South American Climate of the LGM: A Regional Modeling Study Kerry H. Cook Department of Earth and Atmospheric Sciences Cornell University Thanks to Edward Vizy and Nancy Saltzman

Goal: Explain the Climate Dynamics behind LGM Aridity Patterns

…. and temperature reconstructions as well

Regional climate modeling on a large domain - MM5 modified for climate applications in the tropics km horizontal resolution; 23 vertical levels; 1 min time step Year-long integrations with climatology used for initial and boundary conditions: u, v, T, q, and surface conditions Regional model domain and topography; shading interval is every 500 meters.

Validation of the present day simulation: Precipitation Jan July ObservationsClimate Model

August September October

DJF 850 hPa geopotential heights (m) and winds (m/s) from the (a) 1949 –2002 NCAR/NCEP reanalysis, (b) MM5 present day simulation interpolated to NCEP’s 2.5   2.5  grid, and present day PMIP simulations from (c) ECHAM3 (fixed SSTs), (d) UGAMP (fixed SSTs), (e) UKMO (calculated SSTs), and (f) GFDL (calculated SSTs). The regional model represents the present day South American climatology much more accurately than the GCM simulations that have been used to study paleoclimate. Using GCM lateral boundary conditions degrades the present day simulation significantly. This presents a problem: We can’t use GCM lateral boundary conditions for our LGM simulations. What to do?

Simulation of the LGM Climate: SSTs Vegetation (land use) Atmospheric CO2 Orbital parameters Initial conditions Lateral boundary conditions

Surface Boundary conditions: Vegetation Present day: USGSLGM: Crowley (2000)

We ran simulations with each of these LGM SST anomalies, and compared the results with the land- based proxy data. 2 of the SST distribu- tions essentially shut down the monsoon. “Line” and CLIMAP produced similar results. We chose “line”. CLIMAP 1981 “Core”, Schäfer-Neth and Paul (2003) “Line”, Paul and Schäfer-Neth (2003) GCM, Shin et al.(2003)

Back to the problem of the lateral boundary conditions: Using GCM conditions on the lateral boundaries seriously degrades the simulation of South American climate. (Also found by Seth and Rojas 2004, and more generally by Pielke et al 2005). In setting the lateral boundary conditions for the LGM simulations, we are not too concerned about eliminating remote effects on South American climate more concerned about the consistency between the LGM SSTs and the atmosphere on the boundaries and over the “nudging” region.

Modify the present day lateral boundary conditions so they are dynamically consistent with the LGM surface boundary conditions (SSTs). Ran model with present day lateral boundary conditions Used interior points to develop a method to modify the points on the boundary: - adjust low-level temperature, retain lapse rate - test for geostrophy (reasonable except within a few degrees of equator) - adjust surface wind based on interior points, and use the thermal wind relation to propagate the difference vertically - assume constant relative (not absolute) humidity The resulting differences in the lateral boundary conditions were small everywhere except over the tropical Atlantic. But the modeled LGM solution with present day lateral boundary conditions captured this as well.

P – E Differences Precipitation Differences LGM minus Present Day Simulations

Solid: Present dayDashed: LGM Monthly Mean Precipitation (mm/day) Region 1 Region 2 Region 3 Region 4

Simulated Winds and Specific Humidity at 850 hPa: October Present day LGM

Vertical Profile of Moist Static Energy at 5ºS and 60ºW March, present day “dry” –“wet” MSE increasing with height => stability; low-level decreases in MSE stabilize the atmosphere against convection Solid: MSE Dash : sensible Dot/dash: latent Dot: geopot MSE = c p T+Lq+gz

Moist static energy Sensible heat content Latent heat content Differences in MSE (solid), sensible (dashed) and latent heat (dotted) terms

P-E Difference A region without increased aridity during the LGM

Annual precipitation differences from the present day simulation LGM SST forcing alone LGM vegetation forcing alone (a deforestation experiment)

Precipitation in Region 5 Present day Full LGM Present day LGM veg alone LGM SST alone

A close up view of Region 5 in May Surface elevation and 910 hPa winds Precipitation differences in May … agrees with Roni’s result that how deforestation occurs is relevant to the sign of the precipitation response

surface temperature differences870 hPa height and wind anoms Difference between LGM-vegetation-only and precipitation simulations May

Vizy, E.K., and K.H. Cook, 2005: Evaluation of LGM SST reconstructions through their influence on South American climate. In press at J. Geophysical Research – Atmospheres. Cook, K.H., and E. K. Vizy, 2005: South American climate during the Last Glacial Maximum: Delayed onset of the South American monsoon. Submitted to J. Geophysical Research – Atmospheres. Current projects: (1) Dynamical interactions between the high Andes and the rest of South America. What is the paleo-record in the high Andes telling us about the Amazon and subtropical South America? (2) Work with a PVM to explore consistency between prescribed vegetation forcing and the modeled climate, and translate climate into potential vegetation. That was an overview of recent results:

Landuse categories: 6 urban/cropland 7 grassland, 8 shrubland 10 savanna, 13 evergreen broadleaf forest, 14 evergreen needleleaf forest 16 water, 19 barren or sparsely vegetated 20 tundra 24 snow/ice Present day simulation LGM Simulation 60 km outer grid resolution with 20-km resolution nested

Topography

Precipitation is not Validating Well in the High Andes Nested Domain in the Present Day Simulation

We are not capturing the wetting signal in the high Andes in the LGM simulation 20-km resolution is not fine enough for this simulation design ….

Another project underway …. using a PVM to translate the climate produced by the regional climate model into vegetation categories (1) To provide a more direct comparison with some of the geological proxy data (2) To better understand the implications of the climate differences simulated by the model (3) To “free” ourselves from uncertainties in specifying the vegetation distribution in simulating LGM climate (iteration)

Potential Vegetation Model (Oyama and Nobre 2004)

Left: initial vegetation Right: vegetation after one iteration Top: “Core” LGM SSTs Bottom: “Line” LGM SSTs

Top: One iteration from Crowley initial vegetation, LGM SSTs Bottom: One iteration from Present day initial vegetation, LGM SSTs Different initial conditions on vegetation might cause differ- ent solutions, as in Oyama and Nobre Esp. note the eastern Amazon.

. Even if we use present day SSTs and this initial vegetation, the eastern Amazon does not become forested.

Cutoffs for rainforest: TC  15.5C h  0.8 s  0.81 s = seasonality index h = wetness index

Conclusions A somewhat different modeling approach to studying paleoclimate, using regional models and our knowledge of how the present day climate works to evaluate the quality of the paleoclimate simulation. (We are working on LGM South America and the AHP.) The approach has plusses and minus – as do other approaches to understanding paleoclimate such as GCM modeling and the analysis of various proxies. Compared with GCMs: + Better simulation of South American climate, finer resolution, able to resolve interactions across space scales (relatively large domain with a relatively fine resolution). - global teleconnections are not considered

Compared with proxy data: + constrained by physics (Navier-Stokes eqns), produces fields that are internally consistent - model dependent results We need all of these approaches. We find that – There is large-scale drying in the Amazon basin during the LGM, delivered in the form of annual precipitation reductions on the order of 30%. In the Southern Hemisphere, this drying is due primarily to a shortening of the rainy season, and a lengthening of the dry season. The shortening of the dry season is caused by a delay in the onset of the monsoon. The monsoon starts later because the tropical Atlantic is cool, so the buildup of moisture/MSE is delayed.

Cooling of more than about 2K in the tropical Atlantic shuts downs the monsoon completely in this model. In the Northern Hemisphere, in which summer precipitation is more ITCZ-like in its circulation, drying is also due to the fact that the low-level convergence is dryer – again associated with cool tropical Atlantic. We find that the first-order forcing is from the SSTs, but there are interesting and important regional responses related to vegetation forcing. For example, the region of increased precipitation along the Equator when the large-scale circulation anomaly interacts with a Regional orographic feature.