A verification framework for interannual-to-decadal predictions experiments

Decadal predictions have a high profile in the climate science community and beyond, yet very little is known about their skill. Nor is there any agreed protocol for estimating their skill. This paper proposes a sound and coordinated framework for verification of decadal hindcast experiments. The framework is illustrated for decadal hindcasts tailored to meet the requirements and specifications of CMIP5 (Coupled Model Intercomparison Project phase 5). The chosen metrics address key questions about the information content in initialized decadal hindcasts. These questions are: (1) Do the initial conditions in the hindcasts lead to more accurate predictions of the climate, compared to un-initialized climate change projections? and (2) Is the prediction model’s ensemble spread an appropriate representation of forecast uncertainty on average? The first question is addressed through deterministic metrics that compare the initialized and uninitialized hindcasts. The second question is addressed through a probabilistic metric applied to the initialized hindcasts and comparing different ways to ascribe forecast uncertainty. Verification is advocated at smoothed regional scales that can illuminate broad areas of predictability, as well as at the grid scale, since many users of the decadal prediction experiments who feed the climate data into applications or decision models will use the data at grid scale, or downscale it to even higher resolution. An overall statement on skill of CMIP5 decadal hindcasts is not the aim of this paper. The results presented are only illustrative of the framework, which would enable such studies. However, broad conclusions that are beginning to emerge from the CMIP5 results include (1) Most predictability at the interannual-to-decadal scale, relative to climatological averages, comes from external forcing, particularly for temperature; (2) though moderate, additional skill is added by the initial conditions over what is imparted by external forcing alone; however, the impact of initialization may result in overall worse predictions in some regions than provided by uninitialized climate change projections; (3) limited hindcast records and the dearth of climate-quality observational data impede our ability to quantify expected skill as well as model biases; and (4) as is common to seasonal-to-interannual model predictions, the spread of the ensemble members is not necessarily a good representation of forecast uncertainty. The authors recommend that this framework be adopted to serve as a starting point to compare prediction quality across prediction systems. The framework can provide a baseline against which future improvements can be quantified. The framework also provides guidance on the use of these model predictions, which differ in fundamental ways from the climate change projections that much of the community has become familiar with, including adjustment of mean and conditional biases, and consideration of how to best approach forecast uncertainty.     

A theory for the scalar roughness and the scalar transfer coefficients over snow and sea ice

Although the bulk aerodynamic transfer coefficients for sensible (C _H ) and latent (C _E ) heat over snow and sea ice surfaces are necessary for accurately modeling the surface energy budget, they have been measured rarely. This paper, therefore, presents a theoretical model that predicts neutral-stability values of C _H and C _E as functions of the wind speed and a surface roughness parameter. The crux of the model is establishing the interfacial sublayer profiles of the scalars, temperature and water vapor, over aerodynamically smooth and rough surfaces on the basis of a surface-renewal model in which turbulent eddies continually scour the surface, transferring scalar contaminants across the interface by molecular diffusion. Matching these interfacial sublayer profiles with the semi-logarithmic inertial sublayer profiles yields the roughness lengths for temperature and water vapor. When coupled with a model for the drag coefficient over snow and sea ice based on actual measurements, these roughness lengths lead to the transfer coefficients. C _E is always a few percent larger than CH. Both decrease monotonically with increasing wind speed for speeds above 1 m s^–1, and both increase at all wind speeds as the surface gets rougher. Both, nevertheless, are almost always between 1.0 × 10^–3 and 1.5 × 10^–3.     

An Optical Disdrometer for Measuring Present Weather Parameters

A new present weather identifier（PWI） based on occlusion and scattering techniques is presented in the study. The present weather parameters are detectable by the meteorological optical range（MOR） approximately up to 50 km and by droplets with diameters ranging from 0.125 mm to 22 mm with velocities up to 16 m s-1. The MOR error is less than 8% for the MOR within 10 km and less than 15% for farther distances. Moreover, the size errors derived from various positions of the light sheet by the particles were checked within ± 0.1 mm ± 5%. The comparison shows that the MOR, in a sudden shower event, is surprisingly consistent with those of the sentry visibility sensors（SVS） with a correlation coefficient up to 98%. For the rain amounts derived from the size and velocity of the droplets, the daily sums by the PWI agree within 10% of those by the Total Rain Weighing Sensor（TRwS205） and the rain gauge. Combined with other sensors such as temperature, humidity, and wind, the PWI can serve as a present weather sensor to distinguish several weather types such as fog, haze, mist, rain, hail, and drizzle.     

地基遥感大气水汽总量和云液态水总量的研究

介绍了地基微波辐射计遥感反演大气柱中的水汽总量和云液态水总量的辐射传输原理和反演方法。给出了实用的有气候代表性的北京地区4个季节的反演公式，并对反演公式进行了数值检验，分析了反演精度：春、夏、秋、冬4季水汽总量反演的相对标准偏差分别为3．1％、1．6％、2．2％和2．4％。用反演公式反演在香河探测的NASA微波辐射计资料发现：微波辐射计反演的水汽总量平均比探空测量值偏大O．21cm，二者的线性相关系数为0．988．均方根误差为0．16cm：云液态水总量除降水云天外．值均在0．1mm以下。     

CoLM模式对青藏高原中部BJ站陆面过程的数值模拟

利用公共陆面模式Common Land Model(CoLM)及"全球协调加强观测计划之亚澳季风青藏高原试验"(CAMP/Tibet)中那曲地区Bujiao(BJ)站2002—2004年的观测资料对该地区进行了单点数值模拟试验。通过比较模拟与观测的地表能量通量,表明CoLM较成功地模拟了该地区的能量分配。模式对向上的短波辐射、向上的长波辐射、净辐射及土壤热通量模拟得较好,但冬季存在偏差。进一步比较了模拟和观测的土壤温度及土壤湿度,发现浅层60 cm土壤温度模拟较好,深层存在偏差,表现为土壤温度变化滞后于实际变化。土壤湿度总体偏小,尤其是冬季冻结期,土壤冻融过程中忽略了土壤液态水在温度0℃以下仍能存在,含冰量模拟偏高。     

A western North Pacific tropical cyclone intensity prediction scheme

A western North Pacific tropical cyclone (TC) intensity prediction scheme (WIPS) is developed based on TC samples from 1996 to 2002 using the stepwise regression technique, with the western North Pacific divided into three sub-regions: the region near the coast of East China (ECR), the South China Sea region (SCR), and the far oceanic region (FOR). Only the TCs with maximum sustained surface wind speed greater than 17.2 m s⁻¹ are used in the scheme. Potential predictors include the climatology and persistence factors, synoptic environmental conditions, potential intensity of a TC and proximity of a TC to land. Variances explained by the selected predictors suggest that the potential intensity of a TC and the proximity of a TC to land are significant in almost all the forecast equations. Other important predictors include vertical wind shear in ECR, 500-hPa geopotential height anomaly at the TC center, zonal component of TC translation speed in SCR, intensity change of TC 12 or 24 h prior to initial time, and the longitude of TC center in FOR.     

Multi-Source Emission Determination Using an Inverse-Dispersion Technique

Inverse-dispersion calculations can be used to infer atmospheric emission rates through a combination of downwind gas concentrations and dispersion model predictions. With multiple concentration sensors downwind of a compound source (whose component positions are known) it is possible to calculate the component emissions. With this in mind, a field experiment was conducted to examine the feasibility of such multi-source inferences, using four synthetic area sources and eight concentration sensors arranged in different configurations. Multi-source problems tend to be mathematically ill-conditioned, as expressed by the condition number κ. In our most successful configuration (average κ = 4.2) the total emissions from all sources were deduced to within 10% on average, while component emissions were deduced to within 50%. In our least successful configuration (average κ = 91) the total emissions were calculated to within only 50%, and component calculations were highly inaccurate. Our study indicates that the most accurate multi-source inferences will occur if each sensor is influenced by only a single source. A “progressive” layout is the next best: one sensor is positioned to “see” only one source, the next sensor is placed to see the first source and another, a third sensor is placed to see the previous two plus a third, and so on. When it is not possible to isolate any sources κ is large and the accuracy of a multi-source inference is doubtful.     

An Efficient Non-iterative Bulk Parametrization of Surface Fluxes for Stable Atmospheric Conditions Over Polar Sea-Ice

In climate and weather prediction models the near-surface turbulent fluxes of heat and momentum and related transfer coefficients are usually parametrized on the basis of Monin–Obukhov similarity theory (MOST). To avoid iteration, required for the numerical solution of the MOST equations, many models apply parametrizations of the transfer coefficients based on an approach relating these coefficients to the bulk Richardson number \(Ri_{b}\). However, the parametrizations that are presently used in most climate models are valid only for weaker stability and larger surface roughnesses than those documented during the Surface Heat Budget of the Arctic Ocean campaign (SHEBA). The latter delivered a well-accepted set of turbulence data in the stable surface layer over polar sea-ice. Using stability functions based on the SHEBA data, we solve the MOST equations applying a new semi-analytic approach that results in transfer coefficients as a function of \(Ri_{b}\) and roughness lengths for momentum and heat. It is shown that the new coefficients reproduce the coefficients obtained by the numerical iterative method with a good accuracy in the most relevant range of stability and roughness lengths. For small \(Ri_{b}\), the new bulk transfer coefficients are similar to the traditional coefficients, but for large \(Ri_{b}\) they are much smaller than currently used coefficients. Finally, a possible adjustment of the latter and the implementation of the new proposed parametrizations in models are discussed.     

Some characteristics of ozone profiles above Hong Kong

Summary Analysis of ozonesonde data shows that in the lower troposphere above Hong Kong, there is a relative maximum with respect to height in all seasons except winter. In the upper troposphere, there is with respect to height a relative minimum in the seasonally averaged ozone mixing ratio in winter. Ozone mixing ratios in the upper troposphere in winter and spring can be significantly enhanced by stratospheric intrusions associated with the passage of cold fronts and upper cut-off lows.For Hong Kong, the seasonally averaged total ozone has the highest value in spring, and the lowest in winter. The seasonally averaged total tropospheric ozone also has the highest value in spring, but the lowest in summer. In a relative sense, total tropospheric ozone contributes most to the total ozone in spring and the least in summer.The phase of the total ozone anomaly above Hong Kong is influenced by the Quasi-Biennial Oscillation (QBO), with the positive anomaly associated with the easterly phase of QBO, and the negative anomaly the westerly phase.     

Reanalysis of western Pacific typhoons in 2004 with multi-satellite observations

Summary A pilot tropical cyclone reanalysis project was conducted to construct a reliable, high temporal and spatial resolution tropical cyclone dataset for selected western Pacific typhoons in summer 2004, with the application of the latest satellite observations and a 4-dimensional variational data assimilation method. Primary data used for the reanalysis include SSM/I rain rate, GOES-retrieved upper-level wind, QuikSCAT surface wind, Aqua AIRS/AMSU retrieved temperature and moisture profiles, and JTWC best track data. A regular reanalysis procedure was established and up to 12 western Pacific typhoons have been reanalyzed. The reanalysis period covers the entire life cycle of a tropical cyclone, from a few days prior to its genesis to its final decay stage. A preliminary analysis shows that the reanalysis product significantly improves typhoon intensity, structure, and track, compared to the NCEP operational final analysis. The validation of the TC structure against independent observations shows that the reanalysis reproduces well the asymmetric characteristics of TC rain bands and cloud bands. A further modeling experiment with an initial condition from the reanalysis product reveals a significant improvement in typhoon intensity forecast compared to a parallel experiment with an initial condition from the NCEP final analysis, which provides a further indication of quality of the tropical cyclone reanalysis. The reanalysis product and the raw observational data will soon be posted on the data server of the IPRC Asia-Pacific Data-Research Center () for public use.