The U.S. Climate Variability and Predictability (CLIVAR) working group on drought recently initiated a series of global climate model simulations forced with idealized SST anomaly patterns, designed ...to address a number of uncertainties regarding the impact of SST forcing and the role of land–atmosphere feedbacks on regional drought. The runs were carried out with five different atmospheric general circulation models (AGCMs) and one coupled atmosphere–ocean model in which the model was continuously nudged to the imposed SST forcing. This paper provides an overview of the experiments and some initial results focusing on the responses to the leading patterns of annual mean SST variability consisting of a Pacific El Niño–Southern Oscillation (ENSO)-like pattern, a pattern that resembles the Atlantic multidecadal oscillation (AMO), and a global trend pattern.
One of the key findings is that all of the AGCMs produce broadly similar (though different in detail) precipitation responses to the Pacific forcing pattern, with a cold Pacific leading to reduced precipitation and a warm Pacific leading to enhanced precipitation over most of the United States. While the response to the Atlantic pattern is less robust, there is general agreement among the models that the largest precipitation response over the United States tends to occur when the two oceans have anomalies of opposite signs. Further highlights of the response over the United States to the Pacific forcing include precipitation signal-to-noise ratios that peak in spring, and surface temperature signal-to-noise ratios that are both lower and show less agreement among the models than those found for the precipitation response. The response to the positive SST trend forcing pattern is an overall surface warming over the world’s land areas, with substantial regional variations that are in part reproduced in runs forced with a globally uniform SST trend forcing. The precipitation response to the trend forcing is weak in all of the models.
It is hoped that these early results, as well as those reported in the other contributions to this special issue on drought, will serve to stimulate further analysis of these simulations, as well as suggest new research on the physical mechanisms contributing to hydroclimatic variability and change throughout the world.
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BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
The energy radiated by the Earth towards space does not compensate the incoming radiation from the Sun leading to a small positive energy imbalance at the top of the atmosphere (0.4-1.Wm-2). This ...imbalance is coined Earth’s Energy Imbalance (EEI). It is mostly caused by anthropogenic greenhouse gases emissions and is driving the current warming of the planet. Precise monitoring of EEI is critical to assess the current status of climate change and the future evolution of climate. But the monitoring of EEI is challenging as EEI is two order of magnitude smaller than the radiation fluxes in and out of the Earth. Over 93% of the excess energy that is gained by the Earth in response to the positive EEI accumulates into the ocean in the form of heat. This accumulation of heat can be tracked with the ocean observing system such that today, the monitoring of Ocean Heat Content (OHC) and its long-term change provide the most efficient approach to estimate EEI. In this community paper we review the current four state-of-the-art methods to estimate global OHC changes and evaluate their relevance to derive EEI estimate on different time scales. These four methods make use of : 1) direct observations of in situ temperature; 2) satellite-based measurements of the ocean surface net heat fluxes; 3) satellite-based estimates of the thermal expansion of the ocean and 4) ocean reanalyses that assimilate observations from both satellite and in situ instruments. For each method we review the potential and the uncertainty of the method to estimate global OHC changes. We also analyze gaps in the current capability of each method and identify ways of progress for the future to fulfill the requirements of EEI monitoring. Achieving the observation of EEI with sufficient accuracy will depend on merging the remote sensing techniques with in situ measurements of key variables as an integral part of the Ocean Observing System.
Since OceanObs’09, the Global Ocean Observing System (GOOS) has evolved from its traditional focus on the ocean’s role in global climate. GOOS now also encompasses operational services and marine ...ecosystem health, from the open ocean into coastal environments where much of the world’s population resides. This has opened a field of opportunity for new collaborations—across regions, communities, and technologies—facilitating enhanced engagement in the global ocean observing enterprise to benefit all nations. Enhancement of collaboration is considered from the perspectives of regional alliances, global networks, national systems, in situ observing, remote sensing, oceanography, and meteorology. Reinvigoration of GOOS Regional Alliances has been important in connecting the power of this expanded remit to the needs of coastal populations and the capabilities of regional and national marine science communities. An assessment of progress is provided, including issues/challenges with the current structure, and opportunities to increase participation and impact. Meeting the expanded requirements of GOOS will entail new system networks. The Joint Technical Commission for Oceanography and Marine Meteorology Observations Coordination Group has been working with some communities to help assess readiness, including high frequency radars, ocean gliders, and animal tracking. Much more needs to be done, with a range of strategies considered. Other opportunities include partnering with programs such as the Global Ocean Acidification Observing Network, engaging with mature and emerging national ocean observing programs, and learning from multinational projects such as Tropical Pacific Observing System 2020 which are bringing renewed rigor to the design and operation of observing systems. Consideration is given to the expansion and advancement that is coming in both in situ and remote sensing ocean observation platforms over the next decade. In combination they provide the potential to measure new Essential Ocean Variables routinely at global scale. Opportunities provided by the World Meteorological Organization Integrated Global Observing System (WIGOS) in fostering a comprehensive and integrated approach across meteorology and oceanography are also considered. The focus of WIGOS on providing accurate, reliable and timely weather, climate, and related environmental observations and products sits well with the expanded requirements of GOOS, in climate, operational services, and marine ecosystem health.
The uncertainties in the NCEP–NCAR reanalysis (NCEPR) products are not well known. Using a newly developed, high-resolution, quality controlled, surface meteorology dataset from research vessels ...participating in the World Ocean Circulation Experiment (WOCE), regional and global uncertainties are quantified for the NCEPR air–sea fluxes and the component fields used to create those fluxes.
For the period 1990–95, WOCE vessel and gridded NCEPR fields are matched in time and space. All in situ data are subject to data quality review to remove suspect data. Adjustment of ship observations to the reference height of the NCEPR variables, and calculation of air–sea fluxes from the in situ data are accomplished using bulk formulas that take atmospheric stability, height of the measurements, and other adjustments into consideration. The advantages of using this new set of WOCE ship observations include the ability to compare 6-h integrated fluxes (much of the ship data originate from automated observing systems recording continual measurements), and the ability to perform more exhaustive quality control on these measurements. Over 4500 6-h component (sea level pressure, air and sea temperature, winds, and specific humidity) and flux (latent, sensible, and momentum) matches are statistically evaluated to quantify uncertainties between the ship observations and the NCEPR.
Primary results include a significant underestimation in NCEPR near-surface wind speed at all latitudes. The magnitude of the low bias increases at higher ship wind speeds and may be related to large (rms = 2.7 hPa) errors in sea level atmospheric pressure over the entire globe. The pressure biases show the NCEPR to underestimate the amplitude and/or position of both high and low pressures. The NCEPR slightly underestimates the momentum flux, in part, due to the weaker winds. The NCEPR sensible and latent heat fluxes are largely overestimated when compared to the WOCE ship data. Potential sources of this overestimation (e.g., the NCEPR model flux parameterization) are discussed. Using the NCEPR meteorological variables and an independent flux parameterization, the revised NCEPR sensible heat fluxes are closer to the observations, and the biases of the revised NCEPR latent heat flux change sign. Furthermore, while the revised latent heat flux values reduce the magnitude of the bias at higher wind speeds, they increase the bias at (more frequently occurring) moderate wind speeds and thus may not be suitable for many applications.
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BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
SeaWinds validation with research vessels Bourassa, Mark A.; Legler, David M.; O'Brien, James J. ...
Journal of Geophysical Research - Oceans,
February 2003, Letnik:
108, Številka:
C2
Journal Article
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The accuracy of the SeaWinds scatterometer's vector winds is assessed through comparison with research vessel observations. Factors that contribute to uncertainty in scatterometer winds are isolated ...and examined as functions of wind speed. For SeaWinds on QuikSCAT, ambiguity selection is found to be near perfect for surface wind speed (w) > 8 m s−1; however, ambiguity selection errors cause directional uncertainty to exceed 20° for w < ∼5 m s−1. These average uncertainties for wind speed and direction are found to be 0.45 m s−1 and 5° for the QSCAT‐1 model function and 0.3 m s−1 and 3° for the Ku‐2000 model function. The QuikSCAT winds are examined as vectors through two new approaches. The first is a method for determining vector correlations that considers uncertainty in the comparison data set. The second approach is a wind speed‐dependent model for the uncertainty in the magnitude of vector errors. For the QSCAT‐1 (Ku‐2000) model function this approach shows ambiguity selection dominates uncertainty for 2.5 < w < 5.5 m s−1 (0.6 < w < 5.5 m s−1), uncertainty in wind speed dominates for w < 2.5 m s−1 and 5.5 < w < 7.5 m s−1 (w < 0.6 m s−1 and 5.5 < w < 18 m s−1), and uncertainty in wind direction (for correctly selected ambiguities) dominates for w > 7.5 m s−1 (w > 18 m s−1). This approach also shows that spatial variability in the wind direction, related to inexact spatial co‐location, is likely to dominate rms differences between scatterometer wind vectors and in situ comparison measurements for w > 4.5 m s−1. The techniques used herein are applicable to any validation effort with uncertainty in the comparison data set or with inexact co‐location.
The Joint Committee for Oceanography and Marine Meteorology (JCOMM), a joint technical commission of IOC of UNESCO and WMO, has devised a coordination mechanism for the fit-for-purpose delivery of an ...end-to-end system, from ocean observations to met-ocean operational services. This paper offers a complete overview of the activities carried out by JCOMM and the status of the achievements up to 2017. The JCOMM stakeholders are the WMO Members and the IOC Member States, their research and operational Institutions, which mandated JCOMM to devise an international strategy to advance toward the achievement of the United Nations Sustainable Development Goals. The three activity areas, namely the Observation Program Area-OPA, the Data Management Program Area-DMPA and the Services and Forecasting Services Program Area-SFSPA have established several expert teams to contribute to the international coordination. OPA is organized in observing networks connected with different observing technologies, DMPA organizes the overall near-real time and delayed mode data assembly and delivery methodology and architecture and the SFSPA coordinates the met-ocean services stemming out of observations and data management. The future developments should strengthen the coordination in the three program areas considering the inclusion of new and emergent observing technologies, the interoperability of met-ocean data assembly centers and the establishment of efficient research to operations protocols, as well as better fit-for-purpose customized services for the public and private sectors.
The Global Ocean Observing System (GOOS) and its partners have worked together over the past decade to break down barriers between open-ocean and coastal observing, between scientific disciplines, ...and between operational and research institutions. Here we discuss some GOOS successes and challenges from the past decade, and present ideas for moving forward, including highlights of the GOOS 2030 Strategy published in 2019. The OceanObs'09 meeting in Venice in 2009 resulted in a remarkable consensus on the need for a common set of guidelines for the global ocean observing community. Work following the meeting led to development of the Framework for Ocean Observing (FOO) published in 2012 and adopted by GOOS as a foundational document that same year. The FOO provides guidelines for the setting of requirements, assessing technology readiness, and assessing the usefulness of data and products for users. Here we evaluate successes and challenges in FOO implementation and consider ways to ensure broader use of the FOO principles. The proliferation of ocean observing activities around the world is extremely diverse and not managed, or even overseen by, any one entity. The lack of coherent governance has resulted in duplication and varying degrees of clarity, responsibility, coordination and data sharing. GOOS has had considerable success over the past decade in encouraging voluntary collaboration across much of this broad community, including increased use of the FOO guidelines and partly effective governance, but much remains to be done. Here we outline and discuss several approaches for GOOS to deliver more effective governance to achieve our collective vision of fully meeting society’s needs. What would a more effective and well-structured governance arrangement look like? Can the existing system be modified? Do we need to rebuild it from scratch? We consider the case for evolution versus revolution. Community-wide consideration of these governance issues will be timely and important before, during and following the OceanObs’19 meeting in September 2019.
Abstract The years since 2000 have been a golden age in in situ ocean observing with the proliferation and organization of autonomous platforms such as surface drogued buoys and subsurface Argo ...profiling floats augmenting ship-based observations. Global time series of mean sea surface temperature and ocean heat content are routinely calculated based on data from these platforms, enhancing our understanding of the ocean’s role in Earth’s climate system. Individual measurements of meteorological, sea surface, and subsurface variables directly improve our understanding of the Earth system, weather forecasting, and climate projections. They also provide the data necessary for validating and calibrating satellite observations. Maintaining this ocean observing system has been a technological, logistical, and funding challenge. The global COVID-19 pandemic, which took hold in 2020, added strain to the maintenance of the observing system. A survey of the contributing components of the observing system illustrates the impacts of the pandemic from January 2020 through December 2021. The pandemic did not reduce the short-term geographic coverage (days to months) capabilities mainly due to the continuation of autonomous platform observations. In contrast, the pandemic caused critical loss to longer-term (years to decades) observations, greatly impairing the monitoring of such crucial variables as ocean carbon and the state of the deep ocean. So, while the observing system has held under the stress of the pandemic, work must be done to restore the interrupted replenishment of the autonomous components and plan for more resilient methods to support components of the system that rely on cruise-based measurements.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Considerable advances in the global ocean observing system over the last two decades offers an opportunity to provide more quantitative information on changes in heat and freshwater storage. ...Variations in these storage terms can arise through internal variability and also the response of the ocean to anthropogenic climate change. Disentangling these competing influences on the regional patterns of change and elucidating their governing processes remains an outstanding scientific challenge. This challenge is compounded by instrumental and sampling uncertainties. The combined use of ocean observations and model simulations is the most viable method to assess the forced signal from noise and ascertain the primary drivers of variability and change. Moreover, this approach offers the potential for improved seasonal-to-decadal predictions and the possibility to develop powerful multi-variate constraints on climate model future projections. Regional heat storage changes dominate the steric contribution to sea level rise over most of the ocean and are vital to understanding both global and regional heat budgets. Variations in regional freshwater storage are particularly relevant to our understanding of changes in the hydrological cycle and can potentially be used to verify local ocean mass addition from terrestrial and cryospheric systems associated with contemporary sea level rise. This White Paper will examine the ability of the current ocean observing system to quantify changes in regional heat and freshwater storage. In particular we will seek to answer the question: What time and space scales are currently resolved in different regions of the global oceans? In light of some of the key scientific questions, we will discuss the requirements for measurement accuracy, sampling, and coverage as well as the synergies that can be leveraged by more comprehensively analysing the multi-variable arrays provided by the integrated observing system.
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