Presentation on theme: "Basic Tools in Meteorology and Climatology René Garreaud www.dgf.uchile.cl/rene."— Presentation transcript:
Basic Tools in Meteorology and Climatology René Garreaud www.dgf.uchile.cl/rene
Since pressure always decrease with height, sometimes we use pressure as the vertical coordinate (instead of m ASL). In this case, geopotential height (Z) is a variable. For instance, at the 500 hPa level, Z usually varies between 5300-5600 m. Atmospheric pressure: Weight of the air column above you Units: hPa = mb = 100 Pa = 100 * N/m 2 p(z) p 0 exp(-z/H*) ~ 1013*exp(z/8000) [hPa if z in meters], H* = R[T]/g height scale
Air temperature ~ kinetic energy of air molecules Changes because heat flux divergence Radiosonde (p,T,RH,…) with height Average (time, space) temperature profile of the earth atmosphere. Note and explain the three maxima. T usually decrease with height (unstable condition) Inversion layers (stable air) where T increase with height
ff [m/s] dd [°] streamline Local wind u > 0 v > 0 u < 0 v < 0 u < 0 v < 0 Blowing from….SW SE NE Wind is a vector: magnitude (speed) and blowing direction (° wrt north) Alternatively, zonal ( u, west-east) and meridional ( v, south-north) components
Mapa de Observaciones Carta del tiempo Every day meteorologist have quite a lot of data that need to be synthesized to detect weather patterns. Analysis: Hand-made (old) or objective (computer)
Isobars: lines of constant pressure at a given level (e.g. sea level pressure chart) and time (snapshot). High (anticyclones) and Low (cyclones) pressure centers. H H L L SLP map, October 17 2010
Isotherms: lines of constant air temperature at a given level (z or p) and time (snapshot). The temperature field usually decreases poleward and often exhibits elongated bands of strong thermal gradient (baroclinicity) called fronts T @ 850 hPa (1500 m ASL) October 17, 2010
Wind @ 300 hPa (9000 m ASL) Map showing wind vectors (arrows) and wind speed (colors) Note the presence of wind maxima (jet streams) Jet stream Mostly zonal flow Mostly meridional flow
XX: Lines of constant geopotential height at a given pressure level Trough: relative minimum pressure. Ridge: relative maximum pressure In both cases “relative” looking at a same latitude Z @ 300 hPa (9000 m ASL) Trough Ridge
pi 1 = pi 2 = pi 3 pi 1 > pi 2 < pi 3 ps 1 = ps 2 = ps 3 ps 1 ps 3 p sup p inf C What causes the pressure gradients (or geopotential gradients) in the atmosphere? Case 1: Thermal contrasts. Combining hydrostatic and ideal gas equations one can show: Z = RTg -1 *log 10 (p inf /p sup ) 1.Inicialmente, las tres columnas son identicas 2.La columna central se calienta diferencialmente 3.Aire en col. más cálida se expande... Aparece gradiente de presión en altura 4.Viento diverge, sacando masa de la columna 5.Presión cae en superficie...parece gradiente cerca de la superficie 6.Viento converge, agregando masa de la columna
0 km 12 km L H L H Warmer Cooler The mass field (pressure) adjust rapidly to the thermal forcing Note that pressure remains unchanged at the level of warming Eventually, atmospheric circulation will flatten pressure field Z = RTg -1 *log 10 (p inf /p sup )
We now can reinterpret troughs and ridges seen in the geopotential height in the upper troposphere (e.g., 300 hPa) as tongues of cold air abnormally at low latitudes and warm air abnormally at high latitudes Geopotential @ 300 hPa (contours) Air temperature averaged between 700 and 400 hPa (colors)
Trayectoria desde sistema terrestre t = 0 t = dT Trayectoria desde sistema inercial F h =0 Observador en Tierra Air will flow from high pressure areas toward low pressure areas Earth rotation, however, complicate things…apparently Earth rotation introduce an apparent force that deviate air parcels from its expected trajectory. This force is called the Coriolis force and obeys the following rules: Acts over moving air and water parcels Deflects air parcels to the left in the SH (right in the NH) Its magnitude is zero at the equator and increase to a maximum at the poles. Partículas flotando sobre superficie parten impulsivamente al ecuador….
AAA En el ecuador o en planeta sin rotación Muy cerca del ecuador o rotación planetaria muy lenta Lejos del ecuador (>20 ) para movimientos lentos ¿Como circula el aire en torno a los centros de alta y baja presión (HS)? B B B Air will flow from high pressure areas toward low pressure areas Earth rotation, however, complicate things…apparently
Atmospheric dynamics (same for ocean) Second Newton’s law: Which in the atmosphere becomes... Scale analysis for large-scale flow leads to… So we can define the geostrophic wind, very close to actual wind in large scale systems Coriolis Pressure gradient Friction
H L H Geostrophic wind (close to actual wind) rules of operation (SH): Clock-wise around a low, anti-clockwise around a high Stronger in areas of tight isobars (or geopotential lines) Not very usefull at low latitudes
B A B B B A A Isobaras ¿Porque nos gustan tanto los mapas del tiempo?
Climate data issues Temporal resolution (daily, monthly, yearly) Temporal coverage and continuity Quality and QControl Station data versus gridded products Spatial context Multi variable records (T, P, ….) Data sources Data formats (ASCII, NC, never Excel!) Data sharing etiquette
Surface (land/ocean) Synoptic Stations Met. Observations (T,Td,P,V,…) @ 0, 6, 12, 18 UTC are transmitted in real-time to WMO and Analysis Centers From where do we get climate data? Almost all climate data is initially meteorological data, acquired to assist weather nowcast and forecast (especially for aviation)
Red de Radiosondas (OMM, GTS) Perfiles verticales (20 km) de T, HR, viento, presión, cada 12 / 24 hr
All stations (anytime, any length) Century-long stations (Ti 1995, missdata<20%) Precipitation Mean Temperature Global Historical Climate Network (GHCN)
Surface and Upper Air Observations Satellite Products Assimilation system Gridded Analysis Gridding method DATA SOURCES AND PRODUCTS
Table 1. Main features of datasets commonly used in climate studies DatasetKey references Input data - Variables Spatial resolution - Coverage Time span - Time resolution Station GHCN Peterson and Vose (1997) Sfc. Obs Precip and SAT N/A Land only 1850(*) – present Daily and Monthly Gridded GHCN Peterson and Vose (1997) Sfc. Obs Precip and SAT 5° 5° lat-lon Land only 1900 – present Monthly Gridded UEA-CRU New et al. 2000 Sfc. Obs Precip and SAT 3.75° 2.5° lat-lon Land only 1900 – present Monthly Gridded UEA-CRU05 Mitchell and Jones (2005) Sfc. Obs Precip and SAT 0.5° 0.5° lat-lon Land only 1901 – present Monthly Griddded U. Delware Legates and Willmott (1999a,b) Sfc. Obs Precip and SAT 0.5° 0.5° lat-lon Land only 1950 – 1999 Monthly Gridded SAM-CDC data Liebmann and Allured (2005) Sfc. Obs Precip 1° 1° lat-lon South America 1940 – 2006 Daily and Monthly Gridded CMAP Xie and Arkin (1987) Sfc. Obs.; Sat. data Precip 2.5° 2.5° lat-lon Global 1979 – present Pentad and Monthly Gridded GCPC Adler et al. (2003) Sfc. Obs.; Sat. data Precip 2.5° 2.5° lat-lon Global 1979 – present Monthly NCEP-NCAR Reanalysis (NNR) Kalnay et al. 1996 Kistler et al. 2001 Sfc. Obs.; UA Obs; Sat. data Pressure, temp., winds, etc. 2.5° 2.5° lat-lon, 17 vertical levels Global 1948 – present 6 hr, daily, monthly ECMWF Reanalysis (ERA-40) Uppala et al. (2005) Sfc. Obs., UA Obs, Sat. data Pressure, temp., winds, etc. 2.5° 2.5° lat-lon, 17 vertical levels Global 1948 – present 6 hr, daily, monthly
Because analysis are produced in real-time, some data is not assimilated, but it was archived. In the 90’s the NCEP-NCAR (USA) began a major project in which they re-run their assimilation system with all the available data. The result is the widely used “Reanalysis” data, including many fields (air temperature, wind, pressure) on a regular 2.5°x2.5° lat-lon grid, from 1948 to present every 6 hours (also available daily, monthly and long- term-mean means). Fields are 2- or 3-Dimensional. Preferred data format: NetCDF. Freely available. Reanalysis?!
Reanalysis system also includes a meteorological model from which precipitation and other not-observed variables (e.g., vertical motion) are derived. Reanalysis data is great for studying interannual and higher frequency variability. Interdecadal variability and trends are not so well depicted (we don’t trust much before the 70’s, particularly in the SH). European Center (ECMWF) did a similar effort (ERA- 15 and ERA-40). Higher horizontal resolution (1.25°x1.25°), but harder to get. Reanalysis
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