Sediment Respiration Pulses in Intermittent Rivers and Ephemeral Streams

Intermittent rivers and ephemeral streams (IRES) may represent over half the global stream network, but their contribution to respiration and carbon dioxide (CO2) emissions is largely undetermined. In particular, little is known about the variability and drivers of respiration in IRES sediments upon rewetting, which could result in large pulses of CO2. We present a global study examining sediments from 200 dry IRES reaches spanning multiple biomes. Results from standardized assays show that mean respiration increased 32-fold to 66-fold upon sediment rewetting. Structural equation modeling indicates that this response was driven by sediment texture and organic matter quantity and quality, which, in turn, were influenced by climate, land use, and riparian plant cover. Our estimates suggest that respiration pulses resulting from rewetting of IRES sediments could contribute significantly to annual CO2 emissions from the global stream network, with a single respiration pulse potentially increasing emission by 0.2-0.7%. As the spatial and temporal extent of IRES increases globally, our results highlight the importance of recognizing the influence of wetting-drying cycles on respiration and CO2 emissions in stream network

Sr0.9_{0.9}K0.1_{0.1}Zn1.8_{1.8}Mn0.2_{0.2}As2_{2}: a ferromagnetic semiconductor with colossal magnetoresistance

A bulk diluted magnetic semiconductor (Sr,K)(Zn,Mn)$_{2}$As$_{2}$ was synthesized with decoupled charge and spin doping. It has a hexagonal CaAl$_{2}$Si$_{2}$-type structure with the (Zn,Mn)$_{2}$As$_{2}$ layer forming a honeycomb-like network. Magnetization measurements show that the sample undergoes a ferromagnetic transition with a Curie temperature of 12 K and \revision{magnetic moment reaches about 1.5 $\mu_{B}$/Mn under $\mu_0H$ = 5 T and $T$ = 2 K}. Surprisingly, a colossal negative magnetoresistance, defined as $[\rho(H)-\rho(0)]/\rho(0)$, up to $-$38\% under a low field of $\mu_0H$ = 0.1 T and to $-$99.8\% under $\mu_0H$ = 5 T, was observed at $T$ = 2 K. The colossal magnetoresistance can be explained based on the Anderson localization theory.Comment: Accepted for publication in EP

Latent heat flux and canopy conductance based on Penman-Monteith and Bouchet’s complementary hypothesis:validation over diverse biomes

Abstract A novel method is presented to analytically resolve the terrestrial latent heat flux (λE) and conductances (boundary layer gB and surface gS) using net radiation (RN), ground heat flux (G), air temperature (Ta), and relative humidity (RH). This method consists of set of equations where the two unknown internal state variables (gB and gS) were expressed in terms of the known core variables, combining diffusion equations, the Penman–Monteith equation, the Priestley–Taylor equation, and Bouchet’s complementary hypothesis. Estimated λE is validated with the independent eddy covariance λE observations over Soil Moisture Experiment 2002 (SMEX-02); the Global Energy and Water Cycle Experiment (GEWEX) Continental-Scale International Project (GCIP) selected sites from FLUXNET and tropics eddy flux, representing four climate zones (tropics, subtropics, temperate, and cold); and multiple biomes. The authors find a RMSE of 23.8–54.6 W m−2 for hourly λE over SMEX-02 and GCIP and 23.8–29.0 W m−2 for monthly λE over the FLUXNET and tropics. Observational and modeled evidence in the reduction in annual evaporation (E) pattern on the order of 33% from 1999 to 2006 was found in central Amazonia. Retrieved gS responded to vapor pressure deficit, measured λE, and gross photosynthesis in a theoretically robust behavior. However, the current scheme [Penman–Monteith–Bouchet–Lhomme (PMBL)] showed some overestimation of λE in limited soil moisture regimes. PMBL provides similar results when compared with another Priestley–Taylor–based λE estimation approach [Priestley–Taylor–Jet Propulsion Laboratory (PT-JPL)] but with the advantage of having the conductances analytically recovered.</jats:p

Cloudbursts in Indian Himalayas: a review

Cloudbursts in and around the southern rim of the Indian Himalayas are elusive in terms of their position and time of occurrences. Most of the reported cloudbursts are in the interior of the Himalayas and hence their observation itself is limited. Most of these events are reported once their affect in terms of loss to life and property is experienced in the downstream habitats. In addition, they are mostly associated with flash floods as an impact of the torrential precipitation. The principal understanding of the cloudburst is associated with sudden heavy deluge of precipitation in very less time interval over a very small area. Except this understanding and India Meteorology Department (IMD) definition of > 100 mm/h precipitation over a geographical region of approximately 20–30 km2, nothing much else is known about these events. There are a very few studies carried out on understanding of these events. Present paper synthesizes the available information and research on cloudburst events and tries to define it based on associated dynamics, thermodynamics and physical processes leading to a cloudburst event. Thus in the present work, characterizations and impacts of cloudburst leading from precipitation to dynamical to thermodynamical to large scale forcings to orographical forcings to followed geomorphology to impacts are intertwined to present comprehensive portray of it. Most of the cloudburst events are seen occurring in the elevation range of 1000 m to 2500 m within the valley folds of the southern rim of the Indian Himalayas. Apart from some of the large scale flow shown by few of the studies, it is found that cloudburst events are convectively triggered followed by orographically locked systems. These intertwined mechanisms lead cloudburst events to form. Amiss of any one of these mechanisms will not lead the cloudburst mechanism to form. These interactions in the present paper established the vagaries associated with the cloudburst events

Urban climate and resiliency: A synthesis report of state of the art and future research directions

The Urban Climate and Resiliency-Science Working Group (i.e., The WG) was convened in the summer of 2018 to explore the scientific grand challenges related to climate resiliency of cities. The WG leveraged the presentations at the 10th International Conference on Urban Climate (ICUC10) held in New York City (NYC) on 6–10 August 2018 as input forum. ICUC10 was a collaboration between the International Association of Urban Climate, American Meteorological Society, and World Meteorological Organization. It attracted more than 600 participants from more than 50 countries, resulting in close to 700 oral and poster presentations under the common theme of “Sustainable & Resilient Urban Environments”. ICUC10 covered topics related to urban climate and weather processes with far-reaching implications to weather forecasting, climate change adaptation, air quality, health, energy, urban planning, and governance. This article provides a synthesis of the analysis of the current state of the art and of the recommendations of the WG for future research along each of the four Grand Challenges in the context of urban climate and weather resiliency; Modeling, Observations, Cyber-Informatics, and Knowledge Transfer & Applications

A modified deep learning weather prediction using cubed sphere for global precipitation

Deep learning (DL), a potent technology to develop Digital Twin (DT), for weather prediction using cubed spheres (DLWP-CS) was recently proposed to facilitate data-driven simulations of global weather fields. DLWP-CS is a temporal mapping algorithm wherein time-stepping is performed through U-NET. Although DLWP-CS has shown impressive results for fields, such as temperature and geopotential height, this technique is complicated and computationally challenging for a complex, non-linear field, such as precipitation, which depends on other prognostic environmental co-variables. To address this challenge, we modify the DLWP-CS and call our technique “modified DLWP-CS” (MDLWP-CS). In this study, we transform the architecture from a temporal to a spatio-temporal mapping (multivariate setup), wherein precursor(s) of precipitation can be used as input. As a proof of concept, as a first simple case, a 2-m surface air temperature is used to predict precipitation using MDLWP-CS. The model is trained using hourly ERA-5 reanalysis and the resulting experimental findings are compared to two benchmark models, viz, the linear regression and an operational numerical weather prediction model, which is the Global Forecast System (GFS). The fidelity of MDLWP-CS is much better compared to linear regression and the results are equivalent to GFS output in terms of daily precipitation prediction with 1 day lag. These results provide an encouraging framework for an efficient DT that can facilitate speedy, high fidelity precipitation predictions.</jats:p

Random geometric complexes

We study the expected topological properties of Cech and Vietoris-Rips complexes built on i.i.d. random points in R^d. We find higher dimensional analogues of known results for connectivity and component counts for random geometric graphs. However, higher homology H_k is not monotone when k > 0. In particular for every k > 0 we exhibit two thresholds, one where homology passes from vanishing to nonvanishing, and another where it passes back to vanishing. We give asymptotic formulas for the expectation of the Betti numbers in the sparser regimes, and bounds in the denser regimes. The main technical contribution of the article is in the application of discrete Morse theory in geometric probability.Comment: 26 pages, 3 figures, final revisions, to appear in Discrete & Computational Geometr