scholarly journals Quantification of Uncertainty in High-Resolution Temperature Scenarios for North America

2012 ◽  
Vol 25 (9) ◽  
pp. 3373-3389 ◽  
Author(s):  
Guilong Li ◽  
Xuebin Zhang ◽  
Francis Zwiers ◽  
Qiuzi H. Wen
Keyword(s):  
High Resolution ◽  
North America ◽  
General Circulation ◽  
Large Scale ◽  
Climate Models ◽  
Internal Variability ◽  
General Circulation Models ◽  
First Century ◽  
Small Scale ◽  
Twenty First Century

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.

scholarly journals Hierarchy of climate and hydrological uncertainties in transient low flow projections

2015 ◽  
Vol 12 (12) ◽  
pp. 12649-12701 ◽  
Author(s):  
J.-P. Vidal ◽  
B. Hingray ◽  
C. Magand ◽  
E. Sauquet ◽  
A. Ducharne
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Internal Variability ◽  
General Circulation Models ◽  
Low Flow ◽  
Small Scale ◽  
Total Uncertainty ◽  
Low Flows ◽  
The Difference ◽  
Flow Variables

Abstract. This paper proposes a methodology for estimating the transient probability distribution of yearly hydrological variables conditional to an ensemble of projections built from multiple general circulation models (GCMs), multiple statistical downscaling methods (SDMs) and multiple hydrological models (HMs). The methodology is based on the quasi-ergodic analysis of variance (QE-ANOVA) framework that allows quantifying the contributions of the different sources of total uncertainty, by critically taking account of large-scale internal variability stemming from the transient evolution of multiple GCM runs, and of small-scale internal variability derived from multiple realizations of stochastic SDMs. The QE-ANOVA framework was initially developed for long-term climate averages and is here extended jointly to (1) yearly anomalies and (2) low flow variables. It is applied to better understand possible transient futures of both winter and summer low flows for two snow-influenced catchments in the southern French Alps. The analysis takes advantage of a very large dataset of transient hydrological projections that combines in a comprehensive way 11 runs from 4 different GCMs, 3 SDMs with 10 stochastic realizations each, as well as 6 diverse HMs. The change signal is a decrease in yearly low flows of around −20 % in 2065, except for the most elevated catchment in winter where low flows barely decrease. This signal is largely masked by both large- and small-scale internal variability, even in 2065. The time of emergence of the change signal on 30 year low-flow averages is however around 2035, i.e. for time slices starting in 2020. The most striking result is that a large part of the total uncertainty – and a higher one than that due to the GCMs – stems from the difference in HM responses. An analysis of the origin of this substantial divergence in HM responses for both catchments and in both seasons suggests that both evapotranspiration and snowpack components of HMs should be carefully checked for their robustness in a changed climate in order to provide reliable outputs for informing water resource adaptation strategies.

scholarly journals Projected Twenty-First-Century Changes in the Length of the Tropical Cyclone Season

2015 ◽  
Vol 28 (15) ◽  
pp. 6181-6192 ◽  
Author(s):  
John G. Dwyer ◽  
Suzana J. Camargo ◽  
Adam H. Sobel ◽  
Michela Biasutti ◽  
Kerry A. Emanuel ◽  
...  
Keyword(s):  
Tropical Cyclone ◽  
Tropical Cyclones ◽  
General Circulation ◽  
Large Scale ◽  
General Circulation Models ◽  
First Century ◽  
Season Length ◽  
Length Changes ◽  
Twenty First Century ◽  
Tropical Cyclone Season

Abstract This study investigates projected changes in the length of the tropical cyclone season due to greenhouse gas increases. Two sets of simulations are analyzed, both of which capture the relevant features of the observed annual cycle of tropical cyclones in the recent historical record. Both sets use output from the general circulation models (GCMs) of either phase 3 or phase 5 of the CMIP suite (CMIP3 and CMIP5, respectively). In one set, downscaling is performed by randomly seeding incipient vortices into the large-scale atmospheric conditions simulated by each GCM and simulating the vortices’ evolution in an axisymmetric dynamical tropical cyclone model; in the other set, the GCMs’ sea surface temperature (SST) is used as the boundary condition for a high-resolution global atmospheric model (HiRAM). The downscaling model projects a longer season (in the late twenty-first century compared to the twentieth century) in most basins when using CMIP5 data but a slightly shorter season using CMIP3. HiRAM with either CMIP3 or CMIP5 SST anomalies projects a shorter tropical cyclone season in most basins. Season length is measured by the number of consecutive days that the mean cyclone count is greater than a fixed threshold, but other metrics give consistent results. The projected season length changes are also consistent with the large-scale changes, as measured by a genesis index of tropical cyclones. The season length changes are mostly explained by an idealized year-round multiplicative change in tropical cyclone frequency, but additional changes in the transition months also contribute.

Interpreting Results from the NARCCAP and NA-CORDEX Ensembles in the Context of Uncertainty in Regional Climate Change Projections

2018 ◽  
Vol 99 (10) ◽  
pp. 2093-2106 ◽  
Author(s):  
Ambarish V. Karmalkar
Keyword(s):  
Climate Change ◽  
North America ◽  
General Circulation ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Change ◽  
Internal Variability ◽  
General Circulation Models ◽  
Eastern United States ◽  
The Impact

AbstractTwo ensembles of dynamically downscaled climate simulations for North America—the North American Regional Climate Change Assessment Program (NARCCAP) and the Coordinated Regional Climate Downscaling Experiment (CORDEX) featuring simulations for North America (NA-CORDEX)—are analyzed to assess the impact of using a small set of global general circulation models (GCMs) and regional climate models (RCMs) on representing uncertainty in regional projections. Selecting GCMs for downscaling based on their equilibrium climate sensitivities is a reasonable strategy, but there are regions where the uncertainty is not fully captured. For instance, the six NA-CORDEX GCMs fail to span the full ranges produced by models in phase 5 of the Coupled Model Intercomparison Project (CMIP5) in summer temperature projections in the western and winter precipitation projections in the eastern United States. Similarly, the four NARCCAP GCMs are overall poor at spanning the full CMIP3 ranges in seasonal temperatures. For the Southeast, the NA-CORDEX GCMs capture the uncertainty in summer but not in winter projections, highlighting one consequence of downscaling a subset of GCMs. Ranges produced by the RCMs are often wider than their driving GCMs but are sensitive to the experimental design. For example, the downscaled projections of summer precipitation are of opposite polarity in two RCM ensembles in some regions. Additionally, the ability of the RCMs to simulate observed temperature trends is affected by the internal variability characteristics of both the RCMs and driving GCMs, and is not systematically related to their historical performance. This has implications for adequately sampling the impact of internal variability on regional trends and for using model performance to identify credible projections. These findings suggest that a multimodel perspective on uncertainties in regional projections is integral to the interpretation of RCM results.

scholarly journals A Review of Uncertainties in Global Temperature Projections over the Twenty-First Century

2008 ◽  
Vol 21 (11) ◽  
pp. 2651-2663 ◽  
Author(s):  
R. Knutti ◽  
M. R. Allen ◽  
P. Friedlingstein ◽  
J. M. Gregory ◽  
G. C. Hegerl ◽  
...  
Keyword(s):  
Carbon Cycle ◽  
General Circulation ◽  
Climate Models ◽  
General Circulation Models ◽  
First Century ◽  
Global Temperature ◽  
Climate Projections ◽  
Uncertainty Range ◽  
Uncertainty Estimates ◽  
Twenty First Century

Abstract Quantification of the uncertainties in future climate projections is crucial for the implementation of climate policies. Here a review of projections of global temperature change over the twenty-first century is provided for the six illustrative emission scenarios from the Special Report on Emissions Scenarios (SRES) that assume no policy intervention, based on the latest generation of coupled general circulation models, climate models of intermediate complexity, and simple models, and uncertainty ranges and probabilistic projections from various published methods and models are assessed. Despite substantial improvements in climate models, projections for given scenarios on average have not changed much in recent years. Recent progress has, however, increased the confidence in uncertainty estimates and now allows a better separation of the uncertainties introduced by scenarios, physical feedbacks, carbon cycle, and structural uncertainty. Projection uncertainties are now constrained by observations and therefore consistent with past observed trends and patterns. Future trends in global temperature resulting from anthropogenic forcing over the next few decades are found to be comparably well constrained. Uncertainties for projections on the century time scale, when accounting for structural and feedback uncertainties, are larger than captured in single models or methods. This is due to differences in the models, the sources of uncertainty taken into account, the type of observational constraints used, and the statistical assumptions made. It is shown that as an approximation, the relative uncertainty range for projected warming in 2100 is the same for all scenarios. Inclusion of uncertainties in carbon cycle–climate feedbacks extends the upper bound of the uncertainty range by more than the lower bound.

scholarly journals A Model Study of Heat Waves over North America: Meteorological Aspects and Projections for the Twenty-First Century

2012 ◽  
Vol 25 (14) ◽  
pp. 4761-4784 ◽  
Author(s):  
Ngar-Cheung Lau ◽  
Mary Jo Nath
Keyword(s):  
Twentieth Century ◽  
North America ◽  
Heat Wave ◽  
General Circulation ◽  
Heat Waves ◽  
General Circulation Models ◽  
Reanalysis Data ◽  
First Century ◽  
Twenty First Century ◽  
The Impact

Abstract 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.

scholarly journals Hierarchy of climate and hydrological uncertainties in transient low-flow projections

2016 ◽  
Vol 20 (9) ◽  
pp. 3651-3672 ◽  
Author(s):  
Jean-Philippe Vidal ◽  
Benoît Hingray ◽  
Claire Magand ◽  
Eric Sauquet ◽  
Agnès Ducharne
Keyword(s):  
General Circulation ◽  
Large Scale ◽  
Large Data ◽  
Internal Variability ◽  
General Circulation Models ◽  
Low Flow ◽  
Small Scale ◽  
Data Set ◽  
Total Uncertainty ◽  
Low Flows

Abstract. This paper proposes a methodology for estimating the transient probability distribution of yearly hydrological variables conditional to an ensemble of projections built from multiple general circulation models (GCMs), multiple statistical downscaling methods (SDMs), and multiple hydrological models (HMs). The methodology is based on the quasi-ergodic analysis of variance (QE-ANOVA) framework that allows quantifying the contributions of the different sources of total uncertainty, by critically taking account of large-scale internal variability stemming from the transient evolution of multiple GCM runs, and of small-scale internal variability derived from multiple realizations of stochastic SDMs. This framework thus allows deriving a hierarchy of climate and hydrological uncertainties, which depends on the time horizon considered. It was initially developed for long-term climate averages and is here extended jointly to (1) yearly anomalies and (2) low-flow variables. It is applied to better understand possible transient futures of both winter and summer low flows for two snow-influenced catchments in the southern French Alps. The analysis takes advantage of a very large data set of transient hydrological projections that combines in a comprehensive way 11 runs from four different GCMs, three SDMs with 10 stochastic realizations each, as well as six diverse HMs. The change signal is a decrease in yearly low flows of around −20  % in 2065, except for the more elevated catchment in winter where low flows barely decrease. This signal is largely masked by both large- and small-scale internal variability, even in 2065. The time of emergence of the change signal is however detected for low-flow averages over 30-year time slices starting as early as 2020. The most striking result is that a large part of the total uncertainty – and a higher one than that due to the GCMs – stems from the difference in HM responses. An analysis of the origin of this substantial divergence in HM responses for both catchments and in both seasons suggests that both evapotranspiration and snowpack components of HMs should be carefully checked for their robustness in a changed climate in order to provide reliable outputs for informing water resource adaptation strategies.

scholarly journals Evaluation of a unique approach to high-resolution climate modeling using the Model for Prediction Across Scales – Atmosphere (MPAS-A) version 5.1

2019 ◽  
Vol 12 (8) ◽  
pp. 3725-3743 ◽  
Author(s):  
Allison C. Michaelis ◽  
Gary M. Lackmann ◽  
Walter A. Robinson
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Sea Ice ◽  
Northern Hemisphere ◽  
General Circulation ◽  
Large Scale ◽  
Southern Oscillation ◽  
Spatial Scales ◽  
Coupled Model ◽  
General Circulation Models

Abstract. We present multi-seasonal simulations representative of present-day and future environments using the global Model for Prediction Across Scales – Atmosphere (MPAS-A) version 5.1 with high resolution (15 km) throughout the Northern Hemisphere. We select 10 simulation years with varying phases of El Niño–Southern Oscillation (ENSO) and integrate each for 14.5 months. We use analyzed sea surface temperature (SST) patterns for present-day simulations. For the future climate simulations, we alter present-day SSTs by applying monthly-averaged temperature changes derived from a 20-member ensemble of Coupled Model Intercomparison Project phase 5 (CMIP5) general circulation models (GCMs) following the Representative Concentration Pathway (RCP) 8.5 emissions scenario. Daily sea ice fields, obtained from the monthly-averaged CMIP5 ensemble mean sea ice, are used for present-day and future simulations. The present-day simulations provide a reasonable reproduction of large-scale atmospheric features in the Northern Hemisphere such as the wintertime midlatitude storm tracks, upper-tropospheric jets, and maritime sea-level pressure features as well as annual precipitation patterns across the tropics. The simulations also adequately represent tropical cyclone (TC) characteristics such as strength, spatial distribution, and seasonal cycles for most Northern Hemisphere basins. These results demonstrate the applicability of these model simulations for future studies examining climate change effects on various Northern Hemisphere phenomena, and, more generally, the utility of MPAS-A for studying climate change at spatial scales generally unachievable in GCMs.

scholarly journals Synoptic Responses to Mountain Gravity Waves Encountering Directional Critical Levels

2007 ◽  
Vol 64 (3) ◽  
pp. 828-848 ◽  
Author(s):  
Armel Martin ◽  
François Lott
Keyword(s):  
Gravity Waves ◽  
General Circulation ◽  
Large Scale ◽  
Baroclinic Instability ◽  
General Circulation Models ◽  
Small Scale ◽  
Mountain Range ◽  
Critical Levels ◽  
Sensitivity Tests ◽  
Large Scale Flow

Abstract A heuristic model is used to study the synoptic response to mountain gravity waves (GWs) absorbed at directional critical levels. The model is a semigeostrophic version of the Eady model for baroclinic instability adapted by Smith to study lee cyclogenesis. The GWs exert a force on the large-scale flow where they encounter directional critical levels. This force is taken into account in the model herein and produces potential vorticity (PV) anomalies in the midtroposphere. First, the authors consider the case of an idealized mountain range such that the orographic variance is well separated between small- and large-scale contributions. In the absence of tropopause, the PV produced by the GW force has a surface impact that is significant compared to the surface response due to the large scales. For a cold front, the GW force produces a trough over the mountain and a larger-amplitude ridge immediately downstream. It opposes somehow to the response due to the large scales of the mountain range, which is anticyclonic aloft and cyclonic downstream. For a warm front, the GW force produces a ridge over the mountain and a trough downstream; hence it reinforces the response due to the large scales. Second, the robustness of the previous results is verified by a series of sensitivity tests. The authors change the specifications of the mountain range and of the background flow. They also repeat some experiments by including baroclinic instabilities, or by using the quasigeostrophic approximation. Finally, they consider the case of a small-scale orographic spectrum representative of the Alps. The significance of the results is discussed in the context of GW parameterization in the general circulation models. The results may also help to interpret the complex PV structures occurring when mountain gravity waves break in a baroclinic environment.

Polar meteorology: a review of some recent research

Polar Record ◽  
1974 ◽  
Vol 17 (108) ◽  
pp. 277-294 ◽  
Author(s):  
Gunter Weller
Keyword(s):  
Heat Source ◽  
General Circulation ◽  
Large Scale ◽  
Climate Models ◽  
General Circulation Models ◽  
Cloud Formation ◽  
Driving Mechanism ◽  
Polar Regions ◽  
International Geophysical Year ◽  
Polar Meteorology

The general large-scale circulation of the global atmosphere has its basic driving mechanism in the equator-poleward temperature gradients in both hemispheres. It has become increasingly obvious over the last few decades that to understand and predict the behaviour of the atmosphere at any point, it is essential to understand the behaviour of the total global fluid system. The Global Atmospheric Research Project (GARP) is an outcome of this recognition. Studies of the heat sinks (the polar regions) are therefore just as important as studies of the heat source (the equatorial regions) to understand the meteorology of the planet. Interest in polar meteorology has undergone many cyclic fluctuations, peaking during the various international polar years and, more recently, during the International Geophysical Year, 1957–58. At the present, the focus of GARP's first objective (improved extended weather forecasts) is on the tropical heat source, where convection and cloud formation and dissipation are still relatively little understood processes. However, the second GARP objective (better understanding of the physical basis of climate) requires more attention to be devoted to the cryosphere, its long-term interaction with oceans and atmosphere, and its role as an indicator of climatic change. The idea of a polar experiment (POLEX) was initially introduced by Treshnikov and others (1968) and by Borisenkov and Treshnikov (1971). A summary of the early history of POLEX was recently given by Weller and Bierly (1973). The two closely related objectives of POLEX that most directly pertain to GARP may be restated in their simplest terms as (1) a better understanding of energy transfer processes and the heat budgets of the polar regions for the purpose of parameterizing them properly in general circulation models and climate models, and (2) provision of adequate data from the polar regions during the First GARP Global Experiment (FGGE) in 1978.

scholarly journals Quantifying Sources of Uncertainty in Projections of Future Climate*

2014 ◽  
Vol 27 (23) ◽  
pp. 8793-8808 ◽  
Author(s):  
Paul J. Northrop ◽  
Richard E. Chandler
Keyword(s):  
General Circulation ◽  
Climate Model ◽  
Internal Variability ◽  
Future Climate ◽  
First Century ◽  
Climate Projections ◽  
Large Contribution ◽  
Sources Of Uncertainty ◽  
Twenty First Century ◽  
Emissions Scenario

Abstract A simple statistical model is used to partition uncertainty from different sources, in projections of future climate from multimodel ensembles. Three major sources of uncertainty are considered: the choice of climate model, the choice of emissions scenario, and the internal variability of the modeled climate system. The relative contributions of these sources are quantified for mid- and late-twenty-first-century climate projections, using data from 23 coupled atmosphere–ocean general circulation models obtained from phase 3 of the Coupled Model Intercomparison Project (CMIP3). Similar investigations have been carried out recently by other authors but within a statistical framework for which the unbalanced nature of the data and the small number (three) of scenarios involved are potentially problematic. Here, a Bayesian analysis is used to overcome these difficulties. Global and regional analyses of surface air temperature and precipitation are performed. It is found that the relative contributions to uncertainty depend on the climate variable considered, as well as the region and time horizon. As expected, the uncertainty due to the choice of emissions scenario becomes more important toward the end of the twenty-first century. However, for midcentury temperature, model internal variability makes a large contribution in high-latitude regions. For midcentury precipitation, model internal variability is even more important and this persists in some regions into the late century. Implications for the design of climate model experiments are discussed.

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