On North American Decadal Climate for 2011–20

2011 ◽  
Vol 24 (16) ◽  
pp. 4519-4528 ◽  
Author(s):  
Martin Hoerling ◽  
James Hurrell ◽  
Arun Kumar ◽  
Laurent Terray ◽  
Jon Eischeid ◽  
...  
Keyword(s):  
North American ◽  
Climate Models ◽  
Noise Analysis ◽  
Surface Air Temperature ◽  
Internal Variability ◽  
External Signal ◽  
Initial State ◽  
The North ◽  
Decadal Scale ◽  
North American Climate

Abstract The predictability of North American climate is diagnosed by taking into account both forced climate change and natural decadal-scale climate variability over the next decade. In particular, the “signal” in North American surface air temperature and precipitation over 2011–20 associated with the expected change in boundary conditions related to future anthropogenic greenhouse gas (GHG) forcing, as well as the “noise” around that signal due to internally generated ocean–atmosphere variability, is estimated. The structural uncertainty in the estimate of decadal predictability is diagnosed by examining the sensitivity to plausible scenarios for the GHG-induced change in boundary forcing, the model dependency of the forced signals, and the dependency on methods for estimating internal decadal noise. The signal-to-noise analysis by the authors is thus different from other published decadal prediction studies, in that this study does not follow a trajectory from a particular initial state but rather considers the statistics of internal variability in comparison with the GHG signal. The 2011–20 decadal signal is characterized by surface warming over the entire North American continent, precipitation decreases over the contiguous United States, and precipitation increases over Canada relative to 1971–2000 climatological conditions. The signs of these forced responses are robust across different sea surface temperature (SST) scenarios and the different models employed, though the amplitude of the response differs. The North American decadal noise is considerably smaller than the signal associated with boundary forcing, implying a potential for high forecast skill for 2011–20 North American climate even for prediction methods that do not attempt to initialize climate models. However, the results do suggest that initialized decadal predictions, which seek to forecast externally forced signals and also constrain the internal variability, could potentially improve upon uninitialized methods in regions where the external signal is small relative to internal variability.

scholarly journals On the Increased Frequency of Mediterranean Drought

2012 ◽  
Vol 25 (6) ◽  
pp. 2146-2161 ◽  
Author(s):  
Martin Hoerling ◽  
Jon Eischeid ◽  
Judith Perlwitz ◽  
Xiaowei Quan ◽  
Tao Zhang ◽  
...  
Keyword(s):  
Radiative Forcing ◽  
Climate Models ◽  
Eastern Mediterranean ◽  
Internal Variability ◽  
Global Ocean ◽  
External Signal ◽  
The North ◽  
Aerosol Forcing ◽  
Tropical Oceans ◽  
The North Atlantic Oscillation

Abstract The land area surrounding the Mediterranean Sea has experienced 10 of the 12 driest winters since 1902 in just the last 20 years. A change in wintertime Mediterranean precipitation toward drier conditions has likely occurred over 1902–2010 whose magnitude cannot be reconciled with internal variability alone. Anthropogenic greenhouse gas and aerosol forcing are key attributable factors for this increased drying, though the external signal explains only half of the drying magnitude. Furthermore, sea surface temperature (SST) forcing during 1902–2010 likely played an important role in the observed Mediterranean drying, and the externally forced drying signal likely also occurs through an SST change signal. The observed wintertime Mediterranean drying over the last century can be understood in a simple framework of the region’s sensitivity to a uniform global ocean warming and to modest changes in the ocean’s zonal and meridional SST gradients. Climate models subjected to a uniform +0.5°C warming of the world oceans induce eastern Mediterranean drying but fail to generate the observed widespread Mediterranean drying pattern. For a +0.5°C SST warming confined to tropical latitudes only, a dry signal spanning the entire Mediterranean region occurs. The simulated Mediterranean drying intensifies further when the Indian Ocean is warmed +0.5°C more than the remaining tropical oceans, an enhanced drying signal attributable to a distinctive atmospheric circulation response resembling the positive phase of the North Atlantic Oscillation. The extent to which these mechanisms and the region’s overall drying since 1902 reflect similar mechanisms operating in association with external radiative forcing are discussed.

IMPROVING THE NORTH AMERICAN MULTI-MODEL ENSEMBLE (NMME) PRECIPITATION FORECASTS AT SEASONAL SCALE OVER THE HIMALAYAN REGION USING MACHINE LEARNING

2021 ◽  
Author(s):  
SOURABH SHRIVASTAVA ◽  
RAM AVTAR ◽  
PRASANTA KUMAR BAL
Keyword(s):  
Machine Learning ◽  
North American ◽  
Climate Models ◽  
Global Climate ◽  
Horizontal Resolution ◽  
Summer Monsoon Rainfall ◽  
Global Climate Models ◽  
Himalayan Region ◽  
Model Ensemble ◽  
The North

The coarse horizontal resolution global climate models (GCMs) have limitations in producing large biases over the mountainous region. Also, single model output or simple multi-model ensemble (SMME) outputs are associated with large biases. While predicting the rainfall extreme events, this study attempts to use an alternative modeling approach by using five different machine learning (ML) algorithms to improve the skill of North American Multi-Model Ensemble (NMME) GCMs during Indian summer monsoon rainfall from 1982 to 2009 by reducing the model biases. Random forest (RF), AdaBoost (Ada), gradient (Grad) boosting, bagging (Bag) and extra (Extra) trees regression models are used and the results from each models are compared against the observations. In simple MME (SMME), a wet bias of 20[Formula: see text]mm/day and an RMSE up to 15[Formula: see text]mm/day are found over the Himalayan region. However, all the ML models can bring down the mean bias up to [Formula: see text][Formula: see text]mm/day and RMSE up to 2[Formula: see text]mm/day. The interannual variability in ML outputs is closer to observation than the SMME. Also, a high correlation from 0.5 to 0.8 is found between in all ML models and then in SMME. Moreover, representation of RF and Grad is found to be best out of all five ML models that represent a high correlation over the Himalayan region. In conclusion, by taking full advantage of different models, the proposed ML-based multi-model ensemble method is shown to be accurate and effective.

scholarly journals Influence of ENSO on North American subseasonal surface air temperature variability

2021 ◽  
Vol 2 (2) ◽  
pp. 395-412
Author(s):  
Patrick Martineau ◽  
Hisashi Nakamura ◽  
Yu Kosaka
Keyword(s):  
North America ◽  
Air Temperature ◽  
North American ◽  
Surface Air Temperature ◽  
Tropical Pacific ◽  
La Niña ◽  
Western North America ◽  
The North ◽  
Subseasonal Variability ◽  
La Nina

Abstract. The wintertime influence of tropical Pacific sea surface temperature (SST) variability on subseasonal variability is revisited by identifying the dominant mode of covariability between 10–60 d band-pass-filtered surface air temperature (SAT) variability over the North American continent and winter-mean SST over the tropical Pacific. We find that the El Niño–Southern Oscillation (ENSO) explains a dominant fraction of the year-to-year changes in subseasonal SAT variability that are covarying with SST and thus likely more predictable. In agreement with previous studies, we find a tendency for La Niña conditions to enhance the subseasonal SAT variability over western North America. This modulation of subseasonal variability is achieved through interactions between subseasonal eddies and La Niña-related changes in the winter-mean circulation. Specifically, eastward-propagating quasi-stationary eddies over the North Pacific are more efficient in extracting energy from the mean flow through the baroclinic conversion during La Niña. Structural changes of these eddies are crucial to enhance the efficiency of the energy conversion via amplified downgradient heat fluxes that energize subseasonal eddy thermal anomalies. The enhanced likelihood of cold extremes over western North America is associated with both an increased subseasonal SAT variability and the cold winter-mean response to La Niña.

scholarly journals Changes in Winter Atmospheric Rivers along the North American West Coast in CMIP5 Climate Models

2015 ◽  
Vol 16 (1) ◽  
pp. 118-128 ◽  
Author(s):  
Michael D. Warner ◽  
Clifford F. Mass ◽  
Eric P. Salathé
Keyword(s):  
Water Vapor ◽  
North American ◽  
West Coast ◽  
American West ◽  
Climate Models ◽  
Water Vapor Transport ◽  
The West ◽  
North American West ◽  
The North ◽  
Extreme Precipitation Events

Abstract Most extreme precipitation events that occur along the North American west coast are associated with winter atmospheric river (AR) events. Global climate models have sufficient resolution to simulate synoptic features associated with AR events, such as high values of vertically integrated water vapor transport (IVT) approaching the coast. From phase 5 of the Coupled Model Intercomparison Project (CMIP5), 10 simulations are used to identify changes in ARs impacting the west coast of North America between historical (1970–99) and end-of-century (2070–99) runs, using representative concentration pathway (RCP) 8.5. The most extreme ARs are identified in both time periods by the 99th percentile of IVT days along a north–south transect offshore of the coast. Integrated water vapor (IWV) and IVT are predicted to increase, while lower-tropospheric winds change little. Winter mean precipitation along the west coast increases by 11%–18% [from 4% to 6% (°C)−1], while precipitation on extreme IVT days increases by 15%–39% [from 5% to 19% (°C)−1]. The frequency of IVT days above the historical 99th percentile threshold increases as much as 290% by the end of this century.

scholarly journals Detecting sulphate aerosol geoengineering with different methods

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Y. T. Eunice Lo ◽  
Andrew J. Charlton-Perez ◽  
Fraser C. Lott ◽  
Eleanor J. Highwood
Keyword(s):  
Climate Models ◽  
Surface Air Temperature ◽  
High Sensitivity ◽  
Internal Variability ◽  
Detection Methods ◽  
Sulphate Aerosol ◽  
Near Surface ◽  
Future Scenario ◽  
External Forcings ◽  
Global Mean

Abstract Sulphate aerosol injection has been widely discussed as a possible way to engineer future climate. Monitoring it would require detecting its effects amidst internal variability and in the presence of other external forcings. We investigate how the use of different detection methods and filtering techniques affects the detectability of sulphate aerosol geoengineering in annual-mean global-mean near-surface air temperature. This is done by assuming a future scenario that injects 5 Tg yr−1 of sulphur dioxide into the stratosphere and cross-comparing simulations from 5 climate models. 64% of the studied comparisons would require 25 years or more for detection when no filter and the multi-variate method that has been extensively used for attributing climate change are used, while 66% of the same comparisons would require fewer than 10 years for detection using a trend-based filter. This highlights the high sensitivity of sulphate aerosol geoengineering detectability to the choice of filter. With the same trend-based filter but a non-stationary method, 80% of the comparisons would require fewer than 10 years for detection. This does not imply sulphate aerosol geoengineering should be deployed, but suggests that both detection methods could be used for monitoring geoengineering in global, annual mean temperature should it be needed.

scholarly journals North American Climate in CMIP5 Experiments. Part I: Evaluation of Historical Simulations of Continental and Regional Climatology

2013 ◽  
Vol 26 (23) ◽  
pp. 9209-9245 ◽  
Author(s):  
Justin Sheffield ◽  
Andrew P. Barrett ◽  
Brian Colle ◽  
D. Nelun Fernando ◽  
Rong Fu ◽  
...  
Keyword(s):  
North American ◽  
Regional Climate ◽  
Arctic Sea Ice ◽  
North American Monsoon ◽  
Multimodel Ensemble ◽  
Western Atlantic ◽  
Large Variability ◽  
The North ◽  
North American Climate ◽  
Hydrological Variables

This is the first part of a three-part paper on North American climate in phase 5 of the Coupled Model Intercomparison Project (CMIP5) that evaluates the historical simulations of continental and regional climatology with a focus on a core set of 17 models. The authors evaluate the models for a set of basic surface climate and hydrological variables and their extremes for the continent. This is supplemented by evaluations for selected regional climate processes relevant to North American climate, including cool season western Atlantic cyclones, the North American monsoon, the U.S. Great Plains low-level jet, and Arctic sea ice. In general, the multimodel ensemble mean represents the observed spatial patterns of basic climate and hydrological variables but with large variability across models and regions in the magnitude and sign of errors. No single model stands out as being particularly better or worse across all analyses, although some models consistently outperform the others for certain variables across most regions and seasons and higher-resolution models tend to perform better for regional processes. The CMIP5 multimodel ensemble shows a slight improvement relative to CMIP3 models in representing basic climate variables, in terms of the mean and spread, although performance has decreased for some models. Improvements in CMIP5 model performance are noticeable for some regional climate processes analyzed, such as the timing of the North American monsoon. The results of this paper have implications for the robustness of future projections of climate and its associated impacts, which are examined in the third part of the paper.

scholarly journals Reduced complexity model intercomparison project phase 1: Protocol, results and initial observations

2020 ◽  
Author(s):  
Zebedee R. J. Nicholls ◽  
Malte Meinshausen ◽  
Jared Lewis ◽  
Robert Gieseke ◽  
Dietmar Dommenget ◽  
...  
Keyword(s):  
Radiative Forcing ◽  
Climate Models ◽  
Phase 1 ◽  
Coupled Model ◽  
Surface Air Temperature ◽  
Internal Variability ◽  
Second Phase ◽  
Model Intercomparison ◽  
Intercomparison Project ◽  
Reduced Complexity

Abstract. Here we present results from the first phase of the Reduced Complexity Model Intercomparison Project (RCMIP). RCMIP is a systematic examination of reduced complexity climate models (RCMs), which are used to complement and extend the insights from more complex Earth System Models (ESMs), in particular those participating in the Sixth Coupled Model Intercomparison Project (CMIP6). In Phase 1 of RCMIP, with 14 participating models namely ACC2, AR5IR (2 and 3 box versions), CICERO-SCM, ESCIMO, FaIR, GIR, GREB, Hector, Held et al. two layer model, MAGICC, MCE, OSCAR and WASP, we highlight the structural differences across various RCMs and show that RCMs are capable of reproducing global-mean surface air temperature (GSAT) changes of ESMs and historical observations. We find that some RCMs are capable of emulating the GSAT response of CMIP6 models to within a root-mean square error of 0.2 °C (of the same order of magnitude as ESM internal variability) over a range of scenarios. Running the same model configurations for both RCP and SSP scenarios, we see that the SSPs exhibit higher effective radiative forcing throughout the second half of the 21st Century. Comparing our results to the difference between CMIP5 and CMIP6 output, we find that the change in scenario explains approximately 46 % of the increase in higher end projected warming between CMIP5 and CMIP6. This suggests that changes in ESMs from CMIP5 to CMIP6 explain the rest of the increase, hence the higher climate sensitivities of available CMIP6 models may not be having as large an impact on GSAT projections as first anticipated. A second phase of RCMIP will complement RCMIP Phase 1 by exploring probabilistic results and emulation in more depth to provide results available for the IPCC's Sixth Assessment Report author teams.

scholarly journals Are the Transient and Equilibrium Climate Change Patterns Similar in Response to Increased CO2?

2020 ◽  
Vol 33 (18) ◽  
pp. 8003-8023
Author(s):  
Danqing Huang ◽  
Aiguo Dai ◽  
Jian Zhu
Keyword(s):  
Climate Change ◽  
North Atlantic ◽  
Climate Models ◽  
Surface Air Temperature ◽  
The Arctic ◽  
The North ◽  
Temperature And Precipitation ◽  
Time Periods ◽  
The North Atlantic ◽  
Subtropical Oceans

AbstractAfter a CO2 increase, whether the early transient and final equilibrium climate change patterns are similar has major implications. Here, we analyze long-term simulations from multiple climate models under increased CO2, together with the extended simulations from CMIP5, to compare the transient and equilibrium climate change patterns under different forcing scenarios. Results show that the normalized warming patterns (per 1 K of global warming) are broadly similar among different forcing scenarios (including abrupt 2 × CO2, 4 × CO2, and 1% CO2 increase per year) and during different time periods, except for the first 50 years or so when warming is weaker over the North Atlantic and Southern Ocean but stronger over most continents. During the first 200 years, this consistency is stronger over land than over ocean, but is lower in midlatitudes than other regions. Normalized precipitation change patterns are also similar, albeit to a lesser degree, among different forcing scenarios and across different time periods, although noticeable differences exist during the first few hundred years with smaller increases over the tropical Pacific. Precipitation over many subtropical oceans and land areas decreases consistently under different forcing scenarios and over all time periods. In particular, the transient and near-equilibrium change patterns for both surface air temperature and precipitation are similar over most of the globe, except for the North Atlantic warming hole, which is mainly a transient feature. The Arctic amplification and land–ocean warming contrast are largest during the first 100–200 years after CO2 quadrupling but they still exist in the equilibrium response.

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