CERES-Wheat模型在我国小麦区的应用效果及误差来源

气候模型与作物模型耦合是评价未来气候变化对作物生产影响的常用方法之一, 但当两者结合时, 存在着空间和时间尺度差异问题, 将作物模型升尺度到区域是解决该差异的一种方法。将CERES-Wheat模型升尺度进行区域模拟, 利用区域校准后的CERES-Wheat模型, 模拟了1981—2000年全国各网格小麦产量, 与同期农调队调查产量相比较, 以探讨CERES-Wheat模型在我国小麦区的模拟效果及误差来源。结果表明:全国小麦产量的区域模拟值与农调队调查产量的相对均方根误差为27.9%, 符合度为0.75, 全国59.2%的模拟网格相对均方根误差在30%以内, 其中相对均方根误差小于15%的占26.3%;各区的效果不同, 种植面积最大的小麦种植生态2区, 模拟效果最好。总体来说, CERES-Wheat的区域模拟, 可以反映产量变化规律, 能为宏观决策提供相应信息, 尤其是在主产区; 但区域模拟中还存在一系列误差, 今后还需进一步研究。     

Mapping near-surface air temperature,pressure, relative humidity and wind speed over Mainland China with high spatiotemporal resolution

As part of a joint effort to construct an atmospheric forcing dataset for mainland China with high spatiotemporal reso- lution, a new approach is proposed to construct gridded near-surface temperature, relative humidity, wind speed and surface pressure with a resolution of 1 km× 1 km. The approach comprises two steps： （1） fit a partial thin-plate smoothing spline with orography and reanalysis data as explanatory variables to ground-based observations for estimating a trend surface; （2） apply a simple kriging procedure to the residual for trend surface correction. The proposed approach is applied to observations collected at approximately 700 stations over mainland China. The generated forcing fields are compared with the corresponding components of the National Centers for Environmental Predic- tion （NCEP） Climate Forecast System Reanalysis dataset and the Princeton meteorological forcing dataset. The comparison shows that, both within the station network and within the resolutions of the two gridded datasets, the interpolation errors of the proposed approach are markedly smaller than the two gridded datasets.     

Trends and uncertainties in surface air temperature over the Tibetan Plateau, 1951–2013

Trends and uncertainties of surface air temperature over the Tibetan Plateau (TP) are evaluated by using observations at 100 meteorological stations during the period 1951–2013. The sampling error variances of gridded monthly data are estimated for every month and every grid box of data. The gridded data and their sampling error variances are used to calculate TP averages, their trends, and associated uncertainties. It is shown that large sampling error variances dominate northern and western TP, while small variances appear over southern and eastern TP. Every month from January to December has a positive linear trend during the study period. February has the largest trend of 0.34 ± 0.18°C (10 yr)^–1, and April the smallest at 0.15 ± 0.11°C (10 yr)^–1. The uncertainties decrease steadily with time, implying that they are not large enough to alter the TP warming trend.     

Rainfall Algorithms Using Oceanic SatelliteObservations from MWHS-2

正1EarthEnvironmental Sciences Department, Vanderbilt University, Nashville, TN 37235, USA2Space ScienceEngineering Center, University of Wisconsin-Madison, Madison, WI 53706, USA     

交叉定标产生的NOAA卫星长期大气温度观测资料

介绍一套用于气候变化研究的NOAA卫星微波观测资料, 资料为全球5 d平均, 2.5°×2.5°经纬网格, 3个深层大气(对流中层、对流层顶以及平流层下层)的温度分布。该文简介了资料产生的方法, 包括交叉定标、角度订正、网格化以及网格误差修正等, 给出了使用这套资料分析得到的1987—2006年间不同大气层的温度变化趋势, 并提供了获取这套资料的方法。     

Precipitation and temperature space–time variability and extremes in the Mediterranean region: evaluation of dynamical and statistical downscaling methods

This study evaluates how statistical and dynamical downscaling models as well as combined approach perform in retrieving the space–time variability of near-surface temperature and rainfall, as well as their extremes, over the whole Mediterranean region. The dynamical downscaling model used in this study is the Weather Research and Forecasting (WRF) model with varying land-surface models and resolutions (20 and 50 km) and the statistical tool is the Cumulative Distribution Function-transform (CDF-t). To achieve a spatially resolved downscaling over the Mediterranean basin, the European Climate Assessment and Dataset (ECA&D) gridded dataset is used for calibration and evaluation of the downscaling models. In the frame of HyMeX and MED-CORDEX international programs, the downscaling is performed on ERA-I reanalysis over the 1989–2008 period. The results show that despite local calibration, CDF-t produces more accurate spatial variability of near-surface temperature and rainfall with respect to ECA&D than WRF which solves the three-dimensional equation of conservation. This first suggests that at 20–50 km resolutions, these three-dimensional processes only weakly contribute to the local value of temperature and precipitation with respect to local one-dimensional processes. Calibration of CDF-t at each individual grid point is thus sufficient to reproduce accurately the spatial pattern. A second explanation is the use of gridded data such as ECA&D which smoothes in part the horizontal variability after data interpolation and damps the added value of dynamical downscaling. This explains partly the absence of added-value of the 2-stage downscaling approach which combines statistical and dynamical downscaling models. The temporal variability of statistically downscaled temperature and rainfall is finally strongly driven by the temporal variability of its forcing (here ERA-Interim or WRF simulations). CDF-t is thus efficient as a bias correction tool but does not show any added-value regarding the time variability of the downscaled field. Finally, the quality of the reference observation dataset is a key issue. Comparison of CDF-t calibrated with ECA&D dataset and WRF simulations to local measurements from weather stations not assimilated in ECA&D, shows that the temporal variability of the downscaled data with respect to the local observations is closer to the local measurements than to ECA&D data. This highlights the strong added-value of dynamical downscaling which improves the temporal variability of the atmospheric dynamics with regard to the driving model. This article highlights the benefits and inconveniences emerging from the use of both downscaling techniques for climate research. Our goal is to contribute to the discussion on the use of downscaling tools to assess the impact of climate change on regional scales.     

基于四维数据同化技术的千米格距网格化气象数据集:构建及初步应用

利用基于张弛逼近的四维数据同化技术,构建了广东深圳的千米格距网格化气象数据集,由于同化了深圳及周边可获得的高频次观测数据,气象数据集基本准确表现出几种关键气象要素的年际变化和月变化特征。在网格化气象数据集基础上开发了“深圳市细网格气候信息平台”,并通过平台推出了若干精细气候数据产品:精细风玫瑰、逐网格风能等。这些数据产品已经在格点气温预报、风能示范项目选址以及详细规划的自然通风评估中发挥了实际作用。这些探索表明,网格化气象数据集的建立,有望为城市的网格化精细管理和建设提供气象科技支撑。      

Estimation of sampling error uncertainties in observed surface air temperature change in China

This study examines the sampling error uncertainties in the monthly surface air temperature (SAT) change in China over recent decades, focusing on the uncertainties of gridded data, national averages, and linear trends. Results indicate that large sampling error variances appear at the station-sparse area of northern and western China with the maximum value exceeding 2.0 K² while small sampling error variances are found at the station-dense area of southern and eastern China with most grid values being less than 0.05 K². In general, the negative temperature existed in each month prior to the 1980s, and a warming in temperature began thereafter, which accelerated in the early and mid-1990s. The increasing trend in the SAT series was observed for each month of the year with the largest temperature increase and highest uncertainty of 0.51 ± 0.29 K (10 year)⁻¹ occurring in February and the weakest trend and smallest uncertainty of 0.13 ± 0.07 K (10 year)⁻¹ in August. The sampling error uncertainties in the national average annual mean SAT series are not sufficiently large to alter the conclusion of the persistent warming in China. In addition, the sampling error uncertainties in the SAT series show a clear variation compared with other uncertainty estimation methods, which is a plausible reason for the inconsistent variations between our estimate and other studies during this period.

     

Resolution effects on regional climate model simulations of seasonal precipitation over Europe

We analyze a set of nine regional climate model simulations for the period 1961–2000 performed at 25 and 50 km horizontal grid spacing over a European domain in order to determine the effects of horizontal resolution on the simulation of precipitation. All of the models represent the seasonal mean spatial patterns and amount of precipitation fairly well. Most models exhibit a tendency to over-predict precipitation, resulting in a domain-average total bias for the ensemble mean of about 20% in winter (DJF) and less than 10% in summer (JJA) at both resolutions, although this bias could be artificially enhanced by the lack of a gauge correction in the observations. A majority of the models show increased precipitation at 25 km relative to 50 km over the oceans and inland seas in DJF, JJA, and ANN (annual average), although the response is strongest during JJA. The ratio of convective precipitation to total precipitation decreases over land for most models at 25 km. In addition, there is an increase in interannual variability in many of the models at 25 km grid spacing. Comparison with gridded observations indicates that a majority of models show improved skill in simulating both the spatial pattern and temporal evolution of precipitation at 25 km compared to 50 km during the summer months, but not in winter or on an annual mean basis. Model skill at higher resolution in simulating the spatial and temporal character of seasonal precipitation is found especially for Great Britain. This geographic dependence of the increased skill suggests that observed data of sufficient density are necessary to capture fine-scale climate signals. As climate models increase their horizontal resolution, it is thus a key priority to produce high quality fine scale observations for model evaluation.     

格点尺度对TRMM微波成像仪云水数据的影响

选取热带测雨卫星(Tropical Rainfall Measuring Mission,TRMM)微波成像仪(TRMM Microwave Imager,TMI)液态水路径(liquid water path,LWP)轨道像元数据为研究对象,探讨了将瞬时探测以及逐月的像元数据进行格点化(0.1°、0.25°、0.5°、1.0°和2.5°五种格点分辨率)时,格点数据的失真情况。对TMI瞬时探测的个例分析结果表明,细分辨率(0.1°、0.25°和0.5°)格点能保留原始像元数据的细节;而随着网格变粗,细节受到较大的平滑。因此对于中尺度到天气尺度的天气系统分析而言,将卫星轨道数据处理到网格尺度不大于0.5°的格点更合适。对逐月LWP像元资料格点化处理的分析表明,细分辨率格点能保留LWP空间分布细节,尽管5种分辨率下LWP的概率密度分布(probability density function,PDF)均相近。因此,对月尺度及以上的气候分析研究而言,格点尺度大小对卫星像元数据格点化的影响不显著。最后利用本实验室计算的TMI/LWP格点数据与欧洲中期数值预报中心再分析资料(European Centre for Medium-range Weather Forecasts Interim reanalysis,ERA-Interim)和NCEP再分析资料(NCEP Climate Forecast System Reanalysis,NCEP CFSR)进行了对比,发现两种再分析资料都高估了LWP;TMI/LWP格点数据与两种再分析资料LWP的多年变化趋势大致相同。     

Role of convective parameterization in simulations of heavy precipitation systems at grey-zone resolutions — case studies

We have investigated the role of convective parameterization in simulations of heavy precipitation systems at grey-zone (2–10 km) resolutions using an approach similar to that used in “observing system simulation experiment”. Simulations with a 1-km grid serve as benchmark simulations. The impacts of convective parameterization at greyzone resolutions (i.e., 3, 6, and 9 km) are then investigated. This study considers two heavy precipitation systems including one associated with a mesoscale cyclone generated over the Shandong Peninsula on 24–25 July 1991, and the other associated with a cloud cluster occurred on 15–16 July 2009. The present study indicates that convective parameterization does not affect much the simulations of the two heavy precipitation systems with 3-km grid size. However, it significantly affects simulations for grid sizes of 6 and 9 km. Simulations with the Kain-Fritsch scheme produce deficiencies such as relatively small heavy rainfall area, smaller maximum precipitation rate, wider area of weak precipitation, etc. Simulations without convective parameterization have also some negative effects such as the overprediction of area-averaged precipitation rate and others. A modified trigger function in the Kain-Fritsch scheme is found to improve the simulations of the heavy precipitation systems over the Korean Peninsula by reducing excessive trigger of convection, especially for simulations with 6- and 9- km grids.     

A Limb Correction Method for the Microwave Temperature Sounder 2 and Its Applications

The Microwave Temperature Sounder 2 (MWTS-2) is a cross-track radiometer that has 13 channels of sampling radiances emitted from different vertical levels of the atmosphere. Because of the varying scan angles of each field of view within a scan line, observations from the MWTS-2 are subject to strong scan-position-dependent features, i.e., the limb effect. When examining brightness temperatures (TBs), weather signals observed at every temperature-sounding channel are often concealed by scan-dependent patterns. This study, therefore, proposes a limb correction method to remove scan-dependent features so that the underlying weather signals can be uncovered. Limb-corrected TBs can be used to monitor large-scale patterns over the globe as well as extreme weather events such as typhoons. Limb-corrected TBs are also more correlated with atmospheric physical variables such as temperature and liquid water path.     

High resolution simulations of January and July climate over the western Alpine region with a nested Regional Modeling system

Summary High resolution January and July present day climatologies over the central-western Alpine region are simulated with a Regional Climate Model (RegCM) nested within a General Circulation Model (GCM). The RegCM was developed at the National Center for Atmospheric Research (NCAR) and is run at 20 km grid point spacing. The model is driven by output from a present day climate simulation performed with the GCM ECHAM3 of the Max Planck Institute for Meteorology (MPI) at T106 resolution (~ 120 km). Five January and July simulations are conducted with the nested RegCM and the results for surface air temperature and precipitation are compared with a gridded observed dataset and a dataset from 99 observing stations throughout the Swiss territory. The driving ECHAM3 simulation reproduces well the position of the northeastern Atlantic jet, but underestimates the jet intensity over the Mediterranean. Precipitation over the Alpine region in the ECHAM3 simulation is close to observed in January but lower than observed in July. Compared to the driving GCM, the nested RegCM produces more precipitation in both seasons, mostly as a result of the stronger model orographic forcing. Average RegCM temperature over the Swiss region is 2–3 degrees higher than observed, while average precipitation is within 30% of observed values. The spatial distribution of precipitation is in general agreement with available gridded observations and the model reproduces the observed elevation dependency of precipitation in the summer. In the winter the simulated elevation of maximum precipitation amounts is lower than observed. Precipitation frequencies are overestimated, while precipitation intensities show a reasonable agreement with observations, especially in the winter. Sensitivity experiments with different cumulus parameterizations, soil moisture initialization and model topography are discussed. Overall, the model performance at the high resolution used here did not deteriorate compared to previous lower resolution experiments.The National Center for Atmospheric Research is sponsored by the National Science Foundation.With 11 Figures     

Observed (1970–1999) climate variability in Central America using a high-resolution meteorological dataset with implication to climate change studies

High spatial resolution of precipitation (P) and average air temperature (Tavg) datasets are ideal for determining the spatial patterns associated with large-scale atmospheric and oceanic indexes, and climate change and variability studies, however such datasets are not usually available. Those datasets are particularly important for Central America because they allow the conception of climate variability and climate change studies in a region of high climatic heterogeneity and at the same time aid the decisionmaking process at the local scale (municipalities and districts). Tavg data from stations and complementary gridded datasets at 50 km resolution were used to generate a high-resolution (5 km grid) dataset for Central America from 1970 to 1999. A highresolution P dataset was used along with the new Tavg dataset to study climate variability and a climate change application. Consistently with other studies, it was found that the 1970-1999 trends in P are generally non-significant, with the exception of a few small locations. In the case of Tavg, there were significant warming trends in most of Central America, and cooling trends in Honduras and northern Panama. When the sea surface temperature anomalies between the Tropical Pacific and the Tropical Atlantic have different (same) sign, they are a good indicator of the sign of P (Tavg) annual anomalies. Even with non-significant trends in precipitation, the significant warming trends in Tavg in most of Central America can have severe consequences in the hydrology and water availability of the region, as the warming would bring increases in evapotranspiration, drier soils and higher aridity.     

Effects of a Remotely Sensed Land Cover Dataset with High Spatial Resolution on the Simulation of Secondary Air Pollutants over China Using the Nested-grid GEOS-Chem Chemical Transport Model简

A number of remotely sensed land cover datasets with spatial resolutions ~〈 1 km have recently become available or are in the process of being mapped. The application of these higher resolution and more up-to-date land cover datasets in chemical transport models （CTMs） is expected to improve the simulation of dry deposition and biogenic emissions of non-methane volatile organic compounds （NMVOCs）, which affect ozone and other secondary air pollutants. In the present study, we updated the land cover dataset in the nested-grid GEOS-Chem CTM with the 1 km resolution GLC2000 land cover map and examined the resulting changes in the simulation of surface ozone and sulfate over China in July 2007. Through affecting the dry deposition velocities of ozone and its precursors, using GLC2000 in the dry deposition module can decrease the simulated surface ozone by 3% （up to 6 ppb） over China. Simulated surface sulfate shows an increase of 3% in northwestern China and a decrease of 1% in northern China. Applying GLC2000 in the biogenic emissions of the NMVOC module can lead to a 0.5--4.5 ppb increase in simulated surface ozone over East China, mainly driven by the larger cove~：age of broadleaf trees in East China in the GLC2000 dataset. Our study quantifies the large sensitivity to land cover dataset~ with different spatial resolutions and time periods of simulated secondary air pollutants over China, supporting ongoing research efforts to produce high resolution and dynamically updated land cover datasets over China, as well as for the globe.     

Analysis of Sampling Error Uncertainties and Trends in Maximum and Minimum Temperatures in China简

In this paper we report an analysis of sampling error uncertainties in mean maximum and minimum temperatures （Tmax and Tmin） carried out on monthly,seasonal and annual scales,including an examination of homogenized and original data collected at 731 meteorological stations across China for the period 1951-2004.Uncertainties of the gridded data and national average,linear trends and their uncertainties,as well as the homogenization effect on uncertainties are assessed.It is shown that the sampling error variances of homogenized Tmax and Tmin,which are larger in winter than in summer,have a marked northwest-southeast gradient distribution,while the sampling error variances of the original data are found to be larger and irregular.Tmax and Tmin increase in all months of the year in the study period 1951-2004,with the largest warming and uncertainties being 0.400℃ （10 yr）-1 ＋ 0.269℃ （10 yr）-1 and 0.578℃ （10 yr）-1 ＋ 0.211℃ （10 yr）-1 in February,and the least being 0.022℃ （10 yr）-1 ＋ 0.085℃ （10 yr）-1 and 0.104℃ （10 yr）-1 ＋0.070℃ （10 yr）-1 in August.Homogenization can remove large uncertainties in the original records resulting from various non-natural changes in China.     

Searching for Added Value in Simulating Climate Extremes with a High-Resolution Regional Climate Model over Western Canada. II: Basin-Scale Results

We evaluate the capacity of a regional climate model to simulate the statistics of extreme events, and also examine the effect of differing horizontal resolution, at the scale of individual hydrological basins in the topographically complex province of British Columbia, Canada. Two climate simulations of western Canada (WCan) were conducted with the Canadian Regional Climate Model (version 4) at 15 (CRCM15) and 45?km (CRCM45) horizontal resolution driven at the lateral boundaries by global reanalysis over the period 1973–1995. The simulations were evaluated with ANUSPLIN, a daily observational gridded surface temperature and precipitation product and with meteorological data recorded at 28 stations within the upper Peace, Nechako, and upper Columbia River basins. In this work, we focus largely on a comparison of the skill of each model configuration in simulating the 90th percentile of daily precipitation (PR90). The companion paper describes the results for a wider range of temperature and precipitation extremes over the entire WCan domain.

Over all three watersheds, both simulations exhibit cold biases compared with observations, with the bias exacerbated at higher resolution. Although both simulations generally display wet biases in median precipitation, CRCM15 features a reduced bias in PR90 in all three basins in summer and throughout the year in the upper Columbia River basin. However, the higher resolution model is inferior to CRCM45 with respect to rarer heavy precipitation events and also displays high spatial variability and lower spatial correlations with ANUSPLIN compared with the coarser resolution model. A reduction in the range of PR90 biases over the upper Columbia basin is noted when the 15?km results are averaged to the 45?km grid. This improvement is partly attributable to the averaging of errors between different elevation data used in the gridded observations and CRCM, but the sensitivity of CRCM15 to resolved topography is also clear from spatial maps of seasonal extremes. At the station scale, modest but systematic reductions in the bias of PR90 relative to ANUSPLIN are again found when the CRCM15 results are averaged to the 45?km grid. Furthermore, the annual cycle of inter-station spatial variance in the upper Columbia River basin is well reproduced by CRCM15 but not by ANUSPLIN or CRCM45. The former result highlights the beneficial effect of spatial averaging of small-scale climate variability, whereas the latter is evidently a demonstration of the added value at high resolution vis-à-vis the improved simulation of precipitation at the resolution limit of the model.     

Climate change scenarios of heat waves in Central Europe and their uncertainties

The study examines climate change scenarios of Central European heat waves with a focus on related uncertainties in a large ensemble of regional climate model (RCM) simulations from the EURO-CORDEX and ENSEMBLES projects. Historical runs (1970–1999) driven by global climate models (GCMs) are evaluated against the E-OBS gridded data set in the first step. Although the RCMs are found to reproduce the frequency of heat waves quite well, those RCMs with the coarser grid (25 and 50 km) considerably overestimate the frequency of severe heat waves. This deficiency is improved in higher-resolution (12.5 km) EURO-CORDEX RCMs. In the near future (2020–2049), heat waves are projected to be nearly twice as frequent in comparison to the modelled historical period, and the increase is even larger for severe heat waves. Uncertainty originates mainly from the selection of RCMs and GCMs because the increase is similar for all concentration scenarios. For the late twenty-first century (2070–2099), a substantial increase in heat wave frequencies is projected, the magnitude of which depends mainly upon concentration scenario. Three to four heat waves per summer are projected in this period (compared to less than one in the recent climate), and severe heat waves are likely to become a regular phenomenon. This increment is primarily driven by a positive shift of temperature distribution, but changes in its scale and enhanced temporal autocorrelation of temperature also contribute to the projected increase in heat wave frequencies.     

Proof of the monotonicity of grid size and its application in grid-size selection for mesoscale models

Terrain characteristics can be accurately represented in spectrum space. Terrain spectra can quantitatively reflect the effect of topographic dynamic forcing on the atmosphere. In wavelength space, topographic spectral energy decreases with decreasing wavelength, in spite of several departures. This relationship is approximated by an exponential function. A power law relationship between the terrain height spectra and wavelength is fitted by the least-squares method, and the fitting slope is associated with grid-size selection for mesoscale models. The monotonicity of grid size is investigated, and it is strictly proved that grid size increases with increasing fitting exponent, indicating that the universal grid size is determined by the minimum fitting exponent. An example of landslide-prone areas in western Sichuan is given, and the universal grid spacing of 4.1 km is shown to be a requirement to resolve 90% of terrain height variance for mesoscale models, without resorting to the parameterization of subgrid-scale terrain variance. Comparison among results of different simulations shows that the simulations estimate the observed precipitation well when using a resolution of 4.1 km or finer. Although the main flow patterns are similar, finer grids produce more complex patterns that show divergence zones, convergence zones and vortices.Horizontal grid size significantly affects the vertical structure of the convective boundary layer. Stronger vertical wind components are simulated for finer grid resolutions. In particular, noticeable sinking airflows over mountains are captured for those model configurations.     

气象网格数据的快速渲染研究与应用

随着更高精度的气象网格数据在气象业务中的广泛应用,使用高精度网格数据为社会公众提供精细化气象服务的需求越来越旺盛。针对气象网格数据文件大,网页前端动态渲染效率低等问题,提出基于瓦片金字塔模型的网格数据快速传输和渲染技术的研究及应用。采用服务器端的金字塔模型的瓦片动态切割、压缩传输以及浏览器终端的插值和渲染等技术,实现基于B/S框架下HTML5的气象网格数据快速展示的流程。同时,利用中国区域1 km分辨率多源融合实况分析产品,基于微信小程序终端进行检验发布,试验结果表明,百兆级气象网格数据可视化更新时间达毫秒量级,可以广泛应用于各类空间网格数据高效可视化的页面渲染。