scholarly journals Do CMIP models capture long-term observed annual precipitation trends?

2021 ◽  
Author(s):  
S. M. Vicente-Serrano ◽  
R. García-Herrera ◽  
D. Peña-Angulo ◽  
M. Tomas-Burguera ◽  
F. Domínguez-Castro ◽  
...  
Keyword(s):  
Global Assessment ◽  
Climate Model ◽  
Coupled Model ◽  
Annual Precipitation ◽  
Model Intercomparison ◽  
The World ◽  
Intercomparison Project ◽  
Using Data ◽  
Precipitation Trends

AbstractThis study provides a long-term (1891–2014) global assessment of precipitation trends using data from two station-based gridded datasets and climate model outputs evolved through the fifth and sixth phases of the Coupled Model Intercomparison Project (CMIP5 and CMIP6, respectively). Our analysis employs a variety of modeling groups that incorporate low- and high-top level members, with the aim of assessing the possible effects of including a well-resolved stratosphere on the model’s ability to reproduce long-term observed annual precipitation trends. Results demonstrate that only a few regions show statistically significant differences in precipitation trends between observations and models. Nevertheless, this pattern is mostly caused by the strong interannual variability of precipitation in most of the world regions. Thus, statistically significant model-observation differences on trends (1891–2014) are found at the zonal mean scale. The different model groups clearly fail to reproduce the spatial patterns of annual precipitation trends and the regions where stronger increases or decreases are recorded. This study also stresses that there are no significant differences between low- and high-top models in capturing observed precipitation trends, indicating that having a well-resolved stratosphere has a low impact on the accuracy of precipitation projections.

scholarly journals The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6

2016 ◽  
Vol 9 (9) ◽  
pp. 3461-3482 ◽  
Author(s):  
Brian C. O'Neill ◽  
Claudia Tebaldi ◽  
Detlef P. van Vuuren ◽  
Veronika Eyring ◽  
Pierre Friedlingstein ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Use ◽  
21St Century ◽  
Integrated Assessment ◽  
Climate Model ◽  
Model Intercomparison ◽  
Wide Range ◽  
Scenario Model ◽  
Intercomparison Project

Abstract. Projections of future climate change play a fundamental role in improving understanding of the climate system as well as characterizing societal risks and response options. The Scenario Model Intercomparison Project (ScenarioMIP) is the primary activity within Phase 6 of the Coupled Model Intercomparison Project (CMIP6) that will provide multi-model climate projections based on alternative scenarios of future emissions and land use changes produced with integrated assessment models. In this paper, we describe ScenarioMIP's objectives, experimental design, and its relation to other activities within CMIP6. The ScenarioMIP design is one component of a larger scenario process that aims to facilitate a wide range of integrated studies across the climate science, integrated assessment modeling, and impacts, adaptation, and vulnerability communities, and will form an important part of the evidence base in the forthcoming Intergovernmental Panel on Climate Change (IPCC) assessments. At the same time, it will provide the basis for investigating a number of targeted science and policy questions that are especially relevant to scenario-based analysis, including the role of specific forcings such as land use and aerosols, the effect of a peak and decline in forcing, the consequences of scenarios that limit warming to below 2 °C, the relative contributions to uncertainty from scenarios, climate models, and internal variability, and long-term climate system outcomes beyond the 21st century. To serve this wide range of scientific communities and address these questions, a design has been identified consisting of eight alternative 21st century scenarios plus one large initial condition ensemble and a set of long-term extensions, divided into two tiers defined by relative priority. Some of these scenarios will also provide a basis for variants planned to be run in other CMIP6-Endorsed MIPs to investigate questions related to specific forcings. Harmonized, spatially explicit emissions and land use scenarios generated with integrated assessment models will be provided to participating climate modeling groups by late 2016, with the climate model simulations run within the 2017–2018 time frame, and output from the climate model projections made available and analyses performed over the 2018–2020 period.

Observational and Model Estimates of Cloud Amount Feedback over the Indian and Pacific Oceans

2014 ◽  
Vol 27 (2) ◽  
pp. 925-940 ◽  
Author(s):  
Katinka Bellomo ◽  
Amy C. Clement ◽  
Joel R. Norris ◽  
Brian J. Soden
Keyword(s):  
Coupled Model ◽  
Cloud Amount ◽  
Western Indian Ocean ◽  
Model Intercomparison ◽  
Central Pacific ◽  
Radiative Impact ◽  
Southern Central ◽  
Intercomparison Project ◽  
Very High

AbstractConstraining intermodel spread in cloud feedback with observations is problematic because available cloud datasets are affected by spurious behavior in long-term variability. This problem is addressed by examining cloud amount in three independent ship-based [Extended Edited Cloud Reports Archive (EECRA)] and satellite-based [International Satellite Cloud Climatology Project (ISCCP) and Advanced Very High Resolution Radiometer Pathfinder Atmosphere–Extended (PATMOS-X)] observational datasets, and models from phase 5 of the Coupled Model Intercomparison Project (CMIP5). The three observational datasets show consistent cloud variability in the overlapping years of coverage (1984–2007). The long-term cloud amount change from 1954 to 2005 in ship-based observations shares many of the same features with the multimodel mean cloud amount change of 42 CMIP5 historical simulations, although the magnitude of the multimodel mean is smaller. The radiative impact of cloud changes is estimated by computing an observationally derived estimate of cloud amount feedback. The observational estimates of cloud amount feedback are statistically significant over four regions: the northeast Pacific subtropical stratocumulus region and equatorial western Pacific, where cloud amount feedback is found to be positive, and the southern central Pacific and western Indian Ocean, where cloud amount feedback is found to be negative. Multimodel mean cloud amount feedback is consistent in sign but smaller in magnitude than in observations over these four regions because models simulate weaker cloud changes. Individual models, however, can simulate cloud amount feedback of the same magnitude if not larger than observed. Focusing on the regions where models and observations agree can lead to improved understanding of the mechanisms of cloud amount changes and associated radiative impact.

Distributions of Tropical Precipitation Cluster Power and Their Changes under Global Warming. Part II: Long-Term Time Dependence in Coupled Model Intercomparison Project Phase 5 Models

2017 ◽  
Vol 30 (20) ◽  
pp. 8045-8059 ◽  
Author(s):  
Kevin M. Quinn ◽  
J. David Neelin
Keyword(s):  
Global Warming ◽  
High Resolution ◽  
Rain Rate ◽  
Climate Model ◽  
Coupled Model ◽  
Atmospheric Model ◽  
Department Of Energy ◽  
Model Intercomparison ◽  
Intense Storm ◽  
Intercomparison Project

Abstract Distributions of precipitation cluster power (latent heat release rate integrated over contiguous precipitating pixels) are examined in 1°–2°-resolution members of phase 5 of the Coupled Model Intercomparison Project (CMIP5) climate model ensemble. These approximately reproduce the power-law range and large event cutoff seen in observations and the High Resolution Atmospheric Model (HiRAM) at 0.25°–0.5° in Part I. Under the representative concentration pathway 8.5 (RCP8.5) global warming scenario, the change in the probability of the most intense storm clusters appears in all models and is consistent with HiRAM output, increasing by up to an order of magnitude relative to historical climate. For the three models in the ensemble with continuous time series of high-resolution output, there is substantial variability on when these probability increases for the most powerful storm clusters become detectable, ranging from detectable within the observational period to statistically significant trends emerging only after 2050. A similar analysis of National Centers for Environmental Prediction (NCEP)–U.S. Department of Energy (DOE) AMIP-II reanalysis and Special Sensor Microwave Imager and Imager/Sounder (SSM/I and SSMIS) rain-rate retrievals in the recent observational record does not yield reliable evidence of trends in high power cluster probabilities at this time. However, the results suggest that maintaining a consistent set of overlapping satellite instrumentation with improvements to SSM/I–SSMIS rain-rate retrieval intercalibrations would be useful for detecting trends in this important tail behavior within the next couple of decades.

scholarly journals Long term precipitation trends and variability within the Mediterranean region

2011 ◽  
Vol 11 (12) ◽  
pp. 3235-3250 ◽  
Author(s):  
C. M. Philandras ◽  
P. T. Nastos ◽  
J. Kapsomenakis ◽  
K. C. Douvis ◽  
G. Tselioudis ◽  
...  
Keyword(s):  
Confidence Level ◽  
Mediterranean Region ◽  
Climate Model ◽  
Future Climate ◽  
Annual Precipitation ◽  
Climatic Research Unit ◽  
Rain Season ◽  
The World ◽  
The Mediterranean

Abstract. In this study, the trends and variability of annual precipitation totals and annual rain days over land within the Mediterranean region are analyzed. Long term ground-based observations concerning, on one hand, monthly precipitation totals (1900–2010) and rain days (1965–2010) from 40 meteorological stations within the Mediterranean region were obtained from the Hellenic National Meteorological Service and the World Climate Data and Monitoring Programme (WCDMP) of the World Meteorological Organization. On the other hand, high spatial resolution (0.5° × 0.5°) gridded monthly data CRU TS 3.1 were acquired from the Climatic Research Unit, University of East Anglia, for the period 1901–2009. The two datasets were compared by means of trends and variability, while the influence of the North Atlantic Oscillation (NAO) in the Mediterranean precipitation was examined. In the process, the climatic changes in the precipitation regime between the period 1961–1990 (reference period) and the period 2071–2100 (future climate) were presented using climate model simulations (RACMO2.1/KNMI). The future climate projections were based on SRES A1B. The findings of the analysis showed that statistically significant (95% confidence level) negative trends of the annual precipitation totals exist in the majority of Mediterranean regions during the period 1901–2009, with an exception of northern Africa, southern Italy and western Iberian peninsula, where slight positive trends (not statistically significant at 95% CL) appear. Concerning the annual number of rain days, a pronounced decrease of 20 %, statistically significant (95% confidence level), appears in representative meteorological stations of east Mediterranean, while the trends are insignificant for west and central Mediterranean. Additionally, NAO index was found to be anticorrelated with the precipitation totals and the number of rain days mainly in Spain, southern France, Italy and Greece. These correlations are higher within the rain season (October–March) than the entire year. Based on the results of regional climate model RACMO2.1/KNMI, precipitation is very likely to decrease almost 20% in the period 2071–2100 compared to 1961–1990, under SRES A1B.

scholarly journals Global exposure to flooding from the new CMIP6 climate model projections

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yukiko Hirabayashi ◽  
Masahiro Tanoue ◽  
Orie Sasaki ◽  
Xudong Zhou ◽  
Dai Yamazaki
Keyword(s):  
Spatial Patterns ◽  
Flood Risk ◽  
Climate Models ◽  
Climate Model ◽  
Model Development ◽  
Coupled Model ◽  
Model Intercomparison ◽  
Internal Climate Variability ◽  
Intercomparison Project ◽  
New Generation

AbstractEstimates of future flood risk rely on projections from climate models. The relatively few climate models used to analyze future flood risk cannot easily quantify of their associated uncertainties. In this study, we demonstrated that the projected fluvial flood changes estimated by a new generation of climate models, the collectively known as Coupled Model Intercomparison Project Phase 6 (CMIP6), are similar to those estimated by CMIP5. The spatial patterns of the multi-model median signs of change (+ or −) were also very consistent, implying greater confidence in the projections. The model spread changed little over the course of model development, suggesting irreducibility of the model spread due to internal climate variability, and the consistent projections of models from the same institute suggest the potential to reduce uncertainties caused by model differences. Potential global exposure to flooding is projected to be proportional to the degree of warming, and a greater threat is anticipated as populations increase, demonstrating the need for immediate decisions.

scholarly journals Overview of the Coupled Model Intercomparison Project Phase 6 (CMIP6) experimental design and organisation

2015 ◽  
Vol 8 (12) ◽  
pp. 10539-10583 ◽  
Author(s):  
V. Eyring ◽  
S. Bony ◽  
G. A. Meehl ◽  
C. Senior ◽  
B. Stevens ◽  
...  
Keyword(s):  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Coupled Model ◽  
Research Programme ◽  
Future Climate ◽  
Model Intercomparison ◽  
Historical Simulation ◽  
Intercomparison Project

Abstract. By coordinating the design and distribution of global climate model simulations of the past, current and future climate, the Coupled Model Intercomparison Project (CMIP) has become one of the foundational elements of climate science. However, the need to address an ever-expanding range of scientific questions arising from more and more research communities has made it necessary to revise the organization of CMIP. After a long and wide community consultation, a new and more federated structure has been put in place. It consists of three major elements: (1) a handful of common experiments, the DECK (Diagnostic, Evaluation and Characterization of Klima experiments) and the CMIP Historical Simulation (1850–near-present) that will maintain continuity and help document basic characteristics of models across different phases of CMIP, (2) common standards, coordination, infrastructure and documentation that will facilitate the distribution of model outputs and the characterization of the model ensemble, and (3) an ensemble of CMIP-Endorsed Model Intercomparison Projects (MIPs) that will be specific to a particular phase of CMIP (now CMIP6) and that will build on the DECK and the CMIP Historical Simulation to address a large range of specific questions and fill the scientific gaps of the previous CMIP phases. The DECK and CMIP Historical Simulation, together with the use of CMIP data standards, will be the entry cards for models participating in CMIP. The participation in the CMIP6-Endorsed MIPs will be at the discretion of the modelling groups, and will depend on scientific interests and priorities. With the Grand Science Challenges of the World Climate Research Programme (WCRP) as its scientific backdrop, CMIP6 will address three broad questions: (i) how does the Earth system respond to forcing?, (ii) what are the origins and consequences of systematic model biases?, and (iii) how can we assess future climate changes given climate variability, predictability and uncertainties in scenarios? This CMIP6 overview paper presents the background and rationale for the new structure of CMIP, provides a detailed description of the DECK and the CMIP6 Historical Simulation, and includes a brief introduction to the 21 CMIP6-Endorsed MIPs.

scholarly journals Uncertainties in projected surface mass balance over the polar ice sheets from downscaled EC-Earth models

2021 ◽  
Author(s):  
Fredrik Boberg ◽  
Ruth Mottram ◽  
Nicolaj Hansen ◽  
Shuting Yang ◽  
Peter L. Langen
Keyword(s):  
Mass Balance ◽  
Climate Model ◽  
Global Climate ◽  
Ice Sheet ◽  
Coupled Model ◽  
Surface Mass Balance ◽  
Model Intercomparison ◽  
Surface Mass ◽  
Intercomparison Project ◽  
The Mean

Abstract. The future rates of ice sheet melt in Greenland and Antarctica are an important factor when making estimates of the likely rate of sea level rise. Global climate models that took part in the fifth Coupled Model Intercomparison Project (CMIP5) have generally been unable to replicate observed rates of ice sheet melt. With the advent of the sixth Coupled Model Intercomparison Project (CMIP6), with a general increase in the equilibrium climate sensitivity, we here compare two versions of the global climate model EC-Earth using the regional climate model HIRHAM5 downscaling EC-Earth for Greenland and Antarctica. One version (v2) of EC-Earth is taken from CMIP5 for the high-emissions Representative Concentration Pathways (RCP8.5) scenario and the other (v3) from CMIP6 for the comparable high-emissions Shared Socioeconomic Pathways (SSP5-8.5) scenario). For Greenland, we downscale the two versions of EC-Earth for the historical period 1991–2010 and for the scenario period 2081–2100. For Antarctica, the periods are 1971–2000 and 2071–2100, respectively. For the Greenland Ice Sheet, we find that the mean change in temperature is 5.9 °C when downscaling EC-Earth v2 and 6.8 °C when downscaling EC-Earth v3. Corresponding values for Antarctica are 4.1 °C for v2 and 4.8 °C for v3. The mean change in surface mass balance at the end of the century under these high emissions scenarios is found to be −210 Gt yr−1 (v2) and −1150 Gt yr−1 (v3) for Greenland and 420 Gt yr−1 (v2) and 80 Gt yr−1 (v3) for Antarctica. These distinct differences in temperature change and particularly surface mass balance change are a result of the higher equilibrium climate sensitivity in EC-Earth v3 (4.3 K) compared with 3.3 K in EC-Earth v2 and the differences in greenhouse gas concentrations between the RCP8.5 and the SSP5-8.5 scenarios.

scholarly journals Evaluation of 22 Precipitation and 23 Soil Moisture Products over a Semiarid Area in Southeastern Arizona*

2015 ◽  
Vol 17 (1) ◽  
pp. 211-230 ◽  
Author(s):  
Susan Stillman ◽  
Xubin Zeng ◽  
Michael G. Bosilovich
Keyword(s):  
Soil Moisture ◽  
Coupled Model ◽  
Cold Season ◽  
Annual Precipitation ◽  
Product Categories ◽  
Scale Mismatch ◽  
Intercomparison Project ◽  
Land Data Assimilation ◽  
Mean Square Difference

Abstract Precipitation and soil moisture are rigorously measured or estimated from a variety of sources. Here, 22 precipitation and 23 soil moisture products are evaluated against long-term daily observed precipitation (Pobs) and July–September daily observationally constrained soil moisture (SM) datasets over a densely monitored 150 km2 watershed in southeastern Arizona, United States. Gauge–radar precipitation products perform best, followed by reanalysis and satellite products, and the median correlations of annual precipitation from these three categories with Pobs are 0.83, 0.68, and 0.46, respectively. Precipitation results from phase 5 of the Coupled Model Intercomparison Project (CMIP5) are the worst, including an overestimate of cold season precipitation and a lack of significant correlation of annual precipitation with Pobs from all (except one) models. Satellite soil moisture products perform best, followed by land data assimilation systems and reanalyses, and the CMIP5 results are the worst. For instance, the median unbiased root-mean-square difference (RMSD) values of July–September soil moisture compared with SM are 0.0070, 0.011, 0.014, and 0.029 m3 m−3 for these four product categories, respectively. All 17 (except 3) precipitation [17 (except 2) soil moisture] products with at least 20 years of data agree with Pobs (SM) without significant trends. The uncertainties associated with the scale mismatch between Pobs and coarser-resolution products are addressed using two 4-km gauge–radar precipitation products, and their impact on the results presented in this study is overall small. These results identify strengths and weaknesses of each product for future improvement; they also emphasize the importance of using multiple gauge–radar and satellite products along with their uncertainties in evaluating reanalyses and models.

scholarly journals LICOM Model Datasets for the CMIP6 Ocean Model Intercomparison Project

2020 ◽  
Vol 37 (3) ◽  
pp. 239-249 ◽  
Author(s):  
Pengfei Lin ◽  
Zhipeng Yu ◽  
Hailong Liu ◽  
Yongqiang Yu ◽  
Yiwen Li ◽  
...  
Keyword(s):  
Coupled Model ◽  
Reanalysis Data ◽  
Ocean Model ◽  
Model Intercomparison ◽  
Surface Data ◽  
Intercomparison Project ◽  
System Bias ◽  
The Mean ◽  
Fully Coupled

Abstract The datasets of two Ocean Model Intercomparison Project (OMIP) simulation experiments from the LASG/IAP Climate Ocean Model, version 3 (LICOM3), forced by two different sets of atmospheric surface data, are described in this paper. The experiment forced by CORE-II (Co-ordinated Ocean–Ice Reference Experiments, Phase II) data (1948–2009) is called OMIP1, and that forced by JRA55-do (surface dataset for driving ocean–sea-ice models based on Japanese 55-year atmospheric reanalysis) data (1958–2018) is called OMIP2. First, the improvement of LICOM from CMIP5 to CMIP6 and the configurations of the two experiments are described. Second, the basic performances of the two experiments are validated using the climatological-mean and interannual time scales from observation. We find that the mean states, interannual variabilities, and long-term linear trends can be reproduced well by the two experiments. The differences between the two datasets are also discussed. Finally, the usage of these data is described. These datasets are helpful toward understanding the origin system bias of the fully coupled model.

scholarly journals The Geoengineering Model Intercomparison Project Phase 6 (GeoMIP6): simulation design and preliminary results

2015 ◽  
Vol 8 (10) ◽  
pp. 3379-3392 ◽  
Author(s):  
B. Kravitz ◽  
A. Robock ◽  
S. Tilmes ◽  
O. Boucher ◽  
J. M. English ◽  
...  
Keyword(s):  
Climate Model ◽  
Coupled Model ◽  
Longwave Radiation ◽  
Open Science ◽  
Model Intercomparison ◽  
Simulation Design ◽  
Preliminary Results ◽  
Climate Model Experiment ◽  
Intercomparison Project ◽  
New Feature

Abstract. We present a suite of new climate model experiment designs for the Geoengineering Model Intercomparison Project (GeoMIP). This set of experiments, named GeoMIP6 (to be consistent with the Coupled Model Intercomparison Project Phase 6), builds on the previous GeoMIP project simulations, and has been expanded to address several further important topics, including key uncertainties in extreme events, the use of geoengineering as part of a portfolio of responses to climate change, and the relatively new idea of cirrus cloud thinning to allow more longwave radiation to escape to space. We discuss experiment designs, as well as the rationale for those designs, showing preliminary results from individual models when available. We also introduce a new feature, called the GeoMIP Testbed, which provides a platform for simulations that will be performed with a few models and subsequently assessed to determine whether the proposed experiment designs will be adopted as core (Tier 1) GeoMIP experiments. This is meant to encourage various stakeholders to propose new targeted experiments that address their key open science questions, with the goal of making GeoMIP more relevant to a broader set of communities.

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