Northwestern Himalaya is one of the most tectonically active domains of the Himalayan arc. The prevailing complex collisional tectonic setup is able to produce destructive earthquakes, most recent being the 8 October 2005 Kashmir earthquake (M7.6). In this study, the probabilistic seismic hazard assessment of the Kashmir basin of northwestern Himalaya is presented. The seismic hazard is assessed using point, areal and linear source models employing appropriate ground motion prediction equations to predict the expected ground motions. The seismic hazard maps are expressed in terms of g, seismic hazard curves at 2% and 10% probability of exceedance in 50 years and the design response spectra at 5% damping for four major towns of the basin at the engineering bedrock. The results are expressed as the hypocentral depth-wise hazard maps, predicted peak ground acceleration (PGA), pseudo-spectral acceleration (PSA) with 2% and 10% probability of exceedance within 50 years and the design response spectra with 5% damping of four major towns of Kashmir for engineering bedrock sites. The hypocentral depth-wise maps are shown in the ranges of 0–25 km, 25–70 km and > 70 km with 10% probability of exceedance in 50 years. The computation is based on smoothly gridded seismicity for each depth zone with a return period of 475 years. With the seismic source zones considered as sources, the seismic hazard maps show predicted peak ground acceleration (PGA) and pseudo-spectral acceleration (PSA) with 2% and 10% probability of exceedance within 50 years for engineering bedrock sites. The PSA maps are expressed in g at 0.2 and 1 s (s). From this preliminary study it is evident that overall Kashmir basin shows a very high seismic hazard, with southeastern part showing relatively higher hazard as compared to northwestern part. Among the major benchmark towns all show high predicted PGA, Anantnag shows the highest (0.65g). The present study thus advocates a significantly higher seismic hazard as compared to the BIS In: IS 1893–2002 (Part 1): Indian standard criteria for earthquake resistant design of structures, Part 1—general provisions and buildings, (2002).

The European Space Agency recently launched the Sentinel mission to perform terrestrial observations in support of tasks such as monitoring forests, detecting land-cover changes, and managing natural disasters. The resolution of these satellite images can be as high as 10 m depending on the bands. In this study, we used the red and near-infrared bands in 10-m resolution from Sentinel-2 images to calculate the Normalized Difference Vegetation Index (NDVI) and estimate of the green vegetation fraction in urban areas within the Pearl River Delta region (PRD). We used vegetation coverage obtained from high-resolution Google satellite images as a reference to validate the vegetation estimates derived from the Sentinel-2 images, and found the correlation between the two to be as high as 0.97. As such, information from the Sentinel-2 imagery can supplement the urban canopy parameters (UCPs) derived from the World Urban Database and Access Portal Tools (WUDAPT) level-0 dataset, which is used in urban meteorological models. The rapid retrieval and open-source nature of the methodology supports high-resolution urban climate modeling studies.

Power spectrum is the considerable aspect in the atmospheric radar data processing to estimate wind parameters. Due to the poor resolution and high sidelobe level problems of the existing algorithms, there is a requisite for the novel data-dependent approaches. A non-parametric and hyperparameter-free iterative adaptive approach (IAA) is presented for the power spectral density estimation. This approach is able to work with single snapshot and is obtained by minimizing the weighted least square fitting criterion. The IAA method provides the accurate amplitude and frequency estimation for the simulated data. The data for the above study is collected from Indian MST (mesosphere, stratosphere, and troposphere) radar. The power spectrum and Doppler frequency are estimated using IAA. In this paper, zonal (U), meridional (V), windspeed (W) are also calculated and validated using Global Positioning System Sonde data. The effectiveness of the spectral estimation performance showed by IAA is demonstrated and assessed.

After publication of the article (Tian et al. 2018), it has been brought to our attention that the date included in the caption of Figure 3 is incorrect. The caption states that the photographs were taken on “July 20, 2013” but they were in fact taken on “Sept 30, 2015”.

The copula–entropy theory combines the entropy theory and the copula theory. The entropy theory has been extensively applied to derive the most probable univariate distribution subject to specified constraints by applying the principle of maximum entropy. With the flexibility to model nonlinear dependence structure, parametric copulas (e.g., Archimedean, extreme value, meta-elliptical, etc.) have been applied to multivariate modeling in water engineering. This study evaluates the copula–entropy theory using a sample dataset with known population information and a flood dataset from the experimental watershed at the Walnut Gulch, Arizona. The study finds the following: (1) both univariate and joint distributions can be derived using the entropy theory. (2) The parametric copula fits the true copula better using empirical marginals than using fitted parametric/entropy-based marginals. This suggests that marginals and copula may be identified separately in which the copula is investigated with empirical marginals. (3) For a given set of constraints, the most entropic canonical copula (MECC) is unique and independent of the marginals. This allows the universal solution for the proposed analysis. (4) The MECC successfully models the joint distribution of bivariate random variables. (5) Using the “AND” case return period analysis as an example, the derived MECC captures the change of return period resulting from different marginals.

Various Tsunami Service Providers (TSPs) within the Mediterranean Basin supply tsunami warnings including CAT-INGV (Italy), KOERI-RETMC (Turkey), and NOA/HL-NTWC (Greece). The 20 July 2017 Bodrum–Kos (Turkey–Greece) earthquake (Mw 6.6) and tsunami provided an opportunity to assess the response from these TSPs. Although the Bodrum–Kos tsunami was moderate (e.g., runup of 1.9 m) with little damage to properties, it was the first noticeable tsunami in the Mediterranean Basin since the 21 May 2003 western Mediterranean tsunami. Tsunami waveform analysis revealed that the trough-to-crest height was 34.1 cm at the near-field tide gauge station of Bodrum (Turkey). Tsunami period band was 2–30 min with peak periods at 7–13 min. We proposed a source fault model for this tsunami with the length and width of 25 and 15 km and uniform slip of 0.4 m. Tsunami simulations using both nodal planes produced almost same results in terms of agreement between tsunami observations and simulations. Different TSPs provided tsunami warnings at 10 min (CAT-INGV), 19 min (KOERI-RETMC), and 18 min (NOA/HL-NTWC) after the earthquake origin time. Apart from CAT-INGV, whose initial Mw estimation differed 0.2 units with respect to the final value, the response from the other two TSPs came relatively late compared to the desired warning time of ~ 10 min, given the difficulties for timely and accurate calculation of earthquake magnitude and tsunami impact assessment. It is argued that even if a warning time of ~ 10 min was achieved, it might not have been sufficient for addressing near-field tsunami hazards. Despite considerable progress and achievements made within the upstream components of NEAMTWS (North East Atlantic, Mediterranean and Connected seas Tsunami Warning System), the experience from this moderate tsunami may highlight the need for improving operational capabilities of TSPs, but more importantly for effectively integrating civil protection authorities into NEAMTWS and strengthening tsunami education programs.

The North Pacific Gyre Oscillation (NPGO) significantly imprints on hydrological fluctuations of the East Asian summer monsoon (EASM) region, but this has not yet been observed in proxy-based hydroclimate reconstructions. This study reports a tree-ring cellulose oxygen isotope (δ18O) record from northeastern Japan spanning A.D. 1927–2010, overlapping with instrumental data, which we analyzed to determine if tree-ring δ18O in northeastern Japan records a signal consistent with the NPGO. Our results indicate that the tree-ring δ18O has a significant negative correlation with May–June (MJ) precipitation, as well as with short-term MJ relative humidity variation. Time-lagged temporal-domain comparisons indicate that the tree-ring δ18O is significantly correlated with the following year March–April (MA) and MJ NPGO index before the North Pacific climate transition in the late 1980s, particularly on decadal timescales. These relationships between our tree-ring δ18O and the climate patterns in the North Pacific are consistent with the actual early-summer precipitation. Spatial spring and early-summer sea-surface temperature anomalies exhibit a NPGO-like pattern in the following year. Spatial early-summer sea-level pressure anomalies also indicate North Pacific Oscillation (NPO) like patterns in the western North Pacific. These results suggest a lagged response of the NPGO to the EASM climate changes, and tree-ring δ18O in northeast Japan has a potential linkage with NPGO index from winter to early summer of the following year.

Ellerman bombs (EBs) are believed to be small-scale reconnection events occurring around the temperature minimum region in the solar atmosphere. They are often identified as significant enhancements in the extended Hα wings without obvious signatures in the Hα core. Here we explore the possibility of using the 1700 Å images taken by the Atmospheric Imaging Assembly (AIA) onboard the Solar Dynamics Observatory (SDO) to study EBs. From the Hα wing images obtained with the New Vacuum Solar Telescope (NVST) on 2015 May 2, we have identified 145 EBs and 51% of them clearly correspond to the bright points (BPs) in the AIA 1700 Å images. If we resize the NVST images using a linear interpolation to make the pixel sizes of the AIA and NVST images the same, some previously identified EBs disappear and about 71% of the remaining EBs are associated with BPs. Meanwhile, 66% of the compact brightenings in the AIA 1700 Å images can be identified as EBs in the Hα wings. The intensity enhancements of the EBs in the Hα wing images reveal a linear correlation with those of the BPs in the AIA 1700 Å images. Our study suggests that a significant fraction of EBs can be observed with the AIA 1700 Å filter, which is promising for large-sample statistical study of EBs as the seeing-free and full-disk SDO/AIA data are routinely available.

The Ikkour watershed located in the Middle Atlas Mountain (Morocco) has been a subject of serious soil erosion problems. This study aimed to assess the soil erosion susceptibility in this mountainous watershed using Universal Soil Loss Equation (USLE) and spectral indices integrated with Geographic Information System (GIS) environment. The USLE model required the integration of thematic factors’ maps which are rainfall aggressiveness, length and steepness of the slope, vegetation cover, soil erodibility, and erosion control practices. These factors were calculated using remote sensing data and GIS. The USLE-based assessment showed that the estimated total annual potential soil loss was about 70.66 ton ha−1 year−1. This soil loss is favored by the steep slopes and degraded vegetation cover. The spectral index method, offering a qualitative evaluation of water erosion, showed different degrees of soil degradation in the study watershed according to FI, BI, CI, and NDVI. The results of this study displayed an agreement between the USLE model and spectral index approach, and indicated that the predicted soil erosion rate can be due to the most rugged land topography and an increase in agricultural areas. Indeed, these results can further assist the decision makers in implementation of suitable conservation program to reduce soil erosion.

Mixing at the ocean surface is key for atmosphere–ocean interactions and the distribution of heat, energy, and gases in the upper ocean. Winds are the primary force for surface mixing. To properly simulate upper ocean dynamics and the flux of these quantities within the upper ocean, models must reproduce mixing in the upper ocean. To evaluate the performance of the Regional Ocean Modeling System (ROMS) in replicating the surface mixing, the results of four different vertical mixing parameterizations were compared against observations, using the surface mixed layer depth, the temperature fields, and observed diffusivities for comparisons. The vertical mixing parameterizations investigated were Mellor–Yamada 2.5 level turbulent closure (MY), Large–McWilliams–Doney Kpp (LMD), Nakanishi–Niino (NN), and the generic length scale (GLS) schemes. This was done for one temperate site in deep water in the Eastern Pacific and three shallow water sites in the Baltic Sea. The model reproduced the surface mixed layer depth reasonably well for all sites; however, the temperature fields were reproduced well for the deep site, but not for the shallow Baltic Sea sites. In the Baltic Sea, the models overmixed the water column after a few days. Vertical temperature diffusivities were higher than those observed and did not show the temporal fluctuations present in the observations. The best performance was by NN and MY; however, MY became unstable in two of the shallow simulations with high winds. The performance of GLS nearly as good as NN and MY. LMD had the poorest performance as it generated temperature diffusivities that were too high and induced too much mixing. Further observational comparisons are needed to evaluate the effects of different stratification and wind conditions and the limitations on the vertical mixing parameterizations.