Simulation of Northeast U.S. Extreme Precipitation and Its Associated Circulation by CMIP5 Models

2020 ◽  
Vol 33 (22) ◽  
pp. 9817-9834
Author(s):  
Laurie Agel ◽  
Mathew Barlow ◽  
Joseph Polonia ◽  
David Coe

AbstractHistorical simulations from 14 models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5) are evaluated for their ability to reproduce observed precipitation in the northeastern United States and its associated circulation, with particular emphasis on extreme (top 1%) precipitation. The models are compared to observations in terms of the spatial variations of extreme precipitation, seasonal cycles of precipitation and extreme precipitation frequency and intensity, and extreme precipitation circulation regimes. The circulation regimes are identified using k-means clustering of 500-hPa geopotential heights on extreme precipitation days, in both observations and in the models. While all models capture an observed northwest-to-southeast gradient of precipitation intensity (reflected in the top 1% threshold), there are substantial differences from observations in the magnitude of the gradient. These differences tend to be more substantial for lower-resolution models. However, regardless of resolution, and despite a bias toward too-frequent precipitation, many of the models capture the seasonality of observed daily precipitation intensity, and the approximate magnitude and seasonality of observed extreme precipitation intensity. Many of the simulated extreme precipitation circulation patterns are visually similar to the set of observed patterns. However, the location and magnitude of specific troughs and ridges within the patterns, as well as the seasonality of the patterns, may differ substantially from the observed corresponding patterns. A series of metrics is developed based on the observed regional characteristics to facilitate comparison between models.

2020 ◽  
Vol 33 (22) ◽  
pp. 9835-9848 ◽  
Author(s):  
Laurie Agel ◽  
Mathew Barlow

AbstractSixteen historical simulations (1950–2014) from phase 6 of the Coupled Model Intercomparison Project (CMIP6) are compared to Northeast U.S. observed precipitation and extreme precipitation–related synoptic circulation. A set of metrics based on the regional climate is used to assess how realistically the models simulate the observed distribution and seasonality of extreme precipitation, as well as the synoptic patterns associated with extreme precipitation. These patterns are determined by k-means typing of 500-hPa geopotential heights on extreme precipitation days (top 1% of days with precipitation). The metrics are formulated to evaluate the models’ extreme precipitation spatial variations, seasonal frequency, and intensity; and for circulation, the fit to observed patterns, pattern seasonality, and pattern location of extreme precipitation. Based on the metrics, the models vary considerably in their ability to simulate different aspects of regional precipitation, and a realistic simulation of the seasonality and distribution of precipitation does not necessarily correspond to a realistic simulation of the circulation patterns (reflecting the underlying dynamics of the precipitation), and vice versa. This highlights the importance of assessing both precipitation and its associated circulation. While the models vary in their ability to reproduce observed results, in general the higher-resolution models score higher in terms of the metrics. Most models produce more frequent precipitation than that for observations, but capture the seasonality of precipitation intensity well, and capture at least several of the key characteristics of extreme precipitation–related circulation. These results do not appear to reflect a substantial improvement over a similar analysis of selected CMIP5 models.


2017 ◽  
Vol 56 (9) ◽  
pp. 2421-2439 ◽  
Author(s):  
Christopher M. Castellano ◽  
Arthur T. DeGaetano

AbstractAn approach for downscaling daily precipitation extremes using historical analogs is applied to simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5). The method employs a multistep procedure in which the occurrence of extreme precipitation on a given target day is determined on the basis of the probability of extreme precipitation on that day’s closest historical analogs. If extreme precipitation is expected, daily precipitation observations associated with the historical analogs are used to approximate precipitation amounts on the target day. By applying the analog method to historical simulations, the ability of the CMIP5 models to simulate synoptic weather patterns associated with extreme precipitation is assessed. Differences between downscaled and observed precipitation extremes are investigated by comparing the precipitation frequency distributions for a subset of rarely selected extreme analog days with those for all observed days with extreme precipitation. A supplemental composite analysis of the synoptic weather patterns on these rarely selected analog days is utilized to elucidate the meteorological factors that contribute to such discrepancies. Overall, the analog method as applied to CMIP5 simulations yields realistic estimates of historical precipitation extremes, with return-period precipitation biases that are comparable in magnitude to those obtained from dynamically downscaled simulations. The analysis of rarely selected analog days reveals that precipitation amounts on these days are generally larger than precipitation amounts on all days with extreme precipitation, leading to an underestimation of return-period precipitation amounts at many stations. Furthermore, the synoptic composite analysis reveals that tropical cyclones are a common feature on these rarely selected analog days.


2016 ◽  
Vol 17 (11) ◽  
pp. 2785-2797 ◽  
Author(s):  
Yanjuan Wu ◽  
Shuang-Ye Wu ◽  
Jiahong Wen ◽  
Felipe Tagle ◽  
Ming Xu ◽  
...  

Abstract In this study, the potential future changes of mean and extreme precipitation in the middle and lower Yangtze River basin (MLYRB), eastern China, are assessed using the models of phase 5 of the Coupled Model Intercomparison Project (CMIP5). Historical model simulations are first compared with observations in order to evaluate model performance. In general, the models simulate the precipitation mean and frequency better than the precipitation intensity and extremes, but still have difficulty capturing precipitation patterns over complex terrains. They tend to overestimate precipitation mean, frequency, and intensity while underestimating the extremes. After correcting for model biases, the spatial variation of mean precipitation projected by the multimodel ensemble mean (MME) is improved, so the MME after the bias correction is used to project changes for the years 2021–50 and 2071–2100 relative to 1971–2000 under two emission scenarios: RCP4.5 and RCP8.5. Results show that with global warming, precipitation will become less frequent but more intense over the MLYRB. Relative changes in extremes generally exceed those in mean precipitation. Moreover, increased precipitation extremes are also expected even in places where mean precipitation is projected to decrease in 2021–50. The overall increase in extreme precipitation could potentially lead to more frequent floods in this already flood-prone region.


2013 ◽  
Vol 26 (17) ◽  
pp. 6257-6286 ◽  
Author(s):  
Leila M. V. Carvalho ◽  
Charles Jones

Abstract Global warming has been linked to systematic changes in North and South America's climates and may severely impact the North American monsoon system (NAMS) and South American monsoon system (SAMS). This study examines interannual-to-decadal variations and changes in the low-troposphere (850 hPa) temperature (T850) and specific humidity (Q850) and relationships with daily precipitation over the tropical Americas using the NCEP–NCAR reanalysis, the Climate Forecast System Reanalysis (CFSR), and phase 5 of the Coupled Model Intercomparison Project (CMIP5) simulations for two scenarios: “historic” and high-emission representative concentration pathway 8.5 (RCP8.5). Trends in the magnitude and area of the 85th percentiles were distinctly examined over North America (NA) and South America (SA) during the peak of the respective monsoon season. The historic simulations (1951–2005) and the two reanalyses agree well and indicate that significant warming has occurred over tropical SA with a remarkable increase in the area and magnitude of the 85th percentile in the last decade (1996–2005). The RCP8.5 CMIP5 ensemble mean projects an increase in the T850 85th percentile of about 2.5°C (2.8°C) by 2050 and 4.8°C (5.5°C) over SA (NA) by 2095 relative to 1955. The area of SA (NA) with T850 ≥ the 85th percentile is projected to increase from ~10% (15%) in 1955 to ~58% (~33%) by 2050 and ~80% (~50%) by 2095. The respective increase in the 85th percentile of Q850 is about 3 g kg−1 over SAMS and NAMS by 2095. CMIP5 models project variable changes in daily precipitation over the tropical Americas. The most consistent is increased rainfall in the intertropical convergence zone in December–February (DJF) and June–August (JJA) and decreased precipitation over NAMS in JJA.


2021 ◽  
Vol 7 (5) ◽  
pp. 1113-1122
Author(s):  
Bo Chen ◽  
Shi-jun Xu ◽  
Xin-ping Zhang ◽  
Yi Xie

Using the methods of literature review, regression analysis and moving average, this paper selects the daily precipitation of Changsha and Chengde from 1951 to 1986 as samples, and analyzes the average precipitation, precipitation frequency, precipitation intensity, extreme precipitation time and other indicators of Changsha and Chengde from the perspective of interannual and seasonal changes Trends. The researches show that: the average precipitation of Changsha in the 36 years is 1151.2mm, spring is the wet season, autumn and winter are the dry seasons, and the maximum average precipitation is in spring; the average annual precipitation, precipitation frequency in spring, summer and winter, annual precipitation frequency, annual precipitation intensity and extreme precipitation events show a decreasing trend. The average annual precipitation of Chengde city is 454.1 mm, wet season in summer and dry season in spring, autumn and winter; the average annual precipitation, precipitation in four seasons, annual precipitation frequency, precipitation frequency in spring, autumn and winter, annual precipitation intensity and extreme precipitation events show a decreasing trend, while the precipitation frequency in summer shows an increasing trend. The study of regional climate change based on the time series data of this stage is of great significance to comprehensively understand the law of regional climate change and predict the future trend of climate change.


2021 ◽  
pp. 1-61
Author(s):  
Jesse Norris ◽  
Alex Hall ◽  
J. David Neelin ◽  
Chad W. Thackeray ◽  
Di Chen

AbstractDaily and sub-daily precipitation extremes in historical Coupled-Model-Intercomparison-Project-Phase-6 (CMIP6) simulations are evaluated against satellite-based observational estimates. Extremes are defined as the precipitation amount exceeded every x years, ranging from 0.01–10, encompassing the rarest events that are detectable in the observational record without noisy results. With increasing temporal resolution there is an increased discrepancy between models and observations: for daily extremes the multi-model median underestimates the highest percentiles by about a third, and for 3-hourly extremes by about 75% in the tropics. The novelty of the current study is that, to understand the model spread, we evaluate the 3-D structure of the atmosphere when extremes occur. In midlatitudes, where extremes are simulated predominantly explicitly, the intuitive relationship exists whereby higher-resolution models produce larger extremes (r=–0.49), via greater vertical velocity. In the tropics, the convective fraction (the fraction of precipitation simulated directly from the convective scheme) is more relevant. For models below 60% convective fraction, precipitation amount decreases with convective fraction (r=–0.63), but above 75% convective fraction, this relationship breaks down. In the lower-convective-fraction models, there is more moisture in the lower troposphere, closer to saturation. In the higher-convective-fraction models, there is deeper convection and higher cloud tops, which appears to be more physical. Thus, the low-convective models are mostly closer to the observations of extreme precipitation in the tropics, but likely for the wrong reasons. These inter-model differences in the environment in which extremes are simulated hold clues into how parameterizations could be modified in general circulation models to produce more credible 21st-Century projections.


2015 ◽  
Vol 56 (70) ◽  
pp. 89-97 ◽  
Author(s):  
Marion Réveillet ◽  
Antoine Rabatel ◽  
Fabien Gillet-Chaulet ◽  
Alvaro Soruco

AbstractBolivian glaciers are an essential source of fresh water for the Altiplano, and any changes they may undergo in the near future due to ongoing climate change are of particular concern. Glaciar Zongo, Bolivia, located near the administrative capital La Paz, has been extensively monitored by the GLACIOCLIM observatory in the last two decades. Here we model the glacier dynamics using the 3-D full-Stokes model Elmer/Ice. The model was calibrated and validated over a recent period (1997–2010) using four independent datasets: available observations of surface velocities and surface mass balance were used for calibration, and changes in surface elevation and retreat of the glacier front were used for validation. Over the validation period, model outputs are in good agreement with observations (differences less than a small percentage). The future surface mass balance is assumed to depend on the equilibrium-line altitude (ELA) and temperature changes through the sensitivity of ELA to temperature. The model was then forced for the 21st century using temperature changes projected by nine Coupled Model Intercomparison Project phase 5 (CMIP5) models. Here we give results for three different representative concentration pathways (RCPs). The intermediate scenario RCP6.0 led to 69 ± 7% volume loss by 2100, while the two extreme scenarios, RCP2.6 and RCP8.5, led to 40 ± 7% and 89 ± 4% loss of volume, respectively.


2007 ◽  
Vol 8 (4) ◽  
pp. 678-689 ◽  
Author(s):  
Scott Curtis ◽  
Ahmed Salahuddin ◽  
Robert F. Adler ◽  
George J. Huffman ◽  
Guojun Gu ◽  
...  

Abstract Global monthly and daily precipitation extremes are examined in relation to the El Niño–Southern Oscillation phenomenon. For each month around the annual cycle and in each 2.5° grid block, extremes in the Global Precipitation Climatology Project dataset are defined as the top five (wet) and bottom five (dry) mean rain rates from 1979 to 2004. Over the tropical oceans El Niño–Southern Oscillation events result in a spatial redistribution and overall increase in extremes. Restricting the analysis to land shows that El Niño is associated with an increase in frequency of dry extremes and a decrease in wet extremes resulting in no change in net extreme months. During La Niña an increase in frequency of dry extremes and no change in wet extremes are observed. Thus, because of the juxtaposition of tropical land areas with the ascending branches of the global Walker Circulation, El Niño (La Niña) contributes to generally dry (wet) conditions in these land areas. In addition, daily rain rates computed from the Tropical Rainfall Measuring Mission Multisatellite Precipitation Analysis are used to define extreme precipitation frequency locally as the number of days within a given season that exceeded the 95th percentile of daily rainfall for all seasons (1998–2005). During this period, the significant relationships between extreme daily precipitation frequency and Niño-3.4 in the Tropics are spatially similar to the significant relationships between seasonal mean rainfall and Niño-3.4. However, to address the shortness of the record extreme daily precipitation frequency is also related to seasonal rainfall for the purpose of identifying regions where positive seasonal rainfall anomalies can be used as proxies for extreme events. Finally, the longer (1979–2005) but coarser Global Precipitation Climatology Project analysis is reexamined to pinpoint regions likely to experience an increase in extreme precipitation during El Niño–Southern Oscillation events. Given the significance of El Niño–Southern Oscillation predictions, this information will enable the efficient use of resources in preparing for and mitigating the adverse effects of extreme precipitation.


2007 ◽  
Vol 20 (19) ◽  
pp. 4801-4818 ◽  
Author(s):  
Ying Sun ◽  
Susan Solomon ◽  
Aiguo Dai ◽  
Robert W. Portmann

Abstract Daily precipitation data from climate change simulations using the latest generation of coupled climate system models are analyzed for potential future changes in precipitation characteristics. For the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) B1 (a low projection), A1B (a medium projection), and A2 (a high projection) during the twenty-first century, all the models consistently show a shift toward more intense and extreme precipitation for the globe as a whole and over various regions. For both SRES B1 and A2, most models show decreased daily precipitation frequency and all the models show increased daily precipitation intensity. The multimodel averaged percentage increase in the precipitation intensity (2.0% K−1) is larger than the magnitude of the precipitation frequency decrease (−0.7% K−1). However, the shift in precipitation frequency distribution toward extremes results in large increases in very heavy precipitation events (>50 mm day−1), so that for very heavy precipitation, the percentage increase in frequency is much larger than the increase in intensity (31.2% versus 2.4%). The climate model projected increases in daily precipitation intensity are, however, smaller than that based on simple thermodynamics (∼7% K−1). Multimodel ensemble means show that precipitation amount increases during the twenty-first century over high latitudes, as well as over currently wet regions in low- and midlatitudes more than other regions. This increase mostly results from a combination of increased frequency and intensity. Over the dry regions in the subtropics, the precipitation amount generally declines because of decreases in both frequency and intensity. This indicates that wet regions may get wetter and dry regions may become drier mostly because of a simultaneous increase (decrease) of precipitation frequency and intensity.


2013 ◽  
Vol 6 (5) ◽  
pp. 1705-1714 ◽  
Author(s):  
J. Xu ◽  
L. Zhao ◽  

Abstract. On the basis of the fifth Coupled Model Intercomparison Project (CMIP5) and the climate model simulations covering 1979 through 2005, the temperature trends and their uncertainties have been examined to note the similarities or differences compared to the radiosonde observations, reanalyses and the third Coupled Model Intercomparison Project (CMIP3) simulations. The results show noticeable discrepancies for the estimated temperature trends in the four data groups (radiosonde, reanalysis, CMIP3 and CMIP5), although similarities can be observed. Compared to the CMIP3 model simulations, the simulations in some of the CMIP5 models were improved. The CMIP5 models displayed a negative temperature trend in the stratosphere closer to the strong negative trend seen in the observations. However, the positive tropospheric trend in the tropics is overestimated by the CMIP5 models relative to CMIP3 models. While some of the models produce temperature trend patterns more highly correlated with the observed patterns in CMIP5, the other models (such as CCSM4 and IPSL_CM5A-LR) exhibit the reverse tendency. The CMIP5 temperature trend uncertainty was significantly reduced in most areas, especially in the Arctic and Antarctic stratosphere, compared to the CMIP3 simulations. Similar to the CMIP3, the CMIP5 simulations overestimated the tropospheric warming in the tropics and Southern Hemisphere and underestimated the stratospheric cooling. The crossover point where tropospheric warming changes into stratospheric cooling occurred near 100 hPa in the tropics, which is higher than in the radiosonde and reanalysis data. The result is likely related to the overestimation of convective activity over the tropical areas in both the CMIP3 and CMIP5 models. Generally, for the temperature trend estimates associated with the numerical models including the reanalyses and global climate models, the uncertainty in the stratosphere is much larger than that in the troposphere, and the uncertainty in the Antarctic is the largest. In addition, note that the reanalyses show the largest uncertainty in the lower tropical stratosphere, and the CMIP3 simulations show the largest uncertainty in both the south and north polar regions.


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