Decadal predictability and forecast skill

The “potential predictability” of the climate system is the upper limit of available forecast skill and can be characterized by the ratio p of the predictable variance to the total variance. While the potential predictability of the actual climate system is unknown its analog q may be obtained for a model of the climate system. The usual correlation skill score r and the mean square skill score M are functions of p in the case of actual forecasts and potential correlation ρ and potential mean square skill score $\mathcal{M}$ are the same functions of q in the idealized model context. In the large ensemble limit the connection between model-based potential predictability and skill scores is particularly straightforward with $q=\rho^{2}=\mathcal{M}.$ Decadal predictions of annual mean temperature produced with the Canadian Centre for Climate Modelling and Analysis coupled climate model are analyzed for information on decadal climate predictability and actual forecast skill. Initialized forecast results are compared with the results of uninitialized climate simulations. Model-based values of potential predictability q and potential correlation skill ρ are obtained and ρ is compared with the actual forecast correlation skill r. The skill of externally forced and internally generated components of the variability are separately estimated. As expected, ρ > r and both decline with forecast range τ, at least for the first five years. The decline of skill is associated mainly with the decline of the skill of the internally generated component. The potential and actual skill of a forecast of time-averaged temperature depends on the averaging period. The skill of uninitialized simulations is low for short averaging times and increases as averaging time increases. By contrast, skill is high at short averaging times for forecasts initialized from observations and declines as averaging times increase to about three years, then increases somewhat at longer averaging times. The skills of the initialized forecasts and uninitialized simulations begin to converge for longer averaging times. The potential correlation skill ρ of the externally forced component of temperature is largest at tropical latitudes and the skill of the internally generated component is largest over the North Atlantic, parts of the Southern Ocean and to some extent the North Pacific. Potential skill over extratropical land is somewhat weaker than over oceans. The distribution of actual correlation skill r is broadly similar to that of potential skill for the externally forced component but less so for the internally generated component. Differences in potential and actual skill suggest where improvements in the forecast system might be found.     

Scale-dependent regional climate predictability over North America inferred from CMIP3 and CMIP5 ensemble simulations

Through the analysis of ensembles of coupled model simulations and projections collected from CMIP3 and CMIP5, we demonstrate that a fundamental spatial scale limit might exist below which useful additional refinement of climate model predictions and projections may not be possible. That limit varies among climate variables and from region to region. We show that the uncertainty (noise) in surface temperature predictions (represented by the spread among an ensemble of global climate model simulations) generally exceeds the ensemble mean (signal) at horizontal scales below 1000 km throughout North America, implying poor predictability at those scales. More limited skill is shown for the predictability of regional precipitation. The ensemble spread in this case tends to exceed or equal the ensemble mean for scales below 2000 km. These findings highlight the challenges in predicting regionally specific future climate anomalies, especially for hydroclimatic impacts such as drought and wetness.     

Impact of interactive vegetation phenology on the Canadian RCM simulated climate over North America

Climate Dynamics - Biosphere–atmosphere interactions play a very important role in modulating regional climate. To capture these bi-directional interactions, a dynamic vegetation model, the...     

Decadal potential predictability of twenty-first century climate

Decadal prediction of the coupled climate system is potentially possible given enough information and knowledge. Predictability will reside in both externally forced and in long timescale internally generated variability. The ??potential predictability?? investigated here is characterized by the fraction of the total variability accounted for by these two components in the presence of short-timescale unpredictable ??noise?? variability. Potential predictability is not a classical measure of predictability nor a measure of forecast skill but it does identify regions where long timescale variability is an appreciable fraction of the total and hence where prediction on these scale may be possible. A multi-model estimate of the potential predictability variance fraction (ppvf) as it evolves through the first part of the twenty-first century is obtained using simulation data from the CMIP3 archive. Two estimates of potential predictability are used which depend on the treatment of the forced component. The multi-decadal estimate considers the magnitude of the forced component as the change from the beginning of the century and so becomes largely a measure of climate change as the century progresses. The next-decade estimate considers the change in the forced component from the past decade and so is more pertinent to an actual forecast for the next decade. Long timescale internally generated variability provides additional potential predictability beyond that of the forced component. The ppvf may be expressed in terms of a signal-to-noise ratio and takes on values between 0 and 1. The largest values of the ppvf for temperature are found over tropical and mid-latitude oceans, with the exception of the equatorial Pacific, and some but not all tropical land areas. Overall the potential predictability for temperature generally declines with latitude and is relatively low over mid- to high-latitude land. Potential predictability for precipitation is generally low and due almost entirely to the forced component and then mainly at high latitudes. To the extent that the multi-model ppvf reflects both the behaviour of the actual climate system and the possibility of decadal prediction, the results give some indication as to where and to what extent decadal forecasts might be possible.     

Influence of ENSO and the South Atlantic Ocean on climate predictability over Southeastern South America

We perform a systematic study of the predictability of surface air temperature and precipitation in Southeastern South America (SESA) using ensembles of AGCM simulations, focusing on the role of the South Atlantic and its interaction with the El Niño-Southern Oscillation (ENSO). It is found that the interannual predictability of climate over SESA is strongly tied to ENSO showing high predictability during the seasons and periods when there is ENSO influence. The most robust ENSO signal during the whole period of study (1949–2006) is during spring when warm events tend to increase the precipitation over Southeastern South America. Moreover, the predictability shows large inter-decadal changes: for the period 1949–1977, the surface temperature shows high predictability during late fall and early winter. On the other hand, for the period 1978–2006, the temperature shows (low) predictability only during winter, while the precipitation shows not only high predictability in spring but also in fall. Furthermore, it is found that the Atlantic does not directly affect the climate over SESA. However, the experiments where air–sea coupling is allowed in the south Atlantic suggest that this ocean can act as a moderator of the ENSO influence. During warm ENSO events the ocean off Brazil and Uruguay tends to warm up through changes in the atmospheric heat fluxes, altering the atmospheric anomalies and the predictability of climate over SESA. The main effect of the air–sea coupling is to strengthen the surface temperature anomalies over SESA; changes in precipitation are more subtle. We further found that the thermodynamic coupling can increase or decrease the predictability. For example, the air–sea coupling significantly increases the skill of the model in simulating the surface air temperature anomalies for most seasons during period 1949–1977, but tends to decrease the skill in late fall during period 1978–2006. This decrease in skill during late fall in 1978–2006 is found to be due to a wrong simulation of the remote ENSO signal that is further intensified by the local air–sea coupling in the south Atlantic. Thus, our results suggest that climate models used for seasonal prediction should simulate correctly not only the remote ENSO signal, but also the local air–sea thermodynamic coupling.     

Interannual variability and expected regional climate change over North America

This study aims to analyse the interannual variability simulated by several regional climate models (RCMs), and its potential for disguising the effect of seasonal temperature increases due to greenhouse gases. In order to accomplish this, we used an ensemble of regional climate change projections over North America belonging to the North American Regional Climate Change Program, with an additional pair of 140-year continuous runs from the Canadian RCM. We find that RCM-simulated interannual variability shows important departures from observed one in some cases, and also from the driving models’ variability, while the expected climate change signal coincides with estimations presented in previous studies. The continuous runs from the Canadian RCM were used to illustrate the effect of interannual variability in trend estimation for horizons of a decade or more. As expected, it can contribute to the existence of transitory cooling trends over a few decades, embedded within the expected long-term warming trends. A new index related to signal-to-noise ratio was developed to evaluate the expected number of years it takes for the warming trend to emerge from interannual variability. Our results suggest that detection of the climate change signal is expected to occur earlier in summer than in winter almost everywhere, despite the fact that winter temperature generally has a much stronger climate change signal. In particular, we find that the province of Quebec and northwestern Mexico may possibly feel climate change in winter earlier than elsewhere in North America. Finally, we show that the spatial and temporal scales of interest are fundamental for our capacity of discriminating climate change from interannual variability.     

北美洲冬季冷空气对南美洲夏季降水异常影响的研究

利用1981—2017年NCEP/NCAR再分析资料和ECMWF再分析资料,研究了北美洲冬季高纬度冷空气对南美洲夏季降水异常的影响。结果表明,北美洲冬季高纬度冷空气通过影响向南越赤道气流的强弱,影响南美洲热带辐合带（intertropical convergence zone, ITCZ）位置和强度的变化,进一步引起南美洲天气的变化。北美洲冬季冷空气的南下过程能够引起80°～70°W的向南越赤道气流明显加强,导致2011年南美洲热带辐合带的位置异常偏南,强度异常偏强,是造成降水异常偏多的重要成因。通过相关分析发现北美洲冬季冷空气对南美洲ITCZ位置的影响更明显。     

东亚—西北太平洋地区夏季季节内振荡的年代际变化

本文重点分析对比热带夏季季节内振荡(Boreal Summer Intraseasonal Oscillation, BSISO)1987—1995年(P1),1996—2007年(P2)和2008—2017年(P3)三阶段东亚—西北太平洋地区(East Asian-Western North Pacific, EAWNP)5—9月BSISO年代际变化的季节内差异特征。结果表明,在P1和P3两阶段,5—7月EAWNP BSISO强度几乎相同,但P2中每个月均显著增强,表明5—7月EAWNP BSISO经历了P1—P2增强和P2—P3减弱的年代际变化。8月,EAWNP BSISO强度从P1到P3逐渐增强,P3阶段比P1有显著增强,孟加拉湾和东亚副热带区域的BSISO活动增强。和P1相比,南海地区BSISO活动在P2阶段异常活跃,在5—7月强度增强,并且北传显著。在P2阶段,负位相的太平洋年代际(Interdecadal Pacific Oscillation, IPO)对应的赤道西太平洋和印度洋海温增暖,及Walker环流的增强为5—7月BSISO活动提供了水汽和对流发展的有利条件,而南...     

Decadal change in relationship between western North Pacific tropical cyclone frequency and the tropical Pacific SST

In this study, we examine the relationship between the number of tropical cyclones (TCs) in the western North Pacific and the tropical Pacific sea surface temperature (SST) during the main TC season (July–November) for the period of 1965–2006. Results show that there are periods when TC frequency and the tropical Pacific SST are well correlated and periods when the relationship breaks down. Therefore, decadal variation is readily apparent in the relationship between the TC frequency and the SST variations in the tropical Pacific. We further examine the oceanic and atmospheric states in the two periods (i.e., 1979–1989 vs. 1990–2000) when the marked contrast in the correlation between the TC frequency and the tropical Pacific SST is observed. Before 1990, the analysis indicates that oceanic conditions largely influenced anomalous TC frequency, whereas atmospheric conditions had little impact. After 1990, there the reverse appears to be the case, i.e., atmospheric conditions drive anomalous TC frequency and oceanic conditions are relatively unimportant. A role of atmosphere and ocean in relation to the TC development in the western North Pacific changes, which is consistent with the change of the correlations between the TC frequency and the tropical Pacific SST.     

春季陆面植被对长江流域夏季降水可预报性的影响分析

利用美国全球监测与模型研究中心(GIMMS)1982—2006年逐月归一化植被指数(NDVI)、美国国家海洋和大气局(NOAA)1854—2008年海温资料以及中国国家气候中心(NCC)1951—2006年160站月降水资料,通过旋转经验正交函数分解(REOF)和相关分析获得了长江流域夏季降水预报序列和植被、海温预报因子集。基于最优子集回归方法(OSR),并借助交叉验证(CV)以及空间重建等手段,构建了单独以前期春季海温为预报因子和同时引入前期春季海温与归一化植被指数为因子的两类预报模型,对比分析引入陆面植被因子前后长江流域夏季降水预报效果改善状况,评估春季陆面植被对长江流域夏季降水可预报性的影响及预报效果的稳健性。结果表明:(1)相对于海温因子,春季陆面植被因子对长江流域夏季降水预报具有同样重要性,引入春季归一化植被指数后,长江流域夏季降水预报得到明显改善,相关系数平均由0.49提升到0.66,提高0.17左右,模型解释方差提升平均60%左右,其中单纯海温因子预报效果较差的汉江—淮河地区和淮河流域地区,相关系数更是提高了0.20—0.30,模型解释方差提升1倍左右;(2)交叉验证预报表明,相对于仅考虑海温因子模拟情形,交叉预报相关系数下降较多,模型稳健性较低,引入归一化植被指数后,长江流域夏季降水预报稳健性得到明显提升,长江中下游及其以南的长江三角洲地区、洞庭湖—鄱阳湖地区改善尤为明显;(3)长江流域降水可预报性存在明显的区域差异,嘉陵江流域地区、汉江—洞庭湖地区预报效果最好,汉江—淮河地区、淮河流域地区、长江三角洲地区预报效果最差,但引入归一化植被指数后预报效果提高最明显,而洞庭湖—鄱阳湖地区虽然模拟效果较好,但预报稳健性较低,交叉验证相关系数降幅达到0.27,这也从侧面说明了长江流域夏季降水分区预报的重要性。     

The role of temperature in drought projections over North America

The effects of future temperature and hence evapotranspiration increases on drought risk over North America, based on ten current (1970–1999) and ten corresponding future (2040–2069) Regional Climate Model (RCM) simulations from the North American Regional Climate Change Assessment Program, are presented in this study. The ten pairs of simulations considered in this study are based on six RCMs and four driving Atmosphere Ocean Coupled Global Climate Models. The effects of temperature and evapotranspiration on drought risks are assessed by comparing characteristics of drought events identified on the basis of Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspration Index (SPEI). The former index uses only precipitation, while the latter uses the difference (DIF) between precipitation and potential evapotranspiration (PET) as input variables. As short- and long-term droughts impact various sectors differently, multi-scale (ranging from 1- to 12-month) drought events are considered. The projected increase in mean temperature by more than 2 °C in the future period compared to the current period for most parts of North America results in large increases in PET and decreases in DIF for the future period, especially for low latitude regions of North America. These changes result in large increases in future drought risks for most parts of the USA and southern Canada. Though similar results are obtained with SPI, the projected increases in the drought characteristics such as severity and duration and the spatial extent of regions susceptible to drought risks in the future are considerably larger in the case of SPEI-based analysis. Both approaches suggest that long-term and extreme drought events are affected more by the future increases in temperature and PET than short-term and moderate drought events, particularly over the high drought risk regions of North America.     

Assessment of regional seasonal predictability using the PRECIS regional climate modeling system over South America

The purpose of this study was to evaluate the accuracy and skill of the UK Met Office Hadley Center Regional Climate Model (HadRM3P) in describing the seasonal variability of the main climatological features over South America and adjacent oceans, in long-term simulations (30 years, 1961–1990). The analysis was performed using seasonal averages from observed and simulated precipitation, temperature, and lower- and upper-level circulation. Precipitation and temperature patterns as well as the main general circulation features, including details captured by the model at finer scales than those resolved by the global model, were simulated by the model. However, in the regional model, there are still systematic errors which might be related to the physics of the model (convective schemes, topography, and land-surface processes) and the lateral boundary conditions and possible biases inherited from the global model.     

Simulating Climate over Western North America Using Stochastic Weather Generators

The climatologies of daily precipitation and of maximum and minimum temperatures over western North America are simulated using stochastic weather generators. Two types of generator, differentiated only by their method of modeling precipitation occurrence, are investigated. A second-order Markov model, in which the probability of the occurrence of precipitation is modeled as contingent upon its occurrence on the previous two days, is compared with a spell-length model, in which mass functions of wet- and dry-spell lengths are modeled. Both models are able to reproduce the observed annual and monthly climatology in the region to a high degree of accuracy. However, there is considerable over-dispersion in annual precipitation, resulting primarily from an underestimation in the interannual variability of precipitation intensity. The interannual variability of temperatures is similarly underestimated, and is most severe for minimum temperatures. There is a severe problem in estimating minimum temperature extremes, which can be attributed to the negatively skewed distribution of daily minimum temperatures. Non-normality in the distribution of daily temperatures is shown to be a problem in simulating extreme temperature maxima as well as of minima. It is suggested that the normal distribution used in the generation of daily temperatures in the widely used Richardson (1981) generator, and its derivations, be supplanted by a more appropriate distribution that permits skewness in either direction.     

Month-Long Simulations of Gravity Waves over North America and North Atlantic in Comparison with Satellite Observations

Mesoscale simulations of gravity waves in the upper troposphere and lower stratosphere over North America and North Atlantic Ocean in January 2003 are compared with satellite radiance measurements from the Advanced Microwave Sounding Unit-A (AMSU-A). Four regions of strong gravity wave (GW) activities are found in the model simulations and the AMSU-A observations: the northwestern Atlantic, the U.S. Rockies, the Appalachians, and Greenland. GWs over the northwestern Atlantic Ocean are associated with the midlatitude baroclinic jet-front system, while the other three regions are apparently related to high topography. Model simulations are further used to analyze momentum fluxes in the zonal and meridional directions. It is found that strong westward momentum fluxes are prevalent over these regions over the whole period. Despite qualitative agreement between model simulations and satellite measurements, sensitivity experiments demonstrate that the simulated GWs are sensitive to the model spin-up time.     

Decadal predictability and prediction skill of sea surface temperatures in the South Pacific region

The South Pacific Ocean is a key driver of climate variability within the Southern Hemisphere at different time scales. Previous studies have characterized the main mode of interannual sea surface temperature (SST) variability in that region as a dipolar pattern of SST anomalies that cover subtropical and extratropical latitudes (the South Pacific Ocean Dipole, or SPOD), which is related to precipitation and temperature anomalies over several regions throughout the Southern Hemisphere. Using that relationship and the reported low predictive skill of precipitation anomalies over the Southern Hemisphere, this work explores the predictability and prediction skill of the SPOD in near-term climate hindcasts using a set of state-of-the-art forecast systems. Results show that predictability greatly benefits from initializing the hindcasts beyond the prescribed radiative forcing, and is modulated by known modes of climate variability, namely El Niño-Southern Oscillation and the Interdecadal Pacific Oscillation. Furthermore, the models are capable of simulating the spatial pattern of the observed SPOD even without initialization, which suggests that the key dynamical processes are properly represented. However, the hindcast of the actual phase of the mode is only achieved when the forecast systems are initialized, pointing at SPOD variability to not be radiatively forced but probably internally generated. The comparison with the performance of an empirical prediction based on persistence suggests that initialization may provide skillful information for SST anomalies, outperforming damping processes, up to 2–3 years into the future.     

Impact of Saharan dust on landfalling North Atlantic tropical cyclones over North America in September

Using reanalysis data and model simulations, this study reveals an increase in September landfalling North Atlantic tropical cyclones (TCs) during years that have a strengthened Saharan dust plume, and the related physical processes are investigated by analyzing the relationship of dust aerosol optical depth with TC track, intensity, and the related meteorological environment. Suppression of the sea surface temperature (SST) by the Saharan dust plume can hinder TC tracks over the central tropical North Atlantic, inducing westward development of TC tracks to the western tropical North Atlantic with higher SST, which is more conducive to TCs forming major hurricanes. This physical process increases TC landfalls in North America, especially major hurricane landfalls in the continental United States, leading to greater potential destructiveness.摘要本项研究利用再分析数据和模式模拟数据分析了沙尘的气溶胶光学厚度与台风的登陆, 轨迹, 强度及相关气象环境参数的关系, 揭示了9月北大西洋台风的登陆次数会在撒哈拉沙尘较强的年份中增加, 以及这一现象的物理机制. 撒哈拉沙尘对热带北大西洋中部海表温度具有抑制作用, 会阻碍该地区的台风活动, 因此台风只能向西移动进入海表温度较高的热带北大西洋西部, 从而更易于形成强台风. 这一物理过程将导致台风登陆北美大陆的频次增加, 特别是强台风登陆美国的可能性增强, 产生更大的潜在破坏性.     

Spatiotemporal changes in the size and shape of heat waves over North America

Heat waves are occurring more frequently across the globe and are likely to increase in intensity and duration under climate change. Much work has already been completed on attributing causes of observed heat waves and on modeling their future occurrence, but such efforts are often lacking in exploration of spatial relationships. Based on principles of landscape ecology, we utilized fragmentation metrics to examine the spatiotemporal changes in heat wave shape and occurrence across North America. This methodological approach enables us to examine area, shape, perimeter, and other key metrics. The application of these shape metrics to high-resolution historical (1950–2013) climate data reveals that the total number and spatial extent of heat waves are increasing over the continent, but at an individual heat wave patch level, they are becoming significantly smaller in extent and more complex in shape, indicating that heat waves have become a more widespread and fragmented phenomena.