Isidora Jankov authored and/or contributed to the following articles/publications.
Assimilating synthetic GOES-R radiances in cloudy conditions using an ensemble-based method
The Weather Research and Forecasting (WRF) model and the Maximum Likelihood Ensemble Filter (MLEF) data assimilation approach are used to examine the potential impact of observations from the future Geostationary Operational Environmental Satellite, generation R (GOES-R) on improving our knowledge about clouds. Synthetic radiances are assimilate...
Impacts of the STMAS cycling data assimilation system on improving severe weather forecasting
his project will study the impacts on analysis and forecast by cycling model forecasts as analysis background fields for the severe weather cases, including hurricane Katrina and Windsor tornado. The impacts of the cycling technique (using high-resolution model as the background information) will be investigated in a data assimilation system - t...
Rapid Response to the Howard A. Hanson Dam Flood Risk Management Crisis
The Howard A. Hanson Dam (HDD) has brought flood protection to Washington's Green River Valley for more than 40 years and opened the way for increased valley development near Seattle. However, following a record high level of water behind the dam in January 2009 and the discovery of elevated seepage through the dam's abutment, the U.S. Army Corp...
We present a method based on optimal data assimilation techniques used today in weather analysis to blend together high-resolution precipitation forecasts with point observations at rain gages or other estimates (for instance, radar). This method is applied to several winter storms during 2005-2007 in the American River Basin (ARB) northeast of ...
Significant precipitation events in California during the winter season are often caused by landfalling “atmospheric rivers” associated with extratropical cyclones from the Pacific Ocean. When an atmospheric river makes landfall on the coast of California, the northwest to southeast orientation of the high terrain will exert forcing on the low-l...
The 4 June 1999 derecho event: A particularly difficult challenge for numerical weather prediction
In recent years, a mixed-physics ensemble approach has been investigated as a method to better predict mesoscale convective system (MCS) rainfall. For both mixed-physics ensemble design and interpretation, knowledge of the general impact of various physical schemes and their interactions on warm season MCS rainfall forecasts would be useful. Ado...
MCS rainfall forecast accuracy as a function of large-scale forcing
The large-scale forcing associated with 20 mesoscale convective system (MCS) events has been evaluated to determine how the magnitude of that forcing influences the rainfall forecasts made with a 10-km grid spacing version of the Eta Model. Different convective parameterizations and initialization modifications were used to simulate these Upper ...
Contrast between good and bad forecasts of warm season MCS rainfall
Large variations in the accuracy of warm season MCS rainfall predictions are investigated by examining several wellforecasted and poorly forecasted cases from a sample of 20 events simulated using a 10 km grid spacing version of the Eta model. Two different convective schemes, the Betts–Miller–Janjic and Kain–Fritsch, have been used in the simul...
Partition of Forecast Error into Positional and Structural Components
Weather manifests in spatiotemporally coherent structures. Weather forecasts hence are affected by both positional and structural or amplitude errors. This has been long recognized by practicing forecasters (cf., e.g., Tropical Cyclone track and intensity errors). Despite the emergence in recent decades of various objective methods for the diagn...
Institution National Oceanic and Atmospheric Administration - NOAA
A Progress Report on the Development of the High-Resolution Rapid Refresh Ensemble
The High-Resolution Rapid Refresh Ensemble (HRRRE) is a 36-member ensemble analysis system with 9 forecast members that utilizes the Advanced Research version of the Weather Research and Forecasting (ARW-WRF) dynamic core and the physics suite from the operational Rapid Refresh/High-Resolution Rapid Refresh deterministic modeling system. A goal ...
Institutions National Center for Atmospheric Research - NCAR National Oceanic and Atmospheric Administration - NOAA
U.S. National Weather Service (NWS) forecasters assess and communicate hazardous weather risks, including the likelihood of a threat and its impacts. Convection-allowing model (CAM) ensembles offer potential to aid forecasting by depicting atmospheric outcomes, including associated uncertainties, at the refined space and time scales at which haz...
Institutions National Center for Atmospheric Research - NCAR National Oceanic and Atmospheric Administration - NOAA
Stochastically Perturbed Parameterizations in a HRRR-Based Ensemble
A stochastically perturbed parameterization (SPP) approach that spatially and temporally perturbs parameters and variables in the Mellor-Yamada-Nakanishi-Niino planetary boundary layer scheme (PBL) and introduces initialization perturbations to soil moisture in the Rapid Update Cycle land surface model was developed within the High Resolution Ra...
Institutions National Center for Atmospheric Research - NCAR National Oceanic and Atmospheric Administration - NOAA
An Adaptive Approach for the Calculation of Ensemble Gridpoint Probabilities
Traditional ensemble probabilities are computed based on the number of members that exceed a threshold at a given point divided by the total number of members. This approach has been employed for many years in coarse-resolution models. However, convection-permitting ensembles of less than ~20 members are generally underdispersive, and spatial di...
Institution National Oceanic and Atmospheric Administration - NOAA
A stochastic parameter perturbation (SPP) scheme consisting of spatially and temporally varying perturbations of uncertain parameters in the Grell–Freitas convective scheme and the Mellor–Yamada–Nakanishi–Niino planetary boundary scheme was developed within the Rapid Refresh ensemble system based on the Weather Research and Forecasting Model. Al...
Institutions National Center for Atmospheric Research - NCAR National Oceanic and Atmospheric Administration - NOAA
Lack of spread is a common deficiency in ensemble models and results in over-confident and inaccurate forecasts. A number of options exist to increase the spread of an ensemble, including the use of multiple physics parameterizations or dynamic cores. However, implementation of these options can be cumbersome, costly, and suffer from certain t...
Institution National Center for Atmospheric Research - NCAR
The 13-km Rapid Refresh (RAP) and 3-km convective-allowing High-Resolution Rapid Refresh (HRRR) are hourly updating weather forecast models that use a specially configured version of the Advanced Research WRF (ARW) model and assimilate many novel and most conventional observation types on an hourly basis using Gridpoint Statistical Interpolation...
Institution National Oceanic and Atmospheric Administration - NOAA
Evaluation of Several Spatial Filtering Methods for Probabilistic CPM Ensemble Forecasts
To support the goals of a collaborative project through the US Weather Research Program (USWRP), which is focused on developing high-resolution ensemble-based hazard detection guidance tools, several convection-allowing model (CAM) ensemble post-processing methods are currently being evaluated with the operational version of the High Resolution ...
The 13-km Rapid Refresh (RAP) and 3-km convective-allowing High-Resolution Rapid Refresh (HRRR) are hourly updating weather forecast models that use a specially configured version of the Advanced Research WRF (ARW) model and assimilate many novel and most conventional observation types on an hourly basis using Gridpoint Statistical Interpolation...
Institution National Oceanic and Atmospheric Administration - NOAA
An operational upgrade of the RAP and HRRR model systems at NCEP is planned for August 2016. This coordinated upgrade (RAP version 3 and HRRR version 2, RAPv3/HRRRv2) includes many enhancements to the data assimilation, model, and post-processing formulations that result in significant improvements to nearly all forecast aspects, including uppe...
Institution National Oceanic and Atmospheric Administration - NOAA
The accurate and timely depiction of the state of the atmosphere on multiple scales is critical to enhance forecaster situational awareness and to initialize very short-range numerical forecasts in support of nowcasting activities. The Local Analysis and Prediction System (LAPS) of the Earth System Research Laboratory (ESRL)/Global Systems Divis...
Institution National Oceanic and Atmospheric Administration - NOAA
Initial-Value vs. Model-Induced Forecast Error: A New Perspective
Numerical models of the atmosphere are based on the best theory available. Understandably, the theoretical assessment of errors induced by the use of such models is confounding. Without clear theoretical guidance, the experimental separation of the model-induced part of the total forecast error is also challenging. In this study, the forecast er...
A new software framework using a well-established high-order spectral element discretization is presented for solving the compressible Navier–Stokes equations for purposes of research in atmospheric dynamics in bounded and unbounded limited-area domains, with a view toward capturing spatiotemporal intermittency that may be particularly challengi...
Institution National Oceanic and Atmospheric Administration - NOAA
Institution National Oceanic and Atmospheric Administration - NOAA
Comparison of adaptive mesh refinement techniques for numerical weather prediction.
This paper examines the application of adaptive mesh refinement (AMR) in the field of numerical weather prediction (NWP). We implement and assess two distinct AMR approaches and evaluate their performance through standard NWP benchmarks. In both cases, we solve the fully compressible Euler equations, fundamental to many non-hydrostatic weather m...
Institution National Oceanic and Atmospheric Administration - NOAA