Simulated Precipitation Amounts Research Articles

ERA5 Precipitation over China: Better Relative Hourly and Daily Distribution than Absolute Values

Abstract The temporal distribution of precipitation is of great importance in water availability and the hydrological cycle. Existing studies, directly comparing observed and simulated precipitation amount and intensity over different temporal intervals, show that reanalyses overestimate precipitation frequency and underestimate precipitation intensity, and therefore cannot characterize extreme precipitations. In this study, relative values of precipitation (i.e., the cumulative fractions of precipitation on different percentiles of wettest hours or days to the annual total) were used to evaluate ERA5 over China during the warm seasons of from 1979 to 2015. We found that ERA5 well reproduced the relative values of daily precipitation to the annual total, although hourly results were less satisfied. The cumulative fractions at the hourly time scale at the 99th, 95th, and 90th percentiles were 15.2% ± 3.4%, 38.7% ± 6.6%, and 54.5% ± 7.4% for the gauge observations, and 9.0% ± 1.7%, 27.2% ± 4.0%, and 41.5% ± 5.0% for ERA5, respectively. ERA5 had excellent agreement with gauge observations at daily time scales: gauge observations were 13.0% ± 3.4%, 32.1% ± 5.1%, and 47.6% ± 5.7%, compared to 11.5% ± 3.7%, 30.7% ± 7.0%, and 46.0% ± 8.8% for ERA5, respectively. This difference was mainly due to the high frequency of hourly precipitation in the reanalyses, which were cancelled out at the daily scale. Gauge observations at the hourly scale showed an increase cumulative fraction at the 99th, 95th, and 90th percentiles (0.07% ± 0.03% decade−1, 0.15% ± 0.03% decade−1, and 0.17% ± 0.03% decade−1, respectively) from 1979 to 2015, but did not show an obvious trend at the daily scale. These tendencies were underestimated at the hourly scale but overestimated at the daily scale in ERA5. The results helped us to characterize the temporal distributions and variations of precipitation, and to deepen our understanding of hydrological processes and reanalyses performance.

Sensitivity of precipitation in the highlands and lowlands of Peru to physics parameterization options in WRFV3.8.1

Abstract. The performance of the Weather Research and Forecasting (WRF) model version 3.8.1 at convection-permitting scale is evaluated by means of several sensitivity simulations over southern Peru down to a grid resolution of 1 km, whereby the main focus is on the domain with 5 km horizontal resolution. Different configurations of microphysics, cumulus, longwave radiation, and planetary boundary layer schemes are tested. For the year 2008, the simulated precipitation amounts and patterns are compared to gridded observational data sets and weather station data gathered from Peru, Bolivia, and Brazil. The temporal correlation of simulated monthly accumulated precipitation against in situ and gridded observational data show that the most challenging regions for WRF are the slopes along both sides of the Andes, i.e. elevations between 1000 and 3000 m above sea level. The pattern correlation analysis between simulated precipitation and station data suggests that all tested WRF setups perform rather poorly along the northeastern slopes of the Andes during the entire year. In the southwestern region of the domain the performance of all setups is better except for the driest period (May–September). The results of the pattern correlation to the gridded observational data sets show that all setups perform reasonably well except along both slopes during the dry season. The precipitation patterns reveal that the typical setup used over Europe is too dry throughout the entire year, and that the experiment with the combination of the single-moment 6-class microphysics scheme and the Grell–Freitas cumulus parameterization in the domains with resolutions larger than 5 km, suitable for East Africa, does not perfectly apply to other equatorial regions such as the Amazon basin in southeastern Peru. The experiment with the Stony Brook University microphysics scheme and the Grell-Freitas cumulus parameterization tends to overestimate precipitation over the northeastern slopes of the Andes, but enforces a positive feedback between the soil moisture, air temperature, relative humidity, mid-level cloud cover and, finally, precipitation. Hence, this setup provides the most accurate results over the Peruvian Amazon, and particularly over the department of Madre de Dios, which is a region of interest because it is considered a biodiversity hotspot of Peru. The robustness of this particular configuration of the model is backed up by similar results obtained during wet climate conditions observed in 2012.

Intercomparison of atmospheric forcing datasets and twoPBLschemes for precipitation modelling over a coastal valley in northern British Columbia, Canada

AbstractEnvironmental modelling of remote areas requires dynamical downscaling of meteorological data to obtain precipitation values that could substitute for sparse in‐situ observations. This study examined numerical simulations of precipitation over the Terrace‐Kitimat Valley, an industrializing corridor in the Coast Mountains of northern British Columbia, Canada. Modelling uncertainty was explored for 1 year of output from the Weather Research and Forecasting model at 1‐km grid spacing for three atmospheric forcing datasets and two planetary boundary layer (PBL) schemes. The observed total precipitation ranged from 1170 to 2380 mm and was often underestimated by more than 40% when using the North American Regional Reanalysis as atmospheric forcing data or the Mellor‐Yamada‐Nakanishi‐Niino level 3 (MYNN3) parameterization as PBL scheme. Persistent low bias from model configurations using these configurations suggested that merely selecting an alternative atmospheric forcing dataset does not ameliorate systematic error occasioned by a poorly performing PBL parameterization. Hence, the choice of the PBL scheme and the meteorological dataset is important for spatial estimation of precipitation using WRF. Model output best corresponded with annual gauge measurements when simulations with the Mellor‐Yamada‐Janjić (MYJ) PBL scheme were forced with ERA5. The North American Mesoscale Analyses (NAM‐ANL) however demonstrated better performance for monthly variation and high‐intensity precipitation than ERA5. Using both datasets therefore may be valuable for calculations related to environmental change. With either NAM‐ANL or ERA5 as atmospheric forcing data and MYJ as the PBL scheme, the uncertainty in annual simulated precipitation amount ranged between 38% overestimation and 21% underestimation of observational data.

Evaluation of Simulated Winter Precipitation Using WRF-ARW during the ICE-POP 2018 Field Campaign

AbstractThis study evaluates the performance of several cloud microphysics parameterizations in simulating surface precipitation for two snowstorm cases during the International Collaborative Experiment held at the PyeongChang 2018 Olympics and Winter Paralympic Games (ICE-POP 2018) field campaign. We compared four different schemes in the Weather Research and Forecasting (WRF) Model, namely the double-moment 6-class (WDM6), the WRF single-moment 6-class (WSM6), and Thompson and Morrison parameterizations. Both WSM6 and WDM6 overestimated the precipitation amount for the shallow precipitation system because of the substantial amount of cloud ice, mostly generated by the deposition process. The simulated precipitation amount and distribution for the deep precipitation system showed no noticeable differences in the different cloud microphysics parameterizations. However, the simulated hydrometeor type at the surface using WSM6 and WDM6 showed good agreement with observations for all cases. The accuracy of the mean mass-weighted terminal velocity of cloud ice applied in WSM6 and WDM6 is ±20%. The number concentration of cloud ice and the ice microphysics processes are newly retrieved with 1.2 times increased . For the shallow snowstorm, the precipitation amount was reduced by approximately 8% because of the inefficient deposition and its effects on the subsequent ice microphysical processes, such as the accretion of cloud ice by snow and the conversion from cloud ice to snow.

Effect of Scale-Aware Nonlocal Planetary Boundary Layer Scheme on Lake-Effect Precipitation at Gray-Zone Resolutions

Abstract The effects of a nonlocal planetary boundary layer (PBL) scheme that considers scale dependency in the parameterized turbulent vertical transport are investigated for a case of wintertime lake-effect precipitation over Korea at gray-zone resolutions using a mesoscale model. An experiment using the scale-aware PBL scheme is compared with that using a conventional PBL scheme, which shows that the simulated precipitation amount at a resolution of less than 1 km is smaller with the scale-aware PBL scheme. The role of turbulent processes in simulating lake-effect precipitation is understood through interaction with microphysical processes. When the scale-aware PBL scheme is used, liquid water content is increased while ice water content is reduced. The higher cloud water content is because of enhanced condensation with stronger updrafts, attributed to the suppression of parameterized turbulent mixing. This results in higher rainwater content by enhancing autoconversion and accretion from cloud water to rainwater. The cloud ice content is reduced mainly because of the suppressed deposition and enhanced sublimation centered near the PBL top, and the snow content is reduced mainly because of the enhanced sublimation below and near the PBL top and suppressed growth of cloud ice to snow. The lower ice water content is mainly due to the drier PBL, attributed to the enhanced resolved (suppressed parameterized) turbulent moisture transport and enhanced condensation. The melting of a smaller amount of snow under dominant cold rain processes is responsible for the reduced surface precipitation with the scale-aware PBL scheme.

Simulations of the 2005, 1910, and 1876 Vb cyclones over the Alps – sensitivity to model physics and cyclonic moisture flux

Abstract. In June 1876, June 1910, and August 2005, northern Switzerland was severely impacted by heavy precipitation and extreme floods. Although occurring in different centuries, all three events featured very similar precipitation patterns and an extratropical storm following a cyclonic, so-called Vb (five b of the van Bebber trajectories) trajectory around the Alps. Going back in time from the recent to the historical cases, we explore the potential of dynamical downscaling of a global reanalysis product from a grid size of 220 to 3 km. We investigate sensitivities of the simulated precipitation amounts to a set of differing configurations in the regional weather model. The best-performing model configuration in the evaluation, featuring a 1 d initialization period, is then applied to assess the sensitivity of simulated precipitation totals to cyclonic moisture flux along the downscaling steps. The analyses show that cyclone fields (closed pressure contours) and tracks (minimum pressure trajectories) are well defined in the reanalysis ensemble for the 2005 and 1910 cases, while deviations from the ensemble mean increase for the 1876 case. In the downscaled ensemble, the accuracy of simulated precipitation totals is closely linked to the exact trajectory and stalling position of the cyclone, with slight shifts producing erroneous precipitation, e.g., due to a break-up of the vortex if simulated too close to the Alpine topography. Simulated precipitation totals only reach the observed ones if the simulation includes continuous moisture fluxes of >200 kg m−1 s−1 from northerly directions and high contributions of (embedded) convection. Misplacement of the vortex and concurrent uncertainties in simulating convection, in particular for the 1876 case, point to limitations of downscaling from coarse input for such complex weather situations and for the more distant past. On the upside, single (contrasting) members of the historical cases are well capable of illustrating variants of Vb cyclone dynamics and features along the downscaling steps.

Parameterization Interactions in Global Aquaplanet Simulations

AbstractGlobal climate simulations rely on parameterizations of physical processes that have scales smaller than the resolved ones. In the atmosphere, these parameterizations represent moist convection, boundary layer turbulence and convection, cloud microphysics, longwave and shortwave radiation, and the interaction with the land and ocean surface. These parameterizations can generate different climates involving a wide range of interactions among parameterizations and between the parameterizations and the resolved dynamics. To gain a simplified understanding of a subset of these interactions, we perform aquaplanet simulations with the global version of the Weather Research and Forecasting (WRF) model employing a range (in terms of properties) of moist convection and boundary layer (BL) parameterizations. Significant differences are noted in the simulated precipitation amounts, its partitioning between convective and large‐scale precipitation, as well as in the radiative impacts. These differences arise from the way the subcloud physics interacts with convection, both directly and through various pathways involving the large‐scale dynamics and the boundary layer, convection, and clouds. A detailed analysis of the profiles of the different tendencies (from the different physical processes) for both potential temperature and water vapor is performed. While different combinations of convection and boundary layer parameterizations can lead to different climates, a key conclusion of this study is that similar climates can be simulated with model versions that are different in terms of the partitioning of the tendencies: the vertically distributed energy and water balances in the tropics can be obtained with significantly different profiles of large‐scale, convection, and cloud microphysics tendencies.

Future projections of extreme precipitation intensity-duration-frequency curves for climate adaptation planning in New York State

A set of future extreme precipitation probabilities are developed for New York State based on different downscaling approaches and climate model projections. Based on nearly 50 downscaling method-climate model combinations, percent differences are computed between simulated extreme precipitation amounts for one historical (1970–1999) and three future (2010–2039, 2040–2069, and 2070–2099) time periods. These percent change factors are then applied to the observed extremes to estimate future precipitation extremes. The results are presented to users via an interactive website (http://ny-idf-projections.nrcc.cornell.edu). As the engineering community is the primary user, the website displays intensity-duration-frequency (IDF) graphs depicting the: 1) mean projected extreme precipitation intensity, 2) range of future model projections, 3) distribution of observed extreme precipitation intensities, 4) confidence intervals about the observed values.One-hundred-year recurrence interval precipitation amounts exhibit a median increase of between 5 and 10% across the state in the 2010–2039 period regardless of greenhouse gas concentration. By the 2040–2069 period, the median increase is on the order of 10–20% for the high concentration case (RCP 8.5), but remains below 10% if concentrations are lower (RCP 4.5). At the end of the century, all downscaling method climate model combinations indicate increases, with a median change of between 20 and 30% in the case of high concentrations.

Sensitivity of the Summer Precipitation Simulated with WRF Model to Planetary Boundary Layer Parameterization over the Tibetan Plateau and its Downstream Areas

This study examines the sensitivity of simulated precipitation to planetary boundary layer (PBL) schemes over the Tibetan Plateau (TP) and the Yangtze River Valley (YRV). The summer precipitation from 15 June to 30 July 2010 is simulated with the Weather Research and Forecasting (WRF) model over these areas. Three PBL parameterization schemes, Mellor-Yamada-JanjiA‡ (MYJ), Yonsei University (YSU), and Medium-Range Forecast (MRF) are compared in the simulation. The simulated hourly precipitation overestimates the observed precipitation, and the simulation of MRF scheme is more close to the observation. In general, the WRF model shows good (poor) ability in simulating the diurnal cycle of precipitation over the TP (the upper YRV). Although the WRF model simulates a two-peak pattern different from the observed one-peak pattern in the middle YRV, both of them are generally close in trend. The choice of PBL parameterization schemes affects not only the amplitude of the precipitation but also the phase of diurnal cycle, and MRF scheme simulates better in precipitation amount than YSU and MYJ schemes. Among the three PBL schemes, the hourly PBL height of MYJ scheme is higher than those of MRF and YSU schemes. All the three PBL schemes present a similar diurnal cycle of PBL height, and the differences of PBL heights are responsible for the discrepancies in the simulated precipitation amounts. The three largest lakes in the central TP result in three large centers of the minimum PBL heights and of the average hourly PBL heights at the same locations, which are responsible for the maximum centers in the simulated precipitation in the central TP.

The Sensitivity of WRF Downscaled Precipitation in Puerto Rico to Cumulus Parameterization and Interior Grid Nudging

AbstractThe sensitivity of the precipitation over Puerto Rico that is simulated by the Weather Research and Forecasting (WRF) Model is evaluated using multiple combinations of cumulus parameterization (CP) schemes and interior grid nudging. The NCEP–DOE AMIP-II reanalysis (R-2) is downscaled to 2-km horizontal grid spacing both with convective-permitting simulations (CP active only in the middle and outer domains) and with CP schemes active in all domains. The results generally show lower simulated precipitation amounts than are observed, regardless of WRF configuration, but activating the CP schemes in the inner domain improves the annual cycle, intensity, and placement of rainfall relative to the convective-permitting simulations. Furthermore, the use of interior-grid-nudging techniques in the outer domains improves the placement and intensity of rainfall in the inner domain. Incorporating a CP scheme at convective-permitting scales (<4 km) and grid nudging at non-convective-permitting scales (>4 km) improves the island average correlation of precipitation by 0.05–0.2 and reduces the island average RMSE by up to 40 mm on average over relying on the explicit microphysics at convective-permitting scales with grid nudging. Projected changes in summer precipitation between 2040–42 and 1985–87 using WRF to downscale CCSM4 range from a 2.6-mm average increase to an 81.9-mm average decrease, depending on the choice of CP scheme. The differences are only associated with differences between WRF configurations, which indicates the importance of CP scheme for projected precipitation change as well as historical accuracy.

Impact of refined land surface properties on the simulation of a heavy convective rainfall process in the Pearl River Delta region, China

The location and occurrence time of convective rainfalls have attracted great public concern as they can lead to terrible disasters. However, the simulation results of convective rainfalls in the Pearl River Delta region often show significant discrepancies from the observations. One of the major causes lies in the inaccurate geographic distribution of land surface properties used in the model simulation of the heavy precipitation. In this study, we replaced the default soil and vegetation datasets of Weather Research and Forecasting (WRF) model with two refined datasets, i.e. the GlobCover 2009 (GLC2009) land cover map and the Harmonized World Soil Database (HWSD) soil texture, to investigate the impact of vegetation and soil on the rainfall patterns. The result showed that the simulation patterns of convective rainfalls obtained from the coupled refined datasets are more consistent with the observations than those obtained from the default ones. By using the coupled refined land surface datasets, the overlap ratio of high precipitation districts reached 36.3% with a variance of 28.5 km from the observed maximum rainfall position, while those of the default United States Geological Survey (USGS) dataset and Moderate Resolution Imaging Spectroradiometer (MODIS) dataset are 17.0%/ 32.8 km and 24.9%/49.0 km, respectively. The simulated total rainfall amount and occurrence time using the coupled refined datasets are the closest to the observed peak values. In addition, the HWSD soil data has improved the accuracy of the simulated precipitation amount, and the GLC2009 land cover data also did better in catching the early peak time.

Evaluation of a multi-site weather generator in simulating precipitation in the Qiantang River Basin, East China

Recent years have seen a surge in assessment of potential impacts of climate change. As one of the most important tools for generating synthetic hydrological model inputs, weather generators have played an important role in climate change impact analysis of water management. However, most weather generators like statistical downscaling model (SDSM) and long Ashton research station weather generator (LARS-WG) are designed for single site data generation. Considering the significance of spatial correlations of hydro-meteorological data, multi-site weather data generation becomes a necessity. In this study we aim to evaluate the performance of a new multi-site stochastic model, geo-spatial temporal weather generator (GiST), in simulating precipitation in the Qiantang River Basin, East China. The correlation matrix, precipitation amount and occurrence of observed and GiST-generated data are first compared for the evaluation process. Then we use the GiST model combined with the change factor method (CFM) to investigate future changes of precipitation (2071–2100) in the study area using one global climate model, Hadgem2_ES, and an extreme emission scenario RCP 8.5. The final results show that the simulated precipitation amount and occurrence by GiST matched their historical counterparts reasonably. The correlation coefficients between simulated and historical precipitations show good consistence as well. Compared with the baseline period (1961–1990), precipitation in the future time period (2071–2100) at high elevation stations will probably increase while at other stations decreases will occur. This study implies potential application of the GiST stochastic model in investigating the impact of climate change on hydrology and water resources.

2-way coupling the hydrological land surface model PROMET with the regional climate model MM5

Abstract. Most land surface hydrological models (LSHMs) consider land surface processes (e.g. soil–plant–atmosphere interactions, lateral water flows, snow and ice) in a spatially detailed manner. The atmosphere is considered as exogenous driver, neglecting feedbacks between the land surface and the atmosphere. On the other hand, regional climate models (RCMs) generally simulate land surface processes through coarse descriptions and spatial scales but include land–atmosphere interactions. What is the impact of the differently applied model physics and spatial resolution of LSHMs on the performance of RCMs? What feedback effects are induced by different land surface models? This study analyses the impact of replacing the land surface module (LSM) within an RCM with a high resolution LSHM. A 2-way coupling approach was applied using the LSHM PROMET (1 × 1 km2) and the atmospheric part of the RCM MM5 (45 × 45 km2). The scaling interface SCALMET is used for down- and upscaling the linear and non-linear fluxes between the model scales. The change in the atmospheric response by MM5 using the LSHM is analysed, and its quality is compared to observations of temperature and precipitation for a 4 yr period from 1996 to 1999 for the Upper Danube catchment. By substituting the Noah-LSM with PROMET, simulated non-bias-corrected near-surface air temperature improves for annual, monthly and daily courses when compared to measurements from 277 meteorological weather stations within the Upper Danube catchment. The mean annual bias was improved from −0.85 to −0.13 K. In particular, the improved afternoon heating from May to September is caused by increased sensible heat flux and decreased latent heat flux as well as more incoming solar radiation in the fully coupled PROMET/MM5 in comparison to the NOAH/MM5 simulation. Triggered by the LSM replacement, precipitation overall is reduced; however simulated precipitation amounts are still of high uncertainty, both spatially and temporally. The distribution of precipitation follows the coarse topography representation in MM5, resulting in a spatial shift of maximum precipitation northwards of the Alps. Consequently, simulation of river runoff inherits precipitation biases from MM5. However, by comparing the water balance, the bias of annual average runoff was improved from 21.2% (NOAH/MM5) to 4.4% (PROMET/MM5) when compared to measurements at the outlet gauge of the Upper Danube watershed in Achleiten.

Numerical Simulations and Analysis of June 16, 2010 Heavy Rainfall Event over Singapore Using the WRFV3 Model

The Numerical Simulations of the June 16, 2010, Heavy Rainfall Event over Singapore are highlighted by an unprecedented precipitation which produced widespread, massive flooding in and around Singapore. The objective of this study is to check the ability of Weather Research Forecasting version 3 (WRFV3) model to predict the heavy rain event over Singapore. Results suggest that simulated precipitation amounts are sensitive to the choice of cumulus parameterization. Various model configurations with initial and boundary conditions from the NCEP Final Global Analysis (FNL), convective and microphysical process parameterizations, and nested-grid interactions have been tested with 48-hour (June 15–17, 2010) integrations of the WRFV3. The spatial distributions of large-scale circulation and dynamical and thermodynamical fields have been simulated reasonably well in the model. The model produced maximum precipitation of ~5 cm over Changi airport which is very near to observation (6.4 cm recorded at Changi airport). The model simulated dynamic and thermodynamic features at 00UTC of June 16, 2010, lead to understand the structure of the mesoscale convective system (MCS) that caused the extreme precipitation over Singapore. It is observed that Singapore heavy rain was the result of an interaction of synoptic-scale weather systems with the mesoscale features.

Effects of Sand Burial and Water Regimes on Seed Germination and Seedling Emergence of Two Desert Species

Reaumuria songarica (Pall.) Maxim and Nitraria tangutorum Bobr. are two species growing on nebkhas in dune system. But N. tangutorum distributes more widely than R. songarica does. Sand burial and drought are two major disturbing factors in the field. Experiments were conducted under controlled conditions to investigate sand burial depth and simulated precipitation amount on seed germination, seedling emergence and seedling mass of the two shrubs to explain the dominance of N. tangutorum over R. songarica. Seeds were buried at 6 depths (0, 0.5, 1.5, 3, 5, 8 cm) and irrigated with 3 water regimes (5, 7, 10 mm) in plastic pots (8 cm in diameter and 11 cm in height) under the same light intensity and alternating temperature in an environment controlled growth chamber. R. songarica has a greater germination percentage than N. tangutorum under each burial depth with any water regime. R songarica seed germination increased with burial depth at each water regime and when depth is deeper than 1.5 cm all the seeds germinated under 7 and 10 mm water treatment. N. tangutorum seed germination increased until an optimal burial depth and then decreased. The optimal burial depth shifts with water regime. Seedling emergence of R songarica did not occur at depth deeper than 1.5 cm under any water regime. N. tangutorum seedling emergence maximized at 3, 1.5 and 0.5 cm with 5, 7 and 10 mm water supply regime respectively. Under all the treatments, N. tangutorum seedlings had larger dry mass than R. songarica seedlings. Higher N. tangutorum seedling emergence percentage and seedling mass with given water supply enhance its possibility to appear on nebkhas in the study area.

CORDEX 동아시아 영역에서 경계조건 및 적운모수화방안이 RegCM4를 이용한 남한 지역 기후모의에 미치는 영향 분석

본 연구에서는 CORDEX 동아시아 영역에서 경계조건(ERA-Interim, NCEP/DOE2) 및 적운모수화방안(Grell, Emanuel)이 2010년 7월에 공개된 지역기후모델(RegCM4)의 모의성능에 미치는 영향을 평가하기 위해 1989년에 대해 총 4개의 민감도 실험(EG, EE, NG, NE)을 수행하였다. 남한에서의 기온, 강수에 대한 RegCM4의 모의성능을 분석하기 위해 기상청의 기온, 강수자료를 이용하였다. RegCM4는 경계조건 및 적운모수화방안에 관계없이 기온의 공간분포, 계절변동을 잘 모의한 반면, 모든 실험에서 강수의 시 공간 분포를 적절히 모의하지 못하였다. 특히, EG, NG, NE 실험은 여름 강수를 관측보다 현저히 적게 모의하는 등 강수의 계절변동을 전혀 모의하지 못하고 있다. 하지만 EE 실험에서는 여름 강수를 포함하여 계절변동을 상대적으로 잘 모의하였다. 동아시아 여름 몬순 및 강수강도별 강수량, 강수빈도 모의에서도 EE 실험이 우수한 모의성능을 보였다. RegCM4는 경계조건에 관계없이 기온, 강수 모두 여름보다는 겨울에, Grell 보다는 Emanuel 방안을 적용할 때 높은 모의성능을 보였다. 또한 전체적으로 모의성능은 경계조건보다는 적운모수화방안에 더 큰 영향을 받는다. In this study, four types of sensitivity experiments (EG, EE, NG, NE; E: ERA-Interim, N: NCEP/DOE2, G: Grell scheme, E: Emanuel scheme) were performed to evaluate the simulation skills of RegCM4 released in July 2010 over the CORDEX (COordinated Regional Downscaling EXperiment) East Asia domain based on the combinations of boundary conditions (BC: ERA-Interim, NCEP/DOE2) and the cumulus parameterization schemes (CPS: Grell, Emanuel) for the 1989. The surface air temperature and precipitation data observed by the Korea Meteorological Adminstration were used to validate the simulation results over South Korea. The RegCM4 well simulates the seasonal and spatial variations of temperature but it fails to capture the seasonal and spatial variations of precipitation without consideration of the BC and CPS. Especially the simulated summer precipitation amount is significantly less in EG, NG, and NE experiments. But the seasonal variation of precipitation including summer precipitation is relatively well simulated in the EE experiment. The EE experiment shows a better skill in the seasonal march of East Asia summer monsoon, distribution of precipitation intensity and frequency than other experiments. In general, the skills of RegCM4 for temperature and precipitation are better during winter than summer, and in Emanuel than Grell schemes. The simulation results are more impacted by cumulus parameterization schemes than boundary conditions.

Seasonal variability in tropical and subtropical convective and stratiform precipitation of the East Asian monsoon

Seasonal variations in tropical and subtropical convective and stratiform precipitation of the East Asian monsoon are analyzed using 10-year (1998–2007) Tropical Rainfall Measuring Mission (TRMM) precipitation radar (PR) rain products (2A25). Datasets from the Intergovernmental Panel on Climate Change Fourth Assessment Report (AR4) 24 general circulation models (GCMs) are evaluated using TRMM PR rain products in terms of their ability to simulate convective and stratiform precipitation and their deficiencies. The results show that Asian monsoon convective and stratiform precipitation increases significantly after onset of the summer monsoon, but the percentage of convective precipitation clearly decreases over tropical areas while it increases in subtropical regions. The GCMs simulate well the seasonal variation in the contribution of Asian monsoon subtropical convective precipitation to the total rainfall; however, the simulated convective precipitation amount is high while the simulated stratiform precipitation amount is low relative to TRMM measurements, especially over the Asian monsoon tropical region. There is simultaneous TRMM-observed convective and stratiform precipitation in space and time, but GCMs cannot simulate this relationship between convective and stratiform precipitation, resulting in the deficiency of stratiform precipitation simulations.

Modeling stable orographic precipitation at small scales: The impact of the autoconversion scheme

This study presents idealized numerical simulations of moist airflow over a narrow isolated mountain in order to investigate the impact of the autoconversion scheme on simulated precipitation. The default setup generates an isolated water cloud over the mountain, implying that autoconversion of cloud water into rain is the only process capable of initiating precipitation. For comparison, a set of sensitivity experiments considers the classical seeder-feeder configuration, which means that ambient precipitation generated by large-scale lifting is intensified within the orographic cloud. Most simulations have been performed with the nonhydrostatic COSMO model developed at the German Weather Service (DWD), comparing three different autoconversion schemes of varying sophistication. For reference, a subset of experiments has also been performed with a spectral (bin) microphysics model. While precipitation enhancement via the seeder-feeder mechanism turns out to be relatively insensitive against the autoconversion scheme because accretion is the leading process in this case, simulated precipitation amounts can vary by 1-2 orders of magnitude for purely orographic precipitation. By comparison to the reference experiments conducted with the bin model, the Seifert-Beheng autoconversion scheme (which is the default in the COSMO model) and the Berry-Reinhardt scheme are found to represent the nonlinear behaviour of orographic precipitation reasonably well, whereas the linear approach of the Kessler scheme appears to be less adequate.

Effects of aerosols on the dynamics and microphysics of squall lines simulated by spectral bin and bulk parameterization schemes

A new spectral bin microphysical scheme (SBM) was implemented into the Weather Research and Forecasting model referred to as Fast‐SBM, which uses a smaller number of size distribution functions than the original version of the scheme referred to as Exact‐SBM. It was shown that both schemes produced similar dynamical and microphysical structure of a squall line simulated. An excellent agreement in the simulated precipitation amounts between the schemes was found within a range of cloud condensation nuclei concentrations from 100 to 3000 cm−3. The Fast‐SBM requires about 40% of the computing power of the Exact‐SBM, allowing it to be used for “real‐time” simulations over limited domains. The results obtained using the SBM simulations have been compared with those using a modified version of the Thompson bulk parameterization scheme. The main extension of the bulk scheme was the implementation of the process of drop nucleation, so that drop concentration is no longer prescribed a priori but rather calculated using the prescribed aerosol concentration. This scheme is referred to as the Drop scheme. A large set of sensitivity studies have been performed, in which microphysical parameters and precipitation, droplet nucleation above cloud base, etc., have been compared with those obtained from SBM. The SBM scheme produces more realistic dynamical and microphysical structure of the squall line. The Drop scheme did relatively little to change the cloud structures simulated by the bulk scheme. Unlike the SBM simulations that show different precipitation sensitivities to aerosol concentrations in relatively dry and humid environments, the Drop scheme indicates monotonic decrease in precipitation with increasing aerosol concentrations.

An intercomparison of regional climate model data for hydrological impact studies in Denmark

Summary The use of high-resolution regional climate models (RCM) to examine the hydrological impacts of climate change has grown significantly in recent years due to the improved representation of the local climate. However, the application is not straightforward because most RCMs are subject to considerable systematic errors. In this study, projected climate change data from the RCM HIRHAM4 are used to generate climate scenario time series of precipitation, temperature, and reference evapotranspiration for the period 2071–2100 for hydrological impact assessments in Denmark. RCM output for the present-day period (1961–1990) are compared to an observational data set, with precipitation corrected for undercatch and wetting losses, to quantify systematic model errors. A delta change method is applied to cope with these biases. A question arises as to how variable the climate change signals are, as they are influenced by the forcing GCM, the emissions scenario, and the choice of RCM. Here, we focus on the choice of RCM and the effect of increasing horizontal resolution. A comparison of HIRHAM4 output to seven similar RCMs showed that for precipitation the HIRHAM4 model is as representative as any of the RCMs in the ensemble. For temperature HIRHAM4 at 50 km resolution simulates higher temperatures than the other RCMs, while HIRHAM4 at 12 km resolution is within the range of the other models. This study highlights some of the uncertainties related to the use of RCM data in hydrological studies, which contribute to a range in hydrological effects of climate change, mainly originating from simulated precipitation amounts.