Detection,characterization, and analysis of land subsidence in Nairobi using InSAR

Natural Hazards - Himalayan mountains are one of the most seismo-tectonically active zones on the surface of the earth. Recurring moderate and high magnitude earthquakes are not uncommon in this...     

Impacts of climate change in three hydrologic regimes in British Columbia,Canada

Hydrologic modelling has been applied to assess the impacts of projected climate change within three study areas in the Peace, Campbell and Columbia River watersheds of British Columbia, Canada. These study areas include interior nival (two sites) and coastal hybrid nival–pluvial (one site) hydro‐climatic regimes. Projections were based on a suite of eight global climate models driven by three emission scenarios to project potential climate responses for the 2050s period (2041–2070). Climate projections were statistically downscaled and used to drive a macro‐scale hydrology model at high spatial resolution. This methodology covers a large range of potential future climates for British Columbia and explicitly addresses both emissions and global climate model uncertainty in the final hydrologic projections. Snow water equivalent is projected to decline throughout the Peace and Campbell and at low elevations within the Columbia. At high elevations within the Columbia, snow water equivalent is projected to increase with increased winter precipitation. Streamflow projections indicate timing shifts in all three watersheds, predominantly because of changes in the dynamics of snow accumulation and melt. The coastal hybrid site shows the largest sensitivity, shifting to more rainfall‐dominated system by mid‐century. The two interior sites are projected to retain the characteristics of a nival regime by mid‐century, although streamflow‐timing shifts result from increased mid‐winter rainfall and snowmelt, and earlier freshet onset. Copyright © 2012 John Wiley & Sons, Ltd.     

In-depth examination of spatiotemporal figures in open reproducible research

ABSTRACT

Figures such as maps and time series are essential means to visualize spatiotemporal results in scientific papers. Being able to recompute them using the underlying source code and data is thus a core aspect in reproducible research. However, many scientists see the preparation of code and data for publication as an additional burden without immediate benefits. In this work, we investigate advantages and new capabilities of reproducible research papers. Our key contributions are (i) the extension of a geoscientist’s workflow while examining papers including reproducible figures such as maps and (ii) the prototypical implementation of the workflow as a web application. The workflow is based on current practices of geoscientists and encapsulates benefits of reproducible figures. It is informed by ideas and needs identified by geoscientists in a survey, interviews, and a focus group. Based on their statements, we first extend the traditional workflow steps Discovery and Inspection by additional capabilities and propose two new steps: Manipulation of the content of a spatiotemporal figure and Substitution of the underlying code and data. The extended workflow and its implementation might facilitate in-depth examination and reusability of geoscientific results.     

The Response of Arctic Sea Ice to Global Change

The sea ice-covered polar oceans have received wider attention recently for two reasons. Firstly, the global conveyor belt circulation of the ocean is believed to be forced in the North and South Atlantic through deep water formation, which to a large degree is controlled by the variations of the sea ice margin and especially by the sea ice export to lower latitudes. Secondly, CO₂ response experiments with coupled climate models show an enhanced warming in polar regions for increased concentrations of atmospheric greenhouse gases. Whether this large response in high latitudes is due to real physical feedback processes or to unrealistic simplifications of the sea ice model component remains to be determined. Coupled climate models generally use thermodynamic sea ice models or sea ice models with oversimplified dynamics schemes. Realistic dynamic-thermodynamic sea ice models are presently implemented only at a few modeling centers. Sensitivity experiments with thermodynamic and dynamic-thermodynamic sea ice models show that the more sophisticated models are less sensitive to perturbations of the atmospheric and oceanic boundary conditions. Because of the importance of the role of sea ice in mediating between atmosphere and ocean an improved representation of sea ice in global climate models is required. This paper discusses present sea ice modeling as well as the sensitivity of the sea ice cover to changes in the atmospheric boundary conditions. These numerical experiments indicate that the sea ice follows a smooth response function: sea ice thickness and export change by 2% of the mean value per 1 Wm^-2 change of the radiative forcing.     

500-yr. precipitation variability in Southern Taihang Mountains,China, and its linkages to ENSO and PDO

An annually resolved and absolutely dated ring-width chronology spanning 657 yrs. is constructed with Whitebark pine (Pinus bungeana Zucc.) samples from the southern Taihang Mountains, Eastern China. On the basis of a significant correlation between the tree-ring width index and observed instrumental data, precipitation in current May is reconstructed for the region since AD 1510, with predictor variables accounting for 37.9 % of the variance in precipitation data. In agreement with other drought reconstructions, notable dry spells occur in the 1630s–1650s, 1680s–1700s, and 1770s–1800s, whereas wet periods prevail in the 1530s–1570s, 1840s–1870s, and 1950s-present. Wavelet analysis reveals clear 2–8, 20–40, and 80–130 yrs cycles at the 95 % confidence level for the reconstructed series over the past 500 yrs, suggesting possible linkages with the El Niño-Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO). Correlation analysis between the tree-ring series, ENSO, and PDO index further demonstrates that precipitation is negatively correlated with PDO and ENSO in the long term.     

Arctic warming,moisture increase and circulation changes observed in the Ny-Ålesund homogenized radiosonde record

The interannual variability of precipitation and temperature is derived from all runs of the Intergovernmental Panel on Climate Change (IPCC) fourth Assessment Report (AR4)-based two Atmospheric Oceanic General Circulation Model (AOGCM) simulations, over Pakistan, on an annual basis. The models are the CM2.0 and CM2.1 versions of Geophysical Fluid Dynamics Laboratory (GFDL)-based AOGCM. Simulations for a recent 22-year period (1979–2000) are validated using Climate Research Unit (CRU) and NCEP/NCAR datasets over Pakistan, for the first time. The study area of Pakistan is divided into three regions: all Pakistan, northern Pakistan, and southern Pakistan. Bias, root mean square error, one sigma standard deviation, and coefficient of variance are used as validation metrics. For all Pakistan and northern Pakistan, all three runs of GFDL-CM2.0 perform better under the above metrics, both for precipitation and temperature (except for one sigma standard deviation and coefficient of variance), whereas for southern Pakistan, third run of GFDL-CM2.1 perform better expect for the root mean square error for temperature. A mean and variance-based bias correction is applied to bias in modeled precipitation and temperature variables. This resulted in a reduced bias, except for the months of June, July, and August, when the reduction in bias is relatively lower.     

A Mediterranean earthquake project

Cumulative frequency and cumulative energy may vary from one sample of earthquakes to another either in the same or in the opposite sense. Conditions for the variations are deduced theoretically and illustrated by numerical examples.     

Recurrent transitions to Little Ice Age-like climatic regimes over the Holocene

Holocene climate variability is punctuated by episodic climatic events such as the Little Ice Age (LIA) predating the industrial-era warming. Their dating and forcing mechanisms have however remained controversial. Even more crucially, it is uncertain whether earlier events represent climatic regimes similar to the LIA. Here we produce and analyse a new 7500-year long palaeoclimate record tailored to detect LIA-like climatic regimes from northern European tree-ring data. In addition to the actual LIA, we identify LIA-like ca. 100–800 year periods with cold temperatures combined with clear sky conditions from 540 CE, 1670 BCE, 3240 BCE and 5450 BCE onwards, these LIA-like regimes covering 20% of the study period. Consistent with climate modelling, the LIA-like regimes originate from a coupled atmosphere–ocean–sea ice North Atlantic-Arctic system and were amplified by volcanic activity (multiple eruptions closely spaced in time), tree-ring evidence pointing to similarly enhanced LIA-like regimes starting after the eruptions recorded in 1627 BCE, 536/540 CE and 1809/1815 CE. Conversely, the ongoing decline in Arctic sea-ice extent is mirrored in our data which shows reversal of the LIA-like conditions since the late nineteenth century, our record also correlating highly with the instrumentally recorded Northern Hemisphere and global temperatures over the same period. Our results bridge the gaps between low- and high-resolution, precisely dated proxies and demonstrate the efficacy of slow and fast components of the climate system to generate LIA-like climate regimes.

     

Temperature and precipitation responses to El Niño-Southern Oscillation in a hierarchy of datasets with different levels of observational constraints

Climate Dynamics - El Niño-Southern Oscillation (ENSO) is the dominant mode of climate variability, affecting climate conditions over large areas of the globe. There are, however, substantial...     

Lagrangian Particle Dispersion Models in the Grey Zone of Turbulence: Adaptations to FLEXPART-COSMO for Simulations at 1 km Grid Resolution

Boundary-Layer Meteorology - Lagrangian particle dispersion models (LPDMs) are frequently used for regional-scale inversions of greenhouse gas emissions. However, the turbulence parameterizations...