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.     

Origin of July Antarctic precipitation and its influence on deuterium content: a GCM analysis

The NASA/GISS GCM is used to estimate the evaporative contributions of several oceanic regions (defined by temperature) to Antarctica's July precipitation. Tracer diagnostics in the GCM suggest that the weighted average evaporative source temperature for Antarctic precipitation as a whole is about 12°C. The average source temperature for local precipitation there varies from 9° C to 14° C. To examine the effect of evaporative source on water isotope concentration, the GCM also follows a global deuterium (HDO) tracer and deuterium tracers evaporating from each oceanic region. The results suggest that although evaporative source temperature does affect the concentrations of the individual HDO tracers, differences in evaporative source do not explain the scatter in the roughly linear relationship between condensation temperature and isotope concentration. Offprint requests to: R Koster     

Boundary-layer diffusion modelling: The Gaussian plume approach versus the spectral solution

The equation of turbulent diffusion is solved for a vertical area source within the planetary boundary layer. The traditional Gaussian-plume approach is compared with the spectral solution of the diffusion equation used together with the barotropic boundary-layer model of Lettau and Dabberdt (1970). The results of the numerical computations are presented and the differences between the solutions are discussed.     

High-resolution numerical modelling of convective precipitation over Northern Italy

Summary A number of forecast experiments were performed in order to assess the capability of reproducing, by means of a limited-area numerical model, the highly structured mesoscale circulations occurring in the Po Valley of Northern Italy during a north-westerly cold front passage across the Alpine chain, with particular attention to the modelling of the effects of organized convection. The case-study occurred during summer 1987 and the model used throughout was the 1989 version of the UB/NMC Limited Area Model (University of Belgrade, National Meteorological Centre of Washington). The model was integrated both with eta, , and sigma, , as vertical coordinates and ECMWF initialized analyses were always used as initial conditions. ECMWF initialized analysis or operational forecast fields were also used for updating in time the lateral boundary conditions. Experiments show qualitative and quantitative agreement with observations, both in upper-air geopotential height fields, in MSLP and in cumulated precipitation. Several modelling issues were also investigated, e.g. sensitivity of the results to horizontal and vertical model resolution and to the influence of the lateral boundaries poitioning, finding large effects of the latter on quantitative precipitation fields. Difficulties in modelling very localized mesoscale phenomena, e.g. organized convective thunderstorms in the Po Valley and Alpine North Foehn in the Milan area, were generally encounted.     

Prediction of spring precipitation in China using a downscaling approach

The aim of this paper is to use a statistical downscaling model to predict spring precipitation over China based on a large-scale circulation simulation using Development of a European Multi-model Ensemble System for Seasonal to Interannual Prediction (DEMETER) General Circulation Models (GCMs) from 1960 to 2001. A singular value decomposition regression analysis was performed to establish the link between the spring precipitation and the large-scale variables, particularly for the geopotential height at 500?hPa and the sea-level pressure. The DEMETER GCM predictors were determined on the basis of their agreement with the reanalysis data for specific domains. This downscaling scheme significantly improved the predictability compared with the raw DEMETER GCM output for both the independent hindcast test and the cross-validation test. For the independent hindcast test, multi-year average spatial correlation coefficients (CCs) increased by at least ~30?% compared with the DEMETER GCMs’ precipitation output. In addition, the root mean-square errors (RMSEs) decreased more than 35?% compared with the raw DEMETER GCM output. For the cross-validation test, the spatial CCs increased to greater than 0.9 for most of the individual years, and the temporal CCs increased to greater than 0.3 (95?% confidence level) for most regions in China from 1960 to 2001. The RMSEs decreased significantly compared with the raw output. Furthermore, the preceding predictor, the Arctic Oscillation, increased the predicted skill of the downscaling scheme during the spring of 1963.     

Quantitative precipitation forecasts: a statistical adaptation of model outputs through an analogues sorting approach

Medium-term quantitative precipitation forecasts (QPFs) up to several days ahead are required to issue early flood warnings and to allow optimum operation of hydraulic structures or reservoirs. This paper describes an approach which can be seen as an adaptation of deterministic meteorological model outputs. It involves searching for a sample of past situations similar to the current one from a long meteorological archive. The analogy is considered in terms of general circulation patterns over a window covering western Europe. For this restricted sample of days similar to the day at hand, the corresponding sample of observed daily precipitation is extracted for each catchment. The rainfall to be observed during the current day is assumed to follow the same distribution, known from this empirical sample. This provides a probabilistic forecast expressed, for example, by a central quantile and a confidence range. This paper describes the many choices underlying the optimisation of this approach: choice of predictor variables to characterise a meteorological situation, choice of similarity criterion between two situations, criterion for performance evaluation between two versions of the algorithm, etc. This method was calibrated over about 50 catchments located in France, Italy and Spain, using a meteorological and hydrological archive running from 1953 to 1996. Comparisons carried out over a validation sample (1995–1996) with three poor-man methods prove the interest of this approach, in a perfect prognosis context. In real-time operation, the use of forecast instead of observed predictor variables, essentially geopotential fields, produces only a minor decrease in performance. The use of the single-valued central quantile supplemented by the confidence interval provided a QPF that has proved effective and informative on the potential for extreme values.     

Development of statistical prediction models for Changma precipitation: An ensemble approach

An ensemble statistical forecast scheme with a one-month lead is developed to predict year-to-year variations of Changma rainfall over the Korean peninsula. Spring sea surface temperature (SST) anomalies over the North Atlantic, the North Pacific and the tropical Pacific Ocean have been proposed as useful predictors in a previous study. Through a forward-stepwise regression method, four additional springtime predictors are selected: the northern Indian Ocean (NIO) SST, the North Atlantic SST change (NAC), the snow cover anomaly over the Eurasian continent (EUSC), and the western North Pacific outgoing longwave radiation anomaly (WNP (OLR)). Using these, three new prediction models are developed. A simple arithmetic ensemble mean produces much improved forecast skills compared to the original prediction model of Lee and Seo (2013). Skill scores measured by temporal correlation and MSSS (mean square error skill score) are improved by about 9% and 17%, respectively. The GMSS (Gerrity skill score) and hit rate based on a tercile prediction validation scheme are also enhanced by about 19% and 13%, respectively. The reversed NIO, reversed WNP (OLR), and reversed NAC are all related to the enhancement of a cyclonic circulation anomaly to the south or southwest of the Korean peninsula, which induces southeasterly moisture flux into the peninsula and increasing Changma precipitation. The EUSC predictor induces an enhancement of the Okhotsk Sea high downstream and thus strengthening of Changma front.     

Downscaling daily precipitation time series using a combined circulation- and regression-based approach

The aim of this paper is to introduce a new conditional statistical model for generating daily precipitation time series. The generated daily precipitation can thus be used for climate change impact studies, e.g., crop production, rainfall–runoff, and other water-related processes. It is a stochastic model that links local rainfall events to a continuous atmospheric predictor, moisture flux, in addition to classified atmospheric circulation patterns. The coupled moisture flux is proved to be capable of capturing continuous property of climate system and providing extra information to determine rainfall probability and rainfall amount. The application was made to simultaneously downscale daily precipitation at multiple sites within the Rhine River basin. The results show that the model can well reproduce statistical properties of daily precipitation time series. Especially for extreme rainfall events, the model is thought to better reflect rainfall variability compared to the pure CP-based downscaling approach.     

Forecasting monthly precipitation in Central Chile: a self-organizing map approach using filtered sea surface temperature

Western South America is subject to considerable inter-annual variability due to El Ni?o–Southern Oscillation (ENSO) so forecasting inter-annual variations associated with ENSO would provide an opportunity to tailor management decisions more appropriately to the season. On one hand, the self-organizing maps (SOM) method is a suitable technique to explore the association between sea surface temperature and precipitation fields. On the other hand, Wavelet transform is a filtering technique, which allows the identification of relevant frequencies in signals, and also allows localization on time. Taking advantage of both methods, we present a method to forecast monthly precipitation using the SOM trained with filtered SST anomalies. The use of the SOM to forecast precipitation for Chillan showed good agreement between forecasted and measured values, with correlation coefficients (r ²) ranging from 0.72 to 0.91, making the combined use filtered SST fields and SOM a suitable tool to assist water management, for example in agricultural water management. The method can be easily tailored to be applied in other stations or to other variables.     

Vegetation dynamics: A deterministic modelling approach using the concept of spreadability

Summary Various approaches have been developed for modelling processes related to vegetation dynamics. Most of them are biogeographical models (empirical) or dynamical models. Recent development in dynamical systems analysis has led to the investigation of an original concept essentially motivated by vegetation migration. It is the so-called spreadability concept developed by El Jai et al. (1994). The purpose of this paper is to consider this new idea and to show how it can lead to dynamical models which describe the expansion of a vegetation area. We give some mathematical examples showing the migration of the system state and also present some results related to control and numerical implementation of such systems. These results are, at the moment, completely academic, but they can be usefully applied in the analysis of real ecosystems and the dynamics that govern the behaviour of these systems.With 6 Figures     

Simulated Antarctic precipitation and surface mass balance at the end of the twentieth and twenty-first centuries

The aim of this work is to assess potential future Antarctic surface mass balance changes, the underlying mechanisms, and the impact of these changes on global sea level. To this end, this paper presents simulations of the Antarctic climate for the end of the twentieth and twenty-first centuries. The simulations were carried out with a stretched-grid atmospheric general circulation model, allowing for high horizontal resolution (60 km) over Antarctica. It is found that the simulated present-day surface mass balance is skilful on continental scales. Errors on regional scales are moderate when observed sea surface conditions are used; more significant regional biases appear when sea surface conditions from a coupled model run are prescribed. The simulated Antarctic surface mass balance increases by 32 mm water equivalent per year in the next century, corresponding to a sea level decrease of 1.2 mm year⁻¹ by the end of the twenty-first century. This surface mass balance increase is largely due to precipitation changes, while changes in snow melt and turbulent latent surface fluxes are weak. The temperature increase leads to an increased moisture transport towards the interior of the continent because of the higher moisture holding capacity of warmer air, but changes in atmospheric dynamics, in particular off the Antarctic coast, regionally modulate this signal.     

Isotopic composition and origin of polar precipitation in present and glacial climate simulations

The Hamburg atmospheric general circulation model (AGCM) ECHAM‐4 is used to identify the main source regions of precipitation falling on Greenland and Antarctica. Both water isotopes H₂¹⁸O and HDO are explicitly built into the water cycle of the AGCM, and in addition the capability to trace water from different source regions was added to the model. Present and LGM climate simulations show that water from the most important source regions has an isotopic signature similar to the mean isotope values of the total precipitation amount. But water from other source regions (with very different isotopic signatures) contributes an additional, non‐negligible part of the total precipitation amount on both Greenland and Antarctica. Analyses of the temperature‐isotope‐relations for both polar regions reveal a solely bias of the glacial isotope signal on Greenland, which is caused by a strong change in the seasonal deposition of precipitation originating from nearby polar seas and the northern Atlantic. Although the performed simulations under LGM boundary conditions show a decrease of the δ ¹⁸O values in precipitation in agreement with ice core measurements, the AGCM fails to reproduce the observed simultaneous decrease of the deuterium excess signal.     

降水时间随机性对月总降水量的影响

降水量在时间分布上呈现较大的随机性,极端降水事件尤为如此。受此影响,月初(月末) 1～5 d之内的累积降水量很可能会超过当月总降水量的50%乃至更多。对1961—2017年中国2 400多站点资料统计分析结果发现,月初(月末) 1～5 d累积降水量对当月总降水量显著影响事件的出现频次,在季节和空间分布上都有鲜明特征。主要包括:1)月初累积降水量对秋冬季中各月的总降水量影响更大,月末累积降水量对1—4月的月总降水量影响较大。2)受月初累积降水量的影响,显著站点数在某些年份的某些月份出现极大值;受单次事件显著影响的站点数占全国总站点数的30%～50%,此即对应着一次全国大范围的极端降水事件。3)受月初(月末)累积降水量显著影响的站点空间分布随季节变化呈现出明显空间集聚特征。     

Nonstationary frequency analysis of extreme daily precipitation amounts in Southeastern Canada using a peaks-over-threshold approach

Theoretical and Applied Climatology - In this paper, a statistical inference of Southeastern Canada extreme daily precipitation amounts is proposed using a classical nonstationary...     

Temperature and precipitation projections for the Antarctic Peninsula over the next two decades: contrasting global and regional climate model simulations

This study presents near future (2020–2044) temperature and precipitation changes over the Antarctic Peninsula under the high-emission scenario (RCP8.5). We make use of historical and projected simulations from 19 global climate models (GCMs) participating in Coupled Model Intercomparison Project phase 5 (CMIP5). We compare and contrast GCMs projections with two groups of regional climate model simulations (RCMs): (1) high resolution (15-km) simulations performed with Polar-WRF model forced with bias-corrected NCAR-CESM1 (NC-CORR) over the Antarctic Peninsula, (2) medium resolution (50-km) simulations of KNMI-RACMO21P forced with EC-EARTH (EC) obtained from the CORDEX-Antarctica. A further comparison of historical simulations (1981–2005) with respect to ERA5 reanalysis is also included for circulation patterns and near-surface temperature climatology. In general, both RCM boundary conditions represent well the main circulation patterns of the historical period. Nonetheless, there are important differences in projections such as a notable deepening and weakening of the Amundsen Sea Low in EC and NC-CORR, respectively. Mean annual near-surface temperatures are projected to increase by about 0.5–1.5 \(^{\circ }\)C across the entire peninsula. Temperature increase is more substantial in autumn and winter (\(\sim \) 2 \(^{\circ }\)C). Following opposite circulation pattern changes, both EC and NC-CORR exhibit different warming rates, indicating a possible continuation of natural decadal variability. Although generally showing similar temperature changes, RCM projections show less warming and a smaller increase in melt days in the Larsen Ice Shelf compared to their respective driving fields. Regarding precipitation, there is a broad agreement among the simulations, indicating an increase in mean annual precipitation (\(\sim \) 5 to 10%). However, RCMs show some notable differences over the Larsen Ice Shelf where total precipitation decreases (for RACMO) and shows a small increase in rain frequency. We conclude that it seems still difficult to get consistent projections from GCMs for the Antarctic Peninsula as depicted in both RCM boundary conditions. In addition, dominant and common changes from the boundary conditions are largely evident in the RCM simulations. We argue that added value of RCM projections is driven by processes shaped by finer local details and different physics schemes that are introduced by RCMs, particularly over the Larsen Ice Shelf.

     

A step-response approach for predicting and understanding non-linear precipitation changes

Future changes in precipitation represent one of the most important and uncertain possible effects of future climate change. We demonstrate a new approach based on idealised CO₂ step-change general circulation model (GCM) experiments, and test it using the HadCM3 GCM. The approach has two purposes: to help understand GCM projections, and to build and test a fast simple model for precipitation projections under a wide range of forcing scenarios. Overall, we find that the CO₂ step experiments contain much information that is relevant to transient projections, but that is more easily extracted due to the idealised experimental design. We find that the temporary acceleration of global-mean precipitation in this GCM following CO₂ ramp-down cannot be fully explained simply using linear responses to CO₂ and temperature. A more complete explanation can be achieved with an additional term representing interaction between CO₂ and temperature effects. Energy budget analysis of this term is dominated by clear-sky outgoing long-wave radiation (CSOLR) and sensible heating, but cloud and short-wave terms also contribute. The dominant CSOLR interaction is attributable to increased CO₂ raising the mean emission level to colder altitudes, which reduces the rate of increase of OLR with warming. This behaviour can be reproduced by our simple model. On regional scales, we compare our approach with linear ‘pattern-scaling’ (scaling regional responses by global-mean temperature change). In regions where our model predicts linear change, pattern-scaling works equally well. In some regions, however, substantial deviations from linear scaling with global-mean temperature are found, and our simple model provides more accurate projections. The idealised experiments reveal a complex pattern of non-linear behaviour. There are likely to be a range of controlling physical mechanisms, different from those dominating the global-mean response, requiring focussed investigation for individual regions, and in other GCMs.