Filamentation instability of Alfvén waves

The filamentation instability of finite amplitude left-hand circularly polarized Alfvén waves has been investigated taking into account the second-order density and magnetic field perturbations that are created by the Alfvén wave pressure. The minimum scale length and time over which the filamentation occurs, are found. Our results are applied to Alfvén waves that should scatter cosmic rays in the interstellar medium (ISM).     

Nonlinear Alfvén wave modulation in the solar atmosphere

Nonlinear interaction of finite-amplitude Alfvén waves with non-resonant finite-frequency electrostatic and stationary electromagnetic perturbations is considered. This interaction is governed by a pair of coupled equations consisting of nonlinear Schrödinger equation for the Alfvén wave envelope and an equation for the plasma slow response that is driven by the ponderomotive force of the Alfvén wave packets. The modulational instability of a constant amplitude Alfvén pump is investigated and some new results for the growth rate of the instability are presented. It is found that a possible stationary state of the modulated Alfvén wave packets could lead to localized structures. The relevance of our investigation to the solar atmosphere is discussed.     

Current gradient-driven linear and nonlinear electromagnetic waves in a magnetized electron-positron plasma

A set of coupled nonlinear differential equations which govern the dynamics of finite amplitude electromagnetic waves in the presence of an external current gradient in a magnetized electron-positron plasma has been derived. It is shown that the current gradient can make shear Alfvén-like waves unstable. A quasi-stationary solution of the mode-coupling equations is the well-localized dipole vortex. Application of our results to plasma transport in the pulsar magnetosphere is briefly discussed.     

Solar and galactic cosmic‐ray records of the Fermo (H) chondrite regolith breccia

Abstract— ‐We demonstrate the presence of solar flare as well as neutron capture effects in the isotopic composition of rare gases in the Fermo regolith breccia acquired on its parent body based on the measurements of tracks, rare gases and radionuclides. The track density along a 3.2 cm long core decreases by a factor of about 6 and by more than a factor of 13 within the meteorite, indicating small (2–9 cm) and asymmetrical ablation. Rare gases show a large trapped component; the isotopic ratios, particularly ²⁰Ne/²²Ne ? 11 and ²⁰Ne/³⁶Ar = 10 are indicative of a solar component. The galactic cosmic‐ray exposure age is determined to be 8.8 Ma. Activities of a dozen radionuclides ranging in half‐life from 16 day ⁴⁸V to 0.73 Ma ²⁶Al are consistent with their expected production rates. Track, rare gas and radionuclide data show that the meteoroid was a small body (≤ 120 kg) and had a simple, one‐stage exposure history to cosmic rays in the interplanetary space. However, ⁸²Kr and ¹²⁸Xe show an excess due to neutron irradiation on the parent body of the meteorite. The presence of solar gases and the neutron capture effects indicate several stages of irradiation on the parent asteroid. The chemical composition of Fermo confirms that it belongs to the H group of ordinary chondrites with lithic clasts having varying compositions. δ¹⁵N is found to be 8.3 ± 1.2%0, close to the typical values observed in H chondrites.     

Effects of cloud types on cloud-radiation interaction over the Asian monsoon region

This paper quantifies the sensitivity of radiation budget quantities to different cloud types over the Asian monsoon region using the International Satellite Cloud Climatology Project. Multiple regression was used to estimate the radiative effects of individual cloud type. It was observed that the regression performed better when the solution was constrained with clear sky fluxes, which is evident by an improvement in R ² statistics. The sensitivity coefficients calculated for the Asian monsoon region reveal that, while the LWCRCF and SWCRF will be most vulnerable to changes in cloud cover of deep convective clouds, NETCRF will be susceptible to changes in the nimbostratus clouds. Although the cloud radiative forcing of individual cloud types are found to be similar in sign to previous global findings, their magnitudes are found to vary. It is seen that cirrus clouds play an important role in governing the radiative behavior of this region.     

Advance and prospectus of seasonal prediction: assessment of the APCC/CliPAS 14-model ensemble retrospective seasonal prediction (1980–2004)

We assessed current status of multi-model ensemble (MME) deterministic and probabilistic seasonal prediction based on 25-year (1980–2004) retrospective forecasts performed by 14 climate model systems (7 one-tier and 7 two-tier systems) that participate in the Climate Prediction and its Application to Society (CliPAS) project sponsored by the Asian-Pacific Economic Cooperation Climate Center (APCC). We also evaluated seven DEMETER models’ MME for the period of 1981–2001 for comparison. Based on the assessment, future direction for improvement of seasonal prediction is discussed. We found that two measures of probabilistic forecast skill, the Brier Skill Score (BSS) and Area under the Relative Operating Characteristic curve (AROC), display similar spatial patterns as those represented by temporal correlation coefficient (TCC) score of deterministic MME forecast. A TCC score of 0.6 corresponds approximately to a BSS of 0.1 and an AROC of 0.7 and beyond these critical threshold values, they are almost linearly correlated. The MME method is demonstrated to be a valuable approach for reducing errors and quantifying forecast uncertainty due to model formulation. The MME prediction skill is substantially better than the averaged skill of all individual models. For instance, the TCC score of CliPAS one-tier MME forecast of Niño 3.4 index at a 6-month lead initiated from 1 May is 0.77, which is significantly higher than the corresponding averaged skill of seven individual coupled models (0.63). The MME made by using 14 coupled models from both DEMETER and CliPAS shows an even higher TCC score of 0.87. Effectiveness of MME depends on the averaged skill of individual models and their mutual independency. For probabilistic forecast the CliPAS MME gains considerable skill from increased forecast reliability as the number of model being used increases; the forecast resolution also increases for 2 m temperature but slightly decreases for precipitation. Equatorial Sea Surface Temperature (SST) anomalies are primary sources of atmospheric climate variability worldwide. The MME 1-month lead hindcast can predict, with high fidelity, the spatial–temporal structures of the first two leading empirical orthogonal modes of the equatorial SST anomalies for both boreal summer (JJA) and winter (DJF), which account for about 80–90% of the total variance. The major bias is a westward shift of SST anomaly between the dateline and 120°E, which may potentially degrade global teleconnection associated with it. The TCC score for SST predictions over the equatorial eastern Indian Ocean reaches about 0.68 with a 6-month lead forecast. However, the TCC score for Indian Ocean Dipole (IOD) index drops below 0.40 at a 3-month lead for both the May and November initial conditions due to the prediction barriers across July, and January, respectively. The MME prediction skills are well correlated with the amplitude of Niño 3.4 SST variation. The forecasts for 2 m air temperature are better in El Niño years than in La Niña years. The precipitation and circulation are predicted better in ENSO-decaying JJA than in ENSO-developing JJA. There is virtually no skill in ENSO-neutral years. Continuing improvement of the one-tier climate model’s slow coupled dynamics in reproducing realistic amplitude, spatial patterns, and temporal evolution of ENSO cycle is a key for long-lead seasonal forecast. Forecast of monsoon precipitation remains a major challenge. The seasonal rainfall predictions over land and during local summer have little skill, especially over tropical Africa. The differences in forecast skills over land areas between the CliPAS and DEMETER MMEs indicate potentials for further improvement of prediction over land. There is an urgent need to assess impacts of land surface initialization on the skill of seasonal and monthly forecast using a multi-model framework.     

Current status of ENSO prediction skill in coupled ocean–atmosphere models

The overall skill of ENSO prediction in retrospective forecasts made with ten different coupled GCMs is investigated. The coupled GCM datasets of the APCC/CliPAS and DEMETER projects are used for four seasons in the common 22 years from 1980 to 2001. As a baseline, a dynamic-statistical SST forecast and persistence are compared. Our study focuses on the tropical Pacific SST, especially by analyzing the NINO34 index. In coupled models, the accuracy of the simulated variability is related to the accuracy of the simulated mean state. Almost all models have problems in simulating the mean and mean annual cycle of SST, in spite of the positive influence of realistic initial conditions. As a result, the simulation of the interannual SST variability is also far from perfect in most coupled models. With increasing lead time, this discrepancy gets worse. As one measure of forecast skill, the tier-1 multi-model ensemble (MME) forecasts of NINO3.4 SST have an anomaly correlation coefficient of 0.86 at the month 6. This is higher than that of any individual model as well as both forecasts based on persistence and those made with the dynamic-statistical model. The forecast skill of individual models and the MME depends strongly on season, ENSO phase, and ENSO intensity. A stronger El Niño is better predicted. The growth phases of both the warm and cold events are better predicted than the corresponding decaying phases. ENSO-neutral periods are far worse predicted than warm or cold events. The skill of forecasts that start in February or May drops faster than that of forecasts that start in August or November. This behavior, often termed the spring predictability barrier, is in part because predictions starting from February or May contain more events in the decaying phase of ENSO.     

Impact of single-point GPS integrated water vapor estimates on short-range WRF model forecasts over southern India

Specifying physically consistent and accurate initial conditions is one of the major challenges of numerical weather prediction (NWP) models. In this study, ground-based global positioning system (GPS) integrated water vapor (IWV) measurements available from the International Global Navigation Satellite Systems (GNSS) Service (IGS) station in Bangalore, India, are used to assess the impact of GPS data on NWP model forecasts over southern India. Two experiments are performed with and without assimilation of GPS-retrieved IWV observations during the Indian winter monsoon period (November–December, 2012) using a four-dimensional variational (4D-Var) data assimilation method. Assimilation of GPS data improved the model IWV analysis as well as the subsequent forecasts. There is a positive impact of ～10 % over Bangalore and nearby regions. The Weather Research and Forecasting (WRF) model-predicted 24-h surface temperature forecasts have also improved when compared with observations. Small but significant improvements were found in the rainfall forecasts compared to control experiments.     

An indicator-based approach to assess village-level social and biophysical vulnerability of agriculture communities in Uttarakhand,India

With the growing recognition to myriad forms of current and future threats in the mountain agriculture systems,there is a pressing need to holistically understand the vulnerability of mountain agriculture communities.The study aims to assess the biophysical and social vulnerability of agriculture communities using an indicator-based approach for the state of Uttarakhand,India.A total of 14 indicators were used to capture biophysical vulnerability and 22 for social vulnerability profiles of15285 villages.Vulnerability analysis was done at village level with weights assigned to each indicator using Analytical Hierarchical Process(AHP).The results of the study highlight the presence of very high biophysical vulnerability(0.82 ± 0.10) and high social vulnerability(0.65 ± 0.15) within the state.Based on the results,it was found that incidences of high biophysical vulnerability coincide with presence of intensified agriculture land and absence of dense forest.Higher social vulnerability scores were found in villages with an absence of local institutions(like Self Helping Groups(SHGs)),negligible infrastructure facilities and higher occupational dependence on agriculture.A contrast was observed in the vulnerability scores of villages present in the three different altitudinal zones in the study area,indicating respective vulnerability generating conditions existing in these three zones.Biophysical vulnerability was recorded to be highest in the villages falling in the lower zone and lowest in the upper zone villages;whereas,social vulnerability was found to be highest in the middle zone villages and lowest in lower zone villages.Our study aids policy makers in identifying areas for intervention to expedite agriculture adaptation planning in the state.Additionally,the adaptation programmes in the region need to be more context-specific to accommodate the differential altitudinal vulnerability profiles.     

Solar coronal heating by high-frequency dispersive Alfvén waves

It is shown that high-frequency dispersive kinetic Alfvén waves can cause significant electron heating in the solar corona. The heating is produced by collisionless electron Landau dissipation of the parallel electron current associated with high-frequency dispersive kinetic Alfvén waves, which have a parallel electric field.