A new paleoclimate classification for deep time

A new paleoclimate classification for deep time

    A New Paleoclimate Classification for Deep Time Laiming Zhang, Chengshan Wang, Xianghui Li, Ke Cao, Ying Song, Bin Hu, Dawei Lu, Qian...

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    A New Paleoclimate Classification for Deep Time Laiming Zhang, Chengshan Wang, Xianghui Li, Ke Cao, Ying Song, Bin Hu, Dawei Lu, Qian Wang, Xiaojing Du, Shuo Cao PII: DOI: Reference:

S0031-0182(15)00711-7 doi: 10.1016/j.palaeo.2015.11.041 PALAEO 7593

To appear in:

Palaeogeography, Palaeoclimatology, Palaeoecology

Received date: Revised date: Accepted date:

26 September 2015 23 November 2015 24 November 2015

Please cite this article as: Zhang, Laiming, Wang, Chengshan, Li, Xianghui, Cao, Ke, Song, Ying, Hu, Bin, Lu, Dawei, Wang, Qian, Du, Xiaojing, Cao, Shuo, A New Paleoclimate Classification for Deep Time, Palaeogeography, Palaeoclimatology, Palaeoecology (2015), doi: 10.1016/j.palaeo.2015.11.041

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ACCEPTED MANUSCRIPT A New Paleoclimate Classification for Deep Time

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Dawei Lue, Qian Wanga, Xiaojing Dua, Shuo Caoa

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Laiming Zhanga, Chengshan Wanga,*, Xianghui Lib, Ke Caoc, Ying Songd, Bin Hua,

State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences,

Beijing 100083, China, and School of the Earth Science and Resources, China University of

State Key Laboratory of Mineral Deposit Research, School of Earth Sciences and Engineering,

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Geosciences, Beijing 100083, China

Nanjing University, Nanjing 210093, China c

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The Key Laboratory of Marine Hydrocarbon Resources and Environment Geology, Qingdao institute

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of marine geology, Qingdao 266071, China

School of Geosciences, China University of Petroleum, Qingdao 266580, China

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College of Geological Science and Engineering, Shandong University of Science and Technology,

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Qingdao 266510, China

Abstract

In deep time, climates are mainly classified by climatically sensitive deposits, paleontological evidences, and

modeling. However, they only have limited applicability in deep time studies. Here, we propose a new

paleoclimate classification based on the widely used Köppen climate classification. The proposed new

classification is simple, quantitative, but bridges the gap between the modern and deep time climate studies. The

new classification is closely related to but differs from that of Köppen by changing some limits. A world map using

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To whom correspondence should be addressed. E-mail: [email protected] (CW).

ACCEPTED MANUSCRIPT the new classification shows the same patterns as the world map of the Köppen climate classification. Using the

new classification, we are able to solve a long-standing problem about the climates of East Asia during the Eocene.

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We found that East Asia shared the same climate type (Ca: Subtropical) at all studied locations, supporting the

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hypothesis of monsoon or monsoon-like climate prevailed there during the Eocene.

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Key word: Paleoclimate classification; Deep time; Köppen climate classification

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1. Introduction

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Systematic grouping of climates into different types based on particular attributes brings

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structure, order and simplicity to a complex climatic system, by which allowing us to set spatial

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boundaries to conditions on Earth‟s surface (Oliver, 2005). A variety of classifications have been established for modern climates based on specific applications (Essenwanger, 2001; Farmer,

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2013). However, paleoclimatologists have found it difficult to apply these modern climate classifications to deep time (pre-Quaternary), and there are no widely accepted paleoclimate classifications.

Deep time climates present special problems for classification, because the instrumental meteorological parameters are totally lacking, such as the temperature, precipitation, wind, and air pressure. All we know about the paleoclimate comes from indirect evidence from the geologic records, i.e., the proxies. However, interpretations of indirect evidence is limited because of our incomplete knowledge on the measurements of proxies and relatively poor understanding on climate dynamics in the past. In consequence, paleoclimate information often has no direct

ACCEPTED MANUSCRIPT relation to climatic variables used for modern climate classification, a gap between modern and deep time climate studies.

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Clearly, a paleoclimate classification should be simple enough to describe the limited

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climatic data available in deep time studies and be relate to modern climates, by which serving a bridge over the gap between modern and deep time climate. More importantly, the paleoclimate classification should be quantitative, with same measures of modern climates when studying

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geological ages and regions. We need to clarify that there is no natural boundary in the world that

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is able to distinctively define two climate types. Although the boundary between types are quantitatively defined, what the climate classification defined is in fact to show the overall

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characteristics.

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Here we propose a new classification for paleoclimates in deep time based on these

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considerations. The new classification is established based on the widely used Köppen climate classification. However, what we need to note is that the „extinct climate‟ in deep time can not be

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discriminated in the new climate classification.

2. Terminology

In this paper, „deep time‟ refers to the pre-Quaternary, the part of Earth‟s history that have to be reconstructed from rock, and is older than historical or ice core records (Montañez et al., 2011; Soreghan, 2005). In a narrow sense, climate can be considered as the “average weather” for 30 years. In a wider sense, climate is the state of all the statistical description of the climate system (Farmer,

ACCEPTED MANUSCRIPT 2013). Climate classification is a systematic arrangement, gathering climates into groups or

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categories using boundaries defined by similar conditions and meteorological elements. In this

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3. Previous Paleoclimate Classifications

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study, the discussion of classifications is limited to global and regional climates.

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In many previous studies, paleoclimates have been classified by climatically sensitive deposits, paleontologic evidence, and by numerical modeling.

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Since the middle of the last century, many researchers have attempted to reconstruct climate

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zones in deep time by analyzing the distribution of climatically sensitive deposits

rdossy,

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1982; Hallam, 1984, 1985; Strakhov, 1967). Deposits indicative of special conditions, such as evaporites, calcretes, tillites, laterites and bauxites, are widely distributed both in time and space.

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They have been used to classify paleoclimates in the early Phanerozoic before the rise of land plants or animals (Boucot et al., 2013), and younger times (Boucot et al., 2013; Chumakov, 2004; Dera et al., 2009; Guo et al., 2008; Winguth and Maier-Reimer, 2005). Most of these indicators are qualitative, although some of them can be interpreted as semi-quantitative (Craggs et al., 2012; Tabor and Poulsen, 2008). However, climate classifications based on these commonly have no more than 5 climatic zones on a global scale, and even fewer on regional scales. Such low-resolution classifications cannot always provide enough climatic information for paleoclimate studies. Palynological and macro-plant materials have been extensively used to evaluate ancient

ACCEPTED MANUSCRIPT climatic conditions (Boucot et al., 2013; Parrish, 1998; Royer, 2012). The abundance, diversity and distribution of vegetation types (Larsson et al., 2010), morphology and structure of the plant,

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especially the leaf physiognomy (Spicer, 2012; Wilf, 1997; Wilf et al., 1998; Wolfe, 1995) are

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valuable climate indicators. It is generally assumed that the conditions under which a plant lived were similar to those of its nearest living relatives (NLRs) (Fernández et al., 2007; Iannuzzi and Rösler, 2000; Iglesias et al., 2011; Sun and Wang, 2005; Vakhrameev et al., 1991).

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Many studies have used the distribution of invertebrates to define biogeographic provinces.

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Among the aquatic invertebrate fossils, the morphology, abundance, diversity and distribution of ostracods (Deng et al., 2010; Deng et al., 2012), conchostrcans (personal communication with

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Gang Li), and bivalves (Deng et al., 2010; Deng et al., 2012) have been used as paleoclimate

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indicators. As with plant fossils, their paleoclimatic interpretation is based on the tolerances of

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their modern counterparts. In practice, information from invertebrate fossils is always combined with other paleoclimatic indicators, such as fossil plants and climatically sensitive deposits

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(Boucot et al., 2013).

An important concept in climate classification is that “the vegetation is the best expression of climate” (Köppen, 2011; Kottek et al., 2006; Peel et al., 2007). Each paleovegetation type represents a set of paleoclimatic conditions (Bergengren et al., 2001; DeConto et al., 2000; Foley et al., 2000; Haxeltine and Prentice, 1996; Kaplan et al., 2003; Walter, 2002). Paleoclimate changes thus can be interpreted from the changes of the paleovegetation, and their interpretations are generally consistent with other evidence. However, the age of the paleofloras are often uncertain, and the number of recognizable vegetation types is limited and the topographic resolution of the environment in which they lived is largely unclear.

ACCEPTED MANUSCRIPT Numerical paleoclimate models start with a specific set of boundary conditions and then calculate atmospheric and oceanic conditions at specific time intervals. The model outputs are

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usually in the averages conditions of temperature, precipitation, and evaporation. The modeled

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paleoclimates can be compared directly with their modern counterparts (De Vleeschouwer et al., 2014; Gulbranson et al., 2014; Otto-Bliesner and Upchurch, 1997; Roscher et al., 2011; Tang et al., 2011; Upchurch et al., 1998; Zhang et al., 2012). The models commonly include

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paleovegetation simulations of varying complexity. However, the results of numerical modeling

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may contradict the geological proxies, as is the case with the „cold continental interior‟ paradox for the Late Cretaceous (DeConto et al., 1999). Such model-data discrepancies may be due to

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incorrect assumption in the initial boundary conditions, poor model resolution, or incomplete

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representation of the relevant physics (Huber, 2012).

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4. A New Paleoclimate Classification for Deep Time

4.1.Method

We modify Köppen climate classification to adapt it to deep time. To accomplish this, we used the following steps: 1) determining the paleoclimate parameters that are available in deep time studies; 2) investigating the relation of these paleoclimate parameters to the modern climate types recognized in Köppen climate classification; 3) redefining the climate types and their boundaries by these paleoclimate parameters; 4) testing and verifying the new paleoclimate classification.

ACCEPTED MANUSCRIPT In the new climate classification, the threshold values for the boundaries are determined based on the principle that the threshold value can minimize the misallocation of observed Köppen

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climate at each station into the new groups.

4.2.Köppen Climate Classification

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In the late 19th century Köppen proposed the first quantitative classification of world climates

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(Kottek et al., 2006), and it remains the most widely used (Rubel and Kottek, 2011). It is based on the idea that the vegetation is the best expression of long-term climate conditions. The boundaries

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are a hierarchical system related to vegetation distributions that reflecting major climate variables.

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Köppen climate classification combines average annual/monthly temperatures, average

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annual/monthly precipitation, and seasonality of precipitation (Kottek et al., 2006; Peel et al., 2007).

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The classification is a hierarchy that starts by recognizing five major climates, denoted by letters: A = Tropical; B = Arid; C = Temperate; D = Continental; and E = Polar (Table 1). A, C, D and E are defined by temperature only; B is defined by the combination of minimal precipitation and temperature. In practice, the E climate is determined first, followed by B and then the A, C, and D climates. Each major climate type is then subdivided using precipitation, indicated by a second letter: W = Desert; S = Steppe; f = fully humid; s = summer dry; w = winter dry; m = monsoonal. These units can then be further subdivided using temperature, indicated by a third letter: h = hot arid; k = cold arid; F = polar frost; T = polar tundra; a = hot summer; b = warm summer; c = cool summer;

ACCEPTED MANUSCRIPT d = extremely continental (Table 1). Each climate type is thus represented by a 2-to-3-letter symbol so that climatologists can

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choose an appropriate level of complexity based on their scientific objectives and the nature of the

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climate data available.

The description and criteria of Köppen climate types are in Table 1, following Peel et al. (2007) update. According to this, thirty climate types in total are recognized in modern climate: 3

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Tropical (Af, Am, and As/Aw), 4 Arid (BWh, BWk, BSh, and BSk), 9 Temperate (Csa, Csb, Csc,

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Cfa, Cfb, Cfc, Cwa, Cwb, and Cwc), 12 Continental (Dsa, Dsb, Dsc, Dsd, Dfa, Dfb, Dfc, Dfd,

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4.3.Parameters and Data

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Dwa, Dwb, Dwc, and Dwd) and 2 Polar (ET and EF).

Köppen climate types are defined by a complex combination of temperature, precipitation,

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and seasonality information, such as mean monthly temperature, maximum and minimum monthly temperatures, lowest and highest monthly precipitation values for the summer and winter half-years, and dryness threshold (Table 1). However, most of these climatic parameters are unknown in deep time. Therefore we here propose to use four simple parameters: mean annual temperature (MAT), mean annual precipitation (MAP), warm months mean temperature (WMMT: defined by warmest monthly mean temperature of three consecutive months), and Köppen aridity index (AIKöppen). In deep time these can be estimated quantitatively using a variety methods with acceptable errors (Table 2). The Köppen aridity index (AIKöppen) is not often cited, but it has the highest accuracy and

ACCEPTED MANUSCRIPT precision among the many aridity indices (Quan et al., 2013). It is calculated by MAP / (MAT + 33) (Köppen, 1923). When AIKöppen < 5.7, the climate is considered to be arid, and when 5.7 ≤

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AIKöppen < 13.6, the climate is considered to be semi-arid (Quan et al., 2013).

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The global climatic data used in the present study are from the Global Historical Climatology Network (GHCN) version 2.0 dataset (Peterson and Vose, 1997). They are based on stations at 4279 locations recorded each month (Table S1). The new classification of modern climates is

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based on the work of Peel et al. (2007).

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4.4.New Paleoclimate Classification

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The paleoclimate classification we propose here utilizes the hierarchy of Köppen climate

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classification, with the first letter indicating the main type and the second and third letters

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indicating the subtypes.

4.4.1. The First Letter

The criteria of the A, C, D and E climates are mutually exclusive and are defined based on the maximum and minimum monthly temperatures (Tmax and Tmin) (Table 1). The MAT can be used as a substitute for Tmax and Tmin (Fig. 1). Generally, the MAT of the A climate is highest, then C and D with the MAT of E being the lowest. In reality all the boundaries are vague and gradual (Fig. 1a) and the boundaries are drawn somewhat arbitrarily. MATs of 23 °C, 9 °C, and -10 °C are used to define the boundaries between the A and C climates, the C and D climates, and the D and

ACCEPTED MANUSCRIPT E climates, respectively (Fig. 1b). The correlation between the MAT and the minimum monthly temperature (Tmin) is positively strong (R2 = 0.9280, p < 0.01; Fig. 1c).

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In the new classification, areas with a MAT no lower than 23 °C are assigned to the A

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climate; with a MAT between 9 °C and 23 °C to the C climate; with a MAT between -10 °C and 9 °C to the D climate, and those with a MAT lower than -10 °C to the category E (Table 3). In the Köppen climate classification, the B climate is defined by the dryness threshold

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(Pthreshold/Pth). This is calculated by one of three functions of mean annual temperature and mean

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annul precipitation; the forms of the function depend on the annual distribution of precipitation (Table 1). The MAT, MAP, and the AIKöppen have been investigated to determine if any of them

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might be substituted for the more complex criterion. These three parameters are plotted against the

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latitudes of the climatic data in Fig. 2 and 3.

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The MAT alone is not enough to define the B climate, because there is no distinct difference between the B climate data and other climate data in MAT (Fig. 2a), and the correlation between

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the MAT and the old criteria is weak (Fig. 3a). The MAP and AIKöppen show similar distributions. In Fig. 2b and Fig. 2c, the data are divided into two distinct groups, and the non-B climate data are generally higher than the B climate data in both hemispheres. The correlation analysis shows similar results; the new criteria (MAP or AIKöppen) and the old criteria are strongly correlated with each other (R2 = 0.9778, p < 0.01 for MAP and R2 = 0.9566, p < 0.01 for AIKöppen) (Fig. 3b and 3c). However, the data points tend to be divergent when towards small values (the B climates) in the MAP figure, whereas this phenomenon is not seen in the AIKöppen data (Fig. 3b and 3c). Therefore, the AIKöppen seems to be the most suitable parameter to define the B climate.

ACCEPTED MANUSCRIPT For the original B climate data, all of the AIKöppen values are smaller than 13.6. The value of 13.6 is defined as the boundary between semi-arid and humid (Quan et al., 2013). However, if

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AIKöppen = 13.6 is defined as the boundary between the B and non-B climates, many non-B climate

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data will be falsely assigned to the B climate. Therefore, this value needs to be revised to make the distributions of data consist with the original distribution in the maximum extent. We compared the data distribution based on AIKöppen value between 5.7 and 13.6, and the AIKöppen value of 10.4 is

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defined as the boundary between the B climate and non-B climates, because only a few non-B

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data are assigned to the B climate using the value of 10.4, and vice versa. An AIKöppen values of 5.7 can be used as the boundary between the BS and BW climates. Again, a few BW climate data will

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be incorrectly assigned to the BS climate, and vice versa.

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Sites with AIKöppen values between 5.7 and 10.4 will be assigned to the BS climate, and those

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with AIKöppen values smaller than 5.7 will be assigned to the BW climate (Table 3).

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4.4.2. The Second Letter

The second letters (W, S, f, m, s, and w) describe the amount and the distribution of the precipitation. W and S define the subtypes of the B climate already discussed in section 4.4.1. The mean annual precipitation (MAP) is one of few reliable measure of precipitation we can obtain in deep time. We can simplify the criteria for the second letters of the MAP: only one boundary within the A climate can be defined. And no subtypes in the C or D climates can be recognized because of MAP does not provide any information about the seasonality of precipitation. This single boundary, MAP = 1800 mm, is between the Af/Am and the As/Aw

ACCEPTED MANUSCRIPT climates (Fig. 4; Table 3). This value can retain the distribution pattern of the Köppen climate

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classification in the new classification at the most extent.

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4.4.3. The Third Letter

The third letters (T, F, h, k, a, b, c, and d) are defined by the mean annual and monthly

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temperature. T and F define the subtypes of the E climate (ET and EF). These are not included in

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the new classification because they are indistinguishable using the available paleoclimatic parameters. The letters h and k designate subtypes of the B climate (BWh, BWk, BSh, and BSk),

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they are defined by MAT in Köppen climate classification. Therefore, the new classification

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follows the original definitions without modifications (Table 3). The rest of the letters (a, b, c, and

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d) define subtypes of the C and D climates. Although introduced as third letter, they can also be used as second letters. For example, the Dfc, Dwc, and Dsc climates taken together are defined as

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a Dc climate (Continental subarctic climates). In Köppen climate classification, the letters a, b, c, and d are defined by the maximum monthly temperature (Tmax) and the number of months where the temperature is above 10 °C. Therefore, we try to employ the warm months mean temperature (WMMT) to differentiate them. The WMMT can be replaced by the summer average temperature (SAT) or maximum monthly temperature (Tmax) if the WMMT is not available. The correlation between the WMMT and Tmax is excellent (R2 = 0.9904, p < 0.01; Fig. 5c). The data generally show a decrease from an „a‟ climate to a „d‟ climate both in the C and D climates. However, the boundaries between these climate subtypes are vague and gradual (Fig. 5a). We draw the boundaries arbitrarily, with as small

ACCEPTED MANUSCRIPT alterations to the original distributions as possible. Accordingly, WMMTs of 21 °C and 15 °C are defined as the boundaries of the „a‟ and „b‟ climates and the „b‟ and „c/d‟ climates (the c and d

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climates are combined as c/d in the new classification) in both the C and D climates, respectively

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(Fig. 5b).

For the B climate, locations having a MAT no lower than 18 °C are assigned to the Bh climate, and locations having a MAT lower than 18 °C, are assigned to the Bk climate. In the C

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and D climates, locations having a WMMT no lower than 21 °C are assigned to the Ca or Da

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climates. However if the maximum monthly temperature (Tmax) is in use, the boundary between a and b is 22 °C instead of 21 °C. Locations having a WMMT between 15 °C and 21 °C are

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assigned to the Cb or Db climates, and locations with a WMMT lower than 15 °C are assigned to

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the Cc or Dc/Dd climates (Table 3).

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4.4.4. New Paleoclimate Classification

In the new paleoclimate classification the number of climate types is reduced to 13: 2 Tropical (Af/Am and As/Aw), 4 Arid (BWh, BWk, BSh, and BSk), 3 Temperate (Ca, Cb, and Cc), 3 Continental (Da, Db, and Dc/Dd) and 1 Polar (E). These are sufficient for deep time paleoclimate studies. A world map using the new classification has been made following the suggestions of Peel et al. (2007) (Fig. 6). Stations from (GHCN) version 2.0 dataset (Peterson and Vose, 1997) with at least 30 observations for each month were used in the analysis; this involves 12,396 precipitation stations and 4,844 temperature stations. Where available, the mean annual temperature (MAT),

ACCEPTED MANUSCRIPT mean annual precipitation (MAP), warm month mean temperature (WMMT), and Köppen aridity index (AIKöppen) were calculated for each station. Then a two-dimensional (latitude and longitude)

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thin-plate spline interpolation with tension was applied to each parameter onto a 0.1×0.1 degree

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grid. All the interpolations are performed in ESRI ArcMap version 10.2 using settings of “weight” = 1 and “points” = 10. The new criteria were then applied to the splined parameters. As shown in Fig. 6, the global configuration of the new world map closely matches the overall pattern of

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Köppen system. Note that in the world map of the Köppen climate classification the climate types

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are combined and reduced to 13.

In the world map of the new climate classification, the areas of the Af/Am climate (Tropical

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rainforest climate and Tropical monsoon climate) commonly straddle the equator, between 5° N

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and 5° S. The representative regions are Southeast Asia, Central and West Africa, and South and

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Central America. The areas of the As/Aw climate (Tropical savanna climate) are usually located in the outer margins of the Tropical climates. The representative regions are located in Africa,

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Southeast Asia and South America. Rainforests are recognized in both Köppen and new classification: the North Pacific temperate rainforest, the Amazon tropical rainforest, and the Congo River Basin tropical rainforest. Figure 6 shows the areas of the BW (Desert) climate to be located between 30° N and 30° S. The deserts are easily recognized along the zonal areas including North Africa, Arabian Peninsula, and Middle East. In addition, they occupy nearly all the Central-West Australia and some small patches of South Africa and North America. The BS climate (Steppe climate) are commonly located at the outer margins of the BW climate areas; most are located in Asia and North America. Compared to the Köppen climate classification map, the areas of BS climate are expanded,

ACCEPTED MANUSCRIPT especially in the Asia. The BS climate is the intermediate between the arid (BW climate) and humid climates and are a combination of the area of these two climate types. The Köppen aridity

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index (AIKöppen) is affected by the mixed climates, although we revised the AIKöppen value from

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13.6 to 10.4.

The areas of the Ca climate (Humid subtropical climate) are mainly in the southeast of North America, the south of South America, East Asia, and Southern Europe. The areas of the Cb/Cc

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(Maritime temperate/subarctic climate) are mostly in Northern Western Europe, with some

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isolated areas in southwestern South America and South Africa. The Mediterranean climate is undistinguishable in the new world map, because of the distribution of the precipitation can not be

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well constrained in deep time. The areas shown as Mediterranean climate in Köppen climate

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classification, such as the area around the Mediterranean Sea, much of California, and parts of

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Western and South Australia, are assigned to other C climates in the new climate classification. Compared to the Köppen world map, the areas of the Ca climate are expanded in North America

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and Africa, and reduced in Asia in the new world map. The distribution of the D climate (Continental climate) is parallel to latitude. The areas of the Da/Db (Continental climates) are above 40° N to 65° N latitude, within central and northeastern of North America, Europe, and Asia. The areas of the Dc/Dd (Subarctic climate) are generally at latitudes from 50° to 70°N, poleward of the Continental climates. In the new map, the areas of the Da climate are often replaced by C climates and areas of the Dc/Dd climates are replaced by the Db climate. This is because the new classification tends to emphasize warmth for these climate types. The two major areas with E climate (Ice Cap and Tundra climates) are Antarctica and

ACCEPTED MANUSCRIPT Greenland. In addition, most northern islands of Canada and high-latitude Russia also belong to this type. We do not take altitude specifically into account because of the uncertainties of

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paleoaltimetry. Some areas with high altitudes (above the snow line) can be assigned to the E

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climate, such as the Andes, the Himalaya, Rocky Mountains, and the Alps.

In the new classification, 3575 (83.55%) of 4279 locations retain their original major climate types, and 3223 (75.32%) of 4279 locations retain their original climate types when classified by

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subtype (Table 4 and Table S1). Because most stations retain their Köppen climate types in the

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new paleoclimate classification, and the others are usually neighboring types, the proposed new

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4.5.Application

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classification for paleoclimate can be considered a close analog of that of Köppen.

In previous studies, it has been assumed that the Paleogene paleoclimate in East Asia was

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controlled by the planetary wind system with a unique pattern of three latitudinal zones (Guo et al., 2008) (see figs in Quan et al., 2014). Two humid zones (indicated by the presence of coal and oil shales) in the north and south, and an arid zone (indicated by red beds and evaporites) in the middle (Guo et al., 2008; Sun and Wang, 2005; Wang et al., 1999). However, there is evidence that monsoon or monsoon-like conditions prevailed in the East Asia during that period (Quan et al., 2011, 2012b; Quan et al., 2014; Wang et al., 2013). This brings into question the planetary wind model and the latitudinal zonation, especially what has been interpreted as an arid zone. Can the Paleogene of the East Asia interior be considered an arid climate using the modern climate classification scheme (Quan et al., 2014)? Unfortunately, verification is impeded due to the

ACCEPTED MANUSCRIPT paucity of data, in terms of both quantity and variety. The new paleoclimate classification with simple parameters is more useful. The paleoclimate

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of East Asia during the Eocene had been reconstructed based on the coexistence approach (CA)

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using 66 plant assemblages by Quan et al. (2012) (Quan et al., 2012a) (Table S2). The 66 paleofloras come from 37 fossil sites throughout China, with age ranging from early to late Eocene. The Köppen aridity index (AIKöppen) has been calculated for each plant assemblages based

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on the reconstructed MAT and MAP. All of the Köppen aridity index (AIKöppen) are larger than the

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semi-arid threshold value of 10.4, and there are no obvious discrepancies between the plant assemblages in the humid and arid zones throughout the Eocene (Table S2). All of the plant

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assemblages represent Ca climates, but two of them can also be classified As/Aw and another two

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classified as Cb climate according to their ranges of MAT or WMMT. This pattern is similar to the

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distribution of climate types in modern China, supporting the idea of a monsoon or monsoon-like

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climatology (Quan et al., 2011, 2012b; Quan et al., 2014; Wang et al., 2013).

5. Summary

Modern climate classifications do not work well in deep time due to the inherent differences of climates in the past. Climatically sensitive deposits, paleontological evidence, and modeling have been employed to describe paleoclimates in deep time. However, they have limited applicability, because of our incomplete knowledge on the measurements of proxies and relatively poor understanding on climate dynamics in the past. We propose a new paleoclimate classification based on modification of Köppen climate classification. It is a simplification of the complex

ACCEPTED MANUSCRIPT modern climate classification using simple quantitative criteria. The new classification is closely related to but differs from that of Köppen by changing some limits. It can serve to bridge the gap

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between the modern and deep time climate studies. A world map using the new classification

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shows the same patterns as the world map of the Köppen climate classification. Using the new classification, we were able to resolve a long-standing dispute about the climate patterns of East Asia during the Paleogene. The new classification indicates that during the

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entire Eocene, all of East Asia shared the same climate type (Ca: Subtropical), supporting the

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monsoon or monsoon-like conditions in East Asia during that time, rather than a system controlled

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Acknowledgments

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by the planetary wind.

We would thank William W. Hay, who reviewed our manuscript and gave us many useful

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comments. Laiming Zhang is supported by a scholarship by the Chinese Scholarship Council. This study was financially supported by the National Basic Research Program of China (973 Project) 2012CB822000.

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References

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Figure Captions

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Fig. 1 Latitudinal distributions (positive/negative values indicate north/south latitudes) of the mean annul

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temperatures (MAT) according to a) the Köppen climate classification and b) the new paleoclimate classification.

The A, C, D, and E climates are represented by red, green, yellow, and blue circles. The MAT values of 23 ºC, 9 ºC

and -10 ºC (dotted lines) are the boundaries between adjacent climate types. c) Correlation between the mean

annual temperatures (MAT) and the minimum monthly temperature (Tmin). The former comes from the new paleoclimate classification and the latter comes from Köppen‟s climate classification.

Fig. 2 Latitudinal distributions (positive/negative values indicate north/south latitudes) of a) the mean annual

temperatures (MAT), b) the mean annual precipitation (MAP), and c) the Köppen arid index (AIKöppen). The B climates and non-B climates are represented by green and red circles. Two data points beyond the scales are

ACCEPTED MANUSCRIPT indicated by the arrows and values.

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Fig. 3 Correlation between MAP-5Pth from the Köppen climate classification and a) mean annul temperatures, b)

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mean annual precipitation (MAP), and c) Köppen aridity index (AIKöppen). See Table 1 for detailed explanations of these indicators.

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Fig. 4 Latitudinal distributions (positive/negative values indicate north/south latitudes) of the mean annual

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precipitation (MAP) according to the Köppen climate classification. The Af/Am and As/Aw climates are presented

by red and green circles. The MAP value of 1800 mm (dotted line) is the boundary between the Af/Am and As/Aw

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climate types according to the new paleoclimate classification. Only A climates are plotted in this figure.

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Fig. 5 Latitudinal distributions (positive/negative values indicate north/south latitudes) of warm months mean

temperature (WMMT) according to a) the Köppen climate classification and b) the new paleoclimate

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classification. The a, b, c, and d climates are represented by red, green, yellow, and blue circles. The c and d

climates (yellow circles) are combined in the new paleoclimate classification. WMMT values of 21 ºC and 15 ºC

(dotted lines) are the boundaries between adjacent climate types. c) Correlation between the warm months mean

temperature (WMMT) and the maximum monthly temperature (Tmax). The former comes from the new paleoclimate classification and the latter comes from the Köppen climate classification. Only C and D climates are

plotted in this figure.

Fig. 6 Comparison between a) the world map of the new paleoclimate classification and b) the world map based on Köppen‟s climate classification, modified after Peel et al., 2007.

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ACCEPTED MANUSCRIPT Table 1 The description and the criteria of Köppen‟s climate classificationa Major Climate

Criteria

A

Tropical

Tmin ≥ 18

Af

Tropical Rainforest

Pmin ≥ 60

Am

Tropical Monsoon

Not (Af) & P min ≥ 100-MAP/25

Aw/As

Tropical Savannah

Not (Af) & P min < 100-MAP/25

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B

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Symbol

Dry

BSh

Hot Steppe

BSk

Cold Steppe

MAT ≥ 18

BWh

Hot Desert

BWk

Cold Desert Temperate

Cs

MAT < 18 MAP < 5 × Pth MAT ≥ 18 MAT < 18 Tmax > 10 & 0 < Tmin < 18

Mediterranean

Psmin < 40 & Psmin < Pwmax/3

Mediterranean (Hot Summer)

Tmax ≥ 22

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Csa

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C

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Desert

D

BW

Csb

Mediterranean (Warm Summer)

Not (a) & Tmon10 ≥ 4

Csc

Mediterranean (Cold Summer)

Not (a or b) & 1 ≤ Tmon10 < 4

Temperate with Dry Winter

Pwmin < Psmax/10

Cwa

Humid Subtropical

Tmax ≥ 22

Cwb

Maritime Temperate

Not (a) & Tmon10 ≥ 4

Cwc

Maritime Subarctic

Not (a or b) & 1 ≤ Tmon10 < 4

Temperate with Fully Humid

Not (Cs or Cw)

Cfa

Humid Subtropical

Tmax ≥ 22

Cfb

Maritime Temperate

Not (a) & Tmon10 ≥ 4

Cfc

Maritime Subarctic

Not (a or b) & 1 ≤ Tmon10 < 4

Continental

Tmax > 10 & Tmin ≤ 0

Continental with Dry Summer

Psmin < 40 & Psmin < Pwmax/3

Continental (Hot Summer)

Tmax ≥ 22

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Cw

5 ≤ MAP < 10 × Pth

Steppe

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BS

MAP < 10 × Pth

Cf

D Ds Dsa

ACCEPTED MANUSCRIPT Continental (Warm Summer)

Not (a) & Tmon10 ≥ 4

Dsc

Continental Subarctic (Cold Summer)

Not (a or b or d)

Dsd

Continental Subarctic (Very Cold Winter)

Not (a or b) & Tmin < -38

Continental with Dry Winter

Pwmin < Psmax/10

Dwa

Continental (Hot Summer)

Tmax ≥ 22

Dwb

Continental (Warm Summer)

Not (a) & Tmon10 ≥ 4

Dwc

Continental Subarctic (Cold Summer)

Dwd

Continental Subarctic (Very Cold Winter)

Not (a or b) & Tmin < -38

Continental with Fully Humid

Not (Cs or Cw)

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Not (a or b or d)

Tmax ≥ 22

Continental (Hot Summer)

Dfb

Continental (Warm Summer)

Dfc

Continental Subarctic (Cold Summer)

Not (a or b or d)

Dfd

Continental Subarctic (Very Cold Winter)

Not (a or b) & Tmin < -38

D

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Dfa

Polar

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E

Not (a) & Tmon10 ≥ 4

Tmax < 10

ET

Tundra

0 < Tmax < 10

EF

Ice Cap

Tmax ≤ 0

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Dsb

MAT = mean annual temperature, MAP = mean annual precipitation, Tmax = maximum monthly temperature, Tmin

= minimum monthly temperature, Tmon10 = number of months where the temperature is above 10, Pmin =

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minimum monthly precipitation, Psmin = minimum monthly precipitation in summer, Pwmin = minimum monthly precipitation in winter, Psmax = maximum monthly precipitation in summer, Pwmax = maximum monthly precipitation in winter. If 70% of MAP occurs in winter then Pth = 2 × MAT, if 70% of MAP occurs in summer then Pth = 2 × MAT + 28, otherwise Pth = 2 × MAT + 14. Summer (winter) is defined as the warmer (cooler) six month period of ONDJFM and AMJJAS. Modified after Peel et al. (2007)

ACCEPTED MANUSCRIPT Table 2 Quantitative methods with acceptable errors in deep time. MATa √

Clumped isotope



TEX86



MBT/CBT





Reference

Passey et al., 2010 Schouten et al., 2013 Schouten et al., 2013



Sheldon and Tabor, 2009





Utescher et al., 2007





Wilf et al., 1998

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Spicer, 2012





Coexistence Approach (CA)





Pollen/leaf composition









a

Retallack, 2005



Element geochemistry of Paleosol

CLAMP

AIKöppen

Grossman, 2012

Depth of Bk to the paleosol surface

b

MAP

PT

Oxygen isotope δ18O)

WMMT

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Method



AC

CE

PT

ED

MA

MAT = mean annual temperature, MAP = mean annual precipitation, WMMT = warm months mean temperature, AIKöppen = Köppen aridity index. b CLAMP = Climate Leaf Analysis Multivariate Program.

ACCEPTED MANUSCRIPT Table 3 The description and the criteria of the new paleoclimate classification Major Climate

Criteriaa

A

Tropical

MAT ≥ 23

Af/Am

Tropical Rainforest

MAP ≥ 1800

As/Aw

Tropical Savannah

MAP < 1800

Dry

AIköppen < 10.4

Steppe

5.7 ≤ AIköppen < 10.4

BS BSh

Hot Steppe

BSk

Cold Steppe

BWh

Hot Desert

BWk

Cold Desert

AIköppen < 5.7 MAT ≥ 18

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Temperate

MAT < 18 9 ≤ MAT < 23

Humid Subtropical

WMMT ≥ 21

Cb

Maritime Temperate

15 ≤ WMMT < 21

Cc

Maritime Subarctic

WMMT < 15

ED

Ca

Continental

-10 ≤ MAT < 9

Da

Continental (Hot Summer)

WMMT ≥ 21

Db

Continental (Warm Summer)

15 ≤ WMMT < 21

Continental Subarctic

WMMT < 15

Polar

MAT < -10

PT

D

CE

Dc/Dd

a

MAT < 18

Desert

C

E

MAT ≥ 18

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BW

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B

PT

Symbol

AC

MAT = mean annual temperature, MAP = mean annual precipitation, WMMT = warm months mean temperature, AIKöppen = Köppen dridity index.

ACCEPTED MANUSCRIPT Table 4 The distribution of the climate types in the new paleoclimate classificationa B

C

D

E

Total

398

872

1753

1202

54

4279

443

1017

1719

1066

34

4279

372

787

1489

907

20

3575

93.47%

90.25%

84.94%

75.46%

37.0

83.5

4%

5%

E

Total

Unchang edb

Koppen‟ s Paleocli mate Unchang ed

As/A

m

w

166

BWh

BWk

232

184

104

152

291

183

196

130

200

167

Percenta

78.3

ge

1%

BSh

BSk

Ca

Cb

Cc

Da

Db

Dc/D d

188

396

1200

536

17

274

679

249

54

4279

145

493

1316

367

36

74

693

299

34

4279

104

113

279

1092

332

1

73

551

161

20

3223

86.21

90.7

100.0

60.1

70.45

91.00

61.9

5.88

26.6

81.15

64.66

37.0

75.3

%

6%

0%

1%

%

%

4%

%

4%

%

%

4%

2%

AC

a

Af/A

D

ge

TE

c

CE P

Percenta

IP

mate

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Paleocli

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Koppen‟

T

A

Stations from the Global Historical Climatology Network (GHCN) version 2.0 dataset (Peterson and Vose, 1997).

Both precipitation and temperature with at least 30 observations for each month were recorded at a total of 4279 locations (Table S1). b

The number of locations which have the same climate types in Koppen‟s climate classification and the new

paleoclimate classification. c

The number of Unchanged locations divide the number of total locations in Koppen‟s climate classification.

38

ACCEPTED MANUSCRIPT Highlights We propose a new paleoclimate classification for deep time.



It is a simplification of the complex modern climate classification.



The new classification indicates monsoon climate in East Asia during Paleogene.

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39