Funded Projects

Program (s): Climate Variability and Predictability

Competition:

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SocioΓÇÉeconomic benefits from skillful prediction of the MaddenΓÇÉJulian Oscillation (MJO) cannot be overemphasized and are well documented. Understanding the atmosphere – ocean processes behind the MJO, however, still remains a large scientific challenge. DYNAMO is an observational campaign that will address atmospheric and oceanic processes relevant to the genesis and growth of the MJO in the central equatorial Indian Ocean. Observations are planned for aircraft, research vessels, buoys and radars.

This project focuses on three major tasks:
(i) Investigat the quality of past NCEP GFS and CFS forecasts, both deterministic and probabilistic, over the DYNAMO area as well as the quality of forecasts from the newly implemented GFS T574L64 during the period of October 2010 to March 2011.
(ii) Develop and/or modify protocols for the transmission of both oceanographic and atmospheric data to the GTS, allow these data through quality control procedures, and finally ingestthem into NCEP data assimilation schemes in realΓÇÉtime as a crucial component of the DYNAMO field campaign.
(iii) Provide operational atmospheric and oceanic monitoring and forecast data to support (i) and (ii) above. For example, this will include realΓÇÉtime information for planning intensive observing periods, including aircraft missions and downtime for flight crews, tied to spells of enhanced or suppressed organized convective activity that are crucial to the success of DYNAMO. The oceanographic component of the campaign also requires guidance on which depths the different instruments should be deployed with a lead time of one to two weeks. NCEP has a rich history of operational support for field campaigns (NAME, AMMA, VOCALS, TPARC). We will establish an operational website that will provide the necessary information for the decision making process during the DYNAMO campaign.

Since much of this work is to be done before and during the campaign, the work and necessary resources are “frontΓÇÉloaded” in this proposal as indicated in the budget justification.

Program (s): Climate Variability and Predictability

Competition:

Award Number: | View Publications on Google Scholar

The Madden-Julian Oscillation (MJO) is the dominant mode of tropical convection variability on the intraseasonal time scale. The MJO initiates in the western equatorial Indian Ocean and propagates eastward as a couplet between multi-scale convection and large-scale circulation. Though upscale/downscale modulations and tropical –extratropical teleconnections, the MJO influences the weather activity and climate variability around the globe. The recurrent nature of the MJO influences the weather activity and climate variability around the globe. The recurrent nature of the MJO with a period of 30-60 days offers an opportunity to bridge the gap between weather forecasting and seasonal prediction. However, current state-of-the-art global models are significantly challenged in realistically simulating the MJO, which severely hampers our capability of predicting its global impacts.

Great efforts have been made to improve the prediction skill of the MJO at NOAA NCEP. Dynamical forecasts from the NCEP Climate Forecast System (CFSv1) have been produced in real-time since 2004. A new Climate Forecast System (CFSv2) is being developed and will replace the earlier version (CFSv1). Additionally, a new Climate Forecast System Reanalysis (CFSR) has recently been completed. The CFSR is superior in capturing intraseasonal convective variability as compared to the previous NCEP reanalyses and is used to initialize the CFSv2. Despite these efforts, outstanding problems in the MJO forecast still remain. Preliminary analysis shows that while the CFSv2 has a better overall skill than the CFSv1, it consistently forecasts too slow eastward propagation. The proposed research aims to take advantage of the unprecedented data that will be collected during DYNAMO/AMIE field campaigns and the CFSR to advance our understanding of the MJO initiating and propagation, and to explore the pathway to improve the representation of the MJO in the CFSv2.

To achieve the above objectives, the following steps will be taken:
1) Relevant processes revealed from previous studies on MJO initiation and propagation will be documented with the CFSR, outputs of the CFSv2 and a model at UH.
2) Results from the CFSR, CFSv2, and the UH model will be carefully compared and further validated with DYNAMO/AMIE observations and possible relationships between errors in the MJO forecasts and errors in associated atmospheric (e.g., heating and moistening profiles, low-level convergence, etc.) and oceanic (e.g., SST) fields will be examined to assess the impacts of atmospheric model physics and oceanic surface variability.
3) Numerical experiments with the CFSv2 and UH model will be conducted to assess the impact of atmospheric model physics (e.g., detrainment of shallow convection and trigger of deep convection).
4) Further numerical experiments with atmosphere-only components of the CFSv2 and UH model will be performed to assess the impact of forecast SST errors and to test the use of a high-resolution 1-dimensional mixed-layer ocean model.

This activity is expected to improve the overall prediction skill of the MJO in the NCEP mode. This project directly responds to the priority 3 of FY2011 ESS program “understanding and Improving Prediction of Tropical Convection”. The proposed study will further our understanding of the physical processes governing the initiation and propagation of the dominant tropical convection variability on the intraseasonal time scale: the MJO. The main accomplishment of this project will be to improve the prediction skill of the MJO and the associated weather and climate variability in the CFSv2, contributing to the economic and societal well-being of the Nation.

Program (s): Climate Variability & Predictability

Competition: Observing and Understanding Upper - Ocean Processes and Shallow Convection in the Tropical Atlantic Ocean

Award Number: NA20OAR4310374, GC20-398 | View Publications on Google Scholar

The population of clouds over the subtropical oceans is dominated by trade wind cumulus which often organize in a variety of mesoscale shapes and sizes. The subtropical ocean, too, exhibits much fine-scale variability, in the form of sea surface temperature (SST) anomalies and ocean mesoscale eddies. Because observed patches of aggregated shallow cumulus, SST variations, ocean eddies, and associated mesoscale circulations exist in the “grey zone” for current global models, our ability to model these phenomena and understand their relevance to the climate system is crude. Here we propose a process modeling study to investigate the role of mesoscale spatial organization in air-sea interactions. Our main objectives are: (i) to assess how mesoscale spatial organization of shallow cumulus may affect atmosphere-ocean coupling by modulating wind speeds and cloudiness, and (ii) to investigate how mesoscale organization of shallow clouds and the circulations in which they are embedded are affected by transient SST perturbations driven by surface fluxes and persistent SST structures maintained by oceanic mesoscale eddies. We will address these questions with large eddy simulations (LES) with resolutions fine enough to resolve cloud-scale circulations but large enough to admit the organizing mesoscale circulations. We will diagnose how mesoscale organization affects the net surface energy budget and how SST perturbations in turn affect mesoscale organization. By using LES to interpolate the data from ATOMIC/EUREC4A-OA, our primary focus is to examine how mesoscale structures in the lower atmosphere and the upper ocean might interact and regulate air-sea coupling. This goal is directly aligned with this CVP target competition aim of better understanding air-sea interactions within the ATOMIC/EUREC4A-OA field campaigns region, with focus on lower atmospheric boundary layer processes and their influence on the ocean. This knowledge will then be used to inform physical parametrizations, and ultimately, to improve climate predictions. Therefore, the proposal also contributes to NOAA’s goal of providing high quality environmental information.

Program (s): Climate Variability and Predictability

Competition: Understanding Arctic Sea Ice Mechanisms and Predictability

Award Number: NA15OAR4310171 | View Publications on Google Scholar

Due to the rapid decline in Arctic sea ice extent and volume over the past decade, there has been a growing focus on developing capabilities for prediction. NOAAΓÇÖs Arctic Action Plan calls for an improvement in sea ice predictability ranging from the short term (e.g. daily and weekly) to seasonal to decadal time-scales. Such an effort is particularly important in light of the large variability seen in annual sea ice minima. To gain predictive skill, one must gain an understanding of sea ice variability and the coupled terrestrial, ocean and atmospheric systems that influence this variability.

We propose to advance the understanding of Arctic sea ice variability and predictability by investigating several interrelated items that have been largely overlooked, but that we hypothesize will give further insight to the seasonal fate of sea ice. These items include (a) the influence of spring and early summer snow cover over Northern Hemisphere lands, (b) the atmospheric circulation patterns that favor ice melt, their precursors and mechanisms by which the atmosphere interacts with snow to impact the sea ice and (c) the ability of models to capture observed relationships. We will also explore additional relationships between the sea ice melt season and quantities such as melt onset date, atmospheric moisture content, and winter ice dynamics

.Speculation regarding relationships between terrestrial snow and sea ice dates back at least 20 years, but there has been no systematic investigation of mechanisms relating the two quantities at regional scales. To fill this gap, we will apply innovative tools such as complex network analysis, which can provide insight into the spatial relationships between various nodes (in this case, gridboxes of snow and ice cover) of a network (the snow and sea ice system). Using such techniques we will search for predictive power amongst snow variables, as well as a multitude of information sources such as atmospheric circulation patterns or ice melt onset date. NOAA climate data records and reanalysis products (e.g. NOAAΓÇÖs CFSR) will be used in our analysis. We also propose to gain an understanding of model abilities, particularly the CMIP5 models and the NOAA Climate Forecast System (CFS), by determining whether they can reproduce observed linkages. Model deficiencies can point to structural issues, which in turn can lead to improvements. Results from the SEARCH Sea Ice Outlook (SIO; now part of the new Sea Ice Prediction Network (SIPN) led by PI J. Stroeve) indicate that there is much room for improvement within current modeling and prediction systems.

This work is directly responsive to this NOAA proposal call in that it seeks to understand where predictability can arise from and how that understanding may be applied in a forecasting context. Greater understanding of sea ice within the Arctic system is one of the goals of NOAAΓÇÖs Next-Generation Strategic Plan and its central mission to understand and predict changes in climate, weather, oceans and coasts.

Program (s): Climate Variability & Predictability

Competition: OAR/CPO/CVP - NWS/OSTI/Modeling Division - Joint Competition to Advance Process Understanding and Representation of Precipitation in Models

Award Number: NA22OAR4310615 NA22OAR4310616 NA22OAR4310617 | View Publications on Google Scholar

Climate models of standard resolution (e.g. approximately 1°) do not properly resolve phenomena such as atmospheric fronts or ocean mesoscale features. Much of the precipitation in mid-latitudes is associated with atmosphere fronts, particularly in the Extratropical storm tracks. In addition, ocean mesoscale features such as western boundary currents and eddies can induce convergence of the near-surface winds, which is an important factor governing precipitation. Thus, the standard resolution models may be missing some key aspects of processes that drive precipitation, with detrimental impacts on longer range predictability and S2S associated with evolution of the ocean mesoscale and fronts. This project will aim to understand linkages between sea surface temperature (SST), surface convergence and precipitation, using high resolution datasets, and use the results to assess standard resolution model results. Key aspects to this work are how the ocean mesoscale SST affects the atmospheric boundary layer and frontogenesis. The proposed work falls into four steps: 1. Describe the co-variability of sea surface temperature, wind convergence and precipitation as a function of time and spatial scales from days to season, and from tens of kilometers to basin scale. 2. Investigate the atmospheric boundary layer responses to the ocean mesoscale in the presence of large-scale atmospheric forcing using a recently developed boundary layer model. 3. Characterize surface wind convergence and precipitation associated with atmospheric fronts using objective atmospheric frontal diagnostics, and explore linkages to the ocean mesoscale. 4. Explore how the responses of atmospheric boundary processes, atmospheric fronts, and mesoscale SST features, are related to each other. The state-of-the-art, high-resolution observational and model datasets to be used here include ERA5, CFSR reanalysis, high-resolution CESM, HighResMIP climate models, precipitation analyzed from satellite and in-situ data (IMERG) and scatterometer winds, and a recently developed boundary layer model (Schneider and Qiu 2015).

Program (s): Climate Variability & Predictability

Competition: Observing and Understanding Processes Affecting the Propagation of Intraseasonal Oscillations in the Maritime Continent Region

Award Number: NA17OAR4310250, GC17-303 | View Publications on Google Scholar

The tropical intraseasonal oscillation (ISO) is one of the most important phenomena in the tropics. It exerts a profound influence on a wide range of weather-climate systems not only in the tropics but also in the extratropics. Thus, predicting the ISO accurately is of critical importance, although our current prediction skill of the ISO based on general circulation models (GCMs) remains unsatisfactory. This is largely due to uncertainties in model physics as well in model initialization. Of the uncertainties in model physics, the cloud and precipitation processes are particularly important. The convective component of the ISO is made up primarily of a number of mesoscale convective systems (MCSs). On the other hand, there is lots of evidence that a substantial fraction of MCSs occur in association with synoptic-scale equatorial waves, often referred to as convectively coupled equatorial waves (CCEWs). However, how the interactions among MCSs, CCEWs, and the ISO operate are poorly understood. The presence of the Maritime Continent (MC) exacerbates the situation. A pronounced diurnal cycle in conjunction with the complex geography comes into play in the interaction. As a result, the ISO convection skirts around the islands and weakens significantly, and simulating the ISO with fidelity is particularly difficult in the MC region, a strong limiting factor in our predictive skill. Taking advantage of the YMC opportunity, this project aims to improve our understanding of the processes that affect the propagation of the ISO in the MC region, especially from the viewpoint of multiscale interaction, through synergistic use of both observations and state-of-the-art numerical models. Because of the diversity in the ISO, a thorough and comprehensive observational and modeling treatment will be the key to any successful diagnosis of ISO dynamics and physics. In this research, we will carefully identify the types of ISOs based on three different indices. We hypothesize from our previous results that CCEWs play a central role in the propagation of the ISO. Novel objective methods including the spatio-temporal wavelet transform (STWT) and objective-based tracking approach will be used to test our hypothesis from morphological point of view. Rigorous analysis of moisture, momentum, and temperature fields with respect to CCEWs, MCSs, and other prominent synoptic-scale components will help us quantify the roles of individual components in the propagation of the ISO. We will further use forecasts of conventional GCMs including CFSv2 and a global-cloud resolving model, NICAM, to examine the processes that are responsible for the propagation of the ISO. By conducting a meticulous comparison among observations, conventional GCMs’ forecasts, and NICAM forecasts in terms of both morphology and budget approaches, it is anticipated that we will gain invaluable insights into the convective processes that affect the propagation and thus predictability of the ISO. Although we will pay special attention to YMC, we will make use of past field campaign opportunities including the CINDY/DYNAMO (October 2011-March 2012) and Pre-YMC (November-December 2015) as well as long-term observational and forecast data in an attempt to draw statistically robust conclusions. Our research will contribute not only to advancing our understanding of the propagation and structure of the ISO, but also to identifying the problematic processes in models simulating the ISO in the MC, which eventually contribute to improving their predictability of the ISO. The objective of this project is entirely in line with the CVP’s goal that “aims to improve understanding of processes that affect the propagation (speed, intensity, disruption, geographic placement) of intraseasonal oscillations in the Maritime Continent and broader region by using a combination of in situ and remote observations, data analysis, modeling and/or theoretical understanding of local and remote processes” as well as NOAA’s long-term climate goals.

Program (s): Climate Variability and Predictability

Competition:

Award Number: NA13OAR4310165 | View Publications on Google Scholar

The Madden-Julian oscillation (MJO) is one of the most important phenomena associated with intraseasonal atmospheric variability in the tropics. A substantial fraction of tropical precipitation, which plays an important role in the general circulation, falls from the mesoscale convective systems (MCSs) associated with the MJO. Because the MJO modulates other components of the atmosphere-ocean system both in the tropics and extratropics on a wide variety of spatio-temporal scales, the performance of medium range weather forecasting and the realism of pronounced atmospheric and oceanic variability in coupled climate models is substantially dependent on skill in simulating the MJO. Thus, a comprehensive understanding of the MJO is of practical as well as of scientific importance. However, some of the fundamental features of the dynamics and physics of the MJO remain elusive and most currently used general circulation models still have difficulty in simulating the MJO.

Our proposed research aims to improve our understanding of the most crucial but problematic aspect of the MJO, the interplay between convection and large-scale circulation. Because of the inherent complexities associated with the multiscale interaction process of the MJO, a thorough and comprehensive treatment will be the key to any successful diagnosis of MJO dynamics and physics. In this research, we intend to use several innovative methods to accurately identify the internal structures of the MJO. A recently introduced spatio-temporal wavelet transform (STWT) method is capable of localizing a spectral signal from a longitude-time section of a variable. This approach will allow us to document the critical internal structures of the MJO, and in conjunction use with an “object-based” feature tracking approach, examine how such structures regulate the development and organization of MJO convection. Because the degree of vertical development of convection and organization arguably depends strongly on the background moisture field, the role of the internal structures in moisture budget will be assessed in a phenomenological manner.

A comprehensive study based on analysis of in-situ and satellite observations, and the use of a state-of-the-art global cloud-system resolving model NICAM (Nonhydrostatic ICosahedral Atmospheric Model), will greatly improve our chances of success in this project. In addition to these datasets, long-term observational data will be used to derive statistically robust conclusions. Ultra-high resolution long-term cloud data and NICAM simulations that are capable of representing MCSs explicitly provide a promising opportunity to examine multiscale interactions of the MJO.

This is a research project that enhances international collaboration. The objective of this project is entirely in line with the ESS program’s aim “to provide a process-level understanding of the climate system through observation, modeling” and with this call’s aim particularly in two aspects, namely, “improving the understanding of interaction between convection and environmental moisture” and “the dynamic evolution of the cloud population”.

Program (s): Climate Variability & Predictability

Competition: Decadal Climate Variability and Predictability

Award Number: NA20OAR4310398, NA20OAR4310399, GC20-203 | View Publications on Google Scholar

Two research areas in the Atlantic Ocean have received elevated interests in the community: (1) the stability and variability of the Atlantic Meridional Circulation (AMOC), and (2) the accelerated sea level rise (SLR) along the North American Coast from Cape Hatteras to Nova Scotia. The relationship between them, i.e., whether the observed coastal SLR is resulted from changes in the AMOC and whether a predicted weakening of the AMOC transport will further accelerate coastal SLR, is still being debated. As a circulation system in the open ocean, the AMOC would need to overcome the strong topographic barrier across the continental shelf break in order to influence coastal sea level. The cross-shelf connection is the least understood aspect in any suggested mechanisms linking coastal sea level variability to the AMOC changes. Most present climate models and basin-scale Ocean General Circulation Models (OGCMs), even with increasing resolutions, are not up to the task to address the complex cross-isobath processes near the continental shelf break. This is due to the fact that many coastal processes are often not well represented or adequately treated in global scale models, which are optimized for the large-scale processes like the AMOC and Gulf Stream (GS). Therefore, a well-treated and carefully designed regional model forced by dynamically consistent global model is more desirable for assessing the relationship between coastal sea level and the AMOC. In this project, we propose an integrated approach using both in situ and satellite observations, eddy-resolving global data-assimilative reanalysis, and a hierarchy of numerical models, including a state-of-the-art regional ocean circulation model and a 2-layer process model to study the dynamical linkages between the AMOC and the sea level variability on the Northwest (NW) Atlantic shelf over interannual and decadal time scales. Specifically, we will analyze the AMOC variations on various time scales using available observations and global eddy-resolving, data assimilative simulations, characterize and quantify their impacts on western boundary currents (WBCs) and slope currents, search possible connections with coastal sea level changes, and identify and examine cross-shelf connection processes and mechanisms using models. Our goal is to identify and understand key cross-shelf processes and mechanisms that are important in connecting the AMOC and coastal sea level variability, based on which we can further develop predictive skills for coastal sea level changes. The outcome of this project will also be useful for the improvements of climate models in their representations of coastal processes. Our proposed work directly addresses the Competition of CVP - Decadal Climate Variability and Predictability in the area of investigation of the relationship between the Atlantic Meridional Overturning Circulation (AMOC) and global and regional sea level (historical, current, and/or future), with a focus on understanding sea level extremes and coastal impacts in the United States, for the improved understanding of the ocean-climate system. This project is also responsive to the CPO’s strategy in addressing challenges in the areas of Weather and Climate Extremes, Climate impacts on water resources and Coasts and climate resilience.

Program (s): Climate Variability & Predictability

Competition: Climate and Changing Ocean Conditions: Research and Modeling to Support the Needs of NOAA Fisheries

Award Number: NA20OAR4310481 | View Publications on Google Scholar

Competition Relevance: One objective in the Northeast Regional Action Plan of NOAA’s Fisheries Climate Science Strategy is to improve medium-term (year to decade) climate forecast products for living marine resources. A key component of medium-term climate prediction is predicting ocean circulation. Two major ocean currents are involved in the Northeast U.S. Shelf Large Marine Ecosystem fisheries management sector, the southward Labrador Current and the northward Gulf Stream. Both are connected to the complex North Atlantic circulation and Atlantic Meridional Overturning Circulation (AMOC). Decadal-scale climate predictability of the state of the North Atlantic Ocean is strongly dependent on AMOC predictability, which requires an understanding of the climate variables that influence and are influenced by AMOC. This is what our proposal is focused on. Scientific Rational: Investigations into the forcing factors driving decadal-scale AMOC variability have been hampered by the relatively short length of direct AMOC observations, difficulties in identifying and modeling the key physical mechanisms, and the convolution of anthropogenic radiative forcing with natural variability during the era of instrumental climate records. This project aims to test a recent hypothesis about the driving mechanism of AMOC decadal variability, using high-resolution paleoclimate archives that provide long (multiple centuries) records of Earth’s climatic behavior, pre-dating significant anthropogenic forcing. The idea is to identify the natural physical relationships between North Atlantic climate variables to test if they are consistent with underlying physical theories developed from modeling studies. Summary of Work: We will specifically gather the highest possible temporal resolution paleoclimate proxies of sea surface temperature from the North Atlantic with a recent multi-proxy reconstruction of North Atlantic Oscillation (NAO) to test if the NAO is associated with heat convergence at high latitudes and if the signal is propagated to lower latitudes. The mechanism we will be testing is laid out by Wills et al. (2018) who find evidence that AMOC and NAO are coupled on decadal to multidecadal timescales. They describe the consequences of that coupling in terms of surface warming, a quantity that can be reconstructed from the highest resolution paleoclimate proxies. Scientific and Broader Impacts: The results of the proposed analysis will provide observational evidence of the relationship between NAO and ocean temperatures in key regions of the North Atlantic that give insight into the mechanistic connections between the atmosphere and ocean circulation in this region on interannual to decadal time scales. Using paleoclimate data, we will test the hypothesis that NAO and AMOC are linked on decadal scales through oceanic heat convergence and buoyancy fluxes based on observational evidence. If the basic hypothesis is rejected, our analysis will provide alternative relationships between NAO and temperature in particular regions that can be further explored in future modeling efforts. In effect, we will be identifying relationships between key variables in a long-term observational dataset that can be used to improve the physical representation of AMOC in climate models used for making climate projections and forecast products in support of fisheries management. Such climate intelligence contributes directly to U.S. prosperity and resilience by helping to maintain healthy fisheries and the communities of people who are dependent on those fisheries.

Program (s): Climate Variability & Predictability

Competition: Observing and Understanding Processes Affecting the Propagation of Intraseasonal Oscillations in the Maritime Continent Region

Award Number: NA17OAR4310252 | View Publications on Google Scholar

Multi-scale interactions in the coupled ocean/atmosphere of the tropics play a crucial role in shaping the climate state and its spatial and temporal variability. On intraseasonal time scales (20-120 days) the Madden-Julian Oscillation (MJO) is the major player in affecting local and far-field conditions. Operational forecasts of the MJO show a significant reduction in skill as MJO events propagate over the the Maritime Continent, the so-called Maritime Continent MJO prediction barrier. Recognizing the importance of the Maritime Continent, the international project the Years of the Maritime Continent (YMC, July 2017 – July 2019) has as a major goal the improvement of the understanding and prediction of the MJO as it interacts with the Maritime Continent through an intensive field campaign and associated modeling studies. The present proposal focuses on identifying the major factors controlling the sea surface temperature, SST, in the Maritime Continent region. Variability of SST on intraseasonal to seasonal timescales strongly influences the maintenance and propagation of the MJO in the region with potential feedbacks between the atmosphere and ocean. In order to make a fair assessment of the role of the ocean in the maintenance and propagation of MJOs over the Maritime Continent in coupled models it is necessary to determine how well the ocean component of the coupled system is capturing the ocean state. A combination of observations and models will be used to determine the physical processes that influence the response of the upper ocean and SST to intraseasonal to seasonal variability of the atmosphere in the Maritime Continent region. A major focus will be salinity, its influence on the stratification of the upper ocean and associated warming of the surface ocean. The factors influencing the presence of fresh surface layers, their temporal and spatial scales, and impact on SST will be ascertained. We will also determine what it takes for a model to capture their impact properly. The results will be used as a guide to improve ocean/atmosphere interactions in coupled models. The potential of improving the simulation and prediction of MJO in models, with focus on the Maritime Continent region, and the associated societal benefits, underlie the goals of this proposal. As such the proposal is directly related to the aims of the NOAA CVP program – Observing and understanding processes of intraseasonal oscillations in the Marine Continent Region. Improving the present day MJO in models also applies to assessing the changes to MJO activity, and its impact on the monsoons and tropical cyclones, brought about by climate change. The proposal, therefore is also aligned with the climate objectives outlined in NOAA’s Next Generation Strategic Plan (NGSP, 2010), namely: Improved scientific understanding of the changing climate system and its impacts.