Impact of Satellite Altimetry on Simulations of Sea Level Variability by an Indian Ocean Model

This article describes the impact of satellite altimeter data on the simulations of sea level variability (SLV) by a nonlinear reduced gravity model of the entire Indian Ocean. The model has been forced by 6-hourly analyzed wind stress data containing SSM/I observations and has been able to produce realistic circulation features. However, SLV values observed by Topex/Poseidon altimeter do not fit these simulations because of imperfect initial data. Hence an attempt has been made to initialize the model using altimeter data. The initialized model-generated SLVvalues have been compared with SLV derived by altimeter for monsoon as well as nonmonsoon months of 1996. Experimental runs have been performed for 10 days, 20 days, and one month. It has been found that the initialized model results on the final day of these experiments are in very good agreement with altimeter data of the same day. It is thus possible, in principle, to hindcast and forecast sea level variations in the time scale of 10 days to one month with the availability of good quality wind data for forcing the model and altimeter observations of sea level for initializing it.     

A 44-year high-resolution ocean and atmospheric hindcast for the Mediterranean Basin developed within the HIPOCAS Project

A set of 44-year (1958–2001) homogeneous and high-resolution hindcasts of atmospheric, sea level residuals, and wave states was performed for the Mediterranean Basin within the framework of the HIPOCAS European Project. To this aim, different numerical models were used. As a first step, a Mediterranean high-resolution atmospheric database, suitable to provide realistic and homogeneous forcing for ocean hindcast runs was generated. The HIPOCAS atmospheric database was created by means of dynamical downscaling from the global reanalysis NCEP, using for that the limited area model SN-REMO along with a spectral nudging technique. In a second stage, different Mediterranean oceanic hindcasts were performed. On one hand a long-term database of sea state over the western Mediterranean was generated by means of the wave model WAM and on the other hand a sea level residual database containing storm surge events was obtained from a long-term integration of the HAMSOM model over the entire basin. The three different hindcast runs have been exhaustively validated. On that score, various simulated parameters have been compared to both satellite and in situ measurements. Such comparisons provide a measure of the skills of the different simulated fields to realistically reproduce the observed features. Once these skills are evaluated, a study of the ocean and atmospheric climate trends as well as the interannual variability for the whole 44-year period was carried out with the hindcasted data. The reliability of the data as shown by its comparison to measurements and a proven temporal homogeneity over the 44 years of simulation make the Mediterranean HIPOCAS ocean–atmosphere hindcasted database a useful tool for studies focused on regional climatic variability, as well as for further applications in coastal and environmental decision processes in the Mediterranean area.     

CCSM4.0模式及其驱动下RegCM4.4模式对中国夏季气候的回报分析

使用区域气候模式Reg CM4.4(Regional Climate Model version 4.4)单向嵌套CCSM4.0(Community Climate System Model version 4.0)气候系统模式输出结果,进行了2001~2010年逐年2月1日至9月1日共10年长度的季节尺度气候预测回报试验,针对平均气温和降水,分析了两个模式对中国地区夏季(6~8月)气候的回报能力。首先对气候态的分析表明,Reg CM4.4对气温和降水的回报/模拟效果均较CCSM4.0有所改进,特别是在提供更详细可靠的局地信息方面,其中降水回报与观测的空间相关系数,由CCSM4.0的0.39提高到Reg CM4.4的0.53,但同时Reg CM4.4对中国东部季风降水的回报表现出类似CCSM4.0北方偏多的偏差。对两个模式2001~2010年逐年气温和降水距平的回报能力,通过回报与观测空间和时间距平相关系数(ACCs和ACCt)、回报与观测空间和时间距平符号一致率(PCs和PCt)以及趋势异常综合评分(PS)进行了考察,结果表明两个模式的表现在整体分布上有一定相似的同时,Reg CM4.4能够提供更多的空间分布细节,并对降水的回报结果有一定的改善,如CCSM4.0和Reg CM4.4回报降水的ACCs多年平均分别为0.03和0.10,PS分别为70.4和71.4。同时给出了两个具体年份(2003年和2009年)的个例分析。     

Impact of Satellite Altimetry on Simulations of Sea Level Variability by an Indian Ocean Model

This article describes the impact of satellite altimeter data on the simulations of sea level variability (SLV) by a nonlinear reduced gravity model of the entire Indian Ocean. The model has been forced by 6-hourly analyzed wind stress data containing SSM/I observations and has been able to produce realistic circulation features. However, SLV values observed by Topex/Poseidon altimeter do not fit these simulations because of imperfect initial data. Hence an attempt has been made to initialize the model using altimeter data. The initialized model-generated SLVvalues have been compared with SLV derived by altimeter for monsoon as well as nonmonsoon months of 1996. Experimental runs have been performed for 10 days, 20 days, and one month. It has been found that the initialized model results on the final day of these experiments are in very good agreement with altimeter data of the same day. It is thus possible, in principle, to hindcast and forecast sea level variations in the time scale of 10 days to one month with the availability of good quality wind data for forcing the model and altimeter observations of sea level for initializing it.     

Detection of changes in variance of oceanographic time-series using changepoint analysis

Changepoint analysis is used to detect changes in variability within GOMOS hindcast time-series for significant wave heights of storm peak events across the Gulf of Mexico for the period 1900-2005. To detect a change in variance, the two-step procedure consists of (1) validating model assumptions per geographic location, followed by (2) application of a penalized likelihood changepoint algorithm. Results suggest that the most important changes in time-series variance occur in 1916 and 1933 at small clusters of boundary locations at which, in general, the variance reduces. No post-war changepoints are detected. The changepoint procedure can be readily applied to other environmental time-series.     

Hindcast of the wave conditions along the west Iberian coast

This paper describes the development of a wave prediction system for the west Iberian coast. The implemented wave prediction system is based on two state-of-the-art spectral wave models, WAM for the ocean area and SWAN for the nearshore. However, because of its extended geographical space the SWAN model will include some generation effects in the coarse SWAN simulations, complemented by wave transformation effects near the coast. The system was validated by means of extended hindcast runs in various regions belonging to the continental Portuguese coastal environment, which were compared with buoy data, focusing on the extreme energetic events and both direct comparisons and statistical results are presented.     

Sensitivity of wave model predictions to wind fields in the Western Mediterranean sea

The paper compares the wave hindcast in the Western Mediterranean sea using the reanalysis wind fields from HIPOCAS and ERA-40 from ECMWF for November 2001. The study has concentrated on the Mediterranean coast of Spain where there are known difficulties with the wind and wave modelling. Two winter storms have been compared. The main differences between the significant wave heights using the ERA-40 reanalysis (ECMWF) and HIPOCAS reanalysis winds were observed to increase when moving southwards in the geographical domain at the offshore locations. Systematic negative biases of Hs were obtained with the ERA-40 data at all the coastal locations analyzed, whereas positive biases are typical for the HIPOCAS reanalysis. For offshore and coastal locations when using the ERA-40 data the Hs biases increased moving to South, while this pattern was not so clear for the HIPOCAS data. The inconsistencies in the comparisons of modelled waves against measurements seem to be associated with the quality of the wind fields.     

Validation of the WAMC4 wave model for the Black Sea

The present paper describes the set-up and application of the third-generation wave model — WAM Cycle 4 to the Black Sea. The wind fields are calculated by a regional atmosphere model (REMO), which was driven with the conditions from the global NCEP re-analysis project. These atmospheric data are used to force the state-of-the-art WAM model. The validation is done by comparison of wave model output against directional buoy measurements registered at three deep-water locations and wave gauge data taken at a point in intermediate depth near the Black Sea coast. The results reveal that agreement between modeled and measured data is satisfactory and the quality of the simulations increases under more energetic and severer wind and wave conditions. Following the validation, a 41-year wave hindcast was implemented spanning the period 1958–1998.     

BCC_CSM模式夏季关键区海温回报评估

利用国家气候中心气候系统模式(Beijing Climate Center Climate System Model, BCC_CSM)的汛期回报试验数据集, 评估了夏季中低纬度海表面温度(Sea Surface Temperature, SST)的预测能力。结果表明:该模式对夏季中低纬海温具有一定的预测能力, 且在低纬地区的预测技巧尤为出色。对太平洋、热带印度洋和北大西洋这三个关键区进一步分析发现, 该模式对不同海区海温的预测能力有所不同。其中, 模式对夏季北太平洋海温及Ni?o 3.4指数表现出显著的预测技巧, 对热带印度洋、北大西洋海温及热带印度洋全区一致海温模态(Indian Ocean Basin-wide Warming, IOBW)也表现出一定的预测技巧, 而对北大西洋海温三极子模态(North Atlantic Tripole, NAT)的技巧相对较低。研究发现, 预测技巧与前冬的ENSO状态密切相关, 当前冬位于ENSO异常位相时, BCC_CSM模式对于三大海区夏季海温的预测技巧要高于前冬位于ENSO正常位相时, 且对NAT指数也具有更高的预测技巧。前冬ENSO所处的位相对于该模式对夏季Ni?o 3.4指数及IOBW指数的预测技巧影响不明显。此外, 该模式对夏季海温的预测技巧依赖于超前时间, 预测技巧在大部分情形下超前1个月的预测技巧相对更高。