High-resolution subtropical summer precipitation derived from dynamical downscaling of the NCEP/DOE reanalysis: how much small-scale information is added by a regional model?

This study assesses the regional-scale summer precipitation produced by the dynamical downscaling of analyzed large-scale fields. The main goal of this study is to investigate how much the regional model adds smaller scale precipitation information that the large-scale fields do not resolve. The modeling region for this study covers the southeastern United States (Florida, Georgia, Alabama, South Carolina, and North Carolina) where the summer climate is subtropical in nature, with a heavy influence of regional-scale convection. The coarse resolution (2.5° latitude/longitude) large-scale atmospheric variables from the National Center for Environmental Prediction (NCEP)/DOE reanalysis (R2) are downscaled using the NCEP/Environmental Climate Prediction Center regional spectral model (RSM) to produce precipitation at 20?km resolution for 16 summer seasons (1990?C2005). The RSM produces realistic details in the regional summer precipitation at 20?km resolution. Compared to R2, the RSM-produced monthly precipitation shows better agreement with observations. There is a reduced wet bias and a more realistic spatial pattern of the precipitation climatology compared with the interpolated R2 values. The root mean square errors of the monthly R2 precipitation are reduced over 93% (1,697) of all the grid points in the five states (1,821). The temporal correlation also improves over 92% (1,675) of all grid points such that the domain-averaged correlation increases from 0.38 (R2) to 0.55 (RSM). The RSM accurately reproduces the first two observed eigenmodes, compared with the R2 product for which the second mode is not properly reproduced. The spatial patterns for wet versus dry summer years are also successfully simulated in RSM. For shorter time scales, the RSM resolves heavy rainfall events and their frequency better than R2. Correlation and categorical classification (above/near/below average) for the monthly frequency of heavy precipitation days is also significantly improved by the RSM.     

The MGO climate model for Siberia

Validation results of the MGO regional climate model (RCM) with 50-km resolution for Siberia are discussed. For the specification of side boundary conditions, the reanalysis data are used. It is shown that the model satisfactorily simulates the sea-level pressure and temperature fields for all seasons and the year as a whole. The lowest computational errors in the simulation of regional surface temperature arise in the fall and winter; in spring and summer, the temperature errors are slightly higher. The model slightly underestimates the variability of daily mean temperature in winter relative to the reanalysis data. In summer, on the contrary, the RCM-simulated variability exceeds the variability in reanalysis. In winter, the space distribution of model precipitation is in qualitative agreement with the data of observational analysis; in summer, the space variability of model precipitation is significantly higher than that of precipitation in the reanalysis, especially in the mountains. Agreement between time changes in precipitation and temperature anomalies in RCM and in the reanalysis is better in the areas with a relatively large number of weather stations. The model can be used for estimation of future climate changes in the above-mentioned region.     

The thermodynamic influence of subgrid orography in a global climate model

Assessments of the impacts of climate change typically require information at scales of 10 km or less. Such a resolution in global climate simulations is unlikely for at least two decades. We have developed an alternative to explicit resolution that provides a framework for meeting the needs of climate change impact assessment much sooner. We have applied to a global climate model a physically based subgrid-scale treatment of the influence of orography on temperature, clouds, precipitation, and land surface hydrology. The treatment represents subgrid variations in surface elevation in terms of fractional area distributions of discrete elevation classes. For each class it calculates the height rise/descent of air parcels traveling through the grid cell, and applies the influence of the rise/descent to the temperature and humidity profiles of the elevation class. Cloud, radiative, and surface processes are calculated separately for each elevation class using the same physical parametrizations used by the model without the subgrid orography parametrization. The simulated climate fields for each elevation class can then be distributed in post-processing according to the spatial distribution of surface elevation within each grid cell. Parallel 10-year simulations with and without the subgrid treatment have been performed. The simulated temperature, precipitation and snow water are mapped to 2.5-minute (~5 km) resolution and compared with gridded analyses of station measurements. The simulation with the subgrid scheme produces a much more realistic distribution of snow water and significantly more realistic distributions of temperature and precipitation than the simulation without the subgrid scheme. Moreover, the 250-km grid cell means of most other fields are virtually unchanged by the subgrid scheme. This suggests that the tuning of the climate model without the subgrid scheme is also applicable to the model with the scheme.     

SIMULATION OF SUMMER MONSOON CLIMATE OVER EASTERN CHINA USING A REGIONAL SPECTRAL MODEL

In this paper, we evaluate the characteristics of the surface air temperature and the precipitation of summer monsoon, using the National Centers for Environmental Prediction (NCEP) Regional Spectral Model (RSM) for 20 years (1984-2003). The RSM model was designated over the eastern China with a horizontal grid spacing of approximately 30 km. The model is driven by the NCEP/NCAR reanalysis data and runs from May 21 to September 1 for each of the 20 years. The distribution and variation patterns of the 20-year summer mean surface air temperature and precipitation are reproduced by the RSM and the differences between the simulation and observation are small. However, the model overestimates the interannual variability of summer precipitation in eastern China. The correlation coefficients of the 20-year averaging summer precipitation over the whole region and the sub-domains are above 0.8. The simulated probability distributions of daily maximum and minimum temperatures are similar to the observations. Days of different precipitation intensities in the simulations are generally consistent with the observations: the simulated days of light rain, moderate rain, heavy rain and torrential rain closely resemble the observations, but the simulated maximum centers of the distribution are north of the observed ones.     

Impact of subgrid scale scheme on topography and landuse for better regional scale simulation of meteorological variables over the western Himalayas

An attempt is made to integrate subgrid scale scheme on the work of Dimri and Ganju (Pure Appl Geophys 167:1–24, 2007) to understand the overall nature of surface heterogeneity and landuse variability along with resolvable finescale micro/meso scale circulation over the Himalayan region, which is having different altitudes and orientations causing prevailing weather conditions to be complex. This region receives large amount of precipitation due to eastward moving low-pressure synoptic weather systems, called western disturbances, during winter season (December, January, February—DJF). Surface heterogeneity and landuse variability of the Himalayan region gives rise to numerous micro/meso scale circulation along with prevailing weather. Therefore, in the present work, a mosaic type parameterization of subgrid scale topography and landuse within a framework of a regional climate model (RegCM3) is extended to study interseasonal variability of surface climate during a winter season (October 1999–March 2000) of the work of Dimri and Ganju (Pure Appl Geophys 167:1–24, 2007). In this scheme, meteorological variables are disaggregated from the coarse grid to the fine grid, land surface calculations are then performed separately for each subgrid cell, and surface fluxes are calculated and reaggregated onto the coarse grid cell for input to the atmospheric model. By doing so, resolvable finescale structures due to surface heterogeneity and landuse variability at coarse grid are subjected to parameterize at regular finescale surface subgrid. Model simulations show that implementation of subgrid scheme presents more realistic simulation of precipitation and surface air temperature. Influence of topographic elevation and valleys is better represented in the scheme. Overall, RegCM3 with subgrid scheme provides more accurate representation of resolvable finescale atmospheric/surface circulations that results in explaining mean variability in a better way.     

Present climate simulation over Korea with a regional climate model using a one-way double-nested system

Summary This study investigates the capability of the regional climate model RegCM3 to simulate surface air temperature and precipitation over the Korean Peninsula. The model is run in one-way double nested mode, with a 60 km grid point spacing “mother” domain encompassing the eastern regions of Asia and a 20 km grid point spacing nested domain covering the Korean Peninsula. The simulation spans the three-year period of 1 October 2000 through 30 September 2003 and the boundary conditions needed to run the mother domain experiment are provided from the NCEP reanalysis of observations. The model results are compared with a high density station observation dataset to examine the fine scale structure of the surface climate signal. The model shows a good performance in capturing both the sign and magnitude of the seasonal and inter-annual variations of the surface variables both over East Asia as a whole and over the Korean Peninsula in the nested system. Some persistent biases are however present. Surface temperature is systematically underestimated, especially over mountainous regions in the warm season. This feature may be due to the relatively coarse representation of the Korean topography. The simulated precipitation over the mother domain successfully reproduces the broad spatial pattern of observed precipitation over East Asia along with its seasonal evolution. On the other hand, fine scale details from the nested results show a varying level of quality for the different individual years. Because of the better resolved topographic forcing, the increased resolution of the nested model improves the spatial agreement with the fine scale observation fields for temperature and cold season precipitation. For summer monsoon precipitation the simulation of individual monsoon convective events and tropical storms is however more important than the topographic forcing, and therefore the performance of the nested system is more case-dependent.     

Evaluation of Hydrologically Relevant PCM Climate Variables and Large-Scale Variability over the Continental U.S.

The ability of the Parallel Climate Model (PCM) to reproduce the mean and variability of hydrologically relevant climate variables was evaluated by comparing PCM historical climate runs with observations over temporal scales from sub-daily to annual. The domain was the continental U.S, and the model spatial resolution was T42 (about 2.8 degrees latitude by longitude). The climate variables evaluated include precipitation, surface air temperature, net surface solar radiation, soil moisture, and snow water equivalent. The results show that PCM has a winter dry bias in the Pacific Northwest and a summer wet bias in the central plains. The diurnal precipitation variation in summer is much stronger than observed, with an afternoon maximum in summer precipitation over much of the U.S. interior, in contrast with an observed nocturnal maximum in parts of the interior. PCM has a cold bias in annual mean temperature over most of the U.S., with deviations as large as ?8 K. The PCM daily temperature range is lower than observed, especiallyin the central U.S. PCM generally overestimates the net solar radiation over most of the U.S, although the diurnal cycle is simulated well in spring, summer and winter. In autumn PCM has a pronounced noontime peak in solar radiation that differs by 5–10% from observations. PCM'ssimulated soil moisture is less variable than that of a sophisticated land-surface hydrology model, especially in the interior of the country. PCM simulates the wetter conditions over the southeastern U.S. and California during warm (El Niño) events, but shifts the drier conditions in the PacificNorthwest northward and underestimates their magnitude. The temperature response to the North Pacific Oscillation is generally captured by PCM, but the amplitude of this response is overestimated by a factor of about two.     

高分辨率MRI模式对青藏高原夏季降水及水汽输送通量的模拟

本文使用MRI模式在不同分辨率下(180 km、120 km、60 km、20 km)的AMIP试验结果, 分析了该模式对青藏高原夏季降水及水汽输送通量的模拟, 并考察模式分辨率的影响。结果表明:MRI模式能够较为合理地模拟出青藏高原夏季气候平均的降水空间分布, 但对气候平均水汽输送通量以及降水年际变化的模拟却存在较大的误差。随着分辨率的提高, 该模式对青藏高原气候平均降水的模拟有明显改进, 包括降水年循环以及夏季降水的空间分布等。分辨率为180 km、120 km、60 km、20 km的MRI模式模拟的青藏高原7月平均降水绝对误差分别为2.2 mm/d、1.2 mm/d、0.7 mm/d、0.2 mm/d。另外, 高分辨率模式模拟的青藏高原夏季水汽输送通量的年际变化也更接近观测。当分辨率达到20 km时, MRI模式模拟的西风水汽输送指数与观测的相关系数达到0.43, 通过了0.1显著性水平的显著性检验。但MRI模式对青藏高原夏季降水的年际变化以及气候平均水汽输送通量的模拟技巧并不随分辨率的增加有明显提高。低分辨率模式中模拟降水量偏大、印度季风槽偏强的现象在高分辨率模式中仍然存在。     

Spatial variability of Holocene changes in the annual precipitation pattern: a model-data synthesis for the Asian monsoon region

This study provides a detailed analysis of the mid-Holocene to present-day precipitation change in the Asian monsoon region. We compare for the first time results of high resolution climate model simulations with a standardised set of mid-Holocene moisture reconstructions. Changes in the simulated summer monsoon characteristics (onset, withdrawal, length and associated rainfall) and the mechanisms causing the Holocene precipitation changes are investigated. According to the model, most parts of the Indian subcontinent received more precipitation (up to 5 mm/day) at mid-Holocene than at present-day. This is related to a stronger Indian summer monsoon accompanied by an intensified vertically integrated moisture flux convergence. The East Asian monsoon region exhibits local inhomogeneities in the simulated annual precipitation signal. The sign of this signal depends on the balance of decreased pre-monsoon and increased monsoon precipitation at mid-Holocene compared to present-day. Hence, rainfall changes in the East Asian monsoon domain are not solely associated with modifications in the summer monsoon circulation but also depend on changes in the mid-latitudinal westerly wind system that dominates the circulation during the pre-monsoon season. The proxy-based climate reconstructions confirm the regional dissimilarities in the annual precipitation signal and agree well with the model results. Our results highlight the importance of including the pre-monsoon season in climate studies of the Asian monsoon system and point out the complex response of this system to the Holocene insolation forcing. The comparison with a coarse climate model simulation reveals that this complex response can only be resolved in high resolution simulations.     

Hydrologic Implications of Dynamical and Statistical Approaches to Downscaling Climate Model Outputs

Six approaches for downscaling climate model outputs for use in hydrologic simulation were evaluated, with particular emphasis on each method's ability to produce precipitation and other variables used to drive a macroscale hydrology model applied at much higher spatial resolution than the climate model. Comparisons were made on the basis of a twenty-year retrospective (1975–1995) climate simulation produced by the NCAR-DOE Parallel ClimateModel (PCM), and the implications of the comparison for a future(2040–2060) PCM climate scenario were also explored. The six approaches were made up of three relatively simple statistical downscaling methods – linear interpolation (LI), spatial disaggregation (SD), and bias-correction and spatial disaggregation (BCSD) – each applied to both PCM output directly(at T42 spatial resolution), and after dynamical downscaling via a Regional Climate Model (RCM – at 1/2-degree spatial resolution), for downscaling the climate model outputs to the 1/8-degree spatial resolution of the hydrological model. For the retrospective climate simulation, results were compared to an observed gridded climatology of temperature and precipitation, and gridded hydrologic variables resulting from forcing the hydrologic model with observations. The most significant findings are that the BCSD method was successful in reproducing the main features of the observed hydrometeorology from the retrospective climate simulation, when applied to both PCM and RCM outputs. Linear interpolation produced better results using RCM output than PCM output, but both methods (PCM-LI and RCM-LI) lead to unacceptably biased hydrologic simulations. Spatial disaggregation of the PCM output produced results similar to those achieved with the RCM interpolated output; nonetheless, neither PCM nor RCM output was useful for hydrologic simulation purposes without a bias-correction step. For the future climate scenario, only the BCSD-method (using PCM or RCM) was able to produce hydrologically plausible results. With the BCSD method, the RCM-derived hydrology was more sensitive to climate change than the PCM-derived hydrology.     

不同分辨率CCSM4对东亚和中国气候模拟能力分析

本文利用通用气候系统模式CCSM4在三种水平分辨率下的工业化革命前期气候模拟试验,结合观测和再分析资料,比较了各分辨率下模式对中国温度和降水、东亚海平面气压和850 hPa风场的模拟能力,综合评价了模式分辨率对东亚和中国气候模拟的影响.结果表明,三种分辨率对中国温度均具有很好的模拟能力,除春季外,低分辨率(T31,约3.75°×3.75°)对全年温度的模拟能力均要稍好于中(f19,约1.9°×2.5°)、高(f09,约0.9°×1.25°)分辨率;各分辨率对中国降水的模拟能力远不如温度,除冬季外全年都出现的中部地区虚假降水并未因为模式分辨率提高而得到本质改善;对于东亚海平面气压场,低分辨率在冬季模拟能力相对最好,中等分辨率在夏季相对较好,而高分辨率的模拟能力均表现最差;低分辨率对850 hPa东亚冬季风和夏季风的模拟能力均要好于中、高分辨率,而两种较高分辨率的模拟能力则比较接近.总的来说,低分辨率CCSM4在东亚和中国气候模拟中表现出了较大优势,加之其计算代价小,适合进行需要较长时间积分的气候模拟研究.     

Sensitivity of simulated wintertime Arctic atmosphere to vertical resolution in the ARPEGE/IFS model

The current state-of-the-art general circulation models, including several of those used by the IPCC, show considerable biases in the simulated present day high-latitude climate compared to observations and reanalysis data. These biases are most pronounced during the winter season. We here employ ideal vertical profiles of temperature and wind from turbulence-resolving simulations to perform a priori studies of the first-order eddy-viscosity closure scheme employed in the ARPEGE/IFS model. This reveals that the coarse vertical resolution (31 layers) of the model cannot be expected to realistically resolve the Arctic stable boundary layer. The curvature of the Arctic inversion and thus also the vertical turbulent-exchange processes cannot be reproduced by the coarse vertical mesh employed. To investigate how turbulent vertical exchange processes in the Arctic boundary layer are represented by the model parameterization, a simulation with high vertical resolution (90 layers in total) in the lower troposphere is performed. Results from the model simulations are validated against data from the ERA-40 reanalysis. The dependence of the surface air temperature on surface winds, surface energy fluxes, free atmosphere stability and boundary layer height is investigated. The coarse-resolution run reveals considerable biases in these parameters, and in their physical relations to surface air temperature. In the simulation with fine vertical resolution, these biases are clearly reduced. The physical relation between governing parameters for the vertical turbulent-exchange processes improves in comparison with ERA-40 data.     

Does increasing the spatial resolution of a regional climate model improve the simulated daily precipitation?

Three different resolution (50, 12, and 1.5 km) regional climate model simulations are compared in terms of their ability to simulate moderate and high daily precipitation events over the southern United Kingdom. The convection-permitting 1.5-km simulation is carried out without convective parametrisation. As in previous studies, increasing resolution (especially from 50 to 12 km) is found to improve the representation of orographic precipitation. The 50-km simulation underestimates mean precipitation over the mountainous region of Wales, and event intensity tends to be too weak; this bias is reduced in both the 12- and 1.5-km simulations for both summer and winter. In south–east England lowlands where summer extremes are mostly convective, increasing resolution does not necessary lead to an improvement in the simulation. For the 12-km simulation, simulated daily extreme events are overly intense. Even though the average intensity of summer daily extremes is improved in the 1.5-km simulation, this simulation has a poorer mean bias with too many events exceeding high thresholds. Spatial density and clustering of summer extremes in south–east England are poorly simulated in both the 12- and 1.5-km simulations. In general, we have not found any clear evidence to show that the 1.5-km simulation is superior to the 12-km simulation, or vice versa at the daily level.     

Spatial Scale Effects of Climate Scenarios on Simulated Cotton Production in the Southeastern U.S.A.

We examine the effect of climate scenarios generated using results from climate models of different spatial resolution on yields simulated by the deterministic cotton model GOSSYM for the southeastern U.S.A. Two related climate change scenarios were used: a coarse-scale scenario produced from results of a general circulation model (GCM) which also provided the boundary conditions to a regional climate model (RCM), from which a fine-scale scenario was constructed. Cotton model simulations were performed for three cases: climate change alone; climate change and elevatedCO₂; climate change, elevated CO₂ and adaptations to climate change. In general, significant differences in state-average projected yield changes between the coarse and fine-scale scenarios are found for these three cases. In the first two cases, different directions of change are found in some sub-regions. With adaptation, yields substantially increase for both climate scenarios, but more so for the coarse-scale scenario (30%domain-average increase). Under irrigation, yield change differences between the two climate scenarios are small in all three cases, and yields are higher under irrigation ( 35% domain-average increase with adaptation case) compared to dryland conditions. For the climate change alone case, differences in summer water-stress levels explain the contrasts in dryland yield patterns between the coarse and fine-scale climate scenarios.     

Impact of horizontal resolution on seasonal integrations

 The effects of changing horizontal resolution are studied using ensembles of seasonal simulations made by a relatively recent version of the ECMWF model. The model is integrated at T63, T_L159 and T_L319 spectral resolutions. The last corresponds approximately to a 0.56° latitude-longitude grid and may be considered, by climate modelling standards, as very high resolution. Though, on average, no dramatically large differences in ensemble mean quantities are found between the three resolutions, some monotonic (systematic) differences with increasing resolution are evident. Whilst the better representation of orography with increasing resolution accounts for many differences between the resolutions considered, not all variations can be associated with changes in local orographic features. The existence of systematic changes with resolution indicates that the development of numerical models, especially physical parametrizations, should be carried out simultaneously at various resolutions. The study indicates that the highest model resolution does not always give the best results in terms of verification. In addition, reanalysis parameters that are mainly driven by model physics may not be optimal for the verification in such resolution studies. Received: 11 August 2000 / Accepted: 13 February 2001     

Improvements in WRF simulation skills of southeastern United States summer rainfall: physical parameterization and horizontal resolution

Realistic regional climate simulations are important in understanding the mechanisms of summer rainfall in the southeastern United States (SE US) and in making seasonal predictions. In this study, skills of SE US summer rainfall simulation at a 15-km resolution are evaluated using the weather research and forecasting (WRF) model driven by climate forecast system reanalysis data. Influences of parameterization schemes and model resolution on the rainfall are investigated. It is shown that the WRF simulations for SE US summer rainfall are most sensitive to cumulus schemes, moderately sensitive to planetary boundary layer schemes, and less sensitive to microphysics schemes. Among five WRF cumulus schemes analyzed in this study, the Zhang–McFarlane scheme outperforms the other four. Further analysis suggests that the superior performance of the Zhang–McFarlane scheme is attributable primarily to its capability of representing rainfall-triggering processes over the SE US, especially the positive relationship between convective available potential energy and rainfall. In addition, simulated rainfall using the Zhang–McFarlane scheme at the 15-km resolution is compared with that at a 3-km convection-permitting resolution without cumulus scheme to test whether the increased horizontal resolution can further improve the SE US rainfall simulation. Results indicate that the simulations at the 3-km resolution do not show obvious advantages over those at the 15-km resolution with the Zhang–McFarlane scheme. In conclusion, our study suggests that in order to obtain a satisfactory simulation of SE US summer rainfall, choosing a cumulus scheme that can realistically represent the convective rainfall triggering mechanism may be more effective than solely increasing model resolution.     

Mean, interannual variability and trends in a regional climate change experiment over Europe. II: climate change scenarios (2071–2100)

We present an analysis of climate change over Europe as simulated by a regional climate model (RCM) nested within time-slice atmospheric general circulation model (AGCM) experiments. Changes in mean and interannual variability are discussed for the 30-year period of 2071–2100 with respect to the present day period of 1961–1990 under forcing from the A2 and B2 IPCC emission scenarios. In both scenarios, the European region undergoes substantial warming in all seasons, in the range of 1–5.5°C, with the warming being 1–2°C lower in the B2 than in the A2 scenario. The spatial patterns of warming are similar in the two scenarios, with a maximum over eastern Europe in winter and over western and southern Europe in summer. The precipitation changes in the two scenarios also show similar spatial patterns. In winter, precipitation increases over most of Europe (except for the southern Mediterranean regions) due to increased storm activity and higher atmospheric water vapor loadings. In summer, a decrease in precipitation is found over most of western and southern Europe in response to a blocking-like anticyclonic circulation over the northeastern Atlantic which deflects summer storms northward. The precipitation changes in the intermediate seasons (spring and fall) are less pronounced than in winter and summer. Overall, the intensity of daily precipitation events predominantly increases, often also in regions where the mean precipitation decreases. Conversely the number of wet days decreases (leading to longer dry periods) except in the winter over western and central Europe. Cloudiness, snow cover and soil water content show predominant decreases, in many cases also in regions where precipitation increases. Interannual variability of both temperature and precipitation increases substantially in the summer and shows only small changes in the other seasons. A number of statistically significant regional trends are found throughout the scenario simulations, especially for temperature and for the A2 scenario. The results from the forcing AGCM simulations and the nested RCM simulations are generally consistent with each other at the broad scale. However, significant differences in the simulated surface climate changes are found between the two models in the summer, when local physics processes are more important. In addition, substantial fine scale detail in the RCM-produced change signal is found in response to local topographical and coastline features.     

对流允许尺度区域气候模拟的研究进展

与以往的区域气候模式相比,对流允许区域气候模式不再依赖于对流参数化方案,其精细的分辨率可以显式表示深对流过程,在夏季对流降水的日变化和极端降水事件模拟等方面具有明显增值能力,是区域气候模拟的发展方向。对现有的对流允许尺度区域气候模拟研究进行了较为详细的回顾和介绍,简述了对流允许尺度区域气候模式中比较重要的物理过程及外部驱动条件的影响,总结了以往对流允许尺度区域气候模拟的研究成果以及当下所面临的挑战和对未来的展望,以期对中国及东亚区域对流允许区域气候模拟的研究提供有益参考。诸多研究表明,对流允许区域气候模拟作为一种有前景的气候模式,可提供更加可靠的区域尺度的气候信息。     

Conditional stochastic simulation model for spatial downscaling for assessing the effects of climate change on hydro-meteorological variables

The current study examines the recently proposed “bias correction and stochastic analogues” (BCSA) statistical spatial downscaling technique and attempts to improve it by conditioning coarse resolution data when generating replicates. While the BCSA method reproduces the statistical features of the observed fine data, this existing model does not replicate the observed coarse spatial pattern, and subsequently, the cross-correlation between the observed coarse data and downscaled fine data with the model cannot be preserved. To address the dissimilarity between the BCSA downscaled data and observed fine data, a new statistical spatial downscaling method, “conditional stochastic simulation with bias correction” (BCCS), which employs the conditional multivariate distribution and principal component analysis, is proposed. Gridded observed climate data of mean daily precipitation (mm/day) covering a month at 1/8° for a fine resolution and at 1° for a coarse resolution over Florida for the current and future periods were used to verify and cross-validate the proposed technique. The observed coarse and fine data cover the 50-year period from 1950 to1999, and the future RCP4.5 and RCP8.5 climate scenarios cover the 100-year period from 2000 to 2099. The verification and cross-validation results show that the proposed BCCS downscaling method serves as an effective alternative means of downscaling monthly precipitation levels to assess climate change effects on hydrological variables. The RCP4.5 and RCP8.5 GCM scenarios are successfully downscaled.     

Simulating the diurnal cycle of rainfall in global climate models: resolution versus parameterization

The effects of horizontal resolution and the treatment of convection on simulation of the diurnal cycle of precipitation during boreal summer are analyzed in several innovative weather and climate model integrations. The simulations include: season-long integrations of the Non-hydrostatic Icosahedral Atmospheric Model (NICAM) with explicit clouds and convection; year-long integrations of the operational Integrated Forecast System (IFS) from the European Centre for Medium-range Weather Forecasts at three resolutions (125, 39 and 16 km); seasonal simulations of the same model at 10 km resolution; and seasonal simulations of the National Center for Atmospheric Research (NCAR) low-resolution climate model with and without an embedded two-dimensional cloud-resolving model in each grid box. NICAM with explicit convection simulates best the phase of the diurnal cycle, as well as many regional features such as rainfall triggered by advancing sea breezes or high topography. However, NICAM greatly overestimates mean rainfall and the magnitude of the diurnal cycle. Introduction of an embedded cloud model within the NCAR model significantly improves global statistics of the seasonal mean and diurnal cycle of rainfall, as well as many regional features. However, errors often remain larger than for the other higher-resolution models. Increasing resolution alone has little impact on the timing of daily rainfall in IFS with parameterized convection, yet the amplitude of the diurnal cycle does improve along with the representation of mean rainfall. Variations during the day in atmospheric prognostic fields appear quite similar among models, suggesting that the distinctive treatments of model physics account for the differences in representing the diurnal cycle of precipitation.