What makes a ‘REDD’ country?

Despite remaining uncertainties, Reducing Emissions from Deforestation and forest Degradation in developing countries (REDD) projects are being planned and implemented across the tropics, primarily targeting countries with high forest cover and high deforestation rates. However, there is growing recognition that REDD planning requires a broadened approach; a future REDD mechanism should incentivise emissions reduction in all developing forested countries, and should address critical non-carbon dimensions of REDD implementation—quality of forest governance, conservation priorities, local rights and tenure frameworks, and sub-national project potential. When considering this broader suite of factors, different REDD priorities can emerge, including in countries with low forest cover that would be overlooked by conventional site selection criteria. Using the Philippines as a case study, the paper highlights the importance of an enabling environment to REDD implementation, and presents a more comprehensive and inclusive approach for thinking about what comprises a “REDD country.”     

Classification of precipitation types using fall velocity-diameter relationships from 2D-video distrometer measurements

Fall velocity-diameter relationships for four different snowflake types (dendrite, plate, needle, and graupel) were investigated in northeastern South Korea, and a new algorithm for classifying hydrometeors is proposed for distrometric measurements based on the new relationships. Falling ice crystals (approximately 40 000 particles) were measured with a two-dimensional video disdrometer (2DVD) during a winter experiment from 15 January to 9 April 2010. The fall velocity-diameter relationships were derived for the four types of snowflakes based on manual classification by experts using snow photos and 2DVD measurements: the coefficients (exponents) for different snowflake types were 0.82 (0.24) for dendrite, 0.74 (0.35) for plate, 1.03 (0.71) for needle, and 1.30 (0.94) for graupel, respectively. These new relationships established in the present study (PS) were compared with those from two previous studies. Hydrometeor types were classified with the derived fall velocity-diameter relationships, and the classification algorithm was evaluated using 3× 3 contingency tables for one rain-snow transition event and three snowfall events. The algorithm showed good performance for the transition event: the critical success indices (CSIs) were 0.89, 0.61 and 0.71 for snow, wet-snow and rain, respectively. For snow events, the algorithm performance for dendrite and plate (CSIs = 1.0 and 1.0, respectively) was better than for needle and graupel (CSIs = 0.67 and 0.50, respectively).     

Ternary forecast of heavy snowfall in the Honam area,Korea

The objective of this study is to improve the statistical modeling for the ternary forecast of heavy snowfall in the Honam area in Korea. The ternary forecast of heavy snowfall consists of one of three values, 0 for less than 50 mm, 1 for an advisory (50–150 mm), and 2 for a warning (more than 150 mm). For our study, the observed daily snow amounts and the numerical model outputs for 45 synoptic factors at 17 stations in the Honam area during 5 years (2001 to 2005) are used as observations and potential pre...     

A robust sequential CO2 emissions strategy based on optimal control of atmospheric CO2 concentrations

This paper formally introduces the concept of mitigation as a stochastic control problem. This is illustrated by applying a digital state variable feedback control approach known as Non-Minimum State Space (NMSS) control to the problem of specifying carbon emissions to control atmospheric CO₂ concentrations in the presence of uncertainty. It is shown that the control approach naturally lends itself to integrating both anticipatory and reflexive mitigation strategies within a single unified framework. The framework explicitly considers the closed-loop nature of climate mitigation, and employs a policy orientated optimisation procedure to specify the properties of this closed-loop system. The product of this exercise is a control law that is suitably conditioned to regulate atmospheric CO₂ concentrations through assimilating online information within a 25-year review cycle framework. It is shown that the optimal control law is also robust when faced with significant levels of uncertainty about the functioning of the global carbon cycle.     

Source identification of PM2.5 particles measured in Gwangju, Korea

The UNMIX and Chemical Mass Balance (CMB) receptor models were used to investigate sources of PM_2.5 aerosols measured between March 2001 and February 2002 in Gwangju, Korea. Measurements of PM_2.5 particles were used for the analysis of carbonaceous species (organic (OC) and elemental carbon (EC)) using the thermal manganese dioxide oxidation (TMO) method, the investigation of seven ionic species using ion chromatography (IC), and the analysis of twenty-four metal species using Inductively Coupled Plasma (ICP)-Atomic Emission Spectrometry (AES)/ICP-Mass Spectrometry (MS). According to annual average PM_2.5 source apportionment results obtained from CMB calculations, diesel vehicle exhaust was the major contributor, accounting for 33.4% of the measured PM_2.5 mass (21.5 μg m^− 3), followed by secondary sulfate (14.6%), meat cooking (11.7%), secondary organic carbon (8.9%), secondary nitrate (7.6%), urban dust (5.5%), Asian dust (4.4%), biomass burning (2.8%), sea salt (2.7%), residual oil combustion (2.6%), gasoline vehicle exhaust (1.9%), automobile lead (0.5%), and components of unknown sources (3.4%). Seven PM_2.5 sources including diesel vehicles (29.6%), secondary sulfate (17.4%), biomass burning (14.7%), secondary nitrate (12.6%), gasoline vehicles (12.4%), secondary organic carbon (5.8%) and Asian dust (1.9%) were identified from the UNMIX analysis. The annual average source apportionment results from the two models are compared and the reasons for differences are qualitatively discussed for better understanding of PM_2.5 sources.Additionally, the impact of air mass pathways on the PM_2.5 mass was evaluated using air mass trajectories calculated with the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) backward trajectory model. Source contributions to PM_2.5 collected during the four air mass patterns and two event periods were calculated with the CMB model and analyzed. Results of source apportionment revealed that the contribution of diesel traffic exhaust (47.0%) in stagnant conditions (S) was much higher than the average contribution of diesel vehicle exhaust (33.4%) during the sampling period. During Asian dust (AD) periods when the air mass passed over the Korean peninsula, Asian dust and secondary organic carbon accounted for 25.2 and 23.0% of the PM_2.5 mass, respectively, whereas Asian dust contributed only 10.8% to the PM_2.5 mass during the AD event when the air mass passed over the Yellow Sea. The contribution of biomass burning to the PM_2.5 mass during the biomass burning (BB) event equaled 63.8%.     

Orbital forced frequencies in the 975 000 year pollen record from Tenagi Philippon (Greece)

Frequency analysis was applied to different time series obtained from the 975 ka pollen record of Tenagi Philippon (Macedonia, Greece). These time series are characteristic of different vegetation types related to specific climatic conditions. Time control of the 196 m deep core was based on 11 finite 14C dates in the upper 17 m, magnetostratigraphy and correlation with the marine oxygen isotope stratigraphy. Maximum entropy spectrum analyses and thomson multitaper spectrum analysis were applied using the complete time series. Periods of 95–99, 40–45, 24.0–25.5 and 19–21 ka which can be related to orbital forcing, as well as periods of about 68, 30 ka and of about 15.5, 13.5, 12 and 10.5 ka were detected. The detected periods of about 68, 30 ka and 16, 14, 12, 10.5 ka are likely to be harmonics and combination tones of the periods related to orbital forcing. The period of around 30 ka is possibly a secondary peak of obliquity. To study the stability of the detected periods through time, analysis with a moving window was employed. Signals in the eccentricity band were detected clearly during the last 650 ka. In the precession band, detected periods of about 24 ka show an increase in amplitude during the last 650 ka. The evolution of orbital frequencies during the last 1.0 Ma is in general agreement with the results of other marine and continental time series. Time series related to different climatic settings showed a different response to orbital forcing. Time series of vegetational elements sensitive to changes in net precipitation were forced in the precession and obliquity bands. changes in precession caused changes in the monsoon system, which indirectly had a strong influence on the climatic history of Greece. Time series of vegetational elements which are more indicative of changes in annual temperature are forced in the eccentricity band.     

Modelling Korean extreme rainfall using a Kappa distribution and maximum likelihood estimate

Summary Attempts to use the 4-parameter Kappa distribution (K4D) with the maximum likelihood estimates (MLE) on the summer extreme daily rainfall data at 61 gauging stations over South Korea have been made to obtain reliable quantile estimates for several return periods. A numerical algorithm for searching MLE of K4D by minimizing the negative log-likelihood function with penalty method has been described. The isopluvial maps of estimated design values corresponding to selected return periods have been presented. The highest return values are centered at sites in the south-western part of the Korean peninsula. The distribution of return values for annual maxima of 2-day precipitation (AMP2) is more similar to the climatological features of annual total precipitation of Korea than that of annual maxima of daily precipitation (AMP1). Our results of return values delineate well the horizontal patterns of the heavy precipitation over the Korean peninsula. Received January 15, 2001 Revised October 8, 2001     

Long-term simulations of the sulfur concentrations over the China, Japan and Korea: A model comparison study

Three comprehensive acid deposition models were used to simulate the sulfur concentrations over northeast Asia over the period covering entire year of 2002, and discussed the aggregated uncertainties and discrepancies of the three models. The participating models are from the countries participating in the project of Longrange Transboundary Air Pollutants in Northeast Asia (LTP): China, Japan and Korea. The Eulerian Model-3/CMAQ (by China), Regional Air Quality Model (RAQM, by Japan), and Comprehensive Acid Deposition Model (CADM, by Korea) were employed by each country with common emissions data established by the administrative agencies of China, Japan and Korea. The episodic simulation results between 1 to 15, March 2002 are also presented, during which aircraft measurements were carried out over the Yellow sea. The episodic results show both a wide short-term variability in simulations against measurements, and maximum concentration differences of 3～5 times among the three models, requiring that further attention before confidence among the three models can be claimed for short-term simulations. However, the year-long cumulative simulations showed almost the same general features, with lower aggregated uncertainties between the three models, produced by the long term integration over northeast Asia.     

Examination of climate risk using a modified uncertainty matrix framework—Applications in the water sector

Previous climate risk assessments provide important methodological insights into how to derive tractable research questions and the appropriate use of data under uncertainty, as well as identifying steps that benefit from stakeholder involvement. Here we propose the use of a framework for the systematic and objective exploration of climate risk assessments. The matrix facilitates a breakdown of information about aim and context, main results, methodological choices, stakeholder involvement, sources and characteristics of uncertainties and overall weaknesses. We then apply the matrix to three risk assessments in the water sector to explore some methodological strengths and weaknesses of approaches strongly linked to climate model outputs (top-down) versus those that originate from local knowledge of climate exposures (bottom-up), and demonstrate that closer integration with social and physical sciences is more likely to yield robust climate risk assessments.