First passage time statistics of Brownian motion with purely time dependent drift and diffusion

Systems where resource availability approaches a critical threshold are common to many engineering and scientific applications and often necessitate the estimation of first passage time statistics of a Brownian motion (Bm) driven by time-dependent drift and diffusion coefficients. Modeling such systems requires solving the associated Fokker-Planck equation subject to an absorbing barrier. Transitional probabilities are derived via the method of images, whose applicability to time dependent problems is shown to be limited to state-independent drift and diffusion coefficients that only depend on time and are proportional to each other. First passage time statistics, such as the survival probabilities and first passage time densities are obtained analytically. The analysis includes the study of different functional forms of the time dependent drift and diffusion, including power-law time dependence and different periodic drivers. As a case study of these theoretical results, a stochastic model for water availability from surface runoff in snowmelt dominated regions is presented, where both temperature effects and snow-precipitation input are incorporated

A note on aerosol sized particle deposition onto dense and tall canopies situated on gentle cosine hills

Micrometeorological measurements of aerosol sized dry particle deposition velocity ( V d ) onto forested canopies have significantly advanced over the past two decades and now include both—airborne and stationary platforms. However, the interpretation of these  V d measurements still relies on stationary and planar homogeneous flow assumptions only appropriate to flat-terrain conditions. Simplified model calculations were used to examine how variations in hill height ( H ) introduce biases in  V d when assumptions appropriate to flat terrain are applied to periodic and gentle 2-D cosine topography covered with tall and dense forested canopies. It was shown that increasing  H reduced the variability in  V d for all aerosol sized particle diameters ( d p ) inside the canopy when the hill slope ( H / L ) remained constant (=0.1), where  L is the cosine hill half-length. At the landscape scale, as may be monitored from airborne platforms, assumptions appropriate to flat-terrain appear accurate with increasing  H for a constant and gentle H/ L (= 0.1). Inside the canopy, variability in  V d tends to be larger than above the canopy for all  H values and  d p classes. DOI: 10.1111/j.1600-0889.2011.00528.

Climate, Not Conflict, Explains Extreme Middle East Dust Storm

The recent dust storm in the Middle East (September 2015) was publicized in the media as a sign of an impending ‘Dust Bowl.’ Its severity, demonstrated by extreme aerosol optical depth in the atmosphere in the 99th percentile compared to historical data, was attributed to the ongoing regional conflict. However, surface meteorological and remote sensing data, as well as regional climate model simulations, support an alternative hypothesis: the historically unprecedented aridity played a more prominent role, as evidenced by unusual climatic and meteorological conditions prior to and during the storm. Remotely sensed normalized difference vegetation index demonstrates that vegetation cover was high in 2015 relative to the prior drought and conflict periods, suggesting that agricultural activity was not diminished during that year, thus negating the media narrative. Instead, meteorological simulations using the Weather Research and Forecasting (WRF) model show that the storm was associated with a cyclone and ‘Shamal’ winds, typical for dust storm generation in this region, that were immediately followed by an unusual wind reversal at low levels that spread dust west to the Mediterranean Coast. These unusual meteorological conditions were aided by a significant reduction in the critical shear stress due to extreme dry and hot conditions, thereby enhancing dust availability for erosion during this storm. Concluding, unusual aridity, combined with unique synoptic weather patterns, enhanced dust emission and westward long-range transport across the region, thus generating the extreme storm

Characteristics of Gravity Waves over an Antarctic Ice Sheet during an Austral Summer

While occurrences of wavelike motion in the stable boundary layer due to the presence of a significant restoring buoyancy force are rarely disputed, their modalities and interaction with turbulence remain a subject of active research. In this work, the characteristics of gravity waves and their impact on flow statistics, including turbulent fluxes, are presented using data collected above an Antarctic Ice sheet during an Austral Summer. Antarctica is an ideal location for exploring the characteristics of gravity waves because of persistent conditions of strong atmospheric stability in the lower troposphere. Periods dominated by wavelike motion have been identified by analysing time series measured by fast response instrumentation. The nature and characteristic of the dominant wavy motions are investigated using Fourier cross-spectral indicators. Moreover, a multi-resolution decomposition has been applied to separate gravity waves from turbulent fluctuations in case of a sufficiently defined spectral gap. Statistics computed after removing wavy disturbances highlight the large impact of gravity waves on second order turbulent quantities including turbulent flux calculations

Collection and analysis of evaporative flux data for various climates

Daily evaporative flux and meteorological data from three sites were collected and analyzed. Analysis included evaluation of several reference evapotranspiration estimating methods which were theoretically based on distinct physical laws. The estimating methods included pan evaporation, energy-based Priestly-Taylor, and combination methods with and without biological adjustments. The data set represented three sites with different climates. Analysis included comparisons of evapotranspiration estimating methods, statistical analysis, linear regression analysis, and a detailed study for possible seasonal trends. An attempt to quantify the effect of climate on the original Penman method and the original Priestly-Taylor method using three variables was performed. The variables included average air relative humidity, incoming shortwave radiation, and wind speed at 2 m height. Validation of the derived climatic coefficients for the three sites was performed using a subset of the three data sets and a fourth simulated data set. Moving average analysis for the various evapotranspiration estimating methods was performed at each of the three sites. The objective was to estimate the optimum averaging interval for a particular estimating method at each site. Five days averaging interval was found to be adequate to reduce substantially reduce the standard error of estimate and increase the coefficient of determination for all methods at each site

Multiscale Legacy Responses of Soil Gas Concentrations to Soil Moisture and Temperature Fluctuations

The sensitivity of soil carbon dynamics to climate change is a major uncertainty in carbon cycle models. Of particular interest is the response of soil biogeochemical cycles to variability in hydroclimatic states and the related quantification of soil memory. Toward this goal, the power spectra of soil hydrologic and biogeochemical states were analyzed using measurements of soil temperature, moisture, oxygen, and carbon dioxide at two sites. Power spectra indicated multiscale power law scaling across subhourly to annual timescales. Precipitation fluctuations were most strongly expressed in the soil biogeochemical signals at monthly to annual timescales. Soil moisture and temperature fluctuations were comparable in strength at one site, while temperature was dominant at the other. The effect of soil hydrologic, thermal, and biogeochemical processes on gas concentration variability was evidenced by low spectral entropy relative to the white noise character of precipitation. A full mass balance model was unable to capture high-frequency soil temperature influence, indicating a gap in commonly used model assumptions. A linearized model was shown to capture the main features of the observed and modeled gas concentration spectra and demonstrated how the means and variances of soil moisture and temperature interact to produce the gas concentration spectra. Breakpoints in the spectra corresponded to the mean rate of gas efflux, providing a first-order estimate of the soil biogeochemical integral timescale (~1 min). These methods can be used to identify biogeochemical system dynamics to develop robust, process-based soil biogeochemistry models that capture variability in addition to long-term mean values. Plain Language Summary The ability to describe how climate change impacts soil carbon and nutrient cycles with models is a necessary tool for ecosystem management and sustainability. One difficulty in developing these predictive models is the so-called “legacy effect”—for example, one wet summer may alter the ecosystem for many years afterward. Soil data and models are used here to quantify the relative strength of short- and long-term variability of soil biogeochemical systems and how it responds to rainfall, soil moisture, and soil temperature. We found that variability in soil biogeochemistry is concentrated at longer timescales of several weeks to months and this is because the soil stores water and heat, retaining a “memory” of past rainfall and temperature. Further, this analysis offered a new perspective on the equations used in current models—models driven by soil moisture and temperature are able to capture the legacy in soil biogeochemical data

Increasing Atmospheric Humidity and CO\u3csub\u3e2\u3c/sub\u3e Concentration Alleviate Forest Mortality Risk

Climate-induced forest mortality is being increasingly observed throughout the globe. Alarmingly, it is expected to exacerbate under climate change due to shifting precipitation patterns and rising air temperature. However, the impact of concomitant changes in atmospheric humidity and CO2 concentration through their influence on stomatal kinetics remains a subject of debate and inquiry. By using a dynamic soil–plant–atmosphere model, mortality risks associated with hydraulic failure and stomatal closure for 13 temperate and tropical forest biomes across the globe are analyzed. The mortality risk is evaluated in response to both individual and combined changes in precipitation amounts and their seasonal distribution, mean air temperature, specific humidity, and atmospheric CO2 concentration. Model results show that the risk is predicted to significantly increase due to changes in precipitation and air temperature regime for the period 2050–2069. However, this increase may largely get alleviated by concurrent increases in atmospheric specific humidity and CO2 concentration. The increase in mortality risk is expected to be higher for needleleaf forests than for broadleaf forests, as a result of disparity in hydraulic traits. These findings will facilitate decisions about intervention and management of different forest types under changing climate

Closure Schemes for Stably Stratified Atmospheric Flows without Turbulence Cutoff

Two recently proposed turbulence closure schemes are compared against the conventional Mellor-Yamada (MY) model for stably stratified atmospheric flows. The Energy and Flux-Budget (EFB) approach solves the budgets of turbulent momentum and heat fluxes and turbulent kinetic and potential energies. The Cospectral Budget (CSB) approach is formulated in wavenumber space and integrated across all turbulent scales to obtain flow variables in physical space. Unlike the MY model, which is subject to a "critical gradient Richardson number," both EFB and CSB models allow turbulence to exist at any gradient Richardson number R-t and predict a saturation of flux Richardson number (R-f -> R-fm) at sufficiently large R-i. The CSB approach further predicts the value of Rim and reveals a unique expression linking the Rotta and von Karman constants. Hence, all constants in the CSB model are nontunable and stability independent. All models agree that the dimensionless sensible heat flux decays with increasing R-i. However, the decay rate and subsequent cutoff in the MY model appear abrupt. The MY model further exhibits an abrupt cutoff in the turbulent stress normalized by vertical velocity variance, while the CSB and EFB models display increasing trends. The EFB model produces a rapid increase in the ratio of turbulent potential energy and vertical velocity variance as Rim is approached, suggesting a strong self-preservation mechanism. Vertical anisotropy in the turbulent kinetic energy is parameterized in different ways in MY and EFB, but this consideration is not required in CSB. Differences between EFB and CSB model predictions originate from how the vertical anisotropy is specified in the EFB model.Peer reviewe

Eddies in motion : visualizing boundary-layer turbulence above an open boreal peatland using UAS thermal videos

High-resolution thermal infrared (TIR) imaging is opening up new vistas in biosphere-atmosphere heat exchange studies. The rapidly developing unmanned aerial systems (UASs) and specially designed cameras offer opportunities for TIR survey with increasingly high resolution, reduced geometric and radiometric noise, and prolonged flight times. A state-of-the-art science platform is assembled using a Matrice 210 V2 drone equipped with a Zenmuse XT2 thermal camera and deployed over a pristine boreal peatland with the aim of testing its performance in a heterogeneous sedgefen ecosystem. The study utilizes the capability of the UAS platform to hover for prolonged times (about 20 min) at a height of 500ma.g.l. while recording high frame rate (30 Hz) TIR videos of an area of ca. 430 x 340 m. A methodology is developed to derive thermal signatures of near-ground coherent turbulent structures impinging on the land surface, surface temperature spectra, and heat fluxes from the retrieved videos. The size, orientation, and movement of the coherent structures are computed from the surface temperature maps, and their dependency on atmospheric conditions is examined. A range of spectral and wavelet-based approaches are used to infer the properties of the dominant turbulent scene structures. A ground-based eddy-covariance system and an in situ meteorological setup are used for reference.Peer reviewe