Experience of using a dynamic stochastic approach for solving the problem of very short-range forecasting of state parameters of the atmospheric boundary layer

Discussed are the results of applying a dynamic stochastic method based on the use of the two-dimensional model and the Kalman filtering algorithm for solving the problem of the very short-range (from 0.5 to 6 hours) fore cast of air temperature and orthogonal components of the wind speed in the atmospheric boundary layer realized using the data of radio metric, sodar, and in creased-frequency radiosonde measurements. It is demonstrated that the pro posed technique and the appropriate algorithm give a rather high ac cu racy of very short-range fore casting of temperature and wind within the lead time range under consideration.     

Effect of wind forcing on the meridional heat transport in a coupled climate model: equilibrium response

Climate Dynamics - The effect of the ocean surface winds on the meridional heat transports is studied in a coupled model. Shutting down the global surface winds causes significant reductions in...     

Conditional stochastic simulation model for spatial downscaling for assessing the effects of climate change on hydro-meteorological variables

The current study examines the recently proposed “bias correction and stochastic analogues” (BCSA) statistical spatial downscaling technique and attempts to improve it by conditioning coarse resolution data when generating replicates. While the BCSA method reproduces the statistical features of the observed fine data, this existing model does not replicate the observed coarse spatial pattern, and subsequently, the cross-correlation between the observed coarse data and downscaled fine data with the model cannot be preserved. To address the dissimilarity between the BCSA downscaled data and observed fine data, a new statistical spatial downscaling method, “conditional stochastic simulation with bias correction” (BCCS), which employs the conditional multivariate distribution and principal component analysis, is proposed. Gridded observed climate data of mean daily precipitation (mm/day) covering a month at 1/8° for a fine resolution and at 1° for a coarse resolution over Florida for the current and future periods were used to verify and cross-validate the proposed technique. The observed coarse and fine data cover the 50-year period from 1950 to1999, and the future RCP4.5 and RCP8.5 climate scenarios cover the 100-year period from 2000 to 2099. The verification and cross-validation results show that the proposed BCCS downscaling method serves as an effective alternative means of downscaling monthly precipitation levels to assess climate change effects on hydrological variables. The RCP4.5 and RCP8.5 GCM scenarios are successfully downscaled.     

Processes governing the predictability of the Atlantic meridional overturning circulation in a coupled GCM

The processes that govern the predictability of decadal variations in the North Atlantic meridional overturning circulation (MOC) are investigated in a long control simulation of the ECHO-G coupled atmosphere?Cocean model. We elucidate the roles of local stochastic forcing by the atmosphere, and other potential ocean processes, and use our results to build a predictive regression model. The primary influence on MOC variability is found to come from air?Csea heat fluxes over the Eastern Labrador Sea. The maximum correlation between such anomalies and the variations in the MOC occurs at a lead time of 2?years, but we demonstrate that the MOC integrates the heat flux variations over a period of 10?years. The corresponding univariate regression model accounts for 74.5% of the interannual variability in the MOC (after the Ekman component has been removed). Dense anomalies to the south of the Greenland-Scotland ridge are also shown to precede the overturning variations by 4?C6?years, and provide a second predictor. With the inclusion of this second predictor the resulting regression model explains 82.8% of the total variance of the MOC. This final bivariate model is also tested during large rapid decadal overturning events. The sign of the rapid change is always well represented by the bivariate model, but the magnitude is usually underestimated, suggesting that other processes are also important for these large rapid decadal changes in the MOC.     

Early Last Interglacial Greenland Ice Sheet melting and a sustained period of meridional overturning weakening: a model analysis of the uncertainties

Proxy-data suggest that the Last Interglacial (LIG; ~130–116 ka BP) climate was characterized by higher temperatures, a partially melted Greenland Ice Sheet (GIS) and a changed Atlantic meridional overturning circulation (AMOC). Notwithstanding the uncertainties in LIG palaeoclimatic reconstructions, this setting potentially provides an opportunity to evaluate the relation between GIS melt and the AMOC as simulated by climate models. However, first we need to assess the extent to which a causal relation between early LIG GIS melt and the weakened AMOC is plausible. With a series of transient LIG climate simulations with the LOVECLIM earth system model, we quantify the importance of the major known uncertainties involved in early LIG GIS melt scenarios. Based on this we construct a specific scenario that is within the parameter space of uncertainties and show that it is physically consistent that early LIG GIS melting kept the AMOC weakened. Notwithstanding, this scenario is at the extreme end of the parameter space. Assuming that proxy-based reconstructions of early LIG AMOC weakening offer a realistic representation of its past state, this indicates that either (1) the AMOC weakening was caused by other forcings than early LIG GIS melt or (2) the early LIG AMOC was less stable than indicated by our simulations and a small amount of GIS melt was sufficient to keep the AMOC in the weak state of a bi-stable regime. We argue that more intensive research is required because of the high potential of the early LIG to evaluate model performance in relation to the AMOC response to GIS melt.     

Response of the meridional overturning circulation to variable buoyancy forcing in a double hemisphere basin

We consider how a highly idealized double-hemisphere basin responds to a zonally constant restoring surface temperature profile that oscillates in time, with periods ranging from 0.5 to 32,000 years. In both hemispheres, the forcing is similar but can be either in phase or out of phase. The set-up is such that the Northern Hemisphere always produces the densest waters. The model’s meridional overturning circulation (MOC) exhibits a strong response in both hemispheres on decadal to multi-millennial timescales. The amplitude of the oscillations reaches up to 140% of the steady-state maximum MOC and exhibits resonance-like behaviour, with a maximum at centennial to millennial forcing periods. When the forcing is in phase between the Northern and Southern Hemispheres, there is a marked decrease in the amplitude of the MOC response as the forcing period is increased beyond the resonance period. In this case the resonance-like behaviour is identical to the one we found earlier in a single-hemisphere model and occurs for the same reasons. When the forcing is out of phase between the Northern and Southern Hemispheres, the amplitude of the MOC response is substantially greater for long forcing periods (millennial and longer), particularly in the Southern Hemisphere. This increased MOC amplitude occurs because for an out of phase forcing, either the northern or the southern deep water source is always active, leading to generally colder bottom waters and thus greater stratification in the opposite hemisphere. This increased stratification in turn stabilises the water column and thus reduces the strength of the weaker overturning cell. The interaction of the two hemispheres leads to response timescales of the deep ocean at half the forcing period. Our results suggest a possible explanation for the half-precessional time scale observed in the deep Atlantic Ocean palaeo-temperature record.     

Changes in tropical Atlantic interannual variability from a substantial weakening of the meridional overturning circulation

In response to a substantial weakening of the Atlantic Meridional Overturning Circulation (AMOC)—from a coupled ocean–atmosphere general circulation model experiment—significant changes in the interannual variability are found over the tropical Atlantic, characterized by an increase of variance (by ~150 %) in boreal late spring-early summer and a decrease of variance (by ~60 %) in boreal autumn. This study focuses on understanding physical mechanisms responsible for these changes in interannual variability in the tropical Atlantic. It demonstrates that the increase of variability in spring is a consequence of an increase in the variance of the El Niño-Southern Oscillation, which has a large impact on the tropical Atlantic via anomalous surface heat fluxes. Winter El Niño (La Niña) affects the eastern equatorial Atlantic by decreasing (increasing) cloud cover and surface wind speed which is associated with anomalous downward (upward) short wave radiation and reduced (enhanced) upward latent heat fluxes, creating anomalous positive (negative) sea surface temperature (SST) anomalies over the region from winter to spring. On the other hand, the decrease of SST variance in autumn is due to a deeper mean thermocline which weakens the impact of the thermocline movement on SST variation. The comparison between the model results and observations is not straightforward owing to the influence of model biases and the lack of a major MOC weakening event in the instrumental record. However, it is argued that the basic physical mechanisms found in the model simulations are likely to be robust and therefore have relevance to understanding tropical Atlantic variability in the real world, perhaps with modified seasonality.     

South Asian monsoon response to weakening of Atlantic meridional overturning circulation in a warming climate

Climate Dynamics - Observational records and climate model projections reveal a considerable decline in the Atlantic Meridional Overturning Circulation (AMOC). Changes in the AMOC can have a...     

Simulation of the Atlantic meridional overturning circulation in an atmosphere-ocean global coupled model. Part II: weakening in a climate change experiment: a feedback mechanism

Most state-of-the art global coupled models simulate a weakening of the Atlantic meridional overturning circulation (MOC) in climate change scenarios but the mechanisms leading to this weakening are still being debated. The third version of the CNRM (Centre National de Recherches Météorologiques) global atmosphere-ocean-sea ice coupled model (CNRM-CM3) was used to conduct climate change experiments for the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC AR4). The analysis of the A1B scenario experiment shows that global warming leads to a slowdown of North Atlantic deep ocean convection and thermohaline circulation south of Iceland. This slowdown is triggered by a freshening of the Arctic Ocean and an increase in freshwater outflow through Fram Strait. Sea ice melting in the Barents Sea induces a local amplification of the surface warming, which enhances the cyclonic atmospheric circulation around Spitzberg. This anti-clockwise circulation forces an increase in Fram Strait outflow and a simultaneous increase in ocean transport of warm waters toward the Barents Sea, favouring further sea ice melting and surface warming in the Barents Sea. Additionally, the retreat of sea ice allows more deep water formation north of Iceland and the thermohaline circulation strengthens there. The transport of warm and saline waters toward the Barents Sea is further enhanced, which constitutes a second positive feedback.     

Electric sector investments under technological and policy-related uncertainties: a stochastic programming approach

Although emerging technologies like carbon capture and storage and advanced nuclear are expected to play leading roles in greenhouse gas mitigation efforts, many engineering and policy-related uncertainties will influence their deployment. Capital-intensive infrastructure decisions depend on understanding the likelihoods and impacts of uncertainties such as the timing and stringency of climate policy as well as the technological availability of carbon capture systems. This paper demonstrates the utility of stochastic programming approaches to uncertainty analysis within a practical policy setting, using uncertainties in the US electric sector as motivating examples. We describe the potential utility of this framework for energy-environmental decision making and use a modeling example to reinforce these points and to stress the need for new tools to better exploit the full range of benefits the stochastic programming approach can provide. Model results illustrate how this framework can give important insights about hedging strategies to reduce risks associated with high compliance costs for tight CO₂ caps and low CCS availability. Metrics for evaluating uncertainties like the expected value of perfect information and the value of the stochastic solution quantify the importance of including uncertainties in capacity planning, of making precautionary low-carbon investments, and of conducting research and gathering information to reduce risk.     

Application of soft computing based hybrid models in hydrological variables modeling: a comprehensive review

Theoretical and Applied Climatology - Snow is a key element for many socioeconomic activities in mountainous regions. Due to the sensitivity of the snow cover to variations of temperature and...     

Assessment of climate change impacts on climate variables using probabilistic ensemble modeling and trend analysis

Water resources in snow-dependent regions have undergone significant changes due to climate change. Snow measurements in these regions have revealed alarming declines in snowfall over the past few years. The Zayandeh-Rud River in central Iran chiefly depends on winter falls as snow for supplying water from wet regions in high Zagrous Mountains to the downstream, (semi-)arid, low-lying lands. In this study, the historical records (baseline: 1971–2000) of climate variables (temperature and precipitation) in the wet region were chosen to construct a probabilistic ensemble model using 15 GCMs in order to forecast future trends and changes while the Long Ashton Research Station Weather Generator (LARS-WG) was utilized to project climate variables under two A2 and B1 scenarios to a future period (2015–2044). Since future snow water equivalent (SWE) forecasts by GCMs were not available for the study area, an artificial neural network (ANN) was implemented to build a relationship between climate variables and snow water equivalent for the baseline period to estimate future snowfall amounts. As a last step, homogeneity and trend tests were performed to evaluate the robustness of the data series and changes were examined to detect past and future variations. Results indicate different characteristics of the climate variables at upstream stations. A shift is observed in the type of precipitation from snow to rain as well as in its quantities across the subregions. The key role in these shifts and the subsequent side effects such as water losses is played by temperature.

     

Generation of a stochastic precipitation model for the tropical climate

Theoretical and Applied Climatology - A tropical country like Malaysia is characterized by intense localized precipitation with temperatures remaining relatively constant throughout the year. A...     

The impact of resolution on the adjustment and decadal variability of the Atlantic meridional overturning circulation in a coupled climate model

Variations in the Atlantic meridional overturning circulation (MOC) exert an important influence on climate, particularly on decadal time scales. Simulation of the MOC in coupled climate models is compromised, to a degree that is unknown, by their lack of fidelity in resolving some of the key processes involved. There is an overarching need to increase the resolution and fidelity of climate models, but also to assess how increases in resolution influence the simulation of key phenomena such as the MOC. In this study we investigate the impact of significantly increasing the (ocean and atmosphere) resolution of a coupled climate model on the simulation of MOC variability by comparing high and low resolution versions of the same model. In both versions, decadal variability of the MOC is closely linked to density anomalies that propagate from the Labrador Sea southward along the deep western boundary. We demonstrate that the MOC adjustment proceeds more rapidly in the higher resolution model due the increased speed of western boundary waves. However, the response of the Atlantic sea surface temperatures to MOC variations is relatively robust—in pattern if not in magnitude—across the two resolutions. The MOC also excites a coupled ocean-atmosphere response in the tropical Atlantic in both model versions. In the higher resolution model, but not the lower resolution model, there is evidence of a significant response in the extratropical atmosphere over the North Atlantic 6?years after a maximum in the MOC. In both models there is evidence of a weak negative feedback on deep density anomalies in the Labrador Sea, and hence on the MOC (with a time scale of approximately ten years). Our results highlight the need for further work to understand the decadal variability of the MOC and its simulation in climate models.     

Revisiting the latent heat nudging scheme for the rainfall assimilation of a simulated convective storm

Summary Next-generation, operational, high-resolution numerical weather prediction models require economical assimilation schemes for radar data. In the present study we evaluate and characterise the latent heat nudging (LHN) rainfall assimilation scheme within a meso-γ scale NWP model in the framework of identical twin simulations of an idealised supercell storm. Consideration is given to the model’s dynamical response to the forcing as well as to the sensitivity of the LHN scheme to uncertainty in the observations and the environment. The results indicate that the LHN scheme is well able to capture the dynamical structure and the right rainfall amount of the storm in a perfect environment. This holds true even in degraded environments but a number of important issues arise. In particular, changes in the low-level humidity field are found to affect mainly the precipitation amplitude during the assimilation with a fast adaptation of the storm to the system dynamics determined by the environment during the free forecast. A constant bias in the environmental wind field, on the other hand, has the potential to render a successful assimilation with the LHN scheme difficult, as the velocity of the forcing is not consistent with the system propagation speed determined by the wind. If the rainfall forcing moves too fast, the system propagation is supported and the assimilated storm and forecasts initialised therefrom develop properly. A too slow forcing, on the other hand, can decelerate the system and eventually disturb the system dynamics by decoupling the low-level moisture inflow from the main updrafts during the assimilation. This distortion is sustained in the free forecast. It has further been found that a sufficient temporal resolution of the rainfall input is crucial for the successful assimilation of a fast moving, coherent convective storm and that the LHN scheme, when applied to a convective storm, appears to necessitate a careful tuning.     

African monsoon teleconnections with tropical SSTs: validation and evolution in a set of IPCC4 simulations

A set of 12 state-of-the-art coupled ocean-atmosphere general circulation models (OAGCMs) is explored to assess their ability to simulate the main teleconnections between the West African monsoon (WAM) and the tropical sea surface temperatures (SSTs) at the interannual to multi-decadal time scales. Such teleconnections are indeed responsible for the main modes of precipitation variability observed over West Africa and represent an interesting benchmark for the models that have contributed to the fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC4). The evaluation is based on a maximum covariance analysis (MCA) applied on tropical SSTs and WAM rainfall. To distinguish between interannual and multi-decadal variability, all datasets are partitioned into low-frequency (LF) and high-frequency (HF) components prior to analysis. First applied to HF observations, the MCA reveals two major teleconnections. The first mode highlights the strong influence of the El Niño Southern Oscillation (ENSO). The second mode reveals a relationship between the SST in the Gulf of Guinea and the northward migration of the monsoon rainbelt over the West African continent. When applied to HF outputs of the twentieth century IPCC4 simulations, the MCA provides heterogeneous results. Most simulations show a single dominant Pacific teleconnection, which is, however, of the wrong sign for half of the models. Only one model shows a significant second mode, emphasizing the OAGCMs’ difficulty in simulating the response of the African rainbelt to Atlantic SST anomalies that are not synchronous with Pacific anomalies. The LF modulation of these HF teleconnections is then explored through running correlations between expansion coefficients (ECs) for SSTs and precipitation. The observed time series indicate that both Pacific and Atlantic teleconnections get stronger during the twentieth century. The IPCC4 simulations of the twentieth and twenty-first centuries do not show any significant change in the pattern of the teleconnections, but the dominant ENSO teleconnection also exhibits a significant strengthening, thereby suggesting that the observed trend could be partly a response to the anthropogenic forcing. Finally, the MCA is also applied to the LF data. The first observed mode reveals a well-known inter-hemispheric SST pattern that is strongly related to the multi-decadal variability of the WAM rainfall dominated by the severe drying trend from the 1950s to the 1980s. Whereas recent studies suggest that this drying could be partly caused by anthropogenic forcings, only 5 among the 12 IPCC4 models capture some features of this LF coupled mode. This result suggests the need for a more detailed validation of the WAM variability, including a dynamical interpretation of the SST–rainfall relationships.