Relating global precipitation to atmospheric fronts

Catto, Jennifer L.; Jakob, Christian; Berry, Gareth; Nicholls, Neville

doi:10.1029/2012gl051736

Cited by 227 publications

(248 citation statements)

References 19 publications

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“…Bolvin et al 2009;McPhee and Margulis 2005;Nicholson et al 2003). The precipitation data have been interpolated to the same 2.5° grid as the front data in order to facilitate the linking of the two datasets as in Catto et al (2012a).…”

Section: Reanalysis Datamentioning

confidence: 99%

“…Over the mid-latitude storm track regions, Catto et al (2012a) found up to 90 per cent of annual precipitation was associated with atmospheric fronts. These frontal precipitation events can cause severe flooding in the regions over which they pass (Mills et al 1995, Pitt 2008, Lavers et al 2011).…”

Section: Introductionmentioning

confidence: 99%

“…The study of Catto et al (2012a) combined the front identification methodology of Berry et al (2011) with the daily precipitation from the Global Precipitation Climatology Project (GPCP) to quantify the global proportion of precipitation that comes from fronts as well as the average precipitation when a front is present.…”

Section: Introductionmentioning

confidence: 99%

“…The method of Catto et al (2012a) is applied to the output from the atmosphere model of the Australian Community Climate and Earth System Simulator version 1.3 (ACCESS1.3; Bi et al 2013) to evaluate the precipitation associated with fronts within the model. This process-oriented method of analysis allows the physical processes producing precipitation in the climate model to be evaluated, rather than just whether or not the model can reproduce the large spatial and temporal scale mean.…”

Section: Introductionmentioning

confidence: 99%

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A global evaluation of fronts and precipitation in the ACCESS model

Catto¹,

Jakob²,

Nicholls³

2013

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How global precipitation will change in the future is of great socio-economic importance. It is therefore vital that climate models are able to adequately simulate the characteristics of precipitation and the individual precipitation events. Fronts play an important role in providing precipitation and they can be associated with heavy rain and flooding.In this paper the ACCESS1.3 atmosphere model is evaluated in terms of frontal and non-frontal precipitation. An objective front identification method is applied to data from reanalysis and the model. The fronts are then linked to daily precipitation from observational estimates and the model. The proportion of precipitation associated with fronts and the average intensity of precipitation associated with fronts are then calculated and compared.The frequency of fronts and the proportion of precipitation associated with fronts are well captured by the model. The intensity of precipitation when a front is present is underestimated by the model in most regions, consistent with many previous studies. Decomposing the total precipitation error into components associated with the frequency and intensity of both frontal and non-frontal precipitation shows that the non-frontal precipitation errors contribute the most to the total error, and that there are compensating errors in the model. This regime-and process-based method of model evaluation provides a useful tool to gain deeper understanding into the sources of precipitation errors in climate models.

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Section: Reanalysis Datamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A global evaluation of fronts and precipitation in the ACCESS model

Catto¹,

Jakob²,

Nicholls³

2013

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“…Satellite observations that are dependent on atmospheric conditions also have the potential for fair-weather bias (Andersson et al, 2011). For example, the weather in the mid-to high-latitudes is dominated by atmospheric fronts with periods of high precipitation occurring with high wind speeds (Catto et al, 2012). These effects will be screened out by the satellite data and may lead to a fair-weather bias in the satellite-based datasets.…”

Section: Fair-weather Biasmentioning

confidence: 99%

A comparative assessment of monthly mean wind speed products over the global ocean

Kent

Fangohr

Berry

2012

Intl Journal of Climatology

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ABSTRACT:The accurate estimation of marine wind speed is important for climate and air-sea interaction applications. There are many datasets of monthly mean wind speeds available based either on in situ measurements, satellite retrievals, atmospheric reanalysis assimilating both in situ and satellite data and blended datasets combining some or all of these other data sources. Twelve different monthly mean wind speed datasets are compared for the period from 1987 to 2009. The results suggest that we cannot presently be confident that the mean wind speed over the ocean is known to the accuracy required for the calculation of air-sea heat fluxes. Comparisons are complicated by different representations of wind speed being presented in different datasets. The in situ and reanalysis datasets present stability-dependent, earth-relative, wind speeds adjusted to a reference level of 10 m. The satellite and blended datasets present neutral equivalent, surface-relative, speeds adjusted to a reference level of 10 m. Differences between these estimates depend on atmospheric stability and ocean currents and can be greater than the required accuracy target. The adjustment for stability is itself uncertain but it is shown that these uncertainties are likely to be smaller than biases caused when the effects of stability are neglected. Further differences among the datasets are identified. Biases are caused by unidentified rain in K u -band scatterometer-derived wind speeds and by atmospheric effects on passive microwave wind retrievals. When satellite observations affected by rain are removed a fair-weather bias remains. Some datasets are biased low in coastal regions by the effects of lower wind speeds over land in atmospheric models affecting wind speeds near the coast. All these uncertainties combine to give a wide range of estimates of monthly mean wind speed for the chosen datasets with uncertainty in mean values, spatial patterns and changes over time.

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A study of macrophysical and microphysical properties of warm clouds over the Northern Hemisphere using CloudSat/CALIPSO data

Sui

2014

J. Geophys. Res. Atmos.

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This study investigates the general macrophysical and microphysical properties of single-layer warm clouds over the Northern Hemisphere using standard CloudSat products during 2008. The yearly averaged occurrence frequency of single-layer warm clouds is 20.9% over oceans and 9.5% over land, respectively. The cloud top heights over land in different latitude zones exhibit a broader spectral width and more frequent occurrence of strong cloud systems in tropics than that over higher latitudes. The maximum values of liquid water content over land are approximately 10-30% smaller but the occurring altitudes are about 0.5 km higher than those over oceans with the same liquid water path (LWP). The reflectivity profiles clearly demonstrate the growth processes of cloud particles and how these processes vary with increasing LWP. The evolutions of reflectivity over land show a frequency shift toward weaker dBZ values relative to that over oceans with the same LWP, suggesting that high aerosol concentrations may induce suppressed drizzle and delayed precipitation in warm clouds. Additionally, there exists a significant difference between warm clouds formation at the initial stage over ocean and land areas. When LWP is 0.1-0.2 kg m À2 and optical depth exceeds 25, the dBZ values over oceans increase rapidly downward with increasing optical depth (decreasing height). The faster growth may be caused by the evaporation-condensation mechanism. Over land, however, large droplets are unlikely to appear in the early stage possibly because continental aerosols prevent the evaporation-condensation mechanism to occur, resulting in partially delayed drizzle formation.

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Relating global precipitation to atmospheric fronts

Cited by 227 publications

References 19 publications

A global evaluation of fronts and precipitation in the ACCESS model

A global evaluation of fronts and precipitation in the ACCESS model

A comparative assessment of monthly mean wind speed products over the global ocean

A study of macrophysical and microphysical properties of warm clouds over the Northern Hemisphere using CloudSat/CALIPSO data

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