AnnaLs rif Glaciology 25 1997 Cl;; Internationa l Glaciologica l Society
Arctic precipitation as represented in the NCEPjNCAR reanalysis
MARK C. SERREZE,I JAMES A. MASLANIK2
ICoopemtive Ins/itll/ejor Research in Environmen/al SCIences, Division rifO)'osjJheric and PoLar Processes. CamjJZlS Box 449, University rifColomdo, Bouldel; CO 80309 -0449, USA.
2Colomdo CenlerJor Aslrod)mamlcs Research, Campus Box 431, Universi(y rifColomdo, BOllLder, CO 80309 -0..)31, USA.
ABSTRACT. Arctic prec ipita tion as depicted in the l\'a tiona l Center for Environmental Prediction (l\CEP) and the National Center for Atmospheric Research (NCAR) reana lysis effort is evaluated using 6 hourly model output for the period 1986- 93 in conjunction with ga uge-corrected climatologies. Climatologica l field s fi'om the model agree favo rably with observations in terms of general spatio-tempora l pa tterns, but with some notable diITerences. In pa rticul a r, the precipitat ion max imum over the centra l Arctic (the region north of 70° N ) is depicted inJuly, onc month too ea rly. Values arc too low from August through D ecember, resulting in underes timates of annua l precipitation of about 40 mm. Despite these shortcomings, the modeled precipita tion fi elds appear to be sufficiently reali stic to represent a base for blending with other data to prov ide g ridded fi eld s suitable for use in climate studies and sea-ice models.
INTRODUCTION
The Arctic sea-ice cover requires maintenance of a low-sa linity surface layer. Surface runoIT provides the largest singleocean fresh-water source of about 35 cm a I (i\agaa rd and Carmack, 1989; Iva nov and Yankina, 1991). Following freshwater import through the Bering Strait, precipitation less evaporation (P - E ) over the Arctic O cean itself provides the next la rges t contribution of \6- \7 cm a I (Serreze and others, \995). C hanges in precipitation over watersheds draining into the Arctic O cean and over the Arctic O cean itself may impact on sea-ice thickness and ice a rea, inOuencing ocean-to-atmosphere heat and Ill oisture Ou xes and, potentia ll y, cloud cover and cyclone activit y. The 0 ux of sea ice through Fram Strait a nd the Canadia n Arctic Archi pelago influences the oceanic convective regime, impacting on the g loba l thermoha line circulat ion (Za ucker and others, 1994). Arctic ma rine life is organized in to compl ex food webs, conditioned by sea ice, nutrient a\'ailability and water densit y. Changes in these factors may i m pac t on mari ne ecosys tems and the biochemical cycling of essenti a l nutrients. Changes in the terrestr ia l hydrologic cycle may a lso alter soil moisture, influencing plant cOlllmunities and their grazers. Arctic soil s and peatl and s serve as so urces and sinks of atmospheric trace gases, and appear to respond sensitively to changes in soil moisture and temperature (McCauley and Meier, 1991).
Addressing these issues requires improved databases of precipitation for model input and validation, as well as for di ag nostic climate studies. Prec ipitat ion data from Arctic land stations (Vose and others, 1992) suffer from severe under catchment in areas of blowing snow (\ Voo and others, 1983). Even in summer, estimates may be low due to neglect of occult precipitation (fog, dew) over tundra a reas (Dingman a nd others, 1980), trace val ues a nd wett ing losses. As
most Arctic stations are at low altitudes, the tendency for
prec ipitation to increase with elevation also implies an underes timate of regional averages when stat ion data a re used. It is possible to adjust station data for exposure, winds and gauge type, but the network is still relatively sparse. Databases for the Arctic O cean a re prim arily for long-term mean a nnu a l and monthl y va lues (e.g. Bryazgin, 1976; Go rshkov, 1983; Legates and Wilmott, 1990). Aerological a nalyses using the reasonably dense network of Arctic rawinsonde stations can provide estimates of P - E, but onl y la rge a rea l averages can be obtained.
MODELED PRECIPITATION FIELDS
Recognition of the need for g ridded fi elds oC Arctic precipitation has led to interest in the evalu ation of output from numerical weather prediction (NWP) models (\VCRP, 1994). Although data assimil ation/forecast sys tems vary between d ifle rent N \ VP centers, the general procedure is to sta rt with a pre\'ious forecast as a fi rst "guess" of present at mospheric conditions. Obsen 'ed data (e.g. from rawinsondes, d ropsondes a nd satell ites ) a re assi m i lated to adj ust the forecas t field s, providing ana lyses representing the best est i mate of th e current true state of the atmosphere, used to produce the next forecas t. Assimilation data are primarily free-atmosphere variables. Archived fields represent a blend of analyses based on the first guess a nd assimilation (e.g. pressure heights), a nd modeled surface \'a ri ables, including precipita tion.
Modeled surface field s for the Arctic have suffered from a number of problem s. These include the scarcity of sounding data over the central Arct ic Basin, difficulti es in quality control and in determining the appropri ate weights for observations vs first-guess fields over such data-sparse a reas, unce rta inti es in satellite-derived soundings, simplistic repre-
429
Serre;:;e and Maslanik: Arctic precipitation in NCEP/NCA R reana01sis
sentation of sea ice (genera ll y taken as a slab with fi xed thickness a nd 100% concentration), inadequate physical pa rameteri zations (pa rticul a rly with respect to clouds), radi a ti on a nd boundary-layer processes, and problems with filtering fi elds at the northernmos t rows of gridpoint models. A furth er problem is a lack of temporal consistency in archived field s due to changes introduced in models a nd data assimilation systems (WCRP, 1994).
Limited cases studies of operational NvVP output for recent yea rs a re nevertheless encouraging. Precipitation field s for April 1993 from a regiona l model of the Canadi an Atmospheric Environment Service showed very good agreement with observations (Environment Canada, 1993). In a recent WCRP Arctic C lim ate Sy tem (ACSYS) workshop (held September 1995), it was demonstrated th at precipitati on fields from United Kingdom M eteorological Office (UKMO ) and Europea n Center for Medium-Range Weather Forecas ts (ECMvVF) model s provide realistic spati o-tempora l patterns in qua li tati ve agreement with ex isting clim atologies (H. Cattle, persona l communication, 1995).
"Reanalysis" projects underway at several agencies a re prov iding internally con istent g ridded fi elds. Although still prone to many of the problems outlined above, including si mpl istic treatments of sea ice, they should provide improved a rchived fi elds through: I) the elimination of tempora l discontinuiti es through the use of "frozen" state-of-the-art data ass imilation/forecast systems; and 2) the assurance that all available historical data a re used in the assimilations, a nd a re subj ected to strict qualit y control. The most comprehensive of these projects represents a cooperati ve efTort between the Ja tional Center for Envi ronmental Prediction (NCEP form erly the Nationa l Meteorological Center) and the la tiona l Center for Atmospheric Research (NCAR).
The NCEP/NCAR proj ect a imed to complete the reana lysis for a 40 year time period (1957- 96) by the end of 1996. Deta il s of the re analysis system a re prov ided by Kalnay and others (1996).
The qua lity of reana lysis prec ipita tion fi elds remains
la rgely untested for the Arctic. A case stud y using NCEP/ NCAR output over the M ackenzie watershed for 1985 a nd 1986 (J. Walsh, personal communication, 1995 shows the seasona l cycles and spati al pa tterns of precipita tion to be reali stic, but with the model totals g reater than from uncorrected station data . As station va lues a re considered to be
underestimates, this difference is in the "correct" direction. However, the la rgest di screpa ncies occur during spring a nd summer, when most prec ipitati on would be in the liquid form. Precipitation patterns over Greenl and and Antarctica, examined using 6 years of ECMvVF rean alysis data, appear reali stic (Genthon and Braun, 1995).
H ere, we provide an initial evaluation of Arctic precipitation as depicted in the NCEP/NCAR reanalysis over the 8 yea r period 1986- 93 for the region north of 60° N . We use the 6 hourl y instantaneous precipitati on ra tes (in kg m 2 S i),
which a re provided over a 192 x 94 gaussian grid. The instantaneous rates were converted into monthl y precipitation
tota ls by month and year. Comparisons are made with severa l gauge-corrected cli matologies, including the map of a nnual tota ls provided by Bryazgi n (1976), based on data from fi xed sta tions, a ircra ft landings a nd the Russian No rth Pole series of manned drifting camps (1916- 74). We al so use monthly means north or70° N based on the Gorshkov (1983) a tl as, which according to Burova (1983), rely on Bryazgin's (1976) results, as well as a recentl y acquired set of gauge-
430
cor rected monthly maps by Bryazgin (1976), updated using data through 1990.
RESULTS
Annual field
Figure I shows the spati a l di stribution of modeled annual prec ipita ti on averaged over the 8 years while Figure 2 provides the a nnual gauge-corrected map of Bryazgin (1976). The reana lysis fi elds were interpolated to the NMC octagona l grid using Cressman weights with a 500 km sphere of influence. This smoo thing eliminates loca l "bull's-eyes" in precipita tion that appear to result from spectral truncati on er rors. The m odel depicts the highest tota ls over the Atlanti c side of the Arcti c. Maximum va lues a re found off the so utheast coas t of Greenl and (1400 mm ), with amounts decreasing to the northeast. Thi s pattern is physicall y consistent with the efTects of the frequent cyc lone acti vity associated with the mean Icelandic Low, and the poleward decay of the North Atlantic cyclone track (Serreze, 1995). High tota ls (up to 1200 mm ) a re a lso depicted near the edge of the map over southern Alas ka, which refl ects the influence of the Aleutian Low and orography. The lowest values (150-200 mm ) a re found over the Beaufort Sea, pa rts of the Canadian Arctic Archipelago, the East Siberi an Sea a nd northern Greenland. These a re regions of infrequent cyclone activity for most of the yea r, and where anticyclonic conditions are common during winter and spring (Serreze and others, 1993).
Fig. 1. Mean annual precipitation (1986- 93) fro m the NCEP/NCA R reanalysis ( in mm).
Although the Bryazgin (1976) climatology is based on data from a difTerent period a nd the gauge corrections employed a re not well documented, comparisons indicate that the model is capturing the mqjor spatial patterns of precipitation reasonably well. In particul a r, the model correctl y depicts precipitation maxim a over the Atl antic side of the Arcti c and southern Alas ka, and low central Arctic values. Nevertheless, there a re some notable differences. In particul ar, Bryazgin (1976) shows high precipitation values (> 400 mm) along the Atlantic side of the Arctic penetrating as fa r as Novaya Zeml ya . The model also fa il s to capture
.'
.....• ~
Fig. 2. M ean annual gauge-corrected precipitation (1916- 74)
redrawn after B lyazgin (1976) (in mm).
precipita ti on maxima related to local orography, such as along the Scandinavian coast, as well as over Iceland, Sva lbard a nd Novaya Zemlya. This is likely to be related to the rela ti vely low (T 62) model resolution, as well as to the smoothing employed here. Nevertheless, these initia l results must be considered encouraging.
Seasonality and inter-annual variability
Figure 3 shows the modeled average precipi ta tion fi elds for J a nuary andJuly. TheJanuary pattern (Fig. 3a) is simila r to tha t for the annual field , with the highest total s over the Atlantic side (up to 200 mm near the position of the Icelan
dic Low) and southern Al aska. By contrast, July (Fig. 3b ) shows a reduction in Atlantic-side precipitation, coupled with increases over the central Arctic Ocean, Eurasia, central Alaska and Canada. These results a re consistent with seasona l changes in atm ospheric circulation (Whittaker and
H orn, 1984; Serreze and others, 1993; Serreze, 1995). During January, the primary North Atlantic cyclone
track and the Icelandic and Aleutian Lows are strong, with the a ffected areas receiving relatively abundant precipitation. During summer, the North Atlantic track a nd subpola r lows weaken, but with cyclone activity becoming common over northern Eurasia, Canada and Al aska. Eura
sian systems in particul a r tend to migrate into the central Arctic O cean, where they subsequently occlude. While lows may enter the Arctic O cean from anywhere along the Eurasian coast, a Laptev Sea track is preferred.
Bryazgin's (1976) updated monthly analyses agree with the model in showing aJanuary precipitation of 10- 20 mm over the centra l Arctic O cean increas ing towards the Atlantic side, but again di splay higher values along the Scandinavian coast. Bryazgin's (1976) data also show a reduction in July precipitati on over the Atlantic side, with increases over the centra l Arctic O cean, but with lower amounts (30 mm)
than in the reana lysis (30- 40 mm ). Bryazgin's maps also di splay sharp increases over land, especially the local maxima over Alas ka and eastern Eurasia, which are regions of frequent summertime cyclogenesis (Serreze, 1995).
The spatial pattern of the month of the precipita ti on maximum (Fig. 4), calculated for each N MC gridpoint from
Serreze and Maslanik: Arctic precipitation in NCEP/ NCA R reanarysis
Fig. 3. Mean precipitation (1986- 93) from the NCEP/ NCA R reanafysis ( in mm) Jor ( a) J anua1), and (b) J ury.
the long-term monthly means, shows two maj or features: I) an O ctober-january maximum over the Atlantic side of the Arctic a nd the Baffin BayjDavis Stra it region; and 2) a June- September maximum over the remainder of the
Arctic, with a spatially homogeneous July peak [or the centra l Arctic O cean. A recent analysis (Cl a rk a nd others, 1996) o[ precipitati on frequencies over the Arctic O cean and its periphera l seas, evaluated from present weather reports conta ined in the Comprehensive Ocea n Atl11.osphere Da taset (COADS ) (Woodruff and others, 1987), shows this Atlantic-side win ter m aximum clearly. The timing of this maximum a lso agrees with the updated monthly maps of Bryazgin (1976). However, it appears that the model's July peak precipitation over the central Arcti c Ocean is in error by at leas t a month.
This is illustrated in Figure 5, which shows the long-term
(1986- 93) monthly reanalysis precipita ti on averaged for the centra l Arctic, taken as the region north of 70° N, the maximum and minimum values based on individua l years, and the climatologica l monthly nl.eans from Gorshkov (1983). FromJanuary through April, the reana lysis means are low, but high from May throughJuly. Despite these differences,
431
Sareze and A1aslanik: Arctic precipitation in NCEPjNCA R rea1la01sis
./ .. ]
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.. ·7' " 6' ·T .. "]" ·· ·· ..
'r;" 6 '·. 6 6 7 7 7 .: 7 '7 ..
7 .7' " 7 '·
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.. '{1~· 1 ··
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ri.g. .f.. Month of the precipitation maxil71umji'Olll the NCEPj . yeA R reana0lsis, based on long-term (1986- 93) monlh£JI means. The solid line sej)amles regions with October-.7anuar)1 andJlIIze-September maxima.
40
35
E 30 E ....., c: .Q !§ "6. "0 Q) "-
Cl..
25
2 4 6 8 Month
10 12
Fig. 5. l'vI.ean monthb precipitation jor the Tegion north ()[ 70° N as dep icted by Gorshkov (1983) (dashed line) and in the NCEPjNCAR reanaOlsis (solid line). The range in the reanaOlsis values over tlze 1986- 93 is shown by the vertical Lines ended by dots (all vaLues ill mm ).
the J anua ry- July reana lysis total s can be considered quite reasonable. H owever, the model shows a very sharp precipita ti on peak inJul y, a month ea rlier than shown the data preented by Gorshkov (1983), remaining far below hi s values
through December. Even the positive ex tremes of the reanalysis precipitati on arc lower tha n the Gorshkov means from August through O ctober. As shown in the monthly time se ries ofmodeled precipi tation (Fig. 6), thi sJuly peak is persistent from year to year. Due largely to the underestimates from August through December, the model's a nnual-precipi
tation total [or the centra l Arctic region is 250 mm, as compared to 293 mm from the Gorshkov a tl as. Interestingly,
432
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50r------------------------------------
40
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:9. 20 f\j\ o ~
Cl.. ~·V
o 86
:.'.: .:
Month
93
Fig. 6. Time series q/lI1onlh!)1 precipitation fin the period 1986- 93 ji-Oln the NCEPjNCA R reanalysis Jar the region north of 70° N ( in mm ).
nca rly a ll models reviewed as part of the Atmospheri c ~Iode l Tnlercomparison Prqjee l (AMIP) display an Aug ust prec ipit ati on maximum for the central Arctic (Kallsov a nd others, in press). Note a lso that the August peak depicted by these models occurs a month ea rli er than the September
peak in the water vapor nu x convergence a nd P - E [or the region north of 70° N as ana lyzed from rawinsonde data (Ser rcze and others, 1995).
DISCUSSION
Based on our initi a l study, the performance o[ the NCEPI NCAR reanalysis to depict Arctic precipitation could perhaps best be described as uneven. The spatial patterns of long- term annual and monthly precipitation agree reasonably well with avail able climatologies, although there are
some notable differences. In particular, the annual peak in prec ipitation over the centra l Arctic O cean occurs too early in July with la rge underes tim ates from August through December. \Ve recogni ze the poss ibili ty that the 8 yea rs (1986- 93) examined here might not be sufficiently long enough [or effective comparisons with observed c1imatolo
gies o r the AMIP outputs, wh ich span the period 1979- 88 (K attsov a nd others, in press).
The past decade has been anomalous in terms of Arctic circu lation (Nlas lanik a nd others, 1996; ' '''alsh and others, 1996). H owever, thi s per iod has been cha racterized by sharp increases in cyclone activity and accompanying recluctions
in sea-level pressure over the central Arctic O cean, which, a /)1'iol'i, suggest that precipitat ion over the centra l Arctic has recently been above norma l. Resolving this issue wi ll require further investigations using additiona l reanalys is data, as we ll as efforts to assess the model's treatment of high-l atitude
hyd rologic processes. D espite the shortcoming in the modeled fi elds, we echo
the recommenda ti ons of the WCRP (WCRP, 1994) to examine methods of blending the reana lysis precipitation fi elds with observed data. Efforts a re underway by C. vVillmott at the University of Delaware to compute monthly gauge-corrected precipitation fi elds [or Arctic land a reas, bui lding on
techniques outlined by Legates a nd Wilmott (1990). Using such field s, along with the upda ted el imatological month ly
means from Bryazgin for the Arctic Ocean, and gaugecorrected station data, techniques such as optimal interpolation could be applied to obtain gridded fields for use 111
climate studies and sea-ice models.
ACKNOWLEDGEMENTS
Thi s study was supported by NSF grants ATM-9315351, OPP-950420l and OPP-9614297.
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