A global modeler looks at regional climate modeling. Zippy:Regional_Climate_01:Regional_Climate_01.frame

Transcription

1 A global modeler looks at regional climate modeling

2 I come in peace.

3 Global climate models, 1 All global climate models must include representations of the ocean, sea ice, and the vegetated land surface, in addition to the troposphere and stratosphere. Important physical processes that must be included include dynamics, radiation, cloud formation and dissipation, turbulence, and photosynthesis. Climate is all about sources and sinks of energy, water, momentum, etc. Time scales of primary interest range from the seasonal cycle, to interannual variations, to decadal variability, to century-scale climate change, to Milankovitch cycles. A long run is a few simulated centuries. On computers currently available in the U.S., such a run takes weeks or even months to complete.

4 Global climate models, 2 Current resolutions of the atmospheric components of climate models are on the order of T42 to T63. This means grid cells a few hundred km across. The whole state of Colorado is represented by just a few grid cells. In the next five years we will see climate models with atmospheric grid cells on the order of 100 km across. This is the current niche of regional climate models. These highresolution global models will be used to investigate climate dynamics on the shorter end of the time scales listed above. We will not see century-scale climate simulations with atmosphere-model grid sizes on the order of 10 km or less in the near future. Such models may be developed by today s graduate students, as they near the ends of their careers.

5 120 km hexagonal mesh

6 Questions that can be attacked using global climate models What are the processes that maintain a given climate state, including the variability within that state? How does the climate state respond to variable forcings? Variable forcings include the seasonal cycle, volcanos, human activities, and Milankovitch cycles.

7 What are regional climates? Main Entry: re gion (noun) 1: an administrative area, division, or district; especially: the basic administrative unit for local government in Scotland 2 a: an indefinite area of the world or universe <few unknown regions left on earth> b: a broad geographical area distinguished by similar features <the Appalachian region> c (1): a major world area that supports a characteristic fauna (2): an area characterized by the prevalence of one or more vegetational climax types

8 What are regional climates? Climates vary regionally due to regional forcings, such as orography, land-water contrasts, urban effects, and islands. Orographic effects Lake effects Such regional forcings can produce statistically predictable effects on the weather, i.e., they can produce regional climate anomalies.

9 Regional climates 1 Examples of regional climate anomalies include: Orographic precipitation Many other orographic effects Sea breezes Lake effect precipitation anomalies Urban heat islands It seems quite likely that some regional climate anomalies, e.g. precipitation maxima over mountain ranges, can feed back to significantly affect the climate on larger scales. There have been few studies to date that quantify such effects, however.

10

11 Regional climates 2 A pragmatic definition of regional climate can be given in terms of spatial scales that global climate models cannot currently simulate. It might be possible to formulate a more physical definition of regional climate in terms of the spheres of influence of specific regional climate forcings, e.g. lakes, mountains, coasts, cities, etc. From this point of view, in the absence of regional forcings, (e.g. in the middle of the Pacific far from islands) there are no regional climates.

12 Simulating regional climates For the practical reasons mentioned earlier, global models cannot be used to simulate regional climates in the near future. At present, regional climates are simulated using highresolution models that are driven at their boundaries with and/or nudged towards observations or with the output of a lower-resolution global climate model. Most regional climate models have grid sizes on the order of km. For purposes of this talk I assume that the results produced by the regional climate model do not feed back to affect the output of the lower-resolution global climate model.

13 Limitations of fixed boundary forcing When boundary forcing is fixed, the lateral fluxes into and out of a region are fixed. This strongly constrains the integral properties of the regional simulation. For example, moisture fluxes on the boundary fix the time-averaged difference between precipitation and evaporation. Therefore a regional climate model cannot predict changes in the domain-average of P - E. A regional climate model can predict how P and E are distributed inside the region, however. Nudging constrains the integral properties of the regional simulation in much the same way as prescribed boundary fluxes.

14 Leung et al., 1999

15 Parameterization for high-resolution models What do grid-cell values represent? Area averages? Time averages? Ensemble averages? In coarse-resolution models these amount to the same thing, but not in fine-resolution models. How can we parameterize sub-grid variability when we do not even know what the grid values represent? With sufficiently small grid cells it makes no sense to parameterize convection, but it is still necessary to parameterize clouds. On horizontal scales comparable to the depth of the troposphere, convection produces important transports in the horizontal as well as the vertical. Good-bye to column physics! Parameterization for regional climate models is much more difficult than parameterization for global models.

16 Scalable parameterizations Is it possible to devise parameterizations that are applicable in models with a wide range of grid sizes? What would such parameterizations look like?

17 A cloud is a cloud In the global modeling community, the interactions between convective and stratiform clouds are increasingly recognized as very close and important. Convective clouds generate stratiform clouds. Almost all stratiform clouds contain convective turbulence. This suggests that we should try to devise a single parameterization that can represent the effects of both stratiform and convective clouds. Such a unified cloud parameterization can help to bridge the gap between coarse- and fine-resolution models, because on sufficiently fine scales all clouds are stratiform.

18 Cloud-System Models Cloud-resolving models (CSMs) are being used to study the dynamics of cloud processes that are parameterized in global climate models and in regional climate models. Global climate models Regional climate models Cloudresolving models

19 Super-Parameterizations A CSM can be viewed as a super-parameterization. Wojciech Grabowski has run with this idea. Others will follow. A CSM represents the state of the cloud field through a large number of dynamically coupled prognostic variables -- namely, the grid cell variables of the CSM. This suggests that future cloud parameterizations should include prognostic variables to represent the state of the cloud field. We are already seeing movement in this direction, with prognostic cumulus closures and prognostic turbulence closures.

20

21 Conclusions and suggestions Global climate models will soon use resolutions comparable to current regional climate models. Regional climate models must use higher resolution. Think big. In the global modeling community, a big simulation takes weeks or months to perform. Parameterizations for fine-resolution regional climate models must meet more demanding requirements than the corresponding parameterizations for coarser-resolution global models. Regional climate modeling must therefore include a strong component of parameterization development research, and in fact it can lead the way for the global models.

22