Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userThe Trouble with Water: Condensation, Circulation and Climate
92
0
0.0
(
0
)
Authors
Geoffrey K. Vallis
Ask ChatGPT about the research
No Arabic abstract
This article discussesl a few of the problems that arise in geophysical fluid dynamics and climate that are associated with the presence of moisture in the air, its condensation and release of latent heat. Our main focus is Earths atmosphere but we also discuss how these problems might manifest themselves on other planetary bodies, with particular attention to Titan where methane takes on the role of water. GFD has traditionally been concerned with understanding the very basic problems that lie at the foundation of dynamical meteorology and ocean-ography. Conventionally, and a little ironically, the subject mainly considers `dry fluids, meaning it does not concern itself overly much with phase changes. The subject is often regarded as dry in another way, because it does not consider problems perceived as relevant to the real world, such as clouds or rainfall, which have typically been the province of complicated numerical models. Those models often rely on parameterizations of unresolved processes, parameterizations that may work very well but that often have a semi-empirical basis. The consequent dichotomy between the foundations and the applications prevents progress being made that has both a secure basis in scientific understanding and a relevance to the Earths climate, especially where moisture is concerned. The dichotomy also inhibits progress in understanding the climate of other planets, where observations are insufficient to tune the parameterizations that weather and climate models for Earth rely upon, and a more fundamental approach is called for. Here we discuss four diverse examples of the problems with moisture: the determination of relative humidity and cloudiness; the transport of water vapor and its possible change under global warming; the moist shallow water equations and the Madden-Julian Oscillation; and the hydrology cycle on other planetary bodies.
rate research
Read More
Power spectra of global surface temperature (GST) records reveal major periodicities at about 9.1, 10-11, 19-22 and 59-62 years. The Coupled Model Intercomparison Project 5 (CMIP5) general circulation models (GCMs), to be used in the IPCC (2013), are analyzed and found not able to reconstruct this variability. From 2000 to 2013.5 a GST plateau is observed while the GCMs predicted a warming rate of about 2 K/century. In contrast, the hypothesis that the climate is regulated by specific natural oscillations more accurately fits the GST records at multiple time scales. The climate sensitivity to CO2 doubling should be reduced by half, e.g. from the IPCC-2007 2.0-4.5 K range to 1.0-2.3 K with 1.5 C median. Also modern paleoclimatic temperature reconstructions yield the same conclusion. The observed natural oscillations could be driven by astronomical forcings. Herein I propose a semi empirical climate model made of six specific astronomical oscillations as constructors of the natural climate variability spanning from the decadal to the millennial scales plus a 50% attenuated radiative warming component deduced from the GCM mean simulation as a measure of the anthropogenic and volcano contributions to climatic changes. The semi empirical model reconstructs the 1850-2013 GST patterns significantly better than any CMIP5 GCM simulation. The model projects a possible 2000-2100 average warming ranging from about 0.3 C to 1.8 C that is significantly below the original CMIP5 GCM ensemble mean range (1 K to 4 K).
Temporary changes in precipitation may lead to sustained and severe drought or massive floods in different parts of the world. Knowing variation in precipitation can effectively help the water resources decision-makers in water resources management. Large-scale circulation drivers have a considerable impact on precipitation in different parts of the world. In this research, the impact of El Ni~no-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), and North Atlantic Oscillation (NAO) on seasonal precipitation over Iran was investigated. For this purpose, 103 synoptic stations with at least 30 years of data were utilized. The Spearman correlation coefficient between the indices in the previous 12 months with seasonal precipitation was calculated, and the meaningful correlations were extracted. Then the month in which each of these indices has the highest correlation with seasonal precipitation was determined. Finally, the overall amount of increase or decrease in seasonal precipitation due to each of these indices was calculated. Results indicate the Southern Oscillation Index (SOI), NAO, and PDO have the most impact on seasonal precipitation, respectively. Also, these indices have the highest impact on the precipitation in winter, autumn, spring, and summer, respectively. SOI has a diverse impact on winter precipitation compared to the PDO and NAO, while in the other seasons, each index has its special impact on seasonal precipitation. Generally, all indices in different phases may decrease the seasonal precipitation up to 100%. However, the seasonal precipitation may increase more than 100% in different seasons due to the impact of these indices. The results of this study can be used effectively in water resources management and especially in dam operation.
Quantifying the mechanisms of tracer dispersion in the ocean remains a central question in oceanography, for problems ranging from nutrient delivery to phytoplankton, to the early detection of contaminants. Most analyses have been based on Lagrangian concepts of transport, focusing on the identification of features minimizing fluid exchange among regions, or more recently on network tools which focus on connectivity and transport pathways. Neither of these approaches allows ranking the geographical sites of major water passage and selecting them so that they monitor waters coming from separate parts of the ocean. These are instead key criteria when deploying an observing network. Here we address this issue by estimating at any point the extent of the ocean surface which transits through it in a given time window. With such information we are able to rank the sites with major fluxes that intercept waters originating from different regions. We show that this allows us to optimize an observing network, where a set of sampling sites can be chosen for monitoring the largest flux of water dispersing out of a given region. When the analysis is performed backward in time, this method allows us to identify the major sources which feed a target region. The method is first applied to a minimalistic model of a mesoscale eddy field, and then to realistic satellite-derived ocean currents in the Kerguelen area. In this region we identify the optimal location of fixed stations capable of intercepting the trajectories of 43 surface drifters, along with statistics on the temporal persistence of the stations determined in this way. We then identify possible hotspots of micro-nutrient enrichment for the recurrent spring phytoplanktonic bloom occuring here. Promising applications to other fields, such as larval connectivity, marine spatial planning or contaminant detection, are then discussed.
We construct and analyze climate networks based on daily satellite measurements of temperatures and geopotential heights. We show that these networks are stable during time and are similar over different altitudes. Each link in our network is stable with typical 15% variability. The entire hierarchy of links is about 80% consistent during time. We show that about half of this stability is due to the spatial 2D embedding of the network, and half is due to physical coupling mechanisms. The network stability of equatorial regions is found to be lower compared to the stability of a typical network in non-equatorial regions.
Climate system teleconnections, which are far-away climate responses to perturbations or oscillations, are difficult to quantify, yet understanding them is crucial for improving climate predictability. Here we leverage Granger causality in a novel method of identifying teleconnections. Because Granger causality is explicitly defined as a statistical test between two time series, our method allows for immediate interpretation of causal relationships between any two fields and provides an estimate of the timescale of the teleconnection response. We demonstrate the power of this new method by recovering known seasonal precipitation responses to the sea surface temperature pattern associated with the El Ni~{n}o Southern Oscillation, with accuracy comparable to previously used correlation-based methods. By adjusting the maximum lag window, Granger causality can evaluate the strength of the teleconnection (the seasonal precipitation response) on different timescales; the lagged correlation method does not show ability to differentiate signals at different lags. We also identify candidates for previously unexplored teleconnection responses, highlighting the improved sensitivity of this method over previously used ones.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
