Impact of temperature and precipitation variability on crop model predictions

Future climate changes, as well as differences in climates from one location to another, may involve changes in climatic variability as well as changes in means. In this study, a synthetic weather generator is used to systematically change the within-year variability of temperature and precipitation (and therefore also the interannual variability), without altering long-term mean values. For precipitation, both the magnitude and the qualitative nature of the variability are manipulated. The synthetic daily weather series serve as input to four crop simulation models. Crop growth is simulated for two locations and three soil types. Results indicate that average predicted yield decreases with increasing temperature variability where growing-season temperatures are below the optimum specified in the crop model for photosynethsis or biomass accumulation. However, increasing within-year variability of temperature has little impact on year-to-year variability of yield. The influence of changed precipitation variability on yield was mediated by the nature of the soil. The response on a droughtier soil was greatest when precipitation amounts were altered while keeping occurrence patterns unchanged. When increasing variability of precipitation was achieved through fewer but larger rain events, average yield on a soil with a large plant-available water capacity was more affected. This second difference is attributed to the manner in which plant water uptake is simulated. Failure to account for within-season changes in temperature and precipitation variability may cause serious errors in predicting crop-yield responses to future climate change when air temperatures deviate from crop optima and when soil water is likely to be depleted at depth.     

Diurnal responses of tropical convective and stratiform rainfall to diurnally varying sea surface temperature

Two experiments were carried out using a two-dimensional cloud-resolving model to study the effects of diurnally varying sea surface temperature (SST) on diurnal variations of tropical convective and stratiform rainfall. Experiment SST29 is imposed by a constant SST of 29°C, whereas experiment SST29D is imposed by a diurnally varying SST with a time-mean of 29°C and a diurnal difference of 1°C. Both experiments are also zonally uniformly imposed by a zero vertical velocity and a constant zonal wind, and are integrated for 40 days to reach quasi-equilibrium states. The model domain mean surface rain rate is larger in SST29D than in SST29 in the late afternoon, when the ocean surface is warmer in SST29D. Convective-stratiform rainfall partitioning analysis reveals that the late-afternoon convective rainfall is larger in SST29D than in SST29, whereas the stratiform rainfalls are similar in both experiments. Further analysis of surface rainfall and cloud microphysical budgets over convective regions shows that, in the late afternoon, the larger amount of water vapor is pumped into the non-raining region through the larger surface evaporation associated with the warmer SST. This water vapor is then transported into convective regions to produce more vapor condensation and greater collection of cloud water by raindrops and larger convective rainfall in SST29D than in SST29.     

On the dependence of climate sensitivity on convective parametrization

Two sensitivity experiments, in which CO₂ is doubled and sea-surface temperatures are enhanced, were carried out using a general circulation model to determine the influence of the convective parametrization on simulated climate change. In the first experiment, a non-penetrative layer-swapping convection scheme is used; in the second, a penetrative scheme is used. It is found that the penetrative scheme gives the greater upper tropospheric warming (over 4.5 K compared to 4 K) and the greater reduction in upper tropospheric cloud, consistent with recent CO₂ sensitivity studies. However, there is a 0.7 Wm^–2 greater increase in net downward radiation at the top of the atmosphere in the experiment with the non-penetrative scheme, implying a larger tropical warming which is inconsistent with recent CO₂ studies. Other possible explanations for discrepancies between recent studies of the equilibrium climate response to increasing CO₂ are considered and discussed. The changes in the atmospheric fluxes of heat and moisture from the tropical continents in the model with the penetrative scheme differ from those found using the non-penetrative scheme, and those in an equilibrium experiment using the penetrative scheme. Thus, changes in circulation may explain the apparent discrepancy in the current experiments, but prescribed sea-surface temperature experiments may not provide a reliable indication of a model's equilibrium climate sensitivity. Offprint requests to: JFB Mitchell     

Cause-effect relationships between sea surface temperature, precipitation and sea level along the Bangladesh coast

Summary  The Bangladesh coast, which lies on the confluence of three mighty rivers, the Ganges, the Brahmaputra and the Meghna, with the Himalayas to the north and the Bay of Bengal to the south, is an ideal zone for sea level rise due to enhanced rainfall during the monsoon season from June to September. An attempt has been made here to look into the cause-effect relationships between observed trends in sea surface temperature (SST) over the Bay of Bengal and the trends in monsoon rains and sea level in Bangladesh. The study utilizes the 14-year satellite-derived SSTs over the Bay of Bengal for 1985–1998, the tide gauge stations data along the Bangladesh coast for 1977–1998 and the 31-year monsoon rainfall data for Bangladesh, 1961–1991. Received October 20, 2000     

Seasonal to decadal predictions of regional Arctic sea ice by assimilating sea surface temperature in the Norwegian Climate Prediction Model

Climate Dynamics - The version of the Norwegian Climate Prediction Model (NorCPM) that only assimilates sea surface temperature (SST) with the Ensemble Kalman Filter has been used to investigate...     

台风生成阶段周期性对流爆发机制及辐射的影响

最新观测统计分析表明台风生成前对流活动存在周期性特征,周期集中在18~26 h,峰值多出现在夜间。本文通过一系列理想的云分辨数值控制试验和辐射敏感性对比试验讨论了台风生成阶段周期性对流爆发的成因以及辐射日变化在此过程中产生的影响。结果表明,在给定无日变化的恒定太阳辐射情况下,台风生成过程中也会出现与观测一致的周期性对流爆发,说明辐射日变化不是该周期性形成的控制因素。对湿静力能扰动的收支分析发现边界层中湿静力能的周期性增减是导致周期性深对流爆发的关键因素。深对流爆发形成的冷池通过平流作用降低了边界层内的湿静力能,需要通过辐射与海表面通量过程使其恢复,才能再次触发对流。辐射日变化对于一些较弱的热带低压涡旋有调制作用,能使其周期性对流爆发的峰值时间相位改变并趋于在夜晚出现;但对于较强的涡旋,辐射的这种调制作用并不显著,涡旋会保持其最初对流爆发的周期和相位。本研究对观测到的台风生成阶段对流峰值出现在白天或夜间的情况都可以作出合理解释,也深化了对台风生成过程对流和辐射的作用和影响科学问题的理解。     

黑龙江省土壤湿度及其对气温和降水的敏感性分析

气温和降水量变化是影响土壤湿度变化的主要原因,研究土壤湿度对气温和降水的敏感性对区域农业生产、生态环境治理和经济可持续发展有重要意义。采用1984-2007年黑龙江省73个气象观测站的气温、降水数据和13个土壤湿度观测站土壤观测数据,利用EOF、相关分析等数理分析方法,对黑龙江省土壤湿度与气温、降水量之间的关系进行了研究。结果表明：1984-2007年黑龙江省土壤湿度变化在不同区域存在差异：除三江平原中西部地区外,大部分农区土壤湿度变化趋势一致,20世纪90年代中期以前基本偏湿,而90年代中期以后则为偏干,2001年偏干严重。土壤湿度对气候变化响应的敏感性也不同,松嫩平原（西南部除外）是土壤湿度对气温和降水变化敏感区域;松嫩平原西南部对气温敏感;伊春南部地区-哈尔滨东部-三江平原西部为降水敏感区;逊克、伊春北部、牡丹江和三江平原东部土壤湿度对气温和降水均不敏感。     

On the temperature spectrum in the convective boundary layer

A model for the temperature spectrum in the convective boundary layer is presented. The model is developed by using local similarity parameterization of the mixed layer. The model is compared with an idealized temperature spectrum obtained during the Minnesota experiment and exhibits behavior very similar to that observed in the atmosphere.     

On the mechanism of winter cyclogenesis in relation to vertical axis tilt

Summary ?This work is concerned with the behavior of the vertical trough axis tilt during the development of a Mediterranean cyclone. The period covering stages of the development of the depression is from 1200 UTC 18 January to 1200 UTC 25 January 1981. Two procedures have been used to illustrate the behavior of the vertical axis tilt with the development of our case study. In the first direct procedure we trace the centers of the cyclone for each level for each day and determine its longitude. In the second indirect procedure we compute the values and signs of the product of the perturbation of temperature and meridional velocity over the computational domain. The energetics of the depression is studied and the partition of available potential energy and kinetic energy into zonal and eddy component is adopted. The energy contents and their changes in different atmospheric levels are discussed in the course of the cyclone’s development. Received April 27, 2001; Revised December 12, 2001     

Evaluation of summer temperature and precipitation predictions from NCEP CFSv2 retrospective forecast over China

National Centers for Environmental Prediction recently upgraded its operational seasonal forecast system to the fully coupled climate modeling system referred to as CFSv2. CFSv2 has been used to make seasonal climate forecast retrospectively between 1982 and 2009 before it became operational. In this study, we evaluate the model’s ability to predict the summer temperature and precipitation over China using the 120 9-month reforecast runs initialized between January 1 and May 26 during each year of the reforecast period. These 120 reforecast runs are evaluated as an ensemble forecast using both deterministic and probabilistic metrics. The overall forecast skill for summer temperature is high while that for summer precipitation is much lower. The ensemble mean reforecasts have reduced spatial variability of the climatology. For temperature, the reforecast bias is lead time-dependent, i.e., reforecast JJA temperature become warmer when lead time is shorter. The lead time dependent bias suggests that the initial condition of temperature is somehow biased towards a warmer condition. CFSv2 is able to predict the summer temperature anomaly in China, although there is an obvious upward trend in both the observation and the reforecast. Forecasts of summer precipitation with dynamical models like CFSv2 at the seasonal time scale and a catchment scale still remain challenge, so it is necessary to improve the model physics and parameterizations for better prediction of Asian monsoon rainfall. The probabilistic skills of temperature and precipitation are quite limited. Only the spatially averaged quantities such as averaged summer temperature over the Northeast China of CFSv2 show higher forecast skill, of which is able to discriminate between event and non-event for three categorical forecasts. The potential forecast skill shows that the above and below normal events can be better forecasted than normal events. Although the shorter the forecast lead time is, the higher deterministic prediction skill appears, the probabilistic prediction skill does not increase with decreased lead time. The ensemble size does not play a significant role in affecting the overall probabilistic forecast skill although adding more members improves the probabilistic forecast skill slightly.     

On the sensitivity of Antarctic sea ice model biases to atmospheric forcing uncertainties

Climate Dynamics - Although atmospheric reanalyses are an extremely valuable tool to study the climate of polar regions, they suffer from large uncertainties in these data-poor areas. In this work,...     

On the estimation of systematic error in regression-based predictions of climate sensitivity

An extension of a regression-based methodology for constraining climate forecasts using a multi-thousand member ensemble of perturbed climate models is presented, using the multi-model CMIP-3 ensemble to estimate the systematic model uncertainty in the prediction, with the caveat that systematic biases common to all models are not accounted for. It is shown that previous methodologies for estimating the systematic uncertainty in predictions of climate sensitivity are dependent on arbitrary choices relating to ensemble sampling strategy. Using a constrained regression approach, a multivariate predictor may be derived based upon the mean climatic state of each ensemble member, but components of this predictor are excluded if they cannot be validated within the CMIP-3 ensemble. It is found that the application of the CMIP-3 constraint serves to decrease the upper bound of likelihood for climate sensitivity when compared with previous studies, with 10th and 90th percentiles of probability at 1.5 K and 4.3 K respectively.     

Storm track sensitivity to sea surface temperature resolution in a regional atmosphere model

A high resolution regional atmosphere model is used to investigate the sensitivity of the North Atlantic storm track to the spatial and temporal resolution of the sea surface temperature (SST) data used as a lower boundary condition. The model is run over an unusually large domain covering all of the North Atlantic and Europe, and is shown to produce a very good simulation of the observed storm track structure. The model is forced at the lateral boundaries with 15–20 years of data from the ERA-40 reanalysis, and at the lower boundary by SST data of differing resolution. The impacts of increasing spatial and temporal resolution are assessed separately, and in both cases increasing the resolution leads to subtle, but significant changes in the storm track. In some, but not all cases these changes act to reduce the small storm track biases seen in the model when it is forced with low-resolution SSTs. In addition there are several clear mesoscale responses to increased spatial SST resolution, with surface heat fluxes and convective precipitation increasing by 10–20% along the Gulf Stream SST gradient.     

印度洋海温异常对贵州夏季降水的影响

利用经验正交函数(EOF)对印度洋海表温度距平(SSTA)进行展开,分析印度洋海温场的时空特征及其与贵州夏季降水的关系.结果表明,同期的印度洋海表温度距平分布场与贵州夏季降水相关显著,西印度洋索马里海区的SSTA与贵州夏季降水关系最为密切,当夏季索马里海区海温偏高(低)时贵州夏季降水偏少(多).