The hydrologic cycle: a challenge to climate modelling Annarita Mariotti ENEA, Italy and ESSIC, University of Maryland, USA
Background and climatologies Relevance to climate variability Observational and modelling challenges Aspects of the variability in oceanic regions Outline
Background and general relevance Moisture is of critical importance for the Earth System: for the water budget (effects on freshwater resources, river discharge and oceanic salinity/buoyancy) for the heat budget (greenhouse effect of water vapor, latent heat moderation of temperature changes and redistribution of energy) The hydrologic cycle has fundamental influences on the planet’s atmospheric and oceanic circulation and their coupling. Its representation is essential in model simulations of climate variations.
Climatological Features ~80% of the global evaporation and ~70% of the Global precipitation occur over the oceans. Plotted: climatologies from ERA40 re-analyses, mm/d
The Atmospheric Water budget ∂w/∂t + div(Q z ) = E-P (water vapor conservation) E-P ~ div(Q z ) (monthly timescales) w, precipitable water; Q z =1/g∫qvdp; q specific humidity ∂w/∂t P E QzQz
Climatological Features Cross-equatorial atmospheric moisture flux North to South hemisphere in DJF and opposite in JJA. Plotted: E-P from ERA40 re-analyses; vertically integrated moisture flux from NCEP re-analyses ( ).
Annual mean atmospheric moisture flux is from Southern to Northern Hemispheres, about 3Sv (Mehta et al., 2005). Climatological Features
Atlantic atmospheric water fluxes Basins draining in the Atlantic (solid grey), deserts (white), other basins (shaded).Arrows give direction of atmospheric transport (SV). Overall the Atlantic loses 0.32 Sv (Broecker, 1997).
Precipitation/diabatic heating, effect the structure of the storm-tracks and are key characteristics of tropical circulations, for example: During ENSO events, precipitation/heating anomalies contribute to anomalous Walker cell/engendering Rossby waves Changes in tropical precipitation and heating, related to trends in Indian Ocean SST, have possibly had far-reaching long-term effects (Sahel droughts, NAO-trends..). Relevance to climate variability and modeling
Freshwater fluxes at the air-sea interface contribute to the interaction of atmosphere and ocean, for example: At mid/high latitudes, changes in freshwater fluxes effect salinity and have potentially important effects on the Atlantic thermohaline circulation Anomalous atmospheric moisture fluxes between the Pacific and Atlantic during ENSO events may play an important role in the inter-basin “atmospheric bridge” Relevance to climate variability and modeling
Water cycle observations - challenges Rainfall and clouds occur on small spatial and time scales Over land, rain gauge observations suffer from “undercatch” especially in windy and snowy conditions Remote sensing of frozen precipitation is still a challenge Evaporation estimates rely on “bulk” aerodynamic formulas and assumptions to parameterize turbulent processes Lack of observations, especially over the oceans and remote land regions; long-term datasets.
Water cycle observations-advances Precipitation: Land-only global datasets: CRU TS2 (high resolution), PREC/L, GHCN, many cover the 20 th century Global, satellite derived: blended analyses (CMAP, GPCP), since 1979; GPROF (SMM/I based), since Evaporation, ocean-only: in situ: COADS-UWM, since 1960 Satellite derived: GSSTF2 (SSMI/NCEP), State-of-the-art for medium to large-scale climatic studies and model validation:
Water cycle modelling – challenges ● In analyses, precipitation and evaporation are model dependent, and forecasts are affected by spin-up problems. ● Tendency to rapidly adjust the moisture fields to be compatible with models moist physics, mainly moist convection ● Overall, the global water budget is not closed ● Region dependent biases exist: many models, tend to mis-represent ITCZ precipitation; storm- tracks are also problematic ● Variability is often better represented
Water cycle modelling – Advances ● Re-analyses have provided the first stable platform for comprehensive studies of the global water cycle. ● At medium to large-scales, these have proven useful for water budget studies ● On-going model improvements include changes in the convection schemes, cloud representation and land-surface runoff ● More realistic E-P fluxes are being used in ocean simulations
DJF Precipitation climatology Climatologies for the period
JJA Precipitation climatology Climatologies for the period
Aspects of the variability in oceanic regions
ENSO and the hydrological cycle
Regression of with an ENSO index over the period , NCEP re- analyses.. ENSO and the hydrological cycle
The North Atlantic Oscillation Images courtesy Martin Visbeck Dominant mode of climate variability in the Atlantic in winter (van Loon & Rogers, 1972) Seesaw of atmospheric mass between subtropical high and subpolar low (Walker and Bliss, 1932) Controls the position of the jet stream and the characteristics of the storm tracks (Hurrell, 1995) NAO + NAO -
Characterize oceanic precipitation anomalies associated with the NAO based on state-of-the-art datasets How do the observed precipitation anomalies relate to atmospheric circulation and SST anomalies? Is there evidence of a connection with tropical climate variability? What is the impact on the oceanic water budgets? Objectives and questions
– Indices, : NAO-CPC (Barnston and Livezey, 1987); NAO-station (Jones et al., 1997); AO-CPC (Thompson and Wallace, 1998) – CMAP and GPCPv.2 merged analyses of precipitation based on satellite and gauge data (2.5°, monthly, ; Xie and Arkin, 1997 and Adler et al., 2003). – PREC/O global precipitation reconstruction (for ocean, eofs of satellite estimates with coastal/island gauge observations; for land, OI of GHCN2 gauges; Chen et al., 2003). – NCEP/NCAR reanalyses (atmospheric circulation, precipitation and evaporation, ; Kalnay et al., 1996). – ERA40 reanalyses (precipitation, ; Simmons and Gibson, 2000). – GISST SST data. Datasets
Seasonal Patterns NCEP precipitation, CPC-NAO index, From Mariotti and Arkin, 2006.
DJF pattern/various data Precipitation from NCEP, ERA40, PREC ( ) and GPCP ( ); CPC NAO index
DJF composite patterns Atmospheric data from NCEP, SST from GISST, CPC NAO index, Prec, shadedSSTs, shaded
“Key” regions of influence
34% (14%, 0.01Sv)59%(65%, Sv) 51% (33%, 0.012Sv)24%(28%, ) Oceanic water budgets - DJF Regressed precipitation anomalies for NCEP (black), ERA40 (red), PREC(green) and GPCP (blu) 15% P clim 10% P clim
Summary - I – The NAO has robust manifestations in North Atlantic Ocean precipitation (“quadrupole” pattern) and circulation during winter (explained variance is over 50% in the high-lat and sub- trop Atlantic) – In summer, the signal present (“tripole”), but weaker and displaced northward (greater sensitivity to the choice of the NAO index) – Intriguing link between NAO variability and the ITCZ in the western tropical Atlantic via anomalous easterlies. – Some connection to precipitation variability in the eastern Indian Ocean, opposite in DJF and JJA, but significance is weak.
– In the sub-tropical and high-latitude North Atlantic in winter interannual precipitation anomalies have been 15% and 10% of climatology per unit change of the NAO – Fresh water variations have been Sv and 0.012Sv respectively. – Decadal changes in the NAO index have been associated with drier (wetter) than usual winter conditions in the high-lat eastern Atlantic (Labrador) in the 1960s and late 1970s, with an opposite situation since the early 1980s – In summer the North Sea/Baltic region has been drier during the period with the NAO being positive. Summary - II
Table 2 Tropical Atlantic[60°E,40°E;12°N,23°N]0.59(34%)/0.58/ (14%)/0.42/0.37 Sub-trop. Atlantic[40°E, 5°E;30°N,45°N]0.77(59%)/0.51/ (65%)/0.76/0.85 High-lat. east. Atl.[35°E,15°E;55°N,65°N]0.72(51%)/0.80/ (33%)/0.77/0.54 Labrador Sea[67°E,57°E;55°N,72°N]0.49(24%)/0.78/ (28%)/0.74/0.59 Mediterranean Sea[10°W,27°W;37°N,45°N]0.56(31%)/0.51/ (36%)/0.64/0.64 North Sea/Baltic Sea[20°E,35°W;50°N,60°N]0.65(42%)/0.83/ (43%)/0.86/0.68 Sub-polar Atlantic[5°W,20°W;65°N,74°N]0.32(10%)/0.52/ (13%)/0.54/0.38 Eastern Indian[95°W,120°W;13°S,5°S] 0.49(24%)/0.60/ (19%)/0.57/0.39 JJA Key regionDomainP Correl.PME Correl Key region DomainP Correl.PME Correl. DJF_______________________________________________________
Table 3 [For comparison discharge from the former Nile is Sv; from the Amazon is about 0.15Sv; Mediterranean evaporative sink 0.07Sv]. Tropical Atlantic / / Sub-trop. Atlantic / / High-lat. east. Atl / / Labrador Sea / / Mediterranean Sea / / North Sea/Baltic Sea / / Sub-polar Atlantic / / Eastern Indian / / JJA Key regionP ClimΔP PME Clim ΔPME DJF_______________________________________________________
Sensitivity of the North Atlantic thermoaline circulation Stability diagram for North Atlantic Deep Water (NADW) flow as function of freshwater input (precipitation and runoff minus evaporation). The location of the present climate is not exactly known, but models generally locate it in a regime where 2 equilibria, with and without NADW formation, exist. The diagram shows that increasing the freshwater input beyond S will shut down NADW flow, while restarting it requires the freshwater input to be reduced to near zero. This diagram is based on general circulation model experiments (see Rahmstorf [1996] for details)
NCEP reanalyses Winter rainfall and the NAO seasonal correlation CRU data
Mediterranean Sea water budget Annual mean components: atmosphere: E-P ~ D sea: D-R-B ~ G
NAO index Table 1 CPC NAO/ STAT NAO CPC NAO/ AO STAT NAO/ AO DJF JJA CPC NAO black (filtered, grey) AO green STAT NAO red
JJA pattern/various indices NCEP precipitation and SLP, various NAO indices,
Oceanic water budgets - JJA 31%(36%, 0.07Sv)42%(43%, Sv) 10%(13%, 0.001Sv)24%(19%, Sv) Regressed precipitation anomalies for NCEP (black), ERA40 (red), PREC(green) and GPCP (blu)
E from COADS/UWM, P from CMAP, R from our derivation Climatological Mediterranean fresh water flux Annual mean E-P~700mm/yr
Fresh water flux variability and the NAO +300 mm/yr NCEP reanalyses, 5yr running means Potential implications for: ● Mediterranean sea level ● Atlantic circulation
Atmospheric data from NCEP, SST from GISST, CPC NAO index, JJA composite patterns