Land Interaction Processes

MERRA Production has been moving along steadily, still on track for a continuous time teries (1979-2006) to be available in early August. Data (missing 1988, 1997, 2005) is presently available for download, see the MERRA home page for access information.

With much of the record available, comparisons to previous studies of reanalyses are possible. For example, there has been a lot of work on the land interaction processes in NCEP and ERA40. Betts and Viterbo (2005) has defined cloud albedo as an observable diagnostic of the all-sky radiative forcing of the surface (Acld = -{SWDNsfc-SWDNsfcclr}/SWDNsfcclr). Below is an example of the cloud albedo comparison for ISCCP and ERA 40 over the Madeira basin, followed by a similar figure for MERRA. ERA40 tends to overestimate the cloud albedo, while MERRA underestimates it. This indicates that for the Madeira, the shortwave at the surface is

too close to the clear sky values. This bias is especially pronounced during the austral winter and less so in summer.

In evaluating the coupling processes, the links between the surface, surface layer and boundary layer relate to precipitation. Below, Betts (2009) shows the relationships of boundary layer (through LCL height in pressure thickness), surface layer (EF, evaporative fraction) and soil wetness (SMI). While lower wetness is often and indicator of higher LCL and lower precipitation, there is a range in the characteristic values. EF results are similar. The LCL - wetness connection in MERRA appears stronger and more linear than that of ERA40, where the MERA LCL height is almost double that determined from ERA40. (Note that the soil moisture index in Betts 2009 is not the same as the MERRA surface soild wetness, the SMI cannot be easily reproduced in MERRA data). The MERRA relationship between LCL and EF is much tighter than that shown for ERA40.

In the figures above, the colors indicate the amount of daily preciitation that occurs relative to the LCL and Wetness/EF values. For the MERRA figures, the dots are each daily mean showing the range in the data, and for ERA40, the range it demonstrated by the error bars.

Betts, A. K., 2009: Land surface coupling in observations and models. J. Adv. Model. Earth Sys. Articles in Press.

Betts, A. K. and P. Viterbo, 2005: Land-surface, boundary layer, and cloud-field coupling over the southwestern Amazon in ERA-40, J. Geophys. Res., 110, D14108, doi:10.1029/2004JD005702

March 1993 East Coast Snow

Recently, Midshipman S. Martin from the United States Naval Academy visited the GMAO, to learn about MERRA. The specific case study evaluated for a brief internship was the March 13, 1993 east coast snow storm (links to a recent Capital Gang discussion on the predictability of the storm). This was just a preliminary evaluation of how MERRA analyses represent the storm, in preparation for a senior paper.  As with the Feb 1979 storm (see the MERRA home page), we generated an animation (~8Mb) to get a sense of the storm track. 

Snowfall totals of 2 feet or more occurred at many observing stations. Below, the snowfall totals from Kocin et al (1995) are compared with MERRA. The northern extent of the heaviest snow seems to be a bit weak (in NY and western PA, for example) . The MERRA snow data was converted from snow water equivalent accumulated for the two days, and converted to snow depth using 10% snow/ice density.

At 12Z13MAR1993, the surface low was centered over Georgia, with the surface front extending southward through Florida. Aloft, the main part of the jet stream was North of the surface low, but a maximum in wind speed (likely a jet streak)was in the 300mb trough, lagging behind the surface front (below).

Looking closer at the vertical cross section through the trough and this wind maximum, we find a well defined tropopause fold associated with the 300 mb wind maximum. Below we compare the MERRA representation of the tropopause fold to a case study (1978) observed with aircraft measurements. The MERRA figure shows wind speed in black, potential temperature in dashed red and potential vorticity in shaded blue.

The main point here is that the MERRA analysis of the storm shows good dynamical structure of a very strong storm. More still would need done, evaluating the cyclogenesis, and how well the system physical processes through the lifecycle of the storm. However, this is one of the stronger examples of cyclogenesis in the MERRA period, and so another question is whether MERRA data can reproduce the dynamical structure of weaker storms. Ultimately it's a promising result so far.

Figures obtained from:

Keyser, Daniel. “Atmospheric Fronts:An Observational   Perspective.” In, Mesoscale Meteorology and Forecasting, 216–257.

Kocin, P., Schumacher, P., Morales, R., and Uccellini, L. (1995, February). Overview of the 12-14 March 1993 Superstorm. Bulletin of the American Meteorological Society, 76, 2, 165-182.

Mt Pinitubo Eruption Summer 1991

The eruption of Mt. Pinatubo in June 1991 was the second largest terrestrial eruption of the 20th century (Novaruption in 1912). This eruption ejected massive amounts of aerosols in the stratosphere. While global surface temperature dropped in the subsequent months, this caused an overall warming of the stratosphere in the tropical latitudes by several degrees due to absorption of radiation by the aerosols. Here, MERRA monthly means of 70mb temperature from August and then December of 199o are subtracted from August and December of 1991 to show that stratospheric warming by about 2 to 4 degrees C as the ejecta traversed the globe at this level during the subsequent months after the eruption.

Feb 19, 1979

The 1979 President's Day snow storm was a significant snow event in the North eastern US. This article presents an interesting review of the impact on the DC region and the modeling capability of the time. With the 30th anniversary of this storm, an animation of the MERRA depiction has been posted on the main WWW page. Here, we just compare a snapshot of the reanalysis to GOES IR imagery. The interesting part is that there is a clear break in the cloud structures of the storm develops over the Atlantic. This is not as apparent in the visible imagery (more like a continuous comma shape). MERRA cloud cover seems to catch this aspect of the storm. This data comes from the assimilation cycle of the system, forecasts for this case have not been run, but may be interesting.

The current estimate for when MERRA will catch up to real time is Fall 2009.

The MERRA cloud data is contoured from no cloud (black) to complete cover (white), the mean sea level pressure is contoured in purple. Wind barbs are colored according to the magnitude of the wind speed, and only 1 in 4 grid points are plotted.

For a study of the event, see: Bosart (1981)

MERRA Workshop Materials

The presentations from the MERRA Workshop have been posted on line at: http://gmao.gsfc.nasa.gov/research/merra/presentations/index.php

Also, the materials from the workshop, including documentation and software (Grads, with online access to the data) are also available online:

ftp://gmaoftp.gsfc.nasa.gov/pub/papers/mikeb/MERRA_Workshop/

AMS Annual Meeting - MERRA Short Course

Today, January 11, we hosted the short course on MERRA and data access. We had 15 attendees from a variety of backgrounds, research and applications, universities and government. Also, there were a range of experiences, some familiar with reanalyses some no prior experience. Our objective was to provide the basic understanding of the system, how we validate and use the data in research and how to access the data (with traditional methods, and newer online software access).

The day started with and overview of the project and the GEOS5 data assimilation system by Michele Rienecker. Michael Bosilovich presented an overview of the validation prior to starting the reanalysis and the current description of the hydrological cycle and global energy budget. Steve Berrick described the access to the data and the various portals at the MDISC. Arlindo da Silva gave a wide ranging presentation on how many different software packages can access MERRA online data.

We were pleased to have Alan Betts give a lunch time presentation covering much of the work he has done over the last 10 years working with ECMWF reanalyses data. The afternoon was reserved for some hands on data analysis and processing activities. We provided digital handouts including many of the presentations but also some software and data that the attendees could run on rented laptops (or their own).

The first hands-on exercise was reproducing some of Alan's figures of ERA land atmosphere interactions except with MERRA data. Next Arlindo da Silva discussed the regridding and reformatting of reanalyses data with the theme of "Look-Alike" imitation. In other words, making MERRA look like NCEP reanalyses (or any other reanalysis) for comparison or reading into existing software applications.

One theme of the meeting was processing data online, not downloading data, but producing the answer with online utilities. This was primarily through GrADS Data Servers (GDS) . The Look-Alike hands-on activity included a walkthrough where participants created MERRA data files from the online data servers using a command line utility (lats4d). Following that, Michael Bosilovich showed examples of using serverside calculations to improve the efficiency of online GDS calculations.

Lastly, Dana Ostrenga of the GSFC MDISC demonstrated the Giovanni access and evaluation of MERRA data, including the along track (satellite track) utility soon to be released. This will allow comparison of MERRA vertical sections compared to A Train data, such as Cloud Sat.

We are currently preparing the materials (including software and presentations) for WWW distribution and will post a message here when they are ready. The networking and online data servers performed well during these exercises.

Hurricane Andrew, Aug 1992

MERRA Stream 2 has completed through 1993. We have been looking at various weather and climate events. Hurricane Andrew was a powerful, but fairly small hurricane. MERRA's 1/2 degree resolution is likely too coarse to adequately resolve the circulation, and there is no bogus or center relocation being done in the system. Still, assimilation of observations will show some circulation or feature.

There isn't much of a circulation prior to landfall in Southern Florida. Landfall was at 9Z24Aug1992. Figure 1 shows the sea level pressure and wind barbs from 6Z the closest analysis time before landfall. The pressure center is much higher than the observed center pressure (955 mb). the center of the pressure is located south of the best track at that time. The feature that really attracted attention is the offset of the wind circulation, even further south than the pressure center, and crossing the isobars at the center.

Figure 1 MERRA Sea Level Pressure and 1000 mb wind barbs from the 6Z 24 AUG92 analysis. The blue line shows the best track befre and after landfall, with red markers at 00Zs.

A closer look at the observations being assimilated shows that ERS1 did track over the center of circulation around 6Z. Figure 2 shows all the observations accepted into the analysis. There are ERS1 wind vectors crossing the center of the circulation, and the assimilation system accepted the data. The vectors closest the center are likely contaminated by precipitation, and should have been rejected. At this point, it's not clear how often this kind of problem occurs, or what might be done to detect and reject the bad data. It's under investigation.
An important point for reanalysis users, especially as resolutions are increased to better resolve weather and smaller scale circulations, is that reanalyses are assimilating vast quantities of observations. sometimes poor quality data does make it into the analyses. While quality of data and analyses are improving, users still need to consider that features may or may not be realistic. Likewise, we are providing some information on the accepted observations in MERRA. More difficult is providing access to the users on the actual observations.

Figure 2. MERRA analysis sea level pressure, analysis streamlines and windbarbs showing the accepted observations (red is buoy or ship, black is ERS1). Most of the ERS1 vectors seem to agree with the mass field, however, close to the center of the low pressure the ERS1 vectors are crossing the isobars. The wind analysis is drawing to the observations, even when they disagree with the mass field.