A multi-model ensemble of downscaled spatial climate change scenarios for the Dommel catchment, Western Europe

Regional or local scale hydrological impact studies require high resolution climate change scenarios which should incorporate some assessment of uncertainties in future climate projections. This paper describes a method used to produce a multi-model ensemble of multivariate weather simulations including spatial–temporal rainfall scenarios and single-site temperature and potential evapotranspiration scenarios for hydrological impact assessment in the Dommel catchment (1,350 km²) in The Netherlands and Belgium. A multi-site stochastic rainfall model combined with a rainfall conditioned weather generator have been used for the first time with the change factor approach to downscale projections of change derived from eight Regional Climate Model (RCM) experiments for the SRES A2 emission scenario for the period 2071–2100. For winter, all downscaled scenarios show an increase in mean daily precipitation (catchment average change of +9% to +40%) and typically an increase in the proportion of wet days, while for summer a decrease in mean daily precipitation (−16% to −57%) and proportion of wet days is projected. The range of projected mean temperature is 7.7°C to 9.1°C for winter and 19.9°C to 23.3°C for summer, relative to means for the control period (1961–1990) of 3.8°C and 16.8°C, respectively. Mean annual potential evapotranspiration is projected to increase by between +17% and +36%. The magnitude and seasonal distribution of changes in the downscaled climate change projections are strongly influenced by the General Circulation Model (GCM) providing boundary conditions for the RCM experiments. Therefore, a multi-model ensemble of climate change scenarios based on different RCMs and GCMs provides more robust estimates of precipitation, temperature and evapotranspiration for hydrological impact assessments, at both regional and local scale.     

4种再分析月降水数据在内蒙古地区的适用性分析

利用1981—2020年气象台站的实测降水数据,对CRA40、ERA5、JRA55和MERRA2这4种再分析月降水数据在内蒙古地区的降水分布特征,与实测降水的相关性和误差进行分析。结果表明：(1)内蒙古地区4种再分析降水数据的空间分布与台站降水基本一致,误差分析表明CRA40与MERRA2的数据质量较高,ERA5次之,而JRA55数据质量相对较差。(2)CRA40和MERRA2在1983—1986年存在明显的降水低估,ERA5在2005年之后的内蒙古中东部出现明显的降水低估,JRA55在115°E以东存在明显降水高估,在115°E以西则以降水低估为主。(3)4种再分析月降水数据的年内最大均方根误差和绝对误差均集中在6—8月,与台站降水相关系数的年内最小值均出现在7月,内蒙古夏季汛期是再分析降水误差产生的主要时段。     

Modelling the Meteorology at the Cabauw Tower for 2005

The meteorology at the Cabauw tower site in the Netherlands has been modelled for 2005 using a local scale prognostic meteorological and air pollution model called TAPM. A number of performance measures have been used to assess model accuracy, including comparison statistics such as root-mean-square error (RMSE) and index of agreement (IOA). Results show that the model performs very well for prediction of wind and temperature at the six tower levels that range from 10 to 200 m above the ground, as well as performing well for radiation and surface fluxes. The model simulation shows almost no bias in mean and standard deviations of wind and temperature at each tower height level, with small RMSE (e.g. RMSE of 1.2 m s⁻¹ for 10-m wind speed, and 1.6°C for 10-m temperature) and high correlation and IOA (e.g. IOA of 0.92 for 10-m wind speed and 0.98 for 10-m temperature). Results for radiation and surface fluxes also show good performance, although some biases were seen for these variables, and possibilities for future model development were identified. An examination of model sensitivity also explored several aspects of the model configuration and input.     

利用深度学习预报美国东北部日降水分布

现阶段降水预报主要依靠数值天气预报模式。但受物理参数化、计算资源等因素的影响,基于数值模式的降水预报还存在非常大的不确定性。近年来,深度学习在天气预报领域显示出巨大优势和潜力。本文通过构建神经网络预报美国东北部日降水分布,探讨神经网络模型基于低分辨率气象场(ERA-Interim, 0.7°)预报高分辨率降水(CPC,0.25°)的能力,并比较3种主流网络框架(VGG,ResNet, GoogleNet)在该任务中的表现。结果表明,3种网络框架都对美国东北部日降水分布具有一定的预报能力(VGG框架表现最优),但三者的均方根误差(RMSE)均高于ERA-Interim 24-h(ERA24)的降水预报。3种神经网络的集合预报结果优于ERA24预报,且这三者与ERA24预报结果的集合平均能够显著提高ERA24对不同季节、不同强度降水的预报。     

利用ERA5资料进行桂林地区GNSS水汽反演精度分析

由于桂林地区地基GNSS站并未配置气象传感器，致使大量GNSS观测数据无法在大气水汽（PWV）监测中发挥作用.针对这一情况，本文将欧洲中期天气预报中心（ECMWF）最新发布的ERA5再分析资料中测站处的气压和温度气象数据加入到GNSS水汽反演中，并将反演结果与利用地面气象站反演的GNSS水汽做对比，以此评估ERA5在桂林地区反演GNSS水汽的精度和适用性.结果表明：1）以桂林地区2017年10个地面气象站的实测气压和温度数据为参考值，ERA5地表气压和温度的年均偏差分别为-0.35 hPa和0.86 K，年均均方根误差（RMSE）分别为0.65 hPa和1.66 K，该精度可用于GNSS水汽反演；2）以2017年6—7月GNSS利用地面气象站反演的PWV为参考值，ERA5反演的GNSS PWV的偏差和RMSE分别为0.17 mm和0.35 mm，且两者具较好的相关性和一致性.由此表明，ERA5地表温压产品可应用于桂林地区GNSS水汽反演，这些研究结果可为桂林地区的GNSS水汽反演及数据源的选用提供重要的参考依据.     

On the Factors Controlling the Snow Surface and 2-m Air Temperatures Over the Arctic Sea Ice in Winter

Factors controlling the magnitudes of, and short-term variations in, the potential temperatures of the snow surface and the air at the height of 2 m θ_S and θ_{2 m} over Arctic sea ice in winter are analysed. The study addresses the winters of 1986–1987 and 1987–1988, and is based on the temperature, wind, and cloud observations made by Russian drifting ice stations. It also relies on the ERA40 re-analyses of the European Centre for Medium-Range Weather Forecasts, which were utilised to calculate the lateral heat advection at the sites of the ice stations. The cloud cover and wind speed were more important than the heat advection in controlling the magnitudes of θ_{2 m} and θ_S, while on a time scale of 24 h, during steady forcing conditions, the heat advection was the most important factor affecting the changes in θ_S and θ_{2 m}. During changing conditions, and considering individual factors separately, the monthly mean 24-h temperature changes were less than ± 5 °C: the effect of the cloud cover was the largest, and that of the heat advection was the smallest. When simultaneous changes in the three factors were analysed, the seasonal mean temperature changes were even of the order of ±15 °C, with the strongest warming events exceeding 35 K in a single day. The difference θ_S − θ_{2 m} reached its lowest seasonal mean values during conditions of clear skies (−1.3 °C), light winds (−1.3 °C) and warm-air advection (−0.8 °C). θ_S and θ_{2 m} followed each other closely, even during major synoptic-scale temperature variations.     

中国区域高分辨率多源降水观测产品的融合方法试验

高质量、高分辨率降水产品研制对于数值天气模式检验、水文陆面模拟、山洪地质灾害监测有着重要意义。利用中国近4万自动气象站逐时降水资料、中国雷达定量降水估计和CMORPH卫星反演降水产品,开展0.05°×0.05°和0.01°×0.01°两种高分辨率下的三源降水融合方法研究试验,探讨如何有效引入雷达高分辨率信息来提高降水产品质量。一方面,在0.05°分辨率上,先以自动气象站观测降水数据为基准,采用概率密度函数（PDF）匹配法订正雷达和卫星估测降水产品的系统偏差,将雷达降水产品的偏差从-0.05 mm/h降至-0.008 mm/h;再采用贝叶斯模型平均（BMA）方法融合雷达和卫星降水产品,形成0.05°分辨率的中国区域覆盖完整且最优的联合降水背景场。此外,在0.01°分辨率上,以0.05°分辨率的卫星-雷达贝叶斯模型平均联合降水产品为背景,采用1 km雷达估测降水的空间结构信息进行降尺度,亦能有效提高0.01°分辨率背景场的质量。然后,分别以不同分辨率的卫星-雷达联合降水产品为背景,采用统计方法量化误差估计,再采用最优插值方法融入地面观测。通过2419个中国国家级气象台站的独立样本检验,评估了多种类型的降水资料及融合试验产品在中国地区的质量。结果表明,两种分辨率的三源融合试验产品的精度均优于任何单一来源的降水产品,特别是在站点稀疏地区,降水精度均较融合前有显著提高,达到了较好的融合效果,其中在0.05°分辨率上采用“概率密度函数+贝叶斯模型平均+最优插值”方法的三源融合降水产品整体质量最好,而0.01°分辨率上基于“概率密度函数+贝叶斯模型平均+降尺度+最优插值”方法的三源融合降水产品在强降水监测上更有优势。      

Influence of vegetation changes during the Last Glacial Maximum using the BMRC atmospheric general circulation model

 The influence of different vegetation distributions on the atmospheric circulation during the Last Glacial Maximum (LGM, 21 000 years before present) is investigated. The atmospheric general circulation model of the Bureau of Meteorology Research Center was run using a modern vegetation and in a second experiment with a vegetation reconstruction for the LGM. It is found that a change from conifer to desert and tundra causes an additional LGM cooling of 1–2 °C in Western Europe, up to −4 °C in North America and −6 °C in Siberia. An expansion of dryland vegetation causes an additional annual cooling of 1–2 °C for Australia and northern Africa. On the other hand, an increase of temperature (2 °C) is found in Alaska due to changes in circulation. In the equatorial region the LGM vegetation leads to an increased modelled temperature of 0.5–1.5 °C and decreased precipitation (30%) over land due to a reduction of the tropical rainforest, mainly in Indonesia, where the reduction of precipitation over land is associated with an increase of precipitation of 30% over the western Pacific. Received: 15 December 1999 / Accepted: 10 January 2001     

An assessment of the latent and sensible heat flux on the simulated regional climate over Southwestern South Atlantic Ocean

A Regional Climate Model (RegCM3) 10-year (1990–1999) simulation over southwestern South Atlantic Ocean (SAO) is evaluated to assess the mean climatology and the simulation errors of turbulent fluxes over the sea. Moreover, the relationship between these fluxes and the rainfall over some cyclogenetic areas is also analyzed. The RegCM3 results are validated using some reanalyses datasets (ERA40, R2, GPCP and WHOI). The summer and winter spatial patterns of latent and sensible heat fluxes simulated by the RegCM3 are in agreement with the reanalyses (WHOI, R2 and ERA40). They show large latent heat fluxes exchange in the subtropical SAO and at higher latitudes in the warm waters of Brazil Current. In particular, the magnitude of RegCM3 latent heat fluxes is similar to the WHOI, which is probably related to two factors: (a) small specific humidity bias, and (b) the RegCM3 flux algorithm. In contrast, the RegCM3 presents large overestimation of sensible heat flux, though it simulates well their spatial pattern. This simulation error is associated with the RegCM3 underestimation of the 2-m air temperature. In southwestern SAO, in three known cyclogenetic areas, the reanalyses and the RegCM3 show the existence of different physical mechanisms that control the annual cycles of latent/sensible heating and rainfall. It is shown that over the eastern coast of Uruguay (35°–43°S) and the southeastern coast of Argentina (44°–52°S) the sea-air moisture and heat exchange play an important role to control the annual cycle of precipitation. This does not happen on the south/southeastern coast of Brazil.     

基于三台测风激光雷达的大气湍流和三维风场研究

为了获取大气湍流和空间三维风场结构,利用3台同型号的测风激光雷达开展协同观测试验。（1）利用虚拟铁塔协同观测技术开展大气湍流探测,与香河102 m铁塔安装的三维超声风速仪观测结果做对比,32 m处高频（10 Hz）风速的相关系数高达0.92,平均误差为0.77 m/s,均方根误差为0.41 m/s;大气湍流强度（TKE）的相关系数高达0.99,平均误差为?0.02 m2/s2,均方根误差为0.08 m2/s2,并且协同观测的高频风速与三维超声风速仪的观测结果具有相同的频谱结构。（2）利用扫描协同观测技术开展三维风场探测,与铁塔上的常规测风设备相比,其90 m高度处的水平风速和风向的相关系数分别为0.92和0.93,平均误差为?0.41 m/s和0°,均方根误差为0.73 m/s和34°。相比于单台测风激光雷达,基于3台测风激光雷达协同观测技术具有一定的优势:不需要风场水平均匀的假设、探测精度更高等。但其对观测环境的要求较高:观测路径上不能有遮挡、观测必须协同等。在科研业务应用中,需要根据实际的观测需求合理制定观测方案。      

Forecasting weather radar propagation conditions

Summary The increasing use of weather radar quantitative precipitation estimates, particularly in automatic applications such as operational hydrometeorological modelling or assimilation in numerical weather prediction (NWP) models, has promoted the development of quality control procedures on radar data. Anomalous propagation (AP) of the radar beam due to deviation from the standard refractivity vertical profile, is one of the factors that may affect seriously the quality of radar observations because of the increase in quantity and intensity of non-precipitating clutter echoes and consequent contamination of the estimated rainfall field. Another undesired effect of AP is the change in the expected radar echo height, which may be relevant when correcting for beam blockage in radar rainfall estimation in complex terrain. The aim of this paper is to study the use of NWP mesoscale forecasts to predict and monitor AP events. A nested 15-km grid resolution version of the MASS model has been used to retrieve refractivity profiles in the coastal area of Barcelona, near a weather radar and a radiosonde station. Using the refractivity profiles two different magnitudes were computed: the vertical refractivity profile of the lowest 1000 m layer and a ducting index which describes the existence and intensity of the most super-refractive layer contained in the lowest 3-km layer. A comparison between model forecasts and radiosonde diagnostics during a six-month period showed that the model tended to underestimate the degree of super-refraction, with a bias of 4 km⁻¹ and RMSE of 11 km⁻¹ in the 1-km vertical refractivity gradient. Further analysis of the data showed that a combination of previous observations and forecasts allowed to produce modified forecasts improving the original direct model output, decreasing substantially the bias, reducing the RMSE by 20% and improving the skill by 40%, beating also radiosonde observations persistence.     

HRCLDAS-V1.0和ERA5海面风场对比评估分析

基于2020年中国近海31个浮标的逐小时数据,使用统计分析方法对中国气象局高分辨率陆面数据同化系统(HRCLDAS-V1.0)和欧洲中期天气预报中心第5代全球大气再分析数据(ERA5)海面风场进行了系统的检验,检验结果表明:两者在我国近海均具有较高的可信度,风速平均绝对误差(MAE)分别为1.16 m/s和1.09 m/s,风向MAE分别为23 °和22 °。随着风力增大两者的风速准确度均有所降低,当风力等级≥10级时,前者准确度优于后者;对于风向而言,随着风力增大,两者准确度均升高。此外,选取2020年典型的两次冷空气过程和2008号台风“巴威”过程,检验两者在不同天气过程影响下的准确度,两类融合产品均能较好地再现冷空气过程引起的风向变化,而对不同强度的冷空气过程下的风速反映存在差异;对于台风引起的大风,在风速较低时两者风速均具有不错的表现,但HRCLDAS-V1.0对峰值强度的表现优于ERA5。      

Tropical Cyclone Genesis Potential Index over the Western North Pacific Simulated by LASG/IAP AGCM

Tropical cyclone genesis potential index(GPI) is a useful metric for gauging the performance of global climate models in the simulation of tropical cyclone(TC) genesis.The performance of LASG/IAP AGCM GAMIL2.0 in the simulation of GPI over the western North Pacific(WNP) is assessed in this paper.Since GPI depends on large scale environmental factors including low-level vorticity at 850 hPa,relative humidity at 700 hPa,vertical wind shear between 850 and 200 hPa,maximum potential intensity(MPI),and vertical velocity,the bias of GPI simulation is discussed from the perspective of thermal and dynamical factors.The results are compared with the ECMWF reanalysis data(ERA40).The analyses show that both the climatological spatial pattern and seasonal cycle of GPI over the WNP are reasonably simulated by GAMIL2.0,but due to the overestimation of relative humidity,the simulated GPI extends to 170°E,about 10°east to that in the reanalysis data.It is demonstrated that the bias in the simulation of monsoon trough,which is about 5°north to the reanalysis,leads to an overestimation of GPI during May-June and September-October,but an underestimation during July-August.Over the WNP,the response of GPI to ENSO is well captured by GAMIL2.0,including the eastward(westward) shift of TC genesis location during El Nin o(La Nin a) years.However,the anomalous convective center associated with El Nin o shifts westward about 20°in comparison to ERA40,which leads to the biases in both vertical velocity and relative humidity.These eventually result in the westward deflection of the boundary between the positive and negative GPI centers along 20°-30°N.The results from this study provide useful clues for the future improvement of GAMIL2.0.     

Interannual variability of the surface mass balance of West Antarctica from ITASE cores and ERA40 reanalyses, 1958–2000

Time series of west-Antarctic (WA) annual surface mass balance (SMB) from ITASE firn/ice cores are compared with the ECMWF 1958–2001 ERA40 reanalysis-based model forecasts. The ITASE series partially confirm the spatial structure of the signature of El Nino Southern Oscillation (ENSO) in WA precipitation as previously identified in ERA40 and other models. However, an improvement of ERA40’s ability to reproduce the west-Antarctic SMB since the 1970s is evidenced and is probably related to the onset and increasing use of satellite data in late 1972 and 1978. Restricting the analysis to the 1973–2000 (satellite) period, interannual correlations between ITASE cores and ERA40 SMB series are generally significant (95% confidence level) but weak. The fraction of common variability increases when the series are spatially averaged, suggesting that small-scale perturbation (SSP) of the large-scale SMB variability significantly contributes to year-to-year variability in single core series. A comparison of stake network and core data from the South Pole suggests that SSP can almost fully obscure the large-scale component of the SMB variability as recorded in a single core. Because of SSP, the 1973–2000 period is too brief to verify whether all aspects of the WA large-scale signatures of ENSO and of the Antarctic Oscillation suggested by ERA40 are confirmed in the core series. More annually resolved field data from cores and stakes, spatially extended using high-resolution ground penetrating radar, are necessary to fully assess the relationship between the Antarctic SMB and the large-scale climate as currently suggested by meteorological and climate models.     

北京MST雷达功率谱密度处理算法改进

北京MST（mesosphere-stratosphere-troposphere,中间层-平流层-对流层）雷达是我国“子午工程”一期中探测大气动力结构的独特大型设备。雷达自2011年建成以来,已获取较好的大气风场数据,但在其他要素提取方面仍有改进需求。从噪声电平估算与目标回波识别这两个关键步骤改进雷达原始功率谱密度处理算法,以期得到更准确的大气要素信息。在噪声电平估算方面,提出应用对数-线性拟合方案快速实现客观分析法,与二分法方案差值的标准差为0.43 dB,表明对数-线性拟合方案能兼顾时效性与准确性。改进后的数据处理算法能够精确识别目标回波。利用改进算法处理2012年1—12月数据结果与雷达、探空以及ERA5再分析数据进行比较,各高度纬向风与探空测值的均方根误差均为2~3 m·s-1,优于雷达产品和探空测值均方根误差（3~4 m·s-1）,信噪比、谱宽和垂直速度质量也有明显提高,表明改进算法可靠、有效且相对易于实现。     

A Comparison Study of Tropical Pacific Ocean State Estimation： Low-Resolution Assimilation vs. High-Resolution Simulation

A comparison study is performed to contrast the improvements in the tropical Pacific oceanic state of a low-resolution model respectively via data assimilation and by an increase in horizontal resolution.A low resolution model (LR) (1°lat by 2°lon) and a high-resolution model (HR) (0.5°lat by 0.5°lon) are employed for the comparison. The authors perform 20-yr numerical experiments and analyze the annual mean fields of temperature and salinity. The results indicate that the low-resolution model with data assimilation behaves better than the high-resolution model in the estimation of ocean large-scale features.From 1990 to 2000, the average of HR's RMSE (root-mean-square error) relative to independent Tropical Atmosphere Ocean project (TAO) mooring data at randomly selected points is 0.97℃ compared to a RMSE of 0.56℃ for LR with temperature assimilation. Moreover, the LR with data assimilation is more frugal in computation. Although there is room to improve the high-resolution model, the low-resolution model with data assimilation may be an advisable choice in achieving a more realistic large-scale state of the ocean at the limited level of information provided by the current observational system.     

Performance assessment of evapotranspiration estimated from different data sources over agricultural landscape in Northern India

Accurate estimation of evapotranspiration is generally constrained due to lack of required hydrometeorological datasets. This study addresses the performance analysis of reference evapotranspiration (ETo) estimated from NASA/POWER, National Center for Environmental Prediction (NCEP) global reanalysis data before and after dynamical downscaling through the Weather Research and Forecasting (WRF) model. The state-of-the-art Hamon’s and Penman-Monteith’s methods were utilized for the ETo estimation in the Northern India. The performance indices such as bias, root mean square error (RMSE), and correlation (r) were calculated, which showed the values 0.242, 0.422, and 0.959 for NCEP data (without downscaling) and 0.230, 0.402, and 0.969 for the downscaled data respectively. The results indicated that after WRF downscaling, there was some marginal improvement found in the ETo as compared to the without downscaling datasets. However, a better performance was found in the case of NASA/POWER datasets with bias, RMSE, and correlation values of 0.154, 0.348, and 0.960 respectively. In overall, the results indicated that the NASA/POWER and WRF downscaled data can be used for ETo estimation, especially in the ungauged areas. However, NASA/POWER is recommended as the ETo calculations are less computationally expensive and easily available than performing WRF simulations.     

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.     

Signature of quasi–biennial oscillation and long-period equatorial disturbances in the lower atmosphere over Thiruvananthapuram

Summary An attempt has been made in this paper to examine different modes of oscillation in the wind field during different seasons over Thiruvananthapuram (lat. 8.29° N, long. 76.59° E, located at the extreme southwest coast of India) based on daily upper air observations for the period from January 1997 to December 1999. A power spectral analysis is carried out with the upper air data of the station. The study shows that one and half cycle of Quasi–Biennial Oscillation (QBO) and the power spectra of the meridional wind component exhibit peaks between the period of four days and seven days (corresponding frequency range between 0.25 day⁻¹ and 0.15 day⁻¹) during all seasons. The seasonal variation of these large-scale oscillations over the station depends upon the background mean zonal flow, which in turn closely related to the QBO structure. The time sequence of power spectra shows that the disturbances with periods between four days and seven days dominantly prevail in the upper troposphere and lower stratosphere throughout the year. The regimes of high power spectral intensity in this period range are maintained in the levels where the mean zonal flow (westerly or easterly) weakens and changes with height. The study establishes the fact that disturbances (mixed Rossby-gravity waves) acquire maximum power in the winter season whereas the south-west monsoon exhibits minimum spectral intensity when spreading of energy over a frequency range takes place.     

中国地面气象要素格点融合业务产品检验

对2018年5 km分辨率中国地面气象要素2m温度、10 m风速和24 h累积降水格点融合产品进行非独立和独立检验.非独立检验结果表明:(1)相比于站点观测,2m温度格点融合产品整体偏暖,各月平均均方根误差在1 ℃左右,35 ℃以上高温和-20 ℃以下低温天气时均方根误差分别在1 ℃和2 ℃以上.(2)10m风速格点融...