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Case, Jonathan

Publications and source records attributed to Case, Jonathan.

At least 19 records

Monitoring Intense Thunderstorms in the Hindu-Kush Himalayan Region

Some of the most extreme thunderstorms on the planet routinely occur in the Hindu-Kush Himalaya (HKH) region— where many government organizations lack the resources needed to fully assess the risk associated with hazards that result from high impact convective weather. This project combines innovative numerical weather prediction, satellite-based precipitation and land imagery techniques into a high impact weather assessment tool kit (HIWAT) that is building the capabilities of national meteorological departments and other weather sensitive agencies in the HKH region to predict, observe and effectively respond to threats and impacts posed by thunderstorms that affect the region, thereby enhancing extreme weather resilience in the region.

extreme weather

Using NASA's Remote Sensing Datasets and Land Information System to Characterize Lightning Initiated Wildfires

Can we use modeled information of the land surface and characteristics of lightning beyond flash occurrence to increase the identification and prediction of wildfires? The goals of this study are to: combine observed cloud-to-ground (CG) flashes with real-time land surface model output; and compare data with areas where lightning did not start a wildfire to determine what land surface conditions, rainfall observations, and lightning characteristics were responsible for causing wildfires.

White, Kristopher

GC13I-0857: Designing a Frost Forecasting Service for Small Scale Tea Farmers in East Africa

Kenya is the third largest tea exporter in the world, producing 10% of the world's black tea. Sixty percent of this production occurs largely by small scale tea holders, with an average farm size of 1.04 acres, and an annual net income of $1,075. According to a recent evaluation, a typical frost event in the tea growing region causes about $200 dollars in losses which can be catastrophic for a small holder farm. A 72-hour frost forecast would provide these small-scale tea farmers with enough notice to reduce losses by approximately 80 USD annually. With this knowledge, SERVIR, a joint NASA-USAID initiative that brings Earth observations for improved decision making in developing countries, sought to design a frost monitoring and forecasting service that would provide farmers with enough lead time to react to and protect against a forecasted frost occurrence on their farm. SERVIR Eastern and Southern Africa, through its implementing partner, the Regional Centre for Mapping of Resources for Development (RCMRD), designed a service that included multiple stakeholder engagement events whereby stakeholders from the tea industry value chain were invited to share their experiences so that the exact needs and flow of information could be identified. This unique event allowed enabled the design of a service that fit the specifications of the stakeholders. The monitoring service component uses the MODIS Land Surface Temperature product to identify frost occurrences in near-real time. The prediction component, currently under testing, uses the 2-m air temperature, relative humidity, and 10-m wind speed from a series of high-resolution Weather Research and Forecasting (WRF) numerical weather prediction model runs over eastern Kenya as inputs into a frost prediction algorithm. Accuracy and sensitivity of the algorithm is being assessed with observations collected from the farmers using a smart phone app developed specifically to report frost occurrences, and from data shared through our partner network developed at the stakeholder engagement meeting. This presentation will illustrate the efficacy of our frost forecasting algorithm, and a way forward for incorporating these forecasts in a meaningful way to the key decision makers - the small-scale farmers of East Africa.

frost

Sensitivity of CONUS Summer Rainfall to the Selection of Cumulus Parameterization Schemes in NU-WRF Seasonal Simulations

This study investigates the sensitivity of daily rainfall rates in regional seasonal simulations over the contiguous United States (CONUS) to different cumulus parameterization schemes. Daily rainfall fields were simulated at 24-km resolution using the NASA-Unified Weather Research and Forecasting (NU-WRF) Model for June-August 2000. Four cumulus parameterization schemes and two options for shallow cumulus components in a specific scheme were tested. The spread in the domain-mean rainfall rates across the parameterization schemes was generally consistent between the entire CONUS and most subregions. The selection of the shallow cumulus component in a specific scheme had more impact than that of the four cumulus parameterization schemes. Regional variability in the performance of each scheme was assessed by calculating optimally weighted ensembles that minimize full root-mean-square errors against reference datasets. The spatial pattern of the seasonally averaged rainfall was insensitive to the selection of cumulus parameterization over mountainous regions because of the topographical pattern constraint, so that the simulation errors were mostly attributed to the overall bias there. In contrast, the spatial patterns over the Great Plains regions as well as the temporal variation over most parts of the CONUS were relatively sensitive to cumulus parameterization selection. Overall, adopting a single simulation result was preferable to generating a better ensemble for the seasonally averaged daily rainfall simulation, as long as their overall biases had the same positive or negative sign. However, an ensemble of multiple simulation results was more effective in reducing errors in the case of also considering temporal variation.

Iguchi, Takamichi

Monitoring Intense Thunderstorms in the Hindu-Kush Himalayan Region

Some of the most intense thunderstorms on the planet routinely occur in the Hindu-Kush Himalaya region(HKH) region where many government organizations lack the capacity needed to predict, observe and effectively respond to the threats and hazards associated with high impact convective weather. This project combines innovative numerical weather prediction, satellite-based precipitation and land imagery techniques into a high impact weather assessment toolkit (HIWAT) that will build the capabilities of national meteorological departments and other weather sensitive agencies in the HKH region to assess the potential threats and impacts of high impact convective weather.

Himalayas

Earth Remote Sensing for Weather Forecasting and Disaster Applications

NASA's constellation of current missions provide several opportunities to apply satellite remote sensing observations to weather forecasting and disaster response applications. Examples include: Using NASA's Terra and Aqua MODIS, and the NASA/NOAA Suomi-NPP VIIRS missions to prepare weather forecasters for capabilities of GOES-R; Incorporating other NASA remote sensing assets for improving aspects of numerical weather prediction; Using NASA, NOAA, and international partner resources (e.g. ESA/Sentinel Series); and commercial platforms (high-res, or UAV) to support disaster mapping.

Molthan, Andrew