Rainfall parameterization in an off-line chemical transport model

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1 ATMOSPHERIC SCIENCE LETTERS Atmos. Sci. Let. 5: (2004) Published online in Wiley InterScience ( DOI: 1002/asl.68 Rainfall parameterization in an off-line chemical transport model C. Giannakopoulos, 1 * P. Good, 1 K. S. Law, 2 K.-Y. Wang, 3 E. Akylas 1 and A. Koussis 1 1 Institute of Environmental Research and Sustainable Development, National Observatory of Athens, Athens, Greece 2 IPSL Service d aeronomie, Université Pierre et Marie Curie, Paris, France 3 Department of Atmospheric Sciences, National Central University, Chung-Li, Taiwan *Correspondence to: C. Giannakopoulos, Institute of Environmental Research and Sustainable Development, National Observatory of Athens, V. Pavlou and Metaxa Str., Palea Pendeli, GR Athens, Greece. cgiannak@meteo.noa.gr Received: 3 July 2003 Revised: 8 September 2003 Accepted: 25 February 2004 Abstract In this paper, techniques for the modelling of both large-scale and convective precipitation in a three-dimensional off-line chemical transport model are proposed. Relatively simple formulations are proposed that will yield meaningful rainfall rates to be used for the wet deposition of chemical species without compromising the computational efficiency of the model. As the profiles of humidity and temperature obtained from available meteorological analyses are too stable to produce any rainfall, we destabilize them through advection. This technique has been tested here for the large-scale rainfall only, but can also be applied to the convective rainfall to make it less spotty and improve the comparison with observations. For an off-line model, TOMCAT seems to capture surprisingly well the global distribution pattern of the rainfall as witnessed by observational climatologies. It performs well in capturing the dry subtropical regions and the wet Asian monsoon season as well as the mitigation of rains in the tropics with the change of season. However, it underestimates precipitation in the continents in the summer and south of 30 S all year round. These shortcomings could be improved if we apply the advection technique to the convective rainfall as well. In addition, we could obtain the surface precipitation totals from the meteorological analyses and subsequently scale these amounts vertically using our modelderived grid point condensation rate. Copyright 2004 Royal Meteorological Society Keywords: atmospheric composition and structure; meteorology and atmospheric dynamics 1. Introduction Three-dimensional chemical transport models (CTMs) are now becoming widely used for studies of atmospheric chemistry in both the stratosphere and troposphere. These models, where the winds and temperatures are specified, have a number of advantages over the inclusion of chemistry directly into a 3D general circulation model (GCM). CTMs are generally computationally cheaper than chemical GCMs because they do not have the overhead of calculating the dynamical and temperature fields. Another important advantage is that, when CTMs are forced using analysed winds from meteorological centres, the model fields are constrained by the meteorology for a particular day, enabling easier comparison of the model results with chemical observations. A disadvantage of the offline approach is that the meteorological forcing fields are only available with a fixed temporal resolution (e.g. every 6 hours) and not all of the fields that could be used to force the CTM may be routinely archived. In this paper, we describe how we have modified our 3D CTM (TOMCAT) to be able to parameterize rainfall rate sensibly enough to be used for the wet deposition of chemicals. Because a chemical transport model is primarily used for describing chemical species distribution, transport and transformation, we need a precipitation scheme that will yield meaningful rainfall rates to be used for the wet deposition of chemicals without compromising the computational efficiency of the model. In this paper, we propose a precipitation scheme that adds large-scale rainfall to the convective one, arising from the previously implemented convective scheme by Stockwell and Chipperfield (1999). The precipitation scheme implemented in the model is subsequently validated using observational climatologies prior to linking it with the wet deposition scheme. 2. Modelling rain in TOMCAT 2. The TOMCAT model TOMCAT is a Eulerian grid-point 3D CTM that has been widely used for stratospheric (e.g. Chipperfield et al. 1993, 1995) and tropospheric (e.g. Law et al. 1998; Giannakopoulos et al. 1999) studies. The large-scale model circulation and temperatures are specified from meteorological analyses (in the studies presented here, from ECMWF European Centre for Medium Range Weather Forecasts), available 6-hourly. The winds and temperatures are read Copyright 2004 Royal Meteorological Society

2 Rainfall parameterization 83 in with this frequency and the fields are linearly interpolated in time to intermediate model time-steps. In the model, advection is performed using the scheme described by Prather (1986), which conserves the tracer mass. The scheme is able to maintain sharp gradients in the tracer distributions. The parameterization of convection in TOMCAT is based on the mass-flux scheme of Tiedtke (1989), which includes cumulus updraughts in the vertical column, turbulent and organized detrainment of environmental air into the cloud and turbulent and organized detrainment of cloud air to the environment. In addition, subgrid subsidence of environmental air (mesoscale downdraughts induced by convection) is also included in order to maintain mass balance within the vertical column (Stockwell and Chipperfield, 1999). We have performed a yearly integration and we present rainfall distributions for January and July. TOMCAT was run at a horizontal resolution corresponding to a Gaussian grid of T42 ( ; latitude longitude) with 31 sigma hybrid levels extending from the surface to about 10 hpa Non-convective condensation processes Large-scale precipitation processes need to be parameterized by means of the large-scale variables given at the model s grid points, which are available at a coarse resolution of some hundred kilometres in the horizontal and in the order of about 1 km in the vertical direction. The most important parameters are humidity, temperature and vertical motion. The vertical motion determines the condensation rate and therefore the supply of liquid water content. Temperature also controls the liquid water content, since the saturation vapour pressure is a function of temperature. The temperature distribution in a cloud is also important for the type of precipitation: rain or snow. In the scheme we have implemented in TOMCAT, only condensation of water vapour is considered, while the clouds are not explicitly parameterized and it is assumed that all the condensed water is immediately converted into precipitation. There is, however, an added complexity in off-line models such as TOM- CAT, as they read profiles of humidity and temperature from available meteorological analyses (ECMWF, UKMO, etc.). These profiles have the drawback of being sub-saturated on the grid-scale, so it is impossible to get any precipitation from them using a condensation scheme that precipitates the supersaturation. The reason for this is that these profiles have been adjusted in the original model from which they have been obtained, as soon as precipitation had occurred. This implies that although they were initially unstable, and hence there was supersaturation, after the condensation of water vapour and conversion to rain they were adjusted so temperature increased due to the release of latent heat, whereas the saturation mixing ratio fell. Therefore, when TOMCAT reads these profiles, it will hardly ever detect any supersaturation. To get around this problem a similar technique to the one described by Mahowald et al. (1997) has been applied. Potential temperature and specific humidity are advected every 6 hours as they are read from TOMCAT. By advecting these profiles for a short period, the air becomes saturated, generally in regions of strongest ascent, rather than becoming buoyant. The procedure of advection destabilizes them and finally supersaturation can then be detected even in an off-line model, such as TOMCAT. The profiles are advected at each time step (every 30 minutes in these runs) until the next values are read (after 6 hours). At the end of the 6-hour period, the precipitation rate is calculated using the advected profiles, rather than the initial profiles, and this rainfall rate is used in the wet deposition of chemicals within the model. In TOMCAT, new values of temperature and water vapour mixing ratio are computed following the advection process. If the atmosphere is stable but supersaturated, condensation occurs and all the condensed water vapour immediately falls out as rain. After the precipitation has been calculated at the end of the 6-hour period, the profiles of humidity and temperature are reset to the next 6-hour values read from ECMWF and re-advected. The wet removal schemes use the large-scale precipitation calculated at the end of the 6-hour period at the next 6-hour interval Convective precipitation In TOMCAT, convective rainfall is parameterized as occurring above a cloud depth of 1500 m (Stockwell and Chipperfield, 1999). This prevents shallow cumuli precipitating. The rainfall rate at each level is related to the convective updraft air mass flux. Stockwell and Chipperfield (1999) give a detailed description of the calculation of the updraft mass flux. In this formulation, almost all the liquid water, which occurs in levels where rainfall is allowed, is parameterized as rain. The liquid water includes both the condensate below cloud base and the condensate to cloud top. The top of the cloud is calculated by lifting the air parcel along the moist adiabat, adjusting the temperature and specific humidity of the parcel and adding any condensate to that calculated at cloud base. Neither the convective nor the large-scale precipitation schemes account for any evaporation of falling rain below the cloud base and therefore should overestimate the rainfall rate. This overestimate should be less in regions where the environmental thermodynamic profile is close to the moist adiabat and the cloud base height low (such as over oceans and particularly in the tropics). Over hot, dry land regions, with a high cloud base height (e.g. deserts) evaporation below the cloud base will be important and the overestimate is expected to be greater. In this paper we have not modified the convection scheme but have run it at a higher resolution (T42 compared to T21 before and with 31 vertical levels compared to 19 before as in Stockwell and Chipperfield (1999).

3 84 C. Giannakopoulos et al. 3. Model integration and comparisons with data To validate the precipitation schemes developed for TOMCAT and prior to linking with the wet deposition scheme for the removal of chemicals, we need to compare the modelled pattern of global precipitation with available observations. Observations used for this purpose are taken from the study of Jaeger (1976) and Legates and Willmott (1990). Model integrations have been performed for 10 consecutive years in January and in July at a resolution of T42 ( ).This removes the factor of interannual variability in the model output so that direct comparisons with the observational climatologies can be made. Figure 1 presents the zonal pattern of the gridproduced precipitation in July. Convective rain is generated mostly in tropical regions, with a shift to the Northern Hemisphere due to the summer season. The convective clouds develop up to 300 hpa and the cloud base is at around 750 hpa (Stockwell and Chipperfield, 1999). The cloud top is around 730 hpa since below 1500 m the precipitation rate is zero. On the other hand, large-scale precipitation develops in the middle latitudes and shows maxima at the austral winter in the Southern Hemisphere. The clouds do not have the vertical extent of the clouds that produce convective Convective rain Zonal mean TOMCAT Dynamic rain Zonal mean TOMCAT Pressure (hpa) Pressure (hpa) Latitude (degrees) Latitude (degrees) Pressure (hpa) Total rain Zonal mean TOMCAT Latitude (degrees) Figure 1. Zonal mean grid-point for convective, dynamical and total rainfall rate calculated by TOMCAT model in July

4 Rainfall parameterization 85 precipitation and the amounts of rainfall are modest. As expected, virtually all the rain produced in the tropical regions is from convective events, whereas in mid latitudes we have rain from both large-scale systems and from convection, as explained in Section 2 of this paper. The zonal pattern of precipitation in January (not shown here) is roughly similar to the pattern in July but there is an equatoward shift of rain. Figure 2 presents the horizontal surface distribution of convective and large-scale precipitation, obtained as a column total from TOMCAT in January and July. Convective rain shows a shift to the north in July, whereas in January the abundant precipitation in the north Atlantic is evident due to the frequent passage of fronts. Dynamic rain, which is mainly associated with low-pressure systems, shows maxima in winter at each hemisphere. In summer, continental Europe and Asia receive rainfall mainly from convection due to surface heating and lifting of moist adiabatically unstable air. Large-scale rain especially complements the rainfall pattern in the Southern Hemisphere middle latitudes. The contribution from convective rain to the total is smaller in the Southern Hemisphere in austral summer than in the Northern Hemisphere in boreal summer because of the difference in the amounts of land, as there is much less land in the Southern Hemisphere. However, the extra-tropical depressions occurring there produce abundant rainfall, which is generated by our large-scale scheme. Furthermore, the large-scale scheme is very important for generating the small amounts of rain observed in the continental Northern Hemisphere in winter. This rainfall amount, either in the form of snow, sleet or rain, is very important for the wet removal of chemicals that originate from the boundary layer of these continents (North America and Europe). A closer examination of Figures 2 and 2(d) reveals that there are small yet significant amounts of rain coming from the dynamical scheme in some parts of the tropics (most obviously over the West Pacific and Indian Ocean). This is probably an artefact of the way in which the dynamical scheme is implemented. In the full model the cooling and moistening due to vertical advection would be balanced by warming and drying from the convection scheme. Since the parameterization used in our model does not include the thermodynamic effects of convection, the vertical advection could result in saturation and large-scale rain, even if in the full GCM only convective rain was being generated. Finally, Figures 3 and 4 show the global pattern of precipitation from TOMCAT in comparison with the two precipitation climatologies of Legates and Convective Rain Convective Rain Dynamic Rain Dynamic Rain (d) Figure 2. Horizontal distribution of convective rain in January, convective rain in July, dynamic rain in January and (d) dynamic rain in July as obtained from TOMCAT model as a column total

5 86 C. Giannakopoulos et al. Total Rain Legates precipitation Jaeger precipitation Figure 3. January rainfall for TOMCAT at resolution, observational climatologies of Legates and Willmott (1990) and observational climatologies of Jaeger (1976) Willmott (1990) and Jaeger (1976) in January and July. The results from the comparisons are very encouraging for an off-line model. In January (Figure 3), TOMCAT generates the gross features found in the observational climatologies of Legates and Willmott (1990) and Jaeger (1976). In this figure, the dry Northern Hemisphere continents with little or no rainfall are evident. However, these regions appear somewhat drier in TOMCAT than in the observations, possibly because our simple large-scale precipitation scheme cannot distinguish between different forms of precipitation like snow and sleet, which are important in these regions. Also, dry subtropical high-pressure systems west of the continents are found in the eastern Pacific, Atlantic and southern Indian Ocean. Significant amounts of rainfall are found in the southwesterly jets off North America and East Asia. The continental convection occurring over the Southern Hemisphere and northern Australia can also be seen clearly. Compared with the observations, TOMCAT does not

6 Rainfall parameterization 87 Total Rain Legates precipitation Jaeger precipitation Figure 4. July rainfall for TOMCAT at resolution, observational climatologies of Legates and Willmott (1990) and observational climatologies of Jaeger (1976) generate sufficient rainfall south of 30 S even with the addition of the large-scale rain. TOMCAT rainfall amounts in this region are between 1 and 2 mm of rain per day whereas the climatologies indicate a range of 2 5 mm/day. In July (Figure 4), again the gross features are captured by TOMCAT, especially the Asian monsoon. The rainfall in this season, compared with January, increases over southern oceans due to the seasonally stronger storm track and decreases in the northern hemisphere. However, the apparent lack of rain in the subtropical regions of the Southern Hemisphere extends for a larger distance to the west (i.e. west coast of South America, Africa and Australia) than seen in the observations. The Northern Hemisphere continental regions (e.g. northern Europe and Asia) also appear drier in TOMCAT than in the climatologies, which can be attributed to the fact that TOMCAT cannot resolve localized features that can produce, for example, orographic rainfall. It is, however, very

7 88 C. Giannakopoulos et al. encouraging that TOMCAT can capture the west-toeast distribution of precipitation. This becomes clear when we look at the rain, produced eastwards and westwards of the subtropical high-pressure systems. The sinking air associated with these systems is more strongly developed on their eastern side. Hence the air along the eastern side of an anticyclone tends to be more stable; it is also drier, as cooler air moves equatoward because of the circulating winds around these systems. Consequently, in July, when, for example, the Pacific high moves to a position centred off the Californian coast, a strong stable subsidence inversion forms above coastal regions. With the strong inversion and the fact that the anticyclone tends to steer storms to the north, central and Southern California experience very little, if any, rainfall during the summer. On the western side of the subtropical highs, the air is less stable and more moist, as warmer air moves poleward. In July, over the North Atlantic, for example, the Bermuda Azores high pumps moist tropical air northward from the Gulf of Mexico into the eastern side of the United States. The humid air is conditionally unstable and by the time it moves over the heated ground it becomes even more unstable, rises and condenses frequently into cumulus clouds, which may build into towering thunderstorms. This feature, which is well captured in TOMCAT, is very important for the wet removal of chemicals from the atmosphere and, of course, cannot be captured by a wet removal scheme that uses only the specific humidity, for example, as the distribution of this variable simply increases from poles to equator, without exhibiting any longitudinal variation. 4. Conclusions and outlook In general, the observed precipitation pattern is uncertain and even the two datasets differ from each other. Given the fact that TOMCAT is an off-line model, its distribution of rainfall is very well represented and so it should be sufficient for use for the wet removal of chemical species. Both large-scale and convective precipitation schemes are required for a sensible parameterization of rainfall. A large-scale precipitation scheme is particularly important for Northern Hemisphere continental regions in winter. There the small winter rainfall amount is very important for the wet deposition of chemicals over a high-emissions region. On the other hand, convective rain is important for the biomass burning tropical regions and the continental regions during the summer. It is very encouraging that TOMCAT captures well the west-to-east distribution of precipitation, being produced eastwards and westwards of the subtropical high pressure systems. There is a tendency for TOMCAT to underestimate the rain, especially south of 30 S, although rain evaporation has not been included. This shortcoming can be explained by the ECMWF atmosphere being too stable. We could, perhaps, increase the amount of convective precipitation adopting a similar procedure to the large-scale precipitation. Consequently, we could advect the ECMWF profiles prior to their use of the convection scheme, too. Another significant improvement would be to obtain the surface precipitation amounts archived by the ECMWF, in addition to the profiles of humidity we are currently getting, and then to compare the model-derived precipitation with the ECMWF values. Subsequently, we could scale vertically the model grid-scale precipitation to match that of the ECMWF. References Chipperfield MP, Cariolle D, Simon P, Ramaroson R, Lary DJ A three-dimensional modelling study of trace species in the Arctic lower stratosphere during winter Journal of Geophysical Research 98: Chipperfield MP, Pyle JA, Blom CE, Glatthor N, Hoepfner M, Gulde T, Piesch C, Simon P The variability of ClONO 2 in the Arctic polar vortex: comparison of transall MIPAS measurements and 3D model results. Journal of Geophysical Research 100: Giannakopoulos C, Chipperfield MP, Law KS, Pyle JA Validation and intercomparison of wet and dry deposition schemes using 210 Pb in a global three-dimensional off-line chemical transport model. Journal of Geophysical Research 104: Jaeger L Monatskarten des Niederschlags fur die ganze Erde. Berichte des Deutschen Wetterdienstes 18: Law KS, Plantevin P-H, Shallcross DE, Rogers HL, Pyle JA Evaluation of modelled O3 using MOZAIC data. Journal of Geophysical Research 103: Legates DR, Willmott CJ Mean seasonal and spatial variability in gauge-corrected, global precipitation. International Journal of Climatology 10: Mahowald NM, Rasch PJ, Eaton BE, Whittlesome S, Prinn PG Transport of radon-222 to the remote troposphere using the model of atmospheric transport and chemistry and assimilated winds from ECMWF and the National Centre for Environmental Prediction NCAR. Journal of Geophysical Research 102: Prather MJ Numerical advection by conservation of second order moments. Journal of Geophysical Research 91: Tiedtke MA The parameterisation of moist atmospheric processes. 1: Parameterisation of non-convective condensation processes, ECMWF internal report. Tiedtke MA A comprehensive mass flux scheme for cumulus parameterisation in large-scale models, Monthly Weather Review 117: Stockwell DZ, Chipperfield MP A tropospheric chemical transport model: development and validation of the model transport schemes. Quarterly Journal of Royal Meteorological Society 125:

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