Time scales in energy balance climate models: 2. The intermediate time solutions

1994 ◽  
Vol 99 (D2) ◽  
pp. 3643 ◽  
Author(s):  
Michael C. Morantine ◽  
Robert G. Watts
Keyword(s):  
Energy Balance ◽  
Time Scales ◽  
Climate Models ◽  
Intermediate Time

scholarly journals Motility at the Origin of Life: Its Characterization and a Model

2014 ◽  
Vol 20 (1) ◽  
pp. 55-76 ◽  
Author(s):  
Tom Froese ◽  
Nathaniel Virgo ◽  
Takashi Ikegami
Keyword(s):  
Origin Of Life ◽  
Time Scales ◽  
Morphological Changes ◽  
Reaction Diffusion ◽  
Dissipative Structures ◽  
Reaction Diffusion Systems ◽  
Diffusion Systems ◽  
Inclusive Approach ◽  
Intermediate Time ◽  
The Origin Of Life

Due to recent advances in synthetic biology and artificial life, the origin of life is currently a hot topic of research. We review the literature and argue that the two traditionally competing replicator-first and metabolism-first approaches are merging into one integrated theory of individuation and evolution. We contribute to the maturation of this more inclusive approach by highlighting some problematic assumptions that still lead to an ximpoverished conception of the phenomenon of life. In particular, we argue that the new consensus has so far failed to consider the relevance of intermediate time scales. We propose that an adequate theory of life must account for the fact that all living beings are situated in at least four distinct time scales, which are typically associated with metabolism, motility, development, and evolution. In this view, self-movement, adaptive behavior, and morphological changes could have already been present at the origin of life. In order to illustrate this possibility, we analyze a minimal model of lifelike phenomena, namely, of precarious, individuated, dissipative structures that can be found in simple reaction-diffusion systems. Based on our analysis, we suggest that processes on intermediate time scales could have already been operative in prebiotic systems. They may have facilitated and constrained changes occurring in the faster- and slower-paced time scales of chemical self-individuation and evolution by natural selection, respectively.

Revisiting albedo from a fuzzy perspective

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Morteza Pakdaman ◽  
Majid Habibi Nokhandan ◽  
Yashar Falamarzi
Keyword(s):  
Differential Equation ◽  
Energy Balance ◽  
Fuzzy Number ◽  
Climate Models ◽  
Energy Balance Model ◽  
Fuzzy Differential Equation ◽  
Balance Model ◽  
Content Type ◽  
Fuzzy Energy ◽  
Fuzzy Derivative

PurposeThe aim of this paper is to revisit the albedo for uncertainty. The albedo is considered as a fuzzy value due to some realistic reasons which they will be discussed in details. After defining an appropriate uncertain albedo by using fuzzy set theory, the related energy balance model is also redefined as a fuzzy differential equation by using the concept of fuzzy derivative.Design/methodology/approachThe well-known Earth energy balance model is redefined as a fuzzy differential equation by using the concept of fuzzy derivative. Thus, instead of an ordinary differential equation, a fuzzy differential equation arises which it's solution procedure will be discussed in details.FindingsResults indicate that the fuzzy uncertainty for albedo causes more real results after solving the fuzzy energy balance equation. Considering albedo as a fuzzy number is more realistic than considering a single certain number for albedo of a surface. This is due to this fact that the Earth's surface coverage is not crisp and the boundaries of different types of lands are not consistent. The proposed approach of this paper can help us to provide more realistic climate models and construct dynamical models which can model the albedo based on its variability.Originality/valueIn this paper, we defined fuzzy energy balance model as a fuzzy differential equation for the first time. We also, considered albedo as a fuzzy number which is another novel approach.

scholarly journals The cloud-free global energy balance and inferred cloud radiative effects: an assessment based on direct observations and climate models

2018 ◽  
Vol 52 (7-8) ◽  
pp. 4787-4812 ◽  
Author(s):  
Martin Wild ◽  
Maria Z. Hakuba ◽  
Doris Folini ◽  
Patricia Dörig-Ott ◽  
Christoph Schär ◽  
...  
Keyword(s):  
Energy Balance ◽  
Climate Models ◽  
Radiative Effects ◽  
Global Energy ◽  
Global Energy Balance ◽  
Direct Observations ◽  
Cloud Radiative Effects

Multiscale Convective Organization and the YOTC Virtual Global Field Campaign

2012 ◽  
Vol 93 (8) ◽  
pp. 1171-1187 ◽  
Author(s):  
Mitchell W. Moncrieff ◽  
Duane E. Waliser ◽  
Martin J. Miller ◽  
Melvyn A. Shapiro ◽  
Ghassem R. Asrar ◽  
...  
Keyword(s):  
Time Scales ◽  
Climate Models ◽  
Water Cycle ◽  
Building Blocks ◽  
Tropical Convection ◽  
Global Water Cycle ◽  
Weather And Climate ◽  
Impact Phenomena ◽  
Meteorological Systems ◽  
The Tropics

The Year of Tropical Convection (YOTC) project recognizes that major improvements are needed in how the tropics are represented in climate models. Tropical convection is organized into multiscale precipitation systems with an underlying chaotic order. These organized systems act as building blocks for meteorological events at the intersection of weather and climate (time scales up to seasonal). These events affect a large percentage of the world's population. Much of the uncertainty associated with weather and climate derives from incomplete understanding of how meteorological systems on the mesoscale (~1–100 km), synoptic scale (~1,000 km), and planetary scale (~10,000 km) interact with each other. This uncertainty complicates attempts to predict high-impact phenomena associated with the tropical atmosphere, such as tropical cyclones, the Madden–Julian oscillation, convectively coupled tropical waves, and the monsoons. These and other phenomena influence the extratropics by migrating out of the tropics and by the remote effects of planetary waves, including those generated by the MJO. The diurnal and seasonal cycles modulate all of the above. It will be impossible to accurately predict climate on regional scales or to comprehend the variability of the global water cycle in a warmer world without comprehensively addressing tropical convection and its interactions across space and time scales.

scholarly journals A general framework for understanding the response of the water cycle to global warming over land and ocean

2013 ◽  
Vol 10 (12) ◽  
pp. 15263-15294 ◽  
Author(s):  
M. L. Roderick ◽  
F. Sun ◽  
W. H. Lim ◽  
G. D. Farquhar
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Surface Energy Balance ◽  
Climate Models ◽  
Climate Model ◽  
Water Cycle ◽  
Specific Humidity ◽  
Water Vapour Content ◽  
Long Wave ◽  
Small Change

Abstract. Climate models project increases in globally averaged atmospheric specific humidity at the Clausius–Clapeyron (CC) value of around 7% K−1 whilst projections for precipitation (P) and evaporation (E) are somewhat muted at around 2% K−1. Such global projections are useful summaries but do not provide guidance at local (grid box) scales where impacts occur. To bridge that gap in spatial scale, previous research has shown that the following relation, Δ(P − E) ∝ P − E, holds for zonal averages in climate model projections. In this paper we first test whether that relation holds at grid box scales over ocean and over land. We find that the zonally averaged relation does not hold at grid box scales. We further find that the zonally averaged relation does not hold over land – it is specific to zonal averages over the ocean. As an alternative we tested whether the long-standing Budyko framework of catchment hydrology could be used to synthesise climate model projections over land. We find that climate model projections of Δ(P − E) out to the year 2100 conform closely to the Budyko framework. The analysis also revealed that climate models project little change in the net irradiance at the surface. To understand that result we examined projections of the key surface energy balance terms. In terms of global averages, we find the climate model projections are dominated by changes in only three terms of the surface energy balance; an increase in the incoming longwave irradiance while the responses are (mostly) restricted to the outgoing longwave irradiance with a small change in the evaporative flux. Because the change in outgoing longwave irradiance is a function of the change in surface temperature, we show that the precipitation sensitivity (i.e. 2% K−1) is an accurate summary of the partitioning of the greenhouse-induced surface forcing. With that we demonstrate that the precipitation sensitivity (2% K−1) is less than the CC value (7% K−1) because most of the greenhouse-induced surface forcing is partitioned into outgoing longwave irradiance (instead of evaporation). In essence, the models respond to elevated [CO2] by an increase in atmospheric water vapour content that increases the incoming long-wave irradiance at the surface. The surface response is dominated by a near equal increase in outgoing long-wave irradiance with only minor changes in other terms of the surface energy balance.

scholarly journals Stochastic energy balance climate models with Legendre weighted diffusion and an additive cylindrical Wiener process forcing

2021 ◽  
Vol 0 (0) ◽  
pp. 0
Author(s):  
Gregorio Díaz ◽  
Jesús Ildefonso Díaz
Keyword(s):  
Energy Balance ◽  
Wiener Process ◽  
Climate Models ◽  
Random Parameter ◽  
Parabolic Problems ◽  
Change Of Variables ◽  
Wiener Processes ◽  
Cylindrical Wiener Process ◽  
The Stability ◽  
Suitable Change

<p style='text-indent:20px;'>We consider a class of one-dimensional nonlinear stochastic parabolic problems associated to Sellers and Budyko diffusive energy balance climate models with a Legendre weighted diffusion and an additive cylindrical Wiener processes forcing. Our results use in an important way that, under suitable assumptions on the Wiener processes, a suitable change of variables leads the problem to a pathwise random PDE, hence an essentially "deterministic" formulation depending on a random parameter. Two applications are also given: the stability of solutions when the Wiener process converges to zero and the asymptotic behaviour of solutions for large time.</p>

scholarly journals A Tropospheric Emission Spectrometer HDO/H<sub>2</sub>O retrieval simulator for climate models

2012 ◽  
Vol 12 (6) ◽  
pp. 13827-13880
Author(s):  
R. D. Field ◽  
C. Risi ◽  
G. A. Schmidt ◽  
J. Worden ◽  
A. Voulgarakis ◽  
...  
Keyword(s):  
Time Scales ◽  
General Circulation ◽  
Climate Models ◽  
Circulation Model ◽  
Satellite Measurement ◽  
Climate Simulations ◽  
Accurate Comparison ◽  
Free Running ◽  
The Tropics ◽  
Short Time

Abstract. Retrievals of the isotopic composition of water vapor from the Aura Tropospheric Emission Spectrometer (TES) have unique value in constraining moist processes in climate models. Accurate comparison between simulated and retrieved values requires that model profiles that would be poorly retrieved are excluded, and that an instrument operator be applied to the remaining profiles. Typically, this is done by sampling model output at satellite measurement points and using the quality flags and averaging kernels from individual retrievals at specific places and times. This approach is not reliable when the modeled meteorological conditions influencing retrieval sensitivity are different from those observed by the instrument at short time scales, which will be the case for free-running climate simulations. In this study, we describe an alternative, "categorical" approach to applying the instrument operator, implemented within the NASA GISS ModelE general circulation model. Retrieval quality and averaging kernel structure are predicted empirically from model conditions, rather than obtained from collocated satellite observations. This approach can be used for arbitrary model configurations, and requires no agreement between satellite-retrieved and modeled meteorology at short time scales. To test this approach, nudged simulations were conducted using both the retrieval-based and categorical operators. Cloud cover, surface temperature and free-tropospheric moisture content were the most important predictors of retrieval quality and averaging kernel structure. There was good agreement between the δD fields after applying the retrieval-based and more detailed categorical operators, with increases of up to 30‰ over the ocean and decreases of up to 40‰ over land relative to the raw model fields. The categorical operator performed better over the ocean than over land, and requires further refinement for use outside of the tropics. After applying the TES operator, ModelE had δD biases of −8‰ over ocean and −34‰ over land compared to TES δD, which were less than the biases using raw modeled δD fields.

scholarly journals Diagnosis of Multiyear Predictability on Continental Scales

2011 ◽  
Vol 24 (19) ◽  
pp. 5108-5124 ◽  
Author(s):  
Liwei Jia ◽  
Timothy DelSole
Keyword(s):  
Time Scales ◽  
Air Temperature ◽  
Climate Models ◽  
Coupled Model ◽  
Surface Air Temperature ◽  
Optimization Method ◽  
First Year ◽  
Temperature And Precipitation ◽  
Regional Prediction ◽  
Intercomparison Project

A new statistical optimization method is used to identify components of surface air temperature and precipitation on six continents that are predictable in multiple climate models on multiyear time scales. The components are identified from unforced “control runs” of the Coupled Model Intercomparison Project phase 3 dataset. The leading predictable components can be calculated in independent control runs with statistically significant skill for 3–6 yr for surface air temperature and 1–3 yr for precipitation, depending on the continent, using a linear regression model with global sea surface temperature (SST) as a predictor. Typically, lag-correlation maps reveal that the leading predictable components of surface air temperature are related to two types of SST patterns: persistent patterns near the continent itself and an oscillatory ENSO-like pattern. The only exception is Europe, which has no significant ENSO relation. The leading predictable components of precipitation are significantly correlated with an ENSO-like SST pattern. No multiyear predictability of land precipitation could be verified in Europe. The squared multiple correlations of surface air temperature and precipitation for nonzero lags on each continent are less than 0.4 in the first year, implying that less than 40% of variations of the leading predictable component can be predicted from global SST. The predictable components describe the spatial structures that can be predicted on multiyear time scales in the absence of anthropogenic and natural forcing, and thus provide a scientific rationale for regional prediction on multiyear time scales.

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