Model:

MERRA (MODERN-ERA RETROSPECTIVE ANALYSIS FOR RESEARCH AND APPLICATIONS)

Ververst:
hourly to monthly from 1980 to last month
Greenwich Mean Time:
12:00 UTC = 13:00 MET
Resolutie:
0.5° x 0.65°
Parameter:
Verticale beweging op 700 hPa in hPa/h
Beschrijving:
De verticale beweging van de lucht bepaald in hoofdlijnen het weer op een bepaalde plaats. Stijgende luchtbeweging (negatieve waardes in de kaart) veroorzaakt meestal bewolking en vaak ook neerslag, terwijl dalende luchtbeweging (positieve waardes in de kaart) voor oplossende bewolking en zonnig weer zorgt. Bij zeer sterke verticale luchtbeweging hoort in principe onweer en zwaar weer. Door de combinatie met vertical 925 kan met zien of ook in diepere lagen al forse stijgbeweging optreedt. Bij vermenigvuldiging van de waardes in (hPa/h) met ongeveer 0.3 krijgt men als resultaat de verticale wind in cm/s. De verticale beweging is de som van vorticiteits- en temperatuuradvectie. Deze twee kunnen afzonderlijk groot zijn en elkaar deels of geheel opheffen.
MERRA:
The MERRA time period covers the modern era of remotely sensed data, from 1979 through the present, and the special focus of the atmospheric assimilation is the hydrological cycle. Previous long-term reanalyses of the Earth's climate had high levels of uncertainty in precipitation and inter-annual variability. The GEOS-5 data assimilation system used for MERRA implements Incremental Analysis Updates (IAU) to slowly adjust the model states toward the observed state. The water cycle benefits as unrealistic spin down is minimized. In addition, the model physical parameterizations have been tested and evaluated in a data assimilation context, which also reduces the shock of adjusting the model system. Land surface processes are modeled with the state-of-the-art GEOS-5 Catchment hydrology land surface model. MERRA thus makes significant advances in the representation of the water cycle in reanalyses.
Reanalyse:
Retrospective-analyses (or reanalyses) integrate a variety of observing systems with numerical models to produce a temporally and spatially consistent synthesis of observations and analyses of variables not easily observed. The breadth of variables, as well as observational influence, make reanalyses ideal for investigating climate variability. The Modern Era-Retrospective Analysis for Research and Applications supports NASA's Earth science objectives, by applying the state-of-the-art GEOS-5 data assimilation system that includes many modern observing systems (such as EOS) in a climate framework.