Response of convective systems to the orbital forcing of the last interglacial in a global nonhydrostatic atmospheric model with and without a convective parameterization

Nonhydrostatic Icosahedral Atmospheric Model (NICAM) coupled with a slab ocean model was applied to a paleoclimate research for the first time. The model was run at a horizontal resolution of 56 km with and without a convective parameterization, given the orbital parameters of the last interglacial (127,000 years before present). The simulated climatological mean-states are qualitatively similar to those in previous studies reinforcing their robustness, however, the resolution of this model enables to represent the narrow precipitation band along the southern edge of the Tibetan Plateau. A particular focus was given to convectively coupled disturbances in our analysis. The simulated results show a greater signal of the Madden–Julian Oscillation and weakening of the moist Kelvin waves. Although the model's representation of the boreal summer intraseasonal oscillation in the present-day simulations is not satisfactory, a significant enhancement of its signal is found in the counterpart of the last interglacial. The density of the tropical cyclones decreases over the western north Pacific, north Atlantic and increases over the south Indian Ocean and south Atlantic. The model's performance is generally better when the convective parameterization is used, but the tropical cyclones are better represented without the convective parameterization. Additional simulations using the low-resolution topography reveals that the better representation of the Tibetan Plateau enhances the boreal summer Asian monsoon and its impact is similar and comparable to that of the orbital parameters over the south Asia and the Indian Ocean.

The effect of Indian Ocean warming on the Indian Monsoon: An atmospheric model study

The results from an atmospheric modeling study using the Florida State University Global Spectral Model indicate that, in years such as 1997 when the Indian Ocean SSTs are large, the Indian monsoon exhibits a typical behaviour. During that year, an extended shift of the tropical convergence zone towards the north played a role in the regional Hadley cell anomalies. The local warm boundary conditions in the northwestern Indian Ocean aided the high rainfall anomaly in Western India during the model simulations. The upper level structure, exhibited in terms of the global velocity potential is slightly shifted east for 1997, but with the correct sign. This structure shows regions of convergence over Indonesia where severe drought had occurred. The performance of the model rainfall over the equatorial Indian Ocean was uncanny for most seasons studied. Overall, the model performed best over the oceanic regions.

Concurrent calculation of radiative transfer in the atmospheric simulation in ECHAM-6.3.05p2

​​​​​​​The scalability of the atmospheric model ECHAM6 at low resolution, as used in palaeoclimate simulations, suffers from the limited number of grid points. As a consequence, the potential of current high-performance computing architectures cannot be used at full scale for such experiments, particularly within the available domain decomposition approach. Radiation calculations are a relatively expensive part of the atmospheric simulations, taking up to approximately 50 % or more of the total runtime. This current level of cost is achieved by calculating the radiative transfer only once in every 2 h of simulation. In response, we propose extending the available concurrency within the model further by running the radiation component in parallel with other atmospheric processes to improve scalability and performance. This paper introduces the concurrent radiation scheme in ECHAM6 and presents a thorough analysis of its impact on the performance of the model. It also evaluates the scientific results from such simulations. Our experiments show that ECHAM6 can achieve a speedup of over 1.9× using the concurrent radiation scheme. By performing a suite of stand-alone atmospheric experiments, we evaluate the influence of the concurrent radiation scheme on the scientific results. The simulated mean climate and internal climate variability by the concurrent radiation generally agree well with the classical radiation scheme, with minor improvements in the mean atmospheric circulation in the Southern Hemisphere and the atmospheric teleconnection to the Southern Annular Mode. This empirical study serves as a successful example that can stimulate research on other concurrent components in atmospheric modelling whenever scalability becomes challenging.

Multi-Objective Optimisation under Uncertainty with Unscented Temporal Finite Elements

This paper presents a novel method for multi-objective optimisation under uncertainty developed to study a range of mission trade-offs, and the impact of uncertainties on the evaluation of launch system mission designs. A memetic multi-objective optimisation algorithm, named MODHOC, which combines the Direct Finite Elements in Time transcription method with Multi Agent Collaborative Search, is extended to account for model uncertainties. An Unscented Transformation is used to capture the first two statistical moments of the quantities of interest. A quantification model of the uncertainty was developed for the atmospheric model parameters. An optimisation under uncertainty was run for the design of descent trajectories for a spaceplane-based two-stage launch system.

Implementing Hybrid Background Error Covariance into the LETKF with Attenuation-based Localization: Experiments with a Simplified AGCM

Recent numerical weather prediction systems have significantly improved medium-range forecasts by implementing hybrid background error covariance, for which climatological (static) and ensemble-based (flow-dependent) error covariance are combined. While the hybrid approach has been investigated mainly in variational systems, this study aims at exploring methods for implementing the hybrid approach for the local ensemble transform Kalman filter (LETKF). Following Kretchmer et al. (2015), the present study constructed hybrid background error covariance by adding collections of climatological perturbations to the forecast ensemble. In addition, this study proposes a new localization method that attenuates the ensemble perturbation (Z-localization) instead of inflating observation error variance (R-localization). A series of experiments with a simplified global atmospheric model revealed that the hybrid LETKF resulted in smaller forecast errors than the LETKF, especially in sparsely observed regions. Due to the larger ensemble enabled by the hybrid approach, optimal localization length scales for the hybrid LETKF were larger than those for the LETKF. With the LETKF, the Z-localization resulted in similar forecast errors as the R-localization. However, Z-localization has an advantage in enabling to apply different localization scales for flow-dependent perturbation and climatological static perturbations with the hybrid LETKF. The optimal localization for climatological perturbations was slightly larger than that for flow-dependent perturbations. This study proposes Optimal EigenDecomposition (OED) ETKF formulation to reduce computational costs. The computational expense of the OED ETKF formulation became significantly smaller than that of standard ETKF formulations as the number of climatological perturbations was increased beyond a few hundred.

Aerosol indirect effects in complex orography areas: a numerical study over the Great Alpine Region

Aerosols play a crucial role in climate through different feedback mechanisms, affecting radiation, clouds and air column stability. This study focuses on the altitude-dependence of the cloud mediated indirect effects of aerosols in the Great Alpine Region (GAR), an area characterised by high pollution levels from anthropic activities in the Po Valley and a complex orography with the highest mountains in Europe. Using a regional atmospheric model, 5-years long convective-permitting sensitivity experiments have been run with different surface aerosol fluxes. The results show that seasonal mean cloud cover, temperature, and precipitations are affected by the aerosol concentrations in the air column, and that the response to pollution is both elevation and season dependent. The overall cloud cover increase with aerosol levels leads to either surface cooling or warming depending on the surface albedo (snow covered or not). Furthermore, different types of clouds have a different sensitivity to aerosols: while the lifetime of low pressure system clouds and orographic clouds is generally increased at high levels of aerosols, convective clouds (typical of the summer season) can actually decrease at high levels of pollution, due to the reduction of strong updrafts.

Climate Modelling in Low Precision: Effects of Both Deterministic & Stochastic Rounding.

Motivated by recent advances in operational weather forecasting, we study the efficacy of low-precision arithmetic for climate simulations. We develop a framework to measure rounding error in a climate model which provides a stress-test for a low-precision version of the model, and we apply our method to a variety of models including the Lorenz system; a shallow water approximation for ow over a ridge; and a coarse resolution spectral global atmospheric model with simplified parameterisations (SPEEDY). Although double precision (52 significant bits) is standard across operational climate models, in our experiments we find that single precision (23 sbits) is more than enough and that as low as half precision (10 sbits) is often sufficient. For example, SPEEDY can be run with 12 sbits across the code with negligible rounding error, and with 10 sbits if minor errors are accepted, amounting to less than 0.1 mm/6hr for average grid-point precipitation, for example. Our test is based on the Wasserstein metric and this provides stringent non-parametric bounds on rounding error accounting for annual means as well as extreme weather events. In addition, by testing models using both round-to-nearest (RN) and stochastic rounding (SR) we find that SR can mitigate rounding error across a range of applications, and thus our results also provide some evidence that SR could be relevant to next-generation climate models. Further research is needed to test if our results can be generalised to higher resolutions and alternative numerical schemes. However, the results open a promising avenue towards the use of low-precision hardware for improved climate modelling.

Interdecadal Changes in the Relationship between Wintertime Surface Air Temperature over the Indo-China Peninsula and ENSO

Interdecadal variations of the relationship between El Niño-Southern Oscillation (ENSO) and the Indo-China Peninsula (ICP) surface air temperature (SAT) in winter are investigated in the study. Generally, there exists a positive correlation between them during 1958–2015 because the ENSO-induced anomalous western North Pacific anticyclone (WNPAC) is conducive to pronounced temperature advection anomalies over the ICP. However, such correlation is unstable in time, having experienced a high-to-low transition around the mid-1970s and a recovery since the early-1990s. This oscillating relationship is owing to the anomalous WNPAC intensity in different decades. During the epoch of high correlation, the anomalous WNPAC and associated southwesterly winds over the ICP are stronger, which brings amounts of warm temperature advections and markedly heats the ICP. Differently, a weaker WNPAC anomaly and insignificant ICP SAT anomalies are the circumstances for the epoch of low correlation. It is also found that substantial southwesterly wind anomalies over the ICP related to the anomalous WNPAC occur only when large sea surface temperature (SST) anomalies over the northwest Indian Ocean (NWIO) coincide with ENSO (namely when the ENSO-NWIO SST connection is strong). The NWIO SST anomalies are capable of driving favorable atmospheric circulation that effectively alters ICP SAT and efficiently modulates the ENSO-ICP SAT correlation, which is further supported by numerical simulations utilizing the Community Atmospheric Model, version 4 (CAM4). This paper emphasizes the non-stationarity of the ENSO-ICP SAT relationship and also uncovers the underlying modulation factors, which has important implications for the seasonal prediction of the ICP temperature.