In order to predict future observations of a noise-driven system, we have find model that exactly or at least approximately describes the behavior system so current state can be recovered from past observations. However, sometimes it is very difficult accurately, such as real ocean waves. It therefore particularly interesting analyze wave properties in time-domain using autoregressive moving average (ARMA) models. Two ARMA/AR based models and their equivalent space representations will used...

Abstract Mesoscale convective systems (MCSs) are the main source of precipitation in tropics and parts mid‐latitudes responsible for high‐impact weather worldwide. Studies showed that deficiencies simulating mid‐latitude MCSs state‐of‐the‐art climate models can be alleviated by kilometer‐scale models. However, whether these also improve tropical we find model settings perform well both regions is understudied. We take advantage high‐quality MCS observations collected over Atmospheric...

Abstract The main objective of this study is to observationally constrain processes in tropical and midlatitude mesoscale convective systems (MCSs), use these constraints for model evaluation. To accomplish this, we leverage MCS observations collected at the U.S. DOE Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site Oklahoma ARM's mobile GoAmazon2014/15 Manaus, Brazil (MAO). We simulate 13 11 observed MCSs SGP MAO site, respectively, using Weather Research Forecasting...

Abstract. The large spatial scale of global Earth system models (ESMs) is often cited as an obstacle to using the output by water resource managers in localized decisions. Recent advances computing have improved fidelity hydrological responses ESMs through increased connectivity between model components. However, are seldom evaluated for their ability reproduce metrics that important and resonate with practitioners or allow situate higher-resolution outputs within a cascade uncertainty...

Organized deep convection plays a critical role in the global water cycle and drives extreme precipitation events tropical mid-latitude regions. However, simulating remains challenging for modern weather forecasts climate models due to complex interactions of processes from microscales mesoscales. Recent with kilometer-scale (km-scale) horizontal grid spacings (∆x) offer notable improvements compared coarser-resolution models. Still, deficiencies representing key physical...

Abstract. A novel approach to modelling the surface wind field of landfalling tropical cyclones (TCs) is presented. The system simulates evolution low-level fields TCs, accounting for terrain effects. two-step process models gradient-level using a parametric model fitted TC track data and then brings winds down numerical boundary layer model. physical response variable drag height produces substantial local modifications smooth provided by profile For set US historical TCs accuracy simulated...

Abstract Using a regional model initial condition ensemble, this study quantifies the magnitude of internal variability North Atlantic tropical cyclone frequency for case year and identifies potential physical sources. For formations from easterly waves, simulated 1998 is approximately two fifths total (externally forced internal) observed frequency. The found to arise in equal measure wave occurrence development transition incipient warm cores cyclones. Variable interaction between...

Objectives: The 2019 coronavirus disease (COVID-19) epidemic has led to persistent negative psychological effects on the general public, especially college students, who are highly susceptible difficulties, such as fear, anxiety, and depression. Little information is known about depressive symptoms among students during normalization stage of COVID-19 prevention control in China. This study aimed understand prevalence factors associated with after a long quarantine time online learning at...

Abstract North American Monsoon (NAM) rainfall is a vital water resource in the United States Southwest, providing 60–80% of region's annual precipitation. However, NAM highly variable and managers lack skillful guidance on summer that could help inform their management decisions operations. Here we show season (June–October) precipitation can be forecasted by European Centre for Medium‐Range Weather Forecast's model months ahead at catchment scales. This possible identifying frequency days...

Abstract The “gray zone” of convective modeling is defined as the range horizontal grid spacings (Δ x ) at which turbulent transport processes are only partially resolved by dynamics numerical model. This zone typically covers Δ from a few kilometers to several hundred meters, wherein realistic representation cloud can be challenging. study characterizes draft behaviors multiple across gray and determines appropriate that reliably capture these salient properties. We perform an ensemble...

ABSTRACT This study demonstrates the capability of Weather Research and Forecasting ( WRF ) model with four‐dimensional data assimilation WRF‐FDDA to produce a high‐resolution climatography seasonal precipitation over Israel surrounding areas. The system was used dynamically downscale global Climate Forecast System CFS reanalysis continuous conventional unconventional observations. Precipitation seasons (December‐January‐February) in 7 years, including two extreme dry wet observed past...

Kalman-based state estimators assume a priori knowledge of the covariance matrices process and observation noise. However, in most practical situations, noise statistics initial conditions are often unknown need to be estimated from measurement data. This paper presents an auto-covariance least-squares-based algorithm for error estimation large-scale linear time-varying (LTV) nonlinear systems. Compared existing least-squares based-algorithms, our method does not involve any approximations...

Skillful mid-term temperature predictions (up to five years out) offer a potential opportunity for water managers, especially in the Colorado River Basin (CRB), where streamflows are sensitive temperature. The purpose of this paper is develop and demonstrate framework how can be incorporated into streamflow forecasting operational projections. consists three steps. First, 5-year average obtained from two large ensemble climate model datasets. Second, hindcasts Ensemble Streamflow Predictions...

Integrating deep learning methods for multi-element regression analysis poses a challenge in constructing safety evaluations building construction. To address this challenge, paper evaluates the integration of construction by quantitatively analyzing practitioners’ information and on-site conditions. The analytic hierarchy process (AHP) method quantifies capabilities, considering four key aspects: operators’ primary conditions, organizational personnel’s working management unsafe behaviors....

Abstract This paper describes a simple technique for creating regional, high-resolution, daytime and nighttime composites of sea surface temperature (SST) use in operational numerical weather prediction (NWP). The are based on observations from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) aboard Aqua Terra. data used typically available nearly real time, applicable anywhere the globe, capable roughly representing diurnal cycle SST. composites’ resolution is much higher than...

Abstract Decadal (∼10‐year)‐scale flow projections in the Colorado River Basin (CRB) are increasingly important for water resources management and planning of its reservoir system. Physical models, ensemble streamflow prediction (ESP), do not have skill beyond interannual time scales. However, Global Climate Models good projecting decadal temperatures. This, combined with sensitivity CRB flows to temperature from recent studies, motivate research question , can be translated operationally...

Abstract. The large spatial scale of global Earth system models (ESM) is often cited as an obstacle to using the output by water resource managers in localized decisions. Recent advances computing have improved fidelity hydrological responses ESMs through increased connectivity between model components. However, are seldom evaluated for their ability reproduce metrics that important practitioners, or present results a manner resonates with users. We draw on combined experience author team...