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Jason M. English authored and/or contributed to the following articles/publications.
Field operations and data impact studies examine how observations from high-altitude unmanned aircraft can improve forecasts of tropical cyclones and other high-impact weather events. The National Oceanic and Atmospheric Administration’s (NOAA) Sensing Hazards with Operational Unmanned Technology (SHOUT) project evaluated the ability of obser...
Institution National Oceanic and Atmospheric Administration - NOAA
Numerous satellites utilized in numerical weather prediction are operating beyond their nominal lifetime, and their replacements are not yet operational. We investigate the impacts of a loss of U.S.-based microwave and infrared satellite data and the addition of dropsonde data on forecast skill by conducting Observing System Simulation Experimen...
Severe weather events can have a significant impact on local communities because of the loss of life and property. Forecast busts associated with high-impact weather events have been attributed to initial condition errors over data-sparse regions, such as the Pacific Ocean. Numerous flight campaigns have found that targeted observations over the...
The Stratospheric Sulfur and its Role in Climate (SSiRC) Interactive Stratospheric Aerosol Model Intercomparison Project (ISA-MIP) explores uncertainties in the processes that connect volcanic emission of sulfur gas species and the radiative forcing associated with the resulting enhancement of the stratospheric aerosol layer. The central aim of ...
Designing the Climate Observing System of the Future
Climate observations are needed to address a large range of important societal issues including sea level rise, droughts, floods, extreme heat events, food security, and freshwater availability in the coming decades. Past, targeted investments in specific climate questions have resulted in tremendous improvements in issues important to human hea...
Institutions Earth System Research Laboratory - ESRL National Oceanic and Atmospheric Administration - NOAA
Spatial Coverage of Monitoring Networks: A Climate Observing System Simulation Experiment
Observing systems consisting of a finite number of in situ monitoring stations can provide high-quality measurements with the ability to quality assure both the instruments and the data but offer limited information over larger geographic areas. This paper quantifies the spatial coverage represented by a finite set of monitoring stations by usin...
Institutions Earth System Research Laboratory - ESRL National Center for Atmospheric Research - NCAR National Oceanic and Atmospheric Administration - NOAA
Sensors on satellites provide unprecedented understanding of the Earth's climate system by measuring incoming solar radiation, as well as both passive and active observations of the entire Earth with outstanding spatial and temporal coverage. A common challenge with satellite observations is to quantify their ability to provide well-calibrated, ...
Institutions Earth System Research Laboratory - ESRL National Oceanic and Atmospheric Administration - NOAA
Improved forecasts of atmospheric river (AR) events, which provide up to half the annual precipitation in California, may reduce impacts to water supply, lives, and property. We evaluate quantitative precipitation forecasts (QPF) from the High-Resolution Rapid Refresh model version 3 (HRRRv3) and version 4 (HRRRv4) for five AR events that occurr...
Institutions Earth System Research Laboratory - ESRL National Oceanic and Atmospheric Administration - NOAA
Accurate quantitative precipitation estimates (QPEs) at high spatial and temporal resolution are difficult to obtain in regions of complex terrain due to the large spatial heterogeneity of orographically enhanced precipitation, sparsity of gauges, precipitation phase variations, and terrain effects that impact the quality of remotely sensed esti...
Institutions Earth System Research Laboratory - ESRL National Oceanic and Atmospheric Administration - NOAA
Ensemble Transform Sensitivity Method for Target Observations: An OSSE Case Study
Unmanned aerial system (UAS) for improving forecast accuracy of high-impact weather systems has been studied under the Sensing Hazards with Operational Unmanned Technology (SHOUT) project in the NOAA joint OSSE system. Due to the limited number of dropsondes, adaptive observation schemes have to be considered in these experiments in order to ful...
Institution National Oceanic and Atmospheric Administration - NOAA
We present a suite of new climate model experiment designs for the Geoengineering Model Intercomparison Project (GeoMIP). This set of experiments, named GeoMIP6 (to be consistent with the Coupled Model Intercomparison Project Phase 6), builds on the previous GeoMIP project simulations, and has been expanded to address several further important t...
The National Oceanic and Atmospheric Administration’s (NOAA) Sensing Hazards with Operational Unmanned Technology (SHOUT) project evaluated the ability of observations from high-altitude unmanned aircraft to improve forecasts of high-impact weather events like tropical cyclones or mitigate potential degradation of forecasts in the event of a fut...
Institutions Earth System Research Laboratory - ESRL National Oceanic and Atmospheric Administration - NOAA
Probabilistic Forecasts of Atmospheric River events using the HRRR Ensemble
The nine-member High-Resolution Rapid Refresh Ensemble (HRRRE) is evaluated for its ability to forecast five Atmospheric River (AR) events that impacted California in February–March 2019. Two sets of retrospective HRRRE simulations are conducted, a control with the standard set of perturbations (initial and boundary conditions, stochastic parame...