The resolution sensitivity of the South Asian monsoon and Indo-Pacific in a global 0.35° AGCM

Johnson, Stephanie J.; Levine, Richard C.; Turner, Andrew G.; Martin, Gill; Woolnough, Steven J.; Schiemann, R.; Mizielinski, Matthew S.; Roberts, Malcolm; Vidale, Pier Luigi; Demory, Marie-Estelle; Strachan, Jane

doi:10.1007/s00382-015-2614-1

Cited by 79 publications

(97 citation statements)

References 73 publications

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Section: Namementioning

confidence: 98%

“…The MetUM-GA6 naming conventions and parameter settings for the different resolutions used in the current study match those described by Johnson et al (2016) for MetUM-GA3. As discussed by Johnson et al (2016), very few parameters in the MetUM are changed with resolution, but there are a few that must be changed to ensure numerical stability. In the MetUM-GA6 simulations analysed in our study, most of the parameter settings for the different resolutions match those shown in Johnson et al (2016;their Table 2).…”

Section: Namementioning

confidence: 98%

“…As discussed by Johnson et al (2016), very few parameters in the MetUM are changed with resolution, but there are a few that must be changed to ensure numerical stability. In the MetUM-GA6 simulations analysed in our study, most of the parameter settings for the different resolutions match those shown in Johnson et al (2016;their Table 2). Note that the inclusion of the ENDGAME dynamical core improved model stability, negating the need for targeted diffusion of moisture.…”

Section: Namementioning

confidence: 99%

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Connecting spatial and temporal scales of tropical precipitation in observations and the MetUM-GA6

2017

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Abstract. This study analyses tropical rainfall variability (on a range of temporal and spatial scales) in a set of parallel Met Office Unified Model (MetUM) simulations at a range of horizontal resolutions, which are compared with two satellitederived rainfall datasets. We focus on the shorter scales, i.e. from the native grid and time step of the model through subdaily to seasonal, since previous studies have paid relatively little attention to sub-daily rainfall variability and how this feeds through to longer scales. We find that the behaviour of the deep convection parametrization in this model on the native grid and time step is largely independent of the grid-box size and time step length over which it operates. There is also little difference in the rainfall variability on larger/longer spatial/temporal scales. Tropical convection in the model on the native grid/time step is spatially and temporally intermittent, producing very large rainfall amounts interspersed with grid boxes/time steps of little or no rain. In contrast, switching off the deep convection parametrization, albeit at an unrealistic resolution for resolving tropical convection, results in very persistent (for limited periods), but very sporadic, rainfall. In both cases, spatial and temporal averaging smoothes out this intermittency. On the ∼ 100 km scale, for oceanic regions, the spectra of 3-hourly and daily mean rainfall in the configurations with parametrized convection agree fairly well with those from satellite-derived rainfall estimates, while at ∼ 10-day timescales the averages are overestimated, indicating a lack of intra-seasonal variability. Over tropical land the results are more varied, but the model often underestimates the daily mean rainfall (partly as a result of a poor diurnal cycle) but still lacks variability on intra-seasonal timescales. Ultimately, such work will shed light on how uncertainties in modelling small-/short-scale processes relate to uncertainty in climate change projections of rainfall distribution and variability, with a view to reducing such uncertainty through improved modelling of small-/short-scale processes.

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Section: Namementioning

confidence: 98%

Section: Namementioning

confidence: 98%

Section: Namementioning

confidence: 99%

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Connecting spatial and temporal scales of tropical precipitation in observations and the MetUM-GA6

2017

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“…Lower resolution simulations with the same forcing were conducted at N216 resolution (3 × 26 years) and at N96 resolution (5 × 26 years). These experiments were designed to test the sensitivity of the simulated climate to horizontal resolution only and therefore parameter changes between the different resolutions have been kept to the minimum necessary to ensure numerical stability (see Demory et al, 2014;Johnson et al, 2016, for more details on this point). Convection is parameterised at all three resolutions.…”

Section: Model Ensemblementioning

confidence: 99%

Mean and extreme precipitation over European river basins better simulated in a 25 km AGCM

Schiemann

Vidale

Shaffrey

et al. 2018

Hydrol. Earth Syst. Sci.

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Abstract. Limited spatial resolution is one of the factors that may hamper applications of global climate models (GCMs), in particular over Europe with its complex coastline and orography. In this study, the representation of European mean and extreme precipitation is evaluated in simulations with an atmospheric GCM (AGCM) at different resolutions between about 135 and 25 km grid spacing in the mid-latitudes. The continent-wide root-mean-square error in mean precipitation in the 25 km model is about 25 % smaller than in the 135 km model in winter. Clear improvements are also seen in autumn and spring, whereas the model's sensitivity to resolution is very small in summer. Extreme precipitation is evaluated by estimating generalised extreme value distributions (GEVs) of daily precipitation aggregated over river basins whose surface area is greater than 50 000 km 2 . GEV location and scale parameters are measures of the typical magnitude and of the interannual variability of extremes, respectively. Median model biases in both these parameters are around 10 % in summer and around 20 % in the other seasons. For some river basins, however, these biases can be much larger and take values between 50 % and 100 %. Extreme precipitation is better simulated in the 25 km model, especially during autumn when the median GEV parameter biases are more than halved, and in the North European Plains, from the Loire in the west to the Vistula in the east. A sensitivity experiment is conducted showing that these resolution sensitivities in both mean and extreme precipitation are in many areas primarily due to the increase in resolution of the model orography. The findings of this study illustrate the improved capability of a global high-resolution model in simulating European mean and extreme precipitation.

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“…Thus, the correct expression of the IAM is limited by the ability of atmospheric general circulation models (AGCMs) to capture regional-scale circulation [Ashfaq et al, 2009;Johnson et al, 2015;Knutti et al, 2017]. This has proven to be challenging, but the availability of higher-resolution modeling has substantially improved the representation of the IAM in climate model simulations [Delworth et al, 2012;Ma et al, 2014;Johnson et al, 2015;Li et al, 2015;Shields et al, 2016]. Significant challenges remain, especially simulating Himalayan Water Tower [Xu et al, 2014] Supporting Information:…”

Section: Introductionmentioning

confidence: 99%

The neglected Indo‐Gangetic Plains low‐level jet and its importance for moisture transport and precipitation during the peak summer monsoon

Acosta

Huber

2017

Geophysical Research Letters

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Accurately simulating the Indo‐Asian monsoon (IAM) using atmospheric general circulation models (AGCMs) is challenging but crucial. This study uses reanalysis products European Centre of Medium‐Range Forecast Interim reanalysis, Japanese Reanalysis year 55, and High Asia Reanalysis to highlight an easterly, low‐level barrier jet along the Indo‐Gangetic Plain (referred from here as IG LLJ), which we identify as the primary moisture transport mechanism for the northeastern branch of the IAM. We show that the NCAR family of AGCMs (Community Atmospheric Model (CAM)) does not capture this circulation until 1/2° or greater spatial horizontal resolution is used. The IG LLJ develops due to a persistent low‐pressure system centered over the Ganges basin and is enhanced by the Himalayas. Using diabatic heating rates and the moist Froude number as diagnostics, we find that in CAM, this branch of the IAM displays two different dynamical regimes as a function of resolution. At low resolution, the atmosphere near the Himalayas is statically unstable, diabatic heating is strong, and the moisture flow is southwesterly from the Arabian Sea and moves over the terrain (unblocked). At high resolution, the moist static stability near the Himalayan Mountains is stable, diabatic heating is weak, and the flow primarily enters easterly from the Bay of Bengal and moves parallel to the terrain (blocked). During the summer season, the low‐resolution CAM is locked into the unblocked mode, which has serious implications for interpreting topography‐monsoon interactions. For a broader context, we demonstrate that more than half of the CMIP5 models do not capture the IG LLJ, which further highlights model‐data mismatch across the IAM region.

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The resolution sensitivity of the South Asian monsoon and Indo-Pacific in a global 0.35° AGCM

Cited by 79 publications

References 73 publications

Connecting spatial and temporal scales of tropical precipitation in observations and the MetUM-GA6

Connecting spatial and temporal scales of tropical precipitation in observations and the MetUM-GA6

Mean and extreme precipitation over European river basins better simulated in a 25 km AGCM

The neglected Indo‐Gangetic Plains low‐level jet and its importance for moisture transport and precipitation during the peak summer monsoon

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