2017

1. [Craig et al. 2017] Abstract. OASIS is coupling software developed primarily for use in the climate community. It provides the ability to couple different models with low implementation and performance overhead. OASIS3-MCT is the latest version of OASIS. It includes several improvements compared to OASIS3, including elimination of a separate hub coupler process, parallelization of the coupling communication and run-time grid interpolation, and the ability to easily reuse mapping weight files. OASIS3-MCT3.0 is the latest release and includes the ability to couple between components running sequentially on the same set of tasks as well as to couple within a single component between different grids or decompositions such as physics, dynamics, and I/O. OASIS3-MCT has been tested with different configurations on up to 32 000 processes, with components running on high-resolution grids with up to 1.5 million grid cells, and with over 10 000 2-D coupling fields. Several new features will be available in OASIS3-MCT-4.0, and some of those are also described.
   oasis in MPIESM

2. [Durán et al. 2017] Abstract. This work describes a mountain meteorological network that was in operation from 1999 to 2014 in a mountain range with elevations ranging from 1104 to 2428 m in Central Spain. Additionally, some technical details of the network are described, as well as variables measured and some meta information presented, which is expected to be useful for future users of the observational database. A strong emphasis is made on showing the observational methods and protocols evolution, as it will help researchers to understand the sources of errors, data gaps and the final stage of the network. This paper summarizes mostly the common sources of errors when designing and operating a small network of this kind, so it can be useful for individual researchers and small size groups that undertake a similar task on their own. Strengths and weaknesses of some of the variables measured are discussed and some basic calculations are made in order to show the potential of the database and to anticipate future deeper climatological analyses over the area. Finally, the configuration of an automatic mountain meteorology station is suggested as a result of the lessons learned and the the common state of the art automatic measuring techniques.
   Data, Guadarrama

3. [Escribano and Lazaro-Touza 2022] Abstract. La dimensión geopolítica de la transición entre un régimen energético fósil y otro renovable viene recibiendo una atención académica y política creciente. Una forma de explorar las implicaciones geopolíticas de las renovables es mediante el estudio de casos en contextos tan diferentes como América Latina y el Mediterráneo, pero las dos relevantes para España. El artículo explora tres aspectos de la compleja interacción entre geopolítica y energías renovables en ambas regiones: los flujos transfronterizos de hidroelectricidad, los de otras renovables modernas, y el potencial del hidrógeno verde. Compone así un conjunto de seis historias sobre la hidroelectricidad en el Nilo y el Paraná, los intercambios eléctricos renovables México-Estados Unidos y la inexistencia de los euromediterráneos, así como el potencial del hidrógeno verde en Chile y Marruecos.
   Geopolítica, renovables

4. [Fernández-Montes et al. 2017] Abstract. Precipitation and surface temperature are interdependent variables, both as a response to atmospheric dynamics and due to intrinsic thermodynamic relationships and feedbacks between them. This study analyzes the covariability of seasonal temperature (T) and precipitation (P) across the Iberian Peninsula (IP) using regional cli- mate paleosimulations for the period 1001–1990, driven by reconstructions of external forcings. Future climate (1990–2099) was simulated according to SRES scenarios A2 and B2. These simulations enable exploring, at high spatial resolution, robust and physically consistent relationships. In winter, positive P-T correlations dominate west-central IP (Pearson correlation coefficient ρ = +0.43, for 1001–1990), due to prevalent cold-dry and warm-wet conditions, while this relationship weakens and become negative towards mountainous, northern and eastern regions. In autumn, negative correlations appear in similar regions as in winter, whereas for summer they extend also to the N/NW of the IP. In spring, the whole IP depicts significant negative correlations, strongest for eastern regions (ρ = − 0.51). This is due to prevalent frequency of warm-dry and cold-wet modes in these regions and seasons. At the temporal scale, regional correlation series be- tween seasonal anomalies of temperature and precipitation (assessed in 31 years running windows in 1001– 1990) show very large multidecadal variability. For winter and spring, periodicities of about 50–60 years arise. The frequency of warm-dry and cold-wet modes appears correlated with the North Atlantic Oscillation (NAO), explaining mainly co-variability changes in spring. For winter and some regions in autumn, maximum and min- imum P-T correlations appear in periods with enhanced meridional or easterly circulation (low or high pressure anomalies in the Mediterranean and Europe). In spring and summer, the Atlantic Multidecadal Oscillation shows some fingerprint on the frequency of warm/cold modes. For future scenarios, an intensification of the negative P-T relationship is generally found, as a result of an in- creased frequency of the warm-dry mode.
   Paleo regional simulations

5. [Fick and Hijmans 2017] ABSTRACT: We created a new dataset of spatially interpolated monthly climate data for global land areas at a very high spatial resolution (approximately 1 km2 ). We included monthly temperature (minimum, maximum and average), precipitation, solar radiation, vapour pressure and wind speed, aggregated across a target temporal range of 1970–2000, using data from between 9000 and 60 000 weather stations. Weather station data were interpolated using thin-plate splines with covariates including elevation, distance to the coast and three satellite-derived covariates: maximum and minimum land surface temperature as well as cloud cover, obtained with the MODIS satellite platform. Interpolation was done for 23 regions of varying size depending on station density. Satellite data improved prediction accuracy for temperature variables 5–15% (0.07–0.17 C), particularly for areas with a low station density, although prediction error remained high in such regions for all climate variables. Contributions of satellite covariates were mostly negligible for the other variables, although their importance varied by region. In contrast to the common approach to use a single model formulation for the entire world, we constructed the final product by selecting the best performing model for each region and variable. Global cross-validation correlations were ≥ 0.99 for temperature and humidity, 0.86 for precipitation and 0.76 for wind speed. The fact that most of our climate surface estimates were only marginally improved by use of satellite covariates highlights the importance having a dense, high-quality network of climate station data.
   Surface climate dataset

6. [Gao et al. 2017] Abstract. The Paris Agreement proposed to keep the increase in global average temperature to well below 2 °C above pre-industrial levels and to pursue efforts to limit the temperature increase to 1.5 °C above pre-industrial levels. It was thus the first international treaty to endow the 2 °C global temperature target with legal effect. The qualitative expression of the ultimate objective in Article 2 of the United Nations Framework Convention on Climate Change (UNFCCC) has now evolved into the numerical temperature rise target in Article 2 of the Paris Agreement. Starting with the Second Assessment Report (SAR) of the Intergovernmental Panel on Cli- mate Change (IPCC), an important task for subsequent assessments has been to provide scientific informa- tion to help determine the quantified long-term goal for UNFCCC negotiation. However, due to involvement in the value judgment within the scope of non-scientific assessment, the IPCC has never scientifically af- firmed the unacceptable extent of global temperature rise. The setting of the long-term goal for addressing climate change has been a long process, and the 2 °C global temperature target is the political consensus on the basis of scientific assessment. This article analyzes the evolution of the long-term global goal for addressing climate change and its impact on scientific assessment, negotiation processes, and global low- carbon development, from aspects of the origin of the target, the series of assessments carried out by the IPCC focusing on Article 2 of the UNFCCC, and the promotion of the global temperature goal at the political level.
   History of the 2C agreement

7. [González-Aparicio et al. 2017] Abstract. The growing share of electricity production from solar and mainly wind resources constantly increases the stochastic nature of the power system. Modelling the high share of renewable energy sources – and in particular wind power – crucially depends on the adequate representation of the intermittency and characteristics of the wind resource which is related to the accuracy of the approach in converting wind speed data into power values. One of the main factors contributing to the uncertainty in these con- version methods is the selection of the spatial resolution. Although numerical weather prediction models can simulate wind speeds at higher spatial resolution (up to 1 1 km) than a reanalysis (generally, rang- ing from about 25 km to 70 km), they require high computational resources and massive storage sys- tems: therefore, the most common alternative is to use the reanalysis data. However, local wind features could not be captured by the use of a reanalysis technique and could be translated into misin- terpretations of the wind power peaks, ramping capacities, the behaviour of power prices, as well as bid- ding strategies for the electricity market. This study contributes to the understanding what is captured by different wind speeds spatial resolution datasets, the importance of using high resolution data for the conversion into power and the implications in power system analyses. It is proposed a methodology to increase the spatial resolution from a reanalysis. This study presents an open access renewable genera- tion time series dataset for the EU-28 and neighbouring countries at hourly intervals and at different geo- graphical aggregation levels (country, bidding zone and administrative territorial unit), for a 30 year period taking into account the wind generating fleet at the end of 2015.
   downscaling of wind

8. [Helbig et al. 2017] Abstract. Subgrid parameterizations are used in coarse-scale meteorological and land surface models to account for the impact of unresolved topography on wind speed. While various parameterizations have been suggested, these were generally validated on a limited number of measurements in specific geographical areas. We used high-resolution wind fields to investigate which terrain parameters most affect near-surface wind speed over complex topography under neutral conditions. Wind fields were simulated using the Advanced Regional Prediction System (ARPS) on Gaussian random fields as model topographies to cover a wide range of terrain characteristics. We computed coarse-scale wind speed, i.e., a spatial average over the large grid cell accounting for influence of unresolved topography, using a previously suggested subgrid parameterization for the sky view factor. We only require correlation length of subgrid topographic features and mean square slope in the coarse grid cell. Computed coarse-scale wind speed compared well with domain-averaged ARPS wind speed. To further statistically downscale coarse-scale wind speed, we use local, fine-scale topographic parameters, namely, the Laplacian of terrain elevations and mean square slope. Both parameters showed large correlations with fine-scale ARPS wind speed. Comparing downscaled numerical weather prediction wind speed with measurements from a large number of stations throughout Switzerland resulted in overall improved correlations and distribution statistics. Since we used a large number of model topographies to derive the subgrid parameterization and the downscaling framework, both are not scale dependent nor bound to a specific geographic region. Both can readily be implemented since they are based on easy to derive terrain parameters.
   Parameterization surface wind Switzerland

9. [Jungclaus et al. 2017] The pre-industrial millennium is among the periods selected by the Paleoclimate Model Intercompari- son Project (PMIP) for experiments contributing to the sixth phase of the Coupled Model Intercomparison Project (CMIP6) and the fourth phase of the PMIP (PMIP4). The past1000 transient simulations serve to investigate the re- sponse to (mainly) natural forcing under background condi- tions not too different from today, and to discriminate be- tween forced and internally generated variability on interan- nual to centennial timescales. This paper describes the mo- tivation and the experimental set-ups for the PMIP4-CMIP6 past1000 simulations, and discusses the forcing agents or- bital, solar, volcanic, and land use/land cover changes, and variations in greenhouse gas concentrations. The past1000 simulations covering the pre-industrial millennium from 850 Common Era (CE) to 1849CE have to be complemented by historical simulations (1850 to 2014 CE) following the CMIP6 protocol. The external forcings for the past1000 ex- periments have been adapted to provide a seamless transition across these time periods. Protocols for the past1000 simu- lations have been divided into three tiers. A default forcing data set has been defined for the Tier 1 (the CMIP6 past1000) experiment. However, the PMIP community has maintained the flexibility to conduct coordinated sensitivity experiments to explore uncertainty in forcing reconstructions as well as parameter uncertainty in dedicated Tier 2 simulations. Addi- tional experiments (Tier 3) are defined to foster collaborative model experiments focusing on the early instrumental period and to extend the temporal range and the scope of the simula- tions. This paper outlines current and future research foci and common analyses for collaborative work between the PMIP and the observational communities (reconstructions, instru- mental data).
   Forcings pmip4

10. [Kendon et al. 2017] Regional climate projections are used in a wide range of impact studies, from assessing future flood risk to climate change impacts on food and energy production. These model projections are typically at 12–50-km resolution, providing valuable regional detail but with inherent limitations, in part because of the need to parameterize convection. The first climate change experiments at convection-permitting resolution (kilometer-scale grid spacing) are now available for the United Kingdom; the Alps; Germany; Sydney, Australia; and the western United States. These models give a more realistic representation of convection and are better able to simulate hourly precipitation characteristics that are poorly represented in coarser-resolution climate models. Here we examine these new experiments to determine whether future midlatitude precipitation projections are robust from coarse to higher resolutions, with implications also for the tropics. We find that the explicit representation of the convective storms themselves, only possible in convection-permitting models, is necessary for capturing changes in the intensity and duration of summertime rain on daily and shorter time scales. Other aspects of rainfall change, including changes in seasonal mean precipitation and event occurrence, appear robust across resolutions, and therefore coarse-resolution regional climate models are likely to provide reliable future projections, provided that large-scale changes from the global climate model are reliable. The improved representation of convective storms also has implications for projections of wind, hail, fog, and lightning. We identify a number of impact areas, especially flooding, but also transport and wind energy, for which very high-resolution models may be needed for reliable future assessments.
    CPS schemes

11. [Knutti et al. 2017] Equilibrium climate sensitivity characterizes the Earth’s long-term global temperature response to increased atmospheric CO2 concentration. It has reached almost iconic status as the single number that describes how severe climate change will be. The consensus on the ‘likely’ range for climate sensitivity of 1.5 C to 4.5 C today is the same as given by Jule Charney in 1979, but now it is based on quantitative evidence from across the climate system and throughout climate history. The quest to constrain climate sensitivity has revealed important insights into the timescales of the climate system response, natural variability and limitations in observations and climate models, but also concerns about the simple concepts underlying climate sensitivity and radiative forcing, which opens avenues to better understand and constrain the climate response to forcing. Estimates of the transient climate response are better constrained by observed warming and are more relevant for predicting warming over the next decades. Newer metrics relating global warming directly to the total emitted CO2 show that in order to keep warming to within 2 C, future CO2 emissions have to remain strongly limited, irrespective of climate sensitivity being at the high or low end.
    Climate sensitivity

12. [Moreno-Chamarro et al. 2017] Abstract We assess the use of the meridional thermal- wind transport estimated from zonal density gradients to reconstruct the oceanic circulation variability during the last millennium in a forced simulation with the ECHO- G coupled climate model. Following a perfect-model approach, model-based pseudo-reconstructions of the Atlantic meridional overturning circulation (AMOC) and the Florida Current volume transport (FCT) are evaluated against their true simulated variability. The pseudo-FCT is additionally veri ed as proxy for AMOC strength and compared with the available proxy-based reconstruction. The thermal-wind component reproduces most of the simu- lated AMOC variability, which is mostly driven by inter- nal climate dynamics during the preindustrial period and by increasing greenhouse gases afterwards. The pseudo- reconstructed FCT reproduces well the simulated FCT and reasonably well the variability of the AMOC strength, including the response to external forcing. The pseudo- reconstructed FCT, however, the simulated variability at deep/shallow levels. Density changes responsible for the pseudo-reconstructed FCT are mainly driven by zonal temperature differences; salinity differences oppose but play a minor role. These results thus support the use of the thermal-wind relationship to recon- structtheoceaniccirculationpastvariability,inparticular at multidecadal timescales. Yet model-data comparison highlights important differences between the simulated and the proxy-based FCT variability. ECHO-G simulates a prominent weakening in the North Atlantic circulation that contrasts with the reconstructed enhancement. Our model results thus do not support the reconstructed FC minimum during the Little Ice Age. This points to a failure in the reconstruction, misrepresented processes in the model, or an important role of internal ocean dynamics.
    Ocean circulation, pseudoreality

13. [Matthes et al. 2017] Abstract: This paper describes the recommended solar forcing dataset for CMIP6 and highlights changes with re- spect to CMIP5. The solar forcing is provided for radiative properties, namely total solar irradiance (TSI), solar spec- tral irradiance (SSI), and the F10.7 index as well as parti- cle forcing, including geomagnetic indices Ap and Kp, and ionization rates to account for effects of solar protons, elec- trons, and galactic cosmic rays. This is the first time that a recommendation for solar-driven particle forcing has been provided for a CMIP exercise. The solar forcing datasets are provided at daily and monthly resolution separately for the CMIP6 preindustrial control, historical (1850–2014), and June 2017 future (2015–2300) simulations. For the preindustrial con- trol simulation, both constant and time-varying solar forcing components are provided, with the latter including variability on 11-year and shorter timescales but no long-term changes. For the future, we provide a realistic scenario of what solar behavior could be, as well as an additional extreme Maunder- minimum-like sensitivity scenario. This paper describes the forcing datasets and also provides detailed recommendations as to their implementation in current climate models.
    Solar forcing, cmip6

14. [REN21 2017] The 2017 edition of the REN21 Renewables Global Status Report (GSR) reveals a global energy transition well under way, with record new additions of installed renewable energy capacity, rapidly falling costs, particularly for solar PV and wind power, and the decoupling of economic growth and energy-related carbon dioxide emissions for the third year running. Innovative and more sustainable ways of meeting our energy needs are accelerating the paradigm shift away from a world run on fossil fuels. Despite these positive trends, the pace of the transition is not on track to achieve the goals established in the Paris Agreement to keep global temperature rise well below 2 degrees Celsius. So how can we speed up the energy transition with renewables? It is clear that policy is essential. Policy support for renewables in 2016, as in past years, focused mostly on power generation, whereas policies for the heating and cooling and transport sectors have remained virtually stagnant. This has to change. A systems approach is also needed across all sectors. There is a need to broaden the definition of a renewables-based energy system to one that moves beyond the traditional, narrow construct of renewable energy sources to one that looks at the role of supporting infrastructure, supply and demand balancing measures, e iciency measures and sector coupling, as well as a wide range of enabling technologies. The systems approach should become the norm in energy and infrastructure planning, financing and policy development...
    wind power

15. [Sanz Rodrigo et al. 2017b] Abstract: The increasing size of wind turbines, with rotors already spanning more than 150 m diameter and hub heights above 100 m, requires proper modeling of the atmospheric boundary layer (ABL) from the surface to the free atmosphere. Furthermore, large wind farm arrays create their own boundary layer structure with unique physics. This poses significant challenges to traditional wind engineering models that rely on surface-layer theories and engineering wind farm models to simulate the flow in and around wind farms. However, adopting an ABL approach offers the opportunity to better integrate wind farm design tools and meteorological models. The challenge is how to build the bridge between atmospheric and wind engineering model communities and how to establish a comprehensive evaluation process that identifies relevant physical phenomena for wind energy applications with modeling and experimental requirements. A framework for model verification, validation, and uncertainty quantification is established to guide this process by a systematic evaluation of the modeling system at increasing levels of complexity. In terms of atmospheric physics, ‘building the bridge’ means developing models for the so-called ‘terra incognita,’ a term used to designate the turbulent scales that transition from mesoscale to microscale. This range of scales within atmospheric research deals with the transition from parameterized to resolved turbulence and the improvement of surface boundary-layer parameterizations. The coupling of meteorological and wind engineering flow models and the definition of a formal model evaluation methodology, is a strong area of research for the next generation of wind conditions assessment and wind farm and wind turbine design tools. Some fundamental challenges are identified in order to guide future research in this area.
    Meso-micro

16. [Sanz Rodrigo et al. 2017a] Abstract. The GEWEX Atmospheric Boundary Layer Studies (GABLS) 1, 2 and 3 are used to develop a methodology for the design and testing of Reynolds-averaged Navier–Stokes (RANS) atmospheric boundary layer (ABL) models for wind energy applications. The first two GABLS cases are based on idealized boundary conditions and are suitable for verification purposes by comparing with results from higher-fidelity models based on large-eddy simulation. Results from three single-column RANS models, of 1st, 1.5th and 2nd turbulence closure order, show high consistency in predicting the mean flow. The third GABLS case is suitable for the study of these ABL models under realistic forcing such that validation versus observations from the Cabauw meteorological tower are possible. The case consists on a diurnal cycle that leads to a nocturnal low-level jet and addresses fundamental questions related to the definition of the large-scale forcing, the interaction of the ABL with the surface and the evaluation of model results with observations. The simulations are evaluated in terms of surface-layer fluxes and wind energy quantities of interest: rotor equivalent wind speed, hub-height wind direction, wind speed shear and wind direction veer. The characterization of mesoscale forcing is based on spatially and temporally averaged momentum budget terms from Weather Research and Forecasting (WRF) simulations. These mesoscale tendencies are used to drive single-column models, which were verified previously in the first two GABLS cases, to first demonstrate that they can produce similar wind profile characteristics to the WRF simulations even though the physics are more simplified. The added value of incorporating different forcing mechanisms into microscale models is quantified by systematically removing forcing terms in the momentum and heat equations. This mesoscale-to-microscale modeling approach is affected, to a large extent, by the input uncertainties of the mesoscale tendencies. Deviations from the profile observations are reduced by introducing observational nudging based on measurements that are typically available from wind energy campaigns. This allows the discussion of the added value of using remote sensing instruments versus tower measurements in the assessment of wind profiles for tall wind turbines reaching heights of 200 m.
    Advection and gradient terms

17. [Simpkins 2017] Progress in climate modelling Development and planning for the sixth phase of the Coupled Model Intercomparison Project (CMIP6) has been years in the making. Nature Climate Change speaks to the Chair of the CMIP Panel, Veronika Eyring, about the aims and projected outcomes of the project.
    cmips

18. [Steiger and Smerdon 2017] Abstract. Because of the relatively brief observational record, the climate dynamics that drive multiyear to centennial hydroclimate variability are not adequately charac- terized and understood. Paleoclimate reconstructions based on data assimilation (DA) optimally fuse paleoclimate prox- ies with the dynamical constraints of climate models, thus providing a coherent dynamical picture of the past. DA is therefore an important new tool for elucidating the mecha- nisms of hydroclimate variability over the last several mil- lennia. But DA has so far remained untested for global hy- droclimate reconstructions. Here we explore whether or not DA can be used to skillfully reconstruct global hydroclimate variability along with the driving climate dynamics. Through a set of idealized pseudoproxy experiments, we find that an established DA reconstruction approach can in principle be used to reconstruct hydroclimate at both annual and sea- sonal timescales. We find that the skill of such reconstruc- tions is generally highest near the proxy sites. This set of re- construction experiments is specifically designed to estimate a realistic upper bound for the skill of this DA approach. Importantly, this experimental framework allows us to see where and for what variables the reconstruction approach may never achieve high skill. In particular for tree rings, we find that hydroclimate reconstructions depend critically on moisture-sensitive trees, while temperature reconstruc- tions depend critically on temperature-sensitive trees. Real- world DA-based reconstructions will therefore likely require a spatial mixture of temperature- and moisture-sensitive trees to reconstruct both temperature and hydroclimate variables. Additionally, we illustrate how DA can be used to elucidate the dynamical mechanisms of drought with two examples: tropical drivers of multiyear droughts in the North American Southwest and in equatorial East Africa. This work thus pro- vides a foundation for future DA-based hydroclimate recon- structions using real-proxy networks while also highlighting the utility of this important tool for hydroclimate research.
    Data Assimilation Hidroclimate

19. [Zhao et al. 2017] Wheat, rice, maize, and soybean provide two-thirds of human caloric intake. Assessing the impact of global temperature increase on production of these crops is therefore critical to maintaining global food supply, but different studies have yielded different results. Here, we investigated the impacts of temperature on yields of the four crops by compiling extensive published results from four analytical methods: global grid-based and local point-based models, statistical regressions, and field-warming experiments. Results from the different methods consistently showed negative temperature impacts on crop yield at the global scale, generally underpinned by similar impacts at country and site scales. Without CO2 fertilization, effective adaptation, and genetic improvement, each degree-Celsius increase in global mean temperature would, on average, reduce global yields of wheat by 6.0%, rice by 3.2%, maize by 7.4%, and soybean by 3.1%. Results are highly heterogeneous across crops and geographical areas, with some positive impact estimates. Multi- method analyses improved the confidence in assessments of future climate impacts on global major crops and suggest crop- and region- specific adaptation strategies to ensure food security for an increas- ing world population.
    food production

20. [Zhang and Wang 2017] A high-resolution regional atmospheric model is employed to project the late twenty-first-century changes of tropical cyclone (TC) activity over the western North Pacific (WP) and southwest Pacific (SP). The model realistically reproduces the basic features of the TC climatology in the present-day simulation. Future pro- jections under the representative concentration pathway 4.5 (RCP45) and 8.5 (RCP85) scenarios are in- vestigated. The results show no significant change of TC genesis frequency (TCGF) in the WP by RCP45 due to the cancellation of the reduction over the western part and the increase over the eastern part together with a considerable decrease of TCGF by RCP85 due to the excessive TCGF reduction in the western part. The TCGF over the SP consistently decreases from RCP45 to RCP85. Despite the fact that the simulated maximum surface wind speeds are below 52 m s21, the change with more strong TCs and fewer weak TCs is robust. The future changes in the TC genesis locations and translational speeds modulate the TC lifetime and frequency of occurrence. The TC genesis potential index (GPI) is used to evaluate the projected TCGF changes. The results show that low-level vorticity and midtropospheric vertical velocity largely contribute to the reduction of GPI in the western part of the WP, while vertical wind shear and midtropospheric vertical velocity mainly contribute to the decrease of GPI over the SP. The weakening of the monsoon trough is found to be responsible for the decreases of GPI and TCGF over the western part of the WP.
    cps