Passive microwave measurements from the AMSR-E instrument on NASA’s Aqua satellite are used to estimate in precipitation associated with weather systems outside the range of land-based radars. In the image above, AMSR-E produces a radar-time analysis of rain associated with Hurricane Katia. Note the intense convective storms just north of Puerto Rico. Could this be another storm developing?
As T.S. Lee strengthens just off the Gulf Coast, the NASA instruments on the Aqua satellite capture dramatic images of the storm. The color enhanced infrared image from MODIS shows the regions of the coldest cloud tops in the storm where the rainfall is likely to be most intense. The companion image from AMSR-E at the same time shows the observed instantaneous rainfall from the storm. This rainfall information is particularly valuable to local forecasters to identify regions for flood and flooding potential, especially from portions of the storm outside land-based radars.
AMSR-E precipitation estimates give forecasters additional information on storm intensity. Note the differences in rain location in the AMSR-E image above and the cold cloud top temperatures in the MODIS infrared image below. Both of these Aqua instruments captured storm information simultaneously while orbiting over Irene early in the afternoon on August 26, 2011.
The AMSR-E instrument on the NASA Aqua satellite provides an instantaneous rain rate product. Outside of radar range, Tropical Storm Don is seen by AMSR-E. Note there is a large area of 1 in/hr rainfall occurring with maximum rates near 1.5 in/hr in a few pixels. While this data is not available as quickly as radar data, it may provide valuable information in radar void areas of the Gulf of Mexico, the Southwest or in areas between radars where rainfall estimates may be less accurate. In flash flooding situations, the AMSR-E data can be compared to radar estimates as little as 2 hours after the event (NASA/LANCE). If large differences are seen, one may determine if further actions are warranted due to the affects of more or less rainfall on the flooding situation.
The 19 May SPoRT run of the Weather Research and Forecasting (WRF) model captured a band of strong convection that developed in advance of a dryline across Kansas and Oklahoma. The mode and orientation of the convection appeared quite similar to the observed radar reflectivity in the late afternoon and evening hours. On the multi-model comparison page as part of the 2011 Hazardous Weather Testbed’s Spring Experiment, the SPoRT-WRF model is compared to the National Severe Storms Laboratory (NSSL) and the National Center for Atmospheric Research (NCAR) WRF runs. For this particular day, the SPoRT-WRF best captured the intensity and timing of the convection over Oklahoma and parts of Kansas during the late afternoon and evening hours (see Figure below of reflectivity comparisons valid at 0000 UTC 20 May 2011). The SPoRT WRF model configuration is nearly identical to the NSSL configuration, but incorporates real-time MODIS vegetation fraction, high-resolution land surface initialization data from the NASA Land Information System, MODIS/AMSR-E SSTs, and also assimilates AIRS temperature and moisture profiles to improve initial conditions and subsequent forecast parameters. Of course, this is only one case; SPoRT team members plan to continue examining the model comparisons throughout the duration of the Spring Experiment and beyond.
This post is a follow-on to both GaryJ’s comments on this morning’s LIS snow water equivalent (SWE) post, and to the post on MODIS snow cover mapping. I went ahead and produced a LIS SWE graphic at 1900 UTC 31 JAN 2010, approximately coincident to the time of the MODIS false color snow map (1919 UTC) and geographical area.
The image below shows the output from the 3-km SPoRT LIS that could be used to help quantify the actual water content of the snow cover. Compared to the MODIS false color image in the previous post, it appears that the LIS-Noah SWE coverage may be slightly overdone on the southern edge of the swath from Arkansas to Georgia. This is probably due to the fact that the Noah land surface model running within LIS adds to the SWE field anytime the land surface temperature is below freezing. Therefore, areas of mixed precipitation or freezing rain also lead to an accumulation of the SWE field.
A unique product that may be worth considering is to supplement the MODIS snow mask with quantitative information from LIS within the mask indicated by MODIS. Another option may be to assimilate AMSR-E SWE information to help adjust the LIS SWE field towards the satellite observations.