Historical effects of temperature and precipitation on California crop yields

For the 1980–2003 period, we analyzed the relationship between crop yield and three climatic variables (minimum temperature, maximum temperature, and precipitation) for 12 major Californian crops: wine grapes, lettuce, almonds, strawberries, table grapes, hay, oranges, cotton, tomatoes, walnuts, avocados, and pistachios. The months and climatic variables of greatest importance to each crop were used to develop regressions relating yield to climatic conditions. For most crops, fairly simple equations using only 2–3 variables explained more than two-thirds of observed yield variance. The types of variables and months identified suggest that relatively poorly understood processes such as crop infection, pollination, and dormancy may be important mechanisms by which climate influences crop yield. Recent climatic trends have had mixed effects on crop yields, with orange and walnut yields aided, avocado yields hurt, and most crops little affected by recent climatic trends. Yield-climate relationships can provide a foundation for forecasting crop production within a year and for projecting the impact of future climate changes.     

Interdecadal variability of temperature and precipitation in China since 1880

Reconstruction of a homogeneous temperature and precipitation series for China is crucial for a proper understanding of climate change over China. The annual mean temperature anomaly series of ten regions are found from 1880 to 2002. Positive anomalies over China during the 1920s and 1940s are noticeable.The linear trend for the period of 1880-2002 is 0.58℃ (100a)^-1, which is a little less than the global mean (0.60℃ (100a)^-l). 1998 was the warmest year in China since 1880, which is in agreement with theestimation of the global mean temperature. The mean precipitation on a national scale depends mainly on the precipitation over East China. Variations of precipitation in West China show some characteristics which are independent of those in the east. However, the 1920s was the driest decade not only for the east, but also for eastern West China during the last 120 years. The most severe drought on a national scale occurred in 1928. Severe droughts also occurred in 1920, 1922, 1926, and 1929 in North China.It is noticeable that precipitation over East China was generally above normal in the 1950s and 1990s;severe floods along the Yangtze River in 1954, 1991, and 1998 only occurred in these two wet decades.An increasing trend in precipitation variations is observed during the second half of the 20th century in West China, but a similar trend is not found in East China, where the 20- to 40-year periodicities are predominant in the precipitation variations.     

On the sensitivity of predictions of maritime cyclogenesis to convective precipitation and sea temperature

Abstract

The influences of surface fluxes and convective precipitation are investigated for two 36‐h periods of cyclogenesis over the northeastern Pacific Ocean. Three methods are tested of specifying the fraction of moisture supply that produces convective precipitation in a modified form of Kuo's (1974) parametrization scheme using an 8‐level primitive equations model.

When convection is included, precipitation amounts are greater and the cyclone deepening is better predicted than when convection is not included. Predicted cyclogenesis is very sensitive to sea temperature. As the low moves over warmer water, the effect of sensible heating is to increase the moisture convergence in the atmospheric boundary layer. This increases the precipitation rates and accelerates deepening. It is concluded that the CISK mechanism plays an important role in extratropical cyclogenesis.     

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.     

Impact of urbanization on recent temperature and precipitation trends in the Korean peninsula

Urbanization has a significant impact on climate in urban areas. In this study, we investigate urbanization impacts on temperature and precipitation trends in Korean peninsula based on statistical relationship between these trends and local population growth. We found that there is a significant positive correlation between temperature rise and local population growth, indicating that urbanization has a significant contribution to temperature increase in city climate. As for temperature, the population growth in Korean cities is positively correlated with precipitation trend. The positive correlation is higher during summer time when small-scale convective activity is dominant. Furthermore, it is demonstrated that the correlation is significantly increased when stations in rural areas and small cities are excluded. Such nonlinear relation between precipitation and urbanization is also discussed.     

Effect of land model ensemble versus coupled model ensemble on the simulation of precipitation climatology and variability

Through a series of model simulations with an atmospheric general circulation model coupled to three different land surface models, this study investigates the impacts of land model ensembles and coupled model ensemble on precipitation simulation. It is found that coupling an ensemble of land models to an atmospheric model has a very minor impact on the improvement of precipitation climatology and variability, but a simple ensemble average of the precipitation from three individually coupled land-atmosphere models produces better results, especially for precipitation variability. The generally weak impact of land processes on precipitation should be the main reason that the land model ensembles do not improve precipitation simulation. However, if there are big biases in the land surface model or land surface data set, correcting them could improve the simulated climate, especially for well-constrained regional climate simulations.     

Long-term variability of temperature and precipitation in the Czech Lands: an attribution analysis

Among the key problems associated with the study of climate variability and its evolution are identification of the factors responsible for observed changes and quantification of their effects. Here, correlation and regression analysis are employed to detect the imprints of selected natural forcings (solar and volcanic activity) and anthropogenic influences (amounts of greenhouse gases—GHGs—and atmospheric aerosols), as well as prominent climatic oscillations (Southern Oscillation—SO, North Atlantic Oscillation—NAO, Atlantic Multidecadal Oscillation—AMO) in the Czech annual and monthly temperature and precipitation series for the 1866–2010 period. We show that the long-term evolution of Czech temperature change is dominated by the influence of an increasing concentration of anthropogenic GHGs (explaining most of the observed warming), combined with substantially lower, and generally statistically insignificant, contributions from the sulphate aerosols (mild cooling) and variations in solar activity (mild warming), but with no distinct imprint from major volcanic eruptions. A significant portion of the observed short-term temperature variability can be linked to the influence of NAO. The contributions from SO and AMO are substantially weaker in magnitude. Aside from NAO, no major influence from the explanatory variables was found in the precipitation series. Nonlinear forms of regression were used to test for nonlinear interactions between the predictors and temperature/precipitation; the nonlinearities disclosed were, however, very weak, or not detectable at all. In addition to the outcomes of the attribution analysis for the Czech series, results for European and global land temperatures are also shown and discussed.     

Impact of remote forcing,model resolution and bathymetry on predictions of currents on the shelf

Impacts of remote forcing, model resolution and bathymetry on current predictions at two moorings located on the shelf of the Monterey Bay area are investigated. We consider three Monterey Bay model configurations which differ in resolution and bathymetry representation, and we specify open boundary conditions for these three configurations from two larger scale models, which have different accuracy in the representation of the remote forcing (in the form of poleward propagating along the coast coastally-trapped Kelvin type waves).Comparisons of correlations between observed and model currents as well as visual comparisons show that the most critical element in reproducing currents on the shelf is accurate representation of the remote forcing. Our results also show that accurate representation of bathymetry is the second most critical factor in reproducing observed currents.     

Impact of southeast Indian Ocean sea surface temperature anomalies on monsoon-ENSO-dipole variability in a coupled ocean–atmosphere model

Recent studies show that SouthEast Indian Ocean (SEIO) SSTs are a highly significant precursor of transitions of the whole monsoon-El Niño-Southern Oscillation (ENSO) system during recent decades. However, the reasons for this specific interannual variability have not yet been identified unequivocally from the observations. Among these, the possibility of SEIO SST-driven variability in the monsoon-ENSO system is investigated here by inserting positive/negative SEIO temperature anomalies in the February’s restart files of a state-of-the-art coupled General Circulation Model (GCM) for 49 years of a control simulation. For each year of the control simulation, the model was then integrated for a 1-year period in fully coupled mode. These experiments show that Indian Summer Monsoon (ISM) and tropical Indian Ocean Dipole Mode (IODM) events are significantly influenced by the SEIO temperature perturbations inserted in the mixed layer of the coupled GCM several months before. A warm SEIO perturbation, inserted in late boreal winter, slowly propagates northward during the following seasons, implies enhanced ISM rainfall and finally triggers a negative IODM pattern during boreal fall in agreement with observations. A reversed evolution is simulated for a cold SEIO perturbation. It is shown that the life cycle of the simulated SEIO signal is driven by the positive wind-evaporation-SST, coastal upwelling and wind-thermocline-SST feedbacks. Further diagnosis of the sensitivity experiments suggests that stronger ISM and IODM variabilities are generated by excluding the El Niño years of the control simulation or when the initial background state in the SEIO is warmer. This finding confirms that IODM events may be triggered by multiple factors, other than ENSO, including subtropical SEIO SST anomalies. However, the ENSO mode does not react significantly to the SEIO temperature perturbation in the perturbed runs even though the simulated Pacific pattern agrees with the observations during boreal fall. These discrepancies with the observations may be linked to model biases in the Pacific and to the too strong ENSO simulated by this coupled GCM. These modeling evidences confirm that subtropical Indian Ocean SST anomalies generated by Mascarene high pulses during austral summer are a significant precursor of both ISM and IODM events occuring several months later.     

澜沧江源区气温与降水对径流变化的影响

为研究澜沧江源区水文气候变化特征,采用线性回归拟合分析方法、M-K非参数检验法对1960—2010年间澜沧江源区的水文气候变化趋势进行分析,计算了各季节气温变化对年气温变化的贡献量,并基于Pearson相关分析法和贡献率的计算讨论了降水量和气温对径流量变化的影响。结果表明:澜沧江源区年平均气温和各季节平均气温均呈显著上升趋势,其中,冬季的增温对年平均气温增加贡献最大(38%)。澜沧江流域源区年降水量无明显增减趋势,但春季降水量显著增加。澜沧江流域源区年径流量未呈现显著变化趋势,冬季和春季径流量呈现出显著的增加趋势。年际尺度上,径流量的主控因素是降水量,降水量对径流量年内变化的影响主要发生在降水相对丰沛的6—10月份;冬季和初春季节气温上升对径流量的改变存在一定的影响,且气温的贡献率要比降水的贡献率大,原因是气温升高加剧研究区内冰雪的消融,进而导致澜沧江源区的径流增加。     

Assessment of RegCM4 simulated inter-annual variability and daily-scale statistics of temperature and precipitation over Mexico

The skill of a regional climate model (RegCM4) in capturing the mean patterns, interannual variability and extreme statistics of daily-scale temperature and precipitation events over Mexico is assessed through a comparison of observations and a 27-year long simulation driven by reanalyses of observations covering the Central America CORDEX domain. The analysis also includes the simulation of tropical cyclones. It is found that RegCM4 reproduces adequately the mean spatial patterns of seasonal precipitation and temperature, along with the associated interannual variability characteristics. The main model bias is an overestimation of precipitation in mountainous regions. The 5 and 95 percentiles of daily temperature, as well as the maximum dry spell length are realistically simulated. The simulated distribution of precipitation events as well as the 95 percentile of precipitation shows a wet bias in topographically complex regions. Based on a simple detection method, the model produces realistic tropical cyclone distributions even at its relatively coarse resolution (dx = 50 km), although the number of cyclone days is underestimated over the Pacific and somewhat overestimated over the Atlantic and Caribbean basins. Overall, it is assessed that the performance of RegCM4 over Mexico is of sufficient quality to study not only mean precipitation and temperature patterns, but also higher order climate statistics.     

成都区域气象中心高低分辨率η模式降水预报检验分析

利用成都区域气象中心η坐标模式,对2002年汛期及主要降水过程进行了η坐标模式降水预报检验,对典型个例进行了详细的分析.结果表明:模式对夏季区域性过程有较强的预报能力,模式预报雨量中心强度有50%与实况相差小于25毫米.模式对晴雨预报有较好的指导意义,对降水强度的预报通常偏弱,对落区的预报位置易偏西、偏北.模式易漏报不易空报,当模式预报有较大量级的降水时,实况出现的概率很大,但要注意落区的位置.高分辨率模式在降水中心强度的预报较低分辨率模式接近实况,低分辨率模式在降水落区和中心位置预报上较接近实况.     

热带太平洋海表温度年际变化对降水季节内振荡的影响

根据 １９８２—１９９２年期间的日平均 ＭＳＵ（Ｓｐｅｎｃｅｒ, １９９３）海洋降水和 ５天平均的ＣＭＡＰ（Ｘｉｅ＆ Ａｒｋｉｎ, １９９７）降水观测资料,分析了热带太平洋大气季节内振荡（ＭＪＯ）的年际变化特征。在太平洋海表温度（ＳＳＴ）年际变化的正常年份（１９８２—８３年, １９８６—８８年, １９９１—９２年）,均有明显的ＭＪＯ信号传到日界线以东并在中、东太平洋维持数月。热带ＭＪＯ活动强度的年际变化与局地ＳＳＴ的变化存在正相关。中、东太平洋降水的季节内振荡的年际变化与热带太平洋ＳＳＴ的最强正相关在Ｎｉｎｏ３区附近。以观测ＳＳＴ场强迫ＣＣＭ３大气模式的数值试验基本上真实地再现了１１年期间热带太平洋降水季节内振荡的年际变化总趋势,但模拟季节内振荡的强度较观测平均偏弱。对比分别采用周平均和月平均ＳＳＴ强迫场的积分结果,发现在中、东太平洋,二个积分模拟的降水季节内振荡强度的年际变化接近并且趋势与观测基本一致,而在西太平洋二个积分的模拟结果差别较大。这表明在热带中、东太平洋,ＳＳＴ强迫的年际变化对ＭＪＯ强度的变化有强的制约。而在ＭＪＯ总体活跃的热带西太平洋,ＳＳＴ强迫场的季节变化对模拟ＭＪＯ活动也有较大影响。ＣＣＭ３模拟     

Impact of intra-daily SST variability on ENSO characteristics in a coupled model

This paper explores the impact of intra-daily Sea Surface Temperature (SST) variability on the tropical large-scale climate variability and differentiates it from the response of the system to the forcing of the solar diurnal cycle. Our methodology is based on a set of numerical experiments based on a fully global coupled ocean–atmosphere general circulation in which we alter (1) the frequency at which the atmosphere sees the SST variations and (2) the amplitude of the SST diurnal cycle. Our results highlight the complexity of the scale interactions existing between the intra-daily and inter-annual variability of the tropical climate system. Neglecting the SST intra-daily variability results, in our CGCM, to a systematic decrease of 15% of El Ni?o—Southern Oscillation (ENSO) amplitude. Furthermore, ENSO frequency and skewness are also significantly modified and are in better agreement with observations when SST intra-daily variability is directly taken into account in the coupling interface of our CGCM. These significant modifications of the SST interannual variability are not associated with any remarkable changes in the mean state or the seasonal variability. They can therefore not be explained by a rectification of the mean state as usually advocated in recent studies focusing on the diurnal cycle and its impact. Furthermore, we demonstrate that SST high frequency coupling is systematically associated with a strengthening of the air-sea feedbacks involved in ENSO physics: SST/sea level pressure (or Bjerknes) feedback, zonal wind/heat content (or Wyrtki) feedback, but also negative surface heat flux feedbacks. In our model, nearly all these results (excepted for SST skewness) are independent of the amplitude of the SST diurnal cycle suggesting that the systematic deterioration of the air-sea coupling by a daily exchange of SST information is cascading toward the major mode of tropical variability, i.e. ENSO.     

Interannual Antarctic tropospheric circulation and precipitation variability

Main modes of variability of the Antarctic tropospheric circulation (500 hPa geopotential height) and precipitation are identified through their empirical orthogonal functions (EOF). This is done by combining various sources of information, including meteorological analyses and forecasts (NCEP and ECMWF), atmospheric general circulation model (LMDZ) simulations, and satellite data (GPCP). Unlike previous similar work on circulation variability, the mode analyses are restricted to the Antarctic region. The main modes that relate the Antarctic region to the mid and tropical latitudes, e.g. in association with ENSO, are nonetheless clearly identified and thus robust. The contribution of the sea-surface or of the circumpolar Antarctic atmospheric dynamics to the occurrence and to the chronology of these modes is evaluated through various atmospheric model simulations. EOF analyses results are somewhat less stable, across the various datasets, and more noisy for precipitation than for circulation. Yet, through moisture advection considerations, the two most significant precipitation modes can be well related to the three main modes of circulation variability. The signatures of both the Southern Oscillation Index (SOI) and the Antarctic Oscillation Index (AOI) are found in one same precipitation mode, suggesting that they have a substantially common spatial structure. In addition, the relative strength of the signature of the AOI and SOI appears to change in time. In particular, the signature of the SOI was weak in the 1980s precipitations, but turned very strong in the 1990s. Common spatial patterns and variable strength in time may explain why hints of an ENSO signature in Antarctic precipitation have been reported but not unequivocally demonstrated so far.