CGCMs have significant problems and display a wide range of skill in simulating the North American monsoon and associated intraseasonal variability. Most of the models reproduce the monsoon rainbelt, extending from southeast to northwest, and its gradual northward shift in early summer, but overestimate the precipitation over the core monsoon region throughout the seasonal cycle and fail to reproduce the monsoon retreat in the fall. Additionally, most models simulate good westward propagation of the easterly waves, but relatively poor eastward propagation of the MJO and overly weak variances for both the easterly waves and the MJO. There is a tendency for models without undiluted updrafts in their deep convection scheme to produce better MJO propagation. [ABSTRACT FROM AUTHOR]

The downscaling ability of a one-way nested regional climate model (RCM) is evaluated over a region subjected to strong surface forcing: the west of North America. The sensitivity of the results to the horizontal resolution jump and updating frequency of the lateral boundary conditions are also evaluated. In order to accomplish this, a perfect-model approach nicknamed the Big-Brother Experiment (BBE) was followed. The experimental protocol consists of first establishing a virtual-reality reference climate over a fairly large area by using the Canadian RCM with grid spacing of 45 km nested within NCEP analyses. The resolution of the simulated climate is then degraded to resemble that of operational general circulation models (GCM) or observation analyses by removing small scales; the filtered fields are then used to drive the same regional model, but over a smaller sub-area. This set-up permits a comparison between two simulations of the same RCM over a common region. The Big-Brother Experiment has been carried out for four winter months over the west coast of North America. The results show that complex topography and coastline have a strong positive impact on the downscaling ability of the one-way nesting technique. These surface forcings, found to be responsible for a large part of small-scale climate features, act primarily locally and yield good climate reproducibility. Precipitation over the Rocky Mountains region is a field in which such effect is found and for which the nesting technique displays significant downscaling ability. The best downscaling ability is obtained when the ratio of spatial resolution between the nested model and the nesting fields is less than 12, and when the update frequency is more than twice a day. Decreasing the spatial resolution jump from a ratio of 12 to six has more benefits on the climate reproducibility than a reduction of spatial resolution jump from two to one. Also, it is found that an update frequency of four times a day leads to a better downscaling than twice a day when a ratio of spatial resolution of one is used. On the other hand, no improvement was found by using high-temporal resolution when the driving fields were degraded in terms of spatial resolution. [ABSTRACT FROM AUTHOR]

Understanding how bird populations respond to changes in waterbody availability in the climatically variable Prairie Pothole Region (PPR) of North America hinges on being able to couple hydrological and climate modeling to represent potential future landscapes. Model experiments run with the Pothole Complex Hydrologic Model using downscaled climate data (variables relating to precipitation, temperature, and potential evapotranspiration at 1/8° spatial resolution under four general circulation climate models and two gas emissions scenarios) were used to forecast the abundances of six focal wetland‐dependent bird species in the Missouri Coteau portion of the PPR, providing ensemble scenarios at a spatial scale relevant to resource management. Although the projected number of May ponds (waterbodies present during bird breeding season) fluctuated through time with some decadal periodicity (and with the number present in a given year reflecting abundance over the previous three years), the ensemble model average indicated an increase in the average number of waterbodies present by the turn of the next century. Overall, the model experiments conservatively projected an 11.75% increase in the number of waterbodies present by 2090–2099 compared to a baseline period from 1967 to 2005 in the PPR. Wetland‐dependent bird occurrence and abundance were significantly associated with temporal patterns and decadal periodicity in waterbody dynamics. Because of the strong associations between wetland‐dependent bird occurrence and abundance and the number of prairie potholes, projected waterbody increases are forecasted to result in an 11.97% overall increase in occurrence and 8.63% increase in abundance of the six focal species by the end of the 21st century; these results contrast with forecasted drought‐associated declines in waterbodies and birds in the PPR. This integrated hydrological–climatological approach offers a means of assessing how wetland‐dependent bird populations may respond to changes in wetland habitat availability due to a changing climate. Our results provide information that can help managers decide how to mitigate the effects of climate shifts on the distribution of wetland habitat and biota. [ABSTRACT FROM AUTHOR]