The NCEP and NCAR are cooperating in a project (denoted “reanalysis”) to produce a 40-year record of global analyses of atmospheric fields in support of the needs of the research and climate monitoring communities. This effort involves the recovery of land surface, ship, rawinsonde, pibal, aircraft, satellite, and other data; quality controlling and assimilating these data with a data assimilation system that is kept unchanged over the reanalysis period 1957–96. This eliminates perceived climate jumps associated with changes in the data assimilation system. The NCEP/NCAR 40-yr reanalysis uses a frozen state-of-the-art global data assimilation system and a database as complete as possible. The data assimilation and the model used are identical to the global system implemented operationally at the NCEP on 11 January 1995, except that the horizontal resolution is T62 (about 210 km). The database has been enhanced with many sources of observations not available in real time for operations, provided b...

The NCEP/NCAR 40-Year Reanalysis Project

ERA-Interim is the latest global atmospheric reanalysis produced by the European Centre for Medium-Range Weather Forecasts (ECMWF). The ERA-Interim project was conducted in part to prepare for a new atmospheric reanalysis to replace ERA-40, which will extend back to the early part of the twentieth century. This article describes the forecast model, data assimilation method, and input datasets used to produce ERA-Interim, and discusses the performance of the system. Special emphasis is placed on various difficulties encountered in the production of ERA-40, including the representation of the hydrological cycle, the quality of the stratospheric circulation, and the consistency in time of the reanalysed fields. We provide evidence for substantial improvements in each of these aspects. We also identify areas where further work is needed and describe opportunities and objectives for future reanalysis projects at ECMWF. Copyright © 2011 Royal Meteorological Society

The ERA-Interim reanalysis: configuration and performance of the data assimilation system

Land use has generally been considered a local environmental issue, but it is becoming a force of global importance. Worldwide changes to forests, farmlands, waterways, and air are being driven by the need to provide food, fiber, water, and shelter to more than six billion people. Global croplands, pastures, plantations, and urban areas have expanded in recent decades, accompanied by large increases in energy, water, and fertilizer consumption, along with considerable losses of biodiversity. Such changes in land use have enabled humans to appropriate an increasing share of the planet’s resources, but they also potentially undermine the capacity of ecosystems to sustain food production, maintain freshwater and forest resources, regulate climate and air quality, and ameliorate infectious diseases. We face the challenge of managing trade-offs between immediate human needs and maintaining the capacity of the biosphere to provide goods and services in the long term.

/pdf/global-consequences-of-land-use-map7a6ziel.pdf

Global Consequences of Land Use

世界経済・社会統計 = World development indicators

Drafting Authors: Neil Adger, Pramod Aggarwal, Shardul Agrawala, Joseph Alcamo, Abdelkader Allali, Oleg Anisimov, Nigel Arnell, Michel Boko, Osvaldo Canziani, Timothy Carter, Gino Casassa, Ulisses Confalonieri, Rex Victor Cruz, Edmundo de Alba Alcaraz, William Easterling, Christopher Field, Andreas Fischlin, Blair Fitzharris, Carlos Gay García, Clair Hanson, Hideo Harasawa, Kevin Hennessy, Saleemul Huq, Roger Jones, Lucka Kajfež Bogataj, David Karoly, Richard Klein, Zbigniew Kundzewicz, Murari Lal, Rodel Lasco, Geoff Love, Xianfu Lu, Graciela Magrín, Luis José Mata, Roger McLean, Bettina Menne, Guy Midgley, Nobuo Mimura, Monirul Qader Mirza, José Moreno, Linda Mortsch, Isabelle Niang-Diop, Robert Nicholls, Béla Nováky, Leonard Nurse, Anthony Nyong, Michael Oppenheimer, Jean Palutikof, Martin Parry, Anand Patwardhan, Patricia Romero Lankao, Cynthia Rosenzweig, Stephen Schneider, Serguei Semenov, Joel Smith, John Stone, Jean-Pascal van Ypersele, David Vaughan, Coleen Vogel, Thomas Wilbanks, Poh Poh Wong, Shaohong Wu, Gary Yohe

Contribution of Working Group II to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change

Forecast Experiments with the NASA/GLA Stratospheric/Tropospheric Data Assimilation System

. Bred vectors characterize the nonlinear instability of dynamical systems and so far have been computed only for systems with known evolution equations. In this article, bred vectors are computed from a single time series data using time-delay embedding, with a new technique, nearest-neighbor breeding. Since the dynamical properties of the standard and nearest-neighbor breeding are shown to be similar, this provides a new and novel way to model and predict sudden transitions in systems represented by time series data alone.

/pdf/brief-communication-breeding-vectors-in-the-phase-space-wn5cpj0dmt.pdf

Brief Communication: Breeding vectors in the phase space reconstructed from time series data

This chapter describes the authors’ effort on ensemble data assimilation of satellite precipitation measurements. The Local Ensemble Transform Kalman Filter (LETKF) was implemented with the Nonhydrostatic Icosahedral Atmospheric Model (NICAM), and JAXA’s GSMaP (Global Satellite Mapping of Precipitation) data were assimilated at 112-km resolution.

Precipitation Ensemble Data Assimilation in NWP Models

With the growing recognition of coupled human and natural systems (CHANS), modeling CHANS with two-way feedbacks has become a frontier research area and a critical tool to achieve sustainability. The challenges in CHANS modeling and opportunities to advance its science and application to promote the sustainability of CHANS are discussed in this paper.

https://academic.oup.com/nsr/advance-article-pdf/doi/10.1093/nsr/nwad054/49448016/nwad054.pdf

Challenges and opportunities for modeling coupled human and natural systems

Introduction: Data assimilation optimally combines spacecraft observations with short-term forecasts from an atmospheric model to produce a record of the atmospheric state and, with an ensemble, its uncertainties. When performed retroactively for a long period of time, this sequence of analyses is termed a reanalysis. The availability of Thermal Emission Spectrometer (TES) and Mars Climate Sounder (MCS) retrievals of temperature and aerosol opacities enables a comprehensive multiannual examination of Martian weather and climate, as data assimilation has proven to be an effective means of reconciling models with observations for Mars (Lewis et al., 2007; Hoffman et al., 2010; Lee et al., 2011; Navarro et al., 2013). We have used the Local Ensemble Transform Kalman Filter (LETKF), an advanced data assimilation system, to construct a sequence of synoptic maps (Figure 1) detailing the evolution of the temperature, wind, and surface pressure over the course of several Martian years (Mars Year 24 – 27, as well as during the MCS period).

Eugenia Kalnay

Papers

Forecast Experiments with the NASA/GLA Stratospheric/Tropospheric Data Assimilation System

Brief Communication: Breeding vectors in the phase space reconstructed from time series data

Precipitation Ensemble Data Assimilation in NWP Models

Challenges and opportunities for modeling coupled human and natural systems

Ensemble Mars Atmosphere Reanalysis System (EMARS)