Comparison of observed seasonal temperature maxima, minima and diurnal range in North America with simulations from three global climate models

1995 ◽  
Vol 37 (1-3) ◽  
pp. 267-275 ◽  
Author(s):  
G. Kukla ◽  
J. Gavin ◽  
M. Schlesinger ◽  
T. Karl
Keyword(s):  
North America ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Seasonal Temperature ◽  
Diurnal Range

scholarly journals Tendency Bias Correction in Coupled and Uncoupled Global Climate Models with a Focus on Impacts over North America

2019 ◽  
Vol 32 (2) ◽  
pp. 639-661 ◽  
Author(s):  
Y. Chang ◽  
S. D. Schubert ◽  
R. D. Koster ◽  
A. M. Molod ◽  
H. Wang
Keyword(s):  
North America ◽  
Bias Correction ◽  
Climate Models ◽  
Global Climate ◽  
Storm Track ◽  
Coupled Model ◽  
Global Climate Models ◽  
Forecast Skill ◽  
Boreal Summer ◽  
Transient Wave

Abstract We revisit the bias correction problem in current climate models, taking advantage of state-of-the-art atmospheric reanalysis data and new data assimilation tools that simplify the estimation of short-term (6 hourly) atmospheric tendency errors. The focus is on the extent to which correcting biases in atmospheric tendencies improves the model’s climatology, variability, and ultimately forecast skill at subseasonal and seasonal time scales. Results are presented for the NASA GMAO GEOS model in both uncoupled (atmosphere only) and coupled (atmosphere–ocean) modes. For the uncoupled model, the focus is on correcting a stunted North Pacific jet and a dry bias over the central United States during boreal summer—long-standing errors that are indeed common to many current AGCMs. The results show that the tendency bias correction (TBC) eliminates the jet bias and substantially increases the precipitation over the Great Plains. These changes are accompanied by much improved (increased) storm-track activity throughout the northern midlatitudes. For the coupled model, the atmospheric TBCs produce substantial improvements in the simulated mean climate and its variability, including a much reduced SST warm bias, more realistic ENSO-related SST variability and teleconnections, and much improved subtropical jets and related submonthly transient wave activity. Despite these improvements, the improvement in subseasonal and seasonal forecast skill over North America is only modest at best. The reasons for this, which are presumably relevant to any forecast system, involve the competing influences of predictability loss with time and the time it takes for climate drift to first have a significant impact on forecast skill.

A Bayesian Hierarchical Model for Heterogeneous RCM–GCM Multimodel Ensembles*

2015 ◽  
Vol 28 (15) ◽  
pp. 6249-6266 ◽  
Author(s):  
Christian Kerkhoff ◽  
Hans R. Künsch ◽  
Christoph Schär
Keyword(s):  
Hierarchical Model ◽  
Climate Models ◽  
Global Climate ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Bayesian Hierarchical Model ◽  
Global Climate Models ◽  
Seasonal Temperature ◽  
Bayesian Hierarchical ◽  
Multimodel Ensembles

Abstract A Bayesian hierarchical model for heterogeneous multimodel ensembles of global and regional climate models is presented. By applying the methodology herein to regional and seasonal temperature averages from the ENSEMBLES project, probabilistic projections of future climate are derived. Intermodel correlations that are particularly strong between regional climate models and their driving global climate models are explicitly accounted for. Instead of working with time slices, a data archive is investigated in a transient setting. This enables a coherent treatment of internal variability on multidecadal time scales. Results are presented for four European regions to highlight the feasibility of the approach. In particular, the methodology is able to objectively identify patterns of variability changes, in ways that previously required subjective expert knowledge. Furthermore, this study underlines that assumptions about bias changes have an effect on the projected warming. It is also shown that validating the out-of-sample predictive performance is possible on short-term prediction horizons and that the hierarchical model herein is competitive. Additionally, the findings indicate that instead of running a large suite of regional climate models all forced by the same driver, priority should be given to a rich diversity of global climate models that force a number of regional climate models in the experimental design of future multimodel ensembles.

Improved trend-aware post-processing of GCM seasonal precipitation forecasts

2021 ◽  
Keyword(s):  
Climate Models ◽  
Global Climate ◽  
Processing Method ◽  
Global Climate Models ◽  
Seasonal Precipitation ◽  
Seasonal Temperature ◽  
Post Processing ◽  
Climate Trends ◽  
Climate Forecasting ◽  
New Formulation

Abstract Climate trends have been observed over the recent decades in many parts of the world, but current global climate models (GCMs) for seasonal climate forecasting often fail to capture these trends. As a result, model forecasts may be biased above or below the trendline. In our previous research, we developed a trend-aware forecast post-processing method to overcome this problem. The method was demonstrated to be effective for embedding observed trends into seasonal temperature forecasts. In this study, we further develop the method for post-processing GCM seasonal precipitation forecasts. We introduce new formulation and evaluation features to cater for special characteristics of precipitation amounts, such as having a zero lower bound and highly positive skewness. We apply the improved method to calibrate ECMWF SEAS5 forecasts of seasonal precipitation for Australia. Our evaluation shows that the calibrated forecasts reproduce observed trends over the hindcast period of 36 years. In some regions where observed trends are statistically significant, forecast skill is greatly improved by embedding trends into the forecasts. In most regions, the calibrated forecasts outperform the raw forecasts in terms of bias, skill, and reliability. Wider applications of the new trend-aware post-processing method are expected to boost user confidence in seasonal precipitation forecasts.

scholarly journals Prediction of the Long-Term Potential Distribution of Cryptorhynchus lapathi (L.) under Climate Change

Forests ◽  
2019 ◽  
Vol 11 (1) ◽  
pp. 5 ◽  
Author(s):  
Ya Zou ◽  
Linjing Zhang ◽  
Xuezhen Ge ◽  
Siwei Guo ◽  
Xue Li ◽  
...  
Keyword(s):  
Climate Change ◽  
North America ◽  
Potential Distribution ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Prevention Measures ◽  
Climate Data ◽  
Effective Prevention ◽  
Future Global Warming

The poplar and willow borer, Cryptorhynchus lapathi (L.), is a severe worldwide quarantine pest that causes great economic, social, and ecological damage in Europe, North America, and Asia. CLIMEX4.0.0 was used to study the likely impact of climate change on the potential global distribution of C. lapathi based on existing (1987–2016) and predicted (2021–2040, 2041–2080, and 2081–2100) climate data. Future climate data were simulated based on global climate models from Coupled Model Inter-comparison Project Phase 5 (CMIP5) under the RCP4.5 projection. The potential distribution of C. lapathi under historical climate conditions mainly includes North America, Africa, Europe, and Asia. Future global warming may cause a northward shift in the northern boundary of potential distribution. The total suitable area would increase by 2080–2100. Additionally, climatic suitability would change in large regions of the northern hemisphere and decrease in a small region of the southern hemisphere. The projected potential distribution will help determine the impacts of climate change and identify areas at risk of pest invasion in the future. In turn, this will help design and implement effective prevention measures for expanding pest populations, using natural enemies, microorganisms, and physical barriers in very favorable regions to impede the movement and oviposition of C. lapathi.

scholarly journals Glacier retreat creating new Pacific salmon habitat in western North America

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Kara J. Pitman ◽  
Jonathan W. Moore ◽  
Matthias Huss ◽  
Matthew R. Sloat ◽  
Diane C. Whited ◽  
...  
Keyword(s):  
North America ◽  
Climate Models ◽  
Pacific Salmon ◽  
Global Climate ◽  
Global Climate Models ◽  
Glacier Retreat ◽  
Western North America ◽  
Mountain Ranges ◽  
Proactive Management ◽  
The Pacific

AbstractGlacier retreat poses risks and benefits for species of cultural and economic importance. One example is Pacific salmon (Oncorhynchus spp.), supporting subsistence harvests, and commercial and recreational fisheries worth billions of dollars annually. Although decreases in summer streamflow and warming freshwater is reducing salmon habitat quality in parts of their range, glacier retreat is creating new streams and lakes that salmon can colonize. However, potential gains in future salmon habitat associated with glacier loss have yet to be quantified across the range of Pacific salmon. Here we project future gains in Pacific salmon freshwater habitat by linking a model of glacier mass change for 315 glaciers, forced by five different Global Climate Models, with a simple model of salmon stream habitat potential throughout the Pacific Mountain ranges of western North America. We project that by the year 2100 glacier retreat will create 6,146 (±1,619) km of new streams accessible for colonization by Pacific salmon, of which 1,930 (±569) km have the potential to be used for spawning and juvenile rearing, representing 0 to 27% gains within the 18 sub-regions we studied. These findings can inform proactive management and conservation of Pacific salmon in this era of rapid climate change.

scholarly journals Projections of North American Snow from NA-CORDEX and their Uncertainties, with a Focus on Model Resolution

2021 ◽  
Author(s):  
Rachel McCrary ◽  
Linda Mearns ◽  
Mimi Hughes ◽  
Sébastien Biner ◽  
Melissa Bukovsky
Keyword(s):  
North America ◽  
North American ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
High Elevation ◽  
Climate Impacts ◽  
Global Climate Models ◽  
High Latitudes ◽  
Model Resolution

Abstract Snow is important for many physical, social, and economic sectors in North America. In a warming climate, the characteristics of snow will likely change in fundamental ways, therefore compelling societal need for future projections of snow. However many stakeholders require climate change information at finer resolutions that global climate models (GCMs) can provide. The North American Coordinated Regional Downscaling Experiment (NA-CORDEX) provides an ensemble of regional climate model (RCMs) simulations at two resolutions (~0.5º and ~0.25º) designed to help serve the climate impacts and adaptation communities. This is the first study to examine the differences in end-of-21st-century projections of snow from the NA-CORDEX RCMs and their driving GCMs. We find the broad patterns of change are similar across RCMs and GCMs: snow cover retreats, snow mass decreases everywhere except at high latitudes, and the duration of the snow covered season decreases. Regionally, the spatial details, magnitude, percent, and uncertainty of future changes varies between the GCM and RCM ensemble, but are similar between the two resolutions of the RCM ensembles. Increases in winter snow amounts at high latitudes is a robust response across all ensembles. Percent snow losses are found to be more substantial in the GCMs than the RCMs over most of North America, especially in regions with high-elevation topography. Specifically, percent snow losses decrease with increasing elevation as the model resolution becomes finer.

scholarly journals Multimodel GCM-RCM Ensemble-Based Projections of Temperature and Precipitation over West Africa for the Early 21st Century

2012 ◽  
Vol 2012 ◽  
pp. 1-19 ◽  
Author(s):  
I. Diallo ◽  
M. B. Sylla ◽  
F. Giorgi ◽  
A. T. Gaye ◽  
M. Camara
Keyword(s):  
Climate Change ◽  
West Africa ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models ◽  
Future Climate ◽  
Climate Projections ◽  
Climate Change Scenarios ◽  
Seasonal Temperature ◽  
Temperature And Precipitation

Reliable climate change scenarios are critical for West Africa, whose economy relies mostly on agriculture and, in this regard, multimodel ensembles are believed to provide the most robust climate change information. Toward this end, we analyze and intercompare the performance of a set of four regional climate models (RCMs) driven by two global climate models (GCMs) (for a total of 4 different GCM-RCM pairs) in simulating present day and future climate over West Africa. The results show that the individual RCM members as well as their ensemble employing the same driving fields exhibit different biases and show mixed results in terms of outperforming the GCM simulation of seasonal temperature and precipitation, indicating a substantial sensitivity of RCMs to regional and local processes. These biases are reduced and GCM simulations improved upon by averaging all four RCM simulations, suggesting that multi-model RCM ensembles based on different driving GCMs help to compensate systematic errors from both the nested and the driving models. This confirms the importance of the multi-model approach for improving robustness of climate change projections. Illustrative examples of such ensemble reveal that the western Sahel undergoes substantial drying in future climate projections mostly due to a decrease in peak monsoon rainfall.

Extreme Events in High Resolution CMCC Regional and Global Climate Models

2011 ◽  
Author(s):  
Enrico Scoccimarro ◽  
Silvio Gualdi ◽  
Antonella Sanna ◽  
Edoardo Bucchignani ◽  
Myriam Montesarchio
Keyword(s):  
High Resolution ◽  
Extreme Events ◽  
Climate Models ◽  
Global Climate ◽  
Global Climate Models

scholarly journals Global climatology and trends in convective environments from ERA5 and rawinsonde data

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Mateusz Taszarek ◽  
John T. Allen ◽  
Mattia Marchio ◽  
Harold E. Brooks
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Global Climate ◽  
Convective Available Potential Energy ◽  
Global Climate Models ◽  
Convective Precipitation ◽  
The Past ◽  
The Tropics ◽  
Rawinsonde Data

AbstractGlobally, thunderstorms are responsible for a significant fraction of rainfall, and in the mid-latitudes often produce extreme weather, including large hail, tornadoes and damaging winds. Despite this importance, how the global frequency of thunderstorms and their accompanying hazards has changed over the past 4 decades remains unclear. Large-scale diagnostics applied to global climate models have suggested that the frequency of thunderstorms and their intensity is likely to increase in the future. Here, we show that according to ERA5 convective available potential energy (CAPE) and convective precipitation (CP) have decreased over the tropics and subtropics with simultaneous increases in 0–6 km wind shear (BS06). Conversely, rawinsonde observations paint a different picture across the mid-latitudes with increasing CAPE and significant decreases to BS06. Differing trends and disagreement between ERA5 and rawinsondes observed over some regions suggest that results should be interpreted with caution, especially for CAPE and CP across tropics where uncertainty is the highest and reliable long-term rawinsonde observations are missing.

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