RADAR Remote Sensing of
Precipitation
RADAR (RAdio Detection And Ranging). Before
we review observations of precipitation from space, it is useful to go over
the methods used for precipitation remote sensing at the surface. You
are encouraged to review a tutorial on weather
RADAR,
a type of "active" remote sensing, based on the principle that we can measure
the radiative back-scatter of emitted microwave radiation. This tutorial
was developed by the University of Illinois Weather World 2010 Project.
Below, I have included material prepared by the NWS, to illustrate what Doppler Radars look like, and to provide an indication of the network density, as well as a summary of radar applications.
NWS Doppler RADAR Summary Information
The National Weather Service (NWS) is undergoing a major modernization program to improve the quality and reliability of its products and services. The keystone of this modernization is the new Doppler weather surveillance radar (Model WSR-88D). The WSR-88D (also known as NEXRAD) excels in detecting the severe weather events that threaten life and property, from early detection of damaging winds to estimating rainfall amounts for use in river and flood forecasting.
NEXRAD
The WSR-88D uses Doppler radar technology to:
The WSR-88D capabilities will also:
How Doppler Radar Sees Into the Future
Radar detects the presence and location of an object by bouncing an electromagnetic signal off of it and measuring the time it takes for the signal to return. This measurement is used to determine the distance and direction of the object from the radar. In the case of radar meteorology, the "objects" being measured are the particles of water, ice or dust in the atmosphere. Doppler radars take additional advantage of the fact that radar signals reflected from a moving object undergo a change in frequency related to the speed of the object traveling to or away from the radar antenna. Therefore, using Doppler technology, the WSR-88D calculates both the speed and direction of motion of severe storms. By providing data on the wind patterns within developing storms, the new WSR-88D identifies the conditions leading to severe weather. A developing tornado, for example, can be detected forming miles above the earth before it reaches the ground. This means earlier detection of the precursors to tornadoes, as well as data on the direction and speed of tornadoes once they form.
Reflectivity
A Tri-agency Approach
In cooperative effort with the Department of Defense and the Federal Aviation Administration, the NWS anticipates a total of 164 radars to be deployed by the mid-1990s. Through an integrated network spanning the entire United States and its island territories, from Guam to Puerto Rico, WSR-88D will dramatically enchance our ability to safeguard life, property and commerce.
Receiving WSR-88D Products
Users of radar data have access to WSR-88D products via the NEXRAD Information
Dissemination Service (NIDS) vendors. There are four NIDS vendors, each offering
the full complement of WSR-88D products:
Alden Electronics, Inc.
40 Washington Street
Westborough, MA 01581-0500
508/366-8851
Kavouras Incorporated
1140 Rupp Drive
Burnsville, MN 55337
612/726-9515
UNISYS Weather Information Services
221 Gale Lane
Kennett Square, PA 19348-1226
610/444-2400 or 800/445-5929
WSI Corporation
4 Federal Street
Billerica, MA 01821-5000
508/670-5000
Here is a link to the current local radar which can be linked to from the UVA Weather Page
[ NWS Modernization Home Page ]
Remotely Sensed
Precipitation
Tropical Rainfall Measuring Mission
This is a NASA mission to study tropical rainfall, and its role in redistributing energy that helps drive the atmospheric circulation which determines weather and climate conditions all around the globe.
The primary rainfall instruments on TRMM are the TRMM Microwave Imager (TMI), the precipitation radar (PR) and the Visible and Infrared Radiometer System (VIRS). Additionally, the TRMM satellite will carry two related EOS instruments in the Clouds and Earth's Radiant Energy System (CERES) and the Lightning Imaging System (LIS).
TRMM is in a 350-km circular orbit with a 35 degree inclination angle. It was scheduled launched in 1997 with a mission life designed to be on the order of at least 3 years.
| Instrument | Spectral Region (V and H refer to polarization of wavelengths) | IFOV resolution |
| Precipitation Radar | Active Pulsed Microwave Radar 13.8 GHz | 4km |
| TRMM Microwave Imager | Passive Microwave sensors 10.65V, 10.65 H, 19.35V, 19.35H, 21.3 V, 37.0V, 37.0H, 85.5V, 85.5H GHz | 4-40km |
| Visible Infrared Radiometer | five channels between 0.63 to 12 micrometers | 2 km @ nadir |
| Cloud and Earth Radiant Energy Sensor | 8x16km @ nadir | |
| Lightening Imaging Sensor | 4km |
The combination of satellite-borne passive and active sensors to be deployed provides critical and unique information regarding the 3D distributions of precipitation and latent heating in tropical regions. Coincident measurements are complementary: passive microwave radiometers measure radiances that result from integrated effects of electromagnetic absorption-emission and scattering through the precipitating cloud along the sensor viewpath. The frequency dependence of electromagnetic properties of cloud and precipitation particles allows for the design of multichannel passive microwave radiometers which can "sound" to different depths in a precipitating cloud, as we have seen other multispectral sounders operate. However the determination of the height of these cloud properties is more difficult. Active microwave sensors (radars) yield more specific height information using the time delay of the precipitation-backscattered return power. However, the TRMM PR only operates at one transmitting/receiving frequency and polarization. To retrieve unambiguous precipitation water content profiles from these radars, secondary signal effects such as path attenuation must be determined independently. The VIRS on TRMM adds cloud-top temperatures and structures to complement the description of the two microwave sensors. VIRS serves an important role as a bridge between the high quality but infrequent observations TRMM from TMI and longer time series data available from the geostationary visible and ir channels. The lightning sensor maps the frequency of lightning events, and plays a role in coupling the occurrence of lightning to the precipitation, enhancing our overall understanding of both processes. The CERES instrument allows for determination of the total radiant energy balance. Together with the latent heating derived from the precipitation, a better estimate of atmospheric energy balance can be derived.
Explanation of Why the TRMM Satellite was needed (from the NASA TRMM Link provided above)
Solar heating of the Earth occurs mostly in the tropics, much of which is
covered by ocean. Oceanic surface currents, such as the Atlantic Gulf Stream
and the Pacific Kuroshio current, transport some of that heat away from the
tropics to influence the climate at mid-latitudes. Oceans store heat in the
summer and release it during the remainder of the year, so that oceanic heat
moderates land temperatures, especially at mid-latitudes. When ocean surface
currents fluctuate, as occurs during El Niño events, the climatic
effects can be disastrous and widespread. The amount and rate of heat transferred
between the Earth and atmosphere is determined by both conduction, which
contributes about 2/3 of the total incident solar energy, and by evaporation
which accounts for the remaining third. Water vapor, having absorbed heat
from the evaporative process, can be transported far from the site of its
origin.
Upon cooling, when moisture laden air
is saturated and the vapor that it contained condenses, rain is produced
and the heat that was originally used to evaporate the water from the Earth's
surface is released into the atmosphere. The rate of energy release for each
mm/hour of rainfall is three times as great as the solar energy (~350 Watts/m2)
that falls on the same surface area. Thus the precipitation process concentrates
heat that was used to evaporate moisture from large expanses of the tropics
by factors of ten to a hundred into those regions where rain occurs. While
solar heating of the atmosphere takes place mainly at the surface, the heat
released by condensation occurs at high altitudes where it has a greater
impact on the atmosphere's large scale circulation. Averaged over the entire
Earth the heating released by precipitation is about five times greater than
that produced by variations in surface heating.
As of late 1997, measurements of the global distribution of rainfall at the
Earth's surface had uncertainties of the order of 50% and the global distribution
of vertical profiles of precipitation was far less well determined.
Summary of TRMM benefits
TRMM, during its three-year mission and broad sampling footprint between
35°N and 35°S, will provide the first detailed and comprehensive
dataset on the four dimensional distribution of rainfall and latent heating
over vastly undersampled oceanic and tropical continental regimes. Combined
with concurrent measurement of the atmosphere's radiation budget, estimates
of the total diabatic heating will be realized for the first time ever on
a global scale.
TRMM will fill many gaps in our
understanding of rainfall properties and their variation. These includes
frequency distributions of rainfall intensity and areal coverage;
the partitioning of rainfall into convective and stratiform categories;
the vertical distribution of hydrometeors (including the structure and intensity of the stratiform region bright band); and
variation of the timing of heaviest rainfall - particularly nocturnal intensification of large mesoscale convective systems over the oceans, and diurnal intensification of orographically and sea-breezed forced systems over land.
TRMM will enable mapping of larger time and space variations of rainfall
in quasi-periodic circulation anomalies, such as the Madden-Julian oscillation
in the western Pacific and ENSO over the broader Pacific basin. Furthermore,
the critical onset of large annual circulation regimes, such as the Asian
summer monsoon, can be more thoroughly studied;
Cumulus heating is the principal driver of regional and global-scale atmospheric
circulations. For example, it is known that the phase speed of the intraseasonal
oscillation (ISO) is highly sensitive to the height of the condensation heating
maximum. Diagnostic budgets of sensible heat source (as inferred from research
networks of soundings) are incomplete in their global coverage and inadequate
to describe the large day-to-day variations that occur in the tropics. Nor
can these networks completely capture the significant structural variations
that occur in heating and cooling profiles between convective and stratiform
rainfall regions. Intensive and globally-distributed observations from TRMM,
however, will be crucial for the formulation of reliable cumulus parameterization
schemes contained in the latest generation of global cloud models (GCMs);
Sensitivity tests using assimilation of latent heating estimates in GCMs
has revealed the potential for improving the prediction of rainfall events.
For example, GCM 24-h rainfall predictions using initial conditions adjusted
from simulated profiles of TRMM latent heating may be improved by as much
as 30% over NMC and ECMWF models.
Example Data Validation Experiment: Currentposted Mon Apr 13 17:00:50 1998 PDT
The TExas and FLorida UNderflights (TEFLUN) Experiment is a mission to obtain validation measurements for the Tropical Rain Measuring Mission (TRMM). TRMM is a NASA and National Space Development Agency of Japan (NASDA) coordinated mission that launched the TRMM satellite on 28 November 1997 with a unique complement of sensors to remotely observe rainfall throughout the global tropics. TEFLUN is the first in a series of experiments using a combination of airborne and surface-based measurements to complement the satellite data. Among these, are important measurements aboard the NASA high-altitude aircraft, similar to those on the TRMM satellite. They are used for direct intercomparisons with TRMM overflights where possible, but more frequently to simulate TRMM data by flying over precipitation systems within the experimental domain. These, along with surface-based measurements and computer models, will make unique contributions to our understanding of the tropical precipitation cycle.
TRMM field campaigns (FCs) aim at validation of the ground validation products derived from radars and rain gauges, TRMM-derived Levels 2 and 3 rain and rain profile products, and vertical profiles of latent heating. Since latent heating profiles cannot be directly measured, numerical cloud models are used in TRMM algorithms to provide the link between the latent heating profiles, TRMM radar and radiometer observations. Consequently, an important part of the campaign is to provide comprehensive observations of the structure and evolution of Mesoscale Convective Systems (MCS), individual convective events, and their environment. Cloud and mesoscale models require these data sets for initialization and the subsequent model results must be validated for realism of vertical structure and latent heating. While the TRMM instantaneous and monthly algorithms can be evaluated through intercomparison with ground validation (GV) and other data sets, the campaigns will provide additional observations required for a more thorough validation and guidance for improving the algorithms.
The overarching scientific objective of TEFLUN is to obtain a database suitable for case studies of a few MCSs, early in the TRMM lifetime, from which cloud-resolving models and forward radiative transfer models can be used to understand and improve the performance of the satellite and GV algorithms.
Perform underflights of TRMM by the ER-2 and DC-8 with high-resolution radar and passive microwave instruments to assist in evaluating the effects of resolution and sensitivity on algorithms using the Precipitation Radar (PR) and TRMM Microwave Imager (TMI) data. (Since underflight opportunities are limited, similar flight lines to simulate TRMM data should be performed over precipitation targets more frequently.)
Evaluate and improve algorithms using ground-based radar data [i.e., GV algorithms] for estimating rain rates, vertical profiles of hydrometors, and separation of convective and stratiform precipitation regions by using a combination of augmented ground-based measurements and aircraft overflights.
Provide guidance for improving the assumptions in algorithms using TRMM satellite data as inputs to estimate rainfall and latent heating profiles, particularly the ones which involve microphysics, i.e., vertical distribution of hydrometeors.
TEFLUN-A will be conducted between April 1 and May 15, 1998, principally focused on the Texas ground validation site. The NASA ER-2 aircraft participation is planned for April 8 - May 8, 1998 based at Eglin AFB, FL. A cloud physics aircraft based within or near the TX site will also participate. There is close coordination with the Houston and other WSR-88Ds, the Texas A&M ADRAD Doppler radar, the NOAA ETL X-band polarization radar (X- POL), and the NOAA AL Profiler system. These ground-based facilities are integrated with dense rain gauge networks and disdrometers. Soundings will be obtained from two mobile systems to provide initialization and validation data for models at strategic times and locations.
TEFLUN-A ER-2 FLIGHT TRACK - 980418
posted Sat Apr 18 09:44:10 1998 PDT
![]() |
| Storm activity over the Houston, Tx. and Lake Charles, La. area. |
![]() |
| Storm activity over Louisiana, Arkansas, & Alabama. |
Investigate complex mixed stratiform and convective
precipitation bands in vicinity of Houston over
X-POL and AL Profiler sites.
The ER-2 takeoff was delayed a half-hour from the originally scheduled time because of instrument problems. The ER-2 was airborne at 16:31 UTC (11:30 CDT) and proceeded to the prescribed point of 2900 N, 92-00 W where radio contact was made with the ground site. The pilot proceeded with the original 120 NM SE-NW (A:28 45 N 94 15 W, B:30 26 N 96 00 W ) track over the ground sites. At point B the ER-2 was met by the cloud physics Lear jet and proceeded back to point A together. Upon returning to point B, the ER-2 was instructed to fly an almost E-W (C: 2945 N 9530 W, D:2919 N 9308 W ) track while the Lear continued along the original A-B track (tracks crossed at the AL Profiler site). After flying C-D,D-C, and C-D again, the ER-2 was called home due to the conditions and forecast at Eglin AFB turning for the worst. The ER-2 landed safely at 21:40 UTC (4:40 CDT). Post-flight showed that although many instruments did have problems, the critical instruments worked well, and overall the mission was deemed a success. TEFLUN Project office / message phone (850) 882-8991
NESDIS/ORA
Microwave Remote Sensing
Group
Sensor
The Special Sensor Microwave/Imager(SSM/I) onboard the DMSP platform is a
sensor which became operational in July 1987 on the F-8 satellite. Subsequent
SSM/I's have been flown on the F- 10 (November 1990), F-11 (December 1991),
F-12 (August 1994), and most recently, F-13 (March 1995) satellites. At present,
the F-10 and F-13 satellites are operational. The SSM/I is a seven channel
passive
microwave
radiometer operating at four frequencies (19,35, 22,235, 37.0,
and 85.5 GHz) and dual- polarization (except at 22.235 GHz which is
V-polarization only), and has many potential uses.
Platform
The Defense Meteorological Satellite Program (DMSP) is a Department of Defense (DoD) program run by the Air Force and Missle Systems Center (MSC). The DMSP program designs, builds, launches and maintains sun synchronous polar orbiting satellites for monitoring of meteorological, oceanographic, and solar-terrestrial physics environments. Each satellite has an orbit altitude of approximately 830 km above the Earth, and has an orbital period of about 101 minutes. Data from the DMSP satellites is received and used at operational centers continuously.
Data collected from the SSM/I are used to estimate several geophysical parameters including:
Rainfall Rate
Rainfall Frequency
Cloud Liquid Water
Cloudiness Frequency
Total Precipitable Water
Snow Cover
Sea-Ice
Sampling Frequency
Ocean Surface Wind Speed (1.0 degree only!)
These products are useful for evaluating the mean climate state, it's interannual and seasonal variations, and the detection of anomalies associated with ENSO and regional climatic variations. The Microwave Sensing Group has assembled a time series of the entire SSM/I archive, which includes data from July 1987 to the present. Monthly average products are produced for precipitation, cloud liquid water, total precipitable water, snow cover, sea-ice cover, and oceanic surface wind speed.
A good overview of the products available from the SSM/I can be found in the May 1996 Bulletin of the American Meteorological Society:
"An Eight Year (1987-1994) Time Series of Rainfall, Clouds, Water Vapor, Snow-cover, and Sea-ice Derived from SSM/I Measurements" by R. Ferraro, F. Weng, N. Grody, and A. Basist"
SSM/I Data Products
Daily Products |
The daily products page contains data for the seven SSM/I microwave channels. Each image has grid spacing of one-third degree and spans 1080 columns and 540 rows. Data for the last seven days are available to browse for any of the 7 channel measurements. Daily products are also now available for browsing. These include snow cover, rain rate and total precipitable water. |
Monthly Products |
Monthly
products at 2.5 degree spatial resolution consist of a time series
of data from July 1987 - present for Rainfall,Rain
Frequency,Cloud Liquid Water,Cloudiness Fraction,Total
Precipitable Water,Snow Cover,Sea-Ice,Sampling
Frequency, Ocean Surface Wind Speed.
These
monthly 1.0 degree products span over the last four operational satellites
(F-8, F-11, F-13, and F-14). |
Monthly Climate Anomalies |
Monthly Climate Anomalies indicate a departure from the climate mean. Anomalies are usefiul in monitoring changes in weather. Of particular interest right now is El Nino. We are including global monthly departures in rainfall amounts and Total Precipitable Water for those interested in keeping up with this phemonenom. |