Data for 2015
Climate Readiness (ND-GAIN), 2015
2015, as ND-GAIN’s 2026 release gives it · stored as published, never rewritten
Climate Readiness (ND-GAIN), 2015 covers 192 countries. Singapore is highest, at 0.80258; Central African Republic is lowest, at 0.12634. The middle country reads 0.39947. Against 2014, 192 values changed (114 up, 78 down), the same countries are covered.
Climate Readiness (ND-GAIN) · Data for 2015
HighestSingapore
0.80258LowestCentral African Republic
0.12634Shaded by value in five groups of equal size, darkest at the better end.
01ND-GAIN’s rank
The table
Every country and every column of Climate Readiness (ND-GAIN), 2015, as published. The rank is ND-GAIN’s own, as printed. “=” marks a shared position.
Showing 25 of 192 countries · select a heading to sort
| 1 | SGPSouth-eastern Asia | 0.80258 |
| 2 | NORNorthern Europe | 0.79975 |
| 3 | NZLAustralia and New Zealand | 0.79719 |
| 4 | DNKNorthern Europe | 0.79532 |
| 5 | FINNorthern Europe | 0.77067 |
| 6 | SWENorthern Europe | 0.75630 |
| 7 | ISLNorthern Europe | 0.73409 |
| =8 | KOREastern Asia | 0.73250 |
| =8 | CHEWestern Europe | 0.73255 |
| 10 | GBRNorthern Europe | 0.71430 |
| 11 | DEUWestern Europe | 0.71246 |
| 12 | MCOWestern Europe | 0.70898 |
| 13 | NLDWestern Europe | 0.70761 |
| 14 | JPNEastern Asia | 0.70715 |
| =15 | AUSAustralia and New Zealand | 0.70623 |
| =15 | AUTWestern Europe | 0.70627 |
| 17 | LUXWestern Europe | 0.70489 |
| 18 | USANorthern America | 0.68061 |
| 19 | CANNorthern America | 0.67605 |
| 20 | FRAWestern Europe | 0.66104 |
| 21 | SMRSouthern Europe | 0.64570 |
| 22 | ESTNorthern Europe | 0.64083 |
| 23 | LIEWestern Europe | 0.63887 |
| 24 | IRLNorthern Europe | 0.63170 |
| 25 | SVNSouthern Europe | 0.62360 |
| 26 | BELWestern Europe | 0.61374 |
| 27 | LTUNorthern Europe | 0.59592 |
| 28 | PRTSouthern Europe | 0.59387 |
| 29 | LVANorthern Europe | 0.58842 |
| =30 | POLEastern Europe | 0.57972 |
| =30 | AREWestern Asia | 0.58033 |
| 32 | NRUMicronesia | 0.57003 |
| 33 | CZEEastern Europe | 0.56914 |
| 34 | KNACaribbean | 0.56760 |
| 35 | GEOWestern Asia | 0.55889 |
| 36 | CHLSouth America | 0.55587 |
| 37 | DMACaribbean | 0.55116 |
| 38 | ISRWestern Asia | 0.54816 |
| 39 | ESPSouthern Europe | 0.54391 |
| 40 | MUSEastern Africa | 0.54125 |
| 41 | ANDSouthern Europe | 0.52515 |
| 42 | MYSSouth-eastern Asia | 0.52262 |
| 43 | GRDCaribbean | 0.52148 |
| 44 | MLTSouthern Europe | 0.51984 |
| 45 | ITASouthern Europe | 0.51919 |
| 46 | BRBCaribbean | 0.51636 |
| =47 | HUNEastern Europe | 0.51541 |
| =47 | RUSEastern Europe | 0.51549 |
| 49 | GRCSouthern Europe | 0.51365 |
| 50 | CYPWestern Asia | 0.51070 |
| 51 | BRNSouth-eastern Asia | 0.50752 |
| 52 | PLWMicronesia | 0.50182 |
| 53 | SVKEastern Europe | 0.50119 |
| 54 | QATWestern Asia | 0.49990 |
| 55 | URYSouth America | 0.49832 |
| 56 | VCTCaribbean | 0.49678 |
| 57 | OMNWestern Asia | 0.49365 |
| 58 | HRVSouthern Europe | 0.49028 |
| 59 | ARMWestern Asia | 0.48379 |
| =60 | BLREastern Europe | 0.47817 |
| =60 | ROUEastern Europe | 0.47801 |
| 62 | BHRWestern Asia | 0.47610 |
| 63 | MNESouthern Europe | 0.47427 |
| 64 | SAUWestern Asia | 0.47185 |
| 65 | ATGCaribbean | 0.47093 |
| 66 | KAZCentral Asia | 0.47043 |
| 67 | LCACaribbean | 0.46924 |
| 68 | MKDSouthern Europe | 0.46802 |
| 69 | BGREastern Europe | 0.46716 |
| 70 | CRICentral America | 0.46369 |
| 71 | FJIMelanesia | 0.46345 |
| 72 | TURWestern Asia | 0.45973 |
| 73 | SYCEastern Africa | 0.45727 |
| 74 | CHNEastern Asia | 0.45061 |
| 75 | CPVWestern Africa | 0.44852 |
| 76 | BTNSouthern Asia | 0.44613 |
| =77 | BHSCaribbean | 0.44513 |
| =77 | THASouth-eastern Asia | 0.44468 |
| 79 | TUNNorthern Africa | 0.43701 |
| 80 | WSMPolynesia | 0.43506 |
| 81 | MNGEastern Asia | 0.42976 |
| 82 | AZEWestern Asia | 0.42566 |
| =83 | BWASouthern Africa | 0.42317 |
| =83 | SLBMelanesia | 0.42283 |
| 85 | MHLMicronesia | 0.42202 |
| =86 | JORWestern Asia | 0.41910 |
| =86 | TONPolynesia | 0.41894 |
| =88 | ALBSouthern Europe | 0.41619 |
| =88 | IRNSouthern Asia | 0.41617 |
| 90 | SRBSouthern Europe | 0.41375 |
| 91 | MDVSouthern Asia | 0.41146 |
| =92 | MARNorthern Africa | 0.40975 |
| =92 | PANCentral America | 0.40990 |
| =92 | TUVPolynesia | 0.41027 |
| 95 | KWTWestern Asia | 0.40390 |
| 96 | PERSouth America | 0.39959 |
| 97 | MDAEastern Europe | 0.39934 |
| 98 | TLSSouth-eastern Asia | 0.39570 |
| =99 | RWAEastern Africa | 0.38736 |
| =99 | LKASouthern Asia | 0.38694 |
| 101 | VNMSouth-eastern Asia | 0.38637 |
| 102 | NAMSouthern Africa | 0.38489 |
| 103 | COLSouth America | 0.37879 |
| 104 | BIHSouthern Europe | 0.37385 |
| =105 | FSMMicronesia | 0.37080 |
| =105 | UKREastern Europe | 0.37070 |
| 107 | TTOCaribbean | 0.36962 |
| =108 | JAMCaribbean | 0.36852 |
| =108 | MEXCentral America | 0.36867 |
| =108 | ZAFSouthern Africa | 0.36933 |
| 111 | VUTMelanesia | 0.36815 |
| 112 | KIRMicronesia | 0.36435 |
| =113 | DOMCaribbean | 0.36255 |
| =113 | KGZCentral Asia | 0.36291 |
| =113 | STPMiddle Africa | 0.36311 |
| 116 | PRYSouth America | 0.35456 |
| 117 | GHAWestern Africa | 0.35283 |
| 118 | BRASouth America | 0.35245 |
| 119 | IDNSouth-eastern Asia | 0.35130 |
| 120 | SLVCentral America | 0.34781 |
| 121 | PRKEastern Asia | 0.34717 |
| 122 | ARGSouth America | 0.34251 |
| 123 | NPLSouthern Asia | 0.34243 |
| 124 | PHLSouth-eastern Asia | 0.33953 |
| 125 | BLZCentral America | 0.33686 |
| =126 | EGYNorthern Africa | 0.33035 |
| =126 | SURSouth America | 0.32960 |
| 128 | SENWestern Africa | 0.32733 |
| =129 | CUBCaribbean | 0.32639 |
| =129 | LBNWestern Asia | 0.32608 |
| 131 | ZMBEastern Africa | 0.32233 |
| 132 | LSOSouthern Africa | 0.31904 |
| =133 | SWZSouthern Africa | 0.31783 |
| =133 | GUYSouth America | 0.31755 |
| 135 | MRTWestern Africa | 0.31697 |
| 136 | ECUSouth America | 0.31610 |
| 137 | BENWestern Africa | 0.31510 |
| 138 | GTMCentral America | 0.31435 |
| 139 | DJIEastern Africa | 0.31207 |
| 140 | NICCentral America | 0.30878 |
| 141 | UZBCentral Asia | 0.30546 |
| 142 | GMBWestern Africa | 0.30388 |
| =143 | LAOSouth-eastern Asia | 0.30264 |
| =143 | TZAEastern Africa | 0.30268 |
| 145 | DZANorthern Africa | 0.30233 |
| 146 | INDSouthern Asia | 0.30033 |
| 147 | MLIWestern Africa | 0.29886 |
| 148 | GABMiddle Africa | 0.29829 |
| =149 | LBRWestern Africa | 0.29713 |
| =149 | NERWestern Africa | 0.29720 |
| =149 | TGOWestern Africa | 0.29686 |
| 152 | COMEastern Africa | 0.29535 |
| 153 | GINWestern Africa | 0.29449 |
| 154 | SLEWestern Africa | 0.29278 |
| 155 | ETHEastern Africa | 0.29101 |
| 156 | PNGMelanesia | 0.28849 |
| 157 | TJKCentral Asia | 0.28677 |
| 158 | BOLSouth America | 0.28354 |
| 159 | BFAWestern Africa | 0.28167 |
| 160 | PAKSouthern Asia | 0.27673 |
| 161 | CIVWestern Africa | 0.27631 |
| 162 | KHMSouth-eastern Asia | 0.27443 |
| 163 | MOZEastern Africa | 0.27155 |
| 164 | IRQWestern Asia | 0.26968 |
| 165 | YEMWestern Asia | 0.26919 |
| =166 | HNDCentral America | 0.26796 |
| =166 | UGAEastern Africa | 0.26840 |
| 168 | MWIEastern Africa | 0.26703 |
| 169 | MDGEastern Africa | 0.26549 |
| =170 | KENEastern Africa | 0.26031 |
| =170 | SYRWestern Asia | 0.25967 |
| 172 | CMRMiddle Africa | 0.25877 |
| 173 | BDIEastern Africa | 0.25605 |
| =174 | BGDSouthern Asia | 0.25138 |
| =174 | GNBWestern Africa | 0.25091 |
| =176 | SOMEastern Africa | 0.24605 |
| =176 | SDNNorthern Africa | 0.24566 |
| 178 | AFGSouthern Asia | 0.24456 |
| 179 | TKMCentral Asia | 0.23831 |
| =180 | GNQMiddle Africa | 0.23480 |
| =180 | MMRSouth-eastern Asia | 0.23482 |
| 182 | LBYNorthern Africa | 0.22583 |
| 183 | HTICaribbean | 0.22499 |
| =184 | NGAWestern Africa | 0.21985 |
| =184 | COGMiddle Africa | 0.21970 |
| 186 | AGOMiddle Africa | 0.20903 |
| 187 | VENSouth America | 0.20153 |
| 188 | ZWEEastern Africa | 0.19960 |
| 189 | ERIEastern Africa | 0.19169 |
| 190 | CODMiddle Africa | 0.18064 |
| 191 | TCDMiddle Africa | 0.17251 |
| 192 | CAFMiddle Africa | 0.12634 |
02In 2015
At either end
The 5 countries at each end of the headline.
Highest
- #1
Singapore0.80258
- #2
Norway0.79975
- #3
New Zealand0.79719
- #4
Denmark0.79532
- #5
Finland0.77067
Lowest
- #192
Central African Republic0.12634
- #191
Chad0.17251
- #190
DR Congo0.18064
- #189
Eritrea0.19169
- #188
Zimbabwe0.19960
A higher value is the better result. The middle country reads 0.39947. “Shared” marks a value another country also holds.
032014 → 2015
Since 2014
What changed between 2014 and this one: who joined or left, and how far the headline moved.
- +0 / −0countries joined / left
- 192values changed, of 192 in both
- 114 · 78rose · fell
- 0unchanged
Rose most
San Marino0.59871 → 0.64570+0.04699
Saint Kitts and Nevis0.53818 → 0.56760+0.02941
Russia0.48948 → 0.51549+0.02601
Côte d’Ivoire0.25294 → 0.27631+0.02337
Seychelles0.43466 → 0.45727+0.02261
Both years come from the same release, so a difference here is a change in the data, not a revision of it. Every country’s full history is charted on the statistic page.
04Caveats
Read before you use
What this edition’s numbers are and are not, worked out from the file itself.
One year of the 2026 release
Every year in this series comes from ND-GAIN’s 2026 release, recalculated on one method. It can differ from what was first published for 2015.
The rank is ND-GAIN’s
Printed as the publisher ranked the countries; never re-ranked here.
Nothing missing
Every one of the 192 countries has every column.
05The files
Download and cite
The table as a file, digit for digit, what this site changed, and a citation for this edition.
- .csv
For a spreadsheet or code
192 rows · 8.1 KB · UTF-8, opens in Excel
Opens with 11 lines of source notes; the table starts on row 13.
Download climate-readiness-2015-nations-inquiry.csv - ↗
The publisher’s original
ND-GAIN’s own file, on its own site.
resources-2026-14-07-13h00.zip
What this site changed: Reshaped into one row per country: regional and income-group totals are left out, only the columns listed are kept, each row gets its ISO 3166 code, and some country names are brought to one spelling. No value is recalculated, rescaled or rounded.
Licence: CC BY 3.0 Unported · what it allows, in plain words
Cite this edition
Notre Dame Global Adaptation Initiative (ND-GAIN), University of Notre Dame (2015). Climate Readiness (ND-GAIN), 2015 [data set], describing 2015. As held by Nations Inquiry, https://nationsinquiry.com/datasets/climate-readiness/2015
0630 held
Other years
‹ The year before
Climate Readiness (ND-GAIN), 2014192 countries
The year after ›
Climate Readiness (ND-GAIN), 2016192 countries
All of them
Climate Readiness (ND-GAIN): every year30 held, with the data dictionary, coverage and licence.
How it has moved, charted by country
07Questions
Climate Readiness (ND-GAIN), 2015: questions and answers
Which country has the highest climate adaptation readiness in Climate Readiness (ND-GAIN), 2015?
Singapore, at 0.80258, of the 192 countries in the file.
What year does Climate Readiness (ND-GAIN), 2015 describe?
2015.
How many countries does Climate Readiness (ND-GAIN), 2015 cover?
192.
Where can I download Climate Readiness (ND-GAIN), 2015?
On this page, as a CSV file holding every value exactly as published, or from the publisher’s own site, linked below.
Is Climate Readiness (ND-GAIN), 2015 the newest?
No. The newest held here is Climate Readiness (ND-GAIN), 2024.