The 2013 Flash Flood and Intense Rainfall experiment (FFaIR)

flash-raindrop-strippedA team from NSSL will partner with the NOAA Hydrometeorological Testbed at the Weather Prediction Center to host the 1st annual Flash Flood and Intense Rainfall Experiment (FFaIR).  FFaIR will explore using high-resolution atmospheric and hydrologic models to improve short-term forecasts of both precipitation amounts and flash flooding. The project runs from July 8-26, 2013.

NSSL’s Flooded Locations And Simulated Hydrographs (FLASH) system will be one of several modeling systems evaluated during FFaIR. The FLASH system uses radar-estimated rainfall from NSSL’s National Mosaic and QPE System (NMQ/Q2) as input into the CREST (Coupled Routing and Excess STorage) hydrologic model.  FLASH then creates real-time 6-hour forecasts on a 1km grid that is updated every 15 minutes.

The 2013 FFaIR experiment will provide, for the first time, a pseudo-real time environment where participants from across the weather enterprise can explore the interface of meteorology and hydrology.  Working together through the forecast process will foster collaboration between National Centers for Environmental Prediction, National Weather Service Forecast Offices, NOAA labs, and the academic community.

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May 20, 2013 tornado outbreak experimental forecast products

The Hazardous Weather Testbed Spring Forecast Experiment was in full operation on May 20, 2013 as the tornado tore through Newcastle and Moore, OK.  Visiting forecasters and researchers were working with state-of-the art convection allowing experimental modeling systems. They also issued experimental outlook-type forecasts that included areas and probabilities of severe weather over shorter time periods than current operational products.  Forecasts generated by the participants were used in real-time to support decisions made for experimental warning operations.  New this year, the UK Met Office was testing their modeling system over the U.S. where there is more severe weather.

NSSL’s Mesoscale Ensemble is an experimental analysis and short-range ensemble forecast system.  These forecasts are designed to be used by forecasters as a 3-D hourly analysis of the environment, a very important tool in the severe weather process. Each panel shows ensemble mean 1 hour forecasts valid at 3pm CDT, the time of the tornado. The Significant Tornado Parameter (bottom right) with values > 1 have been shown to discriminate supercells that do and don’t produce significant tornadoes.   This field highlighted the storm over Moore more so than the storms further south with values > 1 shaded in red.  Composite reflectivity from NSSL’s National Mosaic and Quantitative precipitation estimation (NMQ) is overlayed to show where the storms actually formed.

The left panel shows NSSL’s mid-level rotation tracks derived from WSR-88D radar from 1 to 4 pm.  The human-generated experimental forecast for severe weather at 12pm, valid from 1 to 4pm on May 20th is overlayed.  They used brown, red, and purple lines to enclose areas that were estimated to have a 5%, 15%, and 30% chance of severe weather within 25 miles of a point during the 3-hour period.  The black line outlines an area that was estimated to have a 10% or greater chance of significant severe weather, also within 25 miles of a point.

Along with the same human-generated forecast, the right panel shows areas of significant mid-level rotation valid from 1 to 4pm from three different convection allowing model forecasts.  The models are the NSSL WRF-ARW model, a parallel version of this model initialized from the NSSL mesoscale ensemble, and a model provided by the United Kingdom Met Office for the Spring Forecasting Experiment run over the CONUS on a domain with 2.2 km grid spacing.

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Field project begins to improve thunderstorm prediction

MPEX-logo-finalToday, researchers launched the Mesoscale Predictability EXperiment (MPEX) field project to collect data on pre-storm and post-storm environments in an effort to better predict where and when thunderstorms will form.  MPEX runs from May 15 – June 15, and is funded by the National Science Foundation.

NSSL researchers will team with Colorado State University and Purdue to launch weather balloons carrying instrument packages called radiosondes.  They hope to find out how thunderstorms interact with the atmosphere that surrounds and supports them, and how this affects formation of new thunderstorms.  They also hope to ingest the balloon data into computer models to see how the extra data collected during the afternoon can help predict the location and severity of evening storms better.

Researchers with the National Center for Atmospheric Research will use a Gulfstream V aircraft to sample pre-storm jet stream winds, upper–level temperatures and other features across Colorado and nearby states.  The aircraft will cruise at 40,000 feet for up to six hours so researchers can thoroughly canvass the region. The data they collect will also be ingested into computer models to show how well the extra data can help predict local and regional weather conditions into the next day.

Additional participants are from the University at Albany, State University of New York and the University of Wisconsin-Milwaukee.

http://www.eol.ucar.edu/projects/mpex/

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NSSL, partners: Thin, low Arctic clouds played an important role in the massive 2012 Greenland ice melt

Thin low clouds over Greenland caused unusual melting.
Thin low clouds over Greenland caused unusual melting.

Better understanding of Arctic clouds will help improve climate and weather forecasts

Clouds over the central Greenland Ice Sheet last July were “just right” for driving surface temperatures there above the melting point, according to a new study by scientists at NOAA and the Universities of Wisconsin, Idaho and Colorado. The study, published today in Nature, found that thin, low-lying clouds allowed the sun’s energy to pass through and warm the surface of the ice, while at the same time trapping heat near the surface of the ice cap. This combination played a significant role in last summer’s record-breaking melt.

“Thicker cloud conditions would not have led to the same amount of surface warming,” said Matthew Shupe, research meteorologist with NOAA’s Cooperative Institute for Research in Environmental Sciences at the University of Colorado and the NOAA Earth System Research Laboratory. “To understand the region’s future, you’ll need to understand its clouds. Our finding has implications for the fate of ice throughout the Arctic.”

Scientists around the world are trying to understand how quickly Greenland is warming because ice melt there contributes to sea level rise globally. The Greenland Ice Sheet is second only to Antarctica in ice volume. In July, more than 97 percent of the Greenland Ice Sheet surface experienced some degree of melting, including at the National Science Foundation’s Summit Station, high atop the ice sheet. According to ice core records, the last time the surface at Summit experienced any degree of melting was in 1889, but it is not known whether this extended across the entire ice sheet.

To investigate whether clouds contributed to, or counteracted, the surface warming that melted the ice, the authors modeled the near-surface conditions. The model was based on observations from a suite of sophisticated atmospheric sensors operated as part of a study called the Integrated Characterization of Energy, Clouds, Atmospheric State and Precipitation at Summit.

“The July 2012 ice melt was triggered by an influx of unusually warm air sweeping in from North America, but that was only one factor,” said David Turner, research meteorologist with the NOAA National Severe Storms Laboratory and one of the lead investigators. “In our paper, we show that low-lying clouds containing a low amount of condensed water were instrumental in pushing surface air temperatures up above freezing and causing the surface ice to melt.”

Clouds can cool the surface by reflecting solar energy back into space, and can warm it by radiating heat energy back down to the surface. The balance of those two processes depends on many factors, including wind speed, turbulence, humidity and cloud “thickness,” or liquid water content.

In certain conditions, these clouds can be thin enough to allow some solar radiation to pass through, while still “trapping” infrared radiation at ground level. That is exactly what happened last July: the clouds were just right for maximum surface warming. Thicker clouds would have reflected away more solar radiation; thinner ones couldn’t have trapped as much heat, and in either of those cases, there would have been less surface warming.

The researchers also found these thin, low-lying liquid clouds occur 30 to 50 percent of the time in summer, both over Greenland and across the Arctic. Current climate models tend to underestimate their occurrence in the Arctic, which limits those models’ ability to predict how clouds and their warming or cooling effects may respond to climate change.

“The cloud properties and atmospheric processes observed with the Summit Station instrument array provide a unique dataset to answer the large range of scientific questions we want to address,” said Turner. “Clouds play a big role in the surface mass and energy budgets over the Greenland Ice Sheet. Melting of the world’s major ice sheets can significantly impact human and environmental conditions via its contribution to sea-level rise.”

Better understanding of clouds also improves climate and weather models.

“Our results may help to explain some of the difficulties that current global climate models have in simulating the Arctic surface energy budget, including the contributions of clouds,” said Ralf Bennartz, lead author for the study and professor at the University of Wisconsin-Madison. “Above all, this study highlights the importance of continuous and detailed ground-based observations over the Greenland Ice Sheet and elsewhere. Only such detailed observations will lead to a better understanding of the processes that drive Arctic climate.”

NOAA’s mission is to understand and predict changes in the Earth’s environment, from the depths of the ocean to the surface of the sun, and to conserve and manage our coastal and marine resources.

Contact:

Keli Pirtle   405-325-6933

keli.pirtle@noaa.gov

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High and Dry – Probing Greenland’s Atmosphere and Clouds

ICECAPS1

– by Matthew Shupe (Cooperative Institute for Research in Environmental Studies)

High atop the Greenland Ice Sheet, cloudy skies portend warmer temperatures and higher winds.  These clouds alter the surface energy budget, diminish the strong near-surface atmospheric stability, and precipitate ice crystal to the surface.  Together these processes comprise the focus of the Integrated Characterization of Energy, Clouds, Atmospheric state, and Precipitation at Summit (ICECAPS) project that has been underway at Summit, Greenland since summer 2010.  Exciting initial results are rolling out, providing the first detailed look at cloud and atmosphere properties and processes over the Greenland Ice Sheet.  The action observed by the extensive, ground-based instrument suite can be followed via daily imagery available at www.esrl.noaa.gov/psd/arctic/observatories/summit.

Playing key roles in the U.S. Arctic Observing Network (AON) and the International Arctic Systems for Observing the Atmosphere (IASOA) network, ICECAPS is a collaborative project between the Universities of Colorado, Idaho, and Wisconsin, with substantial support from the National Science Foundation, the National Oceanic and Atmospheric Administration, the Department of Energy, and Environment Canada.  Principle Investigators Von Walden (University of Idaho), Matthew Shupe (ESRL/CIRES), David Turner (NSSL), and Ralf Bennartz (University of Wisconsin) lead a large team of field technicians, engineers, graduate students, and collaborators as they endeavor to make year-round measurements of the atmosphere and clouds in the extreme Greenland Ice Sheet environment.  The instrument suite, housed in a movable facility, includes highly complementary observational perspectives from microwave and infrared radiometers, lidars, radar, ceilometer, sodar, precipitation sensor, and twice-daily radiosonde profiles (see Figure1).  These measurements can be jointly used to characterize the diurnal and seasonal variability of atmospheric structure, cloud microphysical and radiative properties, and precipitation.  ICECAPS provides a new and unique observational examination of these climatically-important aspects of the ice sheet environment and will offer important context for ongoing precipitation and surface energy budget measurements at the site.

At Summit, the atmosphere is extremely dry and cold with strong near-surface static stability predominating throughout the year, particularly in winter.  This low-level thermodynamic structure, coupled with frequent moisture inversions, conveys the importance of advection for local cloud and precipitation formation.  Cloud liquid water is observed in all months of the year, even in the particularly cold and dry winter, while annual cycle observations indicate the largest atmospheric moisture amounts, cloud water contents, and snowfall occur in summer and under southwesterly flow.  Atmospheric ice crystals, or diamond dust, readily form as advecting air masses cool over the ice sheet, leading to outstanding optical displays.  Surprisingly, many of the basic structural properties of clouds observed at Summit, and particularly the low-level stratiform clouds, are very similar to their counterparts in other Arctic regions in spite of the unique environment encountered on top of the ice sheet.  The ICECAPS observations and accompanying analyses will be used to improve the understanding of key cloud–atmosphere processes and the manner in which they interact with the GIS. Furthermore, they will facilitate model evaluation and development in this data-sparse but environmentally unique region.

Related Article:  Shupe, M. D., D. D. Turner, V. P. Walden, R. Bennartz, M. Cadeddu, B. Castellani, C. Cox, D. Hudak, M. Kulie, N. Miller, R. R. Neely III, W. Neff, and P. Rowe, 2013:  High and Dry:  New observations of tropospheric and cloud properties above the Greenland Ice Sheet.  Bull. Amer. Meteor. Soc., 94, 169-186, doi:10.1175/BAMS-D-11-00249.1.

 

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NSSL Launches iPhone and Android Apps to collect precipitation reports from the public

Screenshot of the mPING app for iPhone

The NOAA National Severe Storms Laboratory (NSSL), in partnership with the University of Oklahoma and has launched an app where users can anonymously report precipitation from their iPhone or Android through the “mobile Precipitation Identification Near the Ground “mPING” app.  NSSL researchers will compare the reports with what radars detect and use the information to develop new radar and forecasting technologies and techniques to determine whether snow, rain, ice pellets, mixtures or hail is falling. NSSL hopes to build a valuable database of tens of thousands of observations from across the U.S.
The apps are available on iTunes or Google Play for use on both phones and tablets.

The reports can be viewed here in real-time:
http://www.nssl.noaa.gov/projects/ping/display/

Learn more at NSSL’s main PING page:  http://www.nssl.noaa.gov/projects/ping/

Link for iTunes mPING app

Link for Android app

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Lower Atmospheric Boundary Layer Experiment

One of the Doppler Lidars at the Southern Great Plains research site.

A NOAA National Severe Storms Laboratory (NSSL) scientist is leading an experiment to collect a comprehensive dataset on vertical turbulence and thermodynamic profiles in a portion of the lower atmosphere known as the boundary layer. A number of instruments deployed in north central Oklahoma will collect data for six weeks during the Lower Atmospheric Boundary Layer Experiment (LABLE).

The unique dataset will help researchers understand turbulent processes and thus improve our ability to reproduce turbulence more accurately in numerical weather models that attempt to simulate the atmosphere.

Turbulence redistributes energy and mass in the atmosphere, and can be influenced by different surface types, horizontal wind speed and direction, and the vertical temperature structure of the atmosphere. However, there have been relatively few studies that have investigated how the vertical turbulence profile changes over short horizontal distances due to these variables.  Data collected during LABLE will also be used to derive water vapor fluxes at the top of the boundary layer, and to compare vertical motions observed by different instruments.

LABLE leverages the strong observing infrastructure currently available from the Department of Energy’s Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site in north-central Oklahoma.  In addition to the instruments already in place at SGP, NSSL and scientists from the University of Oklahoma deployed two Doppler lidars, a sodar, and a laser scintillometer to measure turbulence, winds, thermodynamic structure and other microphysical properties.

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Addition to weather model helps forecast precip types more accurately

An NSSL microphysics scheme that will help forecast six different types of precipitation more accurately was included in the most recent update of the Weather Research and Forecasting (WRF) model. The model is used by operational meteorologists and refined by atmospheric researchers to help forecast thunderstorms and other smaller scale weather with greater realism.

The NSSL scheme predicts the development of water and ice particles in clouds. Like other schemes, it categorizes particles into broad classes of liquid (small cloud droplets or larger rain drops) and ice (small crystals, snow particles, graupel, and hail). Both the amount of mass and the number of particles are tracked, so that the average particle size is predicted. The new NSSL scheme adds a prediction of graupel particle density.

Graupel is a type of ice particle that has a lot of small water drops frozen onto it (rime ice), and can vary in widely in density. Graupel that starts as a freezing rain drop will have higher density than graupel that starts as a rimed ice crystal. Typical schemes have a constant density for graupel and a constant fall speed relationship. Predicting the density, however, allows a much greater range of fall speeds and can result in a more realistic distribution of graupel in a storm. This then affects where the rain (melted graupel) falls to ground, and the melting and evaporation cool the air. The cold air outflow is important for storm motion, longevity, and even severity.

NSSL’s Ted Mansell was instrumental in getting the scheme into NCAR WRF and plans to test it in the NOAA Hazardous Weather Testbed during the 2013 Spring Experiment.

Addition to weather model helps forecast precip types more accurately

An NSSL microphysics scheme that will help forecast six different types of precipitation more accurately was included in the most recent update of the Weather Research and Forecasting (WRF) model. The model is used by operational meteorologists and refined by atmospheric researchers to help forecast thunderstorms and other smaller scale weather with greater realism.

The NSSL scheme predicts the development of water and ice particles in clouds. Like other schemes, it categorizes particles into broad classes of liquid (small cloud droplets or larger rain drops) and ice (small crystals, snow particles, graupel, and hail). Both the amount of mass and the number of particles are tracked, so that the average particle size is predicted. The new NSSL scheme adds a prediction of graupel particle density.

Graupel is a type of ice particle that has a lot of small water drops frozen onto it (rime ice), and can vary in widely in density. Graupel that starts as a freezing rain drop will have higher density than graupel that starts as a rimed ice crystal. Typical schemes have a constant density for graupel and a constant fall speed relationship. Predicting the density, however, allows a much greater range of fall speeds and can result in a more realistic distribution of graupel in a storm. This then affects where the rain (melted graupel) falls to ground, and the melting and evaporation cool the air. The cold air outflow is important for storm motion, longevity, and even severity.

NSSL’s Ted Mansell was instrumental in getting the scheme into NCAR WRF and plans to test it in the NOAA Hazardous Weather Testbed during the 2013 Spring Experiment.

Addition to weather model helps forecast precip types more accurately

An NSSL microphysics scheme that will help forecast six different types of precipitation more accurately was included in the most recent update of the Weather Research and Forecasting (WRF) model. The model is used by operational meteorologists and refined by atmospheric researchers to help forecast thunderstorms and other smaller scale weather with greater realism.

The NSSL scheme predicts the development of water and ice particles in clouds. Like other schemes, it categorizes particles into broad classes of liquid (small cloud droplets or larger rain drops) and ice (small crystals, snow particles, graupel, and hail). Both the amount of mass and the number of particles are tracked, so that the average particle size is predicted. The new NSSL scheme adds a prediction of graupel particle density.

Graupel is a type of ice particle that has a lot of small water drops frozen onto it (rime ice), and can vary in widely in density. Graupel that starts as a freezing rain drop will have higher density than graupel that starts as a rimed ice crystal. Typical schemes have a constant density for graupel and a constant fall speed relationship. Predicting the density, however, allows a much greater range of fall speeds and can result in a more realistic distribution of graupel in a storm. This then affects where the rain (melted graupel) falls to ground, and the melting and evaporation cool the air. The cold air outflow is important for storm motion, longevity, and even severity.

NSSL’s Ted Mansell was instrumental in getting the scheme into NCAR WRF and plans to test it in the NOAA Hazardous Weather Testbed during the 2013 Spring Experiment.

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Researchers plan first extensive U.S. study looking for link between cities and storms

A group of researchers, including NSSL’s Dave Stensrud, recently announced they plan to study the effects of cities on thunderstorms. Looking at a number of different U.S. cities, the project hopes to clarify how urban pollution, canopy, and surrounding landscape influences the intensity and track of an approaching thunderstorm.

Stensrud is a principal investigator on the three-year $1.5 million NASA grant.

Researchers will use data from the space-borne MODIS sensors on NASA satellites to look at city shape and size, as well as pollution and other aerosols, for selected cities in the Great Plains.  These measurements, along with geographic data of the urban canopy and the vegetation of surrounding rural areas, will be combined with archived radar data of storms in high-resolution computer simulations.

“We are going to set up and run the model many times but with different variables; city or no city, pollution or vegetation,” Stensrud said.  “From this we hope to learn what size a city needs to be to have an impact on a storm.”

The information will be valuable for city and regional planners, as well as agricultural producers in surrounding areas.

The team includes weather computer modelers, radar meteorologists, landscape architects, atmospheric chemists and geographers from NSSL, South Dakota State University, the University of Oklahoma, the University of Michigan, Columbia University and the University of Minnesota.

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2012 Atlantic hurricane season to provide CI-FLOW research opportunity

Hurricane Irene in 2011

The 2012 Atlantic hurricane season will provide a valuable research opportunity for the Coastal and Inland-Flooding Observation and Warning Project (CI-FLOW). The goal during the 2012 hurricane season is to produce realistic simulations of total water level in real time for coastal storms. National Weather Service forecasters will have access to CI-FLOW during these events to help them evaluate the system for application in the flood and flash-flood warning process.

CI-FLOW is a demonstration project that captures the complex interaction between rainfall, river flows, waves, tides and storm surge, and how these factors affect water levels in the Tar-Pamlico and Neuse rivers and the Pamlico Sound in North Carolina.

CI-FLOW was tested in August 2011 as Hurricane Irene made landfall near Morehead City, NC.  CI-FLOW total water-level simulations were compared with water levels observed during the storm. Researchers found a high level of agreement in both the timing and water-level heights for the Tar-Pamlico and Neuse coastal watershed.

The CI-FLOW project is motivated by NOAA’s critical forecast need for detailed water-level predictions in coastal areas and has a vision to transition CI-FLOW research findings and technologies to other U.S. coastal watersheds.

This real-time demonstration will offer valuable insight on the accuracy and utility of total water level predictions for communities in the coastal plain of the Tar-Pamlico and Neuse rivers and the Pamlico Sound. Real-time simulations of coastal water levels for the 2012 Atlantic hurricane season are available on the CI-FLOW website (http://www.nssl.noaa.gov/projects/ciflow/). The site also includes an introductory video that highlights the flooding from Hurricane Floyd in 1999 and the response from Sea Grant and NOAA partners. (http://www.nssl.noaa.gov/ciflow/)

The NOAA National Severe Storms Laboratory with support from the NOAA National Sea Grant College Program leads the unique interdisciplinary team including the North Carolina, South Carolina, and Texas Sea Grant Programs; University of Oklahoma; Renaissance Computing Institute (RENCI), University of North Carolina at Chapel Hill; Seahorse Consulting; NWS Forecast Offices in Raleigh, and Newport/Morehead City; NWS Southeast River Forecast Center; NOAA’s Coastal Services Center; NOAA in the Carolinas; NOAA Southeast and Caribbean Regional Team (SECART); NOAA-Integrated Ocean Observing System; Department of Homeland Security, Center of Excellence-Natural Disasters, Coastal Infrastructure and Emergency Management; Centers for Ocean Sciences Education Excellence SouthEast; Coast Survey Development Laboratory; and NWS Office of Hydrologic Development.

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