A National Strategy for Advancing Climate Modeling (2012) / Chapter Skim
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5 Integrated Climate Observing System and Earth System Analysis
5 Integrated Climate Observing System and Earth System Analysis
Pages 109-128
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From page 109... ...
Knowing how the measurements of today relate to those of years or decades ago is a very important component of climate science. Another challenge for a climate observing system is that monitoring climate involves measuring many more variables than for monitoring weather.
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From page 110... ...
Some observation systems critical for model evaluation and improvement are at risk, either because they require substantial investments that cannot be done incrementally, or because budget constraints and aging equipment have gradually reduced capabilities or data quality to unacceptable levels. While nations have continued to recognize the importance of climate observations, for example through acceptance of the Global Climate Observing System (GCOS)
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From page 111... ...
On the positive side, GCOS (2009) concluded both operational and research networks and systems were increasingly responsive to needs for climate data and information, including the need for timely data exchange, and that space agencies had improved mission continuity observational capability, data reprocessing, product generation, and access.
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From page 112... ...
. Because coupled climate models can drift if one component of the system is poorly represented, subsystems that are poorly initialized, modeled, or constrained can compromise the full climate solution.
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From page 113... ...
. The spatial density of required data depends on the application and on the resolution of climate models in the coming decades (see below)
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From page 114... ...
concept. The key aim of a CPT is to bridge gaps among field and remote sensing observation programs, process modelers, and global modelers by building new communities, in which those with observational expertise and data, those with highly detailed process models, and those building global models work together to address systematically the issues that most limit progress in improving global climate models.
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From page 115... ...
There are many candidate processes to be considered by future CPTs, for example: tropical convection, radiative transfer processes, aerosol indirect effects, cloud microphysics, land-surface processes including soil moisture and ice, ocean mesoscale eddy processes, sea-ice processes, equatorial ocean upwelling and mixing, Southern Ocean ventilation and deepwater formation, atmospheric gravity waves, air-sea fluxes, and ice-sheet dynamics.
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From page 116... ...
Sea ice and open water conditions affect heat and moisture advection to the ice sheets, affecting snow accumulation and melt, so sea-ice concentration and coastal wind patterns need to be well resolved and constrained, as do the larger-scale cyclonic systems that deliver heat and moisture to the ice sheets. In addition, ocean mesoscale circulation patterns that move warm water from depth into contact with sea ice, marine-based outlet glaciers, and ice shelves play a leading role in interannual sea- and land-ice mass balance variability (e.g., Holland et al., 2008)
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From page 117... ...
A single or limited number of recommended data sets that best represents each ECV would be helpful for climate model validation and intercomparison exercises. One example highlighting data set differences and the need for data assessment and intercomparison is the study of 20th-century sea-surface temperature (SST)
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From page 118... ...
show results from six different SST products and highlight a number of significant differences among them. Ongoing improvements to measurement capability and resolution for a number of climate fields will also facilitate improvements in the climate models.
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From page 119... ...
Over the past several years GRACE data have provided important insights into many features of the global climate, including the hydrologic cycle, sea-level rise, and mass balance of the polar ice sheets. The prognostic capability of climate models and ESMs hinges on the quality of such observational data sets and their ability to provide insight into these and other essential Earth system processes.
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From page 120... ...
. These are the meteorological events that impact society the most and, thus, are needed for informed decision making, but the observing system and climate models themselves are ill equipped to capture and simulate extreme conditions.
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From page 121... ...
The past decade has seen a proliferation of efforts to synthesize these diverse observations into a common framework to produce global synoptic data sets for evaluating the atmospheric, oceanic, and terrestrial components of climate and Earth system models. Such global analyses of climate fields have supported many needs of the research and climate modeling communities.
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From page 123... ...
. AIRS/IASI, Atmospheric Infrared Sounder/ Infrared Atmospheric Sounding Interferometer; AMV, Atmospheric Motion Vector; ATOVS, Advanced TIROS (Television Infrared Observation Satellite) Operational Vertical Sounder; GPSRO, Global Positioning System Radio Occultation; TMI, TRMM (Tropical Rainfall measuring Mission)
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From page 124... ...
Data assimilation efforts have grown in the United States, for instance, and now include assimilation of data for weather (e.g., National Centers for Environmental Prediction) , seasonal-to-interannual climate variability (e.g., Climate Prediction Center)
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From page 125... ...
Finding 5.5: Assessments of data sets, of individual variables, and of reanalyses are essential to ensure quality data for the evaluation and development of climate models. THE WAY FORWARD Earth is observed more extensively today than at any other time, but many of the observations are not of sufficient quality to monitor long-term climate variability and change.
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From page 126... ...
Both confrontation of climate model simulations with climate observations and enhanced communication between the modeling and observational communities are critical for assessing model performance, for improving the representation of physical processes in the models, and in some cases for identifying problems with observational data sets. The assimilation of observations into models exploits known relationships among the different climate variables to select or reject the observations and to propagate and/or extrapolate the observations into data gaps in space or time.
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From page 127... ...
provide "expert-user" guidance and advice on the strengths and limitations of selected observational data sets and their applicability to model evaluations. Another effort in its early stages is "Obs4MIPs," which is an attempt to provide modeling groups with a limited collection of well-established and documented data sets that have been organized according to the CMIP5 model output requirements.4 More activities along these lines should be supported, because they are vital to the integrity of observational, modeling, and prediction studies of climate variability and change. Climate data archives are scattered among federal agencies, laboratories, universities, and other repositories (also discussed in Chapter 10)
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From page 128... ...
Recommendation 5.2: To better synthesize the diversity of climate-relevant observations, the United States should establish a national Earth system data assimilation effort that builds from existing efforts and merges weather observations, satellite radiances or retrievals for precipitation and various trace constituents, ocean measurements, and land and other observations into the same Earth system model simultaneously. Recommendation 5.3: Building from existing efforts, the United States should develop a national IT infrastructure for Earth system data so as to facilitate and accelerate data display, visualization, and analysis.
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