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Comparison of COSMO-CLM results with CM-SAF products: Radiation components ToA, at the Surface and Cloud Properties

  • For the first time all radiation components TOA and at the surface of the regional climate model COSMO-CLM have been systematically compared with the CMSAF products aiming to analyse the potential of such a comparison for evaluation of the model and of the CMSAF data. The group Environmental Meteorology at BTU Cottbus conducted a systematic comparison of CMSAF products for Europe with the model output of two regional climate model simulations with COSMO-CLM on the model grid of 0.165◦. COSMO-CLM was forced with the analysis of the global model GME provided by the German Weather Service. The discussion of the significance of the deviations between model and data for all radiation components and integral cloud properties for selected regions confirmed the potential of the method. First, different types of differences could be identified and hypotheses on possible origins could be formulated. Second, specific properties of CMSAF variables could be identified which should be improved in order to substantially increase the relevance ofFor the first time all radiation components TOA and at the surface of the regional climate model COSMO-CLM have been systematically compared with the CMSAF products aiming to analyse the potential of such a comparison for evaluation of the model and of the CMSAF data. The group Environmental Meteorology at BTU Cottbus conducted a systematic comparison of CMSAF products for Europe with the model output of two regional climate model simulations with COSMO-CLM on the model grid of 0.165◦. COSMO-CLM was forced with the analysis of the global model GME provided by the German Weather Service. The discussion of the significance of the deviations between model and data for all radiation components and integral cloud properties for selected regions confirmed the potential of the method. First, different types of differences could be identified and hypotheses on possible origins could be formulated. Second, specific properties of CMSAF variables could be identified which should be improved in order to substantially increase the relevance of the CMSAF products for climate model evaluations. This study is based • on the accuracy statements of the SAF data and • on the comparisons of absolute values and differences between model results and between model results and SAF products for – annual means, – monthly means and – annual cycles of spatial averages for 35 selected regions. All differences exceeding the accuracy on space scales larger than 200 × 200 km2 are regarded as significant and the systematic analysis is restricted to the significant differences. The comparison of second moments and other statistical quantities like the spatio-temporal correlations remains for future work. The analysis of the results aims to determine the consistency of the provided SAF products with the accuracy statements, to quantify the inevitable uncertainties, and to draw conclusions about the origin of the differences between model and data taking into account the assumed typical spatial structures of the differences originating in model deficiencies and/or Satellite data bias. It is assumed that • a SAF data bias typically exhibits – a North-South contrast, – an annual cycle, – a land-sea contrast, – a day-night contrast and/or – a cloud free to cloudy contrast in the differences, 115 • a typical model bias exhibits – a land-sea contrast, – a spatial structure defined by a typical local climate, – a seasonal structure, – a cloud free to cloudy contrast and/or – a model domain boundary symmetry. However, the land-sea contrast, the annual cycle, the daily cycle and/or the cloud free to cloudy contrast may have its origin in both, the SAF data bias and/or a model deficiency. As additional informations the model evaluation results obtained from comparisons with ground station observation products are taken into account. Furthermore, the inter comparison between the results for variables, which have a direct physical relation, like e.g. the albedo the incoming and the outgoing short-wave radiation at the surface is considered. All discussions and analyses presented in this study are restricted to a previously selected set of parameters, regions, and time periods. The conclusions drawn in this report for a certain parameter in a specific region cannot generally be assigned to other parameters, regions and model configurations. Additionally to the results presented in this report the annual cycles for the other regions are provided as a supplement. In the following the main results of this first study are summarized. Two model simulations have been conducted with different initial conditions for the soil variables temperature and soil moisture. The internal model variability due to this difference appeared to be of minor importance in comparison with the stated accuracy of the SAF products. It increases slightly the total accuracy and will not be discussed in the follwing (see the discussion of each variable for details). One year data over Europe appeared to be sufficient for identification of different patterns of significant differences and to make suggestions on its possible origins like model deficiencies and/or SAF-data bias exceeding the stated accuracy. In the following the main hypotheses derived from the results are listed. • Boundary conditions inconsistent with cloud conditions in the model causing: – Negative differences of CLCT in the boundary shown in 24. – negative differences of ASWU_T shown in 8, – positive differences of ASWG_S shown in 36, – positive differences of ASOB_S shown in 49, – negative differences of ATHB_S shown in 60. • Overestimation of CLCT in the model over central to northern Europe of up to 0.3 in summer in Scandinavia causing: – Positive differences of ASOU_T shown in 9 116 – Positive differences in ATHB_T shown in 17 – Negative differences of ASWG_S shown in 37 – Negative differences of ASWDIFU_S in summer shown in 45 – Negative differences of ASOB_S shown in 49 – Positive differences of ALWD_S in SCA shown in 53 • Overestimation of formation of clouds over land in the model or bias over land in CMSAF data causing – negative differences of TQV over land shown in 32 – Neutral to positive differences in CLCT shown in 25 – CLCT and TQV show a weak negative correlation in winter (33 and 25 Jan.) and weak positive correlation in summer (33 and 25 Jul..) • Overestimation of deep convection in the model over land in summer or overestimated NorthSouth gradient in CMSAF data causing – positive differences of HTOP_CON in summer shown in 29 and 31, • Underestimation of formation of clouds in the model over water or CMSAF data bias over water surfaces – negative CLCT shown in 24 and 26 – negative differences (downward positive!) and weaker land-sea contrast in SAF120, especially in winter in ToA LW net shown in 16 and 18 – negative differences in ALWD_S shown in 52 and 55 especially in late winter to early spring. – negative differences in ATHB_S over WAS and Italy shown in 60 – negative TOT_PREC shown in 75 • Overestimation of the model surface albedo in regions covered by snow causing: – Positive albedo values over ALP and SCA in winter and spring shown in 41 – Positive ASWDIFU_S over ALP and SCA in late winter shown in 45 • Inconsistency of 2m temperature of the model and of the outgoing LW radiation in CMSAF indicating a bias in the GME analysis used in the SAF product. – negative differences in the 2m temperature shown in 68 and 69 all over the year and – neutral to positive (in SUE and POE in spring and autumn) differences of ALWU_S shown in 53 • Additional summer cold bias of GME008 configuration causing 117 – negative differences in central and northern Europe in summer in T_2M shown in 69 – negative differences in central and northern Europe in summer in ALWU_S shown in 57 – no differences in central and northern Europe in summer in ALWD_S shown in 53 – positive differences in central and northern Europe in summer in ATHB_S shown in 53 • Weaker variability on regional scale in CCLM in – monthly and annual means of ALB_RAD in 40 and 41 – monthly and annual means of surface up SW in 44 and 45 • CMSAF data bias: – higher north-south gradient in SIS than in ASOG_S in January shown in 37 – stronger land-sea contrast in CMSAF data CLC (24 and 25) – strong land-sea contrast in SDL shown in 52 The results show that the availability of independent SAF products for complementary variables allows to identify different space-time patterns of differences and to draw up hypotheses on its possible origins. However, the typical SAF product time scale of 1 or 2 years appears to be a limiting factor of the analysis. In this sense the results confirm the potential of the CMSAF data for model evaluation and the analysis of the quality of the CMSAF data. The availability of many variables can not replace the limited length of the time serieses. From physical point of view the cloud cover and the atmospheric content of water vapour, liquid and ice water in dependence on the height appear as the primary variables and it is suggested to focus in the future on these variables and on the consistency of the results obtained for these variables with the results for the radiation components. Assuming the accuracy stated for each SAF variable the provided SAF data are of satisfying quality for state of the art climate model evaluation. The SAF product accuracy values are substantially larger than the internal model variability and they are in many regions and seasons smaller than the differences between model results and SAF data. Assuming the accuracy stated as not certain, most of the difference patterns can be attributed to SAF product bias or to a model deficiency. Additional investigations are necessary to find the right answers. In this sense this report exhibits the potential of the method and invites to make additional contributions. Substantial progress can be expected from the analysis of the vertical structure, daily cycle and cloud free/cloudy states focussing on the cloud properties and related variables. Furthermore, a specification of the SAF accuracy limits in space and time and the extension of the time serieses are important for clarification of the applicability of the SAF products for model evaluation.show moreshow less

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Author: Andreas Will, Michael Woldt
URL:https://www.hereon.de/imperia/md/assets/clm/will__a._and_m._woldt.pdf
Publisher:Satellite Application Facility on Climae Monitoring
Place of publication:Offenbach
Document Type:Report
Language:English
Year of publication:2009
Number of pages:121
Series ; volume number:Visiting Scientist Report ; No. 16
Faculty/Chair:Fakultät 2 Umwelt und Naturwissenschaften / FG Atmosphärische Prozesse
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