scholarly journals A study of AR, TS, and MCS associated precipitation and extreme precipitation in present and warmer climates

2021 ◽  
pp. 1-49
Author(s):  
Ming Zhao

AbstractAtmospheric rivers (AR), tropical storms (TS) and mesoscale convective systems (MCS) are important weather phenomena which often threaten society through heavy precipitation and strong winds. Despite their potentially vital role in global and regional hydrological cycles, their contributions to long-term mean and extreme precipitation have not been systematically explored at the global scale. Using observational and reanalysis data, and NOAA’s Geophysical Fluid Dynamics Laboratory’s new high-resolution global climate model, we quantify that despite their occasional (13%) occurrence globally, AR, TS, and MCS days together account for ~55% of global mean precipitation and ~75% of extreme precipitation with daily rates exceeding its local 99th percentile. The model reproduces well the observed percentage of mean and extreme precipitation associated with AR, TS and MCS days. In an idealized global warming simulation with a homogeneous 4K SST increase, the modeled changes in global mean and regional distribution of precipitation correspond well with changes in AR/TS/MCS precipitation. Globally, the frequency of AR days increases and migrates towards higher latitudes while the frequency of TS days increases over the central Pacific and part of the South Indian Ocean with a decrease elsewhere. The frequency of MCS days tends to increase over parts of the equatorial western and eastern Pacific warm pools and high latitudes and decreases over most part of the tropics and subtropics. The AR/TS/MCS mean precipitation intensity increases by ~5%/K due primarily to precipitation increases in the top 25% of AR/TS/MCS days with the heaviest precipitation, which are dominated by the thermodynamic component with the dynamic and microphysical components playing a secondary role.

2018 ◽  
Vol 32 (1) ◽  
pp. 195-212 ◽  
Author(s):  
Sicheng He ◽  
Jing Yang ◽  
Qing Bao ◽  
Lei Wang ◽  
Bin Wang

AbstractRealistic reproduction of historical extreme precipitation has been challenging for both reanalysis and global climate model (GCM) simulations. This work assessed the fidelities of the combined gridded observational datasets, reanalysis datasets, and GCMs [CMIP5 and the Chinese Academy of Sciences Flexible Global Ocean–Atmospheric Land System Model–Finite-Volume Atmospheric Model, version 2 (FGOALS-f2)] in representing extreme precipitation over East China. The assessment used 552 stations’ rain gauge data as ground truth and focused on the probability distribution function of daily precipitation and spatial structure of extreme precipitation days. The TRMM observation displays similar rainfall intensity–frequency distributions as the stations. However, three combined gridded observational datasets, four reanalysis datasets, and most of the CMIP5 models cannot capture extreme precipitation exceeding 150 mm day−1, and all underestimate extreme precipitation frequency. The observed spatial distribution of extreme precipitation exhibits two maximum centers, located over the lower-middle reach of Yangtze River basin and the deep South China region, respectively. Combined gridded observations and JRA-55 capture these two centers, but ERA-Interim, MERRA, and CFSR and almost all CMIP5 models fail to capture them. The percentage of extreme rainfall in the total rainfall amount is generally underestimated by 25%–75% in all CMIP5 models. Higher-resolution models tend to have better performance, and physical parameterization may be crucial for simulating correct extreme precipitation. The performances are significantly improved in the newly released FGOALS-f2 as a result of increased resolution and a more realistic simulation of moisture and heating profiles. This work pinpoints the common biases in the combined gridded observational datasets and reanalysis datasets and helps to improve models’ simulation of extreme precipitation, which is critically important for reliable projection of future changes in extreme precipitation.


2012 ◽  
Vol 25 (2) ◽  
pp. 527-542 ◽  
Author(s):  
Christopher B. Skinner ◽  
Moetasim Ashfaq ◽  
Noah S. Diffenbaugh

Abstract The persistence of extended drought events throughout West Africa during the twentieth century has motivated a substantial effort to understand the mechanisms driving African climate variability as well as the possible response to elevated greenhouse gas (GHG) forcing. An ensemble of global climate model experiments is used to examine the relative roles of future direct atmospheric radiative forcing and SST forcing in shaping potential future changes in boreal summer precipitation over West Africa. The authors find that projected increases in precipitation throughout the western Sahel result primarily from direct atmospheric radiative forcing. The changes in atmospheric forcing generate a slight northward displacement and weakening of the African easterly jet (AEJ), a strengthening of westward monsoon flow onto West Africa, and an intensification of the tropical easterly jet (TEJ). Alternatively, the projected decreases in precipitation over much of the Guinea Coast region are caused by SST changes induced by the atmospheric radiative forcing. The changes in SSTs generate a weakening of the monsoon westerlies and the TEJ as well as a decrease in low-level convergence and resultant rising air throughout the midlevels of the troposphere. Experiments suggest a potential shift in the regional moisture balance of West Africa should global radiative forcing continue to increase, highlighting the importance of climate system feedbacks in shaping the response of regional-scale climate to global-scale changes in radiative forcing.


2013 ◽  
Vol 14 (4) ◽  
pp. 1212-1227 ◽  
Author(s):  
Sho Kawazoe ◽  
William J. Gutowski

Abstract The authors analyze the ability of the North American Regional Climate Change Assessment Program's ensemble of climate models to simulate very heavy daily precipitation and its supporting processes, comparing simulations that used observation-based boundary conditions with observations. The analysis includes regional climate models and a time-slice global climate model that all used approximately half-degree resolution. Analysis focuses on an upper Mississippi River region for winter (December–February), when it is assumed that resolved synoptic circulation governs precipitation. All models generally reproduce the precipitation-versus-intensity spectrum seen in observations well, with a small tendency toward producing overly strong precipitation at high-intensity thresholds, such as the 95th, 99th, and 99.5th percentiles. Further analysis focuses on precipitation events exceeding the 99.5th percentile that occur simultaneously at several points in the region, yielding so-called “widespread events.” Examination of additional fields shows that the models produce very heavy precipitation events for the same physical conditions seen in the observations.


2017 ◽  
Author(s):  
Lamprini V. Papadimitriou ◽  
Aristeidis G. Koutroulis ◽  
Manolis G. Grillakis ◽  
Ioannis K. Tsanis

Abstract. Global Climate Model (GCM) outputs feature systematic biases that render them unsuitable for direct use by impact models, especially for hydrological studies. To deal with this issue many bias correction techniques have been developed to adjust the modelled variables against observations, focusing mainly on precipitation and temperature. However most state-of-art hydrological models require more forcing variables, additionally to precipitation and temperature, such as radiation, humidity, air pressure and wind speed. The biases in these additional variables can hinder hydrological simulations, but the effect of the bias of each variable is unexplored. Here we examine the effect of GCM biases on historical runoff simulations for each forcing variable individually, using the land surface model JULES set up at the global scale. Based on the quantified effect, we assess which variables should be included in bias correction procedures. To this end, a partial correction bias assessment experiment is conducted, to test the effect of the biases of six climate variables from a set of three GCMs. The effect of the bias of each climate variable individually is quantified by comparing the changes in simulated runoff that correspond to the bias of each tested variable. A methodology for the classification of the effect of biases in four Effect Categories (ECs), based on the magnitude and sensitivity of runoff changes, is developed and applied. Our results show that, while globally the largest changes in modelled runoff are caused by precipitation and temperature biases, there are regions where runoff is substantially affected by and/or more sensitive to radiation and humidity. Global maps of bias ECs reveal the regions mostly affected by the bias of each variable. Based on our findings, for global scale applications, bias correction of radiation and humidity, in addition to that of precipitation and temperature, is advised. Finer spatial scale information is also provided, to suggest bias correction of variables beyond precipitation and temperature for regional studies.


Author(s):  
Michael Wehner ◽  
Jiwoo Lee ◽  
Mark Risser ◽  
Paul Ullrich ◽  
Peter Gleckler ◽  
...  

We examine the resolution dependence of errors in extreme sub-daily precipitation in available high-resolution climate models. We find that simulated extreme precipitation increases as horizontal resolution increases but that appropriately constructed model skill metrics do not significantly change. We find little evidence that simulated extreme winter or summer storm processes significantly improve with the resolution because the model performance changes identified are consistent with expectations from scale dependence arguments alone. We also discuss the implications of these scale-dependent limitations on the interpretation of simulated extreme precipitation. This article is part of a discussion meeting issue ‘Intensification of short-duration rainfall extremes and implications for flash flood risks’.


2009 ◽  
Vol 22 (9) ◽  
pp. 2276-2301 ◽  
Author(s):  
Lennart Bengtsson ◽  
Kevin I. Hodges ◽  
Noel Keenlyside

Abstract Extratropical cyclones and how they may change in a warmer climate have been investigated in detail with a high-resolution version of the ECHAM5 global climate model. A spectral resolution of T213 (63 km) is used for two 32-yr periods at the end of the twentieth and twenty-first centuries and integrated for the Intergovernmental Panel on Climate Change (IPCC) A1B scenario. Extremes of pressure, vorticity, wind, and precipitation associated with the cyclones are investigated and compared with a lower-resolution simulation. Comparison with observations of extreme wind speeds indicates that the model reproduces realistic values. This study also investigates the ability of the model to simulate extratropical cyclones by computing composites of intense storms and contrasting them with the same composites from the 40-yr ECMWF Re-Analysis (ERA-40). Composites of the time evolution of intense cyclones are reproduced with great fidelity; in particular the evolution of central surface pressure is almost exactly replicated, but vorticity, maximum wind speed, and precipitation are higher in the model. Spatial composites also show that the distributions of pressure, winds, and precipitation at different stages of the cyclone life cycle compare well with those from ERA-40, as does the vertical structure. For the twenty-first century, changes in the distribution of storms are very similar to those of previous study. There is a small reduction in the number of cyclones but no significant changes in the extremes of wind and vorticity in both hemispheres. There are larger regional changes in agreement with previous studies. The largest changes are in the total precipitation, where a significant increase is seen. Cumulative precipitation along the tracks of the cyclones increases by some 11% per track, or about twice the increase in global precipitation, while the extreme precipitation is close to the globally averaged increase in column water vapor (some 27%). Regionally, changes in extreme precipitation are even higher because of changes in the storm tracks.


2017 ◽  
Vol 21 (9) ◽  
pp. 4379-4401 ◽  
Author(s):  
Lamprini V. Papadimitriou ◽  
Aristeidis G. Koutroulis ◽  
Manolis G. Grillakis ◽  
Ioannis K. Tsanis

Abstract. Global climate model (GCM) outputs feature systematic biases that render them unsuitable for direct use by impact models, especially for hydrological studies. To deal with this issue, many bias correction techniques have been developed to adjust the modelled variables against observations, focusing mainly on precipitation and temperature. However, most state-of-the-art hydrological models require more forcing variables, in addition to precipitation and temperature, such as radiation, humidity, air pressure, and wind speed. The biases in these additional variables can hinder hydrological simulations, but the effect of the bias of each variable is unexplored. Here we examine the effect of GCM biases on historical runoff simulations for each forcing variable individually, using the JULES land surface model set up at the global scale. Based on the quantified effect, we assess which variables should be included in bias correction procedures. To this end, a partial correction bias assessment experiment is conducted, to test the effect of the biases of six climate variables from a set of three GCMs. The effect of the bias of each climate variable individually is quantified by comparing the changes in simulated runoff that correspond to the bias of each tested variable. A methodology for the classification of the effect of biases in four effect categories (ECs), based on the magnitude and sensitivity of runoff changes, is developed and applied. Our results show that, while globally the largest changes in modelled runoff are caused by precipitation and temperature biases, there are regions where runoff is substantially affected by and/or more sensitive to radiation and humidity. Global maps of bias ECs reveal the regions mostly affected by the bias of each variable. Based on our findings, for global-scale applications, bias correction of radiation and humidity, in addition to that of precipitation and temperature, is advised. Finer spatial-scale information is also provided, to suggest bias correction of variables beyond precipitation and temperature for regional studies.


2009 ◽  
Vol 66 (9) ◽  
pp. 2796-2811 ◽  
Author(s):  
Hongyan Zhu ◽  
Harry Hendon ◽  
Christian Jakob

Abstract The behavior of convection and the Madden–Julian oscillation (MJO) is compared in two simulations from the same global climate model but with two very different treatments of convection: one has a conventional parameterization of moist processes and the other replaces the parameterization with a two-dimensional cloud-resolving model, the so-called superparameterization. The different behavior of local convection and the MJO in the two model simulations reveals that the accurate representation of the following characteristics in the modes of convection might contribute to the improvement of the MJO simulations: (i) precipitation should be an exponentially increasing function of the column saturation fraction, (ii) heavy precipitation should be associated with a stratiform diabatic heating profile, and (iii) there should be a positive relationship between precipitation and surface latent heat flux.


2020 ◽  
Author(s):  
Len Shaffrey ◽  
Helene Bresson ◽  
Kevin Hodges ◽  
Giuseppe Zappa

<p>Polar lows are small, intense cyclones that form at high latitudes during winter. Their high wind speeds and heavy precipitation can have substantial impacts on shipping, coastal communities and infrastructure. However, climate models typically have low resolutions and therefore poorly simulate Polar Lows. This reduces the confidence that can be placed in future projections of extreme high latitude weather and associated risks.</p><p>In this study, Polar Lows are assessed for the first time in a high-resolution (25 km) global climate atmosphere-only model, N512 HadGEM3-GA3, for both present-day and future RCP 8.5 climate scenarios. Using an objective tracking algorithm, the representation of Polar Lows in the N512 HadGEM3-GA3 present-day simulation is found to agree reasonably well the NCEP-CFS reanalysis. RCP8.5 scenario conditions are generated by adding SST changes between 1990-2010 and 2090-2110 from the RCP8.5 experiments with the HadGEM2-ES model to observed SSTs from the present-day climate. In the RCP8.5 N512 HadGEM-GA3 simulations, the number of Northern Hemisphere Polar Lows are projected to substantially decrease (by over 60%) by the end of the 21st century, which is largely due to an increase in atmospheric static stability. However, new regions of Polar Low activity along the northern Russian coastlines are found where the Arctic sea ice is projected to retreat.</p>


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